diff --git a/pkgdown.yml b/pkgdown.yml index 06aa4f62..ee1df427 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -2,7 +2,7 @@ pandoc: 2.19.2 pkgdown: 2.0.7 pkgdown_sha: ~ articles: {} -last_built: 2023-11-13T10:06Z +last_built: 2023-11-13T10:32Z urls: reference: http://momx.github.io/Momocs/reference article: http://momx.github.io/Momocs/articles diff --git a/reference/LDA.html b/reference/LDA.html index 05c84509..923a6c4d 100644 --- a/reference/LDA.html +++ b/reference/LDA.html @@ -229,7 +229,7 @@

Examples#> { #> .pal_brewer(n, "Set2") %>% pal_alpha(transp = transp) #> } -#> <bytecode: 0x55fea46b9e58> +#> <bytecode: 0x5633aca186b8> #> <environment: namespace:Momocs> #> #> $method diff --git a/reference/NMDS.html b/reference/NMDS.html index 5adcfc6b..955ddfeb 100644 --- a/reference/NMDS.html +++ b/reference/NMDS.html @@ -116,7 +116,7 @@

Examples#> Run 0 stress 0.07227125 #> Run 1 stress 0.07227125 #> ... New best solution -#> ... Procrustes: rmse 3.936045e-06 max resid 1.87576e-05 +#> ... Procrustes: rmse 3.936046e-06 max resid 1.87576e-05 #> ... Similar to previous best #> Run 2 stress 0.1536609 #> Run 3 stress 0.1729702 @@ -127,20 +127,20 @@

Examples#> ... Procrustes: rmse 2.19081e-06 max resid 8.275813e-06 #> ... Similar to previous best #> Run 6 stress 0.07227125 -#> ... Procrustes: rmse 7.028882e-06 max resid 2.808569e-05 +#> ... Procrustes: rmse 7.02888e-06 max resid 2.808569e-05 #> ... Similar to previous best #> Run 7 stress 0.07227125 -#> ... Procrustes: rmse 9.669053e-06 max resid 3.852924e-05 +#> ... Procrustes: rmse 9.669054e-06 max resid 3.852924e-05 #> ... Similar to previous best #> Run 8 stress 0.1476475 #> Run 9 stress 0.07227125 -#> ... Procrustes: rmse 1.146131e-06 max resid 4.040052e-06 +#> ... Procrustes: rmse 1.146136e-06 max resid 4.040052e-06 #> ... Similar to previous best #> Run 10 stress 0.07227125 -#> ... Procrustes: rmse 2.035531e-06 max resid 8.084339e-06 +#> ... Procrustes: rmse 2.035528e-06 max resid 8.084339e-06 #> ... Similar to previous best #> Run 11 stress 0.07227126 -#> ... Procrustes: rmse 7.291376e-06 max resid 2.685535e-05 +#> ... Procrustes: rmse 7.291375e-06 max resid 2.685535e-05 #> ... Similar to previous best #> Run 12 stress 0.1647891 #> Run 13 stress 0.07227125 @@ -158,10 +158,10 @@

Examples#> ... Similar to previous best #> Run 18 stress 0.1776127 #> Run 19 stress 0.07227125 -#> ... Procrustes: rmse 4.920735e-06 max resid 1.945613e-05 +#> ... Procrustes: rmse 4.920737e-06 max resid 1.945613e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 -#> ... Procrustes: rmse 1.95309e-06 max resid 6.877957e-06 +#> ... Procrustes: rmse 1.953093e-06 max resid 6.877957e-06 #> ... Similar to previous best #> *** Best solution repeated 14 times diff --git a/reference/PCA-4.png b/reference/PCA-4.png index 2820b42a..8a4d5d49 100644 Binary files a/reference/PCA-4.png and b/reference/PCA-4.png differ diff --git a/reference/Rplot008.png b/reference/Rplot008.png index 2fe72f06..fb20d223 100644 Binary files a/reference/Rplot008.png and b/reference/Rplot008.png differ diff --git a/reference/Rplot015.png b/reference/Rplot015.png index 8a41311b..1416ff51 100644 Binary files a/reference/Rplot015.png and b/reference/Rplot015.png differ diff --git a/reference/boxplot.PCA-1.png b/reference/boxplot.PCA-1.png index f87a74e1..269fa850 100644 Binary files a/reference/boxplot.PCA-1.png and b/reference/boxplot.PCA-1.png differ diff --git a/reference/coo_chull.html b/reference/coo_chull.html index 2fbd1fe2..1cd03e0d 100644 --- a/reference/coo_chull.html +++ b/reference/coo_chull.html @@ -1443,7 +1443,7 @@

Examples#> { #> UseMethod("coo_chull_onion") #> } -#> <bytecode: 0x55fea4517f10> +#> <bytecode: 0x5633ac870008> #> <environment: namespace:Momocs> x <- bot %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details diff --git a/reference/fgsProcrustes-1.png b/reference/fgsProcrustes-1.png index 06db6f0f..57a13e44 100644 Binary files a/reference/fgsProcrustes-1.png and b/reference/fgsProcrustes-1.png differ diff --git a/reference/import_jpg.html b/reference/import_jpg.html index 9ef91142..ee0cb7ea 100644 --- a/reference/import_jpg.html +++ b/reference/import_jpg.html @@ -131,7 +131,7 @@

Examples#> empty Out coo <- import_jpg() -#> Warning: unable to translate '<d0><ff><ff><ff><ff><ff><ff><ff><c0><aa><8f><b7>' to a wide string +#> Warning: unable to translate '<d0><ff><ff><ff><ff><ff><ff><ff><c0><aa><cf>d' to a wide string #> Warning: input string 1 is invalid #> Extracting 0.jpg outlines... #> Done in 0 secs diff --git a/reference/plot.PCA-15.png b/reference/plot.PCA-15.png index 2820b42a..8a4d5d49 100644 Binary files a/reference/plot.PCA-15.png and b/reference/plot.PCA-15.png differ diff --git a/reference/plot_CV-1.png b/reference/plot_CV-1.png index 58fa3314..85ca178d 100644 Binary files a/reference/plot_CV-1.png and b/reference/plot_CV-1.png differ diff --git a/reference/plot_NMDS.html b/reference/plot_NMDS.html index 9b8815a9..6e22e896 100644 --- a/reference/plot_NMDS.html +++ b/reference/plot_NMDS.html @@ -177,17 +177,17 @@

Examples#> ... Similar to previous best #> Run 2 stress 0.07227125 #> ... New best solution -#> ... Procrustes: rmse 1.848564e-06 max resid 7.686046e-06 +#> ... Procrustes: rmse 1.848561e-06 max resid 7.686046e-06 #> ... Similar to previous best #> Run 3 stress 0.1610098 #> Run 4 stress 0.07227125 -#> ... Procrustes: rmse 6.814351e-06 max resid 2.80386e-05 +#> ... Procrustes: rmse 6.814352e-06 max resid 2.80386e-05 #> ... Similar to previous best #> Run 5 stress 0.07227125 -#> ... Procrustes: rmse 8.042267e-06 max resid 3.293377e-05 +#> ... Procrustes: rmse 8.042268e-06 max resid 3.293377e-05 #> ... Similar to previous best #> Run 6 stress 0.07227125 -#> ... Procrustes: rmse 2.510738e-06 max resid 7.634959e-06 +#> ... Procrustes: rmse 2.510741e-06 max resid 7.634959e-06 #> ... Similar to previous best #> Run 7 stress 0.1660041 #> Run 8 stress 0.07227125 @@ -201,27 +201,27 @@

Examples#> ... Procrustes: rmse 1.396985e-06 max resid 6.777242e-06 #> ... Similar to previous best #> Run 12 stress 0.07227125 -#> ... Procrustes: rmse 5.297105e-06 max resid 2.060719e-05 +#> ... Procrustes: rmse 5.297107e-06 max resid 2.060719e-05 #> ... Similar to previous best #> Run 13 stress 0.07227125 -#> ... Procrustes: rmse 5.873071e-06 max resid 2.1449e-05 +#> ... Procrustes: rmse 5.87307e-06 max resid 2.1449e-05 #> ... Similar to previous best #> Run 14 stress 0.1660723 #> Run 15 stress 0.07227125 #> ... Procrustes: rmse 8.005086e-06 max resid 3.40387e-05 #> ... Similar to previous best #> Run 16 stress 0.07227125 -#> ... Procrustes: rmse 4.941502e-06 max resid 1.943066e-05 +#> ... Procrustes: rmse 4.941503e-06 max resid 1.943066e-05 #> ... Similar to previous best #> Run 17 stress 0.1591579 #> Run 18 stress 0.07227125 -#> ... Procrustes: rmse 1.363297e-06 max resid 5.158787e-06 +#> ... Procrustes: rmse 1.363299e-06 max resid 5.158787e-06 #> ... Similar to previous best #> Run 19 stress 0.07227125 #> ... Procrustes: rmse 5.783015e-06 max resid 2.420838e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 -#> ... Procrustes: rmse 3.842552e-06 max resid 1.520619e-05 +#> ... Procrustes: rmse 3.842551e-06 max resid 1.520619e-05 #> ... Similar to previous best #> *** Best solution repeated 14 times diff --git a/reference/stack.Coo-8.png b/reference/stack.Coo-8.png index e743527e..ec80cecb 100644 Binary files a/reference/stack.Coo-8.png and b/reference/stack.Coo-8.png differ diff --git a/reference/stack.Coo.html b/reference/stack.Coo.html index 1fdacb97..b861b735 100644 --- a/reference/stack.Coo.html +++ b/reference/stack.Coo.html @@ -281,14 +281,14 @@

Examples#> iteration: 34 gain: 5.7787e-09 #> iteration: 35 gain: 3.9287e-09 #> iteration: 36 gain: 1.0587e-09 -#> iteration: 37 gain: 9.259e-10 +#> iteration: 37 gain: 9.2591e-10 #> iteration: 38 gain: 1.4847e-09 #> iteration: 39 gain: 1.039e-09 #> iteration: 40 gain: 2.9925e-10 #> iteration: 41 gain: 2.2588e-10 #> iteration: 42 gain: 3.8255e-10 #> iteration: 43 gain: 2.7403e-10 -#> iteration: 44 gain: 8.3659e-11 +#> iteration: 44 gain: 8.3666e-11 stack(chaffal, slidings=FALSE) stack(chaffal, meanshape=TRUE, meanshape_col="blue") diff --git a/reference/tps2d-1.png b/reference/tps2d-1.png index 3f28269b..659b19f7 100644 Binary files a/reference/tps2d-1.png and b/reference/tps2d-1.png differ diff --git a/search.json b/search.json index 6ed179f5..b69c617a 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"http://momx.github.io/Momocs/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Vincent Bonhomme. Author, maintainer. Julien Claude. Author. core functions base R","code":""},{"path":"http://momx.github.io/Momocs/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Bonhomme V, Picq S, Gaucherel C, Claude J (2014). Momocs: Outline Analysis Using R, volume 56 number 13. https://www.jstatsoft.org/v56/i13/.","code":"@Manual{, textversion = {Vincent Bonhomme, Sandrine Picq, Cedric Gaucherel, Julien Claude (2014).}, title = {Momocs: Outline Analysis Using R}, journal = {Journal of Statistical Software}, year = {2014}, volume = {56}, number = {13}, pages = {1--24}, url = {https://www.jstatsoft.org/v56/i13/}, author = {Vincent Bonhomme and Sandrine Picq and Cédric Gaucherel and Julien Claude}, }"},{"path":[]},{"path":"http://momx.github.io/Momocs/index.html","id":"news","dir":"","previous_headings":"Momocs","what":"News","title":"Morphometrics using R","text":"’m still looking funding develop MomX. idea, please email ’m available consulting, training collaboration, worldwide. Momocs back CRAN longer relies retired rgeos dependency tutorial/introduction back! Download **","code":""},{"path":"http://momx.github.io/Momocs/index.html","id":"installation","dir":"","previous_headings":"Momocs","what":"Installation","title":"Morphometrics using R","text":"last released version can installed CRAN : recommend using (support) development version GitHub :","code":"install.packages(\"Momocs\") # install.packages(\"devtools\") devtools::install_github(\"MomX/Momocs\")"},{"path":"http://momx.github.io/Momocs/index.html","id":"example","dir":"","previous_headings":"Momocs","what":"Example","title":"Morphometrics using R","text":"basic example complete analysis : inspection, normalization raw outlines, elliptical Fourier transforms, dimmensionality reduction classification, using single line.","code":"library(Momocs) devtools::load_all() #> ℹ Loading Momocs #> Registered S3 method overwritten by 'vegan': #> method from #> rev.hclust dendextend hearts %T>% # A toy dataset stack() %>% # Take a family picture of raw outlines fgProcrustes() %>% # Full generalized Procrustes alignment coo_slide(ldk = 2) %T>% # Redefine a robust 1st point between the cheeks stack() %>% # Another picture of aligned outlines efourier(6, norm=FALSE) %>% # Elliptical Fourier Transforms PCA() %T>% # Principal Component Analysis plot_PCA(~aut) %>% # A PC1:2 plot LDA(~aut) %>% # Linear Discriminant Analysis plot_CV() # And the confusion matrix after leave one out cross validation #> Warning: The `` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated."},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":null,"dir":"Reference","previous_headings":"","what":"Hierarchical clustering — CLUST","title":"Hierarchical clustering — CLUST","text":"Performs hierarchical clustering dist hclust. far mainly wrapper around two functions, plus plotting using dendextend package facilities.","code":""},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Hierarchical clustering — CLUST","text":"","code":"CLUST(x, ...) # S3 method for default CLUST(x, ...) # S3 method for Coe CLUST( x, fac, type = c(\"horizontal\", \"vertical\", \"fan\")[1], k, dist_method = \"euclidean\", hclust_method = \"complete\", retain = 0.99, labels, lwd = 1/4, cex = 1/2, palette = pal_qual, ... )"},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Hierarchical clustering — CLUST","text":"x Coe PCA object ... useless fac factor specification fac_dispatcher type character one c(\"horizontal\", \"vertical\", \"fan\") (default: horizontal) k numeric provided greater 1, cut tree number groups dist_method feed dist's method argument, one euclidean (default), maximum, manhattan, canberra, binary minkowski. hclust_method feed hclust's method argument, one ward.D, ward.D2, single, complete (default), average, mcquitty, median centroid. retain number axis retain PCA object passed. number < 1 passed, number PCs retained enough capture proportion variance via scree_min labels factor specification labelling tips feed fac_dispatcher lwd branches (default: 0.25) cex labels (default: 1) palette one available palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Hierarchical clustering — CLUST","text":"ggplot plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Hierarchical clustering — CLUST","text":"","code":"# On Coe bf <- bot %>% efourier(6) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details CLUST(bf) # with a factor and vertical CLUST(bf, ~type, \"v\") # with some cutting and different dist/hclust methods CLUST(bf, dist_method=\"maximum\", hclust_method=\"average\", labels=~type, k=3, lwd=1, cex=1, palette=pal_manual(c(\"green\", \"yellow\", \"red\"))) # On PCA bf %>% PCA %>% CLUST"},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":null,"dir":"Reference","previous_headings":"","what":"Coe ","title":"Coe ","text":"Coe class 'parent' 'super' class OutCoe, OpnCoe, LdkCoe TraCoe classes.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Coe ","text":"","code":"Coe(...)"},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Coe ","text":"... anything , anyway, function simply returns message.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Coe ","text":"list class Coe","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Coe ","text":"Useful shortcuts described . See browseVignettes(\"Momocs\") detail design behind Momocs' classes. Coe class 'parent' class following 'child' classes OutCoe coefficients closed outlines morphometrics OpnCoe coefficients open outlines morphometrics LdkCoe coefficients configuration landmarks morphometrics. words, OutCoe, OpnCoe LdkCoe classes , primarily, Coe objects define generic specific methods. See respective help pages help. can access methods available Coe objects methods(class=Coe).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Coe ","text":"","code":"# to see all methods for Coe objects. methods(class='Coe') #> [1] $ CLUST KMEDOIDS LDA MDS NMDS #> [7] [ [<- arrange as_df breed chop #> [13] dim dissolve export filter get_pairs length #> [19] mutate names names<- perm reLDA rename #> [25] sample_frac sample_n select slice str subsetize #> [31] which_out #> see '?methods' for accessing help and source code # to see all methods for OutCoe objects. methods(class='OutCoe') # same for OpnCoe, LdkCoe, TraCoe #> [1] MANOVA MSHAPES PCA boxplot combine hcontrib print rm_asym #> [9] rm_sym symmetry #> see '?methods' for accessing help and source code bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.f #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 40 outlines described, 12 harmonics #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows class(bot.f) #> [1] \"OutCoe\" \"Coe\" inherits(bot.f, \"Coe\") #> [1] TRUE # if you want to work directly on the matrix of coefficients bot.f$coe #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 1 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> franziskaner 1 0.007314669 0.09110003 0.01294912 0.023136784 0.010558958 #> grimbergen 1 0.009522713 0.08573641 0.01974880 0.012878126 0.008485338 #> guiness 1 0.009589570 0.08825041 0.02268926 0.017770767 0.010695823 #> hoegardeen 1 0.009598003 0.09186435 0.01393702 0.020136724 0.008952962 #> jupiler 1 0.008152360 0.09595083 0.01206957 0.023549986 0.007484692 #> kingfisher 1 0.007788546 0.09459391 0.01346605 0.024571428 0.009229773 #> latrappe 1 0.018476561 0.06035470 0.03974568 0.010493387 0.026379718 #> lindemanskriek 1 0.012406103 0.09289294 0.01773845 0.020632152 0.010949655 #> nicechouffe 1 0.015167563 0.09058037 0.02094971 0.020007417 0.014345165 #> pecheresse 1 0.008436476 0.09409400 0.01181167 0.022221176 0.007960411 #> sierranevada 1 0.015038107 0.08208708 0.02647382 0.013697543 0.013869924 #> tanglefoot 1 0.018782346 0.07275504 0.03848616 0.008439294 0.018172933 #> tauro 1 0.007333709 0.09536301 0.01149374 0.023043384 0.007093187 #> westmalle 1 0.009100416 0.09469091 0.01450202 0.023460557 0.009582984 #> amrut 1 0.004198631 0.09500128 0.02143863 0.026005715 0.011729658 #> ballantines 1 -0.000653116 0.05733309 0.03154946 0.017516836 0.034198742 #> bushmills 1 -0.004927807 0.08149528 0.01036776 0.023910616 0.017320375 #> chivas 1 0.021613712 0.08642271 0.04314511 0.008460823 0.014376414 #> dalmore 1 0.038669436 0.07265717 0.05680730 0.003277741 0.019363348 #> famousgrouse 1 0.003373189 0.08802317 0.02019928 0.025507211 0.016776448 #> glendronach 1 0.003257554 0.09526153 0.02074249 0.026167146 0.010932661 #> glenmorangie 1 0.008572527 0.09410920 0.02136020 0.024756735 0.011430941 #> highlandpark 1 -0.002122354 0.06989902 0.03612531 0.023554876 0.027350465 #> jackdaniels 1 0.008777794 0.08626120 0.02940216 0.019373419 0.015295504 #> jb 1 0.004384491 0.09517564 0.02460733 0.023505329 0.010741163 #> johnniewalker 1 0.002370576 0.08321025 0.01719991 0.022474617 0.017724976 #> magallan 1 -0.008648015 0.09924533 0.01455296 0.037258989 0.011586345 #> makersmark 1 0.016536161 0.10229688 0.03388156 0.008773613 0.010192259 #> oban 1 0.001652893 0.09909342 0.02127249 0.028337047 0.009671380 #> oldpotrero 1 0.022935601 0.09391465 0.03109455 0.009138035 0.012979620 #> redbreast 1 0.017769276 0.09281598 0.04425688 0.011246633 0.012792733 #> tamdhu 1 0.005270821 0.09375949 0.02020814 0.025073663 0.010943288 #> wildturkey 1 0.008605609 0.09229119 0.03228916 0.020978082 0.013010663 #> yoichi 1 -0.001738226 0.07733113 0.02843759 0.024035740 0.023420967 #> A7 A8 A9 A10 #> brahma 0.0031835706 0.005158502 -7.262824e-04 0.0047287291 #> caney 0.0035527091 0.007010166 1.214949e-03 0.0038734169 #> chimay -0.0047412879 0.007814037 -2.112661e-03 0.0022043011 #> corona 0.0055045888 0.007852411 8.767189e-04 0.0044201528 #> deusventrue 0.0025214510 0.011391904 -1.733965e-03 0.0062083192 #> duvel -0.0016871288 0.011025502 -1.042906e-04 0.0017042044 #> franziskaner 0.0045813399 0.006927102 -5.793922e-04 0.0045217266 #> grimbergen -0.0021957902 0.008213656 -1.577404e-03 0.0026346248 #> guiness -0.0015195731 0.008550727 2.093772e-04 0.0060163830 #> hoegardeen 0.0024034912 0.007507503 -1.234721e-03 0.0046892597 #> jupiler 0.0055270378 0.006597011 1.073131e-03 0.0041448892 #> kingfisher 0.0059527872 0.006778517 1.169809e-03 0.0044984721 #> latrappe -0.0057950372 0.005954999 -5.463098e-03 -0.0001140651 #> lindemanskriek 0.0033428880 0.008381096 -1.707332e-04 0.0050506285 #> nicechouffe 0.0026214920 0.010288304 -4.913646e-04 0.0065828560 #> pecheresse 0.0046954032 0.006669592 4.015144e-05 0.0042466561 #> sierranevada -0.0043828769 0.009275932 -1.465646e-03 0.0059555586 #> tanglefoot -0.0108560295 0.008370133 -2.988319e-03 0.0052185654 #> tauro 0.0052560957 0.006425077 9.461829e-04 0.0040141970 #> westmalle 0.0051463840 0.006848999 3.534839e-04 0.0042382642 #> amrut 0.0019176785 0.008515916 1.392307e-03 0.0089150426 #> ballantines 0.0045419501 0.014014932 -5.273138e-03 0.0006083616 #> bushmills 0.0095020099 0.012457087 -3.988679e-04 0.0048132802 #> chivas -0.0053775410 0.013797633 2.198119e-03 0.0031741809 #> dalmore -0.0072008170 0.012093037 5.368701e-03 0.0025492686 #> famousgrouse 0.0035195429 0.008617844 -1.621645e-03 0.0075384656 #> glendronach 0.0018504691 0.007851391 1.483976e-03 0.0086527932 #> glenmorangie 0.0023552959 0.007521806 1.103445e-03 0.0069834516 #> highlandpark -0.0024258364 0.003973480 -7.894105e-03 0.0013284975 #> jackdaniels -0.0047279969 0.008903250 -2.124758e-03 0.0090062900 #> jb -0.0015584637 0.008915452 4.097146e-04 0.0089915939 #> johnniewalker 0.0034197782 0.009945811 -3.913888e-03 0.0059350940 #> magallan 0.0095026108 0.003088506 1.575409e-03 0.0054824432 #> makersmark 0.0003303914 0.016520390 -1.901653e-03 0.0031138042 #> oban 0.0022492968 0.007479292 2.478319e-03 0.0090114539 #> oldpotrero 0.0015843674 0.012237947 -4.671411e-04 0.0023549220 #> redbreast -0.0046107656 0.015170859 3.884228e-03 0.0045806501 #> tamdhu 0.0013188307 0.006535142 1.700604e-04 0.0072170216 #> wildturkey -0.0038244377 0.010171775 1.641229e-03 0.0092477531 #> yoichi -0.0011328612 0.006117569 -8.008551e-03 0.0034639875 #> A11 A12 B1 B2 B3 #> brahma -0.0013733386 0.0016363823 0 -1.900652e-04 3.306231e-04 #> caney -0.0018777601 0.0011330555 0 5.012013e-04 -3.851293e-04 #> chimay -0.0012371979 -0.0018514226 0 1.843629e-04 4.196107e-04 #> corona -0.0021742849 0.0026300698 0 -3.586724e-04 1.711055e-05 #> deusventrue -0.0007936789 0.0028680575 0 1.774985e-04 -8.326845e-05 #> duvel -0.0006045816 -0.0028942242 0 -4.198782e-04 7.447638e-05 #> franziskaner -0.0015947508 0.0021935018 0 -8.367911e-04 -3.508429e-04 #> grimbergen -0.0035563564 -0.0004162333 0 -4.478525e-04 -1.575351e-04 #> guiness -0.0015222476 0.0005646464 0 4.379065e-05 -3.284575e-04 #> hoegardeen -0.0024579838 0.0023152691 0 -1.402306e-05 3.803656e-04 #> jupiler -0.0009974596 0.0023379940 0 1.831345e-04 -1.827727e-04 #> kingfisher -0.0004648420 0.0023788807 0 -1.644074e-04 -3.059412e-04 #> latrappe 0.0015068375 -0.0015514855 0 2.164816e-04 1.803082e-04 #> lindemanskriek -0.0009359325 0.0022848386 0 4.100249e-04 2.208045e-04 #> nicechouffe -0.0007619565 0.0033654095 0 5.495158e-04 -2.042167e-05 #> pecheresse -0.0013782823 0.0024185755 0 2.181959e-04 -7.311833e-05 #> sierranevada -0.0017933279 -0.0005349683 0 -2.089826e-04 -3.847117e-04 #> tanglefoot -0.0003179777 -0.0031166695 0 2.257469e-04 -2.009399e-04 #> tauro -0.0010466330 0.0023514452 0 1.762712e-04 -8.961804e-05 #> westmalle -0.0004882420 0.0023217071 0 2.683034e-04 5.829510e-04 #> amrut -0.0004155995 0.0028189180 0 3.259091e-04 3.840090e-04 #> ballantines -0.0024674938 -0.0002274846 0 -8.980074e-06 1.013064e-03 #> bushmills -0.0043970618 0.0017818484 0 8.084328e-04 8.012671e-04 #> chivas -0.0016654883 -0.0026415175 0 6.073651e-04 3.070684e-04 #> dalmore 0.0025922354 -0.0039822137 0 1.097768e-03 6.881659e-04 #> famousgrouse 0.0001300206 0.0046515437 0 1.287495e-04 -1.324051e-04 #> glendronach -0.0002084792 0.0025405566 0 4.149836e-04 1.394907e-04 #> glenmorangie -0.0001692272 0.0025838514 0 8.773153e-05 -6.257124e-05 #> highlandpark 0.0023214993 0.0028070218 0 -6.291662e-04 -7.091405e-04 #> jackdaniels -0.0011544544 0.0013660407 0 1.828207e-04 -5.854778e-04 #> jb -0.0026073348 0.0016289320 0 5.770034e-04 1.295536e-04 #> johnniewalker -0.0026799451 0.0046998857 0 1.610309e-03 1.521699e-03 #> magallan 0.0034410693 0.0056372281 0 -1.110357e-03 -1.017379e-03 #> makersmark -0.0037381840 0.0031052372 0 -2.272912e-03 -1.921977e-03 #> oban -0.0000555700 0.0026159662 0 5.217373e-04 3.289690e-04 #> oldpotrero 0.0002650070 0.0005717670 0 -4.566144e-04 2.434271e-04 #> redbreast -0.0017153754 -0.0017080604 0 1.568632e-04 1.213587e-04 #> tamdhu -0.0004660552 0.0022520466 0 1.013117e-03 4.671170e-04 #> wildturkey -0.0011040540 0.0003877287 0 9.489660e-04 9.344159e-04 #> yoichi -0.0005670111 0.0040850862 0 2.371406e-04 3.337929e-04 #> B4 B5 B6 B7 #> brahma -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 #> caney 3.333918e-04 -2.899903e-04 7.350207e-05 -4.952054e-04 #> chimay 3.227901e-04 -2.906714e-05 5.573360e-04 1.059517e-04 #> corona -5.501057e-04 -1.907425e-04 -4.256287e-04 -2.147013e-04 #> deusventrue -1.403373e-03 -3.240180e-04 -9.330047e-04 6.515692e-04 #> duvel -6.627095e-04 6.107940e-05 -4.746985e-04 2.450959e-04 #> franziskaner -6.983186e-04 -1.894199e-04 -5.170165e-04 5.988419e-05 #> grimbergen 1.554676e-04 5.257427e-05 1.132609e-04 -6.848791e-05 #> guiness -1.677242e-04 -5.817648e-04 -2.853668e-04 -5.620867e-04 #> hoegardeen 3.285812e-04 4.813766e-04 3.691213e-04 5.309204e-04 #> jupiler -4.540203e-05 -1.242456e-04 -5.198885e-05 -2.289954e-04 #> kingfisher -1.751841e-04 3.014782e-05 2.132220e-04 4.144846e-04 #> latrappe 5.468038e-04 2.303760e-04 5.053959e-04 2.603399e-04 #> lindemanskriek 2.791269e-04 -2.076986e-04 -1.312595e-04 -1.367999e-04 #> nicechouffe 2.492854e-04 2.171344e-04 2.155297e-04 1.621249e-04 #> pecheresse 2.879648e-04 3.072908e-05 1.503582e-04 2.875235e-05 #> sierranevada 2.254752e-04 -1.582761e-04 3.201773e-04 -2.506594e-04 #> tanglefoot -3.556495e-04 -4.589428e-04 -1.231722e-04 -1.030225e-04 #> tauro 8.045507e-05 4.030041e-05 1.942858e-04 7.124766e-05 #> westmalle 2.086425e-04 5.569697e-04 -1.481080e-04 2.680453e-04 #> amrut 2.692429e-04 2.370884e-04 4.975910e-05 1.929742e-04 #> ballantines -2.175286e-04 1.006239e-03 -2.063087e-04 6.874951e-04 #> bushmills 9.888621e-04 5.333749e-04 6.026329e-04 3.382499e-07 #> chivas 1.231654e-04 -3.404412e-05 8.988476e-05 1.476812e-04 #> dalmore 2.545366e-04 1.352642e-04 -1.253930e-04 2.101188e-04 #> famousgrouse -1.274614e-04 2.141211e-04 -1.073666e-04 1.188717e-05 #> glendronach 1.071609e-04 -2.016928e-04 -6.904446e-05 -1.327779e-04 #> glenmorangie 1.913928e-04 -9.675222e-05 1.480796e-04 -8.118855e-05 #> highlandpark -2.204109e-04 -5.021317e-04 3.287316e-04 -2.505046e-04 #> jackdaniels -7.969529e-04 -4.880520e-04 -1.903562e-04 3.092736e-04 #> jb -1.422141e-04 -2.056778e-04 -2.053789e-04 1.048725e-04 #> johnniewalker 1.140415e-03 1.505532e-04 2.156619e-04 -1.772208e-04 #> magallan -7.964354e-04 -6.143625e-04 -3.734865e-04 -1.291146e-04 #> makersmark -3.452843e-04 -1.437534e-04 4.289043e-04 -9.732915e-04 #> oban 3.351843e-04 4.359254e-05 1.826487e-05 -6.027186e-05 #> oldpotrero -2.060062e-04 3.778706e-05 -5.576392e-04 2.258336e-04 #> redbreast -1.087561e-04 -1.587376e-04 -9.420764e-05 -7.636860e-06 #> tamdhu 2.449976e-04 3.452581e-05 -1.344683e-04 1.407481e-04 #> wildturkey 2.048265e-04 1.038328e-04 7.988232e-06 2.379076e-04 #> yoichi 2.790195e-04 2.201285e-04 1.423493e-05 -5.626562e-05 #> B8 B9 B10 B11 #> brahma 6.268503e-06 -1.960132e-04 1.334431e-04 4.058288e-05 #> caney 8.536695e-05 -4.143363e-04 1.667420e-04 -3.134942e-04 #> chimay 6.209192e-04 1.441644e-04 1.715223e-04 5.930974e-05 #> corona -1.931107e-04 -3.048499e-04 -2.065499e-04 -2.244684e-04 #> deusventrue -8.354423e-04 2.287499e-05 -6.080012e-04 2.971827e-04 #> duvel -1.676532e-04 1.512500e-04 6.986965e-05 2.318703e-04 #> franziskaner -3.810484e-04 5.133436e-05 -3.407356e-04 5.681736e-05 #> grimbergen -9.289817e-05 2.532879e-05 1.655384e-04 3.086461e-04 #> guiness -1.496463e-04 -4.662246e-04 -1.905673e-04 -3.642220e-04 #> hoegardeen 3.462062e-04 4.557837e-04 4.205444e-04 3.080245e-04 #> jupiler -8.073101e-05 -2.203453e-04 -1.514837e-04 -1.572771e-04 #> kingfisher 1.324881e-05 1.991329e-04 1.802238e-04 2.681872e-04 #> latrappe 1.829641e-04 2.106651e-04 -1.447749e-04 2.756836e-04 #> lindemanskriek 4.871774e-05 -4.788973e-05 -2.120403e-04 -1.394498e-04 #> nicechouffe 1.463372e-04 2.488056e-04 8.034353e-05 2.586078e-04 #> pecheresse 2.759482e-04 1.481251e-05 1.433130e-04 -1.556835e-05 #> sierranevada 1.406542e-04 -1.888577e-04 6.806233e-05 -5.042849e-05 #> tanglefoot 5.673867e-06 -2.751261e-04 -3.002656e-04 -2.455063e-04 #> tauro 2.932668e-04 1.286768e-04 1.547277e-04 1.336644e-04 #> westmalle -1.539093e-04 4.586356e-04 1.799417e-05 3.301881e-04 #> amrut 1.570262e-04 2.548664e-04 1.115168e-04 7.490810e-06 #> ballantines -3.868333e-05 3.003380e-04 1.592670e-04 -5.079525e-05 #> bushmills 2.135771e-04 -2.019147e-04 1.348464e-04 -1.302260e-04 #> chivas 1.332194e-04 1.056333e-04 2.227781e-05 4.227956e-05 #> dalmore -4.021158e-06 2.679348e-04 -2.632871e-05 1.881627e-04 #> famousgrouse -2.566731e-04 2.195639e-04 -7.568478e-05 1.842423e-04 #> glendronach 2.453495e-05 -7.915842e-06 -1.865175e-05 -6.786263e-05 #> glenmorangie 1.557411e-04 -3.527084e-06 1.414448e-04 -9.027797e-06 #> highlandpark 3.870735e-04 -4.437162e-04 1.970082e-04 -4.866817e-04 #> jackdaniels -1.751848e-04 -3.777874e-05 -1.953733e-04 2.389926e-04 #> jb 1.396719e-04 1.902920e-04 -7.877557e-05 4.429623e-05 #> johnniewalker 5.133497e-04 1.719490e-04 5.339652e-04 -1.814410e-04 #> magallan -1.577770e-04 -1.006505e-04 -1.482048e-04 -8.058980e-06 #> makersmark -5.600587e-04 -7.200799e-04 4.777646e-04 2.581853e-04 #> oban 8.787835e-05 1.113193e-04 1.307306e-04 -2.483305e-05 #> oldpotrero -3.831452e-04 2.156873e-04 -5.679089e-04 2.063675e-04 #> redbreast 2.541246e-05 2.426826e-05 -8.753325e-05 -8.652635e-06 #> tamdhu -3.383952e-05 3.365051e-04 -1.785979e-04 -4.280721e-06 #> wildturkey 3.002663e-04 1.207047e-04 1.615231e-04 -7.004425e-06 #> yoichi -1.168653e-04 -8.227670e-05 5.854442e-05 8.229082e-05 #> B12 C1 C2 C3 C4 #> brahma -1.917814e-04 0 -1.637571e-03 -3.936895e-03 5.408096e-03 #> caney 2.011956e-05 0 1.239828e-03 -2.845651e-04 3.757825e-04 #> chimay -3.197006e-06 0 -3.757608e-03 -1.797357e-03 -2.127924e-03 #> corona -6.091420e-06 0 -1.652864e-03 1.573302e-03 4.897281e-04 #> deusventrue -2.794108e-04 0 1.552775e-03 7.706329e-04 -1.416448e-03 #> duvel 1.659893e-04 0 2.872128e-04 -5.422392e-06 -7.785717e-04 #> franziskaner -2.140707e-04 0 -1.253868e-03 3.476506e-04 1.004621e-03 #> grimbergen 1.890428e-04 0 1.700875e-03 -1.452474e-04 4.332935e-04 #> guiness -2.602631e-04 0 -5.088378e-04 1.628258e-03 5.025916e-05 #> hoegardeen 2.814325e-04 0 -2.538102e-03 6.627214e-04 -1.481847e-03 #> jupiler -1.151375e-04 0 9.877198e-04 -8.223351e-05 1.286204e-04 #> kingfisher 1.550433e-04 0 8.355893e-04 -2.193322e-03 -9.853901e-04 #> latrappe -1.942322e-04 0 2.026476e-03 6.109498e-04 -1.518299e-04 #> lindemanskriek -5.113408e-05 0 -1.736348e-03 1.465734e-03 -1.513403e-03 #> nicechouffe 4.652882e-05 0 -5.467071e-04 2.799211e-04 -4.577128e-04 #> pecheresse 1.587407e-04 0 1.796104e-03 -3.206383e-04 -1.338857e-04 #> sierranevada 3.125122e-05 0 9.370620e-04 -7.543929e-04 2.972714e-04 #> tanglefoot -9.215486e-05 0 -7.405447e-04 3.028807e-04 6.337466e-04 #> tauro 1.226045e-04 0 1.122815e-04 -2.572009e-04 -8.133564e-04 #> westmalle 4.757341e-05 0 1.228197e-03 -2.741133e-04 9.140310e-05 #> amrut -9.179140e-05 0 4.658444e-04 -4.347520e-04 -3.326225e-05 #> ballantines 3.235267e-04 0 -5.591149e-04 1.469581e-03 -1.536579e-03 #> bushmills 2.015409e-04 0 -3.958316e-04 1.944836e-03 -7.053533e-05 #> chivas -6.666931e-05 0 -1.172232e-03 -1.218925e-03 -3.262755e-05 #> dalmore -9.894417e-05 0 6.958725e-04 -1.680610e-03 6.152298e-04 #> famousgrouse -7.211196e-05 0 7.115395e-05 8.468121e-04 -4.933730e-04 #> glendronach -9.224044e-05 0 -7.099606e-05 6.421159e-04 -4.706785e-04 #> glenmorangie 6.261072e-05 0 -8.919633e-06 -2.628346e-04 9.674043e-05 #> highlandpark 1.369676e-04 0 -1.617000e-03 5.528353e-04 -3.372340e-04 #> jackdaniels 3.169089e-04 0 5.328968e-04 -1.540810e-03 -5.769145e-04 #> jb -5.463792e-05 0 -2.505933e-03 -9.424246e-04 -8.780719e-04 #> johnniewalker -5.200179e-05 0 4.677592e-03 -4.233763e-04 -1.898993e-03 #> magallan -1.072102e-04 0 2.189543e-04 4.632813e-04 1.888985e-04 #> makersmark 8.085419e-06 0 1.698257e-03 -6.596354e-04 3.533379e-04 #> oban -6.805926e-05 0 6.795967e-07 1.085005e-06 -4.641661e-04 #> oldpotrero -3.604369e-04 0 -6.093255e-05 4.513517e-05 -4.902640e-04 #> redbreast 1.217829e-04 0 -1.468386e-03 1.265193e-04 -1.396525e-04 #> tamdhu -2.219702e-04 0 9.586941e-04 6.330302e-04 -2.779959e-04 #> wildturkey 2.260401e-05 0 -9.213008e-05 -1.129525e-03 -4.176692e-04 #> yoichi 1.472054e-04 0 5.380772e-05 -7.906572e-05 -7.656576e-04 #> C5 C6 C7 C8 #> brahma -1.259407e-03 -3.994402e-03 3.268582e-03 4.792269e-04 #> caney -4.017802e-05 4.699805e-04 2.518166e-04 6.300072e-04 #> chimay -4.663387e-04 -7.424827e-05 -8.096453e-05 9.946667e-04 #> corona 1.867708e-04 6.888736e-04 3.145355e-04 5.189042e-04 #> deusventrue 1.463377e-03 9.055123e-04 -2.834923e-04 -1.443910e-03 #> duvel 3.178998e-04 2.219253e-04 5.438377e-04 -3.518900e-06 #> franziskaner 1.054384e-03 2.433412e-04 9.526672e-04 8.662476e-04 #> grimbergen -6.417041e-04 -1.403671e-03 1.850428e-04 1.990252e-04 #> guiness 8.516115e-05 5.947385e-04 -3.856099e-04 2.426892e-04 #> hoegardeen -6.536099e-04 -5.091092e-04 -6.872483e-04 -4.089876e-04 #> jupiler 4.242307e-04 1.903101e-04 -1.512322e-04 3.486794e-04 #> kingfisher 1.200089e-03 4.039578e-05 -2.246083e-04 -6.682649e-04 #> latrappe -2.100725e-04 4.680496e-04 1.907268e-04 -1.386083e-04 #> lindemanskriek 2.721525e-04 -8.593526e-04 -1.905709e-04 1.402970e-04 #> nicechouffe -4.033887e-04 -3.674008e-04 -1.582921e-04 -3.898917e-04 #> pecheresse -3.165154e-04 -6.798663e-04 -1.857663e-04 -5.070674e-04 #> sierranevada 4.903049e-04 5.175725e-04 -5.450918e-04 -6.169308e-04 #> tanglefoot 6.556462e-04 1.058980e-03 8.585128e-04 5.745493e-04 #> tauro -4.748704e-04 -3.315681e-04 -4.564306e-04 -3.514821e-04 #> westmalle -4.491227e-04 -2.495132e-04 -7.270457e-05 -1.344863e-04 #> amrut 8.477464e-05 -1.080422e-04 2.126076e-04 -9.256970e-05 #> ballantines 6.528392e-04 -2.944984e-04 -5.656855e-04 1.789388e-04 #> bushmills 9.280815e-04 -4.013982e-04 -6.650163e-04 -5.644542e-04 #> chivas 1.300827e-04 -3.851168e-05 4.239507e-05 1.334791e-04 #> dalmore -2.964899e-04 -1.304289e-04 7.782306e-04 -4.877421e-04 #> famousgrouse 6.303902e-04 -1.322629e-04 -2.372041e-04 -2.550728e-05 #> glendronach -3.501431e-04 -2.525866e-04 3.742212e-04 1.133101e-04 #> glenmorangie -3.395833e-04 -4.246431e-04 -3.274667e-04 1.061570e-04 #> highlandpark 6.066669e-04 1.088092e-03 5.256719e-04 5.273203e-04 #> jackdaniels 1.023982e-03 9.323203e-04 1.214171e-03 5.898250e-04 #> jb 2.339479e-04 3.473492e-04 3.733691e-04 1.626720e-04 #> johnniewalker -8.686486e-04 -1.355694e-03 1.175580e-03 3.264915e-04 #> magallan 2.310078e-04 -1.038695e-04 -1.026307e-05 1.023165e-04 #> makersmark -5.037028e-04 -1.240866e-04 -7.956100e-05 -6.606345e-05 #> oban -3.076544e-04 -4.937905e-04 -1.310019e-05 -2.416906e-04 #> oldpotrero -5.717320e-04 -9.307817e-04 1.291075e-04 -5.512552e-04 #> redbreast -6.765261e-04 1.325618e-04 4.297985e-04 3.419357e-04 #> tamdhu -1.871447e-04 -1.524034e-04 6.923348e-05 -5.932353e-04 #> wildturkey -5.568095e-04 1.396939e-04 -3.130911e-04 -2.441291e-05 #> yoichi -1.807137e-04 -7.887244e-04 -4.647802e-04 -2.321719e-04 #> C9 C10 C11 C12 #> brahma -1.321861e-03 7.225736e-04 2.052451e-04 1.666890e-04 #> caney 4.837212e-04 -3.443095e-04 1.349160e-04 4.336526e-06 #> chimay -5.660053e-04 2.292011e-04 3.851391e-04 -2.066153e-05 #> corona 3.419355e-04 -4.427112e-05 5.053095e-04 2.703064e-04 #> deusventrue 5.149210e-05 4.983572e-04 -8.471361e-05 3.773608e-04 #> duvel 4.727181e-05 8.518990e-04 5.267156e-05 -7.761916e-06 #> franziskaner 4.052798e-04 2.307566e-04 5.425481e-04 8.822035e-04 #> grimbergen -4.235811e-04 -1.047152e-04 8.528320e-05 -4.862829e-04 #> guiness 2.578559e-05 -4.057230e-04 3.454914e-04 3.070080e-04 #> hoegardeen -2.093222e-04 -8.166019e-05 -5.849685e-04 -1.080950e-04 #> jupiler 3.426590e-04 1.476449e-04 3.134641e-04 2.698336e-04 #> kingfisher 1.267526e-04 2.565541e-04 -2.246671e-04 6.355569e-05 #> latrappe -4.351985e-06 -5.637614e-05 4.355069e-04 3.406179e-04 #> lindemanskriek -4.691485e-04 6.262551e-04 3.619995e-05 5.173449e-04 #> nicechouffe -2.084102e-04 4.207808e-04 7.211961e-05 -7.528575e-05 #> pecheresse -2.691263e-04 -5.693772e-04 -3.209598e-04 2.785471e-04 #> sierranevada 1.686643e-04 2.583335e-04 8.547137e-04 -1.139936e-04 #> tanglefoot 7.740523e-04 4.070373e-04 5.906937e-04 9.596081e-04 #> tauro -3.210499e-04 -2.265987e-04 5.213196e-05 1.560054e-07 #> westmalle 4.839335e-04 5.801730e-05 1.736045e-04 -1.456983e-04 #> amrut -1.864115e-04 -2.461486e-04 -3.925113e-04 -1.058934e-04 #> ballantines -5.195587e-04 3.044292e-04 -2.940957e-04 -8.254562e-05 #> bushmills -7.180710e-04 9.032786e-05 -3.120552e-04 3.338259e-04 #> chivas -3.525098e-05 -9.088640e-05 2.114664e-04 -4.123221e-05 #> dalmore 2.200639e-05 -1.248926e-04 -1.755355e-06 2.379108e-04 #> famousgrouse -3.212998e-04 3.215665e-04 -7.784050e-05 -5.945648e-04 #> glendronach 9.391914e-05 1.721023e-04 -5.496005e-04 -4.452810e-05 #> glenmorangie -1.452951e-05 2.274608e-05 8.210480e-05 2.227747e-04 #> highlandpark -1.043832e-04 2.593737e-04 7.274696e-06 -7.945600e-05 #> jackdaniels -6.541464e-05 8.873609e-04 3.142194e-04 5.911319e-04 #> jb -2.944987e-04 2.504811e-05 -2.127576e-05 -1.962938e-04 #> johnniewalker -8.111435e-05 -2.403699e-04 -1.403144e-03 -1.314933e-04 #> magallan 4.068423e-04 5.073294e-04 1.401801e-04 3.243760e-04 #> makersmark 4.971815e-04 6.070002e-04 1.442476e-05 -8.225582e-05 #> oban -1.976049e-04 -2.813942e-04 -2.577944e-04 -9.115022e-05 #> oldpotrero -5.682370e-04 1.529407e-07 -2.873197e-04 -1.840435e-04 #> redbreast -3.874401e-05 4.931648e-05 3.073398e-04 8.441133e-05 #> tamdhu -5.985664e-04 -4.647946e-04 -1.822017e-04 1.592463e-04 #> wildturkey 1.524887e-05 -6.414600e-04 2.874523e-04 -2.824274e-05 #> yoichi -2.834302e-04 1.556736e-04 -8.243757e-05 1.918715e-04 #> D1 D2 D3 D4 D5 #> brahma 0.2937120 -0.04602927 0.05240292 -0.035768593 0.03999516 #> caney 0.3046235 -0.07069129 0.05062805 -0.011400633 0.04383297 #> chimay 0.4156841 -0.09356117 0.04692603 -0.019249436 0.03965332 #> corona 0.2745921 -0.05755121 0.05150878 -0.011252954 0.03689351 #> deusventrue 0.3149661 -0.11964363 0.05529900 0.007135060 0.03861865 #> duvel 0.4496172 -0.09170033 0.05080071 -0.024018306 0.03036868 #> franziskaner 0.3002734 -0.05637154 0.04411627 -0.030282997 0.03014850 #> grimbergen 0.3651919 -0.09065897 0.05082210 -0.010242594 0.04317369 #> guiness 0.3505997 -0.08196508 0.04422914 -0.022614638 0.04330972 #> hoegardeen 0.2945708 -0.06921001 0.05080275 -0.012677940 0.04146196 #> jupiler 0.2872499 -0.06835188 0.05058090 -0.011055591 0.04109503 #> kingfisher 0.3038732 -0.06930174 0.04366992 -0.021888850 0.03308585 #> latrappe 0.4672257 -0.08743553 0.04401705 -0.038810531 0.02809569 #> lindemanskriek 0.3008112 -0.08389446 0.04783652 -0.013888395 0.04157982 #> nicechouffe 0.3127453 -0.09102591 0.04393446 -0.019927059 0.03779695 #> pecheresse 0.2877918 -0.07053519 0.05180968 -0.009320568 0.04090001 #> sierranevada 0.3773035 -0.07825101 0.05234901 -0.021705236 0.03981425 #> tanglefoot 0.4079636 -0.09801072 0.04110270 -0.028374451 0.04305818 #> tauro 0.2869165 -0.06868727 0.05072815 -0.010829946 0.04098501 #> westmalle 0.2901614 -0.07168182 0.04932024 -0.012449351 0.03886788 #> amrut 0.2916508 -0.07148727 0.03950517 -0.025866432 0.04086520 #> ballantines 0.4617826 -0.07263052 0.04705459 -0.054513278 0.00386769 #> bushmills 0.3159155 -0.02993821 0.05271205 -0.040523047 0.01619821 #> chivas 0.4010304 -0.12319740 0.04665481 -0.003452339 0.05226216 #> dalmore 0.4148687 -0.14805699 0.04396881 -0.010373143 0.05369374 #> famousgrouse 0.3082730 -0.05984603 0.04245023 -0.038145717 0.02994654 #> glendronach 0.2880496 -0.06941189 0.04010808 -0.026119002 0.04146027 #> glenmorangie 0.2784428 -0.06974209 0.02918920 -0.025306813 0.04836028 #> highlandpark 0.4216191 -0.07914764 0.04537064 -0.044351756 0.02868104 #> jackdaniels 0.3474874 -0.08171102 0.04501412 -0.023326513 0.04362364 #> jb 0.2978504 -0.07724044 0.04167029 -0.021228975 0.04549082 #> johnniewalker 0.3097702 -0.04720860 0.04457306 -0.040162288 0.02378800 #> magallan 0.2790080 -0.04764937 0.01811567 -0.036589697 0.02988117 #> makersmark 0.3905990 -0.12195322 0.04665759 0.014950483 0.04867625 #> oban 0.2773362 -0.07277254 0.03313763 -0.023775433 0.04405146 #> oldpotrero 0.3550787 -0.13906787 0.05059907 0.008348999 0.04726562 #> redbreast 0.3884532 -0.13265717 0.04117925 -0.003816545 0.05332588 #> tamdhu 0.2956700 -0.06219547 0.04086923 -0.024902731 0.04397834 #> wildturkey 0.3186215 -0.08962249 0.03633236 -0.023651702 0.05160018 #> yoichi 0.3745590 -0.07064336 0.04209729 -0.040564238 0.03281077 #> D6 D7 D8 D9 #> brahma 1.156917e-02 1.544573e-02 0.0013278090 0.0017860170 #> caney 4.485691e-03 9.597789e-03 0.0016029758 0.0082459711 #> chimay 1.731744e-02 1.044446e-02 0.0104067305 0.0026404547 #> corona -4.664986e-03 9.465002e-03 0.0001838085 0.0120730321 #> deusventrue -8.770510e-04 1.356919e-02 0.0076757796 0.0034745699 #> duvel 1.486796e-02 7.642213e-03 0.0154756340 0.0060020330 #> franziskaner 1.266218e-03 1.748451e-02 0.0047455611 0.0067787344 #> grimbergen 7.100085e-03 6.253179e-03 0.0076965820 0.0090999349 #> guiness 9.543784e-03 9.549881e-03 0.0017249204 0.0017518501 #> hoegardeen 2.601196e-03 1.267815e-02 0.0028528664 0.0079320590 #> jupiler 2.215650e-03 1.160311e-02 0.0034969489 0.0080290760 #> kingfisher 2.046087e-03 1.149394e-02 0.0039224376 0.0069746627 #> latrappe 2.444196e-02 2.163781e-02 0.0204539980 -0.0001441159 #> lindemanskriek 2.496230e-03 1.222294e-02 0.0053531769 0.0062723553 #> nicechouffe 3.314725e-03 1.247704e-02 0.0066425182 0.0051531928 #> pecheresse 2.471297e-03 1.468476e-02 0.0056123765 0.0084044229 #> sierranevada 1.057630e-02 8.974816e-03 0.0026404084 0.0003673360 #> tanglefoot 1.902021e-02 1.046530e-02 0.0039430719 -0.0033493172 #> tauro 2.321158e-03 1.173141e-02 0.0034750116 0.0079425387 #> westmalle 1.786521e-03 1.515342e-02 0.0060316179 0.0079388255 #> amrut 6.369733e-03 1.572832e-02 -0.0038463793 0.0013700406 #> ballantines 4.344419e-03 1.645402e-02 0.0254142957 0.0095935791 #> bushmills -1.167929e-02 2.000745e-02 0.0117755165 0.0158424792 #> chivas 7.036241e-03 -4.363041e-03 0.0063540528 0.0079672331 #> dalmore 1.718407e-02 -6.837798e-03 0.0070735547 -0.0019258037 #> famousgrouse 4.059251e-03 2.229183e-02 0.0037608752 0.0010406075 #> glendronach 6.223170e-03 1.521132e-02 -0.0043261577 0.0013210684 #> glenmorangie 5.822448e-03 1.976818e-02 -0.0044147538 0.0033213121 #> highlandpark 1.979571e-02 2.717259e-02 0.0200795294 -0.0021232596 #> jackdaniels 1.186579e-02 1.329499e-02 -0.0005343742 -0.0016003714 #> jb 6.441694e-03 1.187397e-02 -0.0057652170 0.0017868329 #> johnniewalker 8.789822e-05 2.661158e-02 0.0128165570 0.0105593342 #> magallan 6.181261e-03 2.628647e-02 0.0002557046 0.0036531313 #> makersmark -5.885380e-03 -3.124763e-04 0.0123974490 0.0123986615 #> oban 7.290747e-03 1.526810e-02 -0.0064234752 0.0024990961 #> oldpotrero -1.263673e-03 9.106123e-06 0.0131403235 0.0062358607 #> redbreast 7.554115e-03 -5.549155e-03 0.0028962725 0.0066649976 #> tamdhu 7.609569e-03 1.817766e-02 -0.0043937269 0.0004398248 #> wildturkey 1.072078e-02 1.329394e-02 -0.0045720419 -0.0006442784 #> yoichi 1.665764e-02 2.932085e-02 0.0147708913 0.0009353830 #> D10 D11 D12 #> brahma 0.006789017 0.0048196384 0.007143143 #> caney 0.011464283 0.0039468981 0.003663644 #> chimay 0.012590865 0.0018154608 0.002625857 #> corona 0.008346831 0.0027556006 0.002567053 #> deusventrue 0.006022626 0.0007085549 0.005811255 #> duvel 0.014318246 0.0021405582 -0.001168779 #> franziskaner 0.007215285 0.0030768626 0.006498196 #> grimbergen 0.013935311 0.0016133249 0.001782113 #> guiness 0.013609736 0.0052742301 0.006464424 #> hoegardeen 0.007661150 0.0026973921 0.005420800 #> jupiler 0.007523271 0.0027339312 0.004363034 #> kingfisher 0.006826146 0.0028630395 0.005290393 #> latrappe 0.007468498 -0.0011091276 0.003570302 #> lindemanskriek 0.007494807 0.0009831097 0.006687031 #> nicechouffe 0.007804735 0.0010554318 0.006544953 #> pecheresse 0.006507851 0.0023044001 0.005130825 #> sierranevada 0.013424754 0.0060565295 0.007716962 #> tanglefoot 0.012760316 0.0055315212 0.008787267 #> tauro 0.007452360 0.0026002512 0.004223806 #> westmalle 0.005389195 0.0009150318 0.004619774 #> amrut 0.008090140 0.0077694214 0.009648834 #> ballantines 0.009641210 -0.0013505569 0.001193993 #> bushmills 0.012190958 0.0027373737 0.003932980 #> chivas 0.019338356 0.0019726115 0.002305432 #> dalmore 0.016575636 0.0049437344 0.004000701 #> famousgrouse 0.003906640 0.0019458696 0.010187413 #> glendronach 0.008581179 0.0087430642 0.009902698 #> glenmorangie 0.007165778 0.0033642678 0.009454943 #> highlandpark 0.003043362 -0.0045393480 0.006887804 #> jackdaniels 0.009896143 0.0071305091 0.011652937 #> jb 0.011312129 0.0089093269 0.008895351 #> johnniewalker 0.004724823 -0.0013880745 0.003178167 #> magallan -0.002901850 0.0030725685 0.006182579 #> makersmark 0.007706173 -0.0025568628 0.002741739 #> oban 0.007789470 0.0092615797 0.008856510 #> oldpotrero 0.009884923 0.0004827760 0.006465018 #> redbreast 0.019010171 0.0030489037 0.003575003 #> tamdhu 0.006990252 0.0067355151 0.011091059 #> wildturkey 0.012225665 0.0056575767 0.009083087 #> yoichi 0.001967838 -0.0043542059 0.006408266 #getters bot.f[1] #> A1 A2 A3 A4 A5 #> 1.000000e+00 6.766531e-03 9.348184e-02 1.374288e-02 2.381857e-02 #> A6 A7 A8 A9 A10 #> 8.592275e-03 3.183571e-03 5.158502e-03 -7.262824e-04 4.728729e-03 #> A11 A12 B1 B2 B3 #> -1.373339e-03 1.636382e-03 0.000000e+00 -1.900652e-04 3.306231e-04 #> B4 B5 B6 B7 B8 #> -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> B9 B10 B11 B12 C1 #> -1.960132e-04 1.334431e-04 4.058288e-05 -1.917814e-04 0.000000e+00 #> C2 C3 C4 C5 C6 #> -1.637571e-03 -3.936895e-03 5.408096e-03 -1.259407e-03 -3.994402e-03 #> C7 C8 C9 C10 C11 #> 3.268582e-03 4.792269e-04 -1.321861e-03 7.225736e-04 2.052451e-04 #> C12 D1 D2 D3 D4 #> 1.666890e-04 2.937120e-01 -4.602927e-02 5.240292e-02 -3.576859e-02 #> D5 D6 D7 D8 D9 #> 3.999516e-02 1.156917e-02 1.544573e-02 1.327809e-03 1.786017e-03 #> D10 D11 D12 #> 6.789017e-03 4.819638e-03 7.143143e-03 bot.f[1:5] #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> A7 A8 A9 A10 A11 #> brahma 0.003183571 0.005158502 -0.0007262824 0.004728729 -0.0013733386 #> caney 0.003552709 0.007010166 0.0012149488 0.003873417 -0.0018777601 #> chimay -0.004741288 0.007814037 -0.0021126606 0.002204301 -0.0012371979 #> corona 0.005504589 0.007852411 0.0008767189 0.004420153 -0.0021742849 #> deusventrue 0.002521451 0.011391904 -0.0017339646 0.006208319 -0.0007936789 #> A12 B1 B2 B3 B4 #> brahma 0.001636382 0 -0.0001900652 3.306231e-04 -0.0005191749 #> caney 0.001133056 0 0.0005012013 -3.851293e-04 0.0003333918 #> chimay -0.001851423 0 0.0001843629 4.196107e-04 0.0003227901 #> corona 0.002630070 0 -0.0003586724 1.711055e-05 -0.0005501057 #> deusventrue 0.002868057 0 0.0001774985 -8.326845e-05 -0.0014033732 #> B5 B6 B7 B8 #> brahma 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> caney -2.899903e-04 7.350207e-05 -4.952054e-04 8.536695e-05 #> chimay -2.906714e-05 5.573360e-04 1.059517e-04 6.209192e-04 #> corona -1.907425e-04 -4.256287e-04 -2.147013e-04 -1.931107e-04 #> deusventrue -3.240180e-04 -9.330047e-04 6.515692e-04 -8.354423e-04 #> B9 B10 B11 B12 C1 #> brahma -1.960132e-04 0.0001334431 4.058288e-05 -1.917814e-04 0 #> caney -4.143363e-04 0.0001667420 -3.134942e-04 2.011956e-05 0 #> chimay 1.441644e-04 0.0001715223 5.930974e-05 -3.197006e-06 0 #> corona -3.048499e-04 -0.0002065499 -2.244684e-04 -6.091420e-06 0 #> deusventrue 2.287499e-05 -0.0006080012 2.971827e-04 -2.794108e-04 0 #> C2 C3 C4 C5 #> brahma -0.001637571 -0.0039368955 0.0054080962 -1.259407e-03 #> caney 0.001239828 -0.0002845651 0.0003757825 -4.017802e-05 #> chimay -0.003757608 -0.0017973566 -0.0021279238 -4.663387e-04 #> corona -0.001652864 0.0015733018 0.0004897281 1.867708e-04 #> deusventrue 0.001552775 0.0007706329 -0.0014164476 1.463377e-03 #> C6 C7 C8 C9 #> brahma -3.994402e-03 3.268582e-03 0.0004792269 -0.0013218613 #> caney 4.699805e-04 2.518166e-04 0.0006300072 0.0004837212 #> chimay -7.424827e-05 -8.096453e-05 0.0009946667 -0.0005660053 #> corona 6.888736e-04 3.145355e-04 0.0005189042 0.0003419355 #> deusventrue 9.055123e-04 -2.834923e-04 -0.0014439096 0.0000514921 #> C10 C11 C12 D1 D2 #> brahma 7.225736e-04 2.052451e-04 1.666890e-04 0.2937120 -0.04602927 #> caney -3.443095e-04 1.349160e-04 4.336526e-06 0.3046235 -0.07069129 #> chimay 2.292011e-04 3.851391e-04 -2.066153e-05 0.4156841 -0.09356117 #> corona -4.427112e-05 5.053095e-04 2.703064e-04 0.2745921 -0.05755121 #> deusventrue 4.983572e-04 -8.471361e-05 3.773608e-04 0.3149661 -0.11964363 #> D3 D4 D5 D6 D7 #> brahma 0.05240292 -0.03576859 0.03999516 0.011569168 0.015445729 #> caney 0.05062805 -0.01140063 0.04383297 0.004485691 0.009597789 #> chimay 0.04692603 -0.01924944 0.03965332 0.017317438 0.010444458 #> corona 0.05150878 -0.01125295 0.03689351 -0.004664986 0.009465002 #> deusventrue 0.05529900 0.00713506 0.03861865 -0.000877051 0.013569192 #> D8 D9 D10 D11 D12 #> brahma 0.0013278090 0.001786017 0.006789017 0.0048196384 0.007143143 #> caney 0.0016029758 0.008245971 0.011464283 0.0039468981 0.003663644 #> chimay 0.0104067305 0.002640455 0.012590865 0.0018154608 0.002625857 #> corona 0.0001838085 0.012073032 0.008346831 0.0027556006 0.002567053 #> deusventrue 0.0076757796 0.003474570 0.006022626 0.0007085549 0.005811255 #setters bot.f[1] <- 1:48 bot.f[1] #> A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 B1 B2 B3 B4 B5 B6 B7 B8 #> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 #> B9 B10 B11 B12 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 D1 D2 D3 D4 #> 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 #> D5 D6 D7 D8 D9 D10 D11 D12 #> 41 42 43 44 45 46 47 48 bot.f[1:5] <- matrix(1:48, nrow=5, ncol=48, byrow=TRUE) bot.f[1:5] #> A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 B1 B2 B3 B4 B5 B6 B7 B8 B9 #> brahma 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> caney 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> chimay 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> corona 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> deusventrue 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> B10 B11 B12 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 D1 D2 D3 D4 D5 #> brahma 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> caney 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> chimay 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> corona 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> deusventrue 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> D6 D7 D8 D9 D10 D11 D12 #> brahma 42 43 44 45 46 47 48 #> caney 42 43 44 45 46 47 48 #> chimay 42 43 44 45 46 47 48 #> corona 42 43 44 45 46 47 48 #> deusventrue 42 43 44 45 46 47 48 # An illustration of Momocs design. See also browseVignettes(\"Momocs\") op <- opoly(olea, 5) #> 'nb.pts' missing and set to 91 op #> An OpnCoe object [ opoly analysis ] #> -------------------- #> - $coe: 210 open outlines described #> - $baseline1: (-0.5; 0), $baseline2: (0.5; 0) #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows class(op) #> [1] \"OpnCoe\" \"Coe\" op$coe # same thing #> Intercept x1 x2 x3 #> 0001-cAglan_O10VD 0.21728164 0.0820952380 -0.9016209 -0.0174933751 #> 0001-cAglan_O10VL 0.17440503 0.0338452396 -0.7077580 0.0188673254 #> 0001-cAglan_O11VD 0.17605784 -0.0181821226 -0.7153938 0.1131745169 #> 0001-cAglan_O11VL 0.20898408 -0.0527533722 -0.8654223 0.1766857390 #> 0001-cAglan_O12VD 0.22447919 0.0803230491 -0.9347773 0.0199351810 #> 0001-cAglan_O12VL 0.16235742 -0.0029369654 -0.6681510 0.0094286444 #> 0001-cAglan_O13VD 0.17792822 0.1754468212 -0.6844379 -0.0426301053 #> 0001-cAglan_O13VL 0.12672618 0.0009579514 -0.4663127 0.0002345741 #> 0001-cAglan_O14VD 0.21462762 0.0275940379 -0.8877420 0.0207363970 #> 0001-cAglan_O14VL 0.24974677 0.0114295543 -1.0496960 0.1144096127 #> 0001-cAglan_O15VD 0.19125493 0.1178119754 -0.7754215 -0.0039554397 #> 0001-cAglan_O15VL 0.12573315 -0.0158948388 -0.4548061 0.0543785873 #> 0001-cAglan_O16VD 0.19275344 0.1335641240 -0.7407366 -0.0987824861 #> 0001-cAglan_O16VL 0.24017875 0.0998083066 -1.0275196 -0.0037535364 #> 0001-cAglan_O17VD 0.22266045 0.0450388784 -0.9143523 0.0821645804 #> 0001-cAglan_O17VL 0.14600009 0.0498660478 -0.5422968 -0.0177351114 #> 0001-cAglan_O18VD 0.18420883 0.0304249548 -0.7217056 0.0571329023 #> 0001-cAglan_O18VL 0.12370513 -0.0362631392 -0.4909825 0.0458185347 #> 0001-cAglan_O19VD 0.20335401 0.0688023425 -0.8376389 0.0301347622 #> 0001-cAglan_O19VL 0.10684954 0.0041514686 -0.4071094 -0.0299624759 #> 0001-cAglan_O1VD 0.16530209 0.1263146505 -0.6782789 -0.0034335994 #> 0001-cAglan_O1VL 0.19264672 0.0047761942 -0.7913757 0.0958098961 #> 0001-cAglan_O20VD 0.18702310 0.1170531651 -0.7718111 -0.0272053979 #> 0001-cAglan_O20VL 0.12455551 -0.1083609770 -0.4811603 0.0629221022 #> 0001-cAglan_O21VD 0.17541333 0.0482173654 -0.7129816 -0.0052934872 #> 0001-cAglan_O21VL 0.13049212 -0.0750878456 -0.4945857 0.0640272991 #> 0001-cAglan_O22VD 0.21975666 0.0479308615 -0.9492226 0.0518640458 #> 0001-cAglan_O22VL 0.13247622 0.1404248712 -0.5054903 -0.0621738164 #> 0001-cAglan_O23VD 0.22546285 0.0560745366 -0.9582186 0.0037159169 #> 0001-cAglan_O23VL 0.24212924 0.0306932017 -1.0294416 0.1008862908 #> 0001-cAglan_O24VD 0.19318748 0.0424466715 -0.7711831 0.0273252643 #> 0001-cAglan_O24VL 0.14187946 -0.1420795711 -0.5392139 0.1535110671 #> 0001-cAglan_O25VD 0.18053154 0.1413722364 -0.7120755 -0.0994062981 #> 0001-cAglan_O25VL 0.11205801 0.1145850318 -0.4103983 -0.0618476073 #> 0001-cAglan_O26VD 0.20239973 0.0491003232 -0.8116939 -0.0175482137 #> 0001-cAglan_O26VL 0.14441048 0.0087197306 -0.5656701 0.0070965080 #> 0001-cAglan_O27VD 0.19430070 0.0758451426 -0.7543155 0.0160106238 #> 0001-cAglan_O27VL 0.13920048 -0.1010581520 -0.5586223 0.0824978707 #> 0001-cAglan_O28VD 0.21103626 0.0480058027 -0.8697517 -0.0050330250 #> 0001-cAglan_O28VL 0.20666836 0.0652070221 -0.8580052 0.0618490877 #> 0001-cAglan_O29VD 0.19468832 0.1445491038 -0.7807559 -0.1027170275 #> 0001-cAglan_O29VL 0.13299249 0.0500979876 -0.5446079 -0.0428964882 #> 0001-cAglan_O2VD 0.18049983 0.0742832172 -0.6915010 0.0075562215 #> 0001-cAglan_O2VL 0.12957708 -0.0371674783 -0.4899516 0.0134470093 #> 0001-cAglan_O30VD 0.19619922 0.0931831051 -0.7633346 -0.0037734250 #> 0001-cAglan_O30VL 0.13428137 -0.0949855468 -0.5180637 0.0730540220 #> 0001-cAglan_O3VD 0.18655581 0.0503218080 -0.7466846 0.0600255045 #> 0001-cAglan_O3VL 0.10854441 -0.0474882700 -0.4081974 -0.0023889824 #> 0001-cAglan_O4VD 0.22464009 0.0530388472 -0.9231306 0.0245281902 #> 0001-cAglan_O4VL 0.25130340 0.0544045848 -1.0351560 0.1001221781 #> 0001-cAglan_O5VD 0.21794122 0.0351172137 -0.8976885 0.0302506978 #> 0001-cAglan_O5VL 0.13854661 -0.1147399504 -0.5017741 0.1196361395 #> 0001-cAglan_O6VD 0.20929001 0.0317274815 -0.7933405 0.0455941659 #> 0001-cAglan_O6VL 0.10830615 -0.1334772845 -0.3818526 0.1085296685 #> 0001-cAglan_O7VD 0.19979218 0.0724848350 -0.7838685 0.0291604988 #> 0001-cAglan_O7VL 0.12137446 -0.1837766964 -0.4631785 0.1706838053 #> 0001-cAglan_O8VD 0.20441821 0.0443971169 -0.7750116 0.0648743263 #> 0001-cAglan_O8VL 0.13794457 -0.0427969220 -0.5336686 0.0354710750 #> 0001-cAglan_O9VD 0.22777242 0.0873679949 -0.9150431 -0.0305524031 #> 0001-cAglan_O9VL 0.13432972 -0.0663483259 -0.5186668 0.0576614115 #> 0010-cCypre_O10VD 0.21664664 0.0771151861 -0.8431580 0.0055686844 #> 0010-cCypre_O11VD 0.22657769 0.0840561136 -0.9403420 0.0351501734 #> 0010-cCypre_O12VD 0.20752990 0.0469980910 -0.8678666 -0.0064508049 #> 0010-cCypre_O13VD 0.21798817 0.1190150584 -0.8851341 0.0095341683 #> 0010-cCypre_O14VD 0.23790243 0.0880242563 -0.9476860 -0.0249063104 #> 0010-cCypre_O15VD 0.20192972 0.1043675498 -0.8099470 -0.0772529666 #> 0010-cCypre_O16VD 0.18846979 0.0521564425 -0.7454236 0.0247565427 #> 0010-cCypre_O17VD 0.19741251 0.1214672023 -0.8177804 0.0094837781 #> 0010-cCypre_O18VD 0.20484860 0.0150117186 -0.8090948 0.0262257293 #> 0010-cCypre_O19VD 0.21911959 -0.0071448581 -0.8783165 0.0950756512 #> 0010-cCypre_O1VD 0.21652524 0.0307253605 -0.8838807 0.0144966562 #> 0010-cCypre_O20VD 0.20437503 0.0446890906 -0.8481292 0.0012982517 #> 0010-cCypre_O21VD 0.20928315 -0.0047425083 -0.8365906 0.0851338181 #> 0010-cCypre_O22VD 0.20068649 0.0263515305 -0.8175089 0.0190617822 #> 0010-cCypre_O23VD 0.20200118 0.0442913447 -0.7690188 0.0286214821 #> 0010-cCypre_O24VD 0.20970105 0.0954665632 -0.8690775 -0.0342843373 #> 0010-cCypre_O25VD 0.19558959 0.0528796642 -0.7621603 -0.0035064562 #> 0010-cCypre_O26VD 0.16092845 0.1105083238 -0.6260891 -0.0519766946 #> 0010-cCypre_O27VD 0.22354804 0.0762563877 -0.9073819 0.0113738310 #> 0010-cCypre_O28VD 0.25284411 0.1135089079 -1.0562199 -0.0705761142 #> 0010-cCypre_O29VD 0.20929228 0.1024298793 -0.8112258 0.0130465695 #> 0010-cCypre_O2VD 0.21539905 0.1119643380 -0.8590483 -0.0027835694 #> 0010-cCypre_O30VD 0.21085574 0.0948220712 -0.8491454 -0.0568053215 #> 0010-cCypre_O3VD 0.21821076 0.0632225313 -0.8760574 0.0047080623 #> 0010-cCypre_O4VD 0.17573972 0.0836760575 -0.6897838 0.0262641847 #> 0010-cCypre_O5VD 0.21132292 0.0716806643 -0.8214542 -0.0261368673 #> 0010-cCypre_O6VD 0.20888227 0.0177411558 -0.8064397 0.0466703965 #> 0010-cCypre_O7VD 0.22546726 0.0742158994 -0.9324599 -0.0103709292 #> 0010-cCypre_O8VD 0.22285661 0.0988769143 -0.8868088 -0.0118949221 #> 0010-cCypre_O9VD 0.18084614 0.0550005047 -0.7079343 0.0372301333 #> 0023-cPicMa_O10VD 0.18023440 -0.0104423084 -0.7036097 0.0574064601 #> 0023-cPicMa_O10VL 0.13896766 -0.0666344995 -0.5452281 0.0685926652 #> 0023-cPicMa_O11VD 0.15869729 -0.0290777606 -0.6325277 0.0379601479 #> 0023-cPicMa_O11VL 0.13502523 -0.1076669957 -0.4992451 0.1154668016 #> 0023-cPicMa_O12VD 0.16826500 0.0741055368 -0.6874212 0.0946456510 #> 0023-cPicMa_O12VL 0.11781090 -0.1453200143 -0.4870541 0.0812109800 #> 0023-cPicMa_O13VD 0.16301131 0.0778725780 -0.6149270 -0.0571360912 #> 0023-cPicMa_O13VL 0.12275098 -0.0527633558 -0.4675046 0.0307095588 #> 0023-cPicMa_O14VD 0.13827935 0.1266522382 -0.5025416 -0.0192610457 #> 0023-cPicMa_O14VL 0.10647158 -0.1522085315 -0.3914520 0.1304719508 #> 0023-cPicMa_O15VD 0.16556813 0.0393342982 -0.6320543 0.0863640911 #> 0023-cPicMa_O15VL 0.12745864 -0.1428865216 -0.4695294 0.1339881982 #> 0023-cPicMa_O16VD 0.16045134 0.0168314773 -0.6108011 0.0134530243 #> 0023-cPicMa_O16VL 0.12029119 -0.1170753181 -0.4365765 0.0835421031 #> 0023-cPicMa_O17VD 0.16226592 0.0816795634 -0.6016251 0.0298334288 #> 0023-cPicMa_O17VL 0.11357658 -0.1792328355 -0.3986460 0.1322992067 #> 0023-cPicMa_O18VD 0.16638132 0.0684949076 -0.5956065 0.0264991566 #> 0023-cPicMa_O18VL 0.11848233 -0.0363097034 -0.4669173 0.0006087119 #> 0023-cPicMa_O19VD 0.16901084 0.0378944650 -0.6589385 0.0740530662 #> 0023-cPicMa_O19VL 0.22644888 0.0763861985 -0.9323757 0.0506926913 #> 0023-cPicMa_O1VD 0.12849178 -0.1342044221 -0.5483587 0.0968465651 #> 0023-cPicMa_O1VL 0.11480402 -0.2179034919 -0.4930746 0.1561838956 #> 0023-cPicMa_O20VD 0.15926487 0.0395733248 -0.5931178 0.0209588733 #> 0023-cPicMa_O20VL 0.21817155 0.0634661933 -0.8472227 0.0489972849 #> 0023-cPicMa_O21VD 0.14475764 0.1162981960 -0.5619421 -0.0020248439 #> 0023-cPicMa_O21VL 0.19242857 0.0943166568 -0.7961330 0.0331400784 #> 0023-cPicMa_O22VD 0.16100106 -0.0427769008 -0.6491867 0.0171716149 #> 0023-cPicMa_O22VL 0.12490782 -0.1809323658 -0.5294327 0.0951303181 #> 0023-cPicMa_O23VD 0.18289145 0.0640759483 -0.7037168 -0.0078132994 #> 0023-cPicMa_O23VL 0.13452876 -0.1312014149 -0.5802704 0.0996591952 #> 0023-cPicMa_O24VD 0.19934999 0.0456096654 -0.7958312 -0.0004781872 #> 0023-cPicMa_O24VL 0.12963319 -0.1572994323 -0.5721961 0.1086123738 #> 0023-cPicMa_O25VD 0.14439059 -0.0146215488 -0.5419901 0.0306888082 #> 0023-cPicMa_O25VL 0.10502262 -0.1073404149 -0.4122691 0.1050740550 #> 0023-cPicMa_O26VD 0.16272318 0.0888197913 -0.5747101 -0.0479273126 #> 0023-cPicMa_O26VL 0.09568899 -0.1213585727 -0.3809030 0.0659043677 #> 0023-cPicMa_O27VD 0.12524989 -0.0573789027 -0.4711746 0.0307401429 #> 0023-cPicMa_O27VL 0.13361958 -0.0928477731 -0.5328221 0.0749206862 #> 0023-cPicMa_O28VD 0.21391197 0.0675319793 -0.8683864 -0.0566872739 #> 0023-cPicMa_O28VL 0.14369714 -0.0701206032 -0.5640867 0.0591683033 #> 0023-cPicMa_O29VD 0.15773919 0.0662362921 -0.6110751 -0.0507006097 #> 0023-cPicMa_O29VL 0.13028478 -0.0471713489 -0.4877567 0.0414531712 #> 0023-cPicMa_O2VD 0.15271084 0.0992512146 -0.6006278 0.0252888763 #> 0023-cPicMa_O2VL 0.12709431 -0.0944840154 -0.5058892 0.0760934497 #> 0023-cPicMa_O30VD 0.17732452 0.0563426943 -0.6601990 0.0621056170 #> 0023-cPicMa_O30VL 0.11544940 -0.1863099061 -0.4840974 0.1826444722 #> 0023-cPicMa_O3VD 0.17960537 0.0191052345 -0.6953965 -0.0004361502 #> 0023-cPicMa_O3VL 0.11576084 -0.0928395617 -0.4491746 0.0710991480 #> 0023-cPicMa_O4VD 0.14926554 0.0864129714 -0.5701828 0.0209237652 #> 0023-cPicMa_O4VL 0.11981147 -0.1522480705 -0.4663968 0.1165253617 #> 0023-cPicMa_O5VD 0.11037121 -0.0432484353 -0.4150343 0.0078200940 #> 0023-cPicMa_O5VL 0.07092883 -0.1236401109 -0.2737980 0.0720750035 #> 0023-cPicMa_O6VD 0.17806477 0.0363866228 -0.7292810 -0.0253226650 #> 0023-cPicMa_O6VL 0.13172240 -0.0529433591 -0.5388466 0.0348096395 #> 0023-cPicMa_O7VD 0.14579934 -0.1049938929 -0.6189755 0.0878308325 #> 0023-cPicMa_O7VL 0.10160327 -0.1987401594 -0.4375640 0.1536385781 #> 0023-cPicMa_O8VD 0.17021212 0.0832735755 -0.6301950 0.0156335714 #> 0023-cPicMa_O8VL 0.21504814 0.0924220700 -0.8673284 0.0367395161 #> 0023-cPicMa_O9VD 0.17824041 -0.0115237793 -0.6806192 0.0372814840 #> 0023-cPicMa_O9VL 0.12788664 -0.1443870373 -0.5150814 0.1169215484 #> 0125-wMouBo1_O10VD 0.23074741 -0.0101734290 -0.9391095 0.0661802550 #> 0125-wMouBo1_O10VL 0.24990343 0.0836208995 -1.0408045 0.0386524965 #> 0125-wMouBo1_O11VD 0.23053038 0.0628572473 -0.9705205 -0.0080583183 #> 0125-wMouBo1_O11VL 0.21624241 0.0449956240 -0.9030091 0.0705556367 #> 0125-wMouBo1_O12VD 0.19066115 0.0458008145 -0.7902542 0.0442912598 #> 0125-wMouBo1_O12VL 0.23561435 0.1028016687 -0.9467364 0.0408696967 #> 0125-wMouBo1_O13VD 0.25267603 0.0925693911 -1.0495399 -0.0191122008 #> 0125-wMouBo1_O13VL 0.23204287 0.0008319173 -0.9553313 0.1079494264 #> 0125-wMouBo1_O14VD 0.21939596 0.0614014037 -0.9278719 0.0073275779 #> 0125-wMouBo1_O14VL 0.22992852 0.1190731238 -0.9126497 -0.0144151468 #> 0125-wMouBo1_O15VD 0.21512832 -0.0272326723 -0.8580552 0.0510604863 #> 0125-wMouBo1_O15VL 0.25352482 0.0977260428 -1.0174843 0.0204523978 #> 0125-wMouBo1_O16VD 0.23423614 0.0633411629 -0.9697099 0.0546065802 #> 0125-wMouBo1_O16VL 0.23326324 0.0488121606 -0.9494775 0.0695524370 #> 0125-wMouBo1_O17VD 0.22052161 0.0832275267 -0.9054632 0.0488414527 #> 0125-wMouBo1_O17VL 0.23176223 0.0423807072 -0.9708804 0.0691689042 #> 0125-wMouBo1_O18VD 0.22137457 0.0667803792 -0.9594549 -0.0053748893 #> 0125-wMouBo1_O18VL 0.21477981 0.0995960722 -0.8879203 0.0419509417 #> 0125-wMouBo1_O19VD 0.20398899 -0.0609533423 -0.8709192 0.1105576865 #> 0125-wMouBo1_O19VL 0.20426129 0.0509978535 -0.8246557 0.0040920315 #> 0125-wMouBo1_O1VD 0.22026276 0.0780412149 -0.9278662 0.0354235848 #> 0125-wMouBo1_O1VL 0.23496803 0.1139643929 -0.9551441 0.0292138104 #> 0125-wMouBo1_O20VD 0.21821767 0.0322591445 -0.9016256 0.0602308906 #> 0125-wMouBo1_O20VL 0.23442593 0.0327895956 -0.9817619 0.0597326015 #> 0125-wMouBo1_O21VD 0.18909979 0.0462617258 -0.7798647 0.0297087552 #> 0125-wMouBo1_O21VL 0.24969155 0.0995791291 -1.0188876 0.0488933559 #> 0125-wMouBo1_O22VD 0.22984107 0.0654461893 -0.9451709 0.0310217968 #> 0125-wMouBo1_O22VL 0.24550951 0.0520980933 -1.0086728 0.0572622480 #> 0125-wMouBo1_O23VD 0.24925436 0.0373694748 -1.0252985 0.0209736348 #> 0125-wMouBo1_O23VL 0.22043348 -0.0301946741 -0.9294530 0.0394466473 #> 0125-wMouBo1_O24VD 0.22290706 0.0805151751 -0.9019173 0.0418668268 #> 0125-wMouBo1_O24VL 0.24100542 0.0335096307 -0.9785418 0.0623975907 #> 0125-wMouBo1_O25VD 0.23384817 0.0816932466 -0.9911284 -0.0068789229 #> 0125-wMouBo1_O25VL 0.22292557 0.0432838189 -0.9333467 0.0574774987 #> 0125-wMouBo1_O26VD 0.21810243 0.0513093050 -0.9217217 -0.0131430251 #> 0125-wMouBo1_O26VL 0.19810765 0.0242678007 -0.8075390 0.0565630002 #> 0125-wMouBo1_O27VD 0.23187453 0.0453093495 -0.9894214 -0.0085185471 #> 0125-wMouBo1_O27VL 0.20408385 0.0202634500 -0.8002120 0.0336295414 #> 0125-wMouBo1_O28VD 0.22025843 0.1121501527 -0.9198706 -0.0582466407 #> 0125-wMouBo1_O28VL 0.18561477 0.0032354513 -0.7452582 0.0375723248 #> 0125-wMouBo1_O29VD 0.25709114 0.1175532466 -1.0950456 -0.0212746551 #> 0125-wMouBo1_O29VL 0.23486253 0.0577475395 -0.9383747 0.0560995104 #> 0125-wMouBo1_O2VD 0.22302483 0.0333965363 -0.9413178 0.0243144765 #> 0125-wMouBo1_O2VL 0.23892087 0.0979275281 -0.9877977 -0.0168207170 #> 0125-wMouBo1_O30VD 0.27219534 0.1190873704 -1.1221068 0.0269060340 #> 0125-wMouBo1_O30VL 0.25088715 0.0935315155 -1.0587948 0.0425885246 #> 0125-wMouBo1_O3VD 0.23337441 0.0519188288 -0.9806883 0.0214060409 #> 0125-wMouBo1_O3VL 0.21313679 0.0075232908 -0.8638998 0.0355457609 #> 0125-wMouBo1_O4VD 0.19510917 -0.0262698897 -0.7865855 0.0824134876 #> 0125-wMouBo1_O4VL 0.24148398 0.0590954249 -1.0192049 0.0133718728 #> 0125-wMouBo1_O5VD 0.23463351 0.0127890100 -0.9947945 0.0617170374 #> 0125-wMouBo1_O5VL 0.23540593 0.0927530157 -0.9473588 0.0241599004 #> 0125-wMouBo1_O6VD 0.21388069 0.0448125843 -0.8811050 -0.0187149803 #> 0125-wMouBo1_O6VL 0.19693370 -0.0404391694 -0.7981819 0.1110957370 #> 0125-wMouBo1_O7VD 0.23515227 0.0636867722 -0.9362205 0.0767137787 #> 0125-wMouBo1_O7VL 0.19075490 0.0693636751 -0.7369358 0.0102032851 #> 0125-wMouBo1_O8VD 0.22059769 0.0238591389 -0.9479522 0.0622891501 #> 0125-wMouBo1_O8VL 0.22524616 0.0696864084 -0.9204583 0.0659353881 #> 0125-wMouBo1_O9VD 0.23668791 0.0296600751 -1.0124501 0.0659259928 #> 0125-wMouBo1_O9VL 0.22708513 0.0726133899 -0.9372184 0.0486002167 #> x4 x5 #> 0001-cAglan_O10VD -0.1122924204 0.011811482 #> 0001-cAglan_O10VL -0.0779230878 0.029245826 #> 0001-cAglan_O11VD -0.0532882009 0.006747825 #> 0001-cAglan_O11VL -0.1117488969 0.023925077 #> 0001-cAglan_O12VD -0.1449913711 -0.042287326 #> 0001-cAglan_O12VL -0.0379246316 0.063364106 #> 0001-cAglan_O13VD -0.1250633094 -0.054783966 #> 0001-cAglan_O13VL -0.0798250819 0.017944805 #> 0001-cAglan_O14VD -0.1308675889 0.011091031 #> 0001-cAglan_O14VL -0.2004433864 0.045232179 #> 0001-cAglan_O15VD -0.0919883678 -0.059553445 #> 0001-cAglan_O15VL -0.0871089172 0.018909477 #> 0001-cAglan_O16VD -0.1380569681 -0.042979021 #> 0001-cAglan_O16VL -0.1548657148 -0.037662322 #> 0001-cAglan_O17VD -0.1444969953 -0.011744608 #> 0001-cAglan_O17VL -0.0694319614 0.033040122 #> 0001-cAglan_O18VD -0.1020634949 -0.029566500 #> 0001-cAglan_O18VL -0.0204580794 0.039427706 #> 0001-cAglan_O19VD -0.1131448867 -0.035180217 #> 0001-cAglan_O19VL -0.0328009617 0.034406695 #> 0001-cAglan_O1VD -0.0494508094 -0.017792278 #> 0001-cAglan_O1VL -0.0675891208 -0.006894284 #> 0001-cAglan_O20VD -0.0693864212 -0.068788491 #> 0001-cAglan_O20VL -0.0519473662 0.069127856 #> 0001-cAglan_O21VD -0.0690504967 0.029583750 #> 0001-cAglan_O21VL -0.0572925691 0.039067673 #> 0001-cAglan_O22VD -0.0733540268 -0.034595355 #> 0001-cAglan_O22VL -0.0211530345 -0.007149806 #> 0001-cAglan_O23VD -0.1693545165 0.035544176 #> 0001-cAglan_O23VL -0.1668900643 0.001166044 #> 0001-cAglan_O24VD -0.1005547221 0.031901050 #> 0001-cAglan_O24VL -0.0719870654 0.036591949 #> 0001-cAglan_O25VD -0.0908727626 0.025277881 #> 0001-cAglan_O25VL -0.0280126192 0.013721081 #> 0001-cAglan_O26VD -0.1245654638 0.046648700 #> 0001-cAglan_O26VL -0.0502755364 0.042628438 #> 0001-cAglan_O27VD -0.1408497750 -0.019202606 #> 0001-cAglan_O27VL -0.0507554258 0.029550696 #> 0001-cAglan_O28VD -0.1154323362 0.032326606 #> 0001-cAglan_O28VL -0.1173164923 -0.017835140 #> 0001-cAglan_O29VD -0.0869127901 0.007539585 #> 0001-cAglan_O29VL -0.0067273762 0.023726566 #> 0001-cAglan_O2VD -0.1032251214 0.016413419 #> 0001-cAglan_O2VL -0.0855077702 0.027421298 #> 0001-cAglan_O30VD -0.1172515186 0.007129656 #> 0001-cAglan_O30VL -0.0600350227 0.050921750 #> 0001-cAglan_O3VD -0.0790997095 -0.023984316 #> 0001-cAglan_O3VL -0.0392628872 0.035887647 #> 0001-cAglan_O4VD -0.1276614263 0.020245469 #> 0001-cAglan_O4VL -0.2121600328 0.034486435 #> 0001-cAglan_O5VD -0.1284843396 0.042959266 #> 0001-cAglan_O5VL -0.1120167371 0.060378285 #> 0001-cAglan_O6VD -0.1633809410 0.053901214 #> 0001-cAglan_O6VL -0.0442512950 0.054976662 #> 0001-cAglan_O7VD -0.1322575676 -0.036853482 #> 0001-cAglan_O7VL -0.0294330372 0.036555650 #> 0001-cAglan_O8VD -0.1652197160 -0.006575256 #> 0001-cAglan_O8VL -0.0707585310 0.040124177 #> 0001-cAglan_O9VD -0.1759010895 -0.037099969 #> 0001-cAglan_O9VL -0.0507375054 0.021052215 #> 0010-cCypre_O10VD -0.1907663852 0.033668073 #> 0010-cCypre_O11VD -0.1525375504 -0.030964361 #> 0010-cCypre_O12VD -0.1231142611 -0.065651764 #> 0010-cCypre_O13VD -0.1644570401 -0.074020050 #> 0010-cCypre_O14VD -0.2271665800 0.041464998 #> 0010-cCypre_O15VD -0.1350791563 -0.004793408 #> 0010-cCypre_O16VD -0.0956731090 -0.003839584 #> 0010-cCypre_O17VD -0.0901885112 -0.046486991 #> 0010-cCypre_O18VD -0.1403705992 0.084359742 #> 0010-cCypre_O19VD -0.1563634433 0.062309880 #> 0010-cCypre_O1VD -0.1346347584 0.051534887 #> 0010-cCypre_O20VD -0.1215729802 0.026564366 #> 0010-cCypre_O21VD -0.1376461798 0.096000661 #> 0010-cCypre_O22VD -0.1060803100 0.064167473 #> 0010-cCypre_O23VD -0.1329278852 0.034698758 #> 0010-cCypre_O24VD -0.0930279840 0.005855714 #> 0010-cCypre_O25VD -0.1381173573 -0.007826328 #> 0010-cCypre_O26VD -0.0775672556 0.009821264 #> 0010-cCypre_O27VD -0.1487340347 -0.031215169 #> 0010-cCypre_O28VD -0.2124403577 -0.001384415 #> 0010-cCypre_O29VD -0.1641377620 -0.029696650 #> 0010-cCypre_O2VD -0.1447761610 -0.044424134 #> 0010-cCypre_O30VD -0.1339518135 0.007734536 #> 0010-cCypre_O3VD -0.1547479282 0.023163341 #> 0010-cCypre_O4VD -0.0997767339 -0.020756902 #> 0010-cCypre_O5VD -0.1761225193 0.041985220 #> 0010-cCypre_O6VD -0.1582268752 0.073067174 #> 0010-cCypre_O7VD -0.1754658206 0.023412541 #> 0010-cCypre_O8VD -0.1851627118 0.035725658 #> 0010-cCypre_O9VD -0.1021910356 -0.012082703 #> 0023-cPicMa_O10VD -0.0857539759 0.061289379 #> 0023-cPicMa_O10VL -0.0564807376 0.068334285 #> 0023-cPicMa_O11VD -0.0551361198 0.042508240 #> 0023-cPicMa_O11VL -0.0853995635 0.046183371 #> 0023-cPicMa_O12VD -0.0327860101 -0.059873043 #> 0023-cPicMa_O12VL -0.0388282159 0.088302812 #> 0023-cPicMa_O13VD -0.1001633543 0.033842951 #> 0023-cPicMa_O13VL -0.0636811761 0.035023652 #> 0023-cPicMa_O14VD -0.0729737229 -0.053417115 #> 0023-cPicMa_O14VL -0.0313737876 0.060946265 #> 0023-cPicMa_O15VD -0.1008239212 -0.032607123 #> 0023-cPicMa_O15VL -0.0984171536 0.029341475 #> 0023-cPicMa_O16VD -0.0607390806 0.081181128 #> 0023-cPicMa_O16VL -0.0721021678 0.094294448 #> 0023-cPicMa_O17VD -0.0772352632 -0.014461957 #> 0023-cPicMa_O17VL -0.0593830883 0.081110589 #> 0023-cPicMa_O18VD -0.1335489220 -0.018785123 #> 0023-cPicMa_O18VL -0.0600621897 0.013575514 #> 0023-cPicMa_O19VD -0.0721537904 -0.027002789 #> 0023-cPicMa_O19VL -0.1612410146 0.015468415 #> 0023-cPicMa_O1VD -0.0091607201 0.080203390 #> 0023-cPicMa_O1VL -0.0291126840 0.076773890 #> 0023-cPicMa_O20VD -0.0843202662 0.014591763 #> 0023-cPicMa_O20VL -0.2102592669 0.049305586 #> 0023-cPicMa_O21VD -0.0294556808 -0.039773874 #> 0023-cPicMa_O21VL -0.1013156169 -0.016776722 #> 0023-cPicMa_O22VD -0.0705997881 0.071158584 #> 0023-cPicMa_O22VL -0.0619885032 0.075882177 #> 0023-cPicMa_O23VD -0.1004483432 0.034087273 #> 0023-cPicMa_O23VL -0.0380569222 0.081488131 #> 0023-cPicMa_O24VD -0.1103975534 0.031535176 #> 0023-cPicMa_O24VL -0.0267003906 0.040516694 #> 0023-cPicMa_O25VD -0.0841112011 0.068130610 #> 0023-cPicMa_O25VL 0.0036493955 0.044123037 #> 0023-cPicMa_O26VD -0.1422762062 0.019234925 #> 0023-cPicMa_O26VL 0.0005981636 0.054609082 #> 0023-cPicMa_O27VD -0.0585286462 0.070009911 #> 0023-cPicMa_O27VL -0.0520978825 0.059749831 #> 0023-cPicMa_O28VD -0.1440411643 0.016242607 #> 0023-cPicMa_O28VL -0.0910726089 0.023344220 #> 0023-cPicMa_O29VD -0.0704700003 0.035313517 #> 0023-cPicMa_O29VL -0.0829926763 0.047269699 #> 0023-cPicMa_O2VD -0.0639971447 -0.056753292 #> 0023-cPicMa_O2VL -0.0459464593 0.034596955 #> 0023-cPicMa_O30VD -0.1006703190 -0.034561788 #> 0023-cPicMa_O30VL -0.0209529952 0.053568090 #> 0023-cPicMa_O3VD -0.1249799045 0.025985322 #> 0023-cPicMa_O3VL -0.0270558927 0.048189316 #> 0023-cPicMa_O4VD -0.0387193850 -0.051098804 #> 0023-cPicMa_O4VL -0.0399518540 0.078274009 #> 0023-cPicMa_O5VD -0.0364361232 0.063559785 #> 0023-cPicMa_O5VL -0.0009228800 0.038845032 #> 0023-cPicMa_O6VD -0.0527213482 0.072467493 #> 0023-cPicMa_O6VL -0.0262096667 0.044631921 #> 0023-cPicMa_O7VD -0.0193040556 0.076181244 #> 0023-cPicMa_O7VL -0.0164588009 0.065974155 #> 0023-cPicMa_O8VD -0.1011002383 -0.050500162 #> 0023-cPicMa_O8VL -0.1474562057 -0.055326861 #> 0023-cPicMa_O9VD -0.1229228162 0.052863918 #> 0023-cPicMa_O9VL -0.0471838228 0.042469701 #> 0125-wMouBo1_O10VD -0.1875598962 0.068769161 #> 0125-wMouBo1_O10VL -0.1832705835 -0.004511738 #> 0125-wMouBo1_O11VD -0.1616470914 0.031138798 #> 0125-wMouBo1_O11VL -0.1223357674 0.011970531 #> 0125-wMouBo1_O12VD -0.1143140795 0.036669271 #> 0125-wMouBo1_O12VL -0.1868888245 -0.011632125 #> 0125-wMouBo1_O13VD -0.1937221789 0.020989146 #> 0125-wMouBo1_O13VL -0.1469640409 0.031287779 #> 0125-wMouBo1_O14VD -0.1114505748 0.031490738 #> 0125-wMouBo1_O14VL -0.1800797076 -0.028402206 #> 0125-wMouBo1_O15VD -0.1869858922 0.072466004 #> 0125-wMouBo1_O15VL -0.2168073770 -0.021286336 #> 0125-wMouBo1_O16VD -0.1535981261 0.011615355 #> 0125-wMouBo1_O16VL -0.1899418287 0.009715178 #> 0125-wMouBo1_O17VD -0.1391688664 -0.005128136 #> 0125-wMouBo1_O17VL -0.1277018851 -0.009272098 #> 0125-wMouBo1_O18VD -0.1443842365 0.031073880 #> 0125-wMouBo1_O18VL -0.1390597617 -0.004759846 #> 0125-wMouBo1_O19VD -0.1441671535 0.060497508 #> 0125-wMouBo1_O19VL -0.1221715131 0.020918665 #> 0125-wMouBo1_O1VD -0.1417840460 -0.015559430 #> 0125-wMouBo1_O1VL -0.1698479339 -0.025768093 #> 0125-wMouBo1_O20VD -0.1372108152 -0.004491672 #> 0125-wMouBo1_O20VL -0.1535939815 0.029665377 #> 0125-wMouBo1_O21VD -0.0891273779 -0.005008645 #> 0125-wMouBo1_O21VL -0.1890499757 -0.015240229 #> 0125-wMouBo1_O22VD -0.1637553199 0.003421954 #> 0125-wMouBo1_O22VL -0.1623708983 -0.008730847 #> 0125-wMouBo1_O23VD -0.1834655316 0.026522318 #> 0125-wMouBo1_O23VL -0.1674130936 0.063389559 #> 0125-wMouBo1_O24VD -0.1586301633 -0.002838081 #> 0125-wMouBo1_O24VL -0.2039197415 -0.013594800 #> 0125-wMouBo1_O25VD -0.1682203008 0.017616638 #> 0125-wMouBo1_O25VL -0.1090353052 0.004866802 #> 0125-wMouBo1_O26VD -0.1583415388 0.030290845 #> 0125-wMouBo1_O26VL -0.1289387583 0.041994378 #> 0125-wMouBo1_O27VD -0.1677297119 0.056390324 #> 0125-wMouBo1_O27VL -0.1377412296 0.047386485 #> 0125-wMouBo1_O28VD -0.1441183994 0.006142353 #> 0125-wMouBo1_O28VL -0.1500057364 0.071254159 #> 0125-wMouBo1_O29VD -0.1841434041 0.006546213 #> 0125-wMouBo1_O29VL -0.1717283394 0.002413615 #> 0125-wMouBo1_O2VD -0.1787113472 0.029780265 #> 0125-wMouBo1_O2VL -0.2069887483 -0.008301580 #> 0125-wMouBo1_O30VD -0.2596889585 -0.033590471 #> 0125-wMouBo1_O30VL -0.2089829321 -0.009712427 #> 0125-wMouBo1_O3VD -0.1822212213 0.068692130 #> 0125-wMouBo1_O3VL -0.1615093101 0.059007889 #> 0125-wMouBo1_O4VD -0.1243448588 0.040692622 #> 0125-wMouBo1_O4VL -0.1712222718 -0.002086956 #> 0125-wMouBo1_O5VD -0.1581744157 0.064188642 #> 0125-wMouBo1_O5VL -0.2060281371 -0.040847996 #> 0125-wMouBo1_O6VD -0.1058225116 0.006360021 #> 0125-wMouBo1_O6VL -0.1285952926 0.066283858 #> 0125-wMouBo1_O7VD -0.1811606623 0.020997417 #> 0125-wMouBo1_O7VL -0.0819459609 0.008617285 #> 0125-wMouBo1_O8VD -0.1270985763 -0.005867603 #> 0125-wMouBo1_O8VL -0.1449122001 -0.006618885 #> 0125-wMouBo1_O9VD -0.1577287178 0.010577178 #> 0125-wMouBo1_O9VL -0.1480660701 -0.003695914 wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wp #> An LdkCoe [full Generalized Procrustes] object with: #> -------------------- #> - $coo: 127 configuration of landmarks (18 +/- 0 coordinates) #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows class(wp) # for Ldk methods, LdkCoe objects can also be considered as Coo objects #> [1] \"LdkCoe\" \"Coe\" \"Ldk\" \"Coo\" # so you can apply all Ldk methods available. wp$coe # Procrustes aligned coordinates #> x1 x2 x3 x4 x5 x6 #> AN1 -0.4907666 -0.0773009715 0.2219542 0.2627437 0.2631416 0.2458310 #> AN2 -0.4814136 -0.0043204711 0.2358591 0.2470304 0.2493796 0.2433619 #> AN3 -0.4624999 0.0085256951 0.2402046 0.2499734 0.2599811 0.2541803 #> AN4 -0.4529120 -0.0290010787 0.2450022 0.2644452 0.2662562 0.2580972 #> AN5 -0.4924779 -0.0212833505 0.2384236 0.2428850 0.2430784 0.2342010 #> AN6 -0.4648300 -0.0155847731 0.2292089 0.2471983 0.2543874 0.2527982 #> AN7 -0.4732081 -0.0574977850 0.2273573 0.2538051 0.2603828 0.2519172 #> AN8 -0.4698594 0.0504698979 0.2434539 0.2591684 0.2579988 0.2547464 #> AN9 -0.4649648 0.0035623360 0.2293834 0.2440605 0.2525448 0.2521638 #> AN10 -0.4504193 -0.0018707051 0.2480358 0.2576366 0.2590623 0.2538704 #> AN11 -0.4594860 -0.0067460377 0.2392940 0.2501128 0.2535707 0.2503424 #> TO12 -0.4549666 -0.0135654597 0.2181489 0.2384352 0.2483764 0.2467695 #> WY13 -0.4704734 0.0116630860 0.2330368 0.2543107 0.2622847 0.2600690 #> WY14 -0.4734689 0.0207999542 0.2337591 0.2504520 0.2525345 0.2461181 #> WY15 -0.4675774 -0.0292250770 0.2444459 0.2544484 0.2613803 0.2591811 #> WY16 -0.4614597 0.0161212662 0.2365561 0.2554997 0.2616627 0.2573814 #> UR17 -0.4679322 0.0137186315 0.2337384 0.2482512 0.2518451 0.2452852 #> UR18 -0.4959530 0.0510005057 0.2047701 0.2231605 0.2329740 0.2367396 #> UR19 -0.4634175 -0.0316943065 0.2226446 0.2456525 0.2585150 0.2571715 #> UR20 -0.4847293 -0.0173597990 0.2345076 0.2501136 0.2553717 0.2513819 #> CA21 -0.4842850 0.0063753386 0.2363630 0.2523859 0.2511070 0.2448517 #> CA22 -0.4686641 0.0433492114 0.2227406 0.2479682 0.2538936 0.2564965 #> CA23 -0.4624115 0.0521370117 0.2462273 0.2587035 0.2603057 0.2514573 #> CA24 -0.4496786 -0.0299209806 0.2410362 0.2679107 0.2707568 0.2625471 #> CA25 -0.4699837 0.0499912336 0.2468421 0.2602165 0.2600191 0.2493553 #> CA26 -0.4652044 -0.0216338175 0.2320537 0.2522195 0.2577222 0.2553325 #> CA27 -0.4539016 -0.0084621369 0.2347432 0.2567309 0.2678166 0.2672198 #> OR28 -0.4642004 -0.0478363995 0.2047891 0.2580593 0.2673629 0.2631468 #> MA29 -0.4629121 0.0321108444 0.2619494 0.2689998 0.2673808 0.2531957 #> MA30 -0.4744066 0.0030967297 0.2335851 0.2499520 0.2561755 0.2494846 #> MA31 -0.4837650 0.0069218722 0.2474991 0.2586511 0.2556787 0.2411284 #> PS32 -0.4966972 0.0391162185 0.2238874 0.2389734 0.2445282 0.2383284 #> PS33 -0.4861101 0.0458740448 0.2217242 0.2376278 0.2494514 0.2411975 #> PS34 -0.4926047 0.0150598747 0.2309942 0.2380733 0.2385704 0.2356709 #> PS35 -0.4707887 -0.0006005030 0.2405639 0.2530304 0.2561273 0.2532259 #> PS36 -0.4804750 0.0102748783 0.2281729 0.2477567 0.2516146 0.2473052 #> PS37 -0.4843792 0.0024029418 0.2177104 0.2418813 0.2524859 0.2451530 #> PS38 -0.4883758 0.0118492596 0.2295506 0.2450205 0.2523039 0.2467107 #> PS39 -0.4689716 0.0189766943 0.2274736 0.2403579 0.2492681 0.2490592 #> PS40 -0.4715872 0.0529053483 0.2305629 0.2444438 0.2523252 0.2487301 #> PS41 -0.4675117 0.0055336845 0.2178562 0.2412046 0.2558821 0.2563120 #> PS42 -0.4702167 -0.0323832015 0.2047675 0.2425465 0.2489391 0.2420843 #> PS43 -0.4640396 0.0755651863 0.2310033 0.2389107 0.2503819 0.2466330 #> AE44 -0.4752231 -0.0190036593 0.2392345 0.2483440 0.2546769 0.2535676 #> AE45 -0.4712468 0.0190843812 0.2210899 0.2369524 0.2457552 0.2464260 #> AE46 -0.4793075 0.0154345164 0.2355639 0.2479250 0.2481327 0.2417271 #> AE47 -0.4654301 0.0330019702 0.2193599 0.2444830 0.2499465 0.2496946 #> AE48 -0.4815365 -0.0064290149 0.2537134 0.2590958 0.2592869 0.2486677 #> AE49 -0.4632723 0.0162815933 0.2186887 0.2481676 0.2534765 0.2518944 #> AE50 -0.4817723 0.0276523610 0.2290102 0.2431281 0.2469943 0.2462860 #> AE51 -0.4717455 -0.0107373284 0.2350966 0.2508590 0.2535008 0.2475562 #> AE52 -0.4752186 0.0079643207 0.2161767 0.2389326 0.2506431 0.2488986 #> AE53 -0.4807181 -0.0193542092 0.2187462 0.2373243 0.2465864 0.2411295 #> AE54 -0.4726770 0.0042104072 0.2320799 0.2441318 0.2497205 0.2443859 #> AE55 -0.4646473 0.0320480284 0.2371872 0.2517296 0.2591495 0.2576346 #> AE56 -0.4658006 -0.0271433977 0.2317464 0.2510340 0.2581889 0.2566246 #> AE57 -0.4844660 -0.0221552886 0.2456692 0.2556408 0.2580763 0.2516870 #> AE58 -0.4730506 0.0582814685 0.2188507 0.2418793 0.2479542 0.2464591 #> AE59 -0.4828655 -0.0055133573 0.2354240 0.2617881 0.2592169 0.2434273 #> AE60 -0.4774249 0.0361789182 0.2263105 0.2476206 0.2512024 0.2451575 #> AE61 -0.4623119 -0.0375587499 0.2440043 0.2601320 0.2585395 0.2505482 #> AE62 -0.4902864 0.0139065201 0.2342103 0.2453327 0.2515635 0.2436809 #> AE63 -0.4779151 0.0059330973 0.2345515 0.2555558 0.2597442 0.2532415 #> AE64 -0.4868197 -0.0211344335 0.2364029 0.2454972 0.2499901 0.2497979 #> AE65 -0.4746840 0.0096365983 0.2263605 0.2404731 0.2468449 0.2468833 #> AE66 -0.4768653 0.0289818014 0.2154092 0.2364947 0.2510466 0.2478843 #> AE67 -0.4739933 -0.0127977235 0.2079788 0.2406013 0.2500045 0.2466718 #> AE68 -0.4695196 0.0127816215 0.2194103 0.2511412 0.2566561 0.2491946 #> AE69 -0.4870751 0.0120547996 0.2188035 0.2356834 0.2457794 0.2419043 #> AE70 -0.4739865 0.0073867906 0.2259563 0.2480186 0.2512018 0.2460852 #> AE71 -0.4876300 0.0068425512 0.2200598 0.2428513 0.2480821 0.2424443 #> AE72 -0.4796960 0.0081015641 0.2245357 0.2411730 0.2474304 0.2432591 #> AE73 -0.4844463 -0.0148392109 0.2478067 0.2592521 0.2566336 0.2446404 #> AE74 -0.4990544 0.0351093589 0.2067677 0.2418032 0.2463419 0.2380992 #> AE75 -0.4927988 0.0129269894 0.2264267 0.2395880 0.2468303 0.2461931 #> AE76 -0.4794825 0.0284282758 0.2124819 0.2288382 0.2378380 0.2369457 #> AE77 -0.4896619 0.0084220519 0.2270959 0.2420128 0.2492127 0.2442261 #> AE78 -0.4816176 0.0110479956 0.2354676 0.2510040 0.2487253 0.2391245 #> AE79 -0.4857004 0.0125998503 0.2206958 0.2543582 0.2570297 0.2508034 #> AE80 -0.4782865 0.0008280900 0.2179316 0.2396095 0.2500093 0.2469745 #> AE81 -0.4614159 0.0164243433 0.2175737 0.2373651 0.2517962 0.2540073 #> AE82 -0.4884021 -0.0106529196 0.2159937 0.2393296 0.2505881 0.2421417 #> AE83 -0.4705928 -0.0056291188 0.2332780 0.2532730 0.2575283 0.2451208 #> AE84 -0.4832577 0.0392237816 0.2217536 0.2451291 0.2578183 0.2496531 #> AE85 -0.4613904 0.0166551212 0.2382053 0.2526753 0.2534802 0.2513185 #> AE86 -0.4742992 0.0023745196 0.2348359 0.2477378 0.2523562 0.2464384 #> AE87 -0.4711525 0.0055153725 0.2358711 0.2574658 0.2635143 0.2571095 #> AE88 -0.4813500 0.0202470374 0.2403003 0.2525533 0.2551104 0.2482657 #> AE89 -0.4725693 0.0600504908 0.2260758 0.2477042 0.2506761 0.2478068 #> AE90 -0.4812507 -0.0129303990 0.2307134 0.2486744 0.2513002 0.2429985 #> AE91 -0.4786523 -0.0063253420 0.2179355 0.2412551 0.2465643 0.2444140 #> AE92 -0.4676820 0.0006938311 0.2213544 0.2480277 0.2560944 0.2529235 #> AE93 -0.4956653 0.0006840548 0.2156897 0.2387205 0.2509945 0.2478962 #> AE94 -0.4711722 -0.0241188538 0.2458578 0.2588251 0.2634248 0.2597967 #> AE95 -0.4682823 -0.0080591902 0.2282772 0.2477356 0.2517442 0.2493961 #> AE96 -0.4495492 0.0408870483 0.2371218 0.2474411 0.2576482 0.2554825 #> AE97 -0.4762984 -0.0156492648 0.2388590 0.2615816 0.2660422 0.2588822 #> AE98 -0.4818158 0.0129963689 0.2323245 0.2449118 0.2507871 0.2465823 #> AE99 -0.4614757 -0.0127074929 0.2380940 0.2533797 0.2576139 0.2549766 #> AE100 -0.4497946 0.0331081611 0.2442956 0.2624796 0.2649207 0.2608630 #> CX101 -0.4692319 0.0043634619 0.2378653 0.2518208 0.2526481 0.2438136 #> CX102 -0.4905300 0.0270883163 0.2294066 0.2431466 0.2477034 0.2460992 #> CX103 -0.4629903 -0.0081103619 0.2330432 0.2540206 0.2680640 0.2619114 #> CX104 -0.4757764 0.0111846575 0.2390570 0.2481937 0.2531685 0.2502457 #> CX105 -0.4707200 0.0024658276 0.2374990 0.2481015 0.2533622 0.2493150 #> CX106 -0.4721575 0.0364674010 0.2257939 0.2468190 0.2503209 0.2461980 #> CX107 -0.4586349 0.0375380173 0.2269382 0.2486108 0.2540931 0.2493498 #> CX108 -0.4555822 0.0433235841 0.2531397 0.2676689 0.2665428 0.2576097 #> CX109 -0.4673782 0.0307466957 0.2398543 0.2519916 0.2555273 0.2465431 #> CX110 -0.4674122 -0.0003222505 0.2453396 0.2530069 0.2577360 0.2522668 #> CX111 -0.4688050 0.0171390626 0.2322253 0.2482204 0.2509553 0.2498708 #> CX112 -0.4611885 0.0166490429 0.2453478 0.2565835 0.2619681 0.2541912 #> CX113 -0.4786753 -0.0009889972 0.2483928 0.2516808 0.2503696 0.2475798 #> CX114 -0.4534517 0.0315357559 0.2316239 0.2553673 0.2601520 0.2521237 #> CX115 -0.4519892 0.0053453871 0.2161357 0.2455742 0.2572942 0.2544695 #> CX116 -0.4664726 0.0505761629 0.2327811 0.2532666 0.2556895 0.2492648 #> CX117 -0.4699322 0.0067800321 0.2546779 0.2582515 0.2585119 0.2545017 #> CX118 -0.4743596 0.0174407482 0.2365392 0.2531061 0.2591999 0.2548841 #> CX119 -0.4852456 0.0178494773 0.2342953 0.2532951 0.2602392 0.2546899 #> CX120 -0.4584556 0.0247948239 0.2311389 0.2564422 0.2619657 0.2556872 #> CX121 -0.4786715 -0.0098771771 0.2132974 0.2425027 0.2597399 0.2573738 #> CX122 -0.4807543 0.0198286069 0.2200394 0.2448613 0.2524591 0.2488141 #> CX123 -0.4702682 0.0047998520 0.2179940 0.2374435 0.2468581 0.2448316 #> CX124 -0.4749652 0.0257023372 0.2346474 0.2481868 0.2486190 0.2419842 #> CX125 -0.4699447 0.0015294908 0.2237478 0.2492571 0.2553474 0.2514616 #> DE126 -0.4610240 0.0098009883 0.2072649 0.2380380 0.2459232 0.2479743 #> DE127 -0.4591336 -0.0137804922 0.2347116 0.2533782 0.2605132 0.2518624 #> x7 x8 x9 x10 x11 x12 #> AN1 0.2299132 0.2029523 0.12754162 0.042182258 -0.06705386 -0.4080934 #> AN2 0.2316637 0.1951394 0.14525661 0.046692739 -0.05400733 -0.4022972 #> AN3 0.2370495 0.1959378 0.12519983 0.014979026 -0.07538362 -0.4104857 #> AN4 0.2423502 0.1836886 0.11677357 0.017108857 -0.09535549 -0.3867750 #> AN5 0.2156942 0.1902824 0.12379899 0.037980571 -0.05810728 -0.4262095 #> AN6 0.2406748 0.2071285 0.13563608 0.022921784 -0.08840736 -0.4054317 #> AN7 0.2386089 0.1839125 0.14393189 0.015529416 -0.06601273 -0.3936616 #> AN8 0.2372610 0.1814280 0.10209739 0.017559790 -0.08976669 -0.4074332 #> AN9 0.2404959 0.1990063 0.13533299 0.022888995 -0.05166237 -0.4022091 #> AN10 0.2380631 0.1927745 0.12773111 0.023555421 -0.05535730 -0.4076816 #> AN11 0.2337952 0.1861500 0.12490842 0.034650317 -0.06861235 -0.4066079 #> TO12 0.2319654 0.1948143 0.11634810 0.010289772 -0.09517636 -0.4024563 #> WY13 0.2429500 0.2027251 0.11103405 0.015210900 -0.10773718 -0.4160152 #> WY14 0.2264757 0.1880802 0.12874425 0.047463769 -0.05674451 -0.4140549 #> WY15 0.2411312 0.1939658 0.12726697 0.028109702 -0.10622496 -0.4001009 #> WY16 0.2348279 0.1856137 0.12656646 0.022195509 -0.09799700 -0.4148173 #> UR17 0.2256359 0.1819762 0.11874875 0.030205566 -0.14620317 -0.3989015 #> UR18 0.2191726 0.1787242 0.11725644 0.035971318 -0.13829494 -0.4153716 #> UR19 0.2370094 0.1772675 0.10888634 0.033122053 -0.15096989 -0.3941168 #> UR20 0.2358529 0.1948558 0.12381844 0.039454341 -0.14588000 -0.4219834 #> CA21 0.2283203 0.1786453 0.11024649 0.011450452 -0.08813603 -0.4023493 #> CA22 0.2353073 0.1700845 0.10343629 0.023933224 -0.08859335 -0.4124978 #> CA23 0.2316811 0.1705135 0.10883994 0.016240897 -0.09614337 -0.4116485 #> CA24 0.2411870 0.1861375 0.10941810 0.025545675 -0.07374133 -0.3933004 #> CA25 0.2246680 0.1693253 0.11010653 0.015072380 -0.10079955 -0.4053513 #> CA26 0.2406196 0.1949255 0.13302253 0.034746032 -0.06341431 -0.4087796 #> CA27 0.2523273 0.2018624 0.10170951 0.028067192 -0.05578732 -0.3953147 #> OR28 0.2382177 0.1847685 0.12537017 0.037917311 -0.03948366 -0.4183748 #> MA29 0.2188114 0.1680060 0.12041047 0.028168458 -0.06859047 -0.3959214 #> MA30 0.2320145 0.1826054 0.10832796 0.038212321 -0.05391403 -0.4119382 #> MA31 0.2160846 0.1739956 0.11601883 0.037618441 -0.06334261 -0.4052627 #> PS32 0.2219508 0.1756635 0.10698420 0.031101903 -0.06916025 -0.4093229 #> PS33 0.2230743 0.1735176 0.11025278 -0.001058697 -0.08194420 -0.4054739 #> PS34 0.2128262 0.1807335 0.11093134 0.027976227 -0.07595346 -0.4223508 #> PS35 0.2397646 0.1978324 0.10179981 0.010201778 -0.08341705 -0.4070977 #> PS36 0.2276580 0.1737842 0.11977437 0.027760114 -0.06736491 -0.4160846 #> PS37 0.2241077 0.1838799 0.10808681 0.037746145 -0.05996708 -0.4100509 #> PS38 0.2292366 0.1882440 0.12219662 0.016952089 -0.09256166 -0.4052013 #> PS39 0.2392189 0.1905865 0.11587287 0.036269066 -0.09184273 -0.4124714 #> PS40 0.2256842 0.1818852 0.10862069 0.034456039 -0.07103136 -0.4122096 #> PS41 0.2427152 0.2024380 0.11492685 0.045251862 -0.07616414 -0.3994672 #> PS42 0.2300983 0.1856700 0.11236211 0.045307471 -0.04888561 -0.4157182 #> PS43 0.2230354 0.1755287 0.09157707 0.010204003 -0.08853094 -0.4031586 #> AE44 0.2379333 0.1778025 0.10740209 0.029505988 -0.06631350 -0.3999825 #> AE45 0.2296212 0.1927084 0.12015866 0.030523858 -0.08138917 -0.4164703 #> AE46 0.2260410 0.1882752 0.11506319 0.039630127 -0.07170307 -0.4128322 #> AE47 0.2336590 0.2022006 0.12438902 0.019005338 -0.10647131 -0.4066207 #> AE48 0.2213836 0.1733830 0.10626360 0.014883547 -0.11623004 -0.3996691 #> AE49 0.2330862 0.2023845 0.12885279 0.036371756 -0.06761234 -0.4001142 #> AE50 0.2316834 0.1912755 0.10355014 0.009909262 -0.08625418 -0.4127075 #> AE51 0.2350902 0.1755556 0.11998012 0.031372778 -0.04560103 -0.3918887 #> AE52 0.2266644 0.1922767 0.12813684 0.042501215 -0.06523957 -0.4062565 #> AE53 0.2271519 0.1847728 0.12010385 0.031181320 -0.07172065 -0.4149213 #> AE54 0.2219091 0.1785521 0.10673129 0.026300268 -0.08067577 -0.4179231 #> AE55 0.2412285 0.2029947 0.10433063 0.014346500 -0.11417625 -0.3982188 #> AE56 0.2387554 0.1855339 0.11091372 0.032685606 -0.08676041 -0.4106891 #> AE57 0.2230746 0.1710064 0.10686284 0.032430972 -0.06965827 -0.3926581 #> AE58 0.2335399 0.1984260 0.11968260 0.039453573 -0.08111629 -0.4088259 #> AE59 0.2190216 0.1658974 0.10659264 0.019676443 -0.06565151 -0.4075436 #> AE60 0.2207965 0.1892755 0.10485114 0.021230955 -0.10622079 -0.3950189 #> AE61 0.2319673 0.1791207 0.11323873 0.033474919 -0.09117433 -0.4028892 #> AE62 0.2301815 0.1893919 0.12121461 0.026022391 -0.07707926 -0.4106974 #> AE63 0.2353506 0.1848351 0.08901796 0.010846011 -0.07838534 -0.3986001 #> AE64 0.2331246 0.1800663 0.12307053 0.036445810 -0.06265560 -0.3965477 #> AE65 0.2339304 0.1980809 0.11928878 0.036953760 -0.11127081 -0.4115693 #> AE66 0.2265853 0.1781210 0.10019600 0.015003709 -0.10125446 -0.4116335 #> AE67 0.2371114 0.1925200 0.12123028 0.039855216 -0.07915587 -0.4158821 #> AE68 0.2253185 0.1745543 0.11024909 0.026342860 -0.09388029 -0.4084570 #> AE69 0.2304674 0.2000356 0.11907429 0.030358001 -0.07848555 -0.4151259 #> AE70 0.2256643 0.1967240 0.11330103 0.034313115 -0.09143355 -0.4073191 #> AE71 0.2312316 0.1856359 0.11612478 0.037422911 -0.06262702 -0.3944163 #> AE72 0.2230091 0.1702759 0.10187699 0.031247530 -0.08736808 -0.4140867 #> AE73 0.2242534 0.1720954 0.10375972 0.046785537 -0.06541305 -0.3923586 #> AE74 0.2097443 0.1688960 0.10269514 0.023631592 -0.08335478 -0.4180446 #> AE75 0.2312035 0.1721142 0.10056175 0.039650964 -0.06626761 -0.4092941 #> AE76 0.2247807 0.1858490 0.12302800 0.023489034 -0.08625115 -0.4218836 #> AE77 0.2265496 0.1878062 0.12198447 0.017234413 -0.08718955 -0.4026411 #> AE78 0.2194152 0.1797335 0.12830989 0.030379126 -0.07166252 -0.4012513 #> AE79 0.2274608 0.1813567 0.12039160 0.043563110 -0.08266743 -0.3908824 #> AE80 0.2367584 0.1957126 0.11536534 0.034683133 -0.07517053 -0.4148166 #> AE81 0.2343733 0.1963869 0.12072100 0.050079773 -0.05214437 -0.4026463 #> AE82 0.2133248 0.1894671 0.12630310 0.037863142 -0.08518389 -0.3987510 #> AE83 0.2225514 0.1849202 0.13031599 0.030076964 -0.07829979 -0.4112970 #> AE84 0.2302822 0.1895577 0.11475210 0.034240590 -0.08772584 -0.3918702 #> AE85 0.2382525 0.1965061 0.10015703 0.017901979 -0.08122826 -0.4125355 #> AE86 0.2294434 0.1865355 0.12273581 0.050832660 -0.05057700 -0.3965911 #> AE87 0.2324682 0.1835045 0.10520558 0.041487007 -0.06038956 -0.3992214 #> AE88 0.2332422 0.1831163 0.10593246 0.041685157 -0.08181925 -0.4081250 #> AE89 0.2212558 0.1820324 0.11815414 0.024810107 -0.09216662 -0.4064017 #> AE90 0.2271603 0.1874579 0.11703971 0.031601069 -0.07166638 -0.4083849 #> AE91 0.2261588 0.1882372 0.12312647 0.031453724 -0.09623608 -0.4075506 #> AE92 0.2353479 0.1999623 0.11753540 0.033427416 -0.08120016 -0.4114561 #> AE93 0.2231146 0.1718510 0.12078223 0.024568179 -0.09254764 -0.3970457 #> AE94 0.2382167 0.1833966 0.11174608 0.037044261 -0.08277851 -0.3934437 #> AE95 0.2377841 0.1993601 0.13289958 0.041383836 -0.08556380 -0.4059580 #> AE96 0.2381113 0.1993834 0.11319767 0.041158904 -0.08367440 -0.3985118 #> AE97 0.2380356 0.1839470 0.11244138 0.035297701 -0.08215951 -0.3915827 #> AE98 0.2247551 0.1909649 0.11376227 0.030210009 -0.07152469 -0.4098340 #> AE99 0.2327722 0.1991402 0.12883015 0.035614550 -0.08682957 -0.3970737 #> AE100 0.2377580 0.1743137 0.09811410 0.010075437 -0.10567541 -0.3991863 #> CX101 0.2290665 0.1922139 0.11706821 0.047500398 -0.08249422 -0.4052462 #> CX102 0.2293068 0.1760098 0.11789188 0.044774087 -0.06106010 -0.4163814 #> CX103 0.2394979 0.1920586 0.11461307 0.025784000 -0.07999779 -0.3953586 #> CX104 0.2314558 0.1810221 0.12188125 0.041325903 -0.06915492 -0.3990015 #> CX105 0.2371495 0.1899093 0.11308927 0.034297130 -0.04974066 -0.4075275 #> CX106 0.2332277 0.1903543 0.13296141 0.043710407 -0.06453407 -0.4054979 #> CX107 0.2422508 0.1841989 0.13510787 0.046406682 -0.07021143 -0.4072995 #> CX108 0.2320185 0.1680546 0.11720697 0.032792588 -0.05510435 -0.3922454 #> CX109 0.2343839 0.2007389 0.12779590 0.032996512 -0.04694209 -0.4017998 #> CX110 0.2378867 0.1832616 0.12064990 0.046324218 -0.06981407 -0.4050046 #> CX111 0.2273768 0.1904418 0.12950512 0.050550179 -0.04985695 -0.4005184 #> CX112 0.2367948 0.1967518 0.10011721 0.016338760 -0.08055712 -0.3962532 #> CX113 0.2251491 0.1857302 0.11471705 0.052234788 -0.06173698 -0.4012369 #> CX114 0.2314432 0.1909076 0.12299680 0.044322702 -0.07351377 -0.4036653 #> CX115 0.2405785 0.2156480 0.13529727 0.039015077 -0.09269088 -0.4036963 #> CX116 0.2285597 0.1913583 0.11685112 0.030245483 -0.06611537 -0.4063325 #> CX117 0.2364835 0.2008391 0.12727829 0.029801740 -0.05116089 -0.3890976 #> CX118 0.2389982 0.1886799 0.11747954 0.042872595 -0.06481456 -0.4009626 #> CX119 0.2295826 0.1891349 0.11231738 0.031713950 -0.08408367 -0.4007293 #> CX120 0.2347531 0.1915745 0.10999010 0.039159281 -0.07421968 -0.4019501 #> CX121 0.2421442 0.2013319 0.14726099 0.041513595 -0.07229422 -0.3877350 #> CX122 0.2266313 0.1953813 0.12523150 0.036805365 -0.07702428 -0.4115588 #> CX123 0.2370076 0.2174658 0.13148120 0.035194985 -0.07744389 -0.4106482 #> CX124 0.2294273 0.1976867 0.12662777 0.037662621 -0.08984945 -0.4065792 #> CX125 0.2367249 0.1948181 0.12741401 0.043421462 -0.07849225 -0.3991977 #> DE126 0.2335108 0.2054635 0.14075607 0.055477722 -0.03540458 -0.4124649 #> DE127 0.2300548 0.1908648 0.12176640 0.045946556 -0.07661308 -0.4020559 #> x13 x14 x15 x16 x17 x18 #> AN1 -0.3123874 -0.1758920 0.071132804 -0.053722681 0.05720471 -0.1393805 #> AN2 -0.3867009 -0.1804640 0.049200176 -0.051613533 0.06225198 -0.1450187 #> AN3 -0.3921854 -0.1725842 0.057531080 -0.046893028 0.07666483 -0.1601955 #> AN4 -0.4048396 -0.1528388 0.063248369 -0.054017479 0.07029203 -0.1515230 #> AN5 -0.3959004 -0.1359723 0.078956283 -0.030094227 0.08796636 -0.1332218 #> AN6 -0.3940038 -0.1638546 0.066460419 -0.059913063 0.08088272 -0.1452717 #> AN7 -0.3793327 -0.1586080 0.068320395 -0.043540824 0.08926659 -0.1611703 #> AN8 -0.3920543 -0.1608568 0.048369015 -0.057842665 0.06620852 -0.1409480 #> AN9 -0.3964814 -0.1875675 0.058923841 -0.067584324 0.07882520 -0.1467186 #> AN10 -0.3937555 -0.1815667 0.050151922 -0.063165682 0.06639335 -0.1634576 #> AN11 -0.3998765 -0.1829062 0.079278212 -0.058328570 0.08913645 -0.1586749 #> TO12 -0.3792285 -0.1573091 0.160588922 -0.068449994 0.09810716 -0.1926913 #> WY13 -0.3560161 -0.1633065 0.043039317 -0.024470515 0.04782334 -0.1461281 #> WY14 -0.4119397 -0.1509246 0.025931927 -0.022880971 0.05624500 -0.1465910 #> WY15 -0.3873511 -0.1769486 0.044837998 -0.033642058 0.07252781 -0.1262252 #> WY16 -0.4053355 -0.1447852 0.041124932 -0.041619850 0.06150684 -0.1330420 #> UR17 -0.3795187 -0.1499897 0.112096041 -0.075700284 0.09462930 -0.1378847 #> UR18 -0.3667555 -0.1229772 0.135646552 -0.069063838 0.08232154 -0.1093214 #> UR19 -0.3734347 -0.1520523 0.141092065 -0.079853773 0.09743056 -0.1332523 #> UR20 -0.3307397 -0.1264103 0.083589542 -0.080261106 0.05968488 -0.1212670 #> CA21 -0.3915900 -0.1669786 0.092579729 -0.022158130 0.07397812 -0.1308064 #> CA22 -0.3938010 -0.1952350 0.063030200 -0.026379879 0.08437946 -0.1194480 #> CA23 -0.3978962 -0.1730481 0.047273593 -0.028019393 0.04890647 -0.1231193 #> CA24 -0.3836838 -0.2047323 0.044936652 -0.037354246 0.05305631 -0.1301203 #> CA25 -0.3867403 -0.1712789 0.067968322 -0.024498614 0.04416991 -0.1390823 #> CA26 -0.3937400 -0.1660372 0.065363612 -0.047291844 0.05142893 -0.1513329 #> CA27 -0.3681559 -0.1830495 0.018062775 -0.034573946 0.05424041 -0.1835350 #> OR28 -0.3922121 -0.1705467 0.068579295 -0.039999358 0.03187299 -0.1074308 #> MA29 -0.3876047 -0.1755705 0.055627902 -0.048117812 0.02617888 -0.1621226 #> MA30 -0.3983553 -0.1747881 0.060321100 -0.015576724 0.04797223 -0.1327685 #> MA31 -0.3858714 -0.1908211 0.070178695 -0.027140640 0.06411273 -0.1316847 #> PS32 -0.4009013 -0.1701479 0.076133748 -0.025721102 0.07937010 -0.1040872 #> PS33 -0.3999745 -0.1598414 0.085627861 -0.012988219 0.07775493 -0.1187115 #> PS34 -0.3997804 -0.1595394 0.079226181 0.001378733 0.08299836 -0.1042104 #> PS35 -0.3917380 -0.1723098 0.063434377 -0.027320762 0.07315293 -0.1358608 #> PS36 -0.3957244 -0.1826283 0.070455306 -0.017542694 0.07782886 -0.1225652 #> PS37 -0.4031093 -0.1676375 0.073776707 -0.012313027 0.09290963 -0.1426835 #> PS38 -0.3943966 -0.1539762 0.075629598 -0.024301247 0.08226797 -0.1411489 #> PS39 -0.3908186 -0.1753054 0.068416040 -0.026234475 0.07275579 -0.1426104 #> PS40 -0.3970239 -0.1774955 0.077246950 -0.032428935 0.04948173 -0.1445656 #> PS41 -0.3851949 -0.1903692 0.056899382 -0.025993187 0.05120127 -0.1455207 #> PS42 -0.3952832 -0.1857938 0.096292088 -0.008344338 0.07966704 -0.1311093 #> PS43 -0.3869340 -0.2037884 0.094782316 -0.020211736 0.07961082 -0.1505692 #> AE44 -0.3935808 -0.1687313 0.080418789 -0.019593863 0.05651851 -0.1429755 #> AE45 -0.4043663 -0.1807524 0.080066700 -0.027367399 0.08757207 -0.1283663 #> AE46 -0.3877556 -0.1826371 0.068465989 -0.028746613 0.07764665 -0.1409232 #> AE47 -0.3953208 -0.1927835 0.053055706 -0.011260156 0.07280239 -0.1237115 #> AE48 -0.3856849 -0.1721881 0.080969398 -0.002019639 0.07130260 -0.1251923 #> AE49 -0.3798684 -0.2306110 0.057022040 -0.031685345 0.06830318 -0.1413658 #> AE50 -0.3898933 -0.1678589 0.081555287 -0.018531416 0.07924866 -0.1332756 #> AE51 -0.3814383 -0.2113389 0.080188309 -0.031438772 0.05430921 -0.1393203 #> AE52 -0.4018099 -0.1968956 0.074185015 -0.016768536 0.05762562 -0.1218164 #> AE53 -0.3956962 -0.1790955 0.093343932 -0.008269994 0.09425627 -0.1248207 #> AE54 -0.3988053 -0.1755086 0.100664053 -0.007742611 0.07639270 -0.1317456 #> AE55 -0.3830524 -0.1814467 0.065155781 -0.040471766 0.07364275 -0.1574346 #> AE56 -0.3906408 -0.1710974 0.074709004 -0.015546169 0.07476288 -0.1472765 #> AE57 -0.3987688 -0.1707297 0.079379215 -0.010544594 0.05237139 -0.1272180 #> AE58 -0.3895450 -0.1739227 0.048346680 -0.040154525 0.06825117 -0.1545096 #> AE59 -0.4000550 -0.1802010 0.085429434 -0.011765784 0.08507985 -0.1279580 #> AE60 -0.3844530 -0.1869755 0.067673441 -0.014802941 0.08506475 -0.1304661 #> AE61 -0.3872808 -0.1838364 0.072708144 -0.022088293 0.07101851 -0.1276127 #> AE62 -0.3980835 -0.1558501 0.072920769 -0.030383001 0.07145942 -0.1375049 #> AE63 -0.3819749 -0.1892579 0.073253276 -0.009680803 0.07092440 -0.1374394 #> AE64 -0.3830723 -0.1818841 0.083419843 -0.020792424 0.05516603 -0.1400750 #> AE65 -0.3950954 -0.1713184 0.056778156 -0.010587947 0.09200406 -0.1327086 #> AE66 -0.3920177 -0.1764438 0.105836190 -0.012763450 0.09219496 -0.1267756 #> AE67 -0.4005061 -0.1817317 0.072579788 -0.005837986 0.08265020 -0.1212986 #> AE68 -0.3979286 -0.1964838 0.096764243 -0.002088618 0.07331423 -0.1273690 #> AE69 -0.3988875 -0.1559526 0.077236543 -0.023061279 0.07910975 -0.1319191 #> AE70 -0.3925072 -0.1727990 0.071299724 -0.019968087 0.07592270 -0.1378603 #> AE71 -0.3861925 -0.2024340 0.082151905 -0.015697031 0.07097288 -0.1348231 #> AE72 -0.3940800 -0.1874311 0.106283254 -0.007228361 0.09394314 -0.1212455 #> AE73 -0.3897005 -0.1879595 0.088836487 -0.026457001 0.04951382 -0.1324029 #> AE74 -0.3997937 -0.1524768 0.093802325 0.008109828 0.08592517 -0.1082014 #> AE75 -0.3970993 -0.1817829 0.093102758 -0.006807875 0.06061804 -0.1151656 #> AE76 -0.3955195 -0.1880763 0.103382907 -0.001083329 0.09360505 -0.1263704 #> AE77 -0.3889041 -0.1764796 0.079500830 -0.013542644 0.07981560 -0.1254420 #> AE78 -0.4099100 -0.1776684 0.069460737 -0.014974501 0.06651128 -0.1220949 #> AE79 -0.3773595 -0.2131280 0.076032489 -0.025486291 0.06233346 -0.1314012 #> AE80 -0.3849712 -0.2015281 0.081245884 -0.015415381 0.07882854 -0.1277587 #> AE81 -0.3812278 -0.2125832 0.060469074 -0.023877574 0.04899794 -0.1542995 #> AE82 -0.3898835 -0.1813821 0.100777839 -0.020363389 0.08602870 -0.1271990 #> AE83 -0.3851831 -0.1927737 0.088931898 -0.020963427 0.04294136 -0.1241991 #> AE84 -0.3794734 -0.1952869 0.062647361 -0.030900169 0.06101529 -0.1375591 #> AE85 -0.3984306 -0.1647072 0.048201877 -0.028486708 0.06931371 -0.1358889 #> AE86 -0.3809376 -0.1916173 0.056772111 -0.028475690 0.04954339 -0.1571078 #> AE87 -0.3873660 -0.1718767 0.049172441 -0.025198075 0.04745461 -0.1635640 #> AE88 -0.4036821 -0.1483002 0.043892652 -0.022359235 0.05684484 -0.1355545 #> AE89 -0.3990820 -0.1741903 0.078732121 -0.032661266 0.06575081 -0.1459775 #> AE90 -0.3866222 -0.1734202 0.074626665 -0.009459741 0.06415615 -0.1319939 #> AE91 -0.3897621 -0.1817775 0.090853341 -0.016262267 0.08433507 -0.1177673 #> AE92 -0.3899454 -0.1846729 0.060100544 -0.018845258 0.07646573 -0.1481314 #> AE93 -0.3837723 -0.1777953 0.105572746 -0.007698944 0.09114540 -0.1364939 #> AE94 -0.3859287 -0.1779382 0.049182813 -0.028392318 0.06120780 -0.1449260 #> AE95 -0.3852472 -0.1989100 0.067213272 -0.018272744 0.06964813 -0.1551490 #> AE96 -0.3886513 -0.1801433 0.048923673 -0.037275416 0.03195851 -0.1735086 #> AE97 -0.3717321 -0.1604576 0.066787089 -0.040595352 0.04740382 -0.1708025 #> AE98 -0.3945421 -0.1857716 0.065278055 -0.017262292 0.08878564 -0.1406077 #> AE99 -0.3820466 -0.2084944 0.055519925 -0.037125707 0.06705659 -0.1372445 #> AE100 -0.3903980 -0.1879970 0.058003315 -0.034426867 0.06144086 -0.1378944 #> CX101 -0.4020885 -0.1791160 0.048786174 -0.024150254 0.06711276 -0.1299322 #> CX102 -0.3976002 -0.1598676 0.044080347 -0.012590737 0.07109391 -0.1385710 #> CX103 -0.3778145 -0.1965009 0.043332770 -0.021978126 0.06459107 -0.1541661 #> CX104 -0.3920948 -0.1905712 0.044782493 -0.023836658 0.07315470 -0.1450364 #> CX105 -0.3983841 -0.1772447 0.042035888 -0.017445516 0.05089486 -0.1370570 #> CX106 -0.3853825 -0.1858871 0.029830212 -0.022877381 0.05320887 -0.1525558 #> CX107 -0.3943242 -0.2024597 0.029972543 -0.022749183 0.05178003 -0.1505679 #> CX108 -0.3847865 -0.2059504 0.017680898 -0.061007843 0.03987377 -0.1412352 #> CX109 -0.3909616 -0.1969576 0.007347111 -0.028313790 0.05008241 -0.1456546 #> CX110 -0.3959867 -0.1872205 0.024263790 -0.023041900 0.06640065 -0.1383339 #> CX111 -0.3905637 -0.1997595 0.033330776 -0.026702817 0.05550112 -0.1489101 #> CX112 -0.3859520 -0.1967629 0.042475088 -0.021379935 0.06012648 -0.1452501 #> CX113 -0.3957362 -0.1824494 0.054807087 -0.020058985 0.05965166 -0.1494302 #> CX114 -0.3879005 -0.1893491 0.028159479 -0.030888990 0.05144192 -0.1613051 #> CX115 -0.3951331 -0.1753281 0.038920274 -0.031822228 0.06154232 -0.1591605 #> CX116 -0.3803402 -0.1578348 0.039463402 -0.028570233 0.03924349 -0.1816337 #> CX117 -0.3752952 -0.1812367 0.014102142 -0.044530391 0.03439492 -0.1643696 #> CX118 -0.3784407 -0.1842759 0.020975280 -0.024425083 0.03881369 -0.1417108 #> CX119 -0.3877947 -0.1642730 0.063045598 -0.026611925 0.04439785 -0.1418231 #> CX120 -0.3884471 -0.1835364 0.046813391 -0.029801285 0.04352303 -0.1594322 #> CX121 -0.3858059 -0.1766316 0.029448989 -0.016405347 0.05021469 -0.1574074 #> CX122 -0.3948824 -0.1545773 0.058090941 -0.023721208 0.07347028 -0.1590947 #> CX123 -0.3968212 -0.1614923 0.057831692 -0.026330484 0.07153597 -0.1594401 #> CX124 -0.3968831 -0.1750125 0.063457007 -0.012313821 0.05506986 -0.1534678 #> CX125 -0.3910056 -0.1815608 0.038032701 -0.007173229 0.05915443 -0.1535347 #> DE126 -0.4010722 -0.1869205 0.028587401 -0.042186617 0.07257509 -0.1462993 #> DE127 -0.3907218 -0.2047855 0.046701459 -0.043417728 0.10136732 -0.1466586 #> y1 y2 y3 y4 y5 y6 #> AN1 0.012949789 0.08278930 0.08567442 0.04597933 0.02598256 3.150553e-04 #> AN2 0.022620158 0.07814870 0.05998946 0.04206154 0.02339979 6.898275e-03 #> AN3 0.013438475 0.06897223 0.05579946 0.04374581 0.02439000 5.250128e-03 #> AN4 0.014143861 0.07489168 0.07164144 0.04601179 0.02224188 4.645497e-03 #> AN5 0.011166720 0.07229243 0.05230952 0.04250442 0.01956350 3.326619e-03 #> AN6 0.012440946 0.06723327 0.05661890 0.04085779 0.02245431 6.525920e-03 #> AN7 0.023595913 0.07056581 0.07480905 0.05084276 0.02654051 2.098330e-03 #> AN8 0.010319015 0.07836381 0.05633338 0.03994427 0.02322133 1.364182e-02 #> AN9 0.021185977 0.07585612 0.06020996 0.04194706 0.02692072 8.397649e-03 #> AN10 0.013775382 0.07005713 0.05209910 0.03621218 0.01966673 5.732559e-03 #> AN11 0.013524963 0.07047621 0.05383143 0.03813986 0.02386315 6.524021e-03 #> TO12 0.011020896 0.05489808 0.05851446 0.04843418 0.02948179 1.135298e-02 #> WY13 0.012690374 0.08974548 0.07154950 0.05142613 0.03115442 7.945565e-03 #> WY14 0.006838952 0.07425376 0.05855540 0.03951210 0.01684673 4.686961e-03 #> WY15 0.012327190 0.07389979 0.05676065 0.04216671 0.02130888 6.762512e-03 #> WY16 0.012734077 0.07486281 0.06343993 0.04269533 0.02284658 8.148998e-03 #> UR17 -0.002272445 0.08504411 0.06568723 0.04988277 0.02803984 2.399601e-03 #> UR18 0.010595208 0.08716386 0.07508599 0.05911723 0.04078312 1.775779e-02 #> UR19 0.005508873 0.06909879 0.06119788 0.04581264 0.02498341 8.528148e-03 #> UR20 0.012396411 0.07799239 0.07198516 0.05098737 0.02522046 5.626080e-03 #> CA21 0.002635902 0.09440017 0.07134001 0.04688346 0.02345164 6.454919e-03 #> CA22 0.015744194 0.08724373 0.07052453 0.04828188 0.03276292 1.179454e-02 #> CA23 0.013027883 0.08808348 0.05921609 0.04609833 0.02443344 6.819944e-03 #> CA24 0.018277036 0.08648570 0.06951016 0.04686661 0.02521702 5.385714e-03 #> CA25 0.008599950 0.08815717 0.06935643 0.05183313 0.03086332 7.787913e-03 #> CA26 0.020834507 0.05992072 0.05711972 0.03839133 0.02688537 1.015034e-02 #> CA27 0.016367946 0.08527756 0.07076670 0.05317126 0.02914834 5.178037e-03 #> OR28 0.016827832 0.07461198 0.07442280 0.04643065 0.02768371 -1.428860e-03 #> MA29 0.010507548 0.08627604 0.05969102 0.04561603 0.02654038 8.884358e-03 #> MA30 0.025995072 0.08319459 0.06945754 0.05089690 0.02871595 6.842935e-03 #> MA31 0.011798644 0.08595290 0.07149388 0.04904952 0.01922665 -6.100331e-05 #> PS32 0.020858385 0.08883745 0.07127037 0.05320765 0.02642967 1.005285e-02 #> PS33 0.019564176 0.09107797 0.08038467 0.06757304 0.03450430 3.602802e-03 #> PS34 0.023210109 0.08901869 0.06173608 0.05023270 0.03095637 1.226244e-02 #> PS35 0.014353551 0.07699700 0.06095585 0.04185292 0.02578438 9.105854e-03 #> PS36 0.016665841 0.08692672 0.07172546 0.04794591 0.02378877 3.989454e-03 #> PS37 0.017832570 0.09050827 0.06565900 0.04890781 0.02110664 3.045869e-03 #> PS38 0.020272149 0.07495732 0.06588390 0.04780263 0.02331908 8.794902e-03 #> PS39 0.024672051 0.08031432 0.06721244 0.05284589 0.03114989 1.041525e-02 #> PS40 0.022707637 0.08147540 0.06533484 0.05252109 0.03007380 1.088509e-02 #> PS41 0.031617885 0.08831678 0.07838941 0.05979106 0.03143316 1.214333e-02 #> PS42 0.032775200 0.08160316 0.07927849 0.04794666 0.02364906 4.957452e-03 #> PS43 0.009549895 0.09705840 0.06595407 0.05464080 0.02973277 7.712228e-03 #> AE44 0.024194386 0.08043082 0.06281371 0.05271229 0.03342474 1.450789e-02 #> AE45 0.020043767 0.07464976 0.06346404 0.05108001 0.03319453 1.238207e-02 #> AE46 0.028843141 0.08336736 0.06916145 0.04413785 0.02509013 7.798185e-03 #> AE47 0.019762588 0.08711498 0.07134883 0.04412614 0.03008310 8.471292e-03 #> AE48 0.004400251 0.07889303 0.05925122 0.04868763 0.02847921 1.129694e-02 #> AE49 0.028804164 0.07968806 0.07268678 0.04628811 0.02623977 5.219770e-03 #> AE50 0.017152508 0.09150904 0.06579800 0.04675409 0.02993258 5.432006e-03 #> AE51 0.024244112 0.10035814 0.07848335 0.05257736 0.02630567 8.506299e-03 #> AE52 0.016687543 0.08215637 0.07006422 0.05467560 0.02854618 8.874160e-03 #> AE53 0.020866743 0.08293980 0.07177936 0.04937694 0.02587003 1.214336e-03 #> AE54 0.016303084 0.08395002 0.06313701 0.04778874 0.03048500 9.340067e-03 #> AE55 0.009794674 0.06923412 0.05935067 0.04571206 0.02509890 7.988179e-03 #> AE56 0.022976188 0.06985700 0.07120533 0.05037744 0.02676315 6.480065e-03 #> AE57 0.014463513 0.08643381 0.06277860 0.04806000 0.02984945 7.880581e-03 #> AE58 0.024562376 0.08351377 0.07057086 0.04923052 0.02851743 1.091822e-02 #> AE59 0.018360929 0.07068281 0.07225106 0.04599054 0.02680356 4.512518e-03 #> AE60 0.020595403 0.09656929 0.08363540 0.06054622 0.02756263 5.413022e-03 #> AE61 0.018530058 0.07997438 0.06974188 0.04297306 0.02953858 9.299743e-03 #> AE62 0.007576305 0.06729175 0.06139850 0.04746917 0.02336475 2.961155e-03 #> AE63 0.015957414 0.08932474 0.07748263 0.05121790 0.02760974 9.750227e-03 #> AE64 0.033051290 0.07655371 0.06347002 0.05159245 0.03439265 1.277309e-02 #> AE65 0.027086223 0.07637610 0.06279530 0.04671867 0.02849960 1.438764e-02 #> AE66 0.018674566 0.09197399 0.07371724 0.05663273 0.02899414 6.109633e-03 #> AE67 0.028409424 0.07503364 0.07199975 0.05225904 0.02612058 7.194398e-03 #> AE68 0.017466427 0.08541910 0.07149689 0.04934195 0.02673386 5.606712e-03 #> AE69 0.025427691 0.07950054 0.06692939 0.04794946 0.02610897 1.075827e-02 #> AE70 0.024397497 0.08676899 0.07352538 0.04876882 0.02613623 7.740551e-03 #> AE71 0.025306610 0.09828523 0.07485413 0.04943489 0.02751513 6.540573e-03 #> AE72 0.018994708 0.08320701 0.07058901 0.05058892 0.02896517 9.816870e-03 #> AE73 0.017638669 0.08081453 0.06154661 0.04410005 0.02802859 4.977306e-03 #> AE74 0.013866970 0.08996534 0.08134595 0.05468616 0.02919334 1.030476e-03 #> AE75 0.019051266 0.08460450 0.06512687 0.05012725 0.02933960 1.204551e-02 #> AE76 0.024064241 0.08748911 0.06281835 0.04649284 0.02840376 1.019351e-02 #> AE77 0.019637439 0.08254312 0.07454355 0.05421194 0.03101338 9.705051e-03 #> AE78 0.020664576 0.08301491 0.06995436 0.04929145 0.02794066 7.814539e-03 #> AE79 0.019112716 0.08929033 0.07642541 0.04518694 0.02111029 5.806409e-03 #> AE80 0.020532270 0.07974954 0.06548313 0.04348238 0.02390729 8.908130e-03 #> AE81 0.032653485 0.09655472 0.07136094 0.05478530 0.03003749 9.625963e-03 #> AE82 0.016068078 0.09009160 0.07315928 0.05722988 0.03114905 8.837045e-03 #> AE83 0.011847216 0.08855522 0.07342359 0.05071607 0.02749338 -1.261610e-03 #> AE84 0.016668378 0.09927702 0.07453788 0.05663099 0.03280063 1.258835e-02 #> AE85 0.018956670 0.09108967 0.06777101 0.04204491 0.02751666 8.322889e-03 #> AE86 0.024398933 0.09834638 0.06994284 0.05154644 0.02823738 9.007741e-03 #> AE87 0.023684110 0.08553089 0.06985999 0.04973592 0.03075232 4.770671e-03 #> AE88 0.009086931 0.08497514 0.05602979 0.04052918 0.02196141 4.263640e-03 #> AE89 0.008697268 0.09415668 0.06619343 0.04559618 0.02268657 6.387914e-03 #> AE90 0.023592133 0.09288445 0.06780117 0.04761940 0.02373946 7.450863e-03 #> AE91 0.027587546 0.08739037 0.07424035 0.05285224 0.03121011 1.336585e-02 #> AE92 0.020877783 0.08354286 0.06453034 0.04529757 0.02508348 2.693451e-03 #> AE93 0.020362274 0.08839049 0.07280876 0.05736176 0.02925530 1.288949e-02 #> AE94 0.018616034 0.07857938 0.06210432 0.04488612 0.02620036 7.954699e-03 #> AE95 0.017466278 0.06626332 0.05950030 0.04144645 0.02093498 8.848699e-03 #> AE96 0.020801841 0.09324421 0.06773196 0.05463775 0.03234757 7.940429e-03 #> AE97 0.014952865 0.07896182 0.07300224 0.04985563 0.02788274 9.014158e-03 #> AE98 0.018048187 0.08218978 0.05785822 0.04056802 0.02329700 4.652032e-03 #> AE99 0.020083707 0.07576149 0.06395041 0.04630429 0.02900600 1.089936e-02 #> AE100 0.015824036 0.08821053 0.07491340 0.05309966 0.03213898 1.087831e-02 #> CX101 0.018795318 0.08935829 0.06789318 0.04795560 0.02523486 6.371738e-03 #> CX102 0.016523832 0.07645851 0.05814991 0.04824675 0.03385777 1.273612e-02 #> CX103 0.015546955 0.08786844 0.07200134 0.05340679 0.02005302 5.641727e-03 #> CX104 0.017186716 0.09086700 0.06213183 0.04676279 0.02521286 5.651021e-03 #> CX105 0.024732997 0.08784311 0.07192773 0.05218250 0.02508507 8.998762e-03 #> CX106 0.025857951 0.09772122 0.07359955 0.04628790 0.02514650 5.161054e-03 #> CX107 0.021438025 0.08574030 0.06659796 0.04418656 0.02230971 5.480441e-03 #> CX108 0.021697750 0.09066793 0.06603259 0.04953728 0.02503477 8.608714e-03 #> CX109 0.023769465 0.08002066 0.05865615 0.04432315 0.02486665 8.734026e-03 #> CX110 0.016554284 0.07594482 0.05471561 0.04478128 0.02505230 7.362556e-03 #> CX111 0.027261641 0.08863600 0.06600806 0.04864079 0.02950304 1.095938e-02 #> CX112 0.011567345 0.09504327 0.06914602 0.05050347 0.02412777 6.095360e-03 #> CX113 0.019372724 0.07856295 0.05797215 0.04557766 0.02528808 7.191655e-03 #> CX114 0.023230961 0.08830329 0.07676627 0.05220000 0.03012530 7.966660e-03 #> CX115 0.027645207 0.08323054 0.07204438 0.05037670 0.02389914 4.849303e-03 #> CX116 0.012671316 0.09954405 0.07257560 0.05202289 0.02616604 8.007566e-03 #> CX117 0.015588267 0.09102118 0.05090721 0.04192613 0.02375173 1.124011e-02 #> CX118 0.031458141 0.09238535 0.06813825 0.05207771 0.02839224 1.141056e-02 #> CX119 0.013748165 0.08552154 0.06632546 0.05062110 0.02802667 4.635430e-03 #> CX120 0.018452306 0.09280082 0.07952526 0.05129996 0.02550388 3.429387e-03 #> CX121 0.020419316 0.07808530 0.06910902 0.04830133 0.02437463 1.095195e-02 #> CX122 0.020437652 0.08050253 0.07033136 0.04799342 0.02581098 5.994960e-03 #> CX123 0.020778083 0.08042975 0.06478748 0.04765908 0.02367922 3.633548e-03 #> CX124 0.008692130 0.08303546 0.05963710 0.04238139 0.02053006 4.573956e-03 #> CX125 0.024193003 0.08506648 0.07389227 0.05162124 0.02943930 1.075803e-02 #> DE126 0.028740812 0.08903327 0.07586163 0.04853023 0.02610944 1.496756e-03 #> DE127 0.017573580 0.07459253 0.06140529 0.04375617 0.02306513 3.169474e-03 #> y7 y8 y9 y10 y11 y12 #> AN1 -0.022666314 -0.04495128 -0.07380235 -0.09608732 -0.11021440 -0.016199734 #> AN2 -0.008294587 -0.03422790 -0.05730591 -0.08756992 -0.10378049 -0.017413291 #> AN3 -0.009247883 -0.02947626 -0.04736125 -0.07195961 -0.08694772 -0.022201347 #> AN4 -0.007266518 -0.03817491 -0.06247395 -0.08534776 -0.09214130 -0.014432794 #> AN5 -0.013178097 -0.02962921 -0.05249050 -0.07247827 -0.09789820 -0.022527432 #> AN6 -0.012722770 -0.03281784 -0.05644748 -0.07669058 -0.08936509 -0.019148946 #> AN7 -0.008408792 -0.04279862 -0.05707903 -0.08968988 -0.10007999 -0.014849557 #> AN8 -0.002200848 -0.02722524 -0.05195370 -0.08021449 -0.09296762 -0.022862331 #> AN9 -0.010947676 -0.03524550 -0.05700364 -0.08079711 -0.09458230 -0.018055142 #> AN10 -0.007966654 -0.02926133 -0.04952115 -0.07859991 -0.09286459 -0.018567396 #> AN11 -0.015736928 -0.03610576 -0.05169961 -0.07002402 -0.08335024 -0.020845591 #> TO12 -0.007196761 -0.03202162 -0.05389319 -0.07018859 -0.08636577 -0.012831315 #> WY13 -0.014517432 -0.03556436 -0.06639870 -0.08844776 -0.10389518 -0.030313163 #> WY14 -0.015250720 -0.03483797 -0.05646906 -0.07746212 -0.08907170 -0.019772339 #> WY15 -0.010211930 -0.03618927 -0.05577035 -0.07262279 -0.08100249 -0.020178753 #> WY16 -0.010708481 -0.03415558 -0.05261327 -0.07363348 -0.08843957 -0.016680404 #> UR17 -0.019627397 -0.04068643 -0.05492440 -0.07645589 -0.09901886 -0.025215610 #> UR18 -0.018616124 -0.04695167 -0.06621731 -0.09086570 -0.11264614 -0.015247597 #> UR19 -0.010306625 -0.03187302 -0.04878683 -0.07199789 -0.08545362 -0.022977244 #> UR20 -0.014260396 -0.03870875 -0.06095216 -0.07791609 -0.10059416 -0.029218565 #> CA21 -0.011424835 -0.04241109 -0.06673866 -0.08717433 -0.10073722 -0.013774957 #> CA22 -0.017118972 -0.04456671 -0.06333256 -0.08548463 -0.09971043 -0.022457033 #> CA23 -0.008347883 -0.03668714 -0.05743793 -0.08221906 -0.10008108 -0.029337037 #> CA24 -0.014179955 -0.04065754 -0.06266514 -0.08979362 -0.10879858 -0.023113773 #> CA25 -0.015459966 -0.04556921 -0.06304180 -0.08676862 -0.10417190 -0.027553536 #> CA26 -0.006852774 -0.03087716 -0.05463273 -0.08502000 -0.10069478 -0.014484320 #> CA27 -0.017374727 -0.04566712 -0.06879405 -0.08809265 -0.09723578 -0.021534472 #> OR28 -0.024906613 -0.04860997 -0.06290004 -0.08224867 -0.09509220 -0.010348802 #> MA29 -0.015304956 -0.03905274 -0.05435187 -0.07951367 -0.09998388 -0.021699642 #> MA30 -0.010834828 -0.04016197 -0.06177193 -0.08862342 -0.11328879 -0.023690279 #> MA31 -0.018696436 -0.04114775 -0.05875278 -0.08531003 -0.10616868 -0.020705521 #> PS32 -0.013966342 -0.04517596 -0.06293986 -0.08771783 -0.11564596 -0.016808723 #> PS33 -0.018770501 -0.04766682 -0.07019447 -0.09609560 -0.11240803 -0.028353056 #> PS34 -0.016077185 -0.03892582 -0.06709499 -0.08915360 -0.11262678 -0.031961548 #> PS35 -0.010669404 -0.03446840 -0.05734935 -0.08175206 -0.09968148 -0.023747638 #> PS36 -0.014159752 -0.04084200 -0.05970849 -0.08591500 -0.09594658 -0.024568635 #> PS37 -0.015253852 -0.03496920 -0.06363514 -0.08431507 -0.10396906 -0.023449907 #> PS38 -0.009658641 -0.03155459 -0.05594592 -0.08233475 -0.10136260 -0.022744632 #> PS39 -0.006756077 -0.04002465 -0.06449392 -0.09299131 -0.11489188 -0.022555610 #> PS40 -0.011218252 -0.03616382 -0.06363627 -0.09112784 -0.10907791 -0.026264079 #> PS41 -0.012940371 -0.03946998 -0.07029977 -0.09689176 -0.11705262 -0.018025681 #> PS42 -0.012199593 -0.03887817 -0.06933953 -0.09428498 -0.12869403 -0.020124919 #> PS43 -0.019393904 -0.04308818 -0.06501801 -0.08619796 -0.11211448 -0.031925724 #> AE44 -0.009864032 -0.04162945 -0.06576743 -0.09725932 -0.11364550 -0.019576973 #> AE45 -0.013916993 -0.03736238 -0.06138435 -0.08687628 -0.09975951 -0.016310318 #> AE46 -0.012293031 -0.03405671 -0.05890388 -0.08537348 -0.11204166 -0.031127229 #> AE47 -0.015122615 -0.03729307 -0.06519826 -0.08781795 -0.10306537 -0.022479401 #> AE48 -0.011283848 -0.03764086 -0.06122137 -0.08007018 -0.09322090 -0.020270023 #> AE49 -0.013578564 -0.03320043 -0.06026791 -0.09253288 -0.10541387 -0.023949586 #> AE50 -0.016251885 -0.03720164 -0.06165119 -0.08784147 -0.10495288 -0.033744689 #> AE51 -0.010476511 -0.04660512 -0.06631610 -0.10182189 -0.11801742 -0.017839934 #> AE52 -0.019738467 -0.04341494 -0.06770016 -0.08995689 -0.11162861 -0.009071347 #> AE53 -0.015349580 -0.04042478 -0.06346917 -0.09056545 -0.10531159 -0.021332153 #> AE54 -0.014567417 -0.03743690 -0.06222308 -0.08733919 -0.10858403 -0.022837649 #> AE55 -0.009483085 -0.03298787 -0.05184618 -0.06911137 -0.09089088 -0.022677930 #> AE56 -0.014517252 -0.03572730 -0.05811263 -0.08361669 -0.10120448 -0.018959718 #> AE57 -0.016428768 -0.04444423 -0.06165616 -0.08731023 -0.10897038 -0.023316265 #> AE58 -0.010374273 -0.03231118 -0.06250651 -0.09107635 -0.11401767 -0.018983293 #> AE59 -0.011140219 -0.03426532 -0.05190264 -0.07858311 -0.09563840 -0.016993894 #> AE60 -0.016646973 -0.03728373 -0.06908015 -0.10354720 -0.12250383 -0.021937227 #> AE61 -0.012104480 -0.04374854 -0.06728928 -0.09264702 -0.11459973 -0.018773675 #> AE62 -0.010676452 -0.03345894 -0.05817475 -0.07512250 -0.08493945 -0.014084994 #> AE63 -0.013637658 -0.04137811 -0.06644285 -0.08819460 -0.10472228 -0.025306267 #> AE64 -0.012351366 -0.04001879 -0.06401090 -0.09337149 -0.11519782 -0.028951646 #> AE65 -0.006834492 -0.03207158 -0.06044547 -0.08432522 -0.09764177 -0.023000019 #> AE66 -0.012863697 -0.04182711 -0.06282764 -0.08872958 -0.11093574 -0.022655471 #> AE67 -0.008988133 -0.03836438 -0.06366265 -0.09116318 -0.10318603 -0.018396435 #> AE68 -0.018182938 -0.04065040 -0.05755426 -0.08005239 -0.10330960 -0.026939918 #> AE69 -0.010162744 -0.03434778 -0.06206309 -0.08433742 -0.10618099 -0.017816293 #> AE70 -0.013339125 -0.03087722 -0.06564962 -0.09583501 -0.11751622 -0.017921942 #> AE71 -0.009674615 -0.04047887 -0.06485963 -0.09489162 -0.11794276 -0.019557379 #> AE72 -0.011023048 -0.04144962 -0.06626343 -0.08850403 -0.10321745 -0.024119634 #> AE73 -0.012326640 -0.03771430 -0.06290116 -0.08707121 -0.11479236 -0.027633459 #> AE74 -0.023284290 -0.04456710 -0.06608998 -0.08808926 -0.10563109 -0.027465109 #> AE75 -0.014429655 -0.03968049 -0.06086849 -0.08665282 -0.10597408 -0.021162926 #> AE76 -0.008968325 -0.03792354 -0.06231543 -0.08502937 -0.10297398 -0.030918327 #> AE77 -0.015540834 -0.04290499 -0.06648039 -0.09428362 -0.10514460 -0.020485588 #> AE78 -0.012718208 -0.03826693 -0.06123567 -0.08909879 -0.10689239 -0.023647537 #> AE79 -0.011669590 -0.03582596 -0.06011012 -0.08866414 -0.11624901 -0.018461960 #> AE80 -0.011376774 -0.03653024 -0.06015092 -0.08237761 -0.10362247 -0.018665167 #> AE81 -0.016036431 -0.04029716 -0.07262006 -0.10446181 -0.12391661 -0.024052190 #> AE82 -0.020087830 -0.04201347 -0.07354814 -0.10065621 -0.10940849 -0.011428821 #> AE83 -0.021645529 -0.04539565 -0.06314253 -0.08529895 -0.10442005 -0.021041966 #> AE84 -0.014980325 -0.04246752 -0.06989970 -0.09745781 -0.10994738 -0.017995235 #> AE85 -0.010222911 -0.03959449 -0.06432343 -0.09074464 -0.10642521 -0.025756313 #> AE86 -0.014930629 -0.04480209 -0.06953731 -0.09809488 -0.12409746 -0.032433350 #> AE87 -0.012022788 -0.03779240 -0.06364329 -0.08785353 -0.11595475 -0.025407828 #> AE88 -0.008955694 -0.03275051 -0.05705711 -0.07994982 -0.09844740 -0.025026526 #> AE89 -0.015982691 -0.03740611 -0.05867094 -0.08552491 -0.10024375 -0.025804413 #> AE90 -0.011306378 -0.03521060 -0.06690911 -0.09599275 -0.12234375 -0.029537958 #> AE91 -0.012111344 -0.04106840 -0.07231039 -0.10062439 -0.11553546 -0.025351922 #> AE92 -0.015689253 -0.03491960 -0.05842990 -0.08010586 -0.10556897 -0.024083862 #> AE93 -0.013901076 -0.04308173 -0.06745768 -0.09390358 -0.09889036 -0.023300202 #> AE94 -0.012763836 -0.03714156 -0.06145234 -0.08746265 -0.10258403 -0.019185244 #> AE95 -0.008317134 -0.03318205 -0.05476635 -0.07909102 -0.09724833 -0.021156993 #> AE96 -0.015012694 -0.04126789 -0.06917529 -0.09235024 -0.11303064 -0.027983805 #> AE97 -0.013629341 -0.04202223 -0.06470694 -0.08938782 -0.10634508 -0.014570628 #> AE98 -0.014268236 -0.03160816 -0.05122169 -0.07681646 -0.10049791 -0.024985362 #> AE99 -0.012077336 -0.03512960 -0.06536965 -0.08814244 -0.10843565 -0.015810894 #> AE100 -0.015056303 -0.04452189 -0.06201376 -0.09154554 -0.10155078 -0.028695098 #> CX101 -0.012506215 -0.03810225 -0.06348897 -0.09067708 -0.10433018 -0.018162774 #> CX102 -0.012983929 -0.04180854 -0.05886266 -0.08220843 -0.10445411 -0.010668165 #> CX103 -0.016869427 -0.04349510 -0.06480692 -0.08860946 -0.10069580 -0.025010278 #> CX104 -0.013144831 -0.04263306 -0.06495377 -0.08813451 -0.10489965 -0.022728276 #> CX105 -0.012350189 -0.04220287 -0.06626618 -0.09078704 -0.11120488 -0.017454695 #> CX106 -0.012491167 -0.04111398 -0.06370969 -0.09441199 -0.11527055 -0.023497145 #> CX107 -0.008315049 -0.03997006 -0.05355706 -0.08196831 -0.10487567 -0.017101308 #> CX108 -0.010673165 -0.03906141 -0.05834507 -0.08205253 -0.10100631 -0.022314285 #> CX109 -0.008018621 -0.03278166 -0.05973300 -0.08491355 -0.10133516 -0.018724402 #> CX110 -0.011894825 -0.03700534 -0.05728326 -0.07951859 -0.09869608 -0.017798403 #> CX111 -0.014985750 -0.03983215 -0.06524722 -0.09406644 -0.11797937 -0.017169369 #> CX112 -0.013257204 -0.03887045 -0.06562399 -0.08856518 -0.10527379 -0.021787205 #> CX113 -0.011450525 -0.03243768 -0.05903150 -0.08555464 -0.10609845 -0.015088975 #> CX114 -0.011663783 -0.03826338 -0.06602557 -0.10037116 -0.11768366 -0.016465993 #> CX115 -0.012353681 -0.03551555 -0.06244976 -0.09033097 -0.10471702 -0.019157513 #> CX116 -0.016204202 -0.04316559 -0.06920846 -0.09247241 -0.11333981 -0.024230163 #> CX117 -0.010294909 -0.03367189 -0.06181392 -0.08869494 -0.10357813 -0.020483250 #> CX118 -0.009854288 -0.03844275 -0.06624935 -0.09575786 -0.10947066 -0.031365179 #> CX119 -0.017650235 -0.04023434 -0.05830157 -0.08376944 -0.10011781 -0.023657629 #> CX120 -0.016994086 -0.04075366 -0.06603417 -0.09305920 -0.10748884 -0.025143006 #> CX121 -0.016097956 -0.04470260 -0.06733971 -0.09199145 -0.11052390 -0.013972544 #> CX122 -0.014023818 -0.03254778 -0.05833005 -0.08242031 -0.10218434 -0.014351771 #> CX123 -0.013940498 -0.03357926 -0.06438180 -0.08609256 -0.10173894 -0.018241610 #> CX124 -0.012729199 -0.03257353 -0.05686875 -0.08601868 -0.09105267 -0.021119040 #> CX125 -0.012021816 -0.03914166 -0.06331033 -0.09482505 -0.11425836 -0.009229708 #> DE126 -0.019319910 -0.03999012 -0.06598948 -0.09151587 -0.10655099 -0.009402691 #> DE127 -0.013157041 -0.03350065 -0.05475301 -0.07904062 -0.09178239 -0.020872877 #> y13 y14 y15 y16 y17 y18 #> AN1 0.031653251 0.03394145 0.05065519 0.023694351 -0.0058531156 -0.02386017 #> AN2 0.023930124 0.02633191 0.03960071 0.017386724 -0.0058883600 -0.02588693 #> AN3 0.016914452 0.01728375 0.03471704 0.011250077 -0.0075009263 -0.01706643 #> AN4 0.007944998 0.02071929 0.04123774 0.023722845 -0.0057300114 -0.02163378 #> AN5 0.024239303 0.02436660 0.04056937 0.019005613 -0.0020748921 -0.01906749 #> AN6 0.014703930 0.02479341 0.04364098 0.020180182 -0.0041146405 -0.01814230 #> AN7 0.023330304 0.02524160 0.04136306 0.017184102 -0.0147098834 -0.02795570 #> AN8 0.012717785 0.02065677 0.03952636 0.014507114 -0.0089944390 -0.02281300 #> AN9 0.019749885 0.02201980 0.03843079 0.012804281 -0.0100737547 -0.02081712 #> AN10 0.010656820 0.02236025 0.04272360 0.021347941 -0.0036869423 -0.01416372 #> AN11 0.009339839 0.02218767 0.04330031 0.020130765 -0.0068556079 -0.01670046 #> TO12 0.012542711 0.01495272 0.04138213 0.009940141 -0.0082878628 -0.02173497 #> WY13 0.025506841 0.02470727 0.04155787 0.016111610 -0.0090264837 -0.02423198 #> WY14 0.015089999 0.03185406 0.04444696 0.024840804 -0.0064136917 -0.01764814 #> WY15 0.011286902 0.02144045 0.03722986 0.016704989 -0.0056998378 -0.01821252 #> WY16 0.009266234 0.01941323 0.03907200 0.015109806 -0.0060277218 -0.02533050 #> UR17 0.011366859 0.03519135 0.05027222 0.022840549 -0.0101491833 -0.02237430 #> UR18 0.016039551 0.03801945 0.05674724 0.011803866 -0.0232327002 -0.03933606 #> UR19 0.015607256 0.02687834 0.04595487 0.013225571 -0.0178589142 -0.02754166 #> UR20 0.016589336 0.03070214 0.04560762 0.017645589 -0.0102842014 -0.02281823 #> CA21 0.012199133 0.03094133 0.04865604 0.019396951 -0.0052322022 -0.02886625 #> CA22 0.012822346 0.02598790 0.04731617 0.018519444 -0.0111925712 -0.02713474 #> CA23 0.009232801 0.02496965 0.04993777 0.023999457 -0.0025086781 -0.02920003 #> CA24 0.019171445 0.03433137 0.04741436 0.020599082 -0.0074399680 -0.02660992 #> CA25 0.009566033 0.02658144 0.05113483 0.022691958 -0.0020231414 -0.02198399 #> CA26 0.017524234 0.02454569 0.03994687 0.019174759 -0.0005099502 -0.02142183 #> CA27 0.018046519 0.02646747 0.04038172 0.018052689 -0.0098840617 -0.01427539 #> OR28 0.017944287 0.03140055 0.04424794 0.027462220 -0.0063186282 -0.02917818 #> MA29 0.012586080 0.02288037 0.04696049 0.021867340 -0.0018019964 -0.03010091 #> MA30 0.020154213 0.02900446 0.04106282 0.017263472 -0.0109026150 -0.02331410 #> MA31 0.014369888 0.02456438 0.04953818 0.027385068 -0.0047871505 -0.01774976 #> PS32 0.015373535 0.02680157 0.04710279 0.021307525 -0.0071921204 -0.03179500 #> PS33 0.022336072 0.02810195 0.05024300 0.022540270 -0.0111040272 -0.03533574 #> PS34 0.020315464 0.03303756 0.04869750 0.021234398 -0.0072347126 -0.02762668 #> PS35 0.012788035 0.02439453 0.04751539 0.020824472 -0.0076933034 -0.01921035 #> PS36 0.020300111 0.02820023 0.04385212 0.017569210 -0.0109004659 -0.02892289 #> PS37 0.019334246 0.02777829 0.04141996 0.018432920 -0.0056363825 -0.02279697 #> PS38 0.014203886 0.01976390 0.03926354 0.018373256 -0.0064799250 -0.02255351 #> PS39 0.018807152 0.02727129 0.04427371 0.020818172 -0.0084929742 -0.02757373 #> PS40 0.017286358 0.02264821 0.04726978 0.019224306 -0.0070545666 -0.02488379 #> PS41 0.026375073 0.02492808 0.03676656 0.010547022 -0.0160261360 -0.02960204 #> PS42 0.024353039 0.02959271 0.04752195 0.018790914 -0.0033314324 -0.02361597 #> PS43 0.009696453 0.02962132 0.05395096 0.028008307 -0.0054060649 -0.02278089 #> AE44 0.022209613 0.02872914 0.04678593 0.021432306 -0.0062438005 -0.03325430 #> AE45 0.017070529 0.02500476 0.04207118 0.015590449 -0.0125041590 -0.02643712 #> AE46 0.019955954 0.02210685 0.04425050 0.016124350 -0.0059187470 -0.02112102 #> AE47 0.012764921 0.02549636 0.04832930 0.021279454 -0.0072668469 -0.03053345 #> AE48 0.009012434 0.02788134 0.04195447 0.019452316 -0.0033602107 -0.02224146 #> AE49 0.020167979 0.02671760 0.03790360 0.017879879 -0.0082872336 -0.02436522 #> AE50 0.017980169 0.02522621 0.04455923 0.022412292 0.0006199068 -0.02573227 #> AE51 0.028273610 0.02475281 0.04560509 0.018289771 -0.0155381857 -0.03078107 #> AE52 0.018498035 0.02806079 0.04598992 0.019078102 -0.0100429219 -0.02107760 #> AE53 0.018989183 0.02826034 0.04836101 0.022696282 -0.0086760730 -0.02522523 #> AE54 0.016955963 0.02749484 0.04935746 0.023671924 -0.0054385706 -0.03005728 #> AE55 0.007775690 0.01964697 0.03970104 0.017668638 -0.0056924635 -0.01928116 #> AE56 0.015528690 0.01944325 0.04181501 0.016532880 -0.0075657410 -0.02127519 #> AE57 0.021657914 0.03143334 0.05045469 0.022103526 -0.0032291590 -0.02976023 #> AE58 0.014852798 0.02357382 0.04124862 0.017758954 -0.0126937695 -0.02278433 #> AE59 0.013820549 0.02138296 0.03838600 0.012431547 -0.0118056825 -0.02429321 #> AE60 0.017799748 0.03216945 0.05085970 0.020439774 -0.0079058535 -0.03668566 #> AE61 0.013592307 0.02666289 0.05506965 0.024674679 -0.0035991276 -0.01729537 #> AE62 0.010791212 0.02280408 0.04030167 0.016172907 -0.0081164709 -0.01555793 #> AE63 0.019867096 0.02713715 0.04740922 0.015228820 -0.0146203454 -0.02668283 #> AE64 0.029566394 0.02811684 0.04582514 0.018185289 -0.0051168536 -0.03450801 #> AE65 0.013745957 0.02120385 0.03460146 0.015391025 -0.0102461772 -0.02624110 #> AE66 0.015232007 0.02321355 0.05194073 0.018371196 -0.0109811519 -0.03403938 #> AE67 0.020651093 0.02197065 0.03654878 0.015461638 -0.0086958717 -0.02319231 #> AE68 0.015037573 0.02794225 0.04623979 0.019435954 -0.0080725868 -0.02995841 #> AE69 0.015459714 0.02141548 0.04330776 0.017231297 -0.0125420006 -0.02663824 #> AE70 0.014133953 0.02400491 0.04993628 0.024999386 -0.0113126526 -0.02796019 #> AE71 0.026204493 0.02682321 0.04498873 0.016597931 -0.0147664476 -0.03437959 #> AE72 0.017115848 0.02847935 0.05058032 0.018729056 -0.0130620477 -0.02942701 #> AE73 0.019057488 0.03181711 0.04992821 0.020752837 -0.0014266702 -0.01479561 #> AE74 0.016245319 0.03259439 0.04730746 0.023664786 -0.0069021820 -0.02787117 #> AE75 0.021831863 0.02721258 0.04641488 0.013558764 -0.0120488307 -0.02849579 #> AE76 0.019244522 0.02578020 0.04748669 0.017166620 -0.0114005808 -0.02961030 #> AE77 0.020455607 0.02536790 0.04869105 0.018380169 -0.0107076381 -0.02900154 #> AE78 0.019015265 0.03337134 0.04117545 0.015356576 -0.0116219684 -0.02411763 #> AE79 0.019995869 0.02636401 0.04234840 0.017890749 -0.0082389520 -0.02431138 #> AE80 0.017930466 0.02416673 0.04377548 0.019651464 -0.0083685772 -0.02649514 #> AE81 0.024148981 0.02919554 0.04869795 0.019255872 -0.0100449592 -0.02488700 #> AE82 0.020578909 0.02706156 0.04897019 0.018344967 -0.0091223541 -0.02522526 #> AE83 0.016781292 0.03114929 0.05394455 0.024519177 -0.0092320644 -0.02699144 #> AE84 0.024609830 0.02873131 0.04198269 0.016284835 -0.0153416977 -0.03602225 #> AE85 0.010396520 0.02846303 0.04731145 0.025320390 -0.0055367524 -0.02458945 #> AE86 0.036343087 0.02984724 0.04512154 0.020647760 -0.0058120162 -0.02373160 #> AE87 0.020225282 0.02813906 0.04238996 0.015529013 -0.0086145568 -0.01932807 #> AE88 0.015667143 0.02902972 0.04316773 0.021523222 -0.0017849076 -0.02226195 #> AE89 0.010784658 0.02446307 0.05051475 0.021313287 -0.0053891002 -0.02177189 #> AE90 0.027142506 0.03212522 0.05108388 0.023257334 -0.0046635032 -0.03073238 #> AE91 0.019033489 0.03167430 0.04462634 0.018496419 -0.0112092137 -0.02226589 #> AE92 0.012810939 0.02363067 0.04162214 0.021165370 -0.0067165829 -0.01574059 #> AE93 0.022471103 0.02651858 0.04508543 0.014069432 -0.0157448155 -0.03293319 #> AE94 0.012305865 0.02681931 0.04454421 0.023851832 -0.0029548417 -0.02231764 #> AE95 0.016906129 0.02469427 0.04023863 0.021999889 -0.0084593595 -0.01607771 #> AE96 0.017485117 0.02547147 0.04704657 0.020538267 -0.0079848838 -0.02043972 #> AE97 0.016648864 0.02472005 0.04875918 0.015428675 -0.0047708489 -0.02379334 #> AE98 0.013391858 0.02393506 0.04162961 0.019367765 -0.0054168820 -0.02012284 #> AE99 0.019977565 0.02394541 0.04300177 0.020764156 -0.0044495209 -0.02427907 #> AE100 0.011980687 0.02528265 0.04703604 0.018302914 -0.0085743289 -0.02570950 #> CX101 0.016228827 0.02795540 0.04467222 0.019165494 -0.0099841850 -0.02637927 #> CX102 0.017259331 0.01912946 0.04067772 0.015083424 -0.0067027356 -0.02043425 #> CX103 0.020074121 0.03029000 0.04633641 0.020038662 -0.0052371329 -0.02653335 #> CX104 0.014934569 0.02833998 0.04791502 0.024512049 -0.0071740845 -0.01984566 #> CX105 0.019219428 0.02529887 0.03836062 0.019788647 -0.0075309252 -0.02564094 #> CX106 0.018299308 0.02768259 0.04677679 0.019768234 -0.0097009633 -0.02610560 #> CX107 0.015806760 0.02182572 0.03975539 0.017122074 -0.0078549731 -0.02662050 #> CX108 0.016215262 0.02519327 0.04243383 0.010268036 -0.0112934336 -0.03094322 #> CX109 0.017068885 0.02501765 0.03545559 0.016413355 -0.0056047239 -0.02321445 #> CX110 0.012385269 0.02481311 0.04163334 0.020597841 -0.0085527751 -0.01309114 #> CX111 0.020635245 0.02905378 0.04625604 0.017163441 -0.0095672256 -0.02526990 #> CX112 0.012659275 0.02760717 0.04363982 0.019186884 -0.0085127474 -0.01768584 #> CX113 0.014469364 0.01985292 0.04219240 0.018608647 -0.0039236081 -0.01550316 #> CX114 0.018322739 0.02242499 0.03905605 0.015973206 -0.0068638956 -0.01703203 #> CX115 0.014974865 0.02220072 0.04055723 0.018212767 -0.0086772873 -0.02478906 #> CX116 0.017431556 0.03145910 0.04683659 0.021299988 -0.0043485687 -0.02504549 #> CX117 0.017905431 0.02938074 0.04469183 0.018408516 -0.0043347815 -0.02194933 #> CX118 0.027152233 0.02328459 0.03539228 0.015205687 -0.0075409103 -0.02621603 #> CX119 0.017132004 0.02244083 0.04338429 0.016764177 -0.0031370859 -0.02173155 #> CX120 0.017126560 0.03024564 0.04707770 0.019113201 -0.0119658108 -0.02313595 #> CX121 0.023244195 0.02442777 0.04507924 0.020724090 -0.0018107845 -0.01827788 #> CX122 0.015060402 0.02122439 0.04010077 0.016097457 -0.0109813961 -0.02871446 #> CX123 0.012181115 0.02677886 0.04411853 0.020245582 -0.0085144121 -0.01780218 #> CX124 0.012934711 0.02604046 0.04671372 0.019656344 -0.0007938145 -0.02303963 #> CX125 0.019920346 0.02308511 0.04046563 0.013778338 -0.0108924185 -0.02854041 #> DE126 0.018362791 0.02746598 0.03974138 0.015250649 -0.0136039673 -0.02421991 #> DE127 0.016632923 0.02410343 0.03776670 0.017676786 -0.0115576584 -0.01507777"},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Coo ","title":"Coo ","text":"Coo class 'parent' 'super' class , Opn Ldk classes.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Coo ","text":"","code":"Coo(...)"},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Coo ","text":"... anything , anyway, function simply returns message.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Coo ","text":"list class Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Coo ","text":"Useful shortcuts described . See browseVignettes(\"Momocs\") detail design behind Momocs' classes. Coo class 'parent' class following 'child' classes closed outlines Opn open outlines Ldk configuration landmarks Since 'child classes' handle \\((x; y)\\) coordinates among generic methods, also specificity, architecture allow recycle generic methods use specific methods. words, , Opn Ldk classes , primarily, Coo objects define generic specific methods. See respective help pages help. Coo objects following components: $coo list matrices coordinates $fac data_frame covariates (). can provide data_frame directly, long many rows matrices $coo (see examples), use helper function lf_structure. can access methods available Coo objects methods(class=Coo).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Coo ","text":"","code":"# to see all methods for Coo objects. methods(class='Coo') #> [1] $ Ldk #> [3] Opn Out #> [5] [ [<- #> [7] arrange as_df #> [9] chop coo_align #> [11] coo_aligncalliper coo_alignminradius #> [13] coo_alignxax coo_angle_edges #> [15] coo_angle_tangent coo_area #> [17] coo_baseline coo_boundingbox #> [19] coo_calliper coo_centdist #> [21] coo_center coo_centpos #> [23] coo_centsize coo_check #> [25] coo_chull coo_chull_onion #> [27] coo_circularity coo_circularityharalick #> [29] coo_circularitynorm coo_close #> [31] coo_convexity coo_diffrange #> [33] coo_down coo_dxy #> [35] coo_eccentricityboundingbox coo_eccentricityeigen #> [37] coo_elongation coo_extract #> [39] coo_flipx coo_flipy #> [41] coo_force2close coo_interpolate #> [43] coo_intersect_angle coo_intersect_direction #> [45] coo_intersect_segment coo_is_closed #> [47] coo_jitter coo_left #> [49] coo_length coo_likely_clockwise #> [51] coo_lw coo_nb #> [53] coo_perim coo_perimcum #> [55] coo_perimpts coo_range #> [57] coo_range_enlarge coo_rectangularity #> [59] coo_rectilinearity coo_rev #> [61] coo_right coo_rotate #> [63] coo_rotatecenter coo_samplerr #> [65] coo_scalars coo_scale #> [67] coo_scalex coo_scaley #> [69] coo_shearx coo_sheary #> [71] coo_slide coo_slidedirection #> [73] coo_slidegap coo_smooth #> [75] coo_solidity coo_tac #> [77] coo_template coo_template_relatively #> [79] coo_trans coo_trim #> [81] coo_trimbottom coo_trimtop #> [83] coo_truss coo_unclose #> [85] coo_untiltx coo_up #> [87] coo_width dfourier #> [89] dim filter #> [91] inspect is_equallyspacedradii #> [93] length measure #> [95] mutate names #> [97] names<- print #> [99] rename sample_frac #> [101] sample_n select #> [103] slice stack #> [105] str subsetize #> [107] verify #> see '?methods' for accessing help and source code # to see all methods for Out objects. methods(class='Out') # same for Opn and Ldk #> [1] add_ldk combine coo_bookstein coo_down #> [5] coo_left coo_right coo_sample coo_sample_prop #> [9] coo_slice coo_up d def_ldk #> [13] def_ldk_angle def_ldk_direction efourier fgProcrustes #> [17] get_ldk mosaic panel pile #> [21] rearrange_ldk rfourier sfourier tfourier #> see '?methods' for accessing help and source code # Let's take an Out example. But all methods shown here # work on Ldk (try on 'wings') and on Opn ('olea') bot #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk # Primarily a 'Coo' object, but also an 'Out' class(bot) #> [1] \"Out\" \"Coo\" inherits(bot, \"Coo\") #> [1] TRUE panel(bot) stack(bot) # Getters (you can also use it to set data) bot[1] %>% coo_plot() bot[1:5] %>% str() #> List of 5 #> $ brahma : num [1:138, 1:2] 37 40 40 43 46 48 52 54 57 59 ... #> $ caney : num [1:168, 1:2] 53 53 54 53 54 54 54 54 54 53 ... #> $ chimay : num [1:189, 1:2] 49 49 49 50 50 50 51 50 50 50 ... #> $ corona : num [1:129, 1:2] 91 91 90 91 91 91 91 91 91 91 ... #> $ deusventrue: num [1:152, 1:2] 74 70 62 59 52 49 47 43 41 38 ... # Setters bot[1] <- shapes[4] panel(bot) bot[1:5] <- shapes[4:8] panel(bot) # access the different components # $coo coordinates head(bot$coo) #> $brahma #> [,1] [,2] #> [1,] 200 62 #> [2,] 200 61 #> [3,] 199 60 #> [4,] 198 59 #> [5,] 197 58 #> [6,] 197 57 #> [7,] 196 56 #> [8,] 195 56 #> [9,] 196 56 #> [10,] 197 56 #> [11,] 198 56 #> [12,] 199 56 #> [13,] 200 56 #> [14,] 201 55 #> [15,] 202 55 #> [16,] 203 55 #> [17,] 204 55 #> [18,] 205 54 #> [19,] 206 54 #> [20,] 207 53 #> [21,] 208 52 #> [22,] 208 51 #> [23,] 209 50 #> [24,] 209 49 #> [25,] 209 48 #> [26,] 209 47 #> [27,] 208 46 #> [28,] 208 45 #> [29,] 207 44 #> [30,] 206 44 #> [31,] 205 43 #> [32,] 204 43 #> [33,] 203 43 #> [34,] 202 43 #> [35,] 201 43 #> [36,] 200 43 #> [37,] 199 43 #> [38,] 198 43 #> [39,] 197 43 #> [40,] 196 42 #> [41,] 195 42 #> [42,] 194 42 #> [43,] 193 42 #> [44,] 192 42 #> [45,] 191 42 #> [46,] 190 42 #> [47,] 189 42 #> [48,] 188 42 #> [49,] 187 42 #> [50,] 186 42 #> [51,] 185 42 #> [52,] 184 42 #> [53,] 183 42 #> [54,] 182 42 #> [55,] 181 42 #> [56,] 180 42 #> [57,] 179 42 #> [58,] 178 43 #> [59,] 177 42 #> [60,] 176 43 #> [61,] 175 43 #> [62,] 174 43 #> [63,] 173 43 #> [64,] 172 43 #> [65,] 171 43 #> [66,] 170 43 #> [67,] 169 43 #> [68,] 168 43 #> [69,] 167 43 #> [70,] 166 43 #> [71,] 165 43 #> [72,] 164 43 #> [73,] 163 43 #> [74,] 162 43 #> [75,] 161 43 #> [76,] 160 43 #> [77,] 159 43 #> [78,] 158 43 #> [79,] 157 43 #> [80,] 156 43 #> [81,] 155 43 #> [82,] 154 43 #> [83,] 153 43 #> [84,] 152 43 #> [85,] 151 43 #> [86,] 150 43 #> [87,] 149 43 #> [88,] 148 43 #> [89,] 147 43 #> [90,] 146 44 #> [91,] 145 44 #> [92,] 144 44 #> [93,] 143 44 #> [94,] 143 43 #> [95,] 143 42 #> [96,] 143 41 #> [97,] 142 40 #> [98,] 142 39 #> [99,] 142 38 #> [100,] 142 37 #> [101,] 142 36 #> [102,] 142 35 #> [103,] 143 34 #> [104,] 143 33 #> [105,] 143 32 #> [106,] 144 31 #> [107,] 145 30 #> [108,] 145 29 #> [109,] 146 28 #> [110,] 147 27 #> [111,] 148 27 #> [112,] 149 26 #> [113,] 150 25 #> [114,] 151 25 #> [115,] 152 24 #> [116,] 153 24 #> [117,] 154 23 #> [118,] 155 23 #> [119,] 156 23 #> [120,] 157 22 #> [121,] 158 22 #> [122,] 159 22 #> [123,] 160 21 #> [124,] 161 21 #> [125,] 162 21 #> [126,] 163 21 #> [127,] 164 21 #> [128,] 165 20 #> [129,] 166 20 #> [130,] 167 20 #> [131,] 168 20 #> [132,] 169 20 #> [133,] 170 20 #> [134,] 171 20 #> [135,] 172 20 #> [136,] 173 20 #> [137,] 174 19 #> [138,] 175 19 #> [139,] 176 19 #> [140,] 177 19 #> [141,] 178 19 #> [142,] 179 19 #> [143,] 180 19 #> [144,] 181 20 #> [145,] 182 20 #> [146,] 183 20 #> [147,] 184 20 #> [148,] 185 20 #> [149,] 186 20 #> [150,] 187 20 #> [151,] 188 20 #> [152,] 189 21 #> [153,] 190 21 #> [154,] 191 21 #> [155,] 192 21 #> [156,] 193 21 #> [157,] 194 21 #> [158,] 195 22 #> [159,] 196 22 #> [160,] 197 22 #> [161,] 198 22 #> [162,] 199 22 #> [163,] 200 22 #> [164,] 201 22 #> [165,] 202 22 #> [166,] 203 22 #> [167,] 204 22 #> [168,] 205 22 #> [169,] 206 22 #> [170,] 207 21 #> [171,] 208 20 #> [172,] 208 19 #> [173,] 207 18 #> [174,] 206 17 #> [175,] 205 17 #> [176,] 204 16 #> [177,] 203 16 #> [178,] 202 15 #> [179,] 201 15 #> [180,] 200 14 #> [181,] 199 14 #> [182,] 198 14 #> [183,] 197 13 #> [184,] 196 13 #> [185,] 195 13 #> [186,] 194 12 #> [187,] 193 12 #> [188,] 192 12 #> [189,] 191 11 #> [190,] 190 11 #> [191,] 189 11 #> [192,] 188 11 #> [193,] 187 10 #> [194,] 186 10 #> [195,] 185 10 #> [196,] 184 10 #> [197,] 183 9 #> [198,] 182 9 #> [199,] 181 10 #> [200,] 180 9 #> [201,] 179 9 #> [202,] 178 9 #> [203,] 177 9 #> [204,] 176 9 #> [205,] 175 9 #> [206,] 174 9 #> [207,] 173 9 #> [208,] 172 9 #> [209,] 171 9 #> [210,] 170 9 #> [211,] 169 9 #> [212,] 168 9 #> [213,] 167 9 #> [214,] 166 9 #> [215,] 165 9 #> [216,] 164 9 #> [217,] 163 9 #> [218,] 162 9 #> [219,] 161 9 #> [220,] 160 10 #> [221,] 159 10 #> [222,] 158 10 #> [223,] 157 10 #> [224,] 156 10 #> [225,] 155 11 #> [226,] 154 11 #> [227,] 153 11 #> [228,] 152 12 #> [229,] 151 12 #> [230,] 150 12 #> [231,] 149 13 #> [232,] 148 13 #> [233,] 147 14 #> [234,] 146 14 #> [235,] 145 15 #> [236,] 144 15 #> [237,] 143 16 #> [238,] 142 17 #> [239,] 141 17 #> [240,] 140 18 #> [241,] 139 19 #> [242,] 138 20 #> [243,] 137 21 #> [244,] 136 22 #> [245,] 135 23 #> [246,] 134 24 #> [247,] 134 25 #> [248,] 133 26 #> [249,] 133 27 #> [250,] 132 28 #> [251,] 132 29 #> [252,] 131 30 #> [253,] 131 31 #> [254,] 131 32 #> [255,] 130 33 #> [256,] 130 34 #> [257,] 130 35 #> [258,] 130 36 #> [259,] 130 37 #> [260,] 130 38 #> [261,] 130 39 #> [262,] 130 40 #> [263,] 130 41 #> [264,] 130 42 #> [265,] 130 43 #> [266,] 130 44 #> [267,] 130 45 #> [268,] 131 46 #> [269,] 131 47 #> [270,] 131 48 #> [271,] 132 49 #> [272,] 132 50 #> [273,] 132 51 #> [274,] 133 52 #> [275,] 133 53 #> [276,] 133 54 #> [277,] 134 55 #> [278,] 135 56 #> [279,] 135 57 #> [280,] 135 58 #> [281,] 135 59 #> [282,] 136 60 #> [283,] 136 61 #> [284,] 135 62 #> [285,] 136 63 #> [286,] 136 64 #> [287,] 136 65 #> [288,] 136 66 #> [289,] 136 67 #> [290,] 135 68 #> [291,] 136 69 #> [292,] 135 70 #> [293,] 135 71 #> [294,] 135 72 #> [295,] 135 73 #> [296,] 135 74 #> [297,] 134 75 #> [298,] 135 76 #> [299,] 134 77 #> [300,] 134 78 #> [301,] 134 79 #> [302,] 134 80 #> [303,] 134 81 #> [304,] 134 82 #> [305,] 134 83 #> [306,] 133 84 #> [307,] 133 85 #> [308,] 134 86 #> [309,] 134 87 #> [310,] 134 88 #> [311,] 133 89 #> [312,] 133 90 #> [313,] 133 91 #> [314,] 133 92 #> [315,] 133 93 #> [316,] 133 94 #> [317,] 133 95 #> [318,] 133 96 #> [319,] 133 97 #> [320,] 133 98 #> [321,] 133 99 #> [322,] 133 100 #> [323,] 133 101 #> [324,] 133 102 #> [325,] 133 103 #> [326,] 133 104 #> [327,] 133 105 #> [328,] 133 106 #> [329,] 133 107 #> [330,] 133 108 #> [331,] 133 109 #> [332,] 134 110 #> [333,] 134 111 #> [334,] 133 112 #> [335,] 134 113 #> [336,] 134 114 #> [337,] 134 115 #> [338,] 134 116 #> [339,] 134 117 #> [340,] 135 118 #> [341,] 135 119 #> [342,] 135 120 #> [343,] 136 121 #> [344,] 136 122 #> [345,] 136 123 #> [346,] 137 124 #> [347,] 137 125 #> [348,] 138 126 #> [349,] 138 127 #> [350,] 139 128 #> [351,] 139 129 #> [352,] 140 130 #> [353,] 140 131 #> [354,] 141 132 #> [355,] 141 133 #> [356,] 142 134 #> [357,] 142 135 #> [358,] 143 136 #> [359,] 143 137 #> [360,] 144 138 #> [361,] 144 139 #> [362,] 145 140 #> [363,] 145 141 #> [364,] 146 142 #> [365,] 147 143 #> [366,] 148 144 #> [367,] 148 145 #> [368,] 149 146 #> [369,] 150 147 #> [370,] 150 148 #> [371,] 151 149 #> [372,] 152 150 #> [373,] 153 151 #> [374,] 154 152 #> [375,] 155 153 #> [376,] 156 154 #> [377,] 157 155 #> [378,] 158 156 #> [379,] 159 157 #> [380,] 160 158 #> [381,] 161 158 #> [382,] 162 159 #> [383,] 163 159 #> [384,] 164 160 #> [385,] 165 160 #> [386,] 166 160 #> [387,] 167 161 #> [388,] 168 161 #> [389,] 169 161 #> [390,] 170 162 #> [391,] 171 162 #> [392,] 172 162 #> [393,] 173 163 #> [394,] 174 164 #> [395,] 175 164 #> [396,] 176 165 #> [397,] 177 165 #> [398,] 178 166 #> [399,] 179 167 #> [400,] 180 167 #> [401,] 181 168 #> [402,] 182 169 #> [403,] 183 170 #> [404,] 184 171 #> [405,] 185 172 #> [406,] 186 173 #> [407,] 187 174 #> [408,] 187 175 #> [409,] 188 176 #> [410,] 189 177 #> [411,] 189 178 #> [412,] 190 179 #> [413,] 190 180 #> [414,] 191 181 #> [415,] 191 182 #> [416,] 191 183 #> [417,] 191 184 #> [418,] 191 185 #> [419,] 191 186 #> [420,] 191 187 #> [421,] 190 188 #> [422,] 191 189 #> [423,] 191 190 #> [424,] 191 191 #> [425,] 191 192 #> [426,] 192 193 #> [427,] 192 194 #> [428,] 192 195 #> [429,] 193 196 #> [430,] 193 197 #> [431,] 194 198 #> [432,] 194 199 #> [433,] 194 200 #> [434,] 195 201 #> [435,] 196 202 #> [436,] 196 203 #> [437,] 197 204 #> [438,] 197 205 #> [439,] 198 206 #> [440,] 199 207 #> [441,] 200 208 #> [442,] 201 209 #> [443,] 202 210 #> [444,] 203 210 #> [445,] 204 211 #> [446,] 205 212 #> [447,] 206 212 #> [448,] 207 213 #> [449,] 208 213 #> [450,] 209 214 #> [451,] 210 215 #> [452,] 211 216 #> [453,] 211 217 #> [454,] 211 218 #> [455,] 212 219 #> [456,] 212 220 #> [457,] 213 221 #> [458,] 213 222 #> [459,] 214 223 #> [460,] 215 224 #> [461,] 215 225 #> [462,] 216 226 #> [463,] 217 227 #> [464,] 217 228 #> [465,] 218 229 #> [466,] 219 230 #> [467,] 220 230 #> [468,] 221 231 #> [469,] 222 231 #> [470,] 223 230 #> [471,] 224 229 #> [472,] 225 228 #> [473,] 225 227 #> [474,] 225 226 #> [475,] 225 225 #> [476,] 226 224 #> [477,] 225 223 #> [478,] 225 222 #> [479,] 225 221 #> [480,] 226 220 #> [481,] 226 219 #> [482,] 226 218 #> [483,] 226 217 #> [484,] 226 216 #> [485,] 226 215 #> [486,] 226 214 #> [487,] 226 213 #> [488,] 226 212 #> [489,] 226 211 #> [490,] 227 211 #> [491,] 228 211 #> [492,] 229 210 #> [493,] 230 210 #> [494,] 231 210 #> [495,] 232 209 #> [496,] 233 209 #> [497,] 234 208 #> [498,] 235 208 #> [499,] 236 207 #> [500,] 237 207 #> [501,] 238 206 #> [502,] 238 205 #> [503,] 239 204 #> [504,] 240 203 #> [505,] 240 202 #> [506,] 241 201 #> [507,] 242 200 #> [508,] 243 199 #> [509,] 244 199 #> [510,] 245 199 #> [511,] 246 198 #> [512,] 247 198 #> [513,] 248 197 #> [514,] 249 196 #> [515,] 249 195 #> [516,] 250 194 #> [517,] 250 193 #> [518,] 249 192 #> [519,] 249 191 #> [520,] 249 190 #> [521,] 248 189 #> [522,] 248 188 #> [523,] 248 187 #> [524,] 247 186 #> [525,] 246 185 #> [526,] 245 184 #> [527,] 244 183 #> [528,] 243 182 #> [529,] 242 181 #> [530,] 241 180 #> [531,] 240 180 #> [532,] 239 179 #> [533,] 238 178 #> [534,] 237 178 #> [535,] 236 177 #> [536,] 235 176 #> [537,] 235 175 #> [538,] 235 174 #> [539,] 235 173 #> [540,] 235 172 #> [541,] 235 171 #> [542,] 235 170 #> [543,] 235 169 #> [544,] 236 168 #> [545,] 235 167 #> [546,] 236 166 #> [547,] 236 165 #> [548,] 236 164 #> [549,] 236 163 #> [550,] 236 162 #> [551,] 237 161 #> [552,] 236 160 #> [553,] 237 159 #> [554,] 237 158 #> [555,] 237 157 #> [556,] 237 156 #> [557,] 237 155 #> [558,] 237 154 #> [559,] 237 153 #> [560,] 238 152 #> [561,] 237 151 #> [562,] 237 150 #> [563,] 237 149 #> [564,] 237 148 #> [565,] 237 147 #> [566,] 238 146 #> [567,] 237 145 #> [568,] 237 144 #> [569,] 237 143 #> [570,] 237 142 #> [571,] 237 141 #> [572,] 237 140 #> [573,] 237 139 #> [574,] 237 138 #> [575,] 236 137 #> [576,] 236 136 #> [577,] 236 135 #> [578,] 235 134 #> [579,] 235 133 #> [580,] 235 132 #> [581,] 234 131 #> [582,] 234 130 #> [583,] 233 129 #> [584,] 232 128 #> [585,] 232 127 #> [586,] 231 126 #> [587,] 230 125 #> [588,] 230 124 #> [589,] 229 123 #> [590,] 228 122 #> [591,] 228 121 #> [592,] 227 120 #> [593,] 226 119 #> [594,] 226 118 #> [595,] 226 117 #> [596,] 225 116 #> [597,] 224 115 #> [598,] 224 114 #> [599,] 224 113 #> [600,] 223 112 #> [601,] 223 111 #> [602,] 223 110 #> [603,] 223 109 #> [604,] 222 108 #> [605,] 222 107 #> [606,] 222 106 #> [607,] 222 105 #> [608,] 222 104 #> [609,] 221 103 #> [610,] 221 102 #> [611,] 221 101 #> [612,] 221 100 #> [613,] 221 99 #> [614,] 221 98 #> [615,] 221 97 #> [616,] 221 96 #> [617,] 221 95 #> [618,] 221 94 #> [619,] 221 93 #> [620,] 221 92 #> [621,] 221 91 #> [622,] 221 90 #> [623,] 221 89 #> [624,] 221 88 #> [625,] 221 87 #> [626,] 221 86 #> [627,] 221 85 #> [628,] 221 84 #> [629,] 221 83 #> [630,] 221 82 #> [631,] 221 81 #> [632,] 221 80 #> [633,] 221 79 #> [634,] 221 78 #> [635,] 221 77 #> [636,] 221 76 #> [637,] 221 75 #> [638,] 221 74 #> [639,] 221 73 #> [640,] 221 72 #> [641,] 221 71 #> [642,] 221 70 #> [643,] 222 69 #> [644,] 222 68 #> [645,] 222 67 #> [646,] 222 66 #> [647,] 222 65 #> [648,] 222 64 #> [649,] 222 63 #> [650,] 223 62 #> [651,] 224 62 #> [652,] 225 61 #> [653,] 226 61 #> [654,] 227 61 #> [655,] 228 61 #> [656,] 229 60 #> [657,] 230 60 #> [658,] 231 60 #> [659,] 232 59 #> [660,] 232 58 #> [661,] 233 57 #> [662,] 232 56 #> [663,] 232 55 #> [664,] 231 54 #> [665,] 230 53 #> [666,] 229 52 #> [667,] 230 51 #> [668,] 229 50 #> [669,] 230 49 #> [670,] 229 48 #> [671,] 228 47 #> [672,] 227 46 #> [673,] 226 46 #> [674,] 225 45 #> [675,] 224 45 #> [676,] 223 45 #> [677,] 222 45 #> [678,] 221 45 #> [679,] 220 45 #> [680,] 219 45 #> [681,] 218 45 #> [682,] 217 45 #> [683,] 216 45 #> [684,] 215 46 #> [685,] 214 46 #> [686,] 213 47 #> [687,] 212 48 #> [688,] 211 49 #> [689,] 210 50 #> [690,] 209 51 #> [691,] 208 52 #> [692,] 208 53 #> [693,] 207 54 #> [694,] 206 55 #> [695,] 206 56 #> [696,] 205 57 #> [697,] 205 58 #> [698,] 204 59 #> [699,] 204 60 #> [700,] 203 61 #> [701,] 203 62 #> [702,] 203 63 #> [703,] 202 64 #> [704,] 202 65 #> [705,] 202 66 #> [706,] 201 66 #> [707,] 201 65 #> [708,] 201 64 #> [709,] 201 63 #> [710,] 200 62 #> #> $caney #> [,1] [,2] #> [1,] 200 75 #> [2,] 199 74 #> [3,] 199 73 #> [4,] 198 72 #> [5,] 197 71 #> [6,] 197 70 #> [7,] 196 69 #> [8,] 195 68 #> [9,] 194 67 #> [10,] 194 66 #> [11,] 193 65 #> [12,] 192 64 #> [13,] 192 63 #> [14,] 191 62 #> [15,] 190 61 #> [16,] 190 60 #> [17,] 189 59 #> [18,] 188 58 #> [19,] 188 57 #> [20,] 187 56 #> [21,] 187 55 #> [22,] 186 54 #> [23,] 185 53 #> [24,] 185 52 #> [25,] 184 51 #> [26,] 183 50 #> [27,] 183 49 #> [28,] 183 48 #> [29,] 182 47 #> [30,] 181 46 #> [31,] 180 46 #> [32,] 179 47 #> [33,] 179 48 #> [34,] 178 49 #> [35,] 177 50 #> [36,] 176 51 #> [37,] 175 52 #> [38,] 174 53 #> [39,] 173 54 #> [40,] 173 55 #> [41,] 172 56 #> [42,] 171 57 #> [43,] 170 58 #> [44,] 169 59 #> [45,] 168 60 #> [46,] 167 61 #> [47,] 166 62 #> [48,] 165 63 #> [49,] 164 64 #> [50,] 163 65 #> [51,] 162 66 #> [52,] 161 67 #> [53,] 160 68 #> [54,] 159 69 #> [55,] 158 70 #> [56,] 157 71 #> [57,] 156 72 #> [58,] 155 73 #> [59,] 154 74 #> [60,] 153 75 #> [61,] 152 76 #> [62,] 151 77 #> [63,] 150 78 #> [64,] 149 79 #> [65,] 148 80 #> [66,] 147 81 #> [67,] 146 82 #> [68,] 145 82 #> [69,] 144 83 #> [70,] 143 84 #> [71,] 142 85 #> [72,] 141 86 #> [73,] 140 87 #> [74,] 139 87 #> [75,] 138 88 #> [76,] 137 89 #> [77,] 136 90 #> [78,] 135 91 #> [79,] 134 91 #> [80,] 133 92 #> [81,] 132 93 #> [82,] 131 94 #> [83,] 130 94 #> [84,] 129 95 #> [85,] 128 96 #> [86,] 127 96 #> [87,] 126 97 #> [88,] 125 98 #> [89,] 124 98 #> [90,] 123 99 #> [91,] 122 100 #> [92,] 121 100 #> [93,] 120 101 #> [94,] 119 101 #> [95,] 118 102 #> [96,] 117 102 #> [97,] 116 103 #> [98,] 115 104 #> [99,] 114 104 #> [100,] 113 105 #> [101,] 112 105 #> [102,] 111 106 #> [103,] 110 106 #> [104,] 109 107 #> [105,] 108 107 #> [106,] 107 107 #> [107,] 106 108 #> [108,] 105 108 #> [109,] 104 109 #> [110,] 105 110 #> [111,] 106 111 #> [112,] 107 111 #> [113,] 108 112 #> [114,] 109 113 #> [115,] 110 113 #> [116,] 111 114 #> [117,] 112 114 #> [118,] 113 115 #> [119,] 114 116 #> [120,] 115 116 #> [121,] 116 117 #> [122,] 117 117 #> [123,] 118 118 #> [124,] 119 119 #> [125,] 120 119 #> [126,] 121 120 #> [127,] 122 120 #> [128,] 123 121 #> [129,] 124 122 #> [130,] 125 122 #> [131,] 126 123 #> [132,] 127 123 #> [133,] 128 124 #> [134,] 129 125 #> [135,] 130 125 #> [136,] 131 126 #> [137,] 132 127 #> [138,] 133 127 #> [139,] 134 128 #> [140,] 135 128 #> [141,] 136 129 #> [142,] 137 130 #> [143,] 138 130 #> [144,] 139 131 #> [145,] 140 131 #> [146,] 141 132 #> [147,] 142 133 #> [148,] 143 133 #> [149,] 144 134 #> [150,] 145 134 #> [151,] 146 135 #> [152,] 147 136 #> [153,] 148 136 #> [154,] 149 137 #> [155,] 150 138 #> [156,] 151 138 #> [157,] 152 139 #> [158,] 153 139 #> [159,] 154 139 #> [160,] 155 138 #> [161,] 155 137 #> [162,] 156 136 #> [163,] 156 135 #> [164,] 157 134 #> [165,] 157 133 #> [166,] 158 132 #> [167,] 158 131 #> [168,] 159 130 #> [169,] 159 129 #> [170,] 160 128 #> [171,] 160 127 #> [172,] 161 126 #> [173,] 161 125 #> [174,] 162 124 #> [175,] 162 123 #> [176,] 163 122 #> [177,] 163 121 #> [178,] 164 120 #> [179,] 164 119 #> [180,] 165 118 #> [181,] 166 117 #> [182,] 166 116 #> [183,] 167 115 #> [184,] 167 114 #> [185,] 168 113 #> [186,] 168 112 #> [187,] 169 111 #> [188,] 169 110 #> [189,] 170 109 #> [190,] 170 108 #> [191,] 171 107 #> [192,] 171 106 #> [193,] 172 105 #> [194,] 172 104 #> [195,] 173 103 #> [196,] 173 102 #> [197,] 174 101 #> [198,] 174 100 #> [199,] 175 99 #> [200,] 175 98 #> [201,] 176 97 #> [202,] 176 96 #> [203,] 177 95 #> [204,] 177 94 #> [205,] 178 94 #> [206,] 178 95 #> [207,] 179 96 #> [208,] 179 97 #> [209,] 180 98 #> [210,] 180 99 #> [211,] 181 100 #> [212,] 181 101 #> [213,] 182 102 #> [214,] 182 103 #> [215,] 183 104 #> [216,] 183 105 #> [217,] 184 106 #> [218,] 184 107 #> [219,] 184 108 #> [220,] 185 109 #> [221,] 186 110 #> [222,] 186 111 #> [223,] 187 112 #> [224,] 187 113 #> [225,] 187 114 #> [226,] 188 115 #> [227,] 189 116 #> [228,] 189 117 #> [229,] 190 118 #> [230,] 190 119 #> [231,] 190 120 #> [232,] 191 121 #> [233,] 192 122 #> [234,] 192 123 #> [235,] 193 124 #> [236,] 193 125 #> [237,] 194 126 #> [238,] 195 127 #> [239,] 195 128 #> [240,] 195 129 #> [241,] 196 130 #> [242,] 197 131 #> [243,] 197 132 #> [244,] 198 133 #> [245,] 199 134 #> [246,] 199 135 #> [247,] 200 136 #> [248,] 200 137 #> [249,] 201 138 #> [250,] 201 139 #> [251,] 202 140 #> [252,] 203 141 #> [253,] 203 142 #> [254,] 204 143 #> [255,] 204 144 #> [256,] 205 145 #> [257,] 206 146 #> [258,] 207 147 #> [259,] 207 148 #> [260,] 208 149 #> [261,] 209 150 #> [262,] 209 151 #> [263,] 210 152 #> [264,] 211 153 #> [265,] 211 154 #> [266,] 212 155 #> [267,] 213 156 #> [268,] 213 157 #> [269,] 214 158 #> [270,] 215 159 #> [271,] 215 160 #> [272,] 216 161 #> [273,] 217 162 #> [274,] 218 163 #> [275,] 218 164 #> [276,] 219 165 #> [277,] 220 166 #> [278,] 221 167 #> [279,] 221 168 #> [280,] 222 169 #> [281,] 223 170 #> [282,] 224 171 #> [283,] 224 172 #> [284,] 225 173 #> [285,] 226 174 #> [286,] 227 175 #> [287,] 228 176 #> [288,] 229 177 #> [289,] 229 178 #> [290,] 230 179 #> [291,] 231 180 #> [292,] 232 181 #> [293,] 233 182 #> [294,] 234 183 #> [295,] 235 184 #> [296,] 235 185 #> [297,] 236 186 #> [298,] 237 187 #> [299,] 238 188 #> [300,] 239 189 #> [301,] 240 190 #> [302,] 241 191 #> [303,] 242 192 #> [304,] 243 193 #> [305,] 244 194 #> [306,] 245 195 #> [307,] 246 196 #> [308,] 247 197 #> [309,] 248 198 #> [310,] 249 198 #> [311,] 250 199 #> [312,] 251 200 #> [313,] 252 201 #> [314,] 253 202 #> [315,] 254 203 #> [316,] 255 204 #> [317,] 256 205 #> [318,] 257 205 #> [319,] 258 206 #> [320,] 259 207 #> [321,] 260 208 #> [322,] 261 208 #> [323,] 262 209 #> [324,] 263 210 #> [325,] 264 211 #> [326,] 265 211 #> [327,] 266 212 #> [328,] 267 213 #> [329,] 268 213 #> [330,] 269 214 #> [331,] 270 214 #> [332,] 271 215 #> [333,] 272 216 #> [334,] 273 216 #> [335,] 274 217 #> [336,] 275 217 #> [337,] 276 218 #> [338,] 277 219 #> [339,] 278 219 #> [340,] 279 218 #> [341,] 279 217 #> [342,] 279 216 #> [343,] 279 215 #> [344,] 278 214 #> [345,] 278 213 #> [346,] 278 212 #> [347,] 279 211 #> [348,] 278 210 #> [349,] 278 209 #> [350,] 278 208 #> [351,] 278 207 #> [352,] 278 206 #> [353,] 278 205 #> [354,] 277 204 #> [355,] 277 203 #> [356,] 278 202 #> [357,] 277 201 #> [358,] 277 200 #> [359,] 277 199 #> [360,] 277 198 #> [361,] 277 197 #> [362,] 277 196 #> [363,] 276 195 #> [364,] 276 194 #> [365,] 276 193 #> [366,] 277 192 #> [367,] 277 191 #> [368,] 276 190 #> [369,] 276 189 #> [370,] 276 188 #> [371,] 276 187 #> [372,] 276 186 #> [373,] 276 185 #> [374,] 276 184 #> [375,] 276 183 #> [376,] 276 182 #> [377,] 276 181 #> [378,] 276 180 #> [379,] 276 179 #> [380,] 276 178 #> [381,] 276 177 #> [382,] 276 176 #> [383,] 277 175 #> [384,] 276 174 #> [385,] 276 173 #> [386,] 277 172 #> [387,] 277 171 #> [388,] 277 170 #> [389,] 277 169 #> [390,] 277 168 #> [391,] 277 167 #> [392,] 278 166 #> [393,] 278 165 #> [394,] 278 164 #> [395,] 278 163 #> [396,] 279 162 #> [397,] 279 161 #> [398,] 279 160 #> [399,] 280 159 #> [400,] 280 158 #> [401,] 280 157 #> [402,] 281 156 #> [403,] 281 155 #> [404,] 282 154 #> [405,] 282 153 #> [406,] 281 152 #> [407,] 280 152 #> [408,] 279 152 #> [409,] 278 151 #> [410,] 277 151 #> [411,] 276 150 #> [412,] 275 150 #> [413,] 274 150 #> [414,] 273 149 #> [415,] 272 148 #> [416,] 271 148 #> [417,] 270 147 #> [418,] 269 146 #> [419,] 268 146 #> [420,] 267 145 #> [421,] 266 145 #> [422,] 265 144 #> [423,] 264 143 #> [424,] 263 142 #> [425,] 262 142 #> [426,] 261 141 #> [427,] 260 140 #> [428,] 259 139 #> [429,] 258 139 #> [430,] 257 138 #> [431,] 256 137 #> [432,] 255 136 #> [433,] 254 135 #> [434,] 253 134 #> [435,] 252 133 #> [436,] 251 133 #> [437,] 250 132 #> [438,] 249 131 #> [439,] 248 130 #> [440,] 247 129 #> [441,] 246 128 #> [442,] 245 127 #> [443,] 244 126 #> [444,] 243 125 #> [445,] 242 124 #> [446,] 241 123 #> [447,] 240 122 #> [448,] 239 121 #> [449,] 238 120 #> [450,] 237 119 #> [451,] 236 118 #> [452,] 235 117 #> [453,] 234 116 #> [454,] 233 115 #> [455,] 232 114 #> [456,] 231 113 #> [457,] 231 112 #> [458,] 230 111 #> [459,] 229 110 #> [460,] 228 109 #> [461,] 227 108 #> [462,] 226 107 #> [463,] 225 106 #> [464,] 224 105 #> [465,] 223 104 #> [466,] 223 103 #> [467,] 222 102 #> [468,] 221 101 #> [469,] 220 100 #> [470,] 219 99 #> [471,] 218 98 #> [472,] 218 97 #> [473,] 217 96 #> [474,] 216 95 #> [475,] 215 94 #> [476,] 214 93 #> [477,] 213 92 #> [478,] 213 91 #> [479,] 212 90 #> [480,] 211 89 #> [481,] 210 88 #> [482,] 209 87 #> [483,] 209 86 #> [484,] 208 85 #> [485,] 207 84 #> [486,] 206 83 #> [487,] 205 82 #> [488,] 205 81 #> [489,] 204 80 #> [490,] 203 79 #> [491,] 202 78 #> [492,] 202 77 #> [493,] 201 76 #> [494,] 200 75 #> #> $chimay #> [,1] [,2] #> [1,] 200 76 #> [2,] 200 75 #> [3,] 199 74 #> [4,] 198 73 #> [5,] 198 72 #> [6,] 197 71 #> [7,] 197 70 #> [8,] 196 69 #> [9,] 195 68 #> [10,] 195 67 #> [11,] 194 66 #> [12,] 194 65 #> [13,] 193 64 #> [14,] 192 63 #> [15,] 192 62 #> [16,] 191 61 #> [17,] 190 60 #> [18,] 190 59 #> [19,] 189 58 #> [20,] 189 57 #> [21,] 188 56 #> [22,] 187 55 #> [23,] 187 54 #> [24,] 186 53 #> [25,] 186 52 #> [26,] 185 51 #> [27,] 184 50 #> [28,] 184 49 #> [29,] 183 48 #> [30,] 183 47 #> [31,] 182 46 #> [32,] 181 45 #> [33,] 181 44 #> [34,] 181 43 #> [35,] 180 42 #> [36,] 179 41 #> [37,] 179 40 #> [38,] 178 39 #> [39,] 177 38 #> [40,] 176 37 #> [41,] 175 37 #> [42,] 174 37 #> [43,] 173 37 #> [44,] 172 37 #> [45,] 171 37 #> [46,] 170 37 #> [47,] 169 37 #> [48,] 168 37 #> [49,] 167 37 #> [50,] 166 37 #> [51,] 165 37 #> [52,] 164 37 #> [53,] 163 37 #> [54,] 162 37 #> [55,] 161 37 #> [56,] 160 37 #> [57,] 159 37 #> [58,] 158 37 #> [59,] 157 37 #> [60,] 156 37 #> [61,] 155 37 #> [62,] 154 37 #> [63,] 153 37 #> [64,] 152 37 #> [65,] 151 37 #> [66,] 150 37 #> [67,] 149 37 #> [68,] 148 37 #> [69,] 147 37 #> [70,] 146 37 #> [71,] 145 37 #> [72,] 144 37 #> [73,] 143 37 #> [74,] 142 37 #> [75,] 141 37 #> [76,] 140 37 #> [77,] 139 37 #> [78,] 138 37 #> [79,] 137 37 #> [80,] 136 37 #> [81,] 135 37 #> [82,] 134 37 #> [83,] 133 37 #> [84,] 132 37 #> [85,] 131 37 #> [86,] 130 37 #> [87,] 129 37 #> [88,] 128 37 #> [89,] 127 37 #> [90,] 126 37 #> [91,] 125 37 #> [92,] 124 37 #> [93,] 123 37 #> [94,] 122 37 #> [95,] 121 37 #> [96,] 120 37 #> [97,] 119 37 #> [98,] 118 37 #> [99,] 117 37 #> [100,] 116 37 #> [101,] 115 37 #> [102,] 114 37 #> [103,] 113 37 #> [104,] 112 37 #> [105,] 111 37 #> [106,] 110 37 #> [107,] 109 37 #> [108,] 108 37 #> [109,] 107 37 #> [110,] 106 37 #> [111,] 105 37 #> [112,] 104 37 #> [113,] 103 37 #> [114,] 102 38 #> [115,] 103 39 #> [116,] 103 40 #> [117,] 104 41 #> [118,] 104 42 #> [119,] 105 43 #> [120,] 106 44 #> [121,] 106 45 #> [122,] 107 46 #> [123,] 107 47 #> [124,] 108 48 #> [125,] 108 49 #> [126,] 109 50 #> [127,] 110 51 #> [128,] 110 52 #> [129,] 111 53 #> [130,] 111 54 #> [131,] 112 55 #> [132,] 113 56 #> [133,] 113 57 #> [134,] 113 58 #> [135,] 114 59 #> [136,] 115 60 #> [137,] 115 61 #> [138,] 116 62 #> [139,] 117 63 #> [140,] 117 64 #> [141,] 117 65 #> [142,] 118 66 #> [143,] 119 67 #> [144,] 119 68 #> [145,] 120 69 #> [146,] 121 70 #> [147,] 121 71 #> [148,] 121 72 #> [149,] 122 73 #> [150,] 123 74 #> [151,] 123 75 #> [152,] 124 76 #> [153,] 125 77 #> [154,] 125 78 #> [155,] 126 79 #> [156,] 126 80 #> [157,] 127 81 #> [158,] 127 82 #> [159,] 128 83 #> [160,] 129 84 #> [161,] 129 85 #> [162,] 130 86 #> [163,] 130 87 #> [164,] 131 88 #> [165,] 131 89 #> [166,] 132 90 #> [167,] 132 91 #> [168,] 133 92 #> [169,] 134 93 #> [170,] 134 94 #> [171,] 135 95 #> [172,] 136 96 #> [173,] 136 97 #> [174,] 136 98 #> [175,] 137 99 #> [176,] 138 100 #> [177,] 138 101 #> [178,] 139 102 #> [179,] 140 103 #> [180,] 140 104 #> [181,] 140 105 #> [182,] 141 106 #> [183,] 142 107 #> [184,] 142 108 #> [185,] 143 109 #> [186,] 144 110 #> [187,] 144 111 #> [188,] 145 112 #> [189,] 145 113 #> [190,] 146 114 #> [191,] 146 115 #> [192,] 147 116 #> [193,] 148 117 #> [194,] 148 118 #> [195,] 149 119 #> [196,] 149 120 #> [197,] 150 121 #> [198,] 150 122 #> [199,] 151 123 #> [200,] 151 124 #> [201,] 152 125 #> [202,] 153 126 #> [203,] 153 127 #> [204,] 152 128 #> [205,] 151 129 #> [206,] 151 130 #> [207,] 150 131 #> [208,] 149 132 #> [209,] 149 133 #> [210,] 149 134 #> [211,] 148 135 #> [212,] 147 136 #> [213,] 147 137 #> [214,] 146 138 #> [215,] 145 139 #> [216,] 145 140 #> [217,] 145 141 #> [218,] 144 142 #> [219,] 143 143 #> [220,] 143 144 #> [221,] 142 145 #> [222,] 141 146 #> [223,] 141 147 #> [224,] 141 148 #> [225,] 140 149 #> [226,] 139 150 #> [227,] 139 151 #> [228,] 138 152 #> [229,] 137 153 #> [230,] 137 154 #> [231,] 137 155 #> [232,] 136 156 #> [233,] 135 157 #> [234,] 135 158 #> [235,] 134 159 #> [236,] 133 160 #> [237,] 133 161 #> [238,] 133 162 #> [239,] 132 163 #> [240,] 131 164 #> [241,] 131 165 #> [242,] 130 166 #> [243,] 129 167 #> [244,] 129 168 #> [245,] 129 169 #> [246,] 128 170 #> [247,] 127 171 #> [248,] 127 172 #> [249,] 126 173 #> [250,] 125 174 #> [251,] 125 175 #> [252,] 125 176 #> [253,] 124 177 #> [254,] 123 178 #> [255,] 123 179 #> [256,] 122 180 #> [257,] 121 181 #> [258,] 121 182 #> [259,] 121 183 #> [260,] 120 184 #> [261,] 119 185 #> [262,] 119 186 #> [263,] 118 187 #> [264,] 117 188 #> [265,] 117 189 #> [266,] 117 190 #> [267,] 116 191 #> [268,] 115 192 #> [269,] 115 193 #> [270,] 114 194 #> [271,] 113 195 #> [272,] 113 196 #> [273,] 113 197 #> [274,] 112 198 #> [275,] 111 199 #> [276,] 111 200 #> [277,] 110 201 #> [278,] 109 202 #> [279,] 109 203 #> [280,] 109 204 #> [281,] 108 205 #> [282,] 107 206 #> [283,] 107 207 #> [284,] 106 208 #> [285,] 105 209 #> [286,] 105 210 #> [287,] 105 211 #> [288,] 106 212 #> [289,] 107 212 #> [290,] 108 212 #> [291,] 109 212 #> [292,] 110 212 #> [293,] 111 212 #> [294,] 112 212 #> [295,] 113 212 #> [296,] 114 212 #> [297,] 115 212 #> [298,] 116 212 #> [299,] 117 212 #> [300,] 118 212 #> [301,] 119 212 #> [302,] 120 212 #> [303,] 121 212 #> [304,] 122 212 #> [305,] 123 212 #> [306,] 124 212 #> [307,] 125 212 #> [308,] 126 212 #> [309,] 127 212 #> [310,] 128 212 #> [311,] 129 212 #> [312,] 130 212 #> [313,] 131 212 #> [314,] 132 212 #> [315,] 133 212 #> [316,] 134 212 #> [317,] 135 212 #> [318,] 136 212 #> [319,] 137 212 #> [320,] 138 212 #> [321,] 139 212 #> [322,] 140 212 #> [323,] 141 212 #> [324,] 142 212 #> [325,] 143 212 #> [326,] 144 212 #> [327,] 145 212 #> [328,] 146 212 #> [329,] 147 212 #> [330,] 148 212 #> [331,] 149 212 #> [332,] 150 212 #> [333,] 151 212 #> [334,] 152 212 #> [335,] 153 212 #> [336,] 154 212 #> [337,] 155 212 #> [338,] 156 212 #> [339,] 157 212 #> [340,] 158 212 #> [341,] 159 212 #> [342,] 160 212 #> [343,] 161 212 #> [344,] 162 212 #> [345,] 163 212 #> [346,] 164 212 #> [347,] 165 212 #> [348,] 166 212 #> [349,] 167 212 #> [350,] 168 212 #> [351,] 169 212 #> [352,] 170 212 #> [353,] 171 212 #> [354,] 172 212 #> [355,] 173 212 #> [356,] 174 212 #> [357,] 175 212 #> [358,] 176 212 #> [359,] 177 212 #> [360,] 178 212 #> [361,] 179 212 #> [362,] 180 211 #> [363,] 181 210 #> [364,] 181 209 #> [365,] 182 208 #> [366,] 182 207 #> [367,] 183 206 #> [368,] 184 205 #> [369,] 184 204 #> [370,] 185 203 #> [371,] 186 202 #> [372,] 186 201 #> [373,] 187 200 #> [374,] 188 199 #> [375,] 188 198 #> [376,] 189 197 #> [377,] 189 196 #> [378,] 190 195 #> [379,] 191 194 #> [380,] 191 193 #> [381,] 192 192 #> [382,] 192 191 #> [383,] 193 190 #> [384,] 194 189 #> [385,] 194 188 #> [386,] 195 187 #> [387,] 195 186 #> [388,] 196 185 #> [389,] 197 184 #> [390,] 197 183 #> [391,] 198 182 #> [392,] 198 181 #> [393,] 199 180 #> [394,] 200 179 #> [395,] 200 178 #> [396,] 201 177 #> [397,] 201 176 #> [398,] 202 175 #> [399,] 203 174 #> [400,] 203 173 #> [401,] 204 173 #> [402,] 204 174 #> [403,] 205 175 #> [404,] 205 176 #> [405,] 206 177 #> [406,] 206 178 #> [407,] 207 179 #> [408,] 207 180 #> [409,] 208 181 #> [410,] 209 182 #> [411,] 209 183 #> [412,] 210 184 #> [413,] 211 185 #> [414,] 211 186 #> [415,] 212 187 #> [416,] 212 188 #> [417,] 213 189 #> [418,] 214 190 #> [419,] 214 191 #> [420,] 214 192 #> [421,] 215 193 #> [422,] 216 194 #> [423,] 216 195 #> [424,] 217 196 #> [425,] 217 197 #> [426,] 218 198 #> [427,] 219 199 #> [428,] 219 200 #> [429,] 220 201 #> [430,] 221 202 #> [431,] 221 203 #> [432,] 222 204 #> [433,] 222 205 #> [434,] 223 206 #> [435,] 224 207 #> [436,] 224 208 #> [437,] 224 209 #> [438,] 225 210 #> [439,] 226 211 #> [440,] 227 212 #> [441,] 228 212 #> [442,] 229 212 #> [443,] 230 212 #> [444,] 231 212 #> [445,] 232 212 #> [446,] 233 212 #> [447,] 234 212 #> [448,] 235 212 #> [449,] 236 212 #> [450,] 237 212 #> [451,] 238 212 #> [452,] 239 212 #> [453,] 240 212 #> [454,] 241 212 #> [455,] 242 212 #> [456,] 243 212 #> [457,] 244 212 #> [458,] 245 212 #> [459,] 246 212 #> [460,] 247 212 #> [461,] 248 212 #> [462,] 249 212 #> [463,] 250 212 #> [464,] 251 212 #> [465,] 252 212 #> [466,] 253 212 #> [467,] 254 212 #> [468,] 255 212 #> [469,] 256 212 #> [470,] 257 212 #> [471,] 258 212 #> [472,] 259 212 #> [473,] 260 212 #> [474,] 261 212 #> [475,] 262 212 #> [476,] 263 212 #> [477,] 264 212 #> [478,] 265 212 #> [479,] 266 212 #> [480,] 267 212 #> [481,] 268 212 #> [482,] 269 212 #> [483,] 270 212 #> [484,] 271 212 #> [485,] 272 212 #> [486,] 273 212 #> [487,] 274 212 #> [488,] 275 212 #> [489,] 276 212 #> [490,] 277 212 #> [491,] 278 212 #> [492,] 279 212 #> [493,] 280 212 #> [494,] 281 212 #> [495,] 282 212 #> [496,] 283 212 #> [497,] 284 212 #> [498,] 285 212 #> [499,] 286 212 #> [500,] 287 212 #> [501,] 288 212 #> [502,] 289 212 #> [503,] 290 212 #> [504,] 291 212 #> [505,] 292 212 #> [506,] 293 212 #> [507,] 294 212 #> [508,] 295 212 #> [509,] 296 212 #> [510,] 297 212 #> [511,] 298 212 #> [512,] 299 212 #> [513,] 300 211 #> [514,] 299 210 #> [515,] 299 209 #> [516,] 298 208 #> [517,] 297 207 #> [518,] 297 206 #> [519,] 297 205 #> [520,] 296 204 #> [521,] 295 203 #> [522,] 295 202 #> [523,] 294 201 #> [524,] 293 200 #> [525,] 293 199 #> [526,] 292 198 #> [527,] 292 197 #> [528,] 291 196 #> [529,] 291 195 #> [530,] 290 194 #> [531,] 289 193 #> [532,] 289 192 #> [533,] 288 191 #> [534,] 288 190 #> [535,] 287 189 #> [536,] 287 188 #> [537,] 286 187 #> [538,] 285 186 #> [539,] 285 185 #> [540,] 284 184 #> [541,] 284 183 #> [542,] 283 182 #> [543,] 282 181 #> [544,] 282 180 #> [545,] 282 179 #> [546,] 281 178 #> [547,] 280 177 #> [548,] 280 176 #> [549,] 279 175 #> [550,] 278 174 #> [551,] 278 173 #> [552,] 278 172 #> [553,] 277 171 #> [554,] 276 170 #> [555,] 276 169 #> [556,] 275 168 #> [557,] 274 167 #> [558,] 274 166 #> [559,] 274 165 #> [560,] 273 164 #> [561,] 272 163 #> [562,] 272 162 #> [563,] 271 161 #> [564,] 270 160 #> [565,] 270 159 #> [566,] 269 158 #> [567,] 269 157 #> [568,] 268 156 #> [569,] 268 155 #> [570,] 267 154 #> [571,] 266 153 #> [572,] 266 152 #> [573,] 265 151 #> [574,] 265 150 #> [575,] 264 149 #> [576,] 264 148 #> [577,] 263 147 #> [578,] 262 146 #> [579,] 262 145 #> [580,] 261 144 #> [581,] 261 143 #> [582,] 260 142 #> [583,] 259 141 #> [584,] 259 140 #> [585,] 259 139 #> [586,] 258 138 #> [587,] 257 137 #> [588,] 257 136 #> [589,] 256 135 #> [590,] 255 134 #> [591,] 255 133 #> [592,] 255 132 #> [593,] 254 131 #> [594,] 253 130 #> [595,] 253 129 #> [596,] 252 128 #> [597,] 251 127 #> [598,] 251 126 #> [599,] 252 125 #> [600,] 253 124 #> [601,] 253 123 #> [602,] 253 122 #> [603,] 254 121 #> [604,] 255 120 #> [605,] 255 119 #> [606,] 256 118 #> [607,] 257 117 #> [608,] 257 116 #> [609,] 257 115 #> [610,] 258 114 #> [611,] 259 113 #> [612,] 259 112 #> [613,] 260 111 #> [614,] 260 110 #> [615,] 261 109 #> [616,] 262 108 #> [617,] 262 107 #> [618,] 263 106 #> [619,] 263 105 #> [620,] 264 104 #> [621,] 264 103 #> [622,] 265 102 #> [623,] 266 101 #> [624,] 266 100 #> [625,] 267 99 #> [626,] 267 98 #> [627,] 268 97 #> [628,] 268 96 #> [629,] 269 95 #> [630,] 270 94 #> [631,] 270 93 #> [632,] 271 92 #> [633,] 272 91 #> [634,] 272 90 #> [635,] 272 89 #> [636,] 273 88 #> [637,] 274 87 #> [638,] 274 86 #> [639,] 275 85 #> [640,] 276 84 #> [641,] 276 83 #> [642,] 276 82 #> [643,] 277 81 #> [644,] 278 80 #> [645,] 278 79 #> [646,] 279 78 #> [647,] 279 77 #> [648,] 280 76 #> [649,] 281 75 #> [650,] 281 74 #> [651,] 282 73 #> [652,] 282 72 #> [653,] 283 71 #> [654,] 283 70 #> [655,] 284 69 #> [656,] 285 68 #> [657,] 285 67 #> [658,] 286 66 #> [659,] 286 65 #> [660,] 287 64 #> [661,] 287 63 #> [662,] 288 62 #> [663,] 289 61 #> [664,] 289 60 #> [665,] 290 59 #> [666,] 291 58 #> [667,] 291 57 #> [668,] 291 56 #> [669,] 292 55 #> [670,] 293 54 #> [671,] 293 53 #> [672,] 294 52 #> [673,] 295 51 #> [674,] 295 50 #> [675,] 295 49 #> [676,] 296 48 #> [677,] 297 47 #> [678,] 297 46 #> [679,] 298 45 #> [680,] 299 44 #> [681,] 299 43 #> [682,] 300 42 #> [683,] 300 41 #> [684,] 301 40 #> [685,] 301 39 #> [686,] 302 38 #> [687,] 301 37 #> [688,] 300 37 #> [689,] 299 37 #> [690,] 298 37 #> [691,] 297 37 #> [692,] 296 37 #> [693,] 295 37 #> [694,] 294 37 #> [695,] 293 37 #> [696,] 292 37 #> [697,] 291 37 #> [698,] 290 37 #> [699,] 289 37 #> [700,] 288 37 #> [701,] 287 37 #> [702,] 286 37 #> [703,] 285 37 #> [704,] 284 37 #> [705,] 283 37 #> [706,] 282 37 #> [707,] 281 37 #> [708,] 280 37 #> [709,] 279 37 #> [710,] 278 37 #> [711,] 277 37 #> [712,] 276 37 #> [713,] 275 37 #> [714,] 274 37 #> [715,] 273 37 #> [716,] 272 37 #> [717,] 271 37 #> [718,] 270 37 #> [719,] 269 37 #> [720,] 268 37 #> [721,] 267 37 #> [722,] 266 37 #> [723,] 265 37 #> [724,] 264 37 #> [725,] 263 37 #> [726,] 262 37 #> [727,] 261 37 #> [728,] 260 37 #> [729,] 259 37 #> [730,] 258 37 #> [731,] 257 37 #> [732,] 256 37 #> [733,] 255 37 #> [734,] 254 37 #> [735,] 253 37 #> [736,] 252 37 #> [737,] 251 37 #> [738,] 250 37 #> [739,] 249 37 #> [740,] 248 37 #> [741,] 247 37 #> [742,] 246 37 #> [743,] 245 37 #> [744,] 244 37 #> [745,] 243 37 #> [746,] 242 37 #> [747,] 241 37 #> [748,] 240 37 #> [749,] 239 37 #> [750,] 238 37 #> [751,] 237 37 #> [752,] 236 37 #> [753,] 235 37 #> [754,] 234 37 #> [755,] 233 37 #> [756,] 232 37 #> [757,] 231 37 #> [758,] 230 37 #> [759,] 229 37 #> [760,] 228 37 #> [761,] 227 37 #> [762,] 226 37 #> [763,] 225 38 #> [764,] 225 39 #> [765,] 224 40 #> [766,] 224 41 #> [767,] 223 42 #> [768,] 222 43 #> [769,] 222 44 #> [770,] 221 45 #> [771,] 221 46 #> [772,] 220 47 #> [773,] 219 48 #> [774,] 219 49 #> [775,] 218 50 #> [776,] 218 51 #> [777,] 217 52 #> [778,] 216 53 #> [779,] 216 54 #> [780,] 215 55 #> [781,] 214 56 #> [782,] 214 57 #> [783,] 213 58 #> [784,] 213 59 #> [785,] 212 60 #> [786,] 211 61 #> [787,] 211 62 #> [788,] 210 63 #> [789,] 210 64 #> [790,] 209 65 #> [791,] 208 66 #> [792,] 208 67 #> [793,] 207 68 #> [794,] 207 69 #> [795,] 206 70 #> [796,] 205 71 #> [797,] 205 72 #> [798,] 205 73 #> [799,] 204 74 #> [800,] 203 75 #> [801,] 203 76 #> [802,] 202 77 #> [803,] 202 78 #> [804,] 201 78 #> [805,] 201 77 #> [806,] 200 76 #> #> $corona #> [,1] [,2] #> [1,] 200 106 #> [2,] 199 105 #> [3,] 198 105 #> [4,] 197 106 #> [5,] 196 105 #> [6,] 195 105 #> [7,] 194 105 #> [8,] 193 106 #> [9,] 192 106 #> [10,] 191 106 #> [11,] 190 106 #> [12,] 189 106 #> [13,] 188 106 #> [14,] 187 106 #> [15,] 186 106 #> [16,] 185 106 #> [17,] 184 106 #> [18,] 183 106 #> [19,] 182 106 #> [20,] 181 106 #> [21,] 180 106 #> [22,] 179 106 #> [23,] 178 106 #> [24,] 177 107 #> [25,] 176 107 #> [26,] 175 107 #> [27,] 174 107 #> [28,] 173 107 #> [29,] 172 107 #> [30,] 171 107 #> [31,] 170 107 #> [32,] 169 107 #> [33,] 168 108 #> [34,] 167 108 #> [35,] 166 108 #> [36,] 165 108 #> [37,] 164 108 #> [38,] 163 107 #> [39,] 162 107 #> [40,] 161 106 #> [41,] 160 105 #> [42,] 160 104 #> [43,] 159 103 #> [44,] 158 102 #> [45,] 157 101 #> [46,] 156 100 #> [47,] 156 99 #> [48,] 155 98 #> [49,] 154 97 #> [50,] 153 96 #> [51,] 153 95 #> [52,] 152 94 #> [53,] 151 93 #> [54,] 150 92 #> [55,] 149 91 #> [56,] 148 90 #> [57,] 147 89 #> [58,] 146 88 #> [59,] 145 87 #> [60,] 144 86 #> [61,] 143 85 #> [62,] 142 85 #> [63,] 141 84 #> [64,] 140 83 #> [65,] 139 83 #> [66,] 138 82 #> [67,] 137 81 #> [68,] 136 80 #> [69,] 135 79 #> [70,] 134 79 #> [71,] 133 78 #> [72,] 132 77 #> [73,] 131 76 #> [74,] 130 75 #> [75,] 129 74 #> [76,] 128 73 #> [77,] 128 72 #> [78,] 127 71 #> [79,] 126 70 #> [80,] 125 69 #> [81,] 125 68 #> [82,] 124 67 #> [83,] 124 66 #> [84,] 124 65 #> [85,] 123 64 #> [86,] 123 63 #> [87,] 123 62 #> [88,] 123 61 #> [89,] 122 60 #> [90,] 122 59 #> [91,] 122 58 #> [92,] 122 57 #> [93,] 122 56 #> [94,] 123 55 #> [95,] 124 54 #> [96,] 125 53 #> [97,] 126 52 #> [98,] 127 52 #> [99,] 128 51 #> [100,] 129 50 #> [101,] 129 49 #> [102,] 129 48 #> [103,] 128 47 #> [104,] 127 46 #> [105,] 126 46 #> [106,] 125 45 #> [107,] 124 45 #> [108,] 123 45 #> [109,] 122 45 #> [110,] 121 45 #> [111,] 120 45 #> [112,] 119 45 #> [113,] 118 45 #> [114,] 117 45 #> [115,] 116 45 #> [116,] 115 45 #> [117,] 114 45 #> [118,] 113 46 #> [119,] 112 46 #> [120,] 111 47 #> [121,] 110 48 #> [122,] 110 49 #> [123,] 110 50 #> [124,] 109 51 #> [125,] 109 52 #> [126,] 109 53 #> [127,] 109 54 #> [128,] 109 55 #> [129,] 109 56 #> [130,] 109 57 #> [131,] 109 58 #> [132,] 109 59 #> [133,] 109 60 #> [134,] 109 61 #> [135,] 109 62 #> [136,] 109 63 #> [137,] 109 64 #> [138,] 109 65 #> [139,] 109 66 #> [140,] 109 67 #> [141,] 109 68 #> [142,] 109 69 #> [143,] 109 70 #> [144,] 109 71 #> [145,] 109 72 #> [146,] 109 73 #> [147,] 109 74 #> [148,] 109 75 #> [149,] 109 76 #> [150,] 109 77 #> [151,] 109 78 #> [152,] 110 79 #> [153,] 111 80 #> [154,] 112 81 #> [155,] 113 82 #> [156,] 114 83 #> [157,] 115 84 #> [158,] 116 85 #> [159,] 117 86 #> [160,] 118 87 #> [161,] 119 88 #> [162,] 120 89 #> [163,] 121 90 #> [164,] 122 91 #> [165,] 122 92 #> [166,] 123 93 #> [167,] 124 94 #> [168,] 125 95 #> [169,] 125 96 #> [170,] 125 97 #> [171,] 126 98 #> [172,] 125 99 #> [173,] 126 100 #> [174,] 126 101 #> [175,] 125 101 #> [176,] 125 100 #> [177,] 124 99 #> [178,] 124 98 #> [179,] 123 97 #> [180,] 123 96 #> [181,] 122 95 #> [182,] 121 94 #> [183,] 120 93 #> [184,] 119 92 #> [185,] 118 91 #> [186,] 117 90 #> [187,] 116 89 #> [188,] 115 88 #> [189,] 114 87 #> [190,] 113 87 #> [191,] 112 86 #> [192,] 111 85 #> [193,] 110 85 #> [194,] 109 84 #> [195,] 108 84 #> [196,] 107 84 #> [197,] 106 83 #> [198,] 105 83 #> [199,] 104 82 #> [200,] 103 83 #> [201,] 103 84 #> [202,] 103 85 #> [203,] 104 86 #> [204,] 105 87 #> [205,] 106 88 #> [206,] 107 89 #> [207,] 108 90 #> [208,] 109 91 #> [209,] 110 92 #> [210,] 111 93 #> [211,] 111 94 #> [212,] 112 95 #> [213,] 112 96 #> [214,] 112 97 #> [215,] 113 98 #> [216,] 113 99 #> [217,] 113 100 #> [218,] 113 101 #> [219,] 114 102 #> [220,] 114 103 #> [221,] 114 104 #> [222,] 114 105 #> [223,] 114 106 #> [224,] 114 107 #> [225,] 115 108 #> [226,] 115 109 #> [227,] 114 110 #> [228,] 115 111 #> [229,] 115 112 #> [230,] 115 113 #> [231,] 115 114 #> [232,] 115 115 #> [233,] 115 116 #> [234,] 115 117 #> [235,] 116 118 #> [236,] 116 119 #> [237,] 116 120 #> [238,] 116 121 #> [239,] 116 122 #> [240,] 116 123 #> [241,] 115 124 #> [242,] 115 125 #> [243,] 115 126 #> [244,] 115 127 #> [245,] 115 128 #> [246,] 115 129 #> [247,] 115 130 #> [248,] 115 131 #> [249,] 115 132 #> [250,] 116 133 #> [251,] 115 134 #> [252,] 116 135 #> [253,] 116 136 #> [254,] 116 137 #> [255,] 117 138 #> [256,] 117 139 #> [257,] 117 140 #> [258,] 118 141 #> [259,] 118 142 #> [260,] 118 143 #> [261,] 119 144 #> [262,] 120 145 #> [263,] 120 146 #> [264,] 121 147 #> [265,] 121 148 #> [266,] 122 149 #> [267,] 123 150 #> [268,] 123 151 #> [269,] 124 152 #> [270,] 125 153 #> [271,] 126 154 #> [272,] 127 155 #> [273,] 128 156 #> [274,] 129 157 #> [275,] 130 158 #> [276,] 131 159 #> [277,] 132 160 #> [278,] 133 161 #> [279,] 134 161 #> [280,] 135 162 #> [281,] 136 162 #> [282,] 137 162 #> [283,] 138 163 #> [284,] 139 163 #> [285,] 140 163 #> [286,] 141 163 #> [287,] 142 164 #> [288,] 143 164 #> [289,] 144 164 #> [290,] 145 164 #> [291,] 146 164 #> [292,] 147 164 #> [293,] 148 165 #> [294,] 149 165 #> [295,] 150 165 #> [296,] 151 165 #> [297,] 152 165 #> [298,] 153 165 #> [299,] 154 166 #> [300,] 155 166 #> [301,] 156 165 #> [302,] 157 165 #> [303,] 158 165 #> [304,] 159 165 #> [305,] 160 166 #> [306,] 161 166 #> [307,] 162 166 #> [308,] 163 166 #> [309,] 164 166 #> [310,] 165 166 #> [311,] 166 166 #> [312,] 167 166 #> [313,] 168 166 #> [314,] 169 166 #> [315,] 170 166 #> [316,] 171 166 #> [317,] 172 166 #> [318,] 173 166 #> [319,] 174 166 #> [320,] 175 166 #> [321,] 176 166 #> [322,] 177 166 #> [323,] 178 166 #> [324,] 179 166 #> [325,] 180 166 #> [326,] 181 166 #> [327,] 182 166 #> [328,] 183 166 #> [329,] 184 166 #> [330,] 185 166 #> [331,] 186 166 #> [332,] 187 166 #> [333,] 188 166 #> [334,] 189 165 #> [335,] 190 165 #> [336,] 191 165 #> [337,] 192 165 #> [338,] 193 165 #> [339,] 194 165 #> [340,] 195 165 #> [341,] 196 165 #> [342,] 197 165 #> [343,] 198 165 #> [344,] 199 165 #> [345,] 200 165 #> [346,] 201 165 #> [347,] 202 165 #> [348,] 203 165 #> [349,] 204 165 #> [350,] 205 165 #> [351,] 206 166 #> [352,] 207 166 #> [353,] 208 166 #> [354,] 209 166 #> [355,] 210 166 #> [356,] 211 166 #> [357,] 212 166 #> [358,] 213 166 #> [359,] 214 166 #> [360,] 215 167 #> [361,] 216 167 #> [362,] 217 167 #> [363,] 218 167 #> [364,] 219 167 #> [365,] 220 168 #> [366,] 221 168 #> [367,] 222 168 #> [368,] 223 169 #> [369,] 224 169 #> [370,] 225 169 #> [371,] 226 170 #> [372,] 227 170 #> [373,] 228 171 #> [374,] 229 171 #> [375,] 230 172 #> [376,] 231 172 #> [377,] 232 173 #> [378,] 233 174 #> [379,] 234 174 #> [380,] 235 175 #> [381,] 236 176 #> [382,] 237 177 #> [383,] 238 178 #> [384,] 238 179 #> [385,] 239 180 #> [386,] 240 181 #> [387,] 241 182 #> [388,] 241 183 #> [389,] 242 184 #> [390,] 243 185 #> [391,] 243 186 #> [392,] 244 187 #> [393,] 245 188 #> [394,] 245 189 #> [395,] 246 190 #> [396,] 246 191 #> [397,] 247 192 #> [398,] 247 193 #> [399,] 248 194 #> [400,] 249 195 #> [401,] 249 196 #> [402,] 250 197 #> [403,] 250 198 #> [404,] 251 199 #> [405,] 251 200 #> [406,] 251 201 #> [407,] 252 202 #> [408,] 252 203 #> [409,] 253 204 #> [410,] 253 205 #> [411,] 254 206 #> [412,] 254 207 #> [413,] 254 208 #> [414,] 255 209 #> [415,] 255 210 #> [416,] 256 211 #> [417,] 256 212 #> [418,] 256 213 #> [419,] 257 214 #> [420,] 257 215 #> [421,] 257 216 #> [422,] 258 217 #> [423,] 258 218 #> [424,] 259 219 #> [425,] 260 220 #> [426,] 261 221 #> [427,] 262 222 #> [428,] 263 223 #> [429,] 264 224 #> [430,] 265 225 #> [431,] 266 225 #> [432,] 267 226 #> [433,] 268 226 #> [434,] 269 226 #> [435,] 270 227 #> [436,] 271 227 #> [437,] 272 227 #> [438,] 273 227 #> [439,] 274 227 #> [440,] 275 227 #> [441,] 276 227 #> [442,] 277 227 #> [443,] 278 227 #> [444,] 279 228 #> [445,] 280 227 #> [446,] 281 227 #> [447,] 282 227 #> [448,] 283 227 #> [449,] 284 226 #> [450,] 285 226 #> [451,] 286 225 #> [452,] 287 224 #> [453,] 288 224 #> [454,] 289 223 #> [455,] 290 222 #> [456,] 291 221 #> [457,] 292 220 #> [458,] 293 219 #> [459,] 294 218 #> [460,] 295 217 #> [461,] 295 216 #> [462,] 296 215 #> [463,] 297 215 #> [464,] 298 214 #> [465,] 299 214 #> [466,] 300 214 #> [467,] 301 214 #> [468,] 302 214 #> [469,] 303 214 #> [470,] 304 214 #> [471,] 305 214 #> [472,] 306 214 #> [473,] 307 214 #> [474,] 308 214 #> [475,] 309 214 #> [476,] 310 214 #> [477,] 311 214 #> [478,] 312 214 #> [479,] 313 214 #> [480,] 314 214 #> [481,] 315 213 #> [482,] 315 212 #> [483,] 316 211 #> [484,] 316 210 #> [485,] 316 209 #> [486,] 316 208 #> [487,] 316 207 #> [488,] 315 206 #> [489,] 316 205 #> [490,] 315 204 #> [491,] 316 203 #> [492,] 316 202 #> [493,] 316 201 #> [494,] 316 200 #> [495,] 316 199 #> [496,] 316 198 #> [497,] 316 197 #> [498,] 316 196 #> [499,] 315 195 #> [500,] 315 194 #> [501,] 314 193 #> [502,] 314 192 #> [503,] 313 191 #> [504,] 312 191 #> [505,] 311 190 #> [506,] 310 190 #> [507,] 309 189 #> [508,] 308 189 #> [509,] 307 189 #> [510,] 306 189 #> [511,] 305 189 #> [512,] 304 188 #> [513,] 303 188 #> [514,] 302 188 #> [515,] 301 188 #> [516,] 300 188 #> [517,] 299 188 #> [518,] 298 188 #> [519,] 297 188 #> [520,] 296 188 #> [521,] 295 188 #> [522,] 294 188 #> [523,] 293 187 #> [524,] 292 187 #> [525,] 291 186 #> [526,] 291 185 #> [527,] 291 184 #> [528,] 290 183 #> [529,] 290 182 #> [530,] 290 181 #> [531,] 289 180 #> [532,] 289 179 #> [533,] 288 178 #> [534,] 288 177 #> [535,] 288 176 #> [536,] 287 175 #> [537,] 287 174 #> [538,] 286 173 #> [539,] 286 172 #> [540,] 286 171 #> [541,] 285 170 #> [542,] 285 169 #> [543,] 284 168 #> [544,] 284 167 #> [545,] 284 166 #> [546,] 283 165 #> [547,] 283 164 #> [548,] 282 163 #> [549,] 282 162 #> [550,] 282 161 #> [551,] 281 160 #> [552,] 281 159 #> [553,] 280 158 #> [554,] 280 157 #> [555,] 280 156 #> [556,] 279 155 #> [557,] 279 154 #> [558,] 278 153 #> [559,] 278 152 #> [560,] 278 151 #> [561,] 277 150 #> [562,] 278 149 #> [563,] 277 148 #> [564,] 277 147 #> [565,] 277 146 #> [566,] 277 145 #> [567,] 277 144 #> [568,] 276 143 #> [569,] 276 142 #> [570,] 277 141 #> [571,] 276 140 #> [572,] 276 139 #> [573,] 276 138 #> [574,] 276 137 #> [575,] 276 136 #> [576,] 275 135 #> [577,] 276 134 #> [578,] 275 133 #> [579,] 275 132 #> [580,] 275 131 #> [581,] 275 130 #> [582,] 274 129 #> [583,] 274 128 #> [584,] 274 127 #> [585,] 274 126 #> [586,] 274 125 #> [587,] 273 124 #> [588,] 273 123 #> [589,] 273 122 #> [590,] 272 121 #> [591,] 272 120 #> [592,] 272 119 #> [593,] 271 118 #> [594,] 271 117 #> [595,] 270 116 #> [596,] 269 115 #> [597,] 268 114 #> [598,] 268 113 #> [599,] 267 112 #> [600,] 267 111 #> [601,] 267 110 #> [602,] 267 109 #> [603,] 267 108 #> [604,] 267 107 #> [605,] 266 106 #> [606,] 266 105 #> [607,] 266 104 #> [608,] 266 103 #> [609,] 266 102 #> [610,] 266 101 #> [611,] 266 100 #> [612,] 266 99 #> [613,] 266 98 #> [614,] 266 97 #> [615,] 266 96 #> [616,] 266 95 #> [617,] 266 94 #> [618,] 266 93 #> [619,] 266 92 #> [620,] 266 91 #> [621,] 266 90 #> [622,] 266 89 #> [623,] 266 88 #> [624,] 266 87 #> [625,] 266 86 #> [626,] 266 85 #> [627,] 266 84 #> [628,] 266 83 #> [629,] 266 82 #> [630,] 266 81 #> [631,] 266 80 #> [632,] 266 79 #> [633,] 266 78 #> [634,] 267 77 #> [635,] 267 76 #> [636,] 267 75 #> [637,] 267 74 #> [638,] 267 73 #> [639,] 267 72 #> [640,] 267 71 #> [641,] 267 70 #> [642,] 267 69 #> [643,] 267 68 #> [644,] 268 67 #> [645,] 267 66 #> [646,] 268 65 #> [647,] 268 64 #> [648,] 269 63 #> [649,] 270 62 #> [650,] 271 62 #> [651,] 272 61 #> [652,] 273 61 #> [653,] 274 60 #> [654,] 275 60 #> [655,] 276 59 #> [656,] 277 58 #> [657,] 277 57 #> [658,] 277 56 #> [659,] 277 55 #> [660,] 276 54 #> [661,] 275 53 #> [662,] 274 53 #> [663,] 273 52 #> [664,] 272 52 #> [665,] 271 51 #> [666,] 270 51 #> [667,] 269 50 #> [668,] 268 50 #> [669,] 267 50 #> [670,] 266 50 #> [671,] 265 50 #> [672,] 264 50 #> [673,] 263 50 #> [674,] 262 50 #> [675,] 261 51 #> [676,] 260 52 #> [677,] 260 53 #> [678,] 260 54 #> [679,] 259 55 #> [680,] 259 56 #> [681,] 259 57 #> [682,] 259 58 #> [683,] 258 59 #> [684,] 258 60 #> [685,] 258 61 #> [686,] 258 62 #> [687,] 258 63 #> [688,] 257 64 #> [689,] 257 65 #> [690,] 257 66 #> [691,] 257 67 #> [692,] 256 68 #> [693,] 256 69 #> [694,] 256 70 #> [695,] 256 71 #> [696,] 255 72 #> [697,] 255 73 #> [698,] 255 74 #> [699,] 254 75 #> [700,] 254 76 #> [701,] 254 77 #> [702,] 253 78 #> [703,] 253 79 #> [704,] 252 80 #> [705,] 252 81 #> [706,] 252 82 #> [707,] 251 83 #> [708,] 251 84 #> [709,] 250 85 #> [710,] 250 86 #> [711,] 249 87 #> [712,] 249 88 #> [713,] 249 89 #> [714,] 248 90 #> [715,] 248 91 #> [716,] 247 92 #> [717,] 247 93 #> [718,] 247 94 #> [719,] 246 95 #> [720,] 246 96 #> [721,] 245 97 #> [722,] 245 98 #> [723,] 244 99 #> [724,] 243 100 #> [725,] 243 101 #> [726,] 242 102 #> [727,] 241 103 #> [728,] 240 104 #> [729,] 239 104 #> [730,] 238 104 #> [731,] 237 104 #> [732,] 236 105 #> [733,] 235 105 #> [734,] 234 105 #> [735,] 233 105 #> [736,] 232 105 #> [737,] 231 105 #> [738,] 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#> [266,] 39 180 #> [267,] 38 181 #> [268,] 39 182 #> [269,] 39 183 #> [270,] 39 184 #> [271,] 39 185 #> [272,] 40 186 #> [273,] 41 187 #> [274,] 42 188 #> [275,] 43 189 #> [276,] 44 190 #> [277,] 45 190 #> [278,] 46 190 #> [279,] 47 190 #> [280,] 48 190 #> [281,] 49 190 #> [282,] 50 190 #> [283,] 51 190 #> [284,] 52 190 #> [285,] 53 190 #> [286,] 54 189 #> [287,] 55 189 #> [288,] 56 189 #> [289,] 57 188 #> [290,] 58 188 #> [291,] 59 188 #> [292,] 60 187 #> [293,] 61 187 #> [294,] 62 186 #> [295,] 63 186 #> [296,] 64 185 #> [297,] 65 185 #> [298,] 66 184 #> [299,] 67 184 #> [300,] 68 183 #> [301,] 69 183 #> [302,] 70 182 #> [303,] 71 182 #> [304,] 72 181 #> [305,] 73 180 #> [306,] 74 180 #> [307,] 75 179 #> [308,] 76 179 #> [309,] 77 178 #> [310,] 78 177 #> [311,] 79 177 #> [312,] 80 176 #> [313,] 81 176 #> [314,] 82 175 #> [315,] 83 174 #> [316,] 84 174 #> [317,] 85 173 #> [318,] 86 173 #> [319,] 87 172 #> [320,] 88 171 #> [321,] 89 171 #> [322,] 90 170 #> [323,] 91 170 #> [324,] 92 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167 #> [381,] 149 167 #> [382,] 150 168 #> [383,] 151 168 #> [384,] 152 169 #> [385,] 153 169 #> [386,] 154 170 #> [387,] 155 170 #> [388,] 156 171 #> [389,] 157 171 #> [390,] 158 172 #> [391,] 159 172 #> [392,] 160 173 #> [393,] 161 173 #> [394,] 162 174 #> [395,] 163 174 #> [396,] 164 174 #> [397,] 165 175 #> [398,] 166 175 #> [399,] 167 175 #> [400,] 168 176 #> [401,] 169 176 #> [402,] 168 177 #> [403,] 168 178 #> [404,] 167 179 #> [405,] 166 180 #> [406,] 165 181 #> [407,] 165 182 #> [408,] 164 183 #> [409,] 163 184 #> [410,] 162 185 #> [411,] 161 186 #> [412,] 160 187 #> [413,] 159 188 #> [414,] 159 189 #> [415,] 158 190 #> [416,] 157 191 #> [417,] 156 192 #> [418,] 155 193 #> [419,] 154 194 #> [420,] 153 195 #> [421,] 152 196 #> [422,] 151 197 #> [423,] 150 198 #> [424,] 149 199 #> [425,] 148 200 #> [426,] 147 201 #> [427,] 146 202 #> [428,] 145 203 #> [429,] 144 204 #> [430,] 143 205 #> [431,] 142 206 #> [432,] 142 207 #> [433,] 141 208 #> [434,] 140 209 #> [435,] 139 210 #> [436,] 138 211 #> [437,] 138 212 #> [438,] 137 213 #> [439,] 137 214 #> [440,] 137 215 #> [441,] 137 216 #> [442,] 138 217 #> [443,] 139 218 #> [444,] 140 218 #> [445,] 141 219 #> [446,] 142 219 #> [447,] 143 219 #> [448,] 144 219 #> [449,] 145 219 #> [450,] 146 220 #> [451,] 147 220 #> [452,] 148 220 #> [453,] 149 220 #> [454,] 150 220 #> [455,] 151 220 #> [456,] 152 220 #> [457,] 153 221 #> [458,] 154 220 #> [459,] 155 221 #> [460,] 156 221 #> [461,] 157 221 #> [462,] 158 221 #> [463,] 159 221 #> [464,] 160 221 #> [465,] 161 221 #> [466,] 162 221 #> [467,] 163 222 #> [468,] 164 221 #> [469,] 165 221 #> [470,] 166 221 #> [471,] 167 221 #> [472,] 168 221 #> [473,] 169 221 #> [474,] 170 221 #> [475,] 171 221 #> [476,] 172 221 #> [477,] 173 222 #> [478,] 174 222 #> [479,] 175 222 #> [480,] 176 222 #> [481,] 177 222 #> [482,] 178 222 #> [483,] 179 222 #> [484,] 180 222 #> [485,] 181 222 #> [486,] 182 222 #> [487,] 183 222 #> [488,] 184 222 #> [489,] 185 222 #> [490,] 186 222 #> [491,] 187 222 #> [492,] 188 222 #> [493,] 189 222 #> [494,] 190 222 #> [495,] 191 222 #> [496,] 192 222 #> [497,] 193 222 #> [498,] 194 222 #> [499,] 195 222 #> [500,] 196 222 #> [501,] 197 222 #> [502,] 198 222 #> [503,] 199 222 #> [504,] 200 222 #> [505,] 201 222 #> [506,] 202 222 #> [507,] 203 222 #> [508,] 204 222 #> [509,] 205 222 #> [510,] 206 222 #> [511,] 207 222 #> [512,] 208 221 #> [513,] 209 221 #> [514,] 210 221 #> [515,] 211 221 #> [516,] 212 221 #> [517,] 213 221 #> [518,] 214 221 #> [519,] 215 221 #> [520,] 216 221 #> [521,] 217 221 #> [522,] 218 221 #> [523,] 219 221 #> [524,] 220 221 #> [525,] 221 221 #> [526,] 222 221 #> [527,] 223 221 #> [528,] 224 221 #> [529,] 225 221 #> [530,] 226 221 #> [531,] 227 221 #> [532,] 228 221 #> [533,] 229 221 #> [534,] 230 220 #> [535,] 231 220 #> [536,] 232 220 #> [537,] 233 220 #> [538,] 234 220 #> [539,] 235 220 #> [540,] 236 220 #> [541,] 237 220 #> [542,] 238 220 #> [543,] 239 220 #> [544,] 240 220 #> [545,] 241 220 #> [546,] 242 219 #> [547,] 243 219 #> [548,] 244 219 #> [549,] 245 219 #> [550,] 246 219 #> [551,] 247 219 #> [552,] 248 219 #> [553,] 249 218 #> [554,] 250 218 #> [555,] 251 218 #> [556,] 252 218 #> [557,] 253 218 #> [558,] 254 218 #> [559,] 255 218 #> [560,] 256 217 #> [561,] 257 217 #> [562,] 258 217 #> [563,] 259 217 #> [564,] 260 216 #> [565,] 261 216 #> [566,] 262 216 #> [567,] 263 216 #> [568,] 264 215 #> [569,] 265 215 #> [570,] 266 215 #> [571,] 267 215 #> [572,] 268 214 #> [573,] 269 214 #> [574,] 270 214 #> [575,] 271 213 #> [576,] 272 213 #> [577,] 273 213 #> [578,] 274 212 #> [579,] 275 212 #> [580,] 276 212 #> [581,] 277 211 #> [582,] 278 211 #> [583,] 279 210 #> [584,] 280 210 #> [585,] 281 209 #> [586,] 282 209 #> [587,] 283 208 #> [588,] 284 208 #> [589,] 285 207 #> [590,] 286 207 #> [591,] 287 206 #> [592,] 288 206 #> [593,] 289 205 #> [594,] 290 205 #> [595,] 291 204 #> [596,] 292 203 #> [597,] 293 202 #> [598,] 294 202 #> [599,] 295 201 #> [600,] 296 200 #> [601,] 297 199 #> [602,] 298 198 #> [603,] 299 197 #> [604,] 300 196 #> [605,] 301 195 #> [606,] 302 194 #> [607,] 303 193 #> [608,] 303 192 #> [609,] 304 191 #> [610,] 305 190 #> [611,] 305 189 #> [612,] 306 188 #> [613,] 307 187 #> [614,] 308 186 #> [615,] 308 185 #> [616,] 309 184 #> [617,] 310 184 #> [618,] 311 184 #> [619,] 312 183 #> [620,] 313 183 #> [621,] 314 183 #> [622,] 315 182 #> [623,] 316 182 #> [624,] 317 182 #> [625,] 318 181 #> [626,] 319 181 #> [627,] 320 180 #> [628,] 321 180 #> [629,] 322 180 #> [630,] 323 179 #> [631,] 324 179 #> [632,] 325 178 #> [633,] 326 178 #> [634,] 327 178 #> [635,] 328 177 #> [636,] 329 177 #> [637,] 330 176 #> [638,] 331 176 #> [639,] 332 175 #> [640,] 333 174 #> [641,] 334 174 #> [642,] 335 173 #> [643,] 336 173 #> [644,] 337 172 #> [645,] 338 171 #> [646,] 339 171 #> [647,] 340 170 #> [648,] 341 170 #> [649,] 342 169 #> [650,] 343 168 #> [651,] 344 168 #> [652,] 345 167 #> [653,] 346 166 #> [654,] 347 165 #> [655,] 348 165 #> [656,] 349 164 #> [657,] 350 163 #> [658,] 351 162 #> [659,] 352 162 #> [660,] 353 161 #> [661,] 354 160 #> [662,] 355 159 #> [663,] 356 158 #> [664,] 357 157 #> [665,] 358 156 #> [666,] 359 155 #> [667,] 360 155 #> [668,] 361 154 #> [669,] 362 153 #> [670,] 362 152 #> [671,] 363 151 #> [672,] 364 150 #> [673,] 365 149 #> [674,] 366 148 #> [675,] 367 147 #> [676,] 368 146 #> [677,] 369 145 #> [678,] 370 144 #> [679,] 370 143 #> [680,] 371 142 #> [681,] 372 141 #> [682,] 373 140 #> [683,] 373 139 #> [684,] 374 138 #> [685,] 375 137 #> [686,] 375 136 #> [687,] 376 135 #> [688,] 377 134 #> [689,] 377 133 #> [690,] 378 132 #> [691,] 379 131 #> [692,] 379 130 #> [693,] 379 129 #> [694,] 380 128 #> [695,] 380 127 #> [696,] 381 126 #> [697,] 381 125 #> [698,] 382 124 #> [699,] 382 123 #> [700,] 382 122 #> [701,] 383 121 #> [702,] 383 120 #> [703,] 383 119 #> [704,] 384 118 #> [705,] 383 117 #> [706,] 383 116 #> [707,] 382 115 #> [708,] 381 114 #> [709,] 380 113 #> [710,] 379 112 #> [711,] 378 112 #> [712,] 377 111 #> [713,] 376 111 #> [714,] 375 110 #> [715,] 374 109 #> [716,] 373 109 #> [717,] 372 108 #> [718,] 371 107 #> [719,] 370 107 #> [720,] 369 106 #> [721,] 368 106 #> [722,] 367 105 #> [723,] 366 105 #> [724,] 365 105 #> [725,] 364 104 #> [726,] 363 103 #> [727,] 362 103 #> [728,] 361 103 #> [729,] 360 102 #> [730,] 359 102 #> [731,] 358 101 #> [732,] 357 101 #> [733,] 356 101 #> [734,] 355 100 #> [735,] 354 100 #> [736,] 353 99 #> [737,] 352 99 #> [738,] 351 99 #> [739,] 350 98 #> [740,] 349 98 #> [741,] 348 98 #> [742,] 347 97 #> [743,] 346 97 #> [744,] 345 97 #> [745,] 344 96 #> [746,] 343 96 #> [747,] 342 96 #> [748,] 341 95 #> [749,] 340 95 #> [750,] 339 95 #> [751,] 338 94 #> [752,] 337 94 #> [753,] 336 94 #> [754,] 335 94 #> [755,] 334 93 #> [756,] 333 93 #> [757,] 332 93 #> [758,] 331 93 #> [759,] 330 92 #> [760,] 329 92 #> [761,] 328 92 #> [762,] 327 92 #> [763,] 326 91 #> [764,] 325 91 #> [765,] 324 91 #> [766,] 323 91 #> [767,] 322 91 #> [768,] 321 90 #> [769,] 320 90 #> [770,] 319 90 #> [771,] 318 90 #> [772,] 317 90 #> [773,] 316 90 #> [774,] 315 89 #> [775,] 314 89 #> [776,] 313 89 #> [777,] 312 89 #> [778,] 311 89 #> [779,] 310 89 #> [780,] 309 88 #> [781,] 308 88 #> [782,] 307 88 #> [783,] 306 88 #> [784,] 305 88 #> [785,] 304 88 #> [786,] 303 88 #> [787,] 302 88 #> [788,] 301 88 #> [789,] 300 87 #> [790,] 299 87 #> [791,] 298 87 #> [792,] 297 87 #> [793,] 296 87 #> [794,] 295 87 #> [795,] 294 87 #> [796,] 293 87 #> [797,] 292 87 #> [798,] 291 87 #> [799,] 290 87 #> [800,] 289 87 #> [801,] 288 87 #> [802,] 287 87 #> [803,] 286 87 #> [804,] 285 87 #> [805,] 284 86 #> [806,] 283 86 #> [807,] 282 86 #> [808,] 282 85 #> [809,] 281 84 #> [810,] 281 83 #> [811,] 280 82 #> [812,] 280 81 #> [813,] 279 80 #> [814,] 278 79 #> [815,] 278 78 #> [816,] 278 77 #> [817,] 277 76 #> [818,] 276 75 #> [819,] 276 74 #> [820,] 276 73 #> [821,] 275 72 #> [822,] 274 71 #> [823,] 274 70 #> [824,] 273 69 #> [825,] 273 68 #> [826,] 272 67 #> [827,] 272 66 #> [828,] 271 65 #> [829,] 270 64 #> [830,] 270 63 #> [831,] 269 62 #> [832,] 269 61 #> [833,] 268 60 #> [834,] 267 59 #> [835,] 266 58 #> [836,] 266 57 #> [837,] 265 56 #> [838,] 264 55 #> [839,] 264 54 #> [840,] 263 53 #> [841,] 262 52 #> [842,] 261 51 #> [843,] 261 50 #> [844,] 260 49 #> [845,] 259 48 #> [846,] 258 47 #> [847,] 257 46 #> [848,] 256 45 #> [849,] 255 44 #> [850,] 254 43 #> [851,] 253 42 #> [852,] 252 42 #> [853,] 251 41 #> [854,] 250 41 #> [855,] 249 40 #> [856,] 248 40 #> [857,] 247 39 #> [858,] 246 39 #> [859,] 245 39 #> [860,] 244 39 #> [861,] 243 39 #> [862,] 242 39 #> [863,] 241 39 #> [864,] 240 39 #> [865,] 239 39 #> [866,] 238 40 #> [867,] 237 40 #> [868,] 236 41 #> [869,] 235 41 #> [870,] 234 42 #> [871,] 233 43 #> [872,] 233 44 #> [873,] 232 45 #> [874,] 231 46 #> [875,] 230 47 #> [876,] 230 48 #> [877,] 230 49 #> [878,] 229 50 #> [879,] 228 51 #> [880,] 228 52 #> [881,] 228 53 #> [882,] 227 54 #> [883,] 227 55 #> [884,] 227 56 #> [885,] 226 57 #> [886,] 226 58 #> [887,] 226 59 #> [888,] 226 60 #> [889,] 225 61 #> [890,] 225 62 #> [891,] 225 63 #> [892,] 224 64 #> [893,] 225 65 #> [894,] 224 66 #> [895,] 224 67 #> [896,] 224 68 #> [897,] 224 69 #> [898,] 224 70 #> [899,] 224 71 #> [900,] 224 72 #> [901,] 224 73 #> [902,] 224 74 #> [903,] 225 75 #> [904,] 224 76 #> [905,] 225 77 #> [906,] 225 78 #> [907,] 225 79 #> [908,] 226 80 #> [909,] 226 81 #> [910,] 226 82 #> [911,] 227 83 #> [912,] 227 84 #> [913,] 227 85 #> [914,] 228 86 #> [915,] 228 87 #> [916,] 227 87 #> [917,] 226 87 #> [918,] 225 88 #> [919,] 224 88 #> [920,] 223 87 #> [921,] 222 88 #> [922,] 221 88 #> [923,] 220 88 #> [924,] 219 88 #> [925,] 218 88 #> [926,] 217 89 #> [927,] 216 89 #> [928,] 215 89 #> [929,] 214 89 #> [930,] 213 89 #> [931,] 212 88 #> [932,] 211 88 #> [933,] 210 88 #> [934,] 209 88 #> [935,] 208 88 #> [936,] 207 88 #> [937,] 206 88 #> [938,] 205 87 #> [939,] 204 87 #> [940,] 203 87 #> [941,] 202 87 #> [942,] 201 87 #> [943,] 200 87 #> #> $duvel #> [,1] [,2] #> [1,] 61 315 #> [2,] 61 304 #> [3,] 61 293 #> [4,] 61 293 #> [5,] 61 282 #> [6,] 59 272 #> [7,] 59 261 #> [8,] 59 250 #> [9,] 59 239 #> [10,] 59 239 #> [11,] 59 228 #> [12,] 59 217 #> [13,] 59 206 #> [14,] 59 195 #> [15,] 59 185 #> [16,] 59 185 #> [17,] 59 174 #> [18,] 59 163 #> [19,] 59 152 #> [20,] 59 141 #> [21,] 59 130 #> [22,] 59 130 #> [23,] 59 119 #> [24,] 59 108 #> [25,] 59 98 #> [26,] 59 87 #> [27,] 59 87 #> [28,] 58 76 #> [29,] 58 65 #> [30,] 58 54 #> [31,] 61 43 #> [32,] 66 32 #> [33,] 66 32 #> [34,] 76 22 #> [35,] 86 18 #> [36,] 97 17 #> [37,] 108 16 #> [38,] 119 15 #> [39,] 119 15 #> [40,] 130 14 #> [41,] 141 12 #> [42,] 152 12 #> [43,] 163 11 #> [44,] 173 11 #> [45,] 173 11 #> [46,] 184 11 #> [47,] 195 11 #> [48,] 206 11 #> [49,] 217 12 #> [50,] 217 12 #> [51,] 228 12 #> [52,] 239 14 #> [53,] 250 15 #> [54,] 260 17 #> [55,] 271 17 #> [56,] 271 17 #> [57,] 282 21 #> [58,] 290 32 #> [59,] 295 43 #> [60,] 297 54 #> [61,] 298 65 #> [62,] 298 65 #> [63,] 298 76 #> [64,] 298 86 #> [65,] 298 97 #> [66,] 298 108 #> [67,] 298 119 #> [68,] 298 119 #> [69,] 298 130 #> [70,] 298 141 #> [71,] 298 152 #> [72,] 298 163 #> [73,] 298 163 #> [74,] 298 173 #> [75,] 298 184 #> [76,] 298 195 #> [77,] 298 206 #> [78,] 298 217 #> [79,] 298 217 #> [80,] 298 228 #> [81,] 298 239 #> [82,] 298 250 #> [83,] 298 260 #> [84,] 298 271 #> [85,] 298 271 #> [86,] 298 282 #> [87,] 298 293 #> [88,] 297 304 #> [89,] 297 315 #> [90,] 296 326 #> [91,] 296 326 #> [92,] 295 336 #> [93,] 292 347 #> [94,] 288 358 #> [95,] 282 369 #> [96,] 282 369 #> [97,] 274 380 #> [98,] 269 391 #> [99,] 265 402 #> [100,] 263 413 #> [101,] 262 423 #> [102,] 262 423 #> [103,] 261 434 #> [104,] 258 445 #> [105,] 253 456 #> [106,] 248 467 #> [107,] 240 478 #> [108,] 240 478 #> [109,] 233 488 #> [110,] 227 499 #> [111,] 223 509 #> [112,] 221 520 #> [113,] 221 531 #> [114,] 221 531 #> [115,] 225 542 #> [116,] 226 553 #> [117,] 223 564 #> [118,] 224 575 #> [119,] 224 575 #> [120,] 226 586 #> [121,] 223 596 #> [122,] 215 606 #> [123,] 204 613 #> [124,] 193 616 #> [125,] 193 616 #> [126,] 182 617 #> [127,] 171 617 #> [128,] 160 616 #> [129,] 149 611 #> [130,] 140 605 #> [131,] 140 605 #> [132,] 135 595 #> [133,] 132 584 #> [134,] 135 573 #> [135,] 133 562 #> [136,] 131 551 #> [137,] 131 551 #> [138,] 133 540 #> [139,] 137 529 #> [140,] 136 519 #> [141,] 133 508 #> [142,] 133 508 #> [143,] 130 497 #> [144,] 123 487 #> [145,] 113 476 #> [146,] 107 465 #> [147,] 103 454 #> [148,] 103 454 #> [149,] 99 444 #> [150,] 96 434 #> [151,] 95 423 #> [152,] 93 412 #> [153,] 92 401 #> [154,] 92 401 #> [155,] 88 390 #> [156,] 81 379 #> [157,] 74 369 #> [158,] 69 358 #> [159,] 65 348 #> [160,] 65 348 #> [161,] 63 337 #> # $fac grouping factors head(bot$fac) #> # A tibble: 6 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a # or if you know the name of the column of interest bot$type #> [1] whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> [11] whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> [21] beer beer beer beer beer beer beer beer beer beer #> [31] beer beer beer beer beer beer beer beer beer beer #> Levels: beer whisky # table table(bot$fac) #> fake #> type a b c d #> beer 0 0 10 10 #> whisky 10 10 0 0 # an internal view of an Out object str(bot) #> coo : List of 40 #> $ brahma : num [1:710, 1:2] 200 200 199 198 197 197 196 195 196 197 ... #> $ caney : num [1:494, 1:2] 200 199 199 198 197 197 196 195 194 194 ... #> $ chimay : num [1:806, 1:2] 200 200 199 198 198 197 197 196 195 195 ... #> $ corona : num [1:768, 1:2] 200 199 198 197 196 195 194 193 192 191 ... #> $ deusventrue : num [1:943, 1:2] 200 199 198 197 196 195 194 193 192 191 ... #> $ duvel : num [1:161, 1:2] 61 61 61 61 61 59 59 59 59 59 ... #> $ franziskaner : num [1:124, 1:2] 54 54 54 54 54 54 56 56 56 56 ... #> $ grimbergen : num [1:126, 1:2] 42 40 40 40 40 40 40 42 41 42 ... #> $ guiness : num [1:183, 1:2] 69 69 69 69 69 69 69 70 69 70 ... #> $ hoegardeen : num [1:193, 1:2] 42 40 40 40 40 40 40 40 40 40 ... #> $ jupiler : num [1:156, 1:2] 55 54 54 54 54 54 54 54 53 53 ... #> $ kingfisher : num [1:182, 1:2] 71 71 71 71 71 71 71 71 71 73 ... #> $ latrappe : num [1:136, 1:2] 26 25 25 25 25 26 26 26 26 26 ... #> $ lindemanskriek: num [1:176, 1:2] 60 60 55 54 54 54 53 54 54 54 ... #> $ nicechouffe : num [1:146, 1:2] 82 81 77 77 76 75 75 75 75 74 ... #> $ pecheresse : num [1:129, 1:2] 63 61 61 60 58 58 58 58 58 58 ... #> $ sierranevada : num [1:176, 1:2] 61 61 61 61 61 61 61 61 61 61 ... #> $ tanglefoot : num [1:174, 1:2] 48 48 48 48 49 49 49 49 49 49 ... #> $ tauro : num [1:174, 1:2] 56 54 54 54 54 54 54 54 54 52 ... #> $ westmalle : num [1:141, 1:2] 70 70 67 67 66 66 66 66 66 66 ... #> $ amrut : num [1:191, 1:2] 57 57 57 57 57 57 57 57 57 57 ... #> $ ballantines : num [1:146, 1:2] 38 38 38 38 38 38 38 38 38 38 ... #> $ bushmills : num [1:165, 1:2] 72 72 72 72 72 72 73 74 74 74 ... #> $ chivas : num [1:164, 1:2] 33 31 29 29 29 29 30 30 30 31 ... #> $ dalmore : num [1:155, 1:2] 52 47 44 42 42 42 42 42 42 42 ... #> $ famousgrouse : num [1:169, 1:2] 99 99 99 99 99 99 99 99 99 99 ... #> $ glendronach : num [1:197, 1:2] 73 73 74 74 74 74 74 74 74 74 ... #> $ glenmorangie : num [1:179, 1:2] 53 54 54 54 55 57 57 57 57 58 ... #> $ highlandpark : num [1:169, 1:2] 42 42 42 42 42 42 42 42 41 42 ... #> $ jackdaniels : num [1:150, 1:2] 63 63 63 63 63 63 63 63 63 63 ... #> $ jb : num [1:174, 1:2] 43 43 42 42 43 43 43 43 43 43 ... #> $ johnniewalker : num [1:168, 1:2] 133 133 133 133 134 134 134 134 134 134 ... #> $ magallan : num [1:141, 1:2] 78 78 80 80 81 81 81 83 83 84 ... #> $ makersmark : num [1:177, 1:2] 31 23 16 16 13 10 8 8 11 11 ... #> $ oban : num [1:179, 1:2] 74 74 74 74 74 74 75 75 75 75 ... #> $ oldpotrero : num [1:131, 1:2] 83 77 71 63 60 58 57 58 58 58 ... #> $ redbreast : num [1:177, 1:2] 105 103 101 98 98 97 97 97 97 97 ... #> $ tamdhu : num [1:176, 1:2] 49 49 49 49 49 50 50 50 50 50 ... #> $ wildturkey : num [1:185, 1:2] 18 18 18 18 18 18 18 18 18 18 ... #> $ yoichi : num [1:123, 1:2] 69 69 69 69 69 70 70 70 70 70 ... #> fac : tibble [40 × 2] (S3: tbl_df/tbl/data.frame) #> ldk : list() # subsetting # see ?filter, ?select, and their 'see also' section for the # complete list of dplyr-like verbs implemented in Momocs length(bot) # the number of shapes #> [1] 40 names(bot) # access all individual names #> [1] \"brahma\" \"caney\" \"chimay\" \"corona\" #> [5] \"deusventrue\" \"duvel\" \"franziskaner\" \"grimbergen\" #> [9] \"guiness\" \"hoegardeen\" \"jupiler\" \"kingfisher\" #> [13] \"latrappe\" \"lindemanskriek\" \"nicechouffe\" \"pecheresse\" #> [17] \"sierranevada\" \"tanglefoot\" \"tauro\" \"westmalle\" #> [21] \"amrut\" \"ballantines\" \"bushmills\" \"chivas\" #> [25] \"dalmore\" \"famousgrouse\" \"glendronach\" \"glenmorangie\" #> [29] \"highlandpark\" \"jackdaniels\" \"jb\" \"johnniewalker\" #> [33] \"magallan\" \"makersmark\" \"oban\" \"oldpotrero\" #> [37] \"redbreast\" \"tamdhu\" \"wildturkey\" \"yoichi\" bot2 <- bot names(bot2) <- paste0('newnames', 1:length(bot2)) # define new names # Add a $fac from scratch coo <- bot[1:5] # a list of five matrices length(coo) #> [1] 5 sapply(coo, class) #> brahma caney chimay corona deusventrue #> [1,] \"matrix\" \"matrix\" \"matrix\" \"matrix\" \"matrix\" #> [2,] \"array\" \"array\" \"array\" \"array\" \"array\" fac <- data.frame(name=letters[1:5], value=c(5:1)) # Then you have to define the subclass using the right builder # here we have outlines, so we use Out x <- Out(coo, fac) x$coo #> $brahma #> [,1] [,2] #> [1,] 200 62 #> [2,] 200 61 #> [3,] 199 60 #> [4,] 198 59 #> [5,] 197 58 #> [6,] 197 57 #> [7,] 196 56 #> [8,] 195 56 #> [9,] 196 56 #> [10,] 197 56 #> [11,] 198 56 #> [12,] 199 56 #> [13,] 200 56 #> [14,] 201 55 #> [15,] 202 55 #> [16,] 203 55 #> [17,] 204 55 #> [18,] 205 54 #> [19,] 206 54 #> [20,] 207 53 #> [21,] 208 52 #> [22,] 208 51 #> [23,] 209 50 #> [24,] 209 49 #> [25,] 209 48 #> [26,] 209 47 #> [27,] 208 46 #> [28,] 208 45 #> [29,] 207 44 #> [30,] 206 44 #> [31,] 205 43 #> [32,] 204 43 #> [33,] 203 43 #> [34,] 202 43 #> [35,] 201 43 #> [36,] 200 43 #> [37,] 199 43 #> [38,] 198 43 #> [39,] 197 43 #> [40,] 196 42 #> [41,] 195 42 #> [42,] 194 42 #> [43,] 193 42 #> [44,] 192 42 #> [45,] 191 42 #> [46,] 190 42 #> [47,] 189 42 #> [48,] 188 42 #> [49,] 187 42 #> [50,] 186 42 #> [51,] 185 42 #> [52,] 184 42 #> [53,] 183 42 #> [54,] 182 42 #> [55,] 181 42 #> [56,] 180 42 #> [57,] 179 42 #> [58,] 178 43 #> [59,] 177 42 #> [60,] 176 43 #> [61,] 175 43 #> [62,] 174 43 #> [63,] 173 43 #> [64,] 172 43 #> [65,] 171 43 #> [66,] 170 43 #> [67,] 169 43 #> [68,] 168 43 #> [69,] 167 43 #> [70,] 166 43 #> [71,] 165 43 #> [72,] 164 43 #> [73,] 163 43 #> [74,] 162 43 #> [75,] 161 43 #> [76,] 160 43 #> [77,] 159 43 #> [78,] 158 43 #> [79,] 157 43 #> [80,] 156 43 #> [81,] 155 43 #> [82,] 154 43 #> [83,] 153 43 #> [84,] 152 43 #> [85,] 151 43 #> [86,] 150 43 #> [87,] 149 43 #> [88,] 148 43 #> [89,] 147 43 #> [90,] 146 44 #> [91,] 145 44 #> [92,] 144 44 #> [93,] 143 44 #> [94,] 143 43 #> [95,] 143 42 #> [96,] 143 41 #> [97,] 142 40 #> [98,] 142 39 #> [99,] 142 38 #> [100,] 142 37 #> [101,] 142 36 #> [102,] 142 35 #> [103,] 143 34 #> [104,] 143 33 #> [105,] 143 32 #> [106,] 144 31 #> [107,] 145 30 #> [108,] 145 29 #> [109,] 146 28 #> [110,] 147 27 #> [111,] 148 27 #> [112,] 149 26 #> [113,] 150 25 #> [114,] 151 25 #> [115,] 152 24 #> [116,] 153 24 #> [117,] 154 23 #> [118,] 155 23 #> [119,] 156 23 #> [120,] 157 22 #> [121,] 158 22 #> [122,] 159 22 #> [123,] 160 21 #> [124,] 161 21 #> [125,] 162 21 #> [126,] 163 21 #> [127,] 164 21 #> [128,] 165 20 #> [129,] 166 20 #> [130,] 167 20 #> [131,] 168 20 #> [132,] 169 20 #> [133,] 170 20 #> [134,] 171 20 #> [135,] 172 20 #> [136,] 173 20 #> [137,] 174 19 #> [138,] 175 19 #> [139,] 176 19 #> [140,] 177 19 #> [141,] 178 19 #> [142,] 179 19 #> [143,] 180 19 #> [144,] 181 20 #> [145,] 182 20 #> [146,] 183 20 #> [147,] 184 20 #> [148,] 185 20 #> [149,] 186 20 #> [150,] 187 20 #> [151,] 188 20 #> [152,] 189 21 #> [153,] 190 21 #> [154,] 191 21 #> [155,] 192 21 #> [156,] 193 21 #> [157,] 194 21 #> [158,] 195 22 #> [159,] 196 22 #> [160,] 197 22 #> [161,] 198 22 #> [162,] 199 22 #> [163,] 200 22 #> [164,] 201 22 #> [165,] 202 22 #> [166,] 203 22 #> [167,] 204 22 #> [168,] 205 22 #> [169,] 206 22 #> [170,] 207 21 #> [171,] 208 20 #> [172,] 208 19 #> [173,] 207 18 #> [174,] 206 17 #> [175,] 205 17 #> [176,] 204 16 #> [177,] 203 16 #> [178,] 202 15 #> [179,] 201 15 #> [180,] 200 14 #> [181,] 199 14 #> [182,] 198 14 #> [183,] 197 13 #> [184,] 196 13 #> [185,] 195 13 #> [186,] 194 12 #> [187,] 193 12 #> [188,] 192 12 #> [189,] 191 11 #> [190,] 190 11 #> [191,] 189 11 #> [192,] 188 11 #> [193,] 187 10 #> [194,] 186 10 #> [195,] 185 10 #> [196,] 184 10 #> [197,] 183 9 #> [198,] 182 9 #> [199,] 181 10 #> [200,] 180 9 #> [201,] 179 9 #> [202,] 178 9 #> [203,] 177 9 #> [204,] 176 9 #> [205,] 175 9 #> [206,] 174 9 #> [207,] 173 9 #> [208,] 172 9 #> [209,] 171 9 #> [210,] 170 9 #> [211,] 169 9 #> [212,] 168 9 #> [213,] 167 9 #> [214,] 166 9 #> [215,] 165 9 #> [216,] 164 9 #> [217,] 163 9 #> [218,] 162 9 #> [219,] 161 9 #> [220,] 160 10 #> [221,] 159 10 #> [222,] 158 10 #> [223,] 157 10 #> [224,] 156 10 #> [225,] 155 11 #> [226,] 154 11 #> [227,] 153 11 #> [228,] 152 12 #> [229,] 151 12 #> [230,] 150 12 #> [231,] 149 13 #> [232,] 148 13 #> [233,] 147 14 #> [234,] 146 14 #> [235,] 145 15 #> [236,] 144 15 #> [237,] 143 16 #> [238,] 142 17 #> [239,] 141 17 #> [240,] 140 18 #> [241,] 139 19 #> [242,] 138 20 #> [243,] 137 21 #> [244,] 136 22 #> [245,] 135 23 #> [246,] 134 24 #> [247,] 134 25 #> [248,] 133 26 #> [249,] 133 27 #> [250,] 132 28 #> [251,] 132 29 #> [252,] 131 30 #> [253,] 131 31 #> [254,] 131 32 #> [255,] 130 33 #> [256,] 130 34 #> [257,] 130 35 #> [258,] 130 36 #> [259,] 130 37 #> [260,] 130 38 #> [261,] 130 39 #> [262,] 130 40 #> [263,] 130 41 #> [264,] 130 42 #> [265,] 130 43 #> [266,] 130 44 #> [267,] 130 45 #> [268,] 131 46 #> [269,] 131 47 #> [270,] 131 48 #> [271,] 132 49 #> [272,] 132 50 #> [273,] 132 51 #> [274,] 133 52 #> [275,] 133 53 #> [276,] 133 54 #> [277,] 134 55 #> [278,] 135 56 #> [279,] 135 57 #> [280,] 135 58 #> [281,] 135 59 #> [282,] 136 60 #> [283,] 136 61 #> [284,] 135 62 #> [285,] 136 63 #> [286,] 136 64 #> [287,] 136 65 #> [288,] 136 66 #> [289,] 136 67 #> [290,] 135 68 #> [291,] 136 69 #> [292,] 135 70 #> [293,] 135 71 #> [294,] 135 72 #> [295,] 135 73 #> [296,] 135 74 #> [297,] 134 75 #> [298,] 135 76 #> [299,] 134 77 #> [300,] 134 78 #> [301,] 134 79 #> [302,] 134 80 #> [303,] 134 81 #> [304,] 134 82 #> [305,] 134 83 #> [306,] 133 84 #> [307,] 133 85 #> [308,] 134 86 #> [309,] 134 87 #> [310,] 134 88 #> [311,] 133 89 #> [312,] 133 90 #> [313,] 133 91 #> [314,] 133 92 #> [315,] 133 93 #> [316,] 133 94 #> [317,] 133 95 #> [318,] 133 96 #> [319,] 133 97 #> [320,] 133 98 #> [321,] 133 99 #> [322,] 133 100 #> [323,] 133 101 #> [324,] 133 102 #> [325,] 133 103 #> [326,] 133 104 #> [327,] 133 105 #> [328,] 133 106 #> [329,] 133 107 #> [330,] 133 108 #> [331,] 133 109 #> [332,] 134 110 #> [333,] 134 111 #> [334,] 133 112 #> [335,] 134 113 #> [336,] 134 114 #> [337,] 134 115 #> [338,] 134 116 #> [339,] 134 117 #> [340,] 135 118 #> [341,] 135 119 #> [342,] 135 120 #> [343,] 136 121 #> [344,] 136 122 #> [345,] 136 123 #> [346,] 137 124 #> [347,] 137 125 #> [348,] 138 126 #> [349,] 138 127 #> [350,] 139 128 #> [351,] 139 129 #> [352,] 140 130 #> [353,] 140 131 #> [354,] 141 132 #> [355,] 141 133 #> [356,] 142 134 #> [357,] 142 135 #> [358,] 143 136 #> [359,] 143 137 #> [360,] 144 138 #> [361,] 144 139 #> [362,] 145 140 #> [363,] 145 141 #> [364,] 146 142 #> [365,] 147 143 #> [366,] 148 144 #> [367,] 148 145 #> [368,] 149 146 #> [369,] 150 147 #> [370,] 150 148 #> [371,] 151 149 #> [372,] 152 150 #> [373,] 153 151 #> [374,] 154 152 #> [375,] 155 153 #> [376,] 156 154 #> [377,] 157 155 #> [378,] 158 156 #> [379,] 159 157 #> [380,] 160 158 #> [381,] 161 158 #> [382,] 162 159 #> [383,] 163 159 #> [384,] 164 160 #> [385,] 165 160 #> [386,] 166 160 #> [387,] 167 161 #> [388,] 168 161 #> [389,] 169 161 #> [390,] 170 162 #> [391,] 171 162 #> [392,] 172 162 #> [393,] 173 163 #> [394,] 174 164 #> [395,] 175 164 #> [396,] 176 165 #> [397,] 177 165 #> [398,] 178 166 #> [399,] 179 167 #> [400,] 180 167 #> [401,] 181 168 #> [402,] 182 169 #> [403,] 183 170 #> [404,] 184 171 #> [405,] 185 172 #> [406,] 186 173 #> [407,] 187 174 #> [408,] 187 175 #> [409,] 188 176 #> [410,] 189 177 #> [411,] 189 178 #> [412,] 190 179 #> [413,] 190 180 #> [414,] 191 181 #> [415,] 191 182 #> [416,] 191 183 #> [417,] 191 184 #> [418,] 191 185 #> [419,] 191 186 #> [420,] 191 187 #> [421,] 190 188 #> [422,] 191 189 #> [423,] 191 190 #> [424,] 191 191 #> [425,] 191 192 #> [426,] 192 193 #> [427,] 192 194 #> [428,] 192 195 #> [429,] 193 196 #> [430,] 193 197 #> [431,] 194 198 #> [432,] 194 199 #> [433,] 194 200 #> [434,] 195 201 #> [435,] 196 202 #> [436,] 196 203 #> [437,] 197 204 #> [438,] 197 205 #> [439,] 198 206 #> [440,] 199 207 #> [441,] 200 208 #> [442,] 201 209 #> [443,] 202 210 #> [444,] 203 210 #> [445,] 204 211 #> [446,] 205 212 #> [447,] 206 212 #> [448,] 207 213 #> [449,] 208 213 #> [450,] 209 214 #> [451,] 210 215 #> [452,] 211 216 #> [453,] 211 217 #> [454,] 211 218 #> [455,] 212 219 #> [456,] 212 220 #> [457,] 213 221 #> [458,] 213 222 #> [459,] 214 223 #> [460,] 215 224 #> [461,] 215 225 #> [462,] 216 226 #> [463,] 217 227 #> [464,] 217 228 #> [465,] 218 229 #> [466,] 219 230 #> [467,] 220 230 #> [468,] 221 231 #> [469,] 222 231 #> [470,] 223 230 #> [471,] 224 229 #> [472,] 225 228 #> [473,] 225 227 #> [474,] 225 226 #> [475,] 225 225 #> [476,] 226 224 #> [477,] 225 223 #> [478,] 225 222 #> [479,] 225 221 #> [480,] 226 220 #> [481,] 226 219 #> [482,] 226 218 #> [483,] 226 217 #> [484,] 226 216 #> [485,] 226 215 #> [486,] 226 214 #> [487,] 226 213 #> [488,] 226 212 #> [489,] 226 211 #> [490,] 227 211 #> [491,] 228 211 #> [492,] 229 210 #> [493,] 230 210 #> [494,] 231 210 #> [495,] 232 209 #> [496,] 233 209 #> [497,] 234 208 #> [498,] 235 208 #> [499,] 236 207 #> [500,] 237 207 #> [501,] 238 206 #> [502,] 238 205 #> [503,] 239 204 #> [504,] 240 203 #> [505,] 240 202 #> [506,] 241 201 #> [507,] 242 200 #> [508,] 243 199 #> [509,] 244 199 #> [510,] 245 199 #> [511,] 246 198 #> [512,] 247 198 #> [513,] 248 197 #> [514,] 249 196 #> [515,] 249 195 #> [516,] 250 194 #> [517,] 250 193 #> [518,] 249 192 #> [519,] 249 191 #> [520,] 249 190 #> [521,] 248 189 #> [522,] 248 188 #> [523,] 248 187 #> [524,] 247 186 #> [525,] 246 185 #> [526,] 245 184 #> [527,] 244 183 #> [528,] 243 182 #> [529,] 242 181 #> [530,] 241 180 #> [531,] 240 180 #> [532,] 239 179 #> [533,] 238 178 #> [534,] 237 178 #> [535,] 236 177 #> [536,] 235 176 #> [537,] 235 175 #> [538,] 235 174 #> [539,] 235 173 #> [540,] 235 172 #> [541,] 235 171 #> [542,] 235 170 #> [543,] 235 169 #> [544,] 236 168 #> [545,] 235 167 #> [546,] 236 166 #> [547,] 236 165 #> [548,] 236 164 #> [549,] 236 163 #> [550,] 236 162 #> [551,] 237 161 #> [552,] 236 160 #> [553,] 237 159 #> [554,] 237 158 #> [555,] 237 157 #> [556,] 237 156 #> [557,] 237 155 #> [558,] 237 154 #> [559,] 237 153 #> [560,] 238 152 #> [561,] 237 151 #> [562,] 237 150 #> [563,] 237 149 #> [564,] 237 148 #> [565,] 237 147 #> [566,] 238 146 #> [567,] 237 145 #> [568,] 237 144 #> [569,] 237 143 #> [570,] 237 142 #> [571,] 237 141 #> [572,] 237 140 #> [573,] 237 139 #> [574,] 237 138 #> [575,] 236 137 #> [576,] 236 136 #> [577,] 236 135 #> [578,] 235 134 #> [579,] 235 133 #> [580,] 235 132 #> [581,] 234 131 #> [582,] 234 130 #> [583,] 233 129 #> [584,] 232 128 #> [585,] 232 127 #> [586,] 231 126 #> [587,] 230 125 #> [588,] 230 124 #> [589,] 229 123 #> [590,] 228 122 #> [591,] 228 121 #> [592,] 227 120 #> [593,] 226 119 #> [594,] 226 118 #> [595,] 226 117 #> [596,] 225 116 #> [597,] 224 115 #> [598,] 224 114 #> [599,] 224 113 #> [600,] 223 112 #> [601,] 223 111 #> [602,] 223 110 #> [603,] 223 109 #> [604,] 222 108 #> [605,] 222 107 #> [606,] 222 106 #> [607,] 222 105 #> [608,] 222 104 #> [609,] 221 103 #> [610,] 221 102 #> [611,] 221 101 #> [612,] 221 100 #> [613,] 221 99 #> [614,] 221 98 #> [615,] 221 97 #> [616,] 221 96 #> [617,] 221 95 #> [618,] 221 94 #> [619,] 221 93 #> [620,] 221 92 #> [621,] 221 91 #> [622,] 221 90 #> [623,] 221 89 #> [624,] 221 88 #> [625,] 221 87 #> [626,] 221 86 #> [627,] 221 85 #> [628,] 221 84 #> [629,] 221 83 #> [630,] 221 82 #> [631,] 221 81 #> [632,] 221 80 #> [633,] 221 79 #> [634,] 221 78 #> [635,] 221 77 #> [636,] 221 76 #> [637,] 221 75 #> [638,] 221 74 #> [639,] 221 73 #> [640,] 221 72 #> [641,] 221 71 #> [642,] 221 70 #> [643,] 222 69 #> [644,] 222 68 #> [645,] 222 67 #> [646,] 222 66 #> [647,] 222 65 #> [648,] 222 64 #> [649,] 222 63 #> [650,] 223 62 #> [651,] 224 62 #> [652,] 225 61 #> [653,] 226 61 #> [654,] 227 61 #> [655,] 228 61 #> [656,] 229 60 #> [657,] 230 60 #> [658,] 231 60 #> [659,] 232 59 #> [660,] 232 58 #> [661,] 233 57 #> [662,] 232 56 #> [663,] 232 55 #> [664,] 231 54 #> [665,] 230 53 #> [666,] 229 52 #> [667,] 230 51 #> [668,] 229 50 #> [669,] 230 49 #> [670,] 229 48 #> [671,] 228 47 #> [672,] 227 46 #> [673,] 226 46 #> [674,] 225 45 #> [675,] 224 45 #> [676,] 223 45 #> [677,] 222 45 #> [678,] 221 45 #> [679,] 220 45 #> [680,] 219 45 #> [681,] 218 45 #> [682,] 217 45 #> [683,] 216 45 #> [684,] 215 46 #> [685,] 214 46 #> [686,] 213 47 #> [687,] 212 48 #> [688,] 211 49 #> [689,] 210 50 #> [690,] 209 51 #> [691,] 208 52 #> [692,] 208 53 #> [693,] 207 54 #> [694,] 206 55 #> [695,] 206 56 #> [696,] 205 57 #> [697,] 205 58 #> [698,] 204 59 #> [699,] 204 60 #> [700,] 203 61 #> [701,] 203 62 #> [702,] 203 63 #> [703,] 202 64 #> [704,] 202 65 #> [705,] 202 66 #> [706,] 201 66 #> [707,] 201 65 #> [708,] 201 64 #> [709,] 201 63 #> [710,] 200 62 #> #> $caney #> [,1] [,2] #> [1,] 200 75 #> [2,] 199 74 #> [3,] 199 73 #> [4,] 198 72 #> [5,] 197 71 #> [6,] 197 70 #> [7,] 196 69 #> [8,] 195 68 #> [9,] 194 67 #> [10,] 194 66 #> [11,] 193 65 #> [12,] 192 64 #> [13,] 192 63 #> [14,] 191 62 #> [15,] 190 61 #> [16,] 190 60 #> [17,] 189 59 #> [18,] 188 58 #> [19,] 188 57 #> [20,] 187 56 #> [21,] 187 55 #> [22,] 186 54 #> [23,] 185 53 #> [24,] 185 52 #> [25,] 184 51 #> [26,] 183 50 #> [27,] 183 49 #> [28,] 183 48 #> [29,] 182 47 #> [30,] 181 46 #> [31,] 180 46 #> [32,] 179 47 #> [33,] 179 48 #> [34,] 178 49 #> [35,] 177 50 #> [36,] 176 51 #> [37,] 175 52 #> [38,] 174 53 #> [39,] 173 54 #> [40,] 173 55 #> [41,] 172 56 #> [42,] 171 57 #> [43,] 170 58 #> [44,] 169 59 #> [45,] 168 60 #> [46,] 167 61 #> [47,] 166 62 #> [48,] 165 63 #> [49,] 164 64 #> [50,] 163 65 #> [51,] 162 66 #> [52,] 161 67 #> [53,] 160 68 #> [54,] 159 69 #> [55,] 158 70 #> [56,] 157 71 #> [57,] 156 72 #> [58,] 155 73 #> [59,] 154 74 #> [60,] 153 75 #> [61,] 152 76 #> [62,] 151 77 #> [63,] 150 78 #> [64,] 149 79 #> [65,] 148 80 #> [66,] 147 81 #> [67,] 146 82 #> [68,] 145 82 #> [69,] 144 83 #> [70,] 143 84 #> [71,] 142 85 #> [72,] 141 86 #> [73,] 140 87 #> [74,] 139 87 #> [75,] 138 88 #> [76,] 137 89 #> [77,] 136 90 #> [78,] 135 91 #> [79,] 134 91 #> [80,] 133 92 #> [81,] 132 93 #> [82,] 131 94 #> [83,] 130 94 #> [84,] 129 95 #> [85,] 128 96 #> [86,] 127 96 #> [87,] 126 97 #> [88,] 125 98 #> [89,] 124 98 #> [90,] 123 99 #> [91,] 122 100 #> [92,] 121 100 #> [93,] 120 101 #> [94,] 119 101 #> [95,] 118 102 #> [96,] 117 102 #> [97,] 116 103 #> [98,] 115 104 #> [99,] 114 104 #> [100,] 113 105 #> [101,] 112 105 #> [102,] 111 106 #> [103,] 110 106 #> [104,] 109 107 #> [105,] 108 107 #> [106,] 107 107 #> [107,] 106 108 #> [108,] 105 108 #> [109,] 104 109 #> [110,] 105 110 #> [111,] 106 111 #> [112,] 107 111 #> [113,] 108 112 #> [114,] 109 113 #> [115,] 110 113 #> [116,] 111 114 #> [117,] 112 114 #> [118,] 113 115 #> [119,] 114 116 #> [120,] 115 116 #> [121,] 116 117 #> [122,] 117 117 #> [123,] 118 118 #> [124,] 119 119 #> [125,] 120 119 #> [126,] 121 120 #> [127,] 122 120 #> [128,] 123 121 #> [129,] 124 122 #> [130,] 125 122 #> [131,] 126 123 #> [132,] 127 123 #> [133,] 128 124 #> [134,] 129 125 #> [135,] 130 125 #> [136,] 131 126 #> [137,] 132 127 #> [138,] 133 127 #> [139,] 134 128 #> [140,] 135 128 #> [141,] 136 129 #> [142,] 137 130 #> [143,] 138 130 #> [144,] 139 131 #> [145,] 140 131 #> [146,] 141 132 #> [147,] 142 133 #> [148,] 143 133 #> [149,] 144 134 #> [150,] 145 134 #> [151,] 146 135 #> [152,] 147 136 #> [153,] 148 136 #> [154,] 149 137 #> [155,] 150 138 #> [156,] 151 138 #> [157,] 152 139 #> [158,] 153 139 #> [159,] 154 139 #> [160,] 155 138 #> [161,] 155 137 #> [162,] 156 136 #> [163,] 156 135 #> [164,] 157 134 #> [165,] 157 133 #> [166,] 158 132 #> [167,] 158 131 #> [168,] 159 130 #> [169,] 159 129 #> [170,] 160 128 #> [171,] 160 127 #> [172,] 161 126 #> [173,] 161 125 #> [174,] 162 124 #> [175,] 162 123 #> [176,] 163 122 #> [177,] 163 121 #> [178,] 164 120 #> [179,] 164 119 #> [180,] 165 118 #> [181,] 166 117 #> [182,] 166 116 #> [183,] 167 115 #> [184,] 167 114 #> [185,] 168 113 #> [186,] 168 112 #> [187,] 169 111 #> [188,] 169 110 #> [189,] 170 109 #> [190,] 170 108 #> [191,] 171 107 #> [192,] 171 106 #> [193,] 172 105 #> [194,] 172 104 #> [195,] 173 103 #> [196,] 173 102 #> [197,] 174 101 #> [198,] 174 100 #> [199,] 175 99 #> [200,] 175 98 #> [201,] 176 97 #> [202,] 176 96 #> [203,] 177 95 #> [204,] 177 94 #> [205,] 178 94 #> [206,] 178 95 #> [207,] 179 96 #> [208,] 179 97 #> [209,] 180 98 #> [210,] 180 99 #> [211,] 181 100 #> [212,] 181 101 #> [213,] 182 102 #> [214,] 182 103 #> [215,] 183 104 #> [216,] 183 105 #> [217,] 184 106 #> [218,] 184 107 #> [219,] 184 108 #> [220,] 185 109 #> [221,] 186 110 #> [222,] 186 111 #> [223,] 187 112 #> [224,] 187 113 #> [225,] 187 114 #> [226,] 188 115 #> [227,] 189 116 #> [228,] 189 117 #> [229,] 190 118 #> [230,] 190 119 #> [231,] 190 120 #> [232,] 191 121 #> [233,] 192 122 #> [234,] 192 123 #> [235,] 193 124 #> [236,] 193 125 #> [237,] 194 126 #> [238,] 195 127 #> [239,] 195 128 #> [240,] 195 129 #> [241,] 196 130 #> [242,] 197 131 #> [243,] 197 132 #> [244,] 198 133 #> [245,] 199 134 #> [246,] 199 135 #> [247,] 200 136 #> [248,] 200 137 #> [249,] 201 138 #> [250,] 201 139 #> [251,] 202 140 #> [252,] 203 141 #> [253,] 203 142 #> [254,] 204 143 #> [255,] 204 144 #> [256,] 205 145 #> [257,] 206 146 #> [258,] 207 147 #> [259,] 207 148 #> [260,] 208 149 #> [261,] 209 150 #> [262,] 209 151 #> [263,] 210 152 #> [264,] 211 153 #> [265,] 211 154 #> [266,] 212 155 #> [267,] 213 156 #> [268,] 213 157 #> [269,] 214 158 #> [270,] 215 159 #> [271,] 215 160 #> [272,] 216 161 #> [273,] 217 162 #> [274,] 218 163 #> [275,] 218 164 #> [276,] 219 165 #> [277,] 220 166 #> [278,] 221 167 #> [279,] 221 168 #> [280,] 222 169 #> [281,] 223 170 #> [282,] 224 171 #> [283,] 224 172 #> [284,] 225 173 #> [285,] 226 174 #> [286,] 227 175 #> [287,] 228 176 #> [288,] 229 177 #> [289,] 229 178 #> [290,] 230 179 #> [291,] 231 180 #> [292,] 232 181 #> [293,] 233 182 #> [294,] 234 183 #> [295,] 235 184 #> [296,] 235 185 #> [297,] 236 186 #> [298,] 237 187 #> [299,] 238 188 #> [300,] 239 189 #> [301,] 240 190 #> [302,] 241 191 #> [303,] 242 192 #> [304,] 243 193 #> [305,] 244 194 #> [306,] 245 195 #> [307,] 246 196 #> [308,] 247 197 #> [309,] 248 198 #> [310,] 249 198 #> [311,] 250 199 #> [312,] 251 200 #> [313,] 252 201 #> [314,] 253 202 #> [315,] 254 203 #> [316,] 255 204 #> [317,] 256 205 #> [318,] 257 205 #> [319,] 258 206 #> [320,] 259 207 #> [321,] 260 208 #> [322,] 261 208 #> [323,] 262 209 #> [324,] 263 210 #> [325,] 264 211 #> [326,] 265 211 #> [327,] 266 212 #> [328,] 267 213 #> [329,] 268 213 #> [330,] 269 214 #> [331,] 270 214 #> [332,] 271 215 #> [333,] 272 216 #> [334,] 273 216 #> [335,] 274 217 #> [336,] 275 217 #> [337,] 276 218 #> [338,] 277 219 #> [339,] 278 219 #> [340,] 279 218 #> [341,] 279 217 #> [342,] 279 216 #> [343,] 279 215 #> [344,] 278 214 #> [345,] 278 213 #> [346,] 278 212 #> [347,] 279 211 #> [348,] 278 210 #> [349,] 278 209 #> [350,] 278 208 #> [351,] 278 207 #> [352,] 278 206 #> [353,] 278 205 #> [354,] 277 204 #> [355,] 277 203 #> [356,] 278 202 #> [357,] 277 201 #> [358,] 277 200 #> [359,] 277 199 #> [360,] 277 198 #> [361,] 277 197 #> [362,] 277 196 #> [363,] 276 195 #> [364,] 276 194 #> [365,] 276 193 #> [366,] 277 192 #> [367,] 277 191 #> [368,] 276 190 #> [369,] 276 189 #> [370,] 276 188 #> [371,] 276 187 #> [372,] 276 186 #> [373,] 276 185 #> [374,] 276 184 #> [375,] 276 183 #> [376,] 276 182 #> [377,] 276 181 #> [378,] 276 180 #> [379,] 276 179 #> [380,] 276 178 #> [381,] 276 177 #> [382,] 276 176 #> [383,] 277 175 #> [384,] 276 174 #> [385,] 276 173 #> [386,] 277 172 #> [387,] 277 171 #> [388,] 277 170 #> [389,] 277 169 #> [390,] 277 168 #> [391,] 277 167 #> [392,] 278 166 #> [393,] 278 165 #> [394,] 278 164 #> [395,] 278 163 #> [396,] 279 162 #> [397,] 279 161 #> [398,] 279 160 #> [399,] 280 159 #> [400,] 280 158 #> [401,] 280 157 #> [402,] 281 156 #> [403,] 281 155 #> [404,] 282 154 #> [405,] 282 153 #> [406,] 281 152 #> [407,] 280 152 #> [408,] 279 152 #> [409,] 278 151 #> [410,] 277 151 #> [411,] 276 150 #> [412,] 275 150 #> [413,] 274 150 #> [414,] 273 149 #> [415,] 272 148 #> [416,] 271 148 #> [417,] 270 147 #> [418,] 269 146 #> [419,] 268 146 #> [420,] 267 145 #> [421,] 266 145 #> [422,] 265 144 #> [423,] 264 143 #> [424,] 263 142 #> [425,] 262 142 #> [426,] 261 141 #> [427,] 260 140 #> [428,] 259 139 #> [429,] 258 139 #> [430,] 257 138 #> [431,] 256 137 #> [432,] 255 136 #> [433,] 254 135 #> [434,] 253 134 #> [435,] 252 133 #> [436,] 251 133 #> [437,] 250 132 #> [438,] 249 131 #> [439,] 248 130 #> [440,] 247 129 #> [441,] 246 128 #> [442,] 245 127 #> [443,] 244 126 #> [444,] 243 125 #> [445,] 242 124 #> [446,] 241 123 #> [447,] 240 122 #> [448,] 239 121 #> [449,] 238 120 #> [450,] 237 119 #> [451,] 236 118 #> [452,] 235 117 #> [453,] 234 116 #> [454,] 233 115 #> [455,] 232 114 #> [456,] 231 113 #> [457,] 231 112 #> [458,] 230 111 #> [459,] 229 110 #> [460,] 228 109 #> [461,] 227 108 #> [462,] 226 107 #> [463,] 225 106 #> [464,] 224 105 #> [465,] 223 104 #> [466,] 223 103 #> [467,] 222 102 #> [468,] 221 101 #> [469,] 220 100 #> [470,] 219 99 #> [471,] 218 98 #> [472,] 218 97 #> [473,] 217 96 #> [474,] 216 95 #> [475,] 215 94 #> [476,] 214 93 #> [477,] 213 92 #> [478,] 213 91 #> [479,] 212 90 #> [480,] 211 89 #> [481,] 210 88 #> [482,] 209 87 #> [483,] 209 86 #> [484,] 208 85 #> [485,] 207 84 #> [486,] 206 83 #> [487,] 205 82 #> [488,] 205 81 #> [489,] 204 80 #> [490,] 203 79 #> [491,] 202 78 #> [492,] 202 77 #> [493,] 201 76 #> [494,] 200 75 #> #> $chimay #> [,1] [,2] #> [1,] 200 76 #> [2,] 200 75 #> [3,] 199 74 #> [4,] 198 73 #> [5,] 198 72 #> [6,] 197 71 #> [7,] 197 70 #> [8,] 196 69 #> [9,] 195 68 #> [10,] 195 67 #> [11,] 194 66 #> [12,] 194 65 #> [13,] 193 64 #> [14,] 192 63 #> [15,] 192 62 #> [16,] 191 61 #> [17,] 190 60 #> [18,] 190 59 #> [19,] 189 58 #> [20,] 189 57 #> [21,] 188 56 #> [22,] 187 55 #> [23,] 187 54 #> [24,] 186 53 #> [25,] 186 52 #> [26,] 185 51 #> [27,] 184 50 #> [28,] 184 49 #> [29,] 183 48 #> [30,] 183 47 #> [31,] 182 46 #> [32,] 181 45 #> [33,] 181 44 #> [34,] 181 43 #> [35,] 180 42 #> [36,] 179 41 #> [37,] 179 40 #> [38,] 178 39 #> [39,] 177 38 #> [40,] 176 37 #> [41,] 175 37 #> [42,] 174 37 #> [43,] 173 37 #> [44,] 172 37 #> [45,] 171 37 #> [46,] 170 37 #> [47,] 169 37 #> [48,] 168 37 #> [49,] 167 37 #> [50,] 166 37 #> [51,] 165 37 #> [52,] 164 37 #> [53,] 163 37 #> [54,] 162 37 #> [55,] 161 37 #> [56,] 160 37 #> [57,] 159 37 #> [58,] 158 37 #> [59,] 157 37 #> [60,] 156 37 #> [61,] 155 37 #> [62,] 154 37 #> [63,] 153 37 #> [64,] 152 37 #> [65,] 151 37 #> [66,] 150 37 #> [67,] 149 37 #> [68,] 148 37 #> [69,] 147 37 #> [70,] 146 37 #> [71,] 145 37 #> [72,] 144 37 #> [73,] 143 37 #> [74,] 142 37 #> [75,] 141 37 #> [76,] 140 37 #> [77,] 139 37 #> [78,] 138 37 #> [79,] 137 37 #> [80,] 136 37 #> [81,] 135 37 #> [82,] 134 37 #> [83,] 133 37 #> [84,] 132 37 #> [85,] 131 37 #> [86,] 130 37 #> [87,] 129 37 #> [88,] 128 37 #> [89,] 127 37 #> [90,] 126 37 #> [91,] 125 37 #> [92,] 124 37 #> [93,] 123 37 #> [94,] 122 37 #> [95,] 121 37 #> [96,] 120 37 #> [97,] 119 37 #> [98,] 118 37 #> [99,] 117 37 #> [100,] 116 37 #> [101,] 115 37 #> [102,] 114 37 #> [103,] 113 37 #> [104,] 112 37 #> [105,] 111 37 #> [106,] 110 37 #> [107,] 109 37 #> [108,] 108 37 #> [109,] 107 37 #> [110,] 106 37 #> [111,] 105 37 #> [112,] 104 37 #> [113,] 103 37 #> [114,] 102 38 #> [115,] 103 39 #> [116,] 103 40 #> [117,] 104 41 #> [118,] 104 42 #> [119,] 105 43 #> [120,] 106 44 #> [121,] 106 45 #> [122,] 107 46 #> [123,] 107 47 #> [124,] 108 48 #> [125,] 108 49 #> [126,] 109 50 #> [127,] 110 51 #> [128,] 110 52 #> [129,] 111 53 #> [130,] 111 54 #> [131,] 112 55 #> [132,] 113 56 #> [133,] 113 57 #> [134,] 113 58 #> [135,] 114 59 #> [136,] 115 60 #> [137,] 115 61 #> [138,] 116 62 #> [139,] 117 63 #> [140,] 117 64 #> [141,] 117 65 #> [142,] 118 66 #> [143,] 119 67 #> [144,] 119 68 #> [145,] 120 69 #> [146,] 121 70 #> [147,] 121 71 #> [148,] 121 72 #> [149,] 122 73 #> [150,] 123 74 #> [151,] 123 75 #> [152,] 124 76 #> [153,] 125 77 #> [154,] 125 78 #> [155,] 126 79 #> [156,] 126 80 #> [157,] 127 81 #> [158,] 127 82 #> [159,] 128 83 #> [160,] 129 84 #> [161,] 129 85 #> [162,] 130 86 #> [163,] 130 87 #> [164,] 131 88 #> [165,] 131 89 #> [166,] 132 90 #> [167,] 132 91 #> [168,] 133 92 #> [169,] 134 93 #> [170,] 134 94 #> [171,] 135 95 #> [172,] 136 96 #> [173,] 136 97 #> [174,] 136 98 #> [175,] 137 99 #> [176,] 138 100 #> [177,] 138 101 #> [178,] 139 102 #> [179,] 140 103 #> [180,] 140 104 #> [181,] 140 105 #> [182,] 141 106 #> [183,] 142 107 #> [184,] 142 108 #> [185,] 143 109 #> [186,] 144 110 #> [187,] 144 111 #> [188,] 145 112 #> [189,] 145 113 #> [190,] 146 114 #> [191,] 146 115 #> [192,] 147 116 #> [193,] 148 117 #> [194,] 148 118 #> [195,] 149 119 #> [196,] 149 120 #> [197,] 150 121 #> [198,] 150 122 #> [199,] 151 123 #> [200,] 151 124 #> [201,] 152 125 #> [202,] 153 126 #> [203,] 153 127 #> [204,] 152 128 #> [205,] 151 129 #> [206,] 151 130 #> [207,] 150 131 #> [208,] 149 132 #> [209,] 149 133 #> [210,] 149 134 #> [211,] 148 135 #> [212,] 147 136 #> [213,] 147 137 #> [214,] 146 138 #> [215,] 145 139 #> [216,] 145 140 #> [217,] 145 141 #> [218,] 144 142 #> [219,] 143 143 #> [220,] 143 144 #> [221,] 142 145 #> [222,] 141 146 #> [223,] 141 147 #> [224,] 141 148 #> [225,] 140 149 #> [226,] 139 150 #> [227,] 139 151 #> [228,] 138 152 #> [229,] 137 153 #> [230,] 137 154 #> [231,] 137 155 #> [232,] 136 156 #> [233,] 135 157 #> [234,] 135 158 #> [235,] 134 159 #> [236,] 133 160 #> [237,] 133 161 #> [238,] 133 162 #> [239,] 132 163 #> [240,] 131 164 #> [241,] 131 165 #> [242,] 130 166 #> [243,] 129 167 #> [244,] 129 168 #> [245,] 129 169 #> [246,] 128 170 #> [247,] 127 171 #> [248,] 127 172 #> [249,] 126 173 #> [250,] 125 174 #> [251,] 125 175 #> [252,] 125 176 #> [253,] 124 177 #> [254,] 123 178 #> [255,] 123 179 #> [256,] 122 180 #> [257,] 121 181 #> [258,] 121 182 #> [259,] 121 183 #> [260,] 120 184 #> [261,] 119 185 #> [262,] 119 186 #> [263,] 118 187 #> [264,] 117 188 #> [265,] 117 189 #> [266,] 117 190 #> [267,] 116 191 #> [268,] 115 192 #> [269,] 115 193 #> [270,] 114 194 #> [271,] 113 195 #> [272,] 113 196 #> [273,] 113 197 #> [274,] 112 198 #> [275,] 111 199 #> [276,] 111 200 #> [277,] 110 201 #> [278,] 109 202 #> [279,] 109 203 #> [280,] 109 204 #> [281,] 108 205 #> [282,] 107 206 #> [283,] 107 207 #> [284,] 106 208 #> [285,] 105 209 #> [286,] 105 210 #> [287,] 105 211 #> [288,] 106 212 #> [289,] 107 212 #> [290,] 108 212 #> [291,] 109 212 #> [292,] 110 212 #> [293,] 111 212 #> [294,] 112 212 #> [295,] 113 212 #> [296,] 114 212 #> [297,] 115 212 #> [298,] 116 212 #> [299,] 117 212 #> [300,] 118 212 #> [301,] 119 212 #> [302,] 120 212 #> [303,] 121 212 #> [304,] 122 212 #> [305,] 123 212 #> [306,] 124 212 #> [307,] 125 212 #> [308,] 126 212 #> [309,] 127 212 #> [310,] 128 212 #> [311,] 129 212 #> [312,] 130 212 #> [313,] 131 212 #> [314,] 132 212 #> [315,] 133 212 #> [316,] 134 212 #> [317,] 135 212 #> [318,] 136 212 #> [319,] 137 212 #> [320,] 138 212 #> [321,] 139 212 #> [322,] 140 212 #> [323,] 141 212 #> [324,] 142 212 #> [325,] 143 212 #> [326,] 144 212 #> [327,] 145 212 #> [328,] 146 212 #> [329,] 147 212 #> [330,] 148 212 #> [331,] 149 212 #> [332,] 150 212 #> [333,] 151 212 #> [334,] 152 212 #> [335,] 153 212 #> [336,] 154 212 #> [337,] 155 212 #> [338,] 156 212 #> [339,] 157 212 #> [340,] 158 212 #> [341,] 159 212 #> [342,] 160 212 #> [343,] 161 212 #> [344,] 162 212 #> [345,] 163 212 #> [346,] 164 212 #> [347,] 165 212 #> [348,] 166 212 #> [349,] 167 212 #> [350,] 168 212 #> [351,] 169 212 #> [352,] 170 212 #> [353,] 171 212 #> [354,] 172 212 #> [355,] 173 212 #> [356,] 174 212 #> [357,] 175 212 #> [358,] 176 212 #> [359,] 177 212 #> [360,] 178 212 #> [361,] 179 212 #> [362,] 180 211 #> [363,] 181 210 #> [364,] 181 209 #> [365,] 182 208 #> [366,] 182 207 #> [367,] 183 206 #> [368,] 184 205 #> [369,] 184 204 #> [370,] 185 203 #> [371,] 186 202 #> [372,] 186 201 #> [373,] 187 200 #> [374,] 188 199 #> [375,] 188 198 #> [376,] 189 197 #> [377,] 189 196 #> [378,] 190 195 #> [379,] 191 194 #> [380,] 191 193 #> [381,] 192 192 #> [382,] 192 191 #> [383,] 193 190 #> [384,] 194 189 #> [385,] 194 188 #> [386,] 195 187 #> [387,] 195 186 #> [388,] 196 185 #> [389,] 197 184 #> [390,] 197 183 #> [391,] 198 182 #> [392,] 198 181 #> [393,] 199 180 #> [394,] 200 179 #> [395,] 200 178 #> [396,] 201 177 #> [397,] 201 176 #> [398,] 202 175 #> [399,] 203 174 #> [400,] 203 173 #> [401,] 204 173 #> [402,] 204 174 #> [403,] 205 175 #> [404,] 205 176 #> [405,] 206 177 #> [406,] 206 178 #> [407,] 207 179 #> [408,] 207 180 #> [409,] 208 181 #> [410,] 209 182 #> [411,] 209 183 #> [412,] 210 184 #> [413,] 211 185 #> [414,] 211 186 #> [415,] 212 187 #> [416,] 212 188 #> [417,] 213 189 #> [418,] 214 190 #> [419,] 214 191 #> [420,] 214 192 #> [421,] 215 193 #> [422,] 216 194 #> [423,] 216 195 #> [424,] 217 196 #> [425,] 217 197 #> [426,] 218 198 #> [427,] 219 199 #> [428,] 219 200 #> [429,] 220 201 #> [430,] 221 202 #> [431,] 221 203 #> [432,] 222 204 #> [433,] 222 205 #> [434,] 223 206 #> [435,] 224 207 #> [436,] 224 208 #> [437,] 224 209 #> [438,] 225 210 #> [439,] 226 211 #> [440,] 227 212 #> [441,] 228 212 #> [442,] 229 212 #> [443,] 230 212 #> [444,] 231 212 #> [445,] 232 212 #> [446,] 233 212 #> [447,] 234 212 #> [448,] 235 212 #> [449,] 236 212 #> [450,] 237 212 #> [451,] 238 212 #> [452,] 239 212 #> [453,] 240 212 #> [454,] 241 212 #> [455,] 242 212 #> [456,] 243 212 #> [457,] 244 212 #> [458,] 245 212 #> [459,] 246 212 #> [460,] 247 212 #> [461,] 248 212 #> [462,] 249 212 #> [463,] 250 212 #> [464,] 251 212 #> [465,] 252 212 #> [466,] 253 212 #> [467,] 254 212 #> [468,] 255 212 #> [469,] 256 212 #> [470,] 257 212 #> [471,] 258 212 #> [472,] 259 212 #> [473,] 260 212 #> [474,] 261 212 #> [475,] 262 212 #> [476,] 263 212 #> [477,] 264 212 #> [478,] 265 212 #> [479,] 266 212 #> [480,] 267 212 #> [481,] 268 212 #> [482,] 269 212 #> [483,] 270 212 #> [484,] 271 212 #> [485,] 272 212 #> [486,] 273 212 #> [487,] 274 212 #> [488,] 275 212 #> [489,] 276 212 #> [490,] 277 212 #> [491,] 278 212 #> [492,] 279 212 #> [493,] 280 212 #> [494,] 281 212 #> [495,] 282 212 #> [496,] 283 212 #> [497,] 284 212 #> [498,] 285 212 #> [499,] 286 212 #> [500,] 287 212 #> [501,] 288 212 #> [502,] 289 212 #> [503,] 290 212 #> [504,] 291 212 #> [505,] 292 212 #> [506,] 293 212 #> [507,] 294 212 #> [508,] 295 212 #> [509,] 296 212 #> [510,] 297 212 #> [511,] 298 212 #> [512,] 299 212 #> [513,] 300 211 #> [514,] 299 210 #> [515,] 299 209 #> [516,] 298 208 #> [517,] 297 207 #> [518,] 297 206 #> [519,] 297 205 #> [520,] 296 204 #> [521,] 295 203 #> [522,] 295 202 #> [523,] 294 201 #> [524,] 293 200 #> [525,] 293 199 #> [526,] 292 198 #> [527,] 292 197 #> [528,] 291 196 #> [529,] 291 195 #> [530,] 290 194 #> [531,] 289 193 #> [532,] 289 192 #> [533,] 288 191 #> [534,] 288 190 #> [535,] 287 189 #> [536,] 287 188 #> [537,] 286 187 #> [538,] 285 186 #> [539,] 285 185 #> [540,] 284 184 #> [541,] 284 183 #> [542,] 283 182 #> [543,] 282 181 #> [544,] 282 180 #> [545,] 282 179 #> [546,] 281 178 #> [547,] 280 177 #> [548,] 280 176 #> [549,] 279 175 #> [550,] 278 174 #> [551,] 278 173 #> [552,] 278 172 #> [553,] 277 171 #> [554,] 276 170 #> [555,] 276 169 #> [556,] 275 168 #> [557,] 274 167 #> [558,] 274 166 #> [559,] 274 165 #> [560,] 273 164 #> [561,] 272 163 #> [562,] 272 162 #> [563,] 271 161 #> [564,] 270 160 #> [565,] 270 159 #> [566,] 269 158 #> [567,] 269 157 #> [568,] 268 156 #> [569,] 268 155 #> [570,] 267 154 #> [571,] 266 153 #> [572,] 266 152 #> [573,] 265 151 #> [574,] 265 150 #> [575,] 264 149 #> [576,] 264 148 #> [577,] 263 147 #> [578,] 262 146 #> [579,] 262 145 #> [580,] 261 144 #> [581,] 261 143 #> [582,] 260 142 #> [583,] 259 141 #> [584,] 259 140 #> [585,] 259 139 #> [586,] 258 138 #> [587,] 257 137 #> [588,] 257 136 #> [589,] 256 135 #> [590,] 255 134 #> [591,] 255 133 #> [592,] 255 132 #> [593,] 254 131 #> [594,] 253 130 #> [595,] 253 129 #> [596,] 252 128 #> [597,] 251 127 #> [598,] 251 126 #> [599,] 252 125 #> [600,] 253 124 #> [601,] 253 123 #> [602,] 253 122 #> [603,] 254 121 #> [604,] 255 120 #> [605,] 255 119 #> [606,] 256 118 #> [607,] 257 117 #> [608,] 257 116 #> [609,] 257 115 #> [610,] 258 114 #> [611,] 259 113 #> [612,] 259 112 #> [613,] 260 111 #> [614,] 260 110 #> [615,] 261 109 #> [616,] 262 108 #> [617,] 262 107 #> [618,] 263 106 #> [619,] 263 105 #> [620,] 264 104 #> [621,] 264 103 #> [622,] 265 102 #> [623,] 266 101 #> [624,] 266 100 #> [625,] 267 99 #> [626,] 267 98 #> [627,] 268 97 #> [628,] 268 96 #> [629,] 269 95 #> [630,] 270 94 #> [631,] 270 93 #> [632,] 271 92 #> [633,] 272 91 #> [634,] 272 90 #> [635,] 272 89 #> [636,] 273 88 #> [637,] 274 87 #> [638,] 274 86 #> [639,] 275 85 #> [640,] 276 84 #> [641,] 276 83 #> [642,] 276 82 #> [643,] 277 81 #> [644,] 278 80 #> [645,] 278 79 #> [646,] 279 78 #> [647,] 279 77 #> [648,] 280 76 #> [649,] 281 75 #> [650,] 281 74 #> [651,] 282 73 #> [652,] 282 72 #> [653,] 283 71 #> [654,] 283 70 #> [655,] 284 69 #> [656,] 285 68 #> [657,] 285 67 #> [658,] 286 66 #> [659,] 286 65 #> [660,] 287 64 #> [661,] 287 63 #> [662,] 288 62 #> [663,] 289 61 #> [664,] 289 60 #> [665,] 290 59 #> [666,] 291 58 #> [667,] 291 57 #> [668,] 291 56 #> [669,] 292 55 #> [670,] 293 54 #> [671,] 293 53 #> [672,] 294 52 #> [673,] 295 51 #> [674,] 295 50 #> [675,] 295 49 #> [676,] 296 48 #> [677,] 297 47 #> [678,] 297 46 #> [679,] 298 45 #> [680,] 299 44 #> [681,] 299 43 #> [682,] 300 42 #> [683,] 300 41 #> [684,] 301 40 #> [685,] 301 39 #> [686,] 302 38 #> [687,] 301 37 #> [688,] 300 37 #> [689,] 299 37 #> [690,] 298 37 #> [691,] 297 37 #> [692,] 296 37 #> [693,] 295 37 #> [694,] 294 37 #> [695,] 293 37 #> [696,] 292 37 #> [697,] 291 37 #> [698,] 290 37 #> [699,] 289 37 #> [700,] 288 37 #> [701,] 287 37 #> [702,] 286 37 #> [703,] 285 37 #> [704,] 284 37 #> [705,] 283 37 #> [706,] 282 37 #> [707,] 281 37 #> [708,] 280 37 #> [709,] 279 37 #> [710,] 278 37 #> [711,] 277 37 #> [712,] 276 37 #> [713,] 275 37 #> [714,] 274 37 #> [715,] 273 37 #> [716,] 272 37 #> [717,] 271 37 #> [718,] 270 37 #> [719,] 269 37 #> [720,] 268 37 #> [721,] 267 37 #> [722,] 266 37 #> [723,] 265 37 #> [724,] 264 37 #> [725,] 263 37 #> [726,] 262 37 #> [727,] 261 37 #> [728,] 260 37 #> [729,] 259 37 #> [730,] 258 37 #> [731,] 257 37 #> [732,] 256 37 #> [733,] 255 37 #> [734,] 254 37 #> [735,] 253 37 #> [736,] 252 37 #> [737,] 251 37 #> [738,] 250 37 #> [739,] 249 37 #> [740,] 248 37 #> [741,] 247 37 #> [742,] 246 37 #> [743,] 245 37 #> [744,] 244 37 #> [745,] 243 37 #> [746,] 242 37 #> [747,] 241 37 #> [748,] 240 37 #> [749,] 239 37 #> [750,] 238 37 #> [751,] 237 37 #> [752,] 236 37 #> [753,] 235 37 #> [754,] 234 37 #> [755,] 233 37 #> [756,] 232 37 #> [757,] 231 37 #> [758,] 230 37 #> [759,] 229 37 #> [760,] 228 37 #> [761,] 227 37 #> [762,] 226 37 #> [763,] 225 38 #> [764,] 225 39 #> [765,] 224 40 #> [766,] 224 41 #> [767,] 223 42 #> [768,] 222 43 #> [769,] 222 44 #> [770,] 221 45 #> [771,] 221 46 #> [772,] 220 47 #> [773,] 219 48 #> [774,] 219 49 #> [775,] 218 50 #> [776,] 218 51 #> [777,] 217 52 #> [778,] 216 53 #> [779,] 216 54 #> [780,] 215 55 #> [781,] 214 56 #> [782,] 214 57 #> [783,] 213 58 #> [784,] 213 59 #> [785,] 212 60 #> [786,] 211 61 #> [787,] 211 62 #> [788,] 210 63 #> [789,] 210 64 #> [790,] 209 65 #> [791,] 208 66 #> [792,] 208 67 #> [793,] 207 68 #> [794,] 207 69 #> [795,] 206 70 #> [796,] 205 71 #> [797,] 205 72 #> [798,] 205 73 #> [799,] 204 74 #> [800,] 203 75 #> [801,] 203 76 #> [802,] 202 77 #> [803,] 202 78 #> [804,] 201 78 #> [805,] 201 77 #> [806,] 200 76 #> #> $corona #> [,1] [,2] #> [1,] 200 106 #> [2,] 199 105 #> [3,] 198 105 #> [4,] 197 106 #> [5,] 196 105 #> [6,] 195 105 #> [7,] 194 105 #> [8,] 193 106 #> [9,] 192 106 #> [10,] 191 106 #> [11,] 190 106 #> [12,] 189 106 #> [13,] 188 106 #> [14,] 187 106 #> [15,] 186 106 #> [16,] 185 106 #> [17,] 184 106 #> [18,] 183 106 #> [19,] 182 106 #> [20,] 181 106 #> [21,] 180 106 #> [22,] 179 106 #> [23,] 178 106 #> [24,] 177 107 #> [25,] 176 107 #> [26,] 175 107 #> [27,] 174 107 #> [28,] 173 107 #> [29,] 172 107 #> [30,] 171 107 #> [31,] 170 107 #> [32,] 169 107 #> [33,] 168 108 #> [34,] 167 108 #> [35,] 166 108 #> [36,] 165 108 #> [37,] 164 108 #> [38,] 163 107 #> [39,] 162 107 #> [40,] 161 106 #> [41,] 160 105 #> [42,] 160 104 #> [43,] 159 103 #> [44,] 158 102 #> [45,] 157 101 #> [46,] 156 100 #> [47,] 156 99 #> [48,] 155 98 #> [49,] 154 97 #> [50,] 153 96 #> [51,] 153 95 #> [52,] 152 94 #> [53,] 151 93 #> [54,] 150 92 #> [55,] 149 91 #> [56,] 148 90 #> [57,] 147 89 #> [58,] 146 88 #> [59,] 145 87 #> [60,] 144 86 #> [61,] 143 85 #> [62,] 142 85 #> [63,] 141 84 #> [64,] 140 83 #> [65,] 139 83 #> [66,] 138 82 #> [67,] 137 81 #> [68,] 136 80 #> [69,] 135 79 #> [70,] 134 79 #> [71,] 133 78 #> [72,] 132 77 #> [73,] 131 76 #> [74,] 130 75 #> [75,] 129 74 #> [76,] 128 73 #> [77,] 128 72 #> [78,] 127 71 #> [79,] 126 70 #> [80,] 125 69 #> [81,] 125 68 #> [82,] 124 67 #> [83,] 124 66 #> [84,] 124 65 #> [85,] 123 64 #> [86,] 123 63 #> [87,] 123 62 #> [88,] 123 61 #> [89,] 122 60 #> [90,] 122 59 #> [91,] 122 58 #> [92,] 122 57 #> [93,] 122 56 #> [94,] 123 55 #> [95,] 124 54 #> [96,] 125 53 #> [97,] 126 52 #> [98,] 127 52 #> [99,] 128 51 #> [100,] 129 50 #> [101,] 129 49 #> [102,] 129 48 #> [103,] 128 47 #> [104,] 127 46 #> [105,] 126 46 #> [106,] 125 45 #> [107,] 124 45 #> [108,] 123 45 #> [109,] 122 45 #> [110,] 121 45 #> [111,] 120 45 #> [112,] 119 45 #> [113,] 118 45 #> [114,] 117 45 #> [115,] 116 45 #> [116,] 115 45 #> [117,] 114 45 #> [118,] 113 46 #> [119,] 112 46 #> [120,] 111 47 #> [121,] 110 48 #> [122,] 110 49 #> [123,] 110 50 #> [124,] 109 51 #> [125,] 109 52 #> [126,] 109 53 #> [127,] 109 54 #> [128,] 109 55 #> [129,] 109 56 #> [130,] 109 57 #> [131,] 109 58 #> [132,] 109 59 #> [133,] 109 60 #> [134,] 109 61 #> [135,] 109 62 #> [136,] 109 63 #> [137,] 109 64 #> [138,] 109 65 #> [139,] 109 66 #> [140,] 109 67 #> [141,] 109 68 #> [142,] 109 69 #> [143,] 109 70 #> [144,] 109 71 #> [145,] 109 72 #> [146,] 109 73 #> [147,] 109 74 #> [148,] 109 75 #> [149,] 109 76 #> [150,] 109 77 #> [151,] 109 78 #> [152,] 110 79 #> [153,] 111 80 #> [154,] 112 81 #> [155,] 113 82 #> [156,] 114 83 #> [157,] 115 84 #> [158,] 116 85 #> [159,] 117 86 #> [160,] 118 87 #> [161,] 119 88 #> [162,] 120 89 #> [163,] 121 90 #> [164,] 122 91 #> [165,] 122 92 #> [166,] 123 93 #> [167,] 124 94 #> [168,] 125 95 #> [169,] 125 96 #> [170,] 125 97 #> [171,] 126 98 #> [172,] 125 99 #> [173,] 126 100 #> [174,] 126 101 #> [175,] 125 101 #> [176,] 125 100 #> [177,] 124 99 #> [178,] 124 98 #> [179,] 123 97 #> [180,] 123 96 #> [181,] 122 95 #> [182,] 121 94 #> [183,] 120 93 #> [184,] 119 92 #> [185,] 118 91 #> [186,] 117 90 #> [187,] 116 89 #> [188,] 115 88 #> [189,] 114 87 #> [190,] 113 87 #> [191,] 112 86 #> [192,] 111 85 #> [193,] 110 85 #> [194,] 109 84 #> [195,] 108 84 #> [196,] 107 84 #> [197,] 106 83 #> [198,] 105 83 #> [199,] 104 82 #> [200,] 103 83 #> [201,] 103 84 #> [202,] 103 85 #> [203,] 104 86 #> [204,] 105 87 #> [205,] 106 88 #> [206,] 107 89 #> [207,] 108 90 #> [208,] 109 91 #> [209,] 110 92 #> [210,] 111 93 #> [211,] 111 94 #> [212,] 112 95 #> [213,] 112 96 #> [214,] 112 97 #> [215,] 113 98 #> [216,] 113 99 #> [217,] 113 100 #> [218,] 113 101 #> [219,] 114 102 #> [220,] 114 103 #> [221,] 114 104 #> [222,] 114 105 #> [223,] 114 106 #> [224,] 114 107 #> [225,] 115 108 #> [226,] 115 109 #> [227,] 114 110 #> [228,] 115 111 #> [229,] 115 112 #> [230,] 115 113 #> [231,] 115 114 #> [232,] 115 115 #> [233,] 115 116 #> [234,] 115 117 #> [235,] 116 118 #> [236,] 116 119 #> [237,] 116 120 #> [238,] 116 121 #> [239,] 116 122 #> [240,] 116 123 #> [241,] 115 124 #> [242,] 115 125 #> [243,] 115 126 #> [244,] 115 127 #> [245,] 115 128 #> [246,] 115 129 #> [247,] 115 130 #> [248,] 115 131 #> [249,] 115 132 #> [250,] 116 133 #> [251,] 115 134 #> [252,] 116 135 #> [253,] 116 136 #> [254,] 116 137 #> [255,] 117 138 #> [256,] 117 139 #> [257,] 117 140 #> [258,] 118 141 #> [259,] 118 142 #> [260,] 118 143 #> [261,] 119 144 #> [262,] 120 145 #> [263,] 120 146 #> [264,] 121 147 #> [265,] 121 148 #> [266,] 122 149 #> [267,] 123 150 #> [268,] 123 151 #> [269,] 124 152 #> [270,] 125 153 #> [271,] 126 154 #> [272,] 127 155 #> [273,] 128 156 #> [274,] 129 157 #> [275,] 130 158 #> [276,] 131 159 #> [277,] 132 160 #> [278,] 133 161 #> [279,] 134 161 #> [280,] 135 162 #> [281,] 136 162 #> [282,] 137 162 #> [283,] 138 163 #> [284,] 139 163 #> [285,] 140 163 #> [286,] 141 163 #> [287,] 142 164 #> [288,] 143 164 #> [289,] 144 164 #> [290,] 145 164 #> [291,] 146 164 #> [292,] 147 164 #> [293,] 148 165 #> [294,] 149 165 #> [295,] 150 165 #> [296,] 151 165 #> [297,] 152 165 #> [298,] 153 165 #> [299,] 154 166 #> [300,] 155 166 #> [301,] 156 165 #> [302,] 157 165 #> [303,] 158 165 #> [304,] 159 165 #> [305,] 160 166 #> [306,] 161 166 #> [307,] 162 166 #> [308,] 163 166 #> [309,] 164 166 #> [310,] 165 166 #> [311,] 166 166 #> [312,] 167 166 #> [313,] 168 166 #> [314,] 169 166 #> [315,] 170 166 #> [316,] 171 166 #> [317,] 172 166 #> [318,] 173 166 #> [319,] 174 166 #> [320,] 175 166 #> [321,] 176 166 #> [322,] 177 166 #> [323,] 178 166 #> [324,] 179 166 #> [325,] 180 166 #> [326,] 181 166 #> [327,] 182 166 #> [328,] 183 166 #> [329,] 184 166 #> [330,] 185 166 #> [331,] 186 166 #> [332,] 187 166 #> [333,] 188 166 #> [334,] 189 165 #> [335,] 190 165 #> [336,] 191 165 #> [337,] 192 165 #> [338,] 193 165 #> [339,] 194 165 #> [340,] 195 165 #> [341,] 196 165 #> [342,] 197 165 #> [343,] 198 165 #> [344,] 199 165 #> [345,] 200 165 #> [346,] 201 165 #> [347,] 202 165 #> [348,] 203 165 #> [349,] 204 165 #> [350,] 205 165 #> [351,] 206 166 #> [352,] 207 166 #> [353,] 208 166 #> [354,] 209 166 #> [355,] 210 166 #> [356,] 211 166 #> [357,] 212 166 #> [358,] 213 166 #> [359,] 214 166 #> [360,] 215 167 #> [361,] 216 167 #> [362,] 217 167 #> [363,] 218 167 #> [364,] 219 167 #> [365,] 220 168 #> [366,] 221 168 #> [367,] 222 168 #> [368,] 223 169 #> [369,] 224 169 #> [370,] 225 169 #> [371,] 226 170 #> [372,] 227 170 #> [373,] 228 171 #> [374,] 229 171 #> [375,] 230 172 #> [376,] 231 172 #> [377,] 232 173 #> [378,] 233 174 #> [379,] 234 174 #> [380,] 235 175 #> [381,] 236 176 #> [382,] 237 177 #> [383,] 238 178 #> [384,] 238 179 #> [385,] 239 180 #> [386,] 240 181 #> [387,] 241 182 #> [388,] 241 183 #> [389,] 242 184 #> [390,] 243 185 #> [391,] 243 186 #> [392,] 244 187 #> [393,] 245 188 #> [394,] 245 189 #> [395,] 246 190 #> [396,] 246 191 #> [397,] 247 192 #> [398,] 247 193 #> [399,] 248 194 #> [400,] 249 195 #> [401,] 249 196 #> [402,] 250 197 #> [403,] 250 198 #> [404,] 251 199 #> [405,] 251 200 #> [406,] 251 201 #> [407,] 252 202 #> [408,] 252 203 #> [409,] 253 204 #> [410,] 253 205 #> [411,] 254 206 #> [412,] 254 207 #> [413,] 254 208 #> [414,] 255 209 #> [415,] 255 210 #> [416,] 256 211 #> [417,] 256 212 #> [418,] 256 213 #> [419,] 257 214 #> [420,] 257 215 #> [421,] 257 216 #> [422,] 258 217 #> [423,] 258 218 #> [424,] 259 219 #> [425,] 260 220 #> [426,] 261 221 #> [427,] 262 222 #> [428,] 263 223 #> [429,] 264 224 #> [430,] 265 225 #> [431,] 266 225 #> [432,] 267 226 #> [433,] 268 226 #> [434,] 269 226 #> [435,] 270 227 #> [436,] 271 227 #> [437,] 272 227 #> [438,] 273 227 #> [439,] 274 227 #> [440,] 275 227 #> [441,] 276 227 #> [442,] 277 227 #> [443,] 278 227 #> [444,] 279 228 #> [445,] 280 227 #> [446,] 281 227 #> [447,] 282 227 #> [448,] 283 227 #> [449,] 284 226 #> [450,] 285 226 #> [451,] 286 225 #> [452,] 287 224 #> [453,] 288 224 #> [454,] 289 223 #> [455,] 290 222 #> [456,] 291 221 #> [457,] 292 220 #> [458,] 293 219 #> [459,] 294 218 #> [460,] 295 217 #> [461,] 295 216 #> [462,] 296 215 #> [463,] 297 215 #> [464,] 298 214 #> [465,] 299 214 #> [466,] 300 214 #> [467,] 301 214 #> [468,] 302 214 #> [469,] 303 214 #> [470,] 304 214 #> [471,] 305 214 #> [472,] 306 214 #> [473,] 307 214 #> [474,] 308 214 #> [475,] 309 214 #> [476,] 310 214 #> [477,] 311 214 #> [478,] 312 214 #> [479,] 313 214 #> [480,] 314 214 #> [481,] 315 213 #> [482,] 315 212 #> [483,] 316 211 #> [484,] 316 210 #> [485,] 316 209 #> [486,] 316 208 #> [487,] 316 207 #> [488,] 315 206 #> [489,] 316 205 #> [490,] 315 204 #> [491,] 316 203 #> [492,] 316 202 #> [493,] 316 201 #> [494,] 316 200 #> [495,] 316 199 #> [496,] 316 198 #> [497,] 316 197 #> [498,] 316 196 #> [499,] 315 195 #> [500,] 315 194 #> [501,] 314 193 #> [502,] 314 192 #> [503,] 313 191 #> [504,] 312 191 #> [505,] 311 190 #> [506,] 310 190 #> [507,] 309 189 #> [508,] 308 189 #> [509,] 307 189 #> [510,] 306 189 #> [511,] 305 189 #> [512,] 304 188 #> [513,] 303 188 #> [514,] 302 188 #> [515,] 301 188 #> [516,] 300 188 #> [517,] 299 188 #> [518,] 298 188 #> [519,] 297 188 #> [520,] 296 188 #> [521,] 295 188 #> [522,] 294 188 #> [523,] 293 187 #> [524,] 292 187 #> [525,] 291 186 #> [526,] 291 185 #> [527,] 291 184 #> [528,] 290 183 #> [529,] 290 182 #> [530,] 290 181 #> [531,] 289 180 #> [532,] 289 179 #> [533,] 288 178 #> [534,] 288 177 #> [535,] 288 176 #> [536,] 287 175 #> [537,] 287 174 #> [538,] 286 173 #> [539,] 286 172 #> [540,] 286 171 #> [541,] 285 170 #> [542,] 285 169 #> [543,] 284 168 #> [544,] 284 167 #> [545,] 284 166 #> [546,] 283 165 #> [547,] 283 164 #> [548,] 282 163 #> [549,] 282 162 #> [550,] 282 161 #> [551,] 281 160 #> [552,] 281 159 #> [553,] 280 158 #> [554,] 280 157 #> [555,] 280 156 #> [556,] 279 155 #> [557,] 279 154 #> [558,] 278 153 #> [559,] 278 152 #> [560,] 278 151 #> [561,] 277 150 #> [562,] 278 149 #> [563,] 277 148 #> [564,] 277 147 #> [565,] 277 146 #> [566,] 277 145 #> [567,] 277 144 #> [568,] 276 143 #> [569,] 276 142 #> [570,] 277 141 #> [571,] 276 140 #> [572,] 276 139 #> [573,] 276 138 #> [574,] 276 137 #> [575,] 276 136 #> [576,] 275 135 #> [577,] 276 134 #> [578,] 275 133 #> [579,] 275 132 #> [580,] 275 131 #> [581,] 275 130 #> [582,] 274 129 #> [583,] 274 128 #> [584,] 274 127 #> [585,] 274 126 #> [586,] 274 125 #> [587,] 273 124 #> [588,] 273 123 #> [589,] 273 122 #> [590,] 272 121 #> [591,] 272 120 #> [592,] 272 119 #> [593,] 271 118 #> [594,] 271 117 #> [595,] 270 116 #> [596,] 269 115 #> [597,] 268 114 #> [598,] 268 113 #> [599,] 267 112 #> [600,] 267 111 #> [601,] 267 110 #> [602,] 267 109 #> [603,] 267 108 #> [604,] 267 107 #> [605,] 266 106 #> [606,] 266 105 #> [607,] 266 104 #> [608,] 266 103 #> [609,] 266 102 #> [610,] 266 101 #> [611,] 266 100 #> [612,] 266 99 #> [613,] 266 98 #> [614,] 266 97 #> [615,] 266 96 #> [616,] 266 95 #> [617,] 266 94 #> [618,] 266 93 #> [619,] 266 92 #> [620,] 266 91 #> [621,] 266 90 #> [622,] 266 89 #> [623,] 266 88 #> [624,] 266 87 #> [625,] 266 86 #> [626,] 266 85 #> [627,] 266 84 #> [628,] 266 83 #> [629,] 266 82 #> [630,] 266 81 #> [631,] 266 80 #> [632,] 266 79 #> [633,] 266 78 #> [634,] 267 77 #> [635,] 267 76 #> [636,] 267 75 #> [637,] 267 74 #> [638,] 267 73 #> [639,] 267 72 #> [640,] 267 71 #> [641,] 267 70 #> [642,] 267 69 #> [643,] 267 68 #> [644,] 268 67 #> [645,] 267 66 #> [646,] 268 65 #> [647,] 268 64 #> [648,] 269 63 #> [649,] 270 62 #> [650,] 271 62 #> [651,] 272 61 #> [652,] 273 61 #> [653,] 274 60 #> [654,] 275 60 #> [655,] 276 59 #> [656,] 277 58 #> [657,] 277 57 #> [658,] 277 56 #> [659,] 277 55 #> [660,] 276 54 #> [661,] 275 53 #> [662,] 274 53 #> [663,] 273 52 #> [664,] 272 52 #> [665,] 271 51 #> [666,] 270 51 #> [667,] 269 50 #> [668,] 268 50 #> [669,] 267 50 #> [670,] 266 50 #> [671,] 265 50 #> [672,] 264 50 #> [673,] 263 50 #> [674,] 262 50 #> [675,] 261 51 #> [676,] 260 52 #> [677,] 260 53 #> [678,] 260 54 #> [679,] 259 55 #> [680,] 259 56 #> [681,] 259 57 #> [682,] 259 58 #> [683,] 258 59 #> [684,] 258 60 #> [685,] 258 61 #> [686,] 258 62 #> [687,] 258 63 #> [688,] 257 64 #> [689,] 257 65 #> [690,] 257 66 #> [691,] 257 67 #> [692,] 256 68 #> [693,] 256 69 #> [694,] 256 70 #> [695,] 256 71 #> [696,] 255 72 #> [697,] 255 73 #> [698,] 255 74 #> [699,] 254 75 #> [700,] 254 76 #> [701,] 254 77 #> [702,] 253 78 #> [703,] 253 79 #> [704,] 252 80 #> [705,] 252 81 #> [706,] 252 82 #> [707,] 251 83 #> [708,] 251 84 #> [709,] 250 85 #> [710,] 250 86 #> [711,] 249 87 #> [712,] 249 88 #> [713,] 249 89 #> [714,] 248 90 #> [715,] 248 91 #> [716,] 247 92 #> [717,] 247 93 #> [718,] 247 94 #> [719,] 246 95 #> [720,] 246 96 #> [721,] 245 97 #> [722,] 245 98 #> [723,] 244 99 #> [724,] 243 100 #> [725,] 243 101 #> [726,] 242 102 #> [727,] 241 103 #> [728,] 240 104 #> [729,] 239 104 #> [730,] 238 104 #> [731,] 237 104 #> [732,] 236 105 #> [733,] 235 105 #> [734,] 234 105 #> [735,] 233 105 #> [736,] 232 105 #> [737,] 231 105 #> [738,] 230 105 #> [739,] 229 105 #> [740,] 228 105 #> [741,] 227 105 #> [742,] 226 105 #> [743,] 225 105 #> [744,] 224 105 #> [745,] 223 105 #> [746,] 222 105 #> [747,] 221 105 #> [748,] 220 105 #> [749,] 219 105 #> [750,] 218 105 #> [751,] 217 105 #> [752,] 216 105 #> [753,] 215 106 #> [754,] 214 106 #> [755,] 213 106 #> [756,] 212 106 #> [757,] 211 106 #> [758,] 210 106 #> [759,] 209 106 #> [760,] 208 106 #> [761,] 207 106 #> [762,] 206 106 #> [763,] 205 106 #> [764,] 204 106 #> [765,] 203 106 #> [766,] 202 106 #> [767,] 201 106 #> [768,] 200 106 #> #> $deusventrue #> [,1] [,2] #> [1,] 200 87 #> [2,] 199 86 #> [3,] 198 86 #> [4,] 197 87 #> [5,] 196 87 #> [6,] 195 87 #> [7,] 194 87 #> [8,] 193 87 #> [9,] 192 87 #> [10,] 191 87 #> [11,] 190 87 #> [12,] 189 87 #> [13,] 188 87 #> [14,] 187 87 #> [15,] 186 87 #> [16,] 185 87 #> [17,] 184 87 #> [18,] 183 87 #> [19,] 182 87 #> [20,] 181 87 #> [21,] 180 87 #> [22,] 179 87 #> [23,] 178 87 #> [24,] 177 87 #> [25,] 176 87 #> [26,] 175 87 #> [27,] 174 87 #> [28,] 173 87 #> [29,] 172 87 #> [30,] 171 87 #> [31,] 170 87 #> [32,] 169 87 #> [33,] 168 87 #> [34,] 167 87 #> [35,] 166 87 #> [36,] 165 87 #> [37,] 164 87 #> [38,] 163 87 #> [39,] 162 88 #> [40,] 161 88 #> [41,] 160 88 #> [42,] 159 88 #> [43,] 158 88 #> [44,] 157 88 #> [45,] 156 89 #> [46,] 155 89 #> [47,] 154 89 #> [48,] 153 90 #> [49,] 153 91 #> [50,] 152 92 #> [51,] 152 93 #> [52,] 152 94 #> [53,] 151 95 #> [54,] 151 96 #> [55,] 151 97 #> [56,] 151 98 #> [57,] 150 99 #> [58,] 151 100 #> [59,] 151 101 #> [60,] 151 102 #> [61,] 151 103 #> [62,] 151 104 #> [63,] 150 105 #> [64,] 151 106 #> [65,] 151 107 #> [66,] 151 108 #> [67,] 151 109 #> [68,] 152 110 #> [69,] 151 111 #> [70,] 150 111 #> [71,] 149 112 #> [72,] 148 113 #> [73,] 147 113 #> [74,] 146 113 #> [75,] 145 114 #> [76,] 144 115 #> [77,] 143 115 #> [78,] 142 115 #> [79,] 141 116 #> [80,] 140 116 #> [81,] 139 117 #> [82,] 138 117 #> [83,] 137 117 #> [84,] 136 118 #> [85,] 135 118 #> [86,] 134 119 #> [87,] 133 119 #> [88,] 132 119 #> [89,] 131 119 #> [90,] 130 120 #> [91,] 129 120 #> [92,] 128 120 #> [93,] 127 120 #> [94,] 126 120 #> [95,] 125 120 #> [96,] 124 120 #> [97,] 123 120 #> [98,] 122 120 #> [99,] 121 120 #> [100,] 120 120 #> [101,] 119 119 #> [102,] 118 119 #> [103,] 117 119 #> [104,] 116 119 #> [105,] 115 118 #> [106,] 114 118 #> [107,] 113 118 #> [108,] 112 118 #> [109,] 111 117 #> [110,] 110 117 #> [111,] 109 117 #> [112,] 108 116 #> [113,] 107 116 #> [114,] 106 115 #> [115,] 105 114 #> [116,] 104 114 #> [117,] 103 113 #> [118,] 102 113 #> [119,] 101 112 #> [120,] 100 111 #> [121,] 99 110 #> [122,] 98 109 #> [123,] 97 109 #> [124,] 96 108 #> [125,] 95 107 #> [126,] 94 106 #> [127,] 93 105 #> [128,] 92 104 #> [129,] 91 103 #> [130,] 90 102 #> [131,] 89 101 #> [132,] 88 100 #> [133,] 87 100 #> [134,] 86 99 #> [135,] 85 98 #> [136,] 84 97 #> [137,] 83 96 #> [138,] 82 95 #> [139,] 81 94 #> [140,] 80 93 #> [141,] 79 92 #> [142,] 78 91 #> [143,] 77 90 #> [144,] 76 89 #> [145,] 75 88 #> [146,] 74 88 #> [147,] 73 87 #> [148,] 72 86 #> [149,] 71 85 #> [150,] 70 84 #> [151,] 69 83 #> [152,] 68 83 #> [153,] 67 82 #> [154,] 66 81 #> [155,] 65 81 #> [156,] 64 80 #> [157,] 63 79 #> [158,] 62 79 #> [159,] 61 78 #> [160,] 60 78 #> [161,] 59 78 #> [162,] 58 77 #> [163,] 57 78 #> [164,] 56 78 #> [165,] 55 79 #> [166,] 54 80 #> [167,] 53 81 #> [168,] 53 82 #> [169,] 52 83 #> [170,] 52 84 #> [171,] 51 85 #> [172,] 51 86 #> [173,] 51 87 #> [174,] 51 88 #> [175,] 51 89 #> [176,] 50 90 #> [177,] 50 91 #> [178,] 50 92 #> [179,] 50 93 #> [180,] 50 94 #> [181,] 49 95 #> [182,] 49 96 #> [183,] 49 97 #> [184,] 50 98 #> [185,] 50 99 #> [186,] 50 100 #> [187,] 50 101 #> [188,] 50 102 #> [189,] 50 103 #> [190,] 50 104 #> [191,] 50 105 #> [192,] 50 106 #> [193,] 50 107 #> [194,] 50 108 #> [195,] 49 109 #> [196,] 50 110 #> [197,] 50 111 #> [198,] 50 112 #> [199,] 50 113 #> [200,] 50 114 #> [201,] 50 115 #> [202,] 50 116 #> [203,] 50 117 #> [204,] 51 118 #> [205,] 50 119 #> [206,] 51 120 #> [207,] 51 121 #> [208,] 51 122 #> [209,] 51 123 #> [210,] 51 124 #> [211,] 52 125 #> [212,] 52 126 #> [213,] 52 127 #> [214,] 53 128 #> [215,] 53 129 #> [216,] 54 130 #> [217,] 55 131 #> [218,] 55 132 #> [219,] 55 133 #> [220,] 54 134 #> [221,] 54 135 #> [222,] 53 136 #> [223,] 52 137 #> [224,] 52 138 #> [225,] 51 139 #> [226,] 50 140 #> [227,] 50 141 #> [228,] 49 142 #> [229,] 49 143 #> [230,] 48 144 #> [231,] 47 145 #> [232,] 47 146 #> [233,] 47 147 #> [234,] 46 148 #> [235,] 46 149 #> [236,] 45 150 #> [237,] 45 151 #> [238,] 45 152 #> [239,] 44 153 #> [240,] 44 154 #> [241,] 43 155 #> [242,] 43 156 #> [243,] 43 157 #> [244,] 42 158 #> [245,] 42 159 #> [246,] 42 160 #> [247,] 42 161 #> [248,] 41 162 #> [249,] 41 163 #> [250,] 41 164 #> [251,] 40 165 #> [252,] 40 166 #> [253,] 40 167 #> [254,] 40 168 #> [255,] 40 169 #> [256,] 39 170 #> [257,] 39 171 #> [258,] 39 172 #> [259,] 39 173 #> [260,] 39 174 #> [261,] 38 175 #> [262,] 39 176 #> [263,] 39 177 #> [264,] 39 178 #> [265,] 39 179 #> [266,] 39 180 #> [267,] 38 181 #> [268,] 39 182 #> [269,] 39 183 #> [270,] 39 184 #> [271,] 39 185 #> [272,] 40 186 #> [273,] 41 187 #> [274,] 42 188 #> [275,] 43 189 #> [276,] 44 190 #> [277,] 45 190 #> [278,] 46 190 #> [279,] 47 190 #> [280,] 48 190 #> [281,] 49 190 #> [282,] 50 190 #> [283,] 51 190 #> [284,] 52 190 #> [285,] 53 190 #> [286,] 54 189 #> [287,] 55 189 #> [288,] 56 189 #> [289,] 57 188 #> [290,] 58 188 #> [291,] 59 188 #> [292,] 60 187 #> [293,] 61 187 #> [294,] 62 186 #> [295,] 63 186 #> [296,] 64 185 #> [297,] 65 185 #> [298,] 66 184 #> [299,] 67 184 #> [300,] 68 183 #> [301,] 69 183 #> [302,] 70 182 #> [303,] 71 182 #> [304,] 72 181 #> [305,] 73 180 #> [306,] 74 180 #> [307,] 75 179 #> [308,] 76 179 #> [309,] 77 178 #> [310,] 78 177 #> [311,] 79 177 #> [312,] 80 176 #> [313,] 81 176 #> [314,] 82 175 #> [315,] 83 174 #> [316,] 84 174 #> [317,] 85 173 #> [318,] 86 173 #> [319,] 87 172 #> [320,] 88 171 #> [321,] 89 171 #> [322,] 90 170 #> [323,] 91 170 #> [324,] 92 169 #> [325,] 93 168 #> [326,] 94 168 #> [327,] 95 167 #> [328,] 96 166 #> [329,] 97 166 #> [330,] 98 165 #> [331,] 99 165 #> [332,] 100 164 #> [333,] 101 164 #> [334,] 102 163 #> [335,] 103 162 #> [336,] 104 162 #> [337,] 105 162 #> [338,] 106 161 #> [339,] 107 161 #> [340,] 108 160 #> [341,] 109 160 #> [342,] 110 160 #> [343,] 111 159 #> [344,] 112 159 #> [345,] 113 159 #> [346,] 114 158 #> [347,] 115 158 #> [348,] 116 158 #> [349,] 117 158 #> [350,] 118 157 #> [351,] 119 157 #> [352,] 120 157 #> [353,] 121 157 #> [354,] 122 157 #> [355,] 123 156 #> [356,] 124 157 #> [357,] 125 156 #> [358,] 126 157 #> [359,] 127 157 #> [360,] 128 157 #> [361,] 129 157 #> [362,] 130 158 #> [363,] 131 158 #> [364,] 132 158 #> [365,] 133 159 #> [366,] 134 159 #> [367,] 135 160 #> [368,] 136 160 #> [369,] 137 161 #> [370,] 138 161 #> [371,] 139 162 #> [372,] 140 162 #> [373,] 141 163 #> [374,] 142 164 #> [375,] 143 164 #> [376,] 144 165 #> [377,] 145 165 #> [378,] 146 166 #> [379,] 147 166 #> [380,] 148 167 #> [381,] 149 167 #> [382,] 150 168 #> [383,] 151 168 #> [384,] 152 169 #> [385,] 153 169 #> [386,] 154 170 #> [387,] 155 170 #> [388,] 156 171 #> [389,] 157 171 #> [390,] 158 172 #> [391,] 159 172 #> [392,] 160 173 #> [393,] 161 173 #> [394,] 162 174 #> [395,] 163 174 #> [396,] 164 174 #> [397,] 165 175 #> [398,] 166 175 #> [399,] 167 175 #> [400,] 168 176 #> [401,] 169 176 #> [402,] 168 177 #> [403,] 168 178 #> [404,] 167 179 #> [405,] 166 180 #> [406,] 165 181 #> [407,] 165 182 #> [408,] 164 183 #> [409,] 163 184 #> [410,] 162 185 #> [411,] 161 186 #> [412,] 160 187 #> [413,] 159 188 #> [414,] 159 189 #> [415,] 158 190 #> [416,] 157 191 #> [417,] 156 192 #> [418,] 155 193 #> [419,] 154 194 #> [420,] 153 195 #> [421,] 152 196 #> [422,] 151 197 #> [423,] 150 198 #> [424,] 149 199 #> [425,] 148 200 #> [426,] 147 201 #> [427,] 146 202 #> [428,] 145 203 #> [429,] 144 204 #> [430,] 143 205 #> [431,] 142 206 #> [432,] 142 207 #> [433,] 141 208 #> [434,] 140 209 #> [435,] 139 210 #> [436,] 138 211 #> [437,] 138 212 #> [438,] 137 213 #> [439,] 137 214 #> [440,] 137 215 #> [441,] 137 216 #> [442,] 138 217 #> [443,] 139 218 #> [444,] 140 218 #> [445,] 141 219 #> [446,] 142 219 #> [447,] 143 219 #> [448,] 144 219 #> [449,] 145 219 #> [450,] 146 220 #> [451,] 147 220 #> [452,] 148 220 #> [453,] 149 220 #> [454,] 150 220 #> [455,] 151 220 #> [456,] 152 220 #> [457,] 153 221 #> [458,] 154 220 #> [459,] 155 221 #> [460,] 156 221 #> [461,] 157 221 #> [462,] 158 221 #> [463,] 159 221 #> [464,] 160 221 #> [465,] 161 221 #> [466,] 162 221 #> [467,] 163 222 #> [468,] 164 221 #> [469,] 165 221 #> [470,] 166 221 #> [471,] 167 221 #> [472,] 168 221 #> [473,] 169 221 #> [474,] 170 221 #> [475,] 171 221 #> [476,] 172 221 #> [477,] 173 222 #> [478,] 174 222 #> [479,] 175 222 #> [480,] 176 222 #> [481,] 177 222 #> [482,] 178 222 #> [483,] 179 222 #> [484,] 180 222 #> [485,] 181 222 #> [486,] 182 222 #> [487,] 183 222 #> [488,] 184 222 #> [489,] 185 222 #> [490,] 186 222 #> [491,] 187 222 #> [492,] 188 222 #> [493,] 189 222 #> [494,] 190 222 #> [495,] 191 222 #> [496,] 192 222 #> [497,] 193 222 #> [498,] 194 222 #> [499,] 195 222 #> [500,] 196 222 #> [501,] 197 222 #> [502,] 198 222 #> [503,] 199 222 #> [504,] 200 222 #> [505,] 201 222 #> [506,] 202 222 #> [507,] 203 222 #> [508,] 204 222 #> [509,] 205 222 #> [510,] 206 222 #> [511,] 207 222 #> [512,] 208 221 #> [513,] 209 221 #> [514,] 210 221 #> [515,] 211 221 #> [516,] 212 221 #> [517,] 213 221 #> [518,] 214 221 #> [519,] 215 221 #> [520,] 216 221 #> [521,] 217 221 #> [522,] 218 221 #> [523,] 219 221 #> [524,] 220 221 #> [525,] 221 221 #> [526,] 222 221 #> [527,] 223 221 #> [528,] 224 221 #> [529,] 225 221 #> [530,] 226 221 #> [531,] 227 221 #> [532,] 228 221 #> [533,] 229 221 #> [534,] 230 220 #> [535,] 231 220 #> [536,] 232 220 #> [537,] 233 220 #> [538,] 234 220 #> [539,] 235 220 #> [540,] 236 220 #> [541,] 237 220 #> [542,] 238 220 #> [543,] 239 220 #> [544,] 240 220 #> [545,] 241 220 #> [546,] 242 219 #> [547,] 243 219 #> [548,] 244 219 #> [549,] 245 219 #> [550,] 246 219 #> [551,] 247 219 #> [552,] 248 219 #> [553,] 249 218 #> [554,] 250 218 #> [555,] 251 218 #> [556,] 252 218 #> [557,] 253 218 #> [558,] 254 218 #> [559,] 255 218 #> [560,] 256 217 #> [561,] 257 217 #> [562,] 258 217 #> [563,] 259 217 #> [564,] 260 216 #> [565,] 261 216 #> [566,] 262 216 #> [567,] 263 216 #> [568,] 264 215 #> [569,] 265 215 #> [570,] 266 215 #> [571,] 267 215 #> [572,] 268 214 #> [573,] 269 214 #> [574,] 270 214 #> [575,] 271 213 #> [576,] 272 213 #> [577,] 273 213 #> [578,] 274 212 #> [579,] 275 212 #> [580,] 276 212 #> [581,] 277 211 #> [582,] 278 211 #> [583,] 279 210 #> [584,] 280 210 #> [585,] 281 209 #> [586,] 282 209 #> [587,] 283 208 #> [588,] 284 208 #> [589,] 285 207 #> [590,] 286 207 #> [591,] 287 206 #> [592,] 288 206 #> [593,] 289 205 #> [594,] 290 205 #> [595,] 291 204 #> [596,] 292 203 #> [597,] 293 202 #> [598,] 294 202 #> [599,] 295 201 #> [600,] 296 200 #> [601,] 297 199 #> [602,] 298 198 #> [603,] 299 197 #> [604,] 300 196 #> [605,] 301 195 #> [606,] 302 194 #> [607,] 303 193 #> [608,] 303 192 #> [609,] 304 191 #> [610,] 305 190 #> [611,] 305 189 #> [612,] 306 188 #> [613,] 307 187 #> [614,] 308 186 #> [615,] 308 185 #> [616,] 309 184 #> [617,] 310 184 #> [618,] 311 184 #> [619,] 312 183 #> [620,] 313 183 #> [621,] 314 183 #> [622,] 315 182 #> [623,] 316 182 #> [624,] 317 182 #> [625,] 318 181 #> [626,] 319 181 #> [627,] 320 180 #> [628,] 321 180 #> [629,] 322 180 #> [630,] 323 179 #> [631,] 324 179 #> [632,] 325 178 #> [633,] 326 178 #> [634,] 327 178 #> [635,] 328 177 #> [636,] 329 177 #> [637,] 330 176 #> [638,] 331 176 #> [639,] 332 175 #> [640,] 333 174 #> [641,] 334 174 #> [642,] 335 173 #> [643,] 336 173 #> [644,] 337 172 #> [645,] 338 171 #> [646,] 339 171 #> [647,] 340 170 #> [648,] 341 170 #> [649,] 342 169 #> [650,] 343 168 #> [651,] 344 168 #> [652,] 345 167 #> [653,] 346 166 #> [654,] 347 165 #> [655,] 348 165 #> [656,] 349 164 #> [657,] 350 163 #> [658,] 351 162 #> [659,] 352 162 #> [660,] 353 161 #> [661,] 354 160 #> [662,] 355 159 #> [663,] 356 158 #> [664,] 357 157 #> [665,] 358 156 #> [666,] 359 155 #> [667,] 360 155 #> [668,] 361 154 #> [669,] 362 153 #> [670,] 362 152 #> [671,] 363 151 #> [672,] 364 150 #> [673,] 365 149 #> [674,] 366 148 #> [675,] 367 147 #> [676,] 368 146 #> [677,] 369 145 #> [678,] 370 144 #> [679,] 370 143 #> [680,] 371 142 #> [681,] 372 141 #> [682,] 373 140 #> [683,] 373 139 #> [684,] 374 138 #> [685,] 375 137 #> [686,] 375 136 #> [687,] 376 135 #> [688,] 377 134 #> [689,] 377 133 #> [690,] 378 132 #> [691,] 379 131 #> [692,] 379 130 #> [693,] 379 129 #> [694,] 380 128 #> [695,] 380 127 #> [696,] 381 126 #> [697,] 381 125 #> [698,] 382 124 #> [699,] 382 123 #> [700,] 382 122 #> [701,] 383 121 #> [702,] 383 120 #> [703,] 383 119 #> [704,] 384 118 #> [705,] 383 117 #> [706,] 383 116 #> [707,] 382 115 #> [708,] 381 114 #> [709,] 380 113 #> [710,] 379 112 #> [711,] 378 112 #> [712,] 377 111 #> [713,] 376 111 #> [714,] 375 110 #> [715,] 374 109 #> [716,] 373 109 #> [717,] 372 108 #> [718,] 371 107 #> [719,] 370 107 #> [720,] 369 106 #> [721,] 368 106 #> [722,] 367 105 #> [723,] 366 105 #> [724,] 365 105 #> [725,] 364 104 #> [726,] 363 103 #> [727,] 362 103 #> [728,] 361 103 #> [729,] 360 102 #> [730,] 359 102 #> [731,] 358 101 #> [732,] 357 101 #> [733,] 356 101 #> [734,] 355 100 #> [735,] 354 100 #> [736,] 353 99 #> [737,] 352 99 #> [738,] 351 99 #> [739,] 350 98 #> [740,] 349 98 #> [741,] 348 98 #> [742,] 347 97 #> [743,] 346 97 #> [744,] 345 97 #> [745,] 344 96 #> [746,] 343 96 #> [747,] 342 96 #> [748,] 341 95 #> [749,] 340 95 #> [750,] 339 95 #> [751,] 338 94 #> [752,] 337 94 #> [753,] 336 94 #> [754,] 335 94 #> [755,] 334 93 #> [756,] 333 93 #> [757,] 332 93 #> [758,] 331 93 #> [759,] 330 92 #> [760,] 329 92 #> [761,] 328 92 #> [762,] 327 92 #> [763,] 326 91 #> [764,] 325 91 #> [765,] 324 91 #> [766,] 323 91 #> [767,] 322 91 #> [768,] 321 90 #> [769,] 320 90 #> [770,] 319 90 #> [771,] 318 90 #> [772,] 317 90 #> [773,] 316 90 #> [774,] 315 89 #> [775,] 314 89 #> [776,] 313 89 #> [777,] 312 89 #> [778,] 311 89 #> [779,] 310 89 #> [780,] 309 88 #> [781,] 308 88 #> [782,] 307 88 #> [783,] 306 88 #> [784,] 305 88 #> [785,] 304 88 #> [786,] 303 88 #> [787,] 302 88 #> [788,] 301 88 #> [789,] 300 87 #> [790,] 299 87 #> [791,] 298 87 #> [792,] 297 87 #> [793,] 296 87 #> [794,] 295 87 #> [795,] 294 87 #> [796,] 293 87 #> [797,] 292 87 #> [798,] 291 87 #> [799,] 290 87 #> [800,] 289 87 #> [801,] 288 87 #> [802,] 287 87 #> [803,] 286 87 #> [804,] 285 87 #> [805,] 284 86 #> [806,] 283 86 #> [807,] 282 86 #> [808,] 282 85 #> [809,] 281 84 #> [810,] 281 83 #> [811,] 280 82 #> [812,] 280 81 #> [813,] 279 80 #> [814,] 278 79 #> [815,] 278 78 #> [816,] 278 77 #> [817,] 277 76 #> [818,] 276 75 #> [819,] 276 74 #> [820,] 276 73 #> [821,] 275 72 #> [822,] 274 71 #> [823,] 274 70 #> [824,] 273 69 #> [825,] 273 68 #> [826,] 272 67 #> [827,] 272 66 #> [828,] 271 65 #> [829,] 270 64 #> [830,] 270 63 #> [831,] 269 62 #> [832,] 269 61 #> [833,] 268 60 #> [834,] 267 59 #> [835,] 266 58 #> [836,] 266 57 #> [837,] 265 56 #> [838,] 264 55 #> [839,] 264 54 #> [840,] 263 53 #> [841,] 262 52 #> [842,] 261 51 #> [843,] 261 50 #> [844,] 260 49 #> [845,] 259 48 #> [846,] 258 47 #> [847,] 257 46 #> [848,] 256 45 #> [849,] 255 44 #> [850,] 254 43 #> [851,] 253 42 #> [852,] 252 42 #> [853,] 251 41 #> [854,] 250 41 #> [855,] 249 40 #> [856,] 248 40 #> [857,] 247 39 #> [858,] 246 39 #> [859,] 245 39 #> [860,] 244 39 #> [861,] 243 39 #> [862,] 242 39 #> [863,] 241 39 #> [864,] 240 39 #> [865,] 239 39 #> [866,] 238 40 #> [867,] 237 40 #> [868,] 236 41 #> [869,] 235 41 #> [870,] 234 42 #> [871,] 233 43 #> [872,] 233 44 #> [873,] 232 45 #> [874,] 231 46 #> [875,] 230 47 #> [876,] 230 48 #> [877,] 230 49 #> [878,] 229 50 #> [879,] 228 51 #> [880,] 228 52 #> [881,] 228 53 #> [882,] 227 54 #> [883,] 227 55 #> [884,] 227 56 #> [885,] 226 57 #> [886,] 226 58 #> [887,] 226 59 #> [888,] 226 60 #> [889,] 225 61 #> [890,] 225 62 #> [891,] 225 63 #> [892,] 224 64 #> [893,] 225 65 #> [894,] 224 66 #> [895,] 224 67 #> [896,] 224 68 #> [897,] 224 69 #> [898,] 224 70 #> [899,] 224 71 #> [900,] 224 72 #> [901,] 224 73 #> [902,] 224 74 #> [903,] 225 75 #> [904,] 224 76 #> [905,] 225 77 #> [906,] 225 78 #> [907,] 225 79 #> [908,] 226 80 #> [909,] 226 81 #> [910,] 226 82 #> [911,] 227 83 #> [912,] 227 84 #> [913,] 227 85 #> [914,] 228 86 #> [915,] 228 87 #> [916,] 227 87 #> [917,] 226 87 #> [918,] 225 88 #> [919,] 224 88 #> [920,] 223 87 #> [921,] 222 88 #> [922,] 221 88 #> [923,] 220 88 #> [924,] 219 88 #> [925,] 218 88 #> [926,] 217 89 #> [927,] 216 89 #> [928,] 215 89 #> [929,] 214 89 #> [930,] 213 89 #> [931,] 212 88 #> [932,] 211 88 #> [933,] 210 88 #> [934,] 209 88 #> [935,] 208 88 #> [936,] 207 88 #> [937,] 206 88 #> [938,] 205 87 #> [939,] 204 87 #> [940,] 203 87 #> [941,] 202 87 #> [942,] 201 87 #> [943,] 200 87 #> x$fac #> # A tibble: 5 × 2 #> name value #> #> 1 a 5 #> 2 b 4 #> 3 c 3 #> 4 d 2 #> 5 e 1"},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":null,"dir":"Reference","previous_headings":"","what":"KMEANS on PCA objects — KMEANS","title":"KMEANS on PCA objects — KMEANS","text":"basic implementation k-means. Beware morphospaces calculated far 1st 2nd component.","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"KMEANS on PCA objects — KMEANS","text":"","code":"KMEANS(x, ...) # S3 method for PCA KMEANS(x, centers, nax = 1:2, pch = 20, cex = 0.5, ...)"},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"KMEANS on PCA objects — KMEANS","text":"x PCA object ... additional arguments passed kmeans centers numeric number centers nax numeric range PC components use (1:2 default) pch draw points cex draw points","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"KMEANS on PCA objects — KMEANS","text":"thing kmeans","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"KMEANS on PCA objects — KMEANS","text":"","code":"data(bot) bp <- PCA(efourier(bot, 10)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details KMEANS(bp, 2) #> K-means clustering with 2 clusters of sizes 14, 26 #> #> Cluster means: #> PC1 PC2 #> 1 0.07496282 -0.003229186 #> 2 -0.04036460 0.001738792 #> #> Clustering vector: #> brahma caney chimay corona deusventrue #> 2 2 1 2 2 #> duvel franziskaner grimbergen guiness hoegardeen #> 1 2 1 2 2 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 2 2 1 2 2 #> pecheresse sierranevada tanglefoot tauro westmalle #> 2 1 1 2 2 #> amrut ballantines bushmills chivas dalmore #> 2 1 2 1 1 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 2 2 2 1 2 #> jb johnniewalker magallan makersmark oban #> 2 2 2 1 2 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 1 1 2 2 1 #> #> Within cluster sum of squares by cluster: #> [1] 0.03758606 0.02127484 #> (between_SS / total_SS = 67.3 %) #> #> Available components: #> #> [1] \"cluster\" \"centers\" \"totss\" \"withinss\" \"tot.withinss\" #> [6] \"betweenss\" \"size\" \"iter\" \"ifault\""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":null,"dir":"Reference","previous_headings":"","what":"KMEDOIDS — KMEDOIDS","title":"KMEDOIDS — KMEDOIDS","text":"basic implementation kmedoids top cluster::pam Beware morphospaces calculated far 1st 2nd component.","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"KMEDOIDS — KMEDOIDS","text":"","code":"KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for default KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for Coe KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for PCA KMEDOIDS(x, k, metric = \"euclidean\", retain, ...)"},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"KMEDOIDS — KMEDOIDS","text":"x Coe PCA object k numeric number centers metric one euclidean (default) manhattan, feed cluster::pam ... additional arguments feed cluster::pam retain passing PCA many PCs retain, proportion total variance, see LDA","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"KMEDOIDS — KMEDOIDS","text":"see cluster::pam. components returned (fac, etc.)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"KMEDOIDS — KMEDOIDS","text":"","code":"data(bot) bp <- PCA(efourier(bot, 10)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details KMEANS(bp, 2) #> K-means clustering with 2 clusters of sizes 14, 26 #> #> Cluster means: #> PC1 PC2 #> 1 0.07496282 -0.003229186 #> 2 -0.04036460 0.001738792 #> #> Clustering vector: #> brahma caney chimay corona deusventrue #> 2 2 1 2 2 #> duvel franziskaner grimbergen guiness hoegardeen #> 1 2 1 2 2 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 2 2 1 2 2 #> pecheresse sierranevada tanglefoot tauro westmalle #> 2 1 1 2 2 #> amrut ballantines bushmills chivas dalmore #> 2 1 2 1 1 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 2 2 2 1 2 #> jb johnniewalker magallan makersmark oban #> 2 2 2 1 2 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 1 1 2 2 1 #> #> Within cluster sum of squares by cluster: #> [1] 0.03758606 0.02127484 #> (between_SS / total_SS = 67.3 %) #> #> Available components: #> #> [1] \"cluster\" \"centers\" \"totss\" \"withinss\" \"tot.withinss\" #> [6] \"betweenss\" \"size\" \"iter\" \"ifault\" set.seed(123) # for reproducibility on a dummy matrix matrix(rnorm(100, 10, 10)) %>% KMEDOIDS(5) #> Medoids: #> ID #> [1,] 10 5.543380 #> [2,] 30 22.538149 #> [3,] 4 10.705084 #> [4,] 7 14.609162 #> [5,] 78 -2.207177 #> Clustering vector: #> [1] 1 1 2 3 3 2 4 5 1 1 2 4 4 3 1 2 4 5 4 1 5 1 5 1 1 5 4 3 5 2 4 1 2 2 4 4 4 #> [38] 3 1 1 1 1 5 2 2 5 1 1 4 3 3 3 3 2 1 2 5 4 3 3 4 1 1 5 5 4 4 3 2 2 1 5 2 1 #> [75] 1 2 1 5 3 3 3 4 1 4 1 4 2 4 1 2 2 4 3 1 2 1 2 2 1 5 #> Objective function: #> build swap #> 2.132534 1.937061 #> #> Available components: #> [1] \"medoids\" \"id.med\" \"clustering\" \"objective\" #> [5] \"isolation\" \"clusinfo\" \"silinfo\" \"diss\" #> [9] \"call\" \"data\" \"k\" \"ids_constant\" #> [13] \"ids_collinear\" # On a Coe bot_f <- bot %>% efourier() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) bot_k <- bot_f %>% KMEDOIDS(2) #> removed these collinear columns:A1, B1, C1 # confusion matrix table(bot_k$fac$type, bot_k$clustering) #> #> 1 2 #> beer 12 8 #> whisky 14 6 # on a PCA bot_k2 <- bot_f %>% PCA() %>% KMEDOIDS(12, retain=0.9) # confusion matrix with(bot_k, table(fac$type, clustering)) #> clustering #> 1 2 #> beer 12 8 #> whisky 14 6 # silhouette plot bot_k %>% plot_silhouette() # average width as a function of k k_range <- 2:12 widths <- sapply(k_range, function(k) KMEDOIDS(bot_f, k=k)$silinfo$avg.width) #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 plot(k_range, widths, type=\"b\")"},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"Linear Discriminant Analysis on Coe objects — LDA","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"Calculates LDA Coe top MASS::lda.","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"","code":"LDA(x, fac, retain, ...) # S3 method for default LDA(x, fac, retain, ...) # S3 method for PCA LDA(x, fac, retain = 0.99, ...)"},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"x Coe PCA object fac grouping factor (names one $fac column column id) retain proportion total variance retain (retain<1) using scree, number PC axis (retain>1). ... additional arguments feed lda","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"'LDA' object apply plot.LDA, list components: x Coe object (matrix) fac grouping factor used removed ids columns original matrix removed since constant () mod raw lda mod lda mod.pred predicted model using x mod CV.fac cross-validated classification CV.tab cross-validation tabke CV.correct proportion correctly classified individuals CV.ce class error LDs unstandardized LD scores see Claude (2008) mshape mean values coefficients original matrix method inherited Coe object ()","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"LDA.PCA, retain can passed vector (eg: 1:5, retain=1, retain=2, ..., retain=5) tried, \"best\" (retain=1:number_of_pc_axes used). Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"","code":"bot.f <- efourier(bot, 24) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) LDA(bot.p, 'type', retain=0.99) # retains 0.99 of the total variance #> 8 PC retained #> * Cross-validation table ($CV.tab): #> classified #> actual beer whisky #> beer 17 3 #> whisky 1 19 #> #> * Class accuracy ($CV.ce): #> beer whisky #> 0.85 0.95 #> #> * Leave-one-out cross-validation ($CV.correct): (90% - 36/40): LDA(bot.p, 'type', retain=5) # retain 5 axis #> 5 PC retained #> * Cross-validation table ($CV.tab): #> classified #> actual beer whisky #> beer 16 4 #> whisky 4 16 #> #> * Class accuracy ($CV.ce): #> beer whisky #> 0.8 0.8 #> #> * Leave-one-out cross-validation ($CV.correct): (80% - 32/40): bot.l <- LDA(bot.p, 'type', retain=0.99) #> 8 PC retained plot_LDA(bot.l) #> * Only two levels, so a single LD and preparing for an histogram #> $xy #> LD1 #> brahma 2.06882655 #> caney 1.95733171 #> chimay 3.18567319 #> corona 1.91972111 #> deusventrue 1.51983847 #> duvel 3.25459981 #> franziskaner 1.20540643 #> grimbergen 1.78612198 #> guiness 0.31717542 #> hoegardeen 2.23601856 #> jupiler 2.41738081 #> kingfisher 1.17563178 #> latrappe 2.48017277 #> lindemanskriek 0.84132717 #> nicechouffe -0.20973451 #> pecheresse 2.73987210 #> sierranevada 2.12878315 #> tanglefoot 0.50802841 #> tauro 2.45585085 #> westmalle 1.86373375 #> amrut -1.63004033 #> ballantines -3.31173062 #> bushmills -1.09107572 #> chivas -1.97923449 #> dalmore -0.60822705 #> famousgrouse -1.43517709 #> glendronach -1.56712869 #> glenmorangie -1.46854222 #> highlandpark -2.62231929 #> jackdaniels -0.70483285 #> jb -2.24638367 #> johnniewalker -0.97832954 #> magallan -2.17603623 #> makersmark -1.23316404 #> oban -2.34336958 #> oldpotrero -0.37639098 #> redbreast -4.17639973 #> tamdhu -0.09818091 #> wildturkey -3.48193578 #> yoichi -2.32326072 #> #> $f #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky #> #> $colors_groups #> [1] \"#66C2A5FF\" \"#FC8D62FF\" #> #> $colors_rows #> [1] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [7] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [13] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [19] \"#FC8D62FF\" \"#FC8D62FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [25] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [31] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [37] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> #> $object #> [1] \"PCA\" #> #> $axes #> [1] 1 #> #> $palette #> function (n, transp = 0) #> { #> .pal_brewer(n, \"Set2\") %>% pal_alpha(transp = transp) #> } #> #> #> #> $method #> [1] \"LDAPCA\" #> #> $mshape #> NULL #> #> $cuts #> NULL #> #> $eig #> NULL #> #> $sdev #> [1] 11.33732 #> #> $rotation #> LD1 #> PC1 -0.0021966326 #> PC2 -0.0004659024 #> PC3 0.0028778651 #> PC4 -0.0020601963 #> PC5 0.0016842402 #> PC6 -0.0008112386 #> PC7 -0.0006776597 #> PC8 -0.0004229307 #> #> $LDs #> LD1 #> PC1 -0.0021966326 #> PC2 -0.0004659024 #> PC3 0.0028778651 #> PC4 -0.0020601963 #> PC5 0.0016842402 #> PC6 -0.0008112386 #> PC7 -0.0006776597 #> PC8 -0.0004229307 #> #> $baseline1 #> NULL #> #> $baseline2 #> NULL #> #> $links #> NULL #> bot.f <- mutate(bot.f, plop=factor(rep(letters[1:4], each=10))) bot.l <- LDA(PCA(bot.f), 'plop') #> 8 PC retained plot_LDA(bot.l) # will replace the former soon"},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Ldk object — Ldk","title":"Builds an Ldk object — Ldk","text":"Momocs, Ldk classes objects lists configurations landmarks, optionnal components, generic methods plotting methods (e.g. stack) specific methods (e.g. fgProcrustes). Ldk objects primarily Coo objects. sense, morphometrics methods Ldk objects preserves (x, y) coordinates LdkCoe also Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Ldk object — Ldk","text":"","code":"Ldk(coo, fac = dplyr::tibble(), links = NULL, slidings = NULL)"},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Ldk object — Ldk","text":"coo list matrices (x; y) coordinates, array, Ldk object data.frame (friends) fac (optionnal) data.frame factors /numerics specifying grouping structure links (optionnal) 2-columns matrix 'links' landmarks, mainly plotting slidings (optionnal) 3-columns matrix defining () sliding landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Ldk object — Ldk","text":"Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Builds an Ldk object — Ldk","text":"shapes x must number landmarks. trying make Ldk object Opn object, try coo_sample beforehand homogeneize number coordinates among shapes. Please note Ldk methods experimental. implementation $slidings inspired geomorph","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Ldk object — Ldk","text":"","code":"#Methods on Ldk methods(class=Ldk) #> [1] MSHAPES combine coo_bookstein coo_slice #> [5] d def_links def_slidings fgProcrustes #> [9] fgsProcrustes get_ldk get_slidings mosaic #> [13] panel pile rearrange_ldk slidings_scheme #> [17] stack which_out #> see '?methods' for accessing help and source code str(mosquito) #> coo : List of 126 #> $ shp1 : num [1:100, 1:2] -0.107 -0.134 -0.164 -0.199 -0.234 ... #> $ shp2 : num [1:100, 1:2] -0.11 -0.137 -0.167 -0.2 -0.236 ... #> $ shp3 : num [1:100, 1:2] -0.0877 -0.1085 -0.1325 -0.1601 -0.1895 ... #> $ shp4 : num [1:100, 1:2] -0.0997 -0.1239 -0.1515 -0.1835 -0.218 ... #> $ shp5 : num [1:100, 1:2] -0.0971 -0.1205 -0.145 -0.1729 -0.2037 ... #> $ shp6 : num [1:100, 1:2] -0.0927 -0.1161 -0.1411 -0.1691 -0.2001 ... #> $ shp7 : num [1:100, 1:2] -0.109 -0.136 -0.166 -0.2 -0.24 ... #> $ shp8 : num [1:100, 1:2] -0.0991 -0.1245 -0.1532 -0.1837 -0.2199 ... #> $ shp9 : num [1:100, 1:2] -0.101 -0.126 -0.155 -0.186 -0.223 ... #> $ shp10 : num [1:100, 1:2] -0.0849 -0.1063 -0.129 -0.1529 -0.1811 ... #> $ shp11 : num [1:100, 1:2] -0.0921 -0.1162 -0.1424 -0.1704 -0.2019 ... #> $ shp12 : num [1:100, 1:2] -0.084 -0.104 -0.129 -0.154 -0.183 ... #> $ shp13 : num [1:100, 1:2] -0.111 -0.139 -0.171 -0.206 -0.247 ... #> $ shp14 : num [1:100, 1:2] -0.0932 -0.1147 -0.1368 -0.164 -0.1953 ... #> $ shp15 : num [1:100, 1:2] -0.101 -0.124 -0.151 -0.183 -0.218 ... #> $ shp16 : num [1:100, 1:2] -0.105 -0.131 -0.16 -0.193 -0.228 ... #> $ shp17 : num [1:100, 1:2] -0.109 -0.137 -0.167 -0.198 -0.234 ... #> $ shp18 : num [1:100, 1:2] -0.128 -0.16 -0.195 -0.235 -0.28 ... #> $ shp19 : num [1:100, 1:2] -0.113 -0.139 -0.171 -0.206 -0.246 ... #> $ shp20 : num [1:100, 1:2] -0.104 -0.131 -0.16 -0.192 -0.228 ... #> $ shp21 : num [1:100, 1:2] -0.126 -0.157 -0.191 -0.23 -0.271 ... #> $ shp22 : num [1:100, 1:2] -0.116 -0.146 -0.181 -0.217 -0.257 ... #> $ shp23 : num [1:100, 1:2] -0.117 -0.146 -0.18 -0.216 -0.255 ... #> $ shp24 : num [1:100, 1:2] -0.123 -0.154 -0.188 -0.225 -0.267 ... #> $ shp25 : num [1:100, 1:2] -0.107 -0.134 -0.163 -0.196 -0.233 ... #> $ shp26 : num [1:100, 1:2] -0.0917 -0.1141 -0.1381 -0.1675 -0.1995 ... #> $ shp27 : num [1:100, 1:2] -0.0979 -0.1222 -0.1477 -0.1744 -0.2049 ... #> $ shp28 : num [1:100, 1:2] -0.121 -0.151 -0.183 -0.217 -0.259 ... #> $ shp29 : num [1:100, 1:2] -0.124 -0.156 -0.193 -0.234 -0.28 ... #> $ shp30 : num [1:100, 1:2] -0.106 -0.132 -0.161 -0.193 -0.232 ... #> $ shp31 : num [1:100, 1:2] -0.101 -0.126 -0.154 -0.186 -0.22 ... #> $ shp32 : num [1:100, 1:2] -0.126 -0.157 -0.19 -0.228 -0.271 ... #> $ shp33 : num [1:100, 1:2] -0.126 -0.157 -0.195 -0.237 -0.284 ... #> $ shp34 : num [1:100, 1:2] -0.125 -0.155 -0.186 -0.224 -0.266 ... #> $ shp35 : num [1:100, 1:2] -0.0985 -0.1235 -0.1506 -0.1799 -0.2125 ... #> $ shp36 : num [1:100, 1:2] -0.119 -0.149 -0.183 -0.221 -0.263 ... #> $ shp37 : num [1:100, 1:2] -0.113 -0.141 -0.173 -0.209 -0.248 ... #> $ shp38 : num [1:100, 1:2] -0.0991 -0.1227 -0.1493 -0.1803 -0.2158 ... #> $ shp39 : num [1:100, 1:2] -0.107 -0.134 -0.164 -0.196 -0.235 ... #> $ shp40 : num [1:100, 1:2] -0.102 -0.128 -0.155 -0.186 -0.221 ... #> $ shp41 : num [1:100, 1:2] -0.122 -0.153 -0.188 -0.23 -0.274 ... #> $ shp42 : num [1:100, 1:2] -0.115 -0.145 -0.178 -0.214 -0.255 ... #> $ shp43 : num [1:100, 1:2] -0.106 -0.133 -0.162 -0.196 -0.232 ... #> $ shp44 : num [1:100, 1:2] -0.119 -0.151 -0.185 -0.225 -0.268 ... #> $ shp45 : num [1:100, 1:2] -0.11 -0.137 -0.167 -0.203 -0.242 ... #> $ shp46 : num [1:100, 1:2] -0.102 -0.126 -0.155 -0.188 -0.225 ... #> $ shp47 : num [1:100, 1:2] -0.117 -0.146 -0.179 -0.218 -0.259 ... #> $ shp48 : num [1:100, 1:2] -0.102 -0.126 -0.154 -0.184 -0.217 ... #> $ shp49 : num [1:100, 1:2] -0.105 -0.132 -0.161 -0.193 -0.231 ... #> $ shp50 : num [1:100, 1:2] -0.121 -0.151 -0.185 -0.224 -0.267 ... #> $ shp51 : num [1:100, 1:2] -0.134 -0.168 -0.205 -0.245 -0.296 ... #> $ shp52 : num [1:100, 1:2] -0.106 -0.133 -0.162 -0.193 -0.23 ... #> $ shp53 : num [1:100, 1:2] -0.119 -0.148 -0.18 -0.217 -0.257 ... #> $ shp54 : num [1:100, 1:2] -0.121 -0.151 -0.184 -0.221 -0.264 ... #> $ shp55 : num [1:100, 1:2] -0.0875 -0.1083 -0.1316 -0.1588 -0.1877 ... #> $ shp56 : num [1:100, 1:2] -0.104 -0.128 -0.159 -0.193 -0.229 ... #> $ shp57 : num [1:100, 1:2] -0.128 -0.16 -0.197 -0.237 -0.283 ... #> $ shp58 : num [1:100, 1:2] -0.101 -0.125 -0.151 -0.184 -0.22 ... #> $ shp59 : num [1:100, 1:2] -0.105 -0.13 -0.16 -0.194 -0.231 ... #> $ shp60 : num [1:100, 1:2] -0.135 -0.169 -0.208 -0.253 -0.304 ... #> $ shp61 : num [1:100, 1:2] -0.104 -0.131 -0.161 -0.193 -0.229 ... #> $ shp62 : num [1:100, 1:2] -0.0895 -0.1115 -0.1345 -0.1587 -0.1884 ... #> $ shp63 : num [1:100, 1:2] -0.117 -0.147 -0.179 -0.216 -0.259 ... #> $ shp64 : num [1:100, 1:2] -0.115 -0.144 -0.176 -0.214 -0.256 ... #> $ shp65 : num [1:100, 1:2] -0.109 -0.135 -0.164 -0.2 -0.238 ... #> $ shp66 : num [1:100, 1:2] -0.125 -0.158 -0.195 -0.234 -0.276 ... #> $ shp67 : num [1:100, 1:2] -0.107 -0.135 -0.163 -0.195 -0.234 ... #> $ shp68 : num [1:100, 1:2] -0.122 -0.152 -0.184 -0.221 -0.266 ... #> $ shp69 : num [1:100, 1:2] -0.118 -0.145 -0.177 -0.216 -0.258 ... #> $ shp70 : num [1:100, 1:2] -0.116 -0.144 -0.176 -0.21 -0.25 ... #> $ shp71 : num [1:100, 1:2] -0.131 -0.164 -0.2 -0.244 -0.292 ... #> $ shp72 : num [1:100, 1:2] -0.118 -0.148 -0.18 -0.215 -0.256 ... #> $ shp73 : num [1:100, 1:2] -0.0996 -0.1229 -0.1496 -0.1778 -0.2106 ... #> $ shp74 : num [1:100, 1:2] -0.118 -0.149 -0.181 -0.218 -0.259 ... #> $ shp75 : num [1:100, 1:2] -0.118 -0.147 -0.179 -0.214 -0.252 ... #> $ shp76 : num [1:100, 1:2] -0.128 -0.159 -0.191 -0.227 -0.268 ... #> $ shp77 : num [1:100, 1:2] -0.126 -0.159 -0.193 -0.229 -0.271 ... #> $ shp78 : num [1:100, 1:2] -0.111 -0.139 -0.173 -0.21 -0.249 ... #> $ shp79 : num [1:100, 1:2] -0.121 -0.151 -0.183 -0.22 -0.261 ... #> $ shp80 : num [1:100, 1:2] -0.117 -0.146 -0.178 -0.213 -0.253 ... #> $ shp81 : num [1:100, 1:2] -0.109 -0.137 -0.168 -0.202 -0.243 ... #> $ shp82 : num [1:100, 1:2] -0.118 -0.149 -0.184 -0.222 -0.264 ... #> $ shp83 : num [1:100, 1:2] -0.12 -0.15 -0.183 -0.219 -0.256 ... #> $ shp84 : num [1:100, 1:2] -0.135 -0.168 -0.207 -0.25 -0.299 ... #> $ shp85 : num [1:100, 1:2] -0.118 -0.149 -0.181 -0.218 -0.261 ... #> $ shp86 : num [1:100, 1:2] -0.119 -0.149 -0.181 -0.221 -0.265 ... #> $ shp87 : num [1:100, 1:2] -0.106 -0.132 -0.162 -0.194 -0.232 ... #> $ shp88 : num [1:100, 1:2] -0.104 -0.128 -0.157 -0.188 -0.22 ... #> $ shp89 : num [1:100, 1:2] -0.106 -0.132 -0.162 -0.195 -0.23 ... #> $ shp90 : num [1:100, 1:2] -0.127 -0.159 -0.195 -0.235 -0.282 ... #> $ shp91 : num [1:100, 1:2] -0.111 -0.139 -0.168 -0.202 -0.238 ... #> $ shp92 : num [1:100, 1:2] -0.101 -0.126 -0.154 -0.187 -0.224 ... #> $ shp93 : num [1:100, 1:2] -0.127 -0.158 -0.193 -0.231 -0.278 ... #> $ shp94 : num [1:100, 1:2] -0.104 -0.13 -0.159 -0.193 -0.23 ... #> $ shp95 : num [1:100, 1:2] -0.0868 -0.1067 -0.1271 -0.1523 -0.182 ... #> $ shp96 : num [1:100, 1:2] -0.103 -0.128 -0.156 -0.188 -0.225 ... #> $ shp97 : num [1:100, 1:2] -0.102 -0.127 -0.156 -0.188 -0.222 ... #> $ shp98 : num [1:100, 1:2] -0.104 -0.132 -0.161 -0.192 -0.225 ... #> $ shp99 : num [1:100, 1:2] -0.108 -0.133 -0.16 -0.193 -0.227 ... #> [list output truncated] #> fac : tibble [0 × 0] (S3: tbl_df/tbl/data.frame) #> Named list() #> ldk : list()"},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate analysis of (co)variance on Coe objects — MANOVA","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Performs multivariate analysis variance PCA objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"","code":"MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for OpnCoe MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for OutCoe MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for PCA MANOVA(x, fac, test = \"Hotelling\", retain = 0.99, drop)"},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"x Coe object fac name colum $fac slot, id, formula test test manova ('Hotelling' default) retain many harmonics (polynomials) retain, PCA highest number PC axis retain, proportion variance capture. drop many harmonics (polynomials) drop","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"list matrices (x,y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Performs MANOVA/MANCOVA PC scores. Just wrapper around manova. See examples multifactorial manova summary.manova details examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Needs review considered experimental. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"","code":"# MANOVA bot.p <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MANOVA(bot.p, 'type') #> PC axes 1 to 7 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 2.7631 12.631 7 32 1.202e-07 *** #> Residuals 38 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 op <- PCA(npoly(olea, 5)) #> 'nb.pts' missing and set to: 91 MANOVA(op, 'domes') #> PC axes 1 to 2 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 0.37378 38.686 2 207 5.315e-15 *** #> Residuals 208 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 m <- manova(op$x[, 1:5] ~ op$fac$domes * op$fac$var) summary(m) #> Df Pillai approx F num Df den Df Pr(>F) #> op$fac$domes 1 0.38594 25.3915 5 202 < 2.2e-16 *** #> op$fac$var 2 0.34192 8.3723 10 406 2.069e-12 *** #> Residuals 206 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 summary.aov(m) #> Response PC1 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 11.79 11.790 1.2623 0.26251 #> op$fac$var 2 109.81 54.903 5.8784 0.00329 ** #> Residuals 206 1924.02 9.340 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC2 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 62.486 62.486 93.511 < 2.2e-16 *** #> op$fac$var 2 34.489 17.244 25.806 9.97e-11 *** #> Residuals 206 137.654 0.668 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC3 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.2345 0.234541 3.9476 0.04826 * #> op$fac$var 2 0.5998 0.299918 5.0479 0.00724 ** #> Residuals 206 12.2393 0.059414 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC4 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.12558 0.125582 8.5246 0.003894 ** #> op$fac$var 2 0.08698 0.043490 2.9521 0.054442 . #> Residuals 206 3.03476 0.014732 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC5 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.000140 0.00014009 0.7838 0.3770 #> op$fac$var 2 0.000299 0.00014964 0.8372 0.4344 #> Residuals 206 0.036819 0.00017873 #> # MANCOVA example # we create a numeric variable, based on centroid size bot %<>% mutate(cs=coo_centsize(.)) # same pipe bot %>% efourier %>% PCA %>% MANOVA(\"cs\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> PC axes 1 to 7 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 0.38135 1.7433 7 32 0.1341 #> Residuals 38"},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":null,"dir":"Reference","previous_headings":"","what":"Pairwise Multivariate analyses of variance — MANOVA_PW","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"wrapper pairwise MANOVAs Coe objects. Calculates MANOVA every pairwise combination factor provided.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"","code":"MANOVA_PW(x, ...) # S3 method for PCA MANOVA_PW(x, fac, retain = 0.99, ...)"},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"x PCA object ... arguments feed MANOVA fac name (id) grouping factor $fac factor formula. retain number PC axis retain (1:retain) proportion variance capture (0.99 par default).","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"list following components returned (invisibly $manovas may long, see examples): manovas list containing raw manovas summary stars.tab table 'significance stars', discutable largely used: '' Pr(>F) < 0.001; '' < 0.01; '' < 0.05; '.' < 0.10 '-' .","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"Needs review considered experimental. fac passed two levels, pair equivalent MANOVA. MANOVA_PW.PCA works regular manova.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"","code":"# we create a fake factor with 4 levels bot$fac$fake <- factor(rep(letters[1:4], each=10)) bot.p <- PCA(efourier(bot, 8)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MANOVA_PW(bot.p, 'fake') # or MANOVA_PW(bot.p, 2) #> PC axes 1 to 6 were retained #> ab #> ac #> ad #> bc #> bd #> cd #> $stars.tab #> a b c d #> a - ** ** #> b * * #> c - #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> a - b 1 0.1848 0.4912 6 13 0.803857 #> a - c 1 0.7785 7.6167 6 13 0.001157 #> a - d 1 0.6865 4.7449 6 13 0.009007 #> b - c 1 0.6634 4.2700 6 13 0.013537 #> b - d 1 0.5793 2.9830 6 13 0.046573 #> c - d 1 0.3489 1.1611 6 13 0.383292 # an example on open outlines op <- PCA(npoly(olea)) #> 'nb.pts' missing and set to: 91 #> 'degree' missing and set to: 5 MANOVA_PW(op, 'domes') #> PC axes 1 to 2 were retained #> cultwild #> $stars.tab #> cult wild #> cult *** #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2721 38.69 2 207 5.315e-15 # to get the results res <- MANOVA_PW(op, 'domes') #> PC axes 1 to 2 were retained #> cultwild #> $stars.tab #> cult wild #> cult *** #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2721 38.69 2 207 5.315e-15 res$manovas #> $`cult - wild` #> Df Pillai approx F num Df den Df Pr(>F) #> fac.i 1 0.27208 38.686 2 207 5.315e-15 *** #> Residuals 208 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> res$stars.tab #> cult wild #> cult *** res$summary #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2720825 38.68644 2 207 5.315003e-15"},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":null,"dir":"Reference","previous_headings":"","what":"(Metric) multidimensional scaling — MDS","title":"(Metric) multidimensional scaling — MDS","text":"wrapper around stats::cmdscale.","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"(Metric) multidimensional scaling — MDS","text":"","code":"MDS(x, method = \"euclidean\", k = 2, ...)"},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"(Metric) multidimensional scaling — MDS","text":"x Coe object method dissiminarity index feed method stats::dist (default: euclidean) k numeric number dimensions feed stats::cmdscale (default: 2) ... additional parameters feed stats::cmdscale","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"(Metric) multidimensional scaling — MDS","text":"returned stats::dist plus $fac. prepend MDS class .","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"(Metric) multidimensional scaling — MDS","text":"Details, see vegan::metaMDS","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"(Metric) multidimensional scaling — MDS","text":"","code":"x <- bot %>% efourier %>% MDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x #> $x #> [,1] [,2] #> brahma -0.05277530 -0.0230987121 #> caney -0.03692797 0.0072496676 #> chimay 0.08091319 -0.0047905849 #> corona -0.06936747 0.0022942672 #> deusventrue -0.01117242 0.0475689844 #> duvel 0.11514484 -0.0169960574 #> franziskaner -0.04425459 -0.0185989836 #> grimbergen 0.02874996 0.0099554795 #> guiness 0.01231138 0.0006027416 #> hoegardeen -0.04579716 0.0056378311 #> jupiler -0.05431287 0.0072952179 #> kingfisher -0.03821463 -0.0034548056 #> latrappe 0.13300133 -0.0384264345 #> lindemanskriek -0.03540248 0.0147002348 #> nicechouffe -0.02097431 0.0133514818 #> pecheresse -0.05277659 0.0083010974 #> sierranevada 0.03905169 -0.0068665050 #> tanglefoot 0.07741376 -0.0020813543 #> tauro -0.05456357 0.0073871372 #> westmalle -0.05000066 0.0065364611 #> amrut -0.04851067 0.0003233973 #> ballantines 0.12125872 -0.0671656955 #> bushmills -0.03619504 -0.0540035080 #> chivas 0.07579382 0.0395367090 #> dalmore 0.10196157 0.0535941215 #> famousgrouse -0.03460400 -0.0243909943 #> glendronach -0.05266032 -0.0003142188 #> glenmorangie -0.06127392 0.0037530633 #> highlandpark 0.08332158 -0.0437952867 #> jackdaniels 0.01064050 -0.0005682657 #> jb -0.04043031 0.0088167995 #> johnniewalker -0.03553374 -0.0387787659 #> magallan -0.07106980 -0.0303786761 #> makersmark 0.06020727 0.0476203806 #> oban -0.06297482 0.0061352696 #> oldpotrero 0.03373439 0.0616822707 #> redbreast 0.06482559 0.0494227507 #> tamdhu -0.04715671 -0.0061720938 #> wildturkey -0.01548202 0.0145967715 #> yoichi 0.03410175 -0.0364811930 #> #> $fac #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> 7 whisky a #> 8 whisky a #> 9 whisky a #> 10 whisky a #> # ℹ 30 more rows #> #> attr(,\"class\") #> [1] \"MDS\" \"list\""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"Quite versatile function calculates mean (median, whatever function) list array shapes, Ldk object. can also used Coe objects. case, reverse transformation (coefficients shapes) calculated, (within groups defined fac argument provided) Coe object also returned ($Coe) along list shapes ($shp) can passed plot_MSHAPES.","code":""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"","code":"MSHAPES(x, fac = NULL, FUN = mean, nb.pts = 120, ...)"},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"x list, array, Ldk, LdkCoe, OutCoe OpnCoe PCA object fac factor specification fac_dispatcher FUN function compute mean shape (mean default, median can considered) nb.pts numeric number points calculated shapes (Coe objects) ... useless .","code":""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"averaged shape; Coe objects, list two components: $Coe object class, $shp list matrices (x, y) coordinates. PCA LDA objects, FUN (typically mean median) scores PCs LDs. method used latter objects may moved another function point.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"","code":"#### on shapes MSHAPES(wings) #> x y #> 1 -0.472151969 0.026257480 #> 2 0.009588976 0.082756693 #> 3 0.231342520 0.063322047 #> 4 0.249218898 0.044129134 #> 5 0.254361417 0.022457480 #> 6 0.249206299 0.003249606 #> 7 0.230685827 -0.017059843 #> 8 0.186659843 -0.041403937 #> 9 0.116231496 -0.063584252 #> 10 0.030126772 -0.087316535 #> 11 -0.080339370 -0.103129134 #> 12 -0.405025984 -0.014459055 #> 13 -0.388690551 0.023895276 #> 14 -0.177349606 0.029181102 #> 15 0.066421260 0.043376378 #> 16 -0.027141732 0.019349606 #> 17 0.067113386 -0.009022047 #> 18 -0.140259843 -0.022011024 MSHAPES(wings$coo) #> x y #> 1 -0.472151969 0.026257480 #> 2 0.009588976 0.082756693 #> 3 0.231342520 0.063322047 #> 4 0.249218898 0.044129134 #> 5 0.254361417 0.022457480 #> 6 0.249206299 0.003249606 #> 7 0.230685827 -0.017059843 #> 8 0.186659843 -0.041403937 #> 9 0.116231496 -0.063584252 #> 10 0.030126772 -0.087316535 #> 11 -0.080339370 -0.103129134 #> 12 -0.405025984 -0.014459055 #> 13 -0.388690551 0.023895276 #> 14 -0.177349606 0.029181102 #> 15 0.066421260 0.043376378 #> 16 -0.027141732 0.019349606 #> 17 0.067113386 -0.009022047 #> 18 -0.140259843 -0.022011024 MSHAPES(coo_sample(bot, 24)$coo) #> x y #> 1 60.725 419.125 #> 2 58.350 344.200 #> 3 59.025 266.000 #> 4 59.925 189.900 #> 5 60.100 112.650 #> 6 72.025 40.300 #> 7 146.625 21.375 #> 8 222.175 24.600 #> 9 278.800 63.475 #> 10 286.850 136.775 #> 11 287.250 211.100 #> 12 287.925 288.400 #> 13 287.700 365.725 #> 14 283.325 441.375 #> 15 262.675 517.250 #> 16 237.325 586.950 #> 17 222.700 664.275 #> 18 215.900 739.350 #> 19 208.550 809.525 #> 20 137.150 808.650 #> 21 128.475 739.425 #> 22 123.650 663.775 #> 23 109.650 590.000 #> 24 83.625 514.500 stack(wings) coo_draw(MSHAPES(wings)) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MSHAPES(bot.f) # the mean (global) shape #> no 'fac' provided, returns meanshape #> x y #> [1,] 1.168906286 -0.0001651753 #> [2,] 1.163078247 0.0421600553 #> [3,] 1.145987931 0.0791545836 #> [4,] 1.119080936 0.1068491537 #> [5,] 1.084462899 0.1234921899 #> [6,] 1.044515489 0.1298160330 #> [7,] 1.001501085 0.1286134238 #> [8,] 0.957247869 0.1237878526 #> [9,] 0.912978161 0.1191956670 #> [10,] 0.869298497 0.1176432074 #> [11,] 0.826324964 0.1203279475 #> [12,] 0.783884894 0.1268487171 #> [13,] 0.741725082 0.1357159282 #> [14,] 0.699667837 0.1451353059 #> [15,] 0.657683275 0.1537690869 #> [16,] 0.615878472 0.1612150898 #> [17,] 0.574430083 0.1680667629 #> [18,] 0.533499333 0.1755775102 #> [19,] 0.493164879 0.1850912925 #> [20,] 0.453393981 0.1974710400 #> [21,] 0.414053341 0.2127369864 #> [22,] 0.374945749 0.2300322600 #> [23,] 0.335852608 0.2479030949 #> [24,] 0.296566207 0.2647662777 #> [25,] 0.256905612 0.2793783445 #> [26,] 0.216720688 0.2911371254 #> [27,] 0.175894459 0.3001249134 #> [28,] 0.134352476 0.3069092041 #> [29,] 0.092080418 0.3122084326 #> [30,] 0.049142076 0.3165718347 #> [31,] 0.005684547 0.3202014303 #> [32,] -0.038080617 0.3229727379 #> [33,] -0.081922450 0.3246211931 #> [34,] -0.125651137 0.3249912594 #> [35,] -0.169173183 0.3242231538 #> [36,] -0.212517809 0.3227854829 #> [37,] -0.255819333 0.3213351308 #> [38,] -0.299256747 0.3204663421 #> [39,] -0.342970452 0.3204641335 #> [40,] -0.386988991 0.3211796377 #> [41,] -0.431199127 0.3220947589 #> [42,] -0.475378578 0.3225609447 #> [43,] -0.519286078 0.3221164568 #> [44,] -0.562776943 0.3207428677 #> [45,] -0.605894989 0.3189350982 #> [46,] -0.648891824 0.3175276310 #> [47,] -0.692145046 0.3173174414 #> [48,] -0.735982396 0.3186132956 #> [49,] -0.780457859 0.3208847676 #> [50,] -0.825153563 0.3226624581 #> [51,] -0.869086061 0.3217583294 #> [52,] -0.910772394 0.3157606556 #> [53,] -0.948465170 0.3026542245 #> [54,] -0.980510370 0.2813630409 #> [55,] -1.005735148 0.2520318883 #> [56,] -1.023752227 0.2159499153 #> [57,] -1.035081884 0.1751434820 #> [58,] -1.041039987 0.1317817301 #> [59,] -1.043407694 0.0876037220 #> [60,] -1.043964872 0.0435658071 #> [61,] -1.044013564 -0.0001747867 #> [62,] -1.044025203 -0.0439492146 #> [63,] -1.043512254 -0.0880697136 #> [64,] -1.041161156 -0.1323293477 #> [65,] -1.035188270 -0.1757099138 #> [66,] -1.023817167 -0.2164219884 #> [67,] -1.005743392 -0.2522778444 #> [68,] -0.980460978 -0.2812740940 #> [69,] -0.948369940 -0.3021819671 #> [70,] -0.910650551 -0.3149377945 #> [71,] -0.868957121 -0.3206959085 #> [72,] -0.825030797 -0.3215245758 #> [73,] -0.780344469 -0.3198490360 #> [74,] -0.735871551 -0.3178294420 #> [75,] -0.692023558 -0.3168762464 #> [76,] -0.648746041 -0.3174481558 #> [77,] -0.605716737 -0.3191716238 #> [78,] -0.562567403 -0.3212066058 #> [79,] -0.519056221 -0.3227031290 #> [80,] -0.475145999 -0.3231749465 #> [81,] -0.430982360 -0.3226635945 #> [82,] -0.386801287 -0.3216571441 #> [83,] -0.342815151 -0.3208256181 #> [84,] -0.299125898 -0.3207013096 #> [85,] -0.255696084 -0.3214429085 #> [86,] -0.212381865 -0.3227761919 #> [87,] -0.169007586 -0.3241225855 #> [88,] -0.125448199 -0.3248451835 #> [89,] -0.081686941 -0.3244939182 #> [90,] -0.037829212 -0.3229368063 #> [91,] 0.005927348 -0.3203193572 #> [92,] 0.049350196 -0.3168750705 #> [93,] 0.092232630 -0.3126812931 #> [94,] 0.134436974 -0.3074850475 #> [95,] 0.175910258 -0.3006982100 #> [96,] 0.216675572 -0.2915894535 #> [97,] 0.256811552 -0.2796108642 #> [98,] 0.296433966 -0.2647280865 #> [99,] 0.335687496 -0.2476054872 #> [100,] 0.374746057 -0.2295433326 #> [101,] 0.413812022 -0.2121578168 #> [102,] 0.453102987 -0.1969013652 #> [103,] 0.492820622 -0.1845967071 #> [104,] 0.533107240 -0.1751700190 #> [105,] 0.574006481 -0.1677059544 #> [106,] 0.615448834 -0.1608297786 #> [107,] 0.657277055 -0.1532916765 #> [108,] 0.699311281 -0.1445361651 #> [109,] 0.741434152 -0.1350246853 #> [110,] 0.783660554 -0.1261538349 #> [111,] 0.826152488 -0.1197537224 #> [112,] 0.869151275 -0.1173116512 #> [113,] 0.912825186 -0.1191865197 #> [114,] 0.957062915 -0.1241110447 #> [115,] 1.001270984 -0.1292041692 #> [116,] 1.044245114 -0.1305548005 #> [117,] 1.084175273 -0.1242429094 #> [118,] 1.118812297 -0.1075023934 #> [119,] 1.145778947 -0.0796605231 #> [120,] 1.162963747 -0.0425396294 ms <- MSHAPES(bot.f, 'type') ms$Coe #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 2 outlines described, 12 harmonics #> # A tibble: 2 × 2 #> type fake #> #> 1 beer c #> 2 whisky a class(ms$Coe) #> [1] \"OutCoe\" \"Coe\" ms <- ms$shp coo_plot(ms$beer) coo_draw(ms$whisky, border='forestgreen')"},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":null,"dir":"Reference","previous_headings":"","what":"Momocs — Momocs","title":"Momocs — Momocs","text":"goal Momocs provide complete, convenient, reproducible open-source toolkit 2D morphometrics. includes common 2D morphometrics approaches outlines, open outlines, configurations landmarks, traditional morphometrics, facilities data preparation, manipulation visualization consistent grammar throughout. allows reproducible, complex morphometric analyses morphometrics approaches easy plug , develop , top canvas.","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Momocs — Momocs","text":"nothing","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Momocs — Momocs","text":"cite Momocs publications: citation(\"Momocs\").","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"cheers","dir":"Reference","previous_headings":"","what":"Cheers","title":"Momocs — Momocs","text":"grateful (alphabetical order): Sean Asselin, Laurent Bouby, Matt Bulbert, Simon Crameri, Julia Cooke, April Dinwiddie, Carl Lipo, Cedric Gaucherel, Catherine Girard, QGouil (GitHub), Christian Steven Hoggard, Sarah Ivorra, Glynis Jones, Nathalie Keller, Ricardo Kriebel, Remi Laffont, Fabien Lafuma, Matthias Mace, Stas Malavin, Neus Martinez, Ben Marwick, Sabrina Renaud, Marcelo Reginato, Evan Saitta, Bill Sellers, David Siddons, Eleanor Stillman, Theodore Stammer, Tom Stubbs, Norbert Telmon, Jean-Frederic Terral, Bill Venables, Daniele Ventura, Michael Wallace, Asher Wishkerman, John Wood helpful ideas bug reports.","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Momocs — Momocs","text":"Bonhomme V, Picq S, Gaucherel C, Claude J. 2014. Momocs: Outline Analysis Using R. Journal Statistical Software 56. https://www.jstatsoft.org/v56/i13. Claude J. 2008. Morphometrics R. Springer-Verlag, New-York.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":null,"dir":"Reference","previous_headings":"","what":"Non metric multidimensional scaling — NMDS","title":"Non metric multidimensional scaling — NMDS","text":"wrapper around vegan::metaMDS.","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Non metric multidimensional scaling — NMDS","text":"","code":"NMDS(x, distance = \"bray\", k = 2, try = 20, trymax = 20, ...)"},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Non metric multidimensional scaling — NMDS","text":"x Coe object distance dissiminarity index feed vegan::vegdist (default: bray) k numeric number dimensions feed vegan::metaMDS (default: 2) try numeric minimum number random starts feed vegan::metaMDS (default: 20) trymax numeric minimum number random starts feed vegan::metaMDS (default: 20) ... additional parameters feed vegan::metaMDS","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Non metric multidimensional scaling — NMDS","text":"returned vegan::metaMDS plus $fac. prepend NMDS class .","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Non metric multidimensional scaling — NMDS","text":"Details, see vegan::metaMDS","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Non metric multidimensional scaling — NMDS","text":"","code":"x <- bot %>% efourier %>% NMDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> 'comm' has negative data: 'autotransform', 'noshare' and 'wascores' set to FALSE #> Warning: results may be meaningless because data have negative entries #> in method “bray” #> Run 0 stress 0.07227125 #> Run 1 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 3.936045e-06 max resid 1.87576e-05 #> ... Similar to previous best #> Run 2 stress 0.1536609 #> Run 3 stress 0.1729702 #> Run 4 stress 0.07227125 #> ... Procrustes: rmse 5.981988e-06 max resid 2.874886e-05 #> ... Similar to previous best #> Run 5 stress 0.07227125 #> ... Procrustes: rmse 2.19081e-06 max resid 8.275813e-06 #> ... Similar to previous best #> Run 6 stress 0.07227125 #> ... Procrustes: rmse 7.028882e-06 max resid 2.808569e-05 #> ... Similar to previous best #> Run 7 stress 0.07227125 #> ... Procrustes: rmse 9.669053e-06 max resid 3.852924e-05 #> ... Similar to previous best #> Run 8 stress 0.1476475 #> Run 9 stress 0.07227125 #> ... Procrustes: rmse 1.146131e-06 max resid 4.040052e-06 #> ... Similar to previous best #> Run 10 stress 0.07227125 #> ... Procrustes: rmse 2.035531e-06 max resid 8.084339e-06 #> ... Similar to previous best #> Run 11 stress 0.07227126 #> ... Procrustes: rmse 7.291376e-06 max resid 2.685535e-05 #> ... Similar to previous best #> Run 12 stress 0.1647891 #> Run 13 stress 0.07227125 #> ... Procrustes: rmse 6.998249e-06 max resid 2.725125e-05 #> ... Similar to previous best #> Run 14 stress 0.07227125 #> ... Procrustes: rmse 5.714742e-06 max resid 2.216745e-05 #> ... Similar to previous best #> Run 15 stress 0.1606935 #> Run 16 stress 0.07227125 #> ... Procrustes: rmse 6.971938e-06 max resid 2.720148e-05 #> ... Similar to previous best #> Run 17 stress 0.07227125 #> ... Procrustes: rmse 8.281581e-07 max resid 2.450366e-06 #> ... Similar to previous best #> Run 18 stress 0.1776127 #> Run 19 stress 0.07227125 #> ... Procrustes: rmse 4.920735e-06 max resid 1.945613e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 #> ... Procrustes: rmse 1.95309e-06 max resid 6.877957e-06 #> ... Similar to previous best #> *** Best solution repeated 14 times # Shepard diagram # before a Momocs wrapper # vegan::stressplot(x)"},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Opn object — Opn","title":"Builds an Opn object — Opn","text":"Momocs, Opn classes objects lists open outlines, optionnal components, generic methods plotting methods (e.g. stack) specific methods (e.g. npoly can applied. Opn objects primarily Coo objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Opn object — Opn","text":"","code":"Opn(x, fac = dplyr::tibble(), ldk = list())"},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Opn object — Opn","text":"x list matrices (x; y) coordinates, array, data.frame (friends) fac (optionnal) data.frame factors /numerics specifying grouping structure ldk (optionnal) list landmarks row number indices","code":""},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Opn object — Opn","text":"Opn object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Opn object — Opn","text":"","code":"#Methods on Opn methods(class=Opn) #> [1] add_ldk combine coo_bookstein coo_sample #> [5] coo_sample_prop coo_slice coo_smoothcurve def_ldk #> [9] def_ldk_angle def_ldk_direction def_ldk_tips dfourier #> [13] fgProcrustes get_ldk mosaic npoly #> [17] opoly panel pile rearrange_ldk #> see '?methods' for accessing help and source code # we load some open outlines. See ?olea for credits olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk panel(olea) # orthogonal polynomials op <- opoly(olea, degree=5) #> 'nb.pts' missing and set to 91 # we print the Coe op #> An OpnCoe object [ opoly analysis ] #> -------------------- #> - $coe: 210 open outlines described #> - $baseline1: (-0.5; 0), $baseline2: (0.5; 0) #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows # Let's do a PCA on it op.p <- PCA(op) plot(op.p, 'domes') #> will be deprecated soon, see ?plot_PCA plot(op.p, 'var') #> will be deprecated soon, see ?plot_PCA # and now an LDA after a PCA olda <- LDA(PCA(op), 'var') #> 4 PC retained # for CV table and others olda #> * Cross-validation table ($CV.tab): #> classified #> actual Aglan Cypre MouBo1 PicMa #> Aglan 21 2 17 20 #> Cypre 12 4 14 0 #> MouBo1 4 2 54 0 #> PicMa 22 1 2 35 #> #> * Class accuracy ($CV.ce): #> Aglan Cypre MouBo1 PicMa #> 0.3500000 0.1333333 0.9000000 0.5833333 #> #> * Leave-one-out cross-validation ($CV.correct): (54.3% - 114/210): plot_LDA(olda)"},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an OpnCoe object — OpnCoe","title":"Builds an OpnCoe object — OpnCoe","text":"Momocs, OpnCoe classes objects wrapping around lists morphometric coefficients, along informations, generic methods plotting methods (e.g. boxplot) specific methods can applied. OpnCoe objects primarily Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an OpnCoe object — OpnCoe","text":"","code":"OpnCoe( coe = matrix(), fac = dplyr::tibble(), method = character(), baseline1 = numeric(), baseline2 = numeric(), mod = list(), r2 = numeric() )"},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an OpnCoe object — OpnCoe","text":"coe matrix morphometric coefficients fac (optionnal) data.frame factors, specifying grouping structure method used obtain coefficients baseline1 \\((x; y)\\) coordinates first baseline point baseline2 \\((x; y)\\) coordinates second baseline point mod R lm object, used reconstruct shapes r2 numeric, r-squared every model","code":""},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an OpnCoe object — OpnCoe","text":"OpnCoe object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an OpnCoe object — OpnCoe","text":"","code":"# all OpnCoe classes methods(class='OpnCoe') #> [1] MANOVA MSHAPES PCA boxplot combine print #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Out object — Out","title":"Builds an Out object — Out","text":"Momocs, -classes objects lists closed outlines, optional components, generic methods plotting methods (e.g. stack) specific methods (e.g. efourier can applied. objects primarily Coo objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Out object — Out","text":"","code":"Out(x, fac = dplyr::tibble(), ldk = list())"},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Out object — Out","text":"x list matrices (x; y) coordinates, array object Ldk object, data.frame (friends) fac (optional) data.frame factors /numerics specifying grouping structure ldk (optional) list landmarks row number indices","code":""},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Out object — Out","text":"object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Out object — Out","text":"","code":"methods(class=Out) #> [1] add_ldk combine coo_bookstein coo_down #> [5] coo_left coo_right coo_sample coo_sample_prop #> [9] coo_slice coo_up d def_ldk #> [13] def_ldk_angle def_ldk_direction efourier fgProcrustes #> [17] get_ldk mosaic panel pile #> [21] rearrange_ldk rfourier sfourier tfourier #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an OutCoe object — OutCoe","title":"Builds an OutCoe object — OutCoe","text":"Momocs, OutCoe classes objects wrapping around lists morphometric coefficients, along informations, generic methods plotting methods (e.g. boxplot) specific methods can applied. OutCoe objects primarily Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an OutCoe object — OutCoe","text":"","code":"OutCoe(coe = matrix(), fac = dplyr::tibble(), method, norm)"},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an OutCoe object — OutCoe","text":"coe matrix harmonic coefficients fac (optional) data.frame factors, specifying grouping structure method used obtain coefficients norm normalisation used obtain coefficients","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an OutCoe object — OutCoe","text":"OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Builds an OutCoe object — OutCoe","text":"methods can applied objects:","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an OutCoe object — OutCoe","text":"","code":"# all OutCoe methods methods(class='OutCoe') #> [1] MANOVA MSHAPES PCA boxplot combine hcontrib print rm_asym #> [9] rm_sym symmetry #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Principal component analysis on Coe objects — PCA","title":"Principal component analysis on Coe objects — PCA","text":"Performs PCA Coe objects, using prcomp.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Principal component analysis on Coe objects — PCA","text":"","code":"PCA(x, scale., center, fac) # S3 method for OutCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for OpnCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for LdkCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for TraCoe PCA(x, scale. = TRUE, center = TRUE, fac) # S3 method for default PCA(x, scale. = TRUE, center = TRUE, fac = dplyr::tibble()) as_PCA(x, fac)"},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Principal component analysis on Coe objects — PCA","text":"x Coe object appropriate object (eg prcomp) as_PCA scale. logical whether scale input data center logical whether center input data fac factor data.frame passed as_PCA use plot.PCA","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Principal component analysis on Coe objects — PCA","text":"'PCA' object apply plot.PCA, among others. list several components, inherited prcomp object: sdev standard deviations principal components (.e., square roots eigenvalues covariance/correlation matrix, though calculation actually done singular values data matrix) eig cumulated proportion variance along PC axes rotation matrix variable loadings (.e., matrix whose columns contain eigenvectors). function princomp returns element loadings. center, scale centering scaling used x PCA scores (value rotated data (centred (scaled requested) data multiplied rotation matrix)) components inherited Coe object passed PCA, eg fac, mshape, method, baseline1 baseline2, etc. documented corresponding *Coe file.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Principal component analysis on Coe objects — PCA","text":"default, methods Coe object scale input data center . also generic method (eg traditional morphometrics) centers scales data.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Principal component analysis on Coe objects — PCA","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) bot.p #> A PCA object #> -------------------- #> - 40 shapes #> - $method: [ efourier analysis ] #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts. plot(bot.p, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA plot(bot.p, 'type') #> will be deprecated soon, see ?plot_PCA op <- npoly(olea, 5) #> 'nb.pts' missing and set to: 91 op.p <- PCA(op) op.p #> A PCA object #> -------------------- #> - 210 shapes #> - $method: [ npoly analysis ] #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, mod, baseline1, baseline2, cuts. plot(op.p, 1, morpho=TRUE) #> will be deprecated soon, see ?plot_PCA wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wpp <- PCA(wp) wpp #> A PCA object #> -------------------- #> - 127 shapes #> - $method: [ procrustes analysis ] #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts, links. plot(wpp, 1) #> will be deprecated soon, see ?plot_PCA # \"foreign prcomp\" head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3.0 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa #> 4 4.6 3.1 1.5 0.2 setosa #> 5 5.0 3.6 1.4 0.2 setosa #> 6 5.4 3.9 1.7 0.4 setosa iris.p <- prcomp(iris[, 1:4]) iris.p <- as_PCA(iris.p, iris[, 5]) class(iris.p) #> [1] \"PCA\" \"prcomp\" plot(iris.p, 1) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":null,"dir":"Reference","previous_headings":"","what":"Shape variation along PC axes — PCcontrib","title":"Shape variation along PC axes — PCcontrib","text":"Calculates plots shape variation along Principal Component axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shape variation along PC axes — PCcontrib","text":"","code":"PCcontrib(PCA, ...) # S3 method for PCA PCcontrib(PCA, nax, sd.r = c(-2, -1, -0.5, 0, 0.5, 1, 2), gap = 1, ...)"},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shape variation along PC axes — PCcontrib","text":"PCA PCA object ... additional parameter pass coo_draw nax range PCs plot (1 99pc total variance default) sd.r single range mean +/- sd values (eg: c(-1, 0, 1)) gap combined-Coe, adjustment variable gap shapes. (bug)Default 1 (whish never superimpose shapes), reduce get compact plot.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shape variation along PC axes — PCcontrib","text":"(invisibly) list gg ggplot object shp list shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shape variation along PC axes — PCcontrib","text":"","code":"bot.p <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details PCcontrib(bot.p, nax=1:3) #> Warning: `mutate_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `mutate()` instead. #> ℹ See vignette('programming') for more help #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . # \\donttest{ library(ggplot2) gg <- PCcontrib(bot.p, nax=1:8, sd.r=c(-5, -3, -2, -1, -0.5, 0, 0.5, 1, 2, 3, 5)) gg$gg + geom_polygon(fill=\"slategrey\", col=\"black\") + ggtitle(\"A nice title\") # }"},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":null,"dir":"Reference","previous_headings":"","what":"Ptolemaic ellipses and illustration of efourier — Ptolemy","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"Calculate display Ptolemaic ellipses illustrates intuitively principle behing elliptical Fourier analysis.","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"","code":"Ptolemy( coo, t = seq(0, 2 * pi, length = 7)[-1], nb.h = 3, nb.pts = 360, palette = col_heat, zoom = 5/4, legend = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"coo matrix (x; y) coordinates t vector af angles (radians) display ellipses nb.h integer. number harmonics display nb.pts integer. number points use display shapes palette color palette zoom numeric zoom factor coo_plot legend logical. Whether plot legend box ... additional parameters feed coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"drawing last plot","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"method inspired figures found followings papers. Kuhl FP, Giardina CR. 1982. Elliptic Fourier features closed contour. Computer Graphics Image Processing 18: 236-258. Crampton JS. 1995. Elliptical Fourier shape analysis fossil bivalves: practical considerations. Lethaia 28: 179-186.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"","code":"cat <- shapes[4] Ptolemy(cat, main=\"An EFT cat\")"},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Traditional morphometrics class — TraCoe","title":"Traditional morphometrics class — TraCoe","text":"Defines builder traditional measurement class Momocs. intended ease calculations, data handling multivariate statistics just ad Momocs' classes","code":""},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Traditional morphometrics class — TraCoe","text":"","code":"TraCoe(coe = matrix(), fac = dplyr::tibble())"},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Traditional morphometrics class — TraCoe","text":"coe matrix measurements fac data.frame covariates","code":""},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Traditional morphometrics class — TraCoe","text":"list class TraCoe","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Traditional morphometrics class — TraCoe","text":"","code":"# let's (more or less) rebuild the flower dataset fl <- TraCoe(iris[, 1:4], dplyr::tibble(sp=iris$Species)) fl %>% PCA() %>% plot(\"sp\") #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Adds new landmarks on Out and Opn objects — add_ldk","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Helps add new landmarks Coo object top existing ones. number landmarks must specified rows indices correspond nearest points clicked every outlines stored $ldk slot Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"","code":"add_ldk(Coo, nb.ldk)"},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Coo Opn object nb.ldk number landmarks add every shape","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Opn object landmarks defined","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Note landmarks already defined, function equivalent def_ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"","code":"if (FALSE) { hearts <- slice(hearts, 1:5) # to make it shorter to try # click on 3 points, 5 times. hearts <- def_ldk(hearts, 3) # Don't forget to save the object returned by def_ldk... hearts2 <- add_ldk(hearts, 3) stack(hearts2) hearts2$ldk }"},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":null,"dir":"Reference","previous_headings":"","what":"Arrange rows by variables — arrange","title":"Arrange rows by variables — arrange","text":"Arrange shapes variables, $fac. See examples ?dplyr::arrange.","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Arrange rows by variables — arrange","text":"","code":"arrange(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Arrange rows by variables — arrange","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Arrange rows by variables — arrange","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Arrange rows by variables — arrange","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Arrange rows by variables — arrange","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk # we create a new column olea %>% mutate(id=1:length(.)) %$% fac$id #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 #> [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 #> [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 #> [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 #> [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 #> [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 #> [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 #> [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 #> [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 #> [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 #> [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 #> [199] 199 200 201 202 203 204 205 206 207 208 209 210 # same but now, shapes are arranged in a desc order, based on id olea %>% mutate(id=1:length(.)) %>% arrange(desc(id)) %$% fac$id #> [1] 210 209 208 207 206 205 204 203 202 201 200 199 198 197 196 195 194 193 #> [19] 192 191 190 189 188 187 186 185 184 183 182 181 180 179 178 177 176 175 #> [37] 174 173 172 171 170 169 168 167 166 165 164 163 162 161 160 159 158 157 #> [55] 156 155 154 153 152 151 150 149 148 147 146 145 144 143 142 141 140 139 #> [73] 138 137 136 135 134 133 132 131 130 129 128 127 126 125 124 123 122 121 #> [91] 120 119 118 117 116 115 114 113 112 111 110 109 108 107 106 105 104 103 #> [109] 102 101 100 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 #> [127] 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 #> [145] 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 #> [163] 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 #> [181] 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 #> [199] 12 11 10 9 8 7 6 5 4 3 2 1"},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Turn Momocs objects into tydy data_frames — as_df","title":"Turn Momocs objects into tydy data_frames — as_df","text":"Used particular compatibility tidyverse","code":""},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Turn Momocs objects into tydy data_frames — as_df","text":"","code":"as_df(x, ...) # S3 method for Coo as_df(x, ...) # S3 method for Coe as_df(x, ...) # S3 method for PCA as_df(x, retain, ...) # S3 method for LDA as_df(x, retain, ...)"},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Turn Momocs objects into tydy data_frames — as_df","text":"x object, typically Momocs object ... useless retain numeric use scree methods. Defaut . <1, enough axes retain proportion variance; >1, number axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Turn Momocs objects into tydy data_frames — as_df","text":"dplyr::tibble()","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Turn Momocs objects into tydy data_frames — as_df","text":"","code":"# first, some (baby) objects b <- bot %>% coo_sample(12) bf <- b %>% efourier(5, norm=TRUE) # Coo object b %>% as_df #> # A tibble: 40 × 3 #> coo type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> 7 whisky a #> 8 whisky a #> 9 whisky a #> 10 whisky a #> # ℹ 30 more rows # Coe object bf %>% as_df #> # A tibble: 40 × 22 #> type fake A1 A2 A3 A4 A5 B1 B2 B3 #> #> 1 whisky a 1 0.0120 0.0917 0.0124 0.0248 0 -0.00112 -0.00100 #> 2 whisky a 1 0.0110 0.0918 0.0124 0.0224 0 -0.00125 -0.00280 #> 3 whisky a 1 0.0213 0.0770 0.0240 0.0140 0 -0.00637 0.00124 #> 4 whisky a 1 0.00905 0.0960 0.00971 0.0263 0 -0.000555 -0.00204 #> 5 whisky a 1 0.0208 0.0913 0.0208 0.0193 0 -0.00108 0.00113 #> 6 whisky a 1 0.0200 0.0722 0.0213 0.0119 0 -0.00215 0.00349 #> 7 whisky a 1 0.00998 0.0912 0.0122 0.0248 0 -0.000172 -0.00124 #> 8 whisky a 1 0.0197 0.0845 0.0217 0.0164 0 -0.000464 -0.00144 #> 9 whisky a 1 0.0194 0.0864 0.0214 0.0191 0 -0.00288 -0.00196 #> 10 whisky a 1 0.0128 0.0929 0.0141 0.0236 0 -0.000998 -0.00170 #> # ℹ 30 more rows #> # ℹ 12 more variables: B4 , B5 , C1 , C2 , C3 , #> # C4 , C5 , D1 , D2 , D3 , D4 , D5 # PCA object bf %>% PCA %>% as_df # all PCs by default #> `retain` is too ambitious. All axes returned #> # A tibble: 40 × 22 #> type fake PC1 PC2 PC3 PC4 PC5 PC6 PC7 #> #> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 1.31e-2 -1.09e-3 -5.06e-3 #> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 1.67e-3 4.14e-3 3.06e-5 #> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 7.56e-4 3.99e-3 -3.37e-3 #> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -1.72e-3 4.63e-3 -1.78e-3 #> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -2.45e-5 -1.69e-2 1.31e-3 #> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 2.42e-3 2.48e-3 2.55e-3 #> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -3.13e-3 -1.78e-3 -4.73e-3 #> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 6.12e-3 -2.03e-3 5.70e-4 #> 9 whisky a 0.0114 0.00619 0.00207 0.00298 5.44e-3 2.31e-4 -3.57e-3 #> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 3.75e-3 -7.95e-4 2.55e-4 #> # ℹ 30 more rows #> # ℹ 13 more variables: PC8 , PC9 , PC10 , PC11 , #> # PC12 , PC13 , PC14 , PC15 , PC16 , PC17 , #> # PC18 , PC19 , PC20 bf %>% PCA %>% as_df(2) # or 2 #> # A tibble: 40 × 4 #> type fake PC1 PC2 #> #> 1 whisky a -0.0520 -0.0226 #> 2 whisky a -0.0356 0.00197 #> 3 whisky a 0.0811 -0.00232 #> 4 whisky a -0.0694 -0.00396 #> 5 whisky a -0.0146 0.0455 #> 6 whisky a 0.121 -0.0208 #> 7 whisky a -0.0428 -0.0170 #> 8 whisky a 0.0343 0.00950 #> 9 whisky a 0.0114 0.00619 #> 10 whisky a -0.0440 0.00410 #> # ℹ 30 more rows bf %>% PCA %>% as_df(0.99) # or enough for 99% #> # A tibble: 40 × 8 #> type fake PC1 PC2 PC3 PC4 PC5 PC6 #> #> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 0.0131 -0.00109 #> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 0.00167 0.00414 #> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 0.000756 0.00399 #> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -0.00172 0.00463 #> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -0.0000245 -0.0169 #> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 0.00242 0.00248 #> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -0.00313 -0.00178 #> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 0.00612 -0.00203 #> 9 whisky a 0.0114 0.00619 0.00207 0.00298 0.00544 0.000231 #> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 0.00375 -0.000795 #> # ℹ 30 more rows # LDA object bf %>% LDA(~fake) %>% as_df #> removed these collinear columns:A1, B1, C1 #> # A tibble: 40 × 8 #> actual predicted posterior type fake LD1 LD2 LD3 #> #> 1 a a 1.00 whisky a -4.19 1.84 -1.56 #> 2 a a 0.997 whisky a -2.74 1.68 -0.0456 #> 3 a a 0.878 whisky a -2.26 0.171 -0.293 #> 4 a a 0.935 whisky a -3.17 -0.527 -0.611 #> 5 a a 0.997 whisky a -2.97 1.54 0.665 #> 6 a a 0.989 whisky a -4.64 -0.937 0.385 #> 7 a d 0.620 whisky a -0.109 2.26 -0.0356 #> 8 a a 0.999 whisky a -4.20 0.797 0.520 #> 9 a a 0.994 whisky a -2.97 0.925 -0.640 #> 10 a b 0.826 whisky a -1.52 -0.749 0.113 #> # ℹ 30 more rows # same options apply"},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":null,"dir":"Reference","previous_headings":"","what":"Retain groups with at least n shapes — at_least","title":"Retain groups with at least n shapes — at_least","text":"Examples self-speaking.","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retain groups with at least n shapes — at_least","text":"","code":"at_least(x, fac, N)"},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retain groups with at least n shapes — at_least","text":"x Momocs object fac id name $fac column N minimal number individuals retain group","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retain groups with at least n shapes — at_least","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retain groups with at least n shapes — at_least","text":"N ambitious original object returned message","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retain groups with at least n shapes — at_least","text":"","code":"table(trilo$onto) #> #> a b c d #> 7 16 18 9 at_least(trilo, \"onto\", 9) #> Out (outlines) #> - 43 outlines, 64 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 43 × 1 #> onto #> #> 1 b #> 2 b #> 3 b #> 4 b #> 5 b #> 6 b #> # ℹ 37 more rows #> - also: $ldk at_least(trilo, \"onto\", 16) #> Out (outlines) #> - 34 outlines, 64 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 34 × 1 #> onto #> #> 1 b #> 2 b #> 3 b #> 4 b #> 5 b #> 6 b #> # ℹ 28 more rows #> - also: $ldk at_least(trilo, \"onto\", 2000) # too ambitious ! #> no group with at least 2000 indidivuals #> empty Out"},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Useful convert (x; y) coordinates chain-coded coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"","code":"pix2chc(coo) chc2pix(chc)"},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"coo (x; y) coordinates passed matrix chc chain coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"matrix numeric","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Kuhl, F. P., & Giardina, C. R. (1982). Elliptic Fourier features closed contour. Computer Graphics Image Processing, 18(3), 236-258.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"","code":"pix2chc(shapes[1]) %T>% print %>% # from pix to chc chc2pix() # and back #> [1] 5 4 3 2 4 4 3 4 4 3 4 4 3 4 3 3 4 3 4 3 3 4 3 3 3 4 3 3 3 3 3 3 3 3 3 2 3 #> [38] 3 3 2 3 3 2 3 3 2 3 2 3 2 3 3 2 3 2 2 3 2 2 3 2 2 2 2 3 2 2 2 2 3 2 2 2 2 #> [75] 2 3 2 1 2 3 2 2 2 2 3 2 2 2 3 2 3 2 3 4 3 4 4 4 4 3 4 4 5 4 4 4 5 4 5 5 5 #> [112] 5 5 5 6 5 5 6 5 5 6 5 6 5 6 5 5 5 6 5 5 5 5 5 5 5 5 4 5 4 5 4 5 4 5 4 5 4 #> [149] 4 4 5 4 4 4 4 4 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 #> [186] 4 4 4 4 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 #> [223] 2 2 2 2 2 2 2 2 2 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [260] 1 0 1 1 1 1 1 2 1 2 1 2 1 1 2 1 2 1 1 2 1 1 1 2 1 1 1 1 1 0 1 1 0 1 0 1 0 #> [297] 1 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [334] 0 7 0 0 0 7 0 0 0 7 0 7 0 7 0 7 0 7 0 7 7 7 7 0 7 7 6 7 7 7 7 6 7 7 6 7 7 #> [371] 6 7 6 6 7 6 7 6 6 7 6 6 7 6 6 7 6 6 6 7 6 6 7 6 6 6 7 6 6 6 7 6 6 6 7 6 6 #> [408] 6 7 6 6 7 6 7 6 7 6 7 7 7 7 7 0 0 7 0 0 1 0 0 1 0 1 1 1 2 1 2 1 2 1 2 1 2 #> [445] 2 1 2 2 1 2 2 1 2 2 1 2 1 2 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 0 1 1 0 #> [482] 1 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [519] 0 0 1 7 1 3 2 2 2 3 2 2 2 3 2 2 2 3 2 2 3 2 2 2 3 2 2 2 3 2 2 2 2 3 2 2 2 #> [556] 2 2 1 2 1 1 0 0 0 0 1 7 0 7 0 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 #> [593] 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 #> [630] 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 5 5 5 4 5 5 4 5 5 5 4 5 #> [667] 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 #> [704] 5 4 5 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 #> [741] 4 4 4 5 3 4 3 3 3 3 2 2 2 2 2 2 2 1 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 #> [778] 2 2 2 1 2 2 1 3 4 4 3 4 4 4 4 4 4 4 4 5 4 4 4 5 4 5 5 6 6 5 6 6 5 6 5 6 6 #> [815] 5 6 5 6 6 5 6 5 6 6 5 6 5 6 5 6 5 6 5 5 6 5 6 5 5 5 6 5 5 5 5 5 5 5 5 5 5 #> [852] 4 5 4 5 5 4 5 4 5 4 4 5 4 4 4 5 4 4 4 4 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 #> [,1] [,2] #> [1,] -1 -1 #> [2,] -2 -1 #> [3,] -3 0 #> [4,] -3 1 #> [5,] -4 1 #> [6,] -5 1 #> [7,] -6 2 #> [8,] -7 2 #> [9,] -8 2 #> [10,] -9 3 #> [11,] -10 3 #> [12,] -11 3 #> [13,] -12 4 #> [14,] -13 4 #> [15,] -14 5 #> [16,] -15 6 #> [17,] -16 6 #> [18,] -17 7 #> [19,] -18 7 #> [20,] -19 8 #> [21,] -20 9 #> [22,] -21 9 #> [23,] -22 10 #> [24,] -23 11 #> [25,] -24 12 #> [26,] -25 12 #> [27,] -26 13 #> [28,] -27 14 #> [29,] -28 15 #> [30,] -29 16 #> [31,] -30 17 #> [32,] -31 18 #> [33,] -32 19 #> [34,] -33 20 #> [35,] -34 21 #> [36,] -34 22 #> [37,] -35 23 #> [38,] -36 24 #> [39,] -37 25 #> [40,] -37 26 #> [41,] -38 27 #> [42,] -39 28 #> [43,] -39 29 #> [44,] -40 30 #> [45,] -41 31 #> [46,] -41 32 #> [47,] -42 33 #> [48,] -42 34 #> [49,] -43 35 #> [50,] -43 36 #> [51,] -44 37 #> [52,] -45 38 #> [53,] -45 39 #> [54,] -46 40 #> [55,] -46 41 #> [56,] -46 42 #> [57,] -47 43 #> [58,] -47 44 #> [59,] -47 45 #> [60,] -48 46 #> [61,] -48 47 #> [62,] -48 48 #> [63,] -48 49 #> [64,] -48 50 #> [65,] -49 51 #> [66,] -49 52 #> [67,] -49 53 #> [68,] -49 54 #> [69,] -49 55 #> [70,] -50 56 #> [71,] -50 57 #> [72,] -50 58 #> [73,] -50 59 #> [74,] -50 60 #> [75,] -50 61 #> [76,] -51 62 #> [77,] -51 63 #> [78,] -50 64 #> [79,] -50 65 #> [80,] -51 66 #> [81,] -51 67 #> [82,] -51 68 #> [83,] -51 69 #> [84,] -51 70 #> [85,] -52 71 #> [86,] -52 72 #> [87,] -52 73 #> [88,] -52 74 #> [89,] -53 75 #> [90,] -53 76 #> [91,] -54 77 #> [92,] -54 78 #> [93,] -55 79 #> [94,] -56 79 #> [95,] -57 80 #> [96,] -58 80 #> [97,] -59 80 #> [98,] -60 80 #> [99,] -61 80 #> [100,] -62 81 #> [101,] -63 81 #> [102,] -64 81 #> [103,] -65 80 #> [104,] -66 80 #> [105,] -67 80 #> [106,] -68 80 #> [107,] -69 79 #> [108,] -70 79 #> [109,] -71 78 #> [110,] -72 77 #> [111,] -73 76 #> [112,] -74 75 #> [113,] -75 74 #> [114,] -76 73 #> [115,] -76 72 #> [116,] -77 71 #> [117,] -78 70 #> [118,] -78 69 #> [119,] -79 68 #> [120,] -80 67 #> [121,] -80 66 #> [122,] -81 65 #> [123,] -81 64 #> [124,] -82 63 #> [125,] -82 62 #> [126,] -83 61 #> [127,] -84 60 #> [128,] -85 59 #> [129,] -85 58 #> [130,] -86 57 #> [131,] -87 56 #> [132,] -88 55 #> [133,] -89 54 #> [134,] -90 53 #> [135,] -91 52 #> [136,] -92 51 #> [137,] -93 50 #> [138,] -94 50 #> [139,] -95 49 #> [140,] -96 49 #> [141,] -97 48 #> [142,] -98 48 #> [143,] -99 47 #> [144,] -100 47 #> [145,] -101 46 #> [146,] -102 46 #> [147,] -103 45 #> [148,] -104 45 #> [149,] -105 45 #> [150,] -106 45 #> [151,] -107 44 #> [152,] -108 44 #> [153,] -109 44 #> [154,] -110 44 #> [155,] -111 44 #> [156,] -112 44 #> [157,] -113 43 #> [158,] -114 43 #> [159,] -115 43 #> [160,] -116 43 #> [161,] -117 43 #> [162,] -118 43 #> [163,] -119 43 #> [164,] -120 43 #> [165,] -121 43 #> [166,] -122 43 #> [167,] -123 43 #> [168,] -124 43 #> [169,] -125 43 #> [170,] -126 43 #> [171,] -127 43 #> [172,] -128 43 #> [173,] -129 43 #> [174,] -130 43 #> [175,] -131 43 #> [176,] -132 43 #> [177,] -133 43 #> [178,] -134 43 #> [179,] -135 43 #> [180,] -136 43 #> [181,] -137 43 #> [182,] -138 43 #> [183,] -139 43 #> [184,] -140 43 #> [185,] -141 43 #> [186,] -142 43 #> [187,] -143 43 #> [188,] -144 43 #> [189,] -145 43 #> [190,] -146 44 #> [191,] -146 45 #> [192,] -146 46 #> [193,] -146 47 #> [194,] -146 48 #> [195,] -146 49 #> [196,] -146 50 #> [197,] -146 51 #> [198,] -146 52 #> [199,] -146 53 #> [200,] -146 54 #> [201,] -146 55 #> [202,] -146 56 #> [203,] -146 57 #> [204,] -146 58 #> [205,] -146 59 #> [206,] -146 60 #> [207,] -146 61 #> [208,] -146 62 #> [209,] -146 63 #> [210,] -146 64 #> [211,] -146 65 #> [212,] -146 66 #> [213,] -146 67 #> [214,] -146 68 #> [215,] -146 69 #> [216,] -146 70 #> [217,] -146 71 #> [218,] -146 72 #> [219,] -146 73 #> [220,] -146 74 #> [221,] -146 75 #> [222,] -146 76 #> [223,] -146 77 #> [224,] -146 78 #> [225,] -146 79 #> [226,] -146 80 #> [227,] -146 81 #> [228,] -146 82 #> [229,] -146 83 #> [230,] -146 84 #> [231,] -146 85 #> [232,] -146 86 #> [233,] -145 87 #> [234,] -144 87 #> [235,] -143 87 #> [236,] -142 87 #> [237,] -141 87 #> [238,] -140 87 #> [239,] -139 87 #> [240,] -138 87 #> [241,] -137 87 #> [242,] -136 87 #> [243,] -135 87 #> [244,] -134 87 #> [245,] -133 87 #> [246,] -132 87 #> [247,] -131 87 #> [248,] -130 87 #> [249,] -129 87 #> [250,] -128 87 #> [251,] -127 87 #> [252,] -126 87 #> [253,] -125 87 #> [254,] -124 87 #> [255,] -123 87 #> [256,] -122 87 #> [257,] -121 87 #> [258,] -120 87 #> [259,] -119 87 #> [260,] -118 88 #> [261,] -117 88 #> [262,] -116 89 #> [263,] -115 90 #> [264,] -114 91 #> [265,] -113 92 #> [266,] -112 93 #> [267,] -112 94 #> [268,] -111 95 #> [269,] -111 96 #> [270,] -110 97 #> [271,] -110 98 #> [272,] -109 99 #> [273,] -108 100 #> [274,] -108 101 #> [275,] -107 102 #> [276,] -107 103 #> [277,] -106 104 #> [278,] -105 105 #> [279,] -105 106 #> [280,] -104 107 #> [281,] -103 108 #> [282,] -102 109 #> [283,] -102 110 #> [284,] -101 111 #> [285,] -100 112 #> [286,] -99 113 #> [287,] -98 114 #> [288,] -97 115 #> [289,] -96 115 #> [290,] -95 116 #> [291,] -94 117 #> [292,] -93 117 #> [293,] -92 118 #> [294,] -91 118 #> [295,] -90 119 #> [296,] -89 119 #> [297,] -88 120 #> [298,] -87 120 #> [299,] -86 121 #> [300,] -85 121 #> [301,] -84 122 #> [302,] -83 122 #> [303,] -82 122 #> [304,] -81 122 #> [305,] -80 123 #> [306,] -79 123 #> [307,] -78 123 #> [308,] -77 123 #> [309,] -76 123 #> [310,] -75 124 #> [311,] -74 124 #> [312,] -73 124 #> [313,] -72 124 #> [314,] -71 124 #> [315,] -70 124 #> [316,] -69 124 #> [317,] -68 124 #> [318,] -67 124 #> [319,] -66 124 #> [320,] -65 124 #> [321,] -64 124 #> [322,] -63 124 #> [323,] -62 124 #> [324,] -61 124 #> [325,] -60 124 #> [326,] -59 124 #> [327,] -58 124 #> [328,] -57 124 #> [329,] -56 124 #> [330,] -55 124 #> [331,] -54 124 #> [332,] -53 124 #> [333,] -52 124 #> [334,] -51 124 #> [335,] -50 123 #> [336,] -49 123 #> [337,] -48 123 #> [338,] -47 123 #> [339,] -46 122 #> [340,] -45 122 #> [341,] -44 122 #> [342,] -43 122 #> [343,] -42 121 #> [344,] -41 121 #> [345,] -40 120 #> [346,] -39 120 #> [347,] -38 119 #> [348,] -37 119 #> [349,] -36 118 #> [350,] -35 118 #> [351,] -34 117 #> [352,] -33 117 #> [353,] -32 116 #> [354,] -31 115 #> [355,] -30 114 #> [356,] -29 113 #> [357,] -28 113 #> [358,] -27 112 #> [359,] -26 111 #> [360,] -26 110 #> [361,] -25 109 #> [362,] -24 108 #> [363,] -23 107 #> [364,] -22 106 #> [365,] -22 105 #> [366,] -21 104 #> [367,] -20 103 #> [368,] -20 102 #> [369,] -19 101 #> [370,] -18 100 #> [371,] -18 99 #> [372,] -17 98 #> [373,] -17 97 #> [374,] -17 96 #> [375,] -16 95 #> [376,] -16 94 #> [377,] -15 93 #> [378,] -15 92 #> [379,] -15 91 #> [380,] -14 90 #> [381,] -14 89 #> [382,] -14 88 #> [383,] -13 87 #> [384,] -13 86 #> [385,] -13 85 #> [386,] -12 84 #> [387,] -12 83 #> [388,] -12 82 #> [389,] -12 81 #> [390,] -11 80 #> [391,] -11 79 #> [392,] -11 78 #> [393,] -10 77 #> [394,] -10 76 #> [395,] -10 75 #> [396,] -10 74 #> [397,] -9 73 #> [398,] -9 72 #> [399,] -9 71 #> [400,] -9 70 #> [401,] -8 69 #> [402,] -8 68 #> [403,] -8 67 #> [404,] -8 66 #> [405,] -7 65 #> [406,] -7 64 #> [407,] -7 63 #> [408,] -7 62 #> [409,] -6 61 #> [410,] -6 60 #> [411,] -6 59 #> [412,] -5 58 #> [413,] -5 57 #> [414,] -4 56 #> [415,] -4 55 #> [416,] -3 54 #> [417,] -3 53 #> [418,] -2 52 #> [419,] -1 51 #> [420,] 0 50 #> [421,] 1 49 #> [422,] 2 48 #> [423,] 3 48 #> [424,] 4 48 #> [425,] 5 47 #> [426,] 6 47 #> [427,] 7 47 #> [428,] 8 48 #> [429,] 9 48 #> [430,] 10 48 #> [431,] 11 49 #> [432,] 12 49 #> [433,] 13 50 #> [434,] 14 51 #> [435,] 15 52 #> [436,] 15 53 #> [437,] 16 54 #> [438,] 16 55 #> [439,] 17 56 #> [440,] 17 57 #> [441,] 18 58 #> [442,] 18 59 #> [443,] 19 60 #> [444,] 19 61 #> [445,] 19 62 #> [446,] 20 63 #> [447,] 20 64 #> [448,] 20 65 #> [449,] 21 66 #> [450,] 21 67 #> [451,] 21 68 #> [452,] 22 69 #> [453,] 22 70 #> [454,] 22 71 #> [455,] 23 72 #> [456,] 23 73 #> [457,] 24 74 #> [458,] 24 75 #> [459,] 24 76 #> [460,] 25 77 #> [461,] 25 78 #> [462,] 26 79 #> [463,] 26 80 #> [464,] 27 81 #> [465,] 27 82 #> [466,] 28 83 #> [467,] 28 84 #> [468,] 29 85 #> [469,] 30 86 #> [470,] 31 87 #> [471,] 31 88 #> [472,] 32 89 #> [473,] 33 90 #> [474,] 34 91 #> [475,] 35 92 #> [476,] 36 93 #> [477,] 37 94 #> [478,] 38 94 #> [479,] 39 95 #> [480,] 40 96 #> [481,] 41 96 #> [482,] 42 97 #> [483,] 43 97 #> [484,] 44 98 #> [485,] 45 98 #> [486,] 46 99 #> [487,] 47 99 #> [488,] 48 99 #> [489,] 49 100 #> [490,] 50 100 #> [491,] 51 100 #> [492,] 52 100 #> [493,] 53 101 #> [494,] 54 101 #> [495,] 55 101 #> [496,] 56 101 #> [497,] 57 101 #> [498,] 58 101 #> [499,] 59 101 #> [500,] 60 101 #> [501,] 61 101 #> [502,] 62 101 #> [503,] 63 101 #> [504,] 64 101 #> [505,] 65 101 #> [506,] 66 101 #> [507,] 67 101 #> [508,] 68 101 #> [509,] 69 101 #> [510,] 70 101 #> [511,] 71 101 #> [512,] 72 101 #> [513,] 73 101 #> [514,] 74 101 #> [515,] 75 101 #> [516,] 76 101 #> [517,] 77 101 #> [518,] 78 101 #> [519,] 79 101 #> [520,] 80 101 #> [521,] 81 102 #> [522,] 82 101 #> [523,] 83 102 #> [524,] 82 103 #> [525,] 82 104 #> [526,] 82 105 #> [527,] 82 106 #> [528,] 81 107 #> [529,] 81 108 #> [530,] 81 109 #> [531,] 81 110 #> [532,] 80 111 #> [533,] 80 112 #> [534,] 80 113 #> [535,] 80 114 #> [536,] 79 115 #> [537,] 79 116 #> [538,] 79 117 #> [539,] 78 118 #> [540,] 78 119 #> [541,] 78 120 #> [542,] 78 121 #> [543,] 77 122 #> [544,] 77 123 #> [545,] 77 124 #> [546,] 77 125 #> [547,] 76 126 #> [548,] 76 127 #> [549,] 76 128 #> [550,] 76 129 #> [551,] 76 130 #> [552,] 75 131 #> [553,] 75 132 #> [554,] 75 133 #> [555,] 75 134 #> [556,] 75 135 #> [557,] 75 136 #> [558,] 76 137 #> [559,] 76 138 #> [560,] 77 139 #> [561,] 78 140 #> [562,] 79 140 #> [563,] 80 140 #> [564,] 81 140 #> [565,] 82 140 #> [566,] 83 141 #> [567,] 84 140 #> [568,] 85 140 #> [569,] 86 139 #> [570,] 87 139 #> [571,] 88 138 #> [572,] 89 138 #> [573,] 90 137 #> [574,] 91 136 #> [575,] 92 136 #> [576,] 93 135 #> [577,] 94 134 #> [578,] 95 134 #> [579,] 96 133 #> [580,] 97 132 #> [581,] 98 131 #> [582,] 99 131 #> [583,] 100 130 #> [584,] 101 129 #> [585,] 102 129 #> [586,] 103 128 #> [587,] 104 127 #> [588,] 105 126 #> [589,] 106 126 #> [590,] 107 125 #> [591,] 108 124 #> [592,] 109 124 #> [593,] 110 123 #> [594,] 111 122 #> [595,] 112 122 #> [596,] 113 121 #> [597,] 114 120 #> [598,] 115 119 #> [599,] 116 119 #> [600,] 117 118 #> [601,] 118 117 #> [602,] 119 117 #> [603,] 120 116 #> [604,] 121 115 #> [605,] 122 114 #> [606,] 123 114 #> [607,] 124 113 #> [608,] 125 112 #> [609,] 126 112 #> [610,] 127 111 #> [611,] 128 110 #> [612,] 129 110 #> [613,] 130 109 #> [614,] 131 108 #> [615,] 132 107 #> [616,] 133 107 #> [617,] 134 106 #> [618,] 135 105 #> [619,] 136 105 #> [620,] 137 104 #> [621,] 138 103 #> [622,] 139 102 #> [623,] 140 102 #> [624,] 141 101 #> [625,] 142 100 #> [626,] 143 100 #> [627,] 144 99 #> [628,] 145 98 #> [629,] 146 98 #> [630,] 147 97 #> [631,] 148 96 #> [632,] 149 95 #> [633,] 150 95 #> [634,] 151 94 #> [635,] 152 93 #> [636,] 153 93 #> [637,] 154 92 #> [638,] 155 91 #> [639,] 156 90 #> [640,] 157 90 #> [641,] 158 89 #> [642,] 159 88 #> [643,] 160 88 #> [644,] 161 87 #> [645,] 162 86 #> [646,] 163 86 #> [647,] 164 85 #> [648,] 165 84 #> [649,] 166 83 #> [650,] 167 83 #> [651,] 168 82 #> [652,] 169 81 #> [653,] 170 81 #> [654,] 171 80 #> [655,] 170 79 #> [656,] 169 78 #> [657,] 168 77 #> [658,] 167 77 #> [659,] 166 76 #> [660,] 165 75 #> [661,] 164 75 #> [662,] 163 74 #> [663,] 162 73 #> [664,] 161 72 #> [665,] 160 72 #> [666,] 159 71 #> [667,] 158 70 #> [668,] 157 70 #> [669,] 156 69 #> [670,] 155 68 #> [671,] 154 67 #> [672,] 153 67 #> [673,] 152 66 #> [674,] 151 65 #> [675,] 150 65 #> [676,] 149 64 #> [677,] 148 63 #> [678,] 147 63 #> [679,] 146 62 #> [680,] 145 61 #> [681,] 144 60 #> [682,] 143 60 #> [683,] 142 59 #> [684,] 141 58 #> [685,] 140 58 #> [686,] 139 57 #> [687,] 138 56 #> [688,] 137 55 #> [689,] 136 55 #> [690,] 135 54 #> [691,] 134 53 #> [692,] 133 53 #> [693,] 132 52 #> [694,] 131 51 #> [695,] 130 51 #> [696,] 129 50 #> [697,] 128 49 #> [698,] 127 48 #> [699,] 126 48 #> [700,] 125 47 #> [701,] 124 46 #> [702,] 123 46 #> [703,] 122 45 #> [704,] 121 44 #> [705,] 120 44 #> [706,] 119 43 #> [707,] 118 42 #> [708,] 117 41 #> [709,] 116 41 #> [710,] 115 40 #> [711,] 114 39 #> [712,] 113 38 #> [713,] 112 38 #> [714,] 111 37 #> [715,] 110 36 #> [716,] 109 36 #> [717,] 108 35 #> [718,] 107 34 #> [719,] 106 34 #> [720,] 105 33 #> [721,] 104 32 #> [722,] 103 31 #> [723,] 102 31 #> [724,] 101 30 #> [725,] 100 29 #> [726,] 99 29 #> [727,] 98 28 #> [728,] 97 27 #> [729,] 96 27 #> [730,] 95 26 #> [731,] 94 25 #> [732,] 93 24 #> [733,] 92 24 #> [734,] 91 23 #> [735,] 90 22 #> [736,] 89 22 #> [737,] 88 21 #> [738,] 87 20 #> [739,] 86 20 #> [740,] 85 19 #> [741,] 84 19 #> [742,] 83 19 #> [743,] 82 19 #> [744,] 81 18 #> [745,] 80 19 #> [746,] 79 19 #> [747,] 78 20 #> [748,] 77 21 #> [749,] 76 22 #> [750,] 75 23 #> [751,] 75 24 #> [752,] 75 25 #> [753,] 75 26 #> [754,] 75 27 #> [755,] 75 28 #> [756,] 75 29 #> [757,] 75 30 #> [758,] 76 31 #> [759,] 76 32 #> [760,] 76 33 #> [761,] 77 34 #> [762,] 77 35 #> [763,] 77 36 #> [764,] 77 37 #> [765,] 78 38 #> [766,] 78 39 #> [767,] 78 40 #> [768,] 78 41 #> [769,] 79 42 #> [770,] 79 43 #> [771,] 79 44 #> [772,] 79 45 #> [773,] 80 46 #> [774,] 80 47 #> [775,] 80 48 #> [776,] 80 49 #> [777,] 81 50 #> [778,] 81 51 #> [779,] 81 52 #> [780,] 81 53 #> [781,] 82 54 #> [782,] 82 55 #> [783,] 82 56 #> [784,] 83 57 #> [785,] 82 58 #> [786,] 81 58 #> [787,] 80 58 #> [788,] 79 59 #> [789,] 78 59 #> [790,] 77 59 #> [791,] 76 59 #> [792,] 75 59 #> [793,] 74 59 #> [794,] 73 59 #> [795,] 72 59 #> [796,] 71 59 #> [797,] 70 58 #> [798,] 69 58 #> [799,] 68 58 #> [800,] 67 58 #> [801,] 66 57 #> [802,] 65 57 #> [803,] 64 56 #> [804,] 63 55 #> [805,] 63 54 #> [806,] 63 53 #> [807,] 62 52 #> [808,] 62 51 #> [809,] 62 50 #> [810,] 61 49 #> [811,] 61 48 #> [812,] 60 47 #> [813,] 60 46 #> [814,] 60 45 #> [815,] 59 44 #> [816,] 59 43 #> [817,] 58 42 #> [818,] 58 41 #> [819,] 58 40 #> [820,] 57 39 #> [821,] 57 38 #> [822,] 56 37 #> [823,] 56 36 #> [824,] 56 35 #> [825,] 55 34 #> [826,] 55 33 #> [827,] 54 32 #> [828,] 54 31 #> [829,] 53 30 #> [830,] 53 29 #> [831,] 52 28 #> [832,] 52 27 #> [833,] 51 26 #> [834,] 50 25 #> [835,] 50 24 #> [836,] 49 23 #> [837,] 49 22 #> [838,] 48 21 #> [839,] 47 20 #> [840,] 46 19 #> [841,] 46 18 #> [842,] 45 17 #> [843,] 44 16 #> [844,] 43 15 #> [845,] 42 14 #> [846,] 41 13 #> [847,] 40 12 #> [848,] 39 11 #> [849,] 38 10 #> [850,] 37 9 #> [851,] 36 8 #> [852,] 35 8 #> [853,] 34 7 #> [854,] 33 7 #> [855,] 32 6 #> [856,] 31 5 #> [857,] 30 5 #> [858,] 29 4 #> [859,] 28 4 #> [860,] 27 3 #> [861,] 26 3 #> [862,] 25 3 #> [863,] 24 2 #> [864,] 23 2 #> [865,] 22 2 #> [866,] 21 2 #> [867,] 20 1 #> [868,] 19 1 #> [869,] 18 1 #> [870,] 17 1 #> [871,] 16 1 #> [872,] 15 0 #> [873,] 14 0 #> [874,] 13 0 #> [875,] 12 0 #> [876,] 11 0 #> [877,] 10 0 #> [878,] 9 0 #> [879,] 8 0 #> [880,] 7 0 #> [881,] 6 0 #> [882,] 5 0 #> [883,] 4 0 #> [884,] 3 0 #> [885,] 2 0 #> [886,] 1 0 #> [887,] 0 0"},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates Bezier coefficients from a shape — bezier","title":"Calculates Bezier coefficients from a shape — bezier","text":"Calculates Bezier coefficients shape","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates Bezier coefficients from a shape — bezier","text":"","code":"bezier(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates Bezier coefficients from a shape — bezier","text":"coo matrix list (x; y) coordinates n degree, default number coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates Bezier coefficients from a shape — bezier","text":"list components: $J matrix Bezier coefficients $B matrix Bezier vertices.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates Bezier coefficients from a shape — bezier","text":"Directly borrowed Claude (2008), also called bezier . implemented open outlines may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates Bezier coefficients from a shape — bezier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates Bezier coefficients from a shape — bezier","text":"","code":"set.seed(34) x <- coo_sample(efourier_shape(), 5) plot(x, ylim=c(-3, 3), asp=1, type='b', pch=20) b <- bezier(x) bi <- bezier_i(b$B) lines(bi, col='red')"},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates a shape from Bezier coefficients — bezier_i","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Calculates shape Bezier coefficients","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"","code":"bezier_i(B, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"B matrix Bezier vertices, produced bezier nb.pts number points sample along curve.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"matrix (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Directly borrowed Claude (2008), called beziercurve . implemented open outlines may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"","code":"set.seed(34) x <- coo_sample(efourier_shape(), 5) plot(x, ylim=c(-3, 3), asp=1, type='b', pch=20) b <- bezier(x) bi <- bezier_i(b$B) lines(bi, col='red')"},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Boxplot of morphometric coefficients — boxplot.OutCoe","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"Explores distribution coefficient values.","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"","code":"# S3 method for OutCoe boxplot(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"x Coe object ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"ggplot2 object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"","code":"# on OutCoe bot %>% efourier(9) %>% rm_harm(1) %>% boxplot() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details data(olea) op <- opoly(olea) #> 'nb.pts' missing and set to 91 #> 'degree' missing and set to 5 boxplot(op)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Boxplot on PCA objects — boxplot.PCA","title":"Boxplot on PCA objects — boxplot.PCA","text":"Boxplot PCA objects","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boxplot on PCA objects — boxplot.PCA","text":"","code":"# S3 method for PCA boxplot(x, fac = NULL, nax, ...)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Boxplot on PCA objects — boxplot.PCA","text":"x PCA, typically obtained PCA fac factor, name column id $fac slot nax range PC plot (1 99pc total variance default) ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Boxplot on PCA objects — boxplot.PCA","text":"ggplot object","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boxplot on PCA objects — boxplot.PCA","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) boxplot(bot.p) #> `prop` not provided. All axes returned p <- boxplot(bot.p, 1) #> `prop` not provided. All axes returned #p + theme_minimal() + scale_fill_grey() #p + facet_wrap(~PC, scales = \"free\")"},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":null,"dir":"Reference","previous_headings":"","what":"Jitters Coe (and others) objects — breed","title":"Jitters Coe (and others) objects — breed","text":"methods applies column-wise coe Coe object relies function can used matrix. simply uses rnorm mean sd calculated every column (row). Coe object, every colum, randomly generates coefficients values centered mean column, sd equals standard deviates multiplied rate.","code":""},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Jitters Coe (and others) objects — breed","text":"","code":"breed(x, ...) # S3 method for default breed(x, fac, margin = 2, size, rate = 1, ...) # S3 method for Coe breed(x, fac, size, rate = 1, ...)"},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Jitters Coe (and others) objects — breed","text":"x object permute ... useless fac column, formula column id $fac margin numeric whether 1 2 (rows columns) size numeric required size final object, size default rate numeric number sd rnorm, 1 default.","code":""},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Jitters Coe (and others) objects — breed","text":"Coe object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Jitters Coe (and others) objects — breed","text":"","code":"m <- matrix(1:12, nrow=3) breed(m, margin=2, size=4) #> [,1] [,2] [,3] [,4] #> [1,] 2.670620 4.597120 8.401255 9.157338 #> [2,] 1.150985 5.719108 9.356390 10.720259 #> [3,] 3.066805 4.819941 8.019227 9.469230 #> [4,] 1.992539 6.046191 7.530582 13.546154 breed(m, margin=1, size=10) #> [,1] [,2] [,3] #> [1,] 1.30970018 1.769321 -1.5597512 #> [2,] -0.01744358 6.486750 0.5512378 #> [3,] 7.13301779 9.320377 7.0219317 #> [4,] 8.52622563 4.558342 10.8915399 #> [5,] 2.01645375 7.194958 8.0983293 #> [6,] 3.54852287 6.733022 14.7962926 #> [7,] 4.57290872 6.963033 4.4282392 #> [8,] 10.02364430 6.407625 10.4446975 #> [9,] 2.40882230 3.826442 11.5882377 #> [10,] 10.19002487 4.197451 3.2041191 bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.m <- breed(bot.f, size=80) bot.m %>% PCA %>% plot #> will be deprecated soon, see ?plot_PCA # breed fac wise # bot.f %>% breed(~type, size=50) %>% PCA %>% plot(~type)"},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert between different classes — bridges","title":"Convert between different classes — bridges","text":"Convert different classes","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert between different classes — bridges","text":"","code":"l2m(l) m2l(m) d2m(d) m2d(m) l2a(l) a2l(a) a2m(a) m2a(m) m2ll(m, index = NULL)"},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert between different classes — bridges","text":"l list x y coordinates components m matrix (x; y) coordinates d data.frame two columns array (x; y) coordinates index numeric, number coordinates every slice","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert between different classes — bridges","text":"data required class","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Convert between different classes — bridges","text":"a2m/m2a change, essence, dimension data. m2ll used internally hanle coo cur Ldk objects may useful elsewhere","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert between different classes — bridges","text":"","code":"# matrix/list wings[1] %>% coo_sample(4) %>% m2l() %T>% print %>% # matrix to list l2m() # and back #> $x #> [1] -0.4933 0.2645 0.0424 -0.1768 #> #> $y #> [1] 0.0130 0.0261 -0.0966 0.0341 #> #> x y #> [1,] -0.4933 0.0130 #> [2,] 0.2645 0.0261 #> [3,] 0.0424 -0.0966 #> [4,] -0.1768 0.0341 # data.frame/matrix wings[1] %>% coo_sample(4) %>% m2d() %T>% print %>% # matrix to data.frame d2m # and back #> # A tibble: 4 × 2 #> x y #> #> 1 -0.493 0.013 #> 2 0.264 0.0261 #> 3 0.0424 -0.0966 #> 4 -0.177 0.0341 #> x y #> [1,] -0.4933 0.0130 #> [2,] 0.2645 0.0261 #> [3,] 0.0424 -0.0966 #> [4,] -0.1768 0.0341 # list/array wings %>% slice(1:2) %$% coo %>% l2a %T>% print %>% # list to array a2l # and back #> , , AN1 #> #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> , , AN2 #> #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> #> [[1]] #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> [[2]] #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> # array/matrix wings %>% slice(1:2) %$% l2a(coo) %>% # and array (from a list) a2m %T>% print %>% # to matrix m2a # and back #> x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 #> AN1 -0.4933 -0.0777 0.2231 0.2641 0.2645 0.2471 0.2311 0.2040 0.1282 0.0424 #> AN2 -0.4814 -0.0058 0.2345 0.2460 0.2487 0.2430 0.2316 0.1956 0.1462 0.0483 #> x11 x12 x13 x14 x15 x16 x17 x18 y1 y2 #> AN1 -0.0674 -0.4102 -0.3140 -0.1768 0.0715 -0.0540 0.0575 -0.1401 0.0130 0.0832 #> AN2 -0.0520 -0.4016 -0.3868 -0.1808 0.0484 -0.0519 0.0623 -0.1444 0.0135 0.0780 #> y3 y4 y5 y6 y7 y8 y9 y10 y11 y12 #> AN1 0.0861 0.0462 0.0261 0.0003 -0.0228 -0.0452 -0.0742 -0.0966 -0.1108 -0.0163 #> AN2 0.0644 0.0467 0.0281 0.0115 -0.0039 -0.0305 -0.0545 -0.0866 -0.1047 -0.0250 #> y13 y14 y15 y16 y17 y18 #> AN1 0.0318 0.0341 0.0509 0.0238 -0.0059 -0.0240 #> AN2 0.0166 0.0229 0.0405 0.0164 -0.0047 -0.0286 #> , , AN1 #> #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> , , AN2 #> #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> # m2ll m2ll(wings[1], c(6, 4, 3, 5)) # grab slices and coordinates #> [[1]] #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> #> [[2]] #> [,1] [,2] #> [1,] 0.2311 -0.0228 #> [2,] 0.2040 -0.0452 #> [3,] 0.1282 -0.0742 #> [4,] 0.0424 -0.0966 #> #> [[3]] #> [,1] [,2] #> [1,] -0.0674 -0.1108 #> [2,] -0.4102 -0.0163 #> [3,] -0.3140 0.0318 #> #> [[4]] #> [,1] [,2] #> [1,] -0.1768 0.0341 #> [2,] 0.0715 0.0509 #> [3,] -0.0540 0.0238 #> [4,] 0.0575 -0.0059 #> [5,] -0.1401 -0.0240 #>"},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"Calculate deviations original reconstructed shapes using range harmonic number.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"","code":"calibrate_deviations() calibrate_deviations_efourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_tfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_rfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_sfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_npoly( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_opoly( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_dfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"x Opn object calibrate_deviations id shape perform calibrate_deviations range vector harmonics (degree opoly npoly Opn) perform calibrate_deviations. provided, harmonics corresponding 0.9, 0.95 0.99% harmonic power used. norm.centsize logical whether normalize deviation centroid size dist.method method edm_nearest calculate deviations interpolate.factor numeric increase number points original shape (1 default) dist.nbpts numeric number points use deviations calculations plot logical whether print graph (FALSE just want calculations)","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"ggplot object full list intermediate results. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"Note version 1.1, calculation changed fixed problem. , 'best' possible shape calculated using highest possible number harmonics. worked well efourier others (eg rfourier, tfourier) known unstable high number harmonics. now , Momocs uses 'real' shape, (must centered) uses coo_interpolate produce interpolate.factor times coordinates shape using default dist.method, eg edm_nearest, latter finds euclidean distance, point reconstructed shape, closest point interpolated shape. interpolate.factor set 1 default, interpolation made ask . Note, interpolation decrease artefactual errors may also done outside calibrate_deviations probably removed versions. Note also code quite old now need good review, planned 2018. *poly methods Opn objects, deviations calculated degree 12 polynom.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"","code":"b5 <- slice(bot, 1:5) #for the sake of speed b5 %>% calibrate_deviations_efourier() b5 %>% calibrate_deviations_rfourier() #> 'range' was too high and set to 4 15 27 39 51 63 b5 %>% calibrate_deviations_tfourier() #> 'range' was too high and set to 4 15 27 39 51 63 b5 %>% calibrate_deviations_sfourier() o5 <- slice(olea, 1:5) #for the sake of speed o5 %>% calibrate_deviations_opoly() #> 'range' was missing and set to 1:8 #> deviations calculated from a degree 12 polynom o5 %>% calibrate_deviations_npoly() #> 'range' was missing and set to 1:8 #> deviations calculated from a degree 12 polynom o5 %>% calibrate_deviations_dfourier() #> 'range' was missing and set to 1:8"},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"Estimates number harmonics required four Fourier methods implemented Momocs: elliptical Fourier analysis (see efourier), radii variation analysis (see rfourier) tangent angle analysis (see tfourier) discrete Fourier transform (see dfourier). returns can plot cumulated harmonic power whether dropping first harmonic , based maximum possible number harmonics Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"","code":"calibrate_harmonicpower() calibrate_harmonicpower_efourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_rfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_tfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_sfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_dfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"x Coo Opn object id shapes perform calibrate_harmonicpower. default nb.h numeric maximum number harmonic, base cumsum drop numeric number harmonics drop cumulative sum thresh vector numeric drawing horizontal lines, also used minh plot logical whether plot result simply return matrix Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"returns list component: gg ggplot object, q quantile matrix minh quick summary returns number harmonics required achieve certain proportion total harmonic power.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"power given harmonic \\(n\\) calculated follows elliptical Fourier analysis n-th harmonic: \\(HarmonicPower_n \\frac{^2_n+B^2_n+C^2_n+D^2_n}{2}\\) follows radii variation tangent angle: \\(HarmonicPower_n= \\frac{^2_n+B^2_n+C^2_n+D^2_n}{2}\\)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"","code":"b5 <- bot %>% slice(1:5) b5 %>% calibrate_harmonicpower_efourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 12.04060 75.93567 84.25707 96.30510 97.54758 98.98871 99.14762 #> caney 25.32919 83.82352 85.52977 97.63251 97.95722 98.48376 98.74498 #> chimay 43.52623 81.74374 87.15624 95.19669 97.62725 98.26072 99.08266 #> corona 18.77387 85.07047 86.60786 97.10591 97.52603 98.19450 98.53979 #> deusventrue 50.01648 89.72983 91.60975 97.48378 98.24316 98.89288 99.54427 #> h8 h9 h10 h11 #> brahma 99.17820 99.56150 99.70128 100 #> caney 99.09524 99.82995 99.92629 100 #> chimay 99.13936 99.92633 99.95030 100 #> corona 99.35699 99.85405 99.92437 100 #> deusventrue 99.59558 99.85220 99.85638 100 #> #> $minh #> 90% 95% 99% 99.9% #> 5 5 8 11 #> b5 %>% calibrate_harmonicpower_rfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 18.78231 33.31995 46.22113 58.10127 67.82970 75.05028 80.97400 #> caney 17.93853 31.33704 42.78188 53.62717 63.27019 70.92538 77.13956 #> chimay 20.15608 32.00851 42.30386 53.69956 63.83688 70.62474 75.70937 #> corona 18.06902 31.19196 42.46484 53.47544 63.40792 71.15173 77.21493 #> deusventrue 16.53275 28.35109 38.13251 47.97348 57.90690 66.78889 74.09914 #> h8 h9 h10 h11 #> brahma 86.70633 92.03264 96.35923 100 #> caney 83.17596 89.45355 95.26884 100 #> chimay 81.97629 89.53235 95.96736 100 #> corona 83.10189 89.40501 95.31295 100 #> deusventrue 80.55553 87.12697 93.87388 100 #> #> $minh #> 90% 95% 99% 99.9% #> 11 11 12 12 #> b5 %>% calibrate_harmonicpower_tfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 59.14067 61.93044 70.84946 73.04960 78.52305 82.00362 83.54236 #> caney 74.23211 77.03198 79.47862 80.42583 81.02169 83.35008 88.47033 #> chimay 51.55592 60.87755 75.55970 82.94807 85.87674 86.60314 87.96999 #> corona 78.37418 84.46833 88.93940 91.30081 91.99456 92.38160 96.07474 #> deusventrue 57.24983 77.47110 86.13551 88.20041 90.42190 93.82247 94.37464 #> h8 h9 h10 h11 #> brahma 88.78847 90.73935 95.65795 100 #> caney 92.95646 93.61725 99.86646 100 #> chimay 95.63758 95.97542 98.66043 100 #> corona 96.39414 97.01762 99.03821 100 #> deusventrue 97.00523 98.45247 99.28416 100 #> #> $minh #> 90% 95% 99% 99.9% #> 9 9 11 12 #> b5 %>% calibrate_harmonicpower_sfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 99.38619 99.44134 99.59446 99.83182 99.92895 99.93156 99.94529 #> caney 99.16488 99.60429 99.82594 99.87251 99.91648 99.95231 99.95269 #> chimay 97.21123 99.21819 99.30029 99.82089 99.87238 99.93107 99.95593 #> corona 99.36094 99.61770 99.72283 99.76601 99.89668 99.95608 99.95715 #> deusventrue 97.32291 99.46403 99.50564 99.53357 99.60031 99.93841 99.94526 #> h8 h9 h10 h11 #> brahma 99.98484 99.98487 99.98688 100 #> caney 99.99360 99.99611 99.99624 100 #> chimay 99.99704 99.99727 99.99749 100 #> corona 99.98672 99.99443 99.99756 100 #> deusventrue 99.97166 99.97681 99.99946 100 #> #> $minh #> 90% 95% 99% 99.9% #> 2 2 2 7 #> # on Opn olea %>% slice(1:5) %>% calibrate_harmonicpower_dfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 #> 0001-cAglan_O10VD 82.53723 88.47281 96.36372 96.81316 98.24342 98.36453 #> 0001-cAglan_O10VL 73.05735 86.54342 94.76133 95.98041 97.40877 97.59487 #> 0001-cAglan_O11VD 76.24284 87.88560 93.49305 94.48904 96.36358 96.62580 #> 0001-cAglan_O11VL 84.21060 91.19903 96.81949 97.09514 98.06219 98.13718 #> 0001-cAglan_O12VD 83.66767 87.90200 95.83034 95.91726 97.55019 97.57227 #> h7 h8 h9 h10 h11 #> 0001-cAglan_O10VD 98.95059 98.99292 99.48780 99.50151 100 #> 0001-cAglan_O10VL 98.45031 98.49851 99.23945 99.26011 100 #> 0001-cAglan_O11VD 97.63205 97.76921 98.91878 99.00197 100 #> 0001-cAglan_O11VL 98.80533 98.83142 99.42881 99.43860 100 #> 0001-cAglan_O12VD 98.59264 98.60478 99.36939 99.37605 100 #> #> $minh #> 90% 95% 99% 99.9% #> 4 4 10 12 #> # \\donttest{ # let customize the ggplot library(ggplot2) cal <- b5 %>% calibrate_harmonicpower_efourier(nb.h=12) cal$gg + theme_minimal() + coord_cartesian(xlim=c(3.5, 12.5), ylim=c(90, 100)) + ggtitle(\"Harmonic power calibration\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one. # }"},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative r2 calibration for Opn objects — calibrate_r2","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Estimates r2 calibrate degree npoly opoly methods. Also returns plot","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"","code":"calibrate_r2() calibrate_r2_opoly( Opn, id = 1:length(Opn), degree.range = 1:8, thresh = c(0.9, 0.95, 0.99, 0.999), plot = TRUE, ... ) calibrate_r2_npoly( Opn, id = 1:length(Opn), degree.range = 1:8, thresh = c(0.9, 0.95, 0.99, 0.999), plot = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Opn Opn object id ids shapes calculate r2 (default) degree.range calculate r2 thresh threshold return diagnostic plot logical whether print plot ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"ggpot2 object","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"May long, can estimate sample either id , one sample_n sample_frac","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"","code":"olea %>% slice(1:5) %>% #for the sake of spped calibrate_r2_opoly(degree.range=1:5, thresh=c(0.9, 0.99)) #> $gg #> #> $q #> degree1 degree2 degree3 degree4 degree5 #> 0001-cAglan_O10VD 0.0004287127 0.9821251 0.9831469 0.9986415 0.9987220 #> 0001-cAglan_O10VL 0.0011742448 0.9838978 0.9841793 0.9955520 0.9972836 #> 0001-cAglan_O11VD 0.0123113197 0.9706618 0.9906431 0.9965470 0.9965690 #> 0001-cAglan_O11VL 0.0151312838 0.9459654 0.9796698 0.9958102 0.9963290 #> 0001-cAglan_O12VD 0.0002310795 0.9673982 0.9674270 0.9912600 0.9938820 #> #> $mind #> 0.9 0.99 #> 2 4 #> olea %>% slice(1:5) %>% #for the sake of spped calibrate_r2_npoly(degree.range=1:5, thresh=c(0.9, 0.99)) #> $gg #> #> $q #> degree1 degree2 degree3 degree4 degree5 #> 0001-cAglan_O10VD 0.0004287127 0.9821251 0.9831469 0.9986415 0.9987220 #> 0001-cAglan_O10VL 0.0011742448 0.9838978 0.9841793 0.9955520 0.9972836 #> 0001-cAglan_O11VD 0.0123113197 0.9706618 0.9906431 0.9965470 0.9965690 #> 0001-cAglan_O11VL 0.0151312838 0.9459654 0.9796698 0.9958102 0.9963290 #> 0001-cAglan_O12VD 0.0002310795 0.9673982 0.9674270 0.9912600 0.9938820 #> #> $mind #> 0.9 0.99 #> 2 4 #>"},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calibrate using reconstructed shapes — calibrate_reconstructions","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"Calculate displays reconstructed shapes using range harmonic number. Compare visually maximal fit. explicitely demonstrates robust efourier compared tfourier rfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"","code":"calibrate_reconstructions_efourier(x, id, range = 1:9) calibrate_reconstructions_rfourier(x, id, range = 1:9) calibrate_reconstructions_tfourier(x, id, range = 1:9) calibrate_reconstructions_sfourier(x, id, range = 1:9) calibrate_reconstructions_npoly( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) ) calibrate_reconstructions_opoly( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) ) calibrate_reconstructions_dfourier( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"x Coo object calibrate_reconstructions id shape perform calibrate_reconstructions range vector harmonics perform calibrate_reconstructions baseline1 \\((x; y)\\) coordinates first point baseline baseline2 \\((x; y)\\) coordinates second point baseline","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"ggplot object full list intermediate results. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"","code":"### On Out shapes %>% calibrate_reconstructions_efourier(id=1, range=1:6) # you may prefer efourier... shapes %>% calibrate_reconstructions_tfourier(id=1, range=1:6) #' you may prefer efourier... shapes %>% calibrate_reconstructions_rfourier(id=1, range=1:6) #' you may prefer efourier... # todo #shapes %>% # calibrate_reconstructions_sfourier(id=5, range=1:6) ### On Opn olea %>% calibrate_reconstructions_opoly(id=1) olea %>% calibrate_reconstructions_npoly(id=1) olea %>% calibrate_reconstructions_dfourier(id=1)"},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":null,"dir":"Reference","previous_headings":"","what":"Split to several objects based on a factor — chop","title":"Split to several objects based on a factor — chop","text":"Rougher slicing accepts classifier ie column name $fac Momocs classes. Returns named (every level) list can lapply-ed combined. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split to several objects based on a factor — chop","text":"","code":"chop(.data, fac)"},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split to several objects based on a factor — chop","text":".data Coo Coe object fac column name $fac","code":""},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split to several objects based on a factor — chop","text":"named list Coo Coe objects","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split to several objects based on a factor — chop","text":"","code":"olea %>% filter(var == \"Aglan\") %>% # to have a balanced nb of 'view' chop(~view) %>% # split into a list of 2 npoly %>% # separately apply npoly # strict equivalent to lapply(npoly) combine %>% # recombine PCA %>% plot # an illustration of the 2 views #> 'nb.pts' missing and set to: 95 #> 'degree' missing and set to: 5 #> 'nb.pts' missing and set to: 91 #> 'degree' missing and set to: 5 #> will be deprecated soon, see ?plot_PCA # treated separately"},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate classification metrics on a confusion matrix — classification_metrics","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"cases, class correctness proportion correctly classified individuals enough, detailed metrics working classification.","code":""},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"","code":"classification_metrics(x)"},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"x table LDA object","code":""},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"list following components returned: accuracy fraction instances correctly classified macro_prf data.frame containing precision (fraction correct predictions certain class); recall, fraction instances class correctly predicted; f1 harmonic mean (weighted average) precision recall. macro_avg, just average three macro_prf indices ova list one-vs-confusion matrices class ova_sum single ova matrices kappa measure agreement predictions actual labels","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"","code":"# some morphometrics on 'hearts' hearts %>% fgProcrustes(tol=1) %>% coo_slide(ldk=1) %>% efourier(norm=FALSE) %>% PCA() %>% # now the LDA and its summary LDA(~aut) %>% classification_metrics() #> iteration: 1 \tgain: 30322 #> iteration: 2 \tgain: 1.2498 #> iteration: 3 \tgain: 0.34194 #> 'nb.h' set to 7 (99% harmonic power) #> 11 PC retained #> $accuracy #> [1] 0.7666667 #> #> $macro_prf #> # A tibble: 8 × 3 #> precision recall f1 #> #> 1 0.839 0.867 0.852 #> 2 0.75 0.8 0.774 #> 3 0.542 0.433 0.481 #> 4 0.893 0.833 0.862 #> 5 0.893 0.833 0.862 #> 6 0.812 0.867 0.839 #> 7 0.871 0.9 0.885 #> 8 0.529 0.6 0.562 #> #> $macro_avg #> # A tibble: 1 × 3 #> avg_precision avg_recall avg_f1 #> #> 1 0.766 0.767 0.765 #> #> $ova #> $ova$ced #> classified #> actual ced others #> ced 26 4 #> others 5 205 #> #> $ova$jeya #> classified #> actual jeya others #> jeya 24 6 #> others 8 202 #> #> $ova$mat #> classified #> actual mat others #> mat 13 17 #> others 11 199 #> #> $ova$ponnu #> classified #> actual ponnu others #> ponnu 25 5 #> others 3 207 #> #> $ova$remi #> classified #> actual remi others #> remi 25 5 #> others 3 207 #> #> $ova$rom #> classified #> actual rom others #> rom 26 4 #> others 6 204 #> #> $ova$ruks #> classified #> actual ruks others #> ruks 27 3 #> others 4 206 #> #> $ova$vince #> classified #> actual vince others #> vince 18 12 #> others 16 194 #> #> #> $ova_sum #> classified #> actual relevant others #> relevant 184 56 #> others 56 1624 #> #> $kappa #> [1] 0.7333333 #>"},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":null,"dir":"Reference","previous_headings":"","what":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"Momocs uses colnamed matrices store (typically) Fourier coefficients Coe objects (typically OutCoe). arranged rank-wise: A1, A2, ..., , B1, ..., Bn, C1, ..., Cn, D1, ..., Dn. softwares may arrive A1, B1, C1, D1, ..., , Bn, Cn, Dn, functions helps go one format. short, function rearranges column order. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"","code":"coeff_rearrange(x, by = c(\"name\", \"rank\")[1])"},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"x matrix (colnames) character either \"name\" (A1, A2, ..) \"rank\" (A1, B1, ...)","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"","code":"m_name <- m_rank <- matrix(1:32, 2, 16) # this one is ordered by name colnames(m_name) <- paste0(rep(letters[1:4], each=4), 1:4) # this one is ordered by rank colnames(m_rank) <- paste0(letters[1:4], rep(1:4, each=4)) m_rank #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_rank %>% coeff_rearrange(by=\"name\") #> Warning: `arrange_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `arrange()` instead. #> ℹ See vignette('programming') for more help #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 9 17 25 3 11 19 27 5 13 21 29 7 15 23 31 #> [2,] 2 10 18 26 4 12 20 28 6 14 22 30 8 16 24 32 m_rank %>% coeff_rearrange(by=\"rank\") #no change #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name %>% coeff_rearrange(by=\"name\") # no change #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name %>% coeff_rearrange(by=\"rank\") #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 9 17 25 3 11 19 27 5 13 21 29 7 15 23 31 #> [2,] 2 10 18 26 4 12 20 28 6 14 22 30 8 16 24 32"},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":null,"dir":"Reference","previous_headings":"","what":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"coeff_sel helps select given number harmonics returning indices arranged numeric vector. instance, harmonic coefficients arranged $coe slot Coe-objects way: \\(A_1, \\dots, A_n, B_1, \\dots, B_n, C_1, \\dots, C_n, D_1, \\dots, D-n\\) elliptical Fourier analysis (see efourier efourier) \\(C_n D_n\\) harmonic absent radii variation tangent angle approaches (see rfourier tfourier respectively). . function used internally might interest elwewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"","code":"coeff_sel(retain = 8, drop = 0, nb.h = 32, cph = 4)"},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"retain numeric. number harmonics retain. drop numeric. number harmonics drop nb.h numeric. maximum harmonic rank. cph numeric. Must set 2 rfourier tfourier used.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"coeff_sel returns indices can used select columns harmonic coefficient matrix. coeff_split returns named list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"","code":"bot.f <- efourier(bot, 32) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details coe <- bot.f$coe # the raw matrix coe #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 1 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> franziskaner 1 0.007314669 0.09110003 0.01294912 0.023136784 0.010558958 #> grimbergen 1 0.009522713 0.08573641 0.01974880 0.012878126 0.008485338 #> guiness 1 0.009589570 0.08825041 0.02268926 0.017770767 0.010695823 #> hoegardeen 1 0.009598003 0.09186435 0.01393702 0.020136724 0.008952962 #> jupiler 1 0.008152360 0.09595083 0.01206957 0.023549986 0.007484692 #> kingfisher 1 0.007788546 0.09459391 0.01346605 0.024571428 0.009229773 #> latrappe 1 0.018476561 0.06035470 0.03974568 0.010493387 0.026379718 #> lindemanskriek 1 0.012406103 0.09289294 0.01773845 0.020632152 0.010949655 #> nicechouffe 1 0.015167563 0.09058037 0.02094971 0.020007417 0.014345165 #> pecheresse 1 0.008436476 0.09409400 0.01181167 0.022221176 0.007960411 #> sierranevada 1 0.015038107 0.08208708 0.02647382 0.013697543 0.013869924 #> tanglefoot 1 0.018782346 0.07275504 0.03848616 0.008439294 0.018172933 #> tauro 1 0.007333709 0.09536301 0.01149374 0.023043384 0.007093187 #> westmalle 1 0.009100416 0.09469091 0.01450202 0.023460557 0.009582984 #> amrut 1 0.004198631 0.09500128 0.02143863 0.026005715 0.011729658 #> ballantines 1 -0.000653116 0.05733309 0.03154946 0.017516836 0.034198742 #> bushmills 1 -0.004927807 0.08149528 0.01036776 0.023910616 0.017320375 #> chivas 1 0.021613712 0.08642271 0.04314511 0.008460823 0.014376414 #> dalmore 1 0.038669436 0.07265717 0.05680730 0.003277741 0.019363348 #> famousgrouse 1 0.003373189 0.08802317 0.02019928 0.025507211 0.016776448 #> glendronach 1 0.003257554 0.09526153 0.02074249 0.026167146 0.010932661 #> glenmorangie 1 0.008572527 0.09410920 0.02136020 0.024756735 0.011430941 #> highlandpark 1 -0.002122354 0.06989902 0.03612531 0.023554876 0.027350465 #> jackdaniels 1 0.008777794 0.08626120 0.02940216 0.019373419 0.015295504 #> jb 1 0.004384491 0.09517564 0.02460733 0.023505329 0.010741163 #> johnniewalker 1 0.002370576 0.08321025 0.01719991 0.022474617 0.017724976 #> magallan 1 -0.008648015 0.09924533 0.01455296 0.037258989 0.011586345 #> makersmark 1 0.016536161 0.10229688 0.03388156 0.008773613 0.010192259 #> oban 1 0.001652893 0.09909342 0.02127249 0.028337047 0.009671380 #> oldpotrero 1 0.022935601 0.09391465 0.03109455 0.009138035 0.012979620 #> redbreast 1 0.017769276 0.09281598 0.04425688 0.011246633 0.012792733 #> tamdhu 1 0.005270821 0.09375949 0.02020814 0.025073663 0.010943288 #> wildturkey 1 0.008605609 0.09229119 0.03228916 0.020978082 0.013010663 #> yoichi 1 -0.001738226 0.07733113 0.02843759 0.024035740 0.023420967 #> A7 A8 A9 A10 #> brahma 0.0031835706 0.005158502 -7.262824e-04 0.0047287291 #> caney 0.0035527091 0.007010166 1.214949e-03 0.0038734169 #> chimay -0.0047412879 0.007814037 -2.112661e-03 0.0022043011 #> corona 0.0055045888 0.007852411 8.767189e-04 0.0044201528 #> deusventrue 0.0025214510 0.011391904 -1.733965e-03 0.0062083192 #> duvel -0.0016871288 0.011025502 -1.042906e-04 0.0017042044 #> franziskaner 0.0045813399 0.006927102 -5.793922e-04 0.0045217266 #> grimbergen -0.0021957902 0.008213656 -1.577404e-03 0.0026346248 #> guiness -0.0015195731 0.008550727 2.093772e-04 0.0060163830 #> hoegardeen 0.0024034912 0.007507503 -1.234721e-03 0.0046892597 #> jupiler 0.0055270378 0.006597011 1.073131e-03 0.0041448892 #> kingfisher 0.0059527872 0.006778517 1.169809e-03 0.0044984721 #> latrappe -0.0057950372 0.005954999 -5.463098e-03 -0.0001140651 #> lindemanskriek 0.0033428880 0.008381096 -1.707332e-04 0.0050506285 #> nicechouffe 0.0026214920 0.010288304 -4.913646e-04 0.0065828560 #> pecheresse 0.0046954032 0.006669592 4.015144e-05 0.0042466561 #> sierranevada -0.0043828769 0.009275932 -1.465646e-03 0.0059555586 #> tanglefoot -0.0108560295 0.008370133 -2.988319e-03 0.0052185654 #> tauro 0.0052560957 0.006425077 9.461829e-04 0.0040141970 #> westmalle 0.0051463840 0.006848999 3.534839e-04 0.0042382642 #> amrut 0.0019176785 0.008515916 1.392307e-03 0.0089150426 #> ballantines 0.0045419501 0.014014932 -5.273138e-03 0.0006083616 #> bushmills 0.0095020099 0.012457087 -3.988679e-04 0.0048132802 #> chivas -0.0053775410 0.013797633 2.198119e-03 0.0031741809 #> dalmore -0.0072008170 0.012093037 5.368701e-03 0.0025492686 #> famousgrouse 0.0035195429 0.008617844 -1.621645e-03 0.0075384656 #> glendronach 0.0018504691 0.007851391 1.483976e-03 0.0086527932 #> glenmorangie 0.0023552959 0.007521806 1.103445e-03 0.0069834516 #> highlandpark -0.0024258364 0.003973480 -7.894105e-03 0.0013284975 #> jackdaniels -0.0047279969 0.008903250 -2.124758e-03 0.0090062900 #> jb -0.0015584637 0.008915452 4.097146e-04 0.0089915939 #> johnniewalker 0.0034197782 0.009945811 -3.913888e-03 0.0059350940 #> magallan 0.0095026108 0.003088506 1.575409e-03 0.0054824432 #> makersmark 0.0003303914 0.016520390 -1.901653e-03 0.0031138042 #> oban 0.0022492968 0.007479292 2.478319e-03 0.0090114539 #> oldpotrero 0.0015843674 0.012237947 -4.671411e-04 0.0023549220 #> redbreast -0.0046107656 0.015170859 3.884228e-03 0.0045806501 #> tamdhu 0.0013188307 0.006535142 1.700604e-04 0.0072170216 #> wildturkey -0.0038244377 0.010171775 1.641229e-03 0.0092477531 #> yoichi -0.0011328612 0.006117569 -8.008551e-03 0.0034639875 #> A11 A12 A13 A14 #> brahma -0.0013733386 0.0016363823 -2.308262e-03 -8.638239e-05 #> caney -0.0018777601 0.0011330555 -6.140388e-04 9.095865e-04 #> chimay -0.0012371979 -0.0018514226 4.671292e-04 -2.460672e-03 #> corona -0.0021742849 0.0026300698 -1.040704e-03 1.308265e-03 #> deusventrue -0.0007936789 0.0028680575 -3.667224e-05 4.628731e-04 #> duvel -0.0006045816 -0.0028942242 1.911167e-03 -1.075121e-03 #> franziskaner -0.0015947508 0.0021935018 -1.336804e-03 4.860914e-04 #> grimbergen -0.0035563564 -0.0004162333 -4.598763e-04 -6.524229e-04 #> guiness -0.0015222476 0.0005646464 -7.106716e-04 2.998013e-04 #> hoegardeen -0.0024579838 0.0023152691 -1.583256e-03 6.149144e-04 #> jupiler -0.0009974596 0.0023379940 -7.214137e-04 9.925517e-04 #> kingfisher -0.0004648420 0.0023788807 -4.654563e-04 7.413209e-04 #> latrappe 0.0015068375 -0.0015514855 2.342018e-03 -3.056608e-03 #> lindemanskriek -0.0009359325 0.0022848386 -6.636932e-04 3.522544e-04 #> nicechouffe -0.0007619565 0.0033654095 1.927898e-05 1.210854e-03 #> pecheresse -0.0013782823 0.0024185755 -1.351070e-03 7.509854e-04 #> sierranevada -0.0017933279 -0.0005349683 -1.031914e-03 -1.110401e-03 #> tanglefoot -0.0003179777 -0.0031166695 -6.330130e-04 -4.040699e-03 #> tauro -0.0010466330 0.0023514452 -6.553020e-04 1.065380e-03 #> westmalle -0.0004882420 0.0023217071 -3.503062e-04 3.148159e-04 #> amrut -0.0004155995 0.0028189180 -2.329164e-03 1.315932e-03 #> ballantines -0.0024674938 -0.0002274846 3.091761e-03 4.251026e-05 #> bushmills -0.0043970618 0.0017818484 -2.593370e-03 1.904341e-03 #> chivas -0.0016654883 -0.0026415175 2.038443e-03 -1.394657e-03 #> dalmore 0.0025922354 -0.0039822137 2.797073e-03 -1.626359e-03 #> famousgrouse 0.0001300206 0.0046515437 -1.163558e-03 2.084764e-04 #> glendronach -0.0002084792 0.0025405566 -2.450515e-03 8.307668e-04 #> glenmorangie -0.0001692272 0.0025838514 -1.298884e-03 1.028122e-03 #> highlandpark 0.0023214993 0.0028070218 3.398979e-03 -2.715598e-03 #> jackdaniels -0.0011544544 0.0013660407 -3.023216e-03 -1.495727e-03 #> jb -0.0026073348 0.0016289320 -3.506245e-03 1.398710e-03 #> johnniewalker -0.0026799451 0.0046998857 -7.408889e-04 1.724087e-03 #> magallan 0.0034410693 0.0056372281 7.595009e-04 1.320484e-03 #> makersmark -0.0037381840 0.0031052372 4.824121e-04 -7.739096e-04 #> oban -0.0000555700 0.0026159662 -2.336986e-03 1.677681e-03 #> oldpotrero 0.0002650070 0.0005717670 1.200764e-03 -1.479504e-03 #> redbreast -0.0017153754 -0.0017080604 2.956339e-03 -2.516789e-04 #> tamdhu -0.0004660552 0.0022520466 -2.360201e-03 1.825931e-04 #> wildturkey -0.0011040540 0.0003877287 -1.425560e-03 7.482844e-04 #> yoichi -0.0005670111 0.0040850862 1.536049e-03 -1.112175e-03 #> A15 A16 A17 A18 #> brahma -1.150816e-03 -3.765755e-04 -8.576746e-04 -0.0011152905 #> caney -4.470877e-04 -9.307845e-04 -6.102760e-04 -0.0008460017 #> chimay 1.560010e-05 -2.625393e-03 -6.111634e-04 -0.0014908027 #> corona -1.317478e-03 -5.180094e-04 -7.007916e-04 -0.0006290111 #> deusventrue 9.538496e-04 -6.759098e-04 7.618085e-04 -0.0011834834 #> duvel 2.113421e-03 -1.342867e-03 -5.580321e-04 -0.0007953381 #> franziskaner -8.169832e-04 -7.064707e-04 -4.330142e-04 -0.0013097566 #> grimbergen -4.937948e-04 -2.362703e-03 -7.577334e-04 -0.0016389273 #> guiness 9.445264e-04 -1.014837e-03 -3.870126e-04 -0.0018246820 #> hoegardeen -9.359774e-04 -6.806132e-04 -3.723940e-04 -0.0012041744 #> jupiler -6.500301e-04 -8.059191e-05 -3.572447e-04 -0.0005173527 #> kingfisher -4.322282e-04 -3.220011e-04 -1.490105e-04 -0.0007168806 #> latrappe -3.929165e-05 -2.305825e-03 -1.500329e-03 -0.0005806765 #> lindemanskriek -7.095128e-05 -5.265070e-04 9.090133e-05 -0.0011401438 #> nicechouffe 4.131153e-04 -1.060484e-05 4.958279e-04 -0.0004262323 #> pecheresse -1.039373e-03 -2.814305e-04 -7.590926e-04 -0.0008703985 #> sierranevada 1.197254e-03 -1.569161e-03 4.580294e-05 -0.0020229627 #> tanglefoot 1.578694e-03 -2.481082e-03 3.148731e-06 -0.0022741243 #> tauro -5.776374e-04 2.422874e-05 -2.473503e-04 -0.0004171947 #> westmalle -4.421245e-04 -7.338895e-04 1.612346e-05 -0.0007666637 #> amrut 4.652313e-04 1.135970e-03 3.402538e-04 -0.0011307959 #> ballantines 2.624766e-03 -1.653235e-03 -9.878081e-05 -0.0017287563 #> bushmills -1.332454e-04 1.113376e-03 1.602089e-04 -0.0006916012 #> chivas 1.116103e-03 -2.491530e-03 -9.913464e-04 -0.0011585308 #> dalmore 1.019313e-03 -9.423920e-04 -2.075399e-03 -0.0001835038 #> famousgrouse -1.222042e-03 -3.192907e-04 1.028735e-03 0.0001611504 #> glendronach 1.969121e-04 6.973513e-04 1.810040e-04 -0.0014310821 #> glenmorangie -4.077866e-05 2.974758e-04 2.699506e-05 -0.0009470779 #> highlandpark -1.096361e-03 -4.080900e-03 -8.356537e-04 -0.0007232859 #> jackdaniels 4.450744e-04 -7.898984e-04 8.654690e-04 -0.0026841687 #> jb 4.497643e-05 3.343889e-04 -1.017336e-03 -0.0020327924 #> johnniewalker -8.204066e-04 -1.173419e-03 -4.161162e-04 -0.0016445323 #> magallan -1.109793e-03 6.828727e-04 7.119352e-04 0.0013949777 #> makersmark -7.150888e-04 -2.119718e-03 4.641016e-04 -0.0020552953 #> oban 7.127703e-04 1.418921e-03 1.652713e-04 -0.0011940845 #> oldpotrero 6.516221e-04 -1.263670e-03 -3.276935e-04 -0.0007770829 #> redbreast 1.664233e-03 -2.352226e-03 -3.191507e-04 -0.0007444397 #> tamdhu -3.765004e-04 2.690095e-04 -2.278638e-05 -0.0013093652 #> wildturkey 2.107198e-03 -5.335998e-04 -5.539288e-07 -0.0025142726 #> yoichi -1.089887e-03 -3.844364e-03 -6.121975e-04 -0.0019437166 #> A19 A20 A21 A22 #> brahma -8.360520e-04 -1.095155e-03 -5.439578e-04 -0.0008608038 #> caney 2.301119e-05 -8.399357e-04 -5.178245e-04 -0.0009469597 #> chimay -1.119706e-03 -9.775433e-04 -1.256788e-03 -0.0002828775 #> corona -3.339722e-04 -1.281244e-03 -4.441549e-04 -0.0010768982 #> deusventrue 4.696431e-04 -8.906751e-04 -3.783424e-05 -0.0004364503 #> duvel -1.052150e-03 1.767706e-04 -1.315824e-03 0.0001575196 #> franziskaner -2.487242e-04 -1.440287e-03 -2.906736e-04 -0.0013413124 #> grimbergen -5.092226e-04 -1.388491e-03 -1.047057e-03 -0.0009030433 #> guiness -5.134258e-04 -9.406369e-04 -7.035895e-04 -0.0010718354 #> hoegardeen -3.030391e-05 -1.375411e-03 -1.083590e-04 -0.0012010324 #> jupiler -1.746120e-04 -7.555265e-04 -2.440347e-04 -0.0007606965 #> kingfisher -1.248337e-04 -9.013070e-04 -2.490120e-04 -0.0009173615 #> latrappe -1.798539e-03 1.557989e-04 -1.580709e-03 -0.0003042140 #> lindemanskriek -1.527305e-05 -1.022777e-03 -1.208019e-04 -0.0008309589 #> nicechouffe 3.237215e-04 -4.025861e-04 -3.535202e-05 -0.0003365178 #> pecheresse -6.085669e-04 -9.703236e-04 -4.706892e-04 -0.0008515637 #> sierranevada -3.026415e-04 -6.164256e-04 -4.048992e-04 -0.0002228167 #> tanglefoot -1.678775e-03 -6.763154e-04 -1.661378e-03 0.0002811837 #> tauro -1.242105e-04 -6.929686e-04 -1.750296e-04 -0.0006968736 #> westmalle 4.796447e-05 -9.153239e-04 -3.625213e-04 -0.0007776180 #> amrut -2.937597e-04 -1.042779e-03 4.676933e-04 -0.0005584716 #> ballantines -1.095479e-03 -5.664907e-04 -1.334292e-03 -0.0001309159 #> bushmills -4.243124e-04 -1.597220e-03 -3.746931e-04 -0.0012943033 #> chivas -1.143344e-03 -1.503350e-04 -1.506499e-03 -0.0005578037 #> dalmore -2.332470e-03 4.045078e-04 -1.415380e-03 -0.0005555167 #> famousgrouse 1.049511e-03 -9.742276e-04 -2.767390e-04 -0.0013519075 #> glendronach -3.271808e-04 -1.252161e-03 4.876743e-04 -0.0007595878 #> glenmorangie -6.036688e-05 -1.153601e-03 6.282828e-05 -0.0010084062 #> highlandpark 9.189143e-06 3.409179e-04 -1.179990e-03 -0.0003642734 #> jackdaniels -5.032865e-04 -2.133471e-03 1.457150e-04 -0.0007421376 #> jb -6.252763e-04 -1.068694e-03 2.480485e-04 -0.0012779648 #> johnniewalker 5.173429e-04 -1.616008e-03 3.050870e-04 -0.0017541528 #> magallan 1.070598e-03 2.807696e-05 -9.598212e-06 -0.0008434404 #> makersmark 2.630934e-04 -1.571250e-03 -3.711217e-04 -0.0014299088 #> oban -2.798357e-04 -9.061662e-04 7.605150e-04 -0.0005982398 #> oldpotrero -7.682701e-04 -3.189202e-04 -1.292703e-03 -0.0004288338 #> redbreast -4.639071e-04 -6.413198e-05 -1.338260e-03 -0.0002888724 #> tamdhu -7.332551e-04 -1.369532e-03 -2.418841e-04 -0.0008026583 #> wildturkey 1.454628e-04 -8.134531e-04 2.078593e-04 -0.0009947430 #> yoichi 5.982287e-04 -6.939296e-04 -3.599693e-04 -0.0010059628 #> A23 A24 A25 A26 #> brahma -5.735915e-04 -7.299627e-04 -5.033864e-04 -4.409200e-04 #> caney -3.939390e-04 -4.249811e-04 -3.278067e-04 -2.777037e-04 #> chimay -6.410642e-04 -3.497060e-04 -3.987327e-04 -3.797373e-04 #> corona -1.717514e-04 -8.503422e-04 -5.002657e-04 -6.613581e-04 #> deusventrue -2.719114e-04 -1.349406e-04 -4.678471e-04 -6.742999e-05 #> duvel -7.818289e-04 3.932732e-04 -9.314404e-06 -2.825668e-05 #> franziskaner -4.046305e-04 -1.021761e-03 -4.715859e-04 -6.988167e-04 #> grimbergen -7.620525e-04 -3.869953e-04 -6.922240e-04 -3.085118e-04 #> guiness -1.351687e-03 -8.291494e-04 -9.365808e-04 -3.617216e-04 #> hoegardeen -2.498091e-04 -8.130813e-04 -3.461347e-04 -4.976229e-04 #> jupiler -2.215773e-04 -5.697297e-04 -2.066056e-04 -4.092564e-04 #> kingfisher -3.967327e-04 -7.678531e-04 -5.048256e-04 -5.527247e-04 #> latrappe -1.006108e-03 -8.063068e-04 -1.898781e-04 -8.045060e-04 #> lindemanskriek -3.973242e-04 -5.696441e-04 -5.273803e-04 -3.157960e-04 #> nicechouffe -3.297171e-04 -2.842429e-04 -4.972024e-04 -2.750759e-04 #> pecheresse -4.105892e-04 -5.570638e-04 -2.828138e-04 -3.578320e-04 #> sierranevada -1.099662e-03 -1.387875e-04 -9.442991e-04 1.096631e-04 #> tanglefoot -1.635148e-03 -4.770303e-05 -1.168425e-03 -3.445467e-04 #> tauro -1.625056e-04 -5.661598e-04 -1.964170e-04 -4.236883e-04 #> westmalle -4.429987e-04 -3.005871e-04 -4.540035e-04 -1.575977e-04 #> amrut -7.244893e-05 -8.542750e-04 -5.559353e-04 -3.654990e-04 #> ballantines -1.390100e-03 -1.531693e-04 -8.488486e-04 -2.444936e-04 #> bushmills -7.789744e-05 -8.117072e-04 -1.020809e-04 -5.697088e-04 #> chivas -1.346262e-03 -5.894841e-04 -3.746380e-04 -6.807200e-04 #> dalmore -7.044950e-04 -1.289471e-03 5.765490e-05 -1.174635e-03 #> famousgrouse -5.212407e-04 -5.448013e-04 -3.704556e-04 -1.542122e-04 #> glendronach -1.149506e-04 -1.118511e-03 -6.721453e-04 -5.846057e-04 #> glenmorangie -2.822714e-04 -8.637078e-04 -6.676302e-04 -4.433941e-04 #> highlandpark -1.555117e-03 -4.896530e-04 -7.493971e-04 -2.547851e-04 #> jackdaniels -4.989083e-04 -7.889162e-04 -1.216612e-03 -2.005722e-04 #> jb -7.216180e-04 -1.498284e-03 -5.639723e-04 -6.661035e-04 #> johnniewalker -8.869808e-05 -1.130499e-03 -6.767161e-05 -5.211472e-04 #> magallan 1.136414e-04 -3.351403e-04 4.998842e-04 -1.129039e-04 #> makersmark -8.579604e-04 -2.116652e-04 -7.427828e-04 -2.690318e-04 #> oban 5.678546e-05 -1.123786e-03 -3.954051e-04 -5.501621e-04 #> oldpotrero -9.468502e-04 -4.171101e-04 -7.033424e-04 -7.954337e-04 #> redbreast -1.186983e-03 -3.016778e-04 -5.536010e-04 -4.264666e-04 #> tamdhu -3.844344e-04 -8.220193e-04 -7.701044e-04 -5.589579e-04 #> wildturkey -1.178700e-03 -7.132883e-04 -9.516387e-04 -4.435690e-05 #> yoichi -1.459839e-03 -7.921361e-04 -1.086323e-03 8.118876e-06 #> A27 A28 A29 A30 #> brahma -3.652079e-04 -2.976623e-04 -3.220750e-04 -2.405557e-04 #> caney -4.543725e-04 -1.340038e-04 -1.715288e-04 8.287078e-05 #> chimay 1.897326e-04 -3.220192e-04 1.012090e-04 -3.939649e-04 #> corona -5.628453e-04 -2.866408e-04 -6.301550e-04 -2.277373e-04 #> deusventrue -4.081023e-04 -6.793693e-06 -2.278672e-04 -1.602607e-04 #> duvel -4.501744e-05 -5.229843e-04 8.047695e-05 -3.443646e-04 #> franziskaner -4.854885e-04 -4.750621e-04 -4.823508e-04 -3.278401e-04 #> grimbergen -4.197697e-04 -1.283767e-04 -1.685585e-04 -1.590373e-04 #> guiness -6.925029e-04 -3.580901e-04 -5.165405e-04 -1.183717e-04 #> hoegardeen -4.969737e-04 -2.495808e-04 -4.912037e-04 -6.346919e-05 #> jupiler -2.483571e-04 -2.993651e-04 -1.920937e-04 -1.788899e-04 #> kingfisher -5.448135e-04 -4.650672e-04 -5.979427e-04 -3.497510e-04 #> latrappe 1.533756e-04 -5.493115e-04 5.599578e-05 -7.649463e-05 #> lindemanskriek -5.437426e-04 -1.937430e-04 -5.135849e-04 -9.406325e-05 #> nicechouffe -3.740962e-04 -2.387508e-04 -2.592933e-04 -3.671187e-04 #> pecheresse -2.370723e-04 -2.125326e-04 -1.635507e-04 -1.002369e-04 #> sierranevada -5.741030e-04 -3.442510e-05 -3.438660e-04 -1.891307e-04 #> tanglefoot -1.719313e-04 -4.589738e-04 3.812701e-04 -6.044718e-04 #> tauro -2.674869e-04 -3.421696e-04 -1.858056e-04 -2.076248e-04 #> westmalle -5.645719e-04 -1.247868e-04 -4.182225e-04 -4.248077e-05 #> amrut -3.710587e-04 -6.939239e-05 -6.261379e-04 -2.992623e-04 #> ballantines -3.251060e-04 -5.994957e-04 -2.757254e-04 -8.154587e-04 #> bushmills -2.720945e-04 -3.599923e-04 -3.414174e-04 -2.377839e-04 #> chivas -2.255766e-04 -8.637994e-04 -1.458373e-04 -3.882162e-04 #> dalmore -9.942863e-05 -7.848302e-04 -5.977677e-04 -2.299701e-04 #> famousgrouse -6.485656e-04 -2.158172e-04 -7.140961e-04 -1.036337e-04 #> glendronach -4.429512e-04 -1.668512e-04 -6.373005e-04 -3.195863e-04 #> glenmorangie -7.765482e-04 -2.094619e-04 -8.242601e-04 -2.409561e-04 #> highlandpark 9.675349e-05 -9.874542e-05 2.967982e-04 -2.470293e-04 #> jackdaniels -8.279356e-04 2.860995e-04 -6.585185e-04 1.297801e-04 #> jb -3.654559e-04 -6.181808e-04 -6.228425e-04 -5.440835e-04 #> johnniewalker -4.614923e-04 -4.769614e-04 -9.140300e-04 -3.536712e-04 #> magallan 1.930942e-04 -4.644705e-04 -1.875115e-04 -4.003883e-04 #> makersmark -1.422649e-03 -3.876731e-05 -4.450249e-04 2.762661e-04 #> oban -1.373020e-04 -1.436324e-04 -4.904222e-04 -3.352663e-04 #> oldpotrero -4.396750e-04 -5.793447e-04 -2.152387e-04 -5.552859e-04 #> redbreast -2.394329e-04 -7.978188e-04 -2.390723e-04 -5.929331e-04 #> tamdhu -6.472657e-04 -2.331427e-04 -4.991397e-04 -1.900026e-04 #> wildturkey -9.059420e-04 -3.046609e-04 -8.375680e-04 -3.434517e-04 #> yoichi -3.472393e-04 1.165942e-04 -2.819714e-04 -3.541959e-04 #> A31 A32 B1 B2 B3 #> brahma -1.974790e-04 -8.094538e-05 0 -1.900652e-04 3.306231e-04 #> caney -5.975848e-05 -7.681466e-06 0 5.012013e-04 -3.851293e-04 #> chimay 3.467138e-05 -3.425039e-05 0 1.843629e-04 4.196107e-04 #> corona -6.391514e-04 -7.778089e-05 0 -3.586724e-04 1.711055e-05 #> deusventrue -5.672855e-05 -9.370594e-05 0 1.774985e-04 -8.326845e-05 #> duvel 2.041590e-04 -1.384422e-04 0 -4.198782e-04 7.447638e-05 #> franziskaner -3.511246e-04 -1.887467e-04 0 -8.367911e-04 -3.508429e-04 #> grimbergen -1.034722e-04 -1.074542e-04 0 -4.478525e-04 -1.575351e-04 #> guiness -9.701532e-05 9.185850e-06 0 4.379065e-05 -3.284575e-04 #> hoegardeen -3.894108e-04 -1.449367e-05 0 -1.402306e-05 3.803656e-04 #> jupiler -1.358161e-04 -1.366520e-04 0 1.831345e-04 -1.827727e-04 #> kingfisher -4.164633e-04 -2.558914e-04 0 -1.644074e-04 -3.059412e-04 #> latrappe -6.701359e-05 2.760955e-04 0 2.164816e-04 1.803082e-04 #> lindemanskriek -2.873840e-04 2.669199e-06 0 4.100249e-04 2.208045e-04 #> nicechouffe -1.738180e-04 -3.703168e-04 0 5.495158e-04 -2.042167e-05 #> pecheresse -1.028221e-04 -5.676952e-05 0 2.181959e-04 -7.311833e-05 #> sierranevada -3.941502e-05 -1.245511e-04 0 -2.089826e-04 -3.847117e-04 #> tanglefoot 3.701320e-04 -3.628268e-04 0 2.257469e-04 -2.009399e-04 #> tauro -1.470322e-04 -2.627287e-04 0 1.762712e-04 -8.961804e-05 #> westmalle -1.340963e-04 -3.584753e-05 0 2.683034e-04 5.829510e-04 #> amrut -6.740665e-04 -1.263649e-04 0 3.259091e-04 3.840090e-04 #> ballantines -3.000458e-04 -5.620135e-04 0 -8.980074e-06 1.013064e-03 #> bushmills -3.951078e-04 -2.398475e-04 0 8.084328e-04 8.012671e-04 #> chivas -6.925496e-05 -8.800981e-06 0 6.073651e-04 3.070684e-04 #> dalmore -7.809275e-04 7.011618e-05 0 1.097768e-03 6.881659e-04 #> famousgrouse -4.672213e-04 -9.582100e-05 0 1.287495e-04 -1.324051e-04 #> glendronach -7.048583e-04 -1.975745e-04 0 4.149836e-04 1.394907e-04 #> glenmorangie -6.325151e-04 -2.741086e-04 0 8.773153e-05 -6.257124e-05 #> highlandpark -7.059637e-05 -2.569712e-04 0 -6.291662e-04 -7.091405e-04 #> jackdaniels -4.208486e-04 7.987137e-05 0 1.828207e-04 -5.854778e-04 #> jb -3.650894e-04 -2.691260e-04 0 5.770034e-04 1.295536e-04 #> johnniewalker -8.042786e-04 -1.053716e-04 0 1.610309e-03 1.521699e-03 #> magallan -1.549710e-04 -9.098292e-05 0 -1.110357e-03 -1.017379e-03 #> makersmark -5.759001e-04 -6.063122e-04 0 -2.272912e-03 -1.921977e-03 #> oban -6.414803e-04 -1.069347e-04 0 5.217373e-04 3.289690e-04 #> oldpotrero -3.440437e-04 -2.888371e-04 0 -4.566144e-04 2.434271e-04 #> redbreast 1.079718e-05 -2.434157e-04 0 1.568632e-04 1.213587e-04 #> tamdhu -4.031862e-04 -2.196594e-04 0 1.013117e-03 4.671170e-04 #> wildturkey -3.706899e-04 -3.840752e-04 0 9.489660e-04 9.344159e-04 #> yoichi -2.793226e-04 -3.702781e-04 0 2.371406e-04 3.337929e-04 #> B4 B5 B6 B7 #> brahma -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 #> caney 3.333918e-04 -2.899903e-04 7.350207e-05 -4.952054e-04 #> chimay 3.227901e-04 -2.906714e-05 5.573360e-04 1.059517e-04 #> corona -5.501057e-04 -1.907425e-04 -4.256287e-04 -2.147013e-04 #> deusventrue -1.403373e-03 -3.240180e-04 -9.330047e-04 6.515692e-04 #> duvel -6.627095e-04 6.107940e-05 -4.746985e-04 2.450959e-04 #> franziskaner -6.983186e-04 -1.894199e-04 -5.170165e-04 5.988419e-05 #> grimbergen 1.554676e-04 5.257427e-05 1.132609e-04 -6.848791e-05 #> guiness -1.677242e-04 -5.817648e-04 -2.853668e-04 -5.620867e-04 #> hoegardeen 3.285812e-04 4.813766e-04 3.691213e-04 5.309204e-04 #> jupiler -4.540203e-05 -1.242456e-04 -5.198885e-05 -2.289954e-04 #> kingfisher -1.751841e-04 3.014782e-05 2.132220e-04 4.144846e-04 #> latrappe 5.468038e-04 2.303760e-04 5.053959e-04 2.603399e-04 #> lindemanskriek 2.791269e-04 -2.076986e-04 -1.312595e-04 -1.367999e-04 #> nicechouffe 2.492854e-04 2.171344e-04 2.155297e-04 1.621249e-04 #> pecheresse 2.879648e-04 3.072908e-05 1.503582e-04 2.875235e-05 #> sierranevada 2.254752e-04 -1.582761e-04 3.201773e-04 -2.506594e-04 #> tanglefoot -3.556495e-04 -4.589428e-04 -1.231722e-04 -1.030225e-04 #> tauro 8.045507e-05 4.030041e-05 1.942858e-04 7.124766e-05 #> westmalle 2.086425e-04 5.569697e-04 -1.481080e-04 2.680453e-04 #> amrut 2.692429e-04 2.370884e-04 4.975910e-05 1.929742e-04 #> ballantines -2.175286e-04 1.006239e-03 -2.063087e-04 6.874951e-04 #> bushmills 9.888621e-04 5.333749e-04 6.026329e-04 3.382499e-07 #> chivas 1.231654e-04 -3.404412e-05 8.988476e-05 1.476812e-04 #> dalmore 2.545366e-04 1.352642e-04 -1.253930e-04 2.101188e-04 #> famousgrouse -1.274614e-04 2.141211e-04 -1.073666e-04 1.188717e-05 #> glendronach 1.071609e-04 -2.016928e-04 -6.904446e-05 -1.327779e-04 #> glenmorangie 1.913928e-04 -9.675222e-05 1.480796e-04 -8.118855e-05 #> highlandpark -2.204109e-04 -5.021317e-04 3.287316e-04 -2.505046e-04 #> jackdaniels -7.969529e-04 -4.880520e-04 -1.903562e-04 3.092736e-04 #> jb -1.422141e-04 -2.056778e-04 -2.053789e-04 1.048725e-04 #> johnniewalker 1.140415e-03 1.505532e-04 2.156619e-04 -1.772208e-04 #> magallan -7.964354e-04 -6.143625e-04 -3.734865e-04 -1.291146e-04 #> makersmark -3.452843e-04 -1.437534e-04 4.289043e-04 -9.732915e-04 #> oban 3.351843e-04 4.359254e-05 1.826487e-05 -6.027186e-05 #> oldpotrero -2.060062e-04 3.778706e-05 -5.576392e-04 2.258336e-04 #> redbreast -1.087561e-04 -1.587376e-04 -9.420764e-05 -7.636860e-06 #> tamdhu 2.449976e-04 3.452581e-05 -1.344683e-04 1.407481e-04 #> wildturkey 2.048265e-04 1.038328e-04 7.988232e-06 2.379076e-04 #> yoichi 2.790195e-04 2.201285e-04 1.423493e-05 -5.626562e-05 #> B8 B9 B10 B11 #> brahma 6.268503e-06 -1.960132e-04 1.334431e-04 4.058288e-05 #> caney 8.536695e-05 -4.143363e-04 1.667420e-04 -3.134942e-04 #> chimay 6.209192e-04 1.441644e-04 1.715223e-04 5.930974e-05 #> corona -1.931107e-04 -3.048499e-04 -2.065499e-04 -2.244684e-04 #> deusventrue -8.354423e-04 2.287499e-05 -6.080012e-04 2.971827e-04 #> duvel -1.676532e-04 1.512500e-04 6.986965e-05 2.318703e-04 #> franziskaner -3.810484e-04 5.133436e-05 -3.407356e-04 5.681736e-05 #> grimbergen -9.289817e-05 2.532879e-05 1.655384e-04 3.086461e-04 #> guiness -1.496463e-04 -4.662246e-04 -1.905673e-04 -3.642220e-04 #> hoegardeen 3.462062e-04 4.557837e-04 4.205444e-04 3.080245e-04 #> jupiler -8.073101e-05 -2.203453e-04 -1.514837e-04 -1.572771e-04 #> kingfisher 1.324881e-05 1.991329e-04 1.802238e-04 2.681872e-04 #> latrappe 1.829641e-04 2.106651e-04 -1.447749e-04 2.756836e-04 #> lindemanskriek 4.871774e-05 -4.788973e-05 -2.120403e-04 -1.394498e-04 #> nicechouffe 1.463372e-04 2.488056e-04 8.034353e-05 2.586078e-04 #> pecheresse 2.759482e-04 1.481251e-05 1.433130e-04 -1.556835e-05 #> sierranevada 1.406542e-04 -1.888577e-04 6.806233e-05 -5.042849e-05 #> tanglefoot 5.673867e-06 -2.751261e-04 -3.002656e-04 -2.455063e-04 #> tauro 2.932668e-04 1.286768e-04 1.547277e-04 1.336644e-04 #> westmalle -1.539093e-04 4.586356e-04 1.799417e-05 3.301881e-04 #> amrut 1.570262e-04 2.548664e-04 1.115168e-04 7.490810e-06 #> ballantines -3.868333e-05 3.003380e-04 1.592670e-04 -5.079525e-05 #> bushmills 2.135771e-04 -2.019147e-04 1.348464e-04 -1.302260e-04 #> chivas 1.332194e-04 1.056333e-04 2.227781e-05 4.227956e-05 #> dalmore -4.021158e-06 2.679348e-04 -2.632871e-05 1.881627e-04 #> famousgrouse -2.566731e-04 2.195639e-04 -7.568478e-05 1.842423e-04 #> glendronach 2.453495e-05 -7.915842e-06 -1.865175e-05 -6.786263e-05 #> glenmorangie 1.557411e-04 -3.527084e-06 1.414448e-04 -9.027797e-06 #> highlandpark 3.870735e-04 -4.437162e-04 1.970082e-04 -4.866817e-04 #> jackdaniels -1.751848e-04 -3.777874e-05 -1.953733e-04 2.389926e-04 #> jb 1.396719e-04 1.902920e-04 -7.877557e-05 4.429623e-05 #> johnniewalker 5.133497e-04 1.719490e-04 5.339652e-04 -1.814410e-04 #> magallan -1.577770e-04 -1.006505e-04 -1.482048e-04 -8.058980e-06 #> makersmark -5.600587e-04 -7.200799e-04 4.777646e-04 2.581853e-04 #> oban 8.787835e-05 1.113193e-04 1.307306e-04 -2.483305e-05 #> oldpotrero -3.831452e-04 2.156873e-04 -5.679089e-04 2.063675e-04 #> redbreast 2.541246e-05 2.426826e-05 -8.753325e-05 -8.652635e-06 #> tamdhu -3.383952e-05 3.365051e-04 -1.785979e-04 -4.280721e-06 #> wildturkey 3.002663e-04 1.207047e-04 1.615231e-04 -7.004425e-06 #> yoichi -1.168653e-04 -8.227670e-05 5.854442e-05 8.229082e-05 #> B12 B13 B14 B15 #> brahma -1.917814e-04 -4.415768e-05 -1.760152e-06 2.542883e-05 #> caney 2.011956e-05 -2.220739e-04 9.710885e-05 -2.929034e-05 #> chimay -3.197006e-06 3.218682e-04 -2.136764e-04 2.996248e-04 #> corona -6.091420e-06 -1.616363e-04 -1.409505e-05 -3.036983e-04 #> deusventrue -2.794108e-04 -2.410553e-04 -5.766037e-06 -1.013081e-04 #> duvel 1.659893e-04 -2.147276e-05 -7.372516e-05 -1.697182e-05 #> franziskaner -2.140707e-04 1.309236e-04 -1.825897e-05 9.453212e-05 #> grimbergen 1.890428e-04 2.030487e-04 4.494496e-05 2.047563e-04 #> guiness -2.602631e-04 -1.363068e-04 -1.037229e-05 4.860333e-05 #> hoegardeen 2.814325e-04 1.153058e-04 7.690851e-05 -7.760464e-05 #> jupiler -1.151375e-04 -1.062093e-04 -1.414838e-04 -5.844711e-06 #> kingfisher 1.550433e-04 3.863328e-05 1.987871e-04 8.556756e-05 #> latrappe -1.942322e-04 3.505642e-04 -2.308454e-04 6.983853e-05 #> lindemanskriek -5.113408e-05 4.601614e-05 2.027442e-05 -3.838834e-05 #> nicechouffe 4.652882e-05 1.804172e-04 -1.750016e-04 2.230781e-04 #> pecheresse 1.587407e-04 -2.017244e-05 7.161075e-05 -1.571287e-04 #> sierranevada 3.125122e-05 4.681375e-05 -5.698779e-05 5.098577e-05 #> tanglefoot -9.215486e-05 2.005060e-05 -6.143058e-05 -1.075625e-04 #> tauro 1.226045e-04 1.507290e-04 8.074917e-05 1.647359e-04 #> westmalle 4.757341e-05 1.853084e-04 3.602525e-05 -1.202643e-06 #> amrut -9.179140e-05 -1.098218e-04 -7.874144e-05 -6.180094e-05 #> ballantines 3.235267e-04 -2.822891e-04 3.832439e-04 -3.134129e-04 #> bushmills 2.015409e-04 -9.005687e-05 1.551691e-04 -1.474612e-04 #> chivas -6.666931e-05 2.594754e-05 -1.465818e-04 -3.962153e-05 #> dalmore -9.894417e-05 1.384451e-04 -3.536678e-05 1.404756e-04 #> famousgrouse -7.211196e-05 3.016994e-05 -2.020980e-04 -1.375501e-04 #> glendronach -9.224044e-05 -7.327995e-05 -4.780469e-05 -6.055072e-05 #> glenmorangie 6.261072e-05 -3.298471e-05 8.810869e-05 7.353097e-05 #> highlandpark 1.369676e-04 -2.344619e-04 1.400952e-04 -7.669050e-05 #> jackdaniels 3.169089e-04 3.555232e-04 1.821979e-04 7.868212e-05 #> jb -5.463792e-05 1.038743e-04 -1.519486e-05 -1.559990e-05 #> johnniewalker -5.200179e-05 -4.843014e-04 -2.187679e-04 -2.056380e-04 #> magallan -1.072102e-04 1.704278e-05 -6.741317e-05 -2.205709e-05 #> makersmark 8.085419e-06 -3.964151e-04 -3.192971e-04 5.139474e-04 #> oban -6.805926e-05 -6.673682e-05 7.219949e-05 1.027476e-04 #> oldpotrero -3.604369e-04 2.247342e-04 -4.303685e-04 9.031801e-05 #> redbreast 1.217829e-04 9.014972e-05 1.107807e-04 -3.676530e-05 #> tamdhu -2.219702e-04 1.160413e-05 -4.931877e-05 5.098733e-05 #> wildturkey 2.260401e-05 5.912870e-06 2.723819e-05 2.216640e-05 #> yoichi 1.472054e-04 3.703653e-06 3.359119e-05 -7.624301e-05 #> B16 B17 B18 B19 #> brahma -1.024642e-04 -8.031982e-05 -7.433041e-05 2.949173e-05 #> caney 1.467454e-04 -1.500259e-05 8.962807e-05 1.017678e-04 #> chimay -4.160132e-04 2.173693e-04 -2.232850e-04 1.410948e-04 #> corona 1.562544e-04 -1.863667e-04 1.898815e-04 -3.051700e-04 #> deusventrue 2.687631e-04 -5.866990e-05 2.532389e-04 4.683303e-05 #> duvel 8.924870e-05 1.724312e-04 1.497399e-04 1.188058e-04 #> franziskaner 2.076190e-05 5.303781e-05 1.447445e-04 2.813898e-05 #> grimbergen 1.197492e-04 9.559379e-05 -1.078603e-04 -4.345587e-05 #> guiness -1.231218e-04 8.402517e-05 -5.232981e-05 1.549783e-04 #> hoegardeen 5.139144e-05 -1.331768e-04 -2.258407e-05 -2.391701e-04 #> jupiler -9.634201e-05 7.584032e-05 -2.484072e-05 1.230285e-04 #> kingfisher 1.629910e-04 1.538249e-05 6.406877e-05 -8.623734e-05 #> latrappe -3.333379e-04 -2.151666e-04 -1.793420e-04 -1.972264e-04 #> lindemanskriek 1.913674e-05 -2.214246e-05 6.308868e-05 1.058368e-04 #> nicechouffe -1.476434e-04 1.487541e-04 -3.189322e-04 7.671453e-05 #> pecheresse -1.502647e-05 -1.256547e-04 -2.111016e-05 -1.795287e-04 #> sierranevada -1.612513e-04 6.781737e-05 -1.868408e-04 1.545018e-04 #> tanglefoot -2.075450e-04 -6.190151e-05 7.110212e-05 1.907329e-04 #> tauro -2.608415e-05 7.036816e-05 -1.112206e-04 -2.070534e-07 #> westmalle 1.555977e-04 2.494345e-05 2.457638e-04 -3.753649e-05 #> amrut -5.808395e-05 -5.726583e-05 -4.347323e-05 -4.142367e-05 #> ballantines 2.695725e-04 -1.723254e-04 6.902277e-05 -2.491346e-05 #> bushmills 2.003848e-05 -1.361937e-04 -3.959514e-05 -8.151185e-05 #> chivas -8.163047e-05 6.400487e-05 2.496293e-05 3.670116e-07 #> dalmore 5.018616e-05 -2.426364e-05 1.517115e-05 -7.169745e-05 #> famousgrouse -5.272581e-05 2.433801e-05 7.999124e-05 1.472625e-05 #> glendronach -3.899954e-05 -1.372083e-04 -6.680409e-05 -1.191487e-04 #> glenmorangie 9.340889e-05 8.779820e-06 1.467657e-06 -4.863149e-05 #> highlandpark -5.506078e-05 -4.375426e-05 -1.601530e-04 1.023000e-05 #> jackdaniels 1.592122e-04 1.994958e-04 4.570234e-04 2.251557e-04 #> jb -1.185695e-04 -8.893584e-05 3.900650e-06 1.331244e-05 #> johnniewalker 1.378430e-04 1.149116e-04 3.109675e-04 2.515221e-04 #> magallan -1.015593e-04 -4.418979e-06 -3.238623e-05 3.993857e-05 #> makersmark 1.443085e-04 1.724064e-04 -5.251779e-04 1.746597e-04 #> oban 9.860858e-05 -4.593528e-05 -8.084187e-05 -5.853302e-05 #> oldpotrero -2.725407e-04 1.367096e-04 -1.893404e-04 -2.795346e-06 #> redbreast 1.181494e-04 -9.309777e-06 1.628999e-04 -2.745219e-05 #> tamdhu -4.983723e-05 -7.376290e-05 -1.044426e-04 -7.987732e-05 #> wildturkey -1.630103e-04 -3.611579e-06 -1.779304e-04 -3.570358e-05 #> yoichi 2.484339e-05 1.257615e-05 9.503541e-05 2.723700e-05 #> B20 B21 B22 B23 #> brahma -1.727433e-05 3.737724e-05 -9.462283e-06 -4.267458e-05 #> caney 1.631617e-04 1.508881e-04 1.414211e-04 1.088653e-04 #> chimay -3.610984e-05 -1.712342e-04 2.100688e-05 -3.082575e-04 #> corona 5.852024e-05 -1.892126e-04 1.439899e-04 -1.701985e-04 #> deusventrue 1.245832e-04 7.313250e-06 -1.170924e-04 1.347852e-04 #> duvel 1.101660e-04 -1.728305e-05 9.542637e-05 -1.277279e-04 #> franziskaner 1.795671e-04 6.095791e-06 1.990743e-04 7.411105e-06 #> grimbergen -5.951324e-05 -1.402638e-05 -1.801951e-04 -1.396215e-04 #> guiness -2.255777e-05 -1.319653e-05 -1.127083e-04 -8.149761e-05 #> hoegardeen -1.346868e-04 -3.083842e-04 -1.133545e-04 -2.005817e-04 #> jupiler -2.427445e-05 1.297878e-04 3.863779e-05 1.328010e-04 #> kingfisher 1.719032e-05 -8.315015e-05 -5.685565e-06 -4.528561e-05 #> latrappe 7.799543e-05 -1.931198e-04 5.065654e-05 -2.027860e-04 #> lindemanskriek 9.064003e-05 1.285962e-04 -7.498356e-05 9.866433e-05 #> nicechouffe -2.076616e-04 3.715694e-05 -1.897096e-04 -8.192524e-05 #> pecheresse -6.967807e-05 -1.204336e-04 -4.034586e-05 -8.286053e-05 #> sierranevada -1.253536e-04 2.231407e-04 -7.914671e-05 2.030511e-04 #> tanglefoot 1.265752e-04 3.645141e-05 8.153378e-05 1.463325e-04 #> tauro -1.673200e-04 -3.795493e-05 -2.216782e-04 -9.138492e-05 #> westmalle 1.513049e-04 -8.741209e-05 1.191689e-04 4.122166e-05 #> amrut -1.620938e-05 -4.241691e-05 -2.872726e-05 -7.706793e-05 #> ballantines -9.511720e-05 3.497929e-05 -1.525410e-04 3.344485e-05 #> bushmills -1.692696e-05 -1.985027e-05 -5.673431e-05 -4.245935e-05 #> chivas -3.520791e-05 -3.239497e-05 3.624818e-05 -7.905990e-05 #> dalmore 1.335714e-04 4.821092e-05 3.029999e-05 -2.866421e-05 #> famousgrouse 3.446106e-05 -9.287266e-05 -5.252847e-05 -1.166408e-04 #> glendronach -8.818028e-06 -5.284867e-05 -4.842191e-05 -1.083835e-04 #> glenmorangie -1.128407e-05 4.185137e-05 6.424851e-05 3.040985e-05 #> highlandpark -6.621924e-05 2.623244e-05 5.174724e-05 -4.722625e-05 #> jackdaniels 3.551884e-04 1.445123e-06 2.762319e-04 1.240702e-04 #> jb -2.384959e-06 -6.979310e-05 -8.136968e-05 -2.918739e-05 #> johnniewalker 2.572639e-04 2.352637e-04 2.062948e-04 1.853106e-04 #> magallan 8.388080e-05 2.286704e-05 8.619190e-05 -1.114752e-06 #> makersmark 1.772977e-04 4.534530e-04 -1.701385e-04 -2.389260e-04 #> oban 5.722186e-05 9.730784e-05 2.947083e-05 -4.596947e-05 #> oldpotrero -9.109679e-05 -1.485829e-05 8.622920e-05 -7.160617e-05 #> redbreast 1.465601e-04 -2.217205e-05 6.081711e-05 5.593471e-05 #> tamdhu -4.444590e-05 -9.622733e-05 -5.446212e-05 -7.968429e-05 #> wildturkey -6.312522e-05 -8.731978e-05 -9.045224e-05 -1.442588e-04 #> yoichi -6.770553e-06 -7.074253e-06 -3.277625e-05 3.448357e-05 #> B24 B25 B26 B27 #> brahma 3.357899e-05 1.692467e-05 1.346898e-04 1.323552e-05 #> caney 8.041007e-05 1.705793e-04 6.811154e-05 6.205877e-05 #> chimay 6.975068e-05 -3.230519e-04 2.772097e-05 -1.930852e-04 #> corona 2.066873e-05 -1.628616e-04 7.895544e-05 9.425535e-06 #> deusventrue -1.235701e-04 1.790799e-04 -1.724233e-04 1.249888e-04 #> duvel 7.759496e-05 -1.131994e-04 1.749479e-04 5.630411e-05 #> franziskaner 2.096840e-04 5.258363e-05 2.046122e-04 9.602614e-05 #> grimbergen -1.934331e-04 -5.077219e-05 -9.668195e-05 -1.152902e-05 #> guiness -3.540174e-05 -1.382297e-04 -7.048572e-05 -2.514223e-04 #> hoegardeen -1.012696e-04 -2.098450e-04 -1.981990e-04 -1.709484e-04 #> jupiler 4.995495e-05 9.924240e-05 3.292957e-05 6.028515e-05 #> kingfisher -4.338832e-05 2.094242e-06 -1.091127e-04 1.809903e-05 #> latrappe 4.481099e-05 -9.750492e-07 1.320075e-04 1.075270e-04 #> lindemanskriek -6.757003e-05 1.553763e-04 -7.707839e-05 5.131619e-05 #> nicechouffe -5.530183e-05 -1.113497e-04 1.000706e-04 -1.285347e-04 #> pecheresse 3.202237e-05 -8.922353e-07 7.525484e-05 6.328643e-06 #> sierranevada -3.979424e-05 2.215211e-04 6.707671e-05 1.786146e-04 #> tanglefoot 2.668517e-04 2.207476e-04 1.806422e-04 1.175903e-04 #> tauro -2.201592e-04 -1.334780e-04 -1.668332e-04 -1.334782e-04 #> westmalle 1.494564e-04 7.630565e-05 6.478230e-05 8.574062e-05 #> amrut -7.423616e-05 -9.642488e-05 -6.096081e-05 -5.130361e-05 #> ballantines -1.139455e-04 -5.063695e-06 -7.587876e-06 -8.630156e-05 #> bushmills -1.070090e-04 -5.351683e-05 -6.508694e-05 -4.250557e-05 #> chivas -6.203789e-05 -1.131152e-04 -2.118968e-05 -2.011372e-05 #> dalmore -1.052443e-04 1.314585e-04 6.223813e-05 8.974265e-05 #> famousgrouse 9.201751e-06 -3.069921e-05 6.168392e-05 -2.812213e-05 #> glendronach -9.443193e-05 -9.402038e-05 -6.862198e-05 -6.239359e-05 #> glenmorangie 8.064676e-06 -9.115729e-05 2.092771e-05 -6.525547e-06 #> highlandpark 1.656563e-04 -1.197451e-04 1.990472e-04 -1.607961e-04 #> jackdaniels 3.141428e-04 1.438902e-04 1.360127e-04 7.677775e-05 #> jb -5.981547e-06 3.209775e-05 -5.872919e-05 -4.055534e-05 #> johnniewalker 1.090105e-04 2.440030e-05 4.631195e-05 -6.158105e-05 #> magallan 4.078643e-05 -5.422248e-05 9.397643e-05 1.807366e-05 #> makersmark 7.660151e-05 2.869973e-04 3.123278e-04 -1.724480e-04 #> oban -8.787218e-05 1.336036e-05 6.898514e-05 1.098895e-04 #> oldpotrero 1.298368e-04 -1.188172e-04 1.233055e-04 -9.419603e-05 #> redbreast 1.608830e-05 1.972762e-05 -8.025162e-06 3.855603e-05 #> tamdhu -7.215626e-05 -5.300043e-05 -6.775627e-05 2.119539e-05 #> wildturkey -4.169666e-05 -8.994826e-05 2.380420e-05 -4.889098e-05 #> yoichi -1.328858e-05 3.447740e-05 -3.698146e-05 -2.869228e-05 #> B28 B29 B30 B31 #> brahma 9.806530e-05 -1.691212e-05 1.229728e-04 6.153001e-06 #> caney 4.057485e-05 3.928378e-05 3.848225e-05 5.608283e-05 #> chimay -2.670005e-05 2.629625e-05 -4.657436e-05 1.626961e-04 #> corona -1.115351e-05 1.797628e-05 -6.512991e-05 1.430262e-04 #> deusventrue -1.098118e-04 -7.708499e-06 -1.093334e-04 -1.335296e-04 #> duvel 8.996050e-05 -1.871001e-05 -1.512385e-04 -1.753386e-05 #> franziskaner 1.770497e-04 7.088446e-05 8.138285e-05 5.397908e-05 #> grimbergen -1.034470e-04 7.562129e-05 -2.509585e-05 1.318461e-04 #> guiness -1.343019e-05 -2.135015e-04 6.528218e-05 -2.138696e-04 #> hoegardeen -1.891331e-04 -2.027795e-05 -1.994452e-04 8.440574e-06 #> jupiler 3.698933e-05 4.153355e-05 -1.269451e-05 2.996676e-06 #> kingfisher -5.937101e-05 4.782661e-05 -4.637724e-05 -1.873467e-05 #> latrappe 3.127671e-05 6.155545e-05 1.090250e-05 1.042136e-04 #> lindemanskriek -7.184754e-05 1.818455e-05 -3.242323e-05 -4.990771e-05 #> nicechouffe 1.757105e-04 -2.027842e-04 2.059657e-04 -1.480986e-04 #> pecheresse 6.500181e-05 3.025513e-05 4.663718e-05 2.857271e-05 #> sierranevada 4.103579e-05 4.237471e-05 8.981611e-05 3.178064e-06 #> tanglefoot 1.359892e-04 1.424025e-04 9.431909e-05 5.521421e-05 #> tauro -1.277568e-04 -1.387930e-04 -9.102122e-05 -7.700952e-05 #> westmalle 1.603183e-05 4.180181e-05 6.597365e-05 1.291222e-04 #> amrut -3.381274e-05 -5.523538e-05 -5.099306e-05 -5.156172e-05 #> ballantines 7.017023e-05 -1.808696e-04 3.999426e-05 -1.901792e-04 #> bushmills -1.565836e-05 -2.836986e-05 -1.194452e-05 -5.279559e-05 #> chivas -4.979588e-05 -8.638138e-06 -7.040279e-05 4.772406e-05 #> dalmore -6.494053e-05 -9.744864e-05 6.715816e-05 3.921296e-05 #> famousgrouse 3.214914e-05 -1.031722e-05 8.491463e-05 5.581120e-05 #> glendronach -6.552423e-05 -4.747638e-05 -6.498987e-05 -2.314333e-05 #> glenmorangie 9.980637e-05 -2.982313e-05 5.485448e-05 -7.232008e-05 #> highlandpark 1.333362e-04 -1.101299e-04 5.583464e-05 3.249483e-05 #> jackdaniels 6.961363e-05 1.125400e-04 6.535658e-05 1.682956e-04 #> jb -1.163580e-04 1.168139e-05 -1.820077e-05 7.989656e-05 #> johnniewalker 1.843935e-04 -4.029596e-05 2.282147e-04 -1.093759e-04 #> magallan 1.905241e-04 -7.821211e-06 9.830610e-05 -1.616843e-05 #> makersmark -1.527610e-05 -1.083002e-05 2.667490e-04 5.665387e-05 #> oban -1.219200e-05 -3.906020e-05 -6.570052e-05 4.842028e-05 #> oldpotrero 1.395086e-04 -1.457807e-05 8.504515e-05 -1.657986e-05 #> redbreast 1.937056e-05 -3.090785e-05 1.655432e-05 -5.152611e-05 #> tamdhu -7.750763e-05 1.806773e-06 -1.030223e-04 -6.475153e-06 #> wildturkey 2.116661e-05 -3.808603e-05 2.629787e-06 1.485641e-06 #> yoichi -1.436536e-05 -6.982657e-06 4.571619e-05 -2.867356e-05 #> B32 C1 C2 C3 C4 #> brahma 1.217078e-04 0 -1.637571e-03 -3.936895e-03 5.408096e-03 #> caney 1.227213e-05 0 1.239828e-03 -2.845651e-04 3.757825e-04 #> chimay -4.552776e-05 0 -3.757608e-03 -1.797357e-03 -2.127924e-03 #> corona -4.547231e-05 0 -1.652864e-03 1.573302e-03 4.897281e-04 #> deusventrue 5.762098e-05 0 1.552775e-03 7.706329e-04 -1.416448e-03 #> duvel -1.615768e-04 0 2.872128e-04 -5.422392e-06 -7.785717e-04 #> franziskaner 5.143834e-05 0 -1.253868e-03 3.476506e-04 1.004621e-03 #> grimbergen -7.062906e-05 0 1.700875e-03 -1.452474e-04 4.332935e-04 #> guiness 7.815836e-05 0 -5.088378e-04 1.628258e-03 5.025916e-05 #> hoegardeen -2.171328e-04 0 -2.538102e-03 6.627214e-04 -1.481847e-03 #> jupiler -2.081774e-05 0 9.877198e-04 -8.223351e-05 1.286204e-04 #> kingfisher -3.244750e-05 0 8.355893e-04 -2.193322e-03 -9.853901e-04 #> latrappe 7.681797e-05 0 2.026476e-03 6.109498e-04 -1.518299e-04 #> lindemanskriek -4.318610e-05 0 -1.736348e-03 1.465734e-03 -1.513403e-03 #> nicechouffe 2.418090e-04 0 -5.467071e-04 2.799211e-04 -4.577128e-04 #> pecheresse 5.132538e-05 0 1.796104e-03 -3.206383e-04 -1.338857e-04 #> sierranevada 1.230683e-04 0 9.370620e-04 -7.543929e-04 2.972714e-04 #> tanglefoot -7.568911e-06 0 -7.405447e-04 3.028807e-04 6.337466e-04 #> tauro 7.872342e-07 0 1.122815e-04 -2.572009e-04 -8.133564e-04 #> westmalle 1.478645e-04 0 1.228197e-03 -2.741133e-04 9.140310e-05 #> amrut -2.042009e-05 0 4.658444e-04 -4.347520e-04 -3.326225e-05 #> ballantines -8.925358e-06 0 -5.591149e-04 1.469581e-03 -1.536579e-03 #> bushmills -2.889262e-05 0 -3.958316e-04 1.944836e-03 -7.053533e-05 #> chivas -7.474859e-05 0 -1.172232e-03 -1.218925e-03 -3.262755e-05 #> dalmore 8.076785e-05 0 6.958725e-04 -1.680610e-03 6.152298e-04 #> famousgrouse 1.145499e-04 0 7.115395e-05 8.468121e-04 -4.933730e-04 #> glendronach -4.912820e-05 0 -7.099606e-05 6.421159e-04 -4.706785e-04 #> glenmorangie 1.828692e-05 0 -8.919633e-06 -2.628346e-04 9.674043e-05 #> highlandpark -4.147565e-05 0 -1.617000e-03 5.528353e-04 -3.372340e-04 #> jackdaniels 6.663192e-06 0 5.328968e-04 -1.540810e-03 -5.769145e-04 #> jb -6.291564e-05 0 -2.505933e-03 -9.424246e-04 -8.780719e-04 #> johnniewalker 1.655345e-04 0 4.677592e-03 -4.233763e-04 -1.898993e-03 #> magallan 3.047713e-05 0 2.189543e-04 4.632813e-04 1.888985e-04 #> makersmark 1.662543e-05 0 1.698257e-03 -6.596354e-04 3.533379e-04 #> oban 5.922167e-05 0 6.795967e-07 1.085005e-06 -4.641661e-04 #> oldpotrero 5.577825e-05 0 -6.093255e-05 4.513517e-05 -4.902640e-04 #> redbreast 7.687024e-05 0 -1.468386e-03 1.265193e-04 -1.396525e-04 #> tamdhu -7.372278e-05 0 9.586941e-04 6.330302e-04 -2.779959e-04 #> wildturkey -4.151273e-05 0 -9.213008e-05 -1.129525e-03 -4.176692e-04 #> yoichi 3.983470e-06 0 5.380772e-05 -7.906572e-05 -7.656576e-04 #> C5 C6 C7 C8 #> brahma -1.259407e-03 -3.994402e-03 3.268582e-03 4.792269e-04 #> caney -4.017802e-05 4.699805e-04 2.518166e-04 6.300072e-04 #> chimay -4.663387e-04 -7.424827e-05 -8.096453e-05 9.946667e-04 #> corona 1.867708e-04 6.888736e-04 3.145355e-04 5.189042e-04 #> deusventrue 1.463377e-03 9.055123e-04 -2.834923e-04 -1.443910e-03 #> duvel 3.178998e-04 2.219253e-04 5.438377e-04 -3.518900e-06 #> franziskaner 1.054384e-03 2.433412e-04 9.526672e-04 8.662476e-04 #> grimbergen -6.417041e-04 -1.403671e-03 1.850428e-04 1.990252e-04 #> guiness 8.516115e-05 5.947385e-04 -3.856099e-04 2.426892e-04 #> hoegardeen -6.536099e-04 -5.091092e-04 -6.872483e-04 -4.089876e-04 #> jupiler 4.242307e-04 1.903101e-04 -1.512322e-04 3.486794e-04 #> kingfisher 1.200089e-03 4.039578e-05 -2.246083e-04 -6.682649e-04 #> latrappe -2.100725e-04 4.680496e-04 1.907268e-04 -1.386083e-04 #> lindemanskriek 2.721525e-04 -8.593526e-04 -1.905709e-04 1.402970e-04 #> nicechouffe -4.033887e-04 -3.674008e-04 -1.582921e-04 -3.898917e-04 #> pecheresse -3.165154e-04 -6.798663e-04 -1.857663e-04 -5.070674e-04 #> sierranevada 4.903049e-04 5.175725e-04 -5.450918e-04 -6.169308e-04 #> tanglefoot 6.556462e-04 1.058980e-03 8.585128e-04 5.745493e-04 #> tauro -4.748704e-04 -3.315681e-04 -4.564306e-04 -3.514821e-04 #> westmalle -4.491227e-04 -2.495132e-04 -7.270457e-05 -1.344863e-04 #> amrut 8.477464e-05 -1.080422e-04 2.126076e-04 -9.256970e-05 #> ballantines 6.528392e-04 -2.944984e-04 -5.656855e-04 1.789388e-04 #> bushmills 9.280815e-04 -4.013982e-04 -6.650163e-04 -5.644542e-04 #> chivas 1.300827e-04 -3.851168e-05 4.239507e-05 1.334791e-04 #> dalmore -2.964899e-04 -1.304289e-04 7.782306e-04 -4.877421e-04 #> famousgrouse 6.303902e-04 -1.322629e-04 -2.372041e-04 -2.550728e-05 #> glendronach -3.501431e-04 -2.525866e-04 3.742212e-04 1.133101e-04 #> glenmorangie -3.395833e-04 -4.246431e-04 -3.274667e-04 1.061570e-04 #> highlandpark 6.066669e-04 1.088092e-03 5.256719e-04 5.273203e-04 #> jackdaniels 1.023982e-03 9.323203e-04 1.214171e-03 5.898250e-04 #> jb 2.339479e-04 3.473492e-04 3.733691e-04 1.626720e-04 #> johnniewalker -8.686486e-04 -1.355694e-03 1.175580e-03 3.264915e-04 #> magallan 2.310078e-04 -1.038695e-04 -1.026307e-05 1.023165e-04 #> makersmark -5.037028e-04 -1.240866e-04 -7.956100e-05 -6.606345e-05 #> oban -3.076544e-04 -4.937905e-04 -1.310019e-05 -2.416906e-04 #> oldpotrero -5.717320e-04 -9.307817e-04 1.291075e-04 -5.512552e-04 #> redbreast -6.765261e-04 1.325618e-04 4.297985e-04 3.419357e-04 #> tamdhu -1.871447e-04 -1.524034e-04 6.923348e-05 -5.932353e-04 #> wildturkey -5.568095e-04 1.396939e-04 -3.130911e-04 -2.441291e-05 #> yoichi -1.807137e-04 -7.887244e-04 -4.647802e-04 -2.321719e-04 #> C9 C10 C11 C12 #> brahma -1.321861e-03 7.225736e-04 2.052451e-04 1.666890e-04 #> caney 4.837212e-04 -3.443095e-04 1.349160e-04 4.336526e-06 #> chimay -5.660053e-04 2.292011e-04 3.851391e-04 -2.066153e-05 #> corona 3.419355e-04 -4.427112e-05 5.053095e-04 2.703064e-04 #> deusventrue 5.149210e-05 4.983572e-04 -8.471361e-05 3.773608e-04 #> duvel 4.727181e-05 8.518990e-04 5.267156e-05 -7.761916e-06 #> franziskaner 4.052798e-04 2.307566e-04 5.425481e-04 8.822035e-04 #> grimbergen -4.235811e-04 -1.047152e-04 8.528320e-05 -4.862829e-04 #> guiness 2.578559e-05 -4.057230e-04 3.454914e-04 3.070080e-04 #> hoegardeen -2.093222e-04 -8.166019e-05 -5.849685e-04 -1.080950e-04 #> jupiler 3.426590e-04 1.476449e-04 3.134641e-04 2.698336e-04 #> kingfisher 1.267526e-04 2.565541e-04 -2.246671e-04 6.355569e-05 #> latrappe -4.351985e-06 -5.637614e-05 4.355069e-04 3.406179e-04 #> lindemanskriek -4.691485e-04 6.262551e-04 3.619995e-05 5.173449e-04 #> nicechouffe -2.084102e-04 4.207808e-04 7.211961e-05 -7.528575e-05 #> pecheresse -2.691263e-04 -5.693772e-04 -3.209598e-04 2.785471e-04 #> sierranevada 1.686643e-04 2.583335e-04 8.547137e-04 -1.139936e-04 #> tanglefoot 7.740523e-04 4.070373e-04 5.906937e-04 9.596081e-04 #> tauro -3.210499e-04 -2.265987e-04 5.213196e-05 1.560054e-07 #> westmalle 4.839335e-04 5.801730e-05 1.736045e-04 -1.456983e-04 #> amrut -1.864115e-04 -2.461486e-04 -3.925113e-04 -1.058934e-04 #> ballantines -5.195587e-04 3.044292e-04 -2.940957e-04 -8.254562e-05 #> bushmills -7.180710e-04 9.032786e-05 -3.120552e-04 3.338259e-04 #> chivas -3.525098e-05 -9.088640e-05 2.114664e-04 -4.123221e-05 #> dalmore 2.200639e-05 -1.248926e-04 -1.755355e-06 2.379108e-04 #> famousgrouse -3.212998e-04 3.215665e-04 -7.784050e-05 -5.945648e-04 #> glendronach 9.391914e-05 1.721023e-04 -5.496005e-04 -4.452810e-05 #> glenmorangie -1.452951e-05 2.274608e-05 8.210480e-05 2.227747e-04 #> highlandpark -1.043832e-04 2.593737e-04 7.274696e-06 -7.945600e-05 #> jackdaniels -6.541464e-05 8.873609e-04 3.142194e-04 5.911319e-04 #> jb -2.944987e-04 2.504811e-05 -2.127576e-05 -1.962938e-04 #> johnniewalker -8.111435e-05 -2.403699e-04 -1.403144e-03 -1.314933e-04 #> magallan 4.068423e-04 5.073294e-04 1.401801e-04 3.243760e-04 #> makersmark 4.971815e-04 6.070002e-04 1.442476e-05 -8.225582e-05 #> oban -1.976049e-04 -2.813942e-04 -2.577944e-04 -9.115022e-05 #> oldpotrero -5.682370e-04 1.529407e-07 -2.873197e-04 -1.840435e-04 #> redbreast -3.874401e-05 4.931648e-05 3.073398e-04 8.441133e-05 #> tamdhu -5.985664e-04 -4.647946e-04 -1.822017e-04 1.592463e-04 #> wildturkey 1.524887e-05 -6.414600e-04 2.874523e-04 -2.824274e-05 #> yoichi -2.834302e-04 1.556736e-04 -8.243757e-05 1.918715e-04 #> C13 C14 C15 C16 #> brahma -7.782826e-05 -1.930624e-05 3.379892e-04 -9.611430e-05 #> caney 5.571557e-05 1.585334e-04 -3.676568e-04 -2.424919e-04 #> chimay 2.069414e-04 -1.059161e-04 -5.895162e-05 -4.070464e-04 #> corona -3.358855e-05 3.794088e-04 7.431417e-05 7.851392e-04 #> deusventrue -2.738947e-04 7.547067e-04 2.411713e-04 2.337981e-04 #> duvel -2.899095e-04 1.153102e-04 4.201454e-04 -9.309399e-05 #> franziskaner 2.887549e-04 1.838704e-04 -1.076209e-04 -8.678411e-05 #> grimbergen -5.441140e-04 -1.117367e-04 8.398864e-05 4.536624e-06 #> guiness 1.002552e-04 4.035924e-04 4.794422e-04 -1.503013e-04 #> hoegardeen -6.620343e-04 -4.558427e-05 1.793707e-04 -2.548946e-04 #> jupiler 4.922288e-05 -5.590358e-08 1.921737e-04 -1.287978e-04 #> kingfisher -9.293274e-07 6.058292e-04 1.754447e-04 -1.321970e-04 #> latrappe 1.258799e-05 -4.563834e-04 -3.980325e-04 -3.632376e-05 #> lindemanskriek 3.942243e-05 1.639314e-04 3.621133e-04 2.603456e-05 #> nicechouffe 8.805995e-05 2.917660e-04 1.356673e-04 -1.709613e-04 #> pecheresse -4.861071e-04 -4.521904e-05 -4.938033e-05 1.569629e-04 #> sierranevada -2.667776e-04 5.072602e-05 -1.791841e-04 -7.011575e-05 #> tanglefoot 2.953027e-04 -9.831802e-06 -8.747989e-05 1.619364e-04 #> tauro -9.632911e-05 -9.375203e-05 -4.284123e-05 -2.047570e-04 #> westmalle -1.393513e-04 -1.584604e-04 -3.324221e-04 2.549518e-04 #> amrut 4.297953e-05 1.515928e-04 8.652384e-05 -1.182304e-04 #> ballantines 1.275977e-04 -1.152623e-04 -9.205056e-05 -4.163553e-09 #> bushmills -3.457626e-04 4.250469e-05 3.552076e-05 -5.053800e-04 #> chivas -1.777372e-04 -9.492327e-05 -2.055696e-04 5.817240e-05 #> dalmore 2.367824e-05 3.601473e-04 -1.802035e-04 -7.233793e-05 #> famousgrouse -5.629740e-04 1.716016e-04 4.970078e-04 1.638608e-04 #> glendronach -1.861826e-04 -2.166241e-04 -2.725060e-05 -2.919820e-04 #> glenmorangie 4.284188e-04 -3.059123e-04 1.548577e-07 5.323021e-05 #> highlandpark -5.202986e-05 -4.127667e-05 2.586090e-05 -1.032951e-04 #> jackdaniels 5.896938e-05 -4.375330e-04 4.011936e-04 2.314189e-04 #> jb -2.916919e-04 -5.900720e-04 -2.136720e-04 7.329517e-05 #> johnniewalker -1.479419e-04 3.073803e-04 3.149823e-04 3.938711e-04 #> magallan 1.154100e-04 2.200612e-04 3.321945e-04 7.696785e-05 #> makersmark 3.337325e-04 -1.068357e-05 4.436158e-04 1.721234e-04 #> oban -2.999197e-04 1.035791e-04 -1.810039e-04 -1.185358e-04 #> oldpotrero -5.099520e-04 -2.591210e-04 -1.489559e-04 -4.091994e-04 #> redbreast -1.790354e-04 -2.991022e-04 1.768442e-04 1.061400e-05 #> tamdhu 2.201204e-04 3.136042e-04 -7.139993e-05 -3.052562e-04 #> wildturkey -4.051933e-04 1.346852e-05 2.079652e-04 -1.649571e-04 #> yoichi -1.379502e-04 -2.627384e-04 2.209794e-04 4.497007e-05 #> C17 C18 C19 C20 #> brahma -2.462206e-05 4.542898e-05 2.594677e-04 1.484945e-04 #> caney -3.200717e-04 -2.643818e-04 1.448941e-04 -1.295417e-04 #> chimay 2.615626e-04 1.230016e-04 -2.602910e-04 4.566772e-04 #> corona 1.619221e-04 -1.010082e-04 -9.475160e-05 4.604978e-05 #> deusventrue 4.889298e-04 3.580373e-04 2.948538e-04 -2.065040e-05 #> duvel 2.191614e-04 8.201863e-05 5.854558e-06 -8.940682e-05 #> franziskaner -8.092666e-05 -6.457841e-05 -2.824789e-04 -3.859311e-04 #> grimbergen -3.961946e-04 3.650999e-05 3.213716e-04 1.180102e-04 #> guiness 2.115046e-04 1.749610e-04 -1.746358e-04 -1.581495e-04 #> hoegardeen 7.197760e-05 -2.012077e-04 -2.334965e-04 4.422896e-05 #> jupiler -2.008260e-05 -2.470511e-04 -1.663822e-04 -1.150708e-04 #> kingfisher -1.203436e-04 1.416556e-05 1.233551e-04 -1.424855e-04 #> latrappe -3.509800e-04 -3.539077e-04 -3.910480e-04 -1.488442e-04 #> lindemanskriek 4.564241e-04 6.139873e-05 2.472946e-04 -7.212713e-05 #> nicechouffe 2.088775e-05 -3.045093e-04 -4.116058e-05 9.187509e-05 #> pecheresse 3.099554e-04 -1.756667e-04 1.277428e-04 -9.767197e-05 #> sierranevada -2.374147e-04 1.934474e-04 3.562142e-04 -2.243221e-05 #> tanglefoot 2.693295e-04 -1.713949e-04 -4.543909e-05 -1.225435e-04 #> tauro -8.921517e-05 -3.763435e-05 2.081496e-05 5.772223e-05 #> westmalle -2.914399e-04 -1.082880e-04 -2.262683e-04 -1.303860e-04 #> amrut -2.450964e-04 -2.485646e-04 -1.839206e-04 -1.708371e-04 #> ballantines -1.568616e-04 -3.125000e-04 -5.701268e-05 -4.566974e-04 #> bushmills 4.389152e-04 1.152775e-04 -2.553003e-05 -2.255408e-04 #> chivas 7.206033e-05 -4.803968e-06 1.003524e-04 -5.006564e-05 #> dalmore -1.373879e-04 -3.425411e-04 1.887325e-04 -6.857783e-05 #> famousgrouse 1.098427e-04 3.769386e-04 -4.635939e-05 -4.732985e-04 #> glendronach 7.079193e-05 6.679345e-05 -1.471216e-05 -3.174342e-05 #> glenmorangie -2.887843e-04 3.663345e-06 8.615632e-05 1.443928e-04 #> highlandpark 4.361895e-05 -3.546641e-04 -2.543206e-04 -1.334150e-04 #> jackdaniels 6.397125e-04 3.132485e-04 -2.083165e-04 2.659526e-04 #> jb -1.357708e-05 6.999975e-06 1.014748e-04 1.390686e-04 #> johnniewalker 2.315024e-04 -7.245385e-04 -2.532287e-04 -1.843753e-04 #> magallan 2.912400e-04 2.959502e-04 2.326573e-04 2.930574e-04 #> makersmark -2.361525e-04 -2.818088e-05 4.879862e-04 3.105270e-05 #> oban -1.633058e-04 -9.438665e-05 1.228272e-04 3.653250e-05 #> oldpotrero 5.903880e-06 -3.358189e-04 1.091066e-04 3.691985e-04 #> redbreast -2.352497e-04 3.310177e-04 4.139320e-05 6.943862e-05 #> tamdhu -3.526671e-04 -1.708794e-04 -2.559883e-04 -1.303370e-04 #> wildturkey -1.566046e-04 3.186305e-04 -2.758046e-04 -4.246431e-05 #> yoichi 9.430638e-06 2.581787e-04 1.886038e-04 -4.095463e-05 #> C21 C22 C23 C24 #> brahma -2.357683e-04 -3.255489e-04 -3.888181e-05 1.601136e-04 #> caney 1.953747e-04 -2.101846e-04 -1.492333e-04 3.676434e-04 #> chimay -2.692597e-04 2.257056e-04 -1.397033e-05 -5.646081e-05 #> corona 1.999724e-04 6.189685e-05 -3.340597e-04 -1.953675e-04 #> deusventrue 1.591834e-04 -2.832760e-04 1.458864e-04 -8.427409e-05 #> duvel -2.955388e-04 -1.892748e-05 -2.437293e-04 -1.378691e-04 #> franziskaner -1.525330e-04 1.618032e-04 -5.139084e-05 -1.606879e-05 #> grimbergen 3.164260e-04 -1.221952e-05 1.167013e-04 3.467071e-04 #> guiness -3.339505e-04 -1.886574e-04 -2.230582e-04 -1.727871e-04 #> hoegardeen 1.874664e-04 1.600131e-04 1.958262e-04 -1.223848e-04 #> jupiler -1.957295e-04 1.587807e-04 -1.426824e-04 8.126834e-06 #> kingfisher -1.145588e-04 3.095102e-04 1.748363e-04 -2.958698e-05 #> latrappe -1.023105e-04 -4.186424e-04 -1.825023e-04 -3.951876e-05 #> lindemanskriek -1.380429e-04 -1.370311e-04 -1.728854e-04 1.500360e-04 #> nicechouffe -3.201139e-04 -4.944808e-04 -1.371930e-05 1.532805e-04 #> pecheresse 2.436237e-04 1.596311e-04 -2.128184e-04 3.576426e-04 #> sierranevada -1.687220e-05 -5.977664e-05 3.650123e-05 1.326880e-04 #> tanglefoot -3.427494e-04 -1.813205e-04 -4.801367e-05 5.543276e-06 #> tauro 9.933100e-05 7.064143e-05 2.098766e-04 6.374442e-05 #> westmalle 3.884283e-05 2.556888e-04 2.913800e-04 2.358729e-05 #> amrut -2.513723e-05 -4.865046e-05 6.915158e-05 9.554616e-05 #> ballantines -1.402023e-05 -1.177383e-04 -3.066781e-04 1.301059e-04 #> bushmills -1.016039e-04 -6.256814e-06 -2.782939e-05 -1.900221e-04 #> chivas -1.197585e-04 -2.656528e-05 -5.029721e-05 -7.452762e-05 #> dalmore 7.727193e-06 4.643119e-06 -1.397221e-04 1.462100e-04 #> famousgrouse -1.411842e-04 1.102486e-04 3.261561e-05 -1.482466e-04 #> glendronach 1.970525e-07 3.802927e-05 -1.079405e-04 -1.582899e-04 #> glenmorangie 8.129446e-05 3.967154e-05 -3.128011e-04 -1.635773e-05 #> highlandpark -1.802191e-04 -8.267955e-05 -1.275983e-04 1.323282e-04 #> jackdaniels -3.325901e-05 -3.256437e-05 -1.762269e-04 -5.790588e-04 #> jb -2.625235e-04 -1.667028e-04 -3.018992e-05 -5.868382e-05 #> johnniewalker -2.834732e-04 -4.393571e-04 -5.273623e-04 -5.014701e-04 #> magallan 6.945665e-05 -4.596990e-05 1.673075e-04 1.056113e-04 #> makersmark -5.032255e-04 -1.915835e-04 -7.805228e-05 2.830415e-04 #> oban 1.973869e-04 -5.481002e-05 1.739785e-05 8.027456e-05 #> oldpotrero 9.772372e-05 5.074158e-04 -1.364118e-04 1.254921e-04 #> redbreast 1.239392e-04 -8.674632e-05 1.488872e-04 -1.211999e-04 #> tamdhu 1.950283e-04 2.290251e-04 1.358859e-04 2.243632e-04 #> wildturkey 1.942568e-04 -2.562719e-04 1.268438e-04 1.317126e-04 #> yoichi -3.707432e-05 1.186764e-04 2.174843e-04 -1.334328e-04 #> C25 C26 C27 C28 #> brahma -2.168918e-04 5.311528e-06 -1.087851e-04 -1.129037e-04 #> caney 1.277543e-04 1.380997e-04 2.220567e-04 3.358853e-04 #> chimay -1.984526e-05 -2.262631e-04 9.411602e-05 -1.216533e-04 #> corona -1.099958e-04 -2.321293e-04 9.791988e-05 -3.093851e-04 #> deusventrue -3.818007e-04 -1.202012e-04 -8.165642e-05 -2.065725e-04 #> duvel 6.570113e-05 1.163622e-05 -1.505426e-04 -3.998066e-04 #> franziskaner 1.056867e-04 2.160659e-04 9.652675e-05 -1.456826e-04 #> grimbergen 1.243239e-04 2.355805e-04 1.329031e-04 2.166290e-04 #> guiness -3.127194e-04 -2.147014e-04 -9.180930e-05 6.054615e-06 #> hoegardeen -1.352939e-04 6.037898e-05 1.957805e-04 4.256147e-04 #> jupiler 1.463359e-04 -3.338668e-05 1.760442e-04 5.815076e-05 #> kingfisher 2.531356e-04 -2.597102e-04 -2.809453e-05 -1.026030e-04 #> latrappe 1.588111e-04 2.847210e-04 1.358552e-04 2.016904e-04 #> lindemanskriek 3.932121e-05 1.442253e-04 2.350166e-05 -2.638866e-05 #> nicechouffe -3.689553e-04 8.847560e-05 -7.805075e-05 -2.565099e-04 #> pecheresse 6.242504e-05 -2.132918e-04 -3.333979e-05 1.240727e-04 #> sierranevada -3.679124e-05 -9.493554e-05 -1.092878e-04 -2.741258e-05 #> tanglefoot -1.101320e-04 -2.362401e-04 -2.339105e-04 -1.321334e-04 #> tauro 8.184466e-05 6.090987e-05 -1.724211e-04 7.187784e-05 #> westmalle 1.390117e-04 -8.097500e-06 2.799535e-04 -2.956551e-05 #> amrut -9.040566e-06 1.628774e-04 4.928935e-05 1.955840e-04 #> ballantines -1.881555e-04 7.913061e-05 1.784297e-04 5.278585e-05 #> bushmills -1.882944e-04 2.576531e-04 1.135306e-04 7.203581e-05 #> chivas -1.217136e-05 1.459306e-04 -9.685215e-05 -2.166137e-04 #> dalmore -9.665762e-05 -1.115235e-05 -1.083964e-05 -1.765557e-04 #> famousgrouse 3.163937e-04 4.802734e-04 5.904108e-05 -6.039223e-05 #> glendronach -1.026367e-04 2.392065e-06 -6.767780e-05 4.176678e-05 #> glenmorangie 2.048456e-04 -1.662791e-04 2.088261e-04 1.762876e-04 #> highlandpark 1.294035e-04 1.854087e-04 1.168264e-04 2.134443e-05 #> jackdaniels -7.053449e-05 -2.075346e-04 -1.639481e-04 -1.499068e-04 #> jb 5.418975e-05 -8.534276e-05 -2.456867e-05 4.274040e-05 #> johnniewalker 1.110272e-04 3.863564e-04 5.023688e-04 4.238384e-04 #> magallan -1.464085e-04 8.875416e-05 -2.200694e-04 1.964866e-04 #> makersmark -5.747589e-05 -2.186057e-04 -4.321386e-04 -2.155324e-04 #> oban 1.759539e-04 1.294537e-04 -1.156101e-04 -1.182355e-04 #> oldpotrero 1.780324e-04 2.109986e-04 4.178527e-04 1.858207e-04 #> redbreast -1.305587e-04 -1.353161e-04 -5.952368e-05 -5.479947e-05 #> tamdhu 1.030517e-04 -1.192849e-04 -7.804091e-05 -1.508532e-04 #> wildturkey 1.934527e-04 3.215318e-04 1.288810e-06 7.522784e-05 #> yoichi -1.419941e-04 7.818576e-05 -1.276250e-05 1.358157e-04 #> C29 C30 C31 C32 #> brahma 5.059658e-05 -9.818126e-06 5.123235e-06 -1.428490e-04 #> caney 1.965508e-05 1.361109e-04 1.243089e-04 -1.336020e-04 #> chimay -9.070337e-05 -2.449328e-04 -6.708875e-05 4.022984e-05 #> corona 1.431245e-04 -2.173931e-04 -2.259074e-04 -2.787437e-04 #> deusventrue -1.783859e-04 -4.874278e-06 -3.212311e-04 -1.202210e-04 #> duvel -1.385701e-04 6.771122e-05 1.314672e-04 1.274480e-04 #> franziskaner -3.544520e-05 -1.570021e-04 4.143696e-05 -3.250007e-05 #> grimbergen 1.283964e-04 -1.619576e-04 -5.782503e-05 -7.440839e-05 #> guiness 1.623033e-04 1.124547e-04 1.457427e-04 2.620457e-04 #> hoegardeen 1.488354e-04 1.008707e-04 1.592857e-04 6.914513e-05 #> jupiler -1.025156e-04 -4.960354e-05 -5.397414e-05 1.393697e-05 #> kingfisher -2.551041e-04 -7.819386e-05 -4.231436e-04 1.136672e-05 #> latrappe 4.093292e-04 5.106237e-04 4.749064e-04 4.502392e-04 #> lindemanskriek -3.724973e-05 -8.158519e-05 -2.793628e-05 -2.304596e-04 #> nicechouffe -3.182117e-04 8.423888e-05 2.658457e-04 -1.540389e-04 #> pecheresse 1.880359e-04 1.197157e-04 2.589766e-04 3.113602e-04 #> sierranevada 1.574300e-05 -1.339857e-04 -3.371716e-05 2.780362e-05 #> tanglefoot -1.327847e-04 -1.552258e-04 -1.073922e-04 1.602931e-05 #> tauro -2.269286e-04 1.424808e-05 -1.177695e-05 4.677918e-05 #> westmalle 1.383318e-04 1.593729e-04 1.948654e-05 -1.302536e-04 #> amrut 1.270967e-04 -4.365482e-06 6.464597e-05 -1.148550e-04 #> ballantines 6.405210e-05 1.648409e-05 1.047806e-04 1.061185e-04 #> bushmills -8.378647e-05 2.595240e-05 -5.337516e-05 7.165584e-05 #> chivas 1.016956e-04 6.725272e-06 5.441987e-05 1.470306e-04 #> dalmore 1.881831e-04 1.517540e-04 7.488225e-05 2.682798e-05 #> famousgrouse -2.725213e-05 3.255800e-05 -5.556833e-05 -2.891368e-05 #> glendronach 3.820905e-05 2.432726e-05 6.797367e-05 -7.383064e-05 #> glenmorangie -2.481661e-04 -5.482361e-05 8.139003e-05 5.261718e-05 #> highlandpark 2.797181e-05 6.660466e-05 1.954252e-04 1.378264e-05 #> jackdaniels -1.941603e-04 -7.448475e-05 -1.546534e-04 -1.620665e-04 #> jb 1.500695e-04 1.005877e-04 -2.723725e-06 5.583773e-05 #> johnniewalker 5.239015e-05 4.615600e-05 1.840488e-04 4.954225e-04 #> magallan -2.830981e-05 -3.374251e-04 -1.457816e-05 1.537940e-04 #> makersmark 2.276041e-04 2.168941e-04 1.270890e-04 -8.071940e-05 #> oban -9.838630e-05 1.646660e-04 1.708445e-04 4.611304e-05 #> oldpotrero 2.634114e-04 1.184883e-05 1.039594e-04 1.387515e-04 #> redbreast -1.449013e-04 1.984628e-05 -1.465977e-04 -8.637397e-05 #> tamdhu -1.684881e-05 -1.183542e-04 2.023348e-04 2.682289e-04 #> wildturkey -5.207759e-05 -1.906513e-04 -1.833178e-04 -2.062892e-04 #> yoichi -1.389330e-05 -4.418834e-05 5.367797e-05 -6.039718e-05 #> D1 D2 D3 D4 D5 #> brahma 0.2937120 -0.04602927 0.05240292 -0.035768593 0.03999516 #> caney 0.3046235 -0.07069129 0.05062805 -0.011400633 0.04383297 #> chimay 0.4156841 -0.09356117 0.04692603 -0.019249436 0.03965332 #> corona 0.2745921 -0.05755121 0.05150878 -0.011252954 0.03689351 #> deusventrue 0.3149661 -0.11964363 0.05529900 0.007135060 0.03861865 #> duvel 0.4496172 -0.09170033 0.05080071 -0.024018306 0.03036868 #> franziskaner 0.3002734 -0.05637154 0.04411627 -0.030282997 0.03014850 #> grimbergen 0.3651919 -0.09065897 0.05082210 -0.010242594 0.04317369 #> guiness 0.3505997 -0.08196508 0.04422914 -0.022614638 0.04330972 #> hoegardeen 0.2945708 -0.06921001 0.05080275 -0.012677940 0.04146196 #> jupiler 0.2872499 -0.06835188 0.05058090 -0.011055591 0.04109503 #> kingfisher 0.3038732 -0.06930174 0.04366992 -0.021888850 0.03308585 #> latrappe 0.4672257 -0.08743553 0.04401705 -0.038810531 0.02809569 #> lindemanskriek 0.3008112 -0.08389446 0.04783652 -0.013888395 0.04157982 #> nicechouffe 0.3127453 -0.09102591 0.04393446 -0.019927059 0.03779695 #> pecheresse 0.2877918 -0.07053519 0.05180968 -0.009320568 0.04090001 #> sierranevada 0.3773035 -0.07825101 0.05234901 -0.021705236 0.03981425 #> tanglefoot 0.4079636 -0.09801072 0.04110270 -0.028374451 0.04305818 #> tauro 0.2869165 -0.06868727 0.05072815 -0.010829946 0.04098501 #> westmalle 0.2901614 -0.07168182 0.04932024 -0.012449351 0.03886788 #> amrut 0.2916508 -0.07148727 0.03950517 -0.025866432 0.04086520 #> ballantines 0.4617826 -0.07263052 0.04705459 -0.054513278 0.00386769 #> bushmills 0.3159155 -0.02993821 0.05271205 -0.040523047 0.01619821 #> chivas 0.4010304 -0.12319740 0.04665481 -0.003452339 0.05226216 #> dalmore 0.4148687 -0.14805699 0.04396881 -0.010373143 0.05369374 #> famousgrouse 0.3082730 -0.05984603 0.04245023 -0.038145717 0.02994654 #> glendronach 0.2880496 -0.06941189 0.04010808 -0.026119002 0.04146027 #> glenmorangie 0.2784428 -0.06974209 0.02918920 -0.025306813 0.04836028 #> highlandpark 0.4216191 -0.07914764 0.04537064 -0.044351756 0.02868104 #> jackdaniels 0.3474874 -0.08171102 0.04501412 -0.023326513 0.04362364 #> jb 0.2978504 -0.07724044 0.04167029 -0.021228975 0.04549082 #> johnniewalker 0.3097702 -0.04720860 0.04457306 -0.040162288 0.02378800 #> magallan 0.2790080 -0.04764937 0.01811567 -0.036589697 0.02988117 #> makersmark 0.3905990 -0.12195322 0.04665759 0.014950483 0.04867625 #> oban 0.2773362 -0.07277254 0.03313763 -0.023775433 0.04405146 #> oldpotrero 0.3550787 -0.13906787 0.05059907 0.008348999 0.04726562 #> redbreast 0.3884532 -0.13265717 0.04117925 -0.003816545 0.05332588 #> tamdhu 0.2956700 -0.06219547 0.04086923 -0.024902731 0.04397834 #> wildturkey 0.3186215 -0.08962249 0.03633236 -0.023651702 0.05160018 #> yoichi 0.3745590 -0.07064336 0.04209729 -0.040564238 0.03281077 #> D6 D7 D8 D9 #> brahma 1.156917e-02 1.544573e-02 0.0013278090 0.0017860170 #> caney 4.485691e-03 9.597789e-03 0.0016029758 0.0082459711 #> chimay 1.731744e-02 1.044446e-02 0.0104067305 0.0026404547 #> corona -4.664986e-03 9.465002e-03 0.0001838085 0.0120730321 #> deusventrue -8.770510e-04 1.356919e-02 0.0076757796 0.0034745699 #> duvel 1.486796e-02 7.642213e-03 0.0154756340 0.0060020330 #> franziskaner 1.266218e-03 1.748451e-02 0.0047455611 0.0067787344 #> grimbergen 7.100085e-03 6.253179e-03 0.0076965820 0.0090999349 #> guiness 9.543784e-03 9.549881e-03 0.0017249204 0.0017518501 #> hoegardeen 2.601196e-03 1.267815e-02 0.0028528664 0.0079320590 #> jupiler 2.215650e-03 1.160311e-02 0.0034969489 0.0080290760 #> kingfisher 2.046087e-03 1.149394e-02 0.0039224376 0.0069746627 #> latrappe 2.444196e-02 2.163781e-02 0.0204539980 -0.0001441159 #> lindemanskriek 2.496230e-03 1.222294e-02 0.0053531769 0.0062723553 #> nicechouffe 3.314725e-03 1.247704e-02 0.0066425182 0.0051531928 #> pecheresse 2.471297e-03 1.468476e-02 0.0056123765 0.0084044229 #> sierranevada 1.057630e-02 8.974816e-03 0.0026404084 0.0003673360 #> tanglefoot 1.902021e-02 1.046530e-02 0.0039430719 -0.0033493172 #> tauro 2.321158e-03 1.173141e-02 0.0034750116 0.0079425387 #> westmalle 1.786521e-03 1.515342e-02 0.0060316179 0.0079388255 #> amrut 6.369733e-03 1.572832e-02 -0.0038463793 0.0013700406 #> ballantines 4.344419e-03 1.645402e-02 0.0254142957 0.0095935791 #> bushmills -1.167929e-02 2.000745e-02 0.0117755165 0.0158424792 #> chivas 7.036241e-03 -4.363041e-03 0.0063540528 0.0079672331 #> dalmore 1.718407e-02 -6.837798e-03 0.0070735547 -0.0019258037 #> famousgrouse 4.059251e-03 2.229183e-02 0.0037608752 0.0010406075 #> glendronach 6.223170e-03 1.521132e-02 -0.0043261577 0.0013210684 #> glenmorangie 5.822448e-03 1.976818e-02 -0.0044147538 0.0033213121 #> highlandpark 1.979571e-02 2.717259e-02 0.0200795294 -0.0021232596 #> jackdaniels 1.186579e-02 1.329499e-02 -0.0005343742 -0.0016003714 #> jb 6.441694e-03 1.187397e-02 -0.0057652170 0.0017868329 #> johnniewalker 8.789822e-05 2.661158e-02 0.0128165570 0.0105593342 #> magallan 6.181261e-03 2.628647e-02 0.0002557046 0.0036531313 #> makersmark -5.885380e-03 -3.124763e-04 0.0123974490 0.0123986615 #> oban 7.290747e-03 1.526810e-02 -0.0064234752 0.0024990961 #> oldpotrero -1.263673e-03 9.106123e-06 0.0131403235 0.0062358607 #> redbreast 7.554115e-03 -5.549155e-03 0.0028962725 0.0066649976 #> tamdhu 7.609569e-03 1.817766e-02 -0.0043937269 0.0004398248 #> wildturkey 1.072078e-02 1.329394e-02 -0.0045720419 -0.0006442784 #> yoichi 1.665764e-02 2.932085e-02 0.0147708913 0.0009353830 #> D10 D11 D12 D13 #> brahma 0.006789017 0.0048196384 0.007143143 1.926114e-03 #> caney 0.011464283 0.0039468981 0.003663644 -7.807175e-04 #> chimay 0.012590865 0.0018154608 0.002625857 -8.084753e-04 #> corona 0.008346831 0.0027556006 0.002567053 5.432929e-04 #> deusventrue 0.006022626 0.0007085549 0.005811255 2.407200e-04 #> duvel 0.014318246 0.0021405582 -0.001168779 -3.377569e-03 #> franziskaner 0.007215285 0.0030768626 0.006498196 8.028161e-04 #> grimbergen 0.013935311 0.0016133249 0.001782113 -1.816164e-03 #> guiness 0.013609736 0.0052742301 0.006464424 -5.287655e-04 #> hoegardeen 0.007661150 0.0026973921 0.005420800 9.995327e-04 #> jupiler 0.007523271 0.0027339312 0.004363034 1.338460e-03 #> kingfisher 0.006826146 0.0028630395 0.005290393 2.293278e-03 #> latrappe 0.007468498 -0.0011091276 0.003570302 2.011317e-03 #> lindemanskriek 0.007494807 0.0009831097 0.006687031 1.442627e-03 #> nicechouffe 0.007804735 0.0010554318 0.006544953 1.205823e-03 #> pecheresse 0.006507851 0.0023044001 0.005130825 6.852104e-04 #> sierranevada 0.013424754 0.0060565295 0.007716962 -7.405564e-04 #> tanglefoot 0.012760316 0.0055315212 0.008787267 1.064633e-03 #> tauro 0.007452360 0.0026002512 0.004223806 1.378572e-03 #> westmalle 0.005389195 0.0009150318 0.004619774 1.262124e-03 #> amrut 0.008090140 0.0077694214 0.009648834 -1.144556e-03 #> ballantines 0.009641210 -0.0013505569 0.001193993 7.396074e-04 #> bushmills 0.012190958 0.0027373737 0.003932980 -3.732204e-03 #> chivas 0.019338356 0.0019726115 0.002305432 -2.020219e-03 #> dalmore 0.016575636 0.0049437344 0.004000701 5.545799e-03 #> famousgrouse 0.003906640 0.0019458696 0.010187413 3.371833e-03 #> glendronach 0.008581179 0.0087430642 0.009902698 -6.391147e-04 #> glenmorangie 0.007165778 0.0033642678 0.009454943 -1.032963e-03 #> highlandpark 0.003043362 -0.0045393480 0.006887804 5.658900e-03 #> jackdaniels 0.009896143 0.0071305091 0.011652937 1.190034e-03 #> jb 0.011312129 0.0089093269 0.008895351 -2.914444e-03 #> johnniewalker 0.004724823 -0.0013880745 0.003178167 -3.556457e-04 #> magallan -0.002901850 0.0030725685 0.006182579 4.129056e-03 #> makersmark 0.007706173 -0.0025568628 0.002741739 2.566683e-03 #> oban 0.007789470 0.0092615797 0.008856510 -4.461327e-04 #> oldpotrero 0.009884923 0.0004827760 0.006465018 2.203812e-03 #> redbreast 0.019010171 0.0030489037 0.003575003 -1.081990e-03 #> tamdhu 0.006990252 0.0067355151 0.011091059 -3.536949e-05 #> wildturkey 0.012225665 0.0056575767 0.009083087 -3.677090e-03 #> yoichi 0.001967838 -0.0043542059 0.006408266 2.324685e-03 #> D14 D15 D16 D17 #> brahma 0.0031275641 4.157794e-04 0.0019555535 9.890925e-04 #> caney 0.0037093445 1.744155e-03 0.0009874891 -4.753255e-04 #> chimay 0.0009166164 2.220375e-03 -0.0019270610 2.484912e-04 #> corona 0.0058977403 1.606741e-03 0.0024960621 -7.639544e-04 #> deusventrue 0.0033919410 1.559680e-04 0.0015420583 9.082901e-04 #> duvel -0.0029313189 2.502233e-03 0.0006963735 1.208427e-03 #> franziskaner 0.0041872022 9.225601e-04 0.0024966790 6.722121e-04 #> grimbergen 0.0019309787 1.956568e-03 0.0005450639 2.675718e-04 #> guiness 0.0018638986 2.692559e-03 0.0019352055 1.628688e-03 #> hoegardeen 0.0041552095 -1.065713e-04 0.0016889222 -3.166547e-04 #> jupiler 0.0033244959 9.848065e-05 0.0010603264 -6.525507e-05 #> kingfisher 0.0044673616 1.485094e-03 0.0023979578 6.894989e-04 #> latrappe -0.0008074752 1.664147e-03 -0.0021635248 7.689496e-04 #> lindemanskriek 0.0037615312 2.793989e-04 0.0016614073 1.352472e-03 #> nicechouffe 0.0038551513 1.311255e-03 0.0016680702 1.116012e-03 #> pecheresse 0.0025371633 -4.489783e-04 0.0008704132 -5.554931e-04 #> sierranevada 0.0005939006 1.474160e-03 0.0011437155 1.682900e-03 #> tanglefoot 0.0004785330 2.150301e-03 -0.0002248900 2.139070e-03 #> tauro 0.0033835451 1.001149e-04 0.0009107426 8.944532e-05 #> westmalle 0.0047945932 5.279402e-04 0.0014031914 -1.127039e-03 #> amrut 0.0006242293 -2.060446e-03 0.0027509103 2.295153e-03 #> ballantines 0.0026091729 2.944401e-03 0.0009597037 1.625268e-03 #> bushmills 0.0008108204 -1.658834e-03 0.0022376452 1.816720e-03 #> chivas -0.0003126890 3.062126e-03 0.0003784012 3.895628e-03 #> dalmore -0.0013721769 4.301123e-03 -0.0007346094 1.919821e-03 #> famousgrouse 0.0051280464 -2.095871e-03 -0.0014353739 -1.017602e-03 #> glendronach 0.0007605817 -2.608913e-03 0.0025423072 1.881103e-03 #> glenmorangie 0.0055043581 -3.529733e-04 0.0026449765 8.745923e-04 #> highlandpark 0.0046886634 2.790613e-03 -0.0028451046 -2.803900e-04 #> jackdaniels 0.0006010724 -1.874443e-03 -0.0001609028 1.721536e-03 #> jb 0.0006629365 -6.083868e-04 0.0040546060 2.647929e-03 #> johnniewalker 0.0052579368 -1.293010e-04 0.0022216234 -3.827680e-04 #> magallan 0.0055039424 -8.305055e-04 0.0012832388 -1.151480e-03 #> makersmark 0.0044651474 6.602691e-04 0.0009437839 -7.127560e-04 #> oban 0.0017261768 -1.145758e-03 0.0039396292 1.243568e-03 #> oldpotrero 0.0012186435 2.697974e-03 0.0002678611 1.879572e-03 #> redbreast 0.0008746647 3.392975e-03 0.0003544991 3.091612e-03 #> tamdhu 0.0033713850 -1.628121e-03 0.0024278166 1.560397e-03 #> wildturkey 0.0022983366 8.120105e-04 0.0033344198 2.666378e-03 #> yoichi 0.0060672149 1.801036e-03 0.0002647738 -5.632091e-05 #> D18 D19 D20 D21 #> brahma 6.293376e-04 3.896704e-04 -3.229345e-04 3.831138e-06 #> caney -7.645439e-04 -6.085621e-04 -3.245536e-04 -4.503156e-04 #> chimay -1.130345e-04 7.926418e-04 -1.780914e-04 -4.887150e-04 #> corona 1.024423e-03 8.842135e-05 4.313700e-04 -4.718718e-04 #> deusventrue -3.583324e-04 1.286906e-03 6.233120e-05 1.544907e-03 #> duvel -5.922990e-04 -1.333335e-04 4.815197e-04 -1.758102e-04 #> franziskaner 6.100396e-04 7.764117e-04 5.491195e-05 3.763780e-04 #> grimbergen -5.904705e-04 4.253926e-04 -2.173942e-04 5.361111e-04 #> guiness -6.191811e-04 -7.865923e-05 -7.407169e-04 -3.602892e-04 #> hoegardeen 5.654900e-04 3.283770e-05 -1.864209e-04 4.023209e-04 #> jupiler 3.689686e-04 -1.719041e-04 1.184231e-04 2.651784e-04 #> kingfisher 1.154506e-03 1.020985e-03 3.611220e-04 6.291875e-04 #> latrappe -2.088876e-03 -1.536620e-03 -1.005470e-03 -1.438940e-03 #> lindemanskriek -6.671207e-05 5.595716e-04 -6.809755e-04 2.883840e-04 #> nicechouffe -4.176123e-04 8.977287e-04 -5.825859e-04 2.514060e-04 #> pecheresse 2.960996e-04 -2.999634e-04 -5.143676e-04 5.298199e-04 #> sierranevada -1.402891e-03 -7.105184e-04 -1.406023e-03 -3.241741e-04 #> tanglefoot -4.466706e-04 1.003752e-03 -2.824955e-04 -4.366636e-04 #> tauro 5.077672e-04 -2.475905e-04 3.158794e-04 1.327427e-04 #> westmalle -4.447622e-04 3.776294e-04 4.195911e-04 8.484127e-04 #> amrut 2.150217e-03 1.310537e-03 5.423311e-04 1.191027e-03 #> ballantines -2.305305e-04 2.030836e-03 1.037686e-03 1.381778e-03 #> bushmills 1.883389e-03 1.671736e-03 1.085006e-03 1.129204e-03 #> chivas -7.487816e-04 -1.848059e-04 -7.542402e-04 -6.898937e-05 #> dalmore 1.853381e-03 -1.461692e-03 1.339406e-03 -6.406724e-04 #> famousgrouse 5.138360e-04 2.530545e-03 2.024220e-03 2.987046e-03 #> glendronach 2.040387e-03 1.241204e-03 4.021827e-04 1.360769e-03 #> glenmorangie 3.519697e-04 2.012743e-03 -9.903207e-04 1.364138e-03 #> highlandpark -2.634427e-03 -2.315674e-04 -8.854821e-04 -4.633894e-04 #> jackdaniels 6.015905e-04 9.398945e-04 -3.644850e-04 2.828080e-05 #> jb 9.951060e-04 8.239419e-04 -2.467022e-04 1.277872e-03 #> johnniewalker 1.083550e-03 1.030500e-03 1.236037e-03 2.082887e-03 #> magallan 2.235758e-03 1.613033e-03 2.732296e-03 1.761473e-03 #> makersmark -4.496665e-04 9.336664e-04 5.524012e-04 9.525012e-04 #> oban 2.228455e-03 -3.486102e-05 -4.580932e-05 6.453033e-04 #> oldpotrero -9.114012e-04 1.132774e-03 5.301941e-04 1.186192e-04 #> redbreast -1.950436e-04 9.281282e-04 -5.109409e-04 -7.237943e-06 #> tamdhu 9.609204e-04 1.925977e-03 -8.205987e-04 3.847804e-04 #> wildturkey -8.344240e-04 2.028382e-03 -1.207846e-03 1.686608e-03 #> yoichi -2.196066e-03 1.676181e-04 -1.415373e-03 1.009761e-03 #> D22 D23 D24 D25 #> brahma -6.023925e-04 -3.704707e-04 -8.677815e-04 -7.248682e-04 #> caney -1.173466e-03 -3.863544e-04 -1.351268e-03 -1.773197e-04 #> chimay -6.522348e-04 -7.978252e-04 -5.495898e-06 -1.800777e-03 #> corona -8.788427e-04 -4.830025e-05 -5.870134e-04 7.484502e-04 #> deusventrue 1.415082e-05 7.733248e-04 3.116257e-05 -6.374096e-04 #> duvel -2.941583e-04 -1.124154e-03 -1.118860e-03 -1.186668e-03 #> franziskaner -3.051374e-04 2.712854e-04 -3.334307e-04 6.527762e-05 #> grimbergen -3.660470e-04 -2.386308e-04 -7.363064e-04 -1.136209e-03 #> guiness -9.874371e-04 -2.115403e-04 -6.115358e-04 -1.042320e-03 #> hoegardeen -7.912932e-04 -6.136135e-05 -9.776025e-04 1.670660e-04 #> jupiler -5.807125e-04 -2.182125e-04 -5.863223e-04 -8.468729e-05 #> kingfisher -1.199056e-04 1.361850e-04 -3.033656e-04 -2.821181e-04 #> latrappe 4.653398e-04 -1.234463e-03 1.614692e-04 -4.335716e-04 #> lindemanskriek -7.295737e-04 4.368240e-06 -5.637679e-05 -1.888630e-04 #> nicechouffe -3.296172e-04 1.792659e-04 -2.905989e-04 -3.368342e-04 #> pecheresse -4.971391e-04 -1.135830e-05 -4.110029e-04 -2.045514e-04 #> sierranevada -6.684311e-04 -3.811855e-04 -4.383820e-04 -5.675429e-04 #> tanglefoot -9.195349e-05 -2.817236e-04 4.991349e-04 -3.507131e-04 #> tauro -7.745611e-04 1.012546e-04 -3.658760e-04 -1.334307e-04 #> westmalle -8.336006e-04 -5.476468e-05 -1.129115e-03 4.607603e-04 #> amrut 3.325703e-04 8.672648e-04 9.145089e-05 7.931481e-04 #> ballantines 6.627349e-04 -3.615268e-04 3.731327e-04 -2.763657e-04 #> bushmills 4.431144e-04 9.888128e-04 1.365332e-06 -1.032528e-04 #> chivas 1.495921e-03 -7.915520e-04 2.552716e-04 -1.400881e-03 #> dalmore 8.620998e-04 5.358565e-04 -2.205899e-04 8.854910e-04 #> famousgrouse 9.740031e-04 7.164023e-04 -5.641393e-04 -5.141442e-04 #> glendronach 6.069209e-04 1.250594e-03 3.418042e-04 8.590618e-04 #> glenmorangie -7.256586e-04 5.892879e-04 -1.846707e-04 -2.215014e-04 #> highlandpark 7.715184e-04 -1.223845e-04 8.942889e-04 -9.207978e-04 #> jackdaniels -7.403164e-05 5.163499e-04 2.071492e-05 2.953354e-04 #> jb 1.765633e-04 1.058650e-03 4.504999e-04 2.865430e-04 #> johnniewalker -8.526645e-05 8.983395e-04 -1.003037e-03 3.799430e-05 #> magallan 7.106320e-04 5.758546e-04 -6.188574e-04 2.465923e-04 #> makersmark -9.846482e-04 -2.252128e-04 -7.251905e-04 5.910814e-04 #> oban -1.589051e-04 1.386830e-03 1.430748e-04 6.763321e-04 #> oldpotrero 5.368851e-04 -3.892557e-04 8.146966e-04 -5.819797e-04 #> redbreast 1.204642e-03 -3.265974e-04 4.350358e-04 -4.717577e-04 #> tamdhu -1.558475e-03 -2.944087e-05 -3.153143e-04 9.049911e-05 #> wildturkey -2.598572e-05 8.017668e-04 7.628013e-04 -5.490242e-04 #> yoichi -5.700515e-05 5.679827e-04 1.700043e-04 -7.948749e-04 #> D26 D27 D28 D29 #> brahma -6.395018e-04 -4.053179e-04 -2.320532e-04 -3.997015e-04 #> caney -2.359438e-04 -2.059137e-04 -5.363116e-05 -5.687334e-04 #> chimay -1.367853e-03 -1.301151e-03 -1.233134e-03 -5.067907e-04 #> corona -5.900023e-04 4.867919e-04 -1.429390e-04 4.416367e-04 #> deusventrue -5.512986e-04 -9.265221e-04 -4.809160e-04 -5.674634e-04 #> duvel -6.434708e-04 -3.994538e-04 -2.003070e-04 -2.293221e-04 #> franziskaner -1.310487e-04 2.683871e-04 8.363468e-06 1.249318e-04 #> grimbergen -1.063777e-03 -1.567251e-03 -9.309061e-04 -1.203667e-03 #> guiness -4.237703e-04 -5.863080e-04 2.091300e-04 -1.398699e-04 #> hoegardeen -4.936265e-04 -3.031387e-04 -5.517384e-04 -6.863028e-04 #> jupiler -4.169136e-04 -2.806707e-04 -4.552180e-04 -5.632157e-04 #> kingfisher -5.282998e-04 -1.829135e-04 -5.253247e-04 -3.984768e-04 #> latrappe -2.182854e-05 6.079916e-04 -3.061676e-04 5.585698e-04 #> lindemanskriek -1.286669e-04 -3.587153e-04 -9.683567e-05 -3.789208e-04 #> nicechouffe -3.874500e-05 -6.006549e-04 1.047084e-04 4.153977e-05 #> pecheresse -4.871025e-04 -5.084450e-04 -6.217106e-04 -9.046258e-04 #> sierranevada -5.253493e-04 -9.103329e-04 -1.472245e-04 -6.919569e-04 #> tanglefoot -2.793185e-04 -9.121267e-04 -5.073682e-04 -7.915067e-04 #> tauro -3.810949e-04 -1.473809e-04 -5.954522e-04 -6.992086e-04 #> westmalle -3.036718e-05 4.895830e-05 -5.574292e-04 -1.059941e-03 #> amrut -6.925384e-05 -6.528198e-06 -7.195273e-04 -4.489611e-04 #> ballantines 5.806837e-04 -4.643040e-05 -1.345115e-04 -4.098110e-04 #> bushmills -9.920516e-04 -6.515162e-04 -9.939962e-04 -7.524942e-04 #> chivas -5.786515e-04 -5.643790e-04 -9.594352e-04 1.266319e-04 #> dalmore -2.071692e-04 9.919664e-05 -6.494984e-04 -8.782649e-04 #> famousgrouse -9.831707e-04 -2.574344e-04 3.023649e-04 1.759037e-04 #> glendronach -3.720452e-04 -6.702764e-04 -1.204797e-03 -6.332506e-04 #> glenmorangie 1.026999e-04 -4.035989e-04 8.014678e-04 -2.994170e-07 #> highlandpark -9.684691e-04 -1.380908e-03 -1.108075e-03 -2.124353e-04 #> jackdaniels -9.776790e-04 -7.222094e-04 -5.648930e-04 -6.747195e-04 #> jb -3.242447e-04 -6.974717e-04 -1.963078e-04 -2.453221e-05 #> johnniewalker -6.179291e-04 -4.241837e-04 -5.206066e-04 -8.604953e-04 #> magallan -1.348410e-04 3.236837e-04 3.675421e-04 4.734675e-04 #> makersmark -1.584742e-04 -7.659618e-04 -1.350651e-03 -1.228912e-03 #> oban -6.637215e-04 5.201189e-05 -4.165461e-04 8.882533e-05 #> oldpotrero -2.942613e-04 -5.427166e-04 -9.393213e-04 -4.784414e-04 #> redbreast 3.593234e-04 -1.693602e-04 -3.678528e-05 6.092724e-05 #> tamdhu 1.211206e-05 -7.018532e-04 1.418592e-05 -7.508705e-04 #> wildturkey 8.160391e-04 -5.939476e-04 2.147085e-04 -2.764873e-04 #> yoichi -4.611316e-04 -1.449003e-03 -3.131254e-04 -7.590933e-04 #> D30 D31 D32 #> brahma -3.902515e-04 -4.657627e-04 -4.591314e-04 #> caney -9.850469e-05 3.166971e-05 1.112523e-04 #> chimay -8.560520e-04 -4.323199e-04 9.946603e-05 #> corona 2.091023e-04 -7.157752e-05 -1.300100e-04 #> deusventrue 1.040810e-04 -8.204937e-04 -5.065759e-04 #> duvel -3.433012e-05 3.583444e-04 3.946036e-04 #> franziskaner -9.090693e-05 -3.654028e-04 -3.017993e-04 #> grimbergen -9.676903e-04 -7.092697e-04 -3.309973e-04 #> guiness -3.334034e-04 -4.702548e-05 1.426591e-04 #> hoegardeen -7.249966e-04 -8.858153e-04 -4.275584e-04 #> jupiler -5.485198e-04 -6.030643e-04 -3.822469e-04 #> kingfisher -4.201484e-04 -5.266630e-04 -1.660344e-04 #> latrappe -1.877748e-04 3.063740e-04 1.703602e-04 #> lindemanskriek -3.260925e-04 -2.780105e-04 -1.944023e-04 #> nicechouffe 3.820829e-04 -4.094818e-05 -2.591452e-05 #> pecheresse -5.103713e-04 -5.697029e-04 -3.993520e-04 #> sierranevada -2.174311e-04 -6.020258e-04 -5.489893e-04 #> tanglefoot -1.002316e-03 -1.046716e-03 -1.052470e-03 #> tauro -6.452311e-04 -5.544896e-04 -3.477609e-04 #> westmalle -4.824287e-04 -9.388615e-04 2.676913e-04 #> amrut -4.766425e-04 -6.277056e-04 -5.517415e-04 #> ballantines -4.625130e-04 -2.404349e-04 -7.489670e-04 #> bushmills -4.214640e-04 -1.678949e-04 1.042195e-04 #> chivas -9.372331e-04 -9.431970e-05 -5.353796e-04 #> dalmore -7.460785e-04 -1.279118e-03 -9.370873e-04 #> famousgrouse 1.304132e-04 -4.899982e-05 5.462999e-04 #> glendronach -3.515166e-04 -2.249163e-04 -1.682467e-04 #> glenmorangie 1.997467e-04 6.023239e-05 -2.466944e-04 #> highlandpark -3.607922e-04 2.362905e-04 -2.757210e-04 #> jackdaniels -2.447913e-04 -1.353065e-03 -5.253405e-04 #> jb -1.147366e-04 -3.104326e-04 -2.916444e-04 #> johnniewalker -6.281539e-04 -1.083614e-03 -2.760545e-04 #> magallan -3.536734e-04 -1.159514e-04 -4.591237e-04 #> makersmark 7.536380e-04 -2.134843e-04 1.025659e-04 #> oban 2.608163e-04 -3.330292e-04 -4.077367e-04 #> oldpotrero -5.492801e-04 -3.007036e-04 -1.206675e-03 #> redbreast -1.042452e-03 -4.929570e-04 -1.024011e-03 #> tamdhu -5.359179e-04 -4.648454e-04 1.256245e-04 #> wildturkey -4.068468e-04 -2.847724e-04 -5.372963e-04 #> yoichi -1.141095e-04 -2.989495e-04 -6.093731e-04 # if you want, say the first 8 harmonics but not the first one retain <- coeff_sel(retain=8, drop=1, nb.h=32, cph=4) head(coe[, retain]) #> A2 A3 A4 A5 A6 #> brahma 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> A7 A8 B2 B3 B4 #> brahma 0.003183571 0.005158502 -0.0001900652 3.306231e-04 -0.0005191749 #> caney 0.003552709 0.007010166 0.0005012013 -3.851293e-04 0.0003333918 #> chimay -0.004741288 0.007814037 0.0001843629 4.196107e-04 0.0003227901 #> corona 0.005504589 0.007852411 -0.0003586724 1.711055e-05 -0.0005501057 #> deusventrue 0.002521451 0.011391904 0.0001774985 -8.326845e-05 -0.0014033732 #> duvel -0.001687129 0.011025502 -0.0004198782 7.447638e-05 -0.0006627095 #> B5 B6 B7 B8 #> brahma 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> caney -2.899903e-04 7.350207e-05 -4.952054e-04 8.536695e-05 #> chimay -2.906714e-05 5.573360e-04 1.059517e-04 6.209192e-04 #> corona -1.907425e-04 -4.256287e-04 -2.147013e-04 -1.931107e-04 #> deusventrue -3.240180e-04 -9.330047e-04 6.515692e-04 -8.354423e-04 #> duvel 6.107940e-05 -4.746985e-04 2.450959e-04 -1.676532e-04 #> C2 C3 C4 C5 #> brahma -0.0016375711 -3.936895e-03 0.0054080962 -1.259407e-03 #> caney 0.0012398277 -2.845651e-04 0.0003757825 -4.017802e-05 #> chimay -0.0037576080 -1.797357e-03 -0.0021279238 -4.663387e-04 #> corona -0.0016528639 1.573302e-03 0.0004897281 1.867708e-04 #> deusventrue 0.0015527752 7.706329e-04 -0.0014164476 1.463377e-03 #> duvel 0.0002872128 -5.422392e-06 -0.0007785717 3.178998e-04 #> C6 C7 C8 D2 D3 #> brahma -3.994402e-03 3.268582e-03 0.0004792269 -0.04602927 0.05240292 #> caney 4.699805e-04 2.518166e-04 0.0006300072 -0.07069129 0.05062805 #> chimay -7.424827e-05 -8.096453e-05 0.0009946667 -0.09356117 0.04692603 #> corona 6.888736e-04 3.145355e-04 0.0005189042 -0.05755121 0.05150878 #> deusventrue 9.055123e-04 -2.834923e-04 -0.0014439096 -0.11964363 0.05529900 #> duvel 2.219253e-04 5.438377e-04 -0.0000035189 -0.09170033 0.05080071 #> D4 D5 D6 D7 D8 #> brahma -0.03576859 0.03999516 0.011569168 0.015445729 0.0013278090 #> caney -0.01140063 0.04383297 0.004485691 0.009597789 0.0016029758 #> chimay -0.01924944 0.03965332 0.017317438 0.010444458 0.0104067305 #> corona -0.01125295 0.03689351 -0.004664986 0.009465002 0.0001838085 #> deusventrue 0.00713506 0.03861865 -0.000877051 0.013569192 0.0076757796 #> duvel -0.02401831 0.03036868 0.014867959 0.007642213 0.0154756340"},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"coeff_split returns named list coordinates vector harmonic coefficients. instance, harmonic coefficients arranged $coe slot Coe-objects way: \\(A_1, \\dots, A_n, B_1, \\dots, B_n, C_1, \\dots, C_n, D_1, \\dots, D-n\\) elliptical Fourier analysis (see efourier efourier) \\(C_n D_n\\) harmonic absent radii variation tangent angle approaches (see rfourier tfourier respectively). function used internally might interest elwewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"","code":"coeff_split(cs, nb.h = 8, cph = 4)"},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"cs vector harmonic coefficients. nb.h numeric. maximum harmonic rank. cph numeric. Must set 2 rfourier tfourier used.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"Returns named list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"","code":"coeff_split(1:128, nb.h=32, cph=4) # efourier #> $an #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 #> [26] 26 27 28 29 30 31 32 #> #> $bn #> [1] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 #> [26] 58 59 60 61 62 63 64 #> #> $cn #> [1] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 #> [26] 90 91 92 93 94 95 96 #> #> $dn #> [1] 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 #> [20] 116 117 118 119 120 121 122 123 124 125 126 127 128 #> coeff_split(1:64, nb.h=32, cph=2) # t/r fourier #> $an #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 #> [26] 26 27 28 29 30 31 32 #> #> $bn #> [1] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 #> [26] 58 59 60 61 62 63 64 #>"},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":null,"dir":"Reference","previous_headings":"","what":"Some color palettes — color_palettes","title":"Some color palettes — color_palettes","text":"Colors, colors, colors.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Some color palettes — color_palettes","text":"","code":"col_summer(n) col_summer2(n) col_spring(n) col_autumn(n) col_black(n) col_solarized(n) col_gallus(n) col_qual(n) col_heat(n) col_hot(n) col_cold(n) col_sari(n) col_india(n) col_bw(n) col_grey(n)"},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Some color palettes — color_palettes","text":"n number colors generate color palette","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Some color palettes — color_palettes","text":"colors (hexadecimal format)","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Some color palettes — color_palettes","text":"Among available color palettes, col_solarized based Solarized: https://ethanschoonover.com/solarized/; col_div, col_qual, col_heat, col_cold col_gallus based ColorBrewer2: https://colorbrewer2.org/.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Some color palettes — color_palettes","text":"","code":"wheel <- function(palette, n=10){ op <- par(mar=rep(0, 4)) ; on.exit(par(op)) pie(rep(1, n), col=palette(n), labels=NA, clockwise=TRUE)} # Qualitative wheel(col_qual) wheel(col_solarized) wheel(col_summer) wheel(col_summer2) wheel(col_spring) wheel(col_autumn) # Divergent wheel(col_gallus) wheel(col_india) # Sequential wheel(col_heat) wheel(col_hot) wheel(col_cold) wheel(col_sari) wheel(col_bw) wheel(col_grey) # Black only for pubs wheel(col_black)"},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":null,"dir":"Reference","previous_headings":"","what":"Transparency helpers and palettes — col_transp","title":"Transparency helpers and palettes — col_transp","text":"ease transparency handling.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transparency helpers and palettes — col_transp","text":"","code":"col_transp(n, col = \"#000000\", ceiling = 1) col_alpha(cols, transp = 0)"},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transparency helpers and palettes — col_transp","text":"n number colors generate col color hexadecimal format generate levels transparency ceiling maximal opacity (0 1) cols colors, provided hexadecimal values transp numeric 0 1, value transparency obtain","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transparency helpers and palettes — col_transp","text":"colors","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transparency helpers and palettes — col_transp","text":"","code":"x <- col_transp(10, col='#000000') x #> [1] \"#000000f0\" \"#0000001c\" \"#00000038\" \"#00000055\" \"#00000071\" \"#0000008d\" #> [7] \"#000000aa\" \"#000000c6\" \"#000000e2\" \"#000000ff\" barplot(1:10, col=x, main='a transparent black is grey') summer10 <- col_summer(10) summer10 #> [1] \"#4876FF\" \"#7094C6\" \"#99B28D\" \"#C2D155\" \"#EAEF1C\" \"#FFE805\" \"#FFBA0F\" #> [8] \"#FF8C1A\" \"#FF5E25\" \"#FF3030\" summer10.transp8 <- col_alpha(summer10, 0.8) summer10.transp8 #> [1] \"#4876FF32\" \"#7094C632\" \"#99B28D32\" \"#C2D15532\" \"#EAEF1C32\" \"#FFE80532\" #> [7] \"#FFBA0F32\" \"#FF8C1A32\" \"#FF5E2532\" \"#FF303032\" summer10.transp2 <- col_alpha(summer10, 0.8) summer10.transp2 #> [1] \"#4876FF32\" \"#7094C632\" \"#99B28D32\" \"#C2D15532\" \"#EAEF1C32\" \"#FFE80532\" #> [7] \"#FFBA0F32\" \"#FF8C1A32\" \"#FF5E2532\" \"#FF303032\" x <- 1:10 barplot(x, col=summer10.transp8) barplot(x/2, col=summer10.transp2, add=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine several objects — combine","title":"Combine several objects — combine","text":"Combine Coo objects slicing, either manual using slice chop. Note Coo object, combines row-wise (ie, merges shapes c ) ; Coe combines column-wise (merges coefficients). latter case, Coe must number shapes (necessarily number coefficients). Also $fac first Coe retrieved. separate version may come point.","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine several objects — combine","text":"","code":"combine(...)"},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine several objects — combine","text":"... list (Coe), Opn(Coe), Ldk objects (class)","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine several objects — combine","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Combine several objects — combine","text":"Note order shapes coefficients checked, anything number rows merged.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine several objects — combine","text":"","code":"w <- filter(bot, type==\"whisky\") b <- filter(bot, type==\"beer\") combine(w, b) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk # or, if you have many levels bot_s <- chop(bot, ~type) bot_s$whisky #> Out (outlines) #> - 20 outlines, 158 +/- 23 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows #> - also: $ldk # note that you can apply something (single function or a more # complex pipe) then combine everyone, since combine also works on lists # eg: # bot_s2 <- efourier(bot_s, 10) # equivalent to lapply(bot_s, efourier, 10) # bot_sf <- combine(bot_s2) # pipe style efourier(bot_s, 10) %>% combine() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> An OutCoe object [ combined: efourier + efourier analyses ] #> -------------------- #> - $coe: 20 outlines described, and (total) 80 coefficients #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows"},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert complex to/from cartesian coordinates — complex","title":"Convert complex to/from cartesian coordinates — complex","text":"Convert complex /cartesian coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert complex to/from cartesian coordinates — complex","text":"","code":"cpx2coo(Z) coo2cpx(coo)"},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert complex to/from cartesian coordinates — complex","text":"Z coordinates expressed complex form coo coordinates expressed cartesian form","code":""},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert complex to/from cartesian coordinates — complex","text":"coordinates expressed cartesian/complex form","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert complex to/from cartesian coordinates — complex","text":"","code":"shapes[4] %>% # from cartesian coo_sample(24) %>% coo2cpx() %T>% # to complex cpx2coo() # and back #> [1] 200+ 62i 205+ 43i 176+ 43i 146+ 44i 156+ 23i 186+ 20i 202+ 15i 172+ 9i #> [9] 143+ 16i 130+ 45i 135+ 74i 133+104i 142+134i 165+160i 191+182i 203+210i #> [17] 225+226i 239+204i 238+178i 237+150i 227+120i 221+ 91i 224+ 62i 219+ 45i"},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns coordinates — coo_align","title":"Aligns coordinates — coo_align","text":"Aligns coordinates along longer axis using var-cov matrix eigen values.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns coordinates — coo_align","text":"","code":"coo_align(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns coordinates — coo_align","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns coordinates — coo_align","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns coordinates — coo_align","text":"","code":"coo_plot(bot[1]) coo_plot(coo_align(bot[1])) # on a Coo b <- bot %>% slice(1:5) # for speed sake stack(coo_align(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes along their 'calliper length' — coo_aligncalliper","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"returns registered bookstein coordinates. See coo_bookstein.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"","code":"coo_aligncalliper(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(coo_aligncalliper(b)) b <- bot %>% slice(1:5) # for speed sake bot.al <- coo_aligncalliper(b) stack(bot.al)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes using their shortest radius — coo_alignminradius","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"returns slided first coordinate east. May used aligning strategy shapes clear 'invaginate' part.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"","code":"coo_alignminradius(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"","code":"b <- bot %>% slice(1:5) # for speed sake stack(coo_alignminradius(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes along the x-axis — coo_alignxax","title":"Aligns shapes along the x-axis — coo_alignxax","text":"Align longest axis shape along x-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes along the x-axis — coo_alignxax","text":"","code":"coo_alignxax(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes along the x-axis — coo_alignxax","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes along the x-axis — coo_alignxax","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Aligns shapes along the x-axis — coo_alignxax","text":"shapes upside-(mirror others), try redefining new starting point (eg coo_slidedirection) alignment step. may solve problem coo_calliper orders $arr.ind used coo_aligncalliper.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes along the x-axis — coo_alignxax","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(coo_alignxax(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the angle of every edge of a shape — coo_angle_edges","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"Returns angle (radians) every edge shape,","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"","code":"coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1]) # S3 method for default coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1]) # S3 method for Coo coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1])"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"coo matrix list (x; y) coordinates Coo method 'atan2' ('acos') signed () angle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"numeric angles radians every edge.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"coo_thetapts deprecated removed future releases.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"","code":"b <- coo_sample(bot[1], 64) coo_angle_edges(b) #> [1] -3.111523 -3.093172 -3.092305 3.081724 3.105229 3.077881 3.110353 #> [8] 3.046641 3.051196 3.135756 -3.074763 -3.017238 -2.926235 -2.628633 #> [15] -2.611156 -2.953906 -3.017238 -3.085049 -2.915581 -2.709056 -2.530867 #> [22] -2.927854 -3.086548 -3.100971 3.114884 -3.060821 3.116579 -3.106746 #> [29] 3.131759 3.116579 3.080363 3.030147 3.035444 3.141593 -3.051196 #> [36] -3.014394 -2.988492 -2.873097 -3.131789 2.993915 2.944112 -3.135728 #> [43] 3.113711 3.137875 -3.106026 3.106746 2.980423 -1.981456 -2.694480 #> [50] -3.062770 -2.583631 -2.029263 3.018319 3.023726 -3.109950 3.085522 #> [57] -3.087530 3.112543 2.978918 3.011861 3.087633 -2.957901 -2.916681 #> [64] -3.046946"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"Calculated using complex numbers returned radians minus first one (modulo 2*pi).","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"","code":"coo_angle_tangent(coo) # S3 method for default coo_angle_tangent(coo) # S3 method for Coo coo_angle_tangent(coo) coo_tangle(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"coo matrix coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"numeric, tangent angle along perimeter, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"","code":"b <- bot[1] phi <- coo_angle_tangent(b) phi2 <- coo_angle_tangent(coo_smooth(b, 2)) plot(phi, type='l') plot(phi2, type='l', col='red') # ta is very sensible to noise # on Coo bot %>% coo_angle_tangent #> $brahma #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $caney #> [1] 0.00000000 0.06226874 0.07482722 6.17098557 0.04973765 6.19585440 #> [7] 6.15845448 6.12105457 6.08365466 5.94658609 6.00885483 6.02141332 #> [13] 5.93405501 5.89665510 5.81167208 5.92152392 5.68478671 5.74705545 #> [19] 5.75961393 5.67225562 5.43746015 5.54749740 5.56005588 5.61331586 #> [25] 5.53521445 5.54752480 5.41045623 5.27338767 5.43532506 5.29825650 #> [31] 5.16118793 5.22345667 5.36591026 5.24832550 5.43300749 5.27125258 #> [37] 5.70474653 5.98185092 6.06880600 6.09653125 6.19140174 6.22285831 #> [43] 0.00000000 6.24578539 0.02486883 6.27065422 0.05494594 0.01233774 #> [49] 0.07266474 0.03526482 0.18097573 0.05452623 0.23276803 0.36301056 #> [55] 0.63366343 0.80375974 1.24653486 0.91207073 0.88384487 1.03466647 #> [61] 0.99726655 0.95986664 1.02213538 0.88506682 0.89762530 0.81026699 #> [67] 0.57547152 0.73546717 0.69806725 0.76033599 0.52359878 0.87732431 #> [73] 0.54846760 0.31367213 0.47366778 0.43626787 0.30820807 0.36146804 #> [79] 0.22439948 0.48406378 0.19930991 0.21186839 0.17446848 0.13706857 #> [85] 0.09966865 6.25479416 0.12453748 6.17098557 6.13358566 6.24581279 #> [91] 6.15845448 0.03526482 0.04544802 0.22671705 0.07444053 0.15191722 #> [97] 0.32561064 0.07711740 6.15071198 6.19274656 5.88412401 5.84672410 #> [103] 5.80460724 5.96371242 5.73452436 5.54749740 5.75745144 5.52265597 #> [109] 5.63414601 5.44785615 5.41045623 5.56127783 5.33565641 5.29825650 #> [115] 5.40974653 5.22345667 5.18605676 5.24832550 5.30865249 4.87646146 #> [121] 4.77913339 5.19645276 5.06132594 4.80714863 5.08425302 5.57609989 #> [127] 6.00234758 6.24578539 6.11065857 6.27065422 6.23325431 0.11006465 #> [133] 0.16672597 0.49891243 0.95304135 1.23419711 1.51513480 1.06167038 #> [139] 1.93029230 1.18426612 1.14686620 0.91207073 0.97239773 0.93499781 #> [145] 0.99726655 0.81097669 0.92246673 0.70521332 0.74799825 0.71059834 #> [151] 0.77286708 0.58657722 0.69806725 0.46327178 0.62326743 0.43697757 #> [157] 0.54846760 0.29239874 0.42370938 0.23887231 0.10741116 6.22179942 #> [163] 5.93251249 5.95912756 6.10959968 6.06842620 6.16619699 6.22285831 #> #> $chimay #> [1] 0.000000000 6.183372777 6.150128410 6.241239038 6.083639677 6.050395310 #> [7] 6.141505938 5.859551582 5.950662210 5.917417843 5.884173476 5.709032055 #> [13] 5.942039737 5.908795371 5.893093064 5.717951643 5.684707276 5.775817904 #> [19] 5.760115597 5.584974176 5.427374815 5.376588388 5.485241076 5.730296368 #> [25] 5.418752342 5.509862970 5.352263609 5.319019242 5.285774876 5.376885504 #> [31] 5.219286142 5.186041776 5.152797409 5.261450097 5.331287339 5.177419303 #> [37] 5.378590612 5.606825061 6.119235749 6.027235560 6.098868132 0.016854134 #> [43] 6.249253014 6.233550707 0.041476028 0.008231661 6.116275547 6.224928235 #> [49] 5.913384209 0.153553853 5.880216472 6.091950768 0.020499758 6.025462035 #> [55] 6.116572663 6.100870356 6.050083929 6.016839563 6.001137256 6.070974498 #> [61] 6.037730131 6.081257656 5.971241398 6.051789038 6.123421610 0.394994540 #> [67] 0.695548337 0.847651921 0.814407554 0.781163187 0.747918820 0.714674454 #> [73] 0.681430087 0.648185720 0.614941354 0.706051982 0.548452620 0.515208254 #> [79] 0.357608892 0.448719520 0.415475153 0.506585781 0.348986420 0.315742053 #> [85] 0.282497687 0.249253320 0.216008953 0.182764587 0.149520220 0.116275853 #> [91] 0.083031486 0.294765783 0.016542753 6.266483693 6.233239327 0.049361185 #> [97] 6.166750593 6.133506227 6.100261860 6.067017493 6.033773127 6.000528760 #> [103] 5.967284393 6.058395021 6.025150654 6.145850952 0.109720934 6.264710169 #> [109] 0.003779000 6.253719940 6.137956619 0.005149272 5.993611396 6.160195675 #> [115] 5.973243779 5.939999412 5.860633930 5.873510679 5.794145196 5.760900829 #> [121] 5.493240787 5.854787540 5.547375722 5.514131355 5.578932266 5.327018953 #> [127] 5.311316647 5.494945896 5.227285853 5.069686492 5.178339180 5.003197759 #> [133] 4.261327120 4.936709025 5.027819653 5.115198955 5.115275584 4.661834504 #> [139] 3.874431807 5.058993379 5.580056509 5.882779748 6.208306052 6.175061685 #> [145] 6.141817318 6.108572952 6.075328585 6.042084218 6.008839851 6.253895144 #> [151] 6.066706113 0.089569053 0.885173745 1.201536502 1.740485780 0.818761641 #> [157] 0.785517274 0.872896576 0.964007204 1.625501114 0.897518471 0.864274104 #> [163] 0.706674743 0.673430376 0.622643949 0.486317974 0.573697276 0.306037233 #> [169] 0.434167977 0.320019511 0.286775145 0.286851774 0.139815400 0.060449917 #> [175] 0.307742342 6.218390668 0.120629940 6.210657758 6.063159063 0.020896840 #> [181] 5.996670329 6.123801407 6.068821333 5.952435735 6.024068307 5.790995295 #> [187] 5.911458457 6.038127214 6.125506516 #> #> $corona #> [1] 0.000000000 0.093190192 6.280085533 0.095445119 6.230254910 6.181548048 #> [7] 6.132841185 6.084134322 6.035427459 5.986720596 5.938013733 5.889306870 #> [13] 5.840600008 5.791893145 5.743186282 5.694479419 5.645772556 5.597065693 #> [19] 5.548358831 5.821402522 5.450945105 5.402238242 5.353531379 5.304824516 #> [25] 5.256117653 5.404806350 5.158703928 5.200656952 5.524937811 6.100866371 #> [31] 0.054091936 6.164215386 0.253742423 0.105366907 0.056660045 0.007953182 #> [37] 0.139099819 0.015416395 0.041686093 0.255499953 0.626588922 1.286508331 #> [43] 1.049579963 1.189094606 1.140387743 1.041722484 1.042974017 0.994267154 #> [49] 0.945560292 0.896853429 0.848146566 0.799439703 0.750732840 0.702025977 #> [55] 0.653319114 0.604612252 0.555905389 0.507198526 0.458491663 0.409784800 #> [61] 0.361077937 0.312371075 0.263664212 0.214957349 0.166250486 0.026883736 #> [67] 0.121419822 0.020129897 6.254608342 0.064613226 0.195759863 0.022698006 #> [73] 0.317015084 0.191536329 6.196110346 5.913660302 5.864953439 5.816246576 #> [79] 5.767539713 5.718832851 5.769794640 5.621419125 5.721602210 5.524005399 #> [85] 5.672694096 5.568488728 5.575280370 5.238518061 5.429361033 5.498016271 #> [91] 5.380452919 5.229302203 5.085643634 4.848715265 5.279686702 5.030182932 #> [97] 5.431235682 0.129720339 0.081013476 0.032306613 6.266785058 0.271567707 #> [103] 1.748439146 1.210879929 1.162173066 1.729086092 1.262154900 1.163489642 #> [109] 0.701093565 1.116034312 0.801075400 1.018620586 0.870245071 0.599456306 #> [115] 0.772831345 0.728841428 0.556417326 0.626710756 0.677672546 0.628965683 #> [121] 0.580258820 0.531551957 0.285449535 0.434138232 0.004924992 6.239403436 #> [127] 6.064104446 6.173725084 6.120798837 #> #> $deusventrue #> [1] 0.00000000 6.22214668 6.18080993 6.23594696 6.17968595 6.11625336 #> [7] 6.21501833 6.19495497 6.13234484 6.16078710 6.07094474 6.22700355 #> [13] 6.18566681 6.14433006 6.10299332 6.06165657 6.02031983 6.08964030 #> [19] 6.13504189 5.89630959 5.90755591 5.81363610 5.88295657 5.83063126 #> [25] 5.78929451 5.70087218 5.70662102 5.66528428 5.52427888 5.68033769 #> [31] 5.63900095 0.01313872 0.29355253 0.22469980 0.46420077 0.41187546 #> [37] 0.48119594 0.38727613 0.28786522 0.25751705 0.31584895 0.27451221 #> [43] 0.23317546 0.19183872 0.25017063 0.20883388 0.06782848 0.36316656 #> [49] 0.64619816 1.05096696 1.21595411 1.33227243 1.28572740 1.24959894 #> [55] 1.20826219 1.10999222 1.22525735 0.96525166 1.09000080 1.10124712 #> [61] 0.95503343 1.01857363 0.87756823 0.93590014 0.67589445 0.85322665 #> [67] 0.81188990 0.52557449 0.72921641 0.68787966 0.85403914 0.60520617 #> [73] 0.66353808 0.67913456 0.67859150 0.71080604 0.68997924 0.73769208 #> [79] 0.68674024 0.69273654 0.73601867 0.51358927 0.65760048 0.44584005 #> [85] 0.53147609 0.37948212 0.27661179 0.26556880 0.15980522 0.15260155 #> [91] 0.07713172 6.16132522 6.13097705 6.14413176 6.03731499 6.05291147 #> [97] 6.07364179 5.81363610 5.66164213 5.73096261 5.68962586 5.64828912 #> [103] 5.60695237 5.56561563 5.62394753 5.37228491 5.29271544 5.40026864 #> [109] 5.41151496 5.31759515 5.49492735 5.07831979 5.48504171 5.97466645 #> [115] 0.10706565 6.25986463 0.31584895 0.47190777 0.61368184 0.91066872 #> [121] 1.52390274 1.77963021 1.27985414 1.33996435 1.93645770 1.22315778 #> [127] 1.64795003 1.62933664 1.49548128 1.34926759 1.30793085 1.26659410 #> [133] 1.22525735 0.96525166 1.52309024 0.90385156 0.95503343 0.79990468 #> [139] 0.87756823 0.78701019 0.64958473 0.65583109 0.61449434 0.30690555 #> [145] 0.52172018 0.39642287 0.32479236 0.31374938 0.27241263 0.15164139 #> [151] 0.15944538 0.16891234 #> #> $duvel #> [1] 0.00000000 0.05163389 0.01260790 1.54437823 6.21774121 5.98131966 #> [7] 6.13968922 6.10066322 6.06163723 1.31022225 5.98358524 5.94455924 #> [13] 5.90553325 5.86650725 5.82748125 1.07606628 5.74942926 5.71040327 #> [19] 5.67137727 5.63235128 5.59332528 0.84191030 5.51527329 5.47624729 #> [25] 5.43722130 5.39819530 0.64678033 5.22948342 5.28111731 5.24209132 #> [31] 5.46931737 5.59066682 0.41262435 5.87138550 6.23725129 0.20488648 #> [37] 0.16586048 0.12683449 0.17846838 0.04878249 6.20374819 0.06139039 #> [43] 6.21488981 6.26652371 6.22749771 6.18847171 6.14944572 6.11041972 #> [49] 6.16205361 6.03236773 5.99334174 6.13416924 6.00594963 6.07365931 #> [55] 5.83723775 5.79821176 6.10795677 0.37897450 0.54211730 0.74986529 #> [61] 0.80003291 5.56405578 0.81264081 0.77361481 0.73458882 0.69556282 #> [67] 0.65653682 5.32989981 0.57848483 0.53945884 0.50043284 0.46140685 #> [73] 5.13476983 0.38335485 0.34432886 0.30530286 0.26627687 0.22725087 #> [79] 4.90061386 0.14919888 0.11017289 0.07114689 0.03212089 6.27628021 #> [85] 4.66645788 6.19822821 6.15920222 6.21083611 6.08115023 6.13278412 #> [91] 4.43230191 6.06374089 6.19129829 6.23479125 0.06315567 4.23717193 #> [97] 0.11455324 6.15654376 6.03966127 5.83171777 5.71250693 4.00301596 #> [103] 5.62544617 5.76201234 5.88336179 5.84433579 6.00747859 3.76885998 #> [109] 5.91135628 5.76095104 5.60308470 5.36340583 5.14452633 3.53470401 #> [115] 4.71770333 4.93678846 5.25467440 4.85873646 3.33957403 4.69149086 #> [121] 5.12377516 5.46803331 5.75833348 6.01978465 3.10541805 6.11732483 #> [127] 6.16895872 6.22059261 0.23434891 0.35669803 2.87126208 0.79779215 #> [133] 0.95616171 1.44963982 0.96450827 0.92548228 2.63710611 1.20713728 #> [139] 1.33702879 0.84956314 0.64395375 2.44197613 0.56590176 0.18240185 #> [145] 0.01628675 0.21572910 0.32727882 2.20782015 0.21749145 0.26751504 #> [151] 0.42928595 0.30106634 0.35123396 1.97366418 0.01507085 6.04127195 #> [157] 5.95824921 6.10332168 6.11041680 1.73950821 6.23301769 #> #> $franziskaner #> [1] 0.00000000 6.23251446 6.18184361 6.13117276 6.08050191 6.02983106 #> [7] 6.17655577 5.92848936 5.87781851 5.82714766 5.77647681 5.72580597 #> [13] 5.67513512 5.62446427 5.57379342 5.52312257 5.47245172 5.42178087 #> [19] 5.37111002 5.32043917 5.26976832 5.21909747 5.06354968 5.11775577 #> [25] 5.11704332 5.11608273 5.28749378 5.75305360 6.07121890 6.09307021 #> [31] 6.23890445 5.92441464 6.13756275 6.18184361 0.06665640 6.12808501 #> [37] 6.22722662 6.21290339 0.02581043 0.43878719 0.84850663 0.96441918 #> [43] 0.92275710 1.06241479 0.91207529 0.86140444 0.81073359 0.76006274 #> [49] 0.70939189 0.65872104 0.60805019 0.55737934 0.50670849 0.45603764 #> [55] 0.40536679 0.35469594 0.30402510 0.25335425 0.20268340 0.15201255 #> [61] 0.10134170 0.05067085 0.00000000 6.23251446 6.18184361 6.13117276 #> [67] 6.08050191 6.02983106 5.97916021 5.97844776 6.14407056 5.97603761 #> [73] 6.04272886 5.98312968 5.94138717 5.88178798 5.84004547 5.81457936 #> [79] 5.76390851 5.74353142 5.60485320 5.61189597 5.50351150 5.51055427 #> [85] 5.31032368 5.21742443 5.20898198 5.01641408 4.91816012 4.59332182 #> [91] 5.01329148 4.81373068 4.81301823 6.23322691 6.05266096 6.18184361 #> [97] 6.22183265 6.18017056 1.21777343 1.41566118 0.86732938 1.47130840 #> [103] 1.11475868 1.06408783 0.66464598 0.81385619 0.91207529 0.60408072 #> [109] 0.72007370 0.42338792 0.43109223 0.46132548 0.24407123 0.23562879 #> [115] 0.21525170 0.13428709 0.12706714 0.15730038 0.07028191 6.24508276 #> [121] 0.15510029 6.23780230 6.24262995 0.05067085 #> #> $grimbergen #> [1] 0.000000000 6.130874904 6.278403913 6.228537363 6.178670813 6.128804263 #> [7] 6.078937713 6.128739816 5.888544726 6.029006716 5.879471513 5.829604963 #> [13] 5.779738413 5.729871863 5.680005313 5.630138763 5.580272213 5.530405663 #> [19] 5.480539112 5.430672562 5.380806012 5.378522566 5.380741565 5.321866249 #> [25] 5.459639471 5.806214204 5.966673528 6.265861669 0.089631132 0.031396576 #> [31] 0.169751531 0.029225094 0.022435328 0.020151881 6.253470638 0.015370487 #> [37] 0.050405731 6.245768043 0.062275925 0.069723584 0.314587140 0.843244804 #> [43] 0.944753698 0.858539527 0.951756270 0.992549607 0.942683057 0.892816507 #> [49] 0.842949957 0.702423520 0.643548205 0.693350307 0.643483757 0.593617207 #> [55] 0.543750657 0.493884107 0.444017557 0.394151007 0.344284457 0.294417907 #> [61] 0.344220009 0.194684806 0.144818256 0.094951706 0.045085156 0.042801710 #> [67] 6.228537363 0.075339006 0.151497827 0.295099128 0.333888459 0.306745270 #> [73] 0.145499478 0.001177992 5.929273615 5.977133973 5.777454966 5.770665200 #> [79] 5.827534323 5.722169267 5.879176666 5.725517776 5.610526062 5.672262807 #> [85] 5.472836517 5.460926412 5.330875015 5.039442758 4.624374758 5.347858761 #> [91] 5.310039821 3.930223399 5.073904116 6.104165835 0.020216329 0.070018431 #> [97] 0.020151881 6.253470638 6.203604088 6.253406191 0.842932605 1.560284404 #> [103] 1.911998394 1.008139177 0.994620248 1.860979257 1.092282707 1.042416157 #> [109] 0.795154048 0.754461552 0.712963007 0.609206776 0.595687847 0.563363357 #> [115] 0.495954747 0.552823870 0.593617207 0.496167554 0.493884107 0.063511180 #> [121] 0.030172050 5.952728822 5.966877249 6.028389942 6.097363737 6.149703905 #> #> $guiness #> [1] 0.000000000 6.248850961 6.214516615 6.180182269 6.145847923 6.111513577 #> [7] 6.077179232 6.167199880 5.884155545 6.098531188 5.939841848 5.905507502 #> [13] 5.871173156 5.836838810 5.802504464 5.768170118 5.733835772 5.699501426 #> [19] 5.665167080 5.630832734 5.596498388 5.562164042 5.527829696 5.610604095 #> [25] 5.459161005 5.424826659 5.390492313 5.356157967 5.321823621 5.009189616 #> [31] 5.253154929 5.218820583 5.184486237 5.150151891 5.334486491 5.205838194 #> [37] 5.479556629 5.798212671 5.961273885 5.894692656 6.235629133 6.124522896 #> [43] 0.004398803 6.253249764 6.232613191 6.184581072 6.274601721 6.240267375 #> [49] 6.205933029 6.171598683 6.199683147 6.102929991 6.179252866 6.034261299 #> [55] 6.244905616 0.041177970 6.162348928 6.141902578 0.222905371 0.454823074 #> [61] 0.522932582 0.688426881 1.012863205 0.978528859 0.944194513 0.909860167 #> [67] 0.875525821 0.965546470 1.051835793 0.772522784 0.738188438 0.703854092 #> [73] 0.669519746 0.635185400 0.600851054 0.566516708 0.532182362 0.497848016 #> [79] 0.463513670 0.429179324 0.176176032 0.360510632 0.326176286 0.291841940 #> [85] 0.257507595 0.223173249 0.188838903 0.154504557 0.120170211 0.085835865 #> [91] 0.051501519 6.175997486 6.266018134 6.231683788 6.197349442 6.163015096 #> [97] 6.128680750 5.816046745 6.060012059 6.270656376 6.115698361 6.201987684 #> [103] 6.261967289 0.163754337 0.129419991 0.197529499 0.287550147 0.088067124 #> [109] 6.107275643 5.927312916 5.772354902 5.891965220 5.689988437 5.669351864 #> [115] 5.635017518 5.593436922 5.686972495 5.549556540 5.497680134 5.449648015 #> [121] 5.429011442 5.455670052 5.454656702 5.201653410 5.291674059 5.274881773 #> [127] 5.209307593 5.342615685 5.256780528 4.995647334 4.175914825 4.648678984 #> [133] 5.016999291 5.076978897 4.752668140 5.377643862 5.705853754 6.046790231 #> [139] 6.257434548 6.223100202 6.188765856 6.271540254 6.120097164 6.210117813 #> [145] 0.326842480 0.945934475 1.394725794 1.236036454 1.142946285 2.043425813 #> [151] 1.133033416 0.390072798 1.206261779 1.030030378 0.878587288 0.961361686 #> [157] 0.802672346 0.647714331 0.747701427 0.824024303 0.544711294 0.631000616 #> [163] 0.476042602 0.562331924 0.527997578 0.373039564 0.583683881 0.364001585 #> [169] 0.404357968 0.235702180 0.201367834 0.053241481 6.153764608 6.006279281 #> [175] 5.917453478 5.969857471 6.004379615 6.025543774 6.049965251 6.201853745 #> [181] 6.125585953 0.193023686 0.144991567 #> #> $hoegardeen #> [1] 0.000000000 6.263129292 0.100037949 0.067482585 0.034927220 0.002371856 #> [7] 6.253001799 6.220446435 6.187891070 6.155335706 6.122780342 6.090224977 #> [13] 6.057669613 6.177763577 5.827410207 5.960003520 5.927448156 5.894892792 #> [19] 5.862337427 5.829782063 5.797226699 5.764671335 5.732115970 5.782701838 #> [25] 5.743777133 5.634449877 5.601894513 5.569339149 5.536783785 5.504228420 #> [31] 5.471673056 5.439117692 5.406562327 0.661617983 5.494100927 5.308896235 #> [37] 5.359482102 5.320557397 5.363879470 5.444926827 5.540910533 5.612910771 #> [43] 6.188157402 0.091085677 0.150859647 6.232388364 0.011599399 0.205842883 #> [49] 0.173287518 0.140732154 6.238712769 0.075621426 0.222919561 0.010510697 #> [55] 0.130604661 0.028541200 0.065493933 6.240246438 0.092712539 0.314525233 #> [61] 0.528042623 0.821517388 1.288308745 1.178981490 1.140056785 1.113870761 #> [67] 1.158087288 1.125531924 1.092976560 1.060421195 1.027865831 0.995310467 #> [73] 0.962755102 0.930199738 0.897644374 0.865089010 0.923193532 0.723206390 #> [79] 0.932571594 0.734867552 0.702312188 0.669756824 0.637201460 0.604646095 #> [85] 0.572090731 0.539535367 0.506980002 0.474424638 0.441869274 0.409313910 #> [91] 0.376758545 0.344203181 0.311647817 0.279092452 0.246537088 0.213981724 #> [97] 0.181426360 4.861259976 0.116315631 0.083760267 0.127976794 0.183798216 #> [103] 0.151242851 0.106188138 0.165962108 0.186927013 0.082671565 0.145067907 #> [109] 0.112512543 0.003185287 0.120442379 0.060269729 6.242224770 6.076319151 #> [115] 6.031264438 6.091038408 5.978653058 6.079447948 5.975192501 5.880986966 #> [121] 5.981781855 5.650727560 5.618172195 5.662388722 5.705710795 5.520506102 #> [127] 5.640600067 5.532167265 5.505981241 5.467056537 5.357729281 5.505027417 #> [133] 5.292618552 5.412712517 5.392656501 5.118180568 4.621977595 5.212982963 #> [139] 5.395785298 5.309709666 4.188021652 5.197015834 5.265563841 5.719907709 #> [145] 6.174251576 0.080237945 0.124454472 0.091899108 0.059343743 0.103560270 #> [151] 0.159381692 0.260176582 0.948263631 1.302214571 1.756558439 1.599648080 #> [157] 1.204548479 1.184492463 1.457235756 1.451884563 1.239475699 2.777716661 #> [163] 1.021715642 1.141809606 1.032482350 0.911550200 1.044143513 0.858938820 #> [169] 0.979032785 0.863336188 0.830780824 0.728717363 0.931952559 0.663606635 #> [175] 0.631051270 0.751145235 0.565940542 0.533385178 0.408500479 0.468274449 #> [181] 0.435719085 0.234062494 0.224758753 0.263903472 0.136396402 0.127092660 #> [187] 0.094537296 6.263159793 0.082946836 6.280056510 0.017836107 6.214945782 #> [193] 0.120932150 #> #> $jupiler #> [1] 0.000000000 0.035494062 0.066524698 0.026247869 6.269156347 6.228879518 #> [7] 6.188602689 6.148325860 6.031277140 6.067772203 6.027495374 5.987218545 #> [13] 5.875634251 5.906664887 5.866388058 5.826111229 5.714526936 5.745557571 #> [19] 5.633973278 5.665003914 5.624727085 5.584450256 5.544173427 5.432589133 #> [25] 5.386847878 5.423342940 5.346045995 5.414096747 5.444409508 5.339007516 #> [31] 5.363855850 5.524705907 5.746949802 5.963298364 6.226756021 0.009686739 #> [37] 0.056815509 0.085734959 0.110583293 0.005181301 0.106801526 0.143296589 #> [43] 0.168144923 0.127868094 0.172493059 0.248441322 0.384286667 0.566810992 #> [49] 0.784045742 1.104013060 1.048030716 1.092655681 1.122968442 1.153999078 #> [55] 1.113722249 1.002137955 1.033168591 0.992891762 0.952614933 0.912338104 #> [61] 0.872061275 0.831784447 0.791507618 0.674458898 0.710953960 0.670677131 #> [67] 0.630400302 0.518816008 0.549846644 0.432797924 0.469292987 0.287119103 #> [73] 0.541388657 0.277155035 0.308185671 0.267908842 0.227632013 0.116047719 #> [79] 0.147078355 0.142500639 0.219174026 0.168144923 0.197064373 0.172493059 #> [85] 0.183717041 0.143440212 0.123362656 0.127610836 0.022609725 0.002532169 #> [91] 6.158035049 6.048561942 6.019037386 6.037204562 5.927731455 5.972356419 #> [97] 5.705280743 5.806900968 5.701498976 5.584450256 5.615480892 5.575204063 #> [103] 5.540391660 5.494650405 5.454373576 5.419561174 5.373819918 5.262235625 #> [109] 5.298730687 4.838658026 5.141405138 5.253777638 5.060851480 4.793775803 #> [115] 5.207096671 5.545565657 6.006892882 6.203464815 0.035494062 0.066524698 #> [121] 0.103019760 0.264270699 0.611663448 1.043805933 1.364629415 1.895006773 #> [127] 1.056884291 1.173209339 1.596580119 1.234552735 1.087540234 1.077227186 #> [133] 1.042414784 1.002137955 0.956396700 0.850994708 0.881307468 0.770441050 #> [139] 0.872061275 0.760476982 0.649610563 0.524431941 0.639646495 0.392377472 #> [145] 0.477750974 0.379030140 0.271546985 0.282770967 0.126269046 0.085992217 #> [151] 0.090240397 0.005438559 6.248347038 0.041109994 6.232517661 6.259447158 #> #> $kingfisher #> [1] 0.00000000 0.07035394 0.03583095 0.00130795 6.24997026 6.21544726 #> [7] 1.46853529 6.14640127 6.11187828 6.27475084 5.94316363 6.13266428 #> [13] 5.97378629 5.93926330 5.90474030 5.87021730 5.83569431 1.08878233 #> [19] 5.76664831 5.73212532 5.69760232 5.66307933 5.62855633 5.59403333 #> [25] 5.55951034 5.52498734 5.49046434 0.74355237 5.42141835 5.38689536 #> [31] 5.35237236 5.31784936 5.28332637 5.46747232 5.21428038 5.29041460 #> [37] 5.34262994 5.43246194 0.36379941 5.42217177 5.79254056 6.00299623 #> [43] 6.04524512 6.22939107 6.14838995 6.20792818 0.08761544 6.11760881 #> [49] 0.01856945 6.26723176 0.16819240 6.19818577 0.09914641 0.06462341 #> [55] 0.10288827 0.19513280 0.12289186 0.54584371 0.78048820 5.92200180 #> [61] 0.95642087 0.92189788 0.90864827 1.07152083 0.92634061 1.00247484 #> [67] 0.96795184 0.93342885 0.70151029 0.86438285 5.54224884 0.99273242 #> [73] 0.76081387 0.72629087 0.69176787 0.65724488 0.62272188 0.58819889 #> [79] 0.55367589 0.62981011 0.48462990 5.16249588 0.41558390 0.38106091 #> [85] 0.34653791 0.31201492 0.27749192 0.24296892 0.20844593 0.17392293 #> [91] 0.13939993 0.10487694 4.78274292 0.03583095 0.00130795 0.16418051 #> [97] 6.21544726 0.09513452 0.06061153 0.02608853 0.15294064 0.05110377 #> [103] 4.43751296 6.17118185 6.23072009 6.12340925 6.25072368 6.03308987 #> [109] 6.01984026 6.08839887 6.02358211 5.80825954 6.12672693 4.05776000 #> [115] 5.79142889 5.85096713 5.72238290 5.73544301 5.55561000 5.61881391 #> [121] 5.60556430 5.45204101 5.53651831 5.48072193 3.67800704 5.43294932 #> [127] 5.37715294 5.14523438 5.11071139 5.29485734 5.23906095 5.00714240 #> [133] 4.55439507 5.22955320 3.33277708 4.57759362 5.12598421 5.72729964 #> [139] 6.23660910 0.01856945 6.26723176 6.23270876 0.01466911 0.46848007 #> [145] 1.30609357 2.95302412 1.56637375 1.21351315 1.37832746 1.35479303 #> [151] 1.10994416 1.07542117 1.14056682 0.88737488 1.07152083 0.81832889 #> [157] 2.57327117 0.77055628 0.93342885 0.79923720 0.66698730 0.61119091 #> [163] 0.59794130 0.66114521 0.52889531 0.27354354 2.22804120 0.52305323 #> [169] 0.36952994 0.13545156 0.40849567 0.28723434 0.06960052 0.41558390 #> [175] 6.24602189 0.14914235 0.11461936 1.84828825 6.20440368 0.01105037 #> [181] 6.16565144 0.13939993 #> #> $latrappe #> [1] 0.00000000 6.15384418 6.19078552 6.14458563 6.09838574 6.13532708 #> [7] 6.00598596 5.95978606 5.91358617 5.86738628 5.82118639 5.69821460 #> [13] 5.81192784 5.68258671 5.63638682 5.59018693 5.54398704 5.49778714 #> [19] 5.53472848 5.40538736 5.35918747 5.31298758 5.26678768 5.30372902 #> [25] 5.17438790 5.12818801 5.23463744 5.03578822 5.71623067 6.21568584 #> [31] 0.01965089 0.06182778 0.09239978 0.04619989 0.00000000 6.23698542 #> [37] 6.19078552 6.14458563 6.09838574 6.05218585 6.00598596 5.95978606 #> [43] 5.91358617 5.86738628 5.89795828 5.85812773 5.80555849 5.76572794 #> [49] 5.79504208 6.27591644 0.74845682 0.70862627 0.73919827 0.69299838 #> [55] 0.64679849 0.60059860 0.55439870 0.50819881 0.46199892 0.41579903 #> [61] 0.36959914 0.32339924 0.27719935 0.23099946 0.18479957 0.13859968 #> [67] 0.09239978 0.04619989 0.00000000 6.23698542 6.19078552 6.14458563 #> [73] 6.09838574 6.05218585 6.00598596 5.95978606 5.91358617 5.86738628 #> [79] 5.82118639 5.77498650 5.80555849 5.76572794 5.86318567 5.83516559 #> [85] 6.00763464 5.99172851 6.03958986 6.06108299 6.14458563 6.11965913 #> [91] 5.87233235 5.74866224 5.47288683 5.37316667 5.23463744 5.11892946 #> [97] 4.98958833 4.94338844 4.89718855 4.68583998 4.23805955 4.75858887 #> [103] 5.06115998 5.18064040 5.94580686 6.14458563 6.09838574 5.97541396 #> [109] 6.08912719 5.95978606 6.07873485 0.17220358 0.61485604 0.97193763 #> [115] 1.38357146 1.13534641 1.00382783 0.95456984 0.83159806 0.70862627 #> [121] 0.57404959 0.54034905 0.40181982 0.16819082 6.24958141 6.08912719 #> [127] 5.91633517 5.91358617 5.91083717 6.05492957 6.14587778 6.19243421 #> [133] 6.24118603 0.22174091 0.09239978 0.04619989 #> #> $lindemanskriek #> [1] 0.0000000000 0.2503515252 6.1760863615 0.0682944710 0.1432517756 #> [6] 0.1075518591 0.0094331326 0.1468092473 0.0004521096 6.2479375002 #> [11] 6.2122375837 6.1765376672 6.1408377507 6.1051378342 6.0694379176 #> [16] 6.0337380011 5.9980380846 5.9623381681 5.9266382516 5.8909383351 #> [21] 5.8552384185 5.8195385020 5.7838385855 5.7481386690 5.7124387525 #> [26] 5.6767388359 5.6410389194 5.6053390029 5.5696390864 5.5339391699 #> [31] 5.4982392534 5.4625393368 5.4268394203 5.3911395038 5.4660968085 #> [36] 5.5647183339 5.6057903086 5.8810886727 6.2248369327 0.0009034153 #> [41] 0.1071005534 0.1620605241 0.2330962802 0.1973963637 0.1689426972 #> [46] 0.2503515252 0.2146516087 0.1789516922 0.1432517756 0.2319068537 #> [51] 0.3168306057 0.1468092473 0.2315427768 0.2097308562 0.2508028309 #> [56] 0.2521230303 0.7261918388 0.8736027395 1.0352983829 1.1969940262 #> [61] 1.4830446641 1.0049705246 1.4329182171 1.1785493547 1.1428494382 #> [66] 1.1071495216 1.0714496051 1.0357496886 1.0000497721 0.9643498556 #> [71] 0.9286499390 0.8929500225 0.8572501060 0.8215501895 0.7858502730 #> [76] 0.7501503565 0.7144504399 0.6787505234 0.6430506069 0.6073506904 #> [81] 0.5716507739 0.5359508573 0.5002509408 0.5233068470 0.4288511078 #> [86] 0.2824939701 0.3574512748 0.3805071810 0.1616964472 0.2503515252 #> [91] 0.3317603532 0.3033066867 0.3882304388 0.3525305223 0.2571998926 #> [96] 0.3949226964 0.2191210554 0.3235228633 0.2151037183 0.1383310231 #> [101] 0.1794029979 0.2268443133 6.2441101167 0.5359508573 6.1223930792 #> [106] 0.0840446472 6.2126896933 6.2126888895 5.9795934131 6.1412890564 #> [111] 5.9081935800 5.9668076149 5.8367937470 5.8514110350 5.8597078653 #> [116] 5.6053390029 5.6802963076 5.5963579799 5.4982392534 5.4625393368 #> [121] 5.4268394203 5.5658117028 5.3554395873 5.3197396708 5.2840397542 #> [126] 5.1895840150 5.2126399212 4.9319613416 5.0168850936 5.1642959944 #> [131] 4.9454852606 5.2528092845 6.0568472886 0.0053728621 0.1039943875 #> [136] 0.1789516922 0.2020075984 0.3525305223 0.1962069372 0.4997996351 #> [141] 1.3401577692 1.7805271830 1.2548699402 1.1053780165 1.7313336387 #> [146] 1.3927488538 1.3570489373 1.0763703576 1.2856491042 1.2499491877 #> [151] 1.2142492712 1.0678921335 1.1428494382 0.9827945271 1.0714496051 #> [156] 0.9769938659 0.8893925509 0.8224528010 0.8179927179 0.7685950280 #> [161] 0.7465928848 0.6971951949 0.4640997186 0.5190596893 0.3556797697 #> [166] 0.4337718603 0.4243816610 0.2485800201 0.3266721107 0.2142003029 #> [171] 0.2552722777 0.1616661559 0.1838724447 0.0714006369 0.1124726116 #> [176] 0.0356999165 #> #> $nicechouffe #> [1] 0.000000000 0.007281689 6.140695807 0.045565652 6.161360448 6.118324933 #> [7] 6.199644411 6.156608896 6.113573380 5.959880643 6.086258171 5.984466832 #> [13] 5.941431317 5.898395801 5.855360285 5.812324769 5.769289253 5.726253738 #> [19] 5.683218222 5.640182706 5.597147190 5.554111674 5.511076159 5.468040643 #> [25] 5.425005127 5.381969611 5.338934095 5.295898580 5.252863064 5.454806211 #> [31] 5.488542587 5.642902631 6.049229981 6.249711141 0.037282325 0.239225473 #> [37] 0.196189957 0.042497220 0.110118925 0.067083410 0.024047894 6.264197685 #> [43] 6.221162169 6.178126653 0.070574776 0.213762101 0.105127413 0.281398598 #> [49] 0.731413980 0.743876969 1.102070252 1.121453547 1.078418031 1.035382515 #> [55] 0.992346999 0.949311483 1.016933189 0.800821642 0.820204936 0.777169420 #> [61] 0.844791126 0.691098389 0.648062873 0.605027357 0.561991841 0.518956325 #> [67] 0.475920810 0.432885294 0.514204773 0.346814262 0.303778746 0.015764567 #> [73] 0.217707715 0.419650862 0.131636683 0.147356990 0.169920646 0.126885130 #> [79] 0.204473283 0.101807054 0.118402252 0.152138627 0.032331220 0.047201909 #> [85] 0.106173311 6.160100262 6.184447242 6.214130955 6.171095439 6.128059924 #> [91] 6.012305179 5.807573216 5.998953376 5.955917860 5.785202342 5.729745104 #> [97] 5.592395637 5.542113871 5.381969611 5.557603041 5.420253574 5.311618886 #> [103] 5.209827548 5.166792032 5.234413737 5.080721001 4.530586980 4.870294974 #> [109] 5.237665895 5.019236158 5.485792907 6.034533562 6.225913722 0.024047894 #> [115] 0.105367372 0.525979466 1.143987119 1.564599212 1.134687978 1.521979076 #> [121] 1.404252831 1.250560094 1.096867357 1.164489062 1.121453547 0.859749085 #> [127] 1.035382515 0.881689778 0.949311483 0.687607022 0.746131707 0.695849942 #> [133] 0.455418866 0.489155241 0.405046947 0.369763214 0.386358411 0.222699227 #> [139] 0.273977662 0.117150139 0.154585635 0.050557164 6.271228899 0.085109801 #> [145] 6.265628879 6.255914359 #> #> $pecheresse #> [1] 0.00000000 0.11558369 0.17175377 0.07308851 6.25264841 0.02563318 #> [7] 6.26011162 6.21140476 6.16269790 6.11399103 6.06528417 5.91690866 #> [13] 5.96787045 5.91916358 5.87045672 5.82174986 5.77304299 5.72433613 #> [19] 5.67562927 5.62692241 5.46755832 5.52950868 5.48080182 5.43209495 #> [25] 5.48305674 5.53207679 5.65686565 6.05491255 6.20075765 0.09078998 #> [31] 0.22986799 0.11138213 0.28134421 0.23263735 0.18393048 0.23489227 #> [37] 0.19139370 0.32926669 0.52952253 0.69354745 1.08197926 1.41377877 #> [43] 1.25441469 1.26640665 1.26765818 1.07006137 1.17024446 1.12153759 #> [49] 1.07283073 1.02412387 0.97541700 0.82704149 0.87800328 0.82929642 #> [55] 0.66993233 0.84899143 0.63059277 0.43707340 0.58576210 0.53705524 #> [61] 0.48834838 0.43964151 0.39093465 0.34222779 0.39318958 0.35547128 #> [67] 0.34499715 0.24706899 0.35601719 0.25748284 0.21994869 0.20989660 #> [73] 0.16118974 0.10013782 0.05143096 6.24842697 6.21089282 6.09240696 #> [79] 6.10230638 5.95098023 5.99479199 5.85356650 5.69998270 5.84867140 #> [85] 5.65806748 5.60644517 5.60482390 5.45644839 5.51261846 5.11405600 #> [91] 4.89791736 5.51894465 4.89116352 5.06453856 5.40155179 6.03204515 #> [97] 0.01424085 0.14633356 0.20828391 0.15957705 0.32953913 0.73690427 #> [103] 1.12060518 1.48296287 1.59749629 1.31377721 1.33946694 1.73132552 #> [109] 1.18713467 1.24330475 1.08394067 1.04622237 1.09718416 0.99589424 #> [115] 0.80237488 0.95106357 0.74575483 0.75398119 0.58627404 0.46477933 #> [121] 0.55092738 0.44015345 0.31865874 0.29046182 0.30520558 0.17253815 #> [127] 0.14434123 0.10925750 0.09920541 #> #> $sierranevada #> [1] 0.000000000 6.247485391 1.499396494 6.176085558 6.140385641 6.104685725 #> [7] 1.356596828 6.033285892 5.997585975 1.249497078 5.926186142 5.890486225 #> [13] 5.854786309 1.106697412 5.783386476 5.747686559 0.999597663 5.676286726 #> [19] 5.640586810 0.892497913 5.569186977 5.533487060 5.497787144 0.749698247 #> [25] 5.426387311 5.473828626 0.642598497 5.319287561 5.283587645 5.164746496 #> [31] 0.499798831 5.176487895 5.293437307 0.392699082 5.234536823 5.561762677 #> [37] 6.136376864 0.249899416 0.049050822 0.013350905 0.142799666 0.030327858 #> [43] 0.071399833 0.035699917 0.000000000 6.247485391 6.211785474 6.176085558 #> [49] 6.140385641 6.104685725 6.152127040 6.033285892 6.162734652 6.114535387 #> [55] 5.926186142 5.890486225 6.176536863 5.819086392 0.285599332 0.713547025 #> [61] 0.916456431 5.676286726 0.775548501 0.892497913 5.569186977 0.986246757 #> [67] 0.785398163 0.749698247 5.426387311 0.678298414 0.642598497 5.319287561 #> [73] 0.571198664 0.535498748 0.499798831 5.176487895 0.428398998 0.392699082 #> [79] 5.069388146 0.321299249 0.285599332 0.249899416 4.926588479 0.178499583 #> [85] 0.225940898 4.819488730 0.071399833 0.035699917 0.000000000 4.676689064 #> [91] 6.211785474 6.176085558 4.569589314 6.104685725 6.068985808 4.462489565 #> [97] 6.074357866 6.045027290 6.091334819 4.319689899 0.004008777 0.063975534 #> [103] 4.212590149 0.093297539 0.131058267 6.071077846 4.069790483 5.688028125 #> [109] 5.721836305 3.962690734 5.580928376 5.545228459 5.579036639 3.819891067 #> [115] 5.599966141 5.484436239 3.712791318 5.400537057 5.457166475 5.421466558 #> [121] 3.569991652 5.331886910 5.152529377 3.462891902 5.242966976 4.613517392 #> [127] 3.355792153 5.212639117 4.436964317 4.972138058 3.212992487 5.730882620 #> [133] 6.118036630 3.105892737 6.135013583 6.176085558 6.223526873 2.963093071 #> [139] 6.234134485 0.424841527 2.855993321 0.822869585 1.754216662 0.856346691 #> [145] 2.713193655 1.286550912 1.147769387 2.606093906 0.754618999 0.784044246 #> [151] 0.629698898 2.463294240 0.691649319 0.655949403 2.356194490 0.597048918 #> [157] 0.630857098 0.513149736 2.213394824 0.530126690 0.488057432 2.106295075 #> [163] 0.334650154 0.311449586 1.999195325 6.281093269 6.011388186 5.948788930 #> [169] 1.856395659 5.966355505 5.998038085 1.749295909 6.273335645 6.225136379 #> [175] 0.236548510 1.606496243 #> #> $tanglefoot #> [1] 0.000000000 6.184656237 6.148545976 6.112435716 6.200680450 6.040215195 #> [7] 6.004104935 5.967994674 5.931884414 5.895774154 5.859663893 5.823553633 #> [13] 5.787443373 5.751333112 5.715222852 5.679112591 5.643002331 5.606892071 #> [19] 5.570781810 5.534671550 5.498561289 5.462451029 5.426340769 5.514585503 #> [25] 5.354120248 5.318009988 5.281899727 5.245789467 5.209679206 5.049213951 #> [31] 5.013103691 5.101348425 5.189593159 5.387898575 5.351788314 5.742305547 #> [37] 0.208408143 0.172297883 0.136187622 0.100077362 0.063967101 0.027856841 #> [43] 6.274931888 6.238821627 6.202711367 6.166601107 6.130490846 6.094380586 #> [49] 6.058270325 6.022160065 5.986049805 5.949939544 5.913829284 5.877719024 #> [55] 5.841608763 5.805498503 5.769388242 5.733277982 5.697167722 0.390069165 #> [61] 0.553787550 0.631469297 0.840337700 0.804227439 0.892472173 0.732006918 #> [67] 0.695896658 0.659786398 0.623676137 0.587565877 0.551455617 0.515345356 #> [73] 0.479235096 0.443124835 0.407014575 0.370904315 0.334794054 0.298683794 #> [79] 0.262573533 0.226463273 0.190353013 0.154242752 0.118132492 6.240852544 #> [85] 0.045911971 0.009801711 6.256876758 6.220766497 6.184656237 6.148545976 #> [91] 6.112435716 6.076325456 6.040215195 5.879749940 5.967994674 5.807529420 #> [97] 6.020129148 5.984018888 6.068532296 6.032422036 6.163743554 0.140663817 #> [103] 0.039428393 0.145215187 0.146125043 0.006426503 6.154921036 5.962208898 #> [109] 5.740750688 5.657431436 5.635209171 5.354120248 5.562988651 5.406254722 #> [115] 5.370144461 5.334034201 5.297923941 5.279355740 5.346327088 5.189593159 #> [121] 5.153482899 5.117372639 5.081262378 5.165775786 4.504180486 4.972931597 #> [127] 5.057445005 5.135126752 4.461946162 4.459156898 5.618572141 6.202711367 #> [133] 6.166601107 6.130490846 6.094380586 6.058270325 6.022160065 5.986049805 #> [139] 5.949939544 0.842669633 1.165330043 2.180869995 0.734338852 0.871651312 #> [145] 1.020889002 1.572781345 0.824313486 0.788203226 0.752092965 0.715982705 #> [151] 0.445456769 0.643762184 0.607651924 0.578787914 0.414807735 0.499321143 #> [157] 0.342587214 0.551455617 0.329997406 0.354880101 0.198146172 0.048243905 #> [163] 6.141700162 5.832581198 5.729902774 5.760360677 5.790818581 5.914939005 #> [169] 5.973780450 6.042547129 6.006436868 6.204742284 6.230568208 6.256876758 #> #> $tauro #> [1] 0.00000000 6.21162891 0.05748202 0.02137176 6.26844680 6.23233654 #> [7] 6.19622628 6.16011602 6.12400576 5.93524617 6.05178524 6.01567498 #> [13] 5.97956472 5.94345446 5.90734420 5.87123394 5.83512368 5.63386474 #> [19] 5.76290316 5.72679290 5.69068264 5.65457238 5.61846212 5.58235186 #> [25] 5.54624160 5.35748201 5.47402107 5.43791081 5.40180055 5.36569029 #> [31] 5.32958003 5.29346977 5.42250819 5.40110275 5.35028767 5.47077929 #> [37] 5.71846313 5.86220637 6.16538873 0.04722005 0.07623495 0.14320630 #> [43] 0.01871925 6.26579430 0.11164741 0.07553715 0.21928039 0.15596595 #> [49] 0.05034760 0.09624478 0.39433257 0.28550308 0.41076793 0.65519446 #> [55] 0.89471364 1.20208964 1.08397193 0.94675830 1.02425076 1.14078983 #> [61] 1.10467957 1.06856931 1.03245905 0.99634879 0.96023853 0.92412827 #> [67] 0.88801801 0.76876651 0.81579748 0.77968722 0.74357696 0.70746670 #> [73] 0.67135644 0.63524618 0.59913592 0.38317216 0.52691540 0.49080514 #> [79] 0.45469488 0.25343594 0.53512369 0.34636410 0.31025384 0.27414358 #> [85] 0.15489209 0.11878183 0.16581280 0.12970254 0.17673351 0.05748202 #> [91] 0.17402108 0.23024016 0.19412990 0.15801964 0.19868127 0.08579912 #> [97] 0.17188403 0.01357860 0.08126068 6.24581677 6.18843312 5.99800409 #> [103] 6.09803279 6.08010234 5.96416210 5.92805183 5.81745278 5.76745453 #> [109] 5.81972105 5.70160335 5.58235186 5.54624160 5.62956026 5.47402107 #> [115] 5.60305949 5.40180055 5.36569029 5.49472871 5.29346977 5.25735951 #> [121] 5.31190914 4.79034787 5.14902873 5.26556780 5.32178687 4.18873162 #> [127] 5.27083974 5.14833093 5.52036977 6.03464546 6.08217197 0.02850618 #> [133] 0.07553715 0.12256812 0.16846530 0.21218503 0.57459721 1.13104533 #> [139] 1.81017829 1.39356165 1.05895246 1.23819990 1.74887848 1.24912061 #> [145] 1.04786167 1.17690009 0.97564115 0.93953089 1.06856931 1.03245905 #> [151] 0.83120011 0.96023853 0.75897959 0.72286933 0.93504898 0.65064881 #> [157] 0.59983372 0.74357696 0.44121465 0.50620777 0.39026752 0.43398724 #> [163] 0.32748068 0.28193674 0.31095164 0.13294433 6.23812232 0.15567551 #> [169] 0.02461355 6.24466814 0.02916492 6.12642751 0.03677438 0.01316347 #> #> $westmalle #> [1] 0.000000000 0.186529069 6.250480580 0.097405873 6.277273760 0.008282678 #> [7] 6.246906387 6.202344789 6.157783191 6.113221593 6.068659995 6.024098397 #> [13] 5.979536799 6.045632423 5.890413603 5.845852006 5.801290408 5.756728810 #> [19] 5.712167212 5.667605614 5.623044016 5.702837413 5.533920820 5.489359222 #> [25] 5.444797624 5.400236026 5.472783173 5.435467825 5.207795410 5.741135749 #> [31] 6.241125859 6.163243265 6.240876838 0.086375599 0.068123719 0.067558868 #> [37] 0.197669469 0.211863694 0.108546273 0.181093420 0.264401740 0.314154094 #> [43] 0.289070551 0.505987769 0.626574849 1.300843250 1.077871153 1.153933224 #> [49] 1.233726620 1.130409200 1.144603425 1.100041827 1.055480229 1.010918631 #> [55] 0.966357033 0.921795435 0.877233837 0.832672239 0.788110641 0.743549043 #> [61] 0.698987445 0.654425847 0.609864250 0.565302652 0.520741054 0.476179456 #> [67] 0.431617858 0.387056260 0.283738839 0.542911727 0.312127289 0.208809868 #> [73] 0.281357015 0.364665336 0.260473024 0.275542140 0.183397438 0.160109227 #> [79] 0.218629237 0.174067639 0.052734150 0.041493548 6.232908265 5.712277337 #> [85] 6.029803147 0.048595106 6.068549870 6.268966935 5.858803005 5.806995157 #> [91] 5.923624474 5.717871962 5.556201619 5.574058831 5.467078423 5.546871820 #> [97] 5.377955227 5.333393629 5.288832031 5.046874874 5.199708836 5.329819437 #> [103] 4.788835085 5.128442852 5.485110053 6.057739847 0.219950268 6.261178417 #> [109] 0.130827072 0.260937673 0.446595662 0.873200329 1.399022012 1.478815409 #> [115] 1.524913698 1.279034992 1.469485610 1.411226239 1.256007419 1.211445822 #> [121] 1.042529229 1.122322626 1.077761028 0.908844435 0.988637832 0.819721239 #> [127] 0.782405891 0.609974375 0.635719241 0.520851179 0.330661201 0.271814860 #> [133] 0.694563859 0.587583451 0.240136984 0.374105260 0.167847215 0.087586504 #> [139] 0.179427511 6.185174841 0.151297271 #> #> $amrut #> [1] 0.00000000 6.25028905 6.21739279 6.18449653 6.15160027 6.11870402 #> [7] 6.08580776 6.05291150 6.02001524 5.98711898 5.95422273 5.92132647 #> [13] 5.88843021 5.85553395 5.82263769 5.78974143 5.75684518 5.72394892 #> [19] 5.69105266 5.65815640 5.62526014 5.59236389 5.55946763 5.52657137 #> [25] 5.49367511 5.46077885 5.42788260 5.39498634 5.36209008 5.32919382 #> [31] 5.29629756 5.26340130 5.23050505 5.19760879 4.96731697 5.03214762 #> [37] 5.09892001 5.16569241 5.23052306 5.09989989 5.16473054 5.77859271 #> [43] 6.00869118 6.14798574 6.20915072 6.27398136 6.24108511 6.20818885 #> [49] 6.27496124 6.24206498 6.20916873 6.17627247 6.14337621 6.11047995 #> [55] 6.07758369 6.14435609 6.11145983 6.07856357 6.23745546 0.13701560 #> [61] 0.50677400 0.93752535 0.90462909 1.06912839 0.93656348 1.00333587 #> [67] 1.07010827 1.03721201 0.90464710 0.87175084 0.83885458 0.80595832 #> [73] 0.77306207 0.74016581 0.60760090 0.67437329 0.64147703 0.60858078 #> [79] 0.57568452 0.54278826 0.50989200 0.47699574 0.44409949 0.41120323 #> [85] 0.37830697 0.34541071 0.31251445 0.27961819 0.24672194 0.21382568 #> [91] 0.18092942 0.14803316 0.11513690 0.08224065 0.04934439 0.01644813 #> [97] 6.26673718 6.23384092 6.20094466 6.16804840 6.13515215 6.10225589 #> [103] 6.06935963 6.03646337 6.00356711 5.97067085 5.83810594 5.90487834 #> [109] 6.06937764 6.21959220 6.26983717 0.03052750 0.11825491 0.20971365 #> [115] 0.28747461 6.22971088 5.98931839 5.99414009 5.64268815 5.51012324 #> [121] 5.47722698 5.34466207 5.31176581 5.37853821 5.44531060 5.31274569 #> [127] 5.69807376 5.44434874 5.31372557 5.28082931 5.24793305 5.49587452 #> [133] 5.27986744 4.85218007 4.81928381 5.18117867 5.05055550 4.91799059 #> [139] 4.98476299 4.95186673 4.71963317 4.78640556 4.85317796 5.50601121 #> [145] 5.93676256 6.12594820 6.19272060 6.15982434 6.22659673 0.10230331 #> [151] 0.38867622 1.31585033 1.28295407 1.25005781 1.11749290 1.18426529 #> [157] 1.15136904 1.01880412 1.08557652 1.05268026 1.13044122 1.08655640 #> [163] 0.95399149 0.72369967 0.59674218 0.85530271 0.62501089 0.78951020 #> [169] 0.24951543 0.62404903 0.59115277 0.65792516 0.62502890 0.69180130 #> [175] 0.55923639 0.42667148 0.17169332 0.08004124 6.17041716 5.78188502 #> [181] 5.91840181 5.95110472 6.03883213 6.08270776 6.22200232 6.28316730 #> [187] 0.06481264 0.32898059 0.09868877 0.06579252 0.03289626 #> #> $ballantines #> [1] 0.00000000 6.24014979 6.19711428 6.15407876 6.11104324 6.06800773 #> [7] 6.02497221 5.98193670 5.93890118 5.89586566 5.85283015 5.80979463 #> [13] 5.76675912 5.72372360 5.68068809 5.63765257 5.59461705 5.55158154 #> [19] 5.50854602 5.40309170 5.17749633 5.37943948 5.33640396 5.29336844 #> [25] 5.37468792 5.33165241 5.34960985 5.36620504 5.45869724 5.67865646 #> [31] 6.26003129 0.11234034 0.13124101 0.15062431 0.04516998 0.18890827 #> [37] 6.24228426 6.26166755 0.00201489 6.17559652 6.13256100 6.08952549 #> [43] 6.04648997 5.87909946 5.96041894 5.91738342 5.87434791 5.83131239 #> [49] 5.85069569 6.26438747 0.43121755 0.70180268 0.65876717 0.66331476 #> [55] 0.69331981 0.77463928 0.73160377 0.68856825 0.76988773 0.66906539 #> [61] 0.55946171 0.51642619 0.47339067 0.49277397 0.38731964 0.34428413 #> [67] 0.30124861 0.25821309 0.21517758 0.17214206 0.12910655 0.08607103 #> [73] 0.04303552 0.00000000 6.24014979 6.19711428 6.21649757 6.11104324 #> [79] 6.06800773 6.02497221 6.04435551 5.93890118 5.89586566 5.85283015 #> [85] 5.80979463 5.89111411 5.72372360 5.68068809 5.51329758 5.59461705 #> [91] 5.67593653 5.86731669 6.06779785 6.27444132 0.12663099 0.16036737 #> [97] 0.02238015 0.07429634 6.05926374 5.60088906 5.24558138 5.43696153 #> [103] 5.03515535 4.71382017 5.35397610 4.84362999 4.86301329 4.94433276 #> [109] 5.18183404 4.52281341 5.27887383 6.03328408 6.17559652 6.13256100 #> [115] 6.08952549 6.17904150 0.18391676 1.24802996 1.34689150 1.02940739 #> [121] 1.11892341 1.07588790 0.97043357 1.34858753 0.68617896 0.90374583 #> [127] 0.55782545 0.35402719 6.27242643 5.90764036 5.94137673 5.91652103 #> [133] 5.87348552 5.99068069 6.21160889 0.11462000 0.30600016 0.38731964 #> [139] 0.46863912 0.30124861 0.25821309 0.21517758 0.17214206 0.12910655 #> [145] 0.08607103 0.04303552 #> #> $bushmills #> [1] 0.00000000 6.18067856 6.14259865 1.39212975 6.06643882 6.02835891 #> [7] 6.05684717 6.01876725 1.20173020 5.87603927 5.83795936 5.79987945 #> [13] 1.04941056 5.79028779 5.68563971 5.64755980 5.60947989 0.85901100 #> [19] 5.59573888 5.42867200 5.58971178 5.41908034 0.66861145 5.34292052 #> [25] 5.36725941 5.26676069 0.51629180 5.12403271 5.09010215 5.04787289 #> [31] 4.95200614 0.32589225 4.93363315 5.09467294 5.10938945 5.37591891 #> [37] 0.13549269 5.79259549 6.14512262 6.23787010 6.26635836 6.22827845 #> [43] 6.19019853 6.15211862 6.17645752 6.07595880 6.03787889 6.06221779 #> [49] 5.96171907 5.99020732 5.88555925 6.09245800 0.15896295 0.70015986 #> [55] 0.95428246 5.69515969 1.01125896 1.03096588 1.00108251 5.54284005 #> [61] 0.91672615 0.82085941 0.71621134 0.61571261 5.35244049 0.60197160 #> [67] 0.56389169 0.52581178 0.48773187 5.16204094 0.41157205 0.37349214 #> [73] 0.27299342 0.23076415 4.97164138 0.22117249 0.18309258 0.14501267 #> [79] 4.81932174 0.06885285 0.03077294 6.27587833 6.17537961 4.62892219 #> [85] 6.09507044 6.12355869 6.08547878 6.04739887 4.43852263 5.97123905 #> [91] 5.93315914 5.89507922 4.28620299 5.75235124 5.71427133 5.74275958 #> [97] 5.70467967 4.09580343 5.62851985 5.59043994 5.48579186 5.51428012 #> [103] 3.90540388 5.43812029 5.33762157 5.49451200 5.78752817 3.71500432 #> [109] 6.00087202 6.10569621 6.02826654 3.56268468 5.88079926 5.43782756 #> [115] 5.14359627 4.54875359 3.37228512 4.96742035 4.86692163 4.82884172 #> [121] 4.85318062 3.18188557 4.78117015 4.61410326 5.55354286 3.02956593 #> [127] 6.00052714 6.09499876 6.05691885 6.15139047 2.83916637 0.24749641 #> [133] 1.33410728 1.09171150 1.04948224 2.64876682 1.03989058 1.00181067 #> [139] 0.96373076 1.28442152 2.45836726 0.84949102 0.37478395 0.05924050 #> [145] 2.30604762 6.07552960 6.15687861 6.22945592 0.20242527 2.11564806 #> [151] 0.38241683 0.46869191 0.43061200 0.39253209 1.92524851 0.31637227 #> [157] 0.27829236 0.24021245 1.77292886 0.22647144 0.19254088 0.08789280 #> [163] 0.04981289 1.58252931 6.25683838 #> #> $chivas #> [1] 0.0000000000 0.1291196729 0.2186774860 0.2974741250 0.2591620195 #> [6] 0.2208499139 0.2449566184 0.1442257029 0.1059135973 0.1263573145 #> [11] 0.0292893863 6.2741625879 6.2358504824 0.0387080642 6.1592262713 #> [16] 6.2315713870 6.0826020603 6.0442899547 6.0059778492 5.9676657437 #> [21] 5.9293536381 5.9497973553 5.8527294271 5.8144173216 5.8867624372 #> [26] 5.7377931105 5.6994810050 5.7855238940 5.6228567939 5.5845446884 #> [31] 5.4874767601 5.3835654828 5.7145870349 0.0102810137 0.4619262344 #> [36] 0.3973044117 0.4796159747 0.4485501192 0.5273467582 0.4890346527 #> [41] 0.3336138026 0.4124104416 0.3740983361 0.2251290094 0.2974741250 #> [46] 0.2591620195 0.2208499139 0.2412936311 0.1442257029 0.1646694201 #> [51] 0.1919564864 0.0292893863 0.0533960907 0.1713341211 0.0997010197 #> [56] 0.0003959587 0.2775714414 0.8116137645 1.0869223112 1.4106976134 #> [61] 1.2552767633 1.1545458478 1.1786525522 1.1403404467 1.1020283412 #> [66] 1.0637162356 0.9666483074 0.9870920246 0.9487799190 0.7861128190 #> [71] 0.8721557080 0.8338436024 0.7955314969 0.6948005814 0.7189072859 #> [76] 0.6805951803 0.6422830748 0.6039709693 0.5069030410 0.5273467582 #> [81] 0.4890346527 0.4507225471 0.4124104416 0.3740983361 0.3357862305 #> [86] 0.2387183023 0.3835170140 0.2208499139 0.4275164715 0.5029963731 #> [91] 0.5183240389 0.5746999962 0.6620382213 0.7763754441 0.7703102211 #> [96] 0.7663193969 0.8033361822 0.5886579210 0.3580160684 0.0060833107 #> [101] 5.8953206280 5.7226870806 5.8049986436 5.7666865381 5.7939736044 #> [106] 5.9387723161 6.0071958832 5.9827717736 5.8238359995 5.8465168494 #> [111] 5.8415257398 5.7698926384 5.6705875774 5.6250292219 5.1108377015 #> [116] 5.5556512608 5.3929841607 5.2303170606 5.3163599496 5.2780478441 #> [121] 5.3640907331 5.2014236330 5.1631115275 5.5884470310 0.1291196729 #> [126] 0.2770304078 0.1731191305 0.2591620195 0.2832687239 0.1825378084 #> [131] 0.2685806974 0.7261630833 1.4073071514 1.6000857131 1.5617736075 #> [136] 1.5234615020 1.3607944019 1.4468372910 1.5191824066 1.3702130799 #> [141] 1.3943197844 1.2935888688 1.1381680187 0.9719859946 0.9475618850 #> [146] 1.1403404467 0.7432576709 0.8187375725 0.9147469089 0.8017440746 #> [151] 0.9487799190 0.9692236362 0.9965107025 0.9581985970 0.9126402415 #> [156] 0.7572193914 0.3601366156 6.2371381468 6.1400702186 6.0351899493 #> [161] 5.9968778437 6.0554276619 6.1287188510 6.1596030241 #> #> $dalmore #> [1] 0.000000000 0.105091701 0.232547293 0.253660785 0.378272783 1.908532430 #> [7] 0.297199424 0.256662744 0.216126065 0.175589386 0.135052706 0.094516027 #> [13] 0.053979347 1.584238995 6.256091296 0.015510541 6.175017937 6.134481258 #> [19] 6.093944578 6.053407899 6.012871219 1.259945560 5.931797861 5.891261181 #> [25] 5.850724502 5.733415931 5.604502466 5.407363909 5.390078853 0.935652124 #> [31] 5.690645657 6.133696964 0.306943582 0.773505407 0.732968727 0.692432048 #> [37] 0.651895369 0.611358689 0.570822010 0.530285330 0.489748651 0.449211972 #> [43] 0.408675292 0.368138613 0.327601933 0.287065254 0.246528575 0.205991895 #> [49] 0.165455216 0.124918536 0.167523089 0.043845178 0.003308498 0.045913051 #> [55] 6.205420447 6.248024999 6.047575197 0.122375656 0.598069647 1.137698741 #> [61] 1.332952622 1.507773642 5.881127011 1.373180015 1.252813350 1.047127993 #> [67] 1.006591313 0.966054634 0.925517955 0.968122507 5.556833576 0.803907916 #> [73] 0.763371237 0.805975789 0.682297878 0.641761199 0.601224519 0.643829072 #> [79] 5.232540141 0.479614481 0.439077802 0.398541122 0.434776334 0.317467764 #> [85] 0.276931084 0.313166296 4.908246706 0.477071600 0.509575486 0.506655463 #> [91] 0.677212117 0.735121596 0.738035812 0.788159020 4.583953271 0.659876670 #> [97] 0.446186558 0.144745372 6.145252208 6.197044863 5.911529521 5.718343513 #> [103] 4.259659835 5.873060715 5.749382803 5.785618015 5.668309445 5.710913997 #> [109] 5.664007977 5.711848084 5.900953847 3.894829721 5.126590437 5.384552689 #> [115] 5.344016009 5.380251221 5.262942651 5.222405971 5.334518620 3.570536286 #> [121] 0.143428289 0.264729041 0.307333594 0.266796914 0.226260235 0.552897389 #> [127] 1.632841971 3.246242850 1.634909844 1.671145056 1.470695253 1.513299806 #> [133] 1.472763126 1.753977001 0.996898648 2.921949415 1.157967080 1.186938498 #> [139] 1.229543050 1.189006371 1.148469691 1.031161121 1.067396332 2.597655980 #> [145] 1.069464206 0.869014403 0.822108383 0.619734272 0.457002422 0.195636973 #> [151] 0.001155629 2.273362545 6.076675450 6.075829107 6.169403211 #> #> $famousgrouse #> [1] 0.000000000 6.141129757 6.103951146 6.066772535 1.317204943 5.992415312 #> [7] 5.955236701 5.918058089 5.880879478 5.843700867 5.806522256 5.769343644 #> [13] 1.019776053 5.694986422 5.657807810 5.620629199 5.583450588 5.546271977 #> [19] 5.509093365 5.471914754 0.722347162 5.397557531 5.360378920 5.323200309 #> [25] 5.286021698 5.248843086 5.211664475 0.462096883 5.137307252 5.100128641 #> [31] 4.844281084 5.025771419 4.988592807 4.951414196 5.273006255 0.164667993 #> [37] 5.427880966 6.014725407 6.044860672 0.015953548 6.064564684 6.224781633 #> [43] 6.187603021 6.150424410 6.113245799 6.076067187 6.038888576 6.001709965 #> [49] 5.964531354 6.038009963 5.890174131 6.050391080 6.034485854 0.002551494 #> [55] 0.470471390 0.794496534 0.954713483 0.917534872 5.592745241 1.040573209 #> [61] 0.805999038 0.966215986 0.731641815 0.694463204 0.657284593 0.620105981 #> [67] 5.295316350 0.545748759 0.508570147 0.471391536 0.434212925 0.397034314 #> [73] 0.359855702 5.035066071 0.285498480 0.248319868 0.211141257 0.173962646 #> [79] 0.136784035 0.099605423 0.062426812 4.737637181 0.206738535 6.234076285 #> [85] 6.196897674 5.941050117 6.122540452 6.085361840 6.048183229 4.440208291 #> [91] 5.973826006 5.936647395 5.899468784 5.862290173 5.825111561 5.787932950 #> [97] 5.750754339 4.142779401 5.676397116 5.857887451 5.799435453 6.123460598 #> [103] 6.034781175 6.217146400 3.882529122 6.260300823 5.886066730 5.586768278 #> [109] 5.304611003 5.267432392 5.032858221 5.514825724 3.585100231 5.582365556 #> [115] 5.621958836 5.155017945 4.907513460 4.970003502 4.932824890 5.020001274 #> [121] 3.287671341 4.710631835 4.784110445 4.965600780 4.709753223 4.672574611 #> [127] 5.344022272 3.027421062 6.131835104 5.897260933 6.276146828 6.020299270 #> [133] 0.408561624 1.344210289 0.837603786 2.729992172 1.122017234 1.084838622 #> [139] 1.047660011 1.010481400 0.973302789 0.936124177 1.096341126 2.432563281 #> [145] 0.627192784 0.676752511 0.089187952 0.308160723 0.478478338 0.857364233 #> [151] 2.172313002 0.564338064 0.527159453 0.109474465 6.092486429 5.913410763 #> [157] 5.876232152 6.160804095 1.874884112 6.131870152 6.154145200 6.278341699 #> [163] 0.155373340 0.118194729 0.191673339 0.043837506 1.577455222 6.252665591 #> [169] 6.215486980 #> #> $glendronach #> [1] 0.00000000 6.25129097 0.01935255 1.47511330 6.15560794 6.12371360 #> [7] 6.09181926 1.34753594 6.02803057 5.99613623 5.96424189 5.93234755 #> [13] 1.18806423 5.86855887 5.83666452 5.80477018 1.06048686 5.74098150 #> [19] 5.70908716 5.67719282 5.72843971 0.90101515 5.58150979 5.54961545 #> [25] 5.51772111 0.77343779 5.45393242 5.42203808 5.39014374 5.27510817 #> [31] 0.61396608 5.29446072 5.26256637 5.23067203 0.48638871 5.16688335 #> [37] 5.05184778 5.01995343 5.15434156 0.32691700 5.09055287 5.14066598 #> [43] 5.26537351 0.19933964 5.86262800 6.12023733 6.22169324 6.18979890 #> [49] 0.03986793 6.20801766 6.17612332 6.22737021 6.19547587 6.16358153 #> [55] 6.13168718 6.18293407 6.06789850 6.11914539 6.16925850 6.05535671 #> [61] 6.18529980 5.90842679 0.01997464 0.29426790 0.87355594 5.78084943 #> [67] 0.95342487 1.00467176 0.88963619 1.18586174 5.62137772 0.87709440 #> [73] 0.84520005 0.81330571 5.49380035 0.74951703 0.71762269 0.68572835 #> [79] 0.65383400 5.33432864 0.59004532 0.63492287 0.52625664 5.20675128 #> [85] 0.46246795 0.43057361 0.39867927 0.36678493 5.04727957 0.30299625 #> [91] 0.27110190 0.23920756 4.91970220 0.17541888 0.14352454 0.11163020 #> [97] 0.07973585 4.76023049 0.01594717 6.26723814 6.23534379 4.63265313 #> [103] 6.08841388 6.13966077 6.10776643 6.07587209 4.47318142 6.01208340 #> [109] 5.98018906 5.94829472 4.34560405 5.71935736 5.93575293 6.06569602 #> [115] 6.18361413 4.18613234 6.25310878 0.11221161 0.25411839 4.05855498 #> [121] 6.24095807 5.96035374 5.69881696 5.41863270 3.89908327 5.35484402 #> [127] 5.32294968 5.45733780 3.77150590 5.39354912 5.36165478 5.32976044 #> [133] 5.45970352 3.61203419 5.39591484 5.36402050 5.31394634 3.48445683 #> [139] 4.70160826 4.99146447 4.95957013 5.01081702 3.32498512 4.86388710 #> [145] 4.91513399 4.80009842 3.19740775 4.73630974 4.86956407 5.84852626 #> [151] 3.06983038 6.17952870 6.14763436 6.19251190 6.16698690 2.91035868 #> [157] 0.30360090 1.27577367 1.24387932 2.78278131 1.18009064 1.14819630 #> [163] 1.03316073 1.08440762 2.62330960 0.93747770 1.31047515 1.03997148 #> [169] 2.49573223 0.64806290 0.53939667 0.58427422 0.57055969 2.33626053 #> [175] 0.65042863 0.61853428 0.66978117 2.20868316 0.60599249 0.57409815 #> [181] 0.70735249 0.59345070 2.04921145 0.20154212 6.23416414 5.97117913 #> [187] 1.92163409 5.77327966 5.92673327 6.10593226 6.11165458 1.76216238 #> [193] 6.27750834 0.12757737 0.17882426 1.63458501 0.03189434 #> #> $glenmorangie #> [1] 0.00000000 0.02365423 1.50059314 6.17788053 6.20153475 6.22478608 #> [7] 1.36018676 6.03747415 6.00237256 6.02602678 1.21978039 6.02142277 #> [13] 5.86196618 5.88562041 1.07937401 5.75666140 5.72155980 5.74521403 #> [19] 0.93896764 5.73336377 5.64357224 5.54605184 0.79856126 5.47584865 #> [25] 5.50316586 5.52275420 0.65815489 5.33544227 5.30034068 5.32399491 #> [31] 0.51774851 5.19503590 5.09751549 4.74432633 0.37734213 4.61800236 #> [37] 4.95710912 5.15909853 0.23693576 5.73960000 6.03750744 6.12876484 #> [43] 0.09652938 6.22750435 6.12416355 6.21565409 6.23930831 6.26296254 #> [49] 6.11034930 6.20057170 6.09890194 6.18090909 6.08745457 6.17894511 #> [55] 5.95849556 0.02071504 6.22758499 0.42671110 5.81808919 1.01184279 #> [61] 1.09425284 1.49035275 5.67768281 1.23307711 0.95384647 0.79757024 #> [67] 5.53727644 0.78978586 0.75468427 0.59522768 5.39687006 0.59062366 #> [73] 0.61427789 0.45482130 5.25646369 0.45021729 0.41511569 0.43876992 #> [79] 5.11605731 0.36856674 0.33346514 0.18125480 4.97565093 0.16574155 #> [85] 0.19305877 0.04084843 4.83524456 0.08775398 6.27708188 0.01755080 #> [91] 4.69483818 6.16811411 6.19543132 6.16032973 4.55443181 5.96577155 #> [97] 6.05502495 6.01992335 4.41402543 6.07407516 6.14570924 6.16556842 #> [103] 4.27361906 6.24594095 6.21405478 0.05821264 4.13321268 6.27119476 #> [109] 6.17422532 6.13042829 3.99280631 5.72589660 5.73837811 5.63297005 #> [115] 3.85239993 5.44685049 5.35299307 5.31789148 3.71199355 5.37204328 #> [121] 5.21258669 5.17748510 3.57158718 5.10728191 5.07218032 5.09583455 #> [127] 3.43118080 4.96687554 4.86935513 4.61062091 3.29077443 4.94357791 #> [133] 4.85378638 4.75626597 3.15036805 5.65131445 6.16300170 6.18665592 #> [139] 3.00996168 6.11645274 6.14010696 0.69035946 2.86955530 1.26365738 #> [145] 1.11144704 1.19345419 2.72914893 1.35434167 1.08814941 1.05304782 #> [151] 2.58874255 0.86573588 0.94774304 0.91264144 2.44833617 0.84243825 #> [157] 0.74858084 0.77223507 2.30792980 0.70203188 0.66693028 0.63182869 #> [163] 2.16752342 0.31664684 0.18723129 0.20537087 2.02711705 6.19201497 #> [169] 6.15691338 5.98135462 1.88671067 6.00539874 6.08905388 6.15450226 #> [175] 1.74630430 6.16298929 6.15739942 0.01144737 1.60589792 #> #> $highlandpark #> [1] 0.000000000 6.246006696 1.496439104 6.171649473 6.134470862 6.097292251 #> [7] 1.347724659 6.022935028 5.914448952 6.019885270 1.199010214 5.802913118 #> [13] 5.913813863 5.799863360 1.050295769 5.725506138 5.688327527 0.938759935 #> [19] 5.613970304 5.576791693 5.539613081 0.790045490 5.465255859 5.428077248 #> [25] 5.390898636 0.641331045 5.316541414 5.208055338 5.242184191 0.492616600 #> [31] 5.096519504 5.130648357 0.381080766 5.461182921 6.095967481 6.209706299 #> [37] 0.232366321 6.251574168 0.086701633 0.049523022 0.083651875 6.118565238 #> [43] 0.009294653 6.255301349 6.218122737 6.180944126 6.215072980 6.106586904 #> [49] 6.140715757 6.103537146 6.066358535 5.957872458 6.062590902 6.025412290 #> [55] 5.988233679 5.809158013 5.983072735 0.280464542 0.843336144 5.660443568 #> [61] 0.982183441 0.873697365 5.548907734 0.941237197 0.762161531 0.724982920 #> [67] 5.400193289 0.721933162 0.613447086 0.576268475 5.251478844 0.501911252 #> [73] 0.464732641 0.427554030 5.102764399 0.353196807 0.316018196 4.991228565 #> [79] 0.241660973 0.204482362 0.167303751 4.842514120 0.092946528 0.055767917 #> [85] 0.018589306 4.693799675 6.227417390 6.190238779 6.153060168 4.545085230 #> [91] 6.078702945 6.041524334 6.004345723 4.396370784 5.929988500 5.892809889 #> [97] 4.284834951 5.818452666 5.709966590 5.672787979 4.136120505 5.811635276 #> [103] 6.096207219 0.137572542 3.987406060 0.237297316 0.366564398 0.329385787 #> [109] 3.838691615 6.114256599 5.487780048 3.727155781 5.118876442 5.294902350 #> [115] 5.397509607 3.578441336 5.253956106 5.146187905 5.037701829 3.429726891 #> [121] 4.685044948 4.926165995 4.888987384 3.281012446 4.814630161 5.075950482 #> [127] 3.169476612 5.779949285 6.094814988 6.128225967 3.020762167 6.196483674 #> [133] 6.159305063 0.045933338 2.872047722 0.478674620 1.226894172 1.331612616 #> [139] 2.723333277 1.186665803 1.149487192 2.611797443 1.145719559 0.966643893 #> [145] 0.787568228 2.463082998 0.644014726 0.746621983 0.709443372 2.314368552 #> [151] 0.706393614 0.205567394 5.838366741 2.165654107 5.613092090 5.752035653 #> [157] 2.054118274 5.710187298 6.036454405 0.004612279 1.905403828 0.226121425 #> [163] 0.331557744 0.294379132 1.756689383 0.220021910 0.111535834 0.074357223 #> [169] 1.607974938 #> #> $jackdaniels #> [1] 0.000000000 0.034883989 6.276181394 6.234293492 6.192405590 6.150517688 #> [7] 6.108629786 6.066741884 6.024853982 5.982966080 5.941078178 5.899190276 #> [13] 5.857302374 5.815414472 5.773526570 5.731638668 0.977361785 5.647862864 #> [19] 5.605974962 5.564087060 5.522199157 5.480311255 5.438423353 5.396535451 #> [25] 5.263987662 5.389531539 5.044072897 5.228983843 5.413894789 5.310356716 #> [31] 5.314413470 5.589506683 6.062266211 0.188495559 0.468358212 6.237878106 #> [37] 0.139603744 0.097715842 0.055827940 0.013940038 6.255237443 6.213349541 #> [43] 6.171461639 6.129573737 6.087685835 6.045797933 6.003910031 5.962022129 #> [49] 6.146933075 0.327876120 0.756795609 0.855282692 0.813394790 0.998305736 #> [55] 1.183216682 0.914529932 0.872642030 0.830754128 0.543887563 0.746978324 #> [61] 0.705090422 0.663202520 0.711974505 0.502654825 0.537538814 0.495650912 #> [67] 0.453763010 0.411875108 0.369987206 0.328099304 0.286211402 0.244323499 #> [73] 0.202435597 0.160547695 0.118659793 0.076771891 4.747272970 6.276181394 #> [79] 6.234293492 6.192405590 6.150517688 0.052243327 5.914092556 5.948082091 #> [85] 6.209764928 6.093727506 0.010796088 6.102281037 0.098958382 0.366399313 #> [91] 0.233851524 0.191963622 0.008178665 5.682746853 5.729235737 5.522199157 #> [97] 5.327661927 5.438423353 5.396535451 5.431419441 5.389531539 5.497670593 #> [103] 5.394132521 5.432074604 5.297857367 3.532523810 5.061432235 4.866895005 #> [109] 4.977656431 4.935768529 4.893880627 4.851992725 4.975253500 5.875365638 #> [115] 0.013940038 6.028438595 6.213349541 6.171461639 6.129573737 0.356155510 #> [121] 1.333408953 1.291521051 1.249633149 1.207745247 0.939058496 1.422468374 #> [127] 1.158853432 0.875044961 0.771506888 0.589244000 0.761880604 0.645843182 #> [133] 0.678104800 0.788866226 0.888875379 0.781862313 2.233998847 0.538173386 #> [139] 0.414278038 0.537538814 6.150039933 5.794948277 5.909662251 5.757117128 #> [145] 6.083210162 0.059412553 0.102426445 6.258822057 0.083775804 0.195431685 #> #> $jb #> [1] 0.0000000000 6.2470750468 6.1112961339 6.1748545260 6.2294041528 #> [6] 6.1026340052 6.0665237449 6.0304134845 5.9943032241 5.9581929637 #> [11] 5.9220827033 5.8859724429 5.8498621825 5.8137519222 5.7776416618 #> [16] 5.7891145047 5.7054211410 5.6693108806 5.6332006202 5.5970903598 #> [21] 5.5609800995 5.5248698391 5.4887595787 5.4526493183 5.4165390579 #> [26] 5.4710886847 5.2536586499 5.3082082768 5.3627579036 5.2359877560 #> [31] 5.1998774956 5.1637672352 5.0369970876 5.0915467144 5.0554364541 #> [36] 5.1099860809 5.4098434264 5.8568588308 6.0551642462 6.0969104753 #> [41] 0.0314342050 0.2146306455 0.1448252778 0.0180551302 6.2651301770 #> [46] 6.2290199166 6.1929096562 6.0571307433 6.1661124149 6.0845788751 #> [51] 6.0484686147 5.8149627944 6.0669079811 0.0374589034 0.1201889876 #> [56] 0.2594729478 0.7554391155 0.9034543118 1.0471975512 1.0110872908 #> [61] 1.1548305302 1.0295266572 0.9027565097 0.8666462493 0.8305359889 #> [66] 0.7944257285 0.7583154681 0.7222052077 0.6860949473 0.6499846869 #> [71] 0.6138744266 0.5777641662 0.5416539058 0.5055436454 0.4694333850 #> [76] 0.4333231246 0.3972128642 0.3611026039 0.4246609960 0.1982221959 #> [81] 0.3434317099 0.1690784590 0.2712111891 0.0537811543 0.1083307812 #> [86] 0.1198036240 0.0361102604 0.0000000000 6.2470750468 6.2109647864 #> [91] 6.1748545260 6.2384129181 6.1026340052 5.9758638577 5.9828303812 #> [96] 5.9943032241 5.8675330765 6.1019362031 6.2077229973 6.2764896757 #> [101] 0.2053075572 0.2798545180 0.3712538158 0.1600508939 6.1329584896 #> [106] 6.0137069973 5.5970903598 5.3635845396 5.4342099519 5.3980996915 #> [111] 5.4526493183 5.4165390579 5.4710886847 5.4349784243 5.4031599831 #> [116] 5.3627579036 5.3266476432 5.3972730554 5.3436207350 5.1752400781 #> [121] 5.0915467144 5.0554364541 5.0193261937 5.0781676396 4.7672521731 #> [126] 4.9109954125 4.9745538046 4.9806719463 4.8026646313 4.4077837007 #> [131] 5.1486684402 6.2197068976 6.2290199166 6.1929096562 6.1567993958 #> [136] 6.1682722387 6.0845788751 0.4087844163 1.4798228737 1.2139007178 #> [141] 1.1370889659 1.1916385927 1.1555283324 1.1194180720 1.0833078116 #> [146] 1.0471975512 1.0110872908 0.9749770304 0.8912836668 0.6365044605 #> [151] 0.6867927495 0.5642839397 0.6525286739 0.6676555809 0.5423517079 #> [156] 0.7857635998 0.5593247997 0.7937279264 0.6774328187 0.5416539058 #> [161] 0.5962035326 0.3697647325 0.0845521210 6.1136689539 5.8332543391 #> [166] 5.7751963840 5.8342523301 5.9071608435 6.1468564817 0.0006978021 #> [171] 6.2477728489 0.3057263410 0.1176438002 0.0361102604 #> #> $johnniewalker #> [1] 0.00000000 6.24578539 6.20838548 6.17098557 6.25794065 6.09618574 #> [7] 6.05878583 6.02138592 5.98398601 5.94658609 5.90918618 5.87178627 #> [13] 5.83438636 5.79698644 5.75958653 5.96716528 5.68478671 5.64738679 #> [19] 5.60998688 5.57258697 5.53518706 5.49778714 5.46038723 5.42298732 #> [25] 5.38558741 5.34818749 5.31078758 5.02840901 5.23598776 5.19858784 #> [31] 5.16118793 5.12378802 5.08638811 5.04898819 5.01158828 4.97418837 #> [37] 5.45593457 6.00653726 6.18780629 0.35717840 0.07479983 0.03739991 #> [43] 0.00000000 6.24578539 6.20838548 6.17098557 0.09537901 6.09618574 #> [49] 6.05878583 6.02138592 5.98398601 5.94658609 6.15416484 5.87178627 #> [55] 0.47849627 0.96024247 1.04719755 1.25477630 0.97239773 0.93499781 #> [61] 0.89759790 0.86019799 0.82279808 0.78539816 0.74799825 0.71059834 #> [67] 0.67319843 0.63579851 0.59839860 0.56099869 0.52359878 0.48619886 #> [73] 0.44879895 0.41139904 0.37399913 0.33659921 0.29919930 0.26179939 #> [79] 0.22439948 0.18699956 0.14959965 0.11219974 0.07479983 0.03739991 #> [85] 0.00000000 6.24578539 6.20838548 6.17098557 6.13358566 6.09618574 #> [91] 6.05878583 6.02138592 5.98398601 5.94658609 5.90918618 5.87178627 #> [97] 5.83438636 5.79698644 6.00456519 5.47720796 5.68478671 5.64738679 #> [103] 5.85496554 5.81756563 5.99883467 6.14128825 6.24578539 6.06648843 #> [109] 6.02908851 5.81183510 5.77443519 5.73703528 5.48096642 5.44356651 #> [115] 5.28554293 5.58743563 5.08638811 4.26359003 5.01158828 4.97418837 #> [121] 4.93678846 4.89938854 4.86198863 5.06956738 4.78718881 4.74978889 #> [127] 5.30039158 6.24578539 5.96340682 6.17098557 6.13358566 6.09618574 #> [133] 0.02057919 0.63425600 1.27159703 1.23419711 1.19679720 1.62304490 #> [139] 0.65834977 1.08459746 1.04719755 1.47344525 1.21737639 0.93499781 #> [145] 0.89759790 0.61521933 0.57781941 0.19739556 0.28435064 0.12259573 #> [151] 0.20955082 0.17215090 6.23808280 6.20068289 0.05995117 0.24122020 #> [157] 0.44879895 0.41139904 0.37399913 0.33659921 0.29919930 0.26179939 #> [163] 0.46937814 0.18699956 0.14959965 0.11219974 0.07479983 0.03739991 #> #> $magallan #> [1] 0.000000000 6.193200430 0.143753184 6.104077234 6.126083800 6.014954038 #> [7] 5.970392440 6.204130501 5.881269244 5.903275810 5.792146049 5.880135983 #> [13] 5.703022853 5.782816249 5.685207122 5.569338059 5.524776461 5.622111918 #> [19] 5.435653265 5.462399132 5.346530069 5.301968471 5.399303928 5.212845276 #> [25] 5.310180732 5.123722080 5.007853017 5.034598884 4.990037286 5.078027220 #> [31] 5.420060204 5.839146215 5.918939612 6.111226775 6.032861633 5.970602768 #> [37] 6.204340829 0.018490979 6.239572628 0.014269576 0.123415508 0.103239319 #> [43] 0.558613024 0.821249993 1.135459066 1.157465631 1.211484547 1.001774272 #> [49] 0.880440783 1.077799753 0.726192423 0.752220415 0.778966282 0.734404684 #> [55] 0.444864423 0.573974024 0.600719890 0.556158293 0.511596695 0.400466933 #> [61] 0.144173840 0.377911901 0.262042838 0.288788705 0.102330052 0.199665509 #> [67] 0.088535747 0.110542313 6.224811028 6.227832533 6.260042827 6.073584174 #> [73] 6.170919631 5.984460978 6.081796435 6.037234837 5.921365774 5.948111641 #> [79] 5.903550043 5.858988445 5.814426847 5.967260809 5.867200706 6.085633840 #> [85] 0.008690775 0.093831714 0.191167171 0.004708518 6.078183550 5.413372466 #> [91] 5.510707923 5.456800803 5.490781006 5.235126074 5.417363325 5.212571042 #> [97] 4.959544226 5.056879683 5.012318085 5.109653542 4.923194889 4.878633291 #> [103] 4.834071693 4.789510095 4.744948497 5.343888008 6.015528295 6.182060030 #> [109] 6.208805897 0.685809578 1.335986256 1.291424658 1.246863060 1.202301462 #> [115] 1.091171701 0.971281212 1.068616669 1.024055071 1.224472136 0.793034820 #> [121] 0.692974717 1.167559233 0.458223141 0.690117319 0.390373331 0.809459342 #> [127] 0.301250135 0.007101612 5.709914083 5.987103039 6.013848906 6.131723024 #> [133] 0.110652439 0.169172449 0.133956374 0.221946308 0.177384710 0.132823112 #> [139] 0.088261514 0.176251449 6.282323626 #> #> $makersmark #> [1] 0.000000000 0.161897338 0.186327271 2.249699824 0.432311942 0.381108205 #> [7] 0.430511776 0.536910609 0.698807947 2.036710492 0.353644051 0.461485884 #> [13] 0.359419499 0.465818331 1.859219381 0.252924832 0.444225458 0.253235853 #> [19] 0.217737631 0.308327504 1.646230049 0.111242965 0.087578510 6.252124363 #> [25] 0.075337888 1.468738938 6.145629697 6.110131475 0.002541279 6.191784359 #> [31] 6.003636808 1.255749606 6.143733697 6.264315976 6.228817754 6.193319532 #> [37] 1.078258496 6.076899808 0.387012565 0.839212297 0.936265607 0.900767385 #> [43] 0.865269163 0.829770941 0.794272719 0.758774497 0.723276275 0.687778053 #> [49] 0.652279831 0.616781609 0.581283386 0.545785164 0.652183997 0.474788720 #> [55] 0.439290498 0.403792276 0.579387387 0.851941946 1.589794278 0.261799388 #> [61] 1.475346938 1.329191495 1.465498657 1.463803978 0.084308277 1.487054850 #> [67] 1.584108160 1.337516605 1.360462388 1.477613494 6.154504252 1.406617050 #> [73] 1.218469499 1.124527272 1.300122383 5.977013142 1.096574407 1.193627717 #> [79] 0.947036162 1.122631273 0.945235996 5.764023809 1.016136607 0.753839537 #> [85] 0.945140163 0.756992612 5.586532699 0.838645497 0.955796603 0.767649052 #> [91] 1.075174771 1.063826442 5.373543367 1.119597533 1.245853568 1.469760420 #> [97] 1.434262198 5.196052256 1.398711895 0.761437835 1.162566773 1.127068551 #> [103] 0.377479630 4.983062924 0.163868256 0.199677499 0.230747441 0.270578110 #> [109] 4.805571813 0.190236143 0.022186389 0.139337495 0.272940499 6.198877030 #> [115] 4.592582481 6.127880586 6.245031692 6.123452305 6.021385919 4.415091371 #> [121] 6.082941008 6.047442785 5.879393031 5.772587344 5.879704052 4.202102038 #> [127] 5.737400143 5.701901921 5.666403699 5.828301036 4.024610928 5.701806087 #> [133] 6.135136775 0.498223949 0.741025386 0.705527164 3.811621595 0.634530720 #> [139] 0.599032498 0.885284830 1.470036094 1.836535310 3.598632263 1.992337714 #> [145] 1.804190163 1.921341270 1.674749714 3.421141152 1.814846604 1.976743941 #> [151] 1.532756826 1.708351937 1.406601666 3.208151820 1.601857271 1.489587158 #> [157] 1.530860827 1.353465550 3.030660710 1.357797997 1.256316406 1.353369717 #> [163] 1.120475935 1.140476218 2.817671377 1.211376828 0.964785273 1.140380384 #> [169] 1.365484554 2.640180267 0.807086870 0.038317133 5.973777186 0.584367111 #> [175] 0.230849661 2.427190934 6.153534852 #> #> $oban #> [1] 0.000000000 6.189327891 6.154226297 6.119124703 6.084023109 6.048921515 #> [7] 6.072575744 5.978718327 5.943616733 5.908515139 5.873413546 5.838311952 #> [13] 5.913867579 5.768108764 5.733007170 5.697905576 5.662803982 5.627702388 #> [19] 5.592600794 5.557499200 5.522397607 5.546051835 5.452194419 5.417092825 #> [25] 5.381991231 5.346889637 5.311788043 5.276686449 5.241584855 5.206483262 #> [31] 5.171381668 5.136280074 5.101178480 5.066076886 5.030975292 4.995873698 #> [37] 4.960772104 5.264963125 5.800322074 6.067492979 6.160071388 6.137391516 #> [43] 6.196603873 0.002671967 6.133646935 6.215654086 6.180552492 6.145450898 #> [49] 6.165847810 6.199602705 6.150803338 6.129399517 6.144615128 6.256591889 #> [55] 6.258510411 0.300282839 0.831096131 1.206400973 1.046944385 1.011842791 #> [61] 0.976741197 0.941639603 0.795880788 0.871436415 0.836334822 0.801233228 #> [67] 0.766131634 0.731030040 0.695928446 0.660826852 0.625725258 0.590623664 #> [73] 0.444864849 0.520420477 0.485318883 0.450217289 0.415115695 0.380014101 #> [79] 0.344912507 0.309810913 0.164052098 0.239607725 0.204506131 0.169404538 #> [85] 0.134302944 0.099201350 0.064099756 6.201526248 6.277081875 6.241980281 #> [91] 6.206878688 6.171777094 6.026018279 6.101573906 6.066472312 6.031370718 #> [97] 5.871914130 5.961167530 5.926065936 6.001621564 6.100841412 6.211368198 #> [103] 0.009572758 0.025971975 0.158913406 0.315119168 0.147466041 6.117250096 #> [109] 5.820028661 5.595446909 5.504846810 5.469745216 5.434643622 5.458297851 #> [115] 5.364440434 5.204983846 5.404894467 5.376244397 5.224034058 5.407601410 #> [121] 5.270939615 5.118729277 5.207982677 5.159183310 5.072180318 4.733344238 #> [127] 4.943221307 4.908119713 4.814262297 4.837916526 4.678459937 4.767713338 #> [133] 4.791367567 5.549476477 5.988226220 6.087446068 6.104245872 6.252255096 #> [139] 6.203455729 0.133282277 0.820249013 1.275104745 1.240003151 1.263657380 #> [145] 1.169799964 1.134698370 1.099596776 1.239167381 0.918736367 0.994291994 #> [151] 0.848533179 0.806980062 0.764632218 0.743228397 0.694429030 0.724926608 #> [157] 0.637923616 0.602822022 0.802732644 0.584520232 0.608174461 0.573072867 #> [163] 0.537971273 0.392212458 0.467768086 0.110915937 6.066087253 5.783478557 #> [169] 5.683251799 5.848803083 5.925680878 6.146471565 6.148390087 0.027498746 #> [175] 6.282828709 0.192307774 0.046548959 0.011447365 6.259531078 #> #> $oldpotrero #> [1] 0.00000000 6.20638390 6.15842066 0.03093063 0.10105941 0.15617777 #> [7] 0.20252848 0.33767605 0.23095698 0.18299373 0.13503049 0.20417598 #> [13] 0.03910399 6.27432605 6.22636281 6.23715538 6.13043631 6.08247307 #> [19] 6.03450982 6.04530240 5.93858333 5.89062008 5.84265683 5.79469359 #> [25] 5.74673034 5.80942431 6.00957452 0.18819469 0.42426404 0.57585618 #> [31] 0.38779121 0.58148989 0.53997817 0.49201492 0.43035390 0.44798982 #> [37] 0.45878240 0.41081915 0.36285591 0.37731147 0.58867997 0.34332116 #> [43] 0.49275348 0.46233229 0.58217493 0.73573945 1.22819571 1.61264024 #> [49] 1.33691102 1.40605652 1.35809327 1.19947281 1.26216678 1.21420353 #> [55] 1.16624029 1.11827704 1.01155797 1.02235055 0.97438730 0.92642405 #> [61] 0.87846081 0.70614257 0.78253432 0.73457107 0.68660782 0.63864458 #> [67] 0.59068133 0.76138703 0.83404745 0.96593770 0.90592685 1.01190826 #> [73] 0.90518920 0.89843971 0.79497796 0.82005528 0.59794809 0.18744061 #> [79] 0.33687292 0.18582807 0.09386807 6.15441794 6.21711191 6.05849144 #> [85] 6.06928402 5.96256495 6.02525892 5.86663846 5.81867521 5.88782071 #> [91] 5.72274872 5.67478547 5.75117722 5.46175023 5.40654074 5.48293248 #> [97] 5.79373991 5.20165804 5.33904274 6.15324955 0.42007005 0.48276402 #> [103] 0.43480078 0.51119253 0.44953151 1.25616270 1.81374412 2.12455154 #> [109] 1.39606707 1.79420937 1.73254835 1.69828288 1.41530742 1.47800139 #> [115] 1.21136920 1.38207490 1.33411165 1.28614840 1.23818516 1.19022191 #> [121] 1.03160144 1.03553960 1.04633217 0.87401393 0.83974846 0.65746377 #> [127] 0.43625486 0.56153728 0.25145419 0.10830210 0.07462359 #> #> $redbreast #> [1] 0.00000000 0.31063774 0.19199829 0.32869088 0.58464945 0.35175567 #> [7] 0.51365301 0.47815479 0.44265656 0.40715834 0.37166012 0.33616190 #> [13] 0.30066368 0.46256101 0.22966723 0.19416901 0.15867079 0.12317257 #> [19] 0.08767434 0.05217612 0.01667790 6.26436498 6.22886676 0.10757879 #> [25] 6.15787032 6.12237210 6.08687387 6.05137565 6.21327299 5.98037921 #> [31] 5.94488099 5.90938276 5.87388454 5.94904354 5.80288810 5.76738988 #> [37] 5.73189165 6.01814399 0.40808673 0.53250163 0.63253112 0.64461600 #> [43] 0.69585612 0.57361956 0.73551690 0.45504001 0.66452045 0.38404357 #> [49] 0.59352401 0.55802579 0.52252756 0.48702934 0.45153112 0.66101156 #> [55] 0.38053468 0.34503645 0.50693379 0.27404001 0.48352045 0.30271222 #> [61] 0.41252401 0.32944268 0.47705528 0.77988068 1.39895322 1.56085056 #> [67] 1.52535234 1.48985412 1.45435589 1.41885767 1.38335945 1.34786123 #> [73] 1.31236300 1.03188612 1.24136656 1.20586834 1.17037012 1.13487189 #> [79] 1.09937367 1.06387545 1.02837723 0.99287901 0.95738078 0.92188256 #> [85] 0.88638434 0.85088612 0.81538790 0.77988967 0.74439145 0.60922458 #> [91] 0.87079057 0.63789679 0.60239856 0.56690034 0.53140212 0.49590390 #> [97] 0.46040568 0.42490745 0.71115979 0.55130657 0.85883229 0.92641567 #> [103] 1.03281451 1.13921334 1.20679673 1.03697706 1.01517661 0.74466617 #> [109] 0.49807462 0.37943517 6.24661587 6.21111765 6.17561943 5.94272565 #> [115] 6.10462298 6.06912476 6.03362654 5.99812832 6.16002566 6.14580082 #> [121] 6.08902921 5.85613543 6.01803277 5.78513899 5.86029799 5.71414254 #> [127] 5.92362298 5.64314610 5.49699065 5.57214965 5.53665143 5.50115321 #> [133] 5.46565499 5.62755233 5.39465854 5.35916032 0.05267380 0.57577490 #> [139] 0.34288111 0.50477845 0.46928023 0.54443923 0.59567935 1.00628667 #> [145] 1.65310501 1.86258545 1.82708722 1.59419344 1.75609078 1.72059256 #> [151] 1.88248990 1.84699167 1.36911923 1.57859967 1.43244423 1.31020767 #> [157] 1.47210500 1.19162812 1.30143991 1.12063167 1.13271656 1.09721833 #> [163] 1.25911567 1.22361745 1.18811923 1.15262101 1.31451834 1.08162456 #> [169] 1.24352190 0.81323256 0.73015123 0.47598406 6.26002354 6.25576515 #> [175] 6.22026693 6.17107093 6.14927049 #> #> $tamdhu #> [1] 0.00000000 6.16765540 6.13195549 6.09625557 6.06055566 6.10162763 #> [7] 5.98915582 5.95345591 5.91775599 5.88205607 6.01150483 5.81065624 #> [13] 5.77495632 5.73925641 5.70355649 5.66785657 5.63215666 5.74910607 #> [19] 5.56075682 5.52505691 5.48935699 5.45365707 5.50109839 5.38225724 #> [25] 5.34655733 5.31085741 5.27515749 5.32259881 5.20375766 5.16805774 #> [31] 5.13235783 4.93150923 5.06095799 4.79845923 4.74457950 4.95385824 #> [37] 5.16313699 5.47046101 5.86589984 6.03308390 6.02440443 5.98870452 #> [43] 6.19161392 6.23905524 6.11661698 6.16765540 6.13195549 6.09625557 #> [49] 6.06055566 6.10799697 6.07229705 6.11860458 6.00089722 6.27684719 #> [55] 6.21352999 0.09420015 0.36782907 0.76061538 0.82601883 1.18226644 #> [61] 1.08491635 1.12904642 0.92819783 0.81266793 0.62431868 0.74126809 #> [67] 0.87071686 0.51721893 0.63416834 0.59846843 0.56276851 0.52706860 #> [73] 0.49136868 0.45566876 0.41996885 0.38426893 0.34856901 0.22972786 #> [79] 0.27716918 0.24146926 0.20576935 0.17006943 0.13436951 6.21670623 #> [85] 0.22811836 0.02726976 6.27475515 6.07390656 6.20335532 6.16765540 #> [91] 6.13195549 6.09625557 6.06055566 6.02485574 5.82400714 5.95345591 #> [97] 5.84098410 5.88205607 5.92312805 6.05563490 6.07345525 6.06100696 #> [103] 6.27028571 0.02817238 0.04370963 0.05108649 0.01038662 6.02440363 #> [109] 5.88414811 5.61880575 5.41795716 5.22960791 5.34655733 5.22771618 #> [115] 5.27515749 5.32259881 5.35640699 5.33320642 5.21549906 5.24930724 #> [121] 5.22610667 5.10202997 4.98955816 5.11900692 4.99493022 5.06231191 #> [127] 4.68160982 4.65840925 4.85849989 4.73965874 4.70395883 4.91323757 #> [133] 5.70400860 6.08451417 6.13195549 6.09625557 6.24040916 6.10162763 #> [139] 0.02772107 0.77741932 1.20536701 1.25280832 1.05719528 1.18140849 #> [145] 1.30754601 0.95009554 0.81131401 0.95546759 0.84299579 0.71891908 #> [151] 0.76853786 0.72952670 0.77696801 0.82440933 0.62242695 0.66986826 #> [157] 0.38918968 0.59846843 0.63954040 0.69221727 0.49136868 0.30301943 #> [163] 6.23950654 6.20380663 6.09133482 5.85823934 5.90465886 5.89585828 #> [169] 6.04143468 6.20827607 6.25240614 0.02189771 6.18100631 0.11041100 #> [175] 0.07471108 0.03901116 #> #> $wildturkey #> [1] 0.00000000 6.14248647 6.10852331 6.07456014 6.04059698 6.00663382 #> [7] 5.97267065 5.93870749 5.90474432 5.87078116 6.06361684 5.80285483 #> [13] 5.76889167 5.73492850 5.70096534 5.66700218 5.63303901 5.59907585 #> [19] 5.56511269 5.53114952 5.49718636 5.46322319 5.64035336 5.39529687 #> [25] 5.36133370 5.32737054 5.29340738 5.25944421 5.22548105 5.19151788 #> [31] 5.15755472 5.33468489 5.08962839 4.84457190 4.55805446 4.79034334 #> [37] 4.95377574 5.13090591 5.58058769 5.99027480 6.11041975 6.20210692 #> [43] 6.16814375 0.00364461 6.25286675 5.99210474 6.18494043 6.15097726 #> [49] 6.11701410 6.08305093 6.04908777 6.01512461 5.98116144 6.15829161 #> [55] 5.91323511 5.87927195 5.99795812 6.03814447 6.00418131 6.00402169 #> [61] 0.21166899 0.55821220 0.92914082 0.96648512 1.22838833 1.05405018 #> [67] 0.79328817 0.75932500 0.72536184 0.69139868 0.65743551 0.62347235 #> [73] 0.58950919 0.55554602 0.52158286 0.48761969 0.45365653 0.41969337 #> [79] 0.38573020 0.35176704 0.31780388 0.21253325 0.11732602 0.21591438 #> [85] 0.18195122 0.14798806 0.11402489 0.08006173 0.04609856 0.01213540 #> [91] 6.26135754 6.22739438 6.19343122 6.15946805 6.12550489 6.09154172 #> [97] 6.05757856 6.02361540 5.98965223 5.72889022 5.92172591 5.88776274 #> [103] 6.06489291 5.89114388 6.08437218 0.05672738 0.10073085 0.30562554 #> [109] 0.47398401 0.07068718 0.28170268 6.01177871 6.00810931 5.77870371 #> [115] 5.44624161 5.63907730 5.37831528 5.34435212 5.53718781 5.27642579 #> [121] 5.24246263 5.35039652 5.17453630 5.14057314 5.10660997 5.07264681 #> [127] 5.26548249 5.00472048 4.97075732 4.93679416 4.90283099 4.86886783 #> [133] 4.44011354 5.14396544 4.76697834 4.73301517 4.69905201 4.66508884 #> [139] 4.70243315 5.22595880 5.90719683 6.10003252 6.06606935 6.03210619 #> [145] 5.99814302 6.11682919 6.27324064 1.04196750 1.14990139 1.11593822 #> [151] 0.85517621 1.04801190 0.88149720 1.19117890 1.09877173 0.91215924 #> [157] 0.66710274 0.84423291 0.81026975 0.77630659 0.74234342 0.70838026 #> [163] 0.44761825 0.64045393 0.60649077 0.57252760 0.39666739 0.42782938 #> [169] 0.47063811 0.43667495 0.19161845 0.36874862 6.25079693 6.24098366 #> [175] 6.03089832 5.62002589 5.57729102 5.58598489 5.58534272 5.80889114 #> [181] 6.06796579 6.15965296 6.05154028 6.24437596 6.21041280 #> #> $yoichi #> [1] 0.00000000 6.23210250 6.18101969 6.12993689 6.07885408 6.16966832 #> [7] 5.97668846 5.92560566 5.87452285 5.82344004 5.77235723 5.72127443 #> [13] 5.67019162 5.61910881 5.56802600 5.51694320 5.46586039 5.41477758 #> [19] 5.36369477 5.24130450 5.32809732 5.21044635 5.15936354 5.10828074 #> [25] 5.05719793 5.34913906 6.03587132 6.26365250 0.07390956 0.02282675 #> [31] 0.03831211 6.14605961 6.21933180 6.16824899 6.11716618 6.13739084 #> [37] 6.01500057 6.03048592 5.98414242 6.05914771 6.21556113 0.39150192 #> [43] 0.99611474 0.94503194 0.89394913 0.84286632 0.79178351 0.74070071 #> [49] 0.62304974 0.63853509 0.58745228 0.53636948 0.48528667 0.43420386 #> [55] 0.38312106 0.33203825 0.28095544 0.16330447 0.17878983 0.12770702 #> [61] 0.07662421 0.02554140 6.25764390 6.20656110 6.08891012 6.10439548 #> [67] 6.05331267 6.00222987 5.95114706 5.83349609 5.84898144 5.79789864 #> [73] 5.81338399 5.82828455 6.04954200 6.05721502 6.20845384 0.19101021 #> [79] 0.29130285 6.21165446 5.54924670 5.28707056 5.23598776 5.18490495 #> [85] 5.13382214 5.15404680 4.96508836 4.78317816 4.92949091 4.81183994 #> [91] 4.82732530 4.91813954 5.85932885 6.10297615 6.19379039 6.14270759 #> [97] 6.09162478 6.23793753 0.75792407 1.15467991 1.24147273 1.05725360 #> [103] 1.07273895 1.28225854 0.97057334 0.85292237 0.86840773 0.81732492 #> [109] 0.76624211 0.64859114 0.25918471 6.03400894 5.71092702 5.87891268 #> [115] 6.06818963 6.20189044 0.14648632 0.23992868 0.25541404 0.20433123 #> [121] 0.15324842 0.10216561 0.11765097 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the area of a shape — coo_area","title":"Calculates the area of a shape — coo_area","text":"Calculates area (non-crossing) shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the area of a shape — coo_area","text":"","code":"coo_area(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the area of a shape — coo_area","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the area of a shape — coo_area","text":"numeric, area.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the area of a shape — coo_area","text":"Using area.poly gpc package good idea, licence impedes Momocs rely . function , gpc loaded: area.poly((coo, 'gpc.poly'))","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the area of a shape — coo_area","text":"","code":"coo_area(bot[1]) #> [1] 234515 # for the distribution of the area of the bottles dataset hist(sapply(bot$coo, coo_area), breaks=10)"},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots (lollipop) differences between two configurations — coo_arrows","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"Draws 'arrows' two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"","code":"coo_arrows(coo1, coo2, length = coo_centsize(coo1)/15, angle = 20, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"coo1 list matrix coordinates. coo2 list matrix coordinates. length length arrows. angle angle arrows ... optional parameters fed arrows.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"","code":"coo_arrows(coo_sample(olea[3], 50), coo_sample(olea[6], 50)) #> Warning: zero-length arrow is of indeterminate angle and so skipped title(\"Hi there !\")"},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":null,"dir":"Reference","previous_headings":"","what":"Register new baselines — coo_baseline","title":"Register new baselines — coo_baseline","text":"non-exact baseline registration t1 t2 coordinates, ldk1-th ldk2-th points. default returns Bookstein's coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register new baselines — coo_baseline","text":"","code":"coo_baseline(coo, ldk1, ldk2, t1, t2)"},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register new baselines — coo_baseline","text":"coo matrix (x; y) coordinates Coo object. ldk1 numeric id first point new baseline ldk2 numeric id second point new baseline t1 numeric (x; y) coordinates 1st point new baseline t2 numeric (x; y) coordinates 2nd point new baseline","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register new baselines — coo_baseline","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register new baselines — coo_baseline","text":"","code":"h <- hearts %>% slice(1:5) # for speed sake stack(h) stack(coo_baseline(h, 2, 4, c(-1, 0), c(1, 1)))"},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":null,"dir":"Reference","previous_headings":"","what":"Register Bookstein's coordinates — coo_bookstein","title":"Register Bookstein's coordinates — coo_bookstein","text":"Registers new baseline shape, ldk1-th ldk2-th points set \\((x= -0.5; y=0)\\) \\((x= 0.5; y=0)\\), respectively.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register Bookstein's coordinates — coo_bookstein","text":"","code":"coo_bookstein(coo, ldk1, ldk2)"},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register Bookstein's coordinates — coo_bookstein","text":"coo matrix (x; y) coordinates Coo object. ldk1 numeric id first point new baseline (first, default) ldk2 numeric id second point new baseline (last, default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register Bookstein's coordinates — coo_bookstein","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Register Bookstein's coordinates — coo_bookstein","text":", tries using $ldk slot. Also case Opn, landmark defined, first last point shape. Opn defines first landmark first point new shapes coo_slide.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register Bookstein's coordinates — coo_bookstein","text":"","code":"h <- hearts %>% slice(1:5) # for the sake of speed stack(h) stack(coo_bookstein(h, 2, 4)) h <- hearts[1] coo_plot(h) coo_plot(coo_bookstein(h, 20, 57), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates coordinates of the bounding box — coo_boundingbox","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"Calculates coordinates bounding box","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"","code":"coo_boundingbox(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"data.frame coordinates bounding box","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"","code":"bot[1] %>% coo_boundingbox() #> # A tibble: 1 × 4 #> x0 x1 y0 y1 #> #> 1 33 316 14 1102 bot %>% coo_boundingbox() #> # A tibble: 40 × 4 #> x0 x1 y0 y1 #> * #> 1 33 316 14 1102 #> 2 51 312 26 1020 #> 3 48 291 11 654 #> 4 90 277 16 822 #> 5 36 323 53 939 #> 6 58 298 11 617 #> 7 54 268 5 870 #> 8 40 292 25 790 #> 9 67 297 17 759 #> 10 40 307 21 1069 #> # ℹ 30 more rows"},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the calliper length — coo_calliper","title":"Calculates the calliper length — coo_calliper","text":"Also called Feret's diameter, longest distance two points shape provided.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the calliper length — coo_calliper","text":"","code":"coo_calliper(coo, arr.ind = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the calliper length — coo_calliper","text":"coo matrix (x; y) coordinates Coo arr.ind logical, see .","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the calliper length — coo_calliper","text":"numeric, centroid size. arr.ind=TRUE, data_frame.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the calliper length — coo_calliper","text":"","code":"b <- bot[1] coo_calliper(b) #> [1] 1088.166 p <- coo_calliper(b, arr.ind=TRUE) p #> # A tibble: 1 × 2 #> length arr_ind #> #> 1 1088. p$length #> [1] 1088.166 ids <- p$arr_ind[[1]] coo_plot(b) segments(b[ids[1], 1], b[ids[1], 2], b[ids[2], 1], b[ids[2], 2], lty=2) # on a Coo bot %>% coo_sample(32) %>% # for speed sake coo_calliper() #> $brahma #> [1] 1087.768 #> #> $caney #> [1] 992.2107 #> #> $chimay #> [1] 644.5991 #> #> $corona #> [1] 806.6778 #> #> $deusventrue #> [1] 880.8053 #> #> $duvel #> [1] 606.7462 #> #> $franziskaner #> [1] 863.4501 #> #> $grimbergen #> [1] 766.5801 #> #> $guiness #> [1] 743.6162 #> #> $hoegardeen #> [1] 1046.608 #> #> $jupiler #> [1] 981.2747 #> #> $kingfisher #> [1] 717.4761 #> #> $latrappe #> [1] 746.2345 #> #> $lindemanskriek #> [1] 819.0562 #> #> $nicechouffe #> [1] 686.7001 #> #> $pecheresse #> [1] 927.4034 #> #> $sierranevada #> [1] 655.6706 #> #> $tanglefoot #> [1] 690.334 #> #> $tauro #> [1] 983.9842 #> #> $westmalle #> [1] 765.7114 #> #> $amrut #> [1] 864.1209 #> #> $ballantines #> [1] 711.5118 #> #> $bushmills #> [1] 882.1485 #> #> $chivas #> [1] 794.3198 #> #> $dalmore #> [1] 683.668 #> #> $famousgrouse #> [1] 607.8199 #> #> $glendronach #> [1] 821.1796 #> #> $glenmorangie #> [1] 986.0183 #> #> $highlandpark #> [1] 705.139 #> #> $jackdaniels #> [1] 798.2042 #> #> $jb #> [1] 1011.163 #> #> $johnniewalker #> [1] 337.8772 #> #> $magallan #> [1] 756.595 #> #> $makersmark #> [1] 858.3298 #> #> $oban #> [1] 858.7974 #> #> $oldpotrero #> [1] 596.5668 #> #> $redbreast #> [1] 425.3011 #> #> $tamdhu #> [1] 1007.425 #> #> $wildturkey #> [1] 1099.426 #> #> $yoichi #> [1] 714.077 #> bot %>% coo_sample(32) %>% # for speed sake coo_calliper(arr.ind=TRUE) #> # A tibble: 40 × 2 #> length arr_ind #> * #> 1 1088. #> 2 992. #> 3 645. #> 4 807. #> 5 881. #> 6 607. #> 7 863. #> 8 767. #> 9 744. #> 10 1047. #> # ℹ 30 more rows"},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns the distance between everypoints and the centroid — coo_centdist","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"every point shape, returns (centroid-points) distance.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"","code":"coo_centdist(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"","code":"b <- coo_sample(bot[1], 64) d <- coo_centdist(b) barplot(d, xlab=\"Points along the outline\", ylab=\"Distance to the centroid (pixels)\")"},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":null,"dir":"Reference","previous_headings":"","what":"Centers coordinates — coo_center","title":"Centers coordinates — coo_center","text":"Returns shape centered origin. two functions strictly equivalent.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Centers coordinates — coo_center","text":"","code":"coo_center(coo) coo_centre(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Centers coordinates — coo_center","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Centers coordinates — coo_center","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Centers coordinates — coo_center","text":"","code":"coo_plot(bot[1]) # same as coo_plot(coo_centre(bot[1])) # this coo_plot(coo_center(bot[1])) # on Coo objects b <- slice(bot, 1:5) # speed sake stack(slice(b, 1:5)) stack(coo_center(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate centroid coordinates — coo_centpos","title":"Calculate centroid coordinates — coo_centpos","text":"Returns (x; y) centroid coordinates shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate centroid coordinates — coo_centpos","text":"","code":"coo_centpos(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate centroid coordinates — coo_centpos","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate centroid coordinates — coo_centpos","text":"(x; y) coordinates centroid vector matrix.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate centroid coordinates — coo_centpos","text":"","code":"b <- bot[1] coo_plot(b) xy <- coo_centpos(b) points(xy[1], xy[2], cex=2, col='blue') # on a Coo coo_centpos(bot) #> x y #> brahma 175.0580 543.8696 #> caney 182.7083 507.7560 #> chimay 169.0106 314.8095 #> corona 185.0155 407.2326 #> deusventrue 179.5592 467.2632 #> duvel 179.2484 287.1180 #> franziskaner 161.3548 423.2016 #> grimbergen 166.7460 394.8651 #> guiness 182.2022 372.0546 #> hoegardeen 173.2539 526.9275 #> jupiler 175.6026 510.9744 #> kingfisher 161.8407 365.2253 #> latrappe 176.0368 344.0147 #> lindemanskriek 163.9261 405.4034 #> nicechouffe 170.5548 338.1233 #> pecheresse 175.3023 489.5271 #> sierranevada 166.5795 333.5682 #> tanglefoot 174.5862 346.1724 #> tauro 175.5230 511.7644 #> westmalle 161.7943 383.0000 #> amrut 162.7225 420.5654 #> ballantines 174.2260 329.5000 #> bushmills 180.8303 432.3697 #> chivas 182.0244 405.7500 #> dalmore 176.4258 328.0452 #> famousgrouse 174.1065 299.2071 #> glendronach 173.2792 409.4365 #> glenmorangie 177.2514 493.9385 #> highlandpark 167.4852 346.6272 #> jackdaniels 182.8867 387.7600 #> jb 172.6149 509.0057 #> johnniewalker 174.4940 165.5655 #> magallan 167.2482 388.9149 #> makersmark 176.4802 402.7571 #> oban 176.5307 447.6536 #> oldpotrero 165.9160 284.7634 #> redbreast 176.8305 202.1977 #> tamdhu 173.7955 530.5625 #> wildturkey 173.7243 537.4973 #> yoichi 181.2764 361.1545"},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates centroid size — coo_centsize","title":"Calculates centroid size — coo_centsize","text":"Calculates centroid size","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates centroid size — coo_centsize","text":"","code":"coo_centsize(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates centroid size — coo_centsize","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates centroid size — coo_centsize","text":"numeric, centroid size.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates centroid size — coo_centsize","text":"function can used integrate size - meaningful - Coo objects. See also coo_length rescale.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates centroid size — coo_centsize","text":"","code":"coo_centsize(bot[1]) #> [1] 364.1006 # on a Coo coo_centsize(bot) #> brahma caney chimay corona deusventrue #> 364.1006 332.6606 232.2377 267.1846 300.2182 #> duvel franziskaner grimbergen guiness hoegardeen #> 220.3785 289.6220 268.2272 256.6651 353.2312 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 325.0180 238.2959 275.5208 275.0680 230.9909 #> pecheresse sierranevada tanglefoot tauro westmalle #> 310.0406 230.7661 248.5782 325.6573 255.6335 #> amrut ballantines bushmills chivas dalmore #> 287.7783 259.1542 297.9153 283.8156 247.1982 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 204.7011 274.2665 328.5136 252.6141 274.6856 #> jb johnniewalker magallan makersmark oban #> 340.9851 114.5988 244.4261 297.1638 283.9853 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 208.3185 150.1516 337.8220 374.5002 249.7048 # add it to $fac mutate(bot, size=coo_centsize(bot)) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 40 × 3 #> type fake size #> #> 1 whisky a 364. #> 2 whisky a 333. #> 3 whisky a 232. #> 4 whisky a 267. #> 5 whisky a 300. #> 6 whisky a 220. #> # ℹ 34 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks shapes — coo_check","title":"Checks shapes — coo_check","text":"simple utility, used internally, mostly coo functions methods. Returns matrix coordinates, passed either list matrix coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks shapes — coo_check","text":"","code":"coo_check(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks shapes — coo_check","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks shapes — coo_check","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks shapes — coo_check","text":"","code":"#coo_check('Not a shape') #coo_check(iris) #coo_check(matrix(1:10, ncol=2)) #coo_check(list(x=1:5, y=6:10))"},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the (recursive) convex hull of a shape — coo_chull","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull returns ids points define convex hull shape. simple wrapper around chull, mainly used graphical functions.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"","code":"coo_chull(coo) # S3 method for default coo_chull(coo) # S3 method for Coo coo_chull(coo) coo_chull_onion(coo, close = TRUE) # S3 method for default coo_chull_onion(coo, close = TRUE) # S3 method for Coo coo_chull_onion(coo, close = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo matrix (x; y) coordinates Coo. close logical whether close onion rings (TRUE default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull returns matrix points defining convex hull shape; list Coo. coo_chull_onion returns list successive onions rings, list lists Coo.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull_onion recursively find convex hull, remove , less 3 points left.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"","code":"# coo_chull h <- coo_sample(hearts[4], 32) coo_plot(h) ch <- coo_chull(h) lines(ch, col='red', lty=2) bot %>% coo_chull #> $brahma #> [,1] [,2] #> [1,] 316 124 #> [2,] 316 113 #> [3,] 315 92 #> [4,] 311 71 #> [5,] 307 60 #> [6,] 290 40 #> [7,] 269 27 #> [8,] 259 24 #> [9,] 238 18 #> [10,] 217 16 #> [11,] 196 15 #> [12,] 164 14 #> [13,] 143 15 #> [14,] 111 19 #> [15,] 90 25 #> [16,] 80 29 #> [17,] 59 45 #> [18,] 47 66 #> [19,] 44 77 #> [20,] 40 98 #> [21,] 33 624 #> [22,] 33 645 #> [23,] 34 656 #> [24,] 105 1082 #> [25,] 120 1098 #> [26,] 131 1100 #> [27,] 173 1102 #> [28,] 183 1102 #> [29,] 205 1101 #> [30,] 226 1096 #> [31,] 232 1087 #> [32,] 307 681 #> [33,] 310 660 #> [34,] 311 629 #> #> $caney #> [,1] [,2] #> [1,] 312 392 #> [2,] 310 130 #> [3,] 305 89 #> [4,] 297 69 #> [5,] 291 60 #> [6,] 281 52 #> [7,] 263 42 #> [8,] 243 35 #> [9,] 213 29 #> [10,] 184 26 #> [11,] 164 26 #> [12,] 134 29 #> [13,] 124 31 #> [14,] 113 34 #> [15,] 94 42 #> [16,] 84 47 #> [17,] 75 53 #> [18,] 60 72 #> [19,] 55 91 #> [20,] 51 122 #> [21,] 51 253 #> [22,] 53 535 #> [23,] 55 555 #> [24,] 122 992 #> [25,] 126 1001 #> [26,] 144 1015 #> [27,] 154 1018 #> [28,] 164 1020 #> [29,] 195 1020 #> [30,] 215 1017 #> [31,] 235 1009 #> [32,] 243 1000 #> [33,] 245 990 #> [34,] 311 553 #> [35,] 312 523 #> #> $chimay #> [,1] [,2] #> [1,] 291 171 #> [2,] 291 56 #> [3,] 288 40 #> [4,] 284 33 #> [5,] 276 29 #> [6,] 268 26 #> [7,] 254 22 #> [8,] 238 18 #> [9,] 231 17 #> [10,] 208 14 #> [11,] 184 11 #> [12,] 155 11 #> [13,] 117 14 #> [14,] 109 15 #> [15,] 94 17 #> [16,] 86 20 #> [17,] 73 26 #> [18,] 63 40 #> [19,] 60 48 #> [20,] 57 64 #> [21,] 56 71 #> [22,] 52 148 #> [23,] 49 241 #> [24,] 48 348 #> [25,] 49 356 #> [26,] 115 640 #> [27,] 117 647 #> [28,] 125 651 #> [29,] 140 654 #> [30,] 194 654 #> [31,] 202 651 #> [32,] 208 646 #> [33,] 213 631 #> [34,] 284 364 #> [35,] 286 348 #> [36,] 290 248 #> #> $corona #> [,1] [,2] #> [1,] 276 111 #> [2,] 275 70 #> [3,] 271 39 #> [4,] 265 32 #> [5,] 246 23 #> [6,] 235 21 #> [7,] 205 17 #> [8,] 154 16 #> [9,] 123 25 #> [10,] 102 36 #> [11,] 97 46 #> [12,] 96 57 #> [13,] 94 87 #> [14,] 91 167 #> [15,] 90 395 #> [16,] 91 426 #> [17,] 144 815 #> [18,] 164 822 #> [19,] 216 822 #> [20,] 225 807 #> [21,] 229 786 #> [22,] 276 431 #> [23,] 277 391 #> #> $deusventrue #> [,1] [,2] #> [1,] 323 349 #> [2,] 323 319 #> [3,] 321 281 #> [4,] 318 232 #> [5,] 315 184 #> [6,] 313 165 #> [7,] 305 97 #> [8,] 300 78 #> [9,] 296 70 #> [10,] 287 63 #> [11,] 267 56 #> [12,] 228 53 #> [13,] 170 53 #> [14,] 122 56 #> [15,] 94 59 #> [16,] 65 70 #> [17,] 55 78 #> [18,] 49 108 #> [19,] 41 204 #> [20,] 36 271 #> [21,] 36 349 #> [22,] 41 379 #> [23,] 132 912 #> [24,] 134 922 #> [25,] 142 929 #> [26,] 162 937 #> [27,] 172 939 #> [28,] 191 939 #> [29,] 211 932 #> [30,] 225 919 #> [31,] 228 909 #> [32,] 315 406 #> [33,] 318 387 #> #> $duvel #> [,1] [,2] #> [1,] 298 65 #> [2,] 297 54 #> [3,] 295 43 #> [4,] 290 32 #> [5,] 282 21 #> [6,] 271 17 #> [7,] 228 12 #> [8,] 206 11 #> [9,] 163 11 #> [10,] 141 12 #> [11,] 86 18 #> [12,] 76 22 #> [13,] 66 32 #> [14,] 61 43 #> [15,] 58 54 #> [16,] 58 76 #> [17,] 59 272 #> [18,] 61 315 #> [19,] 63 337 #> [20,] 65 348 #> [21,] 135 595 #> [22,] 140 605 #> [23,] 149 611 #> [24,] 160 616 #> [25,] 171 617 #> [26,] 182 617 #> [27,] 193 616 #> [28,] 204 613 #> [29,] 215 606 #> [30,] 223 596 #> [31,] 226 586 #> [32,] 292 347 #> [33,] 295 336 #> [34,] 296 326 #> [35,] 297 315 #> [36,] 298 293 #> #> $franziskaner #> [,1] [,2] #> [1,] 268 79 #> [2,] 267 68 #> [3,] 265 48 #> [4,] 262 37 #> [5,] 246 19 #> [6,] 236 15 #> [7,] 215 10 #> [8,] 205 8 #> [9,] 175 5 #> [10,] 154 5 #> [11,] 133 7 #> [12,] 104 12 #> [13,] 94 15 #> [14,] 73 23 #> [15,] 63 32 #> [16,] 56 53 #> [17,] 55 63 #> [18,] 54 83 #> [19,] 54 480 #> [20,] 60 532 #> [21,] 120 867 #> [22,] 140 869 #> [23,] 151 870 #> [24,] 171 870 #> [25,] 202 867 #> [26,] 265 512 #> [27,] 266 492 #> #> $grimbergen #> [,1] [,2] #> [1,] 292 190 #> [2,] 290 107 #> [3,] 289 96 #> [4,] 282 65 #> [5,] 278 54 #> [6,] 258 39 #> [7,] 247 35 #> [8,] 237 32 #> [9,] 205 27 #> [10,] 184 25 #> [11,] 164 25 #> [12,] 122 27 #> [13,] 90 33 #> [14,] 70 40 #> [15,] 59 49 #> [16,] 51 59 #> [17,] 45 80 #> [18,] 43 101 #> [19,] 42 122 #> [20,] 40 320 #> [21,] 40 394 #> [22,] 44 425 #> [23,] 110 771 #> [24,] 121 789 #> [25,] 131 790 #> [26,] 194 790 #> [27,] 204 789 #> [28,] 215 785 #> [29,] 288 431 #> [30,] 290 420 #> [31,] 291 389 #> [32,] 292 326 #> #> $guiness #> [,1] [,2] #> [1,] 295 61 #> [2,] 292 53 #> [3,] 287 45 #> [4,] 280 36 #> [5,] 272 30 #> [6,] 239 21 #> [7,] 231 19 #> [8,] 214 18 #> [9,] 190 17 #> [10,] 157 17 #> [11,] 140 19 #> [12,] 116 22 #> [13,] 99 27 #> [14,] 86 36 #> [15,] 79 43 #> [16,] 73 56 #> [17,] 70 73 #> [18,] 67 418 #> [19,] 138 743 #> [20,] 141 751 #> [21,] 149 756 #> [22,] 157 757 #> [23,] 182 759 #> [24,] 206 759 #> [25,] 214 757 #> [26,] 221 752 #> [27,] 225 746 #> [28,] 294 431 #> [29,] 297 415 #> [30,] 297 406 #> #> $hoegardeen #> [,1] [,2] #> [1,] 307 262 #> [2,] 307 111 #> [3,] 304 61 #> [4,] 298 50 #> [5,] 285 38 #> [6,] 274 32 #> [7,] 262 29 #> [8,] 211 23 #> [9,] 187 21 #> [10,] 174 21 #> [11,] 124 23 #> [12,] 111 26 #> [13,] 86 32 #> [14,] 74 35 #> [15,] 62 41 #> [16,] 56 52 #> [17,] 51 64 #> [18,] 48 75 #> [19,] 46 88 #> [20,] 44 113 #> [21,] 42 139 #> [22,] 40 265 #> [23,] 40 531 #> [24,] 108 1037 #> [25,] 110 1049 #> [26,] 118 1062 #> [27,] 131 1066 #> [28,] 143 1068 #> [29,] 156 1069 #> [30,] 194 1069 #> [31,] 207 1068 #> [32,] 220 1064 #> [33,] 229 1055 #> [34,] 233 1042 #> [35,] 235 1032 #> [36,] 304 540 #> [37,] 305 527 #> #> $jupiler #> [,1] [,2] #> [1,] 290 176 #> [2,] 289 135 #> [3,] 288 121 #> [4,] 286 107 #> [5,] 280 80 #> [6,] 271 66 #> [7,] 259 55 #> [8,] 245 47 #> [9,] 231 42 #> [10,] 218 39 #> [11,] 190 35 #> [12,] 177 34 #> [13,] 163 34 #> [14,] 136 37 #> [15,] 122 39 #> [16,] 108 42 #> [17,] 95 46 #> [18,] 81 52 #> [19,] 67 64 #> [20,] 58 77 #> [21,] 53 91 #> [22,] 51 105 #> [23,] 48 132 #> [24,] 47 146 #> [25,] 54 501 #> [26,] 55 515 #> [27,] 125 989 #> [28,] 131 1002 #> [29,] 145 1013 #> [30,] 159 1017 #> [31,] 172 1018 #> [32,] 186 1018 #> [33,] 200 1017 #> [34,] 213 1014 #> [35,] 227 1007 #> [36,] 236 994 #> [37,] 239 981 #> [38,] 294 518 #> [39,] 295 490 #> [40,] 295 395 #> #> $kingfisher #> [,1] [,2] #> [1,] 258 151 #> [2,] 258 141 #> [3,] 256 102 #> [4,] 255 83 #> [5,] 253 73 #> [6,] 249 55 #> [7,] 244 45 #> [8,] 235 35 #> [9,] 216 27 #> [10,] 206 24 #> [11,] 188 20 #> [12,] 169 18 #> [13,] 159 18 #> [14,] 140 20 #> [15,] 130 22 #> [16,] 112 27 #> [17,] 104 31 #> [18,] 94 37 #> [19,] 85 46 #> [20,] 81 56 #> [21,] 78 65 #> [22,] 76 75 #> [23,] 75 84 #> [24,] 73 103 #> [25,] 71 316 #> [26,] 71 384 #> [27,] 73 413 #> [28,] 123 729 #> [29,] 132 735 #> [30,] 142 736 #> [31,] 171 736 #> [32,] 181 735 #> [33,] 189 729 #> [34,] 192 719 #> [35,] 253 384 #> [36,] 255 365 #> #> $latrappe #> [,1] [,2] #> [1,] 326 53 #> [2,] 325 40 #> [3,] 324 28 #> [4,] 313 19 #> [5,] 288 15 #> [6,] 276 14 #> [7,] 251 12 #> [8,] 238 11 #> [9,] 76 11 #> [10,] 63 12 #> [11,] 51 14 #> [12,] 38 18 #> [13,] 30 27 #> [14,] 28 52 #> [15,] 27 89 #> [16,] 25 239 #> [17,] 25 451 #> [18,] 28 464 #> [19,] 111 724 #> [20,] 118 737 #> [21,] 130 745 #> [22,] 142 747 #> [23,] 167 748 #> [24,] 205 747 #> [25,] 217 744 #> [26,] 230 721 #> [27,] 234 710 #> [28,] 318 477 #> [29,] 321 465 #> [30,] 324 452 #> [31,] 325 440 #> [32,] 326 427 #> #> $lindemanskriek #> [,1] [,2] #> [1,] 275 67 #> [2,] 274 59 #> [3,] 271 50 #> [4,] 267 43 #> [5,] 256 30 #> [6,] 248 27 #> [7,] 239 24 #> [8,] 231 22 #> [9,] 214 18 #> [10,] 197 15 #> [11,] 189 14 #> [12,] 146 14 #> [13,] 129 16 #> [14,] 113 18 #> [15,] 96 22 #> [16,] 87 25 #> [17,] 79 29 #> [18,] 71 34 #> [19,] 60 49 #> [20,] 57 58 #> [21,] 55 66 #> [22,] 54 75 #> [23,] 53 362 #> [24,] 54 395 #> [25,] 55 404 #> [26,] 119 810 #> [27,] 123 827 #> [28,] 131 831 #> [29,] 147 834 #> [30,] 164 835 #> [31,] 172 835 #> [32,] 181 834 #> [33,] 189 832 #> [34,] 205 823 #> [35,] 207 814 #> [36,] 269 411 #> [37,] 270 403 #> [38,] 272 386 #> #> $nicechouffe #> [,1] [,2] #> [1,] 267 157 #> [2,] 267 64 #> [3,] 266 48 #> [4,] 262 40 #> [5,] 258 33 #> [6,] 250 28 #> [7,] 226 19 #> [8,] 217 17 #> [9,] 150 17 #> [10,] 116 18 #> [11,] 108 20 #> [12,] 100 23 #> [13,] 84 34 #> [14,] 80 41 #> [15,] 77 50 #> [16,] 75 58 #> [17,] 74 269 #> [18,] 75 311 #> [19,] 77 336 #> [20,] 135 683 #> [21,] 138 692 #> [22,] 153 702 #> [23,] 161 703 #> [24,] 170 703 #> [25,] 186 701 #> [26,] 194 698 #> [27,] 199 691 #> [28,] 205 665 #> [29,] 261 350 #> [30,] 263 334 #> [31,] 266 300 #> #> $pecheresse #> [,1] [,2] #> [1,] 290 355 #> [2,] 286 164 #> [3,] 280 87 #> [4,] 272 67 #> [5,] 256 52 #> [6,] 246 46 #> [7,] 226 40 #> [8,] 207 38 #> [9,] 187 36 #> [10,] 138 36 #> [11,] 109 41 #> [12,] 89 48 #> [13,] 81 53 #> [14,] 65 68 #> [15,] 58 86 #> [16,] 56 96 #> [17,] 54 116 #> [18,] 54 165 #> [19,] 56 310 #> [20,] 58 428 #> [21,] 61 476 #> [22,] 63 495 #> [23,] 124 940 #> [24,] 128 948 #> [25,] 143 960 #> [26,] 161 964 #> [27,] 191 964 #> [28,] 209 962 #> [29,] 219 959 #> [30,] 232 950 #> [31,] 237 933 #> [32,] 288 471 #> [33,] 290 451 #> #> $sierranevada #> [,1] [,2] #> [1,] 275 95 #> [2,] 275 83 #> [3,] 272 58 #> [4,] 268 46 #> [5,] 257 35 #> [6,] 245 31 #> [7,] 208 27 #> [8,] 196 26 #> [9,] 122 26 #> [10,] 109 27 #> [11,] 85 31 #> [12,] 72 37 #> [13,] 65 49 #> [14,] 63 61 #> [15,] 61 74 #> [16,] 59 382 #> [17,] 63 407 #> [18,] 118 658 #> [19,] 123 669 #> [20,] 133 677 #> [21,] 145 679 #> [22,] 157 680 #> [23,] 169 680 #> [24,] 182 679 #> [25,] 194 677 #> [26,] 206 669 #> [27,] 268 403 #> [28,] 270 391 #> [29,] 271 379 #> [30,] 272 366 #> #> $tanglefoot #> [,1] [,2] #> [1,] 298 64 #> [2,] 294 48 #> [3,] 291 40 #> [4,] 286 32 #> [5,] 62 32 #> [6,] 56 38 #> [7,] 50 54 #> [8,] 48 70 #> [9,] 47 383 #> [10,] 47 391 #> [11,] 48 407 #> [12,] 49 415 #> [13,] 130 704 #> [14,] 133 712 #> [15,] 213 712 #> [16,] 220 707 #> [17,] 295 425 #> [18,] 299 409 #> [19,] 301 393 #> #> $tauro #> [,1] [,2] #> [1,] 295 398 #> [2,] 290 132 #> [3,] 288 119 #> [4,] 282 84 #> [5,] 277 73 #> [6,] 266 60 #> [7,] 254 52 #> [8,] 232 41 #> [9,] 220 39 #> [10,] 184 34 #> [11,] 160 34 #> [12,] 123 39 #> [13,] 112 41 #> [14,] 100 44 #> [15,] 77 55 #> [16,] 67 65 #> [17,] 58 78 #> [18,] 54 90 #> [19,] 50 113 #> [20,] 48 125 #> [21,] 48 198 #> [22,] 52 405 #> [23,] 54 503 #> [24,] 59 538 #> [25,] 124 980 #> [26,] 132 1003 #> [27,] 144 1012 #> [28,] 156 1015 #> [29,] 168 1017 #> [30,] 180 1018 #> [31,] 192 1018 #> [32,] 204 1017 #> [33,] 215 1013 #> [34,] 228 1007 #> [35,] 236 995 #> [36,] 241 973 #> [37,] 293 532 #> [38,] 295 496 #> #> $westmalle #> [,1] [,2] #> [1,] 258 105 #> [2,] 257 80 #> [3,] 255 64 #> [4,] 252 41 #> [5,] 246 35 #> [6,] 232 25 #> [7,] 224 22 #> [8,] 207 16 #> [9,] 199 14 #> [10,] 182 12 #> [11,] 157 11 #> [12,] 149 11 #> [13,] 132 14 #> [14,] 123 16 #> [15,] 107 20 #> [16,] 98 24 #> [17,] 74 38 #> [18,] 70 45 #> [19,] 68 87 #> [20,] 67 145 #> [21,] 66 244 #> [22,] 66 344 #> [23,] 67 369 #> [24,] 70 394 #> [25,] 117 761 #> [26,] 127 773 #> [27,] 134 776 #> [28,] 151 779 #> [29,] 159 779 #> [30,] 182 776 #> [31,] 197 768 #> [32,] 201 760 #> [33,] 254 389 #> [34,] 256 372 #> [35,] 259 339 #> #> $amrut #> [,1] [,2] #> [1,] 269 74 #> [2,] 268 54 #> [3,] 264 34 #> [4,] 257 25 #> [5,] 248 20 #> [6,] 228 14 #> [7,] 198 11 #> [8,] 129 11 #> [9,] 99 14 #> [10,] 89 16 #> [11,] 79 19 #> [12,] 69 24 #> [13,] 60 32 #> [14,] 58 42 #> [15,] 55 62 #> [16,] 54 72 #> [17,] 54 82 #> [18,] 55 501 #> [19,] 56 511 #> [20,] 124 864 #> [21,] 134 871 #> [22,] 144 874 #> [23,] 154 875 #> [24,] 174 875 #> [25,] 184 874 #> [26,] 193 871 #> [27,] 200 864 #> [28,] 269 513 #> #> $ballantines #> [,1] [,2] #> [1,] 313 107 #> [2,] 313 67 #> [3,] 312 59 #> [4,] 309 44 #> [5,] 303 20 #> [6,] 298 12 #> [7,] 284 4 #> [8,] 268 3 #> [9,] 118 3 #> [10,] 95 4 #> [11,] 79 5 #> [12,] 71 6 #> [13,] 55 11 #> [14,] 49 19 #> [15,] 43 34 #> [16,] 41 42 #> [17,] 38 58 #> [18,] 35 82 #> [19,] 35 121 #> [20,] 36 483 #> [21,] 38 499 #> [22,] 41 507 #> [23,] 133 704 #> [24,] 141 708 #> [25,] 156 710 #> [26,] 188 710 #> [27,] 204 707 #> [28,] 208 701 #> [29,] 304 508 #> [30,] 307 500 #> [31,] 309 484 #> #> $bushmills #> [,1] [,2] #> [1,] 291 60 #> [2,] 290 45 #> [3,] 284 29 #> [4,] 269 18 #> [5,] 253 14 #> [6,] 238 13 #> [7,] 176 11 #> [8,] 130 11 #> [9,] 115 12 #> [10,] 100 15 #> [11,] 85 25 #> [12,] 77 40 #> [13,] 74 56 #> [14,] 72 71 #> [15,] 68 564 #> [16,] 68 656 #> [17,] 70 672 #> [18,] 132 881 #> [19,] 147 891 #> [20,] 162 893 #> [21,] 193 893 #> [22,] 208 891 #> [23,] 221 881 #> [24,] 290 676 #> [25,] 292 661 #> #> $chivas #> [,1] [,2] #> [1,] 332 316 #> [2,] 329 77 #> [3,] 327 69 #> [4,] 322 61 #> [5,] 305 53 #> [6,] 272 47 #> [7,] 240 45 #> [8,] 223 44 #> [9,] 198 43 #> [10,] 166 43 #> [11,] 133 44 #> [12,] 100 46 #> [13,] 83 48 #> [14,] 75 49 #> [15,] 50 55 #> [16,] 36 67 #> [17,] 34 75 #> [18,] 29 379 #> [19,] 29 412 #> [20,] 31 429 #> [21,] 33 437 #> [22,] 135 828 #> [23,] 142 833 #> [24,] 158 835 #> [25,] 183 836 #> [26,] 191 836 #> [27,] 216 834 #> [28,] 224 832 #> [29,] 232 816 #> [30,] 330 431 #> [31,] 332 423 #> [32,] 333 398 #> #> $dalmore #> [,1] [,2] #> [1,] 325 63 #> [2,] 323 50 #> [3,] 314 40 #> [4,] 302 36 #> [5,] 228 34 #> [6,] 49 34 #> [7,] 40 39 #> [8,] 33 50 #> [9,] 32 62 #> [10,] 42 334 #> [11,] 44 346 #> [12,] 47 359 #> [13,] 136 701 #> [14,] 149 706 #> [15,] 186 706 #> [16,] 198 705 #> [17,] 210 702 #> [18,] 310 347 #> [19,] 311 334 #> #> $famousgrouse #> [,1] [,2] #> [1,] 254 58 #> [2,] 254 39 #> [3,] 252 29 #> [4,] 247 21 #> [5,] 238 16 #> [6,] 229 14 #> [7,] 219 12 #> [8,] 210 11 #> [9,] 143 11 #> [10,] 124 13 #> [11,] 114 16 #> [12,] 106 19 #> [13,] 100 28 #> [14,] 97 36 #> [15,] 96 370 #> [16,] 96 389 #> [17,] 98 399 #> [18,] 146 611 #> [19,] 153 617 #> [20,] 172 619 #> [21,] 192 617 #> [22,] 198 610 #> [23,] 246 410 #> [24,] 250 391 #> #> $glendronach #> [,1] [,2] #> [1,] 275 90 #> [2,] 274 66 #> [3,] 273 54 #> [4,] 270 41 #> [5,] 260 32 #> [6,] 249 27 #> [7,] 237 24 #> [8,] 213 21 #> [9,] 189 19 #> [10,] 153 19 #> [11,] 129 21 #> [12,] 105 25 #> [13,] 92 29 #> [14,] 80 37 #> [15,] 76 49 #> [16,] 74 61 #> [17,] 72 85 #> [18,] 72 495 #> [19,] 74 507 #> [20,] 134 832 #> [21,] 145 839 #> [22,] 157 840 #> [23,] 170 841 #> [24,] 194 841 #> [25,] 206 836 #> [26,] 273 500 #> [27,] 274 488 #> #> $glenmorangie #> [,1] [,2] #> [1,] 298 76 #> [2,] 297 59 #> [3,] 284 44 #> [4,] 252 32 #> [5,] 236 29 #> [6,] 202 26 #> [7,] 187 25 #> [8,] 153 25 #> [9,] 136 26 #> [10,] 103 31 #> [11,] 86 36 #> [12,] 70 43 #> [13,] 57 55 #> [14,] 54 72 #> [15,] 53 518 #> [16,] 53 550 #> [17,] 54 567 #> [18,] 133 998 #> [19,] 142 1010 #> [20,] 159 1011 #> [21,] 176 1011 #> [22,] 192 1011 #> [23,] 209 1010 #> [24,] 222 1001 #> [25,] 298 574 #> [26,] 300 558 #> [27,] 300 524 #> #> $highlandpark #> [,1] [,2] #> [1,] 295 55 #> [2,] 293 41 #> [3,] 282 29 #> [4,] 268 26 #> [5,] 226 20 #> [6,] 170 16 #> [7,] 128 16 #> [8,] 86 21 #> [9,] 73 24 #> [10,] 59 29 #> [11,] 46 36 #> [12,] 40 50 #> [13,] 39 469 #> [14,] 40 483 #> [15,] 117 705 #> [16,] 128 716 #> [17,] 142 720 #> [18,] 170 722 #> [19,] 184 721 #> [20,] 198 719 #> [21,] 211 712 #> [22,] 291 487 #> [23,] 293 473 #> #> $jackdaniels #> [,1] [,2] #> [1,] 301 68 #> [2,] 295 42 #> [3,] 290 29 #> [4,] 280 20 #> [5,] 267 17 #> [6,] 100 17 #> [7,] 87 18 #> [8,] 75 25 #> [9,] 68 37 #> [10,] 65 51 #> [11,] 60 76 #> [12,] 60 89 #> [13,] 63 414 #> [14,] 64 453 #> [15,] 65 466 #> [16,] 70 493 #> [17,] 137 802 #> [18,] 150 810 #> [19,] 189 810 #> [20,] 215 807 #> [21,] 227 801 #> [22,] 296 480 #> [23,] 301 454 #> #> $jb #> [,1] [,2] #> [1,] 305 102 #> [2,] 305 81 #> [3,] 303 70 #> [4,] 295 49 #> [5,] 285 41 #> [6,] 274 35 #> [7,] 264 31 #> [8,] 242 29 #> [9,] 106 29 #> [10,] 85 31 #> [11,] 74 35 #> [12,] 63 40 #> [13,] 54 47 #> [14,] 44 69 #> [15,] 43 80 #> [16,] 40 595 #> [17,] 44 617 #> [18,] 123 1030 #> [19,] 131 1036 #> [20,] 163 1037 #> [21,] 195 1037 #> [22,] 217 1036 #> [23,] 221 1027 #> [24,] 300 608 #> [25,] 302 597 #> #> $johnniewalker #> [,1] [,2] #> [1,] 218 24 #> [2,] 218 20 #> [3,] 217 12 #> [4,] 214 8 #> [5,] 206 7 #> [6,] 178 6 #> [7,] 146 5 #> [8,] 142 6 #> [9,] 138 8 #> [10,] 134 15 #> [11,] 132 211 #> [12,] 132 239 #> [13,] 154 337 #> [14,] 158 342 #> [15,] 162 343 #> [16,] 174 343 #> [17,] 186 342 #> [18,] 188 339 #> [19,] 215 240 #> [20,] 217 232 #> #> $magallan #> [,1] [,2] #> [1,] 241 57 #> [2,] 238 49 #> [3,] 227 35 #> [4,] 220 32 #> [5,] 205 26 #> [6,] 192 23 #> [7,] 170 20 #> [8,] 155 20 #> [9,] 120 29 #> [10,] 114 32 #> [11,] 99 42 #> [12,] 95 49 #> [13,] 93 64 #> [14,] 75 441 #> [15,] 75 484 #> [16,] 77 499 #> [17,] 79 513 #> [18,] 140 766 #> [19,] 150 778 #> [20,] 164 779 #> [21,] 171 779 #> [22,] 185 776 #> [23,] 194 764 #> [24,] 254 516 #> [25,] 258 494 #> [26,] 258 450 #> [27,] 257 414 #> #> $makersmark #> [,1] [,2] #> [1,] 328 144 #> [2,] 323 103 #> [3,] 321 88 #> [4,] 318 75 #> [5,] 314 60 #> [6,] 299 18 #> [7,] 285 10 #> [8,] 271 7 #> [9,] 228 5 #> [10,] 82 5 #> [11,] 67 7 #> [12,] 53 17 #> [13,] 33 71 #> [14,] 30 85 #> [15,] 25 127 #> [16,] 13 267 #> [17,] 11 296 #> [18,] 8 353 #> [19,] 8 367 #> [20,] 10 381 #> [21,] 16 408 #> [22,] 126 840 #> [23,] 134 851 #> [24,] 149 856 #> [25,] 207 856 #> [26,] 221 852 #> [27,] 228 842 #> [28,] 343 386 #> [29,] 345 358 #> [30,] 345 343 #> [31,] 343 315 #> #> $oban #> [,1] [,2] #> [1,] 275 74 #> [2,] 270 57 #> [3,] 262 50 #> [4,] 254 47 #> [5,] 245 44 #> [6,] 228 41 #> [7,] 220 40 #> [8,] 203 38 #> [9,] 185 37 #> [10,] 160 37 #> [11,] 134 39 #> [12,] 126 40 #> [13,] 117 42 #> [14,] 100 46 #> [15,] 92 49 #> [16,] 83 56 #> [17,] 77 73 #> [18,] 72 517 #> [19,] 74 534 #> [20,] 75 542 #> [21,] 138 879 #> [22,] 146 894 #> [23,] 154 897 #> [24,] 171 899 #> [25,] 188 898 #> [26,] 197 897 #> [27,] 205 895 #> [28,] 213 888 #> [29,] 279 535 #> [30,] 280 526 #> [31,] 280 500 #> #> $oldpotrero #> [,1] [,2] #> [1,] 271 93 #> [2,] 269 41 #> [3,] 266 32 #> [4,] 259 26 #> [5,] 250 21 #> [6,] 233 15 #> [7,] 224 12 #> [8,] 207 8 #> [9,] 191 7 #> [10,] 165 7 #> [11,] 148 8 #> [12,] 122 11 #> [13,] 105 13 #> [14,] 88 18 #> [15,] 79 22 #> [16,] 66 33 #> [17,] 63 41 #> [18,] 62 50 #> [19,] 58 205 #> [20,] 57 248 #> [21,] 58 256 #> [22,] 130 588 #> [23,] 139 601 #> [24,] 156 603 #> [25,] 182 603 #> [26,] 191 602 #> [27,] 198 596 #> [28,] 273 256 #> [29,] 273 204 #> #> $redbreast #> [,1] [,2] #> [1,] 255 78 #> [2,] 254 27 #> [3,] 253 22 #> [4,] 245 15 #> [5,] 240 13 #> [6,] 231 11 #> [7,] 217 9 #> [8,] 207 8 #> [9,] 189 7 #> [10,] 160 7 #> [11,] 146 8 #> [12,] 137 9 #> [13,] 123 11 #> [14,] 118 12 #> [15,] 114 13 #> [16,] 109 15 #> [17,] 104 18 #> [18,] 101 27 #> [19,] 100 50 #> [20,] 98 107 #> [21,] 97 163 #> [22,] 97 205 #> [23,] 98 214 #> [24,] 154 428 #> [25,] 158 431 #> [26,] 163 432 #> [27,] 172 433 #> [28,] 181 433 #> [29,] 191 432 #> [30,] 199 427 #> [31,] 255 214 #> [32,] 256 172 #> #> $tamdhu #> [,1] [,2] #> [1,] 304 106 #> [2,] 302 94 #> [3,] 299 83 #> [4,] 289 71 #> [5,] 278 64 #> [6,] 253 54 #> [7,] 229 51 #> [8,] 205 49 #> [9,] 155 49 #> [10,] 120 51 #> [11,] 108 52 #> [12,] 84 60 #> [13,] 73 64 #> [14,] 60 72 #> [15,] 52 84 #> [16,] 49 96 #> [17,] 44 613 #> [18,] 47 638 #> [19,] 49 650 #> [20,] 116 1038 #> [21,] 122 1050 #> [22,] 134 1054 #> [23,] 158 1057 #> [24,] 183 1057 #> [25,] 207 1055 #> [26,] 218 1049 #> [27,] 221 1037 #> [28,] 301 638 #> [29,] 302 625 #> #> $wildturkey #> [,1] [,2] #> [1,] 333 76 #> [2,] 333 63 #> [3,] 327 49 #> [4,] 316 38 #> [5,] 301 34 #> [6,] 275 28 #> [7,] 262 26 #> [8,] 220 23 #> [9,] 122 23 #> [10,] 81 26 #> [11,] 55 30 #> [12,] 41 34 #> [13,] 28 40 #> [14,] 18 52 #> [15,] 15 66 #> [16,] 15 625 #> [17,] 20 651 #> [18,] 120 1113 #> [19,] 134 1118 #> [20,] 147 1120 #> [21,] 203 1120 #> [22,] 216 1117 #> [23,] 224 1106 #> [24,] 326 648 #> [25,] 330 620 #> #> $yoichi #> [,1] [,2] #> [1,] 290 48 #> [2,] 280 35 #> [3,] 273 32 #> [4,] 258 29 #> [5,] 244 28 #> [6,] 229 27 #> [7,] 200 26 #> [8,] 156 26 #> [9,] 134 27 #> [10,] 104 29 #> [11,] 90 32 #> [12,] 75 40 #> [13,] 70 54 #> [14,] 69 120 #> [15,] 68 421 #> [16,] 68 472 #> [17,] 69 487 #> [18,] 72 501 #> [19,] 136 721 #> [20,] 144 735 #> [21,] 159 738 #> [22,] 203 738 #> [23,] 210 737 #> [24,] 225 730 #> [25,] 291 496 #> [26,] 293 481 #> [27,] 294 466 #> [28,] 294 437 #> coo_chull_onion #> function (coo, close = TRUE) #> { #> UseMethod(\"coo_chull_onion\") #> } #> #> x <- bot %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details all_whisky_points <- x %>% as_df() %>% filter(type==\"whisky\") %>% select(PC1, PC2) #> `retain` is too ambitious. All axes returned plot(x, ~type, eig=FALSE) #> will be deprecated soon, see ?plot_PCA peeling_the_whisky_onion <- all_whisky_points %>% as.matrix %>% coo_chull_onion() # you may need to par(xpd=NA) to ensure all segments # even those outside the graphical window are drawn peeling_the_whisky_onion$coo %>% lapply(coo_draw) #> [[1]] #> NULL #> #> [[2]] #> NULL #> #> [[3]] #> NULL #> # simulated data xy <- replicate(2, rnorm(50)) coo_plot(xy, poly=FALSE) xy %>% coo_chull_onion() %$% coo %>% lapply(polygon, col=\"#00000022\") #> [[1]] #> NULL #> #> [[2]] #> NULL #> #> [[3]] #> NULL #> #> [[4]] #> NULL #> #> [[5]] #> NULL #> #> [[6]] #> NULL #> #> [[7]] #> NULL #>"},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the Haralick's circularity of a shape — coo_circularity","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"coo_circularity calculates 'circularity measure'. Also called 'compactness' 'shape factor' sometimes. coo_circularityharalick calculates Haralick's circularity less sensible digitalization noise coo_circularity. coo_circularitynorm calculates 'circularity', also called compactness shape factor, normalized unit circle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"","code":"coo_circularity(coo) # S3 method for default coo_circularity(coo) # S3 method for Coo coo_circularity(coo) coo_circularityharalick(coo) # S3 method for default coo_circularityharalick(coo) # S3 method for Coo coo_circularityharalick(coo) coo_circularitynorm(coo) # S3 method for default coo_circularitynorm(coo) # S3 method for Coo coo_circularitynorm(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"numeric single shapes, list Coo corresponding circularity measurement.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"","code":"# coo_circularity bot[1] %>% coo_circularity() #> [1] 26.26463 bot %>% slice(1:5) %>% # for speed sake only coo_circularity #> $brahma #> [1] 26.26463 #> #> $caney #> [1] 25.60553 #> #> $chimay #> [1] 20.83278 #> #> $corona #> [1] 27.61134 #> #> $deusventrue #> [1] 25.75573 #> # coo_circularityharalick bot[1] %>% coo_circularityharalick() #> [1] 2.320493 bot %>% slice(1:5) %>% # for speed sake only coo_circularityharalick #> $brahma #> [1] 2.320493 #> #> $caney #> [1] 2.374045 #> #> $chimay #> [1] 2.935174 #> #> $corona #> [1] 2.261573 #> #> $deusventrue #> [1] 2.397828 #> # coo_circularitynorm bot[1] %>% coo_circularitynorm() #> [1] 2.090073 bot %>% slice(1:5) %>% # for speed sake only coo_circularitynorm #> $brahma #> [1] 2.090073 #> #> $caney #> [1] 2.037623 #> #> $chimay #> [1] 1.65782 #> #> $corona #> [1] 2.197241 #> #> $deusventrue #> [1] 2.049576 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":null,"dir":"Reference","previous_headings":"","what":"Closes/uncloses shapes — coo_close","title":"Closes/uncloses shapes — coo_close","text":"Returns closed shape (un)closed shapes. See also coo_unclose. Returns unclosed shape (un)closed shapes. See also coo_close.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Closes/uncloses shapes — coo_close","text":"","code":"coo_close(coo) coo_unclose(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Closes/uncloses shapes — coo_close","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Closes/uncloses shapes — coo_close","text":"matrix (x; y) coordinates, Coo object. matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Closes/uncloses shapes — coo_close","text":"","code":"x <- (matrix(1:10, ncol=2)) x2 <- coo_close(x) x3 <- coo_unclose(x2) x #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x) #> [1] FALSE x2 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 #> [6,] 1 6 coo_is_closed(x2) #> [1] TRUE x3 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x3) #> [1] FALSE x <- (matrix(1:10, ncol=2)) x2 <- coo_close(x) x3 <- coo_unclose(x2) x #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x) #> [1] FALSE x2 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 #> [6,] 1 6 coo_is_closed(x2) #> [1] TRUE x3 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x3) #> [1] FALSE"},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the convexity of a shape — coo_convexity","title":"Calculates the convexity of a shape — coo_convexity","text":"Calculated using ratio eigen values (inertia axis)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the convexity of a shape — coo_convexity","text":"","code":"coo_convexity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the convexity of a shape — coo_convexity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the convexity of a shape — coo_convexity","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the convexity of a shape — coo_convexity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the convexity of a shape — coo_convexity","text":"","code":"coo_convexity(bot[1]) #> [1] 0.8003675 bot %>% slice(1:3) %>% # for speed sake only coo_convexity() #> $brahma #> [1] 0.8003675 #> #> $caney #> [1] 0.9409434 #> #> $chimay #> [1] 0.9454935 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":null,"dir":"Reference","previous_headings":"","what":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"Useful shapes aligned along x-axis (e.g. bilateral symmetry) one wants retain just lower side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"","code":"coo_down(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_down","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"shapes \"sliced\" along x-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"","code":"b <- coo_alignxax(bot[1]) coo_plot(b) coo_draw(coo_down(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":null,"dir":"Reference","previous_headings":"","what":"Adds a shape to the current plot — coo_draw","title":"Adds a shape to the current plot — coo_draw","text":"coo_draw simply coo_plot plot.new=FALSE, ie adds shape active plot.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Adds a shape to the current plot — coo_draw","text":"","code":"coo_draw(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Adds a shape to the current plot — coo_draw","text":"coo list matrix coordinates. ... optional parameters coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Adds a shape to the current plot — coo_draw","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Adds a shape to the current plot — coo_draw","text":"","code":"b1 <- bot[4] b2 <- bot[5] coo_plot(b1) coo_draw(b2, border='red') # all coo_plot arguments will work for coo_draw"},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":null,"dir":"Reference","previous_headings":"","what":"Draw radii to the current plot — coo_draw_rads","title":"Draw radii to the current plot — coo_draw_rads","text":"Given shape, centroid-points radii drawn using segments can passed options","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draw radii to the current plot — coo_draw_rads","text":"","code":"coo_draw_rads(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draw radii to the current plot — coo_draw_rads","text":"coo shape ... arguments feed segments","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draw radii to the current plot — coo_draw_rads","text":"drawing last plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draw radii to the current plot — coo_draw_rads","text":"","code":"shp <- shapes[4] %>% coo_sample(24) %T>% coo_plot coo_draw_rads(shp, col=col_summer(24))"},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate abscissa and ordinate on a shape — coo_dxy","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"simple wrapper calculate dxi - dx1 dyi - dx1.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"","code":"coo_dxy(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"coo matrix (list) (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"data.frame two components dx dy single shapes list data.frames Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"","code":"coo_dxy(coo_sample(bot[1], 12)) #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 26 -200 #> 3 5 -411 #> 4 106 -546 #> 5 279 -448 #> 6 268 -259 #> 7 258 -38 #> 8 259 152 #> 9 203 351 #> 10 168 540 #> 11 73 441 #> 12 45 220 bot %>% slice(1:5) %>% coo_sample(12) %>% # for readability and speed only coo_dxy() #> $brahma #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 26 -200 #> 3 5 -411 #> 4 106 -546 #> 5 279 -448 #> 6 268 -259 #> 7 258 -38 #> 8 259 152 #> 9 203 351 #> 10 168 540 #> 11 73 441 #> 12 45 220 #> #> $caney #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -192 #> 3 0 -373 #> 4 91 -507 #> 5 251 -436 #> 6 258 -244 #> 7 258 -73 #> 8 219 109 #> 9 193 299 #> 10 182 474 #> 11 76 392 #> 12 58 211 #> #> $chimay #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 3 -131 #> 3 7 -254 #> 4 99 -320 #> 5 227 -304 #> 6 242 -185 #> 7 239 -54 #> 8 209 83 #> 9 163 204 #> 10 145 321 #> 11 65 265 #> 12 49 145 #> #> $corona #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -155 #> 3 3 -298 #> 4 73 -409 #> 5 184 -346 #> 6 185 -201 #> 7 185 -46 #> 8 155 106 #> 9 145 246 #> 10 125 396 #> 11 53 309 #> 12 33 171 #> #> $deusventrue #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 -38 -171 #> 3 -28 -334 #> 4 86 -427 #> 5 231 -384 #> 6 245 -209 #> 7 234 -47 #> 8 168 123 #> 9 151 294 #> 10 137 451 #> 11 56 347 #> 12 57 197 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the eccentricity of a shape — coo_eccentricity","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"coo_eccentricityeigen uses ratio eigen values (inertia axes coordinates). coo_eccentricityboundingbox uses width/length ratio (see coo_lw).","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"","code":"coo_eccentricityeigen(coo) # S3 method for default coo_eccentricityeigen(coo) # S3 method for Coo coo_eccentricityeigen(coo) coo_eccentricityboundingbox(coo) # S3 method for default coo_eccentricityboundingbox(coo) # S3 method for Coo coo_eccentricityboundingbox(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"numeric single shapes, list Coo.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"","code":"# coo_eccentricityeigen bot[1] %>% coo_eccentricityeigen() #> [1] 0.09292547 bot %>% slice(1:3) %>% # for speed sake only coo_eccentricityeigen() #> $brahma #> [1] 0.09292547 #> #> $caney #> [1] 0.100634 #> #> $chimay #> [1] 0.1813198 #> # coo_eccentricityboundingbox bot[1] %>% coo_eccentricityboundingbox() #> [1] 0.2555899 bot %>% slice(1:3) %>% # for speed sake only coo_eccentricityboundingbox() #> $brahma #> [1] 0.2555899 #> #> $caney #> [1] 0.2617262 #> #> $chimay #> [1] 0.3744498 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the elongation of a shape — coo_elongation","title":"Calculates the elongation of a shape — coo_elongation","text":"Calculates elongation shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the elongation of a shape — coo_elongation","text":"","code":"coo_elongation(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the elongation of a shape — coo_elongation","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the elongation of a shape — coo_elongation","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the elongation of a shape — coo_elongation","text":"numeric, eccentricity bounding box","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the elongation of a shape — coo_elongation","text":"","code":"coo_elongation(bot[1]) #> [1] 0.7444101 # on Coo # for speed sake bot %>% slice(1:3) %>% coo_elongation #> $brahma #> [1] 0.7444101 #> #> $caney #> [1] 0.7382738 #> #> $chimay #> [1] 0.6255502 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract coordinates from a shape — coo_extract","title":"Extract coordinates from a shape — coo_extract","text":"Extract ids coordinates single shape Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract coordinates from a shape — coo_extract","text":"","code":"coo_extract(coo, ids)"},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract coordinates from a shape — coo_extract","text":"coo either matrix (x; y) coordinates Coo object. ids integer, ids points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract coordinates from a shape — coo_extract","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract coordinates from a shape — coo_extract","text":"probably make sense Coo objects number coordinates homologous, typically Ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract coordinates from a shape — coo_extract","text":"","code":"coo_extract(bot[1], c(3, 9, 12)) # or : #> [,1] [,2] #> [1,] 40 529 #> [2,] 57 414 #> [3,] 63 361 bot[1] %>% coo_extract(c(3, 9, 12)) #> [,1] [,2] #> [1,] 40 529 #> [2,] 57 414 #> [3,] 63 361"},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":null,"dir":"Reference","previous_headings":"","what":"Flips shapes — coo_flipx","title":"Flips shapes — coo_flipx","text":"coo_flipx flips shapes x-axis; coo_flipy y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flips shapes — coo_flipx","text":"","code":"coo_flipx(coo) coo_flipy(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flips shapes — coo_flipx","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flips shapes — coo_flipx","text":"matrix (x; y) coordinates","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flips shapes — coo_flipx","text":"","code":"cat <- shapes[4] cat <- coo_center(cat) coo_plot(cat) coo_draw(coo_flipx(cat), border=\"red\") coo_draw(coo_flipy(cat), border=\"blue\") #' # to flip an entire Coo: shapes2 <- shapes shapes$coo <- lapply(shapes2$coo, coo_flipx)"},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":null,"dir":"Reference","previous_headings":"","what":"Forces shapes to close — coo_force2close","title":"Forces shapes to close — coo_force2close","text":"exotic function distribute distance first last points unclosed shapes, become closed. May useful (?) e.g. t/rfourier methods reconstructed shapes may closed.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Forces shapes to close — coo_force2close","text":"","code":"coo_force2close(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Forces shapes to close — coo_force2close","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Forces shapes to close — coo_force2close","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Forces shapes to close — coo_force2close","text":"","code":"b <- coo_sample(bot[1], 64) b <- b[1:40,] coo_plot(b) coo_draw(coo_force2close(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":null,"dir":"Reference","previous_headings":"","what":"Interpolates coordinates — coo_interpolate","title":"Interpolates coordinates — coo_interpolate","text":"Interpolates n coordinates 'among existing points'' existing points, along perimeter coordinates provided keeping first point","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Interpolates coordinates — coo_interpolate","text":"","code":"coo_interpolate(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Interpolates coordinates — coo_interpolate","text":"coo matrix (x; y) coordinates Coo object. n integer, number fo points interpolate.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Interpolates coordinates — coo_interpolate","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Interpolates coordinates — coo_interpolate","text":"","code":"b5 <- bot %>% slice(1:5) # for speed sake stack(b5) stack(coo_scale(b5)) stack(b5) stack(coo_interpolate(coo_sample(b5, 12), 120)) coo_plot(bot[1]) coo_plot(coo_interpolate(coo_sample(bot[1], 12), 120))"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":null,"dir":"Reference","previous_headings":"","what":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"Take shape, segment starting centroid particular angle, point nearest segment intersects shape?","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"","code":"coo_intersect_angle(coo, angle = 0) coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for default coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Coo coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4])"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"coo matrix (x; y) coordinates Coo object. angle numeric angle radians (0 default). direction character one \"\", \"left\", \"\", \"right\" (\"right\" default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"numeric id nearest point list Coo See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"shapes always centered operation. need simple direction (, left, , right)ward, use coo_intersect_direction need find intersection relies coordinates 1000.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"","code":"coo <- bot[1] %>% coo_center %>% coo_scale coo_plot(coo) coo %>% coo_intersect_angle(pi/7) %>% coo[., , drop=FALSE] %>% points(col=\"red\") # many angles coo_plot(coo) sapply(seq(0, pi, pi/12), function(x) coo %>% coo_intersect_angle(x)) -> ids coo[ids, ] %>% points(col=\"blue\") coo %>% coo_intersect_direction(\"down\") %>% coo[.,, drop=FALSE] %>% points(col=\"orange\")"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":null,"dir":"Reference","previous_headings":"","what":"Nearest intersection between a shape and a segment — coo_intersect_segment","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"Take shape, intersecting segment, point nearest segment intersects shape? time, centering makes sense.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"","code":"coo_intersect_segment(coo, seg, center = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"coo matrix (x; y) coordinates Coo object. seg 2x2 matrix defining starting ending points; list numeric length 4. center logical whether center shape (TRUE default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"numeric id nearest point, list Coo. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"","code":"coo <- bot[1] %>% coo_center %>% coo_scale seg <- c(0, 0, 2, 2) # passed as a numeric of length(4) coo_plot(coo) segments(seg[1], seg[2], seg[3], seg[4]) coo %>% coo_intersect_segment(seg) %T>% print %>% # prints on the console and draw it coo[., , drop=FALSE] %>% points(col=\"red\") #> [1] 79 # on Coo bot %>% slice(1:3) %>% # for the sake of speed coo_center %>% coo_intersect_segment(matrix(c(0, 0, 1000, 1000), ncol=2, byrow=TRUE)) #> $brahma #> [1] 79 #> #> $caney #> [1] 96 #> #> $chimay #> [1] 110 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":null,"dir":"Reference","previous_headings":"","what":"Test if shapes are closed — coo_is_closed","title":"Test if shapes are closed — coo_is_closed","text":"Returns TRUE/FALSE whether last coordinate shapes first one.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Test if shapes are closed — coo_is_closed","text":"","code":"coo_is_closed(coo) is_open(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Test if shapes are closed — coo_is_closed","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Test if shapes are closed — coo_is_closed","text":"single vector logical.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Test if shapes are closed — coo_is_closed","text":"","code":"coo_is_closed(matrix(1:10, ncol=2)) #> [1] FALSE coo_is_closed(coo_close(matrix(1:10, ncol=2))) #> [1] TRUE coo_is_closed(bot) #> brahma caney chimay corona deusventrue #> FALSE FALSE FALSE FALSE FALSE #> duvel franziskaner grimbergen guiness hoegardeen #> FALSE FALSE FALSE FALSE FALSE #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> FALSE FALSE FALSE FALSE FALSE #> pecheresse sierranevada tanglefoot tauro westmalle #> FALSE FALSE FALSE FALSE FALSE #> amrut ballantines bushmills chivas dalmore #> FALSE FALSE FALSE FALSE FALSE #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> FALSE FALSE FALSE FALSE FALSE #> jb johnniewalker magallan makersmark oban #> FALSE FALSE FALSE FALSE FALSE #> oldpotrero redbreast tamdhu wildturkey yoichi #> FALSE FALSE FALSE FALSE FALSE coo_is_closed(coo_close(bot)) #> brahma caney chimay corona deusventrue #> TRUE TRUE TRUE TRUE TRUE #> duvel franziskaner grimbergen guiness hoegardeen #> TRUE TRUE TRUE TRUE TRUE #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> TRUE TRUE TRUE TRUE TRUE #> pecheresse sierranevada tanglefoot tauro westmalle #> TRUE TRUE TRUE TRUE TRUE #> amrut ballantines bushmills chivas dalmore #> TRUE TRUE TRUE TRUE TRUE #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> TRUE TRUE TRUE TRUE TRUE #> jb johnniewalker magallan makersmark oban #> TRUE TRUE TRUE TRUE TRUE #> oldpotrero redbreast tamdhu wildturkey yoichi #> TRUE TRUE TRUE TRUE TRUE"},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":null,"dir":"Reference","previous_headings":"","what":"Jitters shapes — coo_jitter","title":"Jitters shapes — coo_jitter","text":"simple wrapper around jitter.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Jitters shapes — coo_jitter","text":"","code":"coo_jitter(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Jitters shapes — coo_jitter","text":"coo matrix (x; y) coordinates Coo object. ... additional parameter jitter","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Jitters shapes — coo_jitter","text":"matrix (x; y) coordinates Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Jitters shapes — coo_jitter","text":"","code":"b <-bot[1] coo_plot(b, zoom=0.2) coo_draw(coo_jitter(b, amount=3), border=\"red\") # for a Coo example, see \\link{get_pairs}"},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines landmarks interactively — coo_ldk","title":"Defines landmarks interactively — coo_ldk","text":"Allows interactively define nb.ldk number landarks shape. Used facilities acquire/manipulate data.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines landmarks interactively — coo_ldk","text":"","code":"coo_ldk(coo, nb.ldk, close = FALSE, points = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines landmarks interactively — coo_ldk","text":"coo matrix list (x; y) coordinates. nb.ldk integer, number landmarks define close logical whether close (typically outlines) points logical whether display points","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines landmarks interactively — coo_ldk","text":"numeric corresponds closest ids, shape, cliked points.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines landmarks interactively — coo_ldk","text":"","code":"if (FALSE) { b <- bot[1] coo_ldk(b, 3) # run this, and click 3 times coo_ldk(bot, 2) # this also works on Out }"},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with negative x-coordinates — coo_left","title":"Retains coordinates with negative x-coordinates — coo_left","text":"Useful shapes aligned along y-axis (e.g. bilateral symmetry) one wants retain just lower side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with negative x-coordinates — coo_left","text":"","code":"coo_left(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with negative x-coordinates — coo_left","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_left","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with negative x-coordinates — coo_left","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with negative x-coordinates — coo_left","text":"shapes \"sliced\" along y-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with negative x-coordinates — coo_left","text":"","code":"b <- coo_center(bot[1]) coo_plot(b) coo_draw(coo_left(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the length of a shape — coo_length","title":"Calculates the length of a shape — coo_length","text":"Nothing coo_lw(coo)[1].","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the length of a shape — coo_length","text":"","code":"coo_length(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the length of a shape — coo_length","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the length of a shape — coo_length","text":"length (pixels) shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the length of a shape — coo_length","text":"function can used integrate size - meaningful - Coo objects. See also coo_centsize rescale.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the length of a shape — coo_length","text":"","code":"coo_length(bot[1]) #> [1] 1087.831 coo_length(bot) #> brahma caney chimay corona deusventrue #> 1087.8309 994.1615 643.8746 805.9889 886.0715 #> duvel franziskaner grimbergen guiness hoegardeen #> 606.0107 865.0272 765.0962 742.1752 1048.1058 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 984.2303 718.3227 737.3475 821.1190 686.2766 #> pecheresse sierranevada tanglefoot tauro westmalle #> 928.6771 654.2412 680.6856 984.3941 768.0226 #> amrut ballantines bushmills chivas dalmore #> 864.0899 707.8465 882.0460 793.0187 672.0897 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 608.2238 822.0508 986.0991 705.9991 793.1392 #> jb johnniewalker magallan makersmark oban #> 1008.1334 337.7117 759.0041 851.3161 862.0016 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 596.0958 426.0429 1008.3194 1097.1657 712.1001 mutate(bot, size=coo_length(bot)) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 40 × 3 #> type fake size #> #> 1 whisky a 1088. #> 2 whisky a 994. #> 3 whisky a 644. #> 4 whisky a 806. #> 5 whisky a 886. #> 6 whisky a 606. #> # ℹ 34 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":null,"dir":"Reference","previous_headings":"","what":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"Tests shapes (likely) developping clockwise anticlockwise","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"","code":"coo_likely_clockwise(coo) # S3 method for default coo_likely_clockwise(coo) # S3 method for Coo coo_likely_clockwise(coo) coo_likely_anticlockwise(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"single vector logical.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"","code":"shapes[4] %>% coo_sample(64) %>% coo_plot() #clockwise cat shapes[4] %>% coo_likely_clockwise() #> [1] TRUE shapes[4] %>% coo_rev() %>% coo_likely_clockwise() #> [1] FALSE # on Coo shapes %>% coo_likely_clockwise %>% `[`(4) #> cat #> TRUE"},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots sets of shapes. — coo_listpanel","title":"Plots sets of shapes. — coo_listpanel","text":"coo_listpanel plots list shapes passed list coordinates. Mainly used panel.Coo functions. used outside latter, shapes must \"templated\", see coo_template. want reorder shapes according factor, use arrange.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots sets of shapes. — coo_listpanel","text":"","code":"coo_listpanel( coo.list, dim, byrow = TRUE, fromtop = TRUE, cols, borders, poly = TRUE, points = FALSE, points.pch = 3, points.cex = 0.2, points.col = \"#333333\", ... )"},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots sets of shapes. — coo_listpanel","text":"coo.list list coordinates dim vector form (nb.row, nb.cols) specify panel display. missing, shapes arranged square. byrow logical. Whether draw successive shape row col. fromtop logical. Whether display shapes top plotting region. cols vector colors fill shapes. borders vector colors draw shape borders. poly logical whether use polygon lines draw shapes. mainly use outlines open outlines. points logical poly set FALSE whether add points points.pch points TRUE, pch points points.cex points TRUE, cex points points.col points TRUE, col points ... additional arguments feed generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots sets of shapes. — coo_listpanel","text":"Returns (invisibly) data.frame position shapes can used sophisticated plotting design.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots sets of shapes. — coo_listpanel","text":"","code":"coo_listpanel(bot$coo) # equivalent to panel(bot)"},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots (lollipop) differences between two configurations — coo_lolli","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"Draws 'lollipops' two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"","code":"coo_lolli(coo1, coo2, pch = NA, cex = 0.5, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"coo1 list matrix coordinates. coo2 list matrix coordinates. pch pch points (default NA) cex cex points ... optional parameters fed points segments.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"","code":"coo_lolli(coo_sample(olea[3], 50), coo_sample(olea[6], 50)) title(\"A nice title !\")"},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates length and width of a shape — coo_lw","title":"Calculates length and width of a shape — coo_lw","text":"Returns length width shape based iniertia axis .e. alignment x-axis. length defined range along x-axis; width range y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates length and width of a shape — coo_lw","text":"","code":"coo_lw(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates length and width of a shape — coo_lw","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates length and width of a shape — coo_lw","text":"vector two numeric: length width.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates length and width of a shape — coo_lw","text":"","code":"coo_lw(bot[1]) #> [1] 1087.8309 278.0386"},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":null,"dir":"Reference","previous_headings":"","what":"Counts coordinates — coo_nb","title":"Counts coordinates — coo_nb","text":"Returns number coordinates, single shape Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Counts coordinates — coo_nb","text":"","code":"coo_nb(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Counts coordinates — coo_nb","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Counts coordinates — coo_nb","text":"either single numeric vector numeric","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Counts coordinates — coo_nb","text":"","code":"# single shape coo_nb(bot[1]) #> [1] 138 # Coo object coo_nb(bot) #> brahma caney chimay corona deusventrue #> 138 168 189 129 152 #> duvel franziskaner grimbergen guiness hoegardeen #> 161 124 126 183 193 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 156 182 136 176 146 #> pecheresse sierranevada tanglefoot tauro westmalle #> 129 176 174 174 141 #> amrut ballantines bushmills chivas dalmore #> 191 146 165 164 155 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 169 197 179 169 150 #> jb johnniewalker magallan makersmark oban #> 174 168 141 177 179 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 131 177 176 185 123"},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":null,"dir":"Reference","previous_headings":"","what":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"Shape analysis deals curve fitting, whether \\(x(t)\\) \\(y(t)\\) positions along curvilinear abscissa /radius/tangent angle variation. functions mainly intended (self-)teaching Fourier-based methods.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"","code":"coo_oscillo( coo, method = c(\"efourier\", \"rfourier\", \"tfourier\", \"all\")[4], shape = TRUE, nb.pts = 12 )"},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"coo list matrix coordinates. method character among c('efourier', 'rfourier', 'tfourier', ''). '' default shape logical whether plot original shape nb.pts integer. number reference points, sampled equidistantly along curvilinear abscissa added oscillo curves.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"plotted values","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"","code":"coo_oscillo(shapes[4]) #> [1] 0.00000000 4.70353942 3.90929170 3.90044215 3.89159259 4.66814120 #> [7] 3.87389348 3.07964576 6.21238885 6.20353930 6.19468974 6.18584018 #> [13] 6.17699063 5.38274291 6.15929151 6.15044196 6.14159240 5.34734468 #> [19] 6.12389329 5.32964557 5.32079601 4.52654829 5.30309689 4.50884917 #> [25] 4.49999962 4.49115006 3.69690234 4.47345095 3.67920323 2.88495551 #> [31] 3.66150411 2.86725639 2.85840684 2.84955728 2.84070772 2.83185817 #> [37] 2.82300861 2.81415905 2.80530950 3.58185810 2.78761038 2.77876083 #> [43] 2.76991127 2.76106171 2.75221216 2.74336260 2.73451304 2.72566349 #> [49] 2.71681393 2.70796437 2.69911482 2.69026526 2.68141570 2.67256614 #> [55] 2.66371659 2.65486703 2.64601747 1.85176975 3.41371652 1.83407064 #> [61] 2.61061925 2.60176969 2.59292013 2.58407058 2.57522102 2.56637146 #> [67] 2.55752191 2.54867235 2.53982279 2.53097324 2.52212368 2.51327412 #> [73] 2.50442457 2.49557501 2.48672545 2.47787590 2.46902634 2.46017678 #> [79] 2.45132723 2.44247767 2.43362811 2.42477856 2.41592900 2.40707944 #> [85] 2.39822988 2.38938033 2.38053077 2.37168121 2.36283166 1.56858394 #> [91] 2.34513254 2.33628299 2.32743343 3.88938020 3.88053064 3.87168109 #> [97] 3.07743337 3.85398197 3.84513242 3.83628286 3.82743330 3.81858375 #> [103] 4.59513235 3.80088463 3.79203508 4.56858368 4.55973413 3.76548641 #> [109] 4.54203501 4.53318546 5.30973406 4.51548634 4.50663679 5.28318539 #> [115] 4.48893767 5.26548628 4.47123856 5.24778717 5.23893761 4.44468989 #> [121] 5.22123849 5.21238894 4.41814122 5.19468982 5.18584027 5.17699071 #> [127] 5.16814115 4.37389343 5.15044204 5.14159248 5.13274293 5.12389337 #> [133] 5.11504381 5.10619426 5.09734470 5.08849514 4.29424742 5.07079603 #> [139] 5.06194647 5.05309692 5.04424736 5.03539780 5.02654825 5.80309685 #> [145] 5.00884913 4.99999958 4.99115002 4.98230046 4.97345091 4.96460135 #> [151] 4.95575179 5.73230040 4.93805268 4.92920312 4.92035356 4.91150401 #> [157] 4.90265445 5.67920306 4.88495534 4.87610578 4.86725622 4.85840667 #> [163] 4.84955711 4.84070755 4.83185800 4.82300844 4.81415888 4.80530933 #> [169] 4.79645977 4.00221205 3.99336249 3.19911477 2.40486705 2.39601750 #> [175] 1.60176978 2.37831838 1.58407066 2.36061927 1.56637155 2.34292016 #> [181] 1.54867243 1.53982288 2.31637148 1.52212376 1.51327421 2.28982281 #> [187] 1.49557509 1.48672554 2.26327414 1.46902642 1.46017687 1.45132731 #> [193] 2.22787592 1.43362820 1.42477864 1.41592908 2.19247769 1.39822997 #> [199] 0.60398225 2.16592902 1.37168130 1.36283174 1.35398219 1.34513263 #> [205] 1.33628307 1.32743352 1.31858396 1.30973440 1.30088485 1.29203529 #> [211] 1.28318573 1.27433617 1.26548662 1.25663706 1.24778750 1.23893795 #> [217] 1.23008839 1.22123883 1.21238928 0.41814156 1.19469016 1.18584061 #> [223] 1.17699105 1.16814149 0.37389377 1.15044238 1.14159282 0.34734510 #> [229] 1.12389371 1.11504415 0.32079643 1.09734504 0.30309732 1.07964593 #> [235] 0.28539821 1.06194681 0.26769909 0.25884954 1.03539814 0.24115042 #> [241] 0.23230087 0.22345131 0.21460175 0.20575219 0.19690264 0.18805308 #> [247] 5.67699067 0.17035397 5.65929155 0.15265485 5.64159244 0.13495574 #> [253] 5.62389333 5.61504377 0.10840707 5.59734466 5.58849510 5.57964554 #> [259] 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 5.52654820 #> [265] 5.51769865 5.50884909 5.49999953 4.70575181 5.48230042 5.47345086 #> [271] 4.67920314 5.45575175 5.44690219 4.65265447 5.42920308 5.42035352 #> [277] 4.62610580 4.61725625 5.39380485 5.38495529 5.37610574 4.58185802 #> [283] 5.35840662 6.13495523 4.55530935 5.33185795 5.32300840 5.31415884 #> [289] 5.30530928 6.08185789 4.50221201 6.06415878 5.26991106 5.26106150 #> [295] 5.25221194 5.24336239 6.01991099 4.44026511 6.00221188 5.20796416 #> [301] 5.19911460 5.19026505 5.18141549 5.17256593 5.16371638 5.94026498 #> [307] 5.14601726 4.35176954 5.12831815 5.11946859 5.89601720 5.10176948 #> [313] 5.09291992 5.08407036 5.07522081 5.06637125 5.05752169 5.04867214 #> [319] 5.03982258 5.03097302 5.02212347 5.01327391 5.00442435 4.99557480 #> [325] 4.98672524 4.97787568 4.96902613 4.96017657 4.95132701 4.94247746 #> [331] 4.93362790 4.13938018 4.91592879 5.69247739 4.11283151 4.88938012 #> [337] 4.88053056 4.87168100 4.86283145 4.06858373 4.84513233 4.83628278 #> [343] 4.04203506 4.81858366 4.80973410 4.01548638 4.79203499 3.99778727 #> [349] 4.77433588 3.98008816 4.75663676 3.96238904 4.73893765 3.94468993 #> [355] 4.72123854 3.92699082 4.70353942 3.90929170 4.68584031 3.89159259 #> [361] 4.66814120 3.87389348 4.65044208 3.85619436 3.84734481 3.83849525 #> [367] 4.61504386 3.82079614 3.81194658 4.58849519 3.79424747 3.78539791 #> [373] 3.77654835 3.76769880 3.75884924 3.74999968 3.74115012 3.73230057 #> [379] 3.72345101 3.71460145 2.92035373 3.69690234 2.90265462 3.67920323 #> [385] 2.88495551 2.87610595 3.65265456 2.85840684 2.84955728 3.62610589 #> [391] 2.83185817 2.82300861 3.59955722 3.59070766 2.79645994 3.57300855 #> [397] 2.77876083 3.55530943 3.54645988 2.75221216 3.52876076 3.51991121 #> [403] 3.51106165 3.50221209 3.49336254 3.48451298 3.47566342 4.25221203 #> [409] 3.45796431 3.44911475 4.22566336 3.43141564 4.20796424 3.41371652 #> [415] 4.19026513 4.18141557 4.17256602 4.16371646 4.15486690 4.14601735 #> [421] 4.92256595 3.34292007 4.11946868 4.11061912 4.10176956 3.30752184 #> [427] 4.08407045 4.07522089 3.28097317 4.05752178 3.26327406 4.03982267 #> [433] 4.03097311 3.23672539 3.22787583 4.00442444 3.21017672 3.98672533 #> [439] 3.19247761 3.18362805 3.17477849 3.16592893 3.15707938 2.36283166 #> [445] 3.13938026 3.13053071 2.33628299 3.11283159 2.31858387 3.09513248 #> [451] 3.08628292 3.07743337 3.85398197 3.84513242 3.05088470 3.82743330 #> [457] 3.03318558 3.80973419 3.01548647 3.00663691 3.78318552 2.98893780 #> [463] 2.98008824 3.75663685 2.96238913 2.95353957 2.15929185 2.93584046 #> [469] 2.14159274 1.34734502 1.33849546 1.32964590 0.53539818 0.52654863 #> [475] 0.51769907 1.29424768 5.99778710 0.49115040 0.48230084 1.25884945 #> [481] 0.46460173 0.45575217 0.44690262 0.43805306 0.42920350 0.42035395 #> [487] 0.41150439 0.40265483 0.39380528 1.95575205 1.94690249 1.15265477 #> [493] 1.92920338 1.92035382 1.12610610 1.90265471 1.10840699 1.88495559 #> [499] 1.09070787 1.86725648 1.07300876 0.27876104 1.05530964 1.04646009 #> [505] 0.25221237 1.02876097 1.01991142 1.01106186 1.78761047 1.77876091 #> [511] 0.98451319 1.76106180 0.96681408 0.95796452 0.16371680 0.94026541 #> [517] 0.14601769 5.63495527 0.12831857 0.11946902 5.60840660 0.10176990 #> [523] 0.09292035 5.58185793 5.57300838 5.56415882 5.55530926 5.54645971 #> [529] 5.53761015 5.52876059 4.73451287 5.51106148 5.50221192 4.70796420 #> [535] 5.48451281 5.47566325 6.25221186 6.24336230 6.23451274 6.22566319 #> [541] 6.21681363 6.20796407 6.19911452 0.69247782 5.39601724 0.67477870 #> [547] 6.16371629 6.15486673 6.14601718 6.13716762 0.63053092 5.33407034 #> [553] 0.61283181 6.10176939 6.09291984 6.08407028 6.07522072 6.06637117 #> [559] 6.05752161 0.55088491 5.25442433 6.03097294 6.02212338 6.01327383 #> [565] 6.00442427 0.49778757 5.20132699 5.97787560 5.96902604 5.96017649 #> [571] 5.95132693 5.94247737 5.93362781 5.92477826 5.13053054 5.90707914 #> [577] 5.89822959 5.10398187 5.88053047 5.87168092 5.07743320 5.85398180 #> [583] 5.05973408 5.05088453 5.82743313 5.03318541 5.02433586 5.80088446 #> [589] 5.00663674 4.99778719 5.77433579 4.98008807 4.97123852 5.74778712 #> [595] 5.73893757 4.94468985 4.93584029 5.71238890 5.70353934 4.90929162 #> [601] 5.68584023 5.67699067 5.66814111 4.87389339 5.65044200 5.64159244 #> [607] 5.63274288 5.62389333 4.82964561 5.60619421 5.59734466 5.58849510 #> [613] 5.57964554 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 #> [619] 5.52654820 5.51769865 5.50884909 5.49999953 5.49114998 5.48230042 #> [625] 5.47345086 5.46460131 5.45575175 5.44690219 5.43805264 5.42920308 #> [631] 5.42035352 5.41150397 5.40265441 5.39380485 5.38495529 5.37610574 #> [637] 5.36725618 5.35840662 5.34955707 5.34070751 5.33185795 5.32300840 #> [643] 6.09955700 5.30530928 5.29645973 5.28761017 5.27876061 5.26991106 #> [649] 5.26106150 6.03761011 0.53097341 6.01991099 0.51327429 0.50442474 #> [655] 0.49557518 5.98451277 0.47787607 0.46902651 5.95796410 5.16371638 #> [661] 5.94026498 4.36061910 5.13716771 4.34291999 4.33407043 4.32522087 #> [667] 5.88716764 4.30752176 5.86946853 4.28982264 4.28097309 4.27212353 #> [673] 3.47787581 4.25442442 3.46017670 3.45132714 3.44247758 3.43362803 #> [679] 3.42477847 3.41592891 3.40707936 3.39822980 3.38938024 2.59513252 #> [685] 3.37168113 2.57743341 2.56858385 2.55973430 2.55088474 2.54203518 #> [691] 2.53318563 1.73893791 2.51548651 2.50663696 1.71238924 2.48893784 #> [697] 1.69469012 2.47123873 1.67699101 2.45353961 1.65929189 1.65044234 #> [703] 2.42699094 1.63274322 1.62389367 3.18584044 4.74778721 4.73893765 #> [709] 4.73008809 3.93584037 coo_oscillo(shapes[4], 'efourier') #> # A tibble: 710 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -1 #> 3 -1 -2 #> 4 -2 -3 #> 5 -3 -4 #> 6 -3 -5 #> 7 -4 -6 #> 8 -5 -6 #> 9 -4 -6 #> 10 -3 -6 #> # ℹ 700 more rows coo_oscillo(shapes[4], 'rfourier') #> [1] 34.28884 35.22856 35.85539 36.52625 37.23875 38.21062 38.96933 #> [8] 38.77938 38.96933 39.18390 39.42267 39.68521 39.97105 41.22840 #> [15] 41.55177 41.89653 42.26213 43.56815 43.96536 45.28850 46.61700 #> [22] 47.52337 48.85250 49.75835 50.66774 51.58049 52.10667 53.03236 #> [29] 53.60027 53.25618 53.87744 53.57247 53.28452 53.01388 52.76080 #> [36] 52.52555 52.30835 52.10945 51.92905 52.75589 52.61573 52.49424 #> [43] 52.39157 52.30782 52.24307 52.19741 52.17088 52.16351 52.17531 #> [50] 52.20626 52.25633 52.32548 52.41361 52.52064 52.64645 52.79090 #> [57] 52.95385 52.15376 53.33453 52.57829 52.81768 53.07484 53.34950 #> [64] 53.64141 53.95027 54.27580 54.61770 54.97567 55.34939 55.73855 #> [71] 56.14283 56.56190 56.99543 57.44311 57.90459 58.37955 58.86768 #> [78] 59.36863 59.88210 60.40775 60.94528 61.49438 62.05473 62.62604 #> [85] 63.20800 63.80033 64.40274 65.01495 65.63669 65.49870 66.14613 #> [92] 66.80226 67.46682 68.21363 68.96685 69.72627 71.13586 71.90019 #> [99] 72.67024 73.44584 74.22680 75.01296 75.20000 76.00241 76.80946 #> [106] 77.04407 77.30385 78.13586 78.43027 78.74899 78.23153 78.58924 #> [113] 78.97065 78.49288 78.91279 78.46017 78.91827 78.49116 78.07453 #> [120] 78.58580 78.19525 77.81559 78.37960 78.02647 77.68461 77.35417 #> [127] 77.03530 77.68226 77.39058 77.11077 76.84296 76.58726 76.34381 #> [134] 76.11273 75.89411 75.68808 76.47732 76.29908 76.13356 75.98084 #> [141] 75.84100 75.71411 75.60023 74.50394 74.41509 74.33959 74.27748 #> [148] 74.22879 74.19355 74.17177 74.16347 73.16873 73.18765 73.22022 #> [155] 73.26643 73.32625 73.39964 72.49103 72.59283 72.70824 72.83719 #> [162] 72.97963 73.13546 73.30460 73.48696 73.68244 73.89094 74.11235 #> [169] 74.34655 75.56127 76.78281 77.74913 78.46964 79.20886 78.98907 #> [176] 79.76109 79.56797 80.37176 80.20506 81.03955 80.89895 80.77048 #> [183] 81.64820 81.54545 81.45484 82.37383 82.30844 82.25515 83.21339 #> [190] 83.18473 83.16808 83.16346 84.17077 84.18996 84.22102 84.26394 #> [197] 85.31688 85.38267 84.46363 85.54918 85.64983 85.76202 85.88571 #> [204] 86.02085 86.16738 86.32525 86.49439 86.67474 86.86623 87.06878 #> [211] 87.28232 87.50677 87.74204 87.98805 88.24470 88.51191 88.78958 #> [218] 89.07761 89.37590 88.73531 89.05721 89.38914 89.73098 90.08263 #> [225] 89.51415 89.88890 90.27317 89.75049 90.15753 90.57379 90.09726 #> [232] 90.53589 90.09246 90.55320 90.14314 90.62570 90.24922 89.89341 #> [239] 90.41049 90.08863 89.78789 89.50849 89.25062 89.01448 88.80024 #> [246] 88.60805 87.81833 87.65822 86.88289 86.75564 85.99543 85.90180 #> [253] 85.15746 84.41839 84.37043 83.64833 82.93200 82.22159 81.51725 #> [260] 80.81915 80.12746 79.44232 78.76392 78.09244 77.42804 76.77093 #> [267] 76.12127 74.71205 74.07134 73.43866 72.03249 71.40975 70.79566 #> [274] 69.39357 68.79056 68.19688 66.80013 65.40412 64.82571 64.25765 #> [281] 63.70023 62.31502 61.77244 62.09459 60.72216 60.21507 59.72041 #> [288] 59.23851 58.76967 59.20961 57.87245 58.35344 57.94651 57.55407 #> [295] 57.17643 56.81388 57.40838 56.13523 56.77207 56.47780 56.19977 #> [302] 55.93825 55.69346 55.46561 55.25493 56.04473 55.87204 54.72776 #> [309] 54.58755 54.46535 55.35682 55.27252 55.20620 55.15793 55.12777 #> [316] 55.11574 55.12184 55.14609 55.18844 55.24887 55.32730 55.42367 #> [323] 55.53789 55.66983 55.81938 55.98640 56.17072 56.37218 56.59060 #> [330] 56.82578 57.07752 56.38515 56.67414 57.92981 57.30013 57.63660 #> [337] 57.98837 58.35516 58.73668 58.21890 58.63543 59.06595 58.61935 #> [344] 59.08386 59.56152 59.18629 59.69666 59.37283 59.91499 59.64267 #> [351] 60.21563 59.99470 60.59734 60.42747 61.05860 60.93927 61.59763 #> [358] 61.52813 62.21241 62.19185 62.90071 62.92807 63.66015 63.73427 #> [365] 63.83964 63.97610 64.75812 64.93887 65.14982 65.96342 66.21642 #> [372] 66.49855 66.80942 67.14865 67.51580 67.91043 68.33204 68.78016 #> [379] 69.25426 69.75382 69.35679 69.89854 69.53111 70.11432 69.77669 #> [386] 69.45182 70.09278 69.79804 69.51644 70.21380 69.96247 69.72457 #> [393] 70.47665 71.24886 71.05751 71.86523 71.70342 72.54532 73.40480 #> [400] 73.28734 74.17868 75.08608 76.00895 76.94676 77.89895 78.86500 #> [407] 79.84441 80.84432 81.83670 82.84134 83.84129 84.85755 85.85730 #> [414] 86.88451 87.88397 88.88344 89.88292 90.88241 91.88191 92.88142 #> [421] 93.85554 94.88048 95.88002 96.87957 97.87913 98.91293 99.91216 #> [428] 100.91141 101.95369 102.95256 104.00323 105.00164 106.00008 107.05821 #> [435] 108.12447 109.12184 110.19536 111.19213 112.27258 113.36038 114.45531 #> [442] 115.55717 116.66577 116.78900 117.91146 119.04014 119.18609 120.32775 #> [449] 120.48874 121.64283 122.80236 123.96718 124.95013 125.93335 127.10095 #> [456] 128.08327 129.25466 130.23609 131.41112 132.59082 133.57020 134.75326 #> [463] 135.94073 136.91806 138.10864 139.30341 139.52852 140.73255 140.96957 #> [470] 140.24449 139.52997 138.82618 137.86237 136.89909 135.93634 135.25082 #> [477] 134.01247 133.05137 132.09086 131.41572 130.45849 129.50191 128.54599 #> [484] 127.59074 126.63619 125.68234 124.72922 123.77683 122.82521 123.13732 #> [491] 123.45675 122.84000 123.17644 123.52005 122.93616 123.29667 122.73616 #> [498] 123.11350 122.57662 122.97072 122.45772 121.54514 121.05088 120.57119 #> [505] 119.66929 119.20920 118.76418 118.33438 118.80149 119.27516 118.88086 #> [512] 119.37097 119.00220 118.64915 117.79197 117.46081 116.61205 115.23423 #> [519] 114.38642 113.54110 112.16122 111.31696 110.47530 109.09331 107.71215 #> [526] 106.33186 104.95248 103.57404 102.19657 100.82012 100.29919 98.92667 #> [533] 97.55533 97.04779 95.68088 94.31537 93.44900 92.58533 91.72442 #> [540] 90.86637 90.01124 89.15913 88.31012 88.00439 86.62177 86.33323 #> [547] 85.50294 84.67632 83.85348 83.03453 82.80597 81.40876 81.20026 #> [554] 80.40404 79.61241 78.82552 78.04351 77.26653 76.49472 76.37761 #> [561] 74.96730 74.21201 73.46257 72.71916 71.98197 71.94094 70.52699 #> [568] 69.80962 69.09928 68.39618 67.70055 67.01262 66.33263 65.66083 #> [575] 64.24875 63.58639 62.93294 61.52327 60.88054 60.24755 58.84152 #> [582] 58.22071 56.81733 55.41450 54.80961 53.41022 52.01162 51.42505 #> [589] 50.03093 48.63796 48.07263 46.68550 45.30004 44.75958 44.23513 #> [596] 42.86379 41.49533 41.00231 40.52797 39.18002 38.73500 38.31093 #> [603] 37.90850 36.60071 36.23449 35.89241 35.57516 35.28341 34.05109 #> [610] 33.80538 33.58765 33.39846 33.23829 33.10756 33.00662 32.93576 #> [617] 32.89515 32.88491 32.90508 32.95559 33.03631 33.14701 33.28740 #> [624] 33.45711 33.65568 33.88261 34.13735 34.41925 34.72768 35.06193 #> [631] 35.42126 35.80492 36.21214 36.64213 37.09410 37.56726 38.06082 #> [638] 38.57399 39.10600 39.65610 40.22354 40.80759 42.20611 42.80984 #> [645] 43.42821 44.06059 44.70640 45.36507 46.03603 47.44904 48.18901 #> [652] 49.60118 50.34924 51.10592 51.87084 53.27926 54.05043 54.82898 #> [659] 56.23445 56.86510 58.27294 58.15749 58.81854 58.75524 58.72594 #> [666] 58.73069 60.14474 60.18261 61.59580 61.66523 61.76697 61.90086 #> [673] 61.27762 61.46141 60.86654 60.28239 59.70928 59.14752 58.59744 #> [680] 58.05937 57.53366 57.02063 56.52065 55.15875 54.67832 53.32563 #> [687] 51.97622 50.63034 49.28829 47.95039 46.61700 45.71452 44.38155 #> [694] 43.05376 42.14616 40.81915 39.91086 38.58472 37.67564 36.35049 #> [701] 35.44054 34.53556 33.20556 32.29988 31.39993 30.97074 31.88281 #> [708] 32.80000 33.72190 34.28884 coo_oscillo(shapes[4], 'tfourier') #> [1] 0.00000000 4.70353942 3.90929170 3.90044215 3.89159259 4.66814120 #> [7] 3.87389348 3.07964576 6.21238885 6.20353930 6.19468974 6.18584018 #> [13] 6.17699063 5.38274291 6.15929151 6.15044196 6.14159240 5.34734468 #> [19] 6.12389329 5.32964557 5.32079601 4.52654829 5.30309689 4.50884917 #> [25] 4.49999962 4.49115006 3.69690234 4.47345095 3.67920323 2.88495551 #> [31] 3.66150411 2.86725639 2.85840684 2.84955728 2.84070772 2.83185817 #> [37] 2.82300861 2.81415905 2.80530950 3.58185810 2.78761038 2.77876083 #> [43] 2.76991127 2.76106171 2.75221216 2.74336260 2.73451304 2.72566349 #> [49] 2.71681393 2.70796437 2.69911482 2.69026526 2.68141570 2.67256614 #> [55] 2.66371659 2.65486703 2.64601747 1.85176975 3.41371652 1.83407064 #> [61] 2.61061925 2.60176969 2.59292013 2.58407058 2.57522102 2.56637146 #> [67] 2.55752191 2.54867235 2.53982279 2.53097324 2.52212368 2.51327412 #> [73] 2.50442457 2.49557501 2.48672545 2.47787590 2.46902634 2.46017678 #> [79] 2.45132723 2.44247767 2.43362811 2.42477856 2.41592900 2.40707944 #> [85] 2.39822988 2.38938033 2.38053077 2.37168121 2.36283166 1.56858394 #> [91] 2.34513254 2.33628299 2.32743343 3.88938020 3.88053064 3.87168109 #> [97] 3.07743337 3.85398197 3.84513242 3.83628286 3.82743330 3.81858375 #> [103] 4.59513235 3.80088463 3.79203508 4.56858368 4.55973413 3.76548641 #> [109] 4.54203501 4.53318546 5.30973406 4.51548634 4.50663679 5.28318539 #> [115] 4.48893767 5.26548628 4.47123856 5.24778717 5.23893761 4.44468989 #> [121] 5.22123849 5.21238894 4.41814122 5.19468982 5.18584027 5.17699071 #> [127] 5.16814115 4.37389343 5.15044204 5.14159248 5.13274293 5.12389337 #> [133] 5.11504381 5.10619426 5.09734470 5.08849514 4.29424742 5.07079603 #> [139] 5.06194647 5.05309692 5.04424736 5.03539780 5.02654825 5.80309685 #> [145] 5.00884913 4.99999958 4.99115002 4.98230046 4.97345091 4.96460135 #> [151] 4.95575179 5.73230040 4.93805268 4.92920312 4.92035356 4.91150401 #> [157] 4.90265445 5.67920306 4.88495534 4.87610578 4.86725622 4.85840667 #> [163] 4.84955711 4.84070755 4.83185800 4.82300844 4.81415888 4.80530933 #> [169] 4.79645977 4.00221205 3.99336249 3.19911477 2.40486705 2.39601750 #> [175] 1.60176978 2.37831838 1.58407066 2.36061927 1.56637155 2.34292016 #> [181] 1.54867243 1.53982288 2.31637148 1.52212376 1.51327421 2.28982281 #> [187] 1.49557509 1.48672554 2.26327414 1.46902642 1.46017687 1.45132731 #> [193] 2.22787592 1.43362820 1.42477864 1.41592908 2.19247769 1.39822997 #> [199] 0.60398225 2.16592902 1.37168130 1.36283174 1.35398219 1.34513263 #> [205] 1.33628307 1.32743352 1.31858396 1.30973440 1.30088485 1.29203529 #> [211] 1.28318573 1.27433617 1.26548662 1.25663706 1.24778750 1.23893795 #> [217] 1.23008839 1.22123883 1.21238928 0.41814156 1.19469016 1.18584061 #> [223] 1.17699105 1.16814149 0.37389377 1.15044238 1.14159282 0.34734510 #> [229] 1.12389371 1.11504415 0.32079643 1.09734504 0.30309732 1.07964593 #> [235] 0.28539821 1.06194681 0.26769909 0.25884954 1.03539814 0.24115042 #> [241] 0.23230087 0.22345131 0.21460175 0.20575219 0.19690264 0.18805308 #> [247] 5.67699067 0.17035397 5.65929155 0.15265485 5.64159244 0.13495574 #> [253] 5.62389333 5.61504377 0.10840707 5.59734466 5.58849510 5.57964554 #> [259] 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 5.52654820 #> [265] 5.51769865 5.50884909 5.49999953 4.70575181 5.48230042 5.47345086 #> [271] 4.67920314 5.45575175 5.44690219 4.65265447 5.42920308 5.42035352 #> [277] 4.62610580 4.61725625 5.39380485 5.38495529 5.37610574 4.58185802 #> [283] 5.35840662 6.13495523 4.55530935 5.33185795 5.32300840 5.31415884 #> [289] 5.30530928 6.08185789 4.50221201 6.06415878 5.26991106 5.26106150 #> [295] 5.25221194 5.24336239 6.01991099 4.44026511 6.00221188 5.20796416 #> [301] 5.19911460 5.19026505 5.18141549 5.17256593 5.16371638 5.94026498 #> [307] 5.14601726 4.35176954 5.12831815 5.11946859 5.89601720 5.10176948 #> [313] 5.09291992 5.08407036 5.07522081 5.06637125 5.05752169 5.04867214 #> [319] 5.03982258 5.03097302 5.02212347 5.01327391 5.00442435 4.99557480 #> [325] 4.98672524 4.97787568 4.96902613 4.96017657 4.95132701 4.94247746 #> [331] 4.93362790 4.13938018 4.91592879 5.69247739 4.11283151 4.88938012 #> [337] 4.88053056 4.87168100 4.86283145 4.06858373 4.84513233 4.83628278 #> [343] 4.04203506 4.81858366 4.80973410 4.01548638 4.79203499 3.99778727 #> [349] 4.77433588 3.98008816 4.75663676 3.96238904 4.73893765 3.94468993 #> [355] 4.72123854 3.92699082 4.70353942 3.90929170 4.68584031 3.89159259 #> [361] 4.66814120 3.87389348 4.65044208 3.85619436 3.84734481 3.83849525 #> [367] 4.61504386 3.82079614 3.81194658 4.58849519 3.79424747 3.78539791 #> [373] 3.77654835 3.76769880 3.75884924 3.74999968 3.74115012 3.73230057 #> [379] 3.72345101 3.71460145 2.92035373 3.69690234 2.90265462 3.67920323 #> [385] 2.88495551 2.87610595 3.65265456 2.85840684 2.84955728 3.62610589 #> [391] 2.83185817 2.82300861 3.59955722 3.59070766 2.79645994 3.57300855 #> [397] 2.77876083 3.55530943 3.54645988 2.75221216 3.52876076 3.51991121 #> [403] 3.51106165 3.50221209 3.49336254 3.48451298 3.47566342 4.25221203 #> [409] 3.45796431 3.44911475 4.22566336 3.43141564 4.20796424 3.41371652 #> [415] 4.19026513 4.18141557 4.17256602 4.16371646 4.15486690 4.14601735 #> [421] 4.92256595 3.34292007 4.11946868 4.11061912 4.10176956 3.30752184 #> [427] 4.08407045 4.07522089 3.28097317 4.05752178 3.26327406 4.03982267 #> [433] 4.03097311 3.23672539 3.22787583 4.00442444 3.21017672 3.98672533 #> [439] 3.19247761 3.18362805 3.17477849 3.16592893 3.15707938 2.36283166 #> [445] 3.13938026 3.13053071 2.33628299 3.11283159 2.31858387 3.09513248 #> [451] 3.08628292 3.07743337 3.85398197 3.84513242 3.05088470 3.82743330 #> [457] 3.03318558 3.80973419 3.01548647 3.00663691 3.78318552 2.98893780 #> [463] 2.98008824 3.75663685 2.96238913 2.95353957 2.15929185 2.93584046 #> [469] 2.14159274 1.34734502 1.33849546 1.32964590 0.53539818 0.52654863 #> [475] 0.51769907 1.29424768 5.99778710 0.49115040 0.48230084 1.25884945 #> [481] 0.46460173 0.45575217 0.44690262 0.43805306 0.42920350 0.42035395 #> [487] 0.41150439 0.40265483 0.39380528 1.95575205 1.94690249 1.15265477 #> [493] 1.92920338 1.92035382 1.12610610 1.90265471 1.10840699 1.88495559 #> [499] 1.09070787 1.86725648 1.07300876 0.27876104 1.05530964 1.04646009 #> [505] 0.25221237 1.02876097 1.01991142 1.01106186 1.78761047 1.77876091 #> [511] 0.98451319 1.76106180 0.96681408 0.95796452 0.16371680 0.94026541 #> [517] 0.14601769 5.63495527 0.12831857 0.11946902 5.60840660 0.10176990 #> [523] 0.09292035 5.58185793 5.57300838 5.56415882 5.55530926 5.54645971 #> [529] 5.53761015 5.52876059 4.73451287 5.51106148 5.50221192 4.70796420 #> [535] 5.48451281 5.47566325 6.25221186 6.24336230 6.23451274 6.22566319 #> [541] 6.21681363 6.20796407 6.19911452 0.69247782 5.39601724 0.67477870 #> [547] 6.16371629 6.15486673 6.14601718 6.13716762 0.63053092 5.33407034 #> [553] 0.61283181 6.10176939 6.09291984 6.08407028 6.07522072 6.06637117 #> [559] 6.05752161 0.55088491 5.25442433 6.03097294 6.02212338 6.01327383 #> [565] 6.00442427 0.49778757 5.20132699 5.97787560 5.96902604 5.96017649 #> [571] 5.95132693 5.94247737 5.93362781 5.92477826 5.13053054 5.90707914 #> [577] 5.89822959 5.10398187 5.88053047 5.87168092 5.07743320 5.85398180 #> [583] 5.05973408 5.05088453 5.82743313 5.03318541 5.02433586 5.80088446 #> [589] 5.00663674 4.99778719 5.77433579 4.98008807 4.97123852 5.74778712 #> [595] 5.73893757 4.94468985 4.93584029 5.71238890 5.70353934 4.90929162 #> [601] 5.68584023 5.67699067 5.66814111 4.87389339 5.65044200 5.64159244 #> [607] 5.63274288 5.62389333 4.82964561 5.60619421 5.59734466 5.58849510 #> [613] 5.57964554 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 #> [619] 5.52654820 5.51769865 5.50884909 5.49999953 5.49114998 5.48230042 #> [625] 5.47345086 5.46460131 5.45575175 5.44690219 5.43805264 5.42920308 #> [631] 5.42035352 5.41150397 5.40265441 5.39380485 5.38495529 5.37610574 #> [637] 5.36725618 5.35840662 5.34955707 5.34070751 5.33185795 5.32300840 #> [643] 6.09955700 5.30530928 5.29645973 5.28761017 5.27876061 5.26991106 #> [649] 5.26106150 6.03761011 0.53097341 6.01991099 0.51327429 0.50442474 #> [655] 0.49557518 5.98451277 0.47787607 0.46902651 5.95796410 5.16371638 #> [661] 5.94026498 4.36061910 5.13716771 4.34291999 4.33407043 4.32522087 #> [667] 5.88716764 4.30752176 5.86946853 4.28982264 4.28097309 4.27212353 #> [673] 3.47787581 4.25442442 3.46017670 3.45132714 3.44247758 3.43362803 #> [679] 3.42477847 3.41592891 3.40707936 3.39822980 3.38938024 2.59513252 #> [685] 3.37168113 2.57743341 2.56858385 2.55973430 2.55088474 2.54203518 #> [691] 2.53318563 1.73893791 2.51548651 2.50663696 1.71238924 2.48893784 #> [697] 1.69469012 2.47123873 1.67699101 2.45353961 1.65929189 1.65044234 #> [703] 2.42699094 1.63274322 1.62389367 3.18584044 4.74778721 4.73893765 #> [709] 4.73008809 3.93584037 #tfourier is prone to high-frequency noise but smoothing can help coo_oscillo(coo_smooth(shapes[4], 10), 'tfourier') #> [1] 0.000000000 6.210281146 6.150339598 6.110870956 6.093957661 6.111051488 #> [7] 6.210841936 0.294826636 1.163080415 1.662325460 1.784906858 1.788459018 #> [13] 1.754364939 1.713694996 1.673686879 1.624391221 1.550688278 1.445544249 #> [19] 1.313650160 1.165054644 1.007403085 0.842241873 0.665533492 0.472501809 #> [25] 0.264958204 0.052746323 6.128257112 5.926985109 5.730762152 5.541624953 #> [31] 5.365867883 5.211467073 5.086389730 4.997097511 4.946510695 4.933000642 #> [37] 4.949742414 4.982955751 5.012460904 5.019029243 4.994585130 4.946466089 #> [43] 4.891849750 4.846153200 4.815140738 4.796127011 4.783744124 4.773987623 #> [49] 4.764958775 4.755946140 4.746333644 4.734694607 4.718307666 4.693917249 #> [55] 4.660156421 4.620031964 4.580677444 4.549991613 4.533287434 4.532292499 #> [61] 4.545279217 4.566934623 4.589359967 4.605421681 4.612112985 4.610800812 #> [67] 4.604740736 4.596653165 4.587948567 4.579116176 4.570267573 4.561418016 #> [73] 4.552568459 4.543718902 4.534869346 4.526019789 4.517170232 4.508320675 #> [79] 4.499471119 4.490620608 4.481752932 4.472741250 4.462985703 4.450603765 #> [85] 4.431608816 4.400770190 4.356068458 4.305424656 4.269520989 4.277135048 #> [91] 4.360538895 4.555194318 4.871254402 5.215038283 5.459664874 5.595213464 #> [97] 5.672103286 5.734294873 5.805171782 5.888871809 5.977816468 6.062603219 #> [103] 6.138686968 6.207147740 6.271367481 0.051070155 0.115529390 0.185002608 #> [109] 0.260266970 0.335648438 0.401580810 0.452499558 0.490752929 0.523002507 #> [115] 0.554570991 0.586753235 0.617247615 0.642073315 0.658350204 0.667047287 #> [121] 0.673606828 0.685132162 0.705052388 0.728633438 0.744734811 0.745801344 #> [127] 0.737404131 0.735346616 0.751874045 0.784845872 0.819132998 0.837128874 #> [133] 0.828297388 0.792765360 0.741689130 0.694623805 0.671233403 0.681431950 #> [139] 0.721943628 0.781107907 0.846153540 0.905318763 0.945847189 0.956185340 #> [145] 0.933520844 0.889053044 0.844590615 0.821054584 0.826911372 0.853852015 #> [151] 0.881659563 0.890921047 0.876241385 0.849987814 0.832106250 0.832287770 #> [157] 0.840824651 0.837648250 0.809803659 0.760803413 0.706008449 0.660112883 #> [163] 0.628012512 0.604377441 0.577183265 0.530156087 0.444950680 0.304766283 #> [169] 0.096072698 6.087754031 5.700461201 5.247258666 4.831451596 4.527523880 #> [175] 4.329498082 4.206491595 4.131062373 4.081089105 4.040449748 4.001478231 #> [181] 3.964579062 3.933656583 3.910945742 3.895211705 3.883184677 3.871266154 #> [187] 3.856146033 3.835553787 3.810038382 3.783889856 3.762402266 3.746921155 #> [193] 3.733416217 3.716285917 3.692075007 3.659767668 3.620829826 3.580502872 #> [199] 3.545836696 3.519458457 3.496862828 3.471910466 3.443688053 3.416538164 #> [205] 3.394773009 3.379129831 3.367634796 3.358040420 3.349046858 3.340179182 #> [211] 3.331310551 3.322298870 3.312543323 3.300160435 3.281145755 3.250115199 #> [217] 3.204257486 3.148748834 3.097182990 3.062798448 3.047139365 3.037836547 #> [223] 3.019070901 2.985270415 2.943990251 2.906371786 2.877162870 2.853033116 #> [229] 2.827294741 2.795605917 2.758775379 2.721017676 2.685491706 2.651638374 #> [235] 2.616756113 2.579249488 2.539266926 2.496642604 2.450285176 2.400599692 #> [241] 2.350909726 2.304563353 2.260820580 2.214420252 2.159471987 2.094718182 #> [247] 2.026085459 1.963248210 1.911995985 1.870137442 1.831022284 1.789478413 #> [253] 1.743510198 1.691608789 1.631150303 1.561569503 1.488650289 1.423172645 #> [259] 1.373787829 1.341690659 1.321606928 1.305654435 1.285571657 1.253491627 #> [265] 1.204250793 1.139519444 1.069263427 1.006648871 0.960120128 0.930025733 #> [271] 0.911026560 0.895946158 0.877978420 0.852313020 0.819389902 0.787791876 #> [277] 0.771357046 0.780349343 0.814054366 0.861526357 0.910083692 0.952417749 #> [283] 0.985608592 1.008800661 1.025873144 1.046448905 1.078707071 1.120695586 #> [289] 1.160889837 1.187477232 1.195902397 1.189182194 1.174564489 1.160112567 #> [295] 1.151279870 1.148175732 1.145840851 1.137610074 1.119048880 1.090947700 #> [301] 1.060659306 1.039140171 1.032285551 1.032745212 1.022979818 0.991476068 #> [307] 0.948086298 0.920008639 0.927148777 0.961284686 0.992101349 0.993873732 #> [313] 0.963915071 0.918406903 0.876060289 0.845934321 0.827081727 0.814716958 #> [319] 0.804962365 0.795950684 0.787083007 0.778231543 0.769363866 0.760353139 #> [325] 0.750614758 0.738375872 0.720105828 0.691716549 0.652608187 0.609790908 #> [331] 0.575970900 0.560292070 0.560253479 0.563707517 0.558656949 0.539780722 #> [337] 0.506825021 0.461757288 0.409794503 0.359637805 0.318856196 0.288830724 #> [343] 0.264555711 0.238816280 0.207252588 0.171067996 0.135611940 0.106165474 #> [349] 0.084689231 0.069773360 0.058688066 0.049228656 0.040263124 0.031399834 #> [355] 0.022548751 0.013684699 0.004705453 6.278316778 6.266646228 6.249714189 #> [361] 6.223378486 6.185711060 6.140814149 6.098429160 6.068030924 6.052616099 #> [367] 6.047041546 6.041070135 6.024843229 5.993927011 5.951419573 5.905757611 #> [373] 5.865459482 5.834682028 5.812125954 5.792458593 5.768502704 5.733457862 #> [379] 5.683206435 5.618467189 5.545329001 5.472432994 5.406413214 5.350205499 #> [385] 5.304888721 5.271062496 5.248378331 5.235801685 5.233541784 5.243796693 #> [391] 5.267701445 5.300728508 5.332712334 5.354453431 5.364377855 5.368534497 #> [397] 5.374741784 5.387390003 5.407383871 5.434201642 5.465689493 5.497519401 #> [403] 5.525769644 5.550355985 5.574942842 5.603203498 5.635133193 5.667217292 #> [409] 5.696503292 5.724011803 5.754170455 5.792492400 5.844118816 5.911952780 #> [415] 5.993258931 6.078066848 6.152989261 6.206858374 6.232226877 6.224754148 #> [421] 6.185255417 6.122244570 6.049372258 5.978525675 5.915552103 5.861307526 #> [427] 5.814628320 5.774712015 5.742004258 5.716275508 5.693379276 5.666055366 #> [433] 5.630481863 5.590829982 5.554144579 5.520973706 5.483347333 5.432738889 #> [439] 5.368764431 5.298373235 5.228480361 5.162317644 5.101305142 5.047172969 #> [445] 5.001770639 4.967325726 4.949028929 4.955822231 4.995559376 5.068649008 #> [451] 5.166128839 5.271169312 5.361943901 5.418816242 5.434261089 5.415787999 #> [457] 5.378749340 5.337253926 5.300066779 5.270326801 5.245798899 5.219095373 #> [463] 5.178948961 5.113005498 5.010509821 4.861906973 4.655872417 4.383607566 #> [469] 4.061035875 3.739006861 3.460013884 3.228975398 3.035724811 2.875726521 #> [475] 2.751418620 2.667347672 2.626605417 2.625083548 2.645200476 2.660136888 #> [481] 2.649921973 2.613646664 2.566698627 2.528381069 2.513356521 2.534150830 #> [487] 2.608723363 2.760815486 2.995303110 3.253844542 3.450019278 3.556829435 #> [493] 3.594254480 3.588553531 3.560325237 3.523018039 3.480988947 3.429095667 #> [499] 3.357730619 3.262973502 3.155419447 3.057566270 2.990178713 2.963327724 #> [505] 2.978269071 3.031263380 3.113254441 3.206490718 3.283579186 3.315652213 #> [511] 3.286439739 3.198490398 3.065780988 2.901072469 2.710327869 2.499825577 #> [517] 2.288736611 2.106853050 1.972716007 1.880608795 1.808217671 1.732016385 #> [523] 1.641441083 1.543848642 1.454766713 1.383471012 1.328109195 1.280445960 #> [529] 1.233298003 1.186051865 1.145835795 1.124395250 1.133998381 1.185203040 #> [535] 1.284655334 1.429095439 1.597639355 1.755997591 1.877909670 1.959627909 #> [541] 2.012852441 2.050062384 2.076448107 2.091254469 2.093166224 2.083874267 #> [547] 2.068528701 2.053935597 2.045086040 2.041980966 2.039645151 2.031397576 #> [553] 2.012695022 1.983859410 1.950961917 1.922825350 1.903874767 1.888886160 #> [559] 1.867115865 1.834104119 1.799091522 1.778085405 1.777842081 1.787473253 #> [565] 1.787246136 1.766366858 1.731953827 1.700820006 1.683021524 1.673232227 #> [571] 1.656126033 1.618934077 1.560828846 1.493152222 1.431106120 1.383899161 #> [577] 1.350760265 1.323321861 1.290847550 1.246070449 1.189727078 1.130361772 #> [583] 1.078468381 1.040047045 1.014823673 0.998771530 0.987568410 0.978706955 #> [589] 0.972097548 0.969825211 0.974911598 0.988572657 1.007325669 1.023813218 #> [595] 1.033242798 1.039315778 1.051423155 1.075752154 1.109940476 1.145106149 #> [601] 1.172013529 1.186848625 1.193363408 1.198926850 1.206369621 1.210402157 #> [607] 1.204972412 1.194030025 1.191273604 1.207820260 1.241670290 1.279478888 #> [613] 1.307637488 1.320968930 1.322284497 1.316968271 1.309024705 1.300337273 #> [619] 1.291505836 1.282657232 1.273807676 1.264958119 1.256108562 1.247259005 #> [625] 1.238409449 1.229559892 1.220710335 1.211860778 1.203011222 1.194161665 #> [631] 1.185312108 1.176462551 1.167613948 1.158782511 1.150095079 1.142151512 #> [637] 1.136835287 1.138149900 1.151463248 1.179461633 1.216397766 1.246996075 #> [643] 1.254805029 1.235032721 1.201996315 1.185517450 1.218031010 1.321091442 #> [649] 1.494393247 1.707858148 1.913968285 2.077528885 2.185390609 2.236504708 #> [655] 2.234154703 2.181616267 2.077397918 1.913965611 1.684446939 1.396172930 #> [661] 1.083379564 0.801165397 0.594838371 0.479858466 0.448502322 0.476558403 #> [667] 0.519940898 0.523261974 0.451098963 0.310029503 0.136270603 6.245725890 #> [673] 6.083883304 5.933308298 5.794794776 5.675631097 5.583900424 5.519806626 #> [679] 5.472922363 5.426039551 5.361978088 5.270595236 5.153649901 5.024269044 #> [685] 4.899718114 4.792550346 4.706581487 4.638154755 4.579941168 4.525357287 #> [691] 4.471842191 4.420780288 4.374056983 4.331365078 4.291374762 4.253868124 #> [697] 4.218994007 4.185218958 4.150165899 4.114424239 4.084166694 4.070249157 #> [703] 4.087829504 4.167359978 4.411768752 5.183594717 6.047475358 0.033827928 #> [709] 0.090954159 0.064865507"},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates perimeter and variations — coo_perim","title":"Calculates perimeter and variations — coo_perim","text":"coo_perim calculates perimeter; coo_perimpts calculates euclidean distance every points shape; coo_perimcum calculates cumulative sum.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates perimeter and variations — coo_perim","text":"","code":"coo_perimpts(coo) # S3 method for default coo_perimpts(coo) # S3 method for Coo coo_perimpts(coo) coo_perimcum(coo) # S3 method for default coo_perimcum(coo) # S3 method for Coo coo_perimcum(coo) coo_perim(coo) # S3 method for default coo_perim(coo) # S3 method for Coo coo_perim(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates perimeter and variations — coo_perim","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates perimeter and variations — coo_perim","text":"numeric distance every point list .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates perimeter and variations — coo_perim","text":"","code":"# for speed sake b1 <- coo_sample(bot[1], 12) b5 <- bot %>% slice(1:5) %>% coo_sample(12) # coo_perim coo_perim(b1) #> [1] 2140.62 coo_perim(b5) #> brahma caney chimay corona deusventrue #> 2140.620 1942.307 1354.083 1555.883 1768.427 # coo_perimpts coo_perimpts(b1) #> [1] 201.6829 212.0424 168.6001 198.8291 189.3198 221.2261 190.0026 206.7293 #> [9] 192.2134 137.2079 222.7667 b5 %>% coo_perimpts() #> $brahma #> [1] 201.6829 212.0424 168.6001 198.8291 189.3198 221.2261 190.0026 206.7293 #> [9] 192.2134 137.2079 222.7667 #> #> $caney #> [1] 192.0000 181.0000 161.9784 175.0457 192.1276 171.0000 186.1317 191.7707 #> [9] 175.3454 134.0149 181.8928 #> #> $chimay #> [1] 131.03435 123.06502 113.22544 128.99612 119.94165 131.03435 140.24621 #> [8] 129.44883 118.37652 97.65244 121.06197 #> #> $corona #> [1] 155.0000 143.0315 131.2288 127.6323 145.0034 155.0000 154.9322 140.3567 #> [9] 151.3275 112.9292 139.4417 #> #> $deusventrue #> [1] 175.1713 163.3065 147.1224 151.2415 175.5591 162.3730 182.3623 171.8430 #> [9] 157.6230 131.8218 150.0033 #> # coo_perimcum b1 %>% coo_perimcum() #> [1] 0.0000 201.6829 413.7254 582.3255 781.1546 970.4744 1191.7005 #> [8] 1381.7032 1588.4324 1780.6459 1917.8537 2140.6204 b5 %>% coo_perimcum() #> $brahma #> [1] 0.0000 201.6829 413.7254 582.3255 781.1546 970.4744 1191.7005 #> [8] 1381.7032 1588.4324 1780.6459 1917.8537 2140.6204 #> #> $caney #> [1] 0.0000 192.0000 373.0000 534.9784 710.0241 902.1517 1073.1517 #> [8] 1259.2833 1451.0540 1626.3994 1760.4143 1942.3072 #> #> $chimay #> [1] 0.0000 131.0343 254.0994 367.3248 496.3209 616.2626 747.2969 #> [8] 887.5431 1016.9920 1135.3685 1233.0209 1354.0829 #> #> $corona #> [1] 0.0000 155.0000 298.0315 429.2603 556.8926 701.8960 856.8960 #> [8] 1011.8282 1152.1849 1303.5124 1416.4416 1555.8833 #> #> $deusventrue #> [1] 0.0000 175.1713 338.4778 485.6002 636.8417 812.4008 974.7739 #> [8] 1157.1361 1328.9791 1486.6021 1618.4239 1768.4272 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a single shape — coo_plot","title":"Plots a single shape — coo_plot","text":"simple wrapper around plot plotting shapes. Widely used Momocs graphical functions, methods, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a single shape — coo_plot","text":"","code":"coo_plot( coo, xlim, ylim, border = \"#333333\", col = NA, lwd = 1, lty = 1, points = FALSE, first.point = TRUE, cex.first.point = 0.5, centroid = TRUE, xy.axis = TRUE, pch = 1, cex = 0.5, main = NA, poly = TRUE, plot.new = TRUE, plot = TRUE, zoom = 1, ... ) ldk_plot(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a single shape — coo_plot","text":"coo list matrix coordinates. xlim coo_plot called coo missing, vector length 2 specifying ylim ploting area. ylim coo_plot called coo missing, vector length 2 specifying ylim ploting area. border color shape border. col color fill shape polygon. lwd lwd drawing shapes. lty lty drawing shapes. points logical. Whether display points. missing number points < 100, points plotted. first.point logical whether plot first point. cex.first.point numeric size first point centroid logical. Whether display centroid. xy.axis logical. Whether draw xy axis. pch pch points. cex cex points. main character. title plot. poly logical whether use polygon lines draw shape, just points. words, whether shape considered configuration landmarks (eg closed outline). plot.new logical whether plot new frame. plot logical whether plot something just create empty plot. zoom numeric take distances. ... arguments use coo_plot methods. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a single shape — coo_plot","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a single shape — coo_plot","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(bot[2], plot.new=FALSE) # equivalent to coo_draw(bot[2]) coo_plot(b, zoom=2) coo_plot(b, border='blue') coo_plot(b, first.point=FALSE, centroid=FALSE) coo_plot(b, points=TRUE, pch=20) coo_plot(b, xy.axis=FALSE, lwd=2, col='#F2F2F2')"},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate coordinates range — coo_range","title":"Calculate coordinates range — coo_range","text":"coo_range simply returns range, coo_range_enlarge enlarges k proportion. coo_diffrange return amplitude (ie diff coo_range)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate coordinates range — coo_range","text":"","code":"coo_range(coo) # S3 method for default coo_range(coo) # S3 method for Coo coo_range(coo) coo_range_enlarge(coo, k) # S3 method for default coo_range_enlarge(coo, k = 0) # S3 method for Coo coo_range_enlarge(coo, k = 0) # S3 method for list coo_range_enlarge(coo, k = 0) coo_diffrange(coo) # S3 method for default coo_diffrange(coo) # S3 method for Coo coo_diffrange(coo) # S3 method for list coo_diffrange(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate coordinates range — coo_range","text":"coo matrix (x; y) coordinates Coo object. k numeric proportion enlarge ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate coordinates range — coo_range","text":"matrix range (min, max) x (x, y)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate coordinates range — coo_range","text":"","code":"bot[1] %>% coo_range # single shape #> x y #> min 33 14 #> max 316 1102 bot %>% coo_range # Coo object #> x y #> min 8 3 #> max 345 1120 bot[1] %>% coo_range_enlarge(1/50) # single shape #> x y #> min 27.34 -7.76 #> max 321.66 1123.76 bot %>% coo_range_enlarge(1/50) # Coo object #> x y #> min 1.26 -19.34 #> max 351.74 1142.34"},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the rectangularity of a shape — coo_rectangularity","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"Calculates rectangularity shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"","code":"coo_rectangularity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"","code":"coo_rectangularity(bot[1]) #> [1] 0.7753614 bot %>% slice(1:3) %>% # for speed sake only coo_rectangularity #> $brahma #> [1] 0.7753614 #> #> $caney #> [1] 0.7772434 #> #> $chimay #> [1] 0.7695281 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the rectilinearity of a shape — coo_rectilinearity","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"proposed Zunic Rosin (see ). May need testing/review.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"","code":"coo_rectilinearity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"Zunic J, Rosin PL. 2003. Rectilinearity measurements polygons. IEEE Transactions Pattern Analysis Machine Intelligence 25: 1193-1200.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"numeric single shape, list Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"due laborious nature algorithm (nb.pts^2), implementation, may long compute.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"","code":"bot[1] %>% coo_sample(32) %>% # for speed sake only coo_rectilinearity #> [1] 0.3539899 bot %>% slice(1:3) %>% coo_sample(32) %>% # for speed sake only coo_rectilinearity #> $brahma #> [1] 0.3539899 #> #> $caney #> [1] 0.3751378 #> #> $chimay #> [1] 0.3597856 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":null,"dir":"Reference","previous_headings":"","what":"Reverses coordinates — coo_rev","title":"Reverses coordinates — coo_rev","text":"Returns reverse suite coordinates, .e. change shape's orientation","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reverses coordinates — coo_rev","text":"","code":"coo_rev(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reverses coordinates — coo_rev","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reverses coordinates — coo_rev","text":"matrix (x; y) coordinates Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reverses coordinates — coo_rev","text":"","code":"b <- coo_sample(bot[1], 4) b #> [,1] [,2] #> [1,] 37 561 #> [2,] 143 15 #> [3,] 295 523 #> [4,] 205 1101 coo_rev(b) #> [,1] [,2] #> [1,] 205 1101 #> [2,] 295 523 #> [3,] 143 15 #> [4,] 37 561"},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with positive x-coordinates — coo_right","title":"Retains coordinates with positive x-coordinates — coo_right","text":"Useful shapes aligned along y-axis (e.g. bilateral symmetry) one wants retain just upper side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with positive x-coordinates — coo_right","text":"","code":"coo_right(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with positive x-coordinates — coo_right","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_right","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with positive x-coordinates — coo_right","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with positive x-coordinates — coo_right","text":"shapes \"sliced\" along y-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with positive x-coordinates — coo_right","text":"","code":"b <- coo_center(bot[1]) coo_plot(b) coo_draw(coo_right(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":null,"dir":"Reference","previous_headings":"","what":"Rotates coordinates — coo_rotate","title":"Rotates coordinates — coo_rotate","text":"Rotates coordinates 'theta' angle (radians) trigonometric direction (anti-clockwise). provided, assumed centroid size. involves three steps: centering current position, dividing coordinates 'scale', translating original position.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rotates coordinates — coo_rotate","text":"","code":"coo_rotate(coo, theta = 0)"},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rotates coordinates — coo_rotate","text":"coo either matrix (x; y) coordinates, Coo object. theta numericthe angle (radians) rotate shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rotates coordinates — coo_rotate","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rotates coordinates — coo_rotate","text":"","code":"coo_plot(bot[1]) coo_plot(coo_rotate(bot[1], pi/2)) # on Coo b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_rotate(b, pi/2))"},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":null,"dir":"Reference","previous_headings":"","what":"Rotates shapes with a custom center — coo_rotatecenter","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"rotates shape 'theta' angles (radians) (x; y) 'center'.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"","code":"coo_rotatecenter(coo, theta, center = c(0, 0))"},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"coo matrix (x; y) coordinates Coo object. theta numeric angle (radians) rotate shapes. center numeric (x; y) position center","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"","code":"b <- bot[1] coo_plot(b) coo_draw(coo_rotatecenter(b, -pi/2, c(200, 200)), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots differences as (colored) segments aka a ruban — coo_ruban","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"Useful display differences shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"","code":"coo_ruban(coo, dev, palette = col_heat, normalize = TRUE, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"coo shape, typically mean shape dev numeric vector distances anythinh relevant palette color palette use palette normalize logical whether normalize (TRUE default) distances ... parameters fed segments, eg lwd (see examples)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"","code":"ms <- MSHAPES(efourier(bot , 10), \"type\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details b <- ms$shp$beer w <- ms$shp$whisky # we obtain the mean shape, then euclidean distances between points m <- MSHAPES(list(b, w)) d <- edm(b, w) # First plot coo_plot(m, plot=FALSE) coo_draw(b) coo_draw(w) coo_ruban(m, d, lwd=5) #Another example coo_plot(m, plot=FALSE) coo_ruban(m, d, palette=col_summer2, lwd=5) #If you want linewidth rather than color coo_plot(m, plot=FALSE) coo_ruban(m, d, palette=col_black)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample coordinates (among points) — coo_sample","title":"Sample coordinates (among points) — coo_sample","text":"Sample n coordinates among existing points.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample coordinates (among points) — coo_sample","text":"","code":"coo_sample(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample coordinates (among points) — coo_sample","text":"coo either matrix (x; y) coordinates Opn object. n integer, number fo points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample coordinates (among points) — coo_sample","text":"matrix (x; y) coordinates, Opn object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Sample coordinates (among points) — coo_sample","text":"Opn methods (pointless Ldk), $ldk component defined, changed accordingly multiplying ids n number coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample coordinates (among points) — coo_sample","text":"","code":"b <- bot[1] stack(bot) stack(coo_sample(bot, 24)) coo_plot(b) coo_plot(coo_sample(b, 24))"},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample a proportion of coordinates (among points) — coo_sample_prop","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"simple wrapper around coo_sample","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"","code":"coo_sample_prop(coo, prop = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"coo either matrix (x; y) coordinates Opn object. prop numeric, proportion points sample","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"matrix (x; y) coordinates, Opn object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"coo_sample $ldk component defined, changed accordingly multiplying ids n number coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"","code":"# single shape bot[1] %>% coo_nb() #> [1] 138 bot[1] %>% coo_sample_prop(0.5) %>% coo_nb() #> [1] 69"},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":null,"dir":"Reference","previous_headings":"","what":"Samples coordinates (regular radius) — coo_samplerr","title":"Samples coordinates (regular radius) — coo_samplerr","text":"Samples n coordinates regular angle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Samples coordinates (regular radius) — coo_samplerr","text":"","code":"coo_samplerr(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Samples coordinates (regular radius) — coo_samplerr","text":"coo matrix (x; y) coordinates Coo object. n integer, number points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Samples coordinates (regular radius) — coo_samplerr","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Samples coordinates (regular radius) — coo_samplerr","text":"design, function samples among existing points, using coo_interpolate prior may useful homogeneous angles. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Samples coordinates (regular radius) — coo_samplerr","text":"","code":"stack(bot) bot <- coo_center(bot) stack(coo_samplerr(bot, 12)) coo_plot(bot[1]) coo_plot(rr <- coo_samplerr(bot[1], 12)) cpos <- coo_centpos(bot[1]) segments(cpos[1], cpos[2], rr[, 1], rr[, 2]) # Sometimes, interpolating may be useful: shp <- hearts[1] %>% coo_center # given a shp, draw segments from each points on it, to its centroid draw_rads <- function(shp, ...){ segments(shp[, 1], shp[, 2], coo_centpos(shp)[1], coo_centpos(shp)[2], ...) } # calculate the sd of argument difference in successive points, # in other words a proxy for the homogeneity of angles sd_theta_diff <- function(shp) shp %>% complex(real=.[, 1], imaginary=.[, 2]) %>% Arg %>% `[`(-1) %>% diff %>% sd # no interpolation: all points are sampled from existing points but the # angles are not equal shp %>% coo_plot(points=TRUE, main=\"no interpolation\") shp %>% coo_samplerr(64) %T>% draw_rads(col=\"red\") %>% sd_theta_diff #> [1] 0.03301767 # with interpolation: much more homogeneous angles shp %>% coo_plot(points=TRUE) shp %>% coo_interpolate(360) %>% coo_samplerr(64) %T>% draw_rads(col=\"blue\") %>% sd_theta_diff #> [1] 0.00696334"},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates all scalar descriptors of shape — coo_scalars","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"See examples full list.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"","code":"coo_scalars(coo, rectilinearity = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"coo matrix (x; y) coordinates Coo rectilinearity logical whether include rectilinearity using coo_rectilinearity","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"data_frame","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"coo_rectilinearity particularly optimized, takes around 30 times time include calculate others thus includedby default. default.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"","code":"df <- bot %>% coo_scalars() # pass bot %>% coo_scalars(TRUE) if you want rectilinearity colnames(df) %>% cat(sep=\"\\n\") # all scalars used #> area #> calliper #> centsize #> circularity #> circularityharalick #> circularitynorm #> convexity #> eccentricityboundingbox #> eccentricityeigen #> elongation #> length #> perim #> rectangularity #> solidity #> width # a PCA on all these descriptors TraCoe(coo_scalars(bot), fac=bot$fac) %>% PCA %>% plot_PCA(~type)"},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":null,"dir":"Reference","previous_headings":"","what":"Scales coordinates — coo_scale","title":"Scales coordinates — coo_scale","text":"coo_scale scales coordinates 'scale' factor. provided, assumed centroid size. involves three steps: centering current position, dividing coordinates 'scale', pushing back original position. coo_scalex applies scaling (shrinking) parallel x-axis, coo_scaley y axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Scales coordinates — coo_scale","text":"","code":"coo_scale(coo, scale) # S3 method for default coo_scale(coo, scale = coo_centsize(coo)) # S3 method for Coo coo_scale(coo, scale) coo_scalex(coo, scale = 1) # S3 method for default coo_scalex(coo, scale = 1) # S3 method for Coo coo_scalex(coo, scale = 1) coo_scaley(coo, scale = 1) # S3 method for default coo_scaley(coo, scale = 1) # S3 method for Coo coo_scaley(coo, scale = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Scales coordinates — coo_scale","text":"coo matrix (x; y) coordinates Coo object. scale scaling factor, default, centroid size coo_scale; 1 scalex scaley.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Scales coordinates — coo_scale","text":"single shape Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Scales coordinates — coo_scale","text":"","code":"# on a single shape b <- bot[1] %>% coo_center %>% coo_scale coo_plot(b, lwd=2) coo_draw(coo_scalex(b, 1.5), bor=\"blue\") coo_draw(coo_scaley(b, 0.5), bor=\"red\") # this also works on Coo objects: b <- slice(bot, 5) # for speed sake stack(b) b %>% coo_center %>% coo_scale %>% stack b %>% coo_center %>% coo_scaley(0.5) %>% stack #equivalent to: #b %>% coo_center %>% coo_scalex(2) %>% stack"},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":null,"dir":"Reference","previous_headings":"","what":"Shears shapes — coo_shearx","title":"Shears shapes — coo_shearx","text":"coo_shearx applies shear mapping matrix (x; y) coordinates (list), parallel x-axis (.e. x' = x + ky; y' = y + kx). coo_sheary parallel y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shears shapes — coo_shearx","text":"","code":"coo_shearx(coo, k) coo_sheary(coo, k)"},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shears shapes — coo_shearx","text":"coo matrix (x; y) coordinates Coo object. k numeric shear factor","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shears shapes — coo_shearx","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shears shapes — coo_shearx","text":"","code":"coo <- coo_template(shapes[11]) coo_plot(coo) coo_draw(coo_shearx(coo, 0.5), border=\"blue\") coo_draw(coo_sheary(coo, 0.5), border=\"red\")"},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":null,"dir":"Reference","previous_headings":"","what":"Slices shapes between successive coordinates — coo_slice","title":"Slices shapes between successive coordinates — coo_slice","text":"Takes shape n coordinates. pass function least two ids (<= n), shape open corresponding coordinates slices returned list","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slices shapes between successive coordinates — coo_slice","text":"","code":"coo_slice(coo, ids, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slices shapes between successive coordinates — coo_slice","text":"coo matrix (x; y) coordinates Coo object. ids numeric length >= 2, slice shape(s) ldk numeric id ldk use ids, Opn. provided, ids ignored.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slices shapes between successive coordinates — coo_slice","text":"list shapes list Opn","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slices shapes between successive coordinates — coo_slice","text":"","code":"h <- slice(hearts, 1:5) # speed purpose only # single shape, a list of matrices is returned sh <- coo_slice(h[1], c(12, 24, 36, 48)) coo_plot(sh[[1]]) panel(Opn(sh)) # on a Coo, a list of Opn is returned # makes no sense if shapes are not normalized first sh2 <- coo_slice(h, c(12, 24, 36, 48)) panel(sh2[[1]]) # Use coo_slice with `ldk` instead: # hearts as an example x <- h %>% fgProcrustes(tol=1) #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224 # 4 landmarks stack(x) x$ldk[1:5] #> [[1]] #> [1] 65 56 50 19 #> #> [[2]] #> [1] 69 60 52 21 #> #> [[3]] #> [1] 68 60 51 21 #> #> [[4]] #> [1] 69 59 53 23 #> #> [[5]] #> [1] 71 61 54 21 #> # here we slice y <- coo_slice(x, ldk=1:4) # plotting stack(y[[1]]) stack(y[[2]]) # new ldks from tipping points, new ldks from angle olea %>% slice(1:5) %>% # for the sake of speed def_ldk_tips %>% def_ldk_angle(0.75*pi) %>% def_ldk_angle(0.25*pi) %>% coo_slice(ldk =1:4) -> oleas oleas[[1]] %>% stack oleas[[2]] %>% stack # etc. # domestic operations y[[3]] %>% coo_area() #> shp1 shp2 shp3 shp4 shp5 #> 0.001684956 0.007028829 0.010968094 0.009962128 0.016920135 # shape analysis of a slice y[[1]] %>% coo_bookstein() %>% npoly %>% PCA %>% plot(~aut) #> 'nb.pts' missing and set to: 31 #> 'degree' missing and set to: 5 #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates — coo_slide","title":"Slides coordinates — coo_slide","text":"Slides coordinates id-th point become first one.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates — coo_slide","text":"","code":"coo_slide(coo, id, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates — coo_slide","text":"coo matrix (x; y) coordinates Coo object. id numeric id point become new first point. See details method Coo objects. ldk numeric id ldk use id, ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates — coo_slide","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Slides coordinates — coo_slide","text":"Coo objects, particular Opn three different ways coo_sliding available: ldk passed single id passed: id-th points within shapes become first points. $ldk slided accordingly. ldk passed vector ids matching length Coo: every shape, id-th point used id-th point. $ldk slided accordingly. single ldk passed: ldk-th ldk used slide every shape. id (also) passed, ignored message. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates — coo_slide","text":"","code":"h <- hearts %>% slice(1:5) # for speed sake stack(h) # set the first landmark as the starting point stack(coo_slide(h, ldk=1)) # set the 50th point as the starting point (everywhere) stack(coo_slide(h, id=50)) # set the id-random-th point as the starting point (everywhere) set.seed(123) # just for the reproducibility id_random <- sample(x=min(sapply(h$coo, nrow)), size=length(h), replace=TRUE) stack(coo_slide(h, id=id_random))"},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates in a particular direction — coo_slidedirection","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"Shapes centered , according direction, point northwards, southwards, eastwards westwards centroid, becomes first point coo_slide. 'right' possibly sensible option (default), since 0 radians points eastwards, relatively origin. followed coo_untiltx cases remove rotationnal dephasing/bias.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"","code":"coo_slidedirection( coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4], center, id )"},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"coo matrix (x; y) coordinates Coo object. direction character one \"\", \"left\", \"\", \"right\" (\"right\" default) center logical whether center sliding id numeric whether return id point slided shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"","code":"b <- coo_rotate(bot[1], pi/6) # dummy example just to make it obvious coo_plot(b) # not the first point coo_plot(coo_slidedirection(b, \"up\")) coo_plot(coo_slidedirection(b, \"right\")) coo_plot(coo_slidedirection(b, \"left\")) coo_plot(coo_slidedirection(b, \"down\")) # on Coo objects b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_slidedirection(b, \"right\")) # This should be followed by a [coo_untiltx] in most (if not all) cases stack(coo_slidedirection(b, \"right\") %>% coo_untiltx)"},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates using the widest gap — coo_slidegap","title":"Slides coordinates using the widest gap — coo_slidegap","text":"slicing shape using two landmarks, functions coo_up, open curve obtained rank points make wrong/artefactual results. widest gap > 5 * median gaps, couple coordinates forming widest gap used starting ending points. switch helps deal open curves. Examples self-speaking. Use force=TRUE bypass check","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates using the widest gap — coo_slidegap","text":"","code":"coo_slidegap(coo, force)"},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates using the widest gap — coo_slidegap","text":"coo matrix (x; y) coordinates Coo object. force logical whether use widest gap, check, real gap","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates using the widest gap — coo_slidegap","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates using the widest gap — coo_slidegap","text":"","code":"cat <- coo_center(shapes[4]) coo_plot(cat) # we only retain the bottom of the cat cat_down <- coo_down(cat, slidegap=FALSE) # see? the segment on the x-axis coorespond to the widest gap. coo_plot(cat_down) # that's what we meant coo_plot(coo_slidegap(cat_down))"},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Smoothes coordinates — coo_smooth","title":"Smoothes coordinates — coo_smooth","text":"Smoothes coordinates using simple moving average. May useful remove digitization noise, mainly outlines open outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Smoothes coordinates — coo_smooth","text":"","code":"coo_smooth(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Smoothes coordinates — coo_smooth","text":"coo matrix (x; y) coordinates Coo object. n integer number smoothing iterations","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Smoothes coordinates — coo_smooth","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Smoothes coordinates — coo_smooth","text":"","code":"b5 <- slice(bot, 1:5) # for speed sake stack(b5) stack(coo_smooth(b5, 10)) coo_plot(b5[1]) coo_plot(coo_smooth(b5[1], 30))"},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":null,"dir":"Reference","previous_headings":"","what":"Smoothes coordinates on curves — coo_smoothcurve","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"Smoothes coordinates using simple moving average let first last points unchanged. May useful remove digitization noise curves.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"","code":"coo_smoothcurve(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"coo matrix (x; y) coordinates Coo object. n integer specify number smoothing iterations","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"","code":"o <- olea[1] coo_plot(o, border='grey50', points=FALSE) coo_draw(coo_smooth(o, 24), border='blue', points=FALSE) coo_draw(coo_smoothcurve(o, 24), border='red', points=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the solidity of a shape — coo_solidity","title":"Calculates the solidity of a shape — coo_solidity","text":"Calculated using ratio shape area convex hull area.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the solidity of a shape — coo_solidity","text":"","code":"coo_solidity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the solidity of a shape — coo_solidity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the solidity of a shape — coo_solidity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the solidity of a shape — coo_solidity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the solidity of a shape — coo_solidity","text":"","code":"coo_solidity(bot[1]) #> [1] 0.8932612 bot %>% slice(1:3) %>% # for speed sake only coo_solidity #> $brahma #> [1] 0.8932612 #> #> $caney #> [1] 0.9201334 #> #> $chimay #> [1] 0.9279237 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the total absolute curvature of a shape — coo_tac","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"Calculated using sum absolute value second derivative smooth.spline prediction defined point.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"","code":"coo_tac(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"Siobhan Braybrook.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"numeric single shape Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"","code":"coo_tac(bot[1]) #> [1] 67.85005 bot %>% slice(1:3) %>% # for speed sake only coo_tac #> brahma caney chimay #> 67.85005 34.81994 46.61054"},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":null,"dir":"Reference","previous_headings":"","what":"'Templates' shapes — coo_template","title":"'Templates' shapes — coo_template","text":"coo_template returns shape centered origin inscribed size-side square. coo_template_relatively biggest shape (prod(coo_diffrange)) size=size consequently defined single shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"'Templates' shapes — coo_template","text":"","code":"coo_template(coo, size) # S3 method for default coo_template(coo, size = 1) # S3 method for list coo_template(coo, size = 1) # S3 method for Coo coo_template(coo, size = 1) coo_template_relatively(coo, size = 1) # S3 method for list coo_template_relatively(coo, size = 1) # S3 method for Coo coo_template_relatively(coo, size = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"'Templates' shapes — coo_template","text":"coo list matrix coordinates. size numeric. Indicates length side 'inscribing' shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"'Templates' shapes — coo_template","text":"Returns matrix (x; y)coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"'Templates' shapes — coo_template","text":"See coo_listpanel illustration function. morphospaces functions also take profit function. May useful develop graphical functions.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"'Templates' shapes — coo_template","text":"","code":"coo <- bot[1] coo_plot(coo_template(coo), xlim=c(-1, 1), ylim=c(-1, 1)) rect(-0.5, -0.5, 0.5, 0.5) s <- 0.01 coo_plot(coo_template(coo, s)) rect(-s/2, -s/2, s/2, s/2)"},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":null,"dir":"Reference","previous_headings":"","what":"Translates coordinates — coo_trans","title":"Translates coordinates — coo_trans","text":"Translates coordinates 'x' 'y' value","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translates coordinates — coo_trans","text":"","code":"coo_trans(coo, x = 0, y = 0)"},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translates coordinates — coo_trans","text":"coo matrix (x; y) coordinates Coo object. x numeric translation along x-axis. y numeric translation along y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Translates coordinates — coo_trans","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translates coordinates — coo_trans","text":"","code":"coo_plot(bot[1]) coo_plot(coo_trans(bot[1], 50, 100)) # on Coo b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_trans(b, 50, 100))"},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims both ends coordinates from shape — coo_trim","title":"Trims both ends coordinates from shape — coo_trim","text":"Removes trim coordinates ends shape, ie top bottom shape matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims both ends coordinates from shape — coo_trim","text":"","code":"coo_trim(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims both ends coordinates from shape — coo_trim","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims both ends coordinates from shape — coo_trim","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims both ends coordinates from shape — coo_trim","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trim(1) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.453100 0.08999 #> [2,] -0.371800 0.17700 #> [3,] -0.269700 0.24720 #> [4,] -0.177400 0.28280 #> [5,] -0.084940 0.30470 #> [6,] 0.007775 0.30940 #> [7,] 0.100600 0.30720 #> [8,] 0.193600 0.28790 #> [9,] 0.287000 0.24450 #> [10,] 0.373900 0.17700"},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims bottom coordinates from shape — coo_trimbottom","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"Removes trim coordinates bottom shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"","code":"coo_trimbottom(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trimbottom(4) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720"},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims top coordinates from shape — coo_trimtop","title":"Trims top coordinates from shape — coo_trimtop","text":"Removes trim coordinates top shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims top coordinates from shape — coo_trimtop","text":"","code":"coo_trimtop(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims top coordinates from shape — coo_trimtop","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims top coordinates from shape — coo_trimtop","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims top coordinates from shape — coo_trimtop","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trimtop(4) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.177400 0.28280 #> [2,] -0.084940 0.30470 #> [3,] 0.007775 0.30940 #> [4,] 0.100600 0.30720 #> [5,] 0.193600 0.28790 #> [6,] 0.287000 0.24450 #> [7,] 0.373900 0.17700 #> [8,] 0.443800 0.09201"},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":null,"dir":"Reference","previous_headings":"","what":"Truss measurement — coo_truss","title":"Truss measurement — coo_truss","text":"method calculate shapes Coo truss measurements, pairwise combinations euclidean distances","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Truss measurement — coo_truss","text":"","code":"coo_truss(x)"},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Truss measurement — coo_truss","text":"x shape Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Truss measurement — coo_truss","text":"named numeric matrix","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Truss measurement — coo_truss","text":"Mainly implemented historical/didactical reasons.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Truss measurement — coo_truss","text":"","code":"# example on a single shape cat <- coo_sample(shapes[4], 6) coo_truss(cat) #> 1-2 1-3 1-4 1-5 1-6 2-3 2-4 2-5 #> 58.79626 73.24616 92.45539 165.89454 63.97656 14.76482 111.87940 214.40616 #> 2-6 3-4 3-5 3-6 4-5 4-6 5-6 #> 120.20815 118.00424 225.44179 133.68620 123.90722 86.14523 106.01887 # example on wings dataset tx <- coo_truss(wings) txp <- PCA(tx, scale. = TRUE, center=TRUE, fac=wings$fac) plot(txp, 1) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"Rotationnal biases appear coo_slidedirection (friends). Typically useful outline analysis phasing matters. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"","code":"coo_untiltx(coo, id, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"coo matrix (x; y) coordinates Coo object. id numeric id point become new first point. See details method Coo objects. ldk numeric id ldk use id, ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"Coo objects, particular Opn two different ways coo_sliding available: ldk passed id passed: id-th points within shapes become first points. single ldk passed: ldk-th ldk used slide every shape. id (also) passed, id ignored message.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"","code":"# on a single shape bot[1] %>% coo_center %>% coo_align %>% coo_sample(12) %>% coo_slidedirection(\"right\") %T>% coo_plot() %>% # the first point is not on the x-axis coo_untiltx() %>% coo_draw(border=\"red\") # this (red) one is # on an Out # prepare bot prebot <- bot %>% coo_center %>% coo_scale %>% coo_align %>% coo_slidedirection(\"right\") prebot %>% stack # some dephasing remains prebot %>% coo_slidedirection(\"right\") %>% coo_untiltx() %>% stack # much better # _here_ there is no change but the second, untilted, is correct prebot %>% efourier(8, norm=FALSE) %>% PCA %>% plot_PCA(~type) prebot %>% coo_untiltx %>% efourier(8, norm=FALSE) %>% PCA %>% plot_PCA(~type) # an example using ldks: # the landmark #2 is on the x-axis hearts %>% slice(1:5) %>% fgProcrustes(tol=1e-3) %>% # for speed sake coo_center %>% coo_untiltx(ldk=2) %>% stack #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224"},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with positive y-coordinates — coo_up","title":"Retains coordinates with positive y-coordinates — coo_up","text":"Useful shapes aligned along x-axis (e.g. bilateral symmetry) one wants retain just upper side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with positive y-coordinates — coo_up","text":"","code":"coo_up(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with positive y-coordinates — coo_up","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_down","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with positive y-coordinates — coo_up","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with positive y-coordinates — coo_up","text":"shapes \"sliced\" along x-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with positive y-coordinates — coo_up","text":"","code":"b <- coo_alignxax(bot[1]) coo_plot(b) coo_draw(coo_up(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the width of a shape — coo_width","title":"Calculates the width of a shape — coo_width","text":"Nothing coo_lw(coo)[2].","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the width of a shape — coo_width","text":"","code":"coo_width(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the width of a shape — coo_width","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the width of a shape — coo_width","text":"width (pixels) shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the width of a shape — coo_width","text":"","code":"coo_width(bot[1]) #> [1] 278.0386"},{"path":"http://momx.github.io/Momocs/reference/d.html","id":null,"dir":"Reference","previous_headings":"","what":"A wrapper to calculates euclidean distances between two points — d","title":"A wrapper to calculates euclidean distances between two points — d","text":"main advantage ed method can passed different objects used combination measure. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A wrapper to calculates euclidean distances between two points — d","text":"","code":"d(x, id1, id2)"},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"A wrapper to calculates euclidean distances between two points — d","text":"x Ldk (typically), matrix id1 id 1st row id2 id 2nd row","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A wrapper to calculates euclidean distances between two points — d","text":"numeric","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"A wrapper to calculates euclidean distances between two points — d","text":"objects, first get_ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A wrapper to calculates euclidean distances between two points — d","text":"","code":"# single shape d(wings[1], 1, 4) #> [1] 0.7581273 # Ldk object d(wings, 1, 4) #> AN1 AN2 AN3 AN4 AN5 AN6 AN7 AN8 #> 0.7581273 0.7281573 0.7127928 0.7185018 0.7367129 0.7124015 0.7285464 0.7301814 #> AN9 AN10 AN11 TO12 WY13 WY14 WY15 WY16 #> 0.7091337 0.7087522 0.7100063 0.6994695 0.7257983 0.7250806 0.7227536 0.7176631 #> UR17 UR18 UR19 UR20 CA21 CA22 CA23 CA24 #> 0.7207639 0.7269677 0.7153795 0.7397394 0.7373042 0.7172436 0.7223663 0.7182525 #> CA25 CA26 CA27 OR28 MA29 MA30 MA31 PS32 #> 0.7317102 0.7172721 0.7127463 0.7244861 0.7335012 0.7238598 0.7424106 0.7366003 #> PS33 PS34 PS35 PS36 PS37 PS38 PS39 PS40 #> 0.7262568 0.7315960 0.7233414 0.7278607 0.7262419 0.7331013 0.7087411 0.7163488 #> PS41 PS42 PS43 AE44 AE45 AE46 AE47 AE48 #> 0.7085592 0.7134963 0.7062850 0.7233241 0.7080950 0.7261707 0.7100848 0.7421942 #> AE49 AE50 AE51 AE52 AE53 AE54 AE55 AE56 #> 0.7115717 0.7248944 0.7230917 0.7144437 0.7182977 0.7168990 0.7175543 0.7165161 #> AE57 AE58 AE59 AE60 AE61 AE62 AE63 AE64 #> 0.7404125 0.7154040 0.7448661 0.7261959 0.7224206 0.7360905 0.7335780 0.7318912 #> AE65 AE66 AE67 AE68 AE69 AE70 AE71 AE72 #> 0.7151047 0.7147967 0.7145111 0.7210058 0.7222862 0.7212556 0.7302622 0.7216666 #> AE73 AE74 AE75 AE76 AE77 AE78 AE79 AE80 #> 0.7437503 0.7436207 0.7327989 0.7092307 0.7315643 0.7322983 0.7398728 0.7173188 #> AE81 AE82 AE83 AE84 AE85 AE86 AE87 AE88 #> 0.6992811 0.7286847 0.7241596 0.7290020 0.7136496 0.7222001 0.7283568 0.7341570 #> AE89 AE90 AE91 AE92 AE93 AE94 AE95 AE96 #> 0.7213378 0.7293730 0.7198584 0.7149219 0.7354247 0.7296066 0.7157059 0.6982300 #> AE97 AE98 AE99 AE100 CX101 CX102 CX103 CX104 #> 0.7382611 0.7261058 0.7145814 0.7133695 0.7205058 0.7340288 0.7172196 0.7235002 #> CX105 CX106 CX107 CX108 CX109 CX110 CX111 CX112 #> 0.7186017 0.7191322 0.7077697 0.7256004 0.7205312 0.7205628 0.7171014 0.7182613 #> CX113 CX114 CX115 CX116 CX117 CX118 CX119 CX120 #> 0.7299714 0.7094558 0.6976466 0.7216434 0.7297104 0.7277296 0.7383755 0.7150724 #> CX121 CX122 CX123 CX124 CX125 DE126 DE127 #> 0.7217969 0.7252883 0.7075976 0.7231878 0.7190234 0.7001547 0.7128613 # Out object d(hearts, 2, 4) #> shp1 shp2 shp3 shp4 shp5 shp6 shp7 shp8 #> 0.7631146 0.7182864 0.8451851 0.8524332 0.6289745 0.7469257 0.7650846 0.5290089 #> shp9 shp10 shp11 shp12 shp13 shp14 shp15 shp16 #> 0.6103333 0.6236372 0.7429723 0.6348490 0.7671199 0.6810554 0.6338818 0.6853828 #> shp17 shp18 shp19 shp20 shp21 shp22 shp23 shp24 #> 0.6238002 0.8866637 0.6208528 0.5822941 0.5880879 0.8852956 0.7346886 0.7203612 #> shp25 shp26 shp27 shp28 shp29 shp30 shp31 shp32 #> 0.6834542 0.6683383 0.6815803 0.6992615 0.8837326 0.6694748 0.9143077 0.7462901 #> shp33 shp34 shp35 shp36 shp37 shp38 shp39 shp40 #> 0.8324069 0.8263567 0.7156152 0.7400215 0.8636179 0.7327721 0.7302947 0.8022611 #> shp41 shp42 shp43 shp44 shp45 shp46 shp47 shp48 #> 0.7876690 0.6702961 0.7657328 0.7114349 0.8160898 0.8514524 0.7864097 0.8544094 #> shp49 shp50 shp51 shp52 shp53 shp54 shp55 shp56 #> 0.8540897 0.7362736 0.7839997 0.7141854 0.7881206 0.7844670 0.7976090 0.7780533 #> shp57 shp58 shp59 shp60 shp61 shp62 shp63 shp64 #> 0.7790919 0.7977559 0.8113749 0.7159091 0.7119202 0.6425247 0.8280741 0.7699237 #> shp65 shp66 shp67 shp68 shp69 shp70 shp71 shp72 #> 0.9112877 0.7542011 0.8073623 0.8916280 0.7638459 0.7394304 0.7120199 0.8475767 #> shp73 shp74 shp75 shp76 shp77 shp78 shp79 shp80 #> 0.8467397 0.7998835 0.9270539 0.7642246 0.8594367 0.7209088 0.7989868 0.7535296 #> shp81 shp82 shp83 shp84 shp85 shp86 shp87 shp88 #> 0.8750936 0.9212785 0.8739192 0.7410993 0.7711573 0.9040280 0.8445564 0.8595617 #> shp89 shp90 shp91 shp92 shp93 shp94 shp95 shp96 #> 0.7544551 0.8765394 0.7649132 0.8566908 0.8672661 0.8905499 0.8167811 0.6780182 #> shp97 shp98 shp99 shp100 shp101 shp102 shp103 shp104 #> 0.7720006 0.9065548 0.8954063 0.8858552 0.8706311 0.8762412 0.9093137 0.9002444 #> shp105 shp106 shp107 shp108 shp109 shp110 shp111 shp112 #> 0.9036831 0.8292070 0.8859845 0.8851778 0.8619118 0.9206441 0.8397867 0.8692543 #> shp113 shp114 shp115 shp116 shp117 shp118 shp119 shp120 #> 0.8671550 0.7668184 0.8522446 0.7407808 0.7615372 0.7884933 0.9120387 0.8496588 #> shp121 shp122 shp123 shp124 shp125 shp126 shp127 shp128 #> 0.7128952 0.8452803 0.7808519 0.8506531 0.8119996 0.7727404 0.7854347 0.8393396 #> shp129 shp130 shp131 shp132 shp133 shp134 shp135 shp136 #> 0.8445801 0.7802361 0.7640858 0.8662670 0.7090051 0.8541041 0.7161086 0.7619554 #> shp137 shp138 shp139 shp140 shp141 shp142 shp143 shp144 #> 0.7454238 0.8066868 0.8413141 0.7679260 0.8279943 0.7932280 0.8050323 0.8471870 #> shp145 shp146 shp147 shp148 shp149 shp150 shp151 shp152 #> 0.7967146 0.8006016 0.8237974 0.8582077 0.9160836 0.8401398 0.7995380 0.6738980 #> shp153 shp154 shp155 shp156 shp157 shp158 shp159 shp160 #> 0.7307879 0.7278767 0.8359675 0.8280149 0.8104836 0.7733338 0.8047466 0.6754903 #> shp161 shp162 shp163 shp164 shp165 shp166 shp167 shp168 #> 0.7218993 0.6596433 0.8148563 0.6368536 0.7098642 0.7902415 0.7481063 0.7169491 #> shp169 shp170 shp171 shp172 shp173 shp174 shp175 shp176 #> 0.7126700 0.7845322 0.7388734 0.7834291 0.6949870 0.6693791 0.6995516 0.6978463 #> shp177 shp178 shp179 shp180 shp181 shp182 shp183 shp184 #> 0.7198900 0.7878513 0.8469718 0.7758912 0.7731482 0.6759113 0.7120142 0.6643103 #> shp185 shp186 shp187 shp188 shp189 shp190 shp191 shp192 #> 0.7535931 0.7760557 0.7520940 0.7106488 0.6974563 0.7151895 0.8647945 0.7771309 #> shp193 shp194 shp195 shp196 shp197 shp198 shp199 shp200 #> 0.7450503 0.6718839 0.7454927 0.5912441 0.7118493 0.7229153 0.8140886 0.8216331 #> shp201 shp202 shp203 shp204 shp205 shp206 shp207 shp208 #> 0.7815022 0.6470323 0.6373149 0.5962023 0.6925027 0.7957830 0.6756185 0.7093084 #> shp209 shp210 shp211 shp212 shp213 shp214 shp215 shp216 #> 0.6560775 0.7320395 0.7869578 0.7326762 0.7769385 0.8253959 0.6940959 0.7130844 #> shp217 shp218 shp219 shp220 shp221 shp222 shp223 shp224 #> 0.6848838 0.8305747 0.7472713 0.7586330 0.8380628 0.7593495 0.6286220 0.7498917 #> shp225 shp226 shp227 shp228 shp229 shp230 shp231 shp232 #> 0.7584135 0.7930154 0.7907987 0.7237335 0.8102214 0.8092945 0.7134718 0.8471743 #> shp233 shp234 shp235 shp236 shp237 shp238 shp239 shp240 #> 0.7870556 0.8002813 0.7853021 0.8028798 0.7940435 0.8044962 0.6784667 0.7779515"},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"Data: Outline coordinates Apodemus (wood mouse) mandibles","code":""},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"object 64 coordinates 30 wood molar outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. Journal Biogeography 30:1617-1628. see https://onlinelibrary.wiley.com/doi/full/10.1046/j.1365-2699.2003.00932.x","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of beer and whisky bottles. — bot","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"Data: Outline coordinates beer whisky bottles.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"object containing outlines coordinates grouping factor 20 beer 20 whisky bottles","code":""},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"Images grabbed internet prepared package's authors. particular choice made dimension original images brands cited .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Data: Landmark semilandmark coordinates cereal glumes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Ldk object 21 configurations landmarks semi-landmarks (4 partitions) sampled cereal glumes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Research support provided European Research Council (Evolutionary Origins Agriculture (grant . 269830-EOA) PI: Glynis Jones, Dept Archaeology, Sheffield, UK. Data collected Emily Forster.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates from an experimental charring on cereal grains — charring","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"Data: Outline coordinates experimental charring cereal grains","code":""},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"object 18 grains, 3 views , 2 cereal species, charred different temperatures 6 hours (0C (charring), 230C 260C).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"Research support provided European Research Council (Evolutionary Origins Agriculture (grant . 269830-EOA) PI: Glynis Jones, Dept Archaeology, Sheffield, UK. Data collected Emily Forster.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Measurement of iris flowers — flower","title":"Data: Measurement of iris flowers — flower","text":"Data: Measurement iris flowers","code":""},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Measurement of iris flowers — flower","text":"TraCoe object 150 measurements 4 variables (petal + sepal) x (length x width) 3 species iris. dataset classical iris formatted Momocs.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Measurement of iris flowers — flower","text":"see iris","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of hand-drawn hearts — hearts","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"Data: Outline coordinates hand-drawn hearts","code":""},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"object outline coordinates 240 hand-drawn hearts 8 different persons, 4 landmarks.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"thank fellows Ecology Department French Institute Pondicherry drawn hearts, smoothed, scaled, centered, downsampled 80 coordinates per outline.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of 360 molars — molars","title":"Data: Outline coordinates of 360 molars — molars","text":"Courtesy Julien Corny Florent Detroit.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of 360 molars — molars","text":"object containing 79 equilinearly spaced (x; y) coordinates 360 crown outlines, modern human molars, along type ($type) - 90 first upper molars (UM1), 90 second upper molars (UM2), 90 first lower molars (LM1), 90 second lower molars (LM2) - individual (ind) come (data 360 molars taken 180 individuals).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of 360 molars — molars","text":"Corny, J., & Detroit, F. (2014). Technical Note: Anatomic identification isolated modern human molars: testing Procrustes aligned outlines standardization procedure elliptic fourier analysis. American Journal Physical Anthropology, 153(2), 314-22. doi:10.1002/ajpa.22428 see https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.22428","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of mosquito wings. — mosquito","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"Data: Outline coordinates mosquito wings.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"object 126 mosquito wing outlines outlines used Rohlf Archie (1984). Note links defined quite approximate.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"Rohlf F, Archie J. 1984. comparison Fourier methods description wing shape mosquitoes (Diptera: Culicidae). Systematic Biology: 302-317.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of mouse molars — mouse","title":"Data: Outline coordinates of mouse molars — mouse","text":"Data: Outline coordinates mouse molars","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of mouse molars — mouse","text":"object 64 coordinates 30 wood molar outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of mouse molars — mouse","text":"Renaud S, Dufour AB, Hardouin EA, Ledevin R, Auffray JC (2015): upon multivariate analyses: tell several stories biological evolution. PLoS One 10:1-18 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132801","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of North Sea fishes — nsfishes","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"Data: Outline coordinates North Sea fishes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"object containing outlines coordinates 218 fishes North Sea along taxonomical cofactors.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"Caillon F, Frelat R, Mollmann C, Bonhomme V (submitted)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Configuration of landmarks of oak leaves — oak","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Viscosi Cardini (2001).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Ldk object containing 11 (x; y) landmarks 176 oak leaves wings, ","code":""},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Viscosi, V., & Cardini, . (2011). Leaf morphology, taxonomy geometric morphometrics: simplified protocol beginners. PloS One, 6(10), e25630. doi:10.1371/journal.pone.0025630","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of olive seeds open outlines. — olea","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"Data: Outline coordinates olive seeds open outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"Opn object outline coordinates olive seeds.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"thank Jean-Frederic Terral Sarah Ivorra (UMR CBAE, Montpellier, France) allowing us share data. can look original paper: Terral J-F, Alonso N, Capdevila RB , Chatti N, Fabre L, Fiorentino G, Marinval P, Jorda GP, Pradat B, Rovira N, et al. 2004. Historical biogeography olive domestication (Olea europaea L.) revealed geometrical morphometry applied biological archaeological material. Journal Biogeography 31: 63-77.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of various shapes — shapes","title":"Data: Outline coordinates of various shapes — shapes","text":"Data: Outline coordinates various shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of various shapes — shapes","text":"object outline coordinates various shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of various shapes — shapes","text":"Borrowed default shapes (c) Adobe Photoshop. send jail.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"Data: Outline coordinates cephalic outlines trilobite","code":""},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"object 64 coordinates 50 cephalic outlines different ontogenetic stages trilobite.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"Arranged : https://folk.universitetetioslo./ (used ohammer website seems deprecated now). original data included 51 outlines 5 ontogenetic stages, one just single outline thas removed.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Landmarks coordinates of mosquito wings — wings","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Data: Landmarks coordinates mosquito wings","code":""},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Ldk object containing 18 (x; y) landmarks 127 mosquito wings, ","code":""},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Rohlf Slice 1990.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines new landmarks on Out and Opn objects — def_ldk","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Helps define landmarks Coo object. number landmarks must specified rows indices correspond nearest points clicked every outlines stored $ldk slot Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"","code":"def_ldk(Coo, nb.ldk, close, points)"},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Coo Opn object nb.ldk number landmarks define every shape close logical whether close (typically outlines) points logical whether display points","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Opn object landmarks defined","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"","code":"if (FALSE) { bot <- bot[1:5] # to make it shorter to try # click on 3 points, 5 times. # Don't forget to save the object returned by def_ldk... bot2 <- def_ldk(bot, 3) stack(bot2) bot2$ldk }"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":null,"dir":"Reference","previous_headings":"","what":"Add new landmarks based on angular positions — def_ldk_angle","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"wrapper coo_intersect_angle coo_intersect_direction Opn objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"","code":"def_ldk_angle(coo, angle) def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for default def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Out def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Opn def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4])"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"coo Opn object angle numeric angle radians (0 default). direction character one \"\", \"left\", \"\", \"right\" (\"right\" default)","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"existing ldk preserved.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"","code":"# adds a new landmark towards south east hearts %>% slice(1:5) %>% # for speed purpose only def_ldk_angle(-pi/6) %>% stack() # on Out and towards NW and NE here olea %>% slice(1:5) %>% #for speed purpose only def_ldk_angle(3*pi/4) %>% def_ldk_angle(pi/4) %>% stack"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":null,"dir":"Reference","previous_headings":"","what":"Define tips as new landmarks — def_ldk_tips","title":"Define tips as new landmarks — def_ldk_tips","text":"Opn objects, can used coo_slice. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define tips as new landmarks — def_ldk_tips","text":"","code":"def_ldk_tips(coo)"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define tips as new landmarks — def_ldk_tips","text":"coo Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define tips as new landmarks — def_ldk_tips","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Define tips as new landmarks — def_ldk_tips","text":"existing ldk preserved.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define tips as new landmarks — def_ldk_tips","text":"","code":"is_ldk(olea) # no ldk for olea #> [1] FALSE olea %>% slice(1:3) %>% #for the sake of speed def_ldk_tips %>% def_ldk_angle(3*pi/4) %>% def_ldk_angle(pi/4) %T>% stack %>% coo_slice(ldk=1:4) -> oleas stack(oleas[[1]]) stack(oleas[[2]]) # etc."},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines links between landmarks — def_links","title":"Defines links between landmarks — def_links","text":"Works Ldk objects, 2-cols matrices, 3-dim arrays (MSHAPES turns matrix).","code":""},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines links between landmarks — def_links","text":"","code":"def_links(x, nb.ldk)"},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines links between landmarks — def_links","text":"x Ldk, matric array nb.ldk numeric iterative procedure stopped user click top graphical window.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines links between landmarks — def_links","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines links between landmarks — def_links","text":"","code":"if (FALSE) { wm <- MSHAPES(wings) links <- def_links(wm, 3) # click to define pairs of landmarks ldk_links(wm, links) }"},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines sliding landmarks matrix — def_slidings","title":"Defines sliding landmarks matrix — def_slidings","text":"Defines sliding landmarks matrix","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines sliding landmarks matrix — def_slidings","text":"","code":"def_slidings(Coo, slidings)"},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines sliding landmarks matrix — def_slidings","text":"Coo Ldk object slidings matrix, numeric list numeric. See Details","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines sliding landmarks matrix — def_slidings","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Defines sliding landmarks matrix — def_slidings","text":"$slidings Ldk must 'valid' matrix: containing ids coordinates, none lower 1 higher number coordinates $coo. slidings matrix contains 3 columns (, slide, ). inspired geomorph compatible . matrix can passed directly slidings argument matrix. course, strictly equivalent Ldk$slidings <- slidings. slidings can also passed \"partition(s)\", sliding landmarks identified ids (row number) consecutive $coo. single partition can passed either numeric (eg 4:12), points 5 11 must considered sliding landmarks (4 12 fixed); list numeric. See examples .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines sliding landmarks matrix — def_slidings","text":"","code":"#waiting for a sliding dataset..."},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Discrete cosinus transform — dfourier","title":"Discrete cosinus transform — dfourier","text":"Calculates discrete cosine transforms, introduced Dommergues colleagues, shape (mainly open outlines).","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Discrete cosinus transform — dfourier","text":"","code":"dfourier(coo, nb.h) # S3 method for default dfourier(coo, nb.h) # S3 method for Opn dfourier(coo, nb.h) # S3 method for list dfourier(coo, nb.h) # S3 method for Coo dfourier(coo, nb.h)"},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Discrete cosinus transform — dfourier","text":"coo matrix (list) (x; y) coordinates nb.h numeric number harmonics calculate","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Discrete cosinus transform — dfourier","text":"list following components: harmonic coefficients bn B harmonic coefficients mod modules points arg arguments points","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Discrete cosinus transform — dfourier","text":"method poorly tested Momocs considered experimental. Yet improved factor 10, method still long execute. improved releases painful right now. also explains progress bar. Shapes aligned performing dct transform. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Discrete cosinus transform — dfourier","text":"Dommergues, C. H., Dommergues, J.-L., & Verrecchia, E. P. (2007). Discrete Cosine Transform, Fourier-related Method Morphometric Analysis Open Contours. Mathematical Geology, 39(8), 749-763. doi:10.1007/s11004-007-9124-6 Many thanks Remi Laffont translation R).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Discrete cosinus transform — dfourier","text":"","code":"o <- olea %>% slice(1:5) # for the sake of speed od <- dfourier(o) #> 'nb.h' not provided and set to 12 #> od #> An OpnCoe object [ discrete cosine tansform analysis ] #> -------------------- #> - $coe: 5 open outlines described #> # A tibble: 5 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 op <- PCA(od) plot(op, 1) #> will be deprecated soon, see ?plot_PCA # dfourier and inverse dfourier o <- olea[1] o <- coo_bookstein(o) coo_plot(o) o.dfourier <- dfourier(o, nb.h=12) o.dfourier #> $an #> [1] -3.11820730 -0.13206715 -0.24781390 -0.09660325 -0.06788311 -0.06691169 #> [7] -0.03519719 -0.06016120 -0.02071002 -0.06544994 -0.01169704 -0.06810722 #> #> $bn #> [1] 0.032926049 -0.914830858 0.005334948 -0.268975696 -0.006644877 #> [6] -0.101625518 0.003834764 -0.049467452 0.003042230 -0.028964333 #> [11] -0.002260202 -0.022833346 #> #> $mod #> [1] 3.11838113 0.92431446 0.24787132 0.28579733 0.06820756 0.12167547 #> [7] 0.03540548 0.07788709 0.02093227 0.07157253 0.01191341 0.07183283 #> #> $phi #> [1] 3.131034 -1.714168 3.120068 -1.915601 -3.044016 -2.153064 3.033070 #> [8] -2.453432 2.995739 -2.724958 -2.950716 -2.818113 #> o.i <- dfourier_i(o.dfourier) o.i <- coo_bookstein(o.i) coo_draw(o.i, border='red') #future calibrate_reconstructions o <- olea[1] h.range <- 2:13 coo <- list() for (i in seq(along=h.range)){ coo[[i]] <- dfourier_i(dfourier(o, nb.h=h.range[i]))} names(coo) <- paste0('h', h.range) panel(Opn(coo), borders=col_india(12), names=TRUE) title('Discrete Cosine Transforms')"},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Investe discrete cosinus transform — dfourier_i","title":"Investe discrete cosinus transform — dfourier_i","text":"Calculates inverse discrete cosine transforms (see dfourier), given list B harmonic coefficients, typically produced dfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Investe discrete cosinus transform — dfourier_i","text":"","code":"dfourier_i(df, nb.h, nb.pts = 60)"},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Investe discrete cosinus transform — dfourier_i","text":"df list $$B components, containing harmonic coefficients. nb.h custom number harmonics use nb.pts numeric number pts shape reconstruction","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Investe discrete cosinus transform — dfourier_i","text":"matrix (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Investe discrete cosinus transform — dfourier_i","text":"core functions far. implemented Opn method soon.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Investe discrete cosinus transform — dfourier_i","text":"Dommergues, C. H., Dommergues, J.-L., & Verrecchia, E. P. (2007). Discrete Cosine Transform, Fourier-related Method Morphometric Analysis Open Contours. Mathematical Geology, 39(8), 749-763. doi:10.1007/s11004-007-9124-6 Many thanks Remi Laffont translation R).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Investe discrete cosinus transform — dfourier_i","text":"","code":"# dfourier and inverse dfourier o <- olea[1] o <- coo_bookstein(o) coo_plot(o) o.dfourier <- dfourier(o, nb.h=12) o.dfourier #> $an #> [1] -3.11820730 -0.13206715 -0.24781390 -0.09660325 -0.06788311 -0.06691169 #> [7] -0.03519719 -0.06016120 -0.02071002 -0.06544994 -0.01169704 -0.06810722 #> #> $bn #> [1] 0.032926049 -0.914830858 0.005334948 -0.268975696 -0.006644877 #> [6] -0.101625518 0.003834764 -0.049467452 0.003042230 -0.028964333 #> [11] -0.002260202 -0.022833346 #> #> $mod #> [1] 3.11838113 0.92431446 0.24787132 0.28579733 0.06820756 0.12167547 #> [7] 0.03540548 0.07788709 0.02093227 0.07157253 0.01191341 0.07183283 #> #> $phi #> [1] 3.131034 -1.714168 3.120068 -1.915601 -3.044016 -2.153064 3.033070 #> [8] -2.453432 2.995739 -2.724958 -2.950716 -2.818113 #> o.i <- dfourier_i(o.dfourier) o.i <- coo_bookstein(o.i) coo_draw(o.i, border='red') o <- olea[1] h.range <- 2:13 coo <- list() for (i in seq(along=h.range)){ coo[[i]] <- dfourier_i(dfourier(o, nb.h=h.range[i]))} names(coo) <- paste0('h', h.range) panel(Opn(coo), borders=col_india(12), names=TRUE) title('Discrete Cosine Transforms')"},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draws 'dfourier' shapes — dfourier_shape","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"Calculates shapes based 'Discrete cosine transforms' given harmonic coefficients (see dfourier) can generate random 'dfourier' shapes. Mainly intended generate shapes /understand dfourier works.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"","code":"dfourier_shape(A, B, nb.h, nb.pts = 60, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"vector harmonic coefficients B vector harmonic coefficients nb.h /B provided, number harmonics generate nb.pts /B provided, number points use reconstruct shapes alpha power coefficient associated (usually decreasing) amplitude harmonic coefficients (see efourier_shape) plot logical whether plot shape","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"list shapes plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"","code":"# some signatures panel(coo_align(Opn(replicate(48, dfourier_shape(alpha=0.5, nb.h=6))))) # some worms panel(coo_align(Opn(replicate(48, dfourier_shape(alpha=2, nb.h=6)))))"},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":null,"dir":"Reference","previous_headings":"","what":"Dissolve Coe objects — dissolve","title":"Dissolve Coe objects — dissolve","text":"opposite combine, typically used . Note $fac slot may wrong since combine...well combines... $fac. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Dissolve Coe objects — dissolve","text":"","code":"dissolve(x, retain)"},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Dissolve Coe objects — dissolve","text":"x Coe object retain partition id retain. name partitions named (see x$method) eg chop","code":""},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Dissolve Coe objects — dissolve","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Dissolve Coe objects — dissolve","text":"","code":"data(bot) w <- filter(bot, type==\"whisky\") b <- filter(bot, type==\"beer\") wf <- efourier(w, 10) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bf <- efourier(b, 10) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details wbf <- combine(wf, bf) dissolve(wbf, 1) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows dissolve(wbf, 2) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows # or using chop (yet combine here makes no sense) bw <- bot %>% chop(~type) %>% lapply(efourier, 10) %>% combine #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bw %>% dissolve(1) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows bw %>% dissolve(2) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows"},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr drawers for shape plots — drawers","title":"grindr drawers for shape plots — drawers","text":"Useful drawers building custom shape plots using grindr approach. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr drawers for shape plots — drawers","text":"","code":"draw_polygon( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_outline( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_outlines( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_points( coo, f, col = par(\"fg\"), cex = 1/2, pch = 20, transp = 0, pal = pal_qual, ... ) draw_landmarks( coo, f, col = par(\"fg\"), cex = 1/2, pch = 20, transp = 0, pal = pal_qual, ... ) draw_lines( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_centroid( coo, f, col = par(\"fg\"), pch = 3, cex = 0.5, transp = 0, pal = pal_qual, ... ) draw_curve( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_curves( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_firstpoint( coo, f, label = \"^\", col = par(\"fg\"), cex = 3/4, transp = 0, pal = pal_qual, ... ) draw_axes(coo, col = \"#999999\", lwd = 1/2, ...) draw_ticks(coo, col = \"#333333\", cex = 3/4, lwd = 3/4, ...) draw_labels(coo, labels = 1:nrow(coo), cex = 1/2, d = 1/20, ...) draw_links( coo, f, links, col = \"#99999955\", lwd = 1/2, lty = 1, transp = 0, pal = pal_qual, ... ) draw_title( coo, main = \"\", sub = \"\", cex = c(1, 3/4), font = c(2, 1), padding = 1/200, ... )"},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr drawers for shape plots — drawers","text":"coo matrix 2 columns (x, y) coordinates f optionnal factor specification feed. See examples vignettes. col color (hexadecimal) draw components fill color (hexadecimal) draw components lwd draw components lty draw components transp numeric transparency (default:0, min:0, max:1) pal palette use col/border/etc. provided. See [palettes] ... additional options feed core functions drawer cex draw components ((c(2, 1) default) draw_title) pch draw components label indicate first point labels character name labels draw (defaut 1:nrow(coo)) d numeric proportion d(centroid-each_point) add centrifugating landmarks links matrix links use draw segments landmarks. See wings$ldk example main character title (empty default) sub character subtitle (empty default) font numeric feed text (c(2, 1) default) padding numeric fraction graphical window (1/200 default)","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr drawers for shape plots — drawers","text":"drawing layer","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"grindr drawers for shape plots — drawers","text":"approach (soon) replace coo_plot friends versions. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"grindr drawers for shape plots — drawers","text":"","code":"bot[1] %>% paper_grid() %>% draw_polygon() olea %>% paper_chess %>% draw_lines(~var) hearts[240] %>% paper_white() %>% draw_outline() %>% coo_sample(24) %>% draw_landmarks %>% draw_labels() %>% draw_links(links=replicate(2, sample(1:24, 8))) bot %>% paper_grid() %>% draw_outlines() %>% draw_title(\"Alcohol abuse \\nis dangerous for health\", \"Drink responsibly\")"},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean distance between two points. — ed","title":"Calculates euclidean distance between two points. — ed","text":"ed simply calculates euclidean distance two points defined (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean distance between two points. — ed","text":"","code":"ed(pt1, pt2)"},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean distance between two points. — ed","text":"pt1 (x; y) coordinates first point. pt2 (x; y) coordinates second point.","code":""},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean distance between two points. — ed","text":"Returns euclidean distance two points.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean distance between two points. — ed","text":"","code":"ed(c(0,1), c(1,0)) #> [1] 1.414214"},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean intermediate between two points. — edi","title":"Calculates euclidean intermediate between two points. — edi","text":"edi simply calculates coordinates points relative distance r pt1-pt2 defined (x; y) coordinates. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean intermediate between two points. — edi","text":"","code":"edi(pt1, pt2, r = 0.5)"},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean intermediate between two points. — edi","text":"pt1 \\((x; y)\\) coordinates first point. pt2 \\((x; y)\\) coordinates second point. r relative distance pt1 pt2.","code":""},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean intermediate between two points. — edi","text":"returns \\((x; y)\\) interpolated coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean intermediate between two points. — edi","text":"","code":"edi(c(0,1), c(1,0), r = 0.5) #> [1] 0.5 0.5"},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean distance every pairs of points in two matrices. — edm","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"edm returns euclidean distances points \\(1 -> n\\) two 2-col matrices dimension. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"","code":"edm(m1, m2)"},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"m1 first matrix coordinates. m2 second matrix coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"Returns vector euclidean distances pairwise coordinates two matrices.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"one wishes align two (shapes) Procrustes surimposition may provide better solution.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"","code":"x <- matrix(1:10, nc=2) edm(x, x) #> [1] 0 0 0 0 0 edm(x, x+1) #> [1] 1.414214 1.414214 1.414214 1.414214 1.414214"},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"edm_nearest calculates shortest euclidean distance found every point one matrix among second. words, m1, m2 n rows, result shortest distance first point m1 point m2 , n times. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"","code":"edm_nearest(m1, m2, full = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"m1 first list matrix coordinates. m2 second list matrix coordinates. full logical. Whether returns condensed version results.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"full TRUE, returns list two components: d every point m1 shortest distance found point m2, pos (m2) row indices points. Otherwise returns d numeric vector shortest distances.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"far function quite time consumming since performs \\( n \\times n \\) euclidean distance computation. one wishes align two (shapes) Procrustes surimposition may provide better solution.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"","code":"x <- matrix(1:10, nc=2) edm_nearest(x, x+rnorm(10)) #> [1] 0.9276974 0.2276210 1.3132366 0.3104909 1.5710566 edm_nearest(x, x+rnorm(10), full=TRUE) #> $d #> [1] 1.2055581 1.0015449 1.1344017 1.1321094 0.5926906 #> #> $pos #> [1] 1 1 3 5 5 #>"},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Elliptical Fourier transform (and its normalization) — efourier","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"efourier computes Elliptical Fourier Analysis (Transforms EFT) matrix (list) (x; y) coordinates. efourier_norm normalizes Fourier coefficients. Read Details carefully.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"","code":"efourier(x, ...) # S3 method for default efourier(x, nb.h, smooth.it = 0, ...) # S3 method for Out efourier(x, nb.h, smooth.it = 0, norm = TRUE, start = FALSE, ...) # S3 method for list efourier(x, ...) efourier_norm(ef, start = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"x list matrix coordinates object ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform. norm whether normalize coefficients using efourier_norm start logical. efourier whether consider first point homologous; efourier_norm whether conserve position first point outline. ef list a_n, b_n, c_n d_n Fourier coefficients, typically returned efourier","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"efourier, list components: , bn, cn, dn harmonic coefficients, plus ao co. latter named a0 c0 Claude (2008) (intentionnaly) propagated error. efourier_norm, list components: , B, C, D harmonic coefficients, plus size, magnitude semi-major axis first fitting ellipse, theta angle, radians, starting semi-major axis first fitting ellipse, psi orientation first fitting ellipse, ao , , lnef concatenation coefficients.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"maths behind see paper JSS. Normalization coefficients long matter trouble, newcomers. two ways normalizing outlines: first, far used, use \"numerical\" alignment, directly matrix coefficients. coefficients first harmonic consumed process harmonics higher rank normalized terms size rotation. sometimes referred using \"first ellipse\", harmonics define ellipse plane, first one mother ellipses, others \"roll\" along. approach really convenient done easily software (option) Momocs . default option efourier. pitfall: shapes prone bad aligments among first ellipses, result poorly (even ) \"homologous\" coefficients. shapes particularly prone either (least roughly) circular /strong bilateral symmetry. can try use stack Coe object returned efourier. Also, perhaps explicitely, morphospace usually show mirroring symmetry, typically visible calculated couple components (usually first two). see upside-(180 degrees rotated) shapes morphospace, seriously consider aligning shapes efourier step, performing latter norm = FALSE. pitfall explains (quite annoying) message passing efourier just . several options align shapes, using control points (landmarks), far time consuming (less reproducible) possibly best one alignment tricky automate. can also try Procrustes alignment (see fgProcrustes) calliper length (see coo_aligncalliper), etc. also make first point homologous either coo_slide coo_slidedirection minimize subsequent problems. dedicate (day) vignette paper problem.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"Directly borrowed Claude (2008). Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"","code":"# single shape coo <- bot[1] coo_plot(coo) ef <- efourier(coo, 12) # same but silent efourier(coo, 12, norm=TRUE) #> $an #> [1] -143.1142910 5.2925309 22.9922936 -11.3596452 -14.9412217 #> [6] -5.4200881 5.7177112 0.4509076 0.3107020 -3.1633079 #> [11] 0.2814646 3.4927761 #> #> $bn #> [1] -13.8501141 -21.8994092 11.4235084 13.5870435 -12.6401807 2.5050679 #> [7] 5.1968464 -0.5366171 -1.0431706 1.0823659 2.3427969 0.1022387 #> #> $cn #> [1] 64.44753053 -3.15375656 -17.96822626 5.76052596 7.17390949 #> [6] -2.98410094 -1.20013013 1.18299684 -0.36305436 -0.46782525 #> [11] 0.67134872 0.08954658 #> #> $dn #> [1] -484.90299209 -1.04774048 42.07408510 3.40654863 -9.19128141 #> [6] -2.99359284 0.96722479 2.22582484 0.02026172 -2.26134728 #> [11] -0.04679906 0.80569603 #> #> $ao #> [1] 349.02 #> #> $co #> [1] 1080.921 #> # inverse EFT efi <- efourier_i(ef) coo_draw(efi, border='red', col=NA) # on Out bot %>% slice(1:5) %>% efourier #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 5 outlines described, 10 harmonics #> # A tibble: 5 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a"},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse elliptical Fourier transform — efourier_i","title":"Inverse elliptical Fourier transform — efourier_i","text":"efourier_i uses inverse elliptical Fourier transformation calculate shape, given list Fourier coefficients, typically obtained computed efourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse elliptical Fourier transform — efourier_i","text":"","code":"efourier_i(ef, nb.h, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse elliptical Fourier transform — efourier_i","text":"ef list. list containing \\(a_n\\), \\(b_n\\), \\(c_n\\) \\(d_n\\) Fourier coefficients, returned efourier. nb.h integer. number harmonics use. specified, length(ef$) used. nb.pts integer. number points calculate.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse elliptical Fourier transform — efourier_i","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse elliptical Fourier transform — efourier_i","text":"See efourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse elliptical Fourier transform — efourier_i","text":"Directly borrowed Claude (2008), also called iefourier .","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse elliptical Fourier transform — efourier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse elliptical Fourier transform — efourier_i","text":"","code":"coo <- bot[1] coo_plot(coo) ef <- efourier(coo, 12) ef #> $an #> [1] -143.1142910 5.2925309 22.9922936 -11.3596452 -14.9412217 #> [6] -5.4200881 5.7177112 0.4509076 0.3107020 -3.1633079 #> [11] 0.2814646 3.4927761 #> #> $bn #> [1] -13.8501141 -21.8994092 11.4235084 13.5870435 -12.6401807 2.5050679 #> [7] 5.1968464 -0.5366171 -1.0431706 1.0823659 2.3427969 0.1022387 #> #> $cn #> [1] 64.44753053 -3.15375656 -17.96822626 5.76052596 7.17390949 #> [6] -2.98410094 -1.20013013 1.18299684 -0.36305436 -0.46782525 #> [11] 0.67134872 0.08954658 #> #> $dn #> [1] -484.90299209 -1.04774048 42.07408510 3.40654863 -9.19128141 #> [6] -2.99359284 0.96722479 2.22582484 0.02026172 -2.26134728 #> [11] -0.04679906 0.80569603 #> #> $ao #> [1] 349.02 #> #> $co #> [1] 1080.921 #> efi <- efourier_i(ef) coo_draw(efi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'efourier' shapes. — efourier_shape","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"efourier_shape calculates 'Fourier elliptical shape' given Fourier coefficients (see Details) can generate 'efourier' shapes. Mainly intended generate shapes /understand efourier works.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"","code":"efourier_shape(an, bn, cn, dn, nb.h, nb.pts = 60, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. cn numeric. \\(c_n\\) Fourier coefficients calculate shape. dn numeric. \\(d_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"list components: x vector x-coordinates y vector y-coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"efourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See efourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"","code":"ef <- efourier(bot[1], 24) efourier_shape(ef$an, ef$bn, ef$cn, ef$dn) # equivalent to efourier_i(ef) #> x y #> [1,] -139.292006 52.55414 #> [2,] -136.616807 10.69211 #> [3,] -131.350271 -30.94211 #> [4,] -125.199336 -72.07640 #> [5,] -118.953152 -113.78248 #> [6,] -113.609682 -155.07182 #> [7,] -110.814096 -196.99594 #> [8,] -110.406802 -238.82588 #> [9,] -114.448576 -280.46843 #> [10,] -121.291958 -321.87890 #> [11,] -128.793705 -362.93618 #> [12,] -133.799480 -404.68963 #> [13,] -133.459946 -446.39242 #> [14,] -121.381226 -485.99486 #> [15,] -90.225043 -512.97786 #> [16,] -49.878625 -523.21089 #> [17,] -8.353210 -526.12066 #> [18,] 33.911396 -525.08469 #> [19,] 74.759609 -519.43972 #> [20,] 113.051448 -502.25491 #> [21,] 136.285584 -468.52283 #> [22,] 141.399365 -427.41134 #> [23,] 140.746409 -385.31652 #> [24,] 138.719031 -343.56495 #> [25,] 136.547192 -301.87577 #> [26,] 132.884166 -259.94004 #> [27,] 128.335128 -218.62173 #> [28,] 123.859620 -176.68909 #> [29,] 118.283114 -135.32263 #> [30,] 115.872309 -93.60856 #> [31,] 116.738256 -51.46991 #> [32,] 121.746650 -10.34707 #> [33,] 130.044438 31.28459 #> [34,] 135.215555 72.30011 #> [35,] 135.968480 114.36171 #> [36,] 127.773756 155.43284 #> [37,] 110.008193 192.61949 #> [38,] 91.059514 230.59227 #> [39,] 78.417823 270.00689 #> [40,] 72.336775 311.64758 #> [41,] 67.126887 353.28501 #> [42,] 63.718346 394.51271 #> [43,] 58.801472 437.18028 #> [44,] 54.675788 477.22927 #> [45,] 57.783825 520.56987 #> [46,] 46.279411 554.26720 #> [47,] 8.173233 561.94185 #> [48,] -37.145543 559.89637 #> [49,] -64.096831 541.62656 #> [50,] -64.927840 500.81669 #> [51,] -64.170645 459.21723 #> [52,] -69.796352 417.94924 #> [53,] -72.732679 375.54798 #> [54,] -77.369097 334.76587 #> [55,] -80.882096 292.41632 #> [56,] -87.983533 251.76743 #> [57,] -103.969321 212.65038 #> [58,] -121.348549 174.68203 #> [59,] -136.478064 135.92288 #> [60,] -141.748300 94.09730 efourier_shape() # is autonomous #> x y #> [1,] -0.15480069 -1.973007909 #> [2,] -0.22809026 -1.818420231 #> [3,] -0.27032753 -1.617424063 #> [4,] -0.29533144 -1.379645958 #> [5,] -0.31810038 -1.115840290 #> [6,] -0.35332863 -0.837066371 #> [7,] -0.41396840 -0.553906111 #> [8,] -0.50997009 -0.275789459 #> [9,] -0.64731572 -0.010481905 #> [10,] -0.82743225 0.236229469 #> [11,] -1.04703483 0.460635732 #> [12,] -1.29840910 0.660997728 #> [13,] -1.57010032 0.837256167 #> [14,] -1.84793879 0.990604033 #> [15,] -2.11630003 1.122977481 #> [16,] -2.35947761 1.236527684 #> [17,] -2.56303702 1.333135713 #> [18,] -2.71502309 1.414025714 #> [19,] -2.80690968 1.479519099 #> [20,] -2.83420662 1.528955598 #> [21,] -2.79667422 1.560787525 #> [22,] -2.69813421 1.572833685 #> [23,] -2.54590625 1.562660872 #> [24,] -2.34993539 1.528046001 #> [25,] -2.12170552 1.467461982 #> [26,] -1.87305376 1.380526662 #> [27,] -1.61500882 1.268356875 #> [28,] -1.35677236 1.133778649 #> [29,] -1.10494596 0.981359078 #> [30,] -0.86308017 0.817243778 #> [31,] -0.63158802 0.648804395 #> [32,] -0.40802730 0.484121281 #> [33,] -0.18771750 0.331344943 #> [34,] 0.03537770 0.197994496 #> [35,] 0.26759916 0.090260326 #> [36,] 0.51448708 0.012380671 #> [37,] 0.77974312 -0.033842603 #> [38,] 1.06437497 -0.049334829 #> [39,] 1.36612060 -0.037808467 #> [40,] 1.67922192 -0.005575404 #> [41,] 1.99458198 0.038882082 #> [42,] 2.30030138 0.085552509 #> [43,] 2.58255024 0.123698665 #> [44,] 2.82669741 0.142757057 #> [45,] 3.01859091 0.133256549 #> [46,] 3.14586632 0.087675830 #> [47,] 3.19915458 0.001163238 #> [48,] 3.17306813 -0.127946593 #> [49,] 3.06686342 -0.297867638 #> [50,] 2.88470784 -0.503375634 #> [51,] 2.63551577 -0.736101825 #> [52,] 2.33235949 -0.985084971 #> [53,] 1.99150137 -1.237536583 #> [54,] 1.63113051 -1.479755629 #> [55,] 1.26991586 -1.698116048 #> [56,] 0.92550660 -1.880044476 #> [57,] 0.61311653 -2.014907112 #> [58,] 0.34432245 -2.094733481 #> [59,] 0.12618734 -2.114720168 #> [60,] -0.03921072 -2.073477807 panel(Out(a2l(replicate(100, efourier_shape(nb.h=6, alpha=2.5, plot=FALSE))))) # Bubble family"},{"path":"http://momx.github.io/Momocs/reference/export.html","id":null,"dir":"Reference","previous_headings":"","what":"Exports Coe objects and shapes — export","title":"Exports Coe objects and shapes — export","text":"Writes .txt .xls whatever readable single shape, Coe, PCA object, along individual names $fac.","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Exports Coe objects and shapes — export","text":"","code":"export(x, file, sep, dec)"},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Exports Coe objects and shapes — export","text":"x Coe PCA object file filenames data.txt default sep field separator string feed write.table). (default tab) tab default dec string feed write.table) (default \".\") default.","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Exports Coe objects and shapes — export","text":"external file","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Exports Coe objects and shapes — export","text":"simple wrapper around write.table. Default parameters write .txt file, readable foreign programs. default parameters, numbers use dots decimal points, considered character chain Excel many countries (locale versions). can solved using dec=',' examples . looking file, specified file, getwd() help. mention everytime use function, cowardly run R Excel 'statistics' , innocent adorable kitten probably murdered somewhere. Use R!","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Exports Coe objects and shapes — export","text":"","code":"# Will write (and remove) files on your working directory! if (FALSE) { bf <- efourier(bot, 6) # Export Coe (here Fourier coefficients) export(bf) # data.txt which can be opened by every software including MS Excel # If you come from a country that uses comma as decimal separator (not recommended, but...) export(bf, dec=',') export(bf, file='data.xls', dec=',') # Export PCA scores bf %>% PCA %>% export() # for shapes (matrices) # export(bot[1], file='bot1.txt') # remove these files from your machine file.remove(\"coefficients.txt\", \"data.xls\", \"scores.txt\") }"},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Procrustes alignment between two shapes — fProcrustes","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"Directly borrowed Claude (2008), called fPsup function.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"","code":"fProcrustes(coo1, coo2)"},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"coo1 configuration matrix superimposed onto centered preshape coo2. coo2 reference configuration matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"list components: coo1 superimposed centered preshape coo1 onto centered preshape coo2 coo2 centered preshape coo2 rotation rotation matrix scale scale parameter DF full Procrustes distance coo1 coo2.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":null,"dir":"Reference","previous_headings":"","what":"Brew and serve fac from Momocs object — fac_dispatcher","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"Ease various specifications fac specification passed Momocs objects. Intensively used (internally).","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"","code":"fac_dispatcher(x, fac)"},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"x Momocs object (Coo, Coe, PCA, etc.) fac specification extract fac","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"prepared factor (numeric). See examples","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"fac can : factor, passed fly column id $fac column name fac; found, return NULL message formula form: ~column_name ($fac, quotes). expresses concise way. Also allows interacting fly. See examples. NULL returns NULL, message","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"","code":"bot <- mutate(bot, s=rnorm(40), fake=factor(rep(letters[1:4], 10))) # factor, on the fly fac_dispatcher(bot, factor(rep(letters[1:4], 10))) #> [1] a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b #> [39] c d #> Levels: a b c d # column id fac_dispatcher(bot, 1) #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # column name fac_dispatcher(bot, \"type\") #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # same, numeric case fac_dispatcher(bot, \"s\") #> s1 s2 s3 s4 s5 s6 #> 1.708650899 -0.759601384 0.972369565 -1.031840383 0.768586627 0.301285060 #> s7 s8 s9 s10 s11 s12 #> 0.424560581 0.006571057 0.741297749 1.559007487 -0.417168752 -0.420322963 #> s13 s14 s15 s16 s17 s18 #> 0.697185864 -0.210961609 1.541085498 0.284831960 0.321961376 -1.068526069 #> s19 s20 s21 s22 s23 s24 #> 1.425715862 1.199570200 -1.678036407 1.828806163 -0.535208856 -0.835660641 #> s25 s26 s27 s28 s29 s30 #> -0.758469900 -1.324129902 0.788467471 -1.376718465 -1.070395242 -0.986740931 #> s31 s32 s33 s34 s35 s36 #> 0.536586184 -0.445206584 -0.003501437 -0.623814095 0.460846925 -0.577520120 #> s37 s38 s39 s40 #> 1.687608566 0.025660517 -0.590307162 1.382021803 # formula interface fac_dispatcher(bot, ~type) #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # formula interface + interaction on the fly fac_dispatcher(bot, ~type+fake) #> [1] whisky_a whisky_b whisky_c whisky_d whisky_a whisky_b whisky_c whisky_d #> [9] whisky_a whisky_b whisky_c whisky_d whisky_a whisky_b whisky_c whisky_d #> [17] whisky_a whisky_b whisky_c whisky_d beer_a beer_b beer_c beer_d #> [25] beer_a beer_b beer_c beer_d beer_a beer_b beer_c beer_d #> [33] beer_a beer_b beer_c beer_d beer_a beer_b beer_c beer_d #> Levels: beer_a beer_b beer_c beer_d whisky_a whisky_b whisky_c whisky_d # when passing NULL or non existing column fac_dispatcher(42, NULL) #> NULL fac_dispatcher(bot, \"loser\") #> not a valid column specification, returning NULL #> NULL"},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Generalized Procrustes alignment between shapes — fgProcrustes","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Directly borrowed Claude (2008), called fgpa2 function.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"","code":"fgProcrustes(x, tol, coo)"},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"x array, list configurations, , Opn Ldk object tol numeric stop iterations coo logical, working Opn, whether use $coo rather $ldk","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"list components: rotated array superimposed configurations iterationnumber number iterations Q convergence criterion Qi full list Q Qd difference successive Q interproc.dist minimal sum squared norms pairwise differences shapes superimposed sample mshape mean shape configuration cent.size vector centroid sizes. , Opn Ldk object.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"performed Opn object, try use $ldk slot, landmarks previousy defined, (message) $coo slot, case, shapes must number coordinates (coo_sample may help).","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Slightly less optimized procGPA shapes package (~20% machine). optimized performance last thing improve! Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"","code":"# on Ldk w <- wings %>% slice(1:5) # for the sake of speed stack(w) fgProcrustes(w, tol=0.1) %>% stack() #> iteration: 1 \tgain: 77.967 #> iteration: 2 \tgain: 0.00039082 # on Out h <- hearts %>% slice(1:5) # for the sake of speed stack(h) fgProcrustes(h) %>% stack() #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224 #> iteration: 3 \tgain: 4.8293e-05 #> iteration: 4 \tgain: 1.0158e-06 #> iteration: 5 \tgain: 4.1771e-05 #> iteration: 6 \tgain: 7.9575e-06 #> iteration: 7 \tgain: 9.2944e-06 #> iteration: 8 \tgain: 3.1971e-07 #> iteration: 9 \tgain: 5.6429e-06 #> iteration: 10 \tgain: 3.6475e-06 #> iteration: 11 \tgain: 1.0455e-06 #> iteration: 12 \tgain: 4.6442e-08 #> iteration: 13 \tgain: 3.9276e-07 #> iteration: 14 \tgain: 5.6006e-07 #> iteration: 15 \tgain: 3.5497e-07 #> iteration: 16 \tgain: 2.2619e-08 #> iteration: 17 \tgain: 1.6228e-07 #> iteration: 18 \tgain: 1.662e-07 #> iteration: 19 \tgain: 8.6435e-08 #> iteration: 20 \tgain: 6.7107e-09 #> iteration: 21 \tgain: 3.6428e-08 #> iteration: 22 \tgain: 4.0699e-08 #> iteration: 23 \tgain: 2.2641e-08 #> iteration: 24 \tgain: 2.0915e-09 #> iteration: 25 \tgain: 9.3406e-09 #> iteration: 26 \tgain: 1.0441e-08 #> iteration: 27 \tgain: 5.8207e-09 #> iteration: 28 \tgain: 6.1735e-10 #> iteration: 29 \tgain: 2.312e-09 #> iteration: 30 \tgain: 2.6457e-09 #> iteration: 31 \tgain: 1.502e-09 #> iteration: 32 \tgain: 1.793e-10 #> iteration: 33 \tgain: 5.7701e-10 #> iteration: 34 \tgain: 6.7226e-10 #> iteration: 35 \tgain: 3.8692e-10 #> iteration: 36 \tgain: 5.1135e-11"},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"Directly wrapped around geomorph::gpagen.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"","code":"fgsProcrustes(x)"},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"See ?gpagen geomorph package","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"x Ldk object $slidings","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"list","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"Landmarks methods less tested Momocs. Keep mind features still experimental help welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"","code":"ch <- chaff %>% slice(1:5) # for the sake of speed chaffp <- fgsProcrustes(ch) #> #> Performing GPA #> | | | 0% | |======= | 10% #> Singular BE matrix; using generalized inverse | |============== | 20% #> Singular BE matrix; using generalized inverse | |===================== | 30% #> Singular BE matrix; using generalized inverse | |============================ | 40% #> Singular BE matrix; using generalized inverse | |=================================== | 50% #> Singular BE matrix; using generalized inverse | |========================================== | 60% #> Singular BE matrix; using generalized inverse | |================================================= | 70% #> Singular BE matrix; using generalized inverse | |======================================================== | 80% #> Singular BE matrix; using generalized inverse | |=============================================================== | 90% #> Singular BE matrix; using generalized inverse | |======================================================================| 100% #> #> Making projections... Finished! chaffp #> An LdkCoe [full Generalized Procrustes] object with: #> -------------------- #> - $coo: 5 configuration of landmarks (172 +/- 0 coordinates) #> # A tibble: 5 × 3 #> id taxa centsize #> #> 1 571 tax1 1343. #> 2 572 tax1 1279. #> 3 573 tax1 1232. #> 4 581 tax1 1296. #> 5 582 tax1 1274. chaffp %>% PCA() %>% plot(\"taxa\") #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset based on conditions — filter","title":"Subset based on conditions — filter","text":"Return shapes matching conditions, $fac. See examples ?dplyr::filter.","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset based on conditions — filter","text":"","code":"filter(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset based on conditions — filter","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset based on conditions — filter","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset based on conditions — filter","text":"dplyr verbs maintained. probbaly filter PCA objects. latter calculated using individuals filtering may lead false conclusions. want highlith individuals, see examples plot_PCA.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset based on conditions — filter","text":"","code":"olea #> Opn (curves) #> - 210 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk # we retain on dorsal views filter(olea, view==\"VD\") #> Opn (curves) #> - 120 curves, 100 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 120 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VD O11 #> 3 Aglan cult VD O12 #> 4 Aglan cult VD O13 #> 5 Aglan cult VD O14 #> 6 Aglan cult VD O15 #> # ℹ 114 more rows #> - also: $ldk # only dorsal views and Aglan+PicMa varieties filter(olea, view==\"VD\", var %in% c(\"Aglan\", \"PicMa\")) #> Opn (curves) #> - 60 curves, 100 +/- 2 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 60 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VD O11 #> 3 Aglan cult VD O12 #> 4 Aglan cult VD O13 #> 5 Aglan cult VD O14 #> 6 Aglan cult VD O15 #> # ℹ 54 more rows #> - also: $ldk # we create an id column and retain the 120 first shapes olea %>% mutate(id=1:length(olea)) %>% filter(id > 120) #> Opn (curves) #> - 90 curves, 99 +/- 4 coords (in $coo) #> - 5 classifiers (in $fac): #> # A tibble: 90 × 5 #> var domes view ind id #> #> 1 PicMa cult VD O24 121 #> 2 PicMa cult VL O24 122 #> 3 PicMa cult VD O25 123 #> 4 PicMa cult VL O25 124 #> 5 PicMa cult VD O26 125 #> 6 PicMa cult VL O26 126 #> # ℹ 84 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":null,"dir":"Reference","previous_headings":"","what":"Flips PCA axes — flip_PCaxes","title":"Flips PCA axes — flip_PCaxes","text":"Simply multiply -1, corresponding scores rotation vectors PCA objects. PC orientation arbitrary, may help better display.","code":""},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flips PCA axes — flip_PCaxes","text":"","code":"flip_PCaxes(x, axs)"},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flips PCA axes — flip_PCaxes","text":"x PCA object axs numeric PC(s) flip","code":""},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flips PCA axes — flip_PCaxes","text":"","code":"bp <- bot %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bp %>% plot #> will be deprecated soon, see ?plot_PCA bp %>% flip_PCaxes(1) %>% plot() #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates convex hull area/volume of PCA scores — get_chull_area","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"May useful compare shape diversity. Expressed PCA units compared within PCA.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"","code":"get_chull_area(x, fac, xax = 1, yax = 2) get_chull_volume(x, fac, xax = 1, yax = 2, zax = 3)"},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"x PCA object fac (optionnal) column name ID $fac slot. xax first PC axis use (1 default) yax second PC axis (2 default) zax third PC axis (3 default volume)","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"fac provided global area/volume returned; otherwise named list every level fac","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"get_chull_area calculated using coo_chull followed coo_area; get_chull_volume calculated using geometry::convexhulln","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"","code":"bp <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details get_chull_area(bp) #> [1] 0.01968577 get_chull_area(bp, 1) #> $beer #> [1] 0.01802331 #> #> $whisky #> [1] 0.008768242 #> get_chull_volume(bp) #> [1] 0.0005563784 get_chull_volume(bp, 1) #> $beer #> [1] 0.0004506466 #> #> $whisky #> [1] 0.0001181342 #>"},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieves landmarks coordinates — get_ldk","title":"Retrieves landmarks coordinates — get_ldk","text":"See Details different behaviors implemented.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieves landmarks coordinates — get_ldk","text":"","code":"get_ldk(Coo)"},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieves landmarks coordinates — get_ldk","text":"Coo , Opn Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieves landmarks coordinates — get_ldk","text":"list shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieves landmarks coordinates — get_ldk","text":"Different behaviors depending class object: Ldk: retrieves landmarks. Ldk slidings defined: retrieves fixed landmarks, sliding ones. See also get_slidings. landmarks $ldk $coo, . Opn: .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieves landmarks coordinates — get_ldk","text":"","code":"# Out example ldk.h <- get_ldk(hearts) stack(Ldk(ldk.h)) # on Ldk (no slidings) get_ldk(wings) # equivalent to wings$coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> [7,] 0.2311 -0.0228 #> [8,] 0.2040 -0.0452 #> [9,] 0.1282 -0.0742 #> [10,] 0.0424 -0.0966 #> [11,] -0.0674 -0.1108 #> [12,] -0.4102 -0.0163 #> [13,] -0.3140 0.0318 #> [14,] -0.1768 0.0341 #> [15,] 0.0715 0.0509 #> [16,] -0.0540 0.0238 #> [17,] 0.0575 -0.0059 #> [18,] -0.1401 -0.0240 #> #> $AN2 #> [,1] [,2] #> [1,] -0.4814 0.0135 #> [2,] -0.0058 0.0780 #> [3,] 0.2345 0.0644 #> [4,] 0.2460 0.0467 #> [5,] 0.2487 0.0281 #> [6,] 0.2430 0.0115 #> [7,] 0.2316 -0.0039 #> [8,] 0.1956 -0.0305 #> [9,] 0.1462 -0.0545 #> [10,] 0.0483 -0.0866 #> [11,] -0.0520 -0.1047 #> [12,] -0.4016 -0.0250 #> [13,] -0.3868 0.0166 #> [14,] -0.1808 0.0229 #> [15,] 0.0484 0.0405 #> [16,] -0.0519 0.0164 #> [17,] 0.0623 -0.0047 #> [18,] -0.1444 -0.0286 #> #> $AN3 #> [,1] [,2] #> [1,] -0.4622 0.0159 #> [2,] 0.0089 0.0689 #> [3,] 0.2404 0.0545 #> [4,] 0.2501 0.0424 #> [5,] 0.2600 0.0230 #> [6,] 0.2541 0.0039 #> [7,] 0.2369 -0.0105 #> [8,] 0.1957 -0.0305 #> [9,] 0.1249 -0.0480 #> [10,] 0.0146 -0.0720 #> [11,] -0.0758 -0.0865 #> [12,] -0.4104 -0.0200 #> [13,] -0.3919 0.0190 #> [14,] -0.1724 0.0182 #> [15,] 0.0577 0.0344 #> [16,] -0.0468 0.0115 #> [17,] 0.0766 -0.0079 #> [18,] -0.1602 -0.0162 #> #> $AN4 #> [,1] [,2] #> [1,] -0.4534 -0.0028 #> [2,] -0.0318 0.0738 #> [3,] 0.2423 0.0808 #> [4,] 0.2627 0.0559 #> [5,] 0.2654 0.0322 #> [6,] 0.2579 0.0143 #> [7,] 0.2426 0.0018 #> [8,] 0.1851 -0.0313 #> [9,] 0.1191 -0.0581 #> [10,] 0.0203 -0.0847 #> [11,] -0.0919 -0.0957 #> [12,] -0.3862 -0.0289 #> [13,] -0.4051 -0.0072 #> [14,] -0.1536 0.0150 #> [15,] 0.0617 0.0436 #> [16,] -0.0549 0.0217 #> [17,] 0.0705 -0.0031 #> [18,] -0.1507 -0.0273 #> #> $AN5 #> [,1] [,2] #> [1,] -0.4926 -0.0212 #> [2,] -0.0260 0.0708 #> [3,] 0.2347 0.0679 #> [4,] 0.2398 0.0584 #> [5,] 0.2415 0.0355 #> [6,] 0.2337 0.0187 #> [7,] 0.2163 0.0010 #> [8,] 0.1920 -0.0171 #> [9,] 0.1271 -0.0443 #> [10,] 0.0427 -0.0699 #> [11,] -0.0516 -0.1016 #> [12,] -0.4242 -0.0505 #> [13,] -0.3970 -0.0018 #> [14,] -0.1374 0.0154 #> [15,] 0.0762 0.0457 #> [16,] -0.0313 0.0170 #> [17,] 0.0880 0.0037 #> [18,] -0.1318 -0.0278 #> #> $AN6 #> [,1] [,2] #> [1,] -0.4614 0.0567 #> [2,] -0.0091 0.0684 #> [3,] 0.2335 0.0345 #> [4,] 0.2499 0.0171 #> [5,] 0.2553 -0.0019 #> [6,] 0.2522 -0.0176 #> [7,] 0.2383 -0.0356 #> [8,] 0.2030 -0.0524 #> [9,] 0.1296 -0.0691 #> [10,] 0.0155 -0.0785 #> [11,] -0.0965 -0.0805 #> [12,] -0.4053 0.0196 #> [13,] -0.3907 0.0522 #> [14,] -0.1607 0.0403 #> [15,] 0.0703 0.0371 #> [16,] -0.0577 0.0258 #> [17,] 0.0801 -0.0118 #> [18,] -0.1463 -0.0042 #> #> $AN7 #> [,1] [,2] #> [1,] -0.4742 -0.0161 #> [2,] -0.0633 0.0656 #> [3,] 0.2206 0.0937 #> [4,] 0.2490 0.0720 #> [5,] 0.2576 0.0483 #> [6,] 0.2512 0.0232 #> [7,] 0.2388 0.0116 #> [8,] 0.1871 -0.0273 #> [9,] 0.1484 -0.0449 #> [10,] 0.0230 -0.0882 #> [11,] -0.0575 -0.1054 #> [12,] -0.3916 -0.0478 #> [13,] -0.3805 -0.0085 #> [14,] -0.1604 0.0119 #> [15,] 0.0647 0.0470 #> [16,] -0.0449 0.0135 #> [17,] 0.0903 -0.0072 #> [18,] -0.1585 -0.0414 #> #> $AN8 #> [,1] [,2] #> [1,] -0.4698 0.0224 #> [2,] 0.0525 0.0771 #> [3,] 0.2450 0.0501 #> [4,] 0.2603 0.0333 #> [5,] 0.2587 0.0166 #> [6,] 0.2552 0.0071 #> [7,] 0.2373 -0.0083 #> [8,] 0.1808 -0.0319 #> [9,] 0.1008 -0.0546 #> [10,] 0.0155 -0.0807 #> [11,] -0.0922 -0.0907 #> [12,] -0.4082 -0.0124 #> [13,] -0.3919 0.0228 #> [14,] -0.1604 0.0248 #> [15,] 0.0494 0.0383 #> [16,] -0.0575 0.0160 #> [17,] 0.0660 -0.0107 #> [18,] -0.1416 -0.0192 #> #> $AN9 #> [,1] [,2] #> [1,] -0.4652 -0.0110 #> [2,] -0.0017 0.0759 #> [3,] 0.2246 0.0759 #> [4,] 0.2405 0.0587 #> [5,] 0.2500 0.0443 #> [6,] 0.2509 0.0258 #> [7,] 0.2406 0.0057 #> [8,] 0.2009 -0.0214 #> [9,] 0.1389 -0.0475 #> [10,] 0.0284 -0.0790 #> [11,] -0.0450 -0.0979 #> [12,] -0.3999 -0.0458 #> [13,] -0.3968 -0.0077 #> [14,] -0.1886 0.0090 #> [15,] 0.0561 0.0424 #> [16,] -0.0683 0.0081 #> [17,] 0.0793 -0.0046 #> [18,] -0.1449 -0.0309 #> #> $AN10 #> [,1] [,2] #> [1,] -0.4496 0.0335 #> [2,] 0.0012 0.0701 #> [3,] 0.2502 0.0412 #> [4,] 0.2591 0.0249 #> [5,] 0.2598 0.0083 #> [6,] 0.2540 -0.0054 #> [7,] 0.2376 -0.0184 #> [8,] 0.1914 -0.0377 #> [9,] 0.1255 -0.0551 #> [10,] 0.0201 -0.0796 #> [11,] -0.0594 -0.0904 #> [12,] -0.4083 -0.0007 #> [13,] -0.3931 0.0279 #> [14,] -0.1805 0.0303 #> [15,] 0.0520 0.0405 #> [16,] -0.0622 0.0241 #> [17,] 0.0662 -0.0066 #> [18,] -0.1640 -0.0070 #> #> $AN11 #> [,1] [,2] #> [1,] -0.4586 0.0314 #> [2,] -0.0040 0.0707 #> [3,] 0.2412 0.0445 #> [4,] 0.2514 0.0284 #> [5,] 0.2543 0.0140 #> [6,] 0.2504 -0.0032 #> [7,] 0.2330 -0.0248 #> [8,] 0.1846 -0.0433 #> [9,] 0.1228 -0.0565 #> [10,] 0.0319 -0.0713 #> [11,] -0.0718 -0.0806 #> [12,] -0.4071 -0.0050 #> [13,] -0.3992 0.0249 #> [14,] -0.1819 0.0293 #> [15,] 0.0809 0.0402 #> [16,] -0.0575 0.0224 #> [17,] 0.0888 -0.0103 #> [18,] -0.1592 -0.0105 #> #> $TO12 #> [,1] [,2] #> [1,] -0.4577 0.0257 #> [2,] -0.0119 0.0557 #> [3,] 0.2215 0.0519 #> [4,] 0.2416 0.0411 #> [5,] 0.2510 0.0217 #> [6,] 0.2488 0.0035 #> [7,] 0.2333 -0.0147 #> [8,] 0.1951 -0.0385 #> [9,] 0.1154 -0.0580 #> [10,] 0.0081 -0.0710 #> [11,] -0.0986 -0.0839 #> [12,] -0.4056 0.0000 #> [13,] -0.3814 0.0248 #> [14,] -0.1579 0.0201 #> [15,] 0.1630 0.0365 #> [16,] -0.0686 0.0122 #> [17,] 0.0985 -0.0115 #> [18,] -0.1947 -0.0157 #> #> $WY13 #> [,1] [,2] #> [1,] -0.4704 0.0144 #> [2,] 0.0120 0.0897 #> [3,] 0.2333 0.0707 #> [4,] 0.2545 0.0505 #> [5,] 0.2624 0.0302 #> [6,] 0.2601 0.0070 #> [7,] 0.2429 -0.0154 #> [8,] 0.2026 -0.0363 #> [9,] 0.1108 -0.0668 #> [10,] 0.0149 -0.0885 #> [11,] -0.1081 -0.1035 #> [12,] -0.4161 -0.0288 #> [13,] -0.3559 0.0268 #> [14,] -0.1632 0.0253 #> [15,] 0.0432 0.0414 #> [16,] -0.0244 0.0162 #> [17,] 0.0478 -0.0092 #> [18,] -0.1462 -0.0237 #> #> $WY14 #> [,1] [,2] #> [1,] -0.4693 -0.0651 #> [2,] 0.0093 0.0766 #> [3,] 0.2223 0.0934 #> [4,] 0.2417 0.0771 #> [5,] 0.2472 0.0550 #> [6,] 0.2427 0.0420 #> [7,] 0.2263 0.0193 #> [8,] 0.1913 -0.0059 #> [9,] 0.1359 -0.0363 #> [10,] 0.0587 -0.0694 #> [11,] -0.0426 -0.0967 #> [12,] -0.4065 -0.0824 #> [13,] -0.4097 -0.0476 #> [14,] -0.1541 0.0086 #> [15,] 0.0189 0.0479 #> [16,] -0.0264 0.0211 #> [17,] 0.0566 0.0022 #> [18,] -0.1423 -0.0397 #> #> $WY15 #> [,1] [,2] #> [1,] -0.4673 0.0220 #> [2,] -0.0277 0.0745 #> [3,] 0.2456 0.0517 #> [4,] 0.2553 0.0369 #> [5,] 0.2618 0.0159 #> [6,] 0.2593 0.0014 #> [7,] 0.2409 -0.0152 #> [8,] 0.1932 -0.0402 #> [9,] 0.1261 -0.0584 #> [10,] 0.0266 -0.0732 #> [11,] -0.1079 -0.0788 #> [12,] -0.4005 -0.0119 #> [13,] -0.3871 0.0193 #> [14,] -0.1765 0.0251 #> [15,] 0.0456 0.0363 #> [16,] -0.0333 0.0174 #> [17,] 0.0724 -0.0072 #> [18,] -0.1266 -0.0156 #> #> $WY16 #> [,1] [,2] #> [1,] -0.4598 0.0418 #> [2,] 0.0208 0.0737 #> [3,] 0.2401 0.0484 #> [4,] 0.2577 0.0265 #> [5,] 0.2626 0.0063 #> [6,] 0.2574 -0.0081 #> [7,] 0.2337 -0.0255 #> [8,] 0.1831 -0.0458 #> [9,] 0.1230 -0.0605 #> [10,] 0.0175 -0.0749 #> [11,] -0.1034 -0.0821 #> [12,] -0.4151 0.0095 #> [13,] -0.4040 0.0348 #> [14,] -0.1433 0.0285 #> [15,] 0.0435 0.0364 #> [16,] -0.0406 0.0177 #> [17,] 0.0610 -0.0099 #> [18,] -0.1344 -0.0169 #> #> $UR17 #> [,1] [,2] #> [1,] -0.4690 0.0256 #> [2,] 0.0188 0.0844 #> [3,] 0.2381 0.0519 #> [4,] 0.2517 0.0352 #> [5,] 0.2540 0.0131 #> [6,] 0.2459 -0.0122 #> [7,] 0.2249 -0.0331 #> [8,] 0.1799 -0.0516 #> [9,] 0.1157 -0.0621 #> [10,] 0.0257 -0.0784 #> [11,] -0.1524 -0.0905 #> [12,] -0.4012 -0.0015 #> [13,] -0.3796 0.0340 #> [14,] -0.1482 0.0442 #> [15,] 0.1153 0.0437 #> [16,] -0.0745 0.0274 #> [17,] 0.0942 -0.0158 #> [18,] -0.1395 -0.0142 #> #> $UR18 #> [,1] [,2] #> [1,] -0.4999 0.0214 #> [2,] 0.0533 0.0868 #> [3,] 0.2081 0.0713 #> [4,] 0.2263 0.0548 #> [5,] 0.2358 0.0361 #> [6,] 0.2391 0.0128 #> [7,] 0.2206 -0.0235 #> [8,] 0.1792 -0.0512 #> [9,] 0.1168 -0.0693 #> [10,] 0.0343 -0.0924 #> [11,] -0.1419 -0.1106 #> [12,] -0.4192 -0.0064 #> [13,] -0.3695 0.0241 #> [14,] -0.1232 0.0410 #> [15,] 0.1380 0.0543 #> [16,] -0.0694 0.0134 #> [17,] 0.0825 -0.0252 #> [18,] -0.1111 -0.0373 #> #> $UR19 #> [,1] [,2] #> [1,] -0.4668 -0.0044 #> [2,] -0.0334 0.0689 #> [3,] 0.2229 0.0664 #> [4,] 0.2464 0.0514 #> [5,] 0.2598 0.0307 #> [6,] 0.2588 0.0141 #> [7,] 0.2389 -0.0053 #> [8,] 0.1792 -0.0283 #> [9,] 0.1107 -0.0468 #> [10,] 0.0349 -0.0718 #> [11,] -0.1502 -0.0893 #> [12,] -0.3964 -0.0316 #> [13,] -0.3764 0.0077 #> [14,] -0.1537 0.0238 #> [15,] 0.1411 0.0493 #> [16,] -0.0807 0.0116 #> [17,] 0.0985 -0.0159 #> [18,] -0.1336 -0.0306 #> #> $UR20 #> [,1] [,2] #> [1,] -0.4873 0.0122 #> [2,] -0.0175 0.0784 #> [3,] 0.2357 0.0725 #> [4,] 0.2514 0.0514 #> [5,] 0.2567 0.0255 #> [6,] 0.2527 0.0058 #> [7,] 0.2371 -0.0142 #> [8,] 0.1959 -0.0388 #> [9,] 0.1245 -0.0612 #> [10,] 0.0397 -0.0783 #> [11,] -0.1466 -0.1012 #> [12,] -0.4242 -0.0296 #> [13,] -0.3325 0.0165 #> [14,] -0.1271 0.0308 #> [15,] 0.0840 0.0459 #> [16,] -0.0807 0.0177 #> [17,] 0.0600 -0.0103 #> [18,] -0.1219 -0.0230 #> #> $CA21 #> [,1] [,2] #> [1,] -0.4829 0.0300 #> [2,] 0.0117 0.0938 #> [3,] 0.2398 0.0578 #> [4,] 0.2544 0.0325 #> [5,] 0.2518 0.0092 #> [6,] 0.2446 -0.0074 #> [7,] 0.2271 -0.0243 #> [8,] 0.1758 -0.0524 #> [9,] 0.1062 -0.0728 #> [10,] 0.0065 -0.0876 #> [11,] -0.0936 -0.0955 #> [12,] -0.4021 0.0090 #> [13,] -0.3899 0.0343 #> [14,] -0.1648 0.0403 #> [15,] 0.0951 0.0433 #> [16,] -0.0210 0.0206 #> [17,] 0.0735 -0.0094 #> [18,] -0.1321 -0.0214 #> #> $CA22 #> [,1] [,2] #> [1,] -0.4683 0.0225 #> [2,] 0.0446 0.0866 #> [3,] 0.2237 0.0673 #> [4,] 0.2486 0.0447 #> [5,] 0.2543 0.0291 #> [6,] 0.2566 0.0081 #> [7,] 0.2350 -0.0205 #> [8,] 0.1694 -0.0470 #> [9,] 0.1025 -0.0648 #> [10,] 0.0227 -0.0858 #> [11,] -0.0900 -0.0984 #> [12,] -0.4127 -0.0165 #> [13,] -0.3935 0.0185 #> [14,] -0.1948 0.0288 #> [15,] 0.0637 0.0464 #> [16,] -0.0261 0.0189 #> [17,] 0.0842 -0.0124 #> [18,] -0.1198 -0.0254 #> #> $CA23 #> [,1] [,2] #> [1,] -0.4625 0.0195 #> [2,] 0.0534 0.0874 #> [3,] 0.2472 0.0558 #> [4,] 0.2595 0.0425 #> [5,] 0.2608 0.0208 #> [6,] 0.2517 0.0033 #> [7,] 0.2317 -0.0116 #> [8,] 0.1701 -0.0391 #> [9,] 0.1081 -0.0590 #> [10,] 0.0151 -0.0825 #> [11,] -0.0976 -0.0988 #> [12,] -0.4123 -0.0236 #> [13,] -0.3980 0.0148 #> [14,] -0.1728 0.0274 #> [15,] 0.0480 0.0493 #> [16,] -0.0277 0.0244 #> [17,] 0.0489 -0.0032 #> [18,] -0.1236 -0.0275 #> #> $CA24 #> [,1] [,2] #> [1,] -0.4473 0.0502 #> [2,] -0.0237 0.0884 #> [3,] 0.2454 0.0522 #> [4,] 0.2706 0.0277 #> [5,] 0.2719 0.0059 #> [6,] 0.2623 -0.0133 #> [7,] 0.2396 -0.0313 #> [8,] 0.1828 -0.0538 #> [9,] 0.1047 -0.0703 #> [10,] 0.0191 -0.0914 #> [11,] -0.0813 -0.1033 #> [12,] -0.3940 0.0049 #> [13,] -0.3814 0.0464 #> [14,] -0.2018 0.0488 #> [15,] 0.0482 0.0441 #> [16,] -0.0358 0.0232 #> [17,] 0.0524 -0.0112 #> [18,] -0.1317 -0.0173 #> #> $CA25 #> [,1] [,2] #> [1,] -0.4681 0.0445 #> [2,] 0.0566 0.0841 #> [3,] 0.2515 0.0503 #> [4,] 0.2635 0.0318 #> [5,] 0.2617 0.0109 #> [6,] 0.2493 -0.0113 #> [7,] 0.2229 -0.0326 #> [8,] 0.1654 -0.0584 #> [9,] 0.1050 -0.0713 #> [10,] 0.0084 -0.0877 #> [11,] -0.1085 -0.0962 #> [12,] -0.4064 0.0035 #> [13,] -0.3850 0.0391 #> [14,] -0.1688 0.0396 #> [15,] 0.0717 0.0458 #> [16,] -0.0227 0.0245 #> [17,] 0.0439 -0.0054 #> [18,] -0.1404 -0.0113 #> #> $CA26 #> [,1] [,2] #> [1,] -0.4654 0.0045 #> [2,] -0.0237 0.0591 #> [3,] 0.2298 0.0652 #> [4,] 0.2506 0.0472 #> [5,] 0.2565 0.0359 #> [6,] 0.2547 0.0191 #> [7,] 0.2406 0.0016 #> [8,] 0.1958 -0.0240 #> [9,] 0.1348 -0.0499 #> [10,] 0.0377 -0.0837 #> [11,] -0.0598 -0.1028 #> [12,] -0.4078 -0.0288 #> [13,] -0.3939 0.0037 #> [14,] -0.1667 0.0187 #> [15,] 0.0639 0.0422 #> [16,] -0.0479 0.0175 #> [17,] 0.0514 0.0013 #> [18,] -0.1504 -0.0267 #> #> $CA27 #> [,1] [,2] #> [1,] -0.4544 0.0221 #> [2,] -0.0074 0.0855 #> [3,] 0.2360 0.0679 #> [4,] 0.2578 0.0500 #> [5,] 0.2686 0.0258 #> [6,] 0.2677 0.0018 #> [7,] 0.2525 -0.0206 #> [8,] 0.2016 -0.0483 #> [9,] 0.1010 -0.0702 #> [10,] 0.0270 -0.0886 #> [11,] -0.0571 -0.0967 #> [12,] -0.3962 -0.0166 #> [13,] -0.3685 0.0227 #> [14,] -0.1830 0.0288 #> [15,] 0.0186 0.0402 #> [16,] -0.0344 0.0185 #> [17,] 0.0542 -0.0106 #> [18,] -0.1840 -0.0120 #> #> $OR28 #> [,1] [,2] #> [1,] -0.4653 -0.0153 #> [2,] -0.0530 0.0713 #> [3,] 0.1996 0.0886 #> [4,] 0.2548 0.0643 #> [5,] 0.2654 0.0462 #> [6,] 0.2632 0.0168 #> [7,] 0.2399 -0.0084 #> [8,] 0.1881 -0.0358 #> [9,] 0.1297 -0.0542 #> [10,] 0.0436 -0.0796 #> [11,] -0.0329 -0.0978 #> [12,] -0.4176 -0.0393 #> [13,] -0.3934 -0.0092 #> [14,] -0.1727 0.0196 #> [15,] 0.0655 0.0490 #> [16,] -0.0419 0.0247 #> [17,] 0.0323 -0.0041 #> [18,] -0.1054 -0.0366 #> #> $MA29 #> [,1] [,2] #> [1,] -0.4624 0.0319 #> [2,] 0.0361 0.0848 #> [3,] 0.2647 0.0476 #> [4,] 0.2711 0.0332 #> [5,] 0.2686 0.0142 #> [6,] 0.2536 -0.0028 #> [7,] 0.2181 -0.0254 #> [8,] 0.1662 -0.0468 #> [9,] 0.1179 -0.0599 #> [10,] 0.0245 -0.0808 #> [11,] -0.0732 -0.0968 #> [12,] -0.3969 -0.0034 #> [13,] -0.3870 0.0305 #> [14,] -0.1745 0.0310 #> [15,] 0.0578 0.0444 #> [16,] -0.0471 0.0241 #> [17,] 0.0261 -0.0030 #> [18,] -0.1635 -0.0226 #> #> $MA30 #> [,1] [,2] #> [1,] -0.4740 0.0220 #> [2,] 0.0024 0.0831 #> [3,] 0.2327 0.0713 #> [4,] 0.2492 0.0529 #> [5,] 0.2556 0.0308 #> [6,] 0.2491 0.0089 #> [7,] 0.2318 -0.0089 #> [8,] 0.1827 -0.0386 #> [9,] 0.1087 -0.0608 #> [10,] 0.0389 -0.0882 #> [11,] -0.0529 -0.1136 #> [12,] -0.4112 -0.0271 #> [13,] -0.3980 0.0168 #> [14,] -0.1748 0.0275 #> [15,] 0.0599 0.0415 #> [16,] -0.0157 0.0171 #> [17,] 0.0480 -0.0105 #> [18,] -0.1324 -0.0244 #> #> $MA31 #> [,1] [,2] #> [1,] -0.4831 -0.0136 #> [2,] 0.0024 0.0861 #> [3,] 0.2431 0.0843 #> [4,] 0.2554 0.0625 #> [5,] 0.2540 0.0326 #> [6,] 0.2405 0.0126 #> [7,] 0.2165 -0.0073 #> [8,] 0.1757 -0.0319 #> [9,] 0.1188 -0.0525 #> [10,] 0.0420 -0.0831 #> [11,] -0.0576 -0.1092 #> [12,] -0.4031 -0.0419 #> [13,] -0.3856 -0.0059 #> [14,] -0.1916 0.0145 #> [15,] 0.0674 0.0531 #> [16,] -0.0285 0.0259 #> [17,] 0.0642 -0.0014 #> [18,] -0.1304 -0.0246 #> #> $PS32 #> [,1] [,2] #> [1,] -0.4955 0.0422 #> [2,] 0.0429 0.0871 #> [3,] 0.2268 0.0616 #> [4,] 0.2411 0.0429 #> [5,] 0.2455 0.0159 #> [6,] 0.2386 -0.0002 #> [7,] 0.2212 -0.0235 #> [8,] 0.1736 -0.0527 #> [9,] 0.1042 -0.0675 #> [10,] 0.0273 -0.0890 #> [11,] -0.0741 -0.1126 #> [12,] -0.4098 0.0008 #> [13,] -0.4000 0.0326 #> [14,] -0.1689 0.0341 #> [15,] 0.0781 0.0438 #> [16,] -0.0248 0.0224 #> [17,] 0.0790 -0.0106 #> [18,] -0.1054 -0.0273 #> #> $PS33 #> [,1] [,2] #> [1,] -0.4870 -0.0111 #> [2,] 0.0401 0.0939 #> [3,] 0.2165 0.0943 #> [4,] 0.2332 0.0825 #> [5,] 0.2471 0.0502 #> [6,] 0.2408 0.0188 #> [7,] 0.2241 -0.0047 #> [8,] 0.1764 -0.0367 #> [9,] 0.1146 -0.0632 #> [10,] 0.0050 -0.0961 #> [11,] -0.0748 -0.1175 #> [12,] -0.4034 -0.0539 #> [13,] -0.4011 -0.0029 #> [14,] -0.1615 0.0180 #> [15,] 0.0824 0.0556 #> [16,] -0.0144 0.0217 #> [17,] 0.0784 -0.0062 #> [18,] -0.1164 -0.0428 #> #> $PS34 #> [,1] [,2] #> [1,] -0.4862 0.0842 #> [2,] 0.0260 0.0865 #> [3,] 0.2370 0.0326 #> [4,] 0.2426 0.0203 #> [5,] 0.2407 0.0011 #> [6,] 0.2355 -0.0171 #> [7,] 0.2093 -0.0424 #> [8,] 0.1746 -0.0611 #> [9,] 0.1018 -0.0804 #> [10,] 0.0167 -0.0920 #> [11,] -0.0894 -0.1024 #> [12,] -0.4233 0.0207 #> [13,] -0.3944 0.0698 #> [14,] -0.1543 0.0526 #> [15,] 0.0847 0.0385 #> [16,] 0.0040 0.0209 #> [17,] 0.0815 -0.0175 #> [18,] -0.1069 -0.0145 #> #> $PS35 #> [,1] [,2] #> [1,] -0.4698 0.0229 #> [2,] 0.0008 0.0769 #> [3,] 0.2413 0.0565 #> [4,] 0.2534 0.0372 #> [5,] 0.2562 0.0211 #> [6,] 0.2530 0.0045 #> [7,] 0.2392 -0.0150 #> [8,] 0.1969 -0.0380 #> [9,] 0.1006 -0.0591 #> [10,] 0.0087 -0.0818 #> [11,] -0.0851 -0.0980 #> [12,] -0.4069 -0.0163 #> [13,] -0.3909 0.0199 #> [14,] -0.1716 0.0275 #> [15,] 0.0642 0.0463 #> [16,] -0.0269 0.0213 #> [17,] 0.0729 -0.0090 #> [18,] -0.1360 -0.0167 #> #> $PS36 #> [,1] [,2] #> [1,] -0.4781 0.0434 #> [2,] 0.0151 0.0861 #> [3,] 0.2315 0.0588 #> [4,] 0.2497 0.0340 #> [5,] 0.2522 0.0097 #> [6,] 0.2468 -0.0098 #> [7,] 0.2262 -0.0268 #> [8,] 0.1710 -0.0504 #> [9,] 0.1161 -0.0662 #> [10,] 0.0229 -0.0872 #> [11,] -0.0725 -0.0919 #> [12,] -0.4162 -0.0013 #> [13,] -0.3934 0.0423 #> [14,] -0.1805 0.0383 #> [15,] 0.0727 0.0398 #> [16,] -0.0165 0.0185 #> [17,] 0.0770 -0.0152 #> [18,] -0.1238 -0.0220 #> #> $PS37 #> [,1] [,2] #> [1,] -0.4831 0.0333 #> [2,] 0.0053 0.0903 #> [3,] 0.2195 0.0586 #> [4,] 0.2431 0.0411 #> [5,] 0.2528 0.0130 #> [6,] 0.2449 -0.0048 #> [7,] 0.2233 -0.0224 #> [8,] 0.1825 -0.0408 #> [9,] 0.1059 -0.0670 #> [10,] 0.0350 -0.0854 #> [11,] -0.0632 -0.1019 #> [12,] -0.4102 -0.0103 #> [13,] -0.4019 0.0322 #> [14,] -0.1665 0.0331 #> [15,] 0.0750 0.0390 #> [16,] -0.0117 0.0188 #> [17,] 0.0926 -0.0086 #> [18,] -0.1432 -0.0182 #> #> $PS38 #> [,1] [,2] #> [1,] -0.4868 0.0376 #> [2,] 0.0145 0.0744 #> [3,] 0.2315 0.0576 #> [4,] 0.2463 0.0390 #> [5,] 0.2527 0.0143 #> [6,] 0.2466 0.0000 #> [7,] 0.2285 -0.0178 #> [8,] 0.1868 -0.0382 #> [9,] 0.1200 -0.0602 #> [10,] 0.0140 -0.0828 #> [11,] -0.0960 -0.0979 #> [12,] -0.4053 -0.0083 #> [13,] -0.3932 0.0282 #> [14,] -0.1530 0.0252 #> [15,] 0.0769 0.0365 #> [16,] -0.0236 0.0192 #> [17,] 0.0819 -0.0094 #> [18,] -0.1417 -0.0175 #> #> $PS39 #> [,1] [,2] #> [1,] -0.4681 0.0267 #> [2,] 0.0193 0.0801 #> [3,] 0.2274 0.0661 #> [4,] 0.2402 0.0517 #> [5,] 0.2490 0.0300 #> [6,] 0.2487 0.0093 #> [7,] 0.2388 -0.0078 #> [8,] 0.1901 -0.0408 #> [9,] 0.1154 -0.0649 #> [10,] 0.0358 -0.0930 #> [11,] -0.0922 -0.1143 #> [12,] -0.4119 -0.0207 #> [13,] -0.3901 0.0205 #> [14,] -0.1749 0.0280 #> [15,] 0.0685 0.0439 #> [16,] -0.0261 0.0209 #> [17,] 0.0726 -0.0088 #> [18,] -0.1425 -0.0269 #> #> $PS40 #> [,1] [,2] #> [1,] -0.4708 0.0327 #> [2,] 0.0546 0.0803 #> [3,] 0.2318 0.0604 #> [4,] 0.2454 0.0473 #> [5,] 0.2528 0.0247 #> [6,] 0.2488 0.0056 #> [7,] 0.2253 -0.0160 #> [8,] 0.1810 -0.0400 #> [9,] 0.1072 -0.0659 #> [10,] 0.0325 -0.0918 #> [11,] -0.0733 -0.1075 #> [12,] -0.4125 -0.0175 #> [13,] -0.3964 0.0257 #> [14,] -0.1769 0.0264 #> [15,] 0.0782 0.0456 #> [16,] -0.0320 0.0199 #> [17,] 0.0493 -0.0081 #> [18,] -0.1450 -0.0218 #> #> $PS41 #> [,1] [,2] #> [1,] -0.4681 0.0007 #> [2,] -0.0003 0.0884 #> [3,] 0.2120 0.0925 #> [4,] 0.2365 0.0755 #> [5,] 0.2530 0.0482 #> [6,] 0.2547 0.0290 #> [7,] 0.2428 0.0031 #> [8,] 0.2044 -0.0260 #> [9,] 0.1192 -0.0625 #> [10,] 0.0515 -0.0936 #> [11,] -0.0682 -0.1217 #> [12,] -0.3970 -0.0443 #> [13,] -0.3857 0.0009 #> [14,] -0.1914 0.0123 #> [15,] 0.0543 0.0404 #> [16,] -0.0266 0.0088 #> [17,] 0.0521 -0.0126 #> [18,] -0.1431 -0.0391 #> #> $PS42 #> [,1] [,2] #> [1,] -0.4716 0.0113 #> [2,] -0.0361 0.0801 #> [3,] 0.2011 0.0886 #> [4,] 0.2403 0.0590 #> [5,] 0.2478 0.0350 #> [6,] 0.2418 0.0160 #> [7,] 0.2306 -0.0017 #> [8,] 0.1874 -0.0304 #> [9,] 0.1155 -0.0642 #> [10,] 0.0496 -0.0922 #> [11,] -0.0430 -0.1309 #> [12,] -0.4147 -0.0391 #> [13,] -0.3963 0.0063 #> [14,] -0.1871 0.0211 #> [15,] 0.0941 0.0519 #> [16,] -0.0092 0.0184 #> [17,] 0.0798 0.0003 #> [18,] -0.1300 -0.0296 #> #> $PS43 #> [,1] [,2] #> [1,] -0.4650 0.0189 #> [2,] 0.0777 0.0958 #> [3,] 0.2329 0.0615 #> [4,] 0.2406 0.0500 #> [5,] 0.2516 0.0248 #> [6,] 0.2474 0.0028 #> [7,] 0.2232 -0.0239 #> [8,] 0.1751 -0.0467 #> [9,] 0.0905 -0.0670 #> [10,] 0.0085 -0.0866 #> [11,] -0.0910 -0.1106 #> [12,] -0.4048 -0.0239 #> [13,] -0.3877 0.0175 #> [14,] -0.2037 0.0338 #> [15,] 0.0961 0.0522 #> [16,] -0.0197 0.0285 #> [17,] 0.0797 -0.0070 #> [18,] -0.1514 -0.0198 #> #> $AE44 #> [,1] [,2] #> [1,] -0.4725 0.0516 #> [2,] -0.0143 0.0813 #> [3,] 0.2422 0.0488 #> [4,] 0.2507 0.0382 #> [5,] 0.2559 0.0186 #> [6,] 0.2537 -0.0002 #> [7,] 0.2367 -0.0236 #> [8,] 0.1749 -0.0518 #> [9,] 0.1033 -0.0718 #> [10,] 0.0238 -0.0987 #> [11,] -0.0727 -0.1095 #> [12,] -0.4000 0.0036 #> [13,] -0.3912 0.0449 #> [14,] -0.1666 0.0384 #> [15,] 0.0829 0.0420 #> [16,] -0.0183 0.0225 #> [17,] 0.0560 -0.0095 #> [18,] -0.1445 -0.0249 #> #> $AE45 #> [,1] [,2] #> [1,] -0.4700 0.0329 #> [2,] 0.0211 0.0740 #> [3,] 0.2225 0.0573 #> [4,] 0.2380 0.0445 #> [5,] 0.2463 0.0264 #> [6,] 0.2464 0.0056 #> [7,] 0.2289 -0.0202 #> [8,] 0.1914 -0.0426 #> [9,] 0.1183 -0.0646 #> [10,] 0.0281 -0.0876 #> [11,] -0.0840 -0.0974 #> [12,] -0.4163 -0.0049 #> [13,] -0.4033 0.0281 #> [14,] -0.1798 0.0299 #> [15,] 0.0811 0.0398 #> [16,] -0.0269 0.0163 #> [17,] 0.0871 -0.0149 #> [18,] -0.1289 -0.0229 #> #> $AE46 #> [,1] [,2] #> [1,] -0.4763 0.0541 #> [2,] 0.0198 0.0823 #> [3,] 0.2385 0.0565 #> [4,] 0.2495 0.0309 #> [5,] 0.2487 0.0119 #> [6,] 0.2414 -0.0050 #> [7,] 0.2247 -0.0242 #> [8,] 0.1859 -0.0439 #> [9,] 0.1116 -0.0648 #> [10,] 0.0350 -0.0872 #> [11,] -0.0774 -0.1079 #> [12,] -0.4132 -0.0092 #> [13,] -0.3855 0.0404 #> [14,] -0.1809 0.0317 #> [15,] 0.0706 0.0405 #> [16,] -0.0278 0.0176 #> [17,] 0.0771 -0.0100 #> [18,] -0.1416 -0.0136 #> #> $AE47 #> [,1] [,2] #> [1,] -0.4650 0.0251 #> [2,] 0.0340 0.0867 #> [3,] 0.2201 0.0688 #> [4,] 0.2449 0.0413 #> [5,] 0.2502 0.0272 #> [6,] 0.2497 0.0056 #> [7,] 0.2334 -0.0178 #> [8,] 0.2017 -0.0396 #> [9,] 0.1236 -0.0666 #> [10,] 0.0180 -0.0880 #> [11,] -0.1076 -0.1018 #> [12,] -0.4067 -0.0178 #> [13,] -0.3950 0.0173 #> [14,] -0.1924 0.0277 #> [15,] 0.0536 0.0477 #> [16,] -0.0110 0.0214 #> [17,] 0.0727 -0.0081 #> [18,] -0.1240 -0.0291 #> #> $AE48 #> [,1] [,2] #> [1,] -0.4816 -0.0101 #> [2,] -0.0088 0.0787 #> [3,] 0.2519 0.0669 #> [4,] 0.2576 0.0565 #> [5,] 0.2584 0.0363 #> [6,] 0.2483 0.0188 #> [7,] 0.2217 -0.0046 #> [8,] 0.1745 -0.0324 #> [9,] 0.1081 -0.0580 #> [10,] 0.0173 -0.0796 #> [11,] -0.1134 -0.0967 #> [12,] -0.3990 -0.0323 #> [13,] -0.3859 -0.0026 #> [14,] -0.1730 0.0227 #> [15,] 0.0797 0.0444 #> [16,] -0.0026 0.0194 #> [17,] 0.0714 -0.0012 #> [18,] -0.1245 -0.0260 #> #> $AE49 #> [,1] [,2] #> [1,] -0.4629 0.0336 #> [2,] 0.0171 0.0795 #> [3,] 0.2194 0.0704 #> [4,] 0.2486 0.0437 #> [5,] 0.2537 0.0236 #> [6,] 0.2519 0.0026 #> [7,] 0.2329 -0.0160 #> [8,] 0.2020 -0.0353 #> [9,] 0.1282 -0.0616 #> [10,] 0.0354 -0.0929 #> [11,] -0.0687 -0.1047 #> [12,] -0.4003 -0.0198 #> [13,] -0.3796 0.0241 #> [14,] -0.2303 0.0291 #> [15,] 0.0574 0.0373 #> [16,] -0.0315 0.0182 #> [17,] 0.0682 -0.0090 #> [18,] -0.1416 -0.0229 #> #> $AE50 #> [,1] [,2] #> [1,] -0.4796 0.0445 #> [2,] 0.0328 0.0897 #> [3,] 0.2322 0.0526 #> [4,] 0.2452 0.0328 #> [5,] 0.2481 0.0158 #> [6,] 0.2460 -0.0086 #> [7,] 0.2302 -0.0294 #> [8,] 0.1887 -0.0480 #> [9,] 0.0998 -0.0674 #> [10,] 0.0049 -0.0882 #> [11,] -0.0920 -0.0998 #> [12,] -0.4136 -0.0102 #> [13,] -0.3879 0.0401 #> [14,] -0.1660 0.0347 #> [15,] 0.0839 0.0398 #> [16,] -0.0172 0.0234 #> [17,] 0.0791 -0.0039 #> [18,] -0.1344 -0.0181 #> #> $AE51 #> [,1] [,2] #> [1,] -0.4677 0.0660 #> [2,] -0.0018 0.1009 #> [3,] 0.2411 0.0573 #> [4,] 0.2545 0.0301 #> [5,] 0.2548 0.0037 #> [6,] 0.2473 -0.0135 #> [7,] 0.2332 -0.0313 #> [8,] 0.1707 -0.0620 #> [9,] 0.1136 -0.0767 #> [10,] 0.0222 -0.1042 #> [11,] -0.0559 -0.1135 #> [12,] -0.3919 0.0170 #> [13,] -0.3774 0.0620 #> [14,] -0.2083 0.0434 #> [15,] 0.0839 0.0383 #> [16,] -0.0297 0.0210 #> [17,] 0.0527 -0.0203 #> [18,] -0.1415 -0.0183 #> #> $AE52 #> [,1] [,2] #> [1,] -0.4727 0.0471 #> [2,] 0.0132 0.0814 #> [3,] 0.2200 0.0560 #> [4,] 0.2417 0.0392 #> [5,] 0.2517 0.0124 #> [6,] 0.2487 -0.0071 #> [7,] 0.2247 -0.0342 #> [8,] 0.1889 -0.0556 #> [9,] 0.1234 -0.0757 #> [10,] 0.0366 -0.0924 #> [11,] -0.0722 -0.1071 #> [12,] -0.4056 0.0170 #> [13,] -0.3994 0.0442 #> [14,] -0.1945 0.0406 #> [15,] 0.0769 0.0411 #> [16,] -0.0155 0.0201 #> [17,] 0.0568 -0.0137 #> [18,] -0.1228 -0.0132 #> #> $AE53 #> [,1] [,2] #> [1,] -0.4807 0.0159 #> [2,] -0.0202 0.0827 #> [3,] 0.2179 0.0740 #> [4,] 0.2367 0.0518 #> [5,] 0.2462 0.0284 #> [6,] 0.2410 0.0037 #> [7,] 0.2272 -0.0130 #> [8,] 0.1851 -0.0385 #> [9,] 0.1207 -0.0622 #> [10,] 0.0321 -0.0902 #> [11,] -0.0706 -0.1060 #> [12,] -0.4145 -0.0256 #> [13,] -0.3957 0.0149 #> [14,] -0.1793 0.0264 #> [15,] 0.0928 0.0493 #> [16,] -0.0085 0.0226 #> [17,] 0.0943 -0.0077 #> [18,] -0.1245 -0.0265 #> #> $AE54 #> [,1] [,2] #> [1,] -0.4692 0.0562 #> [2,] 0.0113 0.0832 #> [3,] 0.2364 0.0432 #> [4,] 0.2471 0.0269 #> [5,] 0.2512 0.0092 #> [6,] 0.2441 -0.0114 #> [7,] 0.2197 -0.0333 #> [8,] 0.1746 -0.0524 #> [9,] 0.1010 -0.0710 #> [10,] 0.0188 -0.0892 #> [11,] -0.0895 -0.1013 #> [12,] -0.4180 0.0126 #> [13,] -0.3956 0.0506 #> [14,] -0.1724 0.0422 #> [15,] 0.1044 0.0406 #> [16,] -0.0057 0.0242 #> [17,] 0.0756 -0.0119 #> [18,] -0.1337 -0.0188 #> #> $AE55 #> [,1] [,2] #> [1,] -0.4647 0.0148 #> [2,] 0.0328 0.0689 #> [3,] 0.2379 0.0568 #> [4,] 0.2523 0.0430 #> [5,] 0.2595 0.0223 #> [6,] 0.2578 0.0052 #> [7,] 0.2412 -0.0121 #> [8,] 0.2027 -0.0352 #> [9,] 0.1038 -0.0530 #> [10,] 0.0136 -0.0693 #> [11,] -0.1152 -0.0897 #> [12,] -0.3986 -0.0184 #> [13,] -0.3831 0.0119 #> [14,] -0.1813 0.0216 #> [15,] 0.0656 0.0390 #> [16,] -0.0403 0.0181 #> [17,] 0.0736 -0.0065 #> [18,] -0.1577 -0.0176 #> #> $AE56 #> [,1] [,2] #> [1,] -0.4643 0.0376 #> [2,] -0.0249 0.0706 #> [3,] 0.2336 0.0638 #> [4,] 0.2522 0.0424 #> [5,] 0.2586 0.0186 #> [6,] 0.2564 -0.0016 #> [7,] 0.2379 -0.0220 #> [8,] 0.1841 -0.0415 #> [9,] 0.1089 -0.0615 #> [10,] 0.0300 -0.0845 #> [11,] -0.0898 -0.0983 #> [12,] -0.4106 -0.0060 #> [13,] -0.3895 0.0278 #> [14,] -0.1702 0.0248 #> [15,] 0.0759 0.0394 #> [16,] -0.0150 0.0170 #> [17,] 0.0744 -0.0099 #> [18,] -0.1477 -0.0166 #> #> $AE57 #> [,1] [,2] #> [1,] -0.4828 0.0392 #> [2,] -0.0177 0.0874 #> [3,] 0.2484 0.0501 #> [4,] 0.2576 0.0349 #> [5,] 0.2591 0.0166 #> [6,] 0.2516 -0.0050 #> [7,] 0.2218 -0.0278 #> [8,] 0.1684 -0.0531 #> [9,] 0.1035 -0.0670 #> [10,] 0.0279 -0.0888 #> [11,] -0.0751 -0.1052 #> [12,] -0.3931 -0.0032 #> [13,] -0.3969 0.0420 #> [14,] -0.1688 0.0401 #> [15,] 0.0818 0.0463 #> [16,] -0.0094 0.0226 #> [17,] 0.0521 -0.0059 #> [18,] -0.1285 -0.0232 #> #> $AE58 #> [,1] [,2] #> [1,] -0.4712 0.0489 #> [2,] 0.0625 0.0804 #> [3,] 0.2222 0.0592 #> [4,] 0.2441 0.0367 #> [5,] 0.2491 0.0157 #> [6,] 0.2467 -0.0018 #> [7,] 0.2327 -0.0224 #> [8,] 0.1965 -0.0425 #> [9,] 0.1163 -0.0686 #> [10,] 0.0347 -0.0930 #> [11,] -0.0869 -0.1097 #> [12,] -0.4093 0.0021 #> [13,] -0.3883 0.0349 #> [14,] -0.1725 0.0325 #> [15,] 0.0504 0.0387 #> [16,] -0.0392 0.0198 #> [17,] 0.0675 -0.0162 #> [18,] -0.1555 -0.0148 #> #> $AE59 #> [,1] [,2] #> [1,] -0.4829 -0.0110 #> [2,] -0.0098 0.0702 #> [3,] 0.2305 0.0864 #> [4,] 0.2584 0.0618 #> [5,] 0.2570 0.0425 #> [6,] 0.2426 0.0193 #> [7,] 0.2192 0.0022 #> [8,] 0.1676 -0.0241 #> [9,] 0.1095 -0.0453 #> [10,] 0.0244 -0.0772 #> [11,] -0.0597 -0.0994 #> [12,] -0.4056 -0.0417 #> [13,] -0.4000 -0.0105 #> [14,] -0.1811 0.0104 #> [15,] 0.0829 0.0435 #> [16,] -0.0125 0.0117 #> [17,] 0.0856 -0.0066 #> [18,] -0.1262 -0.0320 #> #> $AE60 #> [,1] [,2] #> [1,] -0.4763 0.0391 #> [2,] 0.0399 0.0951 #> [3,] 0.2294 0.0748 #> [4,] 0.2498 0.0509 #> [5,] 0.2521 0.0178 #> [6,] 0.2452 -0.0041 #> [7,] 0.2200 -0.0252 #> [8,] 0.1877 -0.0446 #> [9,] 0.1021 -0.0731 #> [10,] 0.0172 -0.1043 #> [11,] -0.1109 -0.1183 #> [12,] -0.3956 -0.0066 #> [13,] -0.3835 0.0327 #> [14,] -0.1856 0.0394 #> [15,] 0.0696 0.0482 #> [16,] -0.0140 0.0210 #> [17,] 0.0847 -0.0112 #> [18,] -0.1318 -0.0316 #> #> $AE61 #> [,1] [,2] #> [1,] -0.4617 0.0257 #> [2,] -0.0363 0.0805 #> [3,] 0.2449 0.0659 #> [4,] 0.2606 0.0389 #> [5,] 0.2588 0.0255 #> [6,] 0.2505 0.0054 #> [7,] 0.2316 -0.0157 #> [8,] 0.1783 -0.0465 #> [9,] 0.1121 -0.0690 #> [10,] 0.0320 -0.0931 #> [11,] -0.0929 -0.1131 #> [12,] -0.4029 -0.0125 #> [13,] -0.3868 0.0196 #> [14,] -0.1833 0.0295 #> [15,] 0.0735 0.0539 #> [16,] -0.0217 0.0250 #> [17,] 0.0709 -0.0047 #> [18,] -0.1278 -0.0153 #> #> $AE62 #> [,1] [,2] #> [1,] -0.4899 -0.0062 #> [2,] 0.0120 0.0676 #> [3,] 0.2322 0.0679 #> [4,] 0.2437 0.0543 #> [5,] 0.2506 0.0304 #> [6,] 0.2433 0.0098 #> [7,] 0.2302 -0.0042 #> [8,] 0.1901 -0.0281 #> [9,] 0.1227 -0.0547 #> [10,] 0.0281 -0.0743 #> [11,] -0.0746 -0.0870 #> [12,] -0.4098 -0.0256 #> [13,] -0.3979 -0.0004 #> [14,] -0.1563 0.0184 #> [15,] 0.0717 0.0423 #> [16,] -0.0308 0.0153 #> [17,] 0.0716 -0.0061 #> [18,] -0.1369 -0.0194 #> #> $AE63 #> [,1] [,2] #> [1,] -0.4755 0.0458 #> [2,] 0.0115 0.0887 #> [3,] 0.2387 0.0626 #> [4,] 0.2580 0.0351 #> [5,] 0.2607 0.0113 #> [6,] 0.2531 -0.0061 #> [7,] 0.2338 -0.0283 #> [8,] 0.1817 -0.0528 #> [9,] 0.0846 -0.0718 #> [10,] 0.0053 -0.0886 #> [11,] -0.0847 -0.0995 #> [12,] -0.3990 -0.0003 #> [13,] -0.3796 0.0437 #> [14,] -0.1870 0.0389 #> [15,] 0.0760 0.0427 #> [16,] -0.0087 0.0158 #> [17,] 0.0698 -0.0190 #> [18,] -0.1387 -0.0180 #> #> $AE64 #> [,1] [,2] #> [1,] -0.4869 0.0242 #> [2,] -0.0225 0.0761 #> [3,] 0.2350 0.0677 #> [4,] 0.2443 0.0560 #> [5,] 0.2491 0.0389 #> [6,] 0.2493 0.0173 #> [7,] 0.2331 -0.0081 #> [8,] 0.1806 -0.0367 #> [9,] 0.1241 -0.0617 #> [10,] 0.0381 -0.0926 #> [11,] -0.0605 -0.1162 #> [12,] -0.3956 -0.0361 #> [13,] -0.3832 0.0226 #> [14,] -0.1822 0.0248 #> [15,] 0.0825 0.0473 #> [16,] -0.0211 0.0178 #> [17,] 0.0552 -0.0041 #> [18,] -0.1393 -0.0370 #> #> $AE65 #> [,1] [,2] #> [1,] -0.4734 0.0418 #> [2,] 0.0120 0.0760 #> [3,] 0.2281 0.0557 #> [4,] 0.2417 0.0392 #> [5,] 0.2475 0.0208 #> [6,] 0.2471 0.0067 #> [7,] 0.2335 -0.0141 #> [8,] 0.1969 -0.0382 #> [9,] 0.1173 -0.0641 #> [10,] 0.0343 -0.0854 #> [11,] -0.1142 -0.0941 #> [12,] -0.4119 -0.0102 #> [13,] -0.3943 0.0260 #> [14,] -0.1705 0.0265 #> [15,] 0.0578 0.0328 #> [16,] -0.0101 0.0157 #> [17,] 0.0916 -0.0131 #> [18,] -0.1334 -0.0221 #> #> $AE66 #> [,1] [,2] #> [1,] -0.4733 0.0634 #> [2,] 0.0375 0.0889 #> [3,] 0.2215 0.0532 #> [4,] 0.2409 0.0342 #> [5,] 0.2528 0.0053 #> [6,] 0.2475 -0.0172 #> [7,] 0.2245 -0.0341 #> [8,] 0.1735 -0.0584 #> [9,] 0.0939 -0.0720 #> [10,] 0.0066 -0.0898 #> [11,] -0.1113 -0.1010 #> [12,] -0.4122 0.0161 #> [13,] -0.3891 0.0520 #> [14,] -0.1736 0.0397 #> [15,] 0.1103 0.0418 #> [16,] -0.0110 0.0195 #> [17,] 0.0908 -0.0196 #> [18,] -0.1295 -0.0220 #> #> $AE67 #> [,1] [,2] #> [1,] -0.4745 -0.0048 #> [2,] -0.0180 0.0739 #> [3,] 0.2023 0.0863 #> [4,] 0.2362 0.0689 #> [5,] 0.2474 0.0435 #> [6,] 0.2454 0.0244 #> [7,] 0.2370 0.0076 #> [8,] 0.1946 -0.0248 #> [9,] 0.1253 -0.0550 #> [10,] 0.0461 -0.0881 #> [11,] -0.0717 -0.1084 #> [12,] -0.4133 -0.0474 #> [13,] -0.4007 -0.0074 #> [14,] -0.1827 0.0092 #> [15,] 0.0698 0.0415 #> [16,] -0.0069 0.0150 #> [17,] 0.0830 -0.0029 #> [18,] -0.1193 -0.0316 #> #> $AE68 #> [,1] [,2] #> [1,] -0.4682 0.0363 #> [2,] 0.0162 0.0848 #> [3,] 0.2220 0.0626 #> [4,] 0.2528 0.0392 #> [5,] 0.2574 0.0164 #> [6,] 0.2491 -0.0044 #> [7,] 0.2243 -0.0272 #> [8,] 0.1727 -0.0476 #> [9,] 0.1078 -0.0619 #> [10,] 0.0231 -0.0810 #> [11,] -0.0979 -0.0994 #> [12,] -0.4090 -0.0105 #> [13,] -0.3968 0.0310 #> [14,] -0.1951 0.0358 #> [15,] 0.0985 0.0423 #> [16,] -0.0013 0.0195 #> [17,] 0.0729 -0.0110 #> [18,] -0.1284 -0.0248 #> #> $AE69 #> [,1] [,2] #> [1,] -0.4863 0.0295 #> [2,] 0.0127 0.0793 #> [3,] 0.2191 0.0650 #> [4,] 0.2358 0.0459 #> [5,] 0.2457 0.0240 #> [6,] 0.2417 0.0087 #> [7,] 0.2301 -0.0121 #> [8,] 0.1995 -0.0360 #> [9,] 0.1184 -0.0630 #> [10,] 0.0296 -0.0845 #> [11,] -0.0793 -0.1054 #> [12,] -0.4148 -0.0143 #> [13,] -0.3983 0.0188 #> [14,] -0.1556 0.0227 #> [15,] 0.0775 0.0426 #> [16,] -0.0229 0.0174 #> [17,] 0.0789 -0.0132 #> [18,] -0.1320 -0.0255 #> #> $AE70 #> [,1] [,2] #> [1,] -0.4737 0.0113 #> [2,] 0.0050 0.0868 #> [3,] 0.2235 0.0796 #> [4,] 0.2462 0.0555 #> [5,] 0.2500 0.0330 #> [6,] 0.2454 0.0145 #> [7,] 0.2256 -0.0071 #> [8,] 0.1972 -0.0254 #> [9,] 0.1149 -0.0624 #> [10,] 0.0369 -0.0947 #> [11,] -0.0880 -0.1198 #> [12,] -0.4060 -0.0291 #> [13,] -0.3921 0.0033 #> [14,] -0.1731 0.0192 #> [15,] 0.0698 0.0518 #> [16,] -0.0206 0.0244 #> [17,] 0.0761 -0.0092 #> [18,] -0.1368 -0.0317 #> #> $AE71 #> [,1] [,2] #> [1,] -0.4874 -0.0215 #> [2,] -0.0026 0.0984 #> [3,] 0.2117 0.0955 #> [4,] 0.2368 0.0724 #> [5,] 0.2441 0.0511 #> [6,] 0.2405 0.0297 #> [7,] 0.2309 0.0125 #> [8,] 0.1885 -0.0225 #> [9,] 0.1217 -0.0534 #> [10,] 0.0463 -0.0908 #> [11,] -0.0510 -0.1233 #> [12,] -0.3904 -0.0572 #> [13,] -0.3866 -0.0109 #> [14,] -0.2039 0.0073 #> [15,] 0.0774 0.0526 #> [16,] -0.0172 0.0150 #> [17,] 0.0720 -0.0079 #> [18,] -0.1308 -0.0471 #> #> $AE72 #> [,1] [,2] #> [1,] -0.4795 0.0247 #> [2,] 0.0091 0.0831 #> [3,] 0.2254 0.0679 #> [4,] 0.2418 0.0477 #> [5,] 0.2478 0.0260 #> [6,] 0.2434 0.0069 #> [7,] 0.2229 -0.0137 #> [8,] 0.1698 -0.0435 #> [9,] 0.1011 -0.0675 #> [10,] 0.0302 -0.0889 #> [11,] -0.0886 -0.1022 #> [12,] -0.4144 -0.0192 #> [13,] -0.3939 0.0218 #> [14,] -0.1871 0.0307 #> [15,] 0.1069 0.0493 #> [16,] -0.0070 0.0188 #> [17,] 0.0938 -0.0142 #> [18,] -0.1216 -0.0280 #> #> $AE73 #> [,1] [,2] #> [1,] -0.4812 0.0565 #> [2,] -0.0083 0.0817 #> [3,] 0.2518 0.0414 #> [4,] 0.2618 0.0231 #> [5,] 0.2579 0.0073 #> [6,] 0.2441 -0.0147 #> [7,] 0.2224 -0.0303 #> [8,] 0.1684 -0.0514 #> [9,] 0.0983 -0.0710 #> [10,] 0.0396 -0.0905 #> [11,] -0.0744 -0.1091 #> [12,] -0.3931 0.0040 #> [13,] -0.3867 0.0503 #> [14,] -0.1847 0.0468 #> [15,] 0.0925 0.0426 #> [16,] -0.0247 0.0228 #> [17,] 0.0492 -0.0054 #> [18,] -0.1331 -0.0041 #> #> $AE74 #> [,1] [,2] #> [1,] -0.4993 0.0324 #> [2,] 0.0385 0.0888 #> [3,] 0.2101 0.0738 #> [4,] 0.2442 0.0458 #> [5,] 0.2478 0.0201 #> [6,] 0.2385 -0.0078 #> [7,] 0.2092 -0.0311 #> [8,] 0.1675 -0.0509 #> [9,] 0.1004 -0.0700 #> [10,] 0.0204 -0.0891 #> [11,] -0.0874 -0.1027 #> [12,] -0.4197 -0.0120 #> [13,] -0.3998 0.0311 #> [14,] -0.1515 0.0383 #> [15,] 0.0957 0.0439 #> [16,] 0.0090 0.0234 #> [17,] 0.0858 -0.0101 #> [18,] -0.1094 -0.0239 #> #> $AE75 #> [,1] [,2] #> [1,] -0.4930 0.0009 #> [2,] 0.0098 0.0850 #> [3,] 0.2238 0.0734 #> [4,] 0.2375 0.0589 #> [5,] 0.2455 0.0384 #> [6,] 0.2455 0.0211 #> [7,] 0.2315 -0.0059 #> [8,] 0.1734 -0.0333 #> [9,] 0.1027 -0.0571 #> [10,] 0.0428 -0.0851 #> [11,] -0.0623 -0.1083 #> [12,] -0.4081 -0.0362 #> [13,] -0.3975 0.0072 #> [14,] -0.1826 0.0205 #> [15,] 0.0913 0.0498 #> [16,] -0.0073 0.0133 #> [17,] 0.0610 -0.0098 #> [18,] -0.1140 -0.0327 #> #> $AE76 #> [,1] [,2] #> [1,] -0.4792 0.0348 #> [2,] 0.0304 0.0869 #> [3,] 0.2140 0.0581 #> [4,] 0.2300 0.0414 #> [5,] 0.2386 0.0231 #> [6,] 0.2373 0.0049 #> [7,] 0.2247 -0.0140 #> [8,] 0.1851 -0.0421 #> [9,] 0.1217 -0.0651 #> [10,] 0.0216 -0.0856 #> [11,] -0.0886 -0.1011 #> [12,] -0.4228 -0.0215 #> [13,] -0.3953 0.0281 #> [14,] -0.1876 0.0300 #> [15,] 0.1045 0.0452 #> [16,] -0.0007 0.0172 #> [17,] 0.0934 -0.0135 #> [18,] -0.1271 -0.0268 #> #> $AE77 #> [,1] [,2] #> [1,] -0.4881 0.0362 #> [2,] 0.0112 0.0821 #> [3,] 0.2292 0.0667 #> [4,] 0.2434 0.0459 #> [5,] 0.2498 0.0225 #> [6,] 0.2441 0.0014 #> [7,] 0.2256 -0.0232 #> [8,] 0.1860 -0.0492 #> [9,] 0.1195 -0.0705 #> [10,] 0.0140 -0.0947 #> [11,] -0.0906 -0.1020 #> [12,] -0.4026 -0.0068 #> [13,] -0.3875 0.0336 #> [14,] -0.1753 0.0313 #> [15,] 0.0810 0.0459 #> [16,] -0.0129 0.0188 #> [17,] 0.0793 -0.0134 #> [18,] -0.1262 -0.0247 #> #> $AE78 #> [,1] [,2] #> [1,] -0.4808 0.0257 #> [2,] 0.0119 0.0828 #> [3,] 0.2359 0.0674 #> [4,] 0.2512 0.0466 #> [5,] 0.2487 0.0253 #> [6,] 0.2389 0.0053 #> [7,] 0.2190 -0.0150 #> [8,] 0.1791 -0.0401 #> [9,] 0.1275 -0.0625 #> [10,] 0.0294 -0.0893 #> [11,] -0.0727 -0.1060 #> [12,] -0.4010 -0.0194 #> [13,] -0.4092 0.0233 #> [14,] -0.1771 0.0352 #> [15,] 0.0698 0.0404 #> [16,] -0.0148 0.0155 #> [17,] 0.0663 -0.0123 #> [18,] -0.1222 -0.0228 #> #> $AE79 #> [,1] [,2] #> [1,] -0.4854 -0.0160 #> [2,] 0.0061 0.0899 #> [3,] 0.2144 0.0921 #> [4,] 0.2502 0.0634 #> [5,] 0.2546 0.0396 #> [6,] 0.2495 0.0239 #> [7,] 0.2275 0.0048 #> [8,] 0.1833 -0.0226 #> [9,] 0.1243 -0.0512 #> [10,] 0.0498 -0.0852 #> [11,] -0.0740 -0.1218 #> [12,] -0.3882 -0.0466 #> [13,] -0.3775 -0.0073 #> [14,] -0.2143 0.0109 #> [15,] 0.0727 0.0477 #> [16,] -0.0267 0.0160 #> [17,] 0.0627 -0.0037 #> [18,] -0.1292 -0.0337 #> #> $AE80 #> [,1] [,2] #> [1,] -0.4770 0.0323 #> [2,] 0.0028 0.0796 #> [3,] 0.2192 0.0600 #> [4,] 0.2403 0.0375 #> [5,] 0.2502 0.0177 #> [6,] 0.2468 0.0028 #> [7,] 0.2361 -0.0172 #> [8,] 0.1945 -0.0413 #> [9,] 0.1137 -0.0629 #> [10,] 0.0326 -0.0831 #> [11,] -0.0776 -0.1016 #> [12,] -0.4146 -0.0084 #> [13,] -0.3839 0.0274 #> [14,] -0.2006 0.0291 #> [15,] 0.0822 0.0417 #> [16,] -0.0149 0.0200 #> [17,] 0.0785 -0.0103 #> [18,] -0.1282 -0.0233 #> #> $AE81 #> [,1] [,2] #> [1,] -0.4625 0.0125 #> [2,] 0.0122 0.0972 #> [3,] 0.2143 0.0808 #> [4,] 0.2348 0.0651 #> [5,] 0.2503 0.0410 #> [6,] 0.2534 0.0207 #> [7,] 0.2349 -0.0058 #> [8,] 0.1980 -0.0317 #> [9,] 0.1238 -0.0673 #> [10,] 0.0546 -0.1022 #> [11,] -0.0467 -0.1261 #> [12,] -0.4013 -0.0416 #> [13,] -0.3820 0.0075 #> [14,] -0.2137 0.0199 #> [15,] 0.0583 0.0513 #> [16,] -0.0247 0.0182 #> [17,] 0.0494 -0.0079 #> [18,] -0.1531 -0.0316 #> #> $AE82 #> [,1] [,2] #> [1,] -0.4883 -0.0152 #> [2,] -0.0164 0.0892 #> [3,] 0.2108 0.0868 #> [4,] 0.2351 0.0724 #> [5,] 0.2480 0.0471 #> [6,] 0.2410 0.0243 #> [7,] 0.2141 -0.0064 #> [8,] 0.1917 -0.0298 #> [9,] 0.1307 -0.0653 #> [10,] 0.0442 -0.0980 #> [11,] -0.0780 -0.1146 #> [12,] -0.3971 -0.0369 #> [13,] -0.3903 -0.0044 #> [14,] -0.1827 0.0154 #> [15,] 0.0974 0.0553 #> [16,] -0.0215 0.0170 #> [17,] 0.0864 -0.0036 #> [18,] -0.1253 -0.0333 #> #> $AE83 #> [,1] [,2] #> [1,] -0.4668 0.0570 #> [2,] 0.0029 0.0886 #> [3,] 0.2390 0.0506 #> [4,] 0.2567 0.0261 #> [5,] 0.2587 0.0026 #> [6,] 0.2436 -0.0248 #> [7,] 0.2192 -0.0429 #> [8,] 0.1795 -0.0629 #> [9,] 0.1235 -0.0753 #> [10,] 0.0217 -0.0877 #> [11,] -0.0879 -0.0963 #> [12,] -0.4110 0.0186 #> [13,] -0.3814 0.0537 #> [14,] -0.1887 0.0495 #> [15,] 0.0936 0.0451 #> [16,] -0.0185 0.0264 #> [17,] 0.0418 -0.0133 #> [18,] -0.1261 -0.0149 #> #> $AE84 #> [,1] [,2] #> [1,] -0.4812 0.0442 #> [2,] 0.0448 0.0968 #> [3,] 0.2255 0.0617 #> [4,] 0.2478 0.0425 #> [5,] 0.2591 0.0180 #> [6,] 0.2498 -0.0017 #> [7,] 0.2289 -0.0281 #> [8,] 0.1867 -0.0532 #> [9,] 0.1105 -0.0763 #> [10,] 0.0286 -0.0992 #> [11,] -0.0938 -0.1047 #> [12,] -0.3920 0.0044 #> [13,] -0.3772 0.0462 #> [14,] -0.1932 0.0398 #> [15,] 0.0649 0.0383 #> [16,] -0.0299 0.0180 #> [17,] 0.0600 -0.0188 #> [18,] -0.1393 -0.0281 #> #> $AE85 #> [,1] [,2] #> [1,] -0.4611 0.0127 #> [2,] 0.0154 0.0912 #> [3,] 0.2370 0.0709 #> [4,] 0.2518 0.0454 #> [5,] 0.2528 0.0309 #> [6,] 0.2509 0.0117 #> [7,] 0.2381 -0.0070 #> [8,] 0.1968 -0.0369 #> [9,] 0.1009 -0.0629 #> [10,] 0.0191 -0.0904 #> [11,] -0.0797 -0.1074 #> [12,] -0.4117 -0.0313 #> [13,] -0.3981 0.0050 #> [14,] -0.1649 0.0262 #> [15,] 0.0475 0.0479 #> [16,] -0.0288 0.0249 #> [17,] 0.0693 -0.0046 #> [18,] -0.1354 -0.0264 #> #> $AE86 #> [,1] [,2] #> [1,] -0.4746 -0.0102 #> [2,] -0.0048 0.0982 #> [3,] 0.2290 0.0868 #> [4,] 0.2432 0.0694 #> [5,] 0.2495 0.0465 #> [6,] 0.2450 0.0269 #> [7,] 0.2298 0.0018 #> [8,] 0.1892 -0.0311 #> [9,] 0.1274 -0.0604 #> [10,] 0.0578 -0.0941 #> [11,] -0.0414 -0.1274 #> [12,] -0.3930 -0.0612 #> [13,] -0.3824 0.0085 #> [14,] -0.1932 0.0158 #> [15,] 0.0533 0.0491 #> [16,] -0.0299 0.0185 #> [17,] 0.0498 -0.0022 #> [18,] -0.1549 -0.0351 #> #> $AE87 #> [,1] [,2] #> [1,] -0.4700 0.0346 #> [2,] 0.0075 0.0853 #> [3,] 0.2372 0.0643 #> [4,] 0.2583 0.0437 #> [5,] 0.2639 0.0246 #> [6,] 0.2569 -0.0012 #> [7,] 0.2319 -0.0174 #> [8,] 0.1824 -0.0420 #> [9,] 0.1036 -0.0660 #> [10,] 0.0394 -0.0887 #> [11,] -0.0630 -0.1144 #> [12,] -0.3993 -0.0161 #> [13,] -0.3864 0.0292 #> [14,] -0.1710 0.0321 #> [15,] 0.0501 0.0412 #> [16,] -0.0248 0.0161 #> [17,] 0.0472 -0.0097 #> [18,] -0.1638 -0.0155 #> #> $AE88 #> [,1] [,2] #> [1,] -0.4789 0.0466 #> [2,] 0.0268 0.0831 #> [3,] 0.2438 0.0371 #> [4,] 0.2548 0.0207 #> [5,] 0.2559 0.0020 #> [6,] 0.2477 -0.0151 #> [7,] 0.2317 -0.0271 #> [8,] 0.1799 -0.0469 #> [9,] 0.1011 -0.0651 #> [10,] 0.0353 -0.0829 #> [11,] -0.0892 -0.0917 #> [12,] -0.4086 0.0069 #> [13,] -0.4010 0.0471 #> [14,] -0.1455 0.0405 #> [15,] 0.0471 0.0396 #> [16,] -0.0206 0.0232 #> [17,] 0.0565 -0.0062 #> [18,] -0.1368 -0.0116 #> #> $AE89 #> [,1] [,2] #> [1,] -0.4690 0.0593 #> [2,] 0.0698 0.0872 #> [3,] 0.2319 0.0416 #> [4,] 0.2512 0.0188 #> [5,] 0.2517 -0.0043 #> [6,] 0.2471 -0.0202 #> [7,] 0.2183 -0.0396 #> [8,] 0.1770 -0.0567 #> [9,] 0.1112 -0.0710 #> [10,] 0.0155 -0.0877 #> [11,] -0.1024 -0.0898 #> [12,] -0.4069 0.0179 #> [13,] -0.3957 0.0535 #> [14,] -0.1706 0.0430 #> [15,] 0.0837 0.0418 #> [16,] -0.0302 0.0247 #> [17,] 0.0648 -0.0124 #> [18,] -0.1475 -0.0060 #> #> $AE90 #> [,1] [,2] #> [1,] -0.4802 -0.0309 #> [2,] -0.0233 0.0907 #> [3,] 0.2213 0.0933 #> [4,] 0.2414 0.0753 #> [5,] 0.2467 0.0519 #> [6,] 0.2403 0.0348 #> [7,] 0.2267 0.0144 #> [8,] 0.1900 -0.0138 #> [9,] 0.1237 -0.0532 #> [10,] 0.0422 -0.0917 #> [11,] -0.0573 -0.1295 #> [12,] -0.4019 -0.0754 #> [13,] -0.3867 -0.0167 #> [14,] -0.1757 0.0123 #> [15,] 0.0683 0.0591 #> [16,] -0.0120 0.0220 #> [17,] 0.0642 0.0026 #> [18,] -0.1275 -0.0454 #> #> $AE91 #> [,1] [,2] #> [1,] -0.4779 0.0343 #> [2,] -0.0051 0.0874 #> [3,] 0.2188 0.0711 #> [4,] 0.2418 0.0494 #> [5,] 0.2468 0.0277 #> [6,] 0.2444 0.0099 #> [7,] 0.2258 -0.0153 #> [8,] 0.1875 -0.0437 #> [9,] 0.1220 -0.0740 #> [10,] 0.0300 -0.1010 #> [11,] -0.0978 -0.1141 #> [12,] -0.4076 -0.0196 #> [13,] -0.3892 0.0245 #> [14,] -0.1812 0.0342 #> [15,] 0.0914 0.0433 #> [16,] -0.0160 0.0187 #> [17,] 0.0841 -0.0124 #> [18,] -0.1180 -0.0206 #> #> $AE92 #> [,1] [,2] #> [1,] -0.4656 0.0404 #> [2,] 0.0042 0.0833 #> [3,] 0.2235 0.0551 #> [4,] 0.2493 0.0348 #> [5,] 0.2565 0.0143 #> [6,] 0.2524 -0.0079 #> [7,] 0.2341 -0.0255 #> [8,] 0.1980 -0.0432 #> [9,] 0.1148 -0.0632 #> [10,] 0.0300 -0.0813 #> [11,] -0.0854 -0.1019 #> [12,] -0.4114 -0.0068 #> [13,] -0.3884 0.0291 #> [14,] -0.1832 0.0313 #> [15,] 0.0617 0.0390 #> [16,] -0.0179 0.0219 #> [17,] 0.0760 -0.0099 #> [18,] -0.1484 -0.0095 #> #> $AE93 #> [,1] [,2] #> [1,] -0.4952 -0.0307 #> [2,] -0.0084 0.0880 #> [3,] 0.2071 0.0946 #> [4,] 0.2316 0.0816 #> [5,] 0.2467 0.0549 #> [6,] 0.2453 0.0383 #> [7,] 0.2234 0.0091 #> [8,] 0.1754 -0.0252 #> [9,] 0.1271 -0.0547 #> [10,] 0.0341 -0.0909 #> [11,] -0.0819 -0.1079 #> [12,] -0.3926 -0.0640 #> [13,] -0.3841 -0.0171 #> [14,] -0.1796 0.0081 #> [15,] 0.1004 0.0557 #> [16,] -0.0091 0.0132 #> [17,] 0.0923 -0.0063 #> [18,] -0.1324 -0.0468 #> #> $AE94 #> [,1] [,2] #> [1,] -0.4698 0.0335 #> [2,] -0.0216 0.0792 #> [3,] 0.2474 0.0542 #> [4,] 0.2598 0.0366 #> [5,] 0.2638 0.0178 #> [6,] 0.2596 -0.0003 #> [7,] 0.2374 -0.0203 #> [8,] 0.1819 -0.0429 #> [9,] 0.1096 -0.0649 #> [10,] 0.0342 -0.0885 #> [11,] -0.0859 -0.0998 #> [12,] -0.3934 -0.0067 #> [13,] -0.3849 0.0245 #> [14,] -0.1768 0.0324 #> [15,] 0.0505 0.0429 #> [16,] -0.0276 0.0247 #> [17,] 0.0610 -0.0049 #> [18,] -0.1454 -0.0177 #> #> $AE95 #> [,1] [,2] #> [1,] -0.4671 0.0312 #> [2,] -0.0061 0.0664 #> [3,] 0.2297 0.0527 #> [4,] 0.2486 0.0341 #> [5,] 0.2520 0.0135 #> [6,] 0.2493 0.0015 #> [7,] 0.2372 -0.0153 #> [8,] 0.1981 -0.0390 #> [9,] 0.1311 -0.0586 #> [10,] 0.0390 -0.0802 #> [11,] -0.0883 -0.0946 #> [12,] -0.4060 -0.0092 #> [13,] -0.3842 0.0282 #> [14,] -0.1979 0.0305 #> [15,] 0.0683 0.0382 #> [16,] -0.0176 0.0225 #> [17,] 0.0693 -0.0105 #> [18,] -0.1554 -0.0115 #> #> $AE96 #> [,1] [,2] #> [1,] -0.4496 0.0251 #> [2,] 0.0418 0.0929 #> [3,] 0.2379 0.0655 #> [4,] 0.2481 0.0523 #> [5,] 0.2581 0.0299 #> [6,] 0.2557 0.0055 #> [7,] 0.2381 -0.0173 #> [8,] 0.1991 -0.0432 #> [9,] 0.1126 -0.0703 #> [10,] 0.0403 -0.0928 #> [11,] -0.0848 -0.1123 #> [12,] -0.3990 -0.0242 #> [13,] -0.3887 0.0212 #> [14,] -0.1800 0.0272 #> [15,] 0.0494 0.0466 #> [16,] -0.0371 0.0209 #> [17,] 0.0319 -0.0083 #> [18,] -0.1738 -0.0188 #> #> $AE97 #> [,1] [,2] #> [1,] -0.4752 0.0313 #> [2,] -0.0129 0.0794 #> [3,] 0.2411 0.0647 #> [4,] 0.2630 0.0408 #> [5,] 0.2667 0.0187 #> [6,] 0.2589 0.0001 #> [7,] 0.2373 -0.0218 #> [8,] 0.1823 -0.0483 #> [9,] 0.1101 -0.0685 #> [10,] 0.0322 -0.0905 #> [11,] -0.0857 -0.1034 #> [12,] -0.3916 -0.0011 #> [13,] -0.3707 0.0294 #> [14,] -0.1594 0.0302 #> [15,] 0.0684 0.0464 #> [16,] -0.0400 0.0168 #> [17,] 0.0472 -0.0064 #> [18,] -0.1714 -0.0179 #> #> $AE98 #> [,1] [,2] #> [1,] -0.4805 0.0310 #> [2,] 0.0152 0.0817 #> [3,] 0.2335 0.0515 #> [4,] 0.2456 0.0339 #> [5,] 0.2510 0.0165 #> [6,] 0.2463 -0.0020 #> [7,] 0.2240 -0.0203 #> [8,] 0.1898 -0.0367 #> [9,] 0.1122 -0.0542 #> [10,] 0.0281 -0.0775 #> [11,] -0.0741 -0.0984 #> [12,] -0.4098 -0.0139 #> [13,] -0.3935 0.0240 #> [14,] -0.1848 0.0289 #> [15,] 0.0663 0.0398 #> [16,] -0.0167 0.0198 #> [17,] 0.0885 -0.0078 #> [18,] -0.1409 -0.0163 #> #> $AE99 #> [,1] [,2] #> [1,] -0.4590 0.0473 #> [2,] -0.0082 0.0763 #> [3,] 0.2412 0.0497 #> [4,] 0.2554 0.0312 #> [5,] 0.2586 0.0137 #> [6,] 0.2549 -0.0042 #> [7,] 0.2314 -0.0258 #> [8,] 0.1965 -0.0468 #> [9,] 0.1246 -0.0728 #> [10,] 0.0303 -0.0900 #> [11,] -0.0930 -0.1030 #> [12,] -0.3969 0.0077 #> [13,] -0.3798 0.0425 #> [14,] -0.2065 0.0362 #> [15,] 0.0579 0.0396 #> [16,] -0.0358 0.0229 #> [17,] 0.0666 -0.0084 #> [18,] -0.1383 -0.0161 #> #> $AE100 #> [,1] [,2] #> [1,] -0.4465 0.0572 #> [2,] 0.0411 0.0848 #> [3,] 0.2502 0.0521 #> [4,] 0.2663 0.0287 #> [5,] 0.2668 0.0076 #> [6,] 0.2608 -0.0132 #> [7,] 0.2354 -0.0369 #> [8,] 0.1695 -0.0604 #> [9,] 0.0920 -0.0708 #> [10,] 0.0016 -0.0921 #> [11,] -0.1146 -0.0914 #> [12,] -0.4002 0.0082 #> [13,] -0.3877 0.0479 #> [14,] -0.1849 0.0425 #> [15,] 0.0621 0.0415 #> [16,] -0.0326 0.0214 #> [17,] 0.0604 -0.0142 #> [18,] -0.1397 -0.0129 #> #> $CX101 #> [,1] [,2] #> [1,] -0.4675 0.0358 #> [2,] 0.0076 0.0890 #> [3,] 0.2398 0.0591 #> [4,] 0.2530 0.0387 #> [5,] 0.2530 0.0160 #> [6,] 0.2435 -0.0025 #> [7,] 0.2281 -0.0208 #> [8,] 0.1904 -0.0450 #> [9,] 0.1145 -0.0676 #> [10,] 0.0441 -0.0922 #> [11,] -0.0861 -0.1011 #> [12,] -0.4050 -0.0034 #> [13,] -0.4006 0.0308 #> [14,] -0.1777 0.0344 #> [15,] 0.0503 0.0428 #> [16,] -0.0234 0.0200 #> [17,] 0.0666 -0.0124 #> [18,] -0.1306 -0.0216 #> #> $CX102 #> [,1] [,2] #> [1,] -0.4888 0.0420 #> [2,] 0.0310 0.0749 #> [3,] 0.2320 0.0461 #> [4,] 0.2452 0.0355 #> [5,] 0.2490 0.0209 #> [6,] 0.2463 -0.0001 #> [7,] 0.2282 -0.0249 #> [8,] 0.1735 -0.0509 #> [9,] 0.1146 -0.0649 #> [10,] 0.0404 -0.0844 #> [11,] -0.0664 -0.1011 #> [12,] -0.4162 0.0110 #> [13,] -0.3960 0.0379 #> [14,] -0.1586 0.0274 #> [15,] 0.0461 0.0383 #> [16,] -0.0118 0.0157 #> [17,] 0.0706 -0.0104 #> [18,] -0.1394 -0.0132 #> #> $CX103 #> [,1] [,2] #> [1,] -0.4607 0.0433 #> [2,] -0.0028 0.0881 #> [3,] 0.2367 0.0578 #> [4,] 0.2565 0.0380 #> [5,] 0.2685 0.0039 #> [6,] 0.2615 -0.0101 #> [7,] 0.2378 -0.0312 #> [8,] 0.1889 -0.0549 #> [9,] 0.1104 -0.0715 #> [10,] 0.0204 -0.0899 #> [11,] -0.0858 -0.0956 #> [12,] -0.3957 -0.0012 #> [13,] -0.3755 0.0427 #> [14,] -0.1941 0.0420 #> [15,] 0.0460 0.0436 #> [16,] -0.0207 0.0213 #> [17,] 0.0641 -0.0091 #> [18,] -0.1553 -0.0172 #> #> $CX104 #> [,1] [,2] #> [1,] -0.4740 0.0362 #> [2,] 0.0148 0.0902 #> [3,] 0.2410 0.0524 #> [4,] 0.2495 0.0367 #> [5,] 0.2536 0.0150 #> [6,] 0.2499 -0.0044 #> [7,] 0.2304 -0.0224 #> [8,] 0.1789 -0.0498 #> [9,] 0.1190 -0.0697 #> [10,] 0.0377 -0.0896 #> [11,] -0.0732 -0.1019 #> [12,] -0.3990 -0.0067 #> [13,] -0.3906 0.0306 #> [14,] -0.1890 0.0359 #> [15,] 0.0466 0.0460 #> [16,] -0.0228 0.0254 #> [17,] 0.0727 -0.0101 #> [18,] -0.1455 -0.0140 #> #> $CX105 #> [,1] [,2] #> [1,] -0.4668 0.0618 #> [2,] 0.0094 0.0873 #> [3,] 0.2422 0.0529 #> [4,] 0.2512 0.0324 #> [5,] 0.2543 0.0050 #> [6,] 0.2490 -0.0107 #> [7,] 0.2352 -0.0310 #> [8,] 0.1858 -0.0570 #> [9,] 0.1074 -0.0749 #> [10,] 0.0270 -0.0931 #> [11,] -0.0583 -0.1068 #> [12,] -0.4072 0.0148 #> [13,] -0.3952 0.0506 #> [14,] -0.1745 0.0392 #> [15,] 0.0449 0.0349 #> [16,] -0.0158 0.0211 #> [17,] 0.0501 -0.0115 #> [18,] -0.1385 -0.0147 #> #> $CX106 #> [,1] [,2] #> [1,] -0.4715 0.0348 #> [2,] 0.0383 0.0970 #> [3,] 0.2271 0.0693 #> [4,] 0.2476 0.0416 #> [5,] 0.2507 0.0204 #> [6,] 0.2462 0.0005 #> [7,] 0.2329 -0.0169 #> [8,] 0.1895 -0.0447 #> [9,] 0.1317 -0.0662 #> [10,] 0.0419 -0.0952 #> [11,] -0.0667 -0.1140 #> [12,] -0.4058 -0.0158 #> [13,] -0.3849 0.0256 #> [14,] -0.1853 0.0312 #> [15,] 0.0307 0.0462 #> [16,] -0.0225 0.0202 #> [17,] 0.0530 -0.0107 #> [18,] -0.1530 -0.0232 #> #> $CX107 #> [,1] [,2] #> [1,] -0.4590 0.0148 #> [2,] 0.0363 0.0863 #> [3,] 0.2260 0.0699 #> [4,] 0.2480 0.0478 #> [5,] 0.2538 0.0260 #> [6,] 0.2493 0.0091 #> [7,] 0.2424 -0.0048 #> [8,] 0.1848 -0.0373 #> [9,] 0.1359 -0.0516 #> [10,] 0.0476 -0.0813 #> [11,] -0.0687 -0.1059 #> [12,] -0.4071 -0.0230 #> [13,] -0.3946 0.0101 #> [14,] -0.2028 0.0189 #> [15,] 0.0294 0.0402 #> [16,] -0.0230 0.0168 #> [17,] 0.0519 -0.0071 #> [18,] -0.1502 -0.0288 #> #> $CX108 #> [,1] [,2] #> [1,] -0.4555 0.0398 #> [2,] 0.0470 0.0891 #> [3,] 0.2562 0.0561 #> [4,] 0.2701 0.0390 #> [5,] 0.2680 0.0145 #> [6,] 0.2584 -0.0016 #> [7,] 0.2320 -0.0199 #> [8,] 0.1668 -0.0458 #> [9,] 0.1151 -0.0631 #> [10,] 0.0296 -0.0835 #> [11,] -0.0592 -0.0990 #> [12,] -0.3938 -0.0068 #> [13,] -0.3848 0.0315 #> [14,] -0.2053 0.0334 #> [15,] 0.0194 0.0418 #> [16,] -0.0607 0.0127 #> [17,] 0.0395 -0.0129 #> [18,] -0.1427 -0.0254 #> #> $CX109 #> [,1] [,2] #> [1,] -0.4667 0.0415 #> [2,] 0.0338 0.0789 #> [3,] 0.2422 0.0496 #> [4,] 0.2538 0.0348 #> [5,] 0.2566 0.0152 #> [6,] 0.2470 -0.0006 #> [7,] 0.2342 -0.0169 #> [8,] 0.1996 -0.0404 #> [9,] 0.1256 -0.0646 #> [10,] 0.0298 -0.0862 #> [11,] -0.0508 -0.0996 #> [12,] -0.4027 -0.0035 #> [13,] -0.3905 0.0319 #> [14,] -0.1961 0.0325 #> [15,] 0.0087 0.0352 #> [16,] -0.0277 0.0175 #> [17,] 0.0499 -0.0075 #> [18,] -0.1466 -0.0177 #> #> $CX110 #> [,1] [,2] #> [1,] -0.4672 0.0148 #> [2,] -0.0006 0.0759 #> [3,] 0.2450 0.0556 #> [4,] 0.2527 0.0457 #> [5,] 0.2575 0.0260 #> [6,] 0.2521 0.0083 #> [7,] 0.2378 -0.0110 #> [8,] 0.1833 -0.0363 #> [9,] 0.1208 -0.0568 #> [10,] 0.0466 -0.0793 #> [11,] -0.0694 -0.0989 #> [12,] -0.4047 -0.0193 #> [13,] -0.3958 0.0109 #> [14,] -0.1872 0.0241 #> [15,] 0.0241 0.0417 #> [16,] -0.0231 0.0205 #> [17,] 0.0664 -0.0083 #> [18,] -0.1382 -0.0136 #> #> $CX111 #> [,1] [,2] #> [1,] -0.4677 0.0403 #> [2,] 0.0196 0.0881 #> [3,] 0.2339 0.0595 #> [4,] 0.2494 0.0417 #> [5,] 0.2516 0.0225 #> [6,] 0.2500 0.0040 #> [7,] 0.2268 -0.0213 #> [8,] 0.1892 -0.0451 #> [9,] 0.1276 -0.0688 #> [10,] 0.0479 -0.0954 #> [11,] -0.0531 -0.1165 #> [12,] -0.4007 -0.0060 #> [13,] -0.3897 0.0315 #> [14,] -0.1988 0.0346 #> [15,] 0.0346 0.0453 #> [16,] -0.0262 0.0179 #> [17,] 0.0552 -0.0111 #> [18,] -0.1495 -0.0211 #> #> $CX112 #> [,1] [,2] #> [1,] -0.4564 0.0647 #> [2,] 0.0275 0.0924 #> [3,] 0.2515 0.0403 #> [4,] 0.2605 0.0205 #> [5,] 0.2628 -0.0063 #> [6,] 0.2530 -0.0233 #> [7,] 0.2335 -0.0405 #> [8,] 0.1908 -0.0613 #> [9,] 0.0918 -0.0767 #> [10,] 0.0060 -0.0898 #> [11,] -0.0921 -0.0952 #> [12,] -0.3958 0.0241 #> [13,] -0.3816 0.0571 #> [14,] -0.1921 0.0501 #> [15,] 0.0472 0.0384 #> [16,] -0.0190 0.0215 #> [17,] 0.0587 -0.0154 #> [18,] -0.1462 -0.0008 #> #> $CX113 #> [,1] [,2] #> [1,] -0.4751 0.0569 #> [2,] 0.0052 0.0783 #> [3,] 0.2519 0.0382 #> [4,] 0.2542 0.0256 #> [5,] 0.2513 0.0055 #> [6,] 0.2471 -0.0123 #> [7,] 0.2233 -0.0291 #> [8,] 0.1824 -0.0469 #> [9,] 0.1096 -0.0678 #> [10,] 0.0453 -0.0893 #> [11,] -0.0698 -0.1008 #> [12,] -0.4007 0.0165 #> [13,] -0.3929 0.0455 #> [14,] -0.1801 0.0341 #> [15,] 0.0579 0.0377 #> [16,] -0.0185 0.0201 #> [17,] 0.0591 -0.0086 #> [18,] -0.1500 -0.0037 #> #> $CX114 #> [,1] [,2] #> [1,] -0.4516 0.0474 #> [2,] 0.0362 0.0865 #> [3,] 0.2354 0.0643 #> [4,] 0.2578 0.0385 #> [5,] 0.2614 0.0162 #> [6,] 0.2522 -0.0055 #> [7,] 0.2305 -0.0240 #> [8,] 0.1886 -0.0484 #> [9,] 0.1193 -0.0725 #> [10,] 0.0389 -0.1026 #> [11,] -0.0797 -0.1136 #> [12,] -0.4040 0.0051 #> [13,] -0.3864 0.0390 #> [14,] -0.1879 0.0325 #> [15,] 0.0302 0.0375 #> [16,] -0.0300 0.0176 #> [17,] 0.0510 -0.0096 #> [18,] -0.1620 -0.0084 #> #> $CX115 #> [,1] [,2] #> [1,] -0.4523 0.0176 #> [2,] 0.0035 0.0833 #> [3,] 0.2144 0.0768 #> [4,] 0.2443 0.0558 #> [5,] 0.2566 0.0296 #> [6,] 0.2542 0.0105 #> [7,] 0.2407 -0.0070 #> [8,] 0.2163 -0.0307 #> [9,] 0.1366 -0.0594 #> [10,] 0.0410 -0.0894 #> [11,] -0.0903 -0.1067 #> [12,] -0.4030 -0.0281 #> [13,] -0.3952 0.0062 #> [14,] -0.1757 0.0183 #> [15,] 0.0380 0.0414 #> [16,] -0.0322 0.0175 #> [17,] 0.0617 -0.0073 #> [18,] -0.1585 -0.0283 #> #> $CX116 #> [,1] [,2] #> [1,] -0.4638 0.0562 #> [2,] 0.0597 0.0945 #> [3,] 0.2388 0.0506 #> [4,] 0.2573 0.0282 #> [5,] 0.2573 0.0022 #> [6,] 0.2492 -0.0153 #> [7,] 0.2263 -0.0375 #> [8,] 0.1867 -0.0609 #> [9,] 0.1100 -0.0799 #> [10,] 0.0215 -0.0950 #> [11,] -0.0765 -0.1068 #> [12,] -0.4073 0.0138 #> [13,] -0.3775 0.0529 #> [14,] -0.1544 0.0461 #> [15,] 0.0437 0.0430 #> [16,] -0.0265 0.0239 #> [17,] 0.0387 -0.0080 #> [18,] -0.1834 -0.0080 #> #> $CX117 #> [,1] [,2] #> [1,] -0.4699 0.0301 #> [2,] 0.0096 0.0909 #> [3,] 0.2565 0.0431 #> [4,] 0.2598 0.0340 #> [5,] 0.2595 0.0158 #> [6,] 0.2551 0.0034 #> [7,] 0.2364 -0.0176 #> [8,] 0.2000 -0.0399 #> [9,] 0.1255 -0.0658 #> [10,] 0.0271 -0.0897 #> [11,] -0.0544 -0.1021 #> [12,] -0.3901 -0.0085 #> [13,] -0.3751 0.0295 #> [14,] -0.1805 0.0350 #> [15,] 0.0155 0.0443 #> [16,] -0.0440 0.0198 #> [17,] 0.0343 -0.0054 #> [18,] -0.1652 -0.0169 #> #> $CX118 #> [,1] [,2] #> [1,] -0.4717 0.0591 #> [2,] 0.0228 0.0912 #> [3,] 0.2401 0.0542 #> [4,] 0.2557 0.0372 #> [5,] 0.2604 0.0132 #> [6,] 0.2551 -0.0035 #> [7,] 0.2380 -0.0238 #> [8,] 0.1861 -0.0494 #> [9,] 0.1134 -0.0730 #> [10,] 0.0372 -0.0981 #> [11,] -0.0711 -0.1055 #> [12,] -0.4021 -0.0079 #> [13,] -0.3762 0.0492 #> [14,] -0.1826 0.0340 #> [15,] 0.0230 0.0341 #> [16,] -0.0235 0.0166 #> [17,] 0.0383 -0.0098 #> [18,] -0.1430 -0.0179 #> #> $CX119 #> [,1] [,2] #> [1,] -0.4823 0.0484 #> [2,] 0.0239 0.0839 #> [3,] 0.2381 0.0493 #> [4,] 0.2559 0.0323 #> [5,] 0.2612 0.0093 #> [6,] 0.2540 -0.0136 #> [7,] 0.2274 -0.0340 #> [8,] 0.1855 -0.0536 #> [9,] 0.1077 -0.0661 #> [10,] 0.0256 -0.0857 #> [11,] -0.0909 -0.0937 #> [12,] -0.4008 0.0051 #> [13,] -0.3850 0.0448 #> [14,] -0.1620 0.0341 #> [15,] 0.0659 0.0387 #> [16,] -0.0253 0.0186 #> [17,] 0.0440 -0.0063 #> [18,] -0.1428 -0.0115 #> #> $CX120 #> [,1] [,2] #> [1,] -0.4575 0.0294 #> [2,] 0.0270 0.0921 #> [3,] 0.2328 0.0739 #> [4,] 0.2574 0.0451 #> [5,] 0.2623 0.0192 #> [6,] 0.2555 -0.0027 #> [7,] 0.2341 -0.0226 #> [8,] 0.1904 -0.0453 #> [9,] 0.1083 -0.0686 #> [10,] 0.0369 -0.0939 #> [11,] -0.0767 -0.1056 #> [12,] -0.4021 -0.0155 #> [13,] -0.3876 0.0264 #> [14,] -0.1826 0.0346 #> [15,] 0.0479 0.0459 #> [16,] -0.0293 0.0198 #> [17,] 0.0432 -0.0130 #> [18,] -0.1598 -0.0193 #> #> $CX121 #> [,1] [,2] #> [1,] -0.4785 0.0252 #> [2,] -0.0091 0.0782 #> [3,] 0.2140 0.0670 #> [4,] 0.2430 0.0459 #> [5,] 0.2600 0.0218 #> [6,] 0.2575 0.0084 #> [7,] 0.2420 -0.0185 #> [8,] 0.2009 -0.0467 #> [9,] 0.1466 -0.0688 #> [10,] 0.0406 -0.0924 #> [11,] -0.0734 -0.1098 #> [12,] -0.3879 -0.0101 #> [13,] -0.3856 0.0271 #> [14,] -0.1764 0.0262 #> [15,] 0.0299 0.0448 #> [16,] -0.0162 0.0209 #> [17,] 0.0502 -0.0023 #> [18,] -0.1576 -0.0167 #> #> $CX122 #> [,1] [,2] #> [1,] -0.4806 0.0049 #> [2,] 0.0172 0.0810 #> [3,] 0.2174 0.0773 #> [4,] 0.2429 0.0558 #> [5,] 0.2512 0.0339 #> [6,] 0.2482 0.0140 #> [7,] 0.2267 -0.0067 #> [8,] 0.1961 -0.0262 #> [9,] 0.1269 -0.0542 #> [10,] 0.0394 -0.0811 #> [11,] -0.0736 -0.1045 #> [12,] -0.4104 -0.0276 #> [13,] -0.3947 0.0023 #> [14,] -0.1550 0.0162 #> [15,] 0.0567 0.0419 #> [16,] -0.0242 0.0153 #> [17,] 0.0737 -0.0086 #> [18,] -0.1579 -0.0338 #> #> $CX123 #> [,1] [,2] #> [1,] -0.4703 -0.0009 #> [2,] 0.0011 0.0805 #> [3,] 0.2146 0.0747 #> [4,] 0.2348 0.0585 #> [5,] 0.2453 0.0350 #> [6,] 0.2442 0.0149 #> [7,] 0.2372 -0.0030 #> [8,] 0.2186 -0.0235 #> [9,] 0.1342 -0.0582 #> [10,] 0.0391 -0.0843 #> [11,] -0.0726 -0.1051 #> [12,] -0.4090 -0.0371 #> [13,] -0.3966 -0.0061 #> [14,] -0.1624 0.0193 #> [15,] 0.0557 0.0467 #> [16,] -0.0272 0.0190 #> [17,] 0.0718 -0.0052 #> [18,] -0.1583 -0.0251 #> #> $CX124 #> [,1] [,2] #> [1,] -0.4725 0.0441 #> [2,] 0.0318 0.0808 #> [3,] 0.2382 0.0419 #> [4,] 0.2504 0.0237 #> [5,] 0.2492 0.0019 #> [6,] 0.2414 -0.0135 #> [7,] 0.2276 -0.0298 #> [8,] 0.1945 -0.0472 #> [9,] 0.1219 -0.0661 #> [10,] 0.0311 -0.0885 #> [11,] -0.0963 -0.0840 #> [12,] -0.4066 0.0093 #> [13,] -0.3944 0.0425 #> [14,] -0.1724 0.0390 #> [15,] 0.0667 0.0418 #> [16,] -0.0108 0.0205 #> [17,] 0.0548 -0.0049 #> [18,] -0.1546 -0.0115 #> #> $CX125 #> [,1] [,2] #> [1,] -0.4697 0.0196 #> [2,] 0.0007 0.0850 #> [3,] 0.2228 0.0760 #> [4,] 0.2485 0.0540 #> [5,] 0.2548 0.0319 #> [6,] 0.2511 0.0132 #> [7,] 0.2366 -0.0097 #> [8,] 0.1950 -0.0372 #> [9,] 0.1279 -0.0620 #> [10,] 0.0443 -0.0943 #> [11,] -0.0773 -0.1149 #> [12,] -0.3987 -0.0131 #> [13,] -0.3908 0.0161 #> [14,] -0.1816 0.0213 #> [15,] 0.0376 0.0408 #> [16,] -0.0073 0.0137 #> [17,] 0.0592 -0.0103 #> [18,] -0.1531 -0.0300 #> #> $DE126 #> [,1] [,2] #> [1,] -0.4620 0.0204 #> [2,] 0.0082 0.0893 #> [3,] 0.2061 0.0797 #> [4,] 0.2374 0.0529 #> [5,] 0.2457 0.0306 #> [6,] 0.2482 0.0060 #> [7,] 0.2341 -0.0151 #> [8,] 0.2064 -0.0363 #> [9,] 0.1421 -0.0635 #> [10,] 0.0572 -0.0906 #> [11,] -0.0335 -0.1073 #> [12,] -0.4127 -0.0169 #> [13,] -0.4018 0.0111 #> [14,] -0.1876 0.0241 #> [15,] 0.0279 0.0403 #> [16,] -0.0425 0.0145 #> [17,] 0.0729 -0.0123 #> [18,] -0.1460 -0.0269 #> #> $DE127 #> [,1] [,2] #> [1,] -0.4570 0.0468 #> [2,] -0.0090 0.0753 #> [3,] 0.2381 0.0463 #> [4,] 0.2556 0.0275 #> [5,] 0.2614 0.0064 #> [6,] 0.2515 -0.0129 #> [7,] 0.2287 -0.0278 #> [8,] 0.1883 -0.0456 #> [9,] 0.1180 -0.0624 #> [10,] 0.0408 -0.0818 #> [11,] -0.0823 -0.0867 #> [12,] -0.4025 0.0048 #> [13,] -0.3888 0.0415 #> [14,] -0.2028 0.0371 #> [15,] 0.0490 0.0347 #> [16,] -0.0422 0.0204 #> [17,] 0.1004 -0.0180 #> [18,] -0.1473 -0.0057 #> # on Ldk (slidings) get_ldk(chaff) #> $shp1 #> x y #> ScarTop 697 977 #> ScarRight 766 991 #> ScarBottom 704 1046 #> ScarLeft 629 1008 #> RofScar 818 981 #> LofScar 567 1017 #> GInsL 594 1077 #> GInsR 809 1044 #> GJoinL 645 950 #> GJoinR 731 926 #> LTop 541 962 #> RTop 835 911 #> #> $shp2 #> x y #> ScarTop 677 964 #> ScarRight 748 992 #> ScarBottom 677 1039 #> ScarLeft 603 985 #> RofScar 803 994 #> LofScar 551 984 #> GInsL 575 1051 #> GInsR 784 1041 #> GJoinL 642 949 #> GJoinR 715 947 #> LTop 541 949 #> RTop 822 955 #> #> $shp3 #> x y #> ScarTop 684 981 #> ScarRight 748 1006 #> ScarBottom 683 1047 #> ScarLeft 620 1006 #> RofScar 808 1009 #> LofScar 566 1007 #> GInsL 594 1082 #> GInsR 788 1064 #> GJoinL 629 957 #> GJoinR 727 953 #> LTop 551 956 #> RTop 823 960 #> #> $shp4 #> x y #> ScarTop 750 1035 #> ScarRight 820 1056 #> ScarBottom 748 1104 #> ScarLeft 681 1058 #> RofScar 880 1058 #> LofScar 626 1059 #> GInsL 646 1114 #> GInsR 845 1137 #> GJoinL 714 984 #> GJoinR 799 1015 #> LTop 611 985 #> RTop 888 1018 #> #> $shp5 #> x y #> ScarTop 740 1067 #> ScarRight 802 1091 #> ScarBottom 739 1136 #> ScarLeft 674 1093 #> RofScar 862 1092 #> LofScar 604 1095 #> GInsL 636 1173 #> GInsR 829 1165 #> GJoinL 697 1054 #> GJoinR 777 1040 #> LTop 594 1052 #> RTop 874 1044 #> #> $shp6 #> x y #> ScarTop 784 903 #> ScarRight 841 921 #> ScarBottom 782 954 #> ScarLeft 720 914 #> RofScar 919 928 #> LofScar 663 913 #> GInsL 704 994 #> GInsR 886 983 #> GJoinL 751 888 #> GJoinR 828 897 #> LTop 654 887 #> RTop 928 905 #> #> $shp7 #> x y #> ScarTop 766 1041 #> ScarRight 841 1055 #> ScarBottom 768 1108 #> ScarLeft 688 1063 #> RofScar 892 1055 #> LofScar 631 1065 #> GInsL 664 1102 #> GInsR 873 1085 #> GJoinL 707 1006 #> GJoinR 824 992 #> LTop 601 1008 #> RTop 921 997 #> #> $shp8 #> x y #> ScarTop 822 1134 #> ScarRight 895 1149 #> ScarBottom 823 1201 #> ScarLeft 747 1159 #> RofScar 951 1146 #> LofScar 688 1161 #> GInsL 721 1201 #> GInsR 920 1188 #> GJoinL 755 1112 #> GJoinR 879 1114 #> LTop 665 1118 #> RTop 964 1121 #> #> $shp9 #> x y #> ScarTop 772 1041 #> ScarRight 829 1054 #> ScarBottom 767 1104 #> ScarLeft 695 1049 #> RofScar 893 1061 #> LofScar 638 1052 #> GInsL 661 1094 #> GInsR 859 1110 #> GJoinL 711 1007 #> GJoinR 822 1015 #> LTop 619 1005 #> RTop 912 1026 #> #> $shp10 #> x y #> ScarTop 824 978 #> ScarRight 875 1013 #> ScarBottom 821 1047 #> ScarLeft 752 1012 #> RofScar 980 1017 #> LofScar 652 1014 #> GInsL 722 1133 #> GInsR 940 1111 #> GJoinL 760 977 #> GJoinR 873 971 #> LTop 640 981 #> RTop 991 985 #> #> $shp11 #> x y #> ScarTop 773 1004 #> ScarRight 832 1022 #> ScarBottom 777 1060 #> ScarLeft 716 1030 #> RofScar 927 1019 #> LofScar 605 1040 #> GInsL 679 1167 #> GInsR 878 1140 #> GJoinL 716 1002 #> GJoinR 861 965 #> LTop 594 1012 #> RTop 945 973 #> #> $shp12 #> x y #> ScarTop 792 986 #> ScarRight 849 992 #> ScarBottom 795 1044 #> ScarLeft 732 1003 #> RofScar 951 987 #> LofScar 636 1014 #> GInsL 700 1159 #> GInsR 899 1119 #> GJoinL 749 983 #> GJoinR 856 969 #> LTop 630 995 #> RTop 959 970 #> #> $shp13 #> x y #> ScarTop 753 1244 #> ScarRight 830 1265 #> ScarBottom 759 1322 #> ScarLeft 678 1288 #> RofScar 940 1259 #> LofScar 566 1306 #> GInsL 634 1413 #> GInsR 884 1392 #> GJoinL 674 1242 #> GJoinR 822 1213 #> LTop 550 1254 #> RTop 952 1220 #> #> $shp14 #> x y #> ScarTop 754 1113 #> ScarRight 819 1149 #> ScarBottom 749 1179 #> ScarLeft 678 1137 #> RofScar 943 1169 #> LofScar 572 1128 #> GInsL 643 1254 #> GInsR 850 1287 #> GJoinL 673 1099 #> GJoinR 831 1115 #> LTop 561 1099 #> RTop 956 1129 #> #> $shp15 #> x y #> ScarTop 742 1127 #> ScarRight 805 1151 #> ScarBottom 740 1182 #> ScarLeft 672 1154 #> RofScar 910 1158 #> LofScar 557 1157 #> GInsL 654 1279 #> GInsR 830 1270 #> GJoinL 658 1118 #> GJoinR 814 1098 #> LTop 543 1113 #> RTop 922 1115 #> #> $shp16 #> x y #> ScarTop 821 1105 #> ScarRight 886 1110 #> ScarBottom 831 1167 #> ScarLeft 763 1140 #> RofScar 985 1101 #> LofScar 656 1167 #> GInsL 715 1240 #> GInsR 954 1184 #> GJoinL 732 1098 #> GJoinR 899 1045 #> LTop 635 1118 #> RTop 1001 1049 #> #> $shp17 #> x y #> ScarTop 829 1103 #> ScarRight 898 1123 #> ScarBottom 825 1162 #> ScarLeft 754 1115 #> RofScar 1004 1134 #> LofScar 661 1109 #> GInsL 703 1199 #> GInsR 958 1215 #> GJoinL 747 1081 #> GJoinR 917 1103 #> LTop 651 1080 #> RTop 1010 1122 #> #> $shp18 #> x y #> ScarTop 763 1102 #> ScarRight 826 1107 #> ScarBottom 774 1158 #> ScarLeft 701 1126 #> RofScar 924 1094 #> LofScar 615 1140 #> GInsL 659 1226 #> GInsR 878 1229 #> GJoinL 695 1110 #> GJoinR 828 1080 #> LTop 612 1123 #> RTop 927 1077 #> #> $shp19 #> x y #> ScarTop 653 1169 #> ScarRight 724 1197 #> ScarBottom 653 1254 #> ScarLeft 569 1202 #> RofScar 830 1210 #> LofScar 439 1212 #> GInsL 523 1311 #> GInsR 775 1297 #> GJoinL 539 1141 #> GJoinR 728 1124 #> LTop 405 1151 #> RTop 873 1128 #> #> $shp20 #> x y #> ScarTop 600 1155 #> ScarRight 663 1197 #> ScarBottom 592 1232 #> ScarLeft 525 1187 #> RofScar 781 1208 #> LofScar 405 1187 #> GInsL 460 1289 #> GInsR 716 1289 #> GJoinL 500 1114 #> GJoinR 667 1128 #> LTop 372 1118 #> RTop 812 1149 #> #> $shp21 #> x y #> ScarTop 612 1193 #> ScarRight 677 1228 #> ScarBottom 610 1269 #> ScarLeft 543 1228 #> RofScar 773 1230 #> LofScar 429 1228 #> GInsL 482 1289 #> GInsR 734 1299 #> GJoinL 527 1167 #> GJoinR 665 1147 #> LTop 403 1169 #> RTop 799 1161 #> get_ldk(chaff) %>% Ldk %>% fgProcrustes(tol=0.1) %>% stack #> iteration: 1 \tgain: 1448.7 #> iteration: 2 \tgain: 0.027479"},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"paired individuals, .e. treatment repeated measures, coded coded $fac, methods allows retrieve corresponding PC/LD scores, coefficients Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"","code":"get_pairs(x, fac, range)"},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"x Coe, PCA LDA object. fac factor column name id corresponding pairing factor. range numeric range coefficients Coe, PC (LD) axes return scores.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"list components x1 coefficients/scores corresponding first level fac provided; x2 thing second level; fac corresponding fac.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"","code":"bot2 <- bot1 <- coo_scale(coo_center(coo_sample(bot, 60))) bot1$fac$session <- factor(rep(\"session1\", 40)) # we simulate an measurement error bot2 <- coo_jitter(bot1, amount=0.01) bot2$fac$session <- factor(rep(\"session2\", 40)) botc <- combine(bot1, bot2) botcf <- efourier(botc, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # we gonna plot the PCA with the two measurement sessions and the two types botcp <- PCA(botcf) plot(botcp, \"type\", col=col_summer(2), pch=rep(c(1, 20), each=40), eigen=FALSE) #> will be deprecated soon, see ?plot_PCA bot.pairs <- get_pairs(botcp, fac = \"session\", range=1:2) segments(bot.pairs$session1[, 1], bot.pairs$session1[, 2], bot.pairs$session2[, 1], bot.pairs$session2[, 2], col=col_summer(2)[bot.pairs$fac$type])"},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts sliding landmarks coordinates — get_slidings","title":"Extracts sliding landmarks coordinates — get_slidings","text":"Ldk object.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts sliding landmarks coordinates — get_slidings","text":"","code":"get_slidings(Coo, partition)"},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts sliding landmarks coordinates — get_slidings","text":"Coo Ldk object partition numeric one(s) get.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts sliding landmarks coordinates — get_slidings","text":"list list(s) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts sliding landmarks coordinates — get_slidings","text":"","code":"# for each example below a list with partition containign shapes is returned # extracts the first partition get_slidings(chaff, 1) %>% names() #> [1] \"partition1\" # the first and the fourth get_slidings(chaff, c(1, 4)) %>% names() #> [1] \"partition1\" \"partition4\" # all of them get_slidings(chaff) %>% names #> [1] \"partition1\" \"partition2\" \"partition3\" \"partition4\" # here we want to see it get_slidings(chaff, 1)[[1]] %>% Ldk %>% stack"},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":null,"dir":"Reference","previous_headings":"","what":"Harmonic contribution to shape — hcontrib","title":"Harmonic contribution to shape — hcontrib","text":"Calculates contribution harmonics shape. amplitude every coefficients given harmonic multiplied coefficients provided resulting shapes reconstructed plotted. Naturally, works Fourier-based methods.","code":""},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Harmonic contribution to shape — hcontrib","text":"","code":"hcontrib(Coe, ...) # S3 method for OutCoe hcontrib( Coe, id, harm.r, amp.r = c(0, 0.5, 1, 2, 5, 10), main = \"Harmonic contribution to shape\", xlab = \"Harmonic rank\", ylab = \"Amplification factor\", ... )"},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Harmonic contribution to shape — hcontrib","text":"Coe Coe object (either OutCoe (soon) OpnCoe) ... additional parameter pass coo_draw id id particular shape, otherwise working meanshape harm.r range harmonics explore contributions amp.r vector numeric multiplying coefficients main title plot xlab title x-axis ylab title y-axis","code":""},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Harmonic contribution to shape — hcontrib","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Harmonic contribution to shape — hcontrib","text":"","code":"data(bot) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details hcontrib(bot.f) #> no 'id' provided, working on the meanshape hcontrib(bot.f, harm.r=3:10, amp.r=1:8, col=\"grey20\", main=\"A huge panel\") #> no 'id' provided, working on the meanshape"},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"Given list , bn (eventually cn dn), returns harmonic power.","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"","code":"harm_pow(xf)"},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"xf list , bn (cn, dn) components, typically e/r/tfourier passed coo_","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"Returns vector harmonic power","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"","code":"ef <- efourier(bot[1], 24) rf <- efourier(bot[1], 24) harm_pow(ef) #> H1 H2 H3 H4 H5 H6 #> 1.299790e+05 2.593195e+02 1.376114e+03 1.792188e+02 2.594795e+02 2.675959e+01 #> H7 H8 H9 H10 H11 H12 #> 3.103764e+01 3.422527e+00 6.584799e-01 8.255293e+00 3.010409e+00 6.433551e+00 #> H13 H14 H15 H16 H17 H18 #> 1.082413e+00 1.171377e+00 1.929022e-01 4.769194e-01 2.059250e-01 1.971375e-01 #> H19 H20 H21 H22 H23 H24 #> 1.099667e-01 1.586647e-01 4.222544e-02 1.447763e-01 5.618937e-02 1.570677e-01 harm_pow(rf) #> H1 H2 H3 H4 H5 H6 #> 1.299790e+05 2.593195e+02 1.376114e+03 1.792188e+02 2.594795e+02 2.675959e+01 #> H7 H8 H9 H10 H11 H12 #> 3.103764e+01 3.422527e+00 6.584799e-01 8.255293e+00 3.010409e+00 6.433551e+00 #> H13 H14 H15 H16 H17 H18 #> 1.082413e+00 1.171377e+00 1.929022e-01 4.769194e-01 2.059250e-01 1.971375e-01 #> H19 H20 H21 H22 H23 H24 #> 1.099667e-01 1.586647e-01 4.222544e-02 1.447763e-01 5.618937e-02 1.570677e-01 plot(cumsum(harm_pow(ef)[-1]), type='o', main='Cumulated harmonic power without the first harmonic', ylab='Cumulated harmonic power', xlab='Harmonic rank')"},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a .jpg image — img_plot","title":"Plots a .jpg image — img_plot","text":"simple image plotter. provided path, reads .jpg plots . provided imagematrix, ask choose interactively .jpeg image.","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a .jpg image — img_plot","text":"","code":"img_plot(img) img_plot0(img)"},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a .jpg image — img_plot","text":"img matrix image, obtained readJPEG.","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a .jpg image — img_plot","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots a .jpg image — img_plot","text":"img_plot used import functions import_jpg1; img_plot0 job preserves par plots axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outlines coordinates from an image silhouette — import_Conte","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Provided image 'mask' (.e. black pixels white background), point form start algorithm, returns (x; y) coordinates outline.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"","code":"import_Conte(img, x)"},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"img matrix binary image mask. x numeric (x; y) coordinates starting point within shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"matrix (x; y) coordinates outline points.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Used internally import_jpg1 may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Note function deprecated Momocs Momacs Momit fully operationnal. image single shape, may want try imager::highlight function. Momocs may use point.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"original algorithm due : Pavlidis, T. (1982). Algorithms graphics image processing. Computer science press. detailed : Rohlf, F. J. (1990). overview image processing analysis techniques morphometrics. Proceedings Michigan Morphometrics Workshop. Special Publication . 2 (pp. 47-60). University Michigan Museum Zoology: Ann Arbor. translated R : Claude, J. (2008). Morphometrics R. (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":null,"dir":"Reference","previous_headings":"","what":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"Helps read .txt files created StereoMorph (x; y) coordinates Momocs objects. Can applied 'curves' 'ldk' text files.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"","code":"import_StereoMorph_curve1(path) import_StereoMorph_curve(path, names) import_StereoMorph_ldk1(path) import_StereoMorph_ldk(path, names)"},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"path toward single file folder containing .txt files produced StereoMorph names feed lf_structure","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"list class Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"*1 functions import single .txt file. counterpart ('1') work path indicates folder, .e. 'curves' 'ldk'. return list Opn Ldk objects, respectively. Please hesitate contact particular case need something.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outline coordinates from multiple .jpg files — import_jpg","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"function used import outline coordinates built around import_jpg1.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"","code":"import_jpg( jpg.paths = .lf.auto(), auto.notcentered = TRUE, fun.notcentered = NULL, threshold = 0.5 )"},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"jpg.paths vector paths corresponding .jpg files import. provided (NULL), switches automatic version. See Details . auto.notcentered logical TRUE random locations used . one (assumed) within shape (black pixel); FALSE locator called, click point within shape. fun.notcentered NULL default. shapes centered random pick black pixel satisfactory. See import_jpg1 help examples. threshold threshold value use binarize images. , pixels turned 1, 0.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"list matrices (x; y) coordinates can passed ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"see import_jpg1 important informations outlines extracted, import_Conte algorithm . jpg.paths provided (NULL), select .jpg file folder contains files. outlines imported .","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"Note function deprecated Momocs Momacs Momit fully operationnal. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"","code":"# \\donttest{ lf <- list.files('/foo/jpegs', full.names=TRUE) coo <- import_jpg(lf) #> Extracting 0.jpg outlines... #> Done in 0 secs Out(coo) #> empty Out coo <- import_jpg() #> Warning: unable to translate '<8f>' to a wide string #> Warning: input string 1 is invalid #> Extracting 0.jpg outlines... #> Done in 0 secs # }"},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outline coordinates from a single .jpg file — import_jpg1","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"Used import outline coordinates .jpg files. function used single images wrapped import_jpg. relies import_Conte","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"","code":"import_jpg1( jpg.path, auto.notcentered = TRUE, fun.notcentered = NULL, threshold = 0.5, ... )"},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"jpg.path vector paths corresponding .jpg files import, obtained list.files. auto.notcentered logical TRUE random locations used one (assumed) within shape (corresponds black pixel) middle point black; FALSE locator called, click point within shape. fun.notcentered NULL default can accept function , passed imagematrix returns numeric length two corresponds starting point imagematrix Conte algorithm. instruction wraps , function may wrong proposing starting position. See examples quick example. threshold threshold value use binarize images. , pixels turned 1, 0. ... arguments passed read.table, eg. 'skip', 'dec', etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"matrix (x; y) coordinates can passed ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"jpegs can provided either RVB 8-bit greylevels monochrome. function binarizes pixels values using 'threshold' argument. try start apply import_Conte algorithm center image 'looking' downwards first black/white 'frontier' pixels. point first outlines. latter may useful align manually images want retain information consequent morphometric analyses. point center image within shape, .e. 'white' two choices defined 'auto.notcentered' argument. TRUE, random starting points tried 'black' within shape; FALSE asked click point within shape. pixels borders white, functions adds 2-pixel border white pixels; otherwise import_Conte fail return error. Finally, remember images working directory, list.files must called argument full.names=TRUE! Note use fun.notcentered argument probably leads serious headaches probably imply dissection functions: import_Conte, img_plot import_jpg ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":null,"dir":"Reference","previous_headings":"","what":"Import a tps file — import_tps","title":"Import a tps file — import_tps","text":"returns list coordinates, curves, scale","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import a tps file — import_tps","text":"","code":"import_tps(tps.path, curves = TRUE) tps2coo(tps, curves = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import a tps file — import_tps","text":"tps.path lines, typically readLines, describing single shape tps-like format. need manually build Coo object : eg (coo=your_list$coo). curves logical whether read curves, tps lines single tps file tps2coo used import_tps may useful data import. provided lines (eg readLines) tps-like description (\"LM\", \"CURVES\", etc.) returns list coordinates, curves, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import a tps file — import_tps","text":"list components: coo matrix coordinates; cur list matrices; scale scale numeric.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import a tps file — import_tps","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":null,"dir":"Reference","previous_headings":"","what":"Import coordinates from a .txt file — import_txt","title":"Import coordinates from a .txt file — import_txt","text":"wrapper around read.table can used import outline/landmark coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import coordinates from a .txt file — import_txt","text":"","code":"import_txt(txt.paths = .lf.auto(), ...)"},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import coordinates from a .txt file — import_txt","text":"txt.paths vector paths corresponding .txt files import. provided (NULL), switches automatic version, just import_jpg. See Details . ... arguments passed read.table, eg. 'skip', 'dec', etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import coordinates from a .txt file — import_txt","text":"list matrix(ces) (x; y) coordinates can passed , Opn Ldk.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import coordinates from a .txt file — import_txt","text":"Columns named .txt files. can tune using ... argument. Define read.table arguments allow import single file, pass function, ie .txt file header (eg ('x', 'y')), forget header=TRUE.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import coordinates from a .txt file — import_txt","text":"Note function deprecated Momocs Momacs Momit fully operationnal. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":null,"dir":"Reference","previous_headings":"","what":"Graphical inspection of shapes — inspect","title":"Graphical inspection of shapes — inspect","text":"Allows plot shapes, individually, Coo (, Opn Ldk) objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graphical inspection of shapes — inspect","text":"","code":"inspect(x, id, ...)"},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graphical inspection of shapes — inspect","text":"x Coo object id id shape plot, provided random shape plotted. passed '' shapes plotted, one one. ... arguments passed coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graphical inspection of shapes — inspect","text":"interactive plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graphical inspection of shapes — inspect","text":"","code":"if (FALSE) { inspect(bot, 5) inspect(bot) inspect(bot, 5, pch=3, points=TRUE) # an example of '...' use }"},{"path":"http://momx.github.io/Momocs/reference/is.html","id":null,"dir":"Reference","previous_headings":"","what":"Class and component testers — is","title":"Class and component testers — is","text":"Class testers test classes object given class. instance is_PCA PCA object (classes PCA prcomp) return TRUE. Component testers check there_is particular component (eg $fac, etc.) object.","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Class and component testers — is","text":"","code":"is_Coo(x) is_PCA(x) is_LDA(x) is_Out(x) is_Opn(x) is_Ldk(x) is_Coe(x) is_OutCoe(x) is_OpnCoe(x) is_LdkCoe(x) is_TraCoe(x) is_shp(x) is_fac(x) is_ldk(x) is_slidings(x) is_links(x)"},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Class and component testers — is","text":"x object test","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Class and component testers — is","text":"logical","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Class and component testers — is","text":"","code":"is_Coo(bot) #> [1] TRUE is_Out(bot) #> [1] TRUE is_Ldk(bot) #> [1] FALSE is_ldk(hearts) # mind the capitals! #> [1] TRUE"},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":null,"dir":"Reference","previous_headings":"","what":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"Returns TRUE/FALSE whether sd angles successive radii /thesh","code":""},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"","code":"is_equallyspacedradii(coo, thres)"},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"coo matrix (x; y) coordinates Coo object. thres numeric threshold (arbitrarily pi/90, eg 2 degrees, default)","code":""},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"single vector logical. NA returned, coordinates likely identical, least x y.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"","code":"bot[1] %>% is_equallyspacedradii #> [1] NA bot[1] %>% coo_samplerr(36) %>% is_equallyspacedradii #> [1] NA # higher tolerance but wrong bot[1] %>% coo_samplerr(36) %>% is_equallyspacedradii(thres=5*2*pi/360) #> [1] NA # coo_interpolate is a better option bot[1] %>% coo_interpolate(1200) %>% coo_samplerr(36) %>% is_equallyspacedradii #> [1] NA # Coo method bot %>% coo_interpolate(360) %>% coo_samplerr(36) %>% is_equallyspacedradii #> brahma caney chimay corona deusventrue #> NA NA NA NA NA #> duvel franziskaner grimbergen guiness hoegardeen #> NA NA NA NA NA #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> NA NA NA NA NA #> pecheresse sierranevada tanglefoot tauro westmalle #> NA NA NA NA NA #> amrut ballantines bushmills chivas dalmore #> NA NA NA NA NA #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> NA NA NA NA NA #> jb johnniewalker magallan makersmark oban #> NA NA NA NA NA #> oldpotrero redbreast tamdhu wildturkey yoichi #> NA NA NA NA NA"},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr layers for multivariate plots — layers","title":"grindr layers for multivariate plots — layers","text":"Useful layers building custom mutivariate plots using cheapbabi approach. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr layers for multivariate plots — layers","text":"","code":"layer_frame(x, center_origin = TRUE, zoom = 0.9) layer_axes(x, col = \"#999999\", lwd = 1/2, ...) layer_ticks(x, col = \"#333333\", cex = 3/4, lwd = 3/4, ...) layer_grid(x, col = \"#999999\", lty = 3, grid = 3, ...) layer_box(x, border = \"#e5e5e5\", ...) layer_fullframe(x, ...) layer_points(x, pch = 20, cex = 4/log1p(nrow(x$xy)), transp = 0, ...) layer_ellipses(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_ellipsesfilled(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_ellipsesaxes(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_chull(x, ...) layer_chullfilled(x, alpha = 0.8, ...) layer_stars(x, alpha = 0.5, ...) layer_delaunay(x, ...) layer_density( x, levels_density = 20, levels_contour = 4, alpha = 1/3, n = 200, density = TRUE, contour = TRUE ) layer_labelpoints( x, col = par(\"fg\"), cex = 2/3, font = 1, abbreviate = FALSE, ... ) layer_labelgroups( x, col = par(\"fg\"), cex = 3/4, font = 2, rect = TRUE, alpha = 1/4, abbreviate = FALSE, ... ) layer_rug(x, size = 1/200, ...) layer_histogram_2(x, freq = FALSE, breaks, split = FALSE, transp = 0) layer_density_2(x, bw, split = FALSE, rug = TRUE, transp = 0) layer_title(x, title = \"\", cex = 3/4, ...) layer_axesnames(x, cex = 3/4, name = \"Axis\", ...) layer_eigen(x, nb_max = 5, cex = 1/2, ...) layer_axesvar(x, cex = 3/4, ...) layer_legend(x, probs = seq(0, 1, 0.25), cex = 3/4, ...)"},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr layers for multivariate plots — layers","text":"x list, typically returned plot_PCA center_origin logical whether center origin (default TRUE) zoom numeric change zoom (default 0.9) col color (hexadecimal) use drawing components lwd linewidth drawing components ... additional options feed core functions layer cex use drawing components lty linetype drawing components grid numeric number grid draw border color (hexadecimal) use draw border pch use drawing components transp transparency use (min: 0 defaut:0 max:1) conf numeric 0 1 confidence ellipses alpha numeric 0 1 transparency components levels_density numeric number levels use feed MASS::kde2d levels_contour numeric number levels use feed graphics::contour n numeric number grid points feed MASS::kde2d density logical whether draw density estimate contour logical whether draw contour lines font feed text abbreviate logical whether abbreviate names rect logical whether draw rectangle names size numeric fraction graphical window (default: 1/200) freq logicalto feed[hist] (default:FALSE`) breaks feed hist (default: calculated pooled values) split logical whether split two distributions two plots bw feed density (default: stats::bw.nrd0) rug logical whether add rug (default: TRUE) title add plot (default \"\") name use axes (default \"Axis\") nb_max numeric number eigen values display (default 5) probs numeric sequence feed stats::quantile indicate draw ticks legend labels","code":""},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr layers for multivariate plots — layers","text":"drawing layer","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":null,"dir":"Reference","previous_headings":"","what":"Morphospace layers — layers_morphospace","title":"Morphospace layers — layers_morphospace","text":"Used internally plot_PCA, plot_LDA, etc. may useful elsewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Morphospace layers — layers_morphospace","text":"","code":"layer_morphospace_PCA( x, position = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb = 12, nr = 6, nc = 5, rotate = 0, size = 0.9, col = \"#999999\", flipx = FALSE, flipy = FALSE, draw = TRUE ) layer_morphospace_LDA( x, position = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb = 12, nr = 6, nc = 5, rotate = 0, size = 0.9, col = \"#999999\", flipx = FALSE, flipy = FALSE, draw = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Morphospace layers — layers_morphospace","text":"x layered PCA LDA. Typically, object returned plot_PCA plot_LDA position one range, full, circle, xy, range_axes, full_axes feed morphospace_positions (default: range) nb numeric total number shapes position=\"circle\" (default: 12) nr numeric number rows position shapes (default: 6) nc numeric number columns position shapes (default 5) rotate numeric angle (radians) rotate shapes displayed morphospace (default: 0) size numeric size use feed coo_template (default: 0.9) col color draw shapes (default: #999999) flipx logical whether flip shapes x-axis (default: FALSE) flipy logical whether flip shapes y-axis (default: FALSE) draw logical whether draw shapes (default: TRUE)","code":""},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Morphospace layers — layers_morphospace","text":"drawing layer","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks 'ldk' shapes — ldk_check","title":"Checks 'ldk' shapes — ldk_check","text":"simple utility, used internally, mostly Ldk methods, graphical functions, notably l2a. Returns array landmarks arranged (nb.ldk) x (x; y) x (nb.shapes), passed either list, matrix array coordinates. list provided, checks number landmarks consistent.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks 'ldk' shapes — ldk_check","text":"","code":"ldk_check(ldk)"},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks 'ldk' shapes — ldk_check","text":"ldk matrix (x; y) coordinates, list, array.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks 'ldk' shapes — ldk_check","text":"array (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks 'ldk' shapes — ldk_check","text":"","code":"#coo_check('Not a shape') #coo_check(matrix(1:10, ncol=2)) #coo_check(list(x=1:5, y=6:10))"},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws convex hulls around landmark positions — ldk_chull","title":"Draws convex hulls around landmark positions — ldk_chull","text":"wrapper uses coo_chull","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws convex hulls around landmark positions — ldk_chull","text":"","code":"ldk_chull(ldk, col = \"grey40\", lty = 1)"},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws convex hulls around landmark positions — ldk_chull","text":"ldk array (list) landmarks col color drawing convex hull lty lty drawing convex hulls","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws convex hulls around landmark positions — ldk_chull","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws convex hulls around landmark positions — ldk_chull","text":"","code":"coo_plot(MSHAPES(wings)) ldk_chull(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws confidence ellipses for landmark positions — ldk_confell","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"Draws confidence ellipses landmark positions","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"","code":"ldk_confell( ldk, conf = 0.5, col = \"grey40\", ell.lty = 1, ax = TRUE, ax.lty = 2 )"},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"ldk array (list) landmarks conf confidence level (normal quantile, 0.5 default) col color ellipse ell.lty lty ellipse ax logical whether draw ellipses axes ax.lty lty ellipses axes","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"","code":"coo_plot(MSHAPES(wings)) ldk_confell(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws kernel density contours around landmark — ldk_contour","title":"Draws kernel density contours around landmark — ldk_contour","text":"Using kde2d MASS package.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws kernel density contours around landmark — ldk_contour","text":"","code":"ldk_contour(ldk, nlevels = 5, grid.nb = 50, col = \"grey60\")"},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws kernel density contours around landmark — ldk_contour","text":"ldk array (list) landmarks nlevels number contour lines grid.nb grid.nb col color drawing contour lines","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws kernel density contours around landmark — ldk_contour","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws kernel density contours around landmark — ldk_contour","text":"","code":"coo_plot(MSHAPES(wings)) ldk_contour(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":null,"dir":"Reference","previous_headings":"","what":"Add landmarks labels — ldk_labels","title":"Add landmarks labels — ldk_labels","text":"Add landmarks labels","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add landmarks labels — ldk_labels","text":"","code":"ldk_labels(ldk, d = 0.05, cex = 2/3, ...)"},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add landmarks labels — ldk_labels","text":"ldk matrix (x; y) coordinates: plot labels d far coordinates, (centroid-landmark) segment cex cex label ... additional parameters fed text","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add landmarks labels — ldk_labels","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add landmarks labels — ldk_labels","text":"","code":"coo_plot(wings[1]) ldk_labels(wings[1]) # closer and smaller coo_plot(wings[1]) ldk_labels(wings[1], d=0.05, cex=0.5)"},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws links between landmarks — ldk_links","title":"Draws links between landmarks — ldk_links","text":"Cosmetics useful visualize shape variation.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws links between landmarks — ldk_links","text":"","code":"ldk_links(ldk, links, ...)"},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws links between landmarks — ldk_links","text":"ldk matrix (x; y) coordinates links matrix links. first column starting-id, second column ending-id (id= number coordinate) ... additional parameters fed segments","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws links between landmarks — ldk_links","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":null,"dir":"Reference","previous_headings":"","what":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"filenames consistently named character serating factors, every individual including belonging levels, e.g.: 001_speciesI_siteA_ind1_dorsalview 002_speciesI_siteA_ind2_lateralview etc., function returns data.frame can passed , Opn, Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"","code":"lf_structure(lf, names = character(), split = \"_\", trim.extension = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"lf list (names used, except list import_tps case names(lf$coo) used) list filenames, characters, typically obtained list.files. Alternatively, path folder containing files. Actually, lf length 1 (single character), function assumes path list.files . names names groups, vector characters length corresponds number groups. split character, spliting factor used file names. trim.extension logical. Whether remove last characters filenames, typically extension, e.g. '.jpg'.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"data.frame , every individual, corresponding level every group.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"number groups must consistent across filenames.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":", view, good practice 'store' grouping structure filenames, course mandatory. Note also can: ) import_jpg save list, say 'foo'; ii) pass 'names(foo)' lf_structure. See Momocs' vignette illustration. Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates links (all pairwise combinations) between landmarks — links_all","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"Creates links (pairwise combinations) landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"","code":"links_all(coo)"},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"coo matrix (list) (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"matrix can passed ldk_links, etc. columns row ids original shape.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"","code":"w <- wings[1] coo_plot(w) links <- links_all(w) ldk_links(w, links)"},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"Creates links (Delaunay triangulation) landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"","code":"links_delaunay(coo)"},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"coo matrix (list) (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"matrix can passed ldk_links, etc. columns row ids original shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"uses delaunayn geometry package.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"","code":"w <- wings[1] coo_plot(w, poly=FALSE) links <- links_delaunay(w) ldk_links(w, links)"},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":null,"dir":"Reference","previous_headings":"","what":"Measures shape descriptors — measure","title":"Measures shape descriptors — measure","text":"Calculates shape descriptors Coo objects. function returns scalar fed coordinates can passed naturally Momocs (pick apropos(\"coo_\")). Functions without arguments (eg coo_area) passed without brackets functions arguments (eg d) passed \"entirely\". See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Measures shape descriptors — measure","text":"","code":"measure(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Measures shape descriptors — measure","text":"x Coo object, list shapes, shape matrix. ... list functions. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Measures shape descriptors — measure","text":"TraCoe object, raw data.frame","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Measures shape descriptors — measure","text":"","code":"bm <- measure(bot, coo_area, coo_perim) bm #> A TraCoe object -------------------- #> - $coe: 40 shapes described with 2 variables #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows bm$coe #> # A tibble: 40 × 2 #> area perim #> #> 1 234515 2482. #> 2 201056. 2269. #> 3 119460. 1578. #> 4 119568. 1817. #> 5 165736. 2066. #> 6 114015 1487. #> 7 149503 1954. #> 8 147642. 1826. #> 9 130178. 1751. #> 10 219548 2399. #> # ℹ 30 more rows # how to use arguments, eg with the d() function measure(wings, coo_area, d(1, 3), d(4, 5)) #> A TraCoe object -------------------- #> - $coe: 127 shapes described with 3 variables #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows # alternatively, to get a data_frame measure(bot$coo, coo_area, coo_perim) #> # A tibble: 40 × 2 #> area perim #> #> 1 234515 2482. #> 2 201056. 2269. #> 3 119460. 1578. #> 4 119568. 1817. #> 5 165736. 2066. #> 6 114015 1487. #> 7 149503 1954. #> 8 147642. 1826. #> 9 130178. 1751. #> 10 219548 2399. #> # ℹ 30 more rows # and also, to get a data_frame (one row) measure(bot[1], coo_area, coo_perim) #> # A tibble: 1 × 2 #> area perim #> #> 1 234515 2482."},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"Calculates nice positions plane drawing shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"","code":"morphospace_positions( xy, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb.shp = 12, nr.shp = 6, nc.shp = 5, circle.r.shp )"},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"xy matrix points typically PCA multivariate method morphospace can calculated pos.shp shapes positionned: range xy, full extent plane, circle rosewind, xy values provided, range_axes range xy axes, full_axes thing (0.85) range axes. can also directly pass matrix (data.frame) columns named (\"x\", \"y\"). nb.shp total number shapes nr.shp number rows position shapes nc.shp number cols position shapes circle.r.shp circle, radius","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"data.frame positions","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"See plot.PCA self-speaking examples","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots mosaics of shapes. — mosaic_engine","title":"Plots mosaics of shapes. — mosaic_engine","text":"soon replace panel. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots mosaics of shapes. — mosaic_engine","text":"","code":"mosaic_engine( coo_list, dim, asp = 1, byrow = TRUE, fromtop = TRUE, sample = 60, relatively = FALSE, template_size = 0.92 ) mosaic(x, ...) # S3 method for Out mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_outlines, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... ) # S3 method for Opn mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_curves, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... ) # S3 method for Ldk mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_landmarks, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots mosaics of shapes. — mosaic_engine","text":"coo_list list shapes dim numeric length 2, desired dimensions rows columns asp numeric yx ratio used calculate dim (1 default). byrow logical whether order shapes rows fromtop logical whether order shapes top sample numeric number points coo_sample relatively logical TRUE use coo_template_relatively , FALSE(default) coo_template. words, whether preserve size . template_size numeric feed coo_template(_relatively). useful add padding around shapes default value (0.95) lowered. x Coo object ... additional arguments feed main drawer number shapes > 1000 (default: 64). non-numeric (eg FALSE) sample. f factor specification feed fac_dispatcher pal one palettes paper_fun papers function (default: paper) draw_fun one drawers pile.list legend logical whether draw legend (improved versions)","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots mosaics of shapes. — mosaic_engine","text":"list templated translated shapes","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots mosaics of shapes. — mosaic_engine","text":"","code":"# On Out --- bot %>% mosaic bot %>% mosaic(~type) # As with other grindr functions you can continue the pipe bot %>% mosaic(~type, asp=0.5) %>% draw_firstpoint # On Opn ---- same grammar olea %>% mosaic(~view+var, paper_fun=paper_dots) # On Ldk mosaic(wings, ~group, pal=pal_qual_Dark2, pch=3) # On Out with different sizes # would work on other Coo too shapes2 <- shapes sizes <- runif(30, 1, 2) shapes2 %>% mosaic(relatively=FALSE) shapes2 %>% mosaic(relatively=TRUE) %>% draw_centroid()"},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":null,"dir":"Reference","previous_headings":"","what":"Add new variables — mutate","title":"Add new variables — mutate","text":"Add new variables $fac. See examples ?dplyr::mutate.","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add new variables — mutate","text":"","code":"mutate(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add new variables — mutate","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add new variables — mutate","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add new variables — mutate","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add new variables — mutate","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk mutate(olea, id=factor(1:length(olea))) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 5 classifiers (in $fac): #> # A tibble: 210 × 5 #> var domes view ind id #> #> 1 Aglan cult VD O10 1 #> 2 Aglan cult VL O10 2 #> 3 Aglan cult VD O11 3 #> 4 Aglan cult VL O11 4 #> 5 Aglan cult VD O12 5 #> 6 Aglan cult VL O12 6 #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate natural polynomial fits on open outlines — npoly","title":"Calculate natural polynomial fits on open outlines — npoly","text":"Calculates natural polynomial coefficients, linear model fit (see lm), matrix (x; y) coordinates Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate natural polynomial fits on open outlines — npoly","text":"","code":"npoly(x, ...) # S3 method for default npoly(x, degree, ...) # S3 method for Opn npoly( x, degree, baseline1 = c(-0.5, 0), baseline2 = c(0.5, 0), nb.pts = 120, ... ) # S3 method for list npoly(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate natural polynomial fits on open outlines — npoly","text":"x matrix (list) (x; y) coordinates Opn object ... useless degree polynomial degree fit (Intercept also returned) baseline1 numeric \\((x; y)\\) coordinates first baseline default \\((x= -0.5; y=0)\\) baseline2 numeric \\((x; y)\\) coordinates second baseline default \\((x= 0.5; y=0)\\) nb.pts number points sample calculate polynomials","code":""},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate natural polynomial fits on open outlines — npoly","text":"applied single shape, list components: coeff coefficients (including intercept) ortho whether orthogonal natural polynomials fitted degree degree fit (retrieved coeff though) baseline1 first baseline point (far first point) baseline2 second baseline point (far last point) r2 r2 fit mod raw lm model otherwise, OpnCoe object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate natural polynomial fits on open outlines — npoly","text":"","code":"data(olea) o <- olea[1] op <- opoly(o, degree=4) op #> $coeff #> (Intercept) x1 x2 x3 x4 #> 0.20937101 0.01991936 -0.95319289 -0.03075138 -0.11975200 #> #> $ortho #> [1] TRUE #> #> $degree #> [1] 4 #> #> $baseline1 #> [1] -0.5 0.0 #> #> $baseline2 #> [1] 0.5 0.0 #> #> $r2 #> [1] 0.9986415 #> #> $mod #> #> Call: #> lm(formula = coo[, 2] ~ x) #> #> Coefficients: #> (Intercept) x1 x2 x3 x4 #> 0.20937 0.01992 -0.95319 -0.03075 -0.11975 #> #> # shape reconstruction opi <- opoly_i(op) coo_plot(o) coo_draw(opi, border=\"red\") # R2 for degree 1 to 10 r <- numeric() for (i in 1:10) { r[i] <- npoly(o, degree=i)$r2 } plot(2:10, r[2:10], type='b', pch=20, col='red', main='R2 / degree')"},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate orthogonal polynomial fits on open outlines — opoly","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"Calculates orthogonal polynomial coefficients, linear model fit (see lm), matrix (x; y) coordinates Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"","code":"opoly(x, ...) # S3 method for default opoly(x, degree, ...) # S3 method for Opn opoly( x, degree, baseline1 = c(-0.5, 0), baseline2 = c(0.5, 0), nb.pts = 120, ... ) # S3 method for list opoly(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"x matrix (list) (x; y) coordinates ... useless degree polynomial degree fit (Intercept also returned) baseline1 numeric \\((x; y)\\) coordinates first baseline default \\((x= -0.5; y=0)\\) baseline2 numeric \\((x; y)\\) coordinates second baseline default \\((x= 0.5; y=0)\\) nb.pts number points sample calculate polynomials","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"list components applied single shape: coeff coefficients (including intercept) ortho whether orthogonal natural polynomials fitted degree degree fit (retrieved coeff though) baseline1 first baseline point (far first point) baseline2 second baseline point (far last point) r2 r2 fit mod raw lm model otherwise OpnCoe object.","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"Orthogonal polynomials sometimes called Legendre's polynomials. preferred natural polynomials since adding degree change lower orders coefficients.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"","code":"data(olea) o <- olea[1] op <- opoly(o, degree=4) op #> $coeff #> (Intercept) x1 x2 x3 x4 #> 0.20937101 0.01991936 -0.95319289 -0.03075138 -0.11975200 #> #> $ortho #> [1] TRUE #> #> $degree #> [1] 4 #> #> $baseline1 #> [1] -0.5 0.0 #> #> $baseline2 #> [1] 0.5 0.0 #> #> $r2 #> [1] 0.9986415 #> #> $mod #> #> Call: #> lm(formula = coo[, 2] ~ x) #> #> Coefficients: #> (Intercept) x1 x2 x3 x4 #> 0.20937 0.01992 -0.95319 -0.03075 -0.11975 #> #> # shape reconstruction opi <- opoly_i(op) coo_plot(o) coo_draw(opi) lines(opi, col='red') # R2 for degree 1 to 10 r <- numeric() for (i in 1:10) { r[i] <- opoly(o, degree=i)$r2 } plot(2:10, r[2:10], type='b', pch=20, col='red', main='R2 / degree')"},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Partial Procrustes alignment between two shapes — pProcrustes","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"Directly borrowed Claude (2008), called pPsup .","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"","code":"pProcrustes(coo1, coo2)"},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"coo1 Configuration matrix superimposed onto centered preshape coo2. coo2 Reference configuration matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"list components coo1 superimposed centered preshape coo1 onto centered preshape coo2 coo2 centered preshape coo2 rotation rotation matrix DP partial Procrustes distance coo1 coo2 rho trigonometric Procrustes distance.","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":null,"dir":"Reference","previous_headings":"","what":"Color palettes — palettes","title":"Color palettes — palettes","text":"colorblind friendly RColorBrewer palettes recreated without number colors limitation transparency support thanks pal_alpha can used alone. Also, viridis palettes (see package CRAN), yet color ramps borrowed Momocs depend . Also, pal_qual_solarized based Solarized: https://ethanschoonover.com/solarized/ pal_seq_grey shades grey grey10 grey90.","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Color palettes — palettes","text":"","code":"pal_alpha(cols, transp = 0) pal_manual(cols, transp = 0) pal_qual_solarized(n, transp = 0) pal_seq_grey(n, transp = 0) pal_div_BrBG(n, transp = 0) pal_div_PiYG(n, transp = 0) pal_div_PRGn(n, transp = 0) pal_div_PuOr(n, transp = 0) pal_div_RdBu(n, transp = 0) pal_div_RdYlBu(n, transp = 0) pal_qual_Dark2(n, transp = 0) pal_qual_Paired(n, transp = 0) pal_qual_Set2(n, transp = 0) pal_seq_Blues(n, transp = 0) pal_seq_BuGn(n, transp = 0) pal_seq_BuPu(n, transp = 0) pal_seq_GnBu(n, transp = 0) pal_seq_Greens(n, transp = 0) pal_seq_Greys(n, transp = 0) pal_seq_Oranges(n, transp = 0) pal_seq_OrRd(n, transp = 0) pal_seq_PuBu(n, transp = 0) pal_seq_PuBuGn(n, transp = 0) pal_seq_PuRd(n, transp = 0) pal_seq_Purples(n, transp = 0) pal_seq_RdPu(n, transp = 0) pal_seq_Reds(n, transp = 0) pal_seq_YlGn(n, transp = 0) pal_seq_YlGnBu(n, transp = 0) pal_seq_YlOrBr(n, transp = 0) pal_seq_YlOrRd(n, transp = 0) pal_seq_magma(n, transp = 0) pal_seq_inferno(n, transp = 0) pal_seq_plasma(n, transp = 0) pal_seq_viridis(n, transp = 0) pal_qual(n, transp = 0) pal_seq(n, transp = 0) pal_div(n, transp = 0)"},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Color palettes — palettes","text":"cols color(s) hexadecimal values transp numeric 0 1 (0, eg opaque, default) n numeric number colors","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Color palettes — palettes","text":"palette function","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Color palettes — palettes","text":"Default color palettes currently: pal_qual=pal_qual_Set2 pal_seq=pal_seq_viridis pal_div=pal_div_RdBu","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Color palettes — palettes","text":"RColorBrewer palettes happy n lower 3 given number palette. case, functions create color palette colorRampPalette return colors even .","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Color palettes — palettes","text":"","code":"pal_div_BrBG(5) %>% barplot(rep(1, 5), col=.) pal_div_BrBG(5, 0.5) %>% barplot(rep(1, 5), col=.)"},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Family picture of shapes — panel","title":"Family picture of shapes — panel","text":"Plots outlines, side side, Coo (, Opn Ldk) objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family picture of shapes — panel","text":"","code":"panel(x, ...) # S3 method for Out panel( x, dim, cols, borders, fac, palette = col_summer, coo_sample = 120, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col, ... ) # S3 method for Opn panel( x, cols, borders, fac, palette = col_summer, coo_sample = 120, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col, ... ) # S3 method for Ldk panel( x, cols, borders, fac, palette = col_summer, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col = \"#333333\", ... )"},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family picture of shapes — panel","text":"x Coo object plot. ... additional arguments feed generic plot dim coo_listpanel: numeric length 2 specifying dimensions panel cols vector colors drawing outlines. Either single value length exactly equal number coordinates. borders vector colors drawing borders. Either single value length exactly equals number coordinates. fac factor within $fac slot colors palette color palette coo_sample NULL number point per shape display (plot quickly) names whether plot names . TRUE uses shape names, something fac_dispatcher cex.names cex names points logical (Ldk) whether draw points points.pch (Ldk) pch points points.cex (Ldk) cex points points.col (Ldk) col points","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family picture of shapes — panel","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Family picture of shapes — panel","text":"want reorder shapes according factor, use arrange.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family picture of shapes — panel","text":"","code":"panel(mosquito, names=TRUE, cex.names=0.5) panel(olea) panel(bot, c(4, 10)) # an illustration of the use of fac panel(bot, fac='type', palette=col_spring, names=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr papers for shape plots — papers","title":"grindr papers for shape plots — papers","text":"Papers use drawers building custom shape plots using grindr approach. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr papers for shape plots — papers","text":"","code":"paper(coo, ...) paper_white(coo) paper_grid(coo, grid = c(10, 5), cols = c(\"#ffa500\", \"#e5e5e5\"), ...) paper_chess(coo, n = 50, col = \"#E5E5E5\") paper_dots(coo, pch = 20, n = 50, col = \"#7F7F7F\")"},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr papers for shape plots — papers","text":"coo single shape Coo object ... arguments feed plotting function within paper function grid numeric length 2 (roughly) specify number majors lines, number minor lines within two major ones cols colors (hexadecimal preferred) use grid drawing n numeric number squares chessboard col color (hexadecimal) use chessboard drawing pch use dots","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr papers for shape plots — papers","text":"drawing layer","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"grindr papers for shape plots — papers","text":"approach (soon) replace coo_plot friends versions. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":null,"dir":"Reference","previous_headings":"","what":"Permutes and breed Coe (and others) objects — perm","title":"Permutes and breed Coe (and others) objects — perm","text":"methods applies permutations column-wise coe Coe object relies function can used matrix. Coe object, uses sample every column (row) (without) replacement.","code":""},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Permutes and breed Coe (and others) objects — perm","text":"","code":"perm(x, ...) # S3 method for default perm(x, margin = 2, size, replace = TRUE, ...) # S3 method for Coe perm(x, size, replace = TRUE, ...)"},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Permutes and breed Coe (and others) objects — perm","text":"x object permute ... useless margin numeric whether 1 2 (rows columns) size numeric required size final object, size default. replace logical, whether use sample replacement","code":""},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Permutes and breed Coe (and others) objects — perm","text":"Coe object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Permutes and breed Coe (and others) objects — perm","text":"","code":"m <- matrix(1:12, nrow=3) m #> [,1] [,2] [,3] [,4] #> [1,] 1 4 7 10 #> [2,] 2 5 8 11 #> [3,] 3 6 9 12 perm(m, margin=2, size=5) #> [,1] [,2] [,3] [,4] #> [1,] 3 4 9 11 #> [2,] 1 6 8 12 #> [3,] 3 5 7 11 #> [4,] 1 6 9 12 #> [5,] 3 4 8 12 perm(m, margin=1, size=10) #> [,1] [,2] [,3] #> [1,] 1 2 9 #> [2,] 10 8 3 #> [3,] 10 5 3 #> [4,] 10 11 6 #> [5,] 1 5 9 #> [6,] 4 5 9 #> [7,] 1 8 6 #> [8,] 7 11 3 #> [9,] 7 2 12 #> [10,] 4 8 3 bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.m <- perm(bot.f, 80) bot.m #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 80 outlines described, 12 harmonics #> # A tibble: 0 × 0"},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":null,"dir":"Reference","previous_headings":"","what":"Graphical pile of shapes — pile","title":"Graphical pile of shapes — pile","text":"Pile shapes graphical window. Useful check normalization terms size, position, rotation, first point, etc. , essentially, shortcut around paper + drawers grindr family.","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graphical pile of shapes — pile","text":"","code":"pile(coo, f, sample, subset, pal, paper_fun, draw_fun, transp, ...) # S3 method for default pile( coo, f, sample, subset, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for list pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for array pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_landmarks, transp = 0, ... ) # S3 method for Out pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_outlines, transp = 0, ... ) # S3 method for Opn pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for Ldk pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_landmarks, transp = 0, ... )"},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graphical pile of shapes — pile","text":"coo single shape Coo object f factor specification sample numeric number points coo_sample number shapes > 1000 (default: 64). non-numeric (eg FALSE) sample. subset numeric draw number (randomly chosen) shapes number shapes > 1000 (default: 1000) non-numeric (eg FALSE) sample. pal palette among palettes (default: pal_qual) paper_fun papers function (default: paper) draw_fun one drawers pile.list transp numeric transparency (default:adjusted, min:0, max=0) ... arguments feed core drawer, depending object","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graphical pile of shapes — pile","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Graphical pile of shapes — pile","text":"Large Coo sampled, terms number shapes points drawn.","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Graphical pile of shapes — pile","text":"variation plot called stack Momocs 1.2.5","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graphical pile of shapes — pile","text":"","code":"# all Coo are supported with sensible defaults pile(bot) # outlines pile(olea, ~var, pal=pal_qual_Dark2, paper_fun=paper_grid) # curves pile(wings) # landmarks # you can continue the pipe with compatible drawers pile(bot, trans=0.9) %>% draw_centroid # if you are not happy with this, build your own ! # eg see Momocs::pile.Out (no quotes) my_pile <- function(x, col_labels=\"red\", transp=0.5){ x %>% paper_chess(n=100) %>% draw_landmarks(transp=transp) %>% draw_labels(col=col_labels) } # using it wings %>% my_pile(transp=3/4) # and as gridr functions propagate, you can even continue: wings %>% my_pile() %>% draw_centroid(col=\"blue\", cex=5) # method on lists bot$coo %>% pile # it can be tuned when we have a list of landmarks with: wings$coo %>% pile(draw_fun=draw_landmarks) # or on arrays (turn for draw_landmarks) wings$coo %>% l2a %>% #we now have an array pile"},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots Linear Discriminant Analysis — plot.LDA","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Momocs' LDA plotter many graphical options.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"","code":"# S3 method for LDA plot( x, fac = x$fac, xax = 1, yax = 2, points = TRUE, col = \"#000000\", pch = 20, cex = 0.5, palette = col_solarized, center.origin = FALSE, zoom = 1, xlim = NULL, ylim = NULL, bg = par(\"bg\"), grid = TRUE, nb.grids = 3, morphospace = FALSE, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], amp.shp = 1, size.shp = 1, nb.shp = 12, nr.shp = 6, nc.shp = 5, rotate.shp = 0, flipx.shp = FALSE, flipy.shp = FALSE, pts.shp = 60, border.shp = col_alpha(\"#000000\", 0.5), lwd.shp = 1, col.shp = col_alpha(\"#000000\", 0.95), stars = FALSE, ellipses = FALSE, conf.ellipses = 0.5, ellipsesax = TRUE, conf.ellipsesax = c(0.5, 0.9), lty.ellipsesax = 1, lwd.ellipsesax = sqrt(2), chull = FALSE, chull.lty = 1, chull.filled = FALSE, chull.filled.alpha = 0.92, density = FALSE, lev.density = 20, contour = FALSE, lev.contour = 3, n.kde2d = 100, delaunay = FALSE, loadings = FALSE, labelspoints = FALSE, col.labelspoints = par(\"fg\"), cex.labelspoints = 0.6, abbreviate.labelspoints = TRUE, labelsgroups = TRUE, cex.labelsgroups = 0.8, rect.labelsgroups = FALSE, abbreviate.labelsgroups = FALSE, color.legend = FALSE, axisnames = TRUE, axisvar = TRUE, unit = FALSE, eigen = TRUE, rug = TRUE, title = substitute(x), box = TRUE, old.par = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"x object class \"LDA\", typically obtained LDA fac name column id $fac slot, formula combining colum names $fac slot (cf. examples). factor numeric length can also passed fly. xax first PC axis yax second PC axis points logical whether plot points col color points (either global, every level fac every individual, see examples) pch pch points (either global, every level fac every individual, see examples) cex size points palette palette center.origin logical whether center plot onto origin zoom keep distances xlim numeric length two ; provided along ylim, x y lims use ylim numeric length two ; provided along xlim, x y lims use bg color background grid logical whether draw grid nb.grids many morphospace logical whether add morphological space pos.shp passed morphospace_positions, one \"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\". directly matrix positions. See morphospace_positions amp.shp amplification factor shape deformation size.shp size shapes nb.shp (pos.shp=\"circle\") number shapes compass nr.shp (pos.shp=\"full\" \"range) number shapes per row nc.shp (pos.shp=\"full\" \"range) number shapes per column rotate.shp angle radians rotate shapes (several methods, vector angles) flipx.shp , whether apply coo_flipx flipy.shp , whether apply coo_flipy pts.shp number points fro drawing shapes border.shp border color shapes lwd.shp line width shapes col.shp color shapes stars logical whether draw \"stars\" ellipses logical whether draw confidence ellipses conf.ellipses numeric quantile (bivariate gaussian) confidence ellipses ellipsesax logical whether draw ellipse axes conf.ellipsesax one numeric, quantiles (bivariate gaussian) ellipses axes lty.ellipsesax yes, lty draw axes lwd.ellipsesax yes, one numeric line widths chull logical whether draw convex hull chull.lty yes, linetype chull.filled logical whether add filled convex hulls chull.filled.alpha numeric alpha transparency density whether add 2d density kernel estimation (based kde2d) lev.density yes, number levels plot (image) contour whether add contour lines based 2d density kernel lev.contour yes, (approximate) number lines draw n.kde2d number bins kde2d, ie 'smoothness' density kernel delaunay logical whether add delaunay 'mesh' points loadings logical whether add loadings every variables labelspoints TRUE rownames used labels, colname $fac can also passed col.labelspoints color labels, otherwise inherited fac cex.labelspoints cex labels abbreviate.labelspoints logical whether abbreviate labelsgroups logical whether add labels groups cex.labelsgroups ifyes, numeric size labels rect.labelsgroups logical whether add rectangle behind groups names abbreviate.labelsgroups logical, whether abbreviate group names color.legend logical whether add (cheap) color legend numeric fac axisnames logical whether add PC names axisvar logical whether draw variance explain unit logical whether add plane unit eigen logical whether draw plot eigen values rug logical whether add rug margins title character name plot box whether draw box around plotting region old.par whether restore old par. Set FALSE want reuse graphical window. ... useless , just fit generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Widely inspired \"layers\" philosophy behind graphical functions ade4 R package.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Morphospaces deprecated far. 99% code shared plot.PCA waiting general rewriting multivariate plotter. See https://github.com/vbonhomme/Momocs/issues/121","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots Principal Component Analysis — plot.PCA","title":"Plots Principal Component Analysis — plot.PCA","text":"Momocs' PCA plotter morphospaces many graphical options.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots Principal Component Analysis — plot.PCA","text":"","code":"# S3 method for PCA plot( x, fac, xax = 1, yax = 2, points = TRUE, col = \"#000000\", pch = 20, cex = 0.5, palette = col_solarized, center.origin = FALSE, zoom = 1, xlim = NULL, ylim = NULL, bg = par(\"bg\"), grid = TRUE, nb.grids = 3, morphospace = TRUE, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], amp.shp = 1, size.shp = 1, nb.shp = 12, nr.shp = 6, nc.shp = 5, rotate.shp = 0, flipx.shp = FALSE, flipy.shp = FALSE, pts.shp = 60, border.shp = col_alpha(\"#000000\", 0.5), lwd.shp = 1, col.shp = col_alpha(\"#000000\", 0.95), stars = FALSE, ellipses = FALSE, conf.ellipses = 0.5, ellipsesax = FALSE, conf.ellipsesax = c(0.5, 0.9), lty.ellipsesax = 1, lwd.ellipsesax = sqrt(2), chull = FALSE, chull.lty = 1, chull.filled = TRUE, chull.filled.alpha = 0.92, density = FALSE, lev.density = 20, contour = FALSE, lev.contour = 3, n.kde2d = 100, delaunay = FALSE, loadings = FALSE, labelspoints = FALSE, col.labelspoints = par(\"fg\"), cex.labelspoints = 0.6, abbreviate.labelspoints = TRUE, labelsgroups = TRUE, cex.labelsgroups = 0.8, rect.labelsgroups = FALSE, abbreviate.labelsgroups = FALSE, color.legend = FALSE, axisnames = TRUE, axisvar = TRUE, unit = FALSE, eigen = TRUE, rug = TRUE, title = substitute(x), box = TRUE, old.par = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots Principal Component Analysis — plot.PCA","text":"x PCA, typically obtained PCA fac name column id $fac slot, formula combining colum names $fac slot (cf. examples). factor numeric length can also passed fly. xax first PC axis yax second PC axis points logical whether plot points col color points (either global, every level fac every individual, see examples) pch pch points (either global, every level fac every individual, see examples) cex size points palette palette center.origin logical whether center plot onto origin zoom keep distances xlim numeric length two ; provided along ylim, x y lims use ylim numeric length two ; provided along xlim, x y lims use bg color background grid logical whether draw grid nb.grids many morphospace logical whether add morphological space pos.shp passed morphospace_positions, one \"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\". directly matrix positions. See morphospace_positions amp.shp amplification factor shape deformation size.shp size shapes nb.shp (pos.shp=\"circle\") number shapes compass nr.shp (pos.shp=\"full\" \"range) number shapes per row nc.shp (pos.shp=\"full\" \"range) number shapes per column rotate.shp angle radians rotate shapes (several methods, vector angles) flipx.shp , whether apply coo_flipx flipy.shp , whether apply coo_flipy pts.shp number points fro drawing shapes border.shp border color shapes lwd.shp line width shapes col.shp color shapes stars logical whether draw \"stars\" ellipses logical whether draw confidence ellipses conf.ellipses numeric quantile (bivariate gaussian) confidence ellipses ellipsesax logical whether draw ellipse axes conf.ellipsesax one numeric, quantiles (bivariate gaussian) ellipses axes lty.ellipsesax yes, lty draw axes lwd.ellipsesax yes, one numeric line widths chull logical whether draw convex hull chull.lty yes, linetype chull.filled logical whether add filled convex hulls chull.filled.alpha numeric alpha transparency density whether add 2d density kernel estimation (based kde2d) lev.density yes, number levels plot (image) contour whether add contour lines based 2d density kernel lev.contour yes, (approximate) number lines draw n.kde2d number bins kde2d, ie 'smoothness' density kernel delaunay logical whether add delaunay 'mesh' points loadings logical whether add loadings every variables labelspoints TRUE rownames used labels, colname $fac can also passed col.labelspoints color labels, otherwise inherited fac cex.labelspoints cex labels abbreviate.labelspoints logical whether abbreviate labelsgroups logical whether add labels groups cex.labelsgroups ifyes, numeric size labels rect.labelsgroups logical whether add rectangle behind groups names abbreviate.labelsgroups logical, whether abbreviate group names color.legend logical whether add (cheap) color legend numeric fac axisnames logical whether add PC names axisvar logical whether draw variance explain unit logical whether add plane unit eigen logical whether draw plot eigen values rug logical whether add rug margins title character name plot box whether draw box around plotting region old.par whether restore old par. Set FALSE want reuse graphical window. ... useless , just fit generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots Principal Component Analysis — plot.PCA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots Principal Component Analysis — plot.PCA","text":"Widely inspired \"layers\" philosophy behind graphical functions ade4 R package.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots Principal Component Analysis — plot.PCA","text":"NAs $fac handled quite experimentally. importantly, early 2018, plan complete rewrite plot.PCA multivariate plotters.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots Principal Component Analysis — plot.PCA","text":"","code":"# \\donttest{ bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) ### Morphospace options plot(bot.p, pos.shp=\"full\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"range\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"xy\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"circle\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"range_axes\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"full_axes\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA ### Passing factors to plot.PCA # 3 equivalent methods plot(bot.p, \"type\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, 1) #> will be deprecated soon, see ?plot_PCA plot(bot.p, ~type) #> will be deprecated soon, see ?plot_PCA # let's create a dummy factor of the correct length # and another added to the $fac with mutate # and a numeric of the correct length f <- factor(rep(letters[1:2], 20)) z <- factor(rep(LETTERS[1:2], 20)) bot %<>% mutate(cs=coo_centsize(.), z=z) bp <- bot %>% efourier %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) # so bp contains type, cs (numeric) and z; not f # yet f can be passed on the fly plot(bp, f) #> will be deprecated soon, see ?plot_PCA # numeric fac are allowed plot(bp, \"cs\", cex=3, color.legend=TRUE) #> will be deprecated soon, see ?plot_PCA # formula allows combinations of factors plot(bp, ~type+z) #> will be deprecated soon, see ?plot_PCA ### other morphometric approaches works the same # open curves op <- npoly(olea, 5) #> 'nb.pts' missing and set to: 91 op.p <- PCA(op) op.p #> A PCA object #> -------------------- #> - 210 shapes #> - $method: [ npoly analysis ] #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, mod, baseline1, baseline2, cuts. plot(op.p, ~ domes + var, morpho=TRUE) # use of formula #> will be deprecated soon, see ?plot_PCA # landmarks wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wpp <- PCA(wp) wpp #> A PCA object #> -------------------- #> - 127 shapes #> - $method: [ procrustes analysis ] #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts, links. plot(wpp, 1) #> will be deprecated soon, see ?plot_PCA ### Cosmetic options # window plot(bp, 1, zoom=2) #> will be deprecated soon, see ?plot_PCA plot(bp, zoom=0.5) #> will be deprecated soon, see ?plot_PCA plot(bp, center.origin=FALSE, grid=FALSE) #> will be deprecated soon, see ?plot_PCA # colors plot(bp, col=\"red\") # globally #> will be deprecated soon, see ?plot_PCA plot(bp, 1, col=c(\"#00FF00\", \"#0000FF\")) # for every level #> will be deprecated soon, see ?plot_PCA # a color vector of the right length plot(bp, 1, col=rep(c(\"#00FF00\", \"#0000FF\"), each=20)) #> will be deprecated soon, see ?plot_PCA # a color vector of the right length, mixign Rcolor names (not a good idea though) plot(bp, 1, col=rep(c(\"#00FF00\", \"forestgreen\"), each=20)) #> will be deprecated soon, see ?plot_PCA # ellipses plot(bp, 1, conf.ellipsesax=2/3) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, ellipsesax=FALSE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, ellipsesax=TRUE, ellipses=TRUE) #> will be deprecated soon, see ?plot_PCA # stars plot(bp, 1, stars=TRUE, ellipsesax=FALSE) #> will be deprecated soon, see ?plot_PCA # convex hulls plot(bp, 1, chull=TRUE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, chull.lty=3) #> will be deprecated soon, see ?plot_PCA # filled convex hulls plot(bp, 1, chull.filled=TRUE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, chull.filled.alpha = 0.8, chull.lty =1) # you can omit chull.filled=TRUE #> will be deprecated soon, see ?plot_PCA # density kernel plot(bp, 1, density=TRUE, contour=TRUE, lev.contour=10) #> will be deprecated soon, see ?plot_PCA # delaunay plot(bp, 1, delaunay=TRUE) #> will be deprecated soon, see ?plot_PCA # loadings flower %>% PCA %>% plot(1, loadings=TRUE) #> will be deprecated soon, see ?plot_PCA # point/group labelling plot(bp, 1, labelspoint=TRUE) # see options for abbreviations #> will be deprecated soon, see ?plot_PCA plot(bp, 1, labelsgroup=TRUE) # see options for abbreviations #> will be deprecated soon, see ?plot_PCA # clean axes, no rug, no border, random title plot(bp, axisvar=FALSE, axisnames=FALSE, rug=FALSE, box=FALSE, title=\"random\") #> will be deprecated soon, see ?plot_PCA # no eigen plot(bp, eigen=FALSE) # eigen cause troubles to graphical window #> will be deprecated soon, see ?plot_PCA # eigen may causes troubles to the graphical window. you can try old.par = TRUE # }"},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a cross-validation table as an heatmap — plot_CV","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"Either frequencies (percentages) plus marginal sums, values heatmaps. Used Momocs plotting cross-validation tables may used table (likely freq=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"","code":"plot_CV( x, freq = FALSE, rm0 = FALSE, pc = FALSE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... ) # S3 method for default plot_CV( x, freq = FALSE, rm0 = FALSE, pc = FALSE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... ) # S3 method for LDA plot_CV( x, freq = TRUE, rm0 = TRUE, pc = TRUE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"x (cross-validation table) LDA object freq logical whether display frequencies (within actual class) counts rm0 logical whether remove zeros pc logical whether multiply proportion 100, ie display percentages fill logical whether fill cell according count/freq labels logical whether add text labels cells axis.size numeric adjust axis labels axis.x.angle numeric rotate x-axis labels cell.size numeric adjust text labels cells signif numeric round frequencies using signif ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"ggplot object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"","code":"h <- hearts %>% fgProcrustes(0.01) %>% coo_slide(ldk=2) %T>% stack %>% efourier(6, norm=FALSE) %>% LDA(~aut) #> iteration: 1 \tgain: 30322 #> iteration: 2 \tgain: 1.2498 #> iteration: 3 \tgain: 0.34194 #> iteration: 4 \tgain: 0.0062954 h %>% plot_CV() #> Warning: The `` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . h %>% plot_CV(freq=FALSE, rm0=FALSE, fill=FALSE) # you can customize the returned gg with some ggplot2 functions h %>% plot_CV(labels=FALSE, fill=TRUE, axis.size=5) + ggplot2::ggtitle(\"A confusion matrix\") # or build your own using the prepared data_frame: df <- h %>% plot_CV() %$% data df #> # A tibble: 34 × 4 #> actual predicted n actual2 #> #> 1 ced ced 0.77 ced #> 2 ced mat 0.1 ced #> 3 ced rom 0.067 ced #> 4 ced vince 0.067 ced #> 5 jeya jeya 0.87 jeya #> 6 jeya ponnu 0.067 jeya #> 7 jeya vince 0.067 jeya #> 8 mat ced 0.033 mat #> 9 mat jeya 0.1 mat #> 10 mat mat 0.47 mat #> # ℹ 24 more rows # you can even use it as a cross-table plotter bot$fac %>% table %>% plot_CV()"},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a cross-correlation table — plot_CV2","title":"Plots a cross-correlation table — plot_CV2","text":"contingency/confusion table. simple graphic representation based variable width /color arrows segments, based relative frequencies.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a cross-correlation table — plot_CV2","text":"","code":"plot_CV2(x, ...) # S3 method for LDA plot_CV2(x, ...) # S3 method for table plot_CV2( x, links.FUN = arrows, col = TRUE, col0 = \"black\", col.breaks = 5, palette = col_heat, lwd = TRUE, lwd0 = 5, gap.dots = 0.2, pch.dots = 20, gap.names = 0.25, cex.names = 1, legend = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a cross-correlation table — plot_CV2","text":"x LDA object, table squared matrix ... useless . links.FUN function draw links: eg segments (default), arrows, etc. col logical whether vary color links col0 color default link (col = FALSE) col.breaks number different colors palette color palette, eg col_summer, col_hot, etc. lwd logical whether vary width links lwd0 width default link (lwd = FALSE) gap.dots numeric set space dots links pch.dots pch dots gap.names numeric set space dots group names cex.names cex names legend logical whether add legend","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a cross-correlation table — plot_CV2","text":"ggplot2 object","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots a cross-correlation table — plot_CV2","text":"freq=FALSE, fill colors weighted within actual classes displayed classes sizes balanced.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a cross-correlation table — plot_CV2","text":"","code":"# Below various table that you can try. We will use the last one for the examples. #pure random a <- sample(rep(letters[1:4], each=10)) b <- sample(rep(letters[1:4], each=10)) tab <- table(a, b) # veryhuge + some structure a <- sample(rep(letters[1:10], each=10)) b <- sample(rep(letters[1:10], each=10)) tab <- table(a, b) diag(tab) <- round(runif(10, 10, 20)) tab <- matrix(c(8, 3, 1, 0, 0, 2, 7, 1, 2, 3, 3, 5, 9, 1, 1, 1, 1, 2, 7, 1, 0, 9, 1, 4, 5), 5, 5, byrow=TRUE) tab <- as.table(tab) # good prediction tab <- matrix(c(8, 1, 1, 0, 0, 1, 7, 1, 0, 0, 1, 2, 9, 1, 0, 1, 1, 1, 7, 1, 0, 0, 0, 1, 8), 5, 5, byrow=TRUE) tab <- as.table(tab) plot_CV2(tab) plot_CV2(tab, arrows) # if you prefer arrows plot_CV2(tab, lwd=FALSE, lwd0=1, palette=col_india) # if you like india but not lwds plot_CV2(tab, col=FALSE, col0='pink') # only lwd plot_CV2(tab, col=FALSE, lwd0=10, cex.names=2) # if you're getting old plot_CV2(tab, col=FALSE, lwd=FALSE) # pretty but useless plot_CV2(tab, col.breaks=2) # if you think it's either good or bad plot_CV2(tab, pch=NA) # if you do not like dots plot_CV2(tab, gap.dots=0) # if you want to 'fill the gap' plot_CV2(tab, gap.dots=1) # or not #trilo examples trilo.f <- efourier(trilo, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details trilo.l <- LDA(PCA(trilo.f), 'onto') #> 8 PC retained trilo.l #> * Cross-validation table ($CV.tab): #> classified #> actual a b c d #> a 0 5 2 0 #> b 3 12 1 0 #> c 0 3 11 4 #> d 0 0 3 6 #> #> * Class accuracy ($CV.ce): #> a b c d #> 0.0000000 0.7500000 0.6111111 0.6666667 #> #> * Leave-one-out cross-validation ($CV.correct): (58% - 29/50): plot_CV2(trilo.l) # olea example op <- opoly(olea, 5) #> 'nb.pts' missing and set to 91 opl <- LDA(PCA(op), 'var') #> 4 PC retained plot_CV2(opl)"},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"LDA plot using grindr layers — plot_LDA","title":"LDA plot using grindr layers — plot_LDA","text":"Quickly vizualise LDA objects build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"LDA plot using grindr layers — plot_LDA","text":"","code":"plot_LDA( x, axes = c(1, 2), palette = pal_qual, points = TRUE, points_transp = 1/4, morphospace = FALSE, morphospace_position = \"range\", chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", center_origin = TRUE, zoom = 0.9, eigen = TRUE, box = TRUE, iftwo_layer = layer_histogram_2, iftwo_split = FALSE, axesnames = TRUE, axesvar = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"LDA plot using grindr layers — plot_LDA","text":"x LDA object axes numeric length two select PCs use (c(1, 2) default) palette color palette use col_summer default points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) morphospace logical whether draw using layer_morphospace_PCA morphospace_position feed layer_morphospace_PCA (default: \"range\") chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") center_origin logical whether center origin zoom numeric zoom level frame (default: 0.9) eigen logical whether draw using layer_eigen box logical whether draw using layer_box iftwo_layer function (quotes) drawing LD1 two levels. far, one layer_histogram_2 (default) layer_density_2 iftwo_split feed split argument layer_histogram_2 layer_density_2 axesnames logical whether draw using layer_axesnames axesvar logical whether draw using layer_axesvar","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"LDA plot using grindr layers — plot_LDA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"LDA plot using grindr layers — plot_LDA","text":"approach replace plot.LDA. part grindr approach may packaged point. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"LDA plot using grindr layers — plot_LDA","text":"","code":"### First prepare an LDA object # Some outlines with bot bl <- bot %>% # cheap alignement before efourier coo_align() %>% coo_center %>% coo_slidedirection(\"left\") %>% # add a fake column mutate(fake=sample(letters[1:5], 40, replace=TRUE)) %>% # EFT efourier(6, norm=FALSE) %>% # LDA LDA(~fake) #> factor passed was a character, and coerced to a factor. bl %>% plot_LDA %>% layer_morphospace_LDA #> * layer_morphospace_LDA is back, but experimental # Below inherited from plot_PCA and to adapt here. #plot_PCA(bp) #plot_PCA(bp, ~type) #plot_PCA(bp, ~fake) # Some curves with olea #op <- olea %>% #mutate(s=coo_area(.)) %>% #filter(var != \"Cypre\") %>% #chop(~view) %>% lapply(opoly, 5, nb.pts=90) %>% #combine %>% PCA #op$fac$s %<>% as.character() %>% as.numeric() #op %>% plot_PCA(title=\"hi there!\") ### Now we can play with layers # and for instance build a custom plot # it should start with plot_PCA() #my_plot <- function(x, ...){ #x %>% # plot_PCA(...) %>% # layer_points %>% # layer_ellipsesaxes %>% # layer_rug # } # and even continue after this function # op %>% my_plot(~var, axes=c(1, 3)) %>% # layer_title(\"hi there!\") %>% # layer_stars() # You get the idea."},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":null,"dir":"Reference","previous_headings":"","what":"Pairwise comparison of a list of shapes — plot_MSHAPES","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"\"Confusion matrix\" list shapes. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"","code":"plot_MSHAPES(x, draw_fun, size, palette)"},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"x list shapes (eg returned MSHAPES) draw_fun one draw_outline, draw_curves, draw_landmarks. result MSHAPES passed, detected based $Coe, otherwise default draw_curves. size numeric shrinking factor shapes (coo_template; 3/4 default) palette palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"Directly inspired Chitwood et al. (2016) New Phytologist","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"","code":"x <- bot %>% efourier(6) %>% MSHAPES(~type) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # custom colors x %>% plot_MSHAPES(palette=pal_manual(c(\"darkgreen\", \"orange\"))) # also works on list of shapes, eg: leaves <- shapes %>% slice(grep(\"leaf\", names(shapes))) %$% coo class(leaves) #> [1] \"list\" leaves %>% plot_MSHAPES() # or shapes %>% # subset and degrade slice(1:12) %>% coo_sample(60) %$% # grab the coo coo %>% plot_MSHAPES()"},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":null,"dir":"Reference","previous_headings":"","what":"NMDS plot unsing grindr layers — plot_NMDS","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"Quickly vizualise MDS NMDS objects build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"","code":"plot_NMDS( x, f = NULL, axes = c(1, 2), points = TRUE, points_transp = 1/4, chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", box = TRUE, axesnames = TRUE, palette = pal_qual ) plot_MDS( x, f = NULL, axes = c(1, 2), points = TRUE, points_transp = 1/4, chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", box = TRUE, axesnames = TRUE, palette = pal_qual )"},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"x result MDS NMDS f factor specification feed fac_dispatcher axes numeric length two select PCs use (c(1, 2) default) points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") box logical whether draw using layer_box axesnames logical whether draw using layer_axesnames palette color palette use col_summer default","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"","code":"### First prepare an NMDS object x <- bot %>% efourier %>% NMDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> 'comm' has negative data: 'autotransform', 'noshare' and 'wascores' set to FALSE #> Warning: results may be meaningless because data have negative entries #> in method “bray” #> Run 0 stress 0.07227125 #> Run 1 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 5.165599e-06 max resid 1.848616e-05 #> ... Similar to previous best #> Run 2 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 1.848564e-06 max resid 7.686046e-06 #> ... Similar to previous best #> Run 3 stress 0.1610098 #> Run 4 stress 0.07227125 #> ... Procrustes: rmse 6.814351e-06 max resid 2.80386e-05 #> ... Similar to previous best #> Run 5 stress 0.07227125 #> ... Procrustes: rmse 8.042267e-06 max resid 3.293377e-05 #> ... Similar to previous best #> Run 6 stress 0.07227125 #> ... Procrustes: rmse 2.510738e-06 max resid 7.634959e-06 #> ... Similar to previous best #> Run 7 stress 0.1660041 #> Run 8 stress 0.07227125 #> ... Procrustes: rmse 1.181586e-06 max resid 3.464235e-06 #> ... Similar to previous best #> Run 9 stress 0.1642555 #> Run 10 stress 0.07227125 #> ... Procrustes: rmse 5.427893e-06 max resid 2.018695e-05 #> ... Similar to previous best #> Run 11 stress 0.07227125 #> ... Procrustes: rmse 1.396985e-06 max resid 6.777242e-06 #> ... Similar to previous best #> Run 12 stress 0.07227125 #> ... Procrustes: rmse 5.297105e-06 max resid 2.060719e-05 #> ... Similar to previous best #> Run 13 stress 0.07227125 #> ... Procrustes: rmse 5.873071e-06 max resid 2.1449e-05 #> ... Similar to previous best #> Run 14 stress 0.1660723 #> Run 15 stress 0.07227125 #> ... Procrustes: rmse 8.005086e-06 max resid 3.40387e-05 #> ... Similar to previous best #> Run 16 stress 0.07227125 #> ... Procrustes: rmse 4.941502e-06 max resid 1.943066e-05 #> ... Similar to previous best #> Run 17 stress 0.1591579 #> Run 18 stress 0.07227125 #> ... Procrustes: rmse 1.363297e-06 max resid 5.158787e-06 #> ... Similar to previous best #> Run 19 stress 0.07227125 #> ... Procrustes: rmse 5.783015e-06 max resid 2.420838e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 #> ... Procrustes: rmse 3.842552e-06 max resid 1.520619e-05 #> ... Similar to previous best #> *** Best solution repeated 14 times plot_NMDS(x) #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet plot_NMDS(x, ~type) %>% layer_stars() %>% layer_labelpoints() #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet ### Same on MDS object x <- bot %>% efourier %>% MDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) plot_MDS(x) #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet plot_MDS(x, ~type) %>% layer_stars() %>% layer_labelpoints() #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet"},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"PCA plot using grindr layers — plot_PCA","title":"PCA plot using grindr layers — plot_PCA","text":"Quickly vizualise PCA objects friends build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PCA plot using grindr layers — plot_PCA","text":"","code":"plot_PCA( x, f = NULL, axes = c(1, 2), palette = NULL, points = TRUE, points_transp = 1/4, morphospace = TRUE, morphospace_position = \"range\", chull = TRUE, chullfilled = FALSE, labelpoints = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", center_origin = TRUE, zoom = 0.9, eigen = TRUE, box = TRUE, axesnames = TRUE, axesvar = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PCA plot using grindr layers — plot_PCA","text":"x PCA object f factor specification feed fac_dispatcher axes numeric length two select PCs use (c(1, 2) default) palette color palette use col_summer default points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) morphospace logical whether draw using layer_morphospace_PCA morphospace_position feed layer_morphospace_PCA (default: \"range\") chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelpoints logical whether draw layer_labelpoints labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") center_origin logical whether center origin zoom numeric zoom level frame (default: 0.9) eigen logical whether draw using layer_eigen box logical whether draw using layer_box axesnames logical whether draw using layer_axesnames axesvar logical whether draw using layer_axesvar","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"PCA plot using grindr layers — plot_PCA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"PCA plot using grindr layers — plot_PCA","text":"approach replace plot.PCA (plot.lda versions. part grindr approach may packaged point. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PCA plot using grindr layers — plot_PCA","text":"","code":"### First prepare two PCA objects. # Some outlines with bot bp <- bot %>% mutate(fake=sample(letters[1:5], 40, replace=TRUE)) %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details plot_PCA(bp) plot_PCA(bp, ~type) plot_PCA(bp, ~fake) #> factor passed was a character, and coerced to a factor. # Some curves with olea op <- olea %>% mutate(s=coo_area(.)) %>% filter(var != \"Cypre\") %>% chop(~view) %>% opoly(5, nb.pts=90) %>% combine %>% PCA op$fac$s %<>% as.character() %>% as.numeric() op %>% plot_PCA(title=\"hi there!\") ### Now we can play with layers # and for instance build a custom plot # it should start with plot_PCA() my_plot <- function(x, ...){ x %>% plot_PCA(...) %>% layer_points %>% layer_ellipsesaxes %>% layer_rug } # and even continue after this function op %>% my_plot(~var, axes=c(1, 3)) %>% layer_title(\"hi there!\") # grindr allows (almost nice) tricks like highlighting: # bp %>% .layerize_PCA(~fake) %>% # layer_frame %>% layer_axes() %>% # layer_morphospace_PCA() -> x # highlight <- function(x, ..., col_F=\"#CCCCCC\", col_T=\"#FC8D62FF\"){ # args <- list(...) # x$colors_groups <- c(col_F, col_T) # x$colors_rows <- c(col_F, col_T)[(x$f %in% args)+1] # x # } # x %>% highlight(\"a\", \"b\") %>% layer_points() # You get the idea."},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws colored segments from a matrix of coordinates. — plot_devsegments","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"Given matrix (x; y) coordinates, draws segments every points defined row matrix uses color display information.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"","code":"plot_devsegments(coo, cols, lwd = 1)"},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"coo matrix coordinates. cols vector color length = nrow(coo). lwd lwd use drawing segments.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"","code":"# we load some data guinness <- coo_sample(bot[9], 100) # we calculate the diff between 48 harm and one with 6 harm. out.6 <- efourier_i(efourier(guinness, nb.h=6), nb.pts=120) # we calculate deviations, you can also try 'edm' dev <- edm_nearest(out.6, guinness) / coo_centsize(out.6) # we prepare the color scale d.cut <- cut(dev, breaks=20, labels=FALSE, include.lowest=TRUE) cols <- paste0(col_summer(20)[d.cut], 'CC') # we draw the results coo_plot(guinness, main='Guiness fitted with 6 harm.', points=FALSE) par(xpd=NA) plot_devsegments(out.6, cols=cols, lwd=4) coo_draw(out.6, lty=2, points=FALSE, col=NA) par(xpd=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":null,"dir":"Reference","previous_headings":"","what":"Silhouette plot — plot_silhouette","title":"Silhouette plot — plot_silhouette","text":"used, far, KMEDOIDS.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Silhouette plot — plot_silhouette","text":"","code":"plot_silhouette(x, palette = pal_qual)"},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Silhouette plot — plot_silhouette","text":"x object returned KMEDOIDS palette one palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Silhouette plot — plot_silhouette","text":"ggplot plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Silhouette plot — plot_silhouette","text":"","code":"olea %>% opoly(5) %>% KMEDOIDS(4) %>% plot_silhouette(pal_qual_solarized) #> 'nb.pts' missing and set to 91"},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots confusion matrix of sample sizes within $fac — plot_table","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"utility plots confusion matrix sample size (barplot) every object $fac. Useful visually large sample sizes, (un)balanced designs, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"","code":"plot_table(x, fac1, fac2 = fac1, rm0 = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"x object $fac slot (Coo, Coe, PCA, etc.) fac1 name id first factor fac2 name id second factor rm0 logical whether print zeros","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"ggplot2 object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"","code":"plot_table(olea, \"var\") #> Warning: `select_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `select()` instead. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . plot_table(olea, \"domes\", \"var\") gg <- plot_table(olea, \"domes\", \"var\", rm0 = TRUE) gg library(ggplot2) gg + coord_equal() gg + scale_fill_gradient(low=\"green\", high = \"red\") #> Scale for fill is already present. #> Adding another scale for fill, which will replace the existing scale. gg + coord_flip()"},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates shape from a polynomial model — opoly_i","title":"Calculates shape from a polynomial model — opoly_i","text":"Returns matrix (x; y) coordinates passed list obtained opoly npoly.","code":""},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates shape from a polynomial model — opoly_i","text":"","code":"opoly_i(pol, nb.pts = 120, reregister = TRUE) npoly_i(pol, nb.pts = 120, reregister = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates shape from a polynomial model — opoly_i","text":"pol pol list created npoly opoly nb.pts number points predict. default (higher) number points original shape. reregister logical whether reregister shape original baseline.","code":""},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates shape from a polynomial model — opoly_i","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates shape from a polynomial model — opoly_i","text":"","code":"data(olea) o <- olea[5] coo_plot(o) for (i in 2:7){ x <- opoly_i(opoly(o, i)) coo_draw(x, border=col_summer(7)[i], points=FALSE) }"},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":null,"dir":"Reference","previous_headings":"","what":"","title":"","text":"Basically wrapper around predict.lda package MASS. Uses LDA model classify new data.","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"","text":"","code":"reLDA(newdata, LDA) # S3 method for default reLDA(newdata, LDA) # S3 method for PCA reLDA(newdata, LDA) # S3 method for Coe reLDA(newdata, LDA)"},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"","text":"newdata use, PCA Coe object LDA LDA object","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"","text":"list components (?predict.lda ). class factor classification posterior posterior probabilities classes x scores test cases res data.frame results CV.tab confusion matrix results CV.correct proportion diagonal CV.tab newdata data used calculate passed predict.lda","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"","text":"Uses number PC axis LDA object provided. probably use rePCA conjunction reLDA get 'homologous' scores.","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"","text":"","code":"# We select the first 10 individuals in bot, # for whisky and beer bottles. It will be our referential. bot1 <- slice(bot, c(1:10, 21:30)) # Same thing for the other 10 individuals. # It will be our unknown dataset on which we want # to calculate classes. bot2 <- slice(bot, c(11:20, 31:40)) # We calculate efourier on these two datasets bot1.f <- efourier(bot1, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot2.f <- efourier(bot2, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # Here we obtain our LDA model: first, a PCA, then a LDA bot1.p <- PCA(bot1.f) bot1.l <- LDA(bot1.p, \"type\") #> 6 PC retained # we redo the same PCA since we worked with scores bot2.p <- rePCA(bot1.p, bot2.f) # we finally \"predict\" with the model obtained before bot2.l <- reLDA(bot2.p, bot1.l) bot2.l #> $class #> [1] whisky whisky whisky whisky beer whisky whisky beer whisky whisky #> [11] beer beer beer whisky beer whisky beer beer beer beer #> Levels: beer whisky #> #> $posterior #> beer whisky #> jupiler 1.588583e-05 9.999841e-01 #> kingfisher 9.172746e-02 9.082725e-01 #> latrappe 2.276644e-02 9.772336e-01 #> lindemanskriek 5.840887e-03 9.941591e-01 #> nicechouffe 7.031244e-01 2.968756e-01 #> pecheresse 1.773492e-06 9.999982e-01 #> sierranevada 2.144720e-04 9.997855e-01 #> tanglefoot 9.372426e-01 6.275742e-02 #> tauro 1.183763e-05 9.999882e-01 #> westmalle 1.157018e-04 9.998843e-01 #> jb 9.975581e-01 2.441892e-03 #> johnniewalker 8.473188e-01 1.526812e-01 #> magallan 1.000000e+00 3.192177e-09 #> makersmark 1.093923e-01 8.906077e-01 #> oban 9.999880e-01 1.199656e-05 #> oldpotrero 2.425202e-02 9.757480e-01 #> redbreast 9.999820e-01 1.795276e-05 #> tamdhu 8.589367e-01 1.410633e-01 #> wildturkey 9.999905e-01 9.478960e-06 #> yoichi 9.744921e-01 2.550790e-02 #> #> $x #> LD1 #> jupiler 2.9341875 #> kingfisher 0.6087998 #> latrappe 0.9982650 #> lindemanskriek 1.3640608 #> nicechouffe -0.2289504 #> pecheresse 3.5163722 #> sierranevada 2.2430113 #> tanglefoot -0.7179197 #> tauro 3.0122943 #> westmalle 2.4069164 #> jb -1.5965434 #> johnniewalker -0.4550552 #> magallan -5.1945591 #> makersmark 0.5568188 #> oban -3.0087530 #> oldpotrero 0.9810760 #> redbreast -2.9017076 #> tamdhu -0.4796867 #> wildturkey -3.0712994 #> yoichi -0.9673275 #> #> $newdata #> PC1 PC2 PC3 PC4 #> jupiler 0.047558323 -0.0009556964 -1.132936e-02 -0.0038135827 #> kingfisher 0.031019804 0.0092893037 -5.639726e-03 0.0006984167 #> latrappe -0.140467542 0.0368452619 8.204030e-03 -0.0074130929 #> lindemanskriek 0.028727335 -0.0093711139 -6.350860e-03 0.0040530566 #> nicechouffe 0.014137615 -0.0087352325 -1.464619e-03 0.0102437348 #> pecheresse 0.046019149 -0.0022071144 -1.263256e-02 -0.0019483303 #> sierranevada -0.045574138 0.0101119946 -4.587309e-03 -0.0139742083 #> tanglefoot -0.083848693 0.0019607973 1.265634e-02 -0.0086813906 #> tauro 0.047804962 -0.0010302173 -1.166643e-02 -0.0038315686 #> westmalle 0.043104213 -0.0006618641 -9.661507e-03 0.0013659528 #> jb 0.033826795 -0.0043832070 8.789680e-03 -0.0012973929 #> johnniewalker 0.027546559 0.0433572509 -5.503569e-07 0.0080407513 #> magallan 0.062757370 0.0344623824 1.994348e-02 0.0054305457 #> makersmark -0.066073754 -0.0410683917 -2.500513e-02 -0.0028195062 #> oban 0.056001340 -0.0017415641 1.469954e-02 0.0024240694 #> oldpotrero -0.039446859 -0.0560097481 -1.838963e-02 0.0143275711 #> redbreast -0.070467008 -0.0453726482 1.443590e-03 0.0008230393 #> tamdhu 0.040245919 0.0099990120 8.849077e-03 -0.0054926858 #> wildturkey 0.009047941 -0.0118958979 1.825586e-02 -0.0002205672 #> yoichi -0.041919333 0.0374066929 1.388610e-02 0.0020851880 #> PC5 PC6 #> jupiler 0.0005273680 -0.003411272 #> kingfisher -0.0025505108 -0.000645225 #> latrappe 0.0014020218 -0.011164248 #> lindemanskriek -0.0005455535 -0.004342575 #> nicechouffe -0.0031229185 -0.005062708 #> pecheresse 0.0030349867 -0.005659553 #> sierranevada -0.0050825894 -0.003254912 #> tanglefoot -0.0051466484 -0.003608419 #> tauro 0.0011495431 -0.003297832 #> westmalle 0.0015195495 -0.004960376 #> jb -0.0020355558 0.003538980 #> johnniewalker -0.0046821155 -0.006875580 #> magallan 0.0055312084 0.011826574 #> makersmark 0.0039534995 0.017991125 #> oban 0.0001554770 0.005786238 #> oldpotrero 0.0023407200 0.001001825 #> redbreast -0.0038050474 0.012566253 #> tamdhu -0.0011719141 0.000222802 #> wildturkey -0.0020315441 0.003880876 #> yoichi 0.0105600234 -0.004531973 #>"},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":null,"dir":"Reference","previous_headings":"","what":"","title":"","text":"Basically reapply rotation new Coe object.","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"","text":"","code":"rePCA(PCA, Coe)"},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"","text":"PCA PCA object Coe Coe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"","text":"Quite experimental. Dimensions matrices methods must match.","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"","text":"","code":"b <- filter(bot, type==\"beer\") w <- filter(bot, type==\"whisky\") bf <- efourier(b, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bp <- PCA(bf) wf <- efourier(w, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # and we use the \"beer\" PCA on the whisky coefficients wp <- rePCA(bp, wf) plot(wp) #> will be deprecated soon, see ?plot_PCA plot(bp, eig=FALSE) #> will be deprecated soon, see ?plot_PCA points(wp$x[, 1:2], col=\"red\", pch=4)"},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Helps reorder retain landmarks simply changing order recorded Coo objects. Note Opn objects, rearranges $ldk component. Ldk, rearranges $coo directly.","code":""},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"","code":"rearrange_ldk(Coo, new_ldk_ids)"},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Coo appropriate Coo object (typically Ldk) landmarks inside new_ldk_ids vector numeric ldk retain right order (see )","code":""},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"","code":"# Out example hearts %>% slice(1) %T>% stack %$% ldk #> [[1]] #> [1] 65 56 50 19 #> hearts %>% rearrange_ldk(c(4, 1)) %>% slice(1) %T>%stack %$% ldk #> [[1]] #> [1] 19 65 #> # Ldk example wings %>% slice(1) %T>% stack %$% coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> [7,] 0.2311 -0.0228 #> [8,] 0.2040 -0.0452 #> [9,] 0.1282 -0.0742 #> [10,] 0.0424 -0.0966 #> [11,] -0.0674 -0.1108 #> [12,] -0.4102 -0.0163 #> [13,] -0.3140 0.0318 #> [14,] -0.1768 0.0341 #> [15,] 0.0715 0.0509 #> [16,] -0.0540 0.0238 #> [17,] 0.0575 -0.0059 #> [18,] -0.1401 -0.0240 #> wings %>% rearrange_ldk(c(1, 3, 12:15)) %>% slice(1) %T>% stack %$% coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] 0.2231 0.0861 #> [3,] -0.4102 -0.0163 #> [4,] -0.3140 0.0318 #> [5,] -0.1768 0.0341 #> [6,] 0.0715 0.0509 #>"},{"path":"http://momx.github.io/Momocs/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. magrittr %$%, %<>%, %>%, %T>%","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename columns by name — rename","title":"Rename columns by name — rename","text":"Rename variables, $fac. See examples dplyr::rename.","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename columns by name — rename","text":"","code":"rename(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename columns by name — rename","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rename columns by name — rename","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rename columns by name — rename","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename columns by name — rename","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk rename(olea, variety=var, domesticated=domes) # rename var column #> Opn (curves) #> - 210 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> variety domesticated view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":null,"dir":"Reference","previous_headings":"","what":"Rescale coordinates from pixels to real length units — rescale","title":"Rescale coordinates from pixels to real length units — rescale","text":"time, (x, y) coordinates recorded pixels. want mm, cm, etc. need convert rescale . functions job two cases: ) either homogeneous rescaling factor, e.g. pictures taken using magnification ii) various magnifications. Details section","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rescale coordinates from pixels to real length units — rescale","text":"","code":"rescale(x, scaling_factor, scale_mapping, magnification_col, ...)"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rescale coordinates from pixels to real length units — rescale","text":"x Coo object scaling_factor numeric homogeneous scaling factor. (x, y) coordinates scale scale_mapping either data.frame path read data.frame. MUST contain three columns order: magnification found $fac, column \"magnification_col\", pixels, real length unit. Column names matter must specified, read.table reads header=TRUE Every different magnification level found $fac, column \"magnification_col\" must row. magnification_col name id $fac column look magnification levels every image ... additional arguments (besides header=TRUE) pass read.table 'scale_mapping' path","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rescale coordinates from pixels to real length units — rescale","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rescale coordinates from pixels to real length units — rescale","text":") case straightforward, 1cm 500pix long pictures, just call rescale(your_Coo, scaling_factor=1/500) coordinates cm. ii) second case subtle. First need code Coo object, fac slot, column named, say \"mag\", magnification. Imagine 4 magnifications: 0.5, 1, 2 5, indicate magnification, many pixels stands many units real world. information passed data.frame, built externally R, must look like : . , optical reasons, ratio pix/real_unit, linear function magnification. shapes centered apply (single different) scaling_factor.","code":"mag pix cm 0.5 1304 10 1 921 10 2 816 5 5 1020 5"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Rescale coordinates from pixels to real length units — rescale","text":"function simple quite complex detail. Feel free contact problem . can just access code (type rescale) reply .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Radii variation Fourier transform (equally spaced radii) — rfourier","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"rfourier computes radii variation Fourier analysis matrix list coordinates points equally spaced radii.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"","code":"rfourier(x, ...) # S3 method for default rfourier(x, nb.h, smooth.it = 0, norm = FALSE, ...) # S3 method for Out rfourier(x, nb.h = 40, smooth.it = 0, norm = TRUE, thres = pi/90, ...) # S3 method for list rfourier(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"x list matrix coordinates object ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform. norm logical. Whether scale outlines mean length radii used equals 1. thres numeric tolerance feed is_equallyspacedradii","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"list following components: vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients ao ao harmonic coefficient. r vector radii lengths.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"see JSS paper maths behind. methods objects tests coordinates equally spaced radii using is_equallyspacedradii. message printed case.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"Silent message progress bars () options(\"verbose\"=FALSE). Directly borrowed Claude (2008), called fourier1 .","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"","code":"data(bot) coo <- coo_center(bot[1]) # centering is almost mandatory for rfourier family coo_plot(coo) rf <- rfourier(coo, 12) rf #> $an #> [1] 9.216460e-15 -4.745309e+02 8.327818e-01 2.719483e+02 -1.430955e+01 #> [6] -1.110619e+02 2.489911e+01 -1.011701e+00 -1.771458e+01 5.542552e+01 #> [11] 6.786737e-01 -5.902187e+01 #> #> $bn #> [1] 1.054744e-13 -1.108663e+01 -5.032796e+01 1.187178e+01 1.332257e+02 #> [6] 4.068663e+00 -1.709325e+02 -1.013725e+01 1.391797e+02 1.085760e+01 #> [11] -7.449979e+01 -2.355442e+00 #> #> $ao #> [1] 669.1267 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- rfourier_i(rf) coo_draw(rfi, border='red', col=NA) # Out method bot %>% rfourier() #> some shapes seem(s) to have some identical coordinates #> 'nb.h' not provided and set to 60 (99% harmonic power) #> An OutCoe object [ radii variation (equally spaced radii) analysis ] #> -------------------- #> - $coe: 40 outlines described, 60 harmonics #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows"},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse radii variation Fourier transform — rfourier_i","title":"Inverse radii variation Fourier transform — rfourier_i","text":"rfourier_i uses inverse radii variation (equally spaced radii) transformation calculate shape, given list Fourier coefficients, typically obtained computed rfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse radii variation Fourier transform — rfourier_i","text":"","code":"rfourier_i(rf, nb.h, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse radii variation Fourier transform — rfourier_i","text":"rf list ao, bn components, typically returned rfourier. nb.h integer. number harmonics calculate/use. nb.pts integer. number points calculate.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse radii variation Fourier transform — rfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. angle vector angles used. r vector radii calculated.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse radii variation Fourier transform — rfourier_i","text":"See JSS paper maths behind.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse radii variation Fourier transform — rfourier_i","text":"Directly borrowed Claude (2008), called ifourier1 .","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse radii variation Fourier transform — rfourier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse radii variation Fourier transform — rfourier_i","text":"","code":"data(bot) coo <- coo_center(bot[1]) # centering is almost mandatory for rfourier family coo_plot(coo) rf <- rfourier(coo, 12) rf #> $an #> [1] 9.216460e-15 -4.745309e+02 8.327818e-01 2.719483e+02 -1.430955e+01 #> [6] -1.110619e+02 2.489911e+01 -1.011701e+00 -1.771458e+01 5.542552e+01 #> [11] 6.786737e-01 -5.902187e+01 #> #> $bn #> [1] 1.054744e-13 -1.108663e+01 -5.032796e+01 1.187178e+01 1.332257e+02 #> [6] 4.068663e+00 -1.709325e+02 -1.013725e+01 1.391797e+02 1.085760e+01 #> [11] -7.449979e+01 -2.355442e+00 #> #> $ao #> [1] 669.1267 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- rfourier_i(rf) coo_draw(rfi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'rfourier' shapes. — rfourier_shape","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"rfourier_shape calculates 'Fourier radii variation shape' given Fourier coefficients (see Details) can generate 'rfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"","code":"rfourier_shape(an, bn, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"rfourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See rfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"","code":"data(bot) rf <- rfourier(bot[1], 24) rfourier_shape(rf$an, rf$bn) # equivalent to rfourier_i(rf) #> x y #> [1,] -504.032401 0.000000e+00 #> [2,] 152.277511 1.213684e+01 #> [3,] 123.922985 1.988014e+01 #> [4,] -405.769720 -9.869758e+01 #> [5,] -299.257786 -9.855215e+01 #> [6,] -64.033528 -2.689724e+01 #> [7,] -297.588603 -1.538718e+02 #> [8,] -247.659860 -1.541471e+02 #> [9,] 34.115634 2.520344e+01 #> [10,] -81.118036 -7.054630e+01 #> [11,] -96.952489 -9.889967e+01 #> [12,] 181.738917 2.175623e+02 #> [13,] 320.377819 4.522104e+02 #> [14,] 650.392457 1.092799e+03 #> [15,] 1019.781679 2.072239e+03 #> [16,] 766.774556 1.932160e+03 #> [17,] 840.274273 2.733288e+03 #> [18,] 1733.216439 7.797650e+03 #> [19,] 1683.030508 1.201390e+04 #> [20,] 472.998568 7.920093e+03 #> [21,] -3.693822 1.857488e+02 #> [22,] 193.709205 -1.942018e+03 #> [23,] 21.862735 -1.208644e+02 #> [24,] 53.714265 -2.031549e+02 #> [25,] 370.520921 -1.054083e+03 #> [26,] 216.540448 -4.880980e+02 #> [27,] 135.732670 -2.501862e+02 #> [28,] 466.908353 -7.179336e+02 #> [29,] 411.781716 -5.348072e+02 #> [30,] 235.560214 -2.602254e+02 #> [31,] 517.224029 -4.872563e+02 #> [32,] 572.278421 -4.590422e+02 #> [33,] 346.348891 -2.351772e+02 #> [34,] 534.117025 -3.036705e+02 #> [35,] 679.577570 -3.178066e+02 #> [36,] 455.098727 -1.702117e+02 #> [37,] 529.331468 -1.512772e+02 #> [38,] 725.483690 -1.461831e+02 #> [39,] 545.014188 -6.533097e+01 #> [40,] 512.204019 -2.037956e+01 #> [41,] 711.685148 2.831651e+01 #> [42,] 599.323333 7.184102e+01 #> [43,] 487.280383 9.818574e+01 #> [44,] 648.008281 1.851938e+02 #> [45,] 605.439186 2.264407e+02 #> [46,] 453.428917 2.120475e+02 #> [47,] 549.059655 3.121661e+02 #> [48,] 558.226691 3.790460e+02 #> [49,] 404.964997 3.248349e+02 #> [50,] 430.145214 4.052228e+02 #> [51,] 461.416259 5.097305e+02 #> [52,] 334.454312 4.343772e+02 #> [53,] 303.642443 4.668906e+02 #> [54,] 326.758921 6.022910e+02 #> [55,] 236.290598 5.326163e+02 #> [56,] 176.846385 5.031047e+02 #> [57,] 171.184806 6.474451e+02 #> [58,] 109.884528 6.074778e+02 #> [59,] 51.833348 5.196517e+02 #> [60,] 12.809119 6.441236e+02 #> [61,] -38.593591 6.462278e+02 #> [62,] -72.750399 5.193108e+02 #> [63,] -133.044116 5.985585e+02 #> [64,] -196.546600 6.393370e+02 #> [65,] -198.662349 5.006002e+02 #> [66,] -256.653752 5.215311e+02 #> [67,] -347.381274 5.836753e+02 #> [68,] -324.847387 4.585191e+02 #> [69,] -354.756103 4.246838e+02 #> [70,] -474.501207 4.840310e+02 #> [71,] -445.049745 3.870485e+02 #> [72,] -429.185843 3.170675e+02 #> [73,] -566.188571 3.524040e+02 #> [74,] -546.614528 2.826337e+02 #> [75,] -483.371296 2.030398e+02 #> [76,] -622.486699 2.049985e+02 #> [77,] -607.488016 1.477626e+02 #> [78,] -514.459992 8.253138e+01 #> [79,] -692.324999 5.517977e+01 #> [80,] -504.032401 1.234523e-13 rfourier_shape() # not very interesting #> x y #> [1,] -1.70783049 0.000000e+00 #> [2,] -1.42387492 -1.134858e-01 #> [3,] -1.12842604 -1.810258e-01 #> [4,] -0.83525063 -2.031626e-01 #> [5,] -0.55314503 -1.821628e-01 #> [6,] -0.28573344 -1.200222e-01 #> [7,] -0.03274864 -1.693308e-02 #> [8,] 0.20762473 1.292287e-01 #> [9,] 0.43605675 3.221435e-01 #> [10,] 0.64983694 5.651467e-01 #> [11,] 0.84177670 8.586828e-01 #> [12,] 1.00061227 1.197848e+00 #> [13,] 1.11285389 1.570783e+00 #> [14,] 1.16562637 1.958503e+00 #> [15,] 1.14977127 2.336383e+00 #> [16,] 1.06240688 2.677111e+00 #> [17,] 0.90828491 2.954516e+00 #> [18,] 0.69959955 3.147462e+00 #> [19,] 0.45430408 3.242938e+00 #> [20,] 0.19336079 3.237717e+00 #> [21,] -0.06240765 3.138252e+00 #> [22,] -0.29514415 2.958947e+00 #> [23,] -0.49188023 2.719276e+00 #> [24,] -0.64526044 2.440466e+00 #> [25,] -0.75311265 2.142507e+00 #> [26,] -0.81720368 1.842037e+00 #> [27,] -0.84168817 1.551423e+00 #> [28,] -0.83175975 1.278941e+00 #> [29,] -0.79285960 1.029737e+00 #> [30,] -0.73054609 8.070406e-01 #> [31,] -0.65086608 6.131551e-01 #> [32,] -0.56087882 4.498982e-01 #> [33,] -0.46892701 3.184099e-01 #> [34,] -0.38434108 2.185159e-01 #> [35,] -0.31647156 1.479989e-01 #> [36,] -0.27319902 1.021793e-01 #> [37,] -0.25928964 7.410219e-02 #> [38,] -0.27507300 5.542650e-02 #> [39,] -0.31587991 3.786459e-02 #> [40,] -0.37249857 1.482096e-02 #> [41,] -0.43263981 -1.721386e-02 #> [42,] -0.48312454 -5.791225e-02 #> [43,] -0.51230209 -1.032276e-01 #> [44,] -0.51213827 -1.463636e-01 #> [45,] -0.47949724 -1.793370e-01 #> [46,] -0.41635659 -1.947105e-01 #> [47,] -0.32897716 -1.870389e-01 #> [48,] -0.22631518 -1.536721e-01 #> [49,] -0.11813866 -9.476267e-02 #> [50,] -0.01334510 -1.257189e-02 #> [51,] 0.08113017 8.962521e-02 #> [52,] 0.16063793 2.086307e-01 #> [53,] 0.22244168 3.420336e-01 #> [54,] 0.26492212 4.883117e-01 #> [55,] 0.28673533 6.463225e-01 #> [56,] 0.28627059 8.144022e-01 #> [57,] 0.26160815 9.894390e-01 #> [58,] 0.21096982 1.166311e+00 #> [59,] 0.13345744 1.337968e+00 #> [60,] 0.02975436 1.496238e+00 #> [61,] -0.09753442 1.633159e+00 #> [62,] -0.24410623 1.742492e+00 #> [63,] -0.40474725 1.820937e+00 #> [64,] -0.57446280 1.868642e+00 #> [65,] -0.74957661 1.888824e+00 #> [66,] -0.92838875 1.886525e+00 #> [67,] -1.11108727 1.866866e+00 #> [68,] -1.29882939 1.833286e+00 #> [69,] -1.49218159 1.786313e+00 #> [70,] -1.68934733 1.723276e+00 #> [71,] -1.88473800 1.639109e+00 #> [72,] -2.06840699 1.528067e+00 #> [73,] -2.22666734 1.385910e+00 #> [74,] -2.34389910 1.211941e+00 #> [75,] -2.40520955 1.010307e+00 #> [76,] -2.39933834 7.901548e-01 #> [77,] -2.32108398 5.645699e-01 #> [78,] -2.17260957 3.485372e-01 #> [79,] -1.96325086 1.564753e-01 #> [80,] -1.70783049 4.182978e-16 rfourier_shape(nb.h=12) # better #> x y #> [1,] 3.17350221 0.000000e+00 #> [2,] 2.82968114 2.255316e-01 #> [3,] 2.43948432 3.913502e-01 #> [4,] 2.06536164 5.023692e-01 #> [5,] 1.74268302 5.739037e-01 #> [6,] 1.47564178 6.198424e-01 #> [7,] 1.24842809 6.455149e-01 #> [8,] 1.04054160 6.476482e-01 #> [9,] 0.83709685 6.184180e-01 #> [10,] 0.63206684 5.496925e-01 #> [11,] 0.42754983 4.361367e-01 #> [12,] 0.23216062 2.779229e-01 #> [13,] 0.05887461 8.310097e-02 #> [14,] -0.07873057 -1.322843e-01 #> [15,] -0.17140187 -3.482958e-01 #> [16,] -0.21769695 -5.485646e-01 #> [17,] -0.22348979 -7.269792e-01 #> [18,] -0.19763895 -8.891673e-01 #> [19,] -0.14677845 -1.047742e+00 #> [20,] -0.07253700 -1.214591e+00 #> [21,] 0.02774197 -1.395042e+00 #> [22,] 0.15824615 -1.586486e+00 #> [23,] 0.32205629 -1.780433e+00 #> [24,] 0.51961489 -1.965257e+00 #> [25,] 0.74804094 -2.128078e+00 #> [26,] 1.00099083 -2.256307e+00 #> [27,] 1.26941847 -2.339827e+00 #> [28,] 1.54350539 -2.373345e+00 #> [29,] 1.81487968 -2.357100e+00 #> [30,] 2.07741451 -2.294938e+00 #> [31,] 2.32588321 -2.191122e+00 #> [32,] 2.55405607 -2.048687e+00 #> [33,] 2.75500192 -1.870696e+00 #> [34,] 2.92452011 -1.662726e+00 #> [35,] 3.06492303 -1.433321e+00 #> [36,] 3.18450875 -1.191040e+00 #> [37,] 3.29071918 -9.404522e-01 #> [38,] 3.38068991 -6.812003e-01 #> [39,] 3.43662398 -4.119489e-01 #> [40,] 3.43105716 -1.365148e-01 #> [41,] 3.33973942 1.328815e-01 #> [42,] 3.15355628 3.780175e-01 #> [43,] 2.88139811 5.805943e-01 #> [44,] 2.54314959 7.268048e-01 #> [45,] 2.15980801 8.077911e-01 #> [46,] 1.74916782 8.180039e-01 #> [47,] 1.32926781 7.557509e-01 #> [48,] 0.92374397 6.272389e-01 #> [49,] 0.56104073 4.500281e-01 #> [50,] 0.26536741 2.499921e-01 #> [51,] 0.04586366 5.066599e-02 #> [52,] -0.10657467 -1.384153e-01 #> [53,] -0.21116372 -3.246923e-01 #> [54,] -0.28370198 -5.229272e-01 #> [55,] -0.32811803 -7.396021e-01 #> [56,] -0.33890179 -9.641311e-01 #> [57,] -0.31062985 -1.174846e+00 #> [58,] -0.24514106 -1.355220e+00 #> [59,] -0.15025456 -1.506367e+00 #> [60,] -0.03270006 -1.644366e+00 #> [61,] 0.10654541 -1.784042e+00 #> [62,] 0.26942175 -1.923201e+00 #> 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0.8523405308 1.610035e-02 #> [253,] 0.7339562151 2.311176e-02 #> [254,] 0.6070058016 2.676834e-02 #> [255,] 0.4716608340 2.675388e-02 #> [256,] 0.3281356702 2.276096e-02 #> [257,] 0.1766873280 1.449337e-02 #> [258,] 0.0176150845 1.668473e-03 #> [259,] -0.1487401725 -1.598046e-02 #> [260,] -0.3219968412 -3.870196e-02 #> [261,] -0.5017337489 -6.672411e-02 #> [262,] -0.6874915390 -1.002524e-01 #> [263,] -0.8787742964 -1.394678e-01 #> [264,] -1.0750514062 -1.845244e-01 #> [265,] -1.2757596359 -2.355482e-01 #> [266,] -1.4803054332 -2.926349e-01 #> [267,] -1.6880674276 -3.558488e-01 #> [268,] -1.8983991234 -4.252210e-01 #> [269,] -2.1106317703 -5.007487e-01 #> [270,] -2.3240773954 -5.823941e-01 #> [271,] -2.5380319828 -6.700832e-01 #> [272,] -2.7517787794 -7.637059e-01 #> [273,] -2.9645917117 -8.631154e-01 #> [274,] -3.1757388921 -9.681279e-01 #> [275,] -3.3844861954 -1.078523e+00 #> [276,] -3.5901008841 -1.194044e+00 #> [277,] -3.7918552610 -1.314399e+00 #> [278,] -3.9890303282 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-4.640957e+00 #> [305,] -5.7302997090 -4.693309e+00 #> [306,] -5.6362205080 -4.736073e+00 #> [307,] -5.5324419493 -4.768996e+00 #> [308,] -5.4194698055 -4.791870e+00 #> [309,] -5.2978431877 -4.804534e+00 #> [310,] -5.1681314720 -4.806871e+00 #> [311,] -5.0309310732 -4.798816e+00 #> [312,] -4.8868620859 -4.780348e+00 #> [313,] -4.7365648154 -4.751499e+00 #> [314,] -4.5806962193 -4.712346e+00 #> [315,] -4.4199262834 -4.663017e+00 #> [316,] -4.2549343536 -4.603689e+00 #> [317,] -4.0864054489 -4.534584e+00 #> [318,] -3.9150265759 -4.455973e+00 #> [319,] -3.7414830713 -4.368169e+00 #> [320,] -3.5664549920 -4.271531e+00 #> [321,] -3.3906135775 -4.166459e+00 #> [322,] -3.2146178059 -4.053391e+00 #> [323,] -3.0391110633 -3.932804e+00 #> [324,] -2.8647179495 -3.805208e+00 #> [325,] -2.6920412365 -3.671144e+00 #> [326,] -2.5216590002 -3.531185e+00 #> [327,] -2.3541219405 -3.385924e+00 #> [328,] -2.1899509060 -3.235982e+00 #> [329,] -2.0296346383 -3.081995e+00 #> [330,] -1.8736277460 -2.924614e+00 #> [331,] -1.7223489218 -2.764504e+00 #> [332,] -1.5761794099 -2.602335e+00 #> [333,] -1.4354617320 -2.438783e+00 #> [334,] -1.3004986772 -2.274524e+00 #> [335,] -1.1715525591 -2.110228e+00 #> [336,] -1.0488447423 -1.946562e+00 #> [337,] -0.9325554379 -1.784179e+00 #> [338,] -0.8228237665 -1.623718e+00 #> [339,] -0.7197480838 -1.465800e+00 #> [340,] -0.6233865647 -1.311026e+00 #> [341,] -0.5337580368 -1.159971e+00 #> [342,] -0.4508430560 -1.013182e+00 #> [343,] -0.3745852119 -8.711775e-01 #> [344,] -0.3048926515 -7.344407e-01 #> [345,] -0.2416398079 -6.034202e-01 #> [346,] -0.1846693177 -4.785269e-01 #> [347,] -0.1337941121 -3.601316e-01 #> [348,] -0.0887996638 -2.485638e-01 #> [349,] -0.0494463715 -1.441101e-01 #> [350,] -0.0154720622 -4.701310e-02 #> [351,] 0.0134054074 4.252949e-02 #> [352,] 0.0374854712 1.243654e-01 #> [353,] 0.0570821171 1.983879e-01 #> [354,] 0.0725211136 2.645363e-01 #> [355,] 0.0841372209 3.227948e-01 #> [356,] 0.0922714074 3.731929e-01 #> [357,] 0.0972680931 4.158035e-01 #> [358,] 0.0994724381 4.507425e-01 #> [359,] 0.0992276988 4.781669e-01 #> [360,] 0.0968726680 4.982736e-01 #> [361,] 0.0927392197 5.112970e-01 #> [362,] 0.0871499740 5.175069e-01 #> [363,] 0.0804160985 5.172066e-01 #> [364,] 0.0728352630 5.107299e-01 #> [365,] 0.0646897580 4.984384e-01 #> [366,] 0.0562447922 4.807189e-01 #> [367,] 0.0477469784 4.579800e-01 #> [368,] 0.0394230163 4.306493e-01 #> [369,] 0.0314785819 3.991701e-01 #> [370,] 0.0240974266 3.639978e-01 #> [371,] 0.0174406929 3.255972e-01 #> [372,] 0.0116464470 2.844384e-01 #> [373,] 0.0068294301 2.409941e-01 #> [374,] 0.0030810269 1.957358e-01 #> [375,] 0.0004694488 1.491308e-01 #> [376,] -0.0009598730 1.016390e-01 #> [377,] -0.0011836908 5.370944e-02 #> [378,] -0.0002001469 5.777811e-03 #> [379,] 0.0019722053 -4.173675e-02 #> [380,] 0.0052955579 -8.843425e-02 #> [381,] 0.0097141677 -1.339364e-01 #> [382,] 0.0151558267 -1.778890e-01 #> [383,] 0.0215334678 -2.199639e-01 #> [384,] 0.0287468917 -2.598611e-01 #> [385,] 0.0366845972 -2.973105e-01 #> [386,] 0.0452256982 -3.320731e-01 #> [387,] 0.0542419100 -3.639424e-01 #> [388,] 0.0635995851 -3.927453e-01 #> [389,] 0.0731617813 -4.183428e-01 #> [390,] 0.0827903424 -4.406302e-01 #> [391,] 0.0923479727 -4.595377e-01 #> [392,] 0.1017002861 -4.750298e-01 #> [393,] 0.1107178119 -4.871055e-01 #> [394,] 0.1192779386 -4.957969e-01 #> [395,] 0.1272667785 -5.011692e-01 #> [396,] 0.1345809348 -5.033190e-01 #> [397,] 0.1411291575 -5.023730e-01 #> [398,] 0.1468338708 -4.984867e-01 #> [399,] 0.1516325589 -4.918424e-01 #> [400,] 0.1554789968 -4.826475e-01 #> [401,] 0.1583443157 -4.711320e-01 #> [402,] 0.1602178907 -4.575464e-01 #> [403,] 0.1611080441 -4.421595e-01 #> [404,] 0.1610425565 -4.252554e-01 #> [405,] 0.1600689790 -4.071311e-01 #> [406,] 0.1582547442 -3.880940e-01 #> [407,] 0.1556870729 -3.684587e-01 #> [408,] 0.1524726756 -3.485441e-01 #> [409,] 0.1487372509 -3.286714e-01 #> [410,] 0.1446247831 -3.091602e-01 #> [411,] 0.1402966432 -2.903264e-01 #> [412,] 0.1359305000 -2.724793e-01 #> [413,] 0.1317190495 -2.559187e-01 #> [414,] 0.1278685704 -2.409329e-01 #> [415,] 0.1245973187 -2.277954e-01 #> [416,] 0.1221337714 -2.167632e-01 #> [417,] 0.1207147347 -2.080744e-01 #> [418,] 0.1205833303 -2.019462e-01 #> [419,] 0.1219868758 -1.985731e-01 #> [420,] 0.1251746763 -1.981249e-01 #> [421,] 0.1303957451 -2.007457e-01 #> [422,] 0.1378964703 -2.065525e-01 #> [423,] 0.1479182489 -2.156342e-01 #> [424,] 0.1606951045 -2.280504e-01 #> [425,] 0.1764513113 -2.438315e-01 #> [426,] 0.1953990416 -2.629782e-01 #> [427,] 0.2177360577 -2.854609e-01 #> [428,] 0.2436434683 -3.112207e-01 #> [429,] 0.2732835666 -3.401690e-01 #> [430,] 0.3067977706 -3.721887e-01 #> [431,] 0.3443046826 -4.071349e-01 #> [432,] 0.3858982853 -4.448357e-01 #> [433,] 0.4316462915 -4.850940e-01 #> [434,] 0.4815886611 -5.276885e-01 #> [435,] 0.5357363014 -5.723759e-01 #> [436,] 0.5940699617 -6.188922e-01 #> [437,] 0.6565393349 -6.669551e-01 #> [438,] 0.7230623754 -7.162661e-01 #> [439,] 0.7935248421 -7.665126e-01 #> [440,] 0.8677800724 -8.173707e-01 #> [441,] 0.9456489928 -8.685073e-01 #> [442,] 1.0269203697 -9.195827e-01 #> [443,] 1.1113513010 -9.702536e-01 #> [444,] 1.1986679491 -1.020175e+00 #> [445,] 1.2885665117 -1.069005e+00 #> [446,] 1.3807144290 -1.116402e+00 #> [447,] 1.4747518185 -1.162036e+00 #> [448,] 1.5702931325 -1.205583e+00 #> [449,] 1.6669290275 -1.246731e+00 #> [450,] 1.7642284357 -1.285184e+00 #> [451,] 1.8617408256 -1.320661e+00 #> [452,] 1.9589986377 -1.352900e+00 #> [453,] 2.0555198811 -1.381659e+00 #> [454,] 2.1508108725 -1.406721e+00 #> [455,] 2.2443691025 -1.427890e+00 #> [456,] 2.3356862074 -1.444999e+00 #> [457,] 2.4242510296 -1.457907e+00 #> [458,] 2.5095527440 -1.466500e+00 #> [459,] 2.5910840309 -1.470694e+00 #> [460,] 2.6683442720 -1.470437e+00 #> [461,] 2.7408427500 -1.465704e+00 #> [462,] 2.8081018272 -1.456504e+00 #> [463,] 2.8696600830 -1.442874e+00 #> [464,] 2.9250753866 -1.424882e+00 #> [465,] 2.9739278858 -1.402627e+00 #> [466,] 3.0158228871 -1.376237e+00 #> [467,] 3.0503936105 -1.345868e+00 #> [468,] 3.0773037961 -1.311704e+00 #> [469,] 3.0962501455 -1.273953e+00 #> [470,] 3.1069645794 -1.232850e+00 #> [471,] 3.1092162952 -1.188653e+00 #> [472,] 3.1028136086 -1.141638e+00 #> [473,] 3.0876055668 -1.092103e+00 #> [474,] 3.0634833183 -1.040361e+00 #> [475,] 3.0303812321 -9.867403e-01 #> [476,] 2.9882777541 -9.315820e-01 #> [477,] 2.9371959947 -8.752358e-01 #> [478,] 2.8772040430 -8.180593e-01 #> [479,] 2.8084150020 -7.604142e-01 #> [480,] 2.7309867450 -7.026646e-01 #> [481,] 2.6451213919 -6.451738e-01 #> [482,] 2.5510645094 -5.883018e-01 #> [483,] 2.4491040361 -5.324030e-01 #> [484,] 2.3395689420 -4.778231e-01 #> [485,] 2.2228276275 -4.248973e-01 #> [486,] 2.0992860718 -3.739474e-01 #> [487,] 1.9693857436 -3.252796e-01 #> [488,] 1.8336012848 -2.791826e-01 #> [489,] 1.6924379826 -2.359253e-01 #> [490,] 1.5464290467 -1.957551e-01 #> [491,] 1.3961327068 -1.588961e-01 #> [492,] 1.2421291512 -1.255476e-01 #> [493,] 1.0850173244 -9.588280e-02 #> [494,] 0.9254116045 -7.004754e-02 #> [495,] 0.7639383824 -4.815950e-02 #> [496,] 0.6012325644 -3.030744e-02 #> [497,] 0.4379340204 -1.655068e-02 #> [498,] 0.2746840012 -6.918859e-03 #> [499,] 0.1121215474 -1.411859e-03 #> [500,] -0.0491200860 1.203095e-17 # Butterflies of the vignette' cover panel(Out(a2l(replicate(100, rfourier_shape(nb.h=6, alpha=0.4, nb.pts=200, plot=FALSE)))))"},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"obtained efourier, otherwise message returned. rm_asym sets B C coefficients 0; rm_sym sets D coefficients 0.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"","code":"rm_asym(OutCoe) # S3 method for default rm_asym(OutCoe) # S3 method for OutCoe rm_asym(OutCoe) rm_sym(OutCoe) # S3 method for default rm_sym(OutCoe) # S3 method for OutCoe rm_sym(OutCoe)"},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"OutCoe OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":": first mention, two applications. Iwata, H., Niikura, S., Matsuura, S., Takano, Y., & Ukai, Y. (1998). Evaluation variation root shape Japanese radish (Raphanus sativus L.) based image analysis using elliptic Fourier descriptors. Euphytica, 102, 143-149. Iwata, H., Nesumi, H., Ninomiya, S., Takano, Y., & Ukai, Y. (2002). Evaluation Genotype x Environment Interactions Citrus Leaf Morphology Using Image Analysis Elliptic Fourier Descriptors. Breeding Science, 52(2), 89-94. doi:10.1270/jsbbs.52.89 Yoshioka, Y., Iwata, H., Ohsawa, R., & Ninomiya, S. (2004). Analysis petal shape variation Primula sieboldii elliptic fourier descriptors principal component analysis. Annals Botany, 94(5), 657-64. doi:10.1093/aob/mch190","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"","code":"botf <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details botSym <- rm_asym(botf) boxplot(botSym) botSymp <- PCA(botSym) plot(botSymp) #> will be deprecated soon, see ?plot_PCA plot(botSymp, amp.shp=5) #> will be deprecated soon, see ?plot_PCA # Asymmetric only botAsym <- rm_sym(botf) boxplot(botAsym) botAsymp <- PCA(botAsym) plot(botAsymp) #> will be deprecated soon, see ?plot_PCA # strange shapes because the original shape was mainly symmetric and would need its # symmetric (eg its average) for a proper reconstruction. Should only be used like that: plot(botAsymp, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes harmonics from Coe objects — rm_harm","title":"Removes harmonics from Coe objects — rm_harm","text":"Useful drop harmonics Coe objects. work Fourier-based approached since looks [-D][1-drop] pattern.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes harmonics from Coe objects — rm_harm","text":"","code":"rm_harm(x, drop = 1)"},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes harmonics from Coe objects — rm_harm","text":"x Coe object drop numeric number harmonics drop","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes harmonics from Coe objects — rm_harm","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes harmonics from Coe objects — rm_harm","text":"","code":"data(bot) bf <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) colnames(rm_harm(bf, 1)$coe) #> [1] \"A2\" \"A3\" \"A4\" \"A5\" \"A6\" \"A7\" \"A8\" \"A9\" \"B2\" \"B3\" \"B4\" \"B5\" \"B6\" \"B7\" \"B8\" #> [16] \"B9\" \"C2\" \"C3\" \"C4\" \"C5\" \"C6\" \"C7\" \"C8\" \"C9\" \"D2\" \"D3\" \"D4\" \"D5\" \"D6\" \"D7\" #> [31] \"D8\" \"D9\""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove shapes with missing data in fac — rm_missing","title":"Remove shapes with missing data in fac — rm_missing","text":"row (within given column specified) containing NA $fac corresponding shapes $coo, lines $coe objects also dropped.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove shapes with missing data in fac — rm_missing","text":"","code":"rm_missing(x, by)"},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove shapes with missing data in fac — rm_missing","text":"x object NA column $fac objects complete views","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove shapes with missing data in fac — rm_missing","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove shapes with missing data in fac — rm_missing","text":"","code":"bot$fac$type[3] <- NA bot$fac$fake[9] <- NA bot %>% length() #> [1] 40 bot %>% rm_missing() %>% length #> [1] 38 bot %>% rm_missing(\"fake\") %>% length() #> [1] 39"},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove shapes with incomplete slices — rm_uncomplete","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"Imagine take three views every object study. , can slice, filter chop entire dataset, morphometrics , want combine . forgotten one view, impossible obtain, one objects, combine work. function helps remove ugly ducklings. See examples","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"","code":"rm_uncomplete(x, id, by)"},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"x object remove uncomplete \"\" id objects, within $fac slot column $fac objects complete views","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"","code":"# we load olea data(olea) # we select the var Aglan since it is the only one complete ol <- filter(olea, var == \"Aglan\") # everything seems fine table(ol$view, ol$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 # indeed rm_uncomplete(ol, id=\"ind\", by=\"view\") #> all ids have 2 slices #> Opn (curves) #> - 60 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 60 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 54 more rows #> - also: $ldk # we mess the ol object by removing a single shape ol.pb <- slice(ol, -1) table(ol.pb$view, ol.pb$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 # the counterpart has been removed with a notice ol.ok <- rm_uncomplete(ol.pb, \"ind\", \"view\") #> those shapes did not have 2 slices and has been removed: O10 # now you can combine them table(ol.ok$view, ol.ok$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> VL 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 0 0 0 0 0 0 0 0 0 0 0 #> VL 0 0 0 0 0 0 0 0 0 0 0"},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":null,"dir":"Reference","previous_headings":"","what":"Renames levels on Momocs objects — rw_fac","title":"Renames levels on Momocs objects — rw_fac","text":"rw_fac stands 'rewriting rule'. Typically useful correct typos import, merge levels within covariates. Drops levels silently.","code":""},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Renames levels on Momocs objects — rw_fac","text":"","code":"rw_fac(x, fac, from, to)"},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Renames levels on Momocs objects — rw_fac","text":"x Momocs object fac id name $fac column look (fac_dispatcher yet supported) level(s) renamed; passed single several characters name used rename /levels","code":""},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Renames levels on Momocs objects — rw_fac","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Renames levels on Momocs objects — rw_fac","text":"","code":"# single renaming rw_fac(bot, \"type\", \"whisky\", \"agua_de_fuego\")$type # 1 instead of \"type\" is fine too #> type1 type2 type3 type4 type5 #> beer beer beer beer beer #> type6 type7 type8 type9 type10 #> beer beer beer beer beer #> type11 type12 type13 type14 type15 #> beer beer beer beer beer #> type16 type17 type18 type19 type20 #> beer beer beer beer beer #> type21 type22 type23 type24 type25 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type26 type27 type28 type29 type30 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type31 type32 type33 type34 type35 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type36 type37 type38 type39 type40 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> Levels: agua_de_fuego beer # several renaming bot2 <- mutate(bot, fake=factor(rep(letters[1:4], 10))) rw_fac(bot2, \"fake\", c(\"a\", \"e\"), \"ae\")$fake #> fake1 fake2 fake3 fake4 fake5 fake6 fake7 fake8 fake9 fake10 fake11 #> ae ae b c ae ae b c ae ae b #> fake12 fake13 fake14 fake15 fake16 fake17 fake18 fake19 fake20 fake21 fake22 #> c ae ae b c ae ae b c ae ae #> fake23 fake24 fake25 fake26 fake27 fake28 fake29 fake30 fake31 fake32 fake33 #> b c ae ae b c ae ae b c ae #> fake34 fake35 fake36 fake37 fake38 fake39 fake40 #> ae b c ae ae b c #> Levels: ae b c"},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample a fraction of shapes — sample_frac","title":"Sample a fraction of shapes — sample_frac","text":"Sample fraction shapes Momocs object. See examples ?dplyr::sample_n.","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample a fraction of shapes — sample_frac","text":"","code":"sample_frac(tbl, size, replace, fac, ...)"},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample a fraction of shapes — sample_frac","text":"tbl Momocs object (Coo, Coe) size numeric (0 < numeric <= 1) fraction shapes select replace logical whether sample done ot without replacement fac column name $fac defined; size applied within levels factor ... additional arguments dplyr::sample_frac maintain generic compatibility","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample a fraction of shapes — sample_frac","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Sample a fraction of shapes — sample_frac","text":"resulting fraction rounded ceiling.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample a fraction of shapes — sample_frac","text":"","code":"# samples 50% of the bottles no matter their type sample_frac(bot, 0.5) #> Out (outlines) #> - 20 outlines, 158 +/- 22 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 20 × 2 #> type fake #> #> 1 beer d #> 2 whisky a #> 3 beer c #> 4 beer d #> 5 beer d #> 6 beer d #> # ℹ 14 more rows #> - also: $ldk # 80% bottles of beer and of whisky table(sample_frac(bot, 0.8, fac=\"type\")$fac) #> fake #> type a b c d #> beer 0 0 7 9 #> whisky 10 6 0 0 # bootstrap the same number of bootles of each type but with replacement table(names(sample_frac(bot, 1, replace=TRUE))) #> #> amrut bushmills caney chimay chivas #> 1 2 1 1 2 #> corona dalmore deusventrue glendronach glenmorangie #> 1 1 2 2 1 #> grimbergen guiness highlandpark hoegardeen jackdaniels #> 1 2 2 1 1 #> kingfisher latrappe lindemanskriek magallan makersmark #> 1 1 3 2 1 #> nicechouffe redbreast tamdhu westmalle wildturkey #> 1 1 1 1 2 #> yoichi #> 5"},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample n shapes — sample_n","title":"Sample n shapes — sample_n","text":"Sample n shapes Momocs object. See examples ?dplyr::sample_n.","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample n shapes — sample_n","text":"","code":"sample_n(tbl, size, replace, fac, ...)"},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample n shapes — sample_n","text":"tbl Momocs object (Coo, Coe) size numeric many shapes sample replace logical whether sample done ot without replacement fac column name $fac defined; size applied within levels factor ... additional arguments dplyr::sample_n maintain generic compatibility","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample n shapes — sample_n","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample n shapes — sample_n","text":"","code":"# samples 5 bottles no matter their type sample_n(bot, 5) #> Out (outlines) #> - 5 outlines, 165 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 5 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky b #> 4 whisky a #> 5 whisky a #> - also: $ldk # 5 bottles of beer and of whisky table(sample_n(bot, 5, fac=\"type\")$type) #> #> beer whisky #> 5 5 # many repetitions table(names(sample_n(bot, 400, replace=TRUE))) #> #> amrut ballantines brahma bushmills caney #> 9 8 8 10 11 #> chimay chivas corona dalmore deusventrue #> 14 9 16 17 6 #> duvel famousgrouse franziskaner glendronach glenmorangie #> 11 13 11 14 11 #> grimbergen guiness highlandpark hoegardeen jackdaniels #> 8 7 9 9 8 #> jb johnniewalker jupiler kingfisher latrappe #> 11 10 11 14 14 #> lindemanskriek magallan makersmark nicechouffe oban #> 7 17 6 4 7 #> oldpotrero pecheresse redbreast sierranevada tamdhu #> 10 10 14 9 10 #> tanglefoot tauro westmalle wildturkey yoichi #> 6 4 7 12 8"},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":null,"dir":"Reference","previous_headings":"","what":"How many axes to retain this much of variance or trace ? — scree","title":"How many axes to retain this much of variance or trace ? — scree","text":"set functions around PCA/LDA eigen/trace. scree calculates proportion cumulated proportion; scree_min returns minimal number axis use retain given proportion; scree_plot displays screeplot.","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"How many axes to retain this much of variance or trace ? — scree","text":"","code":"scree(x, nax) # S3 method for PCA scree(x, nax) # S3 method for LDA scree(x, nax) scree_min(x, prop) scree_plot(x, nax)"},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"How many axes to retain this much of variance or trace ? — scree","text":"x PCA object nax numeric range axes consider. default scree_min, display 0.99 scree_plot prop numeric many axes enough gather proportion variance. Default 1, axes returned defaut 1: axis returned","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"How many axes to retain this much of variance or trace ? — scree","text":"scree returns data.frame, scree_min numeric, scree_plot ggplot.","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"How many axes to retain this much of variance or trace ? — scree","text":"","code":"# On PCA bp <- PCA(efourier(bot)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) scree(bp) #> # A tibble: 40 × 3 #> axis proportion cumsum #> #> 1 1 0.761 0.761 #> 2 2 0.170 0.931 #> 3 3 0.0294 0.960 #> 4 4 0.0135 0.974 #> 5 5 0.00860 0.982 #> 6 6 0.00719 0.990 #> 7 7 0.00306 0.993 #> 8 8 0.00190 0.994 #> 9 9 0.00159 0.996 #> 10 10 0.00122 0.997 #> # ℹ 30 more rows scree_min(bp, 0.99) #> [1] 7 scree_min(bp, 1) #> [1] 37 scree_plot(bp) scree_plot(bp, 1:5) # on LDA, it uses svd bl <- LDA(PCA(opoly(olea)), \"var\") #> 'nb.pts' missing and set to 91 #> 'degree' missing and set to 5 #> 4 PC retained scree(bl) #> # A tibble: 3 × 3 #> axis proportion cumsum #> #> 1 1 0.913 0.913 #> 2 2 0.0603 0.973 #> 3 3 0.0268 1"},{"path":"http://momx.github.io/Momocs/reference/select.html","id":null,"dir":"Reference","previous_headings":"","what":"Select columns by name — select","title":"Select columns by name — select","text":"Select variables name, $fac. Selected variables can also renamed fly. See examples ?dplyr::select.","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select columns by name — select","text":"","code":"select(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select columns by name — select","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select columns by name — select","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Select columns by name — select","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select columns by name — select","text":"","code":"olea #> Opn (curves) #> - 210 curves, 98 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk select(olea, var, view) # drops domes and ind #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 210 × 2 #> var view #> #> 1 Aglan VD #> 2 Aglan VL #> 3 Aglan VD #> 4 Aglan VL #> 5 Aglan VD #> 6 Aglan VL #> # ℹ 204 more rows #> - also: $ldk select(olea, variety=var, domesticated_status=domes, view) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 210 × 3 #> variety domesticated_status view #> #> 1 Aglan cult VD #> 2 Aglan cult VL #> 3 Aglan cult VD #> 4 Aglan cult VL #> 5 Aglan cult VD #> 6 Aglan cult VL #> # ℹ 204 more rows #> - also: $ldk # combine with filter with magrittr pipes # only dorsal views, and 'var' and 'domes' columns filter(olea, view==\"VD\") %>% select(var, domes) #> Opn (curves) #> - 120 curves, 99 +/- 3 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 120 × 2 #> var domes #> #> 1 Aglan cult #> 2 Aglan cult #> 3 Aglan cult #> 4 Aglan cult #> 5 Aglan cult #> 6 Aglan cult #> # ℹ 114 more rows #> - also: $ldk head(olea$fac) #> # A tibble: 6 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 # select some columns select(olea, domes, view) #> Opn (curves) #> - 210 curves, 98 +/- 3 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 210 × 2 #> domes view #> #> 1 cult VD #> 2 cult VL #> 3 cult VD #> 4 cult VL #> 5 cult VD #> 6 cult VL #> # ℹ 204 more rows #> - also: $ldk # remove some columns select(olea, -ind) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 210 × 3 #> var domes view #> #> 1 Aglan cult VD #> 2 Aglan cult VL #> 3 Aglan cult VD #> 4 Aglan cult VL #> 5 Aglan cult VD #> 6 Aglan cult VL #> # ℹ 204 more rows #> - also: $ldk # rename on the fly and select some columns select(olea, foo=domes) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 210 × 1 #> foo #> #> 1 cult #> 2 cult #> 3 cult #> 4 cult #> 5 cult #> 6 cult #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"sfourier computes radii variation Fourier analysis matrix list coordinates points equally spaced aong curvilinear abscissa.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"","code":"sfourier(x, nb.h) # S3 method for default sfourier(x, nb.h) # S3 method for Out sfourier(x, nb.h) # S3 method for list sfourier(x, nb.h)"},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"x list matrix coordinates object nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"list following components: vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients ao ao harmonic coefficient r vector radii lengths","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"implementation still quite experimental (Dec. 2016)","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"Renaud S, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"","code":"molars[4] %>% coo_center %>% coo_scale %>% coo_interpolate(1080) %>% coo_slidedirection(\"right\") %>% coo_sample(360) %T>% coo_plot(zoom=2) %>% sfourier(16) %>% sfourier_i() %>% coo_draw(bor=\"red\", points=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse radii variation Fourier transform — sfourier_i","title":"Inverse radii variation Fourier transform — sfourier_i","text":"sfourier_i uses inverse radii variation (equally spaced curvilinear abscissa) transformation calculate shape, given list Fourier coefficients, typically obtained computed sfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse radii variation Fourier transform — sfourier_i","text":"","code":"sfourier_i(rf, nb.h, nb.pts = 120, dtheta = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse radii variation Fourier transform — sfourier_i","text":"rf list ao, bn components, typically returned sfourier. nb.h integer. number harmonics calculate/use. nb.pts integer. number points calculate. dtheta logical. Whether use dtheta correction method. FALSE default. TRUE, tries correct angular difference reconstructed points; otherwise equal angles used.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse radii variation Fourier transform — sfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. angle vector angles used. r vector radii calculated.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse radii variation Fourier transform — sfourier_i","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse radii variation Fourier transform — sfourier_i","text":"","code":"coo <- coo_center(bot[1]) # centering is almost mandatory for sfourier family coo_plot(coo) rf <- sfourier(coo, 12) rf #> $an #> [1] 4.604028e-03 -2.999389e-01 -9.402145e-04 1.149290e-02 7.204731e-03 #> [6] -9.029436e-03 -3.801153e-04 -3.509909e-03 3.066128e-03 -1.605563e-04 #> [11] -5.282196e-05 -2.663480e-03 #> #> $bn #> [1] -5.890572e-03 3.958517e-02 -7.064423e-03 -2.988931e-03 1.291082e-02 #> [6] 2.814025e-03 -1.504084e-03 5.682629e-04 5.198896e-03 -3.561684e-05 #> [11] -1.358067e-03 2.234144e-03 #> #> $ao #> [1] 334.5633 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- sfourier_i(rf) coo_draw(rfi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'sfourier' shapes. — sfourier_shape","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"sfourier_shape calculates 'Fourier radii variation shape' given Fourier coefficients (see Details) can generate 'sfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"","code":"sfourier_shape(an, bn, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"sfourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See sfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"","code":"rf <- sfourier(bot[1], 24) sfourier_shape(rf$an, rf$bn) # equivalent to sfourier_i(rf) #> x y #> [1,] -0.290097233 0.000000e+00 #> [2,] -0.271959700 -2.167576e-02 #> [3,] -0.246484918 -3.954193e-02 #> [4,] -0.217733972 -5.296062e-02 #> [5,] -0.189896582 -6.253711e-02 #> [6,] -0.161756328 -6.794564e-02 #> [7,] -0.129280368 -6.684598e-02 #> [8,] -0.093457131 -5.816908e-02 #> [9,] -0.056911599 -4.204430e-02 #> [10,] -0.020498051 -1.782664e-02 #> [11,] 0.012003787 1.224487e-02 #> [12,] 0.037674640 4.510087e-02 #> [13,] 0.059580159 8.409685e-02 #> [14,] 0.077938313 1.309531e-01 #> [15,] 0.087952301 1.787227e-01 #> [16,] 0.089723461 2.260901e-01 #> [17,] 0.084960971 2.763655e-01 #> [18,] 0.070321004 3.163705e-01 #> [19,] 0.046429512 3.314256e-01 #> [20,] 0.019913853 3.334462e-01 #> [21,] -0.006649182 3.343630e-01 #> [22,] -0.031682610 3.176318e-01 #> [23,] -0.049327516 2.726987e-01 #> [24,] -0.057930387 2.191009e-01 #> [25,] -0.060592889 1.723788e-01 #> [26,] -0.056570309 1.275136e-01 #> [27,] -0.044606160 8.221929e-02 #> [28,] -0.026786000 4.118703e-02 #> [29,] -0.003378834 4.388307e-03 #> [30,] 0.025798149 -2.849944e-02 #> [31,] 0.058618676 -5.522233e-02 #> [32,] 0.094446012 -7.575806e-02 #> [33,] 0.130822044 -8.883054e-02 #> [34,] 0.161850879 -9.201979e-02 #> [35,] 0.189408545 -8.857751e-02 #> [36,] 0.220645564 -8.252378e-02 #> [37,] 0.252775395 -7.224049e-02 #> [38,] 0.279699320 -5.635869e-02 #> [39,] 0.302648329 -3.627852e-02 #> [40,] 0.317717406 -1.264133e-02 #> [41,] 0.314194975 1.250118e-02 #> [42,] 0.292885334 3.510823e-02 #> [43,] 0.262693915 5.293215e-02 #> [44,] 0.225005085 6.430404e-02 #> [45,] 0.180944070 6.767500e-02 #> [46,] 0.137869807 6.447525e-02 #> [47,] 0.097568618 5.547232e-02 #> [48,] 0.056393859 3.829245e-02 #> [49,] 0.016752301 1.343754e-02 #> [50,] -0.016789374 -1.581660e-02 #> [51,] -0.044589066 -4.925793e-02 #> [52,] -0.067069580 -8.710755e-02 #> [53,] -0.083178505 -1.278980e-01 #> [54,] -0.093570208 -1.724712e-01 #> [55,] -0.097166720 -2.190209e-01 #> [56,] -0.090346447 -2.570238e-01 #> [57,] -0.073587369 -2.783178e-01 #> [58,] -0.051890843 -2.868696e-01 #> [59,] -0.028919129 -2.899267e-01 #> [60,] -0.005779918 -2.906509e-01 #> [61,] 0.017359802 -2.906800e-01 #> [62,] 0.040168810 -2.867352e-01 #> [63,] 0.059710443 -2.686342e-01 #> [64,] 0.071446661 -2.324054e-01 #> [65,] 0.074293397 -1.872085e-01 #> [66,] 0.069720055 -1.416741e-01 #> [67,] 0.057052553 -9.586057e-02 #> [68,] 0.036028165 -5.085343e-02 #> [69,] 0.009821433 -1.175738e-02 #> [70,] -0.020089825 2.049331e-02 #> [71,] -0.055257428 4.805599e-02 #> [72,] -0.094037716 6.947178e-02 #> [73,] -0.132851358 8.268862e-02 #> [74,] -0.171860865 8.886274e-02 #> [75,] -0.210848274 8.856668e-02 #> [76,] -0.245371280 8.080615e-02 #> [77,] -0.272295567 6.623194e-02 #> [78,] -0.290646288 4.662644e-02 #> [79,] -0.297232987 2.369010e-02 #> [80,] -0.290097233 7.105333e-17 sfourier_shape() # not very interesting #> x y #> [1,] -0.945118007 0.000000e+00 #> [2,] -1.089655560 -8.684786e-02 #> [3,] -1.224220418 -1.963935e-01 #> [4,] -1.343537389 -3.267959e-01 #> [5,] -1.442069318 -4.749051e-01 #> [6,] -1.515125904 -6.364277e-01 #> [7,] -1.559856027 -8.065425e-01 #> [8,] -1.575773677 -9.807844e-01 #> [9,] -1.564617563 -1.155885e+00 #> [10,] -1.529566340 -1.330225e+00 #> [11,] -1.474053174 -1.503658e+00 #> [12,] -1.400572047 -1.676645e+00 #> [13,] -1.309892716 -1.848902e+00 #> [14,] -1.200988990 -2.017920e+00 #> [15,] -1.071767042 -2.177875e+00 #> [16,] -0.920422241 -2.319330e+00 #> [17,] -0.747034817 -2.429994e+00 #> [18,] -0.554907030 -2.496498e+00 #> [19,] -0.351185770 -2.506853e+00 #> [20,] -0.146498336 -2.453031e+00 #> [21,] 0.046394820 -2.333025e+00 #> [22,] 0.214638297 -2.151842e+00 #> [23,] 0.347504343 -1.921118e+00 #> [24,] 0.438218807 -1.657405e+00 #> [25,] 0.484901075 -1.379480e+00 #> [26,] 0.490363516 -1.105315e+00 #> [27,] 0.460828661 -8.494120e-01 #> [28,] 0.403923046 -6.210854e-01 #> [29,] 0.326508157 -4.240570e-01 #> [30,] 0.232951810 -2.573439e-01 #> [31,] 0.124314258 -1.171115e-01 #> [32,] -0.001340897 1.075575e-03 #> [33,] -0.147624087 1.002394e-01 #> [34,] -0.317886999 1.807336e-01 #> [35,] -0.513251749 2.400238e-01 #> [36,] -0.731178192 2.734684e-01 #> [37,] -0.964983613 2.757819e-01 #> [38,] -1.204450247 2.426936e-01 #> [39,] -1.437343375 1.722947e-01 #> [40,] -1.651408292 6.570619e-02 #> [41,] -1.836292173 -7.306234e-02 #> [42,] -1.984880367 -2.379280e-01 #> [43,] -2.093730023 -4.218812e-01 #> [44,] -2.162566216 -6.180382e-01 #> [45,] -2.193090184 -8.202390e-01 #> [46,] -2.187549211 -1.023014e+00 #> [47,] -2.147572924 -1.220996e+00 #> [48,] -2.073675643 -1.408063e+00 #> [49,] -1.965592490 -1.576662e+00 #> [50,] -1.823330567 -1.717688e+00 #> [51,] -1.648565296 -1.821184e+00 #> [52,] -1.445874819 -1.877850e+00 #> [53,] -1.223327227 -1.881028e+00 #> [54,] -0.992112686 -1.828689e+00 #> [55,] -0.765194301 -1.724804e+00 #> [56,] -0.555254267 -1.579625e+00 #> [57,] -0.372444248 -1.408637e+00 #> [58,] -0.222539419 -1.230271e+00 #> [59,] -0.106013852 -1.062835e+00 #> [60,] -0.018321147 -9.213033e-01 #> [61,] 0.048656444 -8.147245e-01 #> [62,] 0.104343507 -7.448305e-01 #> [63,] 0.156966287 -7.061831e-01 #> [64,] 0.211445246 -6.878001e-01 #> [65,] 0.268211852 -6.758548e-01 #> [66,] 0.323221424 -6.567994e-01 #> [67,] 0.369109956 -6.201842e-01 #> [68,] 0.397141945 -5.605622e-01 #> [69,] 0.399402278 -4.781304e-01 #> [70,] 0.370649888 -3.780940e-01 #> [71,] 0.309378472 -2.690586e-01 #> [72,] 0.217877577 -1.609604e-01 #> [73,] 0.101379497 -6.310007e-02 #> [74,] -0.033373044 1.725594e-02 #> [75,] -0.179667239 7.546911e-02 #> [76,] -0.332009446 1.093380e-01 #> [77,] -0.486653324 1.183713e-01 #> [78,] -0.641391147 1.028941e-01 #> [79,] -0.794775929 6.334533e-02 #> [80,] -0.945118007 2.314871e-16 sfourier_shape(nb.h=12) # better #> x y #> [1,] -3.73028216 0.000000e+00 #> [2,] -3.79081371 -3.021359e-01 #> [3,] -3.74114732 -6.001673e-01 #> [4,] -3.61177769 -8.785124e-01 #> [5,] -3.43507276 -1.131245e+00 #> [6,] -3.22637825 -1.355238e+00 #> [7,] -2.98195669 -1.541857e+00 #> [8,] -2.69374968 -1.676629e+00 #> [9,] -2.36746422 -1.749000e+00 #> [10,] -2.02848468 -1.764122e+00 #> [11,] -1.71086482 -1.745226e+00 #> [12,] -1.43868404 -1.722270e+00 #> [13,] -1.21456649 -1.714350e+00 #> [14,] -1.02323427 -1.719254e+00 #> [15,] -0.84545308 -1.717996e+00 #> [16,] -0.67059890 -1.689812e+00 #> [17,] -0.49955732 -1.624986e+00 #> [18,] -0.33920388 -1.526061e+00 #> [19,] -0.19602476 -1.399275e+00 #> [20,] -0.07446420 -1.246861e+00 #> [21,] 0.02125625 -1.068899e+00 #> [22,] 0.08706282 -8.728423e-01 #> [23,] 0.12298195 -6.798846e-01 #> [24,] 0.13720637 -5.189339e-01 #> [25,] 0.14417303 -4.101533e-01 #> [26,] 0.15553796 -3.505940e-01 #> [27,] 0.17054532 -3.143538e-01 #> [28,] 0.17457563 -2.684332e-01 #> [29,] 0.14836597 -1.926924e-01 #> [30,] 0.08076147 -8.921790e-02 #> [31,] -0.02595140 2.444779e-02 #> [32,] -0.16280016 1.305870e-01 #> [33,] -0.32648936 2.216922e-01 #> [34,] -0.52516205 2.985792e-01 #> [35,] -0.77085296 3.604918e-01 #> [36,] -1.06420436 3.980237e-01 #> [37,] -1.38501767 3.958232e-01 #> [38,] -1.69830982 3.422051e-01 #> [39,] -1.97268399 2.364661e-01 #> [40,] -2.19714866 8.742009e-02 #> [41,] -2.38344487 -9.483244e-02 #> [42,] -2.55272406 -3.059956e-01 #> [43,] -2.71784631 -5.476390e-01 #> [44,] -2.87509273 -8.216706e-01 #> [45,] -3.01006409 -1.125796e+00 #> [46,] -3.11033755 -1.454559e+00 #> [47,] -3.17270089 -1.803829e+00 #> [48,] -3.19899367 -2.172175e+00 #> [49,] -3.18554363 -2.555223e+00 #> [50,] -3.11700723 -2.936409e+00 #> [51,] -2.97140412 -3.282536e+00 #> [52,] -2.73341309 -3.550058e+00 #> [53,] -2.40622080 -3.699884e+00 #> [54,] -2.01370848 -3.711722e+00 #> [55,] -1.59238058 -3.589343e+00 #> [56,] -1.17931764 -3.355004e+00 #> [57,] -0.80341929 -3.038645e+00 #> [58,] -0.48285695 -2.669392e+00 #> [59,] -0.22670844 -2.272850e+00 #> [60,] -0.03722754 -1.872036e+00 #> [61,] 0.08884098 -1.487592e+00 #> [62,] 0.15903666 -1.135244e+00 #> [63,] 0.18276462 -8.222485e-01 #> [64,] 0.16785204 -5.459978e-01 #> [65,] 0.11761273 -2.963670e-01 #> [66,] 0.02989255 -6.074290e-02 #> [67,] -0.10145958 1.704739e-01 #> [68,] -0.28309891 3.995915e-01 #> [69,] -0.51751306 6.195225e-01 #> [70,] -0.79872291 8.147643e-01 #> [71,] -1.11093808 9.661547e-01 #> [72,] -1.43263632 1.058382e+00 #> [73,] -1.74574192 1.086575e+00 #> [74,] -2.04499551 1.057390e+00 #> [75,] -2.34006808 9.829441e-01 #> [76,] -2.64618338 8.714462e-01 #> [77,] -2.96731752 7.217568e-01 #> [78,] -3.28344281 5.267408e-01 #> [79,] -3.55279054 2.831649e-01 #> [80,] -3.73028216 9.136556e-16 sfourier_shape(nb.h=6, alpha=0.4, nb.pts=500) #> x y #> [1,] -4.627376537 0.000000e+00 #> [2,] -4.433329065 -5.582545e-02 #> [3,] -4.224758345 -1.064150e-01 #> [4,] -4.002543436 -1.512667e-01 #> [5,] -3.767629800 -1.899219e-01 #> [6,] -3.521024150 -2.219692e-01 #> [7,] -3.263788935 -2.470472e-01 #> [8,] -2.997036513 -2.648476e-01 #> [9,] -2.721923035 -2.751171e-01 #> [10,] -2.439642077 -2.776596e-01 #> [11,] -2.151418074 -2.723378e-01 #> [12,] -1.858499581 -2.590742e-01 #> [13,] -1.562152419 -2.378520e-01 #> [14,] -1.263652728 -2.087150e-01 #> [15,] -0.964280000 -1.717679e-01 #> [16,] -0.665310099 -1.271752e-01 #> [17,] -0.368008349 -7.516038e-02 #> [18,] -0.073622700 -1.600461e-02 #> [19,] 0.216622959 4.995549e-02 #> [20,] 0.501535323 1.223299e-01 #> [21,] 0.779957967 2.006780e-01 #> [22,] 1.050777396 2.845114e-01 #> [23,] 1.312928801 3.732977e-01 #> [24,] 1.565401492 4.664638e-01 #> [25,] 1.807243971 5.634001e-01 #> [26,] 2.037568623 6.634647e-01 #> [27,] 2.255555987 7.659880e-01 #> [28,] 2.460458599 8.702773e-01 #> [29,] 2.651604365 9.756215e-01 #> [30,] 2.828399466 1.081296e+00 #> [31,] 2.990330767 1.186570e+00 #> [32,] 3.136967724 1.290706e+00 #> [33,] 3.267963782 1.392973e+00 #> [34,] 3.383057253 1.492643e+00 #> [35,] 3.482071683 1.589005e+00 #> [36,] 3.564915697 1.681362e+00 #> [37,] 3.631582343 1.769040e+00 #> [38,] 3.682147928 1.851395e+00 #> [39,] 3.716770372 1.927811e+00 #> [40,] 3.735687085 1.997711e+00 #> [41,] 3.739212390 2.060557e+00 #> [42,] 3.727734519 2.115855e+00 #> [43,] 3.701712184 2.163158e+00 #> [44,] 3.661670782 2.202072e+00 #> [45,] 3.608198236 2.232254e+00 #> [46,] 3.541940509 2.253418e+00 #> [47,] 3.463596839 2.265338e+00 #> [48,] 3.373914701 2.267845e+00 #> [49,] 3.273684558 2.260832e+00 #> [50,] 3.163734428 2.244255e+00 #> [51,] 3.044924295 2.218130e+00 #> [52,] 2.918140422 2.182539e+00 #> [53,] 2.784289581 2.137621e+00 #> [54,] 2.644293265 2.083581e+00 #> [55,] 2.499081894 2.020679e+00 #> [56,] 2.349589075 1.949237e+00 #> [57,] 2.196745937 1.869630e+00 #> [58,] 2.041475583 1.782289e+00 #> [59,] 1.884687703 1.687693e+00 #> [60,] 1.727273364 1.586370e+00 #> [61,] 1.570100018 1.478893e+00 #> [62,] 1.414006763 1.365873e+00 #> [63,] 1.259799875 1.247959e+00 #> [64,] 1.108248641 1.125831e+00 #> [65,] 0.960081515 1.000197e+00 #> [66,] 0.815982618 8.717886e-01 #> [67,] 0.676588603 7.413547e-01 #> [68,] 0.542485892 6.096580e-01 #> [69,] 0.414208305 4.774694e-01 #> [70,] 0.292235085 3.455634e-01 #> [71,] 0.176989328 2.147129e-01 #> [72,] 0.068836826 8.568446e-02 #> [73,] -0.031914693 -4.076659e-02 #> [74,] -0.125015907 -1.639010e-01 #> [75,] -0.210275850 -2.830002e-01 #> [76,] -0.287561464 -3.973705e-01 #> [77,] -0.356796774 -5.063479e-01 #> [78,] -0.417961694 -6.093015e-01 #> [79,] -0.471090475 -7.056376e-01 #> [80,] -0.516269827 -7.948032e-01 #> [81,] -0.553636720 -8.762891e-01 #> [82,] -0.583375898 -9.496328e-01 #> [83,] -0.605717121 -1.014421e+00 #> [84,] -0.620932169 -1.070293e+00 #> [85,] -0.629331624 -1.116939e+00 #> [86,] -0.631261470 -1.154105e+00 #> [87,] -0.627099534 -1.181595e+00 #> [88,] -0.617251795 -1.199267e+00 #> [89,] -0.602148591 -1.207036e+00 #> [90,] -0.582240768 -1.204875e+00 #> [91,] -0.557995780 -1.192811e+00 #> [92,] -0.529893781 -1.170930e+00 #> [93,] -0.498423747 -1.139369e+00 #> [94,] -0.464079635 -1.098320e+00 #> [95,] -0.427356630 -1.048023e+00 #> [96,] -0.388747489 -9.887688e-01 #> [97,] -0.348739018 -9.208941e-01 #> [98,] -0.307808706 -8.447780e-01 #> [99,] -0.266421528 -7.608402e-01 #> [100,] -0.225026950 -6.695371e-01 #> [101,] -0.184056148 -5.713584e-01 #> [102,] -0.143919460 -4.668239e-01 #> [103,] -0.105004083 -3.564786e-01 #> [104,] -0.067672028 -2.408900e-01 #> [105,] -0.032258349 -1.206429e-01 #> [106,] 0.000930360 3.663704e-03 #> [107,] 0.031617179 1.314216e-01 #> [108,] 0.059555797 2.620170e-01 #> [109,] 0.084531157 3.948349e-01 #> [110,] 0.106359826 5.292628e-01 #> [111,] 0.124890076 6.646951e-01 #> [112,] 0.140001702 8.005368e-01 #> [113,] 0.151605574 9.362071e-01 #> [114,] 0.159642930 1.071143e+00 #> [115,] 0.164084435 1.204802e+00 #> [116,] 0.164929016 1.336668e+00 #> [117,] 0.162202475 1.466249e+00 #> [118,] 0.155955923 1.593086e+00 #> [119,] 0.146264033 1.716749e+00 #> [120,] 0.133223137 1.836846e+00 #> [121,] 0.116949199 1.953017e+00 #> [122,] 0.097575667 2.064943e+00 #> [123,] 0.075251245 2.172341e+00 #> [124,] 0.050137591 2.274971e+00 #> [125,] 0.022406980 2.372629e+00 #> [126,] -0.007760058 2.465155e+00 #> [127,] -0.040177094 2.552427e+00 #> [128,] -0.074654133 2.634364e+00 #> [129,] -0.110999897 2.710924e+00 #> [130,] -0.149024040 2.782103e+00 #> [131,] -0.188539275 2.847934e+00 #> [132,] -0.229363393 2.908485e+00 #> [133,] -0.271321155 2.963859e+00 #> [134,] -0.314246041 3.014189e+00 #> [135,] -0.357981845 3.059637e+00 #> [136,] -0.402384096 3.100393e+00 #> [137,] -0.447321296 3.136673e+00 #> [138,] -0.492675970 3.168710e+00 #> [139,] -0.538345508 3.196760e+00 #> [140,] -0.584242813 3.221092e+00 #> [141,] -0.630296726 3.241990e+00 #> [142,] -0.676452245 3.259746e+00 #> [143,] -0.722670536 3.274659e+00 #> [144,] -0.768928722 3.287031e+00 #> [145,] -0.815219480 3.297166e+00 #> [146,] -0.861550426 3.305363e+00 #> [147,] -0.907943314 3.311917e+00 #> [148,] -0.954433052 3.317116e+00 #> [149,] -1.001066541 3.321233e+00 #> [150,] -1.047901360 3.324532e+00 #> [151,] -1.095004306 3.327258e+00 #> [152,] -1.142449802 3.329639e+00 #> [153,] -1.190318193 3.331882e+00 #> [154,] -1.238693949 3.334174e+00 #> [155,] -1.287663792 3.336676e+00 #> [156,] -1.337314765 3.339528e+00 #> [157,] -1.387732261 3.342839e+00 #> [158,] -1.438998042 3.346696e+00 #> [159,] -1.491188260 3.351156e+00 #> [160,] -1.544371493 3.356251e+00 #> [161,] -1.598606842 3.361983e+00 #> [162,] -1.653942074 3.368329e+00 #> [163,] -1.710411865 3.375238e+00 #> [164,] -1.768036130 3.382633e+00 #> [165,] -1.826818484 3.390412e+00 #> [166,] -1.886744835 3.398450e+00 #> [167,] -1.947782128 3.406598e+00 #> [168,] -2.009877256 3.414689e+00 #> [169,] -2.072956149 3.422533e+00 #> [170,] -2.136923057 3.429927e+00 #> [171,] -2.201660027 3.436652e+00 #> [172,] -2.267026591 3.442474e+00 #> [173,] -2.332859667 3.447151e+00 #> [174,] -2.398973676 3.450435e+00 #> [175,] -2.465160879 3.452068e+00 #> [176,] -2.531191939 3.451794e+00 #> [177,] -2.596816695 3.449354e+00 #> [178,] -2.661765154 3.444494e+00 #> [179,] -2.725748693 3.436964e+00 #> [180,] -2.788461461 3.426521e+00 #> [181,] -2.849581979 3.412935e+00 #> [182,] -2.908774916 3.395985e+00 #> [183,] -2.965693039 3.375468e+00 #> [184,] -3.019979320 3.351197e+00 #> [185,] -3.071269177 3.323005e+00 #> [186,] -3.119192842 3.290745e+00 #> [187,] -3.163377841 3.254293e+00 #> [188,] -3.203451545 3.213552e+00 #> [189,] -3.239043804 3.168446e+00 #> [190,] -3.269789615 3.118929e+00 #> [191,] -3.295331819 3.064983e+00 #> [192,] -3.315323806 3.006617e+00 #> [193,] -3.329432188 2.943869e+00 #> [194,] -3.337339447 2.876805e+00 #> [195,] -3.338746512 2.805523e+00 #> [196,] -3.333375252 2.730147e+00 #> [197,] -3.320970870 2.650830e+00 #> [198,] -3.301304172 2.567752e+00 #> [199,] -3.274173686 2.481120e+00 #> [200,] -3.239407629 2.391167e+00 #> [201,] -3.196865687 2.298148e+00 #> [202,] -3.146440608 2.202341e+00 #> [203,] -3.088059580 2.104048e+00 #> [204,] -3.021685390 2.003584e+00 #> [205,] -2.947317354 1.901284e+00 #> [206,] -2.864991998 1.797499e+00 #> [207,] -2.774783494 1.692590e+00 #> [208,] -2.676803843 1.586927e+00 #> [209,] -2.571202796 1.480890e+00 #> [210,] -2.458167516 1.374862e+00 #> [211,] -2.337921982 1.269229e+00 #> [212,] -2.210726134 1.164378e+00 #> [213,] -2.076874767 1.060692e+00 #> [214,] -1.936696174 9.585491e-01 #> [215,] -1.790550564 8.583193e-01 #> [216,] -1.638828235 7.603634e-01 #> [217,] -1.481947546 6.650295e-01 #> [218,] -1.320352681 5.726511e-01 #> [219,] -1.154511226 4.835452e-01 #> [220,] -0.984911582 3.980103e-01 #> [221,] -0.812060220 3.163244e-01 #> [222,] -0.636478812 2.387439e-01 #> [223,] -0.458701243 1.655015e-01 #> [224,] -0.279270541 9.680565e-02 #> [225,] -0.098735734 3.283887e-02 #> [226,] 0.082351332 -2.624263e-02 #> [227,] 0.263439206 -8.030977e-02 #> [228,] 0.443980029 -1.292610e-01 #> [229,] 0.623432721 -1.730224e-01 #> [230,] 0.801266107 -2.115477e-01 #> [231,] 0.976961978 -2.448184e-01 #> [232,] 1.150018056 -2.728425e-01 #> [233,] 1.319950846 -2.956548e-01 #> [234,] 1.486298345 -3.133153e-01 #> [235,] 1.648622604 -3.259088e-01 #> [236,] 1.806512109 -3.335429e-01 #> [237,] 1.959583970 -3.363477e-01 #> [238,] 2.107485904 -3.344731e-01 #> [239,] 2.249897996 -3.280880e-01 #> [240,] 2.386534221 -3.173782e-01 #> [241,] 2.517143730 -3.025445e-01 #> [242,] 2.641511868 -2.838008e-01 #> [243,] 2.759460944 -2.613717e-01 #> [244,] 2.870850727 -2.354911e-01 #> [245,] 2.975578676 -2.063994e-01 #> [246,] 3.073579898 -1.743418e-01 #> [247,] 3.164826842 -1.395657e-01 #> [248,] 3.249328723 -1.023190e-01 #> [249,] 3.327130692 -6.284809e-02 #> [250,] 3.398312748 -2.139530e-02 #> [251,] 3.462988412 2.180249e-02 #> [252,] 3.521303171 6.651593e-02 #> [253,] 3.573432693 1.125248e-01 #> [254,] 3.619580855 1.596199e-01 #> [255,] 3.659977569 2.076038e-01 #> [256,] 3.694876447 2.562932e-01 #> [257,] 3.724552310 3.055188e-01 #> [258,] 3.749298571 3.551275e-01 #> [259,] 3.769424505 4.049823e-01 #> [260,] 3.785252431 4.549631e-01 #> [261,] 3.797114832 5.049672e-01 #> [262,] 3.805351432 5.549097e-01 #> [263,] 3.810306249 6.047228e-01 #> [264,] 3.812324661 6.543565e-01 #> [265,] 3.811750493 7.037775e-01 #> [266,] 3.808923154 7.529688e-01 #> [267,] 3.804174856 8.019294e-01 #> [268,] 3.797827914 8.506726e-01 #> [269,] 3.790192174 8.992255e-01 #> [270,] 3.781562572 9.476275e-01 #> [271,] 3.772216846 9.959287e-01 #> [272,] 3.762413426 1.044189e+00 #> [273,] 3.752389504 1.092476e+00 #> [274,] 3.742359318 1.140863e+00 #> [275,] 3.732512645 1.189428e+00 #> [276,] 3.723013520 1.238250e+00 #> [277,] 3.713999198 1.287412e+00 #> [278,] 3.705579358 1.336990e+00 #> [279,] 3.697835550 1.387062e+00 #> [280,] 3.690820904 1.437697e+00 #> [281,] 3.684560088 1.488959e+00 #> [282,] 3.679049519 1.540900e+00 #> [283,] 3.674257826 1.593565e+00 #> [284,] 3.670126556 1.646983e+00 #> [285,] 3.666571124 1.701171e+00 #> [286,] 3.663481986 1.756129e+00 #> [287,] 3.660726033 1.811841e+00 #> [288,] 3.658148195 1.868273e+00 #> [289,] 3.655573232 1.925372e+00 #> [290,] 3.652807708 1.983065e+00 #> [291,] 3.649642117 2.041258e+00 #> [292,] 3.645853154 2.099837e+00 #> [293,] 3.641206113 2.158667e+00 #> [294,] 3.635457372 2.217592e+00 #> [295,] 3.628356972 2.276435e+00 #> [296,] 3.619651246 2.335000e+00 #> [297,] 3.609085484 2.393070e+00 #> [298,] 3.596406612 2.450409e+00 #> [299,] 3.581365857 2.506766e+00 #> [300,] 3.563721386 2.561871e+00 #> [301,] 3.543240883 2.615441e+00 #> [302,] 3.519704048 2.667179e+00 #> [303,] 3.492905004 2.716779e+00 #> [304,] 3.462654575 2.763923e+00 #> [305,] 3.428782438 2.808289e+00 #> [306,] 3.391139102 2.849548e+00 #> [307,] 3.349597726 2.887372e+00 #> [308,] 3.304055742 2.921431e+00 #> [309,] 3.254436270 2.951399e+00 #> [310,] 3.200689328 2.976956e+00 #> [311,] 3.142792800 2.997792e+00 #> [312,] 3.080753184 3.013605e+00 #> [313,] 3.014606088 3.024111e+00 #> [314,] 2.944416478 3.029039e+00 #> [315,] 2.870278686 3.028141e+00 #> [316,] 2.792316158 3.021188e+00 #> [317,] 2.710680960 3.007976e+00 #> [318,] 2.625553034 2.988330e+00 #> [319,] 2.537139220 2.962102e+00 #> [320,] 2.445672038 2.929173e+00 #> [321,] 2.351408260 2.889461e+00 #> [322,] 2.254627259 2.842915e+00 #> [323,] 2.155629168 2.789522e+00 #> [324,] 2.054732853 2.729304e+00 #> [325,] 1.952273723 2.662321e+00 #> [326,] 1.848601387 2.588674e+00 #> [327,] 1.744077187 2.508499e+00 #> [328,] 1.639071619 2.421975e+00 #> [329,] 1.533961667 2.329317e+00 #> [330,] 1.429128070 2.230778e+00 #> [331,] 1.324952549 2.126652e+00 #> [332,] 1.221815014 2.017265e+00 #> [333,] 1.120090768 1.902982e+00 #> [334,] 1.020147745 1.784200e+00 #> [335,] 0.922343796 1.661348e+00 #> [336,] 0.827024043 1.534883e+00 #> [337,] 0.734518334 1.405291e+00 #> [338,] 0.645138807 1.273083e+00 #> [339,] 0.559177600 1.138791e+00 #> [340,] 0.476904708 1.002964e+00 #> [341,] 0.398566021 8.661696e-01 #> [342,] 0.324381551 7.289846e-01 #> [343,] 0.254543865 5.919958e-01 #> [344,] 0.189216744 4.557947e-01 #> [345,] 0.128534065 3.209738e-01 #> [346,] 0.072598937 1.881230e-01 #> [347,] 0.021483077 5.782568e-02 #> [348,] -0.024773551 -6.934495e-02 #> [349,] -0.066162841 -1.928298e-01 #> [350,] -0.102708380 -3.120876e-01 #> [351,] -0.134465034 -4.265987e-01 #> [352,] -0.161518265 -5.358683e-01 #> [353,] -0.183983198 -6.394304e-01 #> [354,] -0.202003441 -7.368507e-01 #> [355,] -0.215749669 -8.277298e-01 #> [356,] -0.225417978 -9.117059e-01 #> [357,] -0.231228029 -9.884580e-01 #> [358,] -0.233420990 -1.057708e+00 #> [359,] -0.232257302 -1.119221e+00 #> [360,] -0.228014273 -1.172813e+00 #> [361,] -0.220983540 -1.218343e+00 #> [362,] -0.211468397 -1.255725e+00 #> [363,] -0.199781029 -1.284918e+00 #> [364,] -0.186239670 -1.305936e+00 #> [365,] -0.171165703 -1.318842e+00 #> [366,] -0.154880737 -1.323751e+00 #> [367,] -0.137703676 -1.320828e+00 #> [368,] -0.119947813 -1.310286e+00 #> [369,] -0.101917969 -1.292390e+00 #> [370,] -0.083907703 -1.267447e+00 #> [371,] -0.066196621 -1.235813e+00 #> [372,] -0.049047805 -1.197883e+00 #> [373,] -0.032705378 -1.154094e+00 #> [374,] -0.017392248 -1.104919e+00 #> [375,] -0.003308021 -1.050866e+00 #> [376,] 0.009372866 -9.924735e-01 #> [377,] 0.020502798 -9.303053e-01 #> [378,] 0.029962396 -8.649498e-01 #> [379,] 0.037661667 -7.970141e-01 #> [380,] 0.043540906 -7.271203e-01 #> [381,] 0.047571307 -6.559008e-01 #> [382,] 0.049755300 -5.839945e-01 #> [383,] 0.050126593 -5.120419e-01 #> [384,] 0.048749926 -4.406810e-01 #> [385,] 0.045720529 -3.705422e-01 #> [386,] 0.041163292 -3.022446e-01 #> [387,] 0.035231645 -2.363908e-01 #> [388,] 0.028106155 -1.735634e-01 #> [389,] 0.019992857 -1.143202e-01 #> [390,] 0.011121318 -5.919034e-02 #> [391,] 0.001742456 -8.670729e-03 #> [392,] -0.007873869 3.677790e-02 #> [393,] -0.017441487 7.673421e-02 #> [394,] -0.026660735 1.108194e-01 #> [395,] -0.035221452 1.387000e-01 #> [396,] -0.042806122 1.600905e-01 #> [397,] -0.049093143 1.747553e-01 #> [398,] -0.053760193 1.825106e-01 #> [399,] -0.056487671 1.832260e-01 #> [400,] -0.056962178 1.768255e-01 #> [401,] -0.054880017 1.632880e-01 #> [402,] -0.049950676 1.426479e-01 #> [403,] -0.041900270 1.149949e-01 #> [404,] -0.030474909 8.047325e-02 #> [405,] -0.015443962 3.928130e-02 #> [406,] 0.003396802 -8.330104e-03 #> [407,] 0.026222243 -6.205918e-02 #> [408,] 0.053175058 -1.215553e-01 #> [409,] 0.084363200 -1.864212e-01 #> [410,] 0.119857537 -2.562160e-01 #> [411,] 0.159689775 -3.304580e-01 #> [412,] 0.203850648 -4.086285e-01 #> [413,] 0.252288427 -4.901746e-01 #> [414,] 0.304907735 -5.745141e-01 #> [415,] 0.361568698 -6.610389e-01 #> [416,] 0.422086443 -7.491195e-01 #> [417,] 0.486230956 -8.381099e-01 #> [418,] 0.553727293 -9.273516e-01 #> [419,] 0.624256173 -1.016179e+00 #> [420,] 0.697454933 -1.103923e+00 #> [421,] 0.772918855 -1.189917e+00 #> [422,] 0.850202861 -1.273503e+00 #> [423,] 0.928823565 -1.354032e+00 #> [424,] 1.008261682 -1.430874e+00 #> [425,] 1.087964768 -1.503418e+00 #> [426,] 1.167350287 -1.571081e+00 #> [427,] 1.245808989 -1.633307e+00 #> [428,] 1.322708566 -1.689576e+00 #> [429,] 1.397397580 -1.739407e+00 #> [430,] 1.469209627 -1.782357e+00 #> [431,] 1.537467710 -1.818031e+00 #> [432,] 1.601488808 -1.846081e+00 #> [433,] 1.660588581 -1.866207e+00 #> [434,] 1.714086213 -1.878166e+00 #> [435,] 1.761309336 -1.881767e+00 #> [436,] 1.801599004 -1.876876e+00 #> [437,] 1.834314694 -1.863415e+00 #> [438,] 1.858839286 -1.841367e+00 #> [439,] 1.874583988 -1.810772e+00 #> [440,] 1.880993174 -1.771726e+00 #> [441,] 1.877549095 -1.724387e+00 #> [442,] 1.863776434 -1.668967e+00 #> [443,] 1.839246654 -1.605735e+00 #> [444,] 1.803582132 -1.535012e+00 #> [445,] 1.756460015 -1.457173e+00 #> [446,] 1.697615797 -1.372639e+00 #> [447,] 1.626846559 -1.281880e+00 #> [448,] 1.544013874 -1.185407e+00 #> [449,] 1.449046324 -1.083772e+00 #> [450,] 1.341941624 -9.775617e-01 #> [451,] 1.222768332 -8.673937e-01 #> [452,] 1.091667110 -7.539138e-01 #> [453,] 0.948851551 -6.377897e-01 #> [454,] 0.794608527 -5.197074e-01 #> [455,] 0.629298075 -4.003658e-01 #> [456,] 0.453352805 -2.804720e-01 #> [457,] 0.267276829 -1.607361e-01 #> [458,] 0.071644204 -4.186650e-02 #> [459,] -0.132903085 7.543553e-02 #> [460,] -0.345657620 1.904806e-01 #> [461,] -0.565849492 3.025960e-01 #> [462,] -0.792649690 4.111309e-01 #> [463,] -1.025173911 5.154605e-01 #> [464,] -1.262486771 6.149909e-01 #> [465,] -1.503606402 7.091629e-01 #> [466,] -1.747509396 7.974565e-01 #> [467,] -1.993136078 8.793942e-01 #> [468,] -2.239396075 9.545447e-01 #> [469,] -2.485174143 1.022526e+00 #> [470,] -2.729336218 1.083007e+00 #> [471,] -2.970735659 1.135712e+00 #> [472,] -3.208219638 1.180420e+00 #> [473,] -3.440635644 1.216971e+00 #> [474,] -3.666838049 1.245260e+00 #> [475,] -3.885694707 1.265244e+00 #> [476,] -4.096093533 1.276938e+00 #> [477,] -4.296949032 1.280420e+00 #> [478,] -4.487208720 1.275823e+00 #> [479,] -4.665859408 1.263341e+00 #> [480,] -4.831933307 1.243224e+00 #> [481,] -4.984513904 1.215777e+00 #> [482,] -5.122741581 1.181357e+00 #> [483,] -5.245818935 1.140372e+00 #> [484,] -5.353015765 1.093276e+00 #> [485,] -5.443673693 1.040568e+00 #> [486,] -5.517210379 9.827848e-01 #> [487,] -5.573123322 9.205018e-01 #> [488,] -5.610993200 8.543250e-01 #> [489,] -5.630486731 7.848879e-01 #> [490,] -5.631359050 7.128469e-01 #> [491,] -5.613455564 6.388764e-01 #> [492,] -5.576713280 5.636637e-01 #> [493,] -5.521161607 4.879042e-01 #> [494,] -5.446922605 4.122960e-01 #> [495,] -5.354210692 3.375352e-01 #> [496,] -5.243331809 2.643103e-01 #> [497,] -5.114682038 1.932973e-01 #> [498,] -4.968745690 1.251549e-01 #> [499,] -4.806092870 6.051937e-02 #> [500,] -4.627376537 1.133380e-15 # Butterflies of the vignette' cover panel(Out(a2l(replicate(100, sfourier_shape(nb.h=6, alpha=0.4, nb.pts=200, plot=FALSE)))))"},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset based on positions — slice","title":"Subset based on positions — slice","text":"Select rows position, based $fac. See examples ?dplyr::slice.","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset based on positions — slice","text":"","code":"slice(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset based on positions — slice","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset based on positions — slice","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset based on positions — slice","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset based on positions — slice","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk slice(olea, 1) # if you only want the coordinates, try bot[1] #> Opn (curves) #> - 1 curves, 99 +/- NA coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 1 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> - also: $ldk slice(olea, 1:20) #> Opn (curves) #> - 20 curves, 99 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 20 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 14 more rows #> - also: $ldk slice(olea, 21:30) #> Opn (curves) #> - 10 curves, 100 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 10 × 4 #> var domes view ind #> #> 1 Aglan cult VD O1 #> 2 Aglan cult VL O1 #> 3 Aglan cult VD O20 #> 4 Aglan cult VL O20 #> 5 Aglan cult VD O21 #> 6 Aglan cult VL O21 #> # ℹ 4 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts partitions of sliding coordinates — slidings_scheme","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"Helper function deduces (likely reminder) partition scheme $slidings Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"","code":"slidings_scheme(Coo)"},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"Coo Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"list two components: n number partition; id position. NULL slidings defined","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"","code":"# no slidings defined a NULL is returned with a message slidings_scheme(wings) #> no sliding defined #> NULL # slidings defined slidings_scheme(chaff) #> $n #> [1] 4 #> #> $id #> start end #> partition1 13 52 #> partition2 53 92 #> partition3 93 132 #> partition4 133 172 #>"},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Family picture of shapes — stack","title":"Family picture of shapes — stack","text":"Plots outlines, graph, Coo (, Opn Ldk) object.","code":""},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family picture of shapes — stack","text":"","code":"# S3 method for Coo stack( x, cols, borders, fac, palette = col_summer, coo_sample = 120, points = FALSE, first.point = TRUE, centroid = TRUE, ldk = TRUE, ldk_pch = 3, ldk_col = \"#FF000055\", ldk_cex = 0.5, ldk_links = FALSE, ldk_confell = FALSE, ldk_contour = FALSE, ldk_chull = FALSE, ldk_labels = FALSE, xy.axis = TRUE, title = substitute(x), ... ) # S3 method for Ldk stack( x, cols, borders, first.point = TRUE, centroid = TRUE, ldk = TRUE, ldk_pch = 20, ldk_col = col_alpha(\"#000000\", 0.5), ldk_cex = 0.3, meanshape = FALSE, meanshape_col = \"#FF0000\", ldk_links = FALSE, ldk_confell = FALSE, ldk_contour = FALSE, ldk_chull = FALSE, ldk_labels = FALSE, slidings = TRUE, slidings_pch = \"\", xy.axis = TRUE, title = substitute(x), ... )"},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family picture of shapes — stack","text":"x Coo object plot. cols vector colors drawing outlines. Either single value length exactly equals number coordinates. borders vector colors drawing borders. Either single value length exactly equals number coordinates. fac factor within $fac slot colors palette color palette use fac provided coo_sample NULL number point per shape display (plot quickly) points logical whether draw points first.point logical whether draw first point centroid logical whether draw centroid ldk logical. Whether display landmarks (). ldk_pch pch landmarks ldk_col color landmarks ldk_cex cex landmarks ldk_links logical whether draw links (mean shape) ldk_confell logical whether draw conf ellipses ldk_contour logical whether draw contour lines ldk_chull logical whether draw convex hull ldk_labels logical whether draw landmark labels xy.axis whether draw x y axes title title plot. name Coo default ... arguments passed coo_plot meanshape logical whether add meanshape related stuff () meanshape_col color everything meanshape slidings logical whether draw slidings semi landmarks slidings_pch pch semi landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family picture of shapes — stack","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family picture of shapes — stack","text":"","code":"# \\donttest{ stack(bot) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details stack(bot.f) #> Warning: non-vector elements will be ignored #> [1] ind #> <0 rows> (or 0-length row.names) stack(mosquito, borders='#1A1A1A22', first.point=FALSE) stack(hearts) stack(hearts, ldk=FALSE) stack(hearts, borders='#1A1A1A22', ldk=TRUE, ldk_col=col_summer(4), ldk_pch=20) stack(hearts, fac=\"aut\", palette=col_sari) chaffal <- fgProcrustes(chaff) #> iteration: 1 \tgain: 75173 #> iteration: 2 \tgain: 0.037814 #> iteration: 3 \tgain: 0.0090566 #> iteration: 4 \tgain: 0.00034224 #> iteration: 5 \tgain: 0.0069657 #> iteration: 6 \tgain: 0.002451 #> iteration: 7 \tgain: 0.0006129 #> iteration: 8 \tgain: 4.8815e-05 #> iteration: 9 \tgain: 0.00046668 #> iteration: 10 \tgain: 0.00018849 #> iteration: 11 \tgain: 2.4521e-05 #> iteration: 12 \tgain: 2.9766e-06 #> iteration: 13 \tgain: 2.4553e-05 #> iteration: 14 \tgain: 6.3825e-06 #> iteration: 15 \tgain: 5.1105e-06 #> iteration: 16 \tgain: 8.2596e-07 #> iteration: 17 \tgain: 2.8678e-06 #> iteration: 18 \tgain: 2.0472e-06 #> iteration: 19 \tgain: 6.5232e-07 #> iteration: 20 \tgain: 1.1298e-07 #> iteration: 21 \tgain: 1.3908e-07 #> iteration: 22 \tgain: 2.8327e-07 #> iteration: 23 \tgain: 2.1788e-07 #> iteration: 24 \tgain: 4.5583e-08 #> iteration: 25 \tgain: 7.0497e-08 #> iteration: 26 \tgain: 8.9792e-08 #> iteration: 27 \tgain: 5.538e-08 #> iteration: 28 \tgain: 1.2621e-08 #> iteration: 29 \tgain: 1.503e-08 #> iteration: 30 \tgain: 2.2108e-08 #> iteration: 31 \tgain: 1.4865e-08 #> iteration: 32 \tgain: 3.7216e-09 #> iteration: 33 \tgain: 3.8289e-09 #> iteration: 34 \tgain: 5.7787e-09 #> iteration: 35 \tgain: 3.9287e-09 #> iteration: 36 \tgain: 1.0587e-09 #> iteration: 37 \tgain: 9.259e-10 #> iteration: 38 \tgain: 1.4847e-09 #> iteration: 39 \tgain: 1.039e-09 #> iteration: 40 \tgain: 2.9925e-10 #> iteration: 41 \tgain: 2.2588e-10 #> iteration: 42 \tgain: 3.8255e-10 #> iteration: 43 \tgain: 2.7403e-10 #> iteration: 44 \tgain: 8.3659e-11 stack(chaffal, slidings=FALSE) stack(chaffal, meanshape=TRUE, meanshape_col=\"blue\") # }"},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":null,"dir":"Reference","previous_headings":"","what":"Subsetize various Momocs objects — subsetize","title":"Subsetize various Momocs objects — subsetize","text":"Subsetize wrapper around dplyr's verbs used directly.","code":""},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subsetize various Momocs objects — subsetize","text":"","code":"subsetize(x, subset, ...)"},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subsetize various Momocs objects — subsetize","text":"x Coo Coe object. subset logical taken $fac slot, indices. See examples. ... useless maintains consistence generic subset.","code":""},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subsetize various Momocs objects — subsetize","text":"subsetted object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subsetize various Momocs objects — subsetize","text":"","code":"# Do not use subset directly"},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":null,"dir":"Reference","previous_headings":"","what":"Calcuates symmetry indices on OutCoe objects — symmetry","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"OutCoe objects obtained efourier, calculates several indices matrix coefficients: AD, sum absolute values harmonic coefficients D; BC thing B C; amp sum absolute value harmonic coefficients sym ratio AD amp. See references details.","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"","code":"symmetry(OutCoe)"},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"OutCoe efourier objects","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"matrix 4 colums described .","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"call symmetry bilateral symmetry. comparing coefficients resulting efourier, AD responsible amplitude Fourier functions, BC phase, results plane fitted/reconstructed shapes symmetry. long shapes aligned along bilateral symmetry axis, can use approach coined Iwata et al., implemented Momocs.","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":": first mention, two applications. Iwata, H., Niikura, S., Matsuura, S., Takano, Y., & Ukai, Y. (1998). Evaluation variation root shape Japanese radish (Raphanus sativus L.) based image analysis using elliptic Fourier descriptors. Euphytica, 102, 143-149. Iwata, H., Nesumi, H., Ninomiya, S., Takano, Y., & Ukai, Y. (2002). Evaluation Genotype x Environment Interactions Citrus Leaf Morphology Using Image Analysis Elliptic Fourier Descriptors. Breeding Science, 52(2), 89-94. doi:10.1270/jsbbs.52.89 Yoshioka, Y., Iwata, H., Ohsawa, R., & Ninomiya, S. (2004). Analysis petal shape variation Primula sieboldii elliptic fourier descriptors principal component analysis. Annals Botany, 94(5), 657-64. doi:10.1093/aob/mch190","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details res <- symmetry(bot.f) hist(res[, 'sym'])"},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Tangent angle Fourier transform — tfourier","title":"Tangent angle Fourier transform — tfourier","text":"tfourier computes tangent angle Fourier analysis matrix list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tangent angle Fourier transform — tfourier","text":"","code":"tfourier(x, ...) # S3 method for default tfourier(x, nb.h, smooth.it = 0, norm = FALSE, ...) # S3 method for Out tfourier(x, nb.h = 40, smooth.it = 0, norm = TRUE, ...) # S3 method for list tfourier(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tangent angle Fourier transform — tfourier","text":"x list matrix coordinates ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform norm logical. Whether scale register new coordinates first point used sent origin.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tangent angle Fourier transform — tfourier","text":"list following components: ao ao harmonic coefficient vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients phi vector variation tangent angle t vector distance along perimeter expressed radians perimeter numeric. perimeter outline thetao numeric. first tangent angle x1 x-coordinate first point y1 y-coordinate first point.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Tangent angle Fourier transform — tfourier","text":"Silent message progress bars () options(\"verbose\"=FALSE). Directly borrowed Claude (2008), called fourier2 .","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Tangent angle Fourier transform — tfourier","text":"Zahn CT, Roskies RZ. 1972. Fourier Descriptors Plane Closed Curves. IEEE Transactions Computers C-21: 269-281. Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tangent angle Fourier transform — tfourier","text":"","code":"coo <- bot[1] coo_plot(coo) tf <- tfourier(coo, 12) tf #> $ao #> [1] 7.733739 #> #> $an #> [1] 0.04522478 -0.37556233 0.02768553 0.94117330 -0.39901487 -0.77638246 #> [7] -0.57686667 0.04409017 -0.76045376 -0.46366388 -0.60869408 -0.14084193 #> #> $bn #> [1] 0.008457058 2.526564125 -0.554083930 0.313312077 -0.288987146 #> [6] 0.032821965 -0.226300468 0.409651090 -0.021830547 0.015586993 #> [11] 0.414880500 0.677636372 #> #> $phi #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $t #> [1] 0.00000000 0.04553033 0.09106066 0.13659098 0.18212131 0.22765164 #> [7] 0.27318197 0.31871230 0.36424263 0.40977295 0.45530328 0.50083361 #> [13] 0.54636394 0.59189427 0.63742460 0.68295492 0.72848525 0.77401558 #> [19] 0.81954591 0.86507624 0.91060657 0.95613689 1.00166722 1.04719755 #> [25] 1.09272788 1.13825821 1.18378854 1.22931886 1.27484919 1.32037952 #> [31] 1.36590985 1.41144018 1.45697051 1.50250083 1.54803116 1.59356149 #> [37] 1.63909182 1.68462215 1.73015248 1.77568280 1.82121313 1.86674346 #> [43] 1.91227379 1.95780412 2.00333445 2.04886477 2.09439510 2.13992543 #> [49] 2.18545576 2.23098609 2.27651642 2.32204674 2.36757707 2.41310740 #> [55] 2.45863773 2.50416806 2.54969839 2.59522871 2.64075904 2.68628937 #> [61] 2.73181970 2.77735003 2.82288036 2.86841068 2.91394101 2.95947134 #> [67] 3.00500167 3.05053200 3.09606233 3.14159265 3.18712298 3.23265331 #> [73] 3.27818364 3.32371397 3.36924430 3.41477462 3.46030495 3.50583528 #> [79] 3.55136561 3.59689594 3.64242627 3.68795659 3.73348692 3.77901725 #> [85] 3.82454758 3.87007791 3.91560823 3.96113856 4.00666889 4.05219922 #> [91] 4.09772955 4.14325988 4.18879020 4.23432053 4.27985086 4.32538119 #> [97] 4.37091152 4.41644185 4.46197217 4.50750250 4.55303283 4.59856316 #> [103] 4.64409349 4.68962382 4.73515414 4.78068447 4.82621480 4.87174513 #> [109] 4.91727546 4.96280579 5.00833611 5.05386644 5.09939677 5.14492710 #> [115] 5.19045743 5.23598776 5.28151808 5.32704841 5.37257874 5.41810907 #> [121] 5.46363940 5.50916973 5.55470005 5.60023038 5.64576071 5.69129104 #> [127] 5.73682137 5.78235170 5.82788202 5.87341235 5.91894268 5.96447301 #> [133] 6.01000334 6.05553367 6.10106399 6.14659432 6.19212465 6.23765498 #> #> $perimeter #> [1] 2513.886 #> #> $thetao #> [1] -1.508378 #> #> $x1 #> [1] 37 #> #> $y1 #> [1] 561 #> tfi <- tfourier_i(tf) coo_draw(tfi, border='red', col=NA) # the outline is not closed... coo_draw(tfourier_i(tf, force2close=TRUE), border='blue', col=NA) # we force it to close."},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse tangent angle Fourier transform — tfourier_i","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"tfourier_i uses inverse tangent angle Fourier transformation calculate shape, given list Fourier coefficients, typically obtained computed tfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"","code":"tfourier_i( tf, nb.h, nb.pts = 120, force2close = FALSE, rescale = TRUE, perim = 2 * pi, thetao = 0 )"},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"tf list ao, bn components, typically returned tfourier nb.h integer. number harmonics calculate/use nb.pts integer. number points calculate force2close logical. Whether force outlines calculated close (see coo_force2close). rescale logical. Whether rescale points calculated perimeter equals perim. perim perimeter length rescale shapes. thetao numeric. Radius angle reference (radians)","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. phi vector interpolated changes tangent angle. angle vector position perimeter (radians).","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"See tfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"Directly borrowed Claude (2008), called ifourier2 .","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"Zahn CT, Roskies RZ. 1972. Fourier Descriptors Plane Closed Curves. IEEE Transactions Computers C-21: 269-281. Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"","code":"tfourier(bot[1], 24) #> $ao #> [1] 7.733739 #> #> $an #> [1] 0.0452247795 -0.3755623338 0.0276855331 0.9411732992 -0.3990148731 #> [6] -0.7763824605 -0.5768666699 0.0440901651 -0.7604537570 -0.4636638848 #> [11] -0.6086940781 -0.1408419257 -0.2906453466 0.1360186290 -0.2905320818 #> [16] -0.0013913889 0.0999975983 0.2531539067 -0.2409440735 -0.0107735036 #> [21] -0.0386305555 -0.0238992918 -0.1631252535 -0.0004085881 #> #> $bn #> [1] 0.008457058 2.526564125 -0.554083930 0.313312077 -0.288987146 #> [6] 0.032821965 -0.226300468 0.409651090 -0.021830547 0.015586993 #> [11] 0.414880500 0.677636372 0.197011887 0.180444429 0.433515510 #> [16] 0.237573437 0.107717915 0.027571558 0.054653201 -0.170505441 #> [21] 0.130595490 -0.014178384 -0.048221455 -0.127039009 #> #> $phi #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $t #> [1] 0.00000000 0.04553033 0.09106066 0.13659098 0.18212131 0.22765164 #> [7] 0.27318197 0.31871230 0.36424263 0.40977295 0.45530328 0.50083361 #> [13] 0.54636394 0.59189427 0.63742460 0.68295492 0.72848525 0.77401558 #> [19] 0.81954591 0.86507624 0.91060657 0.95613689 1.00166722 1.04719755 #> [25] 1.09272788 1.13825821 1.18378854 1.22931886 1.27484919 1.32037952 #> [31] 1.36590985 1.41144018 1.45697051 1.50250083 1.54803116 1.59356149 #> [37] 1.63909182 1.68462215 1.73015248 1.77568280 1.82121313 1.86674346 #> [43] 1.91227379 1.95780412 2.00333445 2.04886477 2.09439510 2.13992543 #> [49] 2.18545576 2.23098609 2.27651642 2.32204674 2.36757707 2.41310740 #> [55] 2.45863773 2.50416806 2.54969839 2.59522871 2.64075904 2.68628937 #> [61] 2.73181970 2.77735003 2.82288036 2.86841068 2.91394101 2.95947134 #> [67] 3.00500167 3.05053200 3.09606233 3.14159265 3.18712298 3.23265331 #> [73] 3.27818364 3.32371397 3.36924430 3.41477462 3.46030495 3.50583528 #> [79] 3.55136561 3.59689594 3.64242627 3.68795659 3.73348692 3.77901725 #> [85] 3.82454758 3.87007791 3.91560823 3.96113856 4.00666889 4.05219922 #> [91] 4.09772955 4.14325988 4.18879020 4.23432053 4.27985086 4.32538119 #> [97] 4.37091152 4.41644185 4.46197217 4.50750250 4.55303283 4.59856316 #> [103] 4.64409349 4.68962382 4.73515414 4.78068447 4.82621480 4.87174513 #> [109] 4.91727546 4.96280579 5.00833611 5.05386644 5.09939677 5.14492710 #> [115] 5.19045743 5.23598776 5.28151808 5.32704841 5.37257874 5.41810907 #> [121] 5.46363940 5.50916973 5.55470005 5.60023038 5.64576071 5.69129104 #> [127] 5.73682137 5.78235170 5.82788202 5.87341235 5.91894268 5.96447301 #> [133] 6.01000334 6.05553367 6.10106399 6.14659432 6.19212465 6.23765498 #> #> $perimeter #> [1] 2513.886 #> #> $thetao #> [1] -1.508378 #> #> $x1 #> [1] 37 #> #> $y1 #> [1] 561 #> tfourier_shape() #> x y #> [1,] 0.09561277 -0.004814825 #> [2,] 0.17323630 0.012512711 #> [3,] 0.24247674 0.051646046 #> [4,] 0.29748929 0.109085359 #> [5,] 0.33385352 0.179819356 #> [6,] 0.34893838 0.257909706 #> [7,] 0.34202693 0.337142828 #> [8,] 0.31420461 0.411651714 #> [9,] 0.26805270 0.476425605 #> [10,] 0.20721414 0.527653777 #> [11,] 0.13590836 0.562883614 #> [12,] 0.05846627 0.581004809 #> [13,] -0.02106025 0.582095153 #> [14,] -0.09918242 0.567175968 #> [15,] -0.17314294 0.537927066 #> [16,] -0.24097751 0.496404468 #> [17,] -0.30149084 0.444792525 #> [18,] -0.35417340 0.385208942 #> [19,] -0.39908549 0.319569319 #> [20,] -0.43673077 0.249508712 #> [21,] -0.46793577 0.176352003 #> [22,] -0.49374533 0.101122207 #> [23,] -0.51533859 0.024575573 #> [24,] -0.53396545 -0.052746453 #> [25,] -0.55090089 -0.130456468 #> [26,] -0.56741250 -0.208257641 #> [27,] -0.58473615 -0.285882037 #> [28,] -0.60405502 -0.363034076 #> [29,] -0.62647771 -0.439341866 #> [30,] -0.65301277 -0.514318839 #> [31,] -0.68453815 -0.587338057 #> [32,] -0.72176597 -0.657621374 #> [33,] -0.76520472 -0.724245173 #> [34,] -0.81512229 -0.786163607 #> [35,] -0.87151466 -0.842248868 #> [36,] -0.93408535 -0.891346370 #> [37,] -1.00224041 -0.932340801 #> [38,] -1.07510266 -0.964227287 #> [39,] -1.15154679 -0.986180670 #> [40,] -1.23025448 -0.997615508 #> [41,] -1.30978610 -0.998229998 #> [42,] -1.38866314 -0.988028677 #> [43,] -1.46545414 -0.967321231 #> [44,] -1.53885612 -0.936697614 #> [45,] -1.60776454 -0.896982570 #> [46,] -1.67132626 -0.849175003 #> [47,] -1.72897228 -0.794379083 #> [48,] -1.78042991 -0.733734485 #> [49,] -1.82571635 -0.668352569 #> [50,] -1.86511718 -0.599264002 #> [51,] -1.89915498 -0.527381571 #> [52,] -1.92855271 -0.453480087 #> [53,] -1.95419642 -0.378193596 #> [54,] -1.97710051 -0.302028917 #> [55,] -1.99837709 -0.225393658 #> [56,] -2.01920947 -0.148636458 #> [57,] -2.04082810 -0.072096988 #> [58,] -2.06448584 0.003836979 #> [59,] -2.09142827 0.078668531 #> [60,] -2.12285438 0.151730528 #> [61,] -2.15986277 0.222129640 #> [62,] -2.20337967 0.288702417 #> [63,] -2.25406724 0.349992107 #> [64,] -2.31221382 0.404256561 #> [65,] -2.37761297 0.449518103 #> [66,] -2.44944361 0.483665071 #> [67,] -2.52616994 0.504610845 #> [68,] -2.60548492 0.510509188 #> [69,] -2.68432347 0.500014501 #> [70,] -2.75896986 0.472563240 #> [71,] -2.82527534 0.428640136 #> [72,] -2.87898770 0.369983183 #> [73,] -2.91617419 0.299677983 #> [74,] -2.93369646 0.222098182 #> [75,] -2.92967593 0.142665876 #> [76,] -2.90387517 0.067433061 #> [77,] -2.85792168 0.002518250 #> [78,] -2.79531652 -0.046535279 #> [79,] -2.72120119 -0.075389641 #> [80,] -2.64189714 -0.081433142"},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draws 'tfourier' shapes. — tfourier_shape","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"tfourier_shape calculates 'Fourier tangent angle shape' given Fourier coefficients (see Details) can generate 'tfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"","code":"tfourier_shape(an, bn, ao = 0, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. ao ao Harmonic coefficient. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"","code":"tf <- tfourier(bot[1], 24) tfourier_shape(tf$an, tf$bn) # equivalent to rfourier_i(rf) #> x y #> [1,] -0.068536123 0.03816985 #> [2,] 0.010421770 0.02861438 #> [3,] -0.063790622 0.05721817 #> [4,] -0.140579972 0.07793172 #> [5,] -0.183238239 0.14505793 #> [6,] -0.247181702 0.19235370 #> [7,] -0.320133871 0.22403393 #> [8,] -0.368197883 0.28740195 #> [9,] -0.418456077 0.34904422 #> [10,] -0.483991433 0.39410832 #> [11,] -0.527015593 0.46100060 #> [12,] -0.558482563 0.53404501 #> [13,] -0.615378810 0.58961904 #> [14,] -0.666002527 0.65096148 #> [15,] -0.703250243 0.72123426 #> [16,] -0.768466384 0.76675910 #> [17,] -0.843721723 0.79249409 #> [18,] -0.920086430 0.81472216 #> [19,] -0.990492372 0.77772677 #> [20,] -1.035089701 0.71187289 #> [21,] -1.107991534 0.68007700 #> [22,] -1.173409209 0.63484224 #> [23,] -1.172271234 0.55531639 #> [24,] -1.245117865 0.52339423 #> [25,] -1.169306190 0.54744097 #> [26,] -1.166890972 0.46794366 #> [27,] -1.134401707 0.39534818 #> [28,] -1.068636587 0.35062006 #> [29,] -1.007856315 0.29932275 #> [30,] -0.955597746 0.23936695 #> [31,] -0.898595892 0.18390125 #> [32,] -0.832707879 0.13935435 #> [33,] -0.769939719 0.09050956 #> [34,] -0.718591641 0.02977217 #> [35,] -0.653105984 -0.01536412 #> [36,] -0.579711689 -0.04600613 #> [37,] -0.541356302 -0.11568052 #> [38,] -0.489158357 -0.17568911 #> [39,] -0.526675851 -0.10555999 #> [40,] -0.483094002 -0.17209027 #> [41,] -0.411233403 -0.20617413 #> [42,] -0.384991638 -0.28125426 #> [43,] -0.346581120 -0.35089827 #> [44,] -0.281483742 -0.39659277 #> [45,] -0.223918101 -0.45147312 #> [46,] -0.163346561 -0.50301673 #> [47,] -0.086698985 -0.52424890 #> [48,] -0.009264515 -0.54240265 #> [49,] 0.061119622 -0.57943951 #> [50,] 0.129392040 -0.62023819 #> [51,] 0.196505793 -0.66291605 #> [52,] 0.256624481 -0.71498715 #> [53,] 0.315395180 -0.76857503 #> [54,] 0.379092808 -0.81620137 #> [55,] 0.442596932 -0.86408541 #> [56,] 0.501564226 -0.91745689 #> [57,] 0.558878373 -0.97259983 #> [58,] 0.616862632 -1.02703770 #> [59,] 0.683127662 -1.07102180 #> [60,] 0.761505112 -1.05750770 #> [61,] 0.789105491 -0.98291631 #> [62,] 0.836639557 -0.91914980 #> [63,] 0.850183366 -0.99752212 #> [64,] 0.787935223 -0.94801632 #> [65,] 0.760460379 -0.87337860 #> [66,] 0.699791505 -0.82194959 #> [67,] 0.638226839 -0.77159636 #> [68,] 0.596708767 -0.70375901 #> [69,] 0.552733618 -0.63748804 #> [70,] 0.492705339 -0.58531274 #> [71,] 0.437325328 -0.52822763 #> [72,] 0.414799359 -0.45195026 #> [73,] 0.364582422 -0.39027438 #> [74,] 0.378601540 -0.46856307 #> [75,] 0.344461362 -0.39672921 #> [76,] 0.268368346 -0.37358815 #> [77,] 0.341471182 -0.34225716 #> [78,] 0.264568188 -0.36254472 #> [79,] 0.260420375 -0.28311896 #> [80,] 0.189614910 -0.24689408 tfourier_shape() #> x y #> [1,] 0.001516715 0.05327275 #> [2,] 0.015779539 0.13151742 #> [3,] 0.030251198 0.20972373 #> [4,] 0.045538391 0.28777472 #> [5,] 0.062199796 0.36554395 #> [6,] 0.080739961 0.44288681 #> [7,] 0.101603447 0.51963556 #> [8,] 0.125169341 0.59559808 #> [9,] 0.151746433 0.67056016 #> [10,] 0.181569435 0.74429105 #> [11,] 0.214796683 0.81655173 #> [12,] 0.251509688 0.88710534 #> [13,] 0.291714820 0.95572897 #> [14,] 0.335347235 1.02222610 #> [15,] 0.382276925 1.08643872 #> [16,] 0.432316607 1.14825850 #> [17,] 0.485230944 1.20763635 #> [18,] 0.540746428 1.26458972 #> [19,] 0.598561178 1.31920758 #> [20,] 0.658353875 1.37165269 #> [21,] 0.719791053 1.42216139 #> [22,] 0.782532121 1.47104098 #> [23,] 0.846231576 1.51866487 #> [24,] 0.910538094 1.56546580 #> [25,] 0.975090367 1.61192718 #> [26,] 1.039509789 1.65857259 #> [27,] 1.103390319 1.70595332 #> [28,] 1.166286114 1.75463365 #> [29,] 1.227697771 1.80517338 #> [30,] 1.287058321 1.85810712 #> [31,] 1.343720418 1.91391987 #> [32,] 1.396946475 1.97301845 #> [33,] 1.445903783 2.03569889 #> [34,] 1.489666884 2.10211009 #> [35,] 1.527229520 2.17221504 #> [36,] 1.557528380 2.24575166 #> [37,] 1.579480384 2.32219618 #> [38,] 1.592034458 2.40073312 #> [39,] 1.594237457 2.48023660 #> [40,] 1.585312261 2.55926822 #> [41,] 1.564744045 2.63609662 #> [42,] 1.532368623 2.70874295 #> [43,] 1.488454817 2.77505458 #> [44,] 1.433771343 2.83280728 #> [45,] 1.369628237 2.87983193 #> [46,] 1.297883552 2.91415912 #> [47,] 1.220908256 2.93417060 #> [48,] 1.141505884 2.93874434 #> [49,] 1.062788251 2.92737817 #> [50,] 0.988013858 2.90027751 #> [51,] 0.920400814 2.85839515 #> [52,] 0.862930169 2.80341533 #> [53,] 0.818157940 2.73768023 #> [54,] 0.788054092 2.66406356 #> [55,] 0.773884313 2.58580199 #> [56,] 0.776145825 2.50630016 #> [57,] 0.794562342 2.42892776 #> [58,] 0.828136648 2.35682768 #> [59,] 0.875253046 2.29275194 #> [60,] 0.933817055 2.23893825 #> [61,] 1.001416873 2.19703455 #> [62,] 1.075490376 2.16807299 #> [63,] 1.153482821 2.15248985 #> [64,] 1.232983360 2.15018335 #> [65,] 1.311832391 2.16059902 #> [66,] 1.388195950 2.18283104 #> [67,] 1.460607221 2.21572881 #> [68,] 1.527978325 2.25799925 #> [69,] 1.589587611 2.30829788 #> [70,] 1.645048769 2.36530416 #> [71,] 1.694268193 2.42777898 #> [72,] 1.737396454 2.49460419 #> [73,] 1.774778736 2.56480548 #> [74,] 1.806907834 2.63756108 #> [75,] 1.834382083 2.71219901 #> [76,] 1.857869426 2.78818586 #> [77,] 1.878077959 2.86510966 #> [78,] 1.895732549 2.94265946 #> [79,] 1.911556753 3.02060335 #> [80,] 1.926258977 3.09876664 tfourier_shape(nb.h=6, alpha=0.4, nb.pts=500) #> x y #> [1,] -0.002108631 -0.01142224 #> [2,] -0.002501370 -0.02400767 #> [3,] -0.001880612 -0.03658391 #> [4,] -0.000235429 -0.04906752 #> [5,] 0.002435011 -0.06137264 #> [6,] 0.006121025 -0.07341260 #> [7,] 0.010802278 -0.08510161 #> [8,] 0.016447951 -0.09635655 #> [9,] 0.023017214 -0.10709862 #> [10,] 0.030460003 -0.11725500 #> [11,] 0.038718070 -0.12676034 #> [12,] 0.047726285 -0.13555803 #> [13,] 0.057414131 -0.14360122 #> [14,] 0.067707341 -0.15085360 #> [15,] 0.078529617 -0.15728987 #> [16,] 0.089804362 -0.16289588 #> [17,] 0.101456362 -0.16766852 #> [18,] 0.113413364 -0.17161534 #> [19,] 0.125607495 -0.17475387 #> [20,] 0.137976476 -0.17711088 #> [21,] 0.150464609 -0.17872140 #> [22,] 0.163023508 -0.17962766 #> [23,] 0.175612571 -0.17987805 #> [24,] 0.188199205 -0.17952609 #> [25,] 0.200758787 -0.17862936 #> [26,] 0.213274414 -0.17724866 #> [27,] 0.225736438 -0.17544723 #> [28,] 0.238141825 -0.17329001 #> [29,] 0.250493362 -0.17084322 #> [30,] 0.262798730 -0.16817392 #> [31,] 0.275069481 -0.16534976 #> [32,] 0.287319934 -0.16243881 #> [33,] 0.299566006 -0.15950949 #> [34,] 0.311824005 -0.15663048 #> [35,] 0.324109401 -0.15387072 #> [36,] 0.336435595 -0.15129931 #> [37,] 0.348812707 -0.14898537 #> [38,] 0.361246402 -0.14699779 #> [39,] 0.373736791 -0.14540487 #> [40,] 0.386277437 -0.14427376 #> [41,] 0.398854497 -0.14366977 #> [42,] 0.411446043 -0.14365552 #> [43,] 0.424021608 -0.14428985 #> [44,] 0.436541994 -0.14562670 #> [45,] 0.448959372 -0.14771379 #> [46,] 0.461217720 -0.15059131 #> [47,] 0.473253593 -0.15429063 #> [48,] 0.484997259 -0.15883305 #> [49,] 0.496374148 -0.16422875 #> [50,] 0.507306617 -0.17047602 #> [51,] 0.517715948 -0.17756073 #> [52,] 0.527524516 -0.18545625 #> [53,] 0.536658044 -0.19412376 #> [54,] 0.545047831 -0.20351305 #> [55,] 0.552632860 -0.21356365 #> [56,] 0.559361680 -0.22420650 #> [57,] 0.565193974 -0.23536587 #> [58,] 0.570101738 -0.24696161 #> [59,] 0.574070028 -0.25891150 #> [60,] 0.577097246 -0.27113374 #> [61,] 0.579194980 -0.28354932 #> [62,] 0.580387426 -0.29608429 #> [63,] 0.580710458 -0.30867169 #> [64,] 0.580210428 -0.32125332 #> [65,] 0.578942782 -0.33378090 #> [66,] 0.576970590 -0.34621704 #> [67,] 0.574363104 -0.35853566 #> [68,] 0.571194404 -0.37072198 #> [69,] 0.567542236 -0.38277225 #> [70,] 0.563487083 -0.39469294 #> [71,] 0.559111504 -0.40649978 #> [72,] 0.554499769 -0.41821640 #> [73,] 0.549737758 -0.42987275 #> [74,] 0.544913126 -0.44150332 #> [75,] 0.540115641 -0.45314511 #> [76,] 0.535437656 -0.46483544 #> [77,] 0.530974607 -0.47660950 #> [78,] 0.526825428 -0.48849779 #> [79,] 0.523092770 -0.50052337 #> [80,] 0.519882881 -0.51269891 #> [81,] 0.517305016 -0.52502376 #> [82,] 0.515470246 -0.53748092 #> [83,] 0.514489542 -0.55003422 #> [84,] 0.514471047 -0.56262576 #> [85,] 0.515516483 -0.57517384 #> [86,] 0.517716714 -0.58757167 #> [87,] 0.521146550 -0.59968709 #> [88,] 0.525858973 -0.61136358 #> [89,] 0.531879072 -0.62242276 #> [90,] 0.539198072 -0.63266871 #> [91,] 0.547767920 -0.64189395 #> [92,] 0.557496962 -0.64988725 #> [93,] 0.568247269 -0.65644302 #> [94,] 0.579834122 -0.66137172 #> [95,] 0.592028072 -0.66451096 #> [96,] 0.604559851 -0.66573642 #> [97,] 0.617128167 -0.66497179 #> [98,] 0.629410174 -0.66219699 #> [99,] 0.641074135 -0.65745365 #> [100,] 0.651793556 -0.65084750 #> [101,] 0.661261840 -0.64254697 #> [102,] 0.669206437 -0.63277811 #> [103,] 0.675401403 -0.62181592 #> [104,] 0.679677420 -0.60997266 #> [105,] 0.681928498 -0.59758396 #> [106,] 0.682114907 -0.58499378 #> [107,] 0.680262169 -0.57253928 #> [108,] 0.676456337 -0.56053666 #> [109,] 0.670836064 -0.54926902 #> [110,] 0.663582217 -0.53897684 #> [111,] 0.654905955 -0.52985162 #> [112,] 0.645036211 -0.52203271 #> [113,] 0.634207485 -0.51560730 #> [114,] 0.622648728 -0.51061306 #> [115,] 0.610573885 -0.50704299 #> [116,] 0.598174478 -0.50485167 #> [117,] 0.585614369 -0.50396235 #> [118,] 0.573026679 -0.50427430 #> [119,] 0.560512676 -0.50566962 #> [120,] 0.548142331 -0.50801947 #> [121,] 0.535956240 -0.51118908 #> [122,] 0.523968541 -0.51504165 #> [123,] 0.512170530 -0.51944099 #> [124,] 0.500534721 -0.52425297 #> [125,] 0.489019154 -0.52934600 #> [126,] 0.477571821 -0.53459059 #> [127,] 0.466135158 -0.53985842 #> [128,] 0.454650578 -0.54502094 #> [129,] 0.443063052 -0.54994806 #> [130,] 0.431325750 -0.55450689 #> [131,] 0.419404746 -0.55856113 #> [132,] 0.407283721 -0.56197112 #> [133,] 0.394968576 -0.56459493 #> [134,] 0.382491745 -0.56629079 #> [135,] 0.369915957 -0.56692069 #> [136,] 0.357337087 -0.56635567 #> [137,] 0.344885689 -0.56448219 #> [138,] 0.332726775 -0.56120988 #> [139,] 0.321057428 -0.55647981 #> [140,] 0.310101919 -0.55027303 #> [141,] 0.300104155 -0.54261850 #> [142,] 0.291317498 -0.53359952 #> [143,] 0.283992284 -0.52335801 #> [144,] 0.278361630 -0.51209556 #> [145,] 0.274626457 -0.50007076 #> [146,] 0.272940836 -0.48759254 #> [147,] 0.273398923 -0.47500933 #> [148,] 0.276024756 -0.46269461 #> [149,] 0.280766008 -0.45102980 #> [150,] 0.287492512 -0.44038549 #> [151,] 0.295999944 -0.43110266 #> [152,] 0.306018542 -0.42347542 #> [153,] 0.317226259 -0.41773657 #> [154,] 0.329265267 -0.41404747 #> [155,] 0.341760448 -0.41249258 #> [156,] 0.354338320 -0.41307940 #> [157,] 0.366644877 -0.41574321 #> [158,] 0.378361032 -0.42035612 #> [159,] 0.389214654 -0.42673939 #> [160,] 0.398988640 -0.43467768 #> [161,] 0.407524855 -0.44393404 #> [162,] 0.414724200 -0.45426441 #> [163,] 0.420543388 -0.46543063 #> [164,] 0.424989183 -0.47721121 #> [165,] 0.428111009 -0.48940963 #> [166,] 0.429992784 -0.50185977 #> [167,] 0.430744760 -0.51442885 #> [168,] 0.430495992 -0.52701795 #> [169,] 0.429387899 -0.53956065 #> [170,] 0.427569155 -0.55202016 #> [171,] 0.425192036 -0.56438529 #> [172,] 0.422410135 -0.57666570 #> [173,] 0.419377309 -0.58888655 #> [174,] 0.416247586 -0.60108294 #> [175,] 0.413175701 -0.61329403 #> [176,] 0.410317926 -0.62555700 #> [177,] 0.407832766 -0.63790087 #> [178,] 0.405881126 -0.65034026 #> [179,] 0.404625544 -0.66286906 #> [180,] 0.404228078 -0.67545433 #> [181,] 0.404846527 -0.68803069 #> [182,] 0.406628741 -0.70049548 #> [183,] 0.409704904 -0.71270549 #> [184,] 0.414177929 -0.72447576 #> [185,] 0.420112297 -0.73558119 #> [186,] 0.427522044 -0.74576170 #> [187,] 0.436358881 -0.75473152 #> [188,] 0.446501744 -0.76219272 #> [189,] 0.457749287 -0.76785311 #> [190,] 0.469816892 -0.77144757 #> [191,] 0.482339680 -0.77276172 #> [192,] 0.494882596 -0.77165606 #> [193,] 0.506958073 -0.76808813 #> [194,] 0.518050962 -0.76213036 #> [195,] 0.527649444 -0.75398074 #> [196,] 0.535279762 -0.74396448 #> [197,] 0.540541754 -0.73252513 #> [198,] 0.543141751 -0.72020493 #> [199,] 0.542919276 -0.70761535 #> [200,] 0.539864452 -0.69539998 #> [201,] 0.534123851 -0.68419316 #> [202,] 0.525993794 -0.67457810 #> [203,] 0.515901498 -0.66704864 #> [204,] 0.504375878 -0.66197840 #> [205,] 0.492010966 -0.65960013 #> [206,] 0.479425663 -0.65999683 #> [207,] 0.467223760 -0.66310501 #> [208,] 0.455957927 -0.66872891 #> [209,] 0.446100612 -0.67656348 #> [210,] 0.438023807 -0.68622332 #> [211,] 0.431988473 -0.69727420 #> [212,] 0.428143312 -0.70926428 #> [213,] 0.426531705 -0.72175227 #> [214,] 0.427104949 -0.73433077 #> [215,] 0.429739668 -0.74664358 #> [216,] 0.434257236 -0.75839683 #> [217,] 0.440443280 -0.76936406 #> [218,] 0.448065724 -0.77938631 #> [219,] 0.456890287 -0.78836820 #> [220,] 0.466692836 -0.79627119 #> [221,] 0.477268369 -0.80310532 #> [222,] 0.488436766 -0.80892031 #> [223,] 0.500045641 -0.81379692 #> [224,] 0.511970771 -0.81783901 #> [225,] 0.524114613 -0.82116682 #> [226,] 0.536403406 -0.82391141 #> [227,] 0.548783310 -0.82621037 #> [228,] 0.561215938 -0.82820461 #> [229,] 0.573673589 -0.83003604 #> [230,] 0.586134395 -0.83184588 #> [231,] 0.598577552 -0.83377333 #> [232,] 0.610978787 -0.83595430 #> [233,] 0.623306164 -0.83852003 #> [234,] 0.635516378 -0.84159540 #> [235,] 0.647551648 -0.84529669 #> [236,] 0.659337383 -0.84972881 #> [237,] 0.670780778 -0.85498199 #> [238,] 0.681770502 -0.86112798 #> [239,] 0.692177644 -0.86821590 #> [240,] 0.701858022 -0.87626808 #> [241,] 0.710655912 -0.88527609 #> [242,] 0.718409155 -0.89519750 #> [243,] 0.724955505 -0.90595355 #> [244,] 0.730139942 -0.91742826 #> [245,] 0.733822593 -0.92946924 #> [246,] 0.735886755 -0.94189045 #> [247,] 0.736246485 -0.95447686 #> [248,] 0.734853191 -0.96699109 #> [249,] 0.731700665 -0.97918162 #> [250,] 0.726828117 -0.99079219 #> [251,] 0.720320890 -1.00157195 #> [252,] 0.712308702 -1.01128545 #> [253,] 0.702961483 -1.01972208 #> [254,] 0.692483056 -1.02670419 #> [255,] 0.681103074 -1.03209336 #> [256,] 0.669067787 -1.03579459 #> [257,] 0.656630248 -1.03775797 #> [258,] 0.644040618 -1.03797807 #> [259,] 0.631537164 -1.03649117 #> [260,] 0.619338444 -1.03337052 #> [261,] 0.607637044 -1.02872031 #> [262,] 0.596595093 -1.02266865 #> [263,] 0.586341602 -1.01536022 #> [264,] 0.576971545 -1.00694897 #> [265,] 0.568546501 -0.99759130 #> [266,] 0.561096561 -0.98744016 #> [267,] 0.554623200 -0.97664003 #> [268,] 0.549102776 -0.96532314 #> [269,] 0.544490327 -0.95360680 #> [270,] 0.540723423 -0.94159191 #> [271,] 0.537725823 -0.92936237 #> [272,] 0.535410781 -0.91698546 #> [273,] 0.533683915 -0.90451289 #> [274,] 0.532445562 -0.89198237 #> [275,] 0.531592646 -0.87941974 #> [276,] 0.531020085 -0.86684121 #> [277,] 0.530621809 -0.85425596 #> [278,] 0.530291482 -0.84166874 #> [279,] 0.529923029 -0.82908258 #> [280,] 0.529411080 -0.81650143 #> [281,] 0.528651442 -0.80393282 #> [282,] 0.527541696 -0.79139026 #> [283,] 0.525982022 -0.77889568 #> [284,] 0.523876323 -0.76648144 #> [285,] 0.521133697 -0.75419221 #> [286,] 0.517670309 -0.74208633 #> [287,] 0.513411637 -0.73023682 #> [288,] 0.508295074 -0.71873169 #> [289,] 0.502272813 -0.70767368 #> [290,] 0.495314891 -0.69717918 #> [291,] 0.487412261 -0.68737634 #> [292,] 0.478579699 -0.67840232 #> [293,] 0.468858353 -0.67039965 #> [294,] 0.458317700 -0.66351185 #> [295,] 0.447056714 -0.65787825 #> [296,] 0.435204029 -0.65362842 #> [297,] 0.422916946 -0.65087618 #> [298,] 0.410379171 -0.64971368 #> [299,] 0.397797234 -0.65020571 #> [300,] 0.385395646 -0.65238467 #> [301,] 0.373410891 -0.65624639 #> [302,] 0.362084473 -0.66174725 #> [303,] 0.351655298 -0.66880271 #> [304,] 0.342351713 -0.67728743 #> [305,] 0.334383602 -0.68703712 #> [306,] 0.327934909 -0.69785200 #> [307,] 0.323156973 -0.70950183 #> [308,] 0.320163022 -0.72173226 #> [309,] 0.319024073 -0.73427220 #> [310,] 0.319766469 -0.74684185 #> [311,] 0.322371111 -0.75916106 #> [312,] 0.326774422 -0.77095759 #> [313,] 0.332870930 -0.78197484 #> [314,] 0.340517297 -0.79197886 #> [315,] 0.349537559 -0.80076419 #> [316,] 0.359729272 -0.80815853 #> [317,] 0.370870249 -0.81402588 #> [318,] 0.382725564 -0.81826837 #> [319,] 0.395054502 -0.82082660 #> [320,] 0.407617192 -0.82167868 #> [321,] 0.420180664 -0.82083821 #> [322,] 0.432524164 -0.81835119 #> [323,] 0.444443587 -0.81429230 #> [324,] 0.455754963 -0.80876057 #> [325,] 0.466296973 -0.80187485 #> [326,] 0.475932513 -0.79376907 #> [327,] 0.484549387 -0.78458775 #> [328,] 0.492060198 -0.77448156 #> [329,] 0.498401565 -0.76360341 #> [330,] 0.503532789 -0.75210481 #> [331,] 0.507434072 -0.74013287 #> [332,] 0.510104440 -0.72782774 #> [333,] 0.511559463 -0.71532054 #> [334,] 0.511828878 -0.70273186 #> [335,] 0.510954212 -0.69017073 #> [336,] 0.508986463 -0.67773388 #> [337,] 0.505983905 -0.66550556 #> [338,] 0.502010062 -0.65355751 #> [339,] 0.497131870 -0.64194930 #> [340,] 0.491418052 -0.63072881 #> [341,] 0.484937714 -0.61993286 #> [342,] 0.477759157 -0.60958803 #> [343,] 0.469948897 -0.59971144 #> [344,] 0.461570887 -0.59031164 #> [345,] 0.452685922 -0.58138950 #> [346,] 0.443351209 -0.57293903 #> [347,] 0.433620088 -0.56494826 #> [348,] 0.423541880 -0.55739995 #> [349,] 0.413161848 -0.55027239 #> [350,] 0.402521259 -0.54354000 #> [351,] 0.391657518 -0.53717397 #> [352,] 0.380604375 -0.53114277 #> [353,] 0.369392188 -0.52541267 #> [354,] 0.358048219 -0.51994809 #> [355,] 0.346596981 -0.51471203 #> [356,] 0.335060595 -0.50966634 #> [357,] 0.323459176 -0.50477202 #> [358,] 0.311811233 -0.49998949 #> [359,] 0.300134071 -0.49527874 #> [360,] 0.288444209 -0.49059960 #> [361,] 0.276757783 -0.48591189 #> [362,] 0.265090965 -0.48117558 #> [363,] 0.253460357 -0.47635104 #> [364,] 0.241883386 -0.47139918 #> [365,] 0.230378680 -0.46628166 #> [366,] 0.218966425 -0.46096117 #> [367,] 0.207668700 -0.45540162 #> [368,] 0.196509773 -0.44956847 #> [369,] 0.185516375 -0.44342906 #> [370,] 0.174717912 -0.43695291 #> [371,] 0.164146643 -0.43011219 #> [372,] 0.153837784 -0.42288207 #> [373,] 0.143829554 -0.41524122 #> [374,] 0.134163142 -0.40717229 #> [375,] 0.124882583 -0.39866238 #> [376,] 0.116034558 -0.38970361 #> [377,] 0.107668080 -0.38029354 #> [378,] 0.099834094 -0.37043576 #> [379,] 0.092584960 -0.36014026 #> [380,] 0.085973843 -0.34942390 #> [381,] 0.080054001 -0.33831073 #> [382,] 0.074877974 -0.32683223 #> [383,] 0.070496704 -0.31502749 #> [384,] 0.066958575 -0.30294325 #> [385,] 0.064308412 -0.29063375 #> [386,] 0.062586451 -0.27816050 #> [387,] 0.061827305 -0.26559185 #> [388,] 0.062058966 -0.25300243 #> [389,] 0.063301849 -0.24047236 #> [390,] 0.065567931 -0.22808640 #> [391,] 0.068860011 -0.21593282 #> [392,] 0.073171098 -0.20410228 #> [393,] 0.078483991 -0.19268648 #> [394,] 0.084771028 -0.18177684 #> [395,] 0.091994062 -0.17146301 #> [396,] 0.100104636 -0.16183151 #> [397,] 0.109044392 -0.15296427 #> [398,] 0.118745680 -0.14493730 #> [399,] 0.129132386 -0.13781946 #> [400,] 0.140120928 -0.13167136 #> [401,] 0.151621420 -0.12654438 #> [402,] 0.163538958 -0.12247996 #> [403,] 0.175775005 -0.11950904 #> [404,] 0.188228826 -0.11765174 #> [405,] 0.200798940 -0.11691726 #> [406,] 0.213384553 -0.11730400 #> [407,] 0.225886932 -0.11879991 #> [408,] 0.238210688 -0.12138298 #> [409,] 0.250264941 -0.12502196 #> [410,] 0.261964339 -0.12967721 #> [411,] 0.273229922 -0.13530161 #> [412,] 0.283989809 -0.14184165 #> [413,] 0.294179715 -0.14923847 #> [414,] 0.303743287 -0.15742903 #> [415,] 0.312632273 -0.16634717 #> [416,] 0.320806528 -0.17592469 #> [417,] 0.328233881 -0.18609236 #> [418,] 0.334889871 -0.19678091 #> [419,] 0.340757371 -0.20792181 #> [420,] 0.345826128 -0.21944808 #> [421,] 0.350092233 -0.23129492 #> [422,] 0.353557540 -0.24340024 #> [423,] 0.356229060 -0.25570513 #> [424,] 0.358118331 -0.26815414 #> [425,] 0.359240806 -0.28069556 #> [426,] 0.359615239 -0.29328155 #> [427,] 0.359263110 -0.30586818 #> [428,] 0.358208071 -0.31841545 #> [429,] 0.356475449 -0.33088723 #> [430,] 0.354091776 -0.34325110 #> [431,] 0.351084379 -0.35547823 #> [432,] 0.347481014 -0.36754318 #> [433,] 0.343309547 -0.37942367 #> [434,] 0.338597684 -0.39110039 #> [435,] 0.333372746 -0.40255670 #> [436,] 0.327661484 -0.41377850 #> [437,] 0.321489931 -0.42475389 #> [438,] 0.314883297 -0.43547301 #> [439,] 0.307865883 -0.44592783 #> [440,] 0.300461033 -0.45611190 #> [441,] 0.292691106 -0.46602026 #> [442,] 0.284577463 -0.47564917 #> [443,] 0.276140481 -0.48499607 #> [444,] 0.267399571 -0.49405939 #> [445,] 0.258373212 -0.50283846 #> [446,] 0.249078990 -0.51133344 #> [447,] 0.239533647 -0.51954524 #> [448,] 0.229753125 -0.52747547 #> [449,] 0.219752622 -0.53512643 #> [450,] 0.209546636 -0.54250105 #> [451,] 0.199149017 -0.54960294 #> [452,] 0.188573012 -0.55643634 #> [453,] 0.177831306 -0.56300619 #> [454,] 0.166936061 -0.56931815 #> [455,] 0.155898946 -0.57537863 #> [456,] 0.144731171 -0.58119481 #> [457,] 0.133443505 -0.58677476 #> [458,] 0.122046301 -0.59212742 #> [459,] 0.110549511 -0.59726269 #> [460,] 0.098962704 -0.60219150 #> [461,] 0.087295079 -0.60692582 #> [462,] 0.075555483 -0.61147874 #> [463,] 0.063752430 -0.61586453 #> [464,] 0.051894127 -0.62009866 #> [465,] 0.039988500 -0.62419784 #> [466,] 0.028043242 -0.62818006 #> [467,] 0.016065863 -0.63206459 #> [468,] 0.004063753 -0.63587203 #> [469,] -0.007955728 -0.63962427 #> [470,] -0.019985155 -0.64334450 #> [471,] -0.032016912 -0.64705719 #> [472,] -0.044043052 -0.65078803 #> [473,] -0.056055133 -0.65456389 #> [474,] -0.068044026 -0.65841274 #> [475,] -0.079999708 -0.66236355 #> [476,] -0.091911031 -0.66644615 #> [477,] -0.103765470 -0.67069109 #> [478,] -0.115548859 -0.67512944 #> [479,] -0.127245112 -0.67979258 #> [480,] -0.138835946 -0.68471191 #> [481,] -0.150300593 -0.68991855 #> [482,] -0.161615540 -0.69544297 #> [483,] -0.172754277 -0.70131458 #> [484,] -0.183687084 -0.70756125 #> [485,] -0.194380867 -0.71420883 #> [486,] -0.204799045 -0.72128052 #> [487,] -0.214901527 -0.72879630 #> [488,] -0.224644766 -0.73677230 #> [489,] -0.233981928 -0.74522006 #> [490,] -0.242863174 -0.75414590 #> [491,] -0.251236071 -0.76355025 #> [492,] -0.259046144 -0.77342699 #> [493,] -0.266237563 -0.78376289 #> [494,] -0.272753971 -0.79453710 #> [495,] -0.278539437 -0.80572082 #> [496,] -0.283539532 -0.81727704 #> [497,] -0.287702482 -0.82916052 #> [498,] -0.290980393 -0.84131793 #> [499,] -0.293330497 -0.85368823 #> [500,] -0.294716374 -0.86620328 panel(Out(a2l(replicate(100, coo_force2close(tfourier_shape(nb.h=6, alpha=2, nb.pts=200, plot=FALSE)))))) # biological shapes"},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":null,"dir":"Reference","previous_headings":"","what":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"Given list files (lf) includes matching filenames .jpg (black masks) .txt (landmark positions .txt), returns $ldk defined. Typically useful use ImageJ define landmarks outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"","code":"tie_jpg_txt(lf)"},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"lf list filenames","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"object","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"optimized (images read twice). Please hesitate contact particular case need something.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":null,"dir":"Reference","previous_headings":"","what":"Thin Plate Splines for 2D data — tps2d","title":"Thin Plate Splines for 2D data — tps2d","text":"tps2d core function Thin Plate Splines. used internally TPS graphical functions.tps_apply function arguments properly named (maintain tps2d historical reasons) want apply trasnformation grid.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Thin Plate Splines for 2D data — tps2d","text":"","code":"tps2d(grid0, fr, to) tps_apply(fr, to, new)"},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Thin Plate Splines for 2D data — tps2d","text":"grid0 matrix coordinates calculate deformations fr reference shape target shape new shape apply shp1->shp2 calibrated tps trasnformation","code":""},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Thin Plate Splines for 2D data — tps2d","text":"shape.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Thin Plate Splines for 2D data — tps2d","text":"","code":"shapes <- shapes %>% coo_scale() %>% coo_center() %>% coo_slidedirection(\"up\") %>% coo_sample(64) leaf1 <- shapes[14] leaf2 <- shapes[15] # tps grid on the two leafs2 tps_grid(leaf1, leaf2) # apply the (leaf1 -> leaf2) tps trasnformation onto leaf1 # (that thus get closer to leaf2) tps_apply(leaf1, leaf2, leaf1) %>% coo_draw(bor=\"purple\")"},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation 'vector field' using Thin Plate Splines — tps_arr","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"tps_arr(ows) calculates deformations two configurations illustrate using arrows.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"","code":"tps_arr( fr, to, amp = 1, grid = TRUE, over = 1.2, palette = col_summer, arr.nb = 200, arr.levels = 100, arr.len = 0.1, arr.ang = 20, arr.lwd = 0.75, arr.col = \"grey50\", poly = TRUE, shp = TRUE, shp.col = rep(NA, 2), shp.border = col_qual(2), shp.lwd = c(2, 2), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr grid whether calculate plot changes across graphical window TRUE just within starting shape (FALSE) numeric indicates much thin plate splines extends shapes palette color palette included Momocs produced colorRampPalette arr.nb numeric number arrows calculate arr.levels numeric. number levels color arrows arr.len numeric length arrows arr.ang numeric angle arrows' heads arr.lwd numeric lwd drawing arrows arr.col palette used color arrows poly whether draw polygons (outlines) points (landmarks) shp logical. whether draw shapes shp.col two colors filling shapes shp.border two colors drawing borders shp.lwd two lwd drawing shapes shp.lty two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"Nothing.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_arr(fr, to, arr.nb=200, palette=col_sari, amp=3) tps_arr(fr, to, arr.nb=200, palette=col_sari, amp=3, grid=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation grids using Thin Plate Splines — tps_grid","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"tps_grid calculates plots deformation grids two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"","code":"tps_grid( fr, to, amp = 1, over = 1.2, grid.size = 15, grid.col = \"grey80\", poly = TRUE, shp = TRUE, shp.col = rep(NA, 2), shp.border = col_qual(2), shp.lwd = c(1, 1), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr numeric indicates much thin plate splines extends shapes grid.size numeric specify number grid cells longer axis outlines grid.col color drawing grid poly whether draw polygons (outlines) points (landmarks) shp logical. Whether draw shapes shp.col Two colors filling shapes shp.border Two colors drawing borders shp.lwd Two lwd drawing shapes shp.lty Two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"Nothing","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_grid(fr, to, amp=3, grid.size=10)"},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation isolines using Thin Plate Splines. — tps_iso","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"tps_iso calculates deformations two configurations map without isolines.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"","code":"tps_iso( fr, to, amp = 1, grid = FALSE, over = 1.2, palette = col_spring, iso.nb = 1000, iso.levels = 12, cont = TRUE, cont.col = \"black\", poly = TRUE, shp = TRUE, shp.border = col_qual(2), shp.lwd = c(2, 2), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr grid whether calculate plot changes across graphical window TRUE just within starting shape (FALSE) numeric indicates much thin plate splines extends shapes palette color palette included Momocs produced colorRampPalette iso.nb numeric. number points use calculation deformation iso.levels numeric. number levels mapping deformations cont logical. Whether draw contour lines cont.col color drawing contour lines poly whether draw polygons (outlines) points (landmarks) shp logical. Whether draw shapes shp.border Two colors drawing borders shp.lwd Two lwd drawing shapes shp.lty Two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"returned value","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_iso(fr, to, iso.nb=200, amp=3) tps_iso(fr, to, iso.nb=200, amp=3, grid=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":null,"dir":"Reference","previous_headings":"","what":"Vanilla Thin Plate Splines — tps_raw","title":"Vanilla Thin Plate Splines — tps_raw","text":"tps_raw calculates deformation grids returns position sampled points .","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vanilla Thin Plate Splines — tps_raw","text":"","code":"tps_raw(fr, to, amp = 1, over = 1.2, grid.size = 15)"},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vanilla Thin Plate Splines — tps_raw","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr numeric indicates much thin plate splines extends shapes grid.size numeric specify number grid cells longer axis outlines","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vanilla Thin Plate Splines — tps_raw","text":"list two components: grid xy coordinates sampled points along grid; dim dimension grid.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vanilla Thin Plate Splines — tps_raw","text":"","code":"# \\donttest{ ms <- MSHAPES(efourier(bot, 10), \"type\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details b <- ms$shp$beer w <- ms$shp$whisky g <- tps_raw(b, w) ldk_plot(g$grid) # a wavy plot ldk_plot(g$grid, pch=NA) cols_ids <- 1:g$dim[1] for (i in 1:g$dim[2]) lines(g$grid[cols_ids + (i-1)*g$dim[1], ]) # }"},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":null,"dir":"Reference","previous_headings":"","what":"Validates Coo objects — verify","title":"Validates Coo objects — verify","text":"validation S3 objects, method (cheap) attempt checking Coo objects, , Opn Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validates Coo objects — verify","text":"","code":"verify(Coo)"},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validates Coo objects — verify","text":"Coo Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validates Coo objects — verify","text":"Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Validates Coo objects — verify","text":"Implemented morphometric methods handling verbs. see checked, try eg Momocs:::verify.Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Validates Coo objects — verify","text":"","code":"verify(bot) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk bot[12] <- NA # you would not use try, but here we cope with R CMD CHECK standards plop <- try(verify(bot), silent=TRUE) class(plop) #> [1] \"try-error\" verify(hearts) #> Out (outlines) #> - 240 outlines, 80 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 240 × 1 #> aut #> #> 1 ced #> 2 ced #> 3 ced #> 4 ced #> 5 ced #> 6 ced #> # ℹ 234 more rows #> - also: $ldk hearts$ldk[[4]] <- c(1, 2) # same remark plop2 <- try(verify(hearts), silent=TRUE) class(plop2) #> [1] \"try-error\""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify outliers — which_out","title":"Identify outliers — which_out","text":"simple wrapper around dnorm helps identify outliers. particular, may useful Coe object (case PCA first calculated) also Ldk detecting possible outliers freshly digitized/imported datasets.","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify outliers — which_out","text":"","code":"which_out(x, conf, nax, ...)"},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify outliers — which_out","text":"x object, either Coe numeric search outliers conf confidence dnorm (1e-3 default) nax number axes retain (Coe), <1 retain enough axes retain proportion variance ... additional parameters passed PCA (Coe)","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify outliers — which_out","text":"vector indices","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Identify outliers — which_out","text":"experimental. dnorm parameters used median(x), sd(x)","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify outliers — which_out","text":"","code":"# on a numeric x <- rnorm(10) x[4] <- 99 which_out(x) #> [1] 4 # on a Coe bf <- bot %>% efourier(6) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bf$coe[c(1, 6), 1] <- 5 which_out(bf) #> [1] 1 6 # on Ldk w_no <- w_ok <- wings w_no$coo[[2]][1, 1] <- 2 w_no$coo[[6]][2, 2] <- 2 which_out(w_ok, conf=1e-12) # with low conf, no outliers #> [1] NA which_out(w_no, conf=1e-12) # as expected #> found 127 possible outliers #> # A tibble: 2 × 4 #> shape id row coordinate #> #> 1 AN2 2 1 x #> 2 AN6 6 2 y # a way to illustrate, filter outliers # conf has been chosen deliberately low to show some outliers x_f <- bot %>% efourier #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x_p <- PCA(x_f) # which are outliers (conf is ridiculously low here) which_out(x_p$x[, 1], 0.5) #> duvel latrappe ballantines #> 6 13 22 cols <- rep(\"black\", nrow(x_p$x)) outliers <- which_out(x_p$x[, 1], 0.5) cols[outliers] <- \"red\" plot(x_p, col=cols) #> will be deprecated soon, see ?plot_PCA # remove them for Coe, rePCA, replot x_f %>% slice(-outliers) %>% PCA %>% plot #> Error in eval(e, Coe$fac, parent.frame()): object 'outliers' not found # or directly with which_out.Coe # which relies on a PCA outliers <- x_f %>% which_out(0.5, nax=0.95) %>% na.omit() x_f %>% slice(-outliers) %>% PCA %>% plot #> Error in eval(e, Coe$fac, parent.frame()): object 'outliers' not found"},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-141","dir":"Changelog","previous_headings":"","what":"Momocs 1.4.1","title":"Momocs 1.4.1","text":"Removed rgeos dependency Momocs can resurect CRAN","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-140","dir":"Changelog","previous_headings":"","what":"Momocs 1.4.0","title":"Momocs 1.4.0","text":"CRAN release: 2022-04-04 Fixed several minor bugs, mostly plotting. coo_slide duplicated initial point cases. Now fixed. coo_likely_clockwise (friends) now uses complex numbers much robust. removed annoying messages. slice(…, 1) now returns matrix $coe, numeric ([,,drop=FALSE]) ’m currently academia ’m looking funding develop MomX. plan give time 2022 ideas, either directly hiring consulting, ring bell!","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-133","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.3","title":"Momocs 1.3.3","text":"plot_PCA plot_LDA consistently work within eg pdf(). Thanks Bill fof pointing . (214) coo_shearx/y return Coo. Fixed.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-132","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.2","title":"Momocs 1.3.2","text":"CRAN release: 2020-10-06 Turned remaining return return() please R CMD check as_df now uses tibble verbs everywhere printing Coo faster now price sampling 100 shapes calculate mean number coordinates sd. Removed (quite) annoying startup message. time MomX 2021 anyway","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-131","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.1","title":"Momocs 1.3.1","text":"Changed dplyr::as_data_frame tibble::as_tibble","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-130","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.0","title":"Momocs 1.3.0","text":"CRAN release: 2020-04-15 version last major one released CRAN. Momocs now retired longer maintained. See momx.github.io. April 15, 2020 satisifies available testing approaches. new multivariate method: KMEDOIDS top cluster::pam. Added plot_silhouette go friend. Now depends cluster. new multivariate method: NMDS top vegan::metaMDS; use plot_NMDS plot vegan::stressplot Shepard plot. Now depends vegan. new multivariate method: MDS top cmdscale; use plot_MDS plot . mshapes now MSHAPES stick capitalized “multivariate” methods. mshapes now just announces future deprecation. MSHAPES now just returns data_frame PCs LDs used PCA LDA objects. Consequently, plot_MSHAPES new method plotting . Works lists result MSHAPES. plot_CV refreshed, better now plotting either small big matrices. fac_dispatcher supports NULL eases lot multivariate plots (notably Momecs side) new handling method rm_missing deal missing data $fac boxplot methods Coe refreshed hist methods Coe deprecated coo_plot longer method gains cex.first.point argument new method: coo_scalars gather scalar descriptors shape TraCoe class properly data_frameize fac build TraCoe() CLUST methods rewrote now wraps around dendextend. Consequently released ape dependency. morphometrics methods now accepts lists elegant working chop+combine LDA methods partly rewritten now handles constant collinear variables dropping storing returned list morphospace LDAs (finally) back, yet still quite experimental. coo_untiltx now removes (residual) rotational biases coo_slidedirection used . plot_LDA now . Pretty much plot_PCA (expected yet nice). .layerize_LDA internal prepare previous new vignettes: Momocs_coo Momocs_FAQ; others refreshed. morphospace_position chullfilled plot_PCA now properly working verify replaces validate avoid conflict shiny::validate (Momecs) subsetize now exported () def_ldk gains close points argument printing Coo errors due forgotten data.frame rather data_frame Coo builders gain .data.frame method, notably ease compatibility Momit as_df now returns useful data_frame everywhere gain retain argument deprecated coo_angle_edge1 friends, now coo_angle_edges see 1.2.9. fixed minor bugs (see GitHub history commits)","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-129","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.9","title":"Momocs 1.2.9","text":"CRAN release: 2018-03-22","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"preamble-1-2-9","dir":"Changelog","previous_headings":"","what":"Preamble","title":"Momocs 1.2.9","text":"Started general review Momocs (including #184) prepare MomX. convenience, changes stack 1.2.5 GitHub appear, end, 1.9.0 CRAN reflect proximity 2.0 huge quantity changes since 1.2 Moved everything github.com/MomX/Momocs ongoing complete review code ongoing complete review manual pages: lots grouping, better graphics dead (aka grindr): pipe-friendly base layers biplots shape drawing cartesian coordinates. used replace multivariate plotters (eg plot.PCA), family pictures (eg stack replace pile remove annoying conflict utils::stack, panel) single shape plotters (eg ldk_plot, coo_plot). strategy faster, much generic ease development maintenance compared previous Momocs graphs. vignette details grindr rationale use.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"new-1-2-9","dir":"Changelog","previous_headings":"","what":"New","title":"Momocs 1.2.9","text":"new functions: andnow andnow_method class tells object, classes supported function/method. new coo_* methods: coo_range, coo_range_enlarge, coo_diffrange, coo_template_relatively. latter prepare ground proper size handling, notably morphospaces. Many coo functions ported methods now supporting .Coo directly: coo_angle_edges, coo_angle_tangent, coo_boundingbox, coo_calliper, coo_chull, coo_chull_onion, coo_circularity, coo_circularityharalick, coo_circularity_norm, coo_convexity, coo_dxy, coo_eccentricityboundingbox, coo_eccentricityeigen, coo_elongation, coo_intersect_angle, coo_intersect_direction, coo_intersect_segment, coo_perim, coo_perimcum, coo_perimpts, coo_rectangularity, coo_rectilinearity, coo_scalex, coo_scaley, coo_solidity, coo_truss. Palettes now colorblind-friendly RColorBrewer , state art, virids palettes. See also pal_manual, pal_qual_solarized pal_seq_grey. dispatch_fac now behind fac arguments fgProcrustes now accepts lists efourier default norm=TRUE now messages wrong may dplyr::tibble() everywhere pertinent","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"deprecated-1-2-9","dir":"Changelog","previous_headings":"","what":"Deprecated","title":"Momocs 1.2.9","text":".* aliases is_* methods Deprecated classify calibrate_*(..., method) renamed calibrate_*_method. See ?calibrate_reconstructions friends. Deprecated plot3.PCA (replaced versions) Ntable now splitted plot_table + table coo_tangle now coo_angle_tangent coo_theta3 now coo_angle_edges truss now coo_truss method plot.Coo now inspect pos.shapes now morphospace_positions is_closed deprecated, now coo_is_closed; is_open now coo_is_open, comply coo_* friends naming scheme is_clockwise deprecated, now coo_likely_clockwise; is_anticlockwise now coo_likely_anticlockwise. Better reflect incertainty gather coo_* friends Deprecated table (poor shortcut anyway avoid boring startup message) Deprecated stack2 panel2 rewriting Deprecated as_Out, efourier_i.OutCoe anyway. Consequently deprecated panel.OutCoe method additionnaly Coe method. May back versions. non-exported functions (ie internals) now homegeneously begin ., eg ..error (try Momocs:::. + complete list). previously exported functions now internals (function_foo renamed .function_foo): .coo_angle_edge1, .vecs_param, .refactor NEWS now decent NEWS file Online doc moved [http://momx.github.io/Momocs/]","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"dependencies-1-2-9","dir":"Changelog","previous_headings":"","what":"Dependencies","title":"Momocs 1.2.9","text":"Released reshape2, plyr dependencies Now depends RColorBrewer, progress Proper indications external functions ::. nice side effect remove annoying messages attaching Momocs. Another removal importFrom.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"breaking-changes-1-2-9","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"Momocs 1.2.9","text":"Besides deprecated/renamed functions breaking changes. Future breaking changes announced within concerned functions.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"minor-1-2-9","dir":"Changelog","previous_headings":"","what":"Minor","title":"Momocs 1.2.9","text":"Waiting cleaner fix, subset now subsetize… Fixed bug LDA retain=1 (#e7704eb) Messages homogeneity Internals lightened verbosity progress bar now handled via options(\"verbose\") Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-124-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.4 (GitHub)","title":"Momocs 1.2.4 (GitHub)","text":"New functions/methods: coo_intersect_segment, coo_intersect_direction, coo_intersect_angle, def_ldk_direction, def_ldk_angle, def_ldk, def_ldk_tips, coo_sample_prop coo_slice.Opn now supports ldk argument. Now depends rgeos intersecting methods. Lightened nsfishes charring comply R CMD CHECK. Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-123-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.3 (GitHub)","title":"Momocs 1.2.3 (GitHub)","text":"Built R 3.4.3 coo_slice now suports ldk argument Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-122-cran--github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.2 (CRAN + GitHub)","title":"Momocs 1.2.2 (CRAN + GitHub)","text":"CRAN release: 2017-09-28 MANOVA_PW now returns p-values New dataset nsfishes minor debugging, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-121-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.1 (GitHub)","title":"Momocs 1.2.1 (GitHub)","text":"Introduced testing testthat Minor debugging, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-116-github--cran","dir":"Changelog","previous_headings":"","what":"Momocs 1.1.6 (GitHub + CRAN)","title":"Momocs 1.1.6 (GitHub + CRAN)","text":"CRAN release: 2017-04-17 sfourier family implementation new datasets: apodemus mouse","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-110-github--cran","dir":"Changelog","previous_headings":"","what":"Momocs 1.1.0 (GitHub + CRAN)","title":"Momocs 1.1.0 (GitHub + CRAN)","text":"CRAN release: 2016-10-25 plot2.PCA deprecated due ggplot2 2.2.0 breaking changes minor changes can followed GitHub commits","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-10-cran--github","dir":"Changelog","previous_headings":"","what":"Momocs 1.0 (CRAN + GitHub)","title":"Momocs 1.0 (CRAN + GitHub)","text":"Release CRAN replaces now completely obsolete 0.2.6 (one JSS paper. consists last version pushed CRAN.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-09-github","dir":"Changelog","previous_headings":"","what":"Momocs 0.9 (Github)","title":"Momocs 0.9 (Github)","text":"Started routinely use GitHub (NEWS) complete rewriting package, inclusion new morphometrics approches (open outlines, configuration landmarks, global shape descriptors). New design classes , Opn Ldk handle (closed) outlines, open outlines configuration landmarks. Coo becomes “super class” encompassing three others. S4 -> S3 rewriting. Maybe less orthodox much easy understand, code, extend probably required Momocs step. Renaming functions/methods consistent scheme New/partial rewriting multivariate methods: MANOVA, MANOVA_PW, LDA, KMEANS, CLUST. Graphics refreshed: panel, stack, plot.PCA New datasets: chaff, flowers, oak, olea, molars, shapes, wings, General review helpfiles Many issues fixed, see GitHub Momocs speed dating: tutorial vignette (see browseVignette(\"Momocs\") available","code":""}] +[{"path":"http://momx.github.io/Momocs/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Vincent Bonhomme. Author, maintainer. Julien Claude. Author. core functions base R","code":""},{"path":"http://momx.github.io/Momocs/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Bonhomme V, Picq S, Gaucherel C, Claude J (2014). Momocs: Outline Analysis Using R, volume 56 number 13. https://www.jstatsoft.org/v56/i13/.","code":"@Manual{, textversion = {Vincent Bonhomme, Sandrine Picq, Cedric Gaucherel, Julien Claude (2014).}, title = {Momocs: Outline Analysis Using R}, journal = {Journal of Statistical Software}, year = {2014}, volume = {56}, number = {13}, pages = {1--24}, url = {https://www.jstatsoft.org/v56/i13/}, author = {Vincent Bonhomme and Sandrine Picq and Cédric Gaucherel and Julien Claude}, }"},{"path":[]},{"path":"http://momx.github.io/Momocs/index.html","id":"news","dir":"","previous_headings":"Momocs","what":"News","title":"Morphometrics using R","text":"’m still looking funding develop MomX. idea, please email ’m available consulting, training collaboration, worldwide. Momocs back CRAN longer relies retired rgeos dependency tutorial/introduction back! Download **","code":""},{"path":"http://momx.github.io/Momocs/index.html","id":"installation","dir":"","previous_headings":"Momocs","what":"Installation","title":"Morphometrics using R","text":"last released version can installed CRAN : recommend using (support) development version GitHub :","code":"install.packages(\"Momocs\") # install.packages(\"devtools\") devtools::install_github(\"MomX/Momocs\")"},{"path":"http://momx.github.io/Momocs/index.html","id":"example","dir":"","previous_headings":"Momocs","what":"Example","title":"Morphometrics using R","text":"basic example complete analysis : inspection, normalization raw outlines, elliptical Fourier transforms, dimmensionality reduction classification, using single line.","code":"library(Momocs) devtools::load_all() #> ℹ Loading Momocs #> Registered S3 method overwritten by 'vegan': #> method from #> rev.hclust dendextend hearts %T>% # A toy dataset stack() %>% # Take a family picture of raw outlines fgProcrustes() %>% # Full generalized Procrustes alignment coo_slide(ldk = 2) %T>% # Redefine a robust 1st point between the cheeks stack() %>% # Another picture of aligned outlines efourier(6, norm=FALSE) %>% # Elliptical Fourier Transforms PCA() %T>% # Principal Component Analysis plot_PCA(~aut) %>% # A PC1:2 plot LDA(~aut) %>% # Linear Discriminant Analysis plot_CV() # And the confusion matrix after leave one out cross validation #> Warning: The `` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . #> This warning is displayed once every 8 hours. #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was #> generated."},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":null,"dir":"Reference","previous_headings":"","what":"Hierarchical clustering — CLUST","title":"Hierarchical clustering — CLUST","text":"Performs hierarchical clustering dist hclust. far mainly wrapper around two functions, plus plotting using dendextend package facilities.","code":""},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Hierarchical clustering — CLUST","text":"","code":"CLUST(x, ...) # S3 method for default CLUST(x, ...) # S3 method for Coe CLUST( x, fac, type = c(\"horizontal\", \"vertical\", \"fan\")[1], k, dist_method = \"euclidean\", hclust_method = \"complete\", retain = 0.99, labels, lwd = 1/4, cex = 1/2, palette = pal_qual, ... )"},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Hierarchical clustering — CLUST","text":"x Coe PCA object ... useless fac factor specification fac_dispatcher type character one c(\"horizontal\", \"vertical\", \"fan\") (default: horizontal) k numeric provided greater 1, cut tree number groups dist_method feed dist's method argument, one euclidean (default), maximum, manhattan, canberra, binary minkowski. hclust_method feed hclust's method argument, one ward.D, ward.D2, single, complete (default), average, mcquitty, median centroid. retain number axis retain PCA object passed. number < 1 passed, number PCs retained enough capture proportion variance via scree_min labels factor specification labelling tips feed fac_dispatcher lwd branches (default: 0.25) cex labels (default: 1) palette one available palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Hierarchical clustering — CLUST","text":"ggplot plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/CLUST.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Hierarchical clustering — CLUST","text":"","code":"# On Coe bf <- bot %>% efourier(6) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details CLUST(bf) # with a factor and vertical CLUST(bf, ~type, \"v\") # with some cutting and different dist/hclust methods CLUST(bf, dist_method=\"maximum\", hclust_method=\"average\", labels=~type, k=3, lwd=1, cex=1, palette=pal_manual(c(\"green\", \"yellow\", \"red\"))) # On PCA bf %>% PCA %>% CLUST"},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":null,"dir":"Reference","previous_headings":"","what":"Coe ","title":"Coe ","text":"Coe class 'parent' 'super' class OutCoe, OpnCoe, LdkCoe TraCoe classes.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Coe ","text":"","code":"Coe(...)"},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Coe ","text":"... anything , anyway, function simply returns message.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Coe ","text":"list class Coe","code":""},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Coe ","text":"Useful shortcuts described . See browseVignettes(\"Momocs\") detail design behind Momocs' classes. Coe class 'parent' class following 'child' classes OutCoe coefficients closed outlines morphometrics OpnCoe coefficients open outlines morphometrics LdkCoe coefficients configuration landmarks morphometrics. words, OutCoe, OpnCoe LdkCoe classes , primarily, Coe objects define generic specific methods. See respective help pages help. can access methods available Coe objects methods(class=Coe).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Coe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Coe ","text":"","code":"# to see all methods for Coe objects. methods(class='Coe') #> [1] $ CLUST KMEDOIDS LDA MDS NMDS #> [7] [ [<- arrange as_df breed chop #> [13] dim dissolve export filter get_pairs length #> [19] mutate names names<- perm reLDA rename #> [25] sample_frac sample_n select slice str subsetize #> [31] which_out #> see '?methods' for accessing help and source code # to see all methods for OutCoe objects. methods(class='OutCoe') # same for OpnCoe, LdkCoe, TraCoe #> [1] MANOVA MSHAPES PCA boxplot combine hcontrib print rm_asym #> [9] rm_sym symmetry #> see '?methods' for accessing help and source code bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.f #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 40 outlines described, 12 harmonics #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows class(bot.f) #> [1] \"OutCoe\" \"Coe\" inherits(bot.f, \"Coe\") #> [1] TRUE # if you want to work directly on the matrix of coefficients bot.f$coe #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 1 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> franziskaner 1 0.007314669 0.09110003 0.01294912 0.023136784 0.010558958 #> grimbergen 1 0.009522713 0.08573641 0.01974880 0.012878126 0.008485338 #> guiness 1 0.009589570 0.08825041 0.02268926 0.017770767 0.010695823 #> hoegardeen 1 0.009598003 0.09186435 0.01393702 0.020136724 0.008952962 #> jupiler 1 0.008152360 0.09595083 0.01206957 0.023549986 0.007484692 #> kingfisher 1 0.007788546 0.09459391 0.01346605 0.024571428 0.009229773 #> latrappe 1 0.018476561 0.06035470 0.03974568 0.010493387 0.026379718 #> lindemanskriek 1 0.012406103 0.09289294 0.01773845 0.020632152 0.010949655 #> nicechouffe 1 0.015167563 0.09058037 0.02094971 0.020007417 0.014345165 #> pecheresse 1 0.008436476 0.09409400 0.01181167 0.022221176 0.007960411 #> sierranevada 1 0.015038107 0.08208708 0.02647382 0.013697543 0.013869924 #> tanglefoot 1 0.018782346 0.07275504 0.03848616 0.008439294 0.018172933 #> tauro 1 0.007333709 0.09536301 0.01149374 0.023043384 0.007093187 #> westmalle 1 0.009100416 0.09469091 0.01450202 0.023460557 0.009582984 #> amrut 1 0.004198631 0.09500128 0.02143863 0.026005715 0.011729658 #> ballantines 1 -0.000653116 0.05733309 0.03154946 0.017516836 0.034198742 #> bushmills 1 -0.004927807 0.08149528 0.01036776 0.023910616 0.017320375 #> chivas 1 0.021613712 0.08642271 0.04314511 0.008460823 0.014376414 #> dalmore 1 0.038669436 0.07265717 0.05680730 0.003277741 0.019363348 #> famousgrouse 1 0.003373189 0.08802317 0.02019928 0.025507211 0.016776448 #> glendronach 1 0.003257554 0.09526153 0.02074249 0.026167146 0.010932661 #> glenmorangie 1 0.008572527 0.09410920 0.02136020 0.024756735 0.011430941 #> highlandpark 1 -0.002122354 0.06989902 0.03612531 0.023554876 0.027350465 #> jackdaniels 1 0.008777794 0.08626120 0.02940216 0.019373419 0.015295504 #> jb 1 0.004384491 0.09517564 0.02460733 0.023505329 0.010741163 #> johnniewalker 1 0.002370576 0.08321025 0.01719991 0.022474617 0.017724976 #> magallan 1 -0.008648015 0.09924533 0.01455296 0.037258989 0.011586345 #> makersmark 1 0.016536161 0.10229688 0.03388156 0.008773613 0.010192259 #> oban 1 0.001652893 0.09909342 0.02127249 0.028337047 0.009671380 #> oldpotrero 1 0.022935601 0.09391465 0.03109455 0.009138035 0.012979620 #> redbreast 1 0.017769276 0.09281598 0.04425688 0.011246633 0.012792733 #> tamdhu 1 0.005270821 0.09375949 0.02020814 0.025073663 0.010943288 #> wildturkey 1 0.008605609 0.09229119 0.03228916 0.020978082 0.013010663 #> yoichi 1 -0.001738226 0.07733113 0.02843759 0.024035740 0.023420967 #> A7 A8 A9 A10 #> brahma 0.0031835706 0.005158502 -7.262824e-04 0.0047287291 #> caney 0.0035527091 0.007010166 1.214949e-03 0.0038734169 #> chimay -0.0047412879 0.007814037 -2.112661e-03 0.0022043011 #> corona 0.0055045888 0.007852411 8.767189e-04 0.0044201528 #> deusventrue 0.0025214510 0.011391904 -1.733965e-03 0.0062083192 #> duvel -0.0016871288 0.011025502 -1.042906e-04 0.0017042044 #> franziskaner 0.0045813399 0.006927102 -5.793922e-04 0.0045217266 #> grimbergen -0.0021957902 0.008213656 -1.577404e-03 0.0026346248 #> guiness -0.0015195731 0.008550727 2.093772e-04 0.0060163830 #> hoegardeen 0.0024034912 0.007507503 -1.234721e-03 0.0046892597 #> jupiler 0.0055270378 0.006597011 1.073131e-03 0.0041448892 #> kingfisher 0.0059527872 0.006778517 1.169809e-03 0.0044984721 #> latrappe -0.0057950372 0.005954999 -5.463098e-03 -0.0001140651 #> lindemanskriek 0.0033428880 0.008381096 -1.707332e-04 0.0050506285 #> nicechouffe 0.0026214920 0.010288304 -4.913646e-04 0.0065828560 #> pecheresse 0.0046954032 0.006669592 4.015144e-05 0.0042466561 #> sierranevada -0.0043828769 0.009275932 -1.465646e-03 0.0059555586 #> tanglefoot -0.0108560295 0.008370133 -2.988319e-03 0.0052185654 #> tauro 0.0052560957 0.006425077 9.461829e-04 0.0040141970 #> westmalle 0.0051463840 0.006848999 3.534839e-04 0.0042382642 #> amrut 0.0019176785 0.008515916 1.392307e-03 0.0089150426 #> ballantines 0.0045419501 0.014014932 -5.273138e-03 0.0006083616 #> bushmills 0.0095020099 0.012457087 -3.988679e-04 0.0048132802 #> chivas -0.0053775410 0.013797633 2.198119e-03 0.0031741809 #> dalmore -0.0072008170 0.012093037 5.368701e-03 0.0025492686 #> famousgrouse 0.0035195429 0.008617844 -1.621645e-03 0.0075384656 #> glendronach 0.0018504691 0.007851391 1.483976e-03 0.0086527932 #> glenmorangie 0.0023552959 0.007521806 1.103445e-03 0.0069834516 #> highlandpark -0.0024258364 0.003973480 -7.894105e-03 0.0013284975 #> jackdaniels -0.0047279969 0.008903250 -2.124758e-03 0.0090062900 #> jb -0.0015584637 0.008915452 4.097146e-04 0.0089915939 #> johnniewalker 0.0034197782 0.009945811 -3.913888e-03 0.0059350940 #> magallan 0.0095026108 0.003088506 1.575409e-03 0.0054824432 #> makersmark 0.0003303914 0.016520390 -1.901653e-03 0.0031138042 #> oban 0.0022492968 0.007479292 2.478319e-03 0.0090114539 #> oldpotrero 0.0015843674 0.012237947 -4.671411e-04 0.0023549220 #> redbreast -0.0046107656 0.015170859 3.884228e-03 0.0045806501 #> tamdhu 0.0013188307 0.006535142 1.700604e-04 0.0072170216 #> wildturkey -0.0038244377 0.010171775 1.641229e-03 0.0092477531 #> yoichi -0.0011328612 0.006117569 -8.008551e-03 0.0034639875 #> A11 A12 B1 B2 B3 #> brahma -0.0013733386 0.0016363823 0 -1.900652e-04 3.306231e-04 #> caney -0.0018777601 0.0011330555 0 5.012013e-04 -3.851293e-04 #> chimay -0.0012371979 -0.0018514226 0 1.843629e-04 4.196107e-04 #> corona -0.0021742849 0.0026300698 0 -3.586724e-04 1.711055e-05 #> deusventrue -0.0007936789 0.0028680575 0 1.774985e-04 -8.326845e-05 #> duvel -0.0006045816 -0.0028942242 0 -4.198782e-04 7.447638e-05 #> franziskaner -0.0015947508 0.0021935018 0 -8.367911e-04 -3.508429e-04 #> grimbergen -0.0035563564 -0.0004162333 0 -4.478525e-04 -1.575351e-04 #> guiness -0.0015222476 0.0005646464 0 4.379065e-05 -3.284575e-04 #> hoegardeen -0.0024579838 0.0023152691 0 -1.402306e-05 3.803656e-04 #> jupiler -0.0009974596 0.0023379940 0 1.831345e-04 -1.827727e-04 #> kingfisher -0.0004648420 0.0023788807 0 -1.644074e-04 -3.059412e-04 #> latrappe 0.0015068375 -0.0015514855 0 2.164816e-04 1.803082e-04 #> lindemanskriek -0.0009359325 0.0022848386 0 4.100249e-04 2.208045e-04 #> nicechouffe -0.0007619565 0.0033654095 0 5.495158e-04 -2.042167e-05 #> pecheresse -0.0013782823 0.0024185755 0 2.181959e-04 -7.311833e-05 #> sierranevada -0.0017933279 -0.0005349683 0 -2.089826e-04 -3.847117e-04 #> tanglefoot -0.0003179777 -0.0031166695 0 2.257469e-04 -2.009399e-04 #> tauro -0.0010466330 0.0023514452 0 1.762712e-04 -8.961804e-05 #> westmalle -0.0004882420 0.0023217071 0 2.683034e-04 5.829510e-04 #> amrut -0.0004155995 0.0028189180 0 3.259091e-04 3.840090e-04 #> ballantines -0.0024674938 -0.0002274846 0 -8.980074e-06 1.013064e-03 #> bushmills -0.0043970618 0.0017818484 0 8.084328e-04 8.012671e-04 #> chivas -0.0016654883 -0.0026415175 0 6.073651e-04 3.070684e-04 #> dalmore 0.0025922354 -0.0039822137 0 1.097768e-03 6.881659e-04 #> famousgrouse 0.0001300206 0.0046515437 0 1.287495e-04 -1.324051e-04 #> glendronach -0.0002084792 0.0025405566 0 4.149836e-04 1.394907e-04 #> glenmorangie -0.0001692272 0.0025838514 0 8.773153e-05 -6.257124e-05 #> highlandpark 0.0023214993 0.0028070218 0 -6.291662e-04 -7.091405e-04 #> jackdaniels -0.0011544544 0.0013660407 0 1.828207e-04 -5.854778e-04 #> jb -0.0026073348 0.0016289320 0 5.770034e-04 1.295536e-04 #> johnniewalker -0.0026799451 0.0046998857 0 1.610309e-03 1.521699e-03 #> magallan 0.0034410693 0.0056372281 0 -1.110357e-03 -1.017379e-03 #> makersmark -0.0037381840 0.0031052372 0 -2.272912e-03 -1.921977e-03 #> oban -0.0000555700 0.0026159662 0 5.217373e-04 3.289690e-04 #> oldpotrero 0.0002650070 0.0005717670 0 -4.566144e-04 2.434271e-04 #> redbreast -0.0017153754 -0.0017080604 0 1.568632e-04 1.213587e-04 #> tamdhu -0.0004660552 0.0022520466 0 1.013117e-03 4.671170e-04 #> wildturkey -0.0011040540 0.0003877287 0 9.489660e-04 9.344159e-04 #> yoichi -0.0005670111 0.0040850862 0 2.371406e-04 3.337929e-04 #> B4 B5 B6 B7 #> brahma -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 #> caney 3.333918e-04 -2.899903e-04 7.350207e-05 -4.952054e-04 #> chimay 3.227901e-04 -2.906714e-05 5.573360e-04 1.059517e-04 #> corona -5.501057e-04 -1.907425e-04 -4.256287e-04 -2.147013e-04 #> deusventrue -1.403373e-03 -3.240180e-04 -9.330047e-04 6.515692e-04 #> duvel -6.627095e-04 6.107940e-05 -4.746985e-04 2.450959e-04 #> franziskaner -6.983186e-04 -1.894199e-04 -5.170165e-04 5.988419e-05 #> grimbergen 1.554676e-04 5.257427e-05 1.132609e-04 -6.848791e-05 #> guiness -1.677242e-04 -5.817648e-04 -2.853668e-04 -5.620867e-04 #> hoegardeen 3.285812e-04 4.813766e-04 3.691213e-04 5.309204e-04 #> jupiler -4.540203e-05 -1.242456e-04 -5.198885e-05 -2.289954e-04 #> kingfisher -1.751841e-04 3.014782e-05 2.132220e-04 4.144846e-04 #> latrappe 5.468038e-04 2.303760e-04 5.053959e-04 2.603399e-04 #> lindemanskriek 2.791269e-04 -2.076986e-04 -1.312595e-04 -1.367999e-04 #> nicechouffe 2.492854e-04 2.171344e-04 2.155297e-04 1.621249e-04 #> pecheresse 2.879648e-04 3.072908e-05 1.503582e-04 2.875235e-05 #> sierranevada 2.254752e-04 -1.582761e-04 3.201773e-04 -2.506594e-04 #> tanglefoot -3.556495e-04 -4.589428e-04 -1.231722e-04 -1.030225e-04 #> tauro 8.045507e-05 4.030041e-05 1.942858e-04 7.124766e-05 #> westmalle 2.086425e-04 5.569697e-04 -1.481080e-04 2.680453e-04 #> amrut 2.692429e-04 2.370884e-04 4.975910e-05 1.929742e-04 #> ballantines -2.175286e-04 1.006239e-03 -2.063087e-04 6.874951e-04 #> bushmills 9.888621e-04 5.333749e-04 6.026329e-04 3.382499e-07 #> chivas 1.231654e-04 -3.404412e-05 8.988476e-05 1.476812e-04 #> dalmore 2.545366e-04 1.352642e-04 -1.253930e-04 2.101188e-04 #> famousgrouse -1.274614e-04 2.141211e-04 -1.073666e-04 1.188717e-05 #> glendronach 1.071609e-04 -2.016928e-04 -6.904446e-05 -1.327779e-04 #> glenmorangie 1.913928e-04 -9.675222e-05 1.480796e-04 -8.118855e-05 #> highlandpark -2.204109e-04 -5.021317e-04 3.287316e-04 -2.505046e-04 #> jackdaniels -7.969529e-04 -4.880520e-04 -1.903562e-04 3.092736e-04 #> jb -1.422141e-04 -2.056778e-04 -2.053789e-04 1.048725e-04 #> johnniewalker 1.140415e-03 1.505532e-04 2.156619e-04 -1.772208e-04 #> magallan -7.964354e-04 -6.143625e-04 -3.734865e-04 -1.291146e-04 #> makersmark -3.452843e-04 -1.437534e-04 4.289043e-04 -9.732915e-04 #> oban 3.351843e-04 4.359254e-05 1.826487e-05 -6.027186e-05 #> oldpotrero -2.060062e-04 3.778706e-05 -5.576392e-04 2.258336e-04 #> redbreast -1.087561e-04 -1.587376e-04 -9.420764e-05 -7.636860e-06 #> tamdhu 2.449976e-04 3.452581e-05 -1.344683e-04 1.407481e-04 #> wildturkey 2.048265e-04 1.038328e-04 7.988232e-06 2.379076e-04 #> yoichi 2.790195e-04 2.201285e-04 1.423493e-05 -5.626562e-05 #> B8 B9 B10 B11 #> brahma 6.268503e-06 -1.960132e-04 1.334431e-04 4.058288e-05 #> caney 8.536695e-05 -4.143363e-04 1.667420e-04 -3.134942e-04 #> chimay 6.209192e-04 1.441644e-04 1.715223e-04 5.930974e-05 #> corona -1.931107e-04 -3.048499e-04 -2.065499e-04 -2.244684e-04 #> deusventrue -8.354423e-04 2.287499e-05 -6.080012e-04 2.971827e-04 #> duvel -1.676532e-04 1.512500e-04 6.986965e-05 2.318703e-04 #> franziskaner -3.810484e-04 5.133436e-05 -3.407356e-04 5.681736e-05 #> grimbergen -9.289817e-05 2.532879e-05 1.655384e-04 3.086461e-04 #> guiness -1.496463e-04 -4.662246e-04 -1.905673e-04 -3.642220e-04 #> hoegardeen 3.462062e-04 4.557837e-04 4.205444e-04 3.080245e-04 #> jupiler -8.073101e-05 -2.203453e-04 -1.514837e-04 -1.572771e-04 #> kingfisher 1.324881e-05 1.991329e-04 1.802238e-04 2.681872e-04 #> latrappe 1.829641e-04 2.106651e-04 -1.447749e-04 2.756836e-04 #> lindemanskriek 4.871774e-05 -4.788973e-05 -2.120403e-04 -1.394498e-04 #> nicechouffe 1.463372e-04 2.488056e-04 8.034353e-05 2.586078e-04 #> pecheresse 2.759482e-04 1.481251e-05 1.433130e-04 -1.556835e-05 #> sierranevada 1.406542e-04 -1.888577e-04 6.806233e-05 -5.042849e-05 #> tanglefoot 5.673867e-06 -2.751261e-04 -3.002656e-04 -2.455063e-04 #> tauro 2.932668e-04 1.286768e-04 1.547277e-04 1.336644e-04 #> westmalle -1.539093e-04 4.586356e-04 1.799417e-05 3.301881e-04 #> amrut 1.570262e-04 2.548664e-04 1.115168e-04 7.490810e-06 #> ballantines -3.868333e-05 3.003380e-04 1.592670e-04 -5.079525e-05 #> bushmills 2.135771e-04 -2.019147e-04 1.348464e-04 -1.302260e-04 #> chivas 1.332194e-04 1.056333e-04 2.227781e-05 4.227956e-05 #> dalmore -4.021158e-06 2.679348e-04 -2.632871e-05 1.881627e-04 #> famousgrouse -2.566731e-04 2.195639e-04 -7.568478e-05 1.842423e-04 #> glendronach 2.453495e-05 -7.915842e-06 -1.865175e-05 -6.786263e-05 #> glenmorangie 1.557411e-04 -3.527084e-06 1.414448e-04 -9.027797e-06 #> highlandpark 3.870735e-04 -4.437162e-04 1.970082e-04 -4.866817e-04 #> jackdaniels -1.751848e-04 -3.777874e-05 -1.953733e-04 2.389926e-04 #> jb 1.396719e-04 1.902920e-04 -7.877557e-05 4.429623e-05 #> johnniewalker 5.133497e-04 1.719490e-04 5.339652e-04 -1.814410e-04 #> magallan -1.577770e-04 -1.006505e-04 -1.482048e-04 -8.058980e-06 #> makersmark -5.600587e-04 -7.200799e-04 4.777646e-04 2.581853e-04 #> oban 8.787835e-05 1.113193e-04 1.307306e-04 -2.483305e-05 #> oldpotrero -3.831452e-04 2.156873e-04 -5.679089e-04 2.063675e-04 #> redbreast 2.541246e-05 2.426826e-05 -8.753325e-05 -8.652635e-06 #> tamdhu -3.383952e-05 3.365051e-04 -1.785979e-04 -4.280721e-06 #> wildturkey 3.002663e-04 1.207047e-04 1.615231e-04 -7.004425e-06 #> yoichi -1.168653e-04 -8.227670e-05 5.854442e-05 8.229082e-05 #> B12 C1 C2 C3 C4 #> brahma -1.917814e-04 0 -1.637571e-03 -3.936895e-03 5.408096e-03 #> caney 2.011956e-05 0 1.239828e-03 -2.845651e-04 3.757825e-04 #> chimay -3.197006e-06 0 -3.757608e-03 -1.797357e-03 -2.127924e-03 #> corona -6.091420e-06 0 -1.652864e-03 1.573302e-03 4.897281e-04 #> deusventrue -2.794108e-04 0 1.552775e-03 7.706329e-04 -1.416448e-03 #> duvel 1.659893e-04 0 2.872128e-04 -5.422392e-06 -7.785717e-04 #> franziskaner -2.140707e-04 0 -1.253868e-03 3.476506e-04 1.004621e-03 #> grimbergen 1.890428e-04 0 1.700875e-03 -1.452474e-04 4.332935e-04 #> guiness -2.602631e-04 0 -5.088378e-04 1.628258e-03 5.025916e-05 #> hoegardeen 2.814325e-04 0 -2.538102e-03 6.627214e-04 -1.481847e-03 #> jupiler -1.151375e-04 0 9.877198e-04 -8.223351e-05 1.286204e-04 #> kingfisher 1.550433e-04 0 8.355893e-04 -2.193322e-03 -9.853901e-04 #> latrappe -1.942322e-04 0 2.026476e-03 6.109498e-04 -1.518299e-04 #> lindemanskriek -5.113408e-05 0 -1.736348e-03 1.465734e-03 -1.513403e-03 #> nicechouffe 4.652882e-05 0 -5.467071e-04 2.799211e-04 -4.577128e-04 #> pecheresse 1.587407e-04 0 1.796104e-03 -3.206383e-04 -1.338857e-04 #> sierranevada 3.125122e-05 0 9.370620e-04 -7.543929e-04 2.972714e-04 #> tanglefoot -9.215486e-05 0 -7.405447e-04 3.028807e-04 6.337466e-04 #> tauro 1.226045e-04 0 1.122815e-04 -2.572009e-04 -8.133564e-04 #> westmalle 4.757341e-05 0 1.228197e-03 -2.741133e-04 9.140310e-05 #> amrut -9.179140e-05 0 4.658444e-04 -4.347520e-04 -3.326225e-05 #> ballantines 3.235267e-04 0 -5.591149e-04 1.469581e-03 -1.536579e-03 #> bushmills 2.015409e-04 0 -3.958316e-04 1.944836e-03 -7.053533e-05 #> chivas -6.666931e-05 0 -1.172232e-03 -1.218925e-03 -3.262755e-05 #> dalmore -9.894417e-05 0 6.958725e-04 -1.680610e-03 6.152298e-04 #> famousgrouse -7.211196e-05 0 7.115395e-05 8.468121e-04 -4.933730e-04 #> glendronach -9.224044e-05 0 -7.099606e-05 6.421159e-04 -4.706785e-04 #> glenmorangie 6.261072e-05 0 -8.919633e-06 -2.628346e-04 9.674043e-05 #> highlandpark 1.369676e-04 0 -1.617000e-03 5.528353e-04 -3.372340e-04 #> jackdaniels 3.169089e-04 0 5.328968e-04 -1.540810e-03 -5.769145e-04 #> jb -5.463792e-05 0 -2.505933e-03 -9.424246e-04 -8.780719e-04 #> johnniewalker -5.200179e-05 0 4.677592e-03 -4.233763e-04 -1.898993e-03 #> magallan -1.072102e-04 0 2.189543e-04 4.632813e-04 1.888985e-04 #> makersmark 8.085419e-06 0 1.698257e-03 -6.596354e-04 3.533379e-04 #> oban -6.805926e-05 0 6.795967e-07 1.085005e-06 -4.641661e-04 #> oldpotrero -3.604369e-04 0 -6.093255e-05 4.513517e-05 -4.902640e-04 #> redbreast 1.217829e-04 0 -1.468386e-03 1.265193e-04 -1.396525e-04 #> tamdhu -2.219702e-04 0 9.586941e-04 6.330302e-04 -2.779959e-04 #> wildturkey 2.260401e-05 0 -9.213008e-05 -1.129525e-03 -4.176692e-04 #> yoichi 1.472054e-04 0 5.380772e-05 -7.906572e-05 -7.656576e-04 #> C5 C6 C7 C8 #> brahma -1.259407e-03 -3.994402e-03 3.268582e-03 4.792269e-04 #> caney -4.017802e-05 4.699805e-04 2.518166e-04 6.300072e-04 #> chimay -4.663387e-04 -7.424827e-05 -8.096453e-05 9.946667e-04 #> corona 1.867708e-04 6.888736e-04 3.145355e-04 5.189042e-04 #> deusventrue 1.463377e-03 9.055123e-04 -2.834923e-04 -1.443910e-03 #> duvel 3.178998e-04 2.219253e-04 5.438377e-04 -3.518900e-06 #> franziskaner 1.054384e-03 2.433412e-04 9.526672e-04 8.662476e-04 #> grimbergen -6.417041e-04 -1.403671e-03 1.850428e-04 1.990252e-04 #> guiness 8.516115e-05 5.947385e-04 -3.856099e-04 2.426892e-04 #> hoegardeen -6.536099e-04 -5.091092e-04 -6.872483e-04 -4.089876e-04 #> jupiler 4.242307e-04 1.903101e-04 -1.512322e-04 3.486794e-04 #> kingfisher 1.200089e-03 4.039578e-05 -2.246083e-04 -6.682649e-04 #> latrappe -2.100725e-04 4.680496e-04 1.907268e-04 -1.386083e-04 #> lindemanskriek 2.721525e-04 -8.593526e-04 -1.905709e-04 1.402970e-04 #> nicechouffe -4.033887e-04 -3.674008e-04 -1.582921e-04 -3.898917e-04 #> pecheresse -3.165154e-04 -6.798663e-04 -1.857663e-04 -5.070674e-04 #> sierranevada 4.903049e-04 5.175725e-04 -5.450918e-04 -6.169308e-04 #> tanglefoot 6.556462e-04 1.058980e-03 8.585128e-04 5.745493e-04 #> tauro -4.748704e-04 -3.315681e-04 -4.564306e-04 -3.514821e-04 #> westmalle -4.491227e-04 -2.495132e-04 -7.270457e-05 -1.344863e-04 #> amrut 8.477464e-05 -1.080422e-04 2.126076e-04 -9.256970e-05 #> ballantines 6.528392e-04 -2.944984e-04 -5.656855e-04 1.789388e-04 #> bushmills 9.280815e-04 -4.013982e-04 -6.650163e-04 -5.644542e-04 #> chivas 1.300827e-04 -3.851168e-05 4.239507e-05 1.334791e-04 #> dalmore -2.964899e-04 -1.304289e-04 7.782306e-04 -4.877421e-04 #> famousgrouse 6.303902e-04 -1.322629e-04 -2.372041e-04 -2.550728e-05 #> glendronach -3.501431e-04 -2.525866e-04 3.742212e-04 1.133101e-04 #> glenmorangie -3.395833e-04 -4.246431e-04 -3.274667e-04 1.061570e-04 #> highlandpark 6.066669e-04 1.088092e-03 5.256719e-04 5.273203e-04 #> jackdaniels 1.023982e-03 9.323203e-04 1.214171e-03 5.898250e-04 #> jb 2.339479e-04 3.473492e-04 3.733691e-04 1.626720e-04 #> johnniewalker -8.686486e-04 -1.355694e-03 1.175580e-03 3.264915e-04 #> magallan 2.310078e-04 -1.038695e-04 -1.026307e-05 1.023165e-04 #> makersmark -5.037028e-04 -1.240866e-04 -7.956100e-05 -6.606345e-05 #> oban -3.076544e-04 -4.937905e-04 -1.310019e-05 -2.416906e-04 #> oldpotrero -5.717320e-04 -9.307817e-04 1.291075e-04 -5.512552e-04 #> redbreast -6.765261e-04 1.325618e-04 4.297985e-04 3.419357e-04 #> tamdhu -1.871447e-04 -1.524034e-04 6.923348e-05 -5.932353e-04 #> wildturkey -5.568095e-04 1.396939e-04 -3.130911e-04 -2.441291e-05 #> yoichi -1.807137e-04 -7.887244e-04 -4.647802e-04 -2.321719e-04 #> C9 C10 C11 C12 #> brahma -1.321861e-03 7.225736e-04 2.052451e-04 1.666890e-04 #> caney 4.837212e-04 -3.443095e-04 1.349160e-04 4.336526e-06 #> chimay -5.660053e-04 2.292011e-04 3.851391e-04 -2.066153e-05 #> corona 3.419355e-04 -4.427112e-05 5.053095e-04 2.703064e-04 #> deusventrue 5.149210e-05 4.983572e-04 -8.471361e-05 3.773608e-04 #> duvel 4.727181e-05 8.518990e-04 5.267156e-05 -7.761916e-06 #> franziskaner 4.052798e-04 2.307566e-04 5.425481e-04 8.822035e-04 #> grimbergen -4.235811e-04 -1.047152e-04 8.528320e-05 -4.862829e-04 #> guiness 2.578559e-05 -4.057230e-04 3.454914e-04 3.070080e-04 #> hoegardeen -2.093222e-04 -8.166019e-05 -5.849685e-04 -1.080950e-04 #> jupiler 3.426590e-04 1.476449e-04 3.134641e-04 2.698336e-04 #> kingfisher 1.267526e-04 2.565541e-04 -2.246671e-04 6.355569e-05 #> latrappe -4.351985e-06 -5.637614e-05 4.355069e-04 3.406179e-04 #> lindemanskriek -4.691485e-04 6.262551e-04 3.619995e-05 5.173449e-04 #> nicechouffe -2.084102e-04 4.207808e-04 7.211961e-05 -7.528575e-05 #> pecheresse -2.691263e-04 -5.693772e-04 -3.209598e-04 2.785471e-04 #> sierranevada 1.686643e-04 2.583335e-04 8.547137e-04 -1.139936e-04 #> tanglefoot 7.740523e-04 4.070373e-04 5.906937e-04 9.596081e-04 #> tauro -3.210499e-04 -2.265987e-04 5.213196e-05 1.560054e-07 #> westmalle 4.839335e-04 5.801730e-05 1.736045e-04 -1.456983e-04 #> amrut -1.864115e-04 -2.461486e-04 -3.925113e-04 -1.058934e-04 #> ballantines -5.195587e-04 3.044292e-04 -2.940957e-04 -8.254562e-05 #> bushmills -7.180710e-04 9.032786e-05 -3.120552e-04 3.338259e-04 #> chivas -3.525098e-05 -9.088640e-05 2.114664e-04 -4.123221e-05 #> dalmore 2.200639e-05 -1.248926e-04 -1.755355e-06 2.379108e-04 #> famousgrouse -3.212998e-04 3.215665e-04 -7.784050e-05 -5.945648e-04 #> glendronach 9.391914e-05 1.721023e-04 -5.496005e-04 -4.452810e-05 #> glenmorangie -1.452951e-05 2.274608e-05 8.210480e-05 2.227747e-04 #> highlandpark -1.043832e-04 2.593737e-04 7.274696e-06 -7.945600e-05 #> jackdaniels -6.541464e-05 8.873609e-04 3.142194e-04 5.911319e-04 #> jb -2.944987e-04 2.504811e-05 -2.127576e-05 -1.962938e-04 #> johnniewalker -8.111435e-05 -2.403699e-04 -1.403144e-03 -1.314933e-04 #> magallan 4.068423e-04 5.073294e-04 1.401801e-04 3.243760e-04 #> makersmark 4.971815e-04 6.070002e-04 1.442476e-05 -8.225582e-05 #> oban -1.976049e-04 -2.813942e-04 -2.577944e-04 -9.115022e-05 #> oldpotrero -5.682370e-04 1.529407e-07 -2.873197e-04 -1.840435e-04 #> redbreast -3.874401e-05 4.931648e-05 3.073398e-04 8.441133e-05 #> tamdhu -5.985664e-04 -4.647946e-04 -1.822017e-04 1.592463e-04 #> wildturkey 1.524887e-05 -6.414600e-04 2.874523e-04 -2.824274e-05 #> yoichi -2.834302e-04 1.556736e-04 -8.243757e-05 1.918715e-04 #> D1 D2 D3 D4 D5 #> brahma 0.2937120 -0.04602927 0.05240292 -0.035768593 0.03999516 #> caney 0.3046235 -0.07069129 0.05062805 -0.011400633 0.04383297 #> chimay 0.4156841 -0.09356117 0.04692603 -0.019249436 0.03965332 #> corona 0.2745921 -0.05755121 0.05150878 -0.011252954 0.03689351 #> deusventrue 0.3149661 -0.11964363 0.05529900 0.007135060 0.03861865 #> duvel 0.4496172 -0.09170033 0.05080071 -0.024018306 0.03036868 #> franziskaner 0.3002734 -0.05637154 0.04411627 -0.030282997 0.03014850 #> grimbergen 0.3651919 -0.09065897 0.05082210 -0.010242594 0.04317369 #> guiness 0.3505997 -0.08196508 0.04422914 -0.022614638 0.04330972 #> hoegardeen 0.2945708 -0.06921001 0.05080275 -0.012677940 0.04146196 #> jupiler 0.2872499 -0.06835188 0.05058090 -0.011055591 0.04109503 #> kingfisher 0.3038732 -0.06930174 0.04366992 -0.021888850 0.03308585 #> latrappe 0.4672257 -0.08743553 0.04401705 -0.038810531 0.02809569 #> lindemanskriek 0.3008112 -0.08389446 0.04783652 -0.013888395 0.04157982 #> nicechouffe 0.3127453 -0.09102591 0.04393446 -0.019927059 0.03779695 #> pecheresse 0.2877918 -0.07053519 0.05180968 -0.009320568 0.04090001 #> sierranevada 0.3773035 -0.07825101 0.05234901 -0.021705236 0.03981425 #> tanglefoot 0.4079636 -0.09801072 0.04110270 -0.028374451 0.04305818 #> tauro 0.2869165 -0.06868727 0.05072815 -0.010829946 0.04098501 #> westmalle 0.2901614 -0.07168182 0.04932024 -0.012449351 0.03886788 #> amrut 0.2916508 -0.07148727 0.03950517 -0.025866432 0.04086520 #> ballantines 0.4617826 -0.07263052 0.04705459 -0.054513278 0.00386769 #> bushmills 0.3159155 -0.02993821 0.05271205 -0.040523047 0.01619821 #> chivas 0.4010304 -0.12319740 0.04665481 -0.003452339 0.05226216 #> dalmore 0.4148687 -0.14805699 0.04396881 -0.010373143 0.05369374 #> famousgrouse 0.3082730 -0.05984603 0.04245023 -0.038145717 0.02994654 #> glendronach 0.2880496 -0.06941189 0.04010808 -0.026119002 0.04146027 #> glenmorangie 0.2784428 -0.06974209 0.02918920 -0.025306813 0.04836028 #> highlandpark 0.4216191 -0.07914764 0.04537064 -0.044351756 0.02868104 #> jackdaniels 0.3474874 -0.08171102 0.04501412 -0.023326513 0.04362364 #> jb 0.2978504 -0.07724044 0.04167029 -0.021228975 0.04549082 #> johnniewalker 0.3097702 -0.04720860 0.04457306 -0.040162288 0.02378800 #> magallan 0.2790080 -0.04764937 0.01811567 -0.036589697 0.02988117 #> makersmark 0.3905990 -0.12195322 0.04665759 0.014950483 0.04867625 #> oban 0.2773362 -0.07277254 0.03313763 -0.023775433 0.04405146 #> oldpotrero 0.3550787 -0.13906787 0.05059907 0.008348999 0.04726562 #> redbreast 0.3884532 -0.13265717 0.04117925 -0.003816545 0.05332588 #> tamdhu 0.2956700 -0.06219547 0.04086923 -0.024902731 0.04397834 #> wildturkey 0.3186215 -0.08962249 0.03633236 -0.023651702 0.05160018 #> yoichi 0.3745590 -0.07064336 0.04209729 -0.040564238 0.03281077 #> D6 D7 D8 D9 #> brahma 1.156917e-02 1.544573e-02 0.0013278090 0.0017860170 #> caney 4.485691e-03 9.597789e-03 0.0016029758 0.0082459711 #> chimay 1.731744e-02 1.044446e-02 0.0104067305 0.0026404547 #> corona -4.664986e-03 9.465002e-03 0.0001838085 0.0120730321 #> deusventrue -8.770510e-04 1.356919e-02 0.0076757796 0.0034745699 #> duvel 1.486796e-02 7.642213e-03 0.0154756340 0.0060020330 #> franziskaner 1.266218e-03 1.748451e-02 0.0047455611 0.0067787344 #> grimbergen 7.100085e-03 6.253179e-03 0.0076965820 0.0090999349 #> guiness 9.543784e-03 9.549881e-03 0.0017249204 0.0017518501 #> hoegardeen 2.601196e-03 1.267815e-02 0.0028528664 0.0079320590 #> jupiler 2.215650e-03 1.160311e-02 0.0034969489 0.0080290760 #> kingfisher 2.046087e-03 1.149394e-02 0.0039224376 0.0069746627 #> latrappe 2.444196e-02 2.163781e-02 0.0204539980 -0.0001441159 #> lindemanskriek 2.496230e-03 1.222294e-02 0.0053531769 0.0062723553 #> nicechouffe 3.314725e-03 1.247704e-02 0.0066425182 0.0051531928 #> pecheresse 2.471297e-03 1.468476e-02 0.0056123765 0.0084044229 #> sierranevada 1.057630e-02 8.974816e-03 0.0026404084 0.0003673360 #> tanglefoot 1.902021e-02 1.046530e-02 0.0039430719 -0.0033493172 #> tauro 2.321158e-03 1.173141e-02 0.0034750116 0.0079425387 #> westmalle 1.786521e-03 1.515342e-02 0.0060316179 0.0079388255 #> amrut 6.369733e-03 1.572832e-02 -0.0038463793 0.0013700406 #> ballantines 4.344419e-03 1.645402e-02 0.0254142957 0.0095935791 #> bushmills -1.167929e-02 2.000745e-02 0.0117755165 0.0158424792 #> chivas 7.036241e-03 -4.363041e-03 0.0063540528 0.0079672331 #> dalmore 1.718407e-02 -6.837798e-03 0.0070735547 -0.0019258037 #> famousgrouse 4.059251e-03 2.229183e-02 0.0037608752 0.0010406075 #> glendronach 6.223170e-03 1.521132e-02 -0.0043261577 0.0013210684 #> glenmorangie 5.822448e-03 1.976818e-02 -0.0044147538 0.0033213121 #> highlandpark 1.979571e-02 2.717259e-02 0.0200795294 -0.0021232596 #> jackdaniels 1.186579e-02 1.329499e-02 -0.0005343742 -0.0016003714 #> jb 6.441694e-03 1.187397e-02 -0.0057652170 0.0017868329 #> johnniewalker 8.789822e-05 2.661158e-02 0.0128165570 0.0105593342 #> magallan 6.181261e-03 2.628647e-02 0.0002557046 0.0036531313 #> makersmark -5.885380e-03 -3.124763e-04 0.0123974490 0.0123986615 #> oban 7.290747e-03 1.526810e-02 -0.0064234752 0.0024990961 #> oldpotrero -1.263673e-03 9.106123e-06 0.0131403235 0.0062358607 #> redbreast 7.554115e-03 -5.549155e-03 0.0028962725 0.0066649976 #> tamdhu 7.609569e-03 1.817766e-02 -0.0043937269 0.0004398248 #> wildturkey 1.072078e-02 1.329394e-02 -0.0045720419 -0.0006442784 #> yoichi 1.665764e-02 2.932085e-02 0.0147708913 0.0009353830 #> D10 D11 D12 #> brahma 0.006789017 0.0048196384 0.007143143 #> caney 0.011464283 0.0039468981 0.003663644 #> chimay 0.012590865 0.0018154608 0.002625857 #> corona 0.008346831 0.0027556006 0.002567053 #> deusventrue 0.006022626 0.0007085549 0.005811255 #> duvel 0.014318246 0.0021405582 -0.001168779 #> franziskaner 0.007215285 0.0030768626 0.006498196 #> grimbergen 0.013935311 0.0016133249 0.001782113 #> guiness 0.013609736 0.0052742301 0.006464424 #> hoegardeen 0.007661150 0.0026973921 0.005420800 #> jupiler 0.007523271 0.0027339312 0.004363034 #> kingfisher 0.006826146 0.0028630395 0.005290393 #> latrappe 0.007468498 -0.0011091276 0.003570302 #> lindemanskriek 0.007494807 0.0009831097 0.006687031 #> nicechouffe 0.007804735 0.0010554318 0.006544953 #> pecheresse 0.006507851 0.0023044001 0.005130825 #> sierranevada 0.013424754 0.0060565295 0.007716962 #> tanglefoot 0.012760316 0.0055315212 0.008787267 #> tauro 0.007452360 0.0026002512 0.004223806 #> westmalle 0.005389195 0.0009150318 0.004619774 #> amrut 0.008090140 0.0077694214 0.009648834 #> ballantines 0.009641210 -0.0013505569 0.001193993 #> bushmills 0.012190958 0.0027373737 0.003932980 #> chivas 0.019338356 0.0019726115 0.002305432 #> dalmore 0.016575636 0.0049437344 0.004000701 #> famousgrouse 0.003906640 0.0019458696 0.010187413 #> glendronach 0.008581179 0.0087430642 0.009902698 #> glenmorangie 0.007165778 0.0033642678 0.009454943 #> highlandpark 0.003043362 -0.0045393480 0.006887804 #> jackdaniels 0.009896143 0.0071305091 0.011652937 #> jb 0.011312129 0.0089093269 0.008895351 #> johnniewalker 0.004724823 -0.0013880745 0.003178167 #> magallan -0.002901850 0.0030725685 0.006182579 #> makersmark 0.007706173 -0.0025568628 0.002741739 #> oban 0.007789470 0.0092615797 0.008856510 #> oldpotrero 0.009884923 0.0004827760 0.006465018 #> redbreast 0.019010171 0.0030489037 0.003575003 #> tamdhu 0.006990252 0.0067355151 0.011091059 #> wildturkey 0.012225665 0.0056575767 0.009083087 #> yoichi 0.001967838 -0.0043542059 0.006408266 #getters bot.f[1] #> A1 A2 A3 A4 A5 #> 1.000000e+00 6.766531e-03 9.348184e-02 1.374288e-02 2.381857e-02 #> A6 A7 A8 A9 A10 #> 8.592275e-03 3.183571e-03 5.158502e-03 -7.262824e-04 4.728729e-03 #> A11 A12 B1 B2 B3 #> -1.373339e-03 1.636382e-03 0.000000e+00 -1.900652e-04 3.306231e-04 #> B4 B5 B6 B7 B8 #> -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> B9 B10 B11 B12 C1 #> -1.960132e-04 1.334431e-04 4.058288e-05 -1.917814e-04 0.000000e+00 #> C2 C3 C4 C5 C6 #> -1.637571e-03 -3.936895e-03 5.408096e-03 -1.259407e-03 -3.994402e-03 #> C7 C8 C9 C10 C11 #> 3.268582e-03 4.792269e-04 -1.321861e-03 7.225736e-04 2.052451e-04 #> C12 D1 D2 D3 D4 #> 1.666890e-04 2.937120e-01 -4.602927e-02 5.240292e-02 -3.576859e-02 #> D5 D6 D7 D8 D9 #> 3.999516e-02 1.156917e-02 1.544573e-02 1.327809e-03 1.786017e-03 #> D10 D11 D12 #> 6.789017e-03 4.819638e-03 7.143143e-03 bot.f[1:5] #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> A7 A8 A9 A10 A11 #> brahma 0.003183571 0.005158502 -0.0007262824 0.004728729 -0.0013733386 #> caney 0.003552709 0.007010166 0.0012149488 0.003873417 -0.0018777601 #> chimay -0.004741288 0.007814037 -0.0021126606 0.002204301 -0.0012371979 #> corona 0.005504589 0.007852411 0.0008767189 0.004420153 -0.0021742849 #> deusventrue 0.002521451 0.011391904 -0.0017339646 0.006208319 -0.0007936789 #> A12 B1 B2 B3 B4 #> brahma 0.001636382 0 -0.0001900652 3.306231e-04 -0.0005191749 #> caney 0.001133056 0 0.0005012013 -3.851293e-04 0.0003333918 #> chimay -0.001851423 0 0.0001843629 4.196107e-04 0.0003227901 #> corona 0.002630070 0 -0.0003586724 1.711055e-05 -0.0005501057 #> deusventrue 0.002868057 0 0.0001774985 -8.326845e-05 -0.0014033732 #> B5 B6 B7 B8 #> brahma 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> caney -2.899903e-04 7.350207e-05 -4.952054e-04 8.536695e-05 #> chimay -2.906714e-05 5.573360e-04 1.059517e-04 6.209192e-04 #> corona -1.907425e-04 -4.256287e-04 -2.147013e-04 -1.931107e-04 #> deusventrue -3.240180e-04 -9.330047e-04 6.515692e-04 -8.354423e-04 #> B9 B10 B11 B12 C1 #> brahma -1.960132e-04 0.0001334431 4.058288e-05 -1.917814e-04 0 #> caney -4.143363e-04 0.0001667420 -3.134942e-04 2.011956e-05 0 #> chimay 1.441644e-04 0.0001715223 5.930974e-05 -3.197006e-06 0 #> corona -3.048499e-04 -0.0002065499 -2.244684e-04 -6.091420e-06 0 #> deusventrue 2.287499e-05 -0.0006080012 2.971827e-04 -2.794108e-04 0 #> C2 C3 C4 C5 #> brahma -0.001637571 -0.0039368955 0.0054080962 -1.259407e-03 #> caney 0.001239828 -0.0002845651 0.0003757825 -4.017802e-05 #> chimay -0.003757608 -0.0017973566 -0.0021279238 -4.663387e-04 #> corona -0.001652864 0.0015733018 0.0004897281 1.867708e-04 #> deusventrue 0.001552775 0.0007706329 -0.0014164476 1.463377e-03 #> C6 C7 C8 C9 #> brahma -3.994402e-03 3.268582e-03 0.0004792269 -0.0013218613 #> caney 4.699805e-04 2.518166e-04 0.0006300072 0.0004837212 #> chimay -7.424827e-05 -8.096453e-05 0.0009946667 -0.0005660053 #> corona 6.888736e-04 3.145355e-04 0.0005189042 0.0003419355 #> deusventrue 9.055123e-04 -2.834923e-04 -0.0014439096 0.0000514921 #> C10 C11 C12 D1 D2 #> brahma 7.225736e-04 2.052451e-04 1.666890e-04 0.2937120 -0.04602927 #> caney -3.443095e-04 1.349160e-04 4.336526e-06 0.3046235 -0.07069129 #> chimay 2.292011e-04 3.851391e-04 -2.066153e-05 0.4156841 -0.09356117 #> corona -4.427112e-05 5.053095e-04 2.703064e-04 0.2745921 -0.05755121 #> deusventrue 4.983572e-04 -8.471361e-05 3.773608e-04 0.3149661 -0.11964363 #> D3 D4 D5 D6 D7 #> brahma 0.05240292 -0.03576859 0.03999516 0.011569168 0.015445729 #> caney 0.05062805 -0.01140063 0.04383297 0.004485691 0.009597789 #> chimay 0.04692603 -0.01924944 0.03965332 0.017317438 0.010444458 #> corona 0.05150878 -0.01125295 0.03689351 -0.004664986 0.009465002 #> deusventrue 0.05529900 0.00713506 0.03861865 -0.000877051 0.013569192 #> D8 D9 D10 D11 D12 #> brahma 0.0013278090 0.001786017 0.006789017 0.0048196384 0.007143143 #> caney 0.0016029758 0.008245971 0.011464283 0.0039468981 0.003663644 #> chimay 0.0104067305 0.002640455 0.012590865 0.0018154608 0.002625857 #> corona 0.0001838085 0.012073032 0.008346831 0.0027556006 0.002567053 #> deusventrue 0.0076757796 0.003474570 0.006022626 0.0007085549 0.005811255 #setters bot.f[1] <- 1:48 bot.f[1] #> A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 B1 B2 B3 B4 B5 B6 B7 B8 #> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 #> B9 B10 B11 B12 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 D1 D2 D3 D4 #> 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 #> D5 D6 D7 D8 D9 D10 D11 D12 #> 41 42 43 44 45 46 47 48 bot.f[1:5] <- matrix(1:48, nrow=5, ncol=48, byrow=TRUE) bot.f[1:5] #> A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 B1 B2 B3 B4 B5 B6 B7 B8 B9 #> brahma 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> caney 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> chimay 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> corona 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> deusventrue 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #> B10 B11 B12 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 D1 D2 D3 D4 D5 #> brahma 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> caney 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> chimay 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> corona 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> deusventrue 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 #> D6 D7 D8 D9 D10 D11 D12 #> brahma 42 43 44 45 46 47 48 #> caney 42 43 44 45 46 47 48 #> chimay 42 43 44 45 46 47 48 #> corona 42 43 44 45 46 47 48 #> deusventrue 42 43 44 45 46 47 48 # An illustration of Momocs design. See also browseVignettes(\"Momocs\") op <- opoly(olea, 5) #> 'nb.pts' missing and set to 91 op #> An OpnCoe object [ opoly analysis ] #> -------------------- #> - $coe: 210 open outlines described #> - $baseline1: (-0.5; 0), $baseline2: (0.5; 0) #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows class(op) #> [1] \"OpnCoe\" \"Coe\" op$coe # same thing #> Intercept x1 x2 x3 #> 0001-cAglan_O10VD 0.21728164 0.0820952380 -0.9016209 -0.0174933751 #> 0001-cAglan_O10VL 0.17440503 0.0338452396 -0.7077580 0.0188673254 #> 0001-cAglan_O11VD 0.17605784 -0.0181821226 -0.7153938 0.1131745169 #> 0001-cAglan_O11VL 0.20898408 -0.0527533722 -0.8654223 0.1766857390 #> 0001-cAglan_O12VD 0.22447919 0.0803230491 -0.9347773 0.0199351810 #> 0001-cAglan_O12VL 0.16235742 -0.0029369654 -0.6681510 0.0094286444 #> 0001-cAglan_O13VD 0.17792822 0.1754468212 -0.6844379 -0.0426301053 #> 0001-cAglan_O13VL 0.12672618 0.0009579514 -0.4663127 0.0002345741 #> 0001-cAglan_O14VD 0.21462762 0.0275940379 -0.8877420 0.0207363970 #> 0001-cAglan_O14VL 0.24974677 0.0114295543 -1.0496960 0.1144096127 #> 0001-cAglan_O15VD 0.19125493 0.1178119754 -0.7754215 -0.0039554397 #> 0001-cAglan_O15VL 0.12573315 -0.0158948388 -0.4548061 0.0543785873 #> 0001-cAglan_O16VD 0.19275344 0.1335641240 -0.7407366 -0.0987824861 #> 0001-cAglan_O16VL 0.24017875 0.0998083066 -1.0275196 -0.0037535364 #> 0001-cAglan_O17VD 0.22266045 0.0450388784 -0.9143523 0.0821645804 #> 0001-cAglan_O17VL 0.14600009 0.0498660478 -0.5422968 -0.0177351114 #> 0001-cAglan_O18VD 0.18420883 0.0304249548 -0.7217056 0.0571329023 #> 0001-cAglan_O18VL 0.12370513 -0.0362631392 -0.4909825 0.0458185347 #> 0001-cAglan_O19VD 0.20335401 0.0688023425 -0.8376389 0.0301347622 #> 0001-cAglan_O19VL 0.10684954 0.0041514686 -0.4071094 -0.0299624759 #> 0001-cAglan_O1VD 0.16530209 0.1263146505 -0.6782789 -0.0034335994 #> 0001-cAglan_O1VL 0.19264672 0.0047761942 -0.7913757 0.0958098961 #> 0001-cAglan_O20VD 0.18702310 0.1170531651 -0.7718111 -0.0272053979 #> 0001-cAglan_O20VL 0.12455551 -0.1083609770 -0.4811603 0.0629221022 #> 0001-cAglan_O21VD 0.17541333 0.0482173654 -0.7129816 -0.0052934872 #> 0001-cAglan_O21VL 0.13049212 -0.0750878456 -0.4945857 0.0640272991 #> 0001-cAglan_O22VD 0.21975666 0.0479308615 -0.9492226 0.0518640458 #> 0001-cAglan_O22VL 0.13247622 0.1404248712 -0.5054903 -0.0621738164 #> 0001-cAglan_O23VD 0.22546285 0.0560745366 -0.9582186 0.0037159169 #> 0001-cAglan_O23VL 0.24212924 0.0306932017 -1.0294416 0.1008862908 #> 0001-cAglan_O24VD 0.19318748 0.0424466715 -0.7711831 0.0273252643 #> 0001-cAglan_O24VL 0.14187946 -0.1420795711 -0.5392139 0.1535110671 #> 0001-cAglan_O25VD 0.18053154 0.1413722364 -0.7120755 -0.0994062981 #> 0001-cAglan_O25VL 0.11205801 0.1145850318 -0.4103983 -0.0618476073 #> 0001-cAglan_O26VD 0.20239973 0.0491003232 -0.8116939 -0.0175482137 #> 0001-cAglan_O26VL 0.14441048 0.0087197306 -0.5656701 0.0070965080 #> 0001-cAglan_O27VD 0.19430070 0.0758451426 -0.7543155 0.0160106238 #> 0001-cAglan_O27VL 0.13920048 -0.1010581520 -0.5586223 0.0824978707 #> 0001-cAglan_O28VD 0.21103626 0.0480058027 -0.8697517 -0.0050330250 #> 0001-cAglan_O28VL 0.20666836 0.0652070221 -0.8580052 0.0618490877 #> 0001-cAglan_O29VD 0.19468832 0.1445491038 -0.7807559 -0.1027170275 #> 0001-cAglan_O29VL 0.13299249 0.0500979876 -0.5446079 -0.0428964882 #> 0001-cAglan_O2VD 0.18049983 0.0742832172 -0.6915010 0.0075562215 #> 0001-cAglan_O2VL 0.12957708 -0.0371674783 -0.4899516 0.0134470093 #> 0001-cAglan_O30VD 0.19619922 0.0931831051 -0.7633346 -0.0037734250 #> 0001-cAglan_O30VL 0.13428137 -0.0949855468 -0.5180637 0.0730540220 #> 0001-cAglan_O3VD 0.18655581 0.0503218080 -0.7466846 0.0600255045 #> 0001-cAglan_O3VL 0.10854441 -0.0474882700 -0.4081974 -0.0023889824 #> 0001-cAglan_O4VD 0.22464009 0.0530388472 -0.9231306 0.0245281902 #> 0001-cAglan_O4VL 0.25130340 0.0544045848 -1.0351560 0.1001221781 #> 0001-cAglan_O5VD 0.21794122 0.0351172137 -0.8976885 0.0302506978 #> 0001-cAglan_O5VL 0.13854661 -0.1147399504 -0.5017741 0.1196361395 #> 0001-cAglan_O6VD 0.20929001 0.0317274815 -0.7933405 0.0455941659 #> 0001-cAglan_O6VL 0.10830615 -0.1334772845 -0.3818526 0.1085296685 #> 0001-cAglan_O7VD 0.19979218 0.0724848350 -0.7838685 0.0291604988 #> 0001-cAglan_O7VL 0.12137446 -0.1837766964 -0.4631785 0.1706838053 #> 0001-cAglan_O8VD 0.20441821 0.0443971169 -0.7750116 0.0648743263 #> 0001-cAglan_O8VL 0.13794457 -0.0427969220 -0.5336686 0.0354710750 #> 0001-cAglan_O9VD 0.22777242 0.0873679949 -0.9150431 -0.0305524031 #> 0001-cAglan_O9VL 0.13432972 -0.0663483259 -0.5186668 0.0576614115 #> 0010-cCypre_O10VD 0.21664664 0.0771151861 -0.8431580 0.0055686844 #> 0010-cCypre_O11VD 0.22657769 0.0840561136 -0.9403420 0.0351501734 #> 0010-cCypre_O12VD 0.20752990 0.0469980910 -0.8678666 -0.0064508049 #> 0010-cCypre_O13VD 0.21798817 0.1190150584 -0.8851341 0.0095341683 #> 0010-cCypre_O14VD 0.23790243 0.0880242563 -0.9476860 -0.0249063104 #> 0010-cCypre_O15VD 0.20192972 0.1043675498 -0.8099470 -0.0772529666 #> 0010-cCypre_O16VD 0.18846979 0.0521564425 -0.7454236 0.0247565427 #> 0010-cCypre_O17VD 0.19741251 0.1214672023 -0.8177804 0.0094837781 #> 0010-cCypre_O18VD 0.20484860 0.0150117186 -0.8090948 0.0262257293 #> 0010-cCypre_O19VD 0.21911959 -0.0071448581 -0.8783165 0.0950756512 #> 0010-cCypre_O1VD 0.21652524 0.0307253605 -0.8838807 0.0144966562 #> 0010-cCypre_O20VD 0.20437503 0.0446890906 -0.8481292 0.0012982517 #> 0010-cCypre_O21VD 0.20928315 -0.0047425083 -0.8365906 0.0851338181 #> 0010-cCypre_O22VD 0.20068649 0.0263515305 -0.8175089 0.0190617822 #> 0010-cCypre_O23VD 0.20200118 0.0442913447 -0.7690188 0.0286214821 #> 0010-cCypre_O24VD 0.20970105 0.0954665632 -0.8690775 -0.0342843373 #> 0010-cCypre_O25VD 0.19558959 0.0528796642 -0.7621603 -0.0035064562 #> 0010-cCypre_O26VD 0.16092845 0.1105083238 -0.6260891 -0.0519766946 #> 0010-cCypre_O27VD 0.22354804 0.0762563877 -0.9073819 0.0113738310 #> 0010-cCypre_O28VD 0.25284411 0.1135089079 -1.0562199 -0.0705761142 #> 0010-cCypre_O29VD 0.20929228 0.1024298793 -0.8112258 0.0130465695 #> 0010-cCypre_O2VD 0.21539905 0.1119643380 -0.8590483 -0.0027835694 #> 0010-cCypre_O30VD 0.21085574 0.0948220712 -0.8491454 -0.0568053215 #> 0010-cCypre_O3VD 0.21821076 0.0632225313 -0.8760574 0.0047080623 #> 0010-cCypre_O4VD 0.17573972 0.0836760575 -0.6897838 0.0262641847 #> 0010-cCypre_O5VD 0.21132292 0.0716806643 -0.8214542 -0.0261368673 #> 0010-cCypre_O6VD 0.20888227 0.0177411558 -0.8064397 0.0466703965 #> 0010-cCypre_O7VD 0.22546726 0.0742158994 -0.9324599 -0.0103709292 #> 0010-cCypre_O8VD 0.22285661 0.0988769143 -0.8868088 -0.0118949221 #> 0010-cCypre_O9VD 0.18084614 0.0550005047 -0.7079343 0.0372301333 #> 0023-cPicMa_O10VD 0.18023440 -0.0104423084 -0.7036097 0.0574064601 #> 0023-cPicMa_O10VL 0.13896766 -0.0666344995 -0.5452281 0.0685926652 #> 0023-cPicMa_O11VD 0.15869729 -0.0290777606 -0.6325277 0.0379601479 #> 0023-cPicMa_O11VL 0.13502523 -0.1076669957 -0.4992451 0.1154668016 #> 0023-cPicMa_O12VD 0.16826500 0.0741055368 -0.6874212 0.0946456510 #> 0023-cPicMa_O12VL 0.11781090 -0.1453200143 -0.4870541 0.0812109800 #> 0023-cPicMa_O13VD 0.16301131 0.0778725780 -0.6149270 -0.0571360912 #> 0023-cPicMa_O13VL 0.12275098 -0.0527633558 -0.4675046 0.0307095588 #> 0023-cPicMa_O14VD 0.13827935 0.1266522382 -0.5025416 -0.0192610457 #> 0023-cPicMa_O14VL 0.10647158 -0.1522085315 -0.3914520 0.1304719508 #> 0023-cPicMa_O15VD 0.16556813 0.0393342982 -0.6320543 0.0863640911 #> 0023-cPicMa_O15VL 0.12745864 -0.1428865216 -0.4695294 0.1339881982 #> 0023-cPicMa_O16VD 0.16045134 0.0168314773 -0.6108011 0.0134530243 #> 0023-cPicMa_O16VL 0.12029119 -0.1170753181 -0.4365765 0.0835421031 #> 0023-cPicMa_O17VD 0.16226592 0.0816795634 -0.6016251 0.0298334288 #> 0023-cPicMa_O17VL 0.11357658 -0.1792328355 -0.3986460 0.1322992067 #> 0023-cPicMa_O18VD 0.16638132 0.0684949076 -0.5956065 0.0264991566 #> 0023-cPicMa_O18VL 0.11848233 -0.0363097034 -0.4669173 0.0006087119 #> 0023-cPicMa_O19VD 0.16901084 0.0378944650 -0.6589385 0.0740530662 #> 0023-cPicMa_O19VL 0.22644888 0.0763861985 -0.9323757 0.0506926913 #> 0023-cPicMa_O1VD 0.12849178 -0.1342044221 -0.5483587 0.0968465651 #> 0023-cPicMa_O1VL 0.11480402 -0.2179034919 -0.4930746 0.1561838956 #> 0023-cPicMa_O20VD 0.15926487 0.0395733248 -0.5931178 0.0209588733 #> 0023-cPicMa_O20VL 0.21817155 0.0634661933 -0.8472227 0.0489972849 #> 0023-cPicMa_O21VD 0.14475764 0.1162981960 -0.5619421 -0.0020248439 #> 0023-cPicMa_O21VL 0.19242857 0.0943166568 -0.7961330 0.0331400784 #> 0023-cPicMa_O22VD 0.16100106 -0.0427769008 -0.6491867 0.0171716149 #> 0023-cPicMa_O22VL 0.12490782 -0.1809323658 -0.5294327 0.0951303181 #> 0023-cPicMa_O23VD 0.18289145 0.0640759483 -0.7037168 -0.0078132994 #> 0023-cPicMa_O23VL 0.13452876 -0.1312014149 -0.5802704 0.0996591952 #> 0023-cPicMa_O24VD 0.19934999 0.0456096654 -0.7958312 -0.0004781872 #> 0023-cPicMa_O24VL 0.12963319 -0.1572994323 -0.5721961 0.1086123738 #> 0023-cPicMa_O25VD 0.14439059 -0.0146215488 -0.5419901 0.0306888082 #> 0023-cPicMa_O25VL 0.10502262 -0.1073404149 -0.4122691 0.1050740550 #> 0023-cPicMa_O26VD 0.16272318 0.0888197913 -0.5747101 -0.0479273126 #> 0023-cPicMa_O26VL 0.09568899 -0.1213585727 -0.3809030 0.0659043677 #> 0023-cPicMa_O27VD 0.12524989 -0.0573789027 -0.4711746 0.0307401429 #> 0023-cPicMa_O27VL 0.13361958 -0.0928477731 -0.5328221 0.0749206862 #> 0023-cPicMa_O28VD 0.21391197 0.0675319793 -0.8683864 -0.0566872739 #> 0023-cPicMa_O28VL 0.14369714 -0.0701206032 -0.5640867 0.0591683033 #> 0023-cPicMa_O29VD 0.15773919 0.0662362921 -0.6110751 -0.0507006097 #> 0023-cPicMa_O29VL 0.13028478 -0.0471713489 -0.4877567 0.0414531712 #> 0023-cPicMa_O2VD 0.15271084 0.0992512146 -0.6006278 0.0252888763 #> 0023-cPicMa_O2VL 0.12709431 -0.0944840154 -0.5058892 0.0760934497 #> 0023-cPicMa_O30VD 0.17732452 0.0563426943 -0.6601990 0.0621056170 #> 0023-cPicMa_O30VL 0.11544940 -0.1863099061 -0.4840974 0.1826444722 #> 0023-cPicMa_O3VD 0.17960537 0.0191052345 -0.6953965 -0.0004361502 #> 0023-cPicMa_O3VL 0.11576084 -0.0928395617 -0.4491746 0.0710991480 #> 0023-cPicMa_O4VD 0.14926554 0.0864129714 -0.5701828 0.0209237652 #> 0023-cPicMa_O4VL 0.11981147 -0.1522480705 -0.4663968 0.1165253617 #> 0023-cPicMa_O5VD 0.11037121 -0.0432484353 -0.4150343 0.0078200940 #> 0023-cPicMa_O5VL 0.07092883 -0.1236401109 -0.2737980 0.0720750035 #> 0023-cPicMa_O6VD 0.17806477 0.0363866228 -0.7292810 -0.0253226650 #> 0023-cPicMa_O6VL 0.13172240 -0.0529433591 -0.5388466 0.0348096395 #> 0023-cPicMa_O7VD 0.14579934 -0.1049938929 -0.6189755 0.0878308325 #> 0023-cPicMa_O7VL 0.10160327 -0.1987401594 -0.4375640 0.1536385781 #> 0023-cPicMa_O8VD 0.17021212 0.0832735755 -0.6301950 0.0156335714 #> 0023-cPicMa_O8VL 0.21504814 0.0924220700 -0.8673284 0.0367395161 #> 0023-cPicMa_O9VD 0.17824041 -0.0115237793 -0.6806192 0.0372814840 #> 0023-cPicMa_O9VL 0.12788664 -0.1443870373 -0.5150814 0.1169215484 #> 0125-wMouBo1_O10VD 0.23074741 -0.0101734290 -0.9391095 0.0661802550 #> 0125-wMouBo1_O10VL 0.24990343 0.0836208995 -1.0408045 0.0386524965 #> 0125-wMouBo1_O11VD 0.23053038 0.0628572473 -0.9705205 -0.0080583183 #> 0125-wMouBo1_O11VL 0.21624241 0.0449956240 -0.9030091 0.0705556367 #> 0125-wMouBo1_O12VD 0.19066115 0.0458008145 -0.7902542 0.0442912598 #> 0125-wMouBo1_O12VL 0.23561435 0.1028016687 -0.9467364 0.0408696967 #> 0125-wMouBo1_O13VD 0.25267603 0.0925693911 -1.0495399 -0.0191122008 #> 0125-wMouBo1_O13VL 0.23204287 0.0008319173 -0.9553313 0.1079494264 #> 0125-wMouBo1_O14VD 0.21939596 0.0614014037 -0.9278719 0.0073275779 #> 0125-wMouBo1_O14VL 0.22992852 0.1190731238 -0.9126497 -0.0144151468 #> 0125-wMouBo1_O15VD 0.21512832 -0.0272326723 -0.8580552 0.0510604863 #> 0125-wMouBo1_O15VL 0.25352482 0.0977260428 -1.0174843 0.0204523978 #> 0125-wMouBo1_O16VD 0.23423614 0.0633411629 -0.9697099 0.0546065802 #> 0125-wMouBo1_O16VL 0.23326324 0.0488121606 -0.9494775 0.0695524370 #> 0125-wMouBo1_O17VD 0.22052161 0.0832275267 -0.9054632 0.0488414527 #> 0125-wMouBo1_O17VL 0.23176223 0.0423807072 -0.9708804 0.0691689042 #> 0125-wMouBo1_O18VD 0.22137457 0.0667803792 -0.9594549 -0.0053748893 #> 0125-wMouBo1_O18VL 0.21477981 0.0995960722 -0.8879203 0.0419509417 #> 0125-wMouBo1_O19VD 0.20398899 -0.0609533423 -0.8709192 0.1105576865 #> 0125-wMouBo1_O19VL 0.20426129 0.0509978535 -0.8246557 0.0040920315 #> 0125-wMouBo1_O1VD 0.22026276 0.0780412149 -0.9278662 0.0354235848 #> 0125-wMouBo1_O1VL 0.23496803 0.1139643929 -0.9551441 0.0292138104 #> 0125-wMouBo1_O20VD 0.21821767 0.0322591445 -0.9016256 0.0602308906 #> 0125-wMouBo1_O20VL 0.23442593 0.0327895956 -0.9817619 0.0597326015 #> 0125-wMouBo1_O21VD 0.18909979 0.0462617258 -0.7798647 0.0297087552 #> 0125-wMouBo1_O21VL 0.24969155 0.0995791291 -1.0188876 0.0488933559 #> 0125-wMouBo1_O22VD 0.22984107 0.0654461893 -0.9451709 0.0310217968 #> 0125-wMouBo1_O22VL 0.24550951 0.0520980933 -1.0086728 0.0572622480 #> 0125-wMouBo1_O23VD 0.24925436 0.0373694748 -1.0252985 0.0209736348 #> 0125-wMouBo1_O23VL 0.22043348 -0.0301946741 -0.9294530 0.0394466473 #> 0125-wMouBo1_O24VD 0.22290706 0.0805151751 -0.9019173 0.0418668268 #> 0125-wMouBo1_O24VL 0.24100542 0.0335096307 -0.9785418 0.0623975907 #> 0125-wMouBo1_O25VD 0.23384817 0.0816932466 -0.9911284 -0.0068789229 #> 0125-wMouBo1_O25VL 0.22292557 0.0432838189 -0.9333467 0.0574774987 #> 0125-wMouBo1_O26VD 0.21810243 0.0513093050 -0.9217217 -0.0131430251 #> 0125-wMouBo1_O26VL 0.19810765 0.0242678007 -0.8075390 0.0565630002 #> 0125-wMouBo1_O27VD 0.23187453 0.0453093495 -0.9894214 -0.0085185471 #> 0125-wMouBo1_O27VL 0.20408385 0.0202634500 -0.8002120 0.0336295414 #> 0125-wMouBo1_O28VD 0.22025843 0.1121501527 -0.9198706 -0.0582466407 #> 0125-wMouBo1_O28VL 0.18561477 0.0032354513 -0.7452582 0.0375723248 #> 0125-wMouBo1_O29VD 0.25709114 0.1175532466 -1.0950456 -0.0212746551 #> 0125-wMouBo1_O29VL 0.23486253 0.0577475395 -0.9383747 0.0560995104 #> 0125-wMouBo1_O2VD 0.22302483 0.0333965363 -0.9413178 0.0243144765 #> 0125-wMouBo1_O2VL 0.23892087 0.0979275281 -0.9877977 -0.0168207170 #> 0125-wMouBo1_O30VD 0.27219534 0.1190873704 -1.1221068 0.0269060340 #> 0125-wMouBo1_O30VL 0.25088715 0.0935315155 -1.0587948 0.0425885246 #> 0125-wMouBo1_O3VD 0.23337441 0.0519188288 -0.9806883 0.0214060409 #> 0125-wMouBo1_O3VL 0.21313679 0.0075232908 -0.8638998 0.0355457609 #> 0125-wMouBo1_O4VD 0.19510917 -0.0262698897 -0.7865855 0.0824134876 #> 0125-wMouBo1_O4VL 0.24148398 0.0590954249 -1.0192049 0.0133718728 #> 0125-wMouBo1_O5VD 0.23463351 0.0127890100 -0.9947945 0.0617170374 #> 0125-wMouBo1_O5VL 0.23540593 0.0927530157 -0.9473588 0.0241599004 #> 0125-wMouBo1_O6VD 0.21388069 0.0448125843 -0.8811050 -0.0187149803 #> 0125-wMouBo1_O6VL 0.19693370 -0.0404391694 -0.7981819 0.1110957370 #> 0125-wMouBo1_O7VD 0.23515227 0.0636867722 -0.9362205 0.0767137787 #> 0125-wMouBo1_O7VL 0.19075490 0.0693636751 -0.7369358 0.0102032851 #> 0125-wMouBo1_O8VD 0.22059769 0.0238591389 -0.9479522 0.0622891501 #> 0125-wMouBo1_O8VL 0.22524616 0.0696864084 -0.9204583 0.0659353881 #> 0125-wMouBo1_O9VD 0.23668791 0.0296600751 -1.0124501 0.0659259928 #> 0125-wMouBo1_O9VL 0.22708513 0.0726133899 -0.9372184 0.0486002167 #> x4 x5 #> 0001-cAglan_O10VD -0.1122924204 0.011811482 #> 0001-cAglan_O10VL -0.0779230878 0.029245826 #> 0001-cAglan_O11VD -0.0532882009 0.006747825 #> 0001-cAglan_O11VL -0.1117488969 0.023925077 #> 0001-cAglan_O12VD -0.1449913711 -0.042287326 #> 0001-cAglan_O12VL -0.0379246316 0.063364106 #> 0001-cAglan_O13VD -0.1250633094 -0.054783966 #> 0001-cAglan_O13VL -0.0798250819 0.017944805 #> 0001-cAglan_O14VD -0.1308675889 0.011091031 #> 0001-cAglan_O14VL -0.2004433864 0.045232179 #> 0001-cAglan_O15VD -0.0919883678 -0.059553445 #> 0001-cAglan_O15VL -0.0871089172 0.018909477 #> 0001-cAglan_O16VD -0.1380569681 -0.042979021 #> 0001-cAglan_O16VL -0.1548657148 -0.037662322 #> 0001-cAglan_O17VD -0.1444969953 -0.011744608 #> 0001-cAglan_O17VL -0.0694319614 0.033040122 #> 0001-cAglan_O18VD -0.1020634949 -0.029566500 #> 0001-cAglan_O18VL -0.0204580794 0.039427706 #> 0001-cAglan_O19VD -0.1131448867 -0.035180217 #> 0001-cAglan_O19VL -0.0328009617 0.034406695 #> 0001-cAglan_O1VD -0.0494508094 -0.017792278 #> 0001-cAglan_O1VL -0.0675891208 -0.006894284 #> 0001-cAglan_O20VD -0.0693864212 -0.068788491 #> 0001-cAglan_O20VL -0.0519473662 0.069127856 #> 0001-cAglan_O21VD -0.0690504967 0.029583750 #> 0001-cAglan_O21VL -0.0572925691 0.039067673 #> 0001-cAglan_O22VD -0.0733540268 -0.034595355 #> 0001-cAglan_O22VL -0.0211530345 -0.007149806 #> 0001-cAglan_O23VD -0.1693545165 0.035544176 #> 0001-cAglan_O23VL -0.1668900643 0.001166044 #> 0001-cAglan_O24VD -0.1005547221 0.031901050 #> 0001-cAglan_O24VL -0.0719870654 0.036591949 #> 0001-cAglan_O25VD -0.0908727626 0.025277881 #> 0001-cAglan_O25VL -0.0280126192 0.013721081 #> 0001-cAglan_O26VD -0.1245654638 0.046648700 #> 0001-cAglan_O26VL -0.0502755364 0.042628438 #> 0001-cAglan_O27VD -0.1408497750 -0.019202606 #> 0001-cAglan_O27VL -0.0507554258 0.029550696 #> 0001-cAglan_O28VD -0.1154323362 0.032326606 #> 0001-cAglan_O28VL -0.1173164923 -0.017835140 #> 0001-cAglan_O29VD -0.0869127901 0.007539585 #> 0001-cAglan_O29VL -0.0067273762 0.023726566 #> 0001-cAglan_O2VD -0.1032251214 0.016413419 #> 0001-cAglan_O2VL -0.0855077702 0.027421298 #> 0001-cAglan_O30VD -0.1172515186 0.007129656 #> 0001-cAglan_O30VL -0.0600350227 0.050921750 #> 0001-cAglan_O3VD -0.0790997095 -0.023984316 #> 0001-cAglan_O3VL -0.0392628872 0.035887647 #> 0001-cAglan_O4VD -0.1276614263 0.020245469 #> 0001-cAglan_O4VL -0.2121600328 0.034486435 #> 0001-cAglan_O5VD -0.1284843396 0.042959266 #> 0001-cAglan_O5VL -0.1120167371 0.060378285 #> 0001-cAglan_O6VD -0.1633809410 0.053901214 #> 0001-cAglan_O6VL -0.0442512950 0.054976662 #> 0001-cAglan_O7VD -0.1322575676 -0.036853482 #> 0001-cAglan_O7VL -0.0294330372 0.036555650 #> 0001-cAglan_O8VD -0.1652197160 -0.006575256 #> 0001-cAglan_O8VL -0.0707585310 0.040124177 #> 0001-cAglan_O9VD -0.1759010895 -0.037099969 #> 0001-cAglan_O9VL -0.0507375054 0.021052215 #> 0010-cCypre_O10VD -0.1907663852 0.033668073 #> 0010-cCypre_O11VD -0.1525375504 -0.030964361 #> 0010-cCypre_O12VD -0.1231142611 -0.065651764 #> 0010-cCypre_O13VD -0.1644570401 -0.074020050 #> 0010-cCypre_O14VD -0.2271665800 0.041464998 #> 0010-cCypre_O15VD -0.1350791563 -0.004793408 #> 0010-cCypre_O16VD -0.0956731090 -0.003839584 #> 0010-cCypre_O17VD -0.0901885112 -0.046486991 #> 0010-cCypre_O18VD -0.1403705992 0.084359742 #> 0010-cCypre_O19VD -0.1563634433 0.062309880 #> 0010-cCypre_O1VD -0.1346347584 0.051534887 #> 0010-cCypre_O20VD -0.1215729802 0.026564366 #> 0010-cCypre_O21VD -0.1376461798 0.096000661 #> 0010-cCypre_O22VD -0.1060803100 0.064167473 #> 0010-cCypre_O23VD -0.1329278852 0.034698758 #> 0010-cCypre_O24VD -0.0930279840 0.005855714 #> 0010-cCypre_O25VD -0.1381173573 -0.007826328 #> 0010-cCypre_O26VD -0.0775672556 0.009821264 #> 0010-cCypre_O27VD -0.1487340347 -0.031215169 #> 0010-cCypre_O28VD -0.2124403577 -0.001384415 #> 0010-cCypre_O29VD -0.1641377620 -0.029696650 #> 0010-cCypre_O2VD -0.1447761610 -0.044424134 #> 0010-cCypre_O30VD -0.1339518135 0.007734536 #> 0010-cCypre_O3VD -0.1547479282 0.023163341 #> 0010-cCypre_O4VD -0.0997767339 -0.020756902 #> 0010-cCypre_O5VD -0.1761225193 0.041985220 #> 0010-cCypre_O6VD -0.1582268752 0.073067174 #> 0010-cCypre_O7VD -0.1754658206 0.023412541 #> 0010-cCypre_O8VD -0.1851627118 0.035725658 #> 0010-cCypre_O9VD -0.1021910356 -0.012082703 #> 0023-cPicMa_O10VD -0.0857539759 0.061289379 #> 0023-cPicMa_O10VL -0.0564807376 0.068334285 #> 0023-cPicMa_O11VD -0.0551361198 0.042508240 #> 0023-cPicMa_O11VL -0.0853995635 0.046183371 #> 0023-cPicMa_O12VD -0.0327860101 -0.059873043 #> 0023-cPicMa_O12VL -0.0388282159 0.088302812 #> 0023-cPicMa_O13VD -0.1001633543 0.033842951 #> 0023-cPicMa_O13VL -0.0636811761 0.035023652 #> 0023-cPicMa_O14VD -0.0729737229 -0.053417115 #> 0023-cPicMa_O14VL -0.0313737876 0.060946265 #> 0023-cPicMa_O15VD -0.1008239212 -0.032607123 #> 0023-cPicMa_O15VL -0.0984171536 0.029341475 #> 0023-cPicMa_O16VD -0.0607390806 0.081181128 #> 0023-cPicMa_O16VL -0.0721021678 0.094294448 #> 0023-cPicMa_O17VD -0.0772352632 -0.014461957 #> 0023-cPicMa_O17VL -0.0593830883 0.081110589 #> 0023-cPicMa_O18VD -0.1335489220 -0.018785123 #> 0023-cPicMa_O18VL -0.0600621897 0.013575514 #> 0023-cPicMa_O19VD -0.0721537904 -0.027002789 #> 0023-cPicMa_O19VL -0.1612410146 0.015468415 #> 0023-cPicMa_O1VD -0.0091607201 0.080203390 #> 0023-cPicMa_O1VL -0.0291126840 0.076773890 #> 0023-cPicMa_O20VD -0.0843202662 0.014591763 #> 0023-cPicMa_O20VL -0.2102592669 0.049305586 #> 0023-cPicMa_O21VD -0.0294556808 -0.039773874 #> 0023-cPicMa_O21VL -0.1013156169 -0.016776722 #> 0023-cPicMa_O22VD -0.0705997881 0.071158584 #> 0023-cPicMa_O22VL -0.0619885032 0.075882177 #> 0023-cPicMa_O23VD -0.1004483432 0.034087273 #> 0023-cPicMa_O23VL -0.0380569222 0.081488131 #> 0023-cPicMa_O24VD -0.1103975534 0.031535176 #> 0023-cPicMa_O24VL -0.0267003906 0.040516694 #> 0023-cPicMa_O25VD -0.0841112011 0.068130610 #> 0023-cPicMa_O25VL 0.0036493955 0.044123037 #> 0023-cPicMa_O26VD -0.1422762062 0.019234925 #> 0023-cPicMa_O26VL 0.0005981636 0.054609082 #> 0023-cPicMa_O27VD -0.0585286462 0.070009911 #> 0023-cPicMa_O27VL -0.0520978825 0.059749831 #> 0023-cPicMa_O28VD -0.1440411643 0.016242607 #> 0023-cPicMa_O28VL -0.0910726089 0.023344220 #> 0023-cPicMa_O29VD -0.0704700003 0.035313517 #> 0023-cPicMa_O29VL -0.0829926763 0.047269699 #> 0023-cPicMa_O2VD -0.0639971447 -0.056753292 #> 0023-cPicMa_O2VL -0.0459464593 0.034596955 #> 0023-cPicMa_O30VD -0.1006703190 -0.034561788 #> 0023-cPicMa_O30VL -0.0209529952 0.053568090 #> 0023-cPicMa_O3VD -0.1249799045 0.025985322 #> 0023-cPicMa_O3VL -0.0270558927 0.048189316 #> 0023-cPicMa_O4VD -0.0387193850 -0.051098804 #> 0023-cPicMa_O4VL -0.0399518540 0.078274009 #> 0023-cPicMa_O5VD -0.0364361232 0.063559785 #> 0023-cPicMa_O5VL -0.0009228800 0.038845032 #> 0023-cPicMa_O6VD -0.0527213482 0.072467493 #> 0023-cPicMa_O6VL -0.0262096667 0.044631921 #> 0023-cPicMa_O7VD -0.0193040556 0.076181244 #> 0023-cPicMa_O7VL -0.0164588009 0.065974155 #> 0023-cPicMa_O8VD -0.1011002383 -0.050500162 #> 0023-cPicMa_O8VL -0.1474562057 -0.055326861 #> 0023-cPicMa_O9VD -0.1229228162 0.052863918 #> 0023-cPicMa_O9VL -0.0471838228 0.042469701 #> 0125-wMouBo1_O10VD -0.1875598962 0.068769161 #> 0125-wMouBo1_O10VL -0.1832705835 -0.004511738 #> 0125-wMouBo1_O11VD -0.1616470914 0.031138798 #> 0125-wMouBo1_O11VL -0.1223357674 0.011970531 #> 0125-wMouBo1_O12VD -0.1143140795 0.036669271 #> 0125-wMouBo1_O12VL -0.1868888245 -0.011632125 #> 0125-wMouBo1_O13VD -0.1937221789 0.020989146 #> 0125-wMouBo1_O13VL -0.1469640409 0.031287779 #> 0125-wMouBo1_O14VD -0.1114505748 0.031490738 #> 0125-wMouBo1_O14VL -0.1800797076 -0.028402206 #> 0125-wMouBo1_O15VD -0.1869858922 0.072466004 #> 0125-wMouBo1_O15VL -0.2168073770 -0.021286336 #> 0125-wMouBo1_O16VD -0.1535981261 0.011615355 #> 0125-wMouBo1_O16VL -0.1899418287 0.009715178 #> 0125-wMouBo1_O17VD -0.1391688664 -0.005128136 #> 0125-wMouBo1_O17VL -0.1277018851 -0.009272098 #> 0125-wMouBo1_O18VD -0.1443842365 0.031073880 #> 0125-wMouBo1_O18VL -0.1390597617 -0.004759846 #> 0125-wMouBo1_O19VD -0.1441671535 0.060497508 #> 0125-wMouBo1_O19VL -0.1221715131 0.020918665 #> 0125-wMouBo1_O1VD -0.1417840460 -0.015559430 #> 0125-wMouBo1_O1VL -0.1698479339 -0.025768093 #> 0125-wMouBo1_O20VD -0.1372108152 -0.004491672 #> 0125-wMouBo1_O20VL -0.1535939815 0.029665377 #> 0125-wMouBo1_O21VD -0.0891273779 -0.005008645 #> 0125-wMouBo1_O21VL -0.1890499757 -0.015240229 #> 0125-wMouBo1_O22VD -0.1637553199 0.003421954 #> 0125-wMouBo1_O22VL -0.1623708983 -0.008730847 #> 0125-wMouBo1_O23VD -0.1834655316 0.026522318 #> 0125-wMouBo1_O23VL -0.1674130936 0.063389559 #> 0125-wMouBo1_O24VD -0.1586301633 -0.002838081 #> 0125-wMouBo1_O24VL -0.2039197415 -0.013594800 #> 0125-wMouBo1_O25VD -0.1682203008 0.017616638 #> 0125-wMouBo1_O25VL -0.1090353052 0.004866802 #> 0125-wMouBo1_O26VD -0.1583415388 0.030290845 #> 0125-wMouBo1_O26VL -0.1289387583 0.041994378 #> 0125-wMouBo1_O27VD -0.1677297119 0.056390324 #> 0125-wMouBo1_O27VL -0.1377412296 0.047386485 #> 0125-wMouBo1_O28VD -0.1441183994 0.006142353 #> 0125-wMouBo1_O28VL -0.1500057364 0.071254159 #> 0125-wMouBo1_O29VD -0.1841434041 0.006546213 #> 0125-wMouBo1_O29VL -0.1717283394 0.002413615 #> 0125-wMouBo1_O2VD -0.1787113472 0.029780265 #> 0125-wMouBo1_O2VL -0.2069887483 -0.008301580 #> 0125-wMouBo1_O30VD -0.2596889585 -0.033590471 #> 0125-wMouBo1_O30VL -0.2089829321 -0.009712427 #> 0125-wMouBo1_O3VD -0.1822212213 0.068692130 #> 0125-wMouBo1_O3VL -0.1615093101 0.059007889 #> 0125-wMouBo1_O4VD -0.1243448588 0.040692622 #> 0125-wMouBo1_O4VL -0.1712222718 -0.002086956 #> 0125-wMouBo1_O5VD -0.1581744157 0.064188642 #> 0125-wMouBo1_O5VL -0.2060281371 -0.040847996 #> 0125-wMouBo1_O6VD -0.1058225116 0.006360021 #> 0125-wMouBo1_O6VL -0.1285952926 0.066283858 #> 0125-wMouBo1_O7VD -0.1811606623 0.020997417 #> 0125-wMouBo1_O7VL -0.0819459609 0.008617285 #> 0125-wMouBo1_O8VD -0.1270985763 -0.005867603 #> 0125-wMouBo1_O8VL -0.1449122001 -0.006618885 #> 0125-wMouBo1_O9VD -0.1577287178 0.010577178 #> 0125-wMouBo1_O9VL -0.1480660701 -0.003695914 wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wp #> An LdkCoe [full Generalized Procrustes] object with: #> -------------------- #> - $coo: 127 configuration of landmarks (18 +/- 0 coordinates) #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows class(wp) # for Ldk methods, LdkCoe objects can also be considered as Coo objects #> [1] \"LdkCoe\" \"Coe\" \"Ldk\" \"Coo\" # so you can apply all Ldk methods available. wp$coe # Procrustes aligned coordinates #> x1 x2 x3 x4 x5 x6 #> AN1 -0.4907666 -0.0773009715 0.2219542 0.2627437 0.2631416 0.2458310 #> AN2 -0.4814136 -0.0043204711 0.2358591 0.2470304 0.2493796 0.2433619 #> AN3 -0.4624999 0.0085256951 0.2402046 0.2499734 0.2599811 0.2541803 #> AN4 -0.4529120 -0.0290010787 0.2450022 0.2644452 0.2662562 0.2580972 #> AN5 -0.4924779 -0.0212833505 0.2384236 0.2428850 0.2430784 0.2342010 #> AN6 -0.4648300 -0.0155847731 0.2292089 0.2471983 0.2543874 0.2527982 #> AN7 -0.4732081 -0.0574977850 0.2273573 0.2538051 0.2603828 0.2519172 #> AN8 -0.4698594 0.0504698979 0.2434539 0.2591684 0.2579988 0.2547464 #> AN9 -0.4649648 0.0035623360 0.2293834 0.2440605 0.2525448 0.2521638 #> AN10 -0.4504193 -0.0018707051 0.2480358 0.2576366 0.2590623 0.2538704 #> AN11 -0.4594860 -0.0067460377 0.2392940 0.2501128 0.2535707 0.2503424 #> TO12 -0.4549666 -0.0135654597 0.2181489 0.2384352 0.2483764 0.2467695 #> WY13 -0.4704734 0.0116630860 0.2330368 0.2543107 0.2622847 0.2600690 #> WY14 -0.4734689 0.0207999542 0.2337591 0.2504520 0.2525345 0.2461181 #> WY15 -0.4675774 -0.0292250770 0.2444459 0.2544484 0.2613803 0.2591811 #> WY16 -0.4614597 0.0161212662 0.2365561 0.2554997 0.2616627 0.2573814 #> UR17 -0.4679322 0.0137186315 0.2337384 0.2482512 0.2518451 0.2452852 #> UR18 -0.4959530 0.0510005057 0.2047701 0.2231605 0.2329740 0.2367396 #> UR19 -0.4634175 -0.0316943065 0.2226446 0.2456525 0.2585150 0.2571715 #> UR20 -0.4847293 -0.0173597990 0.2345076 0.2501136 0.2553717 0.2513819 #> CA21 -0.4842850 0.0063753386 0.2363630 0.2523859 0.2511070 0.2448517 #> CA22 -0.4686641 0.0433492114 0.2227406 0.2479682 0.2538936 0.2564965 #> CA23 -0.4624115 0.0521370117 0.2462273 0.2587035 0.2603057 0.2514573 #> CA24 -0.4496786 -0.0299209806 0.2410362 0.2679107 0.2707568 0.2625471 #> CA25 -0.4699837 0.0499912336 0.2468421 0.2602165 0.2600191 0.2493553 #> CA26 -0.4652044 -0.0216338175 0.2320537 0.2522195 0.2577222 0.2553325 #> CA27 -0.4539016 -0.0084621369 0.2347432 0.2567309 0.2678166 0.2672198 #> OR28 -0.4642004 -0.0478363995 0.2047891 0.2580593 0.2673629 0.2631468 #> MA29 -0.4629121 0.0321108444 0.2619494 0.2689998 0.2673808 0.2531957 #> MA30 -0.4744066 0.0030967297 0.2335851 0.2499520 0.2561755 0.2494846 #> MA31 -0.4837650 0.0069218722 0.2474991 0.2586511 0.2556787 0.2411284 #> PS32 -0.4966972 0.0391162185 0.2238874 0.2389734 0.2445282 0.2383284 #> PS33 -0.4861101 0.0458740448 0.2217242 0.2376278 0.2494514 0.2411975 #> PS34 -0.4926047 0.0150598747 0.2309942 0.2380733 0.2385704 0.2356709 #> PS35 -0.4707887 -0.0006005030 0.2405639 0.2530304 0.2561273 0.2532259 #> PS36 -0.4804750 0.0102748783 0.2281729 0.2477567 0.2516146 0.2473052 #> PS37 -0.4843792 0.0024029418 0.2177104 0.2418813 0.2524859 0.2451530 #> PS38 -0.4883758 0.0118492596 0.2295506 0.2450205 0.2523039 0.2467107 #> PS39 -0.4689716 0.0189766943 0.2274736 0.2403579 0.2492681 0.2490592 #> PS40 -0.4715872 0.0529053483 0.2305629 0.2444438 0.2523252 0.2487301 #> PS41 -0.4675117 0.0055336845 0.2178562 0.2412046 0.2558821 0.2563120 #> PS42 -0.4702167 -0.0323832015 0.2047675 0.2425465 0.2489391 0.2420843 #> PS43 -0.4640396 0.0755651863 0.2310033 0.2389107 0.2503819 0.2466330 #> AE44 -0.4752231 -0.0190036593 0.2392345 0.2483440 0.2546769 0.2535676 #> AE45 -0.4712468 0.0190843812 0.2210899 0.2369524 0.2457552 0.2464260 #> AE46 -0.4793075 0.0154345164 0.2355639 0.2479250 0.2481327 0.2417271 #> AE47 -0.4654301 0.0330019702 0.2193599 0.2444830 0.2499465 0.2496946 #> AE48 -0.4815365 -0.0064290149 0.2537134 0.2590958 0.2592869 0.2486677 #> AE49 -0.4632723 0.0162815933 0.2186887 0.2481676 0.2534765 0.2518944 #> AE50 -0.4817723 0.0276523610 0.2290102 0.2431281 0.2469943 0.2462860 #> AE51 -0.4717455 -0.0107373284 0.2350966 0.2508590 0.2535008 0.2475562 #> AE52 -0.4752186 0.0079643207 0.2161767 0.2389326 0.2506431 0.2488986 #> AE53 -0.4807181 -0.0193542092 0.2187462 0.2373243 0.2465864 0.2411295 #> AE54 -0.4726770 0.0042104072 0.2320799 0.2441318 0.2497205 0.2443859 #> AE55 -0.4646473 0.0320480284 0.2371872 0.2517296 0.2591495 0.2576346 #> AE56 -0.4658006 -0.0271433977 0.2317464 0.2510340 0.2581889 0.2566246 #> AE57 -0.4844660 -0.0221552886 0.2456692 0.2556408 0.2580763 0.2516870 #> AE58 -0.4730506 0.0582814685 0.2188507 0.2418793 0.2479542 0.2464591 #> AE59 -0.4828655 -0.0055133573 0.2354240 0.2617881 0.2592169 0.2434273 #> AE60 -0.4774249 0.0361789182 0.2263105 0.2476206 0.2512024 0.2451575 #> AE61 -0.4623119 -0.0375587499 0.2440043 0.2601320 0.2585395 0.2505482 #> AE62 -0.4902864 0.0139065201 0.2342103 0.2453327 0.2515635 0.2436809 #> AE63 -0.4779151 0.0059330973 0.2345515 0.2555558 0.2597442 0.2532415 #> AE64 -0.4868197 -0.0211344335 0.2364029 0.2454972 0.2499901 0.2497979 #> AE65 -0.4746840 0.0096365983 0.2263605 0.2404731 0.2468449 0.2468833 #> AE66 -0.4768653 0.0289818014 0.2154092 0.2364947 0.2510466 0.2478843 #> AE67 -0.4739933 -0.0127977235 0.2079788 0.2406013 0.2500045 0.2466718 #> AE68 -0.4695196 0.0127816215 0.2194103 0.2511412 0.2566561 0.2491946 #> AE69 -0.4870751 0.0120547996 0.2188035 0.2356834 0.2457794 0.2419043 #> AE70 -0.4739865 0.0073867906 0.2259563 0.2480186 0.2512018 0.2460852 #> AE71 -0.4876300 0.0068425512 0.2200598 0.2428513 0.2480821 0.2424443 #> AE72 -0.4796960 0.0081015641 0.2245357 0.2411730 0.2474304 0.2432591 #> AE73 -0.4844463 -0.0148392109 0.2478067 0.2592521 0.2566336 0.2446404 #> AE74 -0.4990544 0.0351093589 0.2067677 0.2418032 0.2463419 0.2380992 #> AE75 -0.4927988 0.0129269894 0.2264267 0.2395880 0.2468303 0.2461931 #> AE76 -0.4794825 0.0284282758 0.2124819 0.2288382 0.2378380 0.2369457 #> AE77 -0.4896619 0.0084220519 0.2270959 0.2420128 0.2492127 0.2442261 #> AE78 -0.4816176 0.0110479956 0.2354676 0.2510040 0.2487253 0.2391245 #> AE79 -0.4857004 0.0125998503 0.2206958 0.2543582 0.2570297 0.2508034 #> AE80 -0.4782865 0.0008280900 0.2179316 0.2396095 0.2500093 0.2469745 #> AE81 -0.4614159 0.0164243433 0.2175737 0.2373651 0.2517962 0.2540073 #> AE82 -0.4884021 -0.0106529196 0.2159937 0.2393296 0.2505881 0.2421417 #> AE83 -0.4705928 -0.0056291188 0.2332780 0.2532730 0.2575283 0.2451208 #> AE84 -0.4832577 0.0392237816 0.2217536 0.2451291 0.2578183 0.2496531 #> AE85 -0.4613904 0.0166551212 0.2382053 0.2526753 0.2534802 0.2513185 #> AE86 -0.4742992 0.0023745196 0.2348359 0.2477378 0.2523562 0.2464384 #> AE87 -0.4711525 0.0055153725 0.2358711 0.2574658 0.2635143 0.2571095 #> AE88 -0.4813500 0.0202470374 0.2403003 0.2525533 0.2551104 0.2482657 #> AE89 -0.4725693 0.0600504908 0.2260758 0.2477042 0.2506761 0.2478068 #> AE90 -0.4812507 -0.0129303990 0.2307134 0.2486744 0.2513002 0.2429985 #> AE91 -0.4786523 -0.0063253420 0.2179355 0.2412551 0.2465643 0.2444140 #> AE92 -0.4676820 0.0006938311 0.2213544 0.2480277 0.2560944 0.2529235 #> AE93 -0.4956653 0.0006840548 0.2156897 0.2387205 0.2509945 0.2478962 #> AE94 -0.4711722 -0.0241188538 0.2458578 0.2588251 0.2634248 0.2597967 #> AE95 -0.4682823 -0.0080591902 0.2282772 0.2477356 0.2517442 0.2493961 #> AE96 -0.4495492 0.0408870483 0.2371218 0.2474411 0.2576482 0.2554825 #> AE97 -0.4762984 -0.0156492648 0.2388590 0.2615816 0.2660422 0.2588822 #> AE98 -0.4818158 0.0129963689 0.2323245 0.2449118 0.2507871 0.2465823 #> AE99 -0.4614757 -0.0127074929 0.2380940 0.2533797 0.2576139 0.2549766 #> AE100 -0.4497946 0.0331081611 0.2442956 0.2624796 0.2649207 0.2608630 #> CX101 -0.4692319 0.0043634619 0.2378653 0.2518208 0.2526481 0.2438136 #> CX102 -0.4905300 0.0270883163 0.2294066 0.2431466 0.2477034 0.2460992 #> CX103 -0.4629903 -0.0081103619 0.2330432 0.2540206 0.2680640 0.2619114 #> CX104 -0.4757764 0.0111846575 0.2390570 0.2481937 0.2531685 0.2502457 #> CX105 -0.4707200 0.0024658276 0.2374990 0.2481015 0.2533622 0.2493150 #> CX106 -0.4721575 0.0364674010 0.2257939 0.2468190 0.2503209 0.2461980 #> CX107 -0.4586349 0.0375380173 0.2269382 0.2486108 0.2540931 0.2493498 #> CX108 -0.4555822 0.0433235841 0.2531397 0.2676689 0.2665428 0.2576097 #> CX109 -0.4673782 0.0307466957 0.2398543 0.2519916 0.2555273 0.2465431 #> CX110 -0.4674122 -0.0003222505 0.2453396 0.2530069 0.2577360 0.2522668 #> CX111 -0.4688050 0.0171390626 0.2322253 0.2482204 0.2509553 0.2498708 #> CX112 -0.4611885 0.0166490429 0.2453478 0.2565835 0.2619681 0.2541912 #> CX113 -0.4786753 -0.0009889972 0.2483928 0.2516808 0.2503696 0.2475798 #> CX114 -0.4534517 0.0315357559 0.2316239 0.2553673 0.2601520 0.2521237 #> CX115 -0.4519892 0.0053453871 0.2161357 0.2455742 0.2572942 0.2544695 #> CX116 -0.4664726 0.0505761629 0.2327811 0.2532666 0.2556895 0.2492648 #> CX117 -0.4699322 0.0067800321 0.2546779 0.2582515 0.2585119 0.2545017 #> CX118 -0.4743596 0.0174407482 0.2365392 0.2531061 0.2591999 0.2548841 #> CX119 -0.4852456 0.0178494773 0.2342953 0.2532951 0.2602392 0.2546899 #> CX120 -0.4584556 0.0247948239 0.2311389 0.2564422 0.2619657 0.2556872 #> CX121 -0.4786715 -0.0098771771 0.2132974 0.2425027 0.2597399 0.2573738 #> CX122 -0.4807543 0.0198286069 0.2200394 0.2448613 0.2524591 0.2488141 #> CX123 -0.4702682 0.0047998520 0.2179940 0.2374435 0.2468581 0.2448316 #> CX124 -0.4749652 0.0257023372 0.2346474 0.2481868 0.2486190 0.2419842 #> CX125 -0.4699447 0.0015294908 0.2237478 0.2492571 0.2553474 0.2514616 #> DE126 -0.4610240 0.0098009883 0.2072649 0.2380380 0.2459232 0.2479743 #> DE127 -0.4591336 -0.0137804922 0.2347116 0.2533782 0.2605132 0.2518624 #> x7 x8 x9 x10 x11 x12 #> AN1 0.2299132 0.2029523 0.12754162 0.042182258 -0.06705386 -0.4080934 #> AN2 0.2316637 0.1951394 0.14525661 0.046692739 -0.05400733 -0.4022972 #> AN3 0.2370495 0.1959378 0.12519983 0.014979026 -0.07538362 -0.4104857 #> AN4 0.2423502 0.1836886 0.11677357 0.017108857 -0.09535549 -0.3867750 #> AN5 0.2156942 0.1902824 0.12379899 0.037980571 -0.05810728 -0.4262095 #> AN6 0.2406748 0.2071285 0.13563608 0.022921784 -0.08840736 -0.4054317 #> AN7 0.2386089 0.1839125 0.14393189 0.015529416 -0.06601273 -0.3936616 #> AN8 0.2372610 0.1814280 0.10209739 0.017559790 -0.08976669 -0.4074332 #> AN9 0.2404959 0.1990063 0.13533299 0.022888995 -0.05166237 -0.4022091 #> AN10 0.2380631 0.1927745 0.12773111 0.023555421 -0.05535730 -0.4076816 #> AN11 0.2337952 0.1861500 0.12490842 0.034650317 -0.06861235 -0.4066079 #> TO12 0.2319654 0.1948143 0.11634810 0.010289772 -0.09517636 -0.4024563 #> WY13 0.2429500 0.2027251 0.11103405 0.015210900 -0.10773718 -0.4160152 #> WY14 0.2264757 0.1880802 0.12874425 0.047463769 -0.05674451 -0.4140549 #> WY15 0.2411312 0.1939658 0.12726697 0.028109702 -0.10622496 -0.4001009 #> WY16 0.2348279 0.1856137 0.12656646 0.022195509 -0.09799700 -0.4148173 #> UR17 0.2256359 0.1819762 0.11874875 0.030205566 -0.14620317 -0.3989015 #> UR18 0.2191726 0.1787242 0.11725644 0.035971318 -0.13829494 -0.4153716 #> UR19 0.2370094 0.1772675 0.10888634 0.033122053 -0.15096989 -0.3941168 #> UR20 0.2358529 0.1948558 0.12381844 0.039454341 -0.14588000 -0.4219834 #> CA21 0.2283203 0.1786453 0.11024649 0.011450452 -0.08813603 -0.4023493 #> CA22 0.2353073 0.1700845 0.10343629 0.023933224 -0.08859335 -0.4124978 #> CA23 0.2316811 0.1705135 0.10883994 0.016240897 -0.09614337 -0.4116485 #> CA24 0.2411870 0.1861375 0.10941810 0.025545675 -0.07374133 -0.3933004 #> CA25 0.2246680 0.1693253 0.11010653 0.015072380 -0.10079955 -0.4053513 #> CA26 0.2406196 0.1949255 0.13302253 0.034746032 -0.06341431 -0.4087796 #> CA27 0.2523273 0.2018624 0.10170951 0.028067192 -0.05578732 -0.3953147 #> OR28 0.2382177 0.1847685 0.12537017 0.037917311 -0.03948366 -0.4183748 #> MA29 0.2188114 0.1680060 0.12041047 0.028168458 -0.06859047 -0.3959214 #> MA30 0.2320145 0.1826054 0.10832796 0.038212321 -0.05391403 -0.4119382 #> MA31 0.2160846 0.1739956 0.11601883 0.037618441 -0.06334261 -0.4052627 #> PS32 0.2219508 0.1756635 0.10698420 0.031101903 -0.06916025 -0.4093229 #> PS33 0.2230743 0.1735176 0.11025278 -0.001058697 -0.08194420 -0.4054739 #> PS34 0.2128262 0.1807335 0.11093134 0.027976227 -0.07595346 -0.4223508 #> PS35 0.2397646 0.1978324 0.10179981 0.010201778 -0.08341705 -0.4070977 #> PS36 0.2276580 0.1737842 0.11977437 0.027760114 -0.06736491 -0.4160846 #> PS37 0.2241077 0.1838799 0.10808681 0.037746145 -0.05996708 -0.4100509 #> PS38 0.2292366 0.1882440 0.12219662 0.016952089 -0.09256166 -0.4052013 #> PS39 0.2392189 0.1905865 0.11587287 0.036269066 -0.09184273 -0.4124714 #> PS40 0.2256842 0.1818852 0.10862069 0.034456039 -0.07103136 -0.4122096 #> PS41 0.2427152 0.2024380 0.11492685 0.045251862 -0.07616414 -0.3994672 #> PS42 0.2300983 0.1856700 0.11236211 0.045307471 -0.04888561 -0.4157182 #> PS43 0.2230354 0.1755287 0.09157707 0.010204003 -0.08853094 -0.4031586 #> AE44 0.2379333 0.1778025 0.10740209 0.029505988 -0.06631350 -0.3999825 #> AE45 0.2296212 0.1927084 0.12015866 0.030523858 -0.08138917 -0.4164703 #> AE46 0.2260410 0.1882752 0.11506319 0.039630127 -0.07170307 -0.4128322 #> AE47 0.2336590 0.2022006 0.12438902 0.019005338 -0.10647131 -0.4066207 #> AE48 0.2213836 0.1733830 0.10626360 0.014883547 -0.11623004 -0.3996691 #> AE49 0.2330862 0.2023845 0.12885279 0.036371756 -0.06761234 -0.4001142 #> AE50 0.2316834 0.1912755 0.10355014 0.009909262 -0.08625418 -0.4127075 #> AE51 0.2350902 0.1755556 0.11998012 0.031372778 -0.04560103 -0.3918887 #> AE52 0.2266644 0.1922767 0.12813684 0.042501215 -0.06523957 -0.4062565 #> AE53 0.2271519 0.1847728 0.12010385 0.031181320 -0.07172065 -0.4149213 #> AE54 0.2219091 0.1785521 0.10673129 0.026300268 -0.08067577 -0.4179231 #> AE55 0.2412285 0.2029947 0.10433063 0.014346500 -0.11417625 -0.3982188 #> AE56 0.2387554 0.1855339 0.11091372 0.032685606 -0.08676041 -0.4106891 #> AE57 0.2230746 0.1710064 0.10686284 0.032430972 -0.06965827 -0.3926581 #> AE58 0.2335399 0.1984260 0.11968260 0.039453573 -0.08111629 -0.4088259 #> AE59 0.2190216 0.1658974 0.10659264 0.019676443 -0.06565151 -0.4075436 #> AE60 0.2207965 0.1892755 0.10485114 0.021230955 -0.10622079 -0.3950189 #> AE61 0.2319673 0.1791207 0.11323873 0.033474919 -0.09117433 -0.4028892 #> AE62 0.2301815 0.1893919 0.12121461 0.026022391 -0.07707926 -0.4106974 #> AE63 0.2353506 0.1848351 0.08901796 0.010846011 -0.07838534 -0.3986001 #> AE64 0.2331246 0.1800663 0.12307053 0.036445810 -0.06265560 -0.3965477 #> AE65 0.2339304 0.1980809 0.11928878 0.036953760 -0.11127081 -0.4115693 #> AE66 0.2265853 0.1781210 0.10019600 0.015003709 -0.10125446 -0.4116335 #> AE67 0.2371114 0.1925200 0.12123028 0.039855216 -0.07915587 -0.4158821 #> AE68 0.2253185 0.1745543 0.11024909 0.026342860 -0.09388029 -0.4084570 #> AE69 0.2304674 0.2000356 0.11907429 0.030358001 -0.07848555 -0.4151259 #> AE70 0.2256643 0.1967240 0.11330103 0.034313115 -0.09143355 -0.4073191 #> AE71 0.2312316 0.1856359 0.11612478 0.037422911 -0.06262702 -0.3944163 #> AE72 0.2230091 0.1702759 0.10187699 0.031247530 -0.08736808 -0.4140867 #> AE73 0.2242534 0.1720954 0.10375972 0.046785537 -0.06541305 -0.3923586 #> AE74 0.2097443 0.1688960 0.10269514 0.023631592 -0.08335478 -0.4180446 #> AE75 0.2312035 0.1721142 0.10056175 0.039650964 -0.06626761 -0.4092941 #> AE76 0.2247807 0.1858490 0.12302800 0.023489034 -0.08625115 -0.4218836 #> AE77 0.2265496 0.1878062 0.12198447 0.017234413 -0.08718955 -0.4026411 #> AE78 0.2194152 0.1797335 0.12830989 0.030379126 -0.07166252 -0.4012513 #> AE79 0.2274608 0.1813567 0.12039160 0.043563110 -0.08266743 -0.3908824 #> AE80 0.2367584 0.1957126 0.11536534 0.034683133 -0.07517053 -0.4148166 #> AE81 0.2343733 0.1963869 0.12072100 0.050079773 -0.05214437 -0.4026463 #> AE82 0.2133248 0.1894671 0.12630310 0.037863142 -0.08518389 -0.3987510 #> AE83 0.2225514 0.1849202 0.13031599 0.030076964 -0.07829979 -0.4112970 #> AE84 0.2302822 0.1895577 0.11475210 0.034240590 -0.08772584 -0.3918702 #> AE85 0.2382525 0.1965061 0.10015703 0.017901979 -0.08122826 -0.4125355 #> AE86 0.2294434 0.1865355 0.12273581 0.050832660 -0.05057700 -0.3965911 #> AE87 0.2324682 0.1835045 0.10520558 0.041487007 -0.06038956 -0.3992214 #> AE88 0.2332422 0.1831163 0.10593246 0.041685157 -0.08181925 -0.4081250 #> AE89 0.2212558 0.1820324 0.11815414 0.024810107 -0.09216662 -0.4064017 #> AE90 0.2271603 0.1874579 0.11703971 0.031601069 -0.07166638 -0.4083849 #> AE91 0.2261588 0.1882372 0.12312647 0.031453724 -0.09623608 -0.4075506 #> AE92 0.2353479 0.1999623 0.11753540 0.033427416 -0.08120016 -0.4114561 #> AE93 0.2231146 0.1718510 0.12078223 0.024568179 -0.09254764 -0.3970457 #> AE94 0.2382167 0.1833966 0.11174608 0.037044261 -0.08277851 -0.3934437 #> AE95 0.2377841 0.1993601 0.13289958 0.041383836 -0.08556380 -0.4059580 #> AE96 0.2381113 0.1993834 0.11319767 0.041158904 -0.08367440 -0.3985118 #> AE97 0.2380356 0.1839470 0.11244138 0.035297701 -0.08215951 -0.3915827 #> AE98 0.2247551 0.1909649 0.11376227 0.030210009 -0.07152469 -0.4098340 #> AE99 0.2327722 0.1991402 0.12883015 0.035614550 -0.08682957 -0.3970737 #> AE100 0.2377580 0.1743137 0.09811410 0.010075437 -0.10567541 -0.3991863 #> CX101 0.2290665 0.1922139 0.11706821 0.047500398 -0.08249422 -0.4052462 #> CX102 0.2293068 0.1760098 0.11789188 0.044774087 -0.06106010 -0.4163814 #> CX103 0.2394979 0.1920586 0.11461307 0.025784000 -0.07999779 -0.3953586 #> CX104 0.2314558 0.1810221 0.12188125 0.041325903 -0.06915492 -0.3990015 #> CX105 0.2371495 0.1899093 0.11308927 0.034297130 -0.04974066 -0.4075275 #> CX106 0.2332277 0.1903543 0.13296141 0.043710407 -0.06453407 -0.4054979 #> CX107 0.2422508 0.1841989 0.13510787 0.046406682 -0.07021143 -0.4072995 #> CX108 0.2320185 0.1680546 0.11720697 0.032792588 -0.05510435 -0.3922454 #> CX109 0.2343839 0.2007389 0.12779590 0.032996512 -0.04694209 -0.4017998 #> CX110 0.2378867 0.1832616 0.12064990 0.046324218 -0.06981407 -0.4050046 #> CX111 0.2273768 0.1904418 0.12950512 0.050550179 -0.04985695 -0.4005184 #> CX112 0.2367948 0.1967518 0.10011721 0.016338760 -0.08055712 -0.3962532 #> CX113 0.2251491 0.1857302 0.11471705 0.052234788 -0.06173698 -0.4012369 #> CX114 0.2314432 0.1909076 0.12299680 0.044322702 -0.07351377 -0.4036653 #> CX115 0.2405785 0.2156480 0.13529727 0.039015077 -0.09269088 -0.4036963 #> CX116 0.2285597 0.1913583 0.11685112 0.030245483 -0.06611537 -0.4063325 #> CX117 0.2364835 0.2008391 0.12727829 0.029801740 -0.05116089 -0.3890976 #> CX118 0.2389982 0.1886799 0.11747954 0.042872595 -0.06481456 -0.4009626 #> CX119 0.2295826 0.1891349 0.11231738 0.031713950 -0.08408367 -0.4007293 #> CX120 0.2347531 0.1915745 0.10999010 0.039159281 -0.07421968 -0.4019501 #> CX121 0.2421442 0.2013319 0.14726099 0.041513595 -0.07229422 -0.3877350 #> CX122 0.2266313 0.1953813 0.12523150 0.036805365 -0.07702428 -0.4115588 #> CX123 0.2370076 0.2174658 0.13148120 0.035194985 -0.07744389 -0.4106482 #> CX124 0.2294273 0.1976867 0.12662777 0.037662621 -0.08984945 -0.4065792 #> CX125 0.2367249 0.1948181 0.12741401 0.043421462 -0.07849225 -0.3991977 #> DE126 0.2335108 0.2054635 0.14075607 0.055477722 -0.03540458 -0.4124649 #> DE127 0.2300548 0.1908648 0.12176640 0.045946556 -0.07661308 -0.4020559 #> x13 x14 x15 x16 x17 x18 #> AN1 -0.3123874 -0.1758920 0.071132804 -0.053722681 0.05720471 -0.1393805 #> AN2 -0.3867009 -0.1804640 0.049200176 -0.051613533 0.06225198 -0.1450187 #> AN3 -0.3921854 -0.1725842 0.057531080 -0.046893028 0.07666483 -0.1601955 #> AN4 -0.4048396 -0.1528388 0.063248369 -0.054017479 0.07029203 -0.1515230 #> AN5 -0.3959004 -0.1359723 0.078956283 -0.030094227 0.08796636 -0.1332218 #> AN6 -0.3940038 -0.1638546 0.066460419 -0.059913063 0.08088272 -0.1452717 #> AN7 -0.3793327 -0.1586080 0.068320395 -0.043540824 0.08926659 -0.1611703 #> AN8 -0.3920543 -0.1608568 0.048369015 -0.057842665 0.06620852 -0.1409480 #> AN9 -0.3964814 -0.1875675 0.058923841 -0.067584324 0.07882520 -0.1467186 #> AN10 -0.3937555 -0.1815667 0.050151922 -0.063165682 0.06639335 -0.1634576 #> AN11 -0.3998765 -0.1829062 0.079278212 -0.058328570 0.08913645 -0.1586749 #> TO12 -0.3792285 -0.1573091 0.160588922 -0.068449994 0.09810716 -0.1926913 #> WY13 -0.3560161 -0.1633065 0.043039317 -0.024470515 0.04782334 -0.1461281 #> WY14 -0.4119397 -0.1509246 0.025931927 -0.022880971 0.05624500 -0.1465910 #> WY15 -0.3873511 -0.1769486 0.044837998 -0.033642058 0.07252781 -0.1262252 #> WY16 -0.4053355 -0.1447852 0.041124932 -0.041619850 0.06150684 -0.1330420 #> UR17 -0.3795187 -0.1499897 0.112096041 -0.075700284 0.09462930 -0.1378847 #> UR18 -0.3667555 -0.1229772 0.135646552 -0.069063838 0.08232154 -0.1093214 #> UR19 -0.3734347 -0.1520523 0.141092065 -0.079853773 0.09743056 -0.1332523 #> UR20 -0.3307397 -0.1264103 0.083589542 -0.080261106 0.05968488 -0.1212670 #> CA21 -0.3915900 -0.1669786 0.092579729 -0.022158130 0.07397812 -0.1308064 #> CA22 -0.3938010 -0.1952350 0.063030200 -0.026379879 0.08437946 -0.1194480 #> CA23 -0.3978962 -0.1730481 0.047273593 -0.028019393 0.04890647 -0.1231193 #> CA24 -0.3836838 -0.2047323 0.044936652 -0.037354246 0.05305631 -0.1301203 #> CA25 -0.3867403 -0.1712789 0.067968322 -0.024498614 0.04416991 -0.1390823 #> CA26 -0.3937400 -0.1660372 0.065363612 -0.047291844 0.05142893 -0.1513329 #> CA27 -0.3681559 -0.1830495 0.018062775 -0.034573946 0.05424041 -0.1835350 #> OR28 -0.3922121 -0.1705467 0.068579295 -0.039999358 0.03187299 -0.1074308 #> MA29 -0.3876047 -0.1755705 0.055627902 -0.048117812 0.02617888 -0.1621226 #> MA30 -0.3983553 -0.1747881 0.060321100 -0.015576724 0.04797223 -0.1327685 #> MA31 -0.3858714 -0.1908211 0.070178695 -0.027140640 0.06411273 -0.1316847 #> PS32 -0.4009013 -0.1701479 0.076133748 -0.025721102 0.07937010 -0.1040872 #> PS33 -0.3999745 -0.1598414 0.085627861 -0.012988219 0.07775493 -0.1187115 #> PS34 -0.3997804 -0.1595394 0.079226181 0.001378733 0.08299836 -0.1042104 #> PS35 -0.3917380 -0.1723098 0.063434377 -0.027320762 0.07315293 -0.1358608 #> PS36 -0.3957244 -0.1826283 0.070455306 -0.017542694 0.07782886 -0.1225652 #> PS37 -0.4031093 -0.1676375 0.073776707 -0.012313027 0.09290963 -0.1426835 #> PS38 -0.3943966 -0.1539762 0.075629598 -0.024301247 0.08226797 -0.1411489 #> PS39 -0.3908186 -0.1753054 0.068416040 -0.026234475 0.07275579 -0.1426104 #> PS40 -0.3970239 -0.1774955 0.077246950 -0.032428935 0.04948173 -0.1445656 #> PS41 -0.3851949 -0.1903692 0.056899382 -0.025993187 0.05120127 -0.1455207 #> PS42 -0.3952832 -0.1857938 0.096292088 -0.008344338 0.07966704 -0.1311093 #> PS43 -0.3869340 -0.2037884 0.094782316 -0.020211736 0.07961082 -0.1505692 #> AE44 -0.3935808 -0.1687313 0.080418789 -0.019593863 0.05651851 -0.1429755 #> AE45 -0.4043663 -0.1807524 0.080066700 -0.027367399 0.08757207 -0.1283663 #> AE46 -0.3877556 -0.1826371 0.068465989 -0.028746613 0.07764665 -0.1409232 #> AE47 -0.3953208 -0.1927835 0.053055706 -0.011260156 0.07280239 -0.1237115 #> AE48 -0.3856849 -0.1721881 0.080969398 -0.002019639 0.07130260 -0.1251923 #> AE49 -0.3798684 -0.2306110 0.057022040 -0.031685345 0.06830318 -0.1413658 #> AE50 -0.3898933 -0.1678589 0.081555287 -0.018531416 0.07924866 -0.1332756 #> AE51 -0.3814383 -0.2113389 0.080188309 -0.031438772 0.05430921 -0.1393203 #> AE52 -0.4018099 -0.1968956 0.074185015 -0.016768536 0.05762562 -0.1218164 #> AE53 -0.3956962 -0.1790955 0.093343932 -0.008269994 0.09425627 -0.1248207 #> AE54 -0.3988053 -0.1755086 0.100664053 -0.007742611 0.07639270 -0.1317456 #> AE55 -0.3830524 -0.1814467 0.065155781 -0.040471766 0.07364275 -0.1574346 #> AE56 -0.3906408 -0.1710974 0.074709004 -0.015546169 0.07476288 -0.1472765 #> AE57 -0.3987688 -0.1707297 0.079379215 -0.010544594 0.05237139 -0.1272180 #> AE58 -0.3895450 -0.1739227 0.048346680 -0.040154525 0.06825117 -0.1545096 #> AE59 -0.4000550 -0.1802010 0.085429434 -0.011765784 0.08507985 -0.1279580 #> AE60 -0.3844530 -0.1869755 0.067673441 -0.014802941 0.08506475 -0.1304661 #> AE61 -0.3872808 -0.1838364 0.072708144 -0.022088293 0.07101851 -0.1276127 #> AE62 -0.3980835 -0.1558501 0.072920769 -0.030383001 0.07145942 -0.1375049 #> AE63 -0.3819749 -0.1892579 0.073253276 -0.009680803 0.07092440 -0.1374394 #> AE64 -0.3830723 -0.1818841 0.083419843 -0.020792424 0.05516603 -0.1400750 #> AE65 -0.3950954 -0.1713184 0.056778156 -0.010587947 0.09200406 -0.1327086 #> AE66 -0.3920177 -0.1764438 0.105836190 -0.012763450 0.09219496 -0.1267756 #> AE67 -0.4005061 -0.1817317 0.072579788 -0.005837986 0.08265020 -0.1212986 #> AE68 -0.3979286 -0.1964838 0.096764243 -0.002088618 0.07331423 -0.1273690 #> AE69 -0.3988875 -0.1559526 0.077236543 -0.023061279 0.07910975 -0.1319191 #> AE70 -0.3925072 -0.1727990 0.071299724 -0.019968087 0.07592270 -0.1378603 #> AE71 -0.3861925 -0.2024340 0.082151905 -0.015697031 0.07097288 -0.1348231 #> AE72 -0.3940800 -0.1874311 0.106283254 -0.007228361 0.09394314 -0.1212455 #> AE73 -0.3897005 -0.1879595 0.088836487 -0.026457001 0.04951382 -0.1324029 #> AE74 -0.3997937 -0.1524768 0.093802325 0.008109828 0.08592517 -0.1082014 #> AE75 -0.3970993 -0.1817829 0.093102758 -0.006807875 0.06061804 -0.1151656 #> AE76 -0.3955195 -0.1880763 0.103382907 -0.001083329 0.09360505 -0.1263704 #> AE77 -0.3889041 -0.1764796 0.079500830 -0.013542644 0.07981560 -0.1254420 #> AE78 -0.4099100 -0.1776684 0.069460737 -0.014974501 0.06651128 -0.1220949 #> AE79 -0.3773595 -0.2131280 0.076032489 -0.025486291 0.06233346 -0.1314012 #> AE80 -0.3849712 -0.2015281 0.081245884 -0.015415381 0.07882854 -0.1277587 #> AE81 -0.3812278 -0.2125832 0.060469074 -0.023877574 0.04899794 -0.1542995 #> AE82 -0.3898835 -0.1813821 0.100777839 -0.020363389 0.08602870 -0.1271990 #> AE83 -0.3851831 -0.1927737 0.088931898 -0.020963427 0.04294136 -0.1241991 #> AE84 -0.3794734 -0.1952869 0.062647361 -0.030900169 0.06101529 -0.1375591 #> AE85 -0.3984306 -0.1647072 0.048201877 -0.028486708 0.06931371 -0.1358889 #> AE86 -0.3809376 -0.1916173 0.056772111 -0.028475690 0.04954339 -0.1571078 #> AE87 -0.3873660 -0.1718767 0.049172441 -0.025198075 0.04745461 -0.1635640 #> AE88 -0.4036821 -0.1483002 0.043892652 -0.022359235 0.05684484 -0.1355545 #> AE89 -0.3990820 -0.1741903 0.078732121 -0.032661266 0.06575081 -0.1459775 #> AE90 -0.3866222 -0.1734202 0.074626665 -0.009459741 0.06415615 -0.1319939 #> AE91 -0.3897621 -0.1817775 0.090853341 -0.016262267 0.08433507 -0.1177673 #> AE92 -0.3899454 -0.1846729 0.060100544 -0.018845258 0.07646573 -0.1481314 #> AE93 -0.3837723 -0.1777953 0.105572746 -0.007698944 0.09114540 -0.1364939 #> AE94 -0.3859287 -0.1779382 0.049182813 -0.028392318 0.06120780 -0.1449260 #> AE95 -0.3852472 -0.1989100 0.067213272 -0.018272744 0.06964813 -0.1551490 #> AE96 -0.3886513 -0.1801433 0.048923673 -0.037275416 0.03195851 -0.1735086 #> AE97 -0.3717321 -0.1604576 0.066787089 -0.040595352 0.04740382 -0.1708025 #> AE98 -0.3945421 -0.1857716 0.065278055 -0.017262292 0.08878564 -0.1406077 #> AE99 -0.3820466 -0.2084944 0.055519925 -0.037125707 0.06705659 -0.1372445 #> AE100 -0.3903980 -0.1879970 0.058003315 -0.034426867 0.06144086 -0.1378944 #> CX101 -0.4020885 -0.1791160 0.048786174 -0.024150254 0.06711276 -0.1299322 #> CX102 -0.3976002 -0.1598676 0.044080347 -0.012590737 0.07109391 -0.1385710 #> CX103 -0.3778145 -0.1965009 0.043332770 -0.021978126 0.06459107 -0.1541661 #> CX104 -0.3920948 -0.1905712 0.044782493 -0.023836658 0.07315470 -0.1450364 #> CX105 -0.3983841 -0.1772447 0.042035888 -0.017445516 0.05089486 -0.1370570 #> CX106 -0.3853825 -0.1858871 0.029830212 -0.022877381 0.05320887 -0.1525558 #> CX107 -0.3943242 -0.2024597 0.029972543 -0.022749183 0.05178003 -0.1505679 #> CX108 -0.3847865 -0.2059504 0.017680898 -0.061007843 0.03987377 -0.1412352 #> CX109 -0.3909616 -0.1969576 0.007347111 -0.028313790 0.05008241 -0.1456546 #> CX110 -0.3959867 -0.1872205 0.024263790 -0.023041900 0.06640065 -0.1383339 #> CX111 -0.3905637 -0.1997595 0.033330776 -0.026702817 0.05550112 -0.1489101 #> CX112 -0.3859520 -0.1967629 0.042475088 -0.021379935 0.06012648 -0.1452501 #> CX113 -0.3957362 -0.1824494 0.054807087 -0.020058985 0.05965166 -0.1494302 #> CX114 -0.3879005 -0.1893491 0.028159479 -0.030888990 0.05144192 -0.1613051 #> CX115 -0.3951331 -0.1753281 0.038920274 -0.031822228 0.06154232 -0.1591605 #> CX116 -0.3803402 -0.1578348 0.039463402 -0.028570233 0.03924349 -0.1816337 #> CX117 -0.3752952 -0.1812367 0.014102142 -0.044530391 0.03439492 -0.1643696 #> CX118 -0.3784407 -0.1842759 0.020975280 -0.024425083 0.03881369 -0.1417108 #> CX119 -0.3877947 -0.1642730 0.063045598 -0.026611925 0.04439785 -0.1418231 #> CX120 -0.3884471 -0.1835364 0.046813391 -0.029801285 0.04352303 -0.1594322 #> CX121 -0.3858059 -0.1766316 0.029448989 -0.016405347 0.05021469 -0.1574074 #> CX122 -0.3948824 -0.1545773 0.058090941 -0.023721208 0.07347028 -0.1590947 #> CX123 -0.3968212 -0.1614923 0.057831692 -0.026330484 0.07153597 -0.1594401 #> CX124 -0.3968831 -0.1750125 0.063457007 -0.012313821 0.05506986 -0.1534678 #> CX125 -0.3910056 -0.1815608 0.038032701 -0.007173229 0.05915443 -0.1535347 #> DE126 -0.4010722 -0.1869205 0.028587401 -0.042186617 0.07257509 -0.1462993 #> DE127 -0.3907218 -0.2047855 0.046701459 -0.043417728 0.10136732 -0.1466586 #> y1 y2 y3 y4 y5 y6 #> AN1 0.012949789 0.08278930 0.08567442 0.04597933 0.02598256 3.150553e-04 #> AN2 0.022620158 0.07814870 0.05998946 0.04206154 0.02339979 6.898275e-03 #> AN3 0.013438475 0.06897223 0.05579946 0.04374581 0.02439000 5.250128e-03 #> AN4 0.014143861 0.07489168 0.07164144 0.04601179 0.02224188 4.645497e-03 #> AN5 0.011166720 0.07229243 0.05230952 0.04250442 0.01956350 3.326619e-03 #> AN6 0.012440946 0.06723327 0.05661890 0.04085779 0.02245431 6.525920e-03 #> AN7 0.023595913 0.07056581 0.07480905 0.05084276 0.02654051 2.098330e-03 #> AN8 0.010319015 0.07836381 0.05633338 0.03994427 0.02322133 1.364182e-02 #> AN9 0.021185977 0.07585612 0.06020996 0.04194706 0.02692072 8.397649e-03 #> AN10 0.013775382 0.07005713 0.05209910 0.03621218 0.01966673 5.732559e-03 #> AN11 0.013524963 0.07047621 0.05383143 0.03813986 0.02386315 6.524021e-03 #> TO12 0.011020896 0.05489808 0.05851446 0.04843418 0.02948179 1.135298e-02 #> WY13 0.012690374 0.08974548 0.07154950 0.05142613 0.03115442 7.945565e-03 #> WY14 0.006838952 0.07425376 0.05855540 0.03951210 0.01684673 4.686961e-03 #> WY15 0.012327190 0.07389979 0.05676065 0.04216671 0.02130888 6.762512e-03 #> WY16 0.012734077 0.07486281 0.06343993 0.04269533 0.02284658 8.148998e-03 #> UR17 -0.002272445 0.08504411 0.06568723 0.04988277 0.02803984 2.399601e-03 #> UR18 0.010595208 0.08716386 0.07508599 0.05911723 0.04078312 1.775779e-02 #> UR19 0.005508873 0.06909879 0.06119788 0.04581264 0.02498341 8.528148e-03 #> UR20 0.012396411 0.07799239 0.07198516 0.05098737 0.02522046 5.626080e-03 #> CA21 0.002635902 0.09440017 0.07134001 0.04688346 0.02345164 6.454919e-03 #> CA22 0.015744194 0.08724373 0.07052453 0.04828188 0.03276292 1.179454e-02 #> CA23 0.013027883 0.08808348 0.05921609 0.04609833 0.02443344 6.819944e-03 #> CA24 0.018277036 0.08648570 0.06951016 0.04686661 0.02521702 5.385714e-03 #> CA25 0.008599950 0.08815717 0.06935643 0.05183313 0.03086332 7.787913e-03 #> CA26 0.020834507 0.05992072 0.05711972 0.03839133 0.02688537 1.015034e-02 #> CA27 0.016367946 0.08527756 0.07076670 0.05317126 0.02914834 5.178037e-03 #> OR28 0.016827832 0.07461198 0.07442280 0.04643065 0.02768371 -1.428860e-03 #> MA29 0.010507548 0.08627604 0.05969102 0.04561603 0.02654038 8.884358e-03 #> MA30 0.025995072 0.08319459 0.06945754 0.05089690 0.02871595 6.842935e-03 #> MA31 0.011798644 0.08595290 0.07149388 0.04904952 0.01922665 -6.100331e-05 #> PS32 0.020858385 0.08883745 0.07127037 0.05320765 0.02642967 1.005285e-02 #> PS33 0.019564176 0.09107797 0.08038467 0.06757304 0.03450430 3.602802e-03 #> PS34 0.023210109 0.08901869 0.06173608 0.05023270 0.03095637 1.226244e-02 #> PS35 0.014353551 0.07699700 0.06095585 0.04185292 0.02578438 9.105854e-03 #> PS36 0.016665841 0.08692672 0.07172546 0.04794591 0.02378877 3.989454e-03 #> PS37 0.017832570 0.09050827 0.06565900 0.04890781 0.02110664 3.045869e-03 #> PS38 0.020272149 0.07495732 0.06588390 0.04780263 0.02331908 8.794902e-03 #> PS39 0.024672051 0.08031432 0.06721244 0.05284589 0.03114989 1.041525e-02 #> PS40 0.022707637 0.08147540 0.06533484 0.05252109 0.03007380 1.088509e-02 #> PS41 0.031617885 0.08831678 0.07838941 0.05979106 0.03143316 1.214333e-02 #> PS42 0.032775200 0.08160316 0.07927849 0.04794666 0.02364906 4.957452e-03 #> PS43 0.009549895 0.09705840 0.06595407 0.05464080 0.02973277 7.712228e-03 #> AE44 0.024194386 0.08043082 0.06281371 0.05271229 0.03342474 1.450789e-02 #> AE45 0.020043767 0.07464976 0.06346404 0.05108001 0.03319453 1.238207e-02 #> AE46 0.028843141 0.08336736 0.06916145 0.04413785 0.02509013 7.798185e-03 #> AE47 0.019762588 0.08711498 0.07134883 0.04412614 0.03008310 8.471292e-03 #> AE48 0.004400251 0.07889303 0.05925122 0.04868763 0.02847921 1.129694e-02 #> AE49 0.028804164 0.07968806 0.07268678 0.04628811 0.02623977 5.219770e-03 #> AE50 0.017152508 0.09150904 0.06579800 0.04675409 0.02993258 5.432006e-03 #> AE51 0.024244112 0.10035814 0.07848335 0.05257736 0.02630567 8.506299e-03 #> AE52 0.016687543 0.08215637 0.07006422 0.05467560 0.02854618 8.874160e-03 #> AE53 0.020866743 0.08293980 0.07177936 0.04937694 0.02587003 1.214336e-03 #> AE54 0.016303084 0.08395002 0.06313701 0.04778874 0.03048500 9.340067e-03 #> AE55 0.009794674 0.06923412 0.05935067 0.04571206 0.02509890 7.988179e-03 #> AE56 0.022976188 0.06985700 0.07120533 0.05037744 0.02676315 6.480065e-03 #> AE57 0.014463513 0.08643381 0.06277860 0.04806000 0.02984945 7.880581e-03 #> AE58 0.024562376 0.08351377 0.07057086 0.04923052 0.02851743 1.091822e-02 #> AE59 0.018360929 0.07068281 0.07225106 0.04599054 0.02680356 4.512518e-03 #> AE60 0.020595403 0.09656929 0.08363540 0.06054622 0.02756263 5.413022e-03 #> AE61 0.018530058 0.07997438 0.06974188 0.04297306 0.02953858 9.299743e-03 #> AE62 0.007576305 0.06729175 0.06139850 0.04746917 0.02336475 2.961155e-03 #> AE63 0.015957414 0.08932474 0.07748263 0.05121790 0.02760974 9.750227e-03 #> AE64 0.033051290 0.07655371 0.06347002 0.05159245 0.03439265 1.277309e-02 #> AE65 0.027086223 0.07637610 0.06279530 0.04671867 0.02849960 1.438764e-02 #> AE66 0.018674566 0.09197399 0.07371724 0.05663273 0.02899414 6.109633e-03 #> AE67 0.028409424 0.07503364 0.07199975 0.05225904 0.02612058 7.194398e-03 #> AE68 0.017466427 0.08541910 0.07149689 0.04934195 0.02673386 5.606712e-03 #> AE69 0.025427691 0.07950054 0.06692939 0.04794946 0.02610897 1.075827e-02 #> AE70 0.024397497 0.08676899 0.07352538 0.04876882 0.02613623 7.740551e-03 #> AE71 0.025306610 0.09828523 0.07485413 0.04943489 0.02751513 6.540573e-03 #> AE72 0.018994708 0.08320701 0.07058901 0.05058892 0.02896517 9.816870e-03 #> AE73 0.017638669 0.08081453 0.06154661 0.04410005 0.02802859 4.977306e-03 #> AE74 0.013866970 0.08996534 0.08134595 0.05468616 0.02919334 1.030476e-03 #> AE75 0.019051266 0.08460450 0.06512687 0.05012725 0.02933960 1.204551e-02 #> AE76 0.024064241 0.08748911 0.06281835 0.04649284 0.02840376 1.019351e-02 #> AE77 0.019637439 0.08254312 0.07454355 0.05421194 0.03101338 9.705051e-03 #> AE78 0.020664576 0.08301491 0.06995436 0.04929145 0.02794066 7.814539e-03 #> AE79 0.019112716 0.08929033 0.07642541 0.04518694 0.02111029 5.806409e-03 #> AE80 0.020532270 0.07974954 0.06548313 0.04348238 0.02390729 8.908130e-03 #> AE81 0.032653485 0.09655472 0.07136094 0.05478530 0.03003749 9.625963e-03 #> AE82 0.016068078 0.09009160 0.07315928 0.05722988 0.03114905 8.837045e-03 #> AE83 0.011847216 0.08855522 0.07342359 0.05071607 0.02749338 -1.261610e-03 #> AE84 0.016668378 0.09927702 0.07453788 0.05663099 0.03280063 1.258835e-02 #> AE85 0.018956670 0.09108967 0.06777101 0.04204491 0.02751666 8.322889e-03 #> AE86 0.024398933 0.09834638 0.06994284 0.05154644 0.02823738 9.007741e-03 #> AE87 0.023684110 0.08553089 0.06985999 0.04973592 0.03075232 4.770671e-03 #> AE88 0.009086931 0.08497514 0.05602979 0.04052918 0.02196141 4.263640e-03 #> AE89 0.008697268 0.09415668 0.06619343 0.04559618 0.02268657 6.387914e-03 #> AE90 0.023592133 0.09288445 0.06780117 0.04761940 0.02373946 7.450863e-03 #> AE91 0.027587546 0.08739037 0.07424035 0.05285224 0.03121011 1.336585e-02 #> AE92 0.020877783 0.08354286 0.06453034 0.04529757 0.02508348 2.693451e-03 #> AE93 0.020362274 0.08839049 0.07280876 0.05736176 0.02925530 1.288949e-02 #> AE94 0.018616034 0.07857938 0.06210432 0.04488612 0.02620036 7.954699e-03 #> AE95 0.017466278 0.06626332 0.05950030 0.04144645 0.02093498 8.848699e-03 #> AE96 0.020801841 0.09324421 0.06773196 0.05463775 0.03234757 7.940429e-03 #> AE97 0.014952865 0.07896182 0.07300224 0.04985563 0.02788274 9.014158e-03 #> AE98 0.018048187 0.08218978 0.05785822 0.04056802 0.02329700 4.652032e-03 #> AE99 0.020083707 0.07576149 0.06395041 0.04630429 0.02900600 1.089936e-02 #> AE100 0.015824036 0.08821053 0.07491340 0.05309966 0.03213898 1.087831e-02 #> CX101 0.018795318 0.08935829 0.06789318 0.04795560 0.02523486 6.371738e-03 #> CX102 0.016523832 0.07645851 0.05814991 0.04824675 0.03385777 1.273612e-02 #> CX103 0.015546955 0.08786844 0.07200134 0.05340679 0.02005302 5.641727e-03 #> CX104 0.017186716 0.09086700 0.06213183 0.04676279 0.02521286 5.651021e-03 #> CX105 0.024732997 0.08784311 0.07192773 0.05218250 0.02508507 8.998762e-03 #> CX106 0.025857951 0.09772122 0.07359955 0.04628790 0.02514650 5.161054e-03 #> CX107 0.021438025 0.08574030 0.06659796 0.04418656 0.02230971 5.480441e-03 #> CX108 0.021697750 0.09066793 0.06603259 0.04953728 0.02503477 8.608714e-03 #> CX109 0.023769465 0.08002066 0.05865615 0.04432315 0.02486665 8.734026e-03 #> CX110 0.016554284 0.07594482 0.05471561 0.04478128 0.02505230 7.362556e-03 #> CX111 0.027261641 0.08863600 0.06600806 0.04864079 0.02950304 1.095938e-02 #> CX112 0.011567345 0.09504327 0.06914602 0.05050347 0.02412777 6.095360e-03 #> CX113 0.019372724 0.07856295 0.05797215 0.04557766 0.02528808 7.191655e-03 #> CX114 0.023230961 0.08830329 0.07676627 0.05220000 0.03012530 7.966660e-03 #> CX115 0.027645207 0.08323054 0.07204438 0.05037670 0.02389914 4.849303e-03 #> CX116 0.012671316 0.09954405 0.07257560 0.05202289 0.02616604 8.007566e-03 #> CX117 0.015588267 0.09102118 0.05090721 0.04192613 0.02375173 1.124011e-02 #> CX118 0.031458141 0.09238535 0.06813825 0.05207771 0.02839224 1.141056e-02 #> CX119 0.013748165 0.08552154 0.06632546 0.05062110 0.02802667 4.635430e-03 #> CX120 0.018452306 0.09280082 0.07952526 0.05129996 0.02550388 3.429387e-03 #> CX121 0.020419316 0.07808530 0.06910902 0.04830133 0.02437463 1.095195e-02 #> CX122 0.020437652 0.08050253 0.07033136 0.04799342 0.02581098 5.994960e-03 #> CX123 0.020778083 0.08042975 0.06478748 0.04765908 0.02367922 3.633548e-03 #> CX124 0.008692130 0.08303546 0.05963710 0.04238139 0.02053006 4.573956e-03 #> CX125 0.024193003 0.08506648 0.07389227 0.05162124 0.02943930 1.075803e-02 #> DE126 0.028740812 0.08903327 0.07586163 0.04853023 0.02610944 1.496756e-03 #> DE127 0.017573580 0.07459253 0.06140529 0.04375617 0.02306513 3.169474e-03 #> y7 y8 y9 y10 y11 y12 #> AN1 -0.022666314 -0.04495128 -0.07380235 -0.09608732 -0.11021440 -0.016199734 #> AN2 -0.008294587 -0.03422790 -0.05730591 -0.08756992 -0.10378049 -0.017413291 #> AN3 -0.009247883 -0.02947626 -0.04736125 -0.07195961 -0.08694772 -0.022201347 #> AN4 -0.007266518 -0.03817491 -0.06247395 -0.08534776 -0.09214130 -0.014432794 #> AN5 -0.013178097 -0.02962921 -0.05249050 -0.07247827 -0.09789820 -0.022527432 #> AN6 -0.012722770 -0.03281784 -0.05644748 -0.07669058 -0.08936509 -0.019148946 #> AN7 -0.008408792 -0.04279862 -0.05707903 -0.08968988 -0.10007999 -0.014849557 #> AN8 -0.002200848 -0.02722524 -0.05195370 -0.08021449 -0.09296762 -0.022862331 #> AN9 -0.010947676 -0.03524550 -0.05700364 -0.08079711 -0.09458230 -0.018055142 #> AN10 -0.007966654 -0.02926133 -0.04952115 -0.07859991 -0.09286459 -0.018567396 #> AN11 -0.015736928 -0.03610576 -0.05169961 -0.07002402 -0.08335024 -0.020845591 #> TO12 -0.007196761 -0.03202162 -0.05389319 -0.07018859 -0.08636577 -0.012831315 #> WY13 -0.014517432 -0.03556436 -0.06639870 -0.08844776 -0.10389518 -0.030313163 #> WY14 -0.015250720 -0.03483797 -0.05646906 -0.07746212 -0.08907170 -0.019772339 #> WY15 -0.010211930 -0.03618927 -0.05577035 -0.07262279 -0.08100249 -0.020178753 #> WY16 -0.010708481 -0.03415558 -0.05261327 -0.07363348 -0.08843957 -0.016680404 #> UR17 -0.019627397 -0.04068643 -0.05492440 -0.07645589 -0.09901886 -0.025215610 #> UR18 -0.018616124 -0.04695167 -0.06621731 -0.09086570 -0.11264614 -0.015247597 #> UR19 -0.010306625 -0.03187302 -0.04878683 -0.07199789 -0.08545362 -0.022977244 #> UR20 -0.014260396 -0.03870875 -0.06095216 -0.07791609 -0.10059416 -0.029218565 #> CA21 -0.011424835 -0.04241109 -0.06673866 -0.08717433 -0.10073722 -0.013774957 #> CA22 -0.017118972 -0.04456671 -0.06333256 -0.08548463 -0.09971043 -0.022457033 #> CA23 -0.008347883 -0.03668714 -0.05743793 -0.08221906 -0.10008108 -0.029337037 #> CA24 -0.014179955 -0.04065754 -0.06266514 -0.08979362 -0.10879858 -0.023113773 #> CA25 -0.015459966 -0.04556921 -0.06304180 -0.08676862 -0.10417190 -0.027553536 #> CA26 -0.006852774 -0.03087716 -0.05463273 -0.08502000 -0.10069478 -0.014484320 #> CA27 -0.017374727 -0.04566712 -0.06879405 -0.08809265 -0.09723578 -0.021534472 #> OR28 -0.024906613 -0.04860997 -0.06290004 -0.08224867 -0.09509220 -0.010348802 #> MA29 -0.015304956 -0.03905274 -0.05435187 -0.07951367 -0.09998388 -0.021699642 #> MA30 -0.010834828 -0.04016197 -0.06177193 -0.08862342 -0.11328879 -0.023690279 #> MA31 -0.018696436 -0.04114775 -0.05875278 -0.08531003 -0.10616868 -0.020705521 #> PS32 -0.013966342 -0.04517596 -0.06293986 -0.08771783 -0.11564596 -0.016808723 #> PS33 -0.018770501 -0.04766682 -0.07019447 -0.09609560 -0.11240803 -0.028353056 #> PS34 -0.016077185 -0.03892582 -0.06709499 -0.08915360 -0.11262678 -0.031961548 #> PS35 -0.010669404 -0.03446840 -0.05734935 -0.08175206 -0.09968148 -0.023747638 #> PS36 -0.014159752 -0.04084200 -0.05970849 -0.08591500 -0.09594658 -0.024568635 #> PS37 -0.015253852 -0.03496920 -0.06363514 -0.08431507 -0.10396906 -0.023449907 #> PS38 -0.009658641 -0.03155459 -0.05594592 -0.08233475 -0.10136260 -0.022744632 #> PS39 -0.006756077 -0.04002465 -0.06449392 -0.09299131 -0.11489188 -0.022555610 #> PS40 -0.011218252 -0.03616382 -0.06363627 -0.09112784 -0.10907791 -0.026264079 #> PS41 -0.012940371 -0.03946998 -0.07029977 -0.09689176 -0.11705262 -0.018025681 #> PS42 -0.012199593 -0.03887817 -0.06933953 -0.09428498 -0.12869403 -0.020124919 #> PS43 -0.019393904 -0.04308818 -0.06501801 -0.08619796 -0.11211448 -0.031925724 #> AE44 -0.009864032 -0.04162945 -0.06576743 -0.09725932 -0.11364550 -0.019576973 #> AE45 -0.013916993 -0.03736238 -0.06138435 -0.08687628 -0.09975951 -0.016310318 #> AE46 -0.012293031 -0.03405671 -0.05890388 -0.08537348 -0.11204166 -0.031127229 #> AE47 -0.015122615 -0.03729307 -0.06519826 -0.08781795 -0.10306537 -0.022479401 #> AE48 -0.011283848 -0.03764086 -0.06122137 -0.08007018 -0.09322090 -0.020270023 #> AE49 -0.013578564 -0.03320043 -0.06026791 -0.09253288 -0.10541387 -0.023949586 #> AE50 -0.016251885 -0.03720164 -0.06165119 -0.08784147 -0.10495288 -0.033744689 #> AE51 -0.010476511 -0.04660512 -0.06631610 -0.10182189 -0.11801742 -0.017839934 #> AE52 -0.019738467 -0.04341494 -0.06770016 -0.08995689 -0.11162861 -0.009071347 #> AE53 -0.015349580 -0.04042478 -0.06346917 -0.09056545 -0.10531159 -0.021332153 #> AE54 -0.014567417 -0.03743690 -0.06222308 -0.08733919 -0.10858403 -0.022837649 #> AE55 -0.009483085 -0.03298787 -0.05184618 -0.06911137 -0.09089088 -0.022677930 #> AE56 -0.014517252 -0.03572730 -0.05811263 -0.08361669 -0.10120448 -0.018959718 #> AE57 -0.016428768 -0.04444423 -0.06165616 -0.08731023 -0.10897038 -0.023316265 #> AE58 -0.010374273 -0.03231118 -0.06250651 -0.09107635 -0.11401767 -0.018983293 #> AE59 -0.011140219 -0.03426532 -0.05190264 -0.07858311 -0.09563840 -0.016993894 #> AE60 -0.016646973 -0.03728373 -0.06908015 -0.10354720 -0.12250383 -0.021937227 #> AE61 -0.012104480 -0.04374854 -0.06728928 -0.09264702 -0.11459973 -0.018773675 #> AE62 -0.010676452 -0.03345894 -0.05817475 -0.07512250 -0.08493945 -0.014084994 #> AE63 -0.013637658 -0.04137811 -0.06644285 -0.08819460 -0.10472228 -0.025306267 #> AE64 -0.012351366 -0.04001879 -0.06401090 -0.09337149 -0.11519782 -0.028951646 #> AE65 -0.006834492 -0.03207158 -0.06044547 -0.08432522 -0.09764177 -0.023000019 #> AE66 -0.012863697 -0.04182711 -0.06282764 -0.08872958 -0.11093574 -0.022655471 #> AE67 -0.008988133 -0.03836438 -0.06366265 -0.09116318 -0.10318603 -0.018396435 #> AE68 -0.018182938 -0.04065040 -0.05755426 -0.08005239 -0.10330960 -0.026939918 #> AE69 -0.010162744 -0.03434778 -0.06206309 -0.08433742 -0.10618099 -0.017816293 #> AE70 -0.013339125 -0.03087722 -0.06564962 -0.09583501 -0.11751622 -0.017921942 #> AE71 -0.009674615 -0.04047887 -0.06485963 -0.09489162 -0.11794276 -0.019557379 #> AE72 -0.011023048 -0.04144962 -0.06626343 -0.08850403 -0.10321745 -0.024119634 #> AE73 -0.012326640 -0.03771430 -0.06290116 -0.08707121 -0.11479236 -0.027633459 #> AE74 -0.023284290 -0.04456710 -0.06608998 -0.08808926 -0.10563109 -0.027465109 #> AE75 -0.014429655 -0.03968049 -0.06086849 -0.08665282 -0.10597408 -0.021162926 #> AE76 -0.008968325 -0.03792354 -0.06231543 -0.08502937 -0.10297398 -0.030918327 #> AE77 -0.015540834 -0.04290499 -0.06648039 -0.09428362 -0.10514460 -0.020485588 #> AE78 -0.012718208 -0.03826693 -0.06123567 -0.08909879 -0.10689239 -0.023647537 #> AE79 -0.011669590 -0.03582596 -0.06011012 -0.08866414 -0.11624901 -0.018461960 #> AE80 -0.011376774 -0.03653024 -0.06015092 -0.08237761 -0.10362247 -0.018665167 #> AE81 -0.016036431 -0.04029716 -0.07262006 -0.10446181 -0.12391661 -0.024052190 #> AE82 -0.020087830 -0.04201347 -0.07354814 -0.10065621 -0.10940849 -0.011428821 #> AE83 -0.021645529 -0.04539565 -0.06314253 -0.08529895 -0.10442005 -0.021041966 #> AE84 -0.014980325 -0.04246752 -0.06989970 -0.09745781 -0.10994738 -0.017995235 #> AE85 -0.010222911 -0.03959449 -0.06432343 -0.09074464 -0.10642521 -0.025756313 #> AE86 -0.014930629 -0.04480209 -0.06953731 -0.09809488 -0.12409746 -0.032433350 #> AE87 -0.012022788 -0.03779240 -0.06364329 -0.08785353 -0.11595475 -0.025407828 #> AE88 -0.008955694 -0.03275051 -0.05705711 -0.07994982 -0.09844740 -0.025026526 #> AE89 -0.015982691 -0.03740611 -0.05867094 -0.08552491 -0.10024375 -0.025804413 #> AE90 -0.011306378 -0.03521060 -0.06690911 -0.09599275 -0.12234375 -0.029537958 #> AE91 -0.012111344 -0.04106840 -0.07231039 -0.10062439 -0.11553546 -0.025351922 #> AE92 -0.015689253 -0.03491960 -0.05842990 -0.08010586 -0.10556897 -0.024083862 #> AE93 -0.013901076 -0.04308173 -0.06745768 -0.09390358 -0.09889036 -0.023300202 #> AE94 -0.012763836 -0.03714156 -0.06145234 -0.08746265 -0.10258403 -0.019185244 #> AE95 -0.008317134 -0.03318205 -0.05476635 -0.07909102 -0.09724833 -0.021156993 #> AE96 -0.015012694 -0.04126789 -0.06917529 -0.09235024 -0.11303064 -0.027983805 #> AE97 -0.013629341 -0.04202223 -0.06470694 -0.08938782 -0.10634508 -0.014570628 #> AE98 -0.014268236 -0.03160816 -0.05122169 -0.07681646 -0.10049791 -0.024985362 #> AE99 -0.012077336 -0.03512960 -0.06536965 -0.08814244 -0.10843565 -0.015810894 #> AE100 -0.015056303 -0.04452189 -0.06201376 -0.09154554 -0.10155078 -0.028695098 #> CX101 -0.012506215 -0.03810225 -0.06348897 -0.09067708 -0.10433018 -0.018162774 #> CX102 -0.012983929 -0.04180854 -0.05886266 -0.08220843 -0.10445411 -0.010668165 #> CX103 -0.016869427 -0.04349510 -0.06480692 -0.08860946 -0.10069580 -0.025010278 #> CX104 -0.013144831 -0.04263306 -0.06495377 -0.08813451 -0.10489965 -0.022728276 #> CX105 -0.012350189 -0.04220287 -0.06626618 -0.09078704 -0.11120488 -0.017454695 #> CX106 -0.012491167 -0.04111398 -0.06370969 -0.09441199 -0.11527055 -0.023497145 #> CX107 -0.008315049 -0.03997006 -0.05355706 -0.08196831 -0.10487567 -0.017101308 #> CX108 -0.010673165 -0.03906141 -0.05834507 -0.08205253 -0.10100631 -0.022314285 #> CX109 -0.008018621 -0.03278166 -0.05973300 -0.08491355 -0.10133516 -0.018724402 #> CX110 -0.011894825 -0.03700534 -0.05728326 -0.07951859 -0.09869608 -0.017798403 #> CX111 -0.014985750 -0.03983215 -0.06524722 -0.09406644 -0.11797937 -0.017169369 #> CX112 -0.013257204 -0.03887045 -0.06562399 -0.08856518 -0.10527379 -0.021787205 #> CX113 -0.011450525 -0.03243768 -0.05903150 -0.08555464 -0.10609845 -0.015088975 #> CX114 -0.011663783 -0.03826338 -0.06602557 -0.10037116 -0.11768366 -0.016465993 #> CX115 -0.012353681 -0.03551555 -0.06244976 -0.09033097 -0.10471702 -0.019157513 #> CX116 -0.016204202 -0.04316559 -0.06920846 -0.09247241 -0.11333981 -0.024230163 #> CX117 -0.010294909 -0.03367189 -0.06181392 -0.08869494 -0.10357813 -0.020483250 #> CX118 -0.009854288 -0.03844275 -0.06624935 -0.09575786 -0.10947066 -0.031365179 #> CX119 -0.017650235 -0.04023434 -0.05830157 -0.08376944 -0.10011781 -0.023657629 #> CX120 -0.016994086 -0.04075366 -0.06603417 -0.09305920 -0.10748884 -0.025143006 #> CX121 -0.016097956 -0.04470260 -0.06733971 -0.09199145 -0.11052390 -0.013972544 #> CX122 -0.014023818 -0.03254778 -0.05833005 -0.08242031 -0.10218434 -0.014351771 #> CX123 -0.013940498 -0.03357926 -0.06438180 -0.08609256 -0.10173894 -0.018241610 #> CX124 -0.012729199 -0.03257353 -0.05686875 -0.08601868 -0.09105267 -0.021119040 #> CX125 -0.012021816 -0.03914166 -0.06331033 -0.09482505 -0.11425836 -0.009229708 #> DE126 -0.019319910 -0.03999012 -0.06598948 -0.09151587 -0.10655099 -0.009402691 #> DE127 -0.013157041 -0.03350065 -0.05475301 -0.07904062 -0.09178239 -0.020872877 #> y13 y14 y15 y16 y17 y18 #> AN1 0.031653251 0.03394145 0.05065519 0.023694351 -0.0058531156 -0.02386017 #> AN2 0.023930124 0.02633191 0.03960071 0.017386724 -0.0058883600 -0.02588693 #> AN3 0.016914452 0.01728375 0.03471704 0.011250077 -0.0075009263 -0.01706643 #> AN4 0.007944998 0.02071929 0.04123774 0.023722845 -0.0057300114 -0.02163378 #> AN5 0.024239303 0.02436660 0.04056937 0.019005613 -0.0020748921 -0.01906749 #> AN6 0.014703930 0.02479341 0.04364098 0.020180182 -0.0041146405 -0.01814230 #> AN7 0.023330304 0.02524160 0.04136306 0.017184102 -0.0147098834 -0.02795570 #> AN8 0.012717785 0.02065677 0.03952636 0.014507114 -0.0089944390 -0.02281300 #> AN9 0.019749885 0.02201980 0.03843079 0.012804281 -0.0100737547 -0.02081712 #> AN10 0.010656820 0.02236025 0.04272360 0.021347941 -0.0036869423 -0.01416372 #> AN11 0.009339839 0.02218767 0.04330031 0.020130765 -0.0068556079 -0.01670046 #> TO12 0.012542711 0.01495272 0.04138213 0.009940141 -0.0082878628 -0.02173497 #> WY13 0.025506841 0.02470727 0.04155787 0.016111610 -0.0090264837 -0.02423198 #> WY14 0.015089999 0.03185406 0.04444696 0.024840804 -0.0064136917 -0.01764814 #> WY15 0.011286902 0.02144045 0.03722986 0.016704989 -0.0056998378 -0.01821252 #> WY16 0.009266234 0.01941323 0.03907200 0.015109806 -0.0060277218 -0.02533050 #> UR17 0.011366859 0.03519135 0.05027222 0.022840549 -0.0101491833 -0.02237430 #> UR18 0.016039551 0.03801945 0.05674724 0.011803866 -0.0232327002 -0.03933606 #> UR19 0.015607256 0.02687834 0.04595487 0.013225571 -0.0178589142 -0.02754166 #> UR20 0.016589336 0.03070214 0.04560762 0.017645589 -0.0102842014 -0.02281823 #> CA21 0.012199133 0.03094133 0.04865604 0.019396951 -0.0052322022 -0.02886625 #> CA22 0.012822346 0.02598790 0.04731617 0.018519444 -0.0111925712 -0.02713474 #> CA23 0.009232801 0.02496965 0.04993777 0.023999457 -0.0025086781 -0.02920003 #> CA24 0.019171445 0.03433137 0.04741436 0.020599082 -0.0074399680 -0.02660992 #> CA25 0.009566033 0.02658144 0.05113483 0.022691958 -0.0020231414 -0.02198399 #> CA26 0.017524234 0.02454569 0.03994687 0.019174759 -0.0005099502 -0.02142183 #> CA27 0.018046519 0.02646747 0.04038172 0.018052689 -0.0098840617 -0.01427539 #> OR28 0.017944287 0.03140055 0.04424794 0.027462220 -0.0063186282 -0.02917818 #> MA29 0.012586080 0.02288037 0.04696049 0.021867340 -0.0018019964 -0.03010091 #> MA30 0.020154213 0.02900446 0.04106282 0.017263472 -0.0109026150 -0.02331410 #> MA31 0.014369888 0.02456438 0.04953818 0.027385068 -0.0047871505 -0.01774976 #> PS32 0.015373535 0.02680157 0.04710279 0.021307525 -0.0071921204 -0.03179500 #> PS33 0.022336072 0.02810195 0.05024300 0.022540270 -0.0111040272 -0.03533574 #> PS34 0.020315464 0.03303756 0.04869750 0.021234398 -0.0072347126 -0.02762668 #> PS35 0.012788035 0.02439453 0.04751539 0.020824472 -0.0076933034 -0.01921035 #> PS36 0.020300111 0.02820023 0.04385212 0.017569210 -0.0109004659 -0.02892289 #> PS37 0.019334246 0.02777829 0.04141996 0.018432920 -0.0056363825 -0.02279697 #> PS38 0.014203886 0.01976390 0.03926354 0.018373256 -0.0064799250 -0.02255351 #> PS39 0.018807152 0.02727129 0.04427371 0.020818172 -0.0084929742 -0.02757373 #> PS40 0.017286358 0.02264821 0.04726978 0.019224306 -0.0070545666 -0.02488379 #> PS41 0.026375073 0.02492808 0.03676656 0.010547022 -0.0160261360 -0.02960204 #> PS42 0.024353039 0.02959271 0.04752195 0.018790914 -0.0033314324 -0.02361597 #> PS43 0.009696453 0.02962132 0.05395096 0.028008307 -0.0054060649 -0.02278089 #> AE44 0.022209613 0.02872914 0.04678593 0.021432306 -0.0062438005 -0.03325430 #> AE45 0.017070529 0.02500476 0.04207118 0.015590449 -0.0125041590 -0.02643712 #> AE46 0.019955954 0.02210685 0.04425050 0.016124350 -0.0059187470 -0.02112102 #> AE47 0.012764921 0.02549636 0.04832930 0.021279454 -0.0072668469 -0.03053345 #> AE48 0.009012434 0.02788134 0.04195447 0.019452316 -0.0033602107 -0.02224146 #> AE49 0.020167979 0.02671760 0.03790360 0.017879879 -0.0082872336 -0.02436522 #> AE50 0.017980169 0.02522621 0.04455923 0.022412292 0.0006199068 -0.02573227 #> AE51 0.028273610 0.02475281 0.04560509 0.018289771 -0.0155381857 -0.03078107 #> AE52 0.018498035 0.02806079 0.04598992 0.019078102 -0.0100429219 -0.02107760 #> AE53 0.018989183 0.02826034 0.04836101 0.022696282 -0.0086760730 -0.02522523 #> AE54 0.016955963 0.02749484 0.04935746 0.023671924 -0.0054385706 -0.03005728 #> AE55 0.007775690 0.01964697 0.03970104 0.017668638 -0.0056924635 -0.01928116 #> AE56 0.015528690 0.01944325 0.04181501 0.016532880 -0.0075657410 -0.02127519 #> AE57 0.021657914 0.03143334 0.05045469 0.022103526 -0.0032291590 -0.02976023 #> AE58 0.014852798 0.02357382 0.04124862 0.017758954 -0.0126937695 -0.02278433 #> AE59 0.013820549 0.02138296 0.03838600 0.012431547 -0.0118056825 -0.02429321 #> AE60 0.017799748 0.03216945 0.05085970 0.020439774 -0.0079058535 -0.03668566 #> AE61 0.013592307 0.02666289 0.05506965 0.024674679 -0.0035991276 -0.01729537 #> AE62 0.010791212 0.02280408 0.04030167 0.016172907 -0.0081164709 -0.01555793 #> AE63 0.019867096 0.02713715 0.04740922 0.015228820 -0.0146203454 -0.02668283 #> AE64 0.029566394 0.02811684 0.04582514 0.018185289 -0.0051168536 -0.03450801 #> AE65 0.013745957 0.02120385 0.03460146 0.015391025 -0.0102461772 -0.02624110 #> AE66 0.015232007 0.02321355 0.05194073 0.018371196 -0.0109811519 -0.03403938 #> AE67 0.020651093 0.02197065 0.03654878 0.015461638 -0.0086958717 -0.02319231 #> AE68 0.015037573 0.02794225 0.04623979 0.019435954 -0.0080725868 -0.02995841 #> AE69 0.015459714 0.02141548 0.04330776 0.017231297 -0.0125420006 -0.02663824 #> AE70 0.014133953 0.02400491 0.04993628 0.024999386 -0.0113126526 -0.02796019 #> AE71 0.026204493 0.02682321 0.04498873 0.016597931 -0.0147664476 -0.03437959 #> AE72 0.017115848 0.02847935 0.05058032 0.018729056 -0.0130620477 -0.02942701 #> AE73 0.019057488 0.03181711 0.04992821 0.020752837 -0.0014266702 -0.01479561 #> AE74 0.016245319 0.03259439 0.04730746 0.023664786 -0.0069021820 -0.02787117 #> AE75 0.021831863 0.02721258 0.04641488 0.013558764 -0.0120488307 -0.02849579 #> AE76 0.019244522 0.02578020 0.04748669 0.017166620 -0.0114005808 -0.02961030 #> AE77 0.020455607 0.02536790 0.04869105 0.018380169 -0.0107076381 -0.02900154 #> AE78 0.019015265 0.03337134 0.04117545 0.015356576 -0.0116219684 -0.02411763 #> AE79 0.019995869 0.02636401 0.04234840 0.017890749 -0.0082389520 -0.02431138 #> AE80 0.017930466 0.02416673 0.04377548 0.019651464 -0.0083685772 -0.02649514 #> AE81 0.024148981 0.02919554 0.04869795 0.019255872 -0.0100449592 -0.02488700 #> AE82 0.020578909 0.02706156 0.04897019 0.018344967 -0.0091223541 -0.02522526 #> AE83 0.016781292 0.03114929 0.05394455 0.024519177 -0.0092320644 -0.02699144 #> AE84 0.024609830 0.02873131 0.04198269 0.016284835 -0.0153416977 -0.03602225 #> AE85 0.010396520 0.02846303 0.04731145 0.025320390 -0.0055367524 -0.02458945 #> AE86 0.036343087 0.02984724 0.04512154 0.020647760 -0.0058120162 -0.02373160 #> AE87 0.020225282 0.02813906 0.04238996 0.015529013 -0.0086145568 -0.01932807 #> AE88 0.015667143 0.02902972 0.04316773 0.021523222 -0.0017849076 -0.02226195 #> AE89 0.010784658 0.02446307 0.05051475 0.021313287 -0.0053891002 -0.02177189 #> AE90 0.027142506 0.03212522 0.05108388 0.023257334 -0.0046635032 -0.03073238 #> AE91 0.019033489 0.03167430 0.04462634 0.018496419 -0.0112092137 -0.02226589 #> AE92 0.012810939 0.02363067 0.04162214 0.021165370 -0.0067165829 -0.01574059 #> AE93 0.022471103 0.02651858 0.04508543 0.014069432 -0.0157448155 -0.03293319 #> AE94 0.012305865 0.02681931 0.04454421 0.023851832 -0.0029548417 -0.02231764 #> AE95 0.016906129 0.02469427 0.04023863 0.021999889 -0.0084593595 -0.01607771 #> AE96 0.017485117 0.02547147 0.04704657 0.020538267 -0.0079848838 -0.02043972 #> AE97 0.016648864 0.02472005 0.04875918 0.015428675 -0.0047708489 -0.02379334 #> AE98 0.013391858 0.02393506 0.04162961 0.019367765 -0.0054168820 -0.02012284 #> AE99 0.019977565 0.02394541 0.04300177 0.020764156 -0.0044495209 -0.02427907 #> AE100 0.011980687 0.02528265 0.04703604 0.018302914 -0.0085743289 -0.02570950 #> CX101 0.016228827 0.02795540 0.04467222 0.019165494 -0.0099841850 -0.02637927 #> CX102 0.017259331 0.01912946 0.04067772 0.015083424 -0.0067027356 -0.02043425 #> CX103 0.020074121 0.03029000 0.04633641 0.020038662 -0.0052371329 -0.02653335 #> CX104 0.014934569 0.02833998 0.04791502 0.024512049 -0.0071740845 -0.01984566 #> CX105 0.019219428 0.02529887 0.03836062 0.019788647 -0.0075309252 -0.02564094 #> CX106 0.018299308 0.02768259 0.04677679 0.019768234 -0.0097009633 -0.02610560 #> CX107 0.015806760 0.02182572 0.03975539 0.017122074 -0.0078549731 -0.02662050 #> CX108 0.016215262 0.02519327 0.04243383 0.010268036 -0.0112934336 -0.03094322 #> CX109 0.017068885 0.02501765 0.03545559 0.016413355 -0.0056047239 -0.02321445 #> CX110 0.012385269 0.02481311 0.04163334 0.020597841 -0.0085527751 -0.01309114 #> CX111 0.020635245 0.02905378 0.04625604 0.017163441 -0.0095672256 -0.02526990 #> CX112 0.012659275 0.02760717 0.04363982 0.019186884 -0.0085127474 -0.01768584 #> CX113 0.014469364 0.01985292 0.04219240 0.018608647 -0.0039236081 -0.01550316 #> CX114 0.018322739 0.02242499 0.03905605 0.015973206 -0.0068638956 -0.01703203 #> CX115 0.014974865 0.02220072 0.04055723 0.018212767 -0.0086772873 -0.02478906 #> CX116 0.017431556 0.03145910 0.04683659 0.021299988 -0.0043485687 -0.02504549 #> CX117 0.017905431 0.02938074 0.04469183 0.018408516 -0.0043347815 -0.02194933 #> CX118 0.027152233 0.02328459 0.03539228 0.015205687 -0.0075409103 -0.02621603 #> CX119 0.017132004 0.02244083 0.04338429 0.016764177 -0.0031370859 -0.02173155 #> CX120 0.017126560 0.03024564 0.04707770 0.019113201 -0.0119658108 -0.02313595 #> CX121 0.023244195 0.02442777 0.04507924 0.020724090 -0.0018107845 -0.01827788 #> CX122 0.015060402 0.02122439 0.04010077 0.016097457 -0.0109813961 -0.02871446 #> CX123 0.012181115 0.02677886 0.04411853 0.020245582 -0.0085144121 -0.01780218 #> CX124 0.012934711 0.02604046 0.04671372 0.019656344 -0.0007938145 -0.02303963 #> CX125 0.019920346 0.02308511 0.04046563 0.013778338 -0.0108924185 -0.02854041 #> DE126 0.018362791 0.02746598 0.03974138 0.015250649 -0.0136039673 -0.02421991 #> DE127 0.016632923 0.02410343 0.03776670 0.017676786 -0.0115576584 -0.01507777"},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Coo ","title":"Coo ","text":"Coo class 'parent' 'super' class , Opn Ldk classes.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Coo ","text":"","code":"Coo(...)"},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Coo ","text":"... anything , anyway, function simply returns message.","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Coo ","text":"list class Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Coo ","text":"Useful shortcuts described . See browseVignettes(\"Momocs\") detail design behind Momocs' classes. Coo class 'parent' class following 'child' classes closed outlines Opn open outlines Ldk configuration landmarks Since 'child classes' handle \\((x; y)\\) coordinates among generic methods, also specificity, architecture allow recycle generic methods use specific methods. words, , Opn Ldk classes , primarily, Coo objects define generic specific methods. See respective help pages help. Coo objects following components: $coo list matrices coordinates $fac data_frame covariates (). can provide data_frame directly, long many rows matrices $coo (see examples), use helper function lf_structure. can access methods available Coo objects methods(class=Coo).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Coo ","text":"","code":"# to see all methods for Coo objects. methods(class='Coo') #> [1] $ Ldk #> [3] Opn Out #> [5] [ [<- #> [7] arrange as_df #> [9] chop coo_align #> [11] coo_aligncalliper coo_alignminradius #> [13] coo_alignxax coo_angle_edges #> [15] coo_angle_tangent coo_area #> [17] coo_baseline coo_boundingbox #> [19] coo_calliper coo_centdist #> [21] coo_center coo_centpos #> [23] coo_centsize coo_check #> [25] coo_chull coo_chull_onion #> [27] coo_circularity coo_circularityharalick #> [29] coo_circularitynorm coo_close #> [31] coo_convexity coo_diffrange #> [33] coo_down coo_dxy #> [35] coo_eccentricityboundingbox coo_eccentricityeigen #> [37] coo_elongation coo_extract #> [39] coo_flipx coo_flipy #> [41] coo_force2close coo_interpolate #> [43] coo_intersect_angle coo_intersect_direction #> [45] coo_intersect_segment coo_is_closed #> [47] coo_jitter coo_left #> [49] coo_length coo_likely_clockwise #> [51] coo_lw coo_nb #> [53] coo_perim coo_perimcum #> [55] coo_perimpts coo_range #> [57] coo_range_enlarge coo_rectangularity #> [59] coo_rectilinearity coo_rev #> [61] coo_right coo_rotate #> [63] coo_rotatecenter coo_samplerr #> [65] coo_scalars coo_scale #> [67] coo_scalex coo_scaley #> [69] coo_shearx coo_sheary #> [71] coo_slide coo_slidedirection #> [73] coo_slidegap coo_smooth #> [75] coo_solidity coo_tac #> [77] coo_template coo_template_relatively #> [79] coo_trans coo_trim #> [81] coo_trimbottom coo_trimtop #> [83] coo_truss coo_unclose #> [85] coo_untiltx coo_up #> [87] coo_width dfourier #> [89] dim filter #> [91] inspect is_equallyspacedradii #> [93] length measure #> [95] mutate names #> [97] names<- print #> [99] rename sample_frac #> [101] sample_n select #> [103] slice stack #> [105] str subsetize #> [107] verify #> see '?methods' for accessing help and source code # to see all methods for Out objects. methods(class='Out') # same for Opn and Ldk #> [1] add_ldk combine coo_bookstein coo_down #> [5] coo_left coo_right coo_sample coo_sample_prop #> [9] coo_slice coo_up d def_ldk #> [13] def_ldk_angle def_ldk_direction efourier fgProcrustes #> [17] get_ldk mosaic panel pile #> [21] rearrange_ldk rfourier sfourier tfourier #> see '?methods' for accessing help and source code # Let's take an Out example. But all methods shown here # work on Ldk (try on 'wings') and on Opn ('olea') bot #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk # Primarily a 'Coo' object, but also an 'Out' class(bot) #> [1] \"Out\" \"Coo\" inherits(bot, \"Coo\") #> [1] TRUE panel(bot) stack(bot) # Getters (you can also use it to set data) bot[1] %>% coo_plot() bot[1:5] %>% str() #> List of 5 #> $ brahma : num [1:138, 1:2] 37 40 40 43 46 48 52 54 57 59 ... #> $ caney : num [1:168, 1:2] 53 53 54 53 54 54 54 54 54 53 ... #> $ chimay : num [1:189, 1:2] 49 49 49 50 50 50 51 50 50 50 ... #> $ corona : num [1:129, 1:2] 91 91 90 91 91 91 91 91 91 91 ... #> $ deusventrue: num [1:152, 1:2] 74 70 62 59 52 49 47 43 41 38 ... # Setters bot[1] <- shapes[4] panel(bot) bot[1:5] <- shapes[4:8] panel(bot) # access the different components # $coo coordinates head(bot$coo) #> $brahma #> [,1] [,2] #> [1,] 200 62 #> [2,] 200 61 #> [3,] 199 60 #> [4,] 198 59 #> [5,] 197 58 #> [6,] 197 57 #> [7,] 196 56 #> [8,] 195 56 #> [9,] 196 56 #> [10,] 197 56 #> [11,] 198 56 #> [12,] 199 56 #> [13,] 200 56 #> [14,] 201 55 #> [15,] 202 55 #> [16,] 203 55 #> [17,] 204 55 #> [18,] 205 54 #> [19,] 206 54 #> [20,] 207 53 #> [21,] 208 52 #> [22,] 208 51 #> [23,] 209 50 #> [24,] 209 49 #> [25,] 209 48 #> [26,] 209 47 #> [27,] 208 46 #> [28,] 208 45 #> [29,] 207 44 #> [30,] 206 44 #> [31,] 205 43 #> [32,] 204 43 #> [33,] 203 43 #> [34,] 202 43 #> [35,] 201 43 #> [36,] 200 43 #> [37,] 199 43 #> [38,] 198 43 #> [39,] 197 43 #> [40,] 196 42 #> [41,] 195 42 #> [42,] 194 42 #> [43,] 193 42 #> [44,] 192 42 #> [45,] 191 42 #> [46,] 190 42 #> [47,] 189 42 #> [48,] 188 42 #> [49,] 187 42 #> [50,] 186 42 #> [51,] 185 42 #> [52,] 184 42 #> [53,] 183 42 #> [54,] 182 42 #> [55,] 181 42 #> [56,] 180 42 #> [57,] 179 42 #> [58,] 178 43 #> [59,] 177 42 #> [60,] 176 43 #> [61,] 175 43 #> [62,] 174 43 #> [63,] 173 43 #> [64,] 172 43 #> [65,] 171 43 #> [66,] 170 43 #> [67,] 169 43 #> [68,] 168 43 #> [69,] 167 43 #> [70,] 166 43 #> [71,] 165 43 #> [72,] 164 43 #> [73,] 163 43 #> [74,] 162 43 #> [75,] 161 43 #> [76,] 160 43 #> [77,] 159 43 #> [78,] 158 43 #> [79,] 157 43 #> [80,] 156 43 #> [81,] 155 43 #> [82,] 154 43 #> [83,] 153 43 #> [84,] 152 43 #> [85,] 151 43 #> [86,] 150 43 #> [87,] 149 43 #> [88,] 148 43 #> [89,] 147 43 #> [90,] 146 44 #> [91,] 145 44 #> [92,] 144 44 #> [93,] 143 44 #> [94,] 143 43 #> [95,] 143 42 #> [96,] 143 41 #> [97,] 142 40 #> [98,] 142 39 #> [99,] 142 38 #> [100,] 142 37 #> [101,] 142 36 #> [102,] 142 35 #> [103,] 143 34 #> [104,] 143 33 #> [105,] 143 32 #> [106,] 144 31 #> [107,] 145 30 #> [108,] 145 29 #> [109,] 146 28 #> [110,] 147 27 #> [111,] 148 27 #> [112,] 149 26 #> [113,] 150 25 #> [114,] 151 25 #> [115,] 152 24 #> [116,] 153 24 #> [117,] 154 23 #> [118,] 155 23 #> [119,] 156 23 #> [120,] 157 22 #> [121,] 158 22 #> [122,] 159 22 #> [123,] 160 21 #> [124,] 161 21 #> [125,] 162 21 #> [126,] 163 21 #> [127,] 164 21 #> [128,] 165 20 #> [129,] 166 20 #> [130,] 167 20 #> [131,] 168 20 #> [132,] 169 20 #> [133,] 170 20 #> [134,] 171 20 #> [135,] 172 20 #> [136,] 173 20 #> [137,] 174 19 #> [138,] 175 19 #> [139,] 176 19 #> [140,] 177 19 #> [141,] 178 19 #> [142,] 179 19 #> [143,] 180 19 #> [144,] 181 20 #> [145,] 182 20 #> [146,] 183 20 #> [147,] 184 20 #> [148,] 185 20 #> [149,] 186 20 #> [150,] 187 20 #> [151,] 188 20 #> [152,] 189 21 #> [153,] 190 21 #> [154,] 191 21 #> [155,] 192 21 #> [156,] 193 21 #> [157,] 194 21 #> [158,] 195 22 #> [159,] 196 22 #> [160,] 197 22 #> [161,] 198 22 #> [162,] 199 22 #> [163,] 200 22 #> [164,] 201 22 #> [165,] 202 22 #> [166,] 203 22 #> [167,] 204 22 #> [168,] 205 22 #> [169,] 206 22 #> [170,] 207 21 #> [171,] 208 20 #> [172,] 208 19 #> [173,] 207 18 #> [174,] 206 17 #> [175,] 205 17 #> [176,] 204 16 #> [177,] 203 16 #> [178,] 202 15 #> [179,] 201 15 #> [180,] 200 14 #> [181,] 199 14 #> [182,] 198 14 #> [183,] 197 13 #> [184,] 196 13 #> [185,] 195 13 #> [186,] 194 12 #> [187,] 193 12 #> [188,] 192 12 #> [189,] 191 11 #> [190,] 190 11 #> [191,] 189 11 #> [192,] 188 11 #> [193,] 187 10 #> [194,] 186 10 #> [195,] 185 10 #> [196,] 184 10 #> [197,] 183 9 #> [198,] 182 9 #> [199,] 181 10 #> [200,] 180 9 #> [201,] 179 9 #> [202,] 178 9 #> [203,] 177 9 #> [204,] 176 9 #> [205,] 175 9 #> [206,] 174 9 #> [207,] 173 9 #> [208,] 172 9 #> [209,] 171 9 #> [210,] 170 9 #> [211,] 169 9 #> [212,] 168 9 #> [213,] 167 9 #> [214,] 166 9 #> [215,] 165 9 #> [216,] 164 9 #> [217,] 163 9 #> [218,] 162 9 #> [219,] 161 9 #> [220,] 160 10 #> [221,] 159 10 #> [222,] 158 10 #> [223,] 157 10 #> [224,] 156 10 #> [225,] 155 11 #> [226,] 154 11 #> [227,] 153 11 #> [228,] 152 12 #> [229,] 151 12 #> [230,] 150 12 #> [231,] 149 13 #> [232,] 148 13 #> [233,] 147 14 #> [234,] 146 14 #> [235,] 145 15 #> [236,] 144 15 #> [237,] 143 16 #> [238,] 142 17 #> [239,] 141 17 #> [240,] 140 18 #> [241,] 139 19 #> [242,] 138 20 #> [243,] 137 21 #> [244,] 136 22 #> [245,] 135 23 #> [246,] 134 24 #> [247,] 134 25 #> [248,] 133 26 #> [249,] 133 27 #> [250,] 132 28 #> [251,] 132 29 #> [252,] 131 30 #> [253,] 131 31 #> [254,] 131 32 #> [255,] 130 33 #> [256,] 130 34 #> [257,] 130 35 #> [258,] 130 36 #> [259,] 130 37 #> [260,] 130 38 #> [261,] 130 39 #> [262,] 130 40 #> [263,] 130 41 #> [264,] 130 42 #> [265,] 130 43 #> [266,] 130 44 #> [267,] 130 45 #> [268,] 131 46 #> [269,] 131 47 #> [270,] 131 48 #> [271,] 132 49 #> [272,] 132 50 #> [273,] 132 51 #> [274,] 133 52 #> [275,] 133 53 #> [276,] 133 54 #> [277,] 134 55 #> [278,] 135 56 #> [279,] 135 57 #> [280,] 135 58 #> [281,] 135 59 #> [282,] 136 60 #> [283,] 136 61 #> [284,] 135 62 #> [285,] 136 63 #> [286,] 136 64 #> [287,] 136 65 #> [288,] 136 66 #> [289,] 136 67 #> [290,] 135 68 #> [291,] 136 69 #> [292,] 135 70 #> [293,] 135 71 #> [294,] 135 72 #> [295,] 135 73 #> [296,] 135 74 #> [297,] 134 75 #> [298,] 135 76 #> [299,] 134 77 #> [300,] 134 78 #> [301,] 134 79 #> [302,] 134 80 #> [303,] 134 81 #> [304,] 134 82 #> [305,] 134 83 #> [306,] 133 84 #> [307,] 133 85 #> [308,] 134 86 #> [309,] 134 87 #> [310,] 134 88 #> [311,] 133 89 #> [312,] 133 90 #> [313,] 133 91 #> [314,] 133 92 #> [315,] 133 93 #> [316,] 133 94 #> [317,] 133 95 #> [318,] 133 96 #> [319,] 133 97 #> [320,] 133 98 #> [321,] 133 99 #> [322,] 133 100 #> [323,] 133 101 #> [324,] 133 102 #> [325,] 133 103 #> [326,] 133 104 #> [327,] 133 105 #> [328,] 133 106 #> [329,] 133 107 #> [330,] 133 108 #> [331,] 133 109 #> [332,] 134 110 #> [333,] 134 111 #> [334,] 133 112 #> [335,] 134 113 #> [336,] 134 114 #> [337,] 134 115 #> [338,] 134 116 #> [339,] 134 117 #> [340,] 135 118 #> [341,] 135 119 #> [342,] 135 120 #> [343,] 136 121 #> [344,] 136 122 #> [345,] 136 123 #> [346,] 137 124 #> [347,] 137 125 #> [348,] 138 126 #> [349,] 138 127 #> [350,] 139 128 #> [351,] 139 129 #> [352,] 140 130 #> [353,] 140 131 #> [354,] 141 132 #> [355,] 141 133 #> [356,] 142 134 #> [357,] 142 135 #> [358,] 143 136 #> [359,] 143 137 #> [360,] 144 138 #> [361,] 144 139 #> [362,] 145 140 #> [363,] 145 141 #> [364,] 146 142 #> [365,] 147 143 #> [366,] 148 144 #> [367,] 148 145 #> [368,] 149 146 #> [369,] 150 147 #> [370,] 150 148 #> [371,] 151 149 #> [372,] 152 150 #> [373,] 153 151 #> [374,] 154 152 #> [375,] 155 153 #> [376,] 156 154 #> [377,] 157 155 #> [378,] 158 156 #> [379,] 159 157 #> [380,] 160 158 #> [381,] 161 158 #> [382,] 162 159 #> [383,] 163 159 #> [384,] 164 160 #> [385,] 165 160 #> [386,] 166 160 #> [387,] 167 161 #> [388,] 168 161 #> [389,] 169 161 #> [390,] 170 162 #> [391,] 171 162 #> [392,] 172 162 #> [393,] 173 163 #> [394,] 174 164 #> [395,] 175 164 #> [396,] 176 165 #> [397,] 177 165 #> [398,] 178 166 #> [399,] 179 167 #> [400,] 180 167 #> [401,] 181 168 #> [402,] 182 169 #> [403,] 183 170 #> [404,] 184 171 #> [405,] 185 172 #> [406,] 186 173 #> [407,] 187 174 #> [408,] 187 175 #> [409,] 188 176 #> [410,] 189 177 #> [411,] 189 178 #> [412,] 190 179 #> [413,] 190 180 #> [414,] 191 181 #> [415,] 191 182 #> [416,] 191 183 #> [417,] 191 184 #> [418,] 191 185 #> [419,] 191 186 #> [420,] 191 187 #> [421,] 190 188 #> [422,] 191 189 #> [423,] 191 190 #> [424,] 191 191 #> [425,] 191 192 #> [426,] 192 193 #> [427,] 192 194 #> [428,] 192 195 #> [429,] 193 196 #> [430,] 193 197 #> [431,] 194 198 #> [432,] 194 199 #> [433,] 194 200 #> [434,] 195 201 #> [435,] 196 202 #> [436,] 196 203 #> [437,] 197 204 #> [438,] 197 205 #> [439,] 198 206 #> [440,] 199 207 #> [441,] 200 208 #> [442,] 201 209 #> [443,] 202 210 #> [444,] 203 210 #> [445,] 204 211 #> [446,] 205 212 #> [447,] 206 212 #> [448,] 207 213 #> [449,] 208 213 #> [450,] 209 214 #> [451,] 210 215 #> [452,] 211 216 #> [453,] 211 217 #> [454,] 211 218 #> [455,] 212 219 #> [456,] 212 220 #> [457,] 213 221 #> [458,] 213 222 #> [459,] 214 223 #> [460,] 215 224 #> [461,] 215 225 #> [462,] 216 226 #> [463,] 217 227 #> [464,] 217 228 #> [465,] 218 229 #> [466,] 219 230 #> [467,] 220 230 #> [468,] 221 231 #> [469,] 222 231 #> [470,] 223 230 #> [471,] 224 229 #> [472,] 225 228 #> [473,] 225 227 #> [474,] 225 226 #> [475,] 225 225 #> [476,] 226 224 #> [477,] 225 223 #> [478,] 225 222 #> [479,] 225 221 #> [480,] 226 220 #> [481,] 226 219 #> [482,] 226 218 #> [483,] 226 217 #> [484,] 226 216 #> [485,] 226 215 #> [486,] 226 214 #> [487,] 226 213 #> [488,] 226 212 #> [489,] 226 211 #> [490,] 227 211 #> [491,] 228 211 #> [492,] 229 210 #> [493,] 230 210 #> [494,] 231 210 #> [495,] 232 209 #> [496,] 233 209 #> [497,] 234 208 #> [498,] 235 208 #> [499,] 236 207 #> [500,] 237 207 #> [501,] 238 206 #> [502,] 238 205 #> [503,] 239 204 #> [504,] 240 203 #> [505,] 240 202 #> [506,] 241 201 #> [507,] 242 200 #> [508,] 243 199 #> [509,] 244 199 #> [510,] 245 199 #> [511,] 246 198 #> [512,] 247 198 #> [513,] 248 197 #> [514,] 249 196 #> [515,] 249 195 #> [516,] 250 194 #> [517,] 250 193 #> [518,] 249 192 #> [519,] 249 191 #> [520,] 249 190 #> [521,] 248 189 #> [522,] 248 188 #> [523,] 248 187 #> [524,] 247 186 #> [525,] 246 185 #> [526,] 245 184 #> [527,] 244 183 #> [528,] 243 182 #> [529,] 242 181 #> [530,] 241 180 #> [531,] 240 180 #> [532,] 239 179 #> [533,] 238 178 #> [534,] 237 178 #> [535,] 236 177 #> [536,] 235 176 #> [537,] 235 175 #> [538,] 235 174 #> [539,] 235 173 #> [540,] 235 172 #> [541,] 235 171 #> [542,] 235 170 #> [543,] 235 169 #> [544,] 236 168 #> [545,] 235 167 #> [546,] 236 166 #> [547,] 236 165 #> [548,] 236 164 #> [549,] 236 163 #> [550,] 236 162 #> [551,] 237 161 #> [552,] 236 160 #> [553,] 237 159 #> [554,] 237 158 #> [555,] 237 157 #> [556,] 237 156 #> [557,] 237 155 #> [558,] 237 154 #> [559,] 237 153 #> [560,] 238 152 #> [561,] 237 151 #> [562,] 237 150 #> [563,] 237 149 #> [564,] 237 148 #> [565,] 237 147 #> [566,] 238 146 #> [567,] 237 145 #> [568,] 237 144 #> [569,] 237 143 #> [570,] 237 142 #> [571,] 237 141 #> [572,] 237 140 #> [573,] 237 139 #> [574,] 237 138 #> [575,] 236 137 #> [576,] 236 136 #> [577,] 236 135 #> [578,] 235 134 #> [579,] 235 133 #> [580,] 235 132 #> [581,] 234 131 #> [582,] 234 130 #> [583,] 233 129 #> [584,] 232 128 #> [585,] 232 127 #> [586,] 231 126 #> [587,] 230 125 #> [588,] 230 124 #> [589,] 229 123 #> [590,] 228 122 #> [591,] 228 121 #> [592,] 227 120 #> [593,] 226 119 #> [594,] 226 118 #> [595,] 226 117 #> [596,] 225 116 #> [597,] 224 115 #> [598,] 224 114 #> [599,] 224 113 #> [600,] 223 112 #> [601,] 223 111 #> [602,] 223 110 #> [603,] 223 109 #> [604,] 222 108 #> [605,] 222 107 #> [606,] 222 106 #> [607,] 222 105 #> [608,] 222 104 #> [609,] 221 103 #> [610,] 221 102 #> [611,] 221 101 #> [612,] 221 100 #> [613,] 221 99 #> [614,] 221 98 #> [615,] 221 97 #> [616,] 221 96 #> [617,] 221 95 #> [618,] 221 94 #> [619,] 221 93 #> [620,] 221 92 #> [621,] 221 91 #> [622,] 221 90 #> [623,] 221 89 #> [624,] 221 88 #> [625,] 221 87 #> [626,] 221 86 #> [627,] 221 85 #> [628,] 221 84 #> [629,] 221 83 #> [630,] 221 82 #> [631,] 221 81 #> [632,] 221 80 #> [633,] 221 79 #> [634,] 221 78 #> [635,] 221 77 #> [636,] 221 76 #> [637,] 221 75 #> [638,] 221 74 #> [639,] 221 73 #> [640,] 221 72 #> [641,] 221 71 #> [642,] 221 70 #> [643,] 222 69 #> [644,] 222 68 #> [645,] 222 67 #> [646,] 222 66 #> [647,] 222 65 #> [648,] 222 64 #> [649,] 222 63 #> [650,] 223 62 #> [651,] 224 62 #> [652,] 225 61 #> [653,] 226 61 #> [654,] 227 61 #> [655,] 228 61 #> [656,] 229 60 #> [657,] 230 60 #> [658,] 231 60 #> [659,] 232 59 #> [660,] 232 58 #> [661,] 233 57 #> [662,] 232 56 #> [663,] 232 55 #> [664,] 231 54 #> [665,] 230 53 #> [666,] 229 52 #> [667,] 230 51 #> [668,] 229 50 #> [669,] 230 49 #> [670,] 229 48 #> [671,] 228 47 #> [672,] 227 46 #> [673,] 226 46 #> [674,] 225 45 #> [675,] 224 45 #> [676,] 223 45 #> [677,] 222 45 #> [678,] 221 45 #> [679,] 220 45 #> [680,] 219 45 #> [681,] 218 45 #> [682,] 217 45 #> [683,] 216 45 #> [684,] 215 46 #> [685,] 214 46 #> [686,] 213 47 #> [687,] 212 48 #> [688,] 211 49 #> [689,] 210 50 #> [690,] 209 51 #> [691,] 208 52 #> [692,] 208 53 #> [693,] 207 54 #> [694,] 206 55 #> [695,] 206 56 #> [696,] 205 57 #> [697,] 205 58 #> [698,] 204 59 #> [699,] 204 60 #> [700,] 203 61 #> [701,] 203 62 #> [702,] 203 63 #> [703,] 202 64 #> [704,] 202 65 #> [705,] 202 66 #> [706,] 201 66 #> [707,] 201 65 #> [708,] 201 64 #> [709,] 201 63 #> [710,] 200 62 #> #> $caney #> [,1] [,2] #> [1,] 200 75 #> [2,] 199 74 #> [3,] 199 73 #> [4,] 198 72 #> [5,] 197 71 #> [6,] 197 70 #> [7,] 196 69 #> [8,] 195 68 #> [9,] 194 67 #> [10,] 194 66 #> [11,] 193 65 #> [12,] 192 64 #> [13,] 192 63 #> [14,] 191 62 #> [15,] 190 61 #> [16,] 190 60 #> [17,] 189 59 #> [18,] 188 58 #> [19,] 188 57 #> [20,] 187 56 #> [21,] 187 55 #> [22,] 186 54 #> [23,] 185 53 #> [24,] 185 52 #> [25,] 184 51 #> [26,] 183 50 #> [27,] 183 49 #> [28,] 183 48 #> [29,] 182 47 #> [30,] 181 46 #> [31,] 180 46 #> [32,] 179 47 #> [33,] 179 48 #> [34,] 178 49 #> [35,] 177 50 #> [36,] 176 51 #> [37,] 175 52 #> [38,] 174 53 #> [39,] 173 54 #> [40,] 173 55 #> [41,] 172 56 #> [42,] 171 57 #> [43,] 170 58 #> [44,] 169 59 #> [45,] 168 60 #> [46,] 167 61 #> [47,] 166 62 #> [48,] 165 63 #> [49,] 164 64 #> [50,] 163 65 #> [51,] 162 66 #> [52,] 161 67 #> [53,] 160 68 #> [54,] 159 69 #> [55,] 158 70 #> [56,] 157 71 #> [57,] 156 72 #> [58,] 155 73 #> [59,] 154 74 #> [60,] 153 75 #> [61,] 152 76 #> [62,] 151 77 #> [63,] 150 78 #> [64,] 149 79 #> [65,] 148 80 #> [66,] 147 81 #> [67,] 146 82 #> [68,] 145 82 #> [69,] 144 83 #> [70,] 143 84 #> [71,] 142 85 #> [72,] 141 86 #> [73,] 140 87 #> [74,] 139 87 #> [75,] 138 88 #> [76,] 137 89 #> [77,] 136 90 #> [78,] 135 91 #> [79,] 134 91 #> [80,] 133 92 #> [81,] 132 93 #> [82,] 131 94 #> [83,] 130 94 #> [84,] 129 95 #> [85,] 128 96 #> [86,] 127 96 #> [87,] 126 97 #> [88,] 125 98 #> [89,] 124 98 #> [90,] 123 99 #> [91,] 122 100 #> [92,] 121 100 #> [93,] 120 101 #> [94,] 119 101 #> [95,] 118 102 #> [96,] 117 102 #> [97,] 116 103 #> [98,] 115 104 #> [99,] 114 104 #> [100,] 113 105 #> [101,] 112 105 #> [102,] 111 106 #> [103,] 110 106 #> [104,] 109 107 #> [105,] 108 107 #> [106,] 107 107 #> [107,] 106 108 #> [108,] 105 108 #> [109,] 104 109 #> [110,] 105 110 #> [111,] 106 111 #> [112,] 107 111 #> [113,] 108 112 #> [114,] 109 113 #> [115,] 110 113 #> [116,] 111 114 #> [117,] 112 114 #> [118,] 113 115 #> [119,] 114 116 #> [120,] 115 116 #> [121,] 116 117 #> [122,] 117 117 #> [123,] 118 118 #> [124,] 119 119 #> [125,] 120 119 #> [126,] 121 120 #> [127,] 122 120 #> [128,] 123 121 #> [129,] 124 122 #> [130,] 125 122 #> [131,] 126 123 #> [132,] 127 123 #> [133,] 128 124 #> [134,] 129 125 #> [135,] 130 125 #> [136,] 131 126 #> [137,] 132 127 #> [138,] 133 127 #> [139,] 134 128 #> [140,] 135 128 #> [141,] 136 129 #> [142,] 137 130 #> [143,] 138 130 #> [144,] 139 131 #> [145,] 140 131 #> [146,] 141 132 #> [147,] 142 133 #> [148,] 143 133 #> [149,] 144 134 #> [150,] 145 134 #> [151,] 146 135 #> [152,] 147 136 #> [153,] 148 136 #> [154,] 149 137 #> [155,] 150 138 #> [156,] 151 138 #> [157,] 152 139 #> [158,] 153 139 #> [159,] 154 139 #> [160,] 155 138 #> [161,] 155 137 #> [162,] 156 136 #> [163,] 156 135 #> [164,] 157 134 #> [165,] 157 133 #> [166,] 158 132 #> [167,] 158 131 #> [168,] 159 130 #> [169,] 159 129 #> [170,] 160 128 #> [171,] 160 127 #> [172,] 161 126 #> [173,] 161 125 #> [174,] 162 124 #> [175,] 162 123 #> [176,] 163 122 #> [177,] 163 121 #> [178,] 164 120 #> [179,] 164 119 #> [180,] 165 118 #> [181,] 166 117 #> [182,] 166 116 #> [183,] 167 115 #> [184,] 167 114 #> [185,] 168 113 #> [186,] 168 112 #> [187,] 169 111 #> [188,] 169 110 #> [189,] 170 109 #> [190,] 170 108 #> [191,] 171 107 #> [192,] 171 106 #> [193,] 172 105 #> [194,] 172 104 #> [195,] 173 103 #> [196,] 173 102 #> [197,] 174 101 #> [198,] 174 100 #> [199,] 175 99 #> [200,] 175 98 #> [201,] 176 97 #> [202,] 176 96 #> [203,] 177 95 #> [204,] 177 94 #> [205,] 178 94 #> [206,] 178 95 #> [207,] 179 96 #> [208,] 179 97 #> [209,] 180 98 #> [210,] 180 99 #> [211,] 181 100 #> [212,] 181 101 #> [213,] 182 102 #> [214,] 182 103 #> [215,] 183 104 #> [216,] 183 105 #> [217,] 184 106 #> [218,] 184 107 #> [219,] 184 108 #> [220,] 185 109 #> [221,] 186 110 #> [222,] 186 111 #> [223,] 187 112 #> [224,] 187 113 #> [225,] 187 114 #> [226,] 188 115 #> [227,] 189 116 #> [228,] 189 117 #> [229,] 190 118 #> [230,] 190 119 #> [231,] 190 120 #> [232,] 191 121 #> [233,] 192 122 #> [234,] 192 123 #> [235,] 193 124 #> [236,] 193 125 #> [237,] 194 126 #> [238,] 195 127 #> [239,] 195 128 #> [240,] 195 129 #> [241,] 196 130 #> [242,] 197 131 #> [243,] 197 132 #> [244,] 198 133 #> [245,] 199 134 #> [246,] 199 135 #> [247,] 200 136 #> [248,] 200 137 #> [249,] 201 138 #> [250,] 201 139 #> [251,] 202 140 #> [252,] 203 141 #> [253,] 203 142 #> [254,] 204 143 #> [255,] 204 144 #> [256,] 205 145 #> [257,] 206 146 #> [258,] 207 147 #> [259,] 207 148 #> [260,] 208 149 #> [261,] 209 150 #> [262,] 209 151 #> [263,] 210 152 #> [264,] 211 153 #> [265,] 211 154 #> [266,] 212 155 #> [267,] 213 156 #> [268,] 213 157 #> [269,] 214 158 #> [270,] 215 159 #> [271,] 215 160 #> [272,] 216 161 #> [273,] 217 162 #> [274,] 218 163 #> [275,] 218 164 #> [276,] 219 165 #> [277,] 220 166 #> [278,] 221 167 #> [279,] 221 168 #> [280,] 222 169 #> [281,] 223 170 #> [282,] 224 171 #> [283,] 224 172 #> [284,] 225 173 #> [285,] 226 174 #> [286,] 227 175 #> [287,] 228 176 #> [288,] 229 177 #> [289,] 229 178 #> [290,] 230 179 #> [291,] 231 180 #> [292,] 232 181 #> [293,] 233 182 #> [294,] 234 183 #> [295,] 235 184 #> [296,] 235 185 #> [297,] 236 186 #> [298,] 237 187 #> [299,] 238 188 #> [300,] 239 189 #> [301,] 240 190 #> [302,] 241 191 #> [303,] 242 192 #> [304,] 243 193 #> [305,] 244 194 #> [306,] 245 195 #> [307,] 246 196 #> [308,] 247 197 #> [309,] 248 198 #> [310,] 249 198 #> [311,] 250 199 #> [312,] 251 200 #> [313,] 252 201 #> [314,] 253 202 #> [315,] 254 203 #> [316,] 255 204 #> [317,] 256 205 #> [318,] 257 205 #> [319,] 258 206 #> [320,] 259 207 #> [321,] 260 208 #> [322,] 261 208 #> [323,] 262 209 #> [324,] 263 210 #> [325,] 264 211 #> [326,] 265 211 #> [327,] 266 212 #> [328,] 267 213 #> [329,] 268 213 #> [330,] 269 214 #> [331,] 270 214 #> [332,] 271 215 #> [333,] 272 216 #> [334,] 273 216 #> [335,] 274 217 #> [336,] 275 217 #> [337,] 276 218 #> [338,] 277 219 #> [339,] 278 219 #> [340,] 279 218 #> [341,] 279 217 #> [342,] 279 216 #> [343,] 279 215 #> [344,] 278 214 #> [345,] 278 213 #> [346,] 278 212 #> [347,] 279 211 #> [348,] 278 210 #> [349,] 278 209 #> [350,] 278 208 #> [351,] 278 207 #> [352,] 278 206 #> [353,] 278 205 #> [354,] 277 204 #> [355,] 277 203 #> [356,] 278 202 #> [357,] 277 201 #> [358,] 277 200 #> [359,] 277 199 #> [360,] 277 198 #> [361,] 277 197 #> [362,] 277 196 #> [363,] 276 195 #> [364,] 276 194 #> [365,] 276 193 #> [366,] 277 192 #> [367,] 277 191 #> [368,] 276 190 #> [369,] 276 189 #> [370,] 276 188 #> [371,] 276 187 #> [372,] 276 186 #> [373,] 276 185 #> [374,] 276 184 #> [375,] 276 183 #> [376,] 276 182 #> [377,] 276 181 #> [378,] 276 180 #> [379,] 276 179 #> [380,] 276 178 #> [381,] 276 177 #> [382,] 276 176 #> [383,] 277 175 #> [384,] 276 174 #> [385,] 276 173 #> [386,] 277 172 #> [387,] 277 171 #> [388,] 277 170 #> [389,] 277 169 #> [390,] 277 168 #> [391,] 277 167 #> [392,] 278 166 #> [393,] 278 165 #> [394,] 278 164 #> [395,] 278 163 #> [396,] 279 162 #> [397,] 279 161 #> [398,] 279 160 #> [399,] 280 159 #> [400,] 280 158 #> [401,] 280 157 #> [402,] 281 156 #> [403,] 281 155 #> [404,] 282 154 #> [405,] 282 153 #> [406,] 281 152 #> [407,] 280 152 #> [408,] 279 152 #> [409,] 278 151 #> [410,] 277 151 #> [411,] 276 150 #> [412,] 275 150 #> [413,] 274 150 #> [414,] 273 149 #> [415,] 272 148 #> [416,] 271 148 #> [417,] 270 147 #> [418,] 269 146 #> [419,] 268 146 #> [420,] 267 145 #> [421,] 266 145 #> [422,] 265 144 #> [423,] 264 143 #> [424,] 263 142 #> [425,] 262 142 #> [426,] 261 141 #> [427,] 260 140 #> [428,] 259 139 #> [429,] 258 139 #> [430,] 257 138 #> [431,] 256 137 #> [432,] 255 136 #> [433,] 254 135 #> [434,] 253 134 #> [435,] 252 133 #> [436,] 251 133 #> [437,] 250 132 #> [438,] 249 131 #> [439,] 248 130 #> [440,] 247 129 #> [441,] 246 128 #> [442,] 245 127 #> [443,] 244 126 #> [444,] 243 125 #> [445,] 242 124 #> [446,] 241 123 #> [447,] 240 122 #> [448,] 239 121 #> [449,] 238 120 #> [450,] 237 119 #> [451,] 236 118 #> [452,] 235 117 #> [453,] 234 116 #> [454,] 233 115 #> [455,] 232 114 #> [456,] 231 113 #> [457,] 231 112 #> [458,] 230 111 #> [459,] 229 110 #> [460,] 228 109 #> [461,] 227 108 #> [462,] 226 107 #> [463,] 225 106 #> [464,] 224 105 #> [465,] 223 104 #> [466,] 223 103 #> [467,] 222 102 #> [468,] 221 101 #> [469,] 220 100 #> [470,] 219 99 #> [471,] 218 98 #> [472,] 218 97 #> [473,] 217 96 #> [474,] 216 95 #> [475,] 215 94 #> [476,] 214 93 #> [477,] 213 92 #> [478,] 213 91 #> [479,] 212 90 #> [480,] 211 89 #> [481,] 210 88 #> [482,] 209 87 #> [483,] 209 86 #> [484,] 208 85 #> [485,] 207 84 #> [486,] 206 83 #> [487,] 205 82 #> [488,] 205 81 #> [489,] 204 80 #> [490,] 203 79 #> [491,] 202 78 #> [492,] 202 77 #> [493,] 201 76 #> [494,] 200 75 #> #> $chimay #> [,1] [,2] #> [1,] 200 76 #> [2,] 200 75 #> [3,] 199 74 #> [4,] 198 73 #> [5,] 198 72 #> [6,] 197 71 #> [7,] 197 70 #> [8,] 196 69 #> [9,] 195 68 #> [10,] 195 67 #> [11,] 194 66 #> [12,] 194 65 #> [13,] 193 64 #> [14,] 192 63 #> [15,] 192 62 #> [16,] 191 61 #> [17,] 190 60 #> [18,] 190 59 #> [19,] 189 58 #> [20,] 189 57 #> [21,] 188 56 #> [22,] 187 55 #> [23,] 187 54 #> [24,] 186 53 #> [25,] 186 52 #> [26,] 185 51 #> [27,] 184 50 #> [28,] 184 49 #> [29,] 183 48 #> [30,] 183 47 #> [31,] 182 46 #> [32,] 181 45 #> [33,] 181 44 #> [34,] 181 43 #> [35,] 180 42 #> [36,] 179 41 #> [37,] 179 40 #> [38,] 178 39 #> [39,] 177 38 #> [40,] 176 37 #> [41,] 175 37 #> [42,] 174 37 #> [43,] 173 37 #> [44,] 172 37 #> [45,] 171 37 #> [46,] 170 37 #> [47,] 169 37 #> [48,] 168 37 #> [49,] 167 37 #> [50,] 166 37 #> [51,] 165 37 #> [52,] 164 37 #> [53,] 163 37 #> [54,] 162 37 #> [55,] 161 37 #> [56,] 160 37 #> [57,] 159 37 #> [58,] 158 37 #> [59,] 157 37 #> [60,] 156 37 #> [61,] 155 37 #> [62,] 154 37 #> [63,] 153 37 #> [64,] 152 37 #> [65,] 151 37 #> [66,] 150 37 #> [67,] 149 37 #> [68,] 148 37 #> [69,] 147 37 #> [70,] 146 37 #> [71,] 145 37 #> [72,] 144 37 #> [73,] 143 37 #> [74,] 142 37 #> [75,] 141 37 #> [76,] 140 37 #> [77,] 139 37 #> [78,] 138 37 #> [79,] 137 37 #> [80,] 136 37 #> [81,] 135 37 #> [82,] 134 37 #> [83,] 133 37 #> [84,] 132 37 #> [85,] 131 37 #> [86,] 130 37 #> [87,] 129 37 #> [88,] 128 37 #> [89,] 127 37 #> [90,] 126 37 #> [91,] 125 37 #> [92,] 124 37 #> [93,] 123 37 #> [94,] 122 37 #> [95,] 121 37 #> [96,] 120 37 #> [97,] 119 37 #> [98,] 118 37 #> [99,] 117 37 #> [100,] 116 37 #> [101,] 115 37 #> [102,] 114 37 #> [103,] 113 37 #> [104,] 112 37 #> [105,] 111 37 #> [106,] 110 37 #> [107,] 109 37 #> [108,] 108 37 #> [109,] 107 37 #> [110,] 106 37 #> [111,] 105 37 #> [112,] 104 37 #> [113,] 103 37 #> [114,] 102 38 #> [115,] 103 39 #> [116,] 103 40 #> [117,] 104 41 #> [118,] 104 42 #> [119,] 105 43 #> [120,] 106 44 #> [121,] 106 45 #> [122,] 107 46 #> [123,] 107 47 #> [124,] 108 48 #> [125,] 108 49 #> [126,] 109 50 #> [127,] 110 51 #> [128,] 110 52 #> [129,] 111 53 #> [130,] 111 54 #> [131,] 112 55 #> [132,] 113 56 #> [133,] 113 57 #> [134,] 113 58 #> [135,] 114 59 #> [136,] 115 60 #> [137,] 115 61 #> [138,] 116 62 #> [139,] 117 63 #> [140,] 117 64 #> [141,] 117 65 #> [142,] 118 66 #> [143,] 119 67 #> [144,] 119 68 #> [145,] 120 69 #> [146,] 121 70 #> [147,] 121 71 #> [148,] 121 72 #> [149,] 122 73 #> [150,] 123 74 #> [151,] 123 75 #> [152,] 124 76 #> [153,] 125 77 #> [154,] 125 78 #> [155,] 126 79 #> [156,] 126 80 #> [157,] 127 81 #> [158,] 127 82 #> [159,] 128 83 #> [160,] 129 84 #> [161,] 129 85 #> [162,] 130 86 #> [163,] 130 87 #> [164,] 131 88 #> [165,] 131 89 #> [166,] 132 90 #> [167,] 132 91 #> [168,] 133 92 #> [169,] 134 93 #> [170,] 134 94 #> [171,] 135 95 #> [172,] 136 96 #> [173,] 136 97 #> [174,] 136 98 #> [175,] 137 99 #> [176,] 138 100 #> [177,] 138 101 #> [178,] 139 102 #> [179,] 140 103 #> [180,] 140 104 #> [181,] 140 105 #> [182,] 141 106 #> [183,] 142 107 #> [184,] 142 108 #> [185,] 143 109 #> [186,] 144 110 #> [187,] 144 111 #> [188,] 145 112 #> [189,] 145 113 #> [190,] 146 114 #> [191,] 146 115 #> [192,] 147 116 #> [193,] 148 117 #> [194,] 148 118 #> [195,] 149 119 #> [196,] 149 120 #> [197,] 150 121 #> [198,] 150 122 #> [199,] 151 123 #> [200,] 151 124 #> [201,] 152 125 #> [202,] 153 126 #> [203,] 153 127 #> [204,] 152 128 #> [205,] 151 129 #> [206,] 151 130 #> [207,] 150 131 #> [208,] 149 132 #> [209,] 149 133 #> [210,] 149 134 #> [211,] 148 135 #> [212,] 147 136 #> [213,] 147 137 #> [214,] 146 138 #> [215,] 145 139 #> [216,] 145 140 #> [217,] 145 141 #> [218,] 144 142 #> [219,] 143 143 #> [220,] 143 144 #> [221,] 142 145 #> [222,] 141 146 #> [223,] 141 147 #> [224,] 141 148 #> [225,] 140 149 #> [226,] 139 150 #> [227,] 139 151 #> [228,] 138 152 #> [229,] 137 153 #> [230,] 137 154 #> [231,] 137 155 #> [232,] 136 156 #> [233,] 135 157 #> [234,] 135 158 #> [235,] 134 159 #> [236,] 133 160 #> [237,] 133 161 #> [238,] 133 162 #> [239,] 132 163 #> [240,] 131 164 #> [241,] 131 165 #> [242,] 130 166 #> [243,] 129 167 #> [244,] 129 168 #> [245,] 129 169 #> [246,] 128 170 #> [247,] 127 171 #> [248,] 127 172 #> [249,] 126 173 #> [250,] 125 174 #> [251,] 125 175 #> [252,] 125 176 #> [253,] 124 177 #> [254,] 123 178 #> [255,] 123 179 #> [256,] 122 180 #> [257,] 121 181 #> [258,] 121 182 #> [259,] 121 183 #> [260,] 120 184 #> [261,] 119 185 #> [262,] 119 186 #> [263,] 118 187 #> [264,] 117 188 #> [265,] 117 189 #> [266,] 117 190 #> [267,] 116 191 #> [268,] 115 192 #> [269,] 115 193 #> [270,] 114 194 #> [271,] 113 195 #> [272,] 113 196 #> [273,] 113 197 #> [274,] 112 198 #> [275,] 111 199 #> [276,] 111 200 #> [277,] 110 201 #> [278,] 109 202 #> [279,] 109 203 #> [280,] 109 204 #> [281,] 108 205 #> [282,] 107 206 #> [283,] 107 207 #> [284,] 106 208 #> [285,] 105 209 #> [286,] 105 210 #> [287,] 105 211 #> [288,] 106 212 #> [289,] 107 212 #> [290,] 108 212 #> [291,] 109 212 #> [292,] 110 212 #> [293,] 111 212 #> [294,] 112 212 #> [295,] 113 212 #> [296,] 114 212 #> [297,] 115 212 #> [298,] 116 212 #> [299,] 117 212 #> [300,] 118 212 #> [301,] 119 212 #> [302,] 120 212 #> [303,] 121 212 #> [304,] 122 212 #> [305,] 123 212 #> [306,] 124 212 #> [307,] 125 212 #> [308,] 126 212 #> [309,] 127 212 #> [310,] 128 212 #> [311,] 129 212 #> [312,] 130 212 #> [313,] 131 212 #> [314,] 132 212 #> [315,] 133 212 #> [316,] 134 212 #> [317,] 135 212 #> [318,] 136 212 #> [319,] 137 212 #> [320,] 138 212 #> [321,] 139 212 #> [322,] 140 212 #> [323,] 141 212 #> [324,] 142 212 #> [325,] 143 212 #> [326,] 144 212 #> [327,] 145 212 #> [328,] 146 212 #> [329,] 147 212 #> [330,] 148 212 #> [331,] 149 212 #> [332,] 150 212 #> [333,] 151 212 #> [334,] 152 212 #> [335,] 153 212 #> [336,] 154 212 #> [337,] 155 212 #> [338,] 156 212 #> [339,] 157 212 #> [340,] 158 212 #> [341,] 159 212 #> [342,] 160 212 #> [343,] 161 212 #> [344,] 162 212 #> [345,] 163 212 #> [346,] 164 212 #> [347,] 165 212 #> [348,] 166 212 #> [349,] 167 212 #> [350,] 168 212 #> [351,] 169 212 #> [352,] 170 212 #> [353,] 171 212 #> [354,] 172 212 #> [355,] 173 212 #> [356,] 174 212 #> [357,] 175 212 #> [358,] 176 212 #> [359,] 177 212 #> [360,] 178 212 #> [361,] 179 212 #> [362,] 180 211 #> [363,] 181 210 #> [364,] 181 209 #> [365,] 182 208 #> [366,] 182 207 #> [367,] 183 206 #> [368,] 184 205 #> [369,] 184 204 #> [370,] 185 203 #> [371,] 186 202 #> [372,] 186 201 #> [373,] 187 200 #> [374,] 188 199 #> [375,] 188 198 #> [376,] 189 197 #> [377,] 189 196 #> [378,] 190 195 #> [379,] 191 194 #> [380,] 191 193 #> [381,] 192 192 #> [382,] 192 191 #> [383,] 193 190 #> [384,] 194 189 #> [385,] 194 188 #> [386,] 195 187 #> [387,] 195 186 #> [388,] 196 185 #> [389,] 197 184 #> [390,] 197 183 #> [391,] 198 182 #> [392,] 198 181 #> [393,] 199 180 #> [394,] 200 179 #> [395,] 200 178 #> [396,] 201 177 #> [397,] 201 176 #> [398,] 202 175 #> [399,] 203 174 #> [400,] 203 173 #> [401,] 204 173 #> [402,] 204 174 #> [403,] 205 175 #> [404,] 205 176 #> [405,] 206 177 #> [406,] 206 178 #> [407,] 207 179 #> [408,] 207 180 #> [409,] 208 181 #> [410,] 209 182 #> [411,] 209 183 #> [412,] 210 184 #> [413,] 211 185 #> [414,] 211 186 #> [415,] 212 187 #> [416,] 212 188 #> [417,] 213 189 #> [418,] 214 190 #> [419,] 214 191 #> [420,] 214 192 #> [421,] 215 193 #> [422,] 216 194 #> [423,] 216 195 #> [424,] 217 196 #> [425,] 217 197 #> [426,] 218 198 #> [427,] 219 199 #> [428,] 219 200 #> [429,] 220 201 #> [430,] 221 202 #> [431,] 221 203 #> [432,] 222 204 #> [433,] 222 205 #> [434,] 223 206 #> [435,] 224 207 #> [436,] 224 208 #> [437,] 224 209 #> [438,] 225 210 #> [439,] 226 211 #> [440,] 227 212 #> [441,] 228 212 #> [442,] 229 212 #> [443,] 230 212 #> [444,] 231 212 #> [445,] 232 212 #> [446,] 233 212 #> [447,] 234 212 #> [448,] 235 212 #> [449,] 236 212 #> [450,] 237 212 #> [451,] 238 212 #> [452,] 239 212 #> [453,] 240 212 #> [454,] 241 212 #> [455,] 242 212 #> [456,] 243 212 #> [457,] 244 212 #> [458,] 245 212 #> [459,] 246 212 #> [460,] 247 212 #> [461,] 248 212 #> [462,] 249 212 #> [463,] 250 212 #> [464,] 251 212 #> [465,] 252 212 #> [466,] 253 212 #> [467,] 254 212 #> [468,] 255 212 #> [469,] 256 212 #> [470,] 257 212 #> [471,] 258 212 #> [472,] 259 212 #> [473,] 260 212 #> [474,] 261 212 #> [475,] 262 212 #> [476,] 263 212 #> [477,] 264 212 #> [478,] 265 212 #> [479,] 266 212 #> [480,] 267 212 #> [481,] 268 212 #> [482,] 269 212 #> [483,] 270 212 #> [484,] 271 212 #> [485,] 272 212 #> [486,] 273 212 #> [487,] 274 212 #> [488,] 275 212 #> [489,] 276 212 #> [490,] 277 212 #> [491,] 278 212 #> [492,] 279 212 #> [493,] 280 212 #> [494,] 281 212 #> [495,] 282 212 #> [496,] 283 212 #> [497,] 284 212 #> [498,] 285 212 #> [499,] 286 212 #> [500,] 287 212 #> [501,] 288 212 #> [502,] 289 212 #> [503,] 290 212 #> [504,] 291 212 #> [505,] 292 212 #> [506,] 293 212 #> [507,] 294 212 #> [508,] 295 212 #> [509,] 296 212 #> [510,] 297 212 #> [511,] 298 212 #> [512,] 299 212 #> [513,] 300 211 #> [514,] 299 210 #> [515,] 299 209 #> [516,] 298 208 #> [517,] 297 207 #> [518,] 297 206 #> [519,] 297 205 #> [520,] 296 204 #> [521,] 295 203 #> [522,] 295 202 #> [523,] 294 201 #> [524,] 293 200 #> [525,] 293 199 #> [526,] 292 198 #> [527,] 292 197 #> [528,] 291 196 #> [529,] 291 195 #> [530,] 290 194 #> [531,] 289 193 #> [532,] 289 192 #> [533,] 288 191 #> [534,] 288 190 #> [535,] 287 189 #> [536,] 287 188 #> [537,] 286 187 #> [538,] 285 186 #> [539,] 285 185 #> [540,] 284 184 #> [541,] 284 183 #> [542,] 283 182 #> [543,] 282 181 #> [544,] 282 180 #> [545,] 282 179 #> [546,] 281 178 #> [547,] 280 177 #> [548,] 280 176 #> [549,] 279 175 #> [550,] 278 174 #> [551,] 278 173 #> [552,] 278 172 #> [553,] 277 171 #> [554,] 276 170 #> [555,] 276 169 #> [556,] 275 168 #> [557,] 274 167 #> [558,] 274 166 #> [559,] 274 165 #> [560,] 273 164 #> [561,] 272 163 #> [562,] 272 162 #> [563,] 271 161 #> [564,] 270 160 #> [565,] 270 159 #> [566,] 269 158 #> [567,] 269 157 #> [568,] 268 156 #> [569,] 268 155 #> [570,] 267 154 #> [571,] 266 153 #> [572,] 266 152 #> [573,] 265 151 #> [574,] 265 150 #> [575,] 264 149 #> [576,] 264 148 #> [577,] 263 147 #> [578,] 262 146 #> [579,] 262 145 #> [580,] 261 144 #> [581,] 261 143 #> [582,] 260 142 #> [583,] 259 141 #> [584,] 259 140 #> [585,] 259 139 #> [586,] 258 138 #> [587,] 257 137 #> [588,] 257 136 #> [589,] 256 135 #> [590,] 255 134 #> [591,] 255 133 #> [592,] 255 132 #> [593,] 254 131 #> [594,] 253 130 #> [595,] 253 129 #> [596,] 252 128 #> [597,] 251 127 #> [598,] 251 126 #> [599,] 252 125 #> [600,] 253 124 #> [601,] 253 123 #> [602,] 253 122 #> [603,] 254 121 #> [604,] 255 120 #> [605,] 255 119 #> [606,] 256 118 #> [607,] 257 117 #> [608,] 257 116 #> [609,] 257 115 #> [610,] 258 114 #> [611,] 259 113 #> [612,] 259 112 #> [613,] 260 111 #> [614,] 260 110 #> [615,] 261 109 #> [616,] 262 108 #> [617,] 262 107 #> [618,] 263 106 #> [619,] 263 105 #> [620,] 264 104 #> [621,] 264 103 #> [622,] 265 102 #> [623,] 266 101 #> [624,] 266 100 #> [625,] 267 99 #> [626,] 267 98 #> [627,] 268 97 #> [628,] 268 96 #> [629,] 269 95 #> [630,] 270 94 #> [631,] 270 93 #> [632,] 271 92 #> [633,] 272 91 #> [634,] 272 90 #> [635,] 272 89 #> [636,] 273 88 #> [637,] 274 87 #> [638,] 274 86 #> [639,] 275 85 #> [640,] 276 84 #> [641,] 276 83 #> [642,] 276 82 #> [643,] 277 81 #> [644,] 278 80 #> [645,] 278 79 #> [646,] 279 78 #> [647,] 279 77 #> [648,] 280 76 #> [649,] 281 75 #> [650,] 281 74 #> [651,] 282 73 #> [652,] 282 72 #> [653,] 283 71 #> [654,] 283 70 #> [655,] 284 69 #> [656,] 285 68 #> [657,] 285 67 #> [658,] 286 66 #> [659,] 286 65 #> [660,] 287 64 #> [661,] 287 63 #> [662,] 288 62 #> [663,] 289 61 #> [664,] 289 60 #> [665,] 290 59 #> [666,] 291 58 #> [667,] 291 57 #> [668,] 291 56 #> [669,] 292 55 #> [670,] 293 54 #> [671,] 293 53 #> [672,] 294 52 #> [673,] 295 51 #> [674,] 295 50 #> [675,] 295 49 #> [676,] 296 48 #> [677,] 297 47 #> [678,] 297 46 #> [679,] 298 45 #> [680,] 299 44 #> [681,] 299 43 #> [682,] 300 42 #> [683,] 300 41 #> [684,] 301 40 #> [685,] 301 39 #> [686,] 302 38 #> [687,] 301 37 #> [688,] 300 37 #> [689,] 299 37 #> [690,] 298 37 #> [691,] 297 37 #> [692,] 296 37 #> [693,] 295 37 #> [694,] 294 37 #> [695,] 293 37 #> [696,] 292 37 #> [697,] 291 37 #> [698,] 290 37 #> [699,] 289 37 #> [700,] 288 37 #> [701,] 287 37 #> [702,] 286 37 #> [703,] 285 37 #> [704,] 284 37 #> [705,] 283 37 #> [706,] 282 37 #> [707,] 281 37 #> [708,] 280 37 #> [709,] 279 37 #> [710,] 278 37 #> [711,] 277 37 #> [712,] 276 37 #> [713,] 275 37 #> [714,] 274 37 #> [715,] 273 37 #> [716,] 272 37 #> [717,] 271 37 #> [718,] 270 37 #> [719,] 269 37 #> [720,] 268 37 #> [721,] 267 37 #> [722,] 266 37 #> [723,] 265 37 #> [724,] 264 37 #> [725,] 263 37 #> [726,] 262 37 #> [727,] 261 37 #> [728,] 260 37 #> [729,] 259 37 #> [730,] 258 37 #> [731,] 257 37 #> [732,] 256 37 #> [733,] 255 37 #> [734,] 254 37 #> [735,] 253 37 #> [736,] 252 37 #> [737,] 251 37 #> [738,] 250 37 #> [739,] 249 37 #> [740,] 248 37 #> [741,] 247 37 #> [742,] 246 37 #> [743,] 245 37 #> [744,] 244 37 #> [745,] 243 37 #> [746,] 242 37 #> [747,] 241 37 #> [748,] 240 37 #> [749,] 239 37 #> [750,] 238 37 #> [751,] 237 37 #> [752,] 236 37 #> [753,] 235 37 #> [754,] 234 37 #> [755,] 233 37 #> [756,] 232 37 #> [757,] 231 37 #> [758,] 230 37 #> [759,] 229 37 #> [760,] 228 37 #> [761,] 227 37 #> [762,] 226 37 #> [763,] 225 38 #> [764,] 225 39 #> [765,] 224 40 #> [766,] 224 41 #> [767,] 223 42 #> [768,] 222 43 #> [769,] 222 44 #> [770,] 221 45 #> [771,] 221 46 #> [772,] 220 47 #> [773,] 219 48 #> [774,] 219 49 #> [775,] 218 50 #> [776,] 218 51 #> [777,] 217 52 #> [778,] 216 53 #> [779,] 216 54 #> [780,] 215 55 #> [781,] 214 56 #> [782,] 214 57 #> [783,] 213 58 #> [784,] 213 59 #> [785,] 212 60 #> [786,] 211 61 #> [787,] 211 62 #> [788,] 210 63 #> [789,] 210 64 #> [790,] 209 65 #> [791,] 208 66 #> [792,] 208 67 #> [793,] 207 68 #> [794,] 207 69 #> [795,] 206 70 #> [796,] 205 71 #> [797,] 205 72 #> [798,] 205 73 #> [799,] 204 74 #> [800,] 203 75 #> [801,] 203 76 #> [802,] 202 77 #> [803,] 202 78 #> [804,] 201 78 #> [805,] 201 77 #> [806,] 200 76 #> #> $corona #> [,1] [,2] #> [1,] 200 106 #> [2,] 199 105 #> [3,] 198 105 #> [4,] 197 106 #> [5,] 196 105 #> [6,] 195 105 #> [7,] 194 105 #> [8,] 193 106 #> [9,] 192 106 #> [10,] 191 106 #> [11,] 190 106 #> [12,] 189 106 #> [13,] 188 106 #> [14,] 187 106 #> [15,] 186 106 #> [16,] 185 106 #> [17,] 184 106 #> [18,] 183 106 #> [19,] 182 106 #> [20,] 181 106 #> [21,] 180 106 #> [22,] 179 106 #> [23,] 178 106 #> [24,] 177 107 #> [25,] 176 107 #> [26,] 175 107 #> [27,] 174 107 #> [28,] 173 107 #> [29,] 172 107 #> [30,] 171 107 #> [31,] 170 107 #> [32,] 169 107 #> [33,] 168 108 #> [34,] 167 108 #> [35,] 166 108 #> [36,] 165 108 #> [37,] 164 108 #> [38,] 163 107 #> [39,] 162 107 #> [40,] 161 106 #> [41,] 160 105 #> [42,] 160 104 #> [43,] 159 103 #> [44,] 158 102 #> [45,] 157 101 #> [46,] 156 100 #> [47,] 156 99 #> [48,] 155 98 #> [49,] 154 97 #> [50,] 153 96 #> [51,] 153 95 #> [52,] 152 94 #> [53,] 151 93 #> [54,] 150 92 #> [55,] 149 91 #> [56,] 148 90 #> [57,] 147 89 #> [58,] 146 88 #> [59,] 145 87 #> [60,] 144 86 #> [61,] 143 85 #> [62,] 142 85 #> [63,] 141 84 #> [64,] 140 83 #> [65,] 139 83 #> [66,] 138 82 #> [67,] 137 81 #> [68,] 136 80 #> [69,] 135 79 #> [70,] 134 79 #> [71,] 133 78 #> [72,] 132 77 #> [73,] 131 76 #> [74,] 130 75 #> [75,] 129 74 #> [76,] 128 73 #> [77,] 128 72 #> [78,] 127 71 #> [79,] 126 70 #> [80,] 125 69 #> [81,] 125 68 #> [82,] 124 67 #> [83,] 124 66 #> [84,] 124 65 #> [85,] 123 64 #> [86,] 123 63 #> [87,] 123 62 #> [88,] 123 61 #> [89,] 122 60 #> [90,] 122 59 #> [91,] 122 58 #> [92,] 122 57 #> [93,] 122 56 #> [94,] 123 55 #> [95,] 124 54 #> [96,] 125 53 #> [97,] 126 52 #> [98,] 127 52 #> [99,] 128 51 #> [100,] 129 50 #> [101,] 129 49 #> [102,] 129 48 #> [103,] 128 47 #> [104,] 127 46 #> [105,] 126 46 #> [106,] 125 45 #> [107,] 124 45 #> [108,] 123 45 #> [109,] 122 45 #> [110,] 121 45 #> [111,] 120 45 #> [112,] 119 45 #> [113,] 118 45 #> [114,] 117 45 #> [115,] 116 45 #> [116,] 115 45 #> [117,] 114 45 #> [118,] 113 46 #> [119,] 112 46 #> [120,] 111 47 #> [121,] 110 48 #> [122,] 110 49 #> [123,] 110 50 #> [124,] 109 51 #> [125,] 109 52 #> [126,] 109 53 #> [127,] 109 54 #> [128,] 109 55 #> [129,] 109 56 #> [130,] 109 57 #> [131,] 109 58 #> [132,] 109 59 #> [133,] 109 60 #> [134,] 109 61 #> [135,] 109 62 #> [136,] 109 63 #> [137,] 109 64 #> [138,] 109 65 #> [139,] 109 66 #> [140,] 109 67 #> [141,] 109 68 #> [142,] 109 69 #> [143,] 109 70 #> [144,] 109 71 #> [145,] 109 72 #> [146,] 109 73 #> [147,] 109 74 #> [148,] 109 75 #> [149,] 109 76 #> [150,] 109 77 #> [151,] 109 78 #> [152,] 110 79 #> [153,] 111 80 #> [154,] 112 81 #> [155,] 113 82 #> [156,] 114 83 #> [157,] 115 84 #> [158,] 116 85 #> [159,] 117 86 #> [160,] 118 87 #> [161,] 119 88 #> [162,] 120 89 #> [163,] 121 90 #> [164,] 122 91 #> [165,] 122 92 #> [166,] 123 93 #> [167,] 124 94 #> [168,] 125 95 #> [169,] 125 96 #> [170,] 125 97 #> [171,] 126 98 #> [172,] 125 99 #> [173,] 126 100 #> [174,] 126 101 #> [175,] 125 101 #> [176,] 125 100 #> [177,] 124 99 #> [178,] 124 98 #> [179,] 123 97 #> [180,] 123 96 #> [181,] 122 95 #> [182,] 121 94 #> [183,] 120 93 #> [184,] 119 92 #> [185,] 118 91 #> [186,] 117 90 #> [187,] 116 89 #> [188,] 115 88 #> [189,] 114 87 #> [190,] 113 87 #> [191,] 112 86 #> [192,] 111 85 #> [193,] 110 85 #> [194,] 109 84 #> [195,] 108 84 #> [196,] 107 84 #> [197,] 106 83 #> [198,] 105 83 #> [199,] 104 82 #> [200,] 103 83 #> [201,] 103 84 #> [202,] 103 85 #> [203,] 104 86 #> [204,] 105 87 #> [205,] 106 88 #> [206,] 107 89 #> [207,] 108 90 #> [208,] 109 91 #> [209,] 110 92 #> [210,] 111 93 #> [211,] 111 94 #> [212,] 112 95 #> [213,] 112 96 #> [214,] 112 97 #> [215,] 113 98 #> [216,] 113 99 #> [217,] 113 100 #> [218,] 113 101 #> [219,] 114 102 #> [220,] 114 103 #> [221,] 114 104 #> [222,] 114 105 #> [223,] 114 106 #> [224,] 114 107 #> [225,] 115 108 #> [226,] 115 109 #> [227,] 114 110 #> [228,] 115 111 #> [229,] 115 112 #> [230,] 115 113 #> [231,] 115 114 #> [232,] 115 115 #> [233,] 115 116 #> [234,] 115 117 #> [235,] 116 118 #> [236,] 116 119 #> [237,] 116 120 #> [238,] 116 121 #> [239,] 116 122 #> [240,] 116 123 #> [241,] 115 124 #> [242,] 115 125 #> [243,] 115 126 #> [244,] 115 127 #> [245,] 115 128 #> [246,] 115 129 #> [247,] 115 130 #> [248,] 115 131 #> [249,] 115 132 #> [250,] 116 133 #> [251,] 115 134 #> [252,] 116 135 #> [253,] 116 136 #> [254,] 116 137 #> [255,] 117 138 #> [256,] 117 139 #> [257,] 117 140 #> [258,] 118 141 #> [259,] 118 142 #> [260,] 118 143 #> [261,] 119 144 #> [262,] 120 145 #> [263,] 120 146 #> [264,] 121 147 #> [265,] 121 148 #> [266,] 122 149 #> [267,] 123 150 #> [268,] 123 151 #> [269,] 124 152 #> [270,] 125 153 #> [271,] 126 154 #> [272,] 127 155 #> [273,] 128 156 #> [274,] 129 157 #> [275,] 130 158 #> [276,] 131 159 #> [277,] 132 160 #> [278,] 133 161 #> [279,] 134 161 #> [280,] 135 162 #> [281,] 136 162 #> [282,] 137 162 #> [283,] 138 163 #> [284,] 139 163 #> [285,] 140 163 #> [286,] 141 163 #> [287,] 142 164 #> [288,] 143 164 #> [289,] 144 164 #> [290,] 145 164 #> [291,] 146 164 #> [292,] 147 164 #> [293,] 148 165 #> [294,] 149 165 #> [295,] 150 165 #> [296,] 151 165 #> [297,] 152 165 #> [298,] 153 165 #> [299,] 154 166 #> [300,] 155 166 #> [301,] 156 165 #> [302,] 157 165 #> [303,] 158 165 #> [304,] 159 165 #> [305,] 160 166 #> [306,] 161 166 #> [307,] 162 166 #> [308,] 163 166 #> [309,] 164 166 #> [310,] 165 166 #> [311,] 166 166 #> [312,] 167 166 #> [313,] 168 166 #> [314,] 169 166 #> [315,] 170 166 #> [316,] 171 166 #> [317,] 172 166 #> [318,] 173 166 #> [319,] 174 166 #> [320,] 175 166 #> [321,] 176 166 #> [322,] 177 166 #> [323,] 178 166 #> [324,] 179 166 #> [325,] 180 166 #> [326,] 181 166 #> [327,] 182 166 #> [328,] 183 166 #> [329,] 184 166 #> [330,] 185 166 #> [331,] 186 166 #> [332,] 187 166 #> [333,] 188 166 #> [334,] 189 165 #> [335,] 190 165 #> [336,] 191 165 #> [337,] 192 165 #> [338,] 193 165 #> [339,] 194 165 #> [340,] 195 165 #> [341,] 196 165 #> [342,] 197 165 #> [343,] 198 165 #> [344,] 199 165 #> [345,] 200 165 #> [346,] 201 165 #> [347,] 202 165 #> [348,] 203 165 #> [349,] 204 165 #> [350,] 205 165 #> [351,] 206 166 #> [352,] 207 166 #> [353,] 208 166 #> [354,] 209 166 #> [355,] 210 166 #> [356,] 211 166 #> [357,] 212 166 #> [358,] 213 166 #> [359,] 214 166 #> [360,] 215 167 #> [361,] 216 167 #> [362,] 217 167 #> [363,] 218 167 #> [364,] 219 167 #> [365,] 220 168 #> [366,] 221 168 #> [367,] 222 168 #> [368,] 223 169 #> [369,] 224 169 #> [370,] 225 169 #> [371,] 226 170 #> [372,] 227 170 #> [373,] 228 171 #> [374,] 229 171 #> [375,] 230 172 #> [376,] 231 172 #> [377,] 232 173 #> [378,] 233 174 #> [379,] 234 174 #> [380,] 235 175 #> [381,] 236 176 #> [382,] 237 177 #> [383,] 238 178 #> [384,] 238 179 #> [385,] 239 180 #> [386,] 240 181 #> [387,] 241 182 #> [388,] 241 183 #> [389,] 242 184 #> [390,] 243 185 #> [391,] 243 186 #> [392,] 244 187 #> [393,] 245 188 #> [394,] 245 189 #> [395,] 246 190 #> [396,] 246 191 #> [397,] 247 192 #> [398,] 247 193 #> [399,] 248 194 #> [400,] 249 195 #> [401,] 249 196 #> [402,] 250 197 #> [403,] 250 198 #> [404,] 251 199 #> [405,] 251 200 #> [406,] 251 201 #> [407,] 252 202 #> [408,] 252 203 #> [409,] 253 204 #> [410,] 253 205 #> [411,] 254 206 #> [412,] 254 207 #> [413,] 254 208 #> [414,] 255 209 #> [415,] 255 210 #> [416,] 256 211 #> [417,] 256 212 #> [418,] 256 213 #> [419,] 257 214 #> [420,] 257 215 #> [421,] 257 216 #> [422,] 258 217 #> [423,] 258 218 #> [424,] 259 219 #> [425,] 260 220 #> [426,] 261 221 #> [427,] 262 222 #> [428,] 263 223 #> [429,] 264 224 #> [430,] 265 225 #> [431,] 266 225 #> [432,] 267 226 #> [433,] 268 226 #> [434,] 269 226 #> [435,] 270 227 #> [436,] 271 227 #> [437,] 272 227 #> [438,] 273 227 #> [439,] 274 227 #> [440,] 275 227 #> [441,] 276 227 #> [442,] 277 227 #> [443,] 278 227 #> [444,] 279 228 #> [445,] 280 227 #> [446,] 281 227 #> [447,] 282 227 #> [448,] 283 227 #> [449,] 284 226 #> [450,] 285 226 #> [451,] 286 225 #> [452,] 287 224 #> [453,] 288 224 #> [454,] 289 223 #> [455,] 290 222 #> [456,] 291 221 #> [457,] 292 220 #> [458,] 293 219 #> [459,] 294 218 #> [460,] 295 217 #> [461,] 295 216 #> [462,] 296 215 #> [463,] 297 215 #> [464,] 298 214 #> [465,] 299 214 #> [466,] 300 214 #> [467,] 301 214 #> [468,] 302 214 #> [469,] 303 214 #> [470,] 304 214 #> [471,] 305 214 #> [472,] 306 214 #> [473,] 307 214 #> [474,] 308 214 #> [475,] 309 214 #> [476,] 310 214 #> [477,] 311 214 #> [478,] 312 214 #> [479,] 313 214 #> [480,] 314 214 #> [481,] 315 213 #> [482,] 315 212 #> [483,] 316 211 #> [484,] 316 210 #> [485,] 316 209 #> [486,] 316 208 #> [487,] 316 207 #> [488,] 315 206 #> [489,] 316 205 #> [490,] 315 204 #> [491,] 316 203 #> [492,] 316 202 #> [493,] 316 201 #> [494,] 316 200 #> [495,] 316 199 #> [496,] 316 198 #> [497,] 316 197 #> [498,] 316 196 #> [499,] 315 195 #> [500,] 315 194 #> [501,] 314 193 #> [502,] 314 192 #> [503,] 313 191 #> [504,] 312 191 #> [505,] 311 190 #> [506,] 310 190 #> [507,] 309 189 #> [508,] 308 189 #> [509,] 307 189 #> [510,] 306 189 #> [511,] 305 189 #> [512,] 304 188 #> [513,] 303 188 #> [514,] 302 188 #> [515,] 301 188 #> [516,] 300 188 #> [517,] 299 188 #> [518,] 298 188 #> [519,] 297 188 #> [520,] 296 188 #> [521,] 295 188 #> [522,] 294 188 #> [523,] 293 187 #> [524,] 292 187 #> [525,] 291 186 #> [526,] 291 185 #> [527,] 291 184 #> [528,] 290 183 #> [529,] 290 182 #> [530,] 290 181 #> [531,] 289 180 #> [532,] 289 179 #> [533,] 288 178 #> [534,] 288 177 #> [535,] 288 176 #> [536,] 287 175 #> [537,] 287 174 #> [538,] 286 173 #> [539,] 286 172 #> [540,] 286 171 #> [541,] 285 170 #> [542,] 285 169 #> [543,] 284 168 #> [544,] 284 167 #> [545,] 284 166 #> [546,] 283 165 #> [547,] 283 164 #> [548,] 282 163 #> [549,] 282 162 #> [550,] 282 161 #> [551,] 281 160 #> [552,] 281 159 #> [553,] 280 158 #> [554,] 280 157 #> [555,] 280 156 #> [556,] 279 155 #> [557,] 279 154 #> [558,] 278 153 #> [559,] 278 152 #> [560,] 278 151 #> [561,] 277 150 #> [562,] 278 149 #> [563,] 277 148 #> [564,] 277 147 #> [565,] 277 146 #> [566,] 277 145 #> [567,] 277 144 #> [568,] 276 143 #> [569,] 276 142 #> [570,] 277 141 #> [571,] 276 140 #> [572,] 276 139 #> [573,] 276 138 #> [574,] 276 137 #> [575,] 276 136 #> [576,] 275 135 #> [577,] 276 134 #> [578,] 275 133 #> [579,] 275 132 #> [580,] 275 131 #> [581,] 275 130 #> [582,] 274 129 #> [583,] 274 128 #> [584,] 274 127 #> [585,] 274 126 #> [586,] 274 125 #> [587,] 273 124 #> [588,] 273 123 #> [589,] 273 122 #> [590,] 272 121 #> [591,] 272 120 #> [592,] 272 119 #> [593,] 271 118 #> [594,] 271 117 #> [595,] 270 116 #> [596,] 269 115 #> [597,] 268 114 #> [598,] 268 113 #> [599,] 267 112 #> [600,] 267 111 #> [601,] 267 110 #> [602,] 267 109 #> [603,] 267 108 #> [604,] 267 107 #> [605,] 266 106 #> [606,] 266 105 #> [607,] 266 104 #> [608,] 266 103 #> [609,] 266 102 #> [610,] 266 101 #> [611,] 266 100 #> [612,] 266 99 #> [613,] 266 98 #> [614,] 266 97 #> [615,] 266 96 #> [616,] 266 95 #> [617,] 266 94 #> [618,] 266 93 #> [619,] 266 92 #> [620,] 266 91 #> [621,] 266 90 #> [622,] 266 89 #> [623,] 266 88 #> [624,] 266 87 #> [625,] 266 86 #> [626,] 266 85 #> [627,] 266 84 #> [628,] 266 83 #> [629,] 266 82 #> [630,] 266 81 #> [631,] 266 80 #> [632,] 266 79 #> [633,] 266 78 #> [634,] 267 77 #> [635,] 267 76 #> [636,] 267 75 #> [637,] 267 74 #> [638,] 267 73 #> [639,] 267 72 #> [640,] 267 71 #> [641,] 267 70 #> [642,] 267 69 #> [643,] 267 68 #> [644,] 268 67 #> [645,] 267 66 #> [646,] 268 65 #> [647,] 268 64 #> [648,] 269 63 #> [649,] 270 62 #> [650,] 271 62 #> [651,] 272 61 #> [652,] 273 61 #> [653,] 274 60 #> [654,] 275 60 #> [655,] 276 59 #> [656,] 277 58 #> [657,] 277 57 #> [658,] 277 56 #> [659,] 277 55 #> [660,] 276 54 #> [661,] 275 53 #> [662,] 274 53 #> [663,] 273 52 #> [664,] 272 52 #> [665,] 271 51 #> [666,] 270 51 #> [667,] 269 50 #> [668,] 268 50 #> [669,] 267 50 #> [670,] 266 50 #> [671,] 265 50 #> [672,] 264 50 #> [673,] 263 50 #> [674,] 262 50 #> [675,] 261 51 #> [676,] 260 52 #> [677,] 260 53 #> [678,] 260 54 #> [679,] 259 55 #> [680,] 259 56 #> [681,] 259 57 #> [682,] 259 58 #> [683,] 258 59 #> [684,] 258 60 #> [685,] 258 61 #> [686,] 258 62 #> [687,] 258 63 #> [688,] 257 64 #> [689,] 257 65 #> [690,] 257 66 #> [691,] 257 67 #> [692,] 256 68 #> [693,] 256 69 #> [694,] 256 70 #> [695,] 256 71 #> [696,] 255 72 #> [697,] 255 73 #> [698,] 255 74 #> [699,] 254 75 #> [700,] 254 76 #> [701,] 254 77 #> [702,] 253 78 #> [703,] 253 79 #> [704,] 252 80 #> [705,] 252 81 #> [706,] 252 82 #> [707,] 251 83 #> [708,] 251 84 #> [709,] 250 85 #> [710,] 250 86 #> [711,] 249 87 #> [712,] 249 88 #> [713,] 249 89 #> [714,] 248 90 #> [715,] 248 91 #> [716,] 247 92 #> [717,] 247 93 #> [718,] 247 94 #> [719,] 246 95 #> [720,] 246 96 #> [721,] 245 97 #> [722,] 245 98 #> [723,] 244 99 #> [724,] 243 100 #> [725,] 243 101 #> [726,] 242 102 #> [727,] 241 103 #> [728,] 240 104 #> [729,] 239 104 #> [730,] 238 104 #> [731,] 237 104 #> [732,] 236 105 #> [733,] 235 105 #> [734,] 234 105 #> [735,] 233 105 #> [736,] 232 105 #> [737,] 231 105 #> [738,] 230 105 #> [739,] 229 105 #> [740,] 228 105 #> [741,] 227 105 #> [742,] 226 105 #> [743,] 225 105 #> [744,] 224 105 #> [745,] 223 105 #> [746,] 222 105 #> [747,] 221 105 #> [748,] 220 105 #> [749,] 219 105 #> [750,] 218 105 #> [751,] 217 105 #> [752,] 216 105 #> [753,] 215 106 #> [754,] 214 106 #> [755,] 213 106 #> [756,] 212 106 #> [757,] 211 106 #> [758,] 210 106 #> [759,] 209 106 #> [760,] 208 106 #> [761,] 207 106 #> [762,] 206 106 #> [763,] 205 106 #> [764,] 204 106 #> [765,] 203 106 #> [766,] 202 106 #> [767,] 201 106 #> [768,] 200 106 #> #> $deusventrue #> [,1] [,2] #> [1,] 200 87 #> [2,] 199 86 #> [3,] 198 86 #> [4,] 197 87 #> [5,] 196 87 #> [6,] 195 87 #> [7,] 194 87 #> [8,] 193 87 #> [9,] 192 87 #> [10,] 191 87 #> [11,] 190 87 #> [12,] 189 87 #> [13,] 188 87 #> [14,] 187 87 #> [15,] 186 87 #> [16,] 185 87 #> [17,] 184 87 #> [18,] 183 87 #> [19,] 182 87 #> [20,] 181 87 #> [21,] 180 87 #> [22,] 179 87 #> [23,] 178 87 #> [24,] 177 87 #> [25,] 176 87 #> [26,] 175 87 #> [27,] 174 87 #> [28,] 173 87 #> [29,] 172 87 #> [30,] 171 87 #> [31,] 170 87 #> [32,] 169 87 #> [33,] 168 87 #> [34,] 167 87 #> [35,] 166 87 #> [36,] 165 87 #> [37,] 164 87 #> [38,] 163 87 #> [39,] 162 88 #> [40,] 161 88 #> [41,] 160 88 #> [42,] 159 88 #> [43,] 158 88 #> [44,] 157 88 #> [45,] 156 89 #> [46,] 155 89 #> [47,] 154 89 #> [48,] 153 90 #> [49,] 153 91 #> [50,] 152 92 #> [51,] 152 93 #> [52,] 152 94 #> [53,] 151 95 #> [54,] 151 96 #> [55,] 151 97 #> [56,] 151 98 #> [57,] 150 99 #> [58,] 151 100 #> [59,] 151 101 #> [60,] 151 102 #> [61,] 151 103 #> [62,] 151 104 #> [63,] 150 105 #> [64,] 151 106 #> [65,] 151 107 #> [66,] 151 108 #> [67,] 151 109 #> [68,] 152 110 #> [69,] 151 111 #> [70,] 150 111 #> [71,] 149 112 #> [72,] 148 113 #> [73,] 147 113 #> [74,] 146 113 #> [75,] 145 114 #> [76,] 144 115 #> [77,] 143 115 #> [78,] 142 115 #> [79,] 141 116 #> [80,] 140 116 #> [81,] 139 117 #> [82,] 138 117 #> [83,] 137 117 #> [84,] 136 118 #> [85,] 135 118 #> [86,] 134 119 #> [87,] 133 119 #> 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#> [266,] 39 180 #> [267,] 38 181 #> [268,] 39 182 #> [269,] 39 183 #> [270,] 39 184 #> [271,] 39 185 #> [272,] 40 186 #> [273,] 41 187 #> [274,] 42 188 #> [275,] 43 189 #> [276,] 44 190 #> [277,] 45 190 #> [278,] 46 190 #> [279,] 47 190 #> [280,] 48 190 #> [281,] 49 190 #> [282,] 50 190 #> [283,] 51 190 #> [284,] 52 190 #> [285,] 53 190 #> [286,] 54 189 #> [287,] 55 189 #> [288,] 56 189 #> [289,] 57 188 #> [290,] 58 188 #> [291,] 59 188 #> [292,] 60 187 #> [293,] 61 187 #> [294,] 62 186 #> [295,] 63 186 #> [296,] 64 185 #> [297,] 65 185 #> [298,] 66 184 #> [299,] 67 184 #> [300,] 68 183 #> [301,] 69 183 #> [302,] 70 182 #> [303,] 71 182 #> [304,] 72 181 #> [305,] 73 180 #> [306,] 74 180 #> [307,] 75 179 #> [308,] 76 179 #> [309,] 77 178 #> [310,] 78 177 #> [311,] 79 177 #> [312,] 80 176 #> [313,] 81 176 #> [314,] 82 175 #> [315,] 83 174 #> [316,] 84 174 #> [317,] 85 173 #> [318,] 86 173 #> [319,] 87 172 #> [320,] 88 171 #> [321,] 89 171 #> [322,] 90 170 #> [323,] 91 170 #> [324,] 92 169 #> [325,] 93 168 #> [326,] 94 168 #> [327,] 95 167 #> [328,] 96 166 #> [329,] 97 166 #> [330,] 98 165 #> [331,] 99 165 #> [332,] 100 164 #> [333,] 101 164 #> [334,] 102 163 #> [335,] 103 162 #> [336,] 104 162 #> [337,] 105 162 #> [338,] 106 161 #> [339,] 107 161 #> [340,] 108 160 #> [341,] 109 160 #> [342,] 110 160 #> [343,] 111 159 #> [344,] 112 159 #> [345,] 113 159 #> [346,] 114 158 #> [347,] 115 158 #> [348,] 116 158 #> [349,] 117 158 #> [350,] 118 157 #> [351,] 119 157 #> [352,] 120 157 #> [353,] 121 157 #> [354,] 122 157 #> [355,] 123 156 #> [356,] 124 157 #> [357,] 125 156 #> [358,] 126 157 #> [359,] 127 157 #> [360,] 128 157 #> [361,] 129 157 #> [362,] 130 158 #> [363,] 131 158 #> [364,] 132 158 #> [365,] 133 159 #> [366,] 134 159 #> [367,] 135 160 #> [368,] 136 160 #> [369,] 137 161 #> [370,] 138 161 #> [371,] 139 162 #> [372,] 140 162 #> [373,] 141 163 #> [374,] 142 164 #> [375,] 143 164 #> [376,] 144 165 #> [377,] 145 165 #> [378,] 146 166 #> [379,] 147 166 #> [380,] 148 167 #> [381,] 149 167 #> [382,] 150 168 #> [383,] 151 168 #> [384,] 152 169 #> [385,] 153 169 #> [386,] 154 170 #> [387,] 155 170 #> [388,] 156 171 #> [389,] 157 171 #> [390,] 158 172 #> [391,] 159 172 #> [392,] 160 173 #> [393,] 161 173 #> [394,] 162 174 #> [395,] 163 174 #> [396,] 164 174 #> [397,] 165 175 #> [398,] 166 175 #> [399,] 167 175 #> [400,] 168 176 #> [401,] 169 176 #> [402,] 168 177 #> [403,] 168 178 #> [404,] 167 179 #> [405,] 166 180 #> [406,] 165 181 #> [407,] 165 182 #> [408,] 164 183 #> [409,] 163 184 #> [410,] 162 185 #> [411,] 161 186 #> [412,] 160 187 #> [413,] 159 188 #> [414,] 159 189 #> [415,] 158 190 #> [416,] 157 191 #> [417,] 156 192 #> [418,] 155 193 #> [419,] 154 194 #> [420,] 153 195 #> [421,] 152 196 #> [422,] 151 197 #> [423,] 150 198 #> [424,] 149 199 #> [425,] 148 200 #> [426,] 147 201 #> [427,] 146 202 #> [428,] 145 203 #> [429,] 144 204 #> [430,] 143 205 #> [431,] 142 206 #> [432,] 142 207 #> [433,] 141 208 #> [434,] 140 209 #> [435,] 139 210 #> [436,] 138 211 #> [437,] 138 212 #> [438,] 137 213 #> [439,] 137 214 #> [440,] 137 215 #> [441,] 137 216 #> [442,] 138 217 #> [443,] 139 218 #> [444,] 140 218 #> [445,] 141 219 #> [446,] 142 219 #> [447,] 143 219 #> [448,] 144 219 #> [449,] 145 219 #> [450,] 146 220 #> [451,] 147 220 #> [452,] 148 220 #> [453,] 149 220 #> [454,] 150 220 #> [455,] 151 220 #> [456,] 152 220 #> [457,] 153 221 #> [458,] 154 220 #> [459,] 155 221 #> [460,] 156 221 #> [461,] 157 221 #> [462,] 158 221 #> [463,] 159 221 #> [464,] 160 221 #> [465,] 161 221 #> [466,] 162 221 #> [467,] 163 222 #> [468,] 164 221 #> [469,] 165 221 #> [470,] 166 221 #> [471,] 167 221 #> [472,] 168 221 #> [473,] 169 221 #> [474,] 170 221 #> [475,] 171 221 #> [476,] 172 221 #> [477,] 173 222 #> [478,] 174 222 #> [479,] 175 222 #> [480,] 176 222 #> [481,] 177 222 #> [482,] 178 222 #> [483,] 179 222 #> [484,] 180 222 #> [485,] 181 222 #> [486,] 182 222 #> [487,] 183 222 #> [488,] 184 222 #> [489,] 185 222 #> [490,] 186 222 #> [491,] 187 222 #> [492,] 188 222 #> [493,] 189 222 #> [494,] 190 222 #> [495,] 191 222 #> [496,] 192 222 #> [497,] 193 222 #> [498,] 194 222 #> [499,] 195 222 #> [500,] 196 222 #> [501,] 197 222 #> [502,] 198 222 #> [503,] 199 222 #> [504,] 200 222 #> [505,] 201 222 #> [506,] 202 222 #> [507,] 203 222 #> [508,] 204 222 #> [509,] 205 222 #> [510,] 206 222 #> [511,] 207 222 #> [512,] 208 221 #> [513,] 209 221 #> [514,] 210 221 #> [515,] 211 221 #> [516,] 212 221 #> [517,] 213 221 #> [518,] 214 221 #> [519,] 215 221 #> [520,] 216 221 #> [521,] 217 221 #> [522,] 218 221 #> [523,] 219 221 #> [524,] 220 221 #> [525,] 221 221 #> [526,] 222 221 #> [527,] 223 221 #> [528,] 224 221 #> [529,] 225 221 #> [530,] 226 221 #> [531,] 227 221 #> [532,] 228 221 #> [533,] 229 221 #> [534,] 230 220 #> [535,] 231 220 #> [536,] 232 220 #> [537,] 233 220 #> [538,] 234 220 #> [539,] 235 220 #> [540,] 236 220 #> [541,] 237 220 #> [542,] 238 220 #> [543,] 239 220 #> [544,] 240 220 #> [545,] 241 220 #> [546,] 242 219 #> [547,] 243 219 #> [548,] 244 219 #> [549,] 245 219 #> [550,] 246 219 #> [551,] 247 219 #> [552,] 248 219 #> [553,] 249 218 #> [554,] 250 218 #> [555,] 251 218 #> [556,] 252 218 #> [557,] 253 218 #> [558,] 254 218 #> [559,] 255 218 #> [560,] 256 217 #> [561,] 257 217 #> [562,] 258 217 #> [563,] 259 217 #> [564,] 260 216 #> [565,] 261 216 #> [566,] 262 216 #> [567,] 263 216 #> [568,] 264 215 #> [569,] 265 215 #> [570,] 266 215 #> [571,] 267 215 #> [572,] 268 214 #> [573,] 269 214 #> [574,] 270 214 #> [575,] 271 213 #> [576,] 272 213 #> [577,] 273 213 #> [578,] 274 212 #> [579,] 275 212 #> [580,] 276 212 #> [581,] 277 211 #> [582,] 278 211 #> [583,] 279 210 #> [584,] 280 210 #> [585,] 281 209 #> [586,] 282 209 #> [587,] 283 208 #> [588,] 284 208 #> [589,] 285 207 #> [590,] 286 207 #> [591,] 287 206 #> [592,] 288 206 #> [593,] 289 205 #> [594,] 290 205 #> [595,] 291 204 #> [596,] 292 203 #> [597,] 293 202 #> [598,] 294 202 #> [599,] 295 201 #> [600,] 296 200 #> [601,] 297 199 #> [602,] 298 198 #> [603,] 299 197 #> [604,] 300 196 #> [605,] 301 195 #> [606,] 302 194 #> [607,] 303 193 #> [608,] 303 192 #> [609,] 304 191 #> [610,] 305 190 #> [611,] 305 189 #> [612,] 306 188 #> [613,] 307 187 #> [614,] 308 186 #> [615,] 308 185 #> [616,] 309 184 #> [617,] 310 184 #> [618,] 311 184 #> [619,] 312 183 #> [620,] 313 183 #> [621,] 314 183 #> [622,] 315 182 #> [623,] 316 182 #> [624,] 317 182 #> [625,] 318 181 #> [626,] 319 181 #> [627,] 320 180 #> [628,] 321 180 #> [629,] 322 180 #> [630,] 323 179 #> [631,] 324 179 #> [632,] 325 178 #> [633,] 326 178 #> [634,] 327 178 #> [635,] 328 177 #> [636,] 329 177 #> [637,] 330 176 #> [638,] 331 176 #> [639,] 332 175 #> [640,] 333 174 #> [641,] 334 174 #> [642,] 335 173 #> [643,] 336 173 #> [644,] 337 172 #> [645,] 338 171 #> [646,] 339 171 #> [647,] 340 170 #> [648,] 341 170 #> [649,] 342 169 #> [650,] 343 168 #> [651,] 344 168 #> [652,] 345 167 #> [653,] 346 166 #> [654,] 347 165 #> [655,] 348 165 #> [656,] 349 164 #> [657,] 350 163 #> [658,] 351 162 #> [659,] 352 162 #> [660,] 353 161 #> [661,] 354 160 #> [662,] 355 159 #> [663,] 356 158 #> [664,] 357 157 #> [665,] 358 156 #> [666,] 359 155 #> [667,] 360 155 #> [668,] 361 154 #> [669,] 362 153 #> [670,] 362 152 #> [671,] 363 151 #> [672,] 364 150 #> [673,] 365 149 #> [674,] 366 148 #> [675,] 367 147 #> [676,] 368 146 #> [677,] 369 145 #> [678,] 370 144 #> [679,] 370 143 #> [680,] 371 142 #> [681,] 372 141 #> [682,] 373 140 #> [683,] 373 139 #> [684,] 374 138 #> [685,] 375 137 #> [686,] 375 136 #> [687,] 376 135 #> [688,] 377 134 #> [689,] 377 133 #> [690,] 378 132 #> [691,] 379 131 #> [692,] 379 130 #> [693,] 379 129 #> [694,] 380 128 #> [695,] 380 127 #> [696,] 381 126 #> [697,] 381 125 #> [698,] 382 124 #> [699,] 382 123 #> [700,] 382 122 #> [701,] 383 121 #> [702,] 383 120 #> [703,] 383 119 #> [704,] 384 118 #> [705,] 383 117 #> [706,] 383 116 #> [707,] 382 115 #> [708,] 381 114 #> [709,] 380 113 #> [710,] 379 112 #> [711,] 378 112 #> [712,] 377 111 #> [713,] 376 111 #> [714,] 375 110 #> [715,] 374 109 #> [716,] 373 109 #> [717,] 372 108 #> [718,] 371 107 #> [719,] 370 107 #> [720,] 369 106 #> [721,] 368 106 #> [722,] 367 105 #> [723,] 366 105 #> [724,] 365 105 #> [725,] 364 104 #> [726,] 363 103 #> [727,] 362 103 #> [728,] 361 103 #> [729,] 360 102 #> [730,] 359 102 #> [731,] 358 101 #> [732,] 357 101 #> [733,] 356 101 #> [734,] 355 100 #> [735,] 354 100 #> [736,] 353 99 #> [737,] 352 99 #> [738,] 351 99 #> [739,] 350 98 #> [740,] 349 98 #> [741,] 348 98 #> [742,] 347 97 #> [743,] 346 97 #> [744,] 345 97 #> [745,] 344 96 #> [746,] 343 96 #> [747,] 342 96 #> [748,] 341 95 #> [749,] 340 95 #> [750,] 339 95 #> [751,] 338 94 #> [752,] 337 94 #> [753,] 336 94 #> [754,] 335 94 #> [755,] 334 93 #> [756,] 333 93 #> [757,] 332 93 #> [758,] 331 93 #> [759,] 330 92 #> [760,] 329 92 #> [761,] 328 92 #> [762,] 327 92 #> [763,] 326 91 #> [764,] 325 91 #> [765,] 324 91 #> [766,] 323 91 #> [767,] 322 91 #> [768,] 321 90 #> [769,] 320 90 #> [770,] 319 90 #> [771,] 318 90 #> [772,] 317 90 #> [773,] 316 90 #> [774,] 315 89 #> [775,] 314 89 #> [776,] 313 89 #> [777,] 312 89 #> [778,] 311 89 #> [779,] 310 89 #> [780,] 309 88 #> [781,] 308 88 #> [782,] 307 88 #> [783,] 306 88 #> [784,] 305 88 #> [785,] 304 88 #> [786,] 303 88 #> [787,] 302 88 #> [788,] 301 88 #> [789,] 300 87 #> [790,] 299 87 #> [791,] 298 87 #> [792,] 297 87 #> [793,] 296 87 #> [794,] 295 87 #> [795,] 294 87 #> [796,] 293 87 #> [797,] 292 87 #> [798,] 291 87 #> [799,] 290 87 #> [800,] 289 87 #> [801,] 288 87 #> [802,] 287 87 #> [803,] 286 87 #> [804,] 285 87 #> [805,] 284 86 #> [806,] 283 86 #> [807,] 282 86 #> [808,] 282 85 #> [809,] 281 84 #> [810,] 281 83 #> [811,] 280 82 #> [812,] 280 81 #> [813,] 279 80 #> [814,] 278 79 #> [815,] 278 78 #> [816,] 278 77 #> [817,] 277 76 #> [818,] 276 75 #> [819,] 276 74 #> [820,] 276 73 #> [821,] 275 72 #> [822,] 274 71 #> [823,] 274 70 #> [824,] 273 69 #> [825,] 273 68 #> [826,] 272 67 #> [827,] 272 66 #> [828,] 271 65 #> [829,] 270 64 #> [830,] 270 63 #> [831,] 269 62 #> [832,] 269 61 #> [833,] 268 60 #> [834,] 267 59 #> [835,] 266 58 #> [836,] 266 57 #> [837,] 265 56 #> [838,] 264 55 #> [839,] 264 54 #> [840,] 263 53 #> [841,] 262 52 #> [842,] 261 51 #> [843,] 261 50 #> [844,] 260 49 #> [845,] 259 48 #> [846,] 258 47 #> [847,] 257 46 #> [848,] 256 45 #> [849,] 255 44 #> [850,] 254 43 #> [851,] 253 42 #> [852,] 252 42 #> [853,] 251 41 #> [854,] 250 41 #> [855,] 249 40 #> [856,] 248 40 #> [857,] 247 39 #> [858,] 246 39 #> [859,] 245 39 #> [860,] 244 39 #> [861,] 243 39 #> [862,] 242 39 #> [863,] 241 39 #> [864,] 240 39 #> [865,] 239 39 #> [866,] 238 40 #> [867,] 237 40 #> [868,] 236 41 #> [869,] 235 41 #> [870,] 234 42 #> [871,] 233 43 #> [872,] 233 44 #> [873,] 232 45 #> [874,] 231 46 #> [875,] 230 47 #> [876,] 230 48 #> [877,] 230 49 #> [878,] 229 50 #> [879,] 228 51 #> [880,] 228 52 #> [881,] 228 53 #> [882,] 227 54 #> [883,] 227 55 #> [884,] 227 56 #> [885,] 226 57 #> [886,] 226 58 #> [887,] 226 59 #> [888,] 226 60 #> [889,] 225 61 #> [890,] 225 62 #> [891,] 225 63 #> [892,] 224 64 #> [893,] 225 65 #> [894,] 224 66 #> [895,] 224 67 #> [896,] 224 68 #> [897,] 224 69 #> [898,] 224 70 #> [899,] 224 71 #> [900,] 224 72 #> [901,] 224 73 #> [902,] 224 74 #> [903,] 225 75 #> [904,] 224 76 #> [905,] 225 77 #> [906,] 225 78 #> [907,] 225 79 #> [908,] 226 80 #> [909,] 226 81 #> [910,] 226 82 #> [911,] 227 83 #> [912,] 227 84 #> [913,] 227 85 #> [914,] 228 86 #> [915,] 228 87 #> [916,] 227 87 #> [917,] 226 87 #> [918,] 225 88 #> [919,] 224 88 #> [920,] 223 87 #> [921,] 222 88 #> [922,] 221 88 #> [923,] 220 88 #> [924,] 219 88 #> [925,] 218 88 #> [926,] 217 89 #> [927,] 216 89 #> [928,] 215 89 #> [929,] 214 89 #> [930,] 213 89 #> [931,] 212 88 #> [932,] 211 88 #> [933,] 210 88 #> [934,] 209 88 #> [935,] 208 88 #> [936,] 207 88 #> [937,] 206 88 #> [938,] 205 87 #> [939,] 204 87 #> [940,] 203 87 #> [941,] 202 87 #> [942,] 201 87 #> [943,] 200 87 #> #> $duvel #> [,1] [,2] #> [1,] 61 315 #> [2,] 61 304 #> [3,] 61 293 #> [4,] 61 293 #> [5,] 61 282 #> [6,] 59 272 #> [7,] 59 261 #> [8,] 59 250 #> [9,] 59 239 #> [10,] 59 239 #> [11,] 59 228 #> [12,] 59 217 #> [13,] 59 206 #> [14,] 59 195 #> [15,] 59 185 #> [16,] 59 185 #> [17,] 59 174 #> [18,] 59 163 #> [19,] 59 152 #> [20,] 59 141 #> [21,] 59 130 #> [22,] 59 130 #> [23,] 59 119 #> [24,] 59 108 #> [25,] 59 98 #> [26,] 59 87 #> [27,] 59 87 #> [28,] 58 76 #> [29,] 58 65 #> [30,] 58 54 #> [31,] 61 43 #> [32,] 66 32 #> [33,] 66 32 #> [34,] 76 22 #> [35,] 86 18 #> [36,] 97 17 #> [37,] 108 16 #> [38,] 119 15 #> [39,] 119 15 #> [40,] 130 14 #> [41,] 141 12 #> [42,] 152 12 #> [43,] 163 11 #> [44,] 173 11 #> [45,] 173 11 #> [46,] 184 11 #> [47,] 195 11 #> [48,] 206 11 #> [49,] 217 12 #> [50,] 217 12 #> [51,] 228 12 #> [52,] 239 14 #> [53,] 250 15 #> [54,] 260 17 #> [55,] 271 17 #> [56,] 271 17 #> [57,] 282 21 #> [58,] 290 32 #> [59,] 295 43 #> [60,] 297 54 #> [61,] 298 65 #> [62,] 298 65 #> [63,] 298 76 #> [64,] 298 86 #> [65,] 298 97 #> [66,] 298 108 #> [67,] 298 119 #> [68,] 298 119 #> [69,] 298 130 #> [70,] 298 141 #> [71,] 298 152 #> [72,] 298 163 #> [73,] 298 163 #> [74,] 298 173 #> [75,] 298 184 #> [76,] 298 195 #> [77,] 298 206 #> [78,] 298 217 #> [79,] 298 217 #> [80,] 298 228 #> [81,] 298 239 #> [82,] 298 250 #> [83,] 298 260 #> [84,] 298 271 #> [85,] 298 271 #> [86,] 298 282 #> [87,] 298 293 #> [88,] 297 304 #> [89,] 297 315 #> [90,] 296 326 #> [91,] 296 326 #> [92,] 295 336 #> [93,] 292 347 #> [94,] 288 358 #> [95,] 282 369 #> [96,] 282 369 #> [97,] 274 380 #> [98,] 269 391 #> [99,] 265 402 #> [100,] 263 413 #> [101,] 262 423 #> [102,] 262 423 #> [103,] 261 434 #> [104,] 258 445 #> [105,] 253 456 #> [106,] 248 467 #> [107,] 240 478 #> [108,] 240 478 #> [109,] 233 488 #> [110,] 227 499 #> [111,] 223 509 #> [112,] 221 520 #> [113,] 221 531 #> [114,] 221 531 #> [115,] 225 542 #> [116,] 226 553 #> [117,] 223 564 #> [118,] 224 575 #> [119,] 224 575 #> [120,] 226 586 #> [121,] 223 596 #> [122,] 215 606 #> [123,] 204 613 #> [124,] 193 616 #> [125,] 193 616 #> [126,] 182 617 #> [127,] 171 617 #> [128,] 160 616 #> [129,] 149 611 #> [130,] 140 605 #> [131,] 140 605 #> [132,] 135 595 #> [133,] 132 584 #> [134,] 135 573 #> [135,] 133 562 #> [136,] 131 551 #> [137,] 131 551 #> [138,] 133 540 #> [139,] 137 529 #> [140,] 136 519 #> [141,] 133 508 #> [142,] 133 508 #> [143,] 130 497 #> [144,] 123 487 #> [145,] 113 476 #> [146,] 107 465 #> [147,] 103 454 #> [148,] 103 454 #> [149,] 99 444 #> [150,] 96 434 #> [151,] 95 423 #> [152,] 93 412 #> [153,] 92 401 #> [154,] 92 401 #> [155,] 88 390 #> [156,] 81 379 #> [157,] 74 369 #> [158,] 69 358 #> [159,] 65 348 #> [160,] 65 348 #> [161,] 63 337 #> # $fac grouping factors head(bot$fac) #> # A tibble: 6 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a # or if you know the name of the column of interest bot$type #> [1] whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> [11] whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> [21] beer beer beer beer beer beer beer beer beer beer #> [31] beer beer beer beer beer beer beer beer beer beer #> Levels: beer whisky # table table(bot$fac) #> fake #> type a b c d #> beer 0 0 10 10 #> whisky 10 10 0 0 # an internal view of an Out object str(bot) #> coo : List of 40 #> $ brahma : num [1:710, 1:2] 200 200 199 198 197 197 196 195 196 197 ... #> $ caney : num [1:494, 1:2] 200 199 199 198 197 197 196 195 194 194 ... #> $ chimay : num [1:806, 1:2] 200 200 199 198 198 197 197 196 195 195 ... #> $ corona : num [1:768, 1:2] 200 199 198 197 196 195 194 193 192 191 ... #> $ deusventrue : num [1:943, 1:2] 200 199 198 197 196 195 194 193 192 191 ... #> $ duvel : num [1:161, 1:2] 61 61 61 61 61 59 59 59 59 59 ... #> $ franziskaner : num [1:124, 1:2] 54 54 54 54 54 54 56 56 56 56 ... #> $ grimbergen : num [1:126, 1:2] 42 40 40 40 40 40 40 42 41 42 ... #> $ guiness : num [1:183, 1:2] 69 69 69 69 69 69 69 70 69 70 ... #> $ hoegardeen : num [1:193, 1:2] 42 40 40 40 40 40 40 40 40 40 ... #> $ jupiler : num [1:156, 1:2] 55 54 54 54 54 54 54 54 53 53 ... #> $ kingfisher : num [1:182, 1:2] 71 71 71 71 71 71 71 71 71 73 ... #> $ latrappe : num [1:136, 1:2] 26 25 25 25 25 26 26 26 26 26 ... #> $ lindemanskriek: num [1:176, 1:2] 60 60 55 54 54 54 53 54 54 54 ... #> $ nicechouffe : num [1:146, 1:2] 82 81 77 77 76 75 75 75 75 74 ... #> $ pecheresse : num [1:129, 1:2] 63 61 61 60 58 58 58 58 58 58 ... #> $ sierranevada : num [1:176, 1:2] 61 61 61 61 61 61 61 61 61 61 ... #> $ tanglefoot : num [1:174, 1:2] 48 48 48 48 49 49 49 49 49 49 ... #> $ tauro : num [1:174, 1:2] 56 54 54 54 54 54 54 54 54 52 ... #> $ westmalle : num [1:141, 1:2] 70 70 67 67 66 66 66 66 66 66 ... #> $ amrut : num [1:191, 1:2] 57 57 57 57 57 57 57 57 57 57 ... #> $ ballantines : num [1:146, 1:2] 38 38 38 38 38 38 38 38 38 38 ... #> $ bushmills : num [1:165, 1:2] 72 72 72 72 72 72 73 74 74 74 ... #> $ chivas : num [1:164, 1:2] 33 31 29 29 29 29 30 30 30 31 ... #> $ dalmore : num [1:155, 1:2] 52 47 44 42 42 42 42 42 42 42 ... #> $ famousgrouse : num [1:169, 1:2] 99 99 99 99 99 99 99 99 99 99 ... #> $ glendronach : num [1:197, 1:2] 73 73 74 74 74 74 74 74 74 74 ... #> $ glenmorangie : num [1:179, 1:2] 53 54 54 54 55 57 57 57 57 58 ... #> $ highlandpark : num [1:169, 1:2] 42 42 42 42 42 42 42 42 41 42 ... #> $ jackdaniels : num [1:150, 1:2] 63 63 63 63 63 63 63 63 63 63 ... #> $ jb : num [1:174, 1:2] 43 43 42 42 43 43 43 43 43 43 ... #> $ johnniewalker : num [1:168, 1:2] 133 133 133 133 134 134 134 134 134 134 ... #> $ magallan : num [1:141, 1:2] 78 78 80 80 81 81 81 83 83 84 ... #> $ makersmark : num [1:177, 1:2] 31 23 16 16 13 10 8 8 11 11 ... #> $ oban : num [1:179, 1:2] 74 74 74 74 74 74 75 75 75 75 ... #> $ oldpotrero : num [1:131, 1:2] 83 77 71 63 60 58 57 58 58 58 ... #> $ redbreast : num [1:177, 1:2] 105 103 101 98 98 97 97 97 97 97 ... #> $ tamdhu : num [1:176, 1:2] 49 49 49 49 49 50 50 50 50 50 ... #> $ wildturkey : num [1:185, 1:2] 18 18 18 18 18 18 18 18 18 18 ... #> $ yoichi : num [1:123, 1:2] 69 69 69 69 69 70 70 70 70 70 ... #> fac : tibble [40 × 2] (S3: tbl_df/tbl/data.frame) #> ldk : list() # subsetting # see ?filter, ?select, and their 'see also' section for the # complete list of dplyr-like verbs implemented in Momocs length(bot) # the number of shapes #> [1] 40 names(bot) # access all individual names #> [1] \"brahma\" \"caney\" \"chimay\" \"corona\" #> [5] \"deusventrue\" \"duvel\" \"franziskaner\" \"grimbergen\" #> [9] \"guiness\" \"hoegardeen\" \"jupiler\" \"kingfisher\" #> [13] \"latrappe\" \"lindemanskriek\" \"nicechouffe\" \"pecheresse\" #> [17] \"sierranevada\" \"tanglefoot\" \"tauro\" \"westmalle\" #> [21] \"amrut\" \"ballantines\" \"bushmills\" \"chivas\" #> [25] \"dalmore\" \"famousgrouse\" \"glendronach\" \"glenmorangie\" #> [29] \"highlandpark\" \"jackdaniels\" \"jb\" \"johnniewalker\" #> [33] \"magallan\" \"makersmark\" \"oban\" \"oldpotrero\" #> [37] \"redbreast\" \"tamdhu\" \"wildturkey\" \"yoichi\" bot2 <- bot names(bot2) <- paste0('newnames', 1:length(bot2)) # define new names # Add a $fac from scratch coo <- bot[1:5] # a list of five matrices length(coo) #> [1] 5 sapply(coo, class) #> brahma caney chimay corona deusventrue #> [1,] \"matrix\" \"matrix\" \"matrix\" \"matrix\" \"matrix\" #> [2,] \"array\" \"array\" \"array\" \"array\" \"array\" fac <- data.frame(name=letters[1:5], value=c(5:1)) # Then you have to define the subclass using the right builder # here we have outlines, so we use Out x <- Out(coo, fac) x$coo #> $brahma #> [,1] [,2] #> [1,] 200 62 #> [2,] 200 61 #> [3,] 199 60 #> [4,] 198 59 #> [5,] 197 58 #> [6,] 197 57 #> [7,] 196 56 #> [8,] 195 56 #> [9,] 196 56 #> [10,] 197 56 #> [11,] 198 56 #> [12,] 199 56 #> [13,] 200 56 #> [14,] 201 55 #> [15,] 202 55 #> [16,] 203 55 #> [17,] 204 55 #> [18,] 205 54 #> [19,] 206 54 #> [20,] 207 53 #> [21,] 208 52 #> [22,] 208 51 #> [23,] 209 50 #> [24,] 209 49 #> [25,] 209 48 #> [26,] 209 47 #> [27,] 208 46 #> [28,] 208 45 #> [29,] 207 44 #> [30,] 206 44 #> [31,] 205 43 #> [32,] 204 43 #> [33,] 203 43 #> [34,] 202 43 #> [35,] 201 43 #> [36,] 200 43 #> [37,] 199 43 #> [38,] 198 43 #> [39,] 197 43 #> [40,] 196 42 #> [41,] 195 42 #> [42,] 194 42 #> [43,] 193 42 #> [44,] 192 42 #> [45,] 191 42 #> [46,] 190 42 #> [47,] 189 42 #> [48,] 188 42 #> [49,] 187 42 #> [50,] 186 42 #> [51,] 185 42 #> [52,] 184 42 #> [53,] 183 42 #> [54,] 182 42 #> [55,] 181 42 #> [56,] 180 42 #> [57,] 179 42 #> [58,] 178 43 #> [59,] 177 42 #> [60,] 176 43 #> [61,] 175 43 #> [62,] 174 43 #> [63,] 173 43 #> [64,] 172 43 #> [65,] 171 43 #> [66,] 170 43 #> [67,] 169 43 #> [68,] 168 43 #> [69,] 167 43 #> [70,] 166 43 #> [71,] 165 43 #> [72,] 164 43 #> [73,] 163 43 #> [74,] 162 43 #> [75,] 161 43 #> [76,] 160 43 #> [77,] 159 43 #> [78,] 158 43 #> [79,] 157 43 #> [80,] 156 43 #> [81,] 155 43 #> [82,] 154 43 #> [83,] 153 43 #> [84,] 152 43 #> [85,] 151 43 #> [86,] 150 43 #> [87,] 149 43 #> [88,] 148 43 #> [89,] 147 43 #> [90,] 146 44 #> [91,] 145 44 #> [92,] 144 44 #> [93,] 143 44 #> [94,] 143 43 #> [95,] 143 42 #> [96,] 143 41 #> [97,] 142 40 #> [98,] 142 39 #> [99,] 142 38 #> [100,] 142 37 #> [101,] 142 36 #> [102,] 142 35 #> [103,] 143 34 #> [104,] 143 33 #> [105,] 143 32 #> [106,] 144 31 #> [107,] 145 30 #> [108,] 145 29 #> [109,] 146 28 #> [110,] 147 27 #> [111,] 148 27 #> [112,] 149 26 #> [113,] 150 25 #> [114,] 151 25 #> [115,] 152 24 #> [116,] 153 24 #> [117,] 154 23 #> [118,] 155 23 #> [119,] 156 23 #> [120,] 157 22 #> [121,] 158 22 #> [122,] 159 22 #> [123,] 160 21 #> [124,] 161 21 #> [125,] 162 21 #> [126,] 163 21 #> [127,] 164 21 #> [128,] 165 20 #> [129,] 166 20 #> [130,] 167 20 #> [131,] 168 20 #> [132,] 169 20 #> [133,] 170 20 #> [134,] 171 20 #> [135,] 172 20 #> [136,] 173 20 #> [137,] 174 19 #> [138,] 175 19 #> [139,] 176 19 #> [140,] 177 19 #> [141,] 178 19 #> [142,] 179 19 #> [143,] 180 19 #> [144,] 181 20 #> [145,] 182 20 #> [146,] 183 20 #> [147,] 184 20 #> [148,] 185 20 #> [149,] 186 20 #> [150,] 187 20 #> [151,] 188 20 #> [152,] 189 21 #> [153,] 190 21 #> [154,] 191 21 #> [155,] 192 21 #> [156,] 193 21 #> [157,] 194 21 #> [158,] 195 22 #> [159,] 196 22 #> [160,] 197 22 #> [161,] 198 22 #> [162,] 199 22 #> [163,] 200 22 #> [164,] 201 22 #> [165,] 202 22 #> [166,] 203 22 #> [167,] 204 22 #> [168,] 205 22 #> [169,] 206 22 #> [170,] 207 21 #> [171,] 208 20 #> [172,] 208 19 #> [173,] 207 18 #> [174,] 206 17 #> [175,] 205 17 #> [176,] 204 16 #> [177,] 203 16 #> [178,] 202 15 #> [179,] 201 15 #> [180,] 200 14 #> [181,] 199 14 #> [182,] 198 14 #> [183,] 197 13 #> [184,] 196 13 #> [185,] 195 13 #> [186,] 194 12 #> [187,] 193 12 #> [188,] 192 12 #> [189,] 191 11 #> [190,] 190 11 #> [191,] 189 11 #> [192,] 188 11 #> [193,] 187 10 #> [194,] 186 10 #> [195,] 185 10 #> [196,] 184 10 #> [197,] 183 9 #> [198,] 182 9 #> [199,] 181 10 #> [200,] 180 9 #> [201,] 179 9 #> [202,] 178 9 #> [203,] 177 9 #> [204,] 176 9 #> [205,] 175 9 #> [206,] 174 9 #> [207,] 173 9 #> [208,] 172 9 #> [209,] 171 9 #> [210,] 170 9 #> [211,] 169 9 #> [212,] 168 9 #> [213,] 167 9 #> [214,] 166 9 #> [215,] 165 9 #> [216,] 164 9 #> [217,] 163 9 #> [218,] 162 9 #> [219,] 161 9 #> [220,] 160 10 #> [221,] 159 10 #> [222,] 158 10 #> [223,] 157 10 #> [224,] 156 10 #> [225,] 155 11 #> [226,] 154 11 #> [227,] 153 11 #> [228,] 152 12 #> [229,] 151 12 #> [230,] 150 12 #> [231,] 149 13 #> [232,] 148 13 #> [233,] 147 14 #> [234,] 146 14 #> [235,] 145 15 #> [236,] 144 15 #> [237,] 143 16 #> [238,] 142 17 #> [239,] 141 17 #> [240,] 140 18 #> [241,] 139 19 #> [242,] 138 20 #> [243,] 137 21 #> [244,] 136 22 #> [245,] 135 23 #> [246,] 134 24 #> [247,] 134 25 #> [248,] 133 26 #> [249,] 133 27 #> [250,] 132 28 #> [251,] 132 29 #> [252,] 131 30 #> [253,] 131 31 #> [254,] 131 32 #> [255,] 130 33 #> [256,] 130 34 #> [257,] 130 35 #> [258,] 130 36 #> [259,] 130 37 #> [260,] 130 38 #> [261,] 130 39 #> [262,] 130 40 #> [263,] 130 41 #> [264,] 130 42 #> [265,] 130 43 #> [266,] 130 44 #> [267,] 130 45 #> [268,] 131 46 #> [269,] 131 47 #> [270,] 131 48 #> [271,] 132 49 #> [272,] 132 50 #> [273,] 132 51 #> [274,] 133 52 #> [275,] 133 53 #> [276,] 133 54 #> [277,] 134 55 #> [278,] 135 56 #> [279,] 135 57 #> [280,] 135 58 #> [281,] 135 59 #> [282,] 136 60 #> [283,] 136 61 #> [284,] 135 62 #> [285,] 136 63 #> [286,] 136 64 #> [287,] 136 65 #> [288,] 136 66 #> [289,] 136 67 #> [290,] 135 68 #> [291,] 136 69 #> [292,] 135 70 #> [293,] 135 71 #> [294,] 135 72 #> [295,] 135 73 #> [296,] 135 74 #> [297,] 134 75 #> [298,] 135 76 #> [299,] 134 77 #> [300,] 134 78 #> [301,] 134 79 #> [302,] 134 80 #> [303,] 134 81 #> [304,] 134 82 #> [305,] 134 83 #> [306,] 133 84 #> [307,] 133 85 #> [308,] 134 86 #> [309,] 134 87 #> [310,] 134 88 #> [311,] 133 89 #> [312,] 133 90 #> [313,] 133 91 #> [314,] 133 92 #> [315,] 133 93 #> [316,] 133 94 #> [317,] 133 95 #> [318,] 133 96 #> [319,] 133 97 #> [320,] 133 98 #> [321,] 133 99 #> [322,] 133 100 #> [323,] 133 101 #> [324,] 133 102 #> [325,] 133 103 #> [326,] 133 104 #> [327,] 133 105 #> [328,] 133 106 #> [329,] 133 107 #> [330,] 133 108 #> [331,] 133 109 #> [332,] 134 110 #> [333,] 134 111 #> [334,] 133 112 #> [335,] 134 113 #> [336,] 134 114 #> [337,] 134 115 #> [338,] 134 116 #> [339,] 134 117 #> [340,] 135 118 #> [341,] 135 119 #> [342,] 135 120 #> [343,] 136 121 #> [344,] 136 122 #> [345,] 136 123 #> [346,] 137 124 #> [347,] 137 125 #> [348,] 138 126 #> [349,] 138 127 #> [350,] 139 128 #> [351,] 139 129 #> [352,] 140 130 #> [353,] 140 131 #> [354,] 141 132 #> [355,] 141 133 #> [356,] 142 134 #> [357,] 142 135 #> [358,] 143 136 #> [359,] 143 137 #> [360,] 144 138 #> [361,] 144 139 #> [362,] 145 140 #> [363,] 145 141 #> [364,] 146 142 #> [365,] 147 143 #> [366,] 148 144 #> [367,] 148 145 #> [368,] 149 146 #> [369,] 150 147 #> [370,] 150 148 #> [371,] 151 149 #> [372,] 152 150 #> [373,] 153 151 #> [374,] 154 152 #> [375,] 155 153 #> [376,] 156 154 #> [377,] 157 155 #> [378,] 158 156 #> [379,] 159 157 #> [380,] 160 158 #> [381,] 161 158 #> [382,] 162 159 #> [383,] 163 159 #> [384,] 164 160 #> [385,] 165 160 #> [386,] 166 160 #> [387,] 167 161 #> [388,] 168 161 #> [389,] 169 161 #> [390,] 170 162 #> [391,] 171 162 #> [392,] 172 162 #> [393,] 173 163 #> [394,] 174 164 #> [395,] 175 164 #> [396,] 176 165 #> [397,] 177 165 #> [398,] 178 166 #> [399,] 179 167 #> [400,] 180 167 #> [401,] 181 168 #> [402,] 182 169 #> [403,] 183 170 #> [404,] 184 171 #> [405,] 185 172 #> [406,] 186 173 #> [407,] 187 174 #> [408,] 187 175 #> [409,] 188 176 #> [410,] 189 177 #> [411,] 189 178 #> [412,] 190 179 #> [413,] 190 180 #> [414,] 191 181 #> [415,] 191 182 #> [416,] 191 183 #> [417,] 191 184 #> [418,] 191 185 #> [419,] 191 186 #> [420,] 191 187 #> [421,] 190 188 #> [422,] 191 189 #> [423,] 191 190 #> [424,] 191 191 #> [425,] 191 192 #> [426,] 192 193 #> [427,] 192 194 #> [428,] 192 195 #> [429,] 193 196 #> [430,] 193 197 #> [431,] 194 198 #> [432,] 194 199 #> [433,] 194 200 #> [434,] 195 201 #> [435,] 196 202 #> [436,] 196 203 #> [437,] 197 204 #> [438,] 197 205 #> [439,] 198 206 #> [440,] 199 207 #> [441,] 200 208 #> [442,] 201 209 #> [443,] 202 210 #> [444,] 203 210 #> [445,] 204 211 #> [446,] 205 212 #> [447,] 206 212 #> [448,] 207 213 #> [449,] 208 213 #> [450,] 209 214 #> [451,] 210 215 #> [452,] 211 216 #> [453,] 211 217 #> [454,] 211 218 #> [455,] 212 219 #> [456,] 212 220 #> [457,] 213 221 #> [458,] 213 222 #> [459,] 214 223 #> [460,] 215 224 #> [461,] 215 225 #> [462,] 216 226 #> [463,] 217 227 #> [464,] 217 228 #> [465,] 218 229 #> [466,] 219 230 #> [467,] 220 230 #> [468,] 221 231 #> [469,] 222 231 #> [470,] 223 230 #> [471,] 224 229 #> [472,] 225 228 #> [473,] 225 227 #> [474,] 225 226 #> [475,] 225 225 #> [476,] 226 224 #> [477,] 225 223 #> [478,] 225 222 #> [479,] 225 221 #> [480,] 226 220 #> [481,] 226 219 #> [482,] 226 218 #> [483,] 226 217 #> [484,] 226 216 #> [485,] 226 215 #> [486,] 226 214 #> [487,] 226 213 #> [488,] 226 212 #> [489,] 226 211 #> [490,] 227 211 #> [491,] 228 211 #> [492,] 229 210 #> [493,] 230 210 #> [494,] 231 210 #> [495,] 232 209 #> [496,] 233 209 #> [497,] 234 208 #> [498,] 235 208 #> [499,] 236 207 #> [500,] 237 207 #> [501,] 238 206 #> [502,] 238 205 #> [503,] 239 204 #> [504,] 240 203 #> [505,] 240 202 #> [506,] 241 201 #> [507,] 242 200 #> [508,] 243 199 #> [509,] 244 199 #> [510,] 245 199 #> [511,] 246 198 #> [512,] 247 198 #> [513,] 248 197 #> [514,] 249 196 #> [515,] 249 195 #> [516,] 250 194 #> [517,] 250 193 #> [518,] 249 192 #> [519,] 249 191 #> [520,] 249 190 #> [521,] 248 189 #> [522,] 248 188 #> [523,] 248 187 #> [524,] 247 186 #> [525,] 246 185 #> [526,] 245 184 #> [527,] 244 183 #> [528,] 243 182 #> [529,] 242 181 #> [530,] 241 180 #> [531,] 240 180 #> [532,] 239 179 #> [533,] 238 178 #> [534,] 237 178 #> [535,] 236 177 #> [536,] 235 176 #> [537,] 235 175 #> [538,] 235 174 #> [539,] 235 173 #> [540,] 235 172 #> [541,] 235 171 #> [542,] 235 170 #> [543,] 235 169 #> [544,] 236 168 #> [545,] 235 167 #> [546,] 236 166 #> [547,] 236 165 #> [548,] 236 164 #> [549,] 236 163 #> [550,] 236 162 #> [551,] 237 161 #> [552,] 236 160 #> [553,] 237 159 #> [554,] 237 158 #> [555,] 237 157 #> [556,] 237 156 #> [557,] 237 155 #> [558,] 237 154 #> [559,] 237 153 #> [560,] 238 152 #> [561,] 237 151 #> [562,] 237 150 #> [563,] 237 149 #> [564,] 237 148 #> [565,] 237 147 #> [566,] 238 146 #> [567,] 237 145 #> [568,] 237 144 #> [569,] 237 143 #> [570,] 237 142 #> [571,] 237 141 #> [572,] 237 140 #> [573,] 237 139 #> [574,] 237 138 #> [575,] 236 137 #> [576,] 236 136 #> [577,] 236 135 #> [578,] 235 134 #> [579,] 235 133 #> [580,] 235 132 #> [581,] 234 131 #> [582,] 234 130 #> [583,] 233 129 #> [584,] 232 128 #> [585,] 232 127 #> [586,] 231 126 #> [587,] 230 125 #> [588,] 230 124 #> [589,] 229 123 #> [590,] 228 122 #> [591,] 228 121 #> [592,] 227 120 #> [593,] 226 119 #> [594,] 226 118 #> [595,] 226 117 #> [596,] 225 116 #> [597,] 224 115 #> [598,] 224 114 #> [599,] 224 113 #> [600,] 223 112 #> [601,] 223 111 #> [602,] 223 110 #> [603,] 223 109 #> [604,] 222 108 #> [605,] 222 107 #> [606,] 222 106 #> [607,] 222 105 #> [608,] 222 104 #> [609,] 221 103 #> [610,] 221 102 #> [611,] 221 101 #> [612,] 221 100 #> [613,] 221 99 #> [614,] 221 98 #> [615,] 221 97 #> [616,] 221 96 #> [617,] 221 95 #> [618,] 221 94 #> [619,] 221 93 #> [620,] 221 92 #> [621,] 221 91 #> [622,] 221 90 #> [623,] 221 89 #> [624,] 221 88 #> [625,] 221 87 #> [626,] 221 86 #> [627,] 221 85 #> [628,] 221 84 #> [629,] 221 83 #> [630,] 221 82 #> [631,] 221 81 #> [632,] 221 80 #> [633,] 221 79 #> [634,] 221 78 #> [635,] 221 77 #> [636,] 221 76 #> [637,] 221 75 #> [638,] 221 74 #> [639,] 221 73 #> [640,] 221 72 #> [641,] 221 71 #> [642,] 221 70 #> [643,] 222 69 #> [644,] 222 68 #> [645,] 222 67 #> [646,] 222 66 #> [647,] 222 65 #> [648,] 222 64 #> [649,] 222 63 #> [650,] 223 62 #> [651,] 224 62 #> [652,] 225 61 #> [653,] 226 61 #> [654,] 227 61 #> [655,] 228 61 #> [656,] 229 60 #> [657,] 230 60 #> [658,] 231 60 #> [659,] 232 59 #> [660,] 232 58 #> [661,] 233 57 #> [662,] 232 56 #> [663,] 232 55 #> [664,] 231 54 #> [665,] 230 53 #> [666,] 229 52 #> [667,] 230 51 #> [668,] 229 50 #> [669,] 230 49 #> [670,] 229 48 #> [671,] 228 47 #> [672,] 227 46 #> [673,] 226 46 #> [674,] 225 45 #> [675,] 224 45 #> [676,] 223 45 #> [677,] 222 45 #> [678,] 221 45 #> [679,] 220 45 #> [680,] 219 45 #> [681,] 218 45 #> [682,] 217 45 #> [683,] 216 45 #> [684,] 215 46 #> [685,] 214 46 #> [686,] 213 47 #> [687,] 212 48 #> [688,] 211 49 #> [689,] 210 50 #> [690,] 209 51 #> [691,] 208 52 #> [692,] 208 53 #> [693,] 207 54 #> [694,] 206 55 #> [695,] 206 56 #> [696,] 205 57 #> [697,] 205 58 #> [698,] 204 59 #> [699,] 204 60 #> [700,] 203 61 #> [701,] 203 62 #> [702,] 203 63 #> [703,] 202 64 #> [704,] 202 65 #> [705,] 202 66 #> [706,] 201 66 #> [707,] 201 65 #> [708,] 201 64 #> [709,] 201 63 #> [710,] 200 62 #> #> $caney #> [,1] [,2] #> [1,] 200 75 #> [2,] 199 74 #> [3,] 199 73 #> [4,] 198 72 #> [5,] 197 71 #> [6,] 197 70 #> [7,] 196 69 #> [8,] 195 68 #> [9,] 194 67 #> [10,] 194 66 #> [11,] 193 65 #> [12,] 192 64 #> [13,] 192 63 #> [14,] 191 62 #> [15,] 190 61 #> [16,] 190 60 #> [17,] 189 59 #> [18,] 188 58 #> [19,] 188 57 #> [20,] 187 56 #> [21,] 187 55 #> [22,] 186 54 #> [23,] 185 53 #> [24,] 185 52 #> [25,] 184 51 #> [26,] 183 50 #> [27,] 183 49 #> [28,] 183 48 #> [29,] 182 47 #> [30,] 181 46 #> [31,] 180 46 #> [32,] 179 47 #> [33,] 179 48 #> [34,] 178 49 #> [35,] 177 50 #> [36,] 176 51 #> [37,] 175 52 #> [38,] 174 53 #> [39,] 173 54 #> [40,] 173 55 #> [41,] 172 56 #> [42,] 171 57 #> [43,] 170 58 #> [44,] 169 59 #> [45,] 168 60 #> [46,] 167 61 #> [47,] 166 62 #> [48,] 165 63 #> [49,] 164 64 #> [50,] 163 65 #> [51,] 162 66 #> [52,] 161 67 #> [53,] 160 68 #> [54,] 159 69 #> [55,] 158 70 #> [56,] 157 71 #> [57,] 156 72 #> [58,] 155 73 #> [59,] 154 74 #> [60,] 153 75 #> [61,] 152 76 #> [62,] 151 77 #> [63,] 150 78 #> [64,] 149 79 #> [65,] 148 80 #> [66,] 147 81 #> [67,] 146 82 #> [68,] 145 82 #> [69,] 144 83 #> [70,] 143 84 #> [71,] 142 85 #> [72,] 141 86 #> [73,] 140 87 #> [74,] 139 87 #> [75,] 138 88 #> [76,] 137 89 #> [77,] 136 90 #> [78,] 135 91 #> [79,] 134 91 #> [80,] 133 92 #> [81,] 132 93 #> [82,] 131 94 #> [83,] 130 94 #> [84,] 129 95 #> [85,] 128 96 #> [86,] 127 96 #> [87,] 126 97 #> [88,] 125 98 #> [89,] 124 98 #> [90,] 123 99 #> [91,] 122 100 #> [92,] 121 100 #> [93,] 120 101 #> [94,] 119 101 #> [95,] 118 102 #> [96,] 117 102 #> [97,] 116 103 #> [98,] 115 104 #> [99,] 114 104 #> [100,] 113 105 #> [101,] 112 105 #> [102,] 111 106 #> [103,] 110 106 #> [104,] 109 107 #> [105,] 108 107 #> [106,] 107 107 #> [107,] 106 108 #> [108,] 105 108 #> [109,] 104 109 #> [110,] 105 110 #> [111,] 106 111 #> [112,] 107 111 #> [113,] 108 112 #> [114,] 109 113 #> [115,] 110 113 #> [116,] 111 114 #> [117,] 112 114 #> [118,] 113 115 #> [119,] 114 116 #> [120,] 115 116 #> [121,] 116 117 #> [122,] 117 117 #> [123,] 118 118 #> [124,] 119 119 #> [125,] 120 119 #> [126,] 121 120 #> [127,] 122 120 #> [128,] 123 121 #> [129,] 124 122 #> [130,] 125 122 #> [131,] 126 123 #> [132,] 127 123 #> [133,] 128 124 #> [134,] 129 125 #> [135,] 130 125 #> [136,] 131 126 #> [137,] 132 127 #> [138,] 133 127 #> [139,] 134 128 #> [140,] 135 128 #> [141,] 136 129 #> [142,] 137 130 #> [143,] 138 130 #> [144,] 139 131 #> [145,] 140 131 #> [146,] 141 132 #> [147,] 142 133 #> [148,] 143 133 #> [149,] 144 134 #> [150,] 145 134 #> [151,] 146 135 #> [152,] 147 136 #> [153,] 148 136 #> [154,] 149 137 #> [155,] 150 138 #> [156,] 151 138 #> [157,] 152 139 #> [158,] 153 139 #> [159,] 154 139 #> [160,] 155 138 #> [161,] 155 137 #> [162,] 156 136 #> [163,] 156 135 #> [164,] 157 134 #> [165,] 157 133 #> [166,] 158 132 #> [167,] 158 131 #> [168,] 159 130 #> [169,] 159 129 #> [170,] 160 128 #> [171,] 160 127 #> [172,] 161 126 #> [173,] 161 125 #> [174,] 162 124 #> [175,] 162 123 #> [176,] 163 122 #> [177,] 163 121 #> [178,] 164 120 #> [179,] 164 119 #> [180,] 165 118 #> [181,] 166 117 #> [182,] 166 116 #> [183,] 167 115 #> [184,] 167 114 #> [185,] 168 113 #> [186,] 168 112 #> [187,] 169 111 #> [188,] 169 110 #> [189,] 170 109 #> [190,] 170 108 #> [191,] 171 107 #> [192,] 171 106 #> [193,] 172 105 #> [194,] 172 104 #> [195,] 173 103 #> [196,] 173 102 #> [197,] 174 101 #> [198,] 174 100 #> [199,] 175 99 #> [200,] 175 98 #> [201,] 176 97 #> [202,] 176 96 #> [203,] 177 95 #> [204,] 177 94 #> [205,] 178 94 #> [206,] 178 95 #> [207,] 179 96 #> [208,] 179 97 #> [209,] 180 98 #> [210,] 180 99 #> [211,] 181 100 #> [212,] 181 101 #> [213,] 182 102 #> [214,] 182 103 #> [215,] 183 104 #> [216,] 183 105 #> [217,] 184 106 #> [218,] 184 107 #> [219,] 184 108 #> [220,] 185 109 #> [221,] 186 110 #> [222,] 186 111 #> [223,] 187 112 #> [224,] 187 113 #> [225,] 187 114 #> [226,] 188 115 #> [227,] 189 116 #> [228,] 189 117 #> [229,] 190 118 #> [230,] 190 119 #> [231,] 190 120 #> [232,] 191 121 #> [233,] 192 122 #> [234,] 192 123 #> [235,] 193 124 #> [236,] 193 125 #> [237,] 194 126 #> [238,] 195 127 #> [239,] 195 128 #> [240,] 195 129 #> [241,] 196 130 #> [242,] 197 131 #> [243,] 197 132 #> [244,] 198 133 #> [245,] 199 134 #> [246,] 199 135 #> [247,] 200 136 #> [248,] 200 137 #> [249,] 201 138 #> [250,] 201 139 #> [251,] 202 140 #> [252,] 203 141 #> [253,] 203 142 #> [254,] 204 143 #> [255,] 204 144 #> [256,] 205 145 #> [257,] 206 146 #> [258,] 207 147 #> [259,] 207 148 #> [260,] 208 149 #> [261,] 209 150 #> [262,] 209 151 #> [263,] 210 152 #> [264,] 211 153 #> [265,] 211 154 #> [266,] 212 155 #> [267,] 213 156 #> [268,] 213 157 #> [269,] 214 158 #> [270,] 215 159 #> [271,] 215 160 #> [272,] 216 161 #> [273,] 217 162 #> [274,] 218 163 #> [275,] 218 164 #> [276,] 219 165 #> [277,] 220 166 #> [278,] 221 167 #> [279,] 221 168 #> [280,] 222 169 #> [281,] 223 170 #> [282,] 224 171 #> [283,] 224 172 #> [284,] 225 173 #> [285,] 226 174 #> [286,] 227 175 #> [287,] 228 176 #> [288,] 229 177 #> [289,] 229 178 #> [290,] 230 179 #> [291,] 231 180 #> [292,] 232 181 #> [293,] 233 182 #> [294,] 234 183 #> [295,] 235 184 #> [296,] 235 185 #> [297,] 236 186 #> [298,] 237 187 #> [299,] 238 188 #> [300,] 239 189 #> [301,] 240 190 #> [302,] 241 191 #> [303,] 242 192 #> [304,] 243 193 #> [305,] 244 194 #> [306,] 245 195 #> [307,] 246 196 #> [308,] 247 197 #> [309,] 248 198 #> [310,] 249 198 #> [311,] 250 199 #> [312,] 251 200 #> [313,] 252 201 #> [314,] 253 202 #> [315,] 254 203 #> [316,] 255 204 #> [317,] 256 205 #> [318,] 257 205 #> [319,] 258 206 #> [320,] 259 207 #> [321,] 260 208 #> [322,] 261 208 #> [323,] 262 209 #> [324,] 263 210 #> [325,] 264 211 #> [326,] 265 211 #> [327,] 266 212 #> [328,] 267 213 #> [329,] 268 213 #> [330,] 269 214 #> [331,] 270 214 #> [332,] 271 215 #> [333,] 272 216 #> [334,] 273 216 #> [335,] 274 217 #> [336,] 275 217 #> [337,] 276 218 #> [338,] 277 219 #> [339,] 278 219 #> [340,] 279 218 #> [341,] 279 217 #> [342,] 279 216 #> [343,] 279 215 #> [344,] 278 214 #> [345,] 278 213 #> [346,] 278 212 #> [347,] 279 211 #> [348,] 278 210 #> [349,] 278 209 #> [350,] 278 208 #> [351,] 278 207 #> [352,] 278 206 #> [353,] 278 205 #> [354,] 277 204 #> [355,] 277 203 #> [356,] 278 202 #> [357,] 277 201 #> [358,] 277 200 #> [359,] 277 199 #> [360,] 277 198 #> [361,] 277 197 #> [362,] 277 196 #> [363,] 276 195 #> [364,] 276 194 #> [365,] 276 193 #> [366,] 277 192 #> [367,] 277 191 #> [368,] 276 190 #> [369,] 276 189 #> [370,] 276 188 #> [371,] 276 187 #> [372,] 276 186 #> [373,] 276 185 #> [374,] 276 184 #> [375,] 276 183 #> [376,] 276 182 #> [377,] 276 181 #> [378,] 276 180 #> [379,] 276 179 #> [380,] 276 178 #> [381,] 276 177 #> [382,] 276 176 #> [383,] 277 175 #> [384,] 276 174 #> [385,] 276 173 #> [386,] 277 172 #> [387,] 277 171 #> [388,] 277 170 #> [389,] 277 169 #> [390,] 277 168 #> [391,] 277 167 #> [392,] 278 166 #> [393,] 278 165 #> [394,] 278 164 #> [395,] 278 163 #> [396,] 279 162 #> [397,] 279 161 #> [398,] 279 160 #> [399,] 280 159 #> [400,] 280 158 #> [401,] 280 157 #> [402,] 281 156 #> [403,] 281 155 #> [404,] 282 154 #> [405,] 282 153 #> [406,] 281 152 #> [407,] 280 152 #> [408,] 279 152 #> [409,] 278 151 #> [410,] 277 151 #> [411,] 276 150 #> [412,] 275 150 #> [413,] 274 150 #> [414,] 273 149 #> [415,] 272 148 #> [416,] 271 148 #> [417,] 270 147 #> [418,] 269 146 #> [419,] 268 146 #> [420,] 267 145 #> [421,] 266 145 #> [422,] 265 144 #> [423,] 264 143 #> [424,] 263 142 #> [425,] 262 142 #> [426,] 261 141 #> [427,] 260 140 #> [428,] 259 139 #> [429,] 258 139 #> [430,] 257 138 #> [431,] 256 137 #> [432,] 255 136 #> [433,] 254 135 #> [434,] 253 134 #> [435,] 252 133 #> [436,] 251 133 #> [437,] 250 132 #> [438,] 249 131 #> [439,] 248 130 #> [440,] 247 129 #> [441,] 246 128 #> [442,] 245 127 #> [443,] 244 126 #> [444,] 243 125 #> [445,] 242 124 #> [446,] 241 123 #> [447,] 240 122 #> [448,] 239 121 #> [449,] 238 120 #> [450,] 237 119 #> [451,] 236 118 #> [452,] 235 117 #> [453,] 234 116 #> [454,] 233 115 #> [455,] 232 114 #> [456,] 231 113 #> [457,] 231 112 #> [458,] 230 111 #> [459,] 229 110 #> [460,] 228 109 #> [461,] 227 108 #> [462,] 226 107 #> [463,] 225 106 #> [464,] 224 105 #> [465,] 223 104 #> [466,] 223 103 #> [467,] 222 102 #> [468,] 221 101 #> [469,] 220 100 #> [470,] 219 99 #> [471,] 218 98 #> [472,] 218 97 #> [473,] 217 96 #> [474,] 216 95 #> [475,] 215 94 #> [476,] 214 93 #> [477,] 213 92 #> [478,] 213 91 #> [479,] 212 90 #> [480,] 211 89 #> [481,] 210 88 #> [482,] 209 87 #> [483,] 209 86 #> [484,] 208 85 #> [485,] 207 84 #> [486,] 206 83 #> [487,] 205 82 #> [488,] 205 81 #> [489,] 204 80 #> [490,] 203 79 #> [491,] 202 78 #> [492,] 202 77 #> [493,] 201 76 #> [494,] 200 75 #> #> $chimay #> [,1] [,2] #> [1,] 200 76 #> [2,] 200 75 #> [3,] 199 74 #> [4,] 198 73 #> [5,] 198 72 #> [6,] 197 71 #> [7,] 197 70 #> [8,] 196 69 #> [9,] 195 68 #> [10,] 195 67 #> [11,] 194 66 #> [12,] 194 65 #> [13,] 193 64 #> [14,] 192 63 #> [15,] 192 62 #> [16,] 191 61 #> [17,] 190 60 #> [18,] 190 59 #> [19,] 189 58 #> [20,] 189 57 #> [21,] 188 56 #> [22,] 187 55 #> [23,] 187 54 #> [24,] 186 53 #> [25,] 186 52 #> [26,] 185 51 #> [27,] 184 50 #> [28,] 184 49 #> [29,] 183 48 #> [30,] 183 47 #> [31,] 182 46 #> [32,] 181 45 #> [33,] 181 44 #> [34,] 181 43 #> [35,] 180 42 #> [36,] 179 41 #> [37,] 179 40 #> [38,] 178 39 #> [39,] 177 38 #> [40,] 176 37 #> [41,] 175 37 #> [42,] 174 37 #> [43,] 173 37 #> [44,] 172 37 #> [45,] 171 37 #> [46,] 170 37 #> [47,] 169 37 #> [48,] 168 37 #> [49,] 167 37 #> [50,] 166 37 #> [51,] 165 37 #> [52,] 164 37 #> [53,] 163 37 #> [54,] 162 37 #> [55,] 161 37 #> [56,] 160 37 #> [57,] 159 37 #> [58,] 158 37 #> [59,] 157 37 #> [60,] 156 37 #> [61,] 155 37 #> [62,] 154 37 #> [63,] 153 37 #> [64,] 152 37 #> [65,] 151 37 #> [66,] 150 37 #> [67,] 149 37 #> [68,] 148 37 #> [69,] 147 37 #> [70,] 146 37 #> [71,] 145 37 #> [72,] 144 37 #> [73,] 143 37 #> [74,] 142 37 #> [75,] 141 37 #> [76,] 140 37 #> [77,] 139 37 #> [78,] 138 37 #> [79,] 137 37 #> [80,] 136 37 #> [81,] 135 37 #> [82,] 134 37 #> [83,] 133 37 #> [84,] 132 37 #> [85,] 131 37 #> [86,] 130 37 #> [87,] 129 37 #> [88,] 128 37 #> [89,] 127 37 #> [90,] 126 37 #> [91,] 125 37 #> [92,] 124 37 #> [93,] 123 37 #> [94,] 122 37 #> [95,] 121 37 #> [96,] 120 37 #> [97,] 119 37 #> [98,] 118 37 #> [99,] 117 37 #> [100,] 116 37 #> [101,] 115 37 #> [102,] 114 37 #> [103,] 113 37 #> [104,] 112 37 #> [105,] 111 37 #> [106,] 110 37 #> [107,] 109 37 #> [108,] 108 37 #> [109,] 107 37 #> [110,] 106 37 #> [111,] 105 37 #> [112,] 104 37 #> [113,] 103 37 #> [114,] 102 38 #> [115,] 103 39 #> [116,] 103 40 #> [117,] 104 41 #> [118,] 104 42 #> [119,] 105 43 #> [120,] 106 44 #> [121,] 106 45 #> [122,] 107 46 #> [123,] 107 47 #> [124,] 108 48 #> [125,] 108 49 #> [126,] 109 50 #> [127,] 110 51 #> [128,] 110 52 #> [129,] 111 53 #> [130,] 111 54 #> [131,] 112 55 #> [132,] 113 56 #> [133,] 113 57 #> [134,] 113 58 #> [135,] 114 59 #> [136,] 115 60 #> [137,] 115 61 #> [138,] 116 62 #> [139,] 117 63 #> [140,] 117 64 #> [141,] 117 65 #> [142,] 118 66 #> [143,] 119 67 #> [144,] 119 68 #> [145,] 120 69 #> [146,] 121 70 #> [147,] 121 71 #> [148,] 121 72 #> [149,] 122 73 #> [150,] 123 74 #> [151,] 123 75 #> [152,] 124 76 #> [153,] 125 77 #> [154,] 125 78 #> [155,] 126 79 #> [156,] 126 80 #> [157,] 127 81 #> [158,] 127 82 #> [159,] 128 83 #> [160,] 129 84 #> [161,] 129 85 #> [162,] 130 86 #> [163,] 130 87 #> [164,] 131 88 #> [165,] 131 89 #> [166,] 132 90 #> [167,] 132 91 #> [168,] 133 92 #> [169,] 134 93 #> [170,] 134 94 #> [171,] 135 95 #> [172,] 136 96 #> [173,] 136 97 #> [174,] 136 98 #> [175,] 137 99 #> [176,] 138 100 #> [177,] 138 101 #> [178,] 139 102 #> [179,] 140 103 #> [180,] 140 104 #> [181,] 140 105 #> [182,] 141 106 #> [183,] 142 107 #> [184,] 142 108 #> [185,] 143 109 #> [186,] 144 110 #> [187,] 144 111 #> [188,] 145 112 #> [189,] 145 113 #> [190,] 146 114 #> [191,] 146 115 #> [192,] 147 116 #> [193,] 148 117 #> [194,] 148 118 #> [195,] 149 119 #> [196,] 149 120 #> [197,] 150 121 #> [198,] 150 122 #> [199,] 151 123 #> [200,] 151 124 #> [201,] 152 125 #> [202,] 153 126 #> [203,] 153 127 #> [204,] 152 128 #> [205,] 151 129 #> [206,] 151 130 #> [207,] 150 131 #> [208,] 149 132 #> [209,] 149 133 #> [210,] 149 134 #> [211,] 148 135 #> [212,] 147 136 #> [213,] 147 137 #> [214,] 146 138 #> [215,] 145 139 #> [216,] 145 140 #> [217,] 145 141 #> [218,] 144 142 #> [219,] 143 143 #> [220,] 143 144 #> [221,] 142 145 #> [222,] 141 146 #> [223,] 141 147 #> [224,] 141 148 #> [225,] 140 149 #> [226,] 139 150 #> [227,] 139 151 #> [228,] 138 152 #> [229,] 137 153 #> [230,] 137 154 #> [231,] 137 155 #> [232,] 136 156 #> [233,] 135 157 #> [234,] 135 158 #> [235,] 134 159 #> [236,] 133 160 #> [237,] 133 161 #> [238,] 133 162 #> [239,] 132 163 #> [240,] 131 164 #> [241,] 131 165 #> [242,] 130 166 #> [243,] 129 167 #> [244,] 129 168 #> [245,] 129 169 #> [246,] 128 170 #> [247,] 127 171 #> [248,] 127 172 #> [249,] 126 173 #> [250,] 125 174 #> [251,] 125 175 #> [252,] 125 176 #> [253,] 124 177 #> [254,] 123 178 #> [255,] 123 179 #> [256,] 122 180 #> [257,] 121 181 #> [258,] 121 182 #> [259,] 121 183 #> [260,] 120 184 #> [261,] 119 185 #> [262,] 119 186 #> [263,] 118 187 #> [264,] 117 188 #> [265,] 117 189 #> [266,] 117 190 #> [267,] 116 191 #> [268,] 115 192 #> [269,] 115 193 #> [270,] 114 194 #> [271,] 113 195 #> [272,] 113 196 #> [273,] 113 197 #> [274,] 112 198 #> [275,] 111 199 #> [276,] 111 200 #> [277,] 110 201 #> [278,] 109 202 #> [279,] 109 203 #> [280,] 109 204 #> [281,] 108 205 #> [282,] 107 206 #> [283,] 107 207 #> [284,] 106 208 #> [285,] 105 209 #> [286,] 105 210 #> [287,] 105 211 #> [288,] 106 212 #> [289,] 107 212 #> [290,] 108 212 #> [291,] 109 212 #> [292,] 110 212 #> [293,] 111 212 #> [294,] 112 212 #> [295,] 113 212 #> [296,] 114 212 #> [297,] 115 212 #> [298,] 116 212 #> [299,] 117 212 #> [300,] 118 212 #> [301,] 119 212 #> [302,] 120 212 #> [303,] 121 212 #> [304,] 122 212 #> [305,] 123 212 #> [306,] 124 212 #> [307,] 125 212 #> [308,] 126 212 #> [309,] 127 212 #> [310,] 128 212 #> [311,] 129 212 #> [312,] 130 212 #> [313,] 131 212 #> [314,] 132 212 #> [315,] 133 212 #> [316,] 134 212 #> [317,] 135 212 #> [318,] 136 212 #> [319,] 137 212 #> [320,] 138 212 #> [321,] 139 212 #> [322,] 140 212 #> [323,] 141 212 #> [324,] 142 212 #> [325,] 143 212 #> [326,] 144 212 #> [327,] 145 212 #> [328,] 146 212 #> [329,] 147 212 #> [330,] 148 212 #> [331,] 149 212 #> [332,] 150 212 #> [333,] 151 212 #> [334,] 152 212 #> [335,] 153 212 #> [336,] 154 212 #> [337,] 155 212 #> [338,] 156 212 #> [339,] 157 212 #> [340,] 158 212 #> [341,] 159 212 #> [342,] 160 212 #> [343,] 161 212 #> [344,] 162 212 #> [345,] 163 212 #> [346,] 164 212 #> [347,] 165 212 #> [348,] 166 212 #> [349,] 167 212 #> [350,] 168 212 #> [351,] 169 212 #> [352,] 170 212 #> [353,] 171 212 #> [354,] 172 212 #> [355,] 173 212 #> [356,] 174 212 #> [357,] 175 212 #> [358,] 176 212 #> [359,] 177 212 #> [360,] 178 212 #> [361,] 179 212 #> [362,] 180 211 #> [363,] 181 210 #> [364,] 181 209 #> [365,] 182 208 #> [366,] 182 207 #> [367,] 183 206 #> [368,] 184 205 #> [369,] 184 204 #> [370,] 185 203 #> [371,] 186 202 #> [372,] 186 201 #> [373,] 187 200 #> [374,] 188 199 #> [375,] 188 198 #> [376,] 189 197 #> [377,] 189 196 #> [378,] 190 195 #> [379,] 191 194 #> [380,] 191 193 #> [381,] 192 192 #> [382,] 192 191 #> [383,] 193 190 #> [384,] 194 189 #> [385,] 194 188 #> [386,] 195 187 #> [387,] 195 186 #> [388,] 196 185 #> [389,] 197 184 #> [390,] 197 183 #> [391,] 198 182 #> [392,] 198 181 #> [393,] 199 180 #> [394,] 200 179 #> [395,] 200 178 #> [396,] 201 177 #> [397,] 201 176 #> [398,] 202 175 #> [399,] 203 174 #> [400,] 203 173 #> [401,] 204 173 #> [402,] 204 174 #> [403,] 205 175 #> [404,] 205 176 #> [405,] 206 177 #> [406,] 206 178 #> [407,] 207 179 #> [408,] 207 180 #> [409,] 208 181 #> [410,] 209 182 #> [411,] 209 183 #> [412,] 210 184 #> [413,] 211 185 #> [414,] 211 186 #> [415,] 212 187 #> [416,] 212 188 #> [417,] 213 189 #> [418,] 214 190 #> [419,] 214 191 #> [420,] 214 192 #> [421,] 215 193 #> [422,] 216 194 #> [423,] 216 195 #> [424,] 217 196 #> [425,] 217 197 #> [426,] 218 198 #> [427,] 219 199 #> [428,] 219 200 #> [429,] 220 201 #> [430,] 221 202 #> [431,] 221 203 #> [432,] 222 204 #> [433,] 222 205 #> [434,] 223 206 #> [435,] 224 207 #> [436,] 224 208 #> [437,] 224 209 #> [438,] 225 210 #> [439,] 226 211 #> [440,] 227 212 #> [441,] 228 212 #> [442,] 229 212 #> [443,] 230 212 #> [444,] 231 212 #> [445,] 232 212 #> [446,] 233 212 #> [447,] 234 212 #> [448,] 235 212 #> [449,] 236 212 #> [450,] 237 212 #> [451,] 238 212 #> [452,] 239 212 #> [453,] 240 212 #> [454,] 241 212 #> [455,] 242 212 #> [456,] 243 212 #> [457,] 244 212 #> [458,] 245 212 #> [459,] 246 212 #> [460,] 247 212 #> [461,] 248 212 #> [462,] 249 212 #> [463,] 250 212 #> [464,] 251 212 #> [465,] 252 212 #> [466,] 253 212 #> [467,] 254 212 #> [468,] 255 212 #> [469,] 256 212 #> [470,] 257 212 #> [471,] 258 212 #> [472,] 259 212 #> [473,] 260 212 #> [474,] 261 212 #> [475,] 262 212 #> [476,] 263 212 #> [477,] 264 212 #> [478,] 265 212 #> [479,] 266 212 #> [480,] 267 212 #> [481,] 268 212 #> [482,] 269 212 #> [483,] 270 212 #> [484,] 271 212 #> [485,] 272 212 #> [486,] 273 212 #> [487,] 274 212 #> [488,] 275 212 #> [489,] 276 212 #> [490,] 277 212 #> [491,] 278 212 #> [492,] 279 212 #> [493,] 280 212 #> [494,] 281 212 #> [495,] 282 212 #> [496,] 283 212 #> [497,] 284 212 #> [498,] 285 212 #> [499,] 286 212 #> [500,] 287 212 #> [501,] 288 212 #> [502,] 289 212 #> [503,] 290 212 #> [504,] 291 212 #> [505,] 292 212 #> [506,] 293 212 #> [507,] 294 212 #> [508,] 295 212 #> [509,] 296 212 #> [510,] 297 212 #> [511,] 298 212 #> [512,] 299 212 #> [513,] 300 211 #> [514,] 299 210 #> [515,] 299 209 #> [516,] 298 208 #> [517,] 297 207 #> [518,] 297 206 #> [519,] 297 205 #> [520,] 296 204 #> [521,] 295 203 #> [522,] 295 202 #> [523,] 294 201 #> [524,] 293 200 #> [525,] 293 199 #> [526,] 292 198 #> [527,] 292 197 #> [528,] 291 196 #> [529,] 291 195 #> [530,] 290 194 #> [531,] 289 193 #> [532,] 289 192 #> [533,] 288 191 #> [534,] 288 190 #> [535,] 287 189 #> [536,] 287 188 #> [537,] 286 187 #> [538,] 285 186 #> [539,] 285 185 #> [540,] 284 184 #> [541,] 284 183 #> [542,] 283 182 #> [543,] 282 181 #> [544,] 282 180 #> [545,] 282 179 #> [546,] 281 178 #> [547,] 280 177 #> [548,] 280 176 #> [549,] 279 175 #> [550,] 278 174 #> [551,] 278 173 #> [552,] 278 172 #> [553,] 277 171 #> [554,] 276 170 #> [555,] 276 169 #> [556,] 275 168 #> [557,] 274 167 #> [558,] 274 166 #> [559,] 274 165 #> [560,] 273 164 #> [561,] 272 163 #> [562,] 272 162 #> [563,] 271 161 #> [564,] 270 160 #> [565,] 270 159 #> [566,] 269 158 #> [567,] 269 157 #> [568,] 268 156 #> [569,] 268 155 #> [570,] 267 154 #> [571,] 266 153 #> [572,] 266 152 #> [573,] 265 151 #> [574,] 265 150 #> [575,] 264 149 #> [576,] 264 148 #> [577,] 263 147 #> [578,] 262 146 #> [579,] 262 145 #> [580,] 261 144 #> [581,] 261 143 #> [582,] 260 142 #> [583,] 259 141 #> [584,] 259 140 #> [585,] 259 139 #> [586,] 258 138 #> [587,] 257 137 #> [588,] 257 136 #> [589,] 256 135 #> [590,] 255 134 #> [591,] 255 133 #> [592,] 255 132 #> [593,] 254 131 #> [594,] 253 130 #> [595,] 253 129 #> [596,] 252 128 #> [597,] 251 127 #> [598,] 251 126 #> [599,] 252 125 #> [600,] 253 124 #> [601,] 253 123 #> [602,] 253 122 #> [603,] 254 121 #> [604,] 255 120 #> [605,] 255 119 #> [606,] 256 118 #> [607,] 257 117 #> [608,] 257 116 #> [609,] 257 115 #> [610,] 258 114 #> [611,] 259 113 #> [612,] 259 112 #> [613,] 260 111 #> [614,] 260 110 #> [615,] 261 109 #> [616,] 262 108 #> [617,] 262 107 #> [618,] 263 106 #> [619,] 263 105 #> [620,] 264 104 #> [621,] 264 103 #> [622,] 265 102 #> [623,] 266 101 #> [624,] 266 100 #> [625,] 267 99 #> [626,] 267 98 #> [627,] 268 97 #> [628,] 268 96 #> [629,] 269 95 #> [630,] 270 94 #> [631,] 270 93 #> [632,] 271 92 #> [633,] 272 91 #> [634,] 272 90 #> [635,] 272 89 #> [636,] 273 88 #> [637,] 274 87 #> [638,] 274 86 #> [639,] 275 85 #> [640,] 276 84 #> [641,] 276 83 #> [642,] 276 82 #> [643,] 277 81 #> [644,] 278 80 #> [645,] 278 79 #> [646,] 279 78 #> [647,] 279 77 #> [648,] 280 76 #> [649,] 281 75 #> [650,] 281 74 #> [651,] 282 73 #> [652,] 282 72 #> [653,] 283 71 #> [654,] 283 70 #> [655,] 284 69 #> [656,] 285 68 #> [657,] 285 67 #> [658,] 286 66 #> [659,] 286 65 #> [660,] 287 64 #> [661,] 287 63 #> [662,] 288 62 #> [663,] 289 61 #> [664,] 289 60 #> [665,] 290 59 #> [666,] 291 58 #> [667,] 291 57 #> [668,] 291 56 #> [669,] 292 55 #> [670,] 293 54 #> [671,] 293 53 #> [672,] 294 52 #> [673,] 295 51 #> [674,] 295 50 #> [675,] 295 49 #> [676,] 296 48 #> [677,] 297 47 #> [678,] 297 46 #> [679,] 298 45 #> [680,] 299 44 #> [681,] 299 43 #> [682,] 300 42 #> [683,] 300 41 #> [684,] 301 40 #> [685,] 301 39 #> [686,] 302 38 #> [687,] 301 37 #> [688,] 300 37 #> [689,] 299 37 #> [690,] 298 37 #> [691,] 297 37 #> [692,] 296 37 #> [693,] 295 37 #> [694,] 294 37 #> [695,] 293 37 #> [696,] 292 37 #> [697,] 291 37 #> [698,] 290 37 #> [699,] 289 37 #> [700,] 288 37 #> [701,] 287 37 #> [702,] 286 37 #> [703,] 285 37 #> [704,] 284 37 #> [705,] 283 37 #> [706,] 282 37 #> [707,] 281 37 #> [708,] 280 37 #> [709,] 279 37 #> [710,] 278 37 #> [711,] 277 37 #> [712,] 276 37 #> [713,] 275 37 #> [714,] 274 37 #> [715,] 273 37 #> [716,] 272 37 #> [717,] 271 37 #> [718,] 270 37 #> [719,] 269 37 #> [720,] 268 37 #> [721,] 267 37 #> [722,] 266 37 #> [723,] 265 37 #> [724,] 264 37 #> [725,] 263 37 #> [726,] 262 37 #> [727,] 261 37 #> [728,] 260 37 #> [729,] 259 37 #> [730,] 258 37 #> [731,] 257 37 #> [732,] 256 37 #> [733,] 255 37 #> [734,] 254 37 #> [735,] 253 37 #> [736,] 252 37 #> [737,] 251 37 #> [738,] 250 37 #> [739,] 249 37 #> [740,] 248 37 #> [741,] 247 37 #> [742,] 246 37 #> [743,] 245 37 #> [744,] 244 37 #> [745,] 243 37 #> [746,] 242 37 #> [747,] 241 37 #> [748,] 240 37 #> [749,] 239 37 #> [750,] 238 37 #> [751,] 237 37 #> [752,] 236 37 #> [753,] 235 37 #> [754,] 234 37 #> [755,] 233 37 #> [756,] 232 37 #> [757,] 231 37 #> [758,] 230 37 #> [759,] 229 37 #> [760,] 228 37 #> [761,] 227 37 #> [762,] 226 37 #> [763,] 225 38 #> [764,] 225 39 #> [765,] 224 40 #> [766,] 224 41 #> [767,] 223 42 #> [768,] 222 43 #> [769,] 222 44 #> [770,] 221 45 #> [771,] 221 46 #> [772,] 220 47 #> [773,] 219 48 #> [774,] 219 49 #> [775,] 218 50 #> [776,] 218 51 #> [777,] 217 52 #> [778,] 216 53 #> [779,] 216 54 #> [780,] 215 55 #> [781,] 214 56 #> [782,] 214 57 #> [783,] 213 58 #> [784,] 213 59 #> [785,] 212 60 #> [786,] 211 61 #> [787,] 211 62 #> [788,] 210 63 #> [789,] 210 64 #> [790,] 209 65 #> [791,] 208 66 #> [792,] 208 67 #> [793,] 207 68 #> [794,] 207 69 #> [795,] 206 70 #> [796,] 205 71 #> [797,] 205 72 #> [798,] 205 73 #> [799,] 204 74 #> [800,] 203 75 #> [801,] 203 76 #> [802,] 202 77 #> [803,] 202 78 #> [804,] 201 78 #> [805,] 201 77 #> [806,] 200 76 #> #> $corona #> [,1] [,2] #> [1,] 200 106 #> [2,] 199 105 #> [3,] 198 105 #> [4,] 197 106 #> [5,] 196 105 #> [6,] 195 105 #> [7,] 194 105 #> [8,] 193 106 #> [9,] 192 106 #> [10,] 191 106 #> [11,] 190 106 #> [12,] 189 106 #> [13,] 188 106 #> [14,] 187 106 #> [15,] 186 106 #> [16,] 185 106 #> [17,] 184 106 #> [18,] 183 106 #> [19,] 182 106 #> [20,] 181 106 #> [21,] 180 106 #> [22,] 179 106 #> [23,] 178 106 #> [24,] 177 107 #> [25,] 176 107 #> [26,] 175 107 #> [27,] 174 107 #> [28,] 173 107 #> [29,] 172 107 #> [30,] 171 107 #> [31,] 170 107 #> [32,] 169 107 #> [33,] 168 108 #> [34,] 167 108 #> [35,] 166 108 #> [36,] 165 108 #> [37,] 164 108 #> [38,] 163 107 #> [39,] 162 107 #> [40,] 161 106 #> [41,] 160 105 #> [42,] 160 104 #> [43,] 159 103 #> [44,] 158 102 #> [45,] 157 101 #> [46,] 156 100 #> [47,] 156 99 #> [48,] 155 98 #> [49,] 154 97 #> [50,] 153 96 #> [51,] 153 95 #> [52,] 152 94 #> [53,] 151 93 #> [54,] 150 92 #> [55,] 149 91 #> [56,] 148 90 #> [57,] 147 89 #> [58,] 146 88 #> [59,] 145 87 #> [60,] 144 86 #> [61,] 143 85 #> [62,] 142 85 #> [63,] 141 84 #> [64,] 140 83 #> [65,] 139 83 #> [66,] 138 82 #> [67,] 137 81 #> [68,] 136 80 #> [69,] 135 79 #> [70,] 134 79 #> [71,] 133 78 #> [72,] 132 77 #> [73,] 131 76 #> [74,] 130 75 #> [75,] 129 74 #> [76,] 128 73 #> [77,] 128 72 #> [78,] 127 71 #> [79,] 126 70 #> [80,] 125 69 #> [81,] 125 68 #> [82,] 124 67 #> [83,] 124 66 #> [84,] 124 65 #> [85,] 123 64 #> [86,] 123 63 #> [87,] 123 62 #> [88,] 123 61 #> [89,] 122 60 #> [90,] 122 59 #> [91,] 122 58 #> [92,] 122 57 #> [93,] 122 56 #> [94,] 123 55 #> [95,] 124 54 #> [96,] 125 53 #> [97,] 126 52 #> [98,] 127 52 #> [99,] 128 51 #> [100,] 129 50 #> [101,] 129 49 #> [102,] 129 48 #> [103,] 128 47 #> [104,] 127 46 #> [105,] 126 46 #> [106,] 125 45 #> [107,] 124 45 #> [108,] 123 45 #> [109,] 122 45 #> [110,] 121 45 #> [111,] 120 45 #> [112,] 119 45 #> [113,] 118 45 #> [114,] 117 45 #> [115,] 116 45 #> [116,] 115 45 #> [117,] 114 45 #> [118,] 113 46 #> [119,] 112 46 #> [120,] 111 47 #> [121,] 110 48 #> [122,] 110 49 #> [123,] 110 50 #> [124,] 109 51 #> [125,] 109 52 #> [126,] 109 53 #> [127,] 109 54 #> [128,] 109 55 #> [129,] 109 56 #> [130,] 109 57 #> [131,] 109 58 #> [132,] 109 59 #> [133,] 109 60 #> [134,] 109 61 #> [135,] 109 62 #> [136,] 109 63 #> [137,] 109 64 #> [138,] 109 65 #> [139,] 109 66 #> [140,] 109 67 #> [141,] 109 68 #> [142,] 109 69 #> 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166 #> [314,] 169 166 #> [315,] 170 166 #> [316,] 171 166 #> [317,] 172 166 #> [318,] 173 166 #> [319,] 174 166 #> [320,] 175 166 #> [321,] 176 166 #> [322,] 177 166 #> [323,] 178 166 #> [324,] 179 166 #> [325,] 180 166 #> [326,] 181 166 #> [327,] 182 166 #> [328,] 183 166 #> [329,] 184 166 #> [330,] 185 166 #> [331,] 186 166 #> [332,] 187 166 #> [333,] 188 166 #> [334,] 189 165 #> [335,] 190 165 #> [336,] 191 165 #> [337,] 192 165 #> [338,] 193 165 #> [339,] 194 165 #> [340,] 195 165 #> [341,] 196 165 #> [342,] 197 165 #> [343,] 198 165 #> [344,] 199 165 #> [345,] 200 165 #> [346,] 201 165 #> [347,] 202 165 #> [348,] 203 165 #> [349,] 204 165 #> [350,] 205 165 #> [351,] 206 166 #> [352,] 207 166 #> [353,] 208 166 #> [354,] 209 166 #> [355,] 210 166 #> [356,] 211 166 #> [357,] 212 166 #> [358,] 213 166 #> [359,] 214 166 #> [360,] 215 167 #> [361,] 216 167 #> [362,] 217 167 #> [363,] 218 167 #> [364,] 219 167 #> [365,] 220 168 #> [366,] 221 168 #> [367,] 222 168 #> [368,] 223 169 #> 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219 #> [425,] 260 220 #> [426,] 261 221 #> [427,] 262 222 #> [428,] 263 223 #> [429,] 264 224 #> [430,] 265 225 #> [431,] 266 225 #> [432,] 267 226 #> [433,] 268 226 #> [434,] 269 226 #> [435,] 270 227 #> [436,] 271 227 #> [437,] 272 227 #> [438,] 273 227 #> [439,] 274 227 #> [440,] 275 227 #> [441,] 276 227 #> [442,] 277 227 #> [443,] 278 227 #> [444,] 279 228 #> [445,] 280 227 #> [446,] 281 227 #> [447,] 282 227 #> [448,] 283 227 #> [449,] 284 226 #> [450,] 285 226 #> [451,] 286 225 #> [452,] 287 224 #> [453,] 288 224 #> [454,] 289 223 #> [455,] 290 222 #> [456,] 291 221 #> [457,] 292 220 #> [458,] 293 219 #> [459,] 294 218 #> [460,] 295 217 #> [461,] 295 216 #> [462,] 296 215 #> [463,] 297 215 #> [464,] 298 214 #> [465,] 299 214 #> [466,] 300 214 #> [467,] 301 214 #> [468,] 302 214 #> [469,] 303 214 #> [470,] 304 214 #> [471,] 305 214 #> [472,] 306 214 #> [473,] 307 214 #> [474,] 308 214 #> [475,] 309 214 #> [476,] 310 214 #> [477,] 311 214 #> [478,] 312 214 #> [479,] 313 214 #> [480,] 314 214 #> [481,] 315 213 #> [482,] 315 212 #> [483,] 316 211 #> [484,] 316 210 #> [485,] 316 209 #> [486,] 316 208 #> [487,] 316 207 #> [488,] 315 206 #> [489,] 316 205 #> [490,] 315 204 #> [491,] 316 203 #> [492,] 316 202 #> [493,] 316 201 #> [494,] 316 200 #> [495,] 316 199 #> [496,] 316 198 #> [497,] 316 197 #> [498,] 316 196 #> [499,] 315 195 #> [500,] 315 194 #> [501,] 314 193 #> [502,] 314 192 #> [503,] 313 191 #> [504,] 312 191 #> [505,] 311 190 #> [506,] 310 190 #> [507,] 309 189 #> [508,] 308 189 #> [509,] 307 189 #> [510,] 306 189 #> [511,] 305 189 #> [512,] 304 188 #> [513,] 303 188 #> [514,] 302 188 #> [515,] 301 188 #> [516,] 300 188 #> [517,] 299 188 #> [518,] 298 188 #> [519,] 297 188 #> [520,] 296 188 #> [521,] 295 188 #> [522,] 294 188 #> [523,] 293 187 #> [524,] 292 187 #> [525,] 291 186 #> [526,] 291 185 #> [527,] 291 184 #> [528,] 290 183 #> [529,] 290 182 #> [530,] 290 181 #> [531,] 289 180 #> [532,] 289 179 #> [533,] 288 178 #> [534,] 288 177 #> [535,] 288 176 #> [536,] 287 175 #> [537,] 287 174 #> [538,] 286 173 #> [539,] 286 172 #> [540,] 286 171 #> [541,] 285 170 #> [542,] 285 169 #> [543,] 284 168 #> [544,] 284 167 #> [545,] 284 166 #> [546,] 283 165 #> [547,] 283 164 #> [548,] 282 163 #> [549,] 282 162 #> [550,] 282 161 #> [551,] 281 160 #> [552,] 281 159 #> [553,] 280 158 #> [554,] 280 157 #> [555,] 280 156 #> [556,] 279 155 #> [557,] 279 154 #> [558,] 278 153 #> [559,] 278 152 #> [560,] 278 151 #> [561,] 277 150 #> [562,] 278 149 #> [563,] 277 148 #> [564,] 277 147 #> [565,] 277 146 #> [566,] 277 145 #> [567,] 277 144 #> [568,] 276 143 #> [569,] 276 142 #> [570,] 277 141 #> [571,] 276 140 #> [572,] 276 139 #> [573,] 276 138 #> [574,] 276 137 #> [575,] 276 136 #> [576,] 275 135 #> [577,] 276 134 #> [578,] 275 133 #> [579,] 275 132 #> [580,] 275 131 #> [581,] 275 130 #> [582,] 274 129 #> [583,] 274 128 #> [584,] 274 127 #> [585,] 274 126 #> [586,] 274 125 #> [587,] 273 124 #> [588,] 273 123 #> [589,] 273 122 #> [590,] 272 121 #> 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63 #> [649,] 270 62 #> [650,] 271 62 #> [651,] 272 61 #> [652,] 273 61 #> [653,] 274 60 #> [654,] 275 60 #> [655,] 276 59 #> [656,] 277 58 #> [657,] 277 57 #> [658,] 277 56 #> [659,] 277 55 #> [660,] 276 54 #> [661,] 275 53 #> [662,] 274 53 #> [663,] 273 52 #> [664,] 272 52 #> [665,] 271 51 #> [666,] 270 51 #> [667,] 269 50 #> [668,] 268 50 #> [669,] 267 50 #> [670,] 266 50 #> [671,] 265 50 #> [672,] 264 50 #> [673,] 263 50 #> [674,] 262 50 #> [675,] 261 51 #> [676,] 260 52 #> [677,] 260 53 #> [678,] 260 54 #> [679,] 259 55 #> [680,] 259 56 #> [681,] 259 57 #> [682,] 259 58 #> [683,] 258 59 #> [684,] 258 60 #> [685,] 258 61 #> [686,] 258 62 #> [687,] 258 63 #> [688,] 257 64 #> [689,] 257 65 #> [690,] 257 66 #> [691,] 257 67 #> [692,] 256 68 #> [693,] 256 69 #> [694,] 256 70 #> [695,] 256 71 #> [696,] 255 72 #> [697,] 255 73 #> [698,] 255 74 #> [699,] 254 75 #> [700,] 254 76 #> [701,] 254 77 #> [702,] 253 78 #> [703,] 253 79 #> [704,] 252 80 #> [705,] 252 81 #> [706,] 252 82 #> [707,] 251 83 #> [708,] 251 84 #> [709,] 250 85 #> [710,] 250 86 #> [711,] 249 87 #> [712,] 249 88 #> [713,] 249 89 #> [714,] 248 90 #> [715,] 248 91 #> [716,] 247 92 #> [717,] 247 93 #> [718,] 247 94 #> [719,] 246 95 #> [720,] 246 96 #> [721,] 245 97 #> [722,] 245 98 #> [723,] 244 99 #> [724,] 243 100 #> [725,] 243 101 #> [726,] 242 102 #> [727,] 241 103 #> [728,] 240 104 #> [729,] 239 104 #> [730,] 238 104 #> [731,] 237 104 #> [732,] 236 105 #> [733,] 235 105 #> [734,] 234 105 #> [735,] 233 105 #> [736,] 232 105 #> [737,] 231 105 #> [738,] 230 105 #> [739,] 229 105 #> [740,] 228 105 #> [741,] 227 105 #> [742,] 226 105 #> [743,] 225 105 #> [744,] 224 105 #> [745,] 223 105 #> [746,] 222 105 #> [747,] 221 105 #> [748,] 220 105 #> [749,] 219 105 #> [750,] 218 105 #> [751,] 217 105 #> [752,] 216 105 #> [753,] 215 106 #> [754,] 214 106 #> [755,] 213 106 #> [756,] 212 106 #> [757,] 211 106 #> [758,] 210 106 #> [759,] 209 106 #> [760,] 208 106 #> [761,] 207 106 #> [762,] 206 106 #> [763,] 205 106 #> [764,] 204 106 #> [765,] 203 106 #> [766,] 202 106 #> [767,] 201 106 #> [768,] 200 106 #> #> $deusventrue #> [,1] [,2] #> [1,] 200 87 #> [2,] 199 86 #> [3,] 198 86 #> [4,] 197 87 #> [5,] 196 87 #> [6,] 195 87 #> [7,] 194 87 #> [8,] 193 87 #> [9,] 192 87 #> [10,] 191 87 #> [11,] 190 87 #> [12,] 189 87 #> [13,] 188 87 #> [14,] 187 87 #> [15,] 186 87 #> [16,] 185 87 #> [17,] 184 87 #> [18,] 183 87 #> [19,] 182 87 #> [20,] 181 87 #> [21,] 180 87 #> [22,] 179 87 #> [23,] 178 87 #> [24,] 177 87 #> [25,] 176 87 #> [26,] 175 87 #> [27,] 174 87 #> [28,] 173 87 #> [29,] 172 87 #> [30,] 171 87 #> [31,] 170 87 #> [32,] 169 87 #> [33,] 168 87 #> [34,] 167 87 #> [35,] 166 87 #> [36,] 165 87 #> [37,] 164 87 #> [38,] 163 87 #> [39,] 162 88 #> [40,] 161 88 #> [41,] 160 88 #> [42,] 159 88 #> [43,] 158 88 #> [44,] 157 88 #> [45,] 156 89 #> [46,] 155 89 #> [47,] 154 89 #> [48,] 153 90 #> [49,] 153 91 #> [50,] 152 92 #> [51,] 152 93 #> [52,] 152 94 #> [53,] 151 95 #> [54,] 151 96 #> [55,] 151 97 #> 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[114,] 106 115 #> [115,] 105 114 #> [116,] 104 114 #> [117,] 103 113 #> [118,] 102 113 #> [119,] 101 112 #> [120,] 100 111 #> [121,] 99 110 #> [122,] 98 109 #> [123,] 97 109 #> [124,] 96 108 #> [125,] 95 107 #> [126,] 94 106 #> [127,] 93 105 #> [128,] 92 104 #> [129,] 91 103 #> [130,] 90 102 #> [131,] 89 101 #> [132,] 88 100 #> [133,] 87 100 #> [134,] 86 99 #> [135,] 85 98 #> [136,] 84 97 #> [137,] 83 96 #> [138,] 82 95 #> [139,] 81 94 #> [140,] 80 93 #> [141,] 79 92 #> [142,] 78 91 #> [143,] 77 90 #> [144,] 76 89 #> [145,] 75 88 #> [146,] 74 88 #> [147,] 73 87 #> [148,] 72 86 #> [149,] 71 85 #> [150,] 70 84 #> [151,] 69 83 #> [152,] 68 83 #> [153,] 67 82 #> [154,] 66 81 #> [155,] 65 81 #> [156,] 64 80 #> [157,] 63 79 #> [158,] 62 79 #> [159,] 61 78 #> [160,] 60 78 #> [161,] 59 78 #> [162,] 58 77 #> [163,] 57 78 #> [164,] 56 78 #> [165,] 55 79 #> [166,] 54 80 #> [167,] 53 81 #> [168,] 53 82 #> [169,] 52 83 #> [170,] 52 84 #> [171,] 51 85 #> [172,] 51 86 #> [173,] 51 87 #> [174,] 51 88 #> [175,] 51 89 #> [176,] 50 90 #> [177,] 50 91 #> [178,] 50 92 #> [179,] 50 93 #> [180,] 50 94 #> [181,] 49 95 #> [182,] 49 96 #> [183,] 49 97 #> [184,] 50 98 #> [185,] 50 99 #> [186,] 50 100 #> [187,] 50 101 #> [188,] 50 102 #> [189,] 50 103 #> [190,] 50 104 #> [191,] 50 105 #> [192,] 50 106 #> [193,] 50 107 #> [194,] 50 108 #> [195,] 49 109 #> [196,] 50 110 #> [197,] 50 111 #> [198,] 50 112 #> [199,] 50 113 #> [200,] 50 114 #> [201,] 50 115 #> [202,] 50 116 #> [203,] 50 117 #> [204,] 51 118 #> [205,] 50 119 #> [206,] 51 120 #> [207,] 51 121 #> [208,] 51 122 #> [209,] 51 123 #> [210,] 51 124 #> [211,] 52 125 #> [212,] 52 126 #> [213,] 52 127 #> [214,] 53 128 #> [215,] 53 129 #> [216,] 54 130 #> [217,] 55 131 #> [218,] 55 132 #> [219,] 55 133 #> [220,] 54 134 #> [221,] 54 135 #> [222,] 53 136 #> [223,] 52 137 #> [224,] 52 138 #> [225,] 51 139 #> [226,] 50 140 #> [227,] 50 141 #> [228,] 49 142 #> [229,] 49 143 #> [230,] 48 144 #> [231,] 47 145 #> [232,] 47 146 #> [233,] 47 147 #> [234,] 46 148 #> [235,] 46 149 #> [236,] 45 150 #> [237,] 45 151 #> [238,] 45 152 #> [239,] 44 153 #> [240,] 44 154 #> [241,] 43 155 #> [242,] 43 156 #> [243,] 43 157 #> [244,] 42 158 #> [245,] 42 159 #> [246,] 42 160 #> [247,] 42 161 #> [248,] 41 162 #> [249,] 41 163 #> [250,] 41 164 #> [251,] 40 165 #> [252,] 40 166 #> [253,] 40 167 #> [254,] 40 168 #> [255,] 40 169 #> [256,] 39 170 #> [257,] 39 171 #> [258,] 39 172 #> [259,] 39 173 #> [260,] 39 174 #> [261,] 38 175 #> [262,] 39 176 #> [263,] 39 177 #> [264,] 39 178 #> [265,] 39 179 #> [266,] 39 180 #> [267,] 38 181 #> [268,] 39 182 #> [269,] 39 183 #> [270,] 39 184 #> [271,] 39 185 #> [272,] 40 186 #> [273,] 41 187 #> [274,] 42 188 #> [275,] 43 189 #> [276,] 44 190 #> [277,] 45 190 #> [278,] 46 190 #> [279,] 47 190 #> [280,] 48 190 #> [281,] 49 190 #> [282,] 50 190 #> [283,] 51 190 #> [284,] 52 190 #> [285,] 53 190 #> [286,] 54 189 #> [287,] 55 189 #> [288,] 56 189 #> [289,] 57 188 #> [290,] 58 188 #> [291,] 59 188 #> [292,] 60 187 #> [293,] 61 187 #> [294,] 62 186 #> [295,] 63 186 #> [296,] 64 185 #> [297,] 65 185 #> [298,] 66 184 #> [299,] 67 184 #> [300,] 68 183 #> [301,] 69 183 #> [302,] 70 182 #> [303,] 71 182 #> [304,] 72 181 #> [305,] 73 180 #> [306,] 74 180 #> [307,] 75 179 #> [308,] 76 179 #> [309,] 77 178 #> [310,] 78 177 #> [311,] 79 177 #> [312,] 80 176 #> [313,] 81 176 #> [314,] 82 175 #> [315,] 83 174 #> [316,] 84 174 #> [317,] 85 173 #> [318,] 86 173 #> [319,] 87 172 #> [320,] 88 171 #> [321,] 89 171 #> [322,] 90 170 #> [323,] 91 170 #> [324,] 92 169 #> [325,] 93 168 #> [326,] 94 168 #> [327,] 95 167 #> [328,] 96 166 #> [329,] 97 166 #> [330,] 98 165 #> [331,] 99 165 #> [332,] 100 164 #> [333,] 101 164 #> [334,] 102 163 #> [335,] 103 162 #> [336,] 104 162 #> [337,] 105 162 #> [338,] 106 161 #> [339,] 107 161 #> [340,] 108 160 #> [341,] 109 160 #> [342,] 110 160 #> [343,] 111 159 #> [344,] 112 159 #> [345,] 113 159 #> [346,] 114 158 #> [347,] 115 158 #> [348,] 116 158 #> [349,] 117 158 #> [350,] 118 157 #> [351,] 119 157 #> [352,] 120 157 #> [353,] 121 157 #> [354,] 122 157 #> [355,] 123 156 #> [356,] 124 157 #> [357,] 125 156 #> [358,] 126 157 #> [359,] 127 157 #> [360,] 128 157 #> [361,] 129 157 #> [362,] 130 158 #> [363,] 131 158 #> [364,] 132 158 #> [365,] 133 159 #> [366,] 134 159 #> [367,] 135 160 #> [368,] 136 160 #> [369,] 137 161 #> [370,] 138 161 #> [371,] 139 162 #> [372,] 140 162 #> [373,] 141 163 #> [374,] 142 164 #> [375,] 143 164 #> [376,] 144 165 #> [377,] 145 165 #> [378,] 146 166 #> [379,] 147 166 #> [380,] 148 167 #> [381,] 149 167 #> [382,] 150 168 #> [383,] 151 168 #> [384,] 152 169 #> [385,] 153 169 #> [386,] 154 170 #> [387,] 155 170 #> [388,] 156 171 #> [389,] 157 171 #> [390,] 158 172 #> [391,] 159 172 #> [392,] 160 173 #> [393,] 161 173 #> [394,] 162 174 #> [395,] 163 174 #> [396,] 164 174 #> [397,] 165 175 #> [398,] 166 175 #> [399,] 167 175 #> [400,] 168 176 #> [401,] 169 176 #> [402,] 168 177 #> [403,] 168 178 #> [404,] 167 179 #> [405,] 166 180 #> [406,] 165 181 #> [407,] 165 182 #> [408,] 164 183 #> [409,] 163 184 #> [410,] 162 185 #> [411,] 161 186 #> [412,] 160 187 #> [413,] 159 188 #> [414,] 159 189 #> [415,] 158 190 #> [416,] 157 191 #> [417,] 156 192 #> [418,] 155 193 #> [419,] 154 194 #> [420,] 153 195 #> [421,] 152 196 #> [422,] 151 197 #> [423,] 150 198 #> [424,] 149 199 #> [425,] 148 200 #> [426,] 147 201 #> [427,] 146 202 #> [428,] 145 203 #> [429,] 144 204 #> [430,] 143 205 #> [431,] 142 206 #> [432,] 142 207 #> [433,] 141 208 #> [434,] 140 209 #> [435,] 139 210 #> [436,] 138 211 #> [437,] 138 212 #> [438,] 137 213 #> [439,] 137 214 #> [440,] 137 215 #> [441,] 137 216 #> [442,] 138 217 #> [443,] 139 218 #> [444,] 140 218 #> [445,] 141 219 #> [446,] 142 219 #> [447,] 143 219 #> [448,] 144 219 #> [449,] 145 219 #> [450,] 146 220 #> [451,] 147 220 #> [452,] 148 220 #> [453,] 149 220 #> [454,] 150 220 #> [455,] 151 220 #> [456,] 152 220 #> [457,] 153 221 #> [458,] 154 220 #> [459,] 155 221 #> [460,] 156 221 #> [461,] 157 221 #> [462,] 158 221 #> [463,] 159 221 #> [464,] 160 221 #> [465,] 161 221 #> [466,] 162 221 #> [467,] 163 222 #> [468,] 164 221 #> [469,] 165 221 #> [470,] 166 221 #> [471,] 167 221 #> [472,] 168 221 #> [473,] 169 221 #> [474,] 170 221 #> [475,] 171 221 #> [476,] 172 221 #> [477,] 173 222 #> [478,] 174 222 #> [479,] 175 222 #> [480,] 176 222 #> [481,] 177 222 #> [482,] 178 222 #> [483,] 179 222 #> [484,] 180 222 #> [485,] 181 222 #> [486,] 182 222 #> [487,] 183 222 #> [488,] 184 222 #> [489,] 185 222 #> [490,] 186 222 #> [491,] 187 222 #> [492,] 188 222 #> [493,] 189 222 #> [494,] 190 222 #> [495,] 191 222 #> [496,] 192 222 #> [497,] 193 222 #> [498,] 194 222 #> [499,] 195 222 #> [500,] 196 222 #> [501,] 197 222 #> [502,] 198 222 #> [503,] 199 222 #> [504,] 200 222 #> [505,] 201 222 #> [506,] 202 222 #> [507,] 203 222 #> [508,] 204 222 #> [509,] 205 222 #> [510,] 206 222 #> [511,] 207 222 #> [512,] 208 221 #> [513,] 209 221 #> [514,] 210 221 #> [515,] 211 221 #> [516,] 212 221 #> [517,] 213 221 #> [518,] 214 221 #> [519,] 215 221 #> [520,] 216 221 #> [521,] 217 221 #> [522,] 218 221 #> [523,] 219 221 #> [524,] 220 221 #> [525,] 221 221 #> [526,] 222 221 #> [527,] 223 221 #> [528,] 224 221 #> [529,] 225 221 #> [530,] 226 221 #> [531,] 227 221 #> [532,] 228 221 #> [533,] 229 221 #> [534,] 230 220 #> [535,] 231 220 #> [536,] 232 220 #> [537,] 233 220 #> [538,] 234 220 #> [539,] 235 220 #> [540,] 236 220 #> [541,] 237 220 #> [542,] 238 220 #> [543,] 239 220 #> [544,] 240 220 #> [545,] 241 220 #> [546,] 242 219 #> [547,] 243 219 #> [548,] 244 219 #> [549,] 245 219 #> [550,] 246 219 #> [551,] 247 219 #> [552,] 248 219 #> [553,] 249 218 #> [554,] 250 218 #> [555,] 251 218 #> [556,] 252 218 #> [557,] 253 218 #> [558,] 254 218 #> [559,] 255 218 #> [560,] 256 217 #> [561,] 257 217 #> [562,] 258 217 #> [563,] 259 217 #> [564,] 260 216 #> [565,] 261 216 #> [566,] 262 216 #> [567,] 263 216 #> [568,] 264 215 #> [569,] 265 215 #> [570,] 266 215 #> [571,] 267 215 #> [572,] 268 214 #> [573,] 269 214 #> [574,] 270 214 #> [575,] 271 213 #> [576,] 272 213 #> [577,] 273 213 #> [578,] 274 212 #> [579,] 275 212 #> [580,] 276 212 #> [581,] 277 211 #> [582,] 278 211 #> [583,] 279 210 #> [584,] 280 210 #> [585,] 281 209 #> [586,] 282 209 #> [587,] 283 208 #> [588,] 284 208 #> [589,] 285 207 #> [590,] 286 207 #> [591,] 287 206 #> [592,] 288 206 #> [593,] 289 205 #> [594,] 290 205 #> [595,] 291 204 #> [596,] 292 203 #> [597,] 293 202 #> [598,] 294 202 #> [599,] 295 201 #> [600,] 296 200 #> [601,] 297 199 #> [602,] 298 198 #> [603,] 299 197 #> [604,] 300 196 #> [605,] 301 195 #> [606,] 302 194 #> [607,] 303 193 #> [608,] 303 192 #> [609,] 304 191 #> [610,] 305 190 #> [611,] 305 189 #> [612,] 306 188 #> [613,] 307 187 #> [614,] 308 186 #> [615,] 308 185 #> [616,] 309 184 #> [617,] 310 184 #> [618,] 311 184 #> [619,] 312 183 #> [620,] 313 183 #> [621,] 314 183 #> [622,] 315 182 #> [623,] 316 182 #> [624,] 317 182 #> [625,] 318 181 #> [626,] 319 181 #> [627,] 320 180 #> [628,] 321 180 #> [629,] 322 180 #> [630,] 323 179 #> [631,] 324 179 #> [632,] 325 178 #> [633,] 326 178 #> [634,] 327 178 #> [635,] 328 177 #> [636,] 329 177 #> [637,] 330 176 #> [638,] 331 176 #> [639,] 332 175 #> [640,] 333 174 #> [641,] 334 174 #> [642,] 335 173 #> [643,] 336 173 #> [644,] 337 172 #> [645,] 338 171 #> [646,] 339 171 #> [647,] 340 170 #> [648,] 341 170 #> [649,] 342 169 #> [650,] 343 168 #> [651,] 344 168 #> [652,] 345 167 #> [653,] 346 166 #> [654,] 347 165 #> [655,] 348 165 #> [656,] 349 164 #> [657,] 350 163 #> [658,] 351 162 #> [659,] 352 162 #> [660,] 353 161 #> [661,] 354 160 #> [662,] 355 159 #> [663,] 356 158 #> [664,] 357 157 #> [665,] 358 156 #> [666,] 359 155 #> [667,] 360 155 #> [668,] 361 154 #> [669,] 362 153 #> [670,] 362 152 #> [671,] 363 151 #> [672,] 364 150 #> [673,] 365 149 #> [674,] 366 148 #> [675,] 367 147 #> [676,] 368 146 #> [677,] 369 145 #> [678,] 370 144 #> [679,] 370 143 #> [680,] 371 142 #> [681,] 372 141 #> [682,] 373 140 #> [683,] 373 139 #> [684,] 374 138 #> [685,] 375 137 #> [686,] 375 136 #> [687,] 376 135 #> [688,] 377 134 #> [689,] 377 133 #> [690,] 378 132 #> [691,] 379 131 #> [692,] 379 130 #> [693,] 379 129 #> [694,] 380 128 #> [695,] 380 127 #> [696,] 381 126 #> [697,] 381 125 #> [698,] 382 124 #> [699,] 382 123 #> [700,] 382 122 #> [701,] 383 121 #> [702,] 383 120 #> [703,] 383 119 #> [704,] 384 118 #> [705,] 383 117 #> [706,] 383 116 #> [707,] 382 115 #> [708,] 381 114 #> [709,] 380 113 #> [710,] 379 112 #> [711,] 378 112 #> [712,] 377 111 #> [713,] 376 111 #> [714,] 375 110 #> [715,] 374 109 #> [716,] 373 109 #> [717,] 372 108 #> [718,] 371 107 #> [719,] 370 107 #> [720,] 369 106 #> [721,] 368 106 #> [722,] 367 105 #> [723,] 366 105 #> [724,] 365 105 #> [725,] 364 104 #> [726,] 363 103 #> [727,] 362 103 #> [728,] 361 103 #> [729,] 360 102 #> [730,] 359 102 #> [731,] 358 101 #> [732,] 357 101 #> [733,] 356 101 #> [734,] 355 100 #> [735,] 354 100 #> [736,] 353 99 #> [737,] 352 99 #> [738,] 351 99 #> [739,] 350 98 #> [740,] 349 98 #> [741,] 348 98 #> [742,] 347 97 #> [743,] 346 97 #> [744,] 345 97 #> [745,] 344 96 #> [746,] 343 96 #> [747,] 342 96 #> [748,] 341 95 #> [749,] 340 95 #> [750,] 339 95 #> [751,] 338 94 #> [752,] 337 94 #> [753,] 336 94 #> [754,] 335 94 #> [755,] 334 93 #> [756,] 333 93 #> [757,] 332 93 #> [758,] 331 93 #> [759,] 330 92 #> [760,] 329 92 #> [761,] 328 92 #> [762,] 327 92 #> [763,] 326 91 #> [764,] 325 91 #> [765,] 324 91 #> [766,] 323 91 #> [767,] 322 91 #> [768,] 321 90 #> [769,] 320 90 #> [770,] 319 90 #> [771,] 318 90 #> [772,] 317 90 #> [773,] 316 90 #> [774,] 315 89 #> [775,] 314 89 #> [776,] 313 89 #> [777,] 312 89 #> [778,] 311 89 #> [779,] 310 89 #> [780,] 309 88 #> [781,] 308 88 #> [782,] 307 88 #> [783,] 306 88 #> [784,] 305 88 #> [785,] 304 88 #> [786,] 303 88 #> [787,] 302 88 #> [788,] 301 88 #> [789,] 300 87 #> [790,] 299 87 #> [791,] 298 87 #> [792,] 297 87 #> [793,] 296 87 #> [794,] 295 87 #> [795,] 294 87 #> [796,] 293 87 #> [797,] 292 87 #> [798,] 291 87 #> [799,] 290 87 #> [800,] 289 87 #> [801,] 288 87 #> [802,] 287 87 #> [803,] 286 87 #> [804,] 285 87 #> [805,] 284 86 #> [806,] 283 86 #> [807,] 282 86 #> [808,] 282 85 #> [809,] 281 84 #> [810,] 281 83 #> [811,] 280 82 #> [812,] 280 81 #> [813,] 279 80 #> [814,] 278 79 #> [815,] 278 78 #> [816,] 278 77 #> [817,] 277 76 #> [818,] 276 75 #> [819,] 276 74 #> [820,] 276 73 #> [821,] 275 72 #> [822,] 274 71 #> [823,] 274 70 #> [824,] 273 69 #> [825,] 273 68 #> [826,] 272 67 #> [827,] 272 66 #> [828,] 271 65 #> [829,] 270 64 #> [830,] 270 63 #> [831,] 269 62 #> [832,] 269 61 #> [833,] 268 60 #> [834,] 267 59 #> [835,] 266 58 #> [836,] 266 57 #> [837,] 265 56 #> [838,] 264 55 #> [839,] 264 54 #> [840,] 263 53 #> [841,] 262 52 #> [842,] 261 51 #> [843,] 261 50 #> [844,] 260 49 #> [845,] 259 48 #> [846,] 258 47 #> [847,] 257 46 #> [848,] 256 45 #> [849,] 255 44 #> [850,] 254 43 #> [851,] 253 42 #> [852,] 252 42 #> [853,] 251 41 #> [854,] 250 41 #> [855,] 249 40 #> [856,] 248 40 #> [857,] 247 39 #> [858,] 246 39 #> [859,] 245 39 #> [860,] 244 39 #> [861,] 243 39 #> [862,] 242 39 #> [863,] 241 39 #> [864,] 240 39 #> [865,] 239 39 #> [866,] 238 40 #> [867,] 237 40 #> [868,] 236 41 #> [869,] 235 41 #> [870,] 234 42 #> [871,] 233 43 #> [872,] 233 44 #> [873,] 232 45 #> [874,] 231 46 #> [875,] 230 47 #> [876,] 230 48 #> [877,] 230 49 #> [878,] 229 50 #> [879,] 228 51 #> [880,] 228 52 #> [881,] 228 53 #> [882,] 227 54 #> [883,] 227 55 #> [884,] 227 56 #> [885,] 226 57 #> [886,] 226 58 #> [887,] 226 59 #> [888,] 226 60 #> [889,] 225 61 #> [890,] 225 62 #> [891,] 225 63 #> [892,] 224 64 #> [893,] 225 65 #> [894,] 224 66 #> [895,] 224 67 #> [896,] 224 68 #> [897,] 224 69 #> [898,] 224 70 #> [899,] 224 71 #> [900,] 224 72 #> [901,] 224 73 #> [902,] 224 74 #> [903,] 225 75 #> [904,] 224 76 #> [905,] 225 77 #> [906,] 225 78 #> [907,] 225 79 #> [908,] 226 80 #> [909,] 226 81 #> [910,] 226 82 #> [911,] 227 83 #> [912,] 227 84 #> [913,] 227 85 #> [914,] 228 86 #> [915,] 228 87 #> [916,] 227 87 #> [917,] 226 87 #> [918,] 225 88 #> [919,] 224 88 #> [920,] 223 87 #> [921,] 222 88 #> [922,] 221 88 #> [923,] 220 88 #> [924,] 219 88 #> [925,] 218 88 #> [926,] 217 89 #> [927,] 216 89 #> [928,] 215 89 #> [929,] 214 89 #> [930,] 213 89 #> [931,] 212 88 #> [932,] 211 88 #> [933,] 210 88 #> [934,] 209 88 #> [935,] 208 88 #> [936,] 207 88 #> [937,] 206 88 #> [938,] 205 87 #> [939,] 204 87 #> [940,] 203 87 #> [941,] 202 87 #> [942,] 201 87 #> [943,] 200 87 #> x$fac #> # A tibble: 5 × 2 #> name value #> #> 1 a 5 #> 2 b 4 #> 3 c 3 #> 4 d 2 #> 5 e 1"},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":null,"dir":"Reference","previous_headings":"","what":"KMEANS on PCA objects — KMEANS","title":"KMEANS on PCA objects — KMEANS","text":"basic implementation k-means. Beware morphospaces calculated far 1st 2nd component.","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"KMEANS on PCA objects — KMEANS","text":"","code":"KMEANS(x, ...) # S3 method for PCA KMEANS(x, centers, nax = 1:2, pch = 20, cex = 0.5, ...)"},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"KMEANS on PCA objects — KMEANS","text":"x PCA object ... additional arguments passed kmeans centers numeric number centers nax numeric range PC components use (1:2 default) pch draw points cex draw points","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"KMEANS on PCA objects — KMEANS","text":"thing kmeans","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/KMEANS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"KMEANS on PCA objects — KMEANS","text":"","code":"data(bot) bp <- PCA(efourier(bot, 10)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details KMEANS(bp, 2) #> K-means clustering with 2 clusters of sizes 14, 26 #> #> Cluster means: #> PC1 PC2 #> 1 0.07496282 -0.003229186 #> 2 -0.04036460 0.001738792 #> #> Clustering vector: #> brahma caney chimay corona deusventrue #> 2 2 1 2 2 #> duvel franziskaner grimbergen guiness hoegardeen #> 1 2 1 2 2 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 2 2 1 2 2 #> pecheresse sierranevada tanglefoot tauro westmalle #> 2 1 1 2 2 #> amrut ballantines bushmills chivas dalmore #> 2 1 2 1 1 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 2 2 2 1 2 #> jb johnniewalker magallan makersmark oban #> 2 2 2 1 2 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 1 1 2 2 1 #> #> Within cluster sum of squares by cluster: #> [1] 0.03758606 0.02127484 #> (between_SS / total_SS = 67.3 %) #> #> Available components: #> #> [1] \"cluster\" \"centers\" \"totss\" \"withinss\" \"tot.withinss\" #> [6] \"betweenss\" \"size\" \"iter\" \"ifault\""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":null,"dir":"Reference","previous_headings":"","what":"KMEDOIDS — KMEDOIDS","title":"KMEDOIDS — KMEDOIDS","text":"basic implementation kmedoids top cluster::pam Beware morphospaces calculated far 1st 2nd component.","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"KMEDOIDS — KMEDOIDS","text":"","code":"KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for default KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for Coe KMEDOIDS(x, k, metric = \"euclidean\", ...) # S3 method for PCA KMEDOIDS(x, k, metric = \"euclidean\", retain, ...)"},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"KMEDOIDS — KMEDOIDS","text":"x Coe PCA object k numeric number centers metric one euclidean (default) manhattan, feed cluster::pam ... additional arguments feed cluster::pam retain passing PCA many PCs retain, proportion total variance, see LDA","code":""},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"KMEDOIDS — KMEDOIDS","text":"see cluster::pam. components returned (fac, etc.)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/KMEDOIDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"KMEDOIDS — KMEDOIDS","text":"","code":"data(bot) bp <- PCA(efourier(bot, 10)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details KMEANS(bp, 2) #> K-means clustering with 2 clusters of sizes 14, 26 #> #> Cluster means: #> PC1 PC2 #> 1 0.07496282 -0.003229186 #> 2 -0.04036460 0.001738792 #> #> Clustering vector: #> brahma caney chimay corona deusventrue #> 2 2 1 2 2 #> duvel franziskaner grimbergen guiness hoegardeen #> 1 2 1 2 2 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 2 2 1 2 2 #> pecheresse sierranevada tanglefoot tauro westmalle #> 2 1 1 2 2 #> amrut ballantines bushmills chivas dalmore #> 2 1 2 1 1 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 2 2 2 1 2 #> jb johnniewalker magallan makersmark oban #> 2 2 2 1 2 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 1 1 2 2 1 #> #> Within cluster sum of squares by cluster: #> [1] 0.03758606 0.02127484 #> (between_SS / total_SS = 67.3 %) #> #> Available components: #> #> [1] \"cluster\" \"centers\" \"totss\" \"withinss\" \"tot.withinss\" #> [6] \"betweenss\" \"size\" \"iter\" \"ifault\" set.seed(123) # for reproducibility on a dummy matrix matrix(rnorm(100, 10, 10)) %>% KMEDOIDS(5) #> Medoids: #> ID #> [1,] 10 5.543380 #> [2,] 30 22.538149 #> [3,] 4 10.705084 #> [4,] 7 14.609162 #> [5,] 78 -2.207177 #> Clustering vector: #> [1] 1 1 2 3 3 2 4 5 1 1 2 4 4 3 1 2 4 5 4 1 5 1 5 1 1 5 4 3 5 2 4 1 2 2 4 4 4 #> [38] 3 1 1 1 1 5 2 2 5 1 1 4 3 3 3 3 2 1 2 5 4 3 3 4 1 1 5 5 4 4 3 2 2 1 5 2 1 #> [75] 1 2 1 5 3 3 3 4 1 4 1 4 2 4 1 2 2 4 3 1 2 1 2 2 1 5 #> Objective function: #> build swap #> 2.132534 1.937061 #> #> Available components: #> [1] \"medoids\" \"id.med\" \"clustering\" \"objective\" #> [5] \"isolation\" \"clusinfo\" \"silinfo\" \"diss\" #> [9] \"call\" \"data\" \"k\" \"ids_constant\" #> [13] \"ids_collinear\" # On a Coe bot_f <- bot %>% efourier() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) bot_k <- bot_f %>% KMEDOIDS(2) #> removed these collinear columns:A1, B1, C1 # confusion matrix table(bot_k$fac$type, bot_k$clustering) #> #> 1 2 #> beer 12 8 #> whisky 14 6 # on a PCA bot_k2 <- bot_f %>% PCA() %>% KMEDOIDS(12, retain=0.9) # confusion matrix with(bot_k, table(fac$type, clustering)) #> clustering #> 1 2 #> beer 12 8 #> whisky 14 6 # silhouette plot bot_k %>% plot_silhouette() # average width as a function of k k_range <- 2:12 widths <- sapply(k_range, function(k) KMEDOIDS(bot_f, k=k)$silinfo$avg.width) #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 #> removed these collinear columns:A1, B1, C1 plot(k_range, widths, type=\"b\")"},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"Linear Discriminant Analysis on Coe objects — LDA","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"Calculates LDA Coe top MASS::lda.","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"","code":"LDA(x, fac, retain, ...) # S3 method for default LDA(x, fac, retain, ...) # S3 method for PCA LDA(x, fac, retain = 0.99, ...)"},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"x Coe PCA object fac grouping factor (names one $fac column column id) retain proportion total variance retain (retain<1) using scree, number PC axis (retain>1). ... additional arguments feed lda","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"'LDA' object apply plot.LDA, list components: x Coe object (matrix) fac grouping factor used removed ids columns original matrix removed since constant () mod raw lda mod lda mod.pred predicted model using x mod CV.fac cross-validated classification CV.tab cross-validation tabke CV.correct proportion correctly classified individuals CV.ce class error LDs unstandardized LD scores see Claude (2008) mshape mean values coefficients original matrix method inherited Coe object ()","code":""},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"LDA.PCA, retain can passed vector (eg: 1:5, retain=1, retain=2, ..., retain=5) tried, \"best\" (retain=1:number_of_pc_axes used). Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/LDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Linear Discriminant Analysis on Coe objects — LDA","text":"","code":"bot.f <- efourier(bot, 24) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) LDA(bot.p, 'type', retain=0.99) # retains 0.99 of the total variance #> 8 PC retained #> * Cross-validation table ($CV.tab): #> classified #> actual beer whisky #> beer 17 3 #> whisky 1 19 #> #> * Class accuracy ($CV.ce): #> beer whisky #> 0.85 0.95 #> #> * Leave-one-out cross-validation ($CV.correct): (90% - 36/40): LDA(bot.p, 'type', retain=5) # retain 5 axis #> 5 PC retained #> * Cross-validation table ($CV.tab): #> classified #> actual beer whisky #> beer 16 4 #> whisky 4 16 #> #> * Class accuracy ($CV.ce): #> beer whisky #> 0.8 0.8 #> #> * Leave-one-out cross-validation ($CV.correct): (80% - 32/40): bot.l <- LDA(bot.p, 'type', retain=0.99) #> 8 PC retained plot_LDA(bot.l) #> * Only two levels, so a single LD and preparing for an histogram #> $xy #> LD1 #> brahma 2.06882655 #> caney 1.95733171 #> chimay 3.18567319 #> corona 1.91972111 #> deusventrue 1.51983847 #> duvel 3.25459981 #> franziskaner 1.20540643 #> grimbergen 1.78612198 #> guiness 0.31717542 #> hoegardeen 2.23601856 #> jupiler 2.41738081 #> kingfisher 1.17563178 #> latrappe 2.48017277 #> lindemanskriek 0.84132717 #> nicechouffe -0.20973451 #> pecheresse 2.73987210 #> sierranevada 2.12878315 #> tanglefoot 0.50802841 #> tauro 2.45585085 #> westmalle 1.86373375 #> amrut -1.63004033 #> ballantines -3.31173062 #> bushmills -1.09107572 #> chivas -1.97923449 #> dalmore -0.60822705 #> famousgrouse -1.43517709 #> glendronach -1.56712869 #> glenmorangie -1.46854222 #> highlandpark -2.62231929 #> jackdaniels -0.70483285 #> jb -2.24638367 #> johnniewalker -0.97832954 #> magallan -2.17603623 #> makersmark -1.23316404 #> oban -2.34336958 #> oldpotrero -0.37639098 #> redbreast -4.17639973 #> tamdhu -0.09818091 #> wildturkey -3.48193578 #> yoichi -2.32326072 #> #> $f #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky #> #> $colors_groups #> [1] \"#66C2A5FF\" \"#FC8D62FF\" #> #> $colors_rows #> [1] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [7] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [13] \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" \"#FC8D62FF\" #> [19] \"#FC8D62FF\" \"#FC8D62FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [25] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [31] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> [37] \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" \"#66C2A5FF\" #> #> $object #> [1] \"PCA\" #> #> $axes #> [1] 1 #> #> $palette #> function (n, transp = 0) #> { #> .pal_brewer(n, \"Set2\") %>% pal_alpha(transp = transp) #> } #> #> #> #> $method #> [1] \"LDAPCA\" #> #> $mshape #> NULL #> #> $cuts #> NULL #> #> $eig #> NULL #> #> $sdev #> [1] 11.33732 #> #> $rotation #> LD1 #> PC1 -0.0021966326 #> PC2 -0.0004659024 #> PC3 0.0028778651 #> PC4 -0.0020601963 #> PC5 0.0016842402 #> PC6 -0.0008112386 #> PC7 -0.0006776597 #> PC8 -0.0004229307 #> #> $LDs #> LD1 #> PC1 -0.0021966326 #> PC2 -0.0004659024 #> PC3 0.0028778651 #> PC4 -0.0020601963 #> PC5 0.0016842402 #> PC6 -0.0008112386 #> PC7 -0.0006776597 #> PC8 -0.0004229307 #> #> $baseline1 #> NULL #> #> $baseline2 #> NULL #> #> $links #> NULL #> bot.f <- mutate(bot.f, plop=factor(rep(letters[1:4], each=10))) bot.l <- LDA(PCA(bot.f), 'plop') #> 8 PC retained plot_LDA(bot.l) # will replace the former soon"},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Ldk object — Ldk","title":"Builds an Ldk object — Ldk","text":"Momocs, Ldk classes objects lists configurations landmarks, optionnal components, generic methods plotting methods (e.g. stack) specific methods (e.g. fgProcrustes). Ldk objects primarily Coo objects. sense, morphometrics methods Ldk objects preserves (x, y) coordinates LdkCoe also Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Ldk object — Ldk","text":"","code":"Ldk(coo, fac = dplyr::tibble(), links = NULL, slidings = NULL)"},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Ldk object — Ldk","text":"coo list matrices (x; y) coordinates, array, Ldk object data.frame (friends) fac (optionnal) data.frame factors /numerics specifying grouping structure links (optionnal) 2-columns matrix 'links' landmarks, mainly plotting slidings (optionnal) 3-columns matrix defining () sliding landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Ldk object — Ldk","text":"Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Builds an Ldk object — Ldk","text":"shapes x must number landmarks. trying make Ldk object Opn object, try coo_sample beforehand homogeneize number coordinates among shapes. Please note Ldk methods experimental. implementation $slidings inspired geomorph","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Ldk object — Ldk","text":"","code":"#Methods on Ldk methods(class=Ldk) #> [1] MSHAPES combine coo_bookstein coo_slice #> [5] d def_links def_slidings fgProcrustes #> [9] fgsProcrustes get_ldk get_slidings mosaic #> [13] panel pile rearrange_ldk slidings_scheme #> [17] stack which_out #> see '?methods' for accessing help and source code str(mosquito) #> coo : List of 126 #> $ shp1 : num [1:100, 1:2] -0.107 -0.134 -0.164 -0.199 -0.234 ... #> $ shp2 : num [1:100, 1:2] -0.11 -0.137 -0.167 -0.2 -0.236 ... #> $ shp3 : num [1:100, 1:2] -0.0877 -0.1085 -0.1325 -0.1601 -0.1895 ... #> $ shp4 : num [1:100, 1:2] -0.0997 -0.1239 -0.1515 -0.1835 -0.218 ... #> $ shp5 : num [1:100, 1:2] -0.0971 -0.1205 -0.145 -0.1729 -0.2037 ... #> $ shp6 : num [1:100, 1:2] -0.0927 -0.1161 -0.1411 -0.1691 -0.2001 ... #> $ shp7 : num [1:100, 1:2] -0.109 -0.136 -0.166 -0.2 -0.24 ... #> $ shp8 : num [1:100, 1:2] -0.0991 -0.1245 -0.1532 -0.1837 -0.2199 ... #> $ shp9 : num [1:100, 1:2] -0.101 -0.126 -0.155 -0.186 -0.223 ... #> $ shp10 : num [1:100, 1:2] -0.0849 -0.1063 -0.129 -0.1529 -0.1811 ... #> $ shp11 : num [1:100, 1:2] -0.0921 -0.1162 -0.1424 -0.1704 -0.2019 ... #> $ shp12 : num [1:100, 1:2] -0.084 -0.104 -0.129 -0.154 -0.183 ... #> $ shp13 : num [1:100, 1:2] -0.111 -0.139 -0.171 -0.206 -0.247 ... #> $ shp14 : num [1:100, 1:2] -0.0932 -0.1147 -0.1368 -0.164 -0.1953 ... #> $ shp15 : num [1:100, 1:2] -0.101 -0.124 -0.151 -0.183 -0.218 ... #> $ shp16 : num [1:100, 1:2] -0.105 -0.131 -0.16 -0.193 -0.228 ... #> $ shp17 : num [1:100, 1:2] -0.109 -0.137 -0.167 -0.198 -0.234 ... #> $ shp18 : num [1:100, 1:2] -0.128 -0.16 -0.195 -0.235 -0.28 ... #> $ shp19 : num [1:100, 1:2] -0.113 -0.139 -0.171 -0.206 -0.246 ... #> $ shp20 : num [1:100, 1:2] -0.104 -0.131 -0.16 -0.192 -0.228 ... #> $ shp21 : num [1:100, 1:2] -0.126 -0.157 -0.191 -0.23 -0.271 ... #> $ shp22 : num [1:100, 1:2] -0.116 -0.146 -0.181 -0.217 -0.257 ... #> $ shp23 : num [1:100, 1:2] -0.117 -0.146 -0.18 -0.216 -0.255 ... #> $ shp24 : num [1:100, 1:2] -0.123 -0.154 -0.188 -0.225 -0.267 ... #> $ shp25 : num [1:100, 1:2] -0.107 -0.134 -0.163 -0.196 -0.233 ... #> $ shp26 : num [1:100, 1:2] -0.0917 -0.1141 -0.1381 -0.1675 -0.1995 ... #> $ shp27 : num [1:100, 1:2] -0.0979 -0.1222 -0.1477 -0.1744 -0.2049 ... #> $ shp28 : num [1:100, 1:2] -0.121 -0.151 -0.183 -0.217 -0.259 ... #> $ shp29 : num [1:100, 1:2] -0.124 -0.156 -0.193 -0.234 -0.28 ... #> $ shp30 : num [1:100, 1:2] -0.106 -0.132 -0.161 -0.193 -0.232 ... #> $ shp31 : num [1:100, 1:2] -0.101 -0.126 -0.154 -0.186 -0.22 ... #> $ shp32 : num [1:100, 1:2] -0.126 -0.157 -0.19 -0.228 -0.271 ... #> $ shp33 : num [1:100, 1:2] -0.126 -0.157 -0.195 -0.237 -0.284 ... #> $ shp34 : num [1:100, 1:2] -0.125 -0.155 -0.186 -0.224 -0.266 ... #> $ shp35 : num [1:100, 1:2] -0.0985 -0.1235 -0.1506 -0.1799 -0.2125 ... #> $ shp36 : num [1:100, 1:2] -0.119 -0.149 -0.183 -0.221 -0.263 ... #> $ shp37 : num [1:100, 1:2] -0.113 -0.141 -0.173 -0.209 -0.248 ... #> $ shp38 : num [1:100, 1:2] -0.0991 -0.1227 -0.1493 -0.1803 -0.2158 ... #> $ shp39 : num [1:100, 1:2] -0.107 -0.134 -0.164 -0.196 -0.235 ... #> $ shp40 : num [1:100, 1:2] -0.102 -0.128 -0.155 -0.186 -0.221 ... #> $ shp41 : num [1:100, 1:2] -0.122 -0.153 -0.188 -0.23 -0.274 ... #> $ shp42 : num [1:100, 1:2] -0.115 -0.145 -0.178 -0.214 -0.255 ... #> $ shp43 : num [1:100, 1:2] -0.106 -0.133 -0.162 -0.196 -0.232 ... #> $ shp44 : num [1:100, 1:2] -0.119 -0.151 -0.185 -0.225 -0.268 ... #> $ shp45 : num [1:100, 1:2] -0.11 -0.137 -0.167 -0.203 -0.242 ... #> $ shp46 : num [1:100, 1:2] -0.102 -0.126 -0.155 -0.188 -0.225 ... #> $ shp47 : num [1:100, 1:2] -0.117 -0.146 -0.179 -0.218 -0.259 ... #> $ shp48 : num [1:100, 1:2] -0.102 -0.126 -0.154 -0.184 -0.217 ... #> $ shp49 : num [1:100, 1:2] -0.105 -0.132 -0.161 -0.193 -0.231 ... #> $ shp50 : num [1:100, 1:2] -0.121 -0.151 -0.185 -0.224 -0.267 ... #> $ shp51 : num [1:100, 1:2] -0.134 -0.168 -0.205 -0.245 -0.296 ... #> $ shp52 : num [1:100, 1:2] -0.106 -0.133 -0.162 -0.193 -0.23 ... #> $ shp53 : num [1:100, 1:2] -0.119 -0.148 -0.18 -0.217 -0.257 ... #> $ shp54 : num [1:100, 1:2] -0.121 -0.151 -0.184 -0.221 -0.264 ... #> $ shp55 : num [1:100, 1:2] -0.0875 -0.1083 -0.1316 -0.1588 -0.1877 ... #> $ shp56 : num [1:100, 1:2] -0.104 -0.128 -0.159 -0.193 -0.229 ... #> $ shp57 : num [1:100, 1:2] -0.128 -0.16 -0.197 -0.237 -0.283 ... #> $ shp58 : num [1:100, 1:2] -0.101 -0.125 -0.151 -0.184 -0.22 ... #> $ shp59 : num [1:100, 1:2] -0.105 -0.13 -0.16 -0.194 -0.231 ... #> $ shp60 : num [1:100, 1:2] -0.135 -0.169 -0.208 -0.253 -0.304 ... #> $ shp61 : num [1:100, 1:2] -0.104 -0.131 -0.161 -0.193 -0.229 ... #> $ shp62 : num [1:100, 1:2] -0.0895 -0.1115 -0.1345 -0.1587 -0.1884 ... #> $ shp63 : num [1:100, 1:2] -0.117 -0.147 -0.179 -0.216 -0.259 ... #> $ shp64 : num [1:100, 1:2] -0.115 -0.144 -0.176 -0.214 -0.256 ... #> $ shp65 : num [1:100, 1:2] -0.109 -0.135 -0.164 -0.2 -0.238 ... #> $ shp66 : num [1:100, 1:2] -0.125 -0.158 -0.195 -0.234 -0.276 ... #> $ shp67 : num [1:100, 1:2] -0.107 -0.135 -0.163 -0.195 -0.234 ... #> $ shp68 : num [1:100, 1:2] -0.122 -0.152 -0.184 -0.221 -0.266 ... #> $ shp69 : num [1:100, 1:2] -0.118 -0.145 -0.177 -0.216 -0.258 ... #> $ shp70 : num [1:100, 1:2] -0.116 -0.144 -0.176 -0.21 -0.25 ... #> $ shp71 : num [1:100, 1:2] -0.131 -0.164 -0.2 -0.244 -0.292 ... #> $ shp72 : num [1:100, 1:2] -0.118 -0.148 -0.18 -0.215 -0.256 ... #> $ shp73 : num [1:100, 1:2] -0.0996 -0.1229 -0.1496 -0.1778 -0.2106 ... #> $ shp74 : num [1:100, 1:2] -0.118 -0.149 -0.181 -0.218 -0.259 ... #> $ shp75 : num [1:100, 1:2] -0.118 -0.147 -0.179 -0.214 -0.252 ... #> $ shp76 : num [1:100, 1:2] -0.128 -0.159 -0.191 -0.227 -0.268 ... #> $ shp77 : num [1:100, 1:2] -0.126 -0.159 -0.193 -0.229 -0.271 ... #> $ shp78 : num [1:100, 1:2] -0.111 -0.139 -0.173 -0.21 -0.249 ... #> $ shp79 : num [1:100, 1:2] -0.121 -0.151 -0.183 -0.22 -0.261 ... #> $ shp80 : num [1:100, 1:2] -0.117 -0.146 -0.178 -0.213 -0.253 ... #> $ shp81 : num [1:100, 1:2] -0.109 -0.137 -0.168 -0.202 -0.243 ... #> $ shp82 : num [1:100, 1:2] -0.118 -0.149 -0.184 -0.222 -0.264 ... #> $ shp83 : num [1:100, 1:2] -0.12 -0.15 -0.183 -0.219 -0.256 ... #> $ shp84 : num [1:100, 1:2] -0.135 -0.168 -0.207 -0.25 -0.299 ... #> $ shp85 : num [1:100, 1:2] -0.118 -0.149 -0.181 -0.218 -0.261 ... #> $ shp86 : num [1:100, 1:2] -0.119 -0.149 -0.181 -0.221 -0.265 ... #> $ shp87 : num [1:100, 1:2] -0.106 -0.132 -0.162 -0.194 -0.232 ... #> $ shp88 : num [1:100, 1:2] -0.104 -0.128 -0.157 -0.188 -0.22 ... #> $ shp89 : num [1:100, 1:2] -0.106 -0.132 -0.162 -0.195 -0.23 ... #> $ shp90 : num [1:100, 1:2] -0.127 -0.159 -0.195 -0.235 -0.282 ... #> $ shp91 : num [1:100, 1:2] -0.111 -0.139 -0.168 -0.202 -0.238 ... #> $ shp92 : num [1:100, 1:2] -0.101 -0.126 -0.154 -0.187 -0.224 ... #> $ shp93 : num [1:100, 1:2] -0.127 -0.158 -0.193 -0.231 -0.278 ... #> $ shp94 : num [1:100, 1:2] -0.104 -0.13 -0.159 -0.193 -0.23 ... #> $ shp95 : num [1:100, 1:2] -0.0868 -0.1067 -0.1271 -0.1523 -0.182 ... #> $ shp96 : num [1:100, 1:2] -0.103 -0.128 -0.156 -0.188 -0.225 ... #> $ shp97 : num [1:100, 1:2] -0.102 -0.127 -0.156 -0.188 -0.222 ... #> $ shp98 : num [1:100, 1:2] -0.104 -0.132 -0.161 -0.192 -0.225 ... #> $ shp99 : num [1:100, 1:2] -0.108 -0.133 -0.16 -0.193 -0.227 ... #> [list output truncated] #> fac : tibble [0 × 0] (S3: tbl_df/tbl/data.frame) #> Named list() #> ldk : list()"},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":null,"dir":"Reference","previous_headings":"","what":"Multivariate analysis of (co)variance on Coe objects — MANOVA","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Performs multivariate analysis variance PCA objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"","code":"MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for OpnCoe MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for OutCoe MANOVA(x, fac, test = \"Hotelling\", retain, drop) # S3 method for PCA MANOVA(x, fac, test = \"Hotelling\", retain = 0.99, drop)"},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"x Coe object fac name colum $fac slot, id, formula test test manova ('Hotelling' default) retain many harmonics (polynomials) retain, PCA highest number PC axis retain, proportion variance capture. drop many harmonics (polynomials) drop","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"list matrices (x,y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Performs MANOVA/MANCOVA PC scores. Just wrapper around manova. See examples multifactorial manova summary.manova details examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"Needs review considered experimental. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MANOVA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Multivariate analysis of (co)variance on Coe objects — MANOVA","text":"","code":"# MANOVA bot.p <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MANOVA(bot.p, 'type') #> PC axes 1 to 7 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 2.7631 12.631 7 32 1.202e-07 *** #> Residuals 38 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 op <- PCA(npoly(olea, 5)) #> 'nb.pts' missing and set to: 91 MANOVA(op, 'domes') #> PC axes 1 to 2 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 0.37378 38.686 2 207 5.315e-15 *** #> Residuals 208 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 m <- manova(op$x[, 1:5] ~ op$fac$domes * op$fac$var) summary(m) #> Df Pillai approx F num Df den Df Pr(>F) #> op$fac$domes 1 0.38594 25.3915 5 202 < 2.2e-16 *** #> op$fac$var 2 0.34192 8.3723 10 406 2.069e-12 *** #> Residuals 206 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 summary.aov(m) #> Response PC1 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 11.79 11.790 1.2623 0.26251 #> op$fac$var 2 109.81 54.903 5.8784 0.00329 ** #> Residuals 206 1924.02 9.340 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC2 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 62.486 62.486 93.511 < 2.2e-16 *** #> op$fac$var 2 34.489 17.244 25.806 9.97e-11 *** #> Residuals 206 137.654 0.668 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC3 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.2345 0.234541 3.9476 0.04826 * #> op$fac$var 2 0.5998 0.299918 5.0479 0.00724 ** #> Residuals 206 12.2393 0.059414 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC4 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.12558 0.125582 8.5246 0.003894 ** #> op$fac$var 2 0.08698 0.043490 2.9521 0.054442 . #> Residuals 206 3.03476 0.014732 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> Response PC5 : #> Df Sum Sq Mean Sq F value Pr(>F) #> op$fac$domes 1 0.000140 0.00014009 0.7838 0.3770 #> op$fac$var 2 0.000299 0.00014964 0.8372 0.4344 #> Residuals 206 0.036819 0.00017873 #> # MANCOVA example # we create a numeric variable, based on centroid size bot %<>% mutate(cs=coo_centsize(.)) # same pipe bot %>% efourier %>% PCA %>% MANOVA(\"cs\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> PC axes 1 to 7 were retained #> Df Hotelling-Lawley approx F num Df den Df Pr(>F) #> fac 1 0.38135 1.7433 7 32 0.1341 #> Residuals 38"},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":null,"dir":"Reference","previous_headings":"","what":"Pairwise Multivariate analyses of variance — MANOVA_PW","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"wrapper pairwise MANOVAs Coe objects. Calculates MANOVA every pairwise combination factor provided.","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"","code":"MANOVA_PW(x, ...) # S3 method for PCA MANOVA_PW(x, fac, retain = 0.99, ...)"},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"x PCA object ... arguments feed MANOVA fac name (id) grouping factor $fac factor formula. retain number PC axis retain (1:retain) proportion variance capture (0.99 par default).","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"list following components returned (invisibly $manovas may long, see examples): manovas list containing raw manovas summary stars.tab table 'significance stars', discutable largely used: '' Pr(>F) < 0.001; '' < 0.01; '' < 0.05; '.' < 0.10 '-' .","code":""},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"Needs review considered experimental. fac passed two levels, pair equivalent MANOVA. MANOVA_PW.PCA works regular manova.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MANOVA_PW.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pairwise Multivariate analyses of variance — MANOVA_PW","text":"","code":"# we create a fake factor with 4 levels bot$fac$fake <- factor(rep(letters[1:4], each=10)) bot.p <- PCA(efourier(bot, 8)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MANOVA_PW(bot.p, 'fake') # or MANOVA_PW(bot.p, 2) #> PC axes 1 to 6 were retained #> ab #> ac #> ad #> bc #> bd #> cd #> $stars.tab #> a b c d #> a - ** ** #> b * * #> c - #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> a - b 1 0.1848 0.4912 6 13 0.803857 #> a - c 1 0.7785 7.6167 6 13 0.001157 #> a - d 1 0.6865 4.7449 6 13 0.009007 #> b - c 1 0.6634 4.2700 6 13 0.013537 #> b - d 1 0.5793 2.9830 6 13 0.046573 #> c - d 1 0.3489 1.1611 6 13 0.383292 # an example on open outlines op <- PCA(npoly(olea)) #> 'nb.pts' missing and set to: 91 #> 'degree' missing and set to: 5 MANOVA_PW(op, 'domes') #> PC axes 1 to 2 were retained #> cultwild #> $stars.tab #> cult wild #> cult *** #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2721 38.69 2 207 5.315e-15 # to get the results res <- MANOVA_PW(op, 'domes') #> PC axes 1 to 2 were retained #> cultwild #> $stars.tab #> cult wild #> cult *** #> #> $summary (see also $manovas) #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2721 38.69 2 207 5.315e-15 res$manovas #> $`cult - wild` #> Df Pillai approx F num Df den Df Pr(>F) #> fac.i 1 0.27208 38.686 2 207 5.315e-15 *** #> Residuals 208 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> res$stars.tab #> cult wild #> cult *** res$summary #> Df Pillai approx F num Df den Df Pr(>F) #> cult - wild 1 0.2720825 38.68644 2 207 5.315003e-15"},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":null,"dir":"Reference","previous_headings":"","what":"(Metric) multidimensional scaling — MDS","title":"(Metric) multidimensional scaling — MDS","text":"wrapper around stats::cmdscale.","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"(Metric) multidimensional scaling — MDS","text":"","code":"MDS(x, method = \"euclidean\", k = 2, ...)"},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"(Metric) multidimensional scaling — MDS","text":"x Coe object method dissiminarity index feed method stats::dist (default: euclidean) k numeric number dimensions feed stats::cmdscale (default: 2) ... additional parameters feed stats::cmdscale","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"(Metric) multidimensional scaling — MDS","text":"returned stats::dist plus $fac. prepend MDS class .","code":""},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"(Metric) multidimensional scaling — MDS","text":"Details, see vegan::metaMDS","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"(Metric) multidimensional scaling — MDS","text":"","code":"x <- bot %>% efourier %>% MDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x #> $x #> [,1] [,2] #> brahma -0.05277530 -0.0230987121 #> caney -0.03692797 0.0072496676 #> chimay 0.08091319 -0.0047905849 #> corona -0.06936747 0.0022942672 #> deusventrue -0.01117242 0.0475689844 #> duvel 0.11514484 -0.0169960574 #> franziskaner -0.04425459 -0.0185989836 #> grimbergen 0.02874996 0.0099554795 #> guiness 0.01231138 0.0006027416 #> hoegardeen -0.04579716 0.0056378311 #> jupiler -0.05431287 0.0072952179 #> kingfisher -0.03821463 -0.0034548056 #> latrappe 0.13300133 -0.0384264345 #> lindemanskriek -0.03540248 0.0147002348 #> nicechouffe -0.02097431 0.0133514818 #> pecheresse -0.05277659 0.0083010974 #> sierranevada 0.03905169 -0.0068665050 #> tanglefoot 0.07741376 -0.0020813543 #> tauro -0.05456357 0.0073871372 #> westmalle -0.05000066 0.0065364611 #> amrut -0.04851067 0.0003233973 #> ballantines 0.12125872 -0.0671656955 #> bushmills -0.03619504 -0.0540035080 #> chivas 0.07579382 0.0395367090 #> dalmore 0.10196157 0.0535941215 #> famousgrouse -0.03460400 -0.0243909943 #> glendronach -0.05266032 -0.0003142188 #> glenmorangie -0.06127392 0.0037530633 #> highlandpark 0.08332158 -0.0437952867 #> jackdaniels 0.01064050 -0.0005682657 #> jb -0.04043031 0.0088167995 #> johnniewalker -0.03553374 -0.0387787659 #> magallan -0.07106980 -0.0303786761 #> makersmark 0.06020727 0.0476203806 #> oban -0.06297482 0.0061352696 #> oldpotrero 0.03373439 0.0616822707 #> redbreast 0.06482559 0.0494227507 #> tamdhu -0.04715671 -0.0061720938 #> wildturkey -0.01548202 0.0145967715 #> yoichi 0.03410175 -0.0364811930 #> #> $fac #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> 7 whisky a #> 8 whisky a #> 9 whisky a #> 10 whisky a #> # ℹ 30 more rows #> #> attr(,\"class\") #> [1] \"MDS\" \"list\""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":null,"dir":"Reference","previous_headings":"","what":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"Quite versatile function calculates mean (median, whatever function) list array shapes, Ldk object. can also used Coe objects. case, reverse transformation (coefficients shapes) calculated, (within groups defined fac argument provided) Coe object also returned ($Coe) along list shapes ($shp) can passed plot_MSHAPES.","code":""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"","code":"MSHAPES(x, fac = NULL, FUN = mean, nb.pts = 120, ...)"},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"x list, array, Ldk, LdkCoe, OutCoe OpnCoe PCA object fac factor specification fac_dispatcher FUN function compute mean shape (mean default, median can considered) nb.pts numeric number points calculated shapes (Coe objects) ... useless .","code":""},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"averaged shape; Coe objects, list two components: $Coe object class, $shp list matrices (x, y) coordinates. PCA LDA objects, FUN (typically mean median) scores PCs LDs. method used latter objects may moved another function point.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/MSHAPES.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mean shape calculation for Coo, Coe, etc. — MSHAPES","text":"","code":"#### on shapes MSHAPES(wings) #> x y #> 1 -0.472151969 0.026257480 #> 2 0.009588976 0.082756693 #> 3 0.231342520 0.063322047 #> 4 0.249218898 0.044129134 #> 5 0.254361417 0.022457480 #> 6 0.249206299 0.003249606 #> 7 0.230685827 -0.017059843 #> 8 0.186659843 -0.041403937 #> 9 0.116231496 -0.063584252 #> 10 0.030126772 -0.087316535 #> 11 -0.080339370 -0.103129134 #> 12 -0.405025984 -0.014459055 #> 13 -0.388690551 0.023895276 #> 14 -0.177349606 0.029181102 #> 15 0.066421260 0.043376378 #> 16 -0.027141732 0.019349606 #> 17 0.067113386 -0.009022047 #> 18 -0.140259843 -0.022011024 MSHAPES(wings$coo) #> x y #> 1 -0.472151969 0.026257480 #> 2 0.009588976 0.082756693 #> 3 0.231342520 0.063322047 #> 4 0.249218898 0.044129134 #> 5 0.254361417 0.022457480 #> 6 0.249206299 0.003249606 #> 7 0.230685827 -0.017059843 #> 8 0.186659843 -0.041403937 #> 9 0.116231496 -0.063584252 #> 10 0.030126772 -0.087316535 #> 11 -0.080339370 -0.103129134 #> 12 -0.405025984 -0.014459055 #> 13 -0.388690551 0.023895276 #> 14 -0.177349606 0.029181102 #> 15 0.066421260 0.043376378 #> 16 -0.027141732 0.019349606 #> 17 0.067113386 -0.009022047 #> 18 -0.140259843 -0.022011024 MSHAPES(coo_sample(bot, 24)$coo) #> x y #> 1 60.725 419.125 #> 2 58.350 344.200 #> 3 59.025 266.000 #> 4 59.925 189.900 #> 5 60.100 112.650 #> 6 72.025 40.300 #> 7 146.625 21.375 #> 8 222.175 24.600 #> 9 278.800 63.475 #> 10 286.850 136.775 #> 11 287.250 211.100 #> 12 287.925 288.400 #> 13 287.700 365.725 #> 14 283.325 441.375 #> 15 262.675 517.250 #> 16 237.325 586.950 #> 17 222.700 664.275 #> 18 215.900 739.350 #> 19 208.550 809.525 #> 20 137.150 808.650 #> 21 128.475 739.425 #> 22 123.650 663.775 #> 23 109.650 590.000 #> 24 83.625 514.500 stack(wings) coo_draw(MSHAPES(wings)) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details MSHAPES(bot.f) # the mean (global) shape #> no 'fac' provided, returns meanshape #> x y #> [1,] 1.168906286 -0.0001651753 #> [2,] 1.163078247 0.0421600553 #> [3,] 1.145987931 0.0791545836 #> [4,] 1.119080936 0.1068491537 #> [5,] 1.084462899 0.1234921899 #> [6,] 1.044515489 0.1298160330 #> [7,] 1.001501085 0.1286134238 #> [8,] 0.957247869 0.1237878526 #> [9,] 0.912978161 0.1191956670 #> [10,] 0.869298497 0.1176432074 #> [11,] 0.826324964 0.1203279475 #> [12,] 0.783884894 0.1268487171 #> [13,] 0.741725082 0.1357159282 #> [14,] 0.699667837 0.1451353059 #> [15,] 0.657683275 0.1537690869 #> [16,] 0.615878472 0.1612150898 #> [17,] 0.574430083 0.1680667629 #> [18,] 0.533499333 0.1755775102 #> [19,] 0.493164879 0.1850912925 #> [20,] 0.453393981 0.1974710400 #> [21,] 0.414053341 0.2127369864 #> [22,] 0.374945749 0.2300322600 #> [23,] 0.335852608 0.2479030949 #> [24,] 0.296566207 0.2647662777 #> [25,] 0.256905612 0.2793783445 #> [26,] 0.216720688 0.2911371254 #> [27,] 0.175894459 0.3001249134 #> [28,] 0.134352476 0.3069092041 #> [29,] 0.092080418 0.3122084326 #> [30,] 0.049142076 0.3165718347 #> [31,] 0.005684547 0.3202014303 #> [32,] -0.038080617 0.3229727379 #> [33,] -0.081922450 0.3246211931 #> [34,] -0.125651137 0.3249912594 #> [35,] -0.169173183 0.3242231538 #> [36,] -0.212517809 0.3227854829 #> [37,] -0.255819333 0.3213351308 #> [38,] -0.299256747 0.3204663421 #> [39,] -0.342970452 0.3204641335 #> [40,] -0.386988991 0.3211796377 #> [41,] -0.431199127 0.3220947589 #> [42,] -0.475378578 0.3225609447 #> [43,] -0.519286078 0.3221164568 #> [44,] -0.562776943 0.3207428677 #> [45,] -0.605894989 0.3189350982 #> [46,] -0.648891824 0.3175276310 #> [47,] -0.692145046 0.3173174414 #> [48,] -0.735982396 0.3186132956 #> [49,] -0.780457859 0.3208847676 #> [50,] -0.825153563 0.3226624581 #> [51,] -0.869086061 0.3217583294 #> [52,] -0.910772394 0.3157606556 #> [53,] -0.948465170 0.3026542245 #> [54,] -0.980510370 0.2813630409 #> [55,] -1.005735148 0.2520318883 #> [56,] -1.023752227 0.2159499153 #> [57,] -1.035081884 0.1751434820 #> [58,] -1.041039987 0.1317817301 #> [59,] -1.043407694 0.0876037220 #> [60,] -1.043964872 0.0435658071 #> [61,] -1.044013564 -0.0001747867 #> [62,] -1.044025203 -0.0439492146 #> [63,] -1.043512254 -0.0880697136 #> [64,] -1.041161156 -0.1323293477 #> [65,] -1.035188270 -0.1757099138 #> [66,] -1.023817167 -0.2164219884 #> [67,] -1.005743392 -0.2522778444 #> [68,] -0.980460978 -0.2812740940 #> [69,] -0.948369940 -0.3021819671 #> [70,] -0.910650551 -0.3149377945 #> [71,] -0.868957121 -0.3206959085 #> [72,] -0.825030797 -0.3215245758 #> [73,] -0.780344469 -0.3198490360 #> [74,] -0.735871551 -0.3178294420 #> [75,] -0.692023558 -0.3168762464 #> [76,] -0.648746041 -0.3174481558 #> [77,] -0.605716737 -0.3191716238 #> [78,] -0.562567403 -0.3212066058 #> [79,] -0.519056221 -0.3227031290 #> [80,] -0.475145999 -0.3231749465 #> [81,] -0.430982360 -0.3226635945 #> [82,] -0.386801287 -0.3216571441 #> [83,] -0.342815151 -0.3208256181 #> [84,] -0.299125898 -0.3207013096 #> [85,] -0.255696084 -0.3214429085 #> [86,] -0.212381865 -0.3227761919 #> [87,] -0.169007586 -0.3241225855 #> [88,] -0.125448199 -0.3248451835 #> [89,] -0.081686941 -0.3244939182 #> [90,] -0.037829212 -0.3229368063 #> [91,] 0.005927348 -0.3203193572 #> [92,] 0.049350196 -0.3168750705 #> [93,] 0.092232630 -0.3126812931 #> [94,] 0.134436974 -0.3074850475 #> [95,] 0.175910258 -0.3006982100 #> [96,] 0.216675572 -0.2915894535 #> [97,] 0.256811552 -0.2796108642 #> [98,] 0.296433966 -0.2647280865 #> [99,] 0.335687496 -0.2476054872 #> [100,] 0.374746057 -0.2295433326 #> [101,] 0.413812022 -0.2121578168 #> [102,] 0.453102987 -0.1969013652 #> [103,] 0.492820622 -0.1845967071 #> [104,] 0.533107240 -0.1751700190 #> [105,] 0.574006481 -0.1677059544 #> [106,] 0.615448834 -0.1608297786 #> [107,] 0.657277055 -0.1532916765 #> [108,] 0.699311281 -0.1445361651 #> [109,] 0.741434152 -0.1350246853 #> [110,] 0.783660554 -0.1261538349 #> [111,] 0.826152488 -0.1197537224 #> [112,] 0.869151275 -0.1173116512 #> [113,] 0.912825186 -0.1191865197 #> [114,] 0.957062915 -0.1241110447 #> [115,] 1.001270984 -0.1292041692 #> [116,] 1.044245114 -0.1305548005 #> [117,] 1.084175273 -0.1242429094 #> [118,] 1.118812297 -0.1075023934 #> [119,] 1.145778947 -0.0796605231 #> [120,] 1.162963747 -0.0425396294 ms <- MSHAPES(bot.f, 'type') ms$Coe #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 2 outlines described, 12 harmonics #> # A tibble: 2 × 2 #> type fake #> #> 1 beer c #> 2 whisky a class(ms$Coe) #> [1] \"OutCoe\" \"Coe\" ms <- ms$shp coo_plot(ms$beer) coo_draw(ms$whisky, border='forestgreen')"},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":null,"dir":"Reference","previous_headings":"","what":"Momocs — Momocs","title":"Momocs — Momocs","text":"goal Momocs provide complete, convenient, reproducible open-source toolkit 2D morphometrics. includes common 2D morphometrics approaches outlines, open outlines, configurations landmarks, traditional morphometrics, facilities data preparation, manipulation visualization consistent grammar throughout. allows reproducible, complex morphometric analyses morphometrics approaches easy plug , develop , top canvas.","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Momocs — Momocs","text":"nothing","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Momocs — Momocs","text":"cite Momocs publications: citation(\"Momocs\").","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"cheers","dir":"Reference","previous_headings":"","what":"Cheers","title":"Momocs — Momocs","text":"grateful (alphabetical order): Sean Asselin, Laurent Bouby, Matt Bulbert, Simon Crameri, Julia Cooke, April Dinwiddie, Carl Lipo, Cedric Gaucherel, Catherine Girard, QGouil (GitHub), Christian Steven Hoggard, Sarah Ivorra, Glynis Jones, Nathalie Keller, Ricardo Kriebel, Remi Laffont, Fabien Lafuma, Matthias Mace, Stas Malavin, Neus Martinez, Ben Marwick, Sabrina Renaud, Marcelo Reginato, Evan Saitta, Bill Sellers, David Siddons, Eleanor Stillman, Theodore Stammer, Tom Stubbs, Norbert Telmon, Jean-Frederic Terral, Bill Venables, Daniele Ventura, Michael Wallace, Asher Wishkerman, John Wood helpful ideas bug reports.","code":""},{"path":"http://momx.github.io/Momocs/reference/Momocs.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Momocs — Momocs","text":"Bonhomme V, Picq S, Gaucherel C, Claude J. 2014. Momocs: Outline Analysis Using R. Journal Statistical Software 56. https://www.jstatsoft.org/v56/i13. Claude J. 2008. Morphometrics R. Springer-Verlag, New-York.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":null,"dir":"Reference","previous_headings":"","what":"Non metric multidimensional scaling — NMDS","title":"Non metric multidimensional scaling — NMDS","text":"wrapper around vegan::metaMDS.","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Non metric multidimensional scaling — NMDS","text":"","code":"NMDS(x, distance = \"bray\", k = 2, try = 20, trymax = 20, ...)"},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Non metric multidimensional scaling — NMDS","text":"x Coe object distance dissiminarity index feed vegan::vegdist (default: bray) k numeric number dimensions feed vegan::metaMDS (default: 2) try numeric minimum number random starts feed vegan::metaMDS (default: 20) trymax numeric minimum number random starts feed vegan::metaMDS (default: 20) ... additional parameters feed vegan::metaMDS","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Non metric multidimensional scaling — NMDS","text":"returned vegan::metaMDS plus $fac. prepend NMDS class .","code":""},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Non metric multidimensional scaling — NMDS","text":"Details, see vegan::metaMDS","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/NMDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Non metric multidimensional scaling — NMDS","text":"","code":"x <- bot %>% efourier %>% NMDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> 'comm' has negative data: 'autotransform', 'noshare' and 'wascores' set to FALSE #> Warning: results may be meaningless because data have negative entries #> in method “bray” #> Run 0 stress 0.07227125 #> Run 1 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 3.936046e-06 max resid 1.87576e-05 #> ... Similar to previous best #> Run 2 stress 0.1536609 #> Run 3 stress 0.1729702 #> Run 4 stress 0.07227125 #> ... Procrustes: rmse 5.981988e-06 max resid 2.874886e-05 #> ... Similar to previous best #> Run 5 stress 0.07227125 #> ... Procrustes: rmse 2.19081e-06 max resid 8.275813e-06 #> ... Similar to previous best #> Run 6 stress 0.07227125 #> ... Procrustes: rmse 7.02888e-06 max resid 2.808569e-05 #> ... Similar to previous best #> Run 7 stress 0.07227125 #> ... Procrustes: rmse 9.669054e-06 max resid 3.852924e-05 #> ... Similar to previous best #> Run 8 stress 0.1476475 #> Run 9 stress 0.07227125 #> ... Procrustes: rmse 1.146136e-06 max resid 4.040052e-06 #> ... Similar to previous best #> Run 10 stress 0.07227125 #> ... Procrustes: rmse 2.035528e-06 max resid 8.084339e-06 #> ... Similar to previous best #> Run 11 stress 0.07227126 #> ... Procrustes: rmse 7.291375e-06 max resid 2.685535e-05 #> ... Similar to previous best #> Run 12 stress 0.1647891 #> Run 13 stress 0.07227125 #> ... Procrustes: rmse 6.998249e-06 max resid 2.725125e-05 #> ... Similar to previous best #> Run 14 stress 0.07227125 #> ... Procrustes: rmse 5.714742e-06 max resid 2.216745e-05 #> ... Similar to previous best #> Run 15 stress 0.1606935 #> Run 16 stress 0.07227125 #> ... Procrustes: rmse 6.971938e-06 max resid 2.720148e-05 #> ... Similar to previous best #> Run 17 stress 0.07227125 #> ... Procrustes: rmse 8.281581e-07 max resid 2.450366e-06 #> ... Similar to previous best #> Run 18 stress 0.1776127 #> Run 19 stress 0.07227125 #> ... Procrustes: rmse 4.920737e-06 max resid 1.945613e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 #> ... Procrustes: rmse 1.953093e-06 max resid 6.877957e-06 #> ... Similar to previous best #> *** Best solution repeated 14 times # Shepard diagram # before a Momocs wrapper # vegan::stressplot(x)"},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Opn object — Opn","title":"Builds an Opn object — Opn","text":"Momocs, Opn classes objects lists open outlines, optionnal components, generic methods plotting methods (e.g. stack) specific methods (e.g. npoly can applied. Opn objects primarily Coo objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Opn object — Opn","text":"","code":"Opn(x, fac = dplyr::tibble(), ldk = list())"},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Opn object — Opn","text":"x list matrices (x; y) coordinates, array, data.frame (friends) fac (optionnal) data.frame factors /numerics specifying grouping structure ldk (optionnal) list landmarks row number indices","code":""},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Opn object — Opn","text":"Opn object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Opn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Opn object — Opn","text":"","code":"#Methods on Opn methods(class=Opn) #> [1] add_ldk combine coo_bookstein coo_sample #> [5] coo_sample_prop coo_slice coo_smoothcurve def_ldk #> [9] def_ldk_angle def_ldk_direction def_ldk_tips dfourier #> [13] fgProcrustes get_ldk mosaic npoly #> [17] opoly panel pile rearrange_ldk #> see '?methods' for accessing help and source code # we load some open outlines. See ?olea for credits olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk panel(olea) # orthogonal polynomials op <- opoly(olea, degree=5) #> 'nb.pts' missing and set to 91 # we print the Coe op #> An OpnCoe object [ opoly analysis ] #> -------------------- #> - $coe: 210 open outlines described #> - $baseline1: (-0.5; 0), $baseline2: (0.5; 0) #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows # Let's do a PCA on it op.p <- PCA(op) plot(op.p, 'domes') #> will be deprecated soon, see ?plot_PCA plot(op.p, 'var') #> will be deprecated soon, see ?plot_PCA # and now an LDA after a PCA olda <- LDA(PCA(op), 'var') #> 4 PC retained # for CV table and others olda #> * Cross-validation table ($CV.tab): #> classified #> actual Aglan Cypre MouBo1 PicMa #> Aglan 21 2 17 20 #> Cypre 12 4 14 0 #> MouBo1 4 2 54 0 #> PicMa 22 1 2 35 #> #> * Class accuracy ($CV.ce): #> Aglan Cypre MouBo1 PicMa #> 0.3500000 0.1333333 0.9000000 0.5833333 #> #> * Leave-one-out cross-validation ($CV.correct): (54.3% - 114/210): plot_LDA(olda)"},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an OpnCoe object — OpnCoe","title":"Builds an OpnCoe object — OpnCoe","text":"Momocs, OpnCoe classes objects wrapping around lists morphometric coefficients, along informations, generic methods plotting methods (e.g. boxplot) specific methods can applied. OpnCoe objects primarily Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an OpnCoe object — OpnCoe","text":"","code":"OpnCoe( coe = matrix(), fac = dplyr::tibble(), method = character(), baseline1 = numeric(), baseline2 = numeric(), mod = list(), r2 = numeric() )"},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an OpnCoe object — OpnCoe","text":"coe matrix morphometric coefficients fac (optionnal) data.frame factors, specifying grouping structure method used obtain coefficients baseline1 \\((x; y)\\) coordinates first baseline point baseline2 \\((x; y)\\) coordinates second baseline point mod R lm object, used reconstruct shapes r2 numeric, r-squared every model","code":""},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an OpnCoe object — OpnCoe","text":"OpnCoe object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/OpnCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an OpnCoe object — OpnCoe","text":"","code":"# all OpnCoe classes methods(class='OpnCoe') #> [1] MANOVA MSHAPES PCA boxplot combine print #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an Out object — Out","title":"Builds an Out object — Out","text":"Momocs, -classes objects lists closed outlines, optional components, generic methods plotting methods (e.g. stack) specific methods (e.g. efourier can applied. objects primarily Coo objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an Out object — Out","text":"","code":"Out(x, fac = dplyr::tibble(), ldk = list())"},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an Out object — Out","text":"x list matrices (x; y) coordinates, array object Ldk object, data.frame (friends) fac (optional) data.frame factors /numerics specifying grouping structure ldk (optional) list landmarks row number indices","code":""},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an Out object — Out","text":"object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Out.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an Out object — Out","text":"","code":"methods(class=Out) #> [1] add_ldk combine coo_bookstein coo_down #> [5] coo_left coo_right coo_sample coo_sample_prop #> [9] coo_slice coo_up d def_ldk #> [13] def_ldk_angle def_ldk_direction efourier fgProcrustes #> [17] get_ldk mosaic panel pile #> [21] rearrange_ldk rfourier sfourier tfourier #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Builds an OutCoe object — OutCoe","title":"Builds an OutCoe object — OutCoe","text":"Momocs, OutCoe classes objects wrapping around lists morphometric coefficients, along informations, generic methods plotting methods (e.g. boxplot) specific methods can applied. OutCoe objects primarily Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Builds an OutCoe object — OutCoe","text":"","code":"OutCoe(coe = matrix(), fac = dplyr::tibble(), method, norm)"},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Builds an OutCoe object — OutCoe","text":"coe matrix harmonic coefficients fac (optional) data.frame factors, specifying grouping structure method used obtain coefficients norm normalisation used obtain coefficients","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Builds an OutCoe object — OutCoe","text":"OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Builds an OutCoe object — OutCoe","text":"methods can applied objects:","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/OutCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Builds an OutCoe object — OutCoe","text":"","code":"# all OutCoe methods methods(class='OutCoe') #> [1] MANOVA MSHAPES PCA boxplot combine hcontrib print rm_asym #> [9] rm_sym symmetry #> see '?methods' for accessing help and source code"},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Principal component analysis on Coe objects — PCA","title":"Principal component analysis on Coe objects — PCA","text":"Performs PCA Coe objects, using prcomp.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Principal component analysis on Coe objects — PCA","text":"","code":"PCA(x, scale., center, fac) # S3 method for OutCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for OpnCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for LdkCoe PCA(x, scale. = FALSE, center = TRUE, fac) # S3 method for TraCoe PCA(x, scale. = TRUE, center = TRUE, fac) # S3 method for default PCA(x, scale. = TRUE, center = TRUE, fac = dplyr::tibble()) as_PCA(x, fac)"},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Principal component analysis on Coe objects — PCA","text":"x Coe object appropriate object (eg prcomp) as_PCA scale. logical whether scale input data center logical whether center input data fac factor data.frame passed as_PCA use plot.PCA","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Principal component analysis on Coe objects — PCA","text":"'PCA' object apply plot.PCA, among others. list several components, inherited prcomp object: sdev standard deviations principal components (.e., square roots eigenvalues covariance/correlation matrix, though calculation actually done singular values data matrix) eig cumulated proportion variance along PC axes rotation matrix variable loadings (.e., matrix whose columns contain eigenvectors). function princomp returns element loadings. center, scale centering scaling used x PCA scores (value rotated data (centred (scaled requested) data multiplied rotation matrix)) components inherited Coe object passed PCA, eg fac, mshape, method, baseline1 baseline2, etc. documented corresponding *Coe file.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Principal component analysis on Coe objects — PCA","text":"default, methods Coe object scale input data center . also generic method (eg traditional morphometrics) centers scales data.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Principal component analysis on Coe objects — PCA","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) bot.p #> A PCA object #> -------------------- #> - 40 shapes #> - $method: [ efourier analysis ] #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts. plot(bot.p, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA plot(bot.p, 'type') #> will be deprecated soon, see ?plot_PCA op <- npoly(olea, 5) #> 'nb.pts' missing and set to: 91 op.p <- PCA(op) op.p #> A PCA object #> -------------------- #> - 210 shapes #> - $method: [ npoly analysis ] #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, mod, baseline1, baseline2, cuts. plot(op.p, 1, morpho=TRUE) #> will be deprecated soon, see ?plot_PCA wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wpp <- PCA(wp) wpp #> A PCA object #> -------------------- #> - 127 shapes #> - $method: [ procrustes analysis ] #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts, links. plot(wpp, 1) #> will be deprecated soon, see ?plot_PCA # \"foreign prcomp\" head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3.0 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa #> 4 4.6 3.1 1.5 0.2 setosa #> 5 5.0 3.6 1.4 0.2 setosa #> 6 5.4 3.9 1.7 0.4 setosa iris.p <- prcomp(iris[, 1:4]) iris.p <- as_PCA(iris.p, iris[, 5]) class(iris.p) #> [1] \"PCA\" \"prcomp\" plot(iris.p, 1) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":null,"dir":"Reference","previous_headings":"","what":"Shape variation along PC axes — PCcontrib","title":"Shape variation along PC axes — PCcontrib","text":"Calculates plots shape variation along Principal Component axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shape variation along PC axes — PCcontrib","text":"","code":"PCcontrib(PCA, ...) # S3 method for PCA PCcontrib(PCA, nax, sd.r = c(-2, -1, -0.5, 0, 0.5, 1, 2), gap = 1, ...)"},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shape variation along PC axes — PCcontrib","text":"PCA PCA object ... additional parameter pass coo_draw nax range PCs plot (1 99pc total variance default) sd.r single range mean +/- sd values (eg: c(-1, 0, 1)) gap combined-Coe, adjustment variable gap shapes. (bug)Default 1 (whish never superimpose shapes), reduce get compact plot.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shape variation along PC axes — PCcontrib","text":"(invisibly) list gg ggplot object shp list shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/PCcontrib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shape variation along PC axes — PCcontrib","text":"","code":"bot.p <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details PCcontrib(bot.p, nax=1:3) #> Warning: `mutate_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `mutate()` instead. #> ℹ See vignette('programming') for more help #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . # \\donttest{ library(ggplot2) gg <- PCcontrib(bot.p, nax=1:8, sd.r=c(-5, -3, -2, -1, -0.5, 0, 0.5, 1, 2, 3, 5)) gg$gg + geom_polygon(fill=\"slategrey\", col=\"black\") + ggtitle(\"A nice title\") # }"},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":null,"dir":"Reference","previous_headings":"","what":"Ptolemaic ellipses and illustration of efourier — Ptolemy","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"Calculate display Ptolemaic ellipses illustrates intuitively principle behing elliptical Fourier analysis.","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"","code":"Ptolemy( coo, t = seq(0, 2 * pi, length = 7)[-1], nb.h = 3, nb.pts = 360, palette = col_heat, zoom = 5/4, legend = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"coo matrix (x; y) coordinates t vector af angles (radians) display ellipses nb.h integer. number harmonics display nb.pts integer. number points use display shapes palette color palette zoom numeric zoom factor coo_plot legend logical. Whether plot legend box ... additional parameters feed coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"drawing last plot","code":""},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"method inspired figures found followings papers. Kuhl FP, Giardina CR. 1982. Elliptic Fourier features closed contour. Computer Graphics Image Processing 18: 236-258. Crampton JS. 1995. Elliptical Fourier shape analysis fossil bivalves: practical considerations. Lethaia 28: 179-186.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/Ptolemy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Ptolemaic ellipses and illustration of efourier — Ptolemy","text":"","code":"cat <- shapes[4] Ptolemy(cat, main=\"An EFT cat\")"},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Traditional morphometrics class — TraCoe","title":"Traditional morphometrics class — TraCoe","text":"Defines builder traditional measurement class Momocs. intended ease calculations, data handling multivariate statistics just ad Momocs' classes","code":""},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Traditional morphometrics class — TraCoe","text":"","code":"TraCoe(coe = matrix(), fac = dplyr::tibble())"},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Traditional morphometrics class — TraCoe","text":"coe matrix measurements fac data.frame covariates","code":""},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Traditional morphometrics class — TraCoe","text":"list class TraCoe","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/TraCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Traditional morphometrics class — TraCoe","text":"","code":"# let's (more or less) rebuild the flower dataset fl <- TraCoe(iris[, 1:4], dplyr::tibble(sp=iris$Species)) fl %>% PCA() %>% plot(\"sp\") #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Adds new landmarks on Out and Opn objects — add_ldk","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Helps add new landmarks Coo object top existing ones. number landmarks must specified rows indices correspond nearest points clicked every outlines stored $ldk slot Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"","code":"add_ldk(Coo, nb.ldk)"},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Coo Opn object nb.ldk number landmarks add every shape","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Opn object landmarks defined","code":""},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"Note landmarks already defined, function equivalent def_ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/add_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Adds new landmarks on Out and Opn objects — add_ldk","text":"","code":"if (FALSE) { hearts <- slice(hearts, 1:5) # to make it shorter to try # click on 3 points, 5 times. hearts <- def_ldk(hearts, 3) # Don't forget to save the object returned by def_ldk... hearts2 <- add_ldk(hearts, 3) stack(hearts2) hearts2$ldk }"},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":null,"dir":"Reference","previous_headings":"","what":"Arrange rows by variables — arrange","title":"Arrange rows by variables — arrange","text":"Arrange shapes variables, $fac. See examples ?dplyr::arrange.","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Arrange rows by variables — arrange","text":"","code":"arrange(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Arrange rows by variables — arrange","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Arrange rows by variables — arrange","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Arrange rows by variables — arrange","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/arrange.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Arrange rows by variables — arrange","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk # we create a new column olea %>% mutate(id=1:length(.)) %$% fac$id #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 #> [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 #> [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 #> [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 #> [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 #> [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 #> [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 #> [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 #> [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 #> [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 #> [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 #> [199] 199 200 201 202 203 204 205 206 207 208 209 210 # same but now, shapes are arranged in a desc order, based on id olea %>% mutate(id=1:length(.)) %>% arrange(desc(id)) %$% fac$id #> [1] 210 209 208 207 206 205 204 203 202 201 200 199 198 197 196 195 194 193 #> [19] 192 191 190 189 188 187 186 185 184 183 182 181 180 179 178 177 176 175 #> [37] 174 173 172 171 170 169 168 167 166 165 164 163 162 161 160 159 158 157 #> [55] 156 155 154 153 152 151 150 149 148 147 146 145 144 143 142 141 140 139 #> [73] 138 137 136 135 134 133 132 131 130 129 128 127 126 125 124 123 122 121 #> [91] 120 119 118 117 116 115 114 113 112 111 110 109 108 107 106 105 104 103 #> [109] 102 101 100 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 #> [127] 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 #> [145] 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 #> [163] 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 #> [181] 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 #> [199] 12 11 10 9 8 7 6 5 4 3 2 1"},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Turn Momocs objects into tydy data_frames — as_df","title":"Turn Momocs objects into tydy data_frames — as_df","text":"Used particular compatibility tidyverse","code":""},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Turn Momocs objects into tydy data_frames — as_df","text":"","code":"as_df(x, ...) # S3 method for Coo as_df(x, ...) # S3 method for Coe as_df(x, ...) # S3 method for PCA as_df(x, retain, ...) # S3 method for LDA as_df(x, retain, ...)"},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Turn Momocs objects into tydy data_frames — as_df","text":"x object, typically Momocs object ... useless retain numeric use scree methods. Defaut . <1, enough axes retain proportion variance; >1, number axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Turn Momocs objects into tydy data_frames — as_df","text":"dplyr::tibble()","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/as_df.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Turn Momocs objects into tydy data_frames — as_df","text":"","code":"# first, some (baby) objects b <- bot %>% coo_sample(12) bf <- b %>% efourier(5, norm=TRUE) # Coo object b %>% as_df #> # A tibble: 40 × 3 #> coo type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> 7 whisky a #> 8 whisky a #> 9 whisky a #> 10 whisky a #> # ℹ 30 more rows # Coe object bf %>% as_df #> # A tibble: 40 × 22 #> type fake A1 A2 A3 A4 A5 B1 B2 B3 #> #> 1 whisky a 1 0.0120 0.0917 0.0124 0.0248 0 -0.00112 -0.00100 #> 2 whisky a 1 0.0110 0.0918 0.0124 0.0224 0 -0.00125 -0.00280 #> 3 whisky a 1 0.0213 0.0770 0.0240 0.0140 0 -0.00637 0.00124 #> 4 whisky a 1 0.00905 0.0960 0.00971 0.0263 0 -0.000555 -0.00204 #> 5 whisky a 1 0.0208 0.0913 0.0208 0.0193 0 -0.00108 0.00113 #> 6 whisky a 1 0.0200 0.0722 0.0213 0.0119 0 -0.00215 0.00349 #> 7 whisky a 1 0.00998 0.0912 0.0122 0.0248 0 -0.000172 -0.00124 #> 8 whisky a 1 0.0197 0.0845 0.0217 0.0164 0 -0.000464 -0.00144 #> 9 whisky a 1 0.0194 0.0864 0.0214 0.0191 0 -0.00288 -0.00196 #> 10 whisky a 1 0.0128 0.0929 0.0141 0.0236 0 -0.000998 -0.00170 #> # ℹ 30 more rows #> # ℹ 12 more variables: B4 , B5 , C1 , C2 , C3 , #> # C4 , C5 , D1 , D2 , D3 , D4 , D5 # PCA object bf %>% PCA %>% as_df # all PCs by default #> `retain` is too ambitious. All axes returned #> # A tibble: 40 × 22 #> type fake PC1 PC2 PC3 PC4 PC5 PC6 PC7 #> #> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 1.31e-2 -1.09e-3 -5.06e-3 #> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 1.67e-3 4.14e-3 3.06e-5 #> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 7.56e-4 3.99e-3 -3.37e-3 #> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -1.72e-3 4.63e-3 -1.78e-3 #> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -2.45e-5 -1.69e-2 1.31e-3 #> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 2.42e-3 2.48e-3 2.55e-3 #> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -3.13e-3 -1.78e-3 -4.73e-3 #> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 6.12e-3 -2.03e-3 5.70e-4 #> 9 whisky a 0.0114 0.00619 0.00207 0.00298 5.44e-3 2.31e-4 -3.57e-3 #> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 3.75e-3 -7.95e-4 2.55e-4 #> # ℹ 30 more rows #> # ℹ 13 more variables: PC8 , PC9 , PC10 , PC11 , #> # PC12 , PC13 , PC14 , PC15 , PC16 , PC17 , #> # PC18 , PC19 , PC20 bf %>% PCA %>% as_df(2) # or 2 #> # A tibble: 40 × 4 #> type fake PC1 PC2 #> #> 1 whisky a -0.0520 -0.0226 #> 2 whisky a -0.0356 0.00197 #> 3 whisky a 0.0811 -0.00232 #> 4 whisky a -0.0694 -0.00396 #> 5 whisky a -0.0146 0.0455 #> 6 whisky a 0.121 -0.0208 #> 7 whisky a -0.0428 -0.0170 #> 8 whisky a 0.0343 0.00950 #> 9 whisky a 0.0114 0.00619 #> 10 whisky a -0.0440 0.00410 #> # ℹ 30 more rows bf %>% PCA %>% as_df(0.99) # or enough for 99% #> # A tibble: 40 × 8 #> type fake PC1 PC2 PC3 PC4 PC5 PC6 #> #> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 0.0131 -0.00109 #> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 0.00167 0.00414 #> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 0.000756 0.00399 #> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -0.00172 0.00463 #> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -0.0000245 -0.0169 #> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 0.00242 0.00248 #> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -0.00313 -0.00178 #> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 0.00612 -0.00203 #> 9 whisky a 0.0114 0.00619 0.00207 0.00298 0.00544 0.000231 #> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 0.00375 -0.000795 #> # ℹ 30 more rows # LDA object bf %>% LDA(~fake) %>% as_df #> removed these collinear columns:A1, B1, C1 #> # A tibble: 40 × 8 #> actual predicted posterior type fake LD1 LD2 LD3 #> #> 1 a a 1.00 whisky a -4.19 1.84 -1.56 #> 2 a a 0.997 whisky a -2.74 1.68 -0.0456 #> 3 a a 0.878 whisky a -2.26 0.171 -0.293 #> 4 a a 0.935 whisky a -3.17 -0.527 -0.611 #> 5 a a 0.997 whisky a -2.97 1.54 0.665 #> 6 a a 0.989 whisky a -4.64 -0.937 0.385 #> 7 a d 0.620 whisky a -0.109 2.26 -0.0356 #> 8 a a 0.999 whisky a -4.20 0.797 0.520 #> 9 a a 0.994 whisky a -2.97 0.925 -0.640 #> 10 a b 0.826 whisky a -1.52 -0.749 0.113 #> # ℹ 30 more rows # same options apply"},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":null,"dir":"Reference","previous_headings":"","what":"Retain groups with at least n shapes — at_least","title":"Retain groups with at least n shapes — at_least","text":"Examples self-speaking.","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retain groups with at least n shapes — at_least","text":"","code":"at_least(x, fac, N)"},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retain groups with at least n shapes — at_least","text":"x Momocs object fac id name $fac column N minimal number individuals retain group","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retain groups with at least n shapes — at_least","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retain groups with at least n shapes — at_least","text":"N ambitious original object returned message","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/at_least.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retain groups with at least n shapes — at_least","text":"","code":"table(trilo$onto) #> #> a b c d #> 7 16 18 9 at_least(trilo, \"onto\", 9) #> Out (outlines) #> - 43 outlines, 64 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 43 × 1 #> onto #> #> 1 b #> 2 b #> 3 b #> 4 b #> 5 b #> 6 b #> # ℹ 37 more rows #> - also: $ldk at_least(trilo, \"onto\", 16) #> Out (outlines) #> - 34 outlines, 64 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 34 × 1 #> onto #> #> 1 b #> 2 b #> 3 b #> 4 b #> 5 b #> 6 b #> # ℹ 28 more rows #> - also: $ldk at_least(trilo, \"onto\", 2000) # too ambitious ! #> no group with at least 2000 indidivuals #> empty Out"},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Useful convert (x; y) coordinates chain-coded coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"","code":"pix2chc(coo) chc2pix(chc)"},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"coo (x; y) coordinates passed matrix chc chain coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"matrix numeric","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"Kuhl, F. P., & Giardina, C. R. (1982). Elliptic Fourier features closed contour. Computer Graphics Image Processing, 18(3), 236-258.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/babel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert (x; y) coordinates to chaincoded coordinates — pix2chc","text":"","code":"pix2chc(shapes[1]) %T>% print %>% # from pix to chc chc2pix() # and back #> [1] 5 4 3 2 4 4 3 4 4 3 4 4 3 4 3 3 4 3 4 3 3 4 3 3 3 4 3 3 3 3 3 3 3 3 3 2 3 #> [38] 3 3 2 3 3 2 3 3 2 3 2 3 2 3 3 2 3 2 2 3 2 2 3 2 2 2 2 3 2 2 2 2 3 2 2 2 2 #> [75] 2 3 2 1 2 3 2 2 2 2 3 2 2 2 3 2 3 2 3 4 3 4 4 4 4 3 4 4 5 4 4 4 5 4 5 5 5 #> [112] 5 5 5 6 5 5 6 5 5 6 5 6 5 6 5 5 5 6 5 5 5 5 5 5 5 5 4 5 4 5 4 5 4 5 4 5 4 #> [149] 4 4 5 4 4 4 4 4 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 #> [186] 4 4 4 4 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 #> [223] 2 2 2 2 2 2 2 2 2 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [260] 1 0 1 1 1 1 1 2 1 2 1 2 1 1 2 1 2 1 1 2 1 1 1 2 1 1 1 1 1 0 1 1 0 1 0 1 0 #> [297] 1 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [334] 0 7 0 0 0 7 0 0 0 7 0 7 0 7 0 7 0 7 0 7 7 7 7 0 7 7 6 7 7 7 7 6 7 7 6 7 7 #> [371] 6 7 6 6 7 6 7 6 6 7 6 6 7 6 6 7 6 6 6 7 6 6 7 6 6 6 7 6 6 6 7 6 6 6 7 6 6 #> [408] 6 7 6 6 7 6 7 6 7 6 7 7 7 7 7 0 0 7 0 0 1 0 0 1 0 1 1 1 2 1 2 1 2 1 2 1 2 #> [445] 2 1 2 2 1 2 2 1 2 2 1 2 1 2 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 0 1 1 0 #> [482] 1 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> [519] 0 0 1 7 1 3 2 2 2 3 2 2 2 3 2 2 2 3 2 2 3 2 2 2 3 2 2 2 3 2 2 2 2 3 2 2 2 #> [556] 2 2 1 2 1 1 0 0 0 0 1 7 0 7 0 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 #> [593] 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 #> [630] 7 7 7 0 7 7 0 7 7 7 0 7 7 0 7 7 0 7 7 7 0 7 7 0 7 5 5 5 4 5 5 4 5 5 5 4 5 #> [667] 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 #> [704] 5 4 5 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 5 5 4 5 5 4 5 5 4 5 #> [741] 4 4 4 5 3 4 3 3 3 3 2 2 2 2 2 2 2 1 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 #> [778] 2 2 2 1 2 2 1 3 4 4 3 4 4 4 4 4 4 4 4 5 4 4 4 5 4 5 5 6 6 5 6 6 5 6 5 6 6 #> [815] 5 6 5 6 6 5 6 5 6 6 5 6 5 6 5 6 5 6 5 5 6 5 6 5 5 5 6 5 5 5 5 5 5 5 5 5 5 #> [852] 4 5 4 5 5 4 5 4 5 4 4 5 4 4 4 5 4 4 4 4 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 #> [,1] [,2] #> [1,] -1 -1 #> [2,] -2 -1 #> [3,] -3 0 #> [4,] -3 1 #> [5,] -4 1 #> [6,] -5 1 #> [7,] -6 2 #> [8,] -7 2 #> [9,] -8 2 #> [10,] -9 3 #> [11,] -10 3 #> [12,] -11 3 #> [13,] -12 4 #> [14,] -13 4 #> [15,] -14 5 #> [16,] -15 6 #> [17,] -16 6 #> [18,] -17 7 #> [19,] -18 7 #> [20,] -19 8 #> [21,] -20 9 #> [22,] -21 9 #> [23,] -22 10 #> [24,] -23 11 #> [25,] -24 12 #> [26,] -25 12 #> [27,] -26 13 #> [28,] -27 14 #> [29,] -28 15 #> [30,] -29 16 #> [31,] -30 17 #> [32,] -31 18 #> [33,] -32 19 #> [34,] -33 20 #> [35,] -34 21 #> [36,] -34 22 #> [37,] -35 23 #> [38,] -36 24 #> [39,] -37 25 #> [40,] -37 26 #> [41,] -38 27 #> [42,] -39 28 #> [43,] -39 29 #> [44,] -40 30 #> [45,] -41 31 #> [46,] -41 32 #> [47,] -42 33 #> [48,] -42 34 #> [49,] -43 35 #> [50,] -43 36 #> [51,] -44 37 #> [52,] -45 38 #> [53,] -45 39 #> [54,] -46 40 #> [55,] -46 41 #> [56,] -46 42 #> [57,] -47 43 #> [58,] -47 44 #> [59,] -47 45 #> [60,] -48 46 #> [61,] -48 47 #> [62,] -48 48 #> [63,] -48 49 #> [64,] -48 50 #> [65,] -49 51 #> [66,] -49 52 #> [67,] -49 53 #> [68,] -49 54 #> [69,] -49 55 #> [70,] -50 56 #> [71,] -50 57 #> [72,] -50 58 #> [73,] -50 59 #> [74,] -50 60 #> [75,] -50 61 #> [76,] -51 62 #> [77,] -51 63 #> [78,] -50 64 #> [79,] -50 65 #> [80,] -51 66 #> [81,] -51 67 #> [82,] -51 68 #> [83,] -51 69 #> [84,] -51 70 #> [85,] -52 71 #> [86,] -52 72 #> [87,] -52 73 #> [88,] -52 74 #> [89,] -53 75 #> [90,] -53 76 #> [91,] -54 77 #> [92,] -54 78 #> [93,] -55 79 #> [94,] -56 79 #> [95,] -57 80 #> [96,] -58 80 #> [97,] -59 80 #> [98,] -60 80 #> [99,] -61 80 #> [100,] -62 81 #> [101,] -63 81 #> [102,] -64 81 #> [103,] -65 80 #> [104,] -66 80 #> [105,] -67 80 #> [106,] -68 80 #> [107,] -69 79 #> [108,] -70 79 #> [109,] -71 78 #> [110,] -72 77 #> [111,] -73 76 #> [112,] -74 75 #> [113,] -75 74 #> [114,] -76 73 #> [115,] -76 72 #> [116,] -77 71 #> [117,] -78 70 #> [118,] -78 69 #> [119,] -79 68 #> [120,] -80 67 #> [121,] -80 66 #> [122,] -81 65 #> [123,] -81 64 #> [124,] -82 63 #> [125,] -82 62 #> [126,] -83 61 #> [127,] -84 60 #> [128,] -85 59 #> [129,] -85 58 #> [130,] -86 57 #> [131,] -87 56 #> [132,] -88 55 #> [133,] -89 54 #> [134,] -90 53 #> [135,] -91 52 #> [136,] -92 51 #> [137,] -93 50 #> [138,] -94 50 #> [139,] -95 49 #> [140,] -96 49 #> [141,] -97 48 #> [142,] -98 48 #> [143,] -99 47 #> [144,] -100 47 #> [145,] -101 46 #> [146,] -102 46 #> [147,] -103 45 #> [148,] -104 45 #> [149,] -105 45 #> [150,] -106 45 #> [151,] -107 44 #> [152,] -108 44 #> [153,] -109 44 #> [154,] -110 44 #> [155,] -111 44 #> [156,] -112 44 #> [157,] -113 43 #> [158,] -114 43 #> [159,] -115 43 #> [160,] -116 43 #> [161,] -117 43 #> [162,] -118 43 #> [163,] -119 43 #> [164,] -120 43 #> [165,] -121 43 #> [166,] -122 43 #> [167,] -123 43 #> [168,] -124 43 #> [169,] -125 43 #> [170,] -126 43 #> [171,] -127 43 #> [172,] -128 43 #> [173,] -129 43 #> [174,] -130 43 #> [175,] -131 43 #> [176,] -132 43 #> [177,] -133 43 #> [178,] -134 43 #> [179,] -135 43 #> [180,] -136 43 #> [181,] -137 43 #> [182,] -138 43 #> [183,] -139 43 #> [184,] -140 43 #> [185,] -141 43 #> [186,] -142 43 #> [187,] -143 43 #> [188,] -144 43 #> [189,] -145 43 #> [190,] -146 44 #> [191,] -146 45 #> [192,] -146 46 #> [193,] -146 47 #> [194,] -146 48 #> [195,] -146 49 #> [196,] -146 50 #> [197,] -146 51 #> [198,] -146 52 #> [199,] -146 53 #> [200,] -146 54 #> [201,] -146 55 #> [202,] -146 56 #> [203,] -146 57 #> [204,] -146 58 #> [205,] -146 59 #> [206,] -146 60 #> [207,] -146 61 #> [208,] -146 62 #> [209,] -146 63 #> [210,] -146 64 #> [211,] -146 65 #> [212,] -146 66 #> [213,] -146 67 #> [214,] -146 68 #> [215,] -146 69 #> [216,] -146 70 #> [217,] -146 71 #> [218,] -146 72 #> [219,] -146 73 #> [220,] -146 74 #> [221,] -146 75 #> [222,] -146 76 #> [223,] -146 77 #> [224,] -146 78 #> [225,] -146 79 #> [226,] -146 80 #> [227,] -146 81 #> [228,] -146 82 #> [229,] -146 83 #> [230,] -146 84 #> [231,] -146 85 #> [232,] -146 86 #> [233,] -145 87 #> [234,] -144 87 #> [235,] -143 87 #> [236,] -142 87 #> [237,] -141 87 #> [238,] -140 87 #> [239,] -139 87 #> [240,] -138 87 #> [241,] -137 87 #> [242,] -136 87 #> [243,] -135 87 #> [244,] -134 87 #> [245,] -133 87 #> [246,] -132 87 #> [247,] -131 87 #> [248,] -130 87 #> [249,] -129 87 #> [250,] -128 87 #> [251,] -127 87 #> [252,] -126 87 #> [253,] -125 87 #> [254,] -124 87 #> [255,] -123 87 #> [256,] -122 87 #> [257,] -121 87 #> [258,] -120 87 #> [259,] -119 87 #> [260,] -118 88 #> [261,] -117 88 #> [262,] -116 89 #> [263,] -115 90 #> [264,] -114 91 #> [265,] -113 92 #> [266,] -112 93 #> [267,] -112 94 #> [268,] -111 95 #> [269,] -111 96 #> [270,] -110 97 #> [271,] -110 98 #> [272,] -109 99 #> [273,] -108 100 #> [274,] -108 101 #> [275,] -107 102 #> [276,] -107 103 #> [277,] -106 104 #> [278,] -105 105 #> [279,] -105 106 #> [280,] -104 107 #> [281,] -103 108 #> [282,] -102 109 #> [283,] -102 110 #> [284,] -101 111 #> [285,] -100 112 #> [286,] -99 113 #> [287,] -98 114 #> [288,] -97 115 #> [289,] -96 115 #> [290,] -95 116 #> [291,] -94 117 #> [292,] -93 117 #> [293,] -92 118 #> [294,] -91 118 #> [295,] -90 119 #> [296,] -89 119 #> [297,] -88 120 #> [298,] -87 120 #> [299,] -86 121 #> [300,] -85 121 #> [301,] -84 122 #> [302,] -83 122 #> [303,] -82 122 #> [304,] -81 122 #> [305,] -80 123 #> [306,] -79 123 #> [307,] -78 123 #> [308,] -77 123 #> [309,] -76 123 #> [310,] -75 124 #> [311,] -74 124 #> [312,] -73 124 #> [313,] -72 124 #> [314,] -71 124 #> [315,] -70 124 #> [316,] -69 124 #> [317,] -68 124 #> [318,] -67 124 #> [319,] -66 124 #> [320,] -65 124 #> [321,] -64 124 #> [322,] -63 124 #> [323,] -62 124 #> [324,] -61 124 #> [325,] -60 124 #> [326,] -59 124 #> [327,] -58 124 #> [328,] -57 124 #> [329,] -56 124 #> [330,] -55 124 #> [331,] -54 124 #> [332,] -53 124 #> [333,] -52 124 #> [334,] -51 124 #> [335,] -50 123 #> [336,] -49 123 #> [337,] -48 123 #> [338,] -47 123 #> [339,] -46 122 #> [340,] -45 122 #> [341,] -44 122 #> [342,] -43 122 #> [343,] -42 121 #> [344,] -41 121 #> [345,] -40 120 #> [346,] -39 120 #> [347,] -38 119 #> [348,] -37 119 #> [349,] -36 118 #> [350,] -35 118 #> [351,] -34 117 #> [352,] -33 117 #> [353,] -32 116 #> [354,] -31 115 #> [355,] -30 114 #> [356,] -29 113 #> [357,] -28 113 #> [358,] -27 112 #> [359,] -26 111 #> [360,] -26 110 #> [361,] -25 109 #> [362,] -24 108 #> [363,] -23 107 #> [364,] -22 106 #> [365,] -22 105 #> [366,] -21 104 #> [367,] -20 103 #> [368,] -20 102 #> [369,] -19 101 #> [370,] -18 100 #> [371,] -18 99 #> [372,] -17 98 #> [373,] -17 97 #> [374,] -17 96 #> [375,] -16 95 #> [376,] -16 94 #> [377,] -15 93 #> [378,] -15 92 #> [379,] -15 91 #> [380,] -14 90 #> [381,] -14 89 #> [382,] -14 88 #> [383,] -13 87 #> [384,] -13 86 #> [385,] -13 85 #> [386,] -12 84 #> [387,] -12 83 #> [388,] -12 82 #> [389,] -12 81 #> [390,] -11 80 #> [391,] -11 79 #> [392,] -11 78 #> [393,] -10 77 #> [394,] -10 76 #> [395,] -10 75 #> [396,] -10 74 #> [397,] -9 73 #> [398,] -9 72 #> [399,] -9 71 #> [400,] -9 70 #> [401,] -8 69 #> [402,] -8 68 #> [403,] -8 67 #> [404,] -8 66 #> [405,] -7 65 #> [406,] -7 64 #> [407,] -7 63 #> [408,] -7 62 #> [409,] -6 61 #> [410,] -6 60 #> [411,] -6 59 #> [412,] -5 58 #> [413,] -5 57 #> [414,] -4 56 #> [415,] -4 55 #> [416,] -3 54 #> [417,] -3 53 #> [418,] -2 52 #> [419,] -1 51 #> [420,] 0 50 #> [421,] 1 49 #> [422,] 2 48 #> [423,] 3 48 #> [424,] 4 48 #> [425,] 5 47 #> [426,] 6 47 #> [427,] 7 47 #> [428,] 8 48 #> [429,] 9 48 #> [430,] 10 48 #> [431,] 11 49 #> [432,] 12 49 #> [433,] 13 50 #> [434,] 14 51 #> [435,] 15 52 #> [436,] 15 53 #> [437,] 16 54 #> [438,] 16 55 #> [439,] 17 56 #> [440,] 17 57 #> [441,] 18 58 #> [442,] 18 59 #> [443,] 19 60 #> [444,] 19 61 #> [445,] 19 62 #> [446,] 20 63 #> [447,] 20 64 #> [448,] 20 65 #> [449,] 21 66 #> [450,] 21 67 #> [451,] 21 68 #> [452,] 22 69 #> [453,] 22 70 #> [454,] 22 71 #> [455,] 23 72 #> [456,] 23 73 #> [457,] 24 74 #> [458,] 24 75 #> [459,] 24 76 #> [460,] 25 77 #> [461,] 25 78 #> [462,] 26 79 #> [463,] 26 80 #> [464,] 27 81 #> [465,] 27 82 #> [466,] 28 83 #> [467,] 28 84 #> [468,] 29 85 #> [469,] 30 86 #> [470,] 31 87 #> [471,] 31 88 #> [472,] 32 89 #> [473,] 33 90 #> [474,] 34 91 #> [475,] 35 92 #> [476,] 36 93 #> [477,] 37 94 #> [478,] 38 94 #> [479,] 39 95 #> [480,] 40 96 #> [481,] 41 96 #> [482,] 42 97 #> [483,] 43 97 #> [484,] 44 98 #> [485,] 45 98 #> [486,] 46 99 #> [487,] 47 99 #> [488,] 48 99 #> [489,] 49 100 #> [490,] 50 100 #> [491,] 51 100 #> [492,] 52 100 #> [493,] 53 101 #> [494,] 54 101 #> [495,] 55 101 #> [496,] 56 101 #> [497,] 57 101 #> [498,] 58 101 #> [499,] 59 101 #> [500,] 60 101 #> [501,] 61 101 #> [502,] 62 101 #> [503,] 63 101 #> [504,] 64 101 #> [505,] 65 101 #> [506,] 66 101 #> [507,] 67 101 #> [508,] 68 101 #> [509,] 69 101 #> [510,] 70 101 #> [511,] 71 101 #> [512,] 72 101 #> [513,] 73 101 #> [514,] 74 101 #> [515,] 75 101 #> [516,] 76 101 #> [517,] 77 101 #> [518,] 78 101 #> [519,] 79 101 #> [520,] 80 101 #> [521,] 81 102 #> [522,] 82 101 #> [523,] 83 102 #> [524,] 82 103 #> [525,] 82 104 #> [526,] 82 105 #> [527,] 82 106 #> [528,] 81 107 #> [529,] 81 108 #> [530,] 81 109 #> [531,] 81 110 #> [532,] 80 111 #> [533,] 80 112 #> [534,] 80 113 #> [535,] 80 114 #> [536,] 79 115 #> [537,] 79 116 #> [538,] 79 117 #> [539,] 78 118 #> [540,] 78 119 #> [541,] 78 120 #> [542,] 78 121 #> [543,] 77 122 #> [544,] 77 123 #> [545,] 77 124 #> [546,] 77 125 #> [547,] 76 126 #> [548,] 76 127 #> [549,] 76 128 #> [550,] 76 129 #> [551,] 76 130 #> [552,] 75 131 #> [553,] 75 132 #> [554,] 75 133 #> [555,] 75 134 #> [556,] 75 135 #> [557,] 75 136 #> [558,] 76 137 #> [559,] 76 138 #> [560,] 77 139 #> [561,] 78 140 #> [562,] 79 140 #> [563,] 80 140 #> [564,] 81 140 #> [565,] 82 140 #> [566,] 83 141 #> [567,] 84 140 #> [568,] 85 140 #> [569,] 86 139 #> [570,] 87 139 #> [571,] 88 138 #> [572,] 89 138 #> [573,] 90 137 #> [574,] 91 136 #> [575,] 92 136 #> [576,] 93 135 #> [577,] 94 134 #> [578,] 95 134 #> [579,] 96 133 #> [580,] 97 132 #> [581,] 98 131 #> [582,] 99 131 #> [583,] 100 130 #> [584,] 101 129 #> [585,] 102 129 #> [586,] 103 128 #> [587,] 104 127 #> [588,] 105 126 #> [589,] 106 126 #> [590,] 107 125 #> [591,] 108 124 #> [592,] 109 124 #> [593,] 110 123 #> [594,] 111 122 #> [595,] 112 122 #> [596,] 113 121 #> [597,] 114 120 #> [598,] 115 119 #> [599,] 116 119 #> [600,] 117 118 #> [601,] 118 117 #> [602,] 119 117 #> [603,] 120 116 #> [604,] 121 115 #> [605,] 122 114 #> [606,] 123 114 #> [607,] 124 113 #> [608,] 125 112 #> [609,] 126 112 #> [610,] 127 111 #> [611,] 128 110 #> [612,] 129 110 #> [613,] 130 109 #> [614,] 131 108 #> [615,] 132 107 #> [616,] 133 107 #> [617,] 134 106 #> [618,] 135 105 #> [619,] 136 105 #> [620,] 137 104 #> [621,] 138 103 #> [622,] 139 102 #> [623,] 140 102 #> [624,] 141 101 #> [625,] 142 100 #> [626,] 143 100 #> [627,] 144 99 #> [628,] 145 98 #> [629,] 146 98 #> [630,] 147 97 #> [631,] 148 96 #> [632,] 149 95 #> [633,] 150 95 #> [634,] 151 94 #> [635,] 152 93 #> [636,] 153 93 #> [637,] 154 92 #> [638,] 155 91 #> [639,] 156 90 #> [640,] 157 90 #> [641,] 158 89 #> [642,] 159 88 #> [643,] 160 88 #> [644,] 161 87 #> [645,] 162 86 #> [646,] 163 86 #> [647,] 164 85 #> [648,] 165 84 #> [649,] 166 83 #> [650,] 167 83 #> [651,] 168 82 #> [652,] 169 81 #> [653,] 170 81 #> [654,] 171 80 #> [655,] 170 79 #> [656,] 169 78 #> [657,] 168 77 #> [658,] 167 77 #> [659,] 166 76 #> [660,] 165 75 #> [661,] 164 75 #> [662,] 163 74 #> [663,] 162 73 #> [664,] 161 72 #> [665,] 160 72 #> [666,] 159 71 #> [667,] 158 70 #> [668,] 157 70 #> [669,] 156 69 #> [670,] 155 68 #> [671,] 154 67 #> [672,] 153 67 #> [673,] 152 66 #> [674,] 151 65 #> [675,] 150 65 #> [676,] 149 64 #> [677,] 148 63 #> [678,] 147 63 #> [679,] 146 62 #> [680,] 145 61 #> [681,] 144 60 #> [682,] 143 60 #> [683,] 142 59 #> [684,] 141 58 #> [685,] 140 58 #> [686,] 139 57 #> [687,] 138 56 #> [688,] 137 55 #> [689,] 136 55 #> [690,] 135 54 #> [691,] 134 53 #> [692,] 133 53 #> [693,] 132 52 #> [694,] 131 51 #> [695,] 130 51 #> [696,] 129 50 #> [697,] 128 49 #> [698,] 127 48 #> [699,] 126 48 #> [700,] 125 47 #> [701,] 124 46 #> [702,] 123 46 #> [703,] 122 45 #> [704,] 121 44 #> [705,] 120 44 #> [706,] 119 43 #> [707,] 118 42 #> [708,] 117 41 #> [709,] 116 41 #> [710,] 115 40 #> [711,] 114 39 #> [712,] 113 38 #> [713,] 112 38 #> [714,] 111 37 #> [715,] 110 36 #> [716,] 109 36 #> [717,] 108 35 #> [718,] 107 34 #> [719,] 106 34 #> [720,] 105 33 #> [721,] 104 32 #> [722,] 103 31 #> [723,] 102 31 #> [724,] 101 30 #> [725,] 100 29 #> [726,] 99 29 #> [727,] 98 28 #> [728,] 97 27 #> [729,] 96 27 #> [730,] 95 26 #> [731,] 94 25 #> [732,] 93 24 #> [733,] 92 24 #> [734,] 91 23 #> [735,] 90 22 #> [736,] 89 22 #> [737,] 88 21 #> [738,] 87 20 #> [739,] 86 20 #> [740,] 85 19 #> [741,] 84 19 #> [742,] 83 19 #> [743,] 82 19 #> [744,] 81 18 #> [745,] 80 19 #> [746,] 79 19 #> [747,] 78 20 #> [748,] 77 21 #> [749,] 76 22 #> [750,] 75 23 #> [751,] 75 24 #> [752,] 75 25 #> [753,] 75 26 #> [754,] 75 27 #> [755,] 75 28 #> [756,] 75 29 #> [757,] 75 30 #> [758,] 76 31 #> [759,] 76 32 #> [760,] 76 33 #> [761,] 77 34 #> [762,] 77 35 #> [763,] 77 36 #> [764,] 77 37 #> [765,] 78 38 #> [766,] 78 39 #> [767,] 78 40 #> [768,] 78 41 #> [769,] 79 42 #> [770,] 79 43 #> [771,] 79 44 #> [772,] 79 45 #> [773,] 80 46 #> [774,] 80 47 #> [775,] 80 48 #> [776,] 80 49 #> [777,] 81 50 #> [778,] 81 51 #> [779,] 81 52 #> [780,] 81 53 #> [781,] 82 54 #> [782,] 82 55 #> [783,] 82 56 #> [784,] 83 57 #> [785,] 82 58 #> [786,] 81 58 #> [787,] 80 58 #> [788,] 79 59 #> [789,] 78 59 #> [790,] 77 59 #> [791,] 76 59 #> [792,] 75 59 #> [793,] 74 59 #> [794,] 73 59 #> [795,] 72 59 #> [796,] 71 59 #> [797,] 70 58 #> [798,] 69 58 #> [799,] 68 58 #> [800,] 67 58 #> [801,] 66 57 #> [802,] 65 57 #> [803,] 64 56 #> [804,] 63 55 #> [805,] 63 54 #> [806,] 63 53 #> [807,] 62 52 #> [808,] 62 51 #> [809,] 62 50 #> [810,] 61 49 #> [811,] 61 48 #> [812,] 60 47 #> [813,] 60 46 #> [814,] 60 45 #> [815,] 59 44 #> [816,] 59 43 #> [817,] 58 42 #> [818,] 58 41 #> [819,] 58 40 #> [820,] 57 39 #> [821,] 57 38 #> [822,] 56 37 #> [823,] 56 36 #> [824,] 56 35 #> [825,] 55 34 #> [826,] 55 33 #> [827,] 54 32 #> [828,] 54 31 #> [829,] 53 30 #> [830,] 53 29 #> [831,] 52 28 #> [832,] 52 27 #> [833,] 51 26 #> [834,] 50 25 #> [835,] 50 24 #> [836,] 49 23 #> [837,] 49 22 #> [838,] 48 21 #> [839,] 47 20 #> [840,] 46 19 #> [841,] 46 18 #> [842,] 45 17 #> [843,] 44 16 #> [844,] 43 15 #> [845,] 42 14 #> [846,] 41 13 #> [847,] 40 12 #> [848,] 39 11 #> [849,] 38 10 #> [850,] 37 9 #> [851,] 36 8 #> [852,] 35 8 #> [853,] 34 7 #> [854,] 33 7 #> [855,] 32 6 #> [856,] 31 5 #> [857,] 30 5 #> [858,] 29 4 #> [859,] 28 4 #> [860,] 27 3 #> [861,] 26 3 #> [862,] 25 3 #> [863,] 24 2 #> [864,] 23 2 #> [865,] 22 2 #> [866,] 21 2 #> [867,] 20 1 #> [868,] 19 1 #> [869,] 18 1 #> [870,] 17 1 #> [871,] 16 1 #> [872,] 15 0 #> [873,] 14 0 #> [874,] 13 0 #> [875,] 12 0 #> [876,] 11 0 #> [877,] 10 0 #> [878,] 9 0 #> [879,] 8 0 #> [880,] 7 0 #> [881,] 6 0 #> [882,] 5 0 #> [883,] 4 0 #> [884,] 3 0 #> [885,] 2 0 #> [886,] 1 0 #> [887,] 0 0"},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates Bezier coefficients from a shape — bezier","title":"Calculates Bezier coefficients from a shape — bezier","text":"Calculates Bezier coefficients shape","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates Bezier coefficients from a shape — bezier","text":"","code":"bezier(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates Bezier coefficients from a shape — bezier","text":"coo matrix list (x; y) coordinates n degree, default number coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates Bezier coefficients from a shape — bezier","text":"list components: $J matrix Bezier coefficients $B matrix Bezier vertices.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates Bezier coefficients from a shape — bezier","text":"Directly borrowed Claude (2008), also called bezier . implemented open outlines may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates Bezier coefficients from a shape — bezier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bezier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates Bezier coefficients from a shape — bezier","text":"","code":"set.seed(34) x <- coo_sample(efourier_shape(), 5) plot(x, ylim=c(-3, 3), asp=1, type='b', pch=20) b <- bezier(x) bi <- bezier_i(b$B) lines(bi, col='red')"},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates a shape from Bezier coefficients — bezier_i","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Calculates shape Bezier coefficients","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"","code":"bezier_i(B, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"B matrix Bezier vertices, produced bezier nb.pts number points sample along curve.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"matrix (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Directly borrowed Claude (2008), called beziercurve . implemented open outlines may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bezier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates a shape from Bezier coefficients — bezier_i","text":"","code":"set.seed(34) x <- coo_sample(efourier_shape(), 5) plot(x, ylim=c(-3, 3), asp=1, type='b', pch=20) b <- bezier(x) bi <- bezier_i(b$B) lines(bi, col='red')"},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":null,"dir":"Reference","previous_headings":"","what":"Boxplot of morphometric coefficients — boxplot.OutCoe","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"Explores distribution coefficient values.","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"","code":"# S3 method for OutCoe boxplot(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"x Coe object ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"ggplot2 object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/boxplot.OutCoe.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boxplot of morphometric coefficients — boxplot.OutCoe","text":"","code":"# on OutCoe bot %>% efourier(9) %>% rm_harm(1) %>% boxplot() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details data(olea) op <- opoly(olea) #> 'nb.pts' missing and set to 91 #> 'degree' missing and set to 5 boxplot(op)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Boxplot on PCA objects — boxplot.PCA","title":"Boxplot on PCA objects — boxplot.PCA","text":"Boxplot PCA objects","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Boxplot on PCA objects — boxplot.PCA","text":"","code":"# S3 method for PCA boxplot(x, fac = NULL, nax, ...)"},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Boxplot on PCA objects — boxplot.PCA","text":"x PCA, typically obtained PCA fac factor, name column id $fac slot nax range PC plot (1 99pc total variance default) ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Boxplot on PCA objects — boxplot.PCA","text":"ggplot object","code":""},{"path":"http://momx.github.io/Momocs/reference/boxplot.PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boxplot on PCA objects — boxplot.PCA","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) boxplot(bot.p) #> `prop` not provided. All axes returned p <- boxplot(bot.p, 1) #> `prop` not provided. All axes returned #p + theme_minimal() + scale_fill_grey() #p + facet_wrap(~PC, scales = \"free\")"},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":null,"dir":"Reference","previous_headings":"","what":"Jitters Coe (and others) objects — breed","title":"Jitters Coe (and others) objects — breed","text":"methods applies column-wise coe Coe object relies function can used matrix. simply uses rnorm mean sd calculated every column (row). Coe object, every colum, randomly generates coefficients values centered mean column, sd equals standard deviates multiplied rate.","code":""},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Jitters Coe (and others) objects — breed","text":"","code":"breed(x, ...) # S3 method for default breed(x, fac, margin = 2, size, rate = 1, ...) # S3 method for Coe breed(x, fac, size, rate = 1, ...)"},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Jitters Coe (and others) objects — breed","text":"x object permute ... useless fac column, formula column id $fac margin numeric whether 1 2 (rows columns) size numeric required size final object, size default rate numeric number sd rnorm, 1 default.","code":""},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Jitters Coe (and others) objects — breed","text":"Coe object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/breed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Jitters Coe (and others) objects — breed","text":"","code":"m <- matrix(1:12, nrow=3) breed(m, margin=2, size=4) #> [,1] [,2] [,3] [,4] #> [1,] 2.670620 4.597120 8.401255 9.157338 #> [2,] 1.150985 5.719108 9.356390 10.720259 #> [3,] 3.066805 4.819941 8.019227 9.469230 #> [4,] 1.992539 6.046191 7.530582 13.546154 breed(m, margin=1, size=10) #> [,1] [,2] [,3] #> [1,] 1.30970018 1.769321 -1.5597512 #> [2,] -0.01744358 6.486750 0.5512378 #> [3,] 7.13301779 9.320377 7.0219317 #> [4,] 8.52622563 4.558342 10.8915399 #> [5,] 2.01645375 7.194958 8.0983293 #> [6,] 3.54852287 6.733022 14.7962926 #> [7,] 4.57290872 6.963033 4.4282392 #> [8,] 10.02364430 6.407625 10.4446975 #> [9,] 2.40882230 3.826442 11.5882377 #> [10,] 10.19002487 4.197451 3.2041191 bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.m <- breed(bot.f, size=80) bot.m %>% PCA %>% plot #> will be deprecated soon, see ?plot_PCA # breed fac wise # bot.f %>% breed(~type, size=50) %>% PCA %>% plot(~type)"},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert between different classes — bridges","title":"Convert between different classes — bridges","text":"Convert different classes","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert between different classes — bridges","text":"","code":"l2m(l) m2l(m) d2m(d) m2d(m) l2a(l) a2l(a) a2m(a) m2a(m) m2ll(m, index = NULL)"},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert between different classes — bridges","text":"l list x y coordinates components m matrix (x; y) coordinates d data.frame two columns array (x; y) coordinates index numeric, number coordinates every slice","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert between different classes — bridges","text":"data required class","code":""},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Convert between different classes — bridges","text":"a2m/m2a change, essence, dimension data. m2ll used internally hanle coo cur Ldk objects may useful elsewhere","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/bridges.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert between different classes — bridges","text":"","code":"# matrix/list wings[1] %>% coo_sample(4) %>% m2l() %T>% print %>% # matrix to list l2m() # and back #> $x #> [1] -0.4933 0.2645 0.0424 -0.1768 #> #> $y #> [1] 0.0130 0.0261 -0.0966 0.0341 #> #> x y #> [1,] -0.4933 0.0130 #> [2,] 0.2645 0.0261 #> [3,] 0.0424 -0.0966 #> [4,] -0.1768 0.0341 # data.frame/matrix wings[1] %>% coo_sample(4) %>% m2d() %T>% print %>% # matrix to data.frame d2m # and back #> # A tibble: 4 × 2 #> x y #> #> 1 -0.493 0.013 #> 2 0.264 0.0261 #> 3 0.0424 -0.0966 #> 4 -0.177 0.0341 #> x y #> [1,] -0.4933 0.0130 #> [2,] 0.2645 0.0261 #> [3,] 0.0424 -0.0966 #> [4,] -0.1768 0.0341 # list/array wings %>% slice(1:2) %$% coo %>% l2a %T>% print %>% # list to array a2l # and back #> , , AN1 #> #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> , , AN2 #> #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> #> [[1]] #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> [[2]] #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> # array/matrix wings %>% slice(1:2) %$% l2a(coo) %>% # and array (from a list) a2m %T>% print %>% # to matrix m2a # and back #> x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 #> AN1 -0.4933 -0.0777 0.2231 0.2641 0.2645 0.2471 0.2311 0.2040 0.1282 0.0424 #> AN2 -0.4814 -0.0058 0.2345 0.2460 0.2487 0.2430 0.2316 0.1956 0.1462 0.0483 #> x11 x12 x13 x14 x15 x16 x17 x18 y1 y2 #> AN1 -0.0674 -0.4102 -0.3140 -0.1768 0.0715 -0.0540 0.0575 -0.1401 0.0130 0.0832 #> AN2 -0.0520 -0.4016 -0.3868 -0.1808 0.0484 -0.0519 0.0623 -0.1444 0.0135 0.0780 #> y3 y4 y5 y6 y7 y8 y9 y10 y11 y12 #> AN1 0.0861 0.0462 0.0261 0.0003 -0.0228 -0.0452 -0.0742 -0.0966 -0.1108 -0.0163 #> AN2 0.0644 0.0467 0.0281 0.0115 -0.0039 -0.0305 -0.0545 -0.0866 -0.1047 -0.0250 #> y13 y14 y15 y16 y17 y18 #> AN1 0.0318 0.0341 0.0509 0.0238 -0.0059 -0.0240 #> AN2 0.0166 0.0229 0.0405 0.0164 -0.0047 -0.0286 #> , , AN1 #> #> x y #> 1 -0.4933 0.0130 #> 2 -0.0777 0.0832 #> 3 0.2231 0.0861 #> 4 0.2641 0.0462 #> 5 0.2645 0.0261 #> 6 0.2471 0.0003 #> 7 0.2311 -0.0228 #> 8 0.2040 -0.0452 #> 9 0.1282 -0.0742 #> 10 0.0424 -0.0966 #> 11 -0.0674 -0.1108 #> 12 -0.4102 -0.0163 #> 13 -0.3140 0.0318 #> 14 -0.1768 0.0341 #> 15 0.0715 0.0509 #> 16 -0.0540 0.0238 #> 17 0.0575 -0.0059 #> 18 -0.1401 -0.0240 #> #> , , AN2 #> #> x y #> 1 -0.4814 0.0135 #> 2 -0.0058 0.0780 #> 3 0.2345 0.0644 #> 4 0.2460 0.0467 #> 5 0.2487 0.0281 #> 6 0.2430 0.0115 #> 7 0.2316 -0.0039 #> 8 0.1956 -0.0305 #> 9 0.1462 -0.0545 #> 10 0.0483 -0.0866 #> 11 -0.0520 -0.1047 #> 12 -0.4016 -0.0250 #> 13 -0.3868 0.0166 #> 14 -0.1808 0.0229 #> 15 0.0484 0.0405 #> 16 -0.0519 0.0164 #> 17 0.0623 -0.0047 #> 18 -0.1444 -0.0286 #> # m2ll m2ll(wings[1], c(6, 4, 3, 5)) # grab slices and coordinates #> [[1]] #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> #> [[2]] #> [,1] [,2] #> [1,] 0.2311 -0.0228 #> [2,] 0.2040 -0.0452 #> [3,] 0.1282 -0.0742 #> [4,] 0.0424 -0.0966 #> #> [[3]] #> [,1] [,2] #> [1,] -0.0674 -0.1108 #> [2,] -0.4102 -0.0163 #> [3,] -0.3140 0.0318 #> #> [[4]] #> [,1] [,2] #> [1,] -0.1768 0.0341 #> [2,] 0.0715 0.0509 #> [3,] -0.0540 0.0238 #> [4,] 0.0575 -0.0059 #> [5,] -0.1401 -0.0240 #>"},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"Calculate deviations original reconstructed shapes using range harmonic number.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"","code":"calibrate_deviations() calibrate_deviations_efourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_tfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_rfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_sfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_npoly( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_opoly( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE ) calibrate_deviations_dfourier( x, id = 1, range, norm.centsize = TRUE, dist.method = edm_nearest, interpolate.factor = 1, dist.nbpts = 120, plot = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"x Opn object calibrate_deviations id shape perform calibrate_deviations range vector harmonics (degree opoly npoly Opn) perform calibrate_deviations. provided, harmonics corresponding 0.9, 0.95 0.99% harmonic power used. norm.centsize logical whether normalize deviation centroid size dist.method method edm_nearest calculate deviations interpolate.factor numeric increase number points original shape (1 default) dist.nbpts numeric number points use deviations calculations plot logical whether print graph (FALSE just want calculations)","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"ggplot object full list intermediate results. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"Note version 1.1, calculation changed fixed problem. , 'best' possible shape calculated using highest possible number harmonics. worked well efourier others (eg rfourier, tfourier) known unstable high number harmonics. now , Momocs uses 'real' shape, (must centered) uses coo_interpolate produce interpolate.factor times coordinates shape using default dist.method, eg edm_nearest, latter finds euclidean distance, point reconstructed shape, closest point interpolated shape. interpolate.factor set 1 default, interpolation made ask . Note, interpolation decrease artefactual errors may also done outside calibrate_deviations probably removed versions. Note also code quite old now need good review, planned 2018. *poly methods Opn objects, deviations calculated degree 12 polynom.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_deviations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative calibration, through deviations, for Out and Opn objects — calibrate_deviations","text":"","code":"b5 <- slice(bot, 1:5) #for the sake of speed b5 %>% calibrate_deviations_efourier() b5 %>% calibrate_deviations_rfourier() #> 'range' was too high and set to 4 15 27 39 51 63 b5 %>% calibrate_deviations_tfourier() #> 'range' was too high and set to 4 15 27 39 51 63 b5 %>% calibrate_deviations_sfourier() o5 <- slice(olea, 1:5) #for the sake of speed o5 %>% calibrate_deviations_opoly() #> 'range' was missing and set to 1:8 #> deviations calculated from a degree 12 polynom o5 %>% calibrate_deviations_npoly() #> 'range' was missing and set to 1:8 #> deviations calculated from a degree 12 polynom o5 %>% calibrate_deviations_dfourier() #> 'range' was missing and set to 1:8"},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"Estimates number harmonics required four Fourier methods implemented Momocs: elliptical Fourier analysis (see efourier), radii variation analysis (see rfourier) tangent angle analysis (see tfourier) discrete Fourier transform (see dfourier). returns can plot cumulated harmonic power whether dropping first harmonic , based maximum possible number harmonics Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"","code":"calibrate_harmonicpower() calibrate_harmonicpower_efourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_rfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_tfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_sfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE ) calibrate_harmonicpower_dfourier( x, id = 1:length(x), nb.h, drop = 1, thresh = c(90, 95, 99, 99.9), plot = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"x Coo Opn object id shapes perform calibrate_harmonicpower. default nb.h numeric maximum number harmonic, base cumsum drop numeric number harmonics drop cumulative sum thresh vector numeric drawing horizontal lines, also used minh plot logical whether plot result simply return matrix Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"returns list component: gg ggplot object, q quantile matrix minh quick summary returns number harmonics required achieve certain proportion total harmonic power.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"power given harmonic \\(n\\) calculated follows elliptical Fourier analysis n-th harmonic: \\(HarmonicPower_n \\frac{^2_n+B^2_n+C^2_n+D^2_n}{2}\\) follows radii variation tangent angle: \\(HarmonicPower_n= \\frac{^2_n+B^2_n+C^2_n+D^2_n}{2}\\)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_harmonicpower.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative calibration, through harmonic power, for Out and Opn objects — calibrate_harmonicpower","text":"","code":"b5 <- bot %>% slice(1:5) b5 %>% calibrate_harmonicpower_efourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 12.04060 75.93567 84.25707 96.30510 97.54758 98.98871 99.14762 #> caney 25.32919 83.82352 85.52977 97.63251 97.95722 98.48376 98.74498 #> chimay 43.52623 81.74374 87.15624 95.19669 97.62725 98.26072 99.08266 #> corona 18.77387 85.07047 86.60786 97.10591 97.52603 98.19450 98.53979 #> deusventrue 50.01648 89.72983 91.60975 97.48378 98.24316 98.89288 99.54427 #> h8 h9 h10 h11 #> brahma 99.17820 99.56150 99.70128 100 #> caney 99.09524 99.82995 99.92629 100 #> chimay 99.13936 99.92633 99.95030 100 #> corona 99.35699 99.85405 99.92437 100 #> deusventrue 99.59558 99.85220 99.85638 100 #> #> $minh #> 90% 95% 99% 99.9% #> 5 5 8 11 #> b5 %>% calibrate_harmonicpower_rfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 18.78231 33.31995 46.22113 58.10127 67.82970 75.05028 80.97400 #> caney 17.93853 31.33704 42.78188 53.62717 63.27019 70.92538 77.13956 #> chimay 20.15608 32.00851 42.30386 53.69956 63.83688 70.62474 75.70937 #> corona 18.06902 31.19196 42.46484 53.47544 63.40792 71.15173 77.21493 #> deusventrue 16.53275 28.35109 38.13251 47.97348 57.90690 66.78889 74.09914 #> h8 h9 h10 h11 #> brahma 86.70633 92.03264 96.35923 100 #> caney 83.17596 89.45355 95.26884 100 #> chimay 81.97629 89.53235 95.96736 100 #> corona 83.10189 89.40501 95.31295 100 #> deusventrue 80.55553 87.12697 93.87388 100 #> #> $minh #> 90% 95% 99% 99.9% #> 11 11 12 12 #> b5 %>% calibrate_harmonicpower_tfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 59.14067 61.93044 70.84946 73.04960 78.52305 82.00362 83.54236 #> caney 74.23211 77.03198 79.47862 80.42583 81.02169 83.35008 88.47033 #> chimay 51.55592 60.87755 75.55970 82.94807 85.87674 86.60314 87.96999 #> corona 78.37418 84.46833 88.93940 91.30081 91.99456 92.38160 96.07474 #> deusventrue 57.24983 77.47110 86.13551 88.20041 90.42190 93.82247 94.37464 #> h8 h9 h10 h11 #> brahma 88.78847 90.73935 95.65795 100 #> caney 92.95646 93.61725 99.86646 100 #> chimay 95.63758 95.97542 98.66043 100 #> corona 96.39414 97.01762 99.03821 100 #> deusventrue 97.00523 98.45247 99.28416 100 #> #> $minh #> 90% 95% 99% 99.9% #> 9 9 11 12 #> b5 %>% calibrate_harmonicpower_sfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 h7 #> brahma 99.38619 99.44134 99.59446 99.83182 99.92895 99.93156 99.94529 #> caney 99.16488 99.60429 99.82594 99.87251 99.91648 99.95231 99.95269 #> chimay 97.21123 99.21819 99.30029 99.82089 99.87238 99.93107 99.95593 #> corona 99.36094 99.61770 99.72283 99.76601 99.89668 99.95608 99.95715 #> deusventrue 97.32291 99.46403 99.50564 99.53357 99.60031 99.93841 99.94526 #> h8 h9 h10 h11 #> brahma 99.98484 99.98487 99.98688 100 #> caney 99.99360 99.99611 99.99624 100 #> chimay 99.99704 99.99727 99.99749 100 #> corona 99.98672 99.99443 99.99756 100 #> deusventrue 99.97166 99.97681 99.99946 100 #> #> $minh #> 90% 95% 99% 99.9% #> 2 2 2 7 #> # on Opn olea %>% slice(1:5) %>% calibrate_harmonicpower_dfourier(nb.h=12) #> $gg #> #> $q #> h1 h2 h3 h4 h5 h6 #> 0001-cAglan_O10VD 82.53723 88.47281 96.36372 96.81316 98.24342 98.36453 #> 0001-cAglan_O10VL 73.05735 86.54342 94.76133 95.98041 97.40877 97.59487 #> 0001-cAglan_O11VD 76.24284 87.88560 93.49305 94.48904 96.36358 96.62580 #> 0001-cAglan_O11VL 84.21060 91.19903 96.81949 97.09514 98.06219 98.13718 #> 0001-cAglan_O12VD 83.66767 87.90200 95.83034 95.91726 97.55019 97.57227 #> h7 h8 h9 h10 h11 #> 0001-cAglan_O10VD 98.95059 98.99292 99.48780 99.50151 100 #> 0001-cAglan_O10VL 98.45031 98.49851 99.23945 99.26011 100 #> 0001-cAglan_O11VD 97.63205 97.76921 98.91878 99.00197 100 #> 0001-cAglan_O11VL 98.80533 98.83142 99.42881 99.43860 100 #> 0001-cAglan_O12VD 98.59264 98.60478 99.36939 99.37605 100 #> #> $minh #> 90% 95% 99% 99.9% #> 4 4 10 12 #> # \\donttest{ # let customize the ggplot library(ggplot2) cal <- b5 %>% calibrate_harmonicpower_efourier(nb.h=12) cal$gg + theme_minimal() + coord_cartesian(xlim=c(3.5, 12.5), ylim=c(90, 100)) + ggtitle(\"Harmonic power calibration\") #> Coordinate system already present. Adding new coordinate system, which will #> replace the existing one. # }"},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":null,"dir":"Reference","previous_headings":"","what":"Quantitative r2 calibration for Opn objects — calibrate_r2","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Estimates r2 calibrate degree npoly opoly methods. Also returns plot","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"","code":"calibrate_r2() calibrate_r2_opoly( Opn, id = 1:length(Opn), degree.range = 1:8, thresh = c(0.9, 0.95, 0.99, 0.999), plot = TRUE, ... ) calibrate_r2_npoly( Opn, id = 1:length(Opn), degree.range = 1:8, thresh = c(0.9, 0.95, 0.99, 0.999), plot = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Opn Opn object id ids shapes calculate r2 (default) degree.range calculate r2 thresh threshold return diagnostic plot logical whether print plot ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"ggpot2 object","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"May long, can estimate sample either id , one sample_n sample_frac","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_r2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Quantitative r2 calibration for Opn objects — calibrate_r2","text":"","code":"olea %>% slice(1:5) %>% #for the sake of spped calibrate_r2_opoly(degree.range=1:5, thresh=c(0.9, 0.99)) #> $gg #> #> $q #> degree1 degree2 degree3 degree4 degree5 #> 0001-cAglan_O10VD 0.0004287127 0.9821251 0.9831469 0.9986415 0.9987220 #> 0001-cAglan_O10VL 0.0011742448 0.9838978 0.9841793 0.9955520 0.9972836 #> 0001-cAglan_O11VD 0.0123113197 0.9706618 0.9906431 0.9965470 0.9965690 #> 0001-cAglan_O11VL 0.0151312838 0.9459654 0.9796698 0.9958102 0.9963290 #> 0001-cAglan_O12VD 0.0002310795 0.9673982 0.9674270 0.9912600 0.9938820 #> #> $mind #> 0.9 0.99 #> 2 4 #> olea %>% slice(1:5) %>% #for the sake of spped calibrate_r2_npoly(degree.range=1:5, thresh=c(0.9, 0.99)) #> $gg #> #> $q #> degree1 degree2 degree3 degree4 degree5 #> 0001-cAglan_O10VD 0.0004287127 0.9821251 0.9831469 0.9986415 0.9987220 #> 0001-cAglan_O10VL 0.0011742448 0.9838978 0.9841793 0.9955520 0.9972836 #> 0001-cAglan_O11VD 0.0123113197 0.9706618 0.9906431 0.9965470 0.9965690 #> 0001-cAglan_O11VL 0.0151312838 0.9459654 0.9796698 0.9958102 0.9963290 #> 0001-cAglan_O12VD 0.0002310795 0.9673982 0.9674270 0.9912600 0.9938820 #> #> $mind #> 0.9 0.99 #> 2 4 #>"},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calibrate using reconstructed shapes — calibrate_reconstructions","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"Calculate displays reconstructed shapes using range harmonic number. Compare visually maximal fit. explicitely demonstrates robust efourier compared tfourier rfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"","code":"calibrate_reconstructions_efourier(x, id, range = 1:9) calibrate_reconstructions_rfourier(x, id, range = 1:9) calibrate_reconstructions_tfourier(x, id, range = 1:9) calibrate_reconstructions_sfourier(x, id, range = 1:9) calibrate_reconstructions_npoly( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) ) calibrate_reconstructions_opoly( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) ) calibrate_reconstructions_dfourier( x, id, range = 2:10, baseline1 = c(-1, 0), baseline2 = c(1, 0) )"},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"x Coo object calibrate_reconstructions id shape perform calibrate_reconstructions range vector harmonics perform calibrate_reconstructions baseline1 \\((x; y)\\) coordinates first point baseline baseline2 \\((x; y)\\) coordinates second point baseline","code":""},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"ggplot object full list intermediate results. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/calibrate_reconstructions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calibrate using reconstructed shapes — calibrate_reconstructions","text":"","code":"### On Out shapes %>% calibrate_reconstructions_efourier(id=1, range=1:6) # you may prefer efourier... shapes %>% calibrate_reconstructions_tfourier(id=1, range=1:6) #' you may prefer efourier... shapes %>% calibrate_reconstructions_rfourier(id=1, range=1:6) #' you may prefer efourier... # todo #shapes %>% # calibrate_reconstructions_sfourier(id=5, range=1:6) ### On Opn olea %>% calibrate_reconstructions_opoly(id=1) olea %>% calibrate_reconstructions_npoly(id=1) olea %>% calibrate_reconstructions_dfourier(id=1)"},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":null,"dir":"Reference","previous_headings":"","what":"Split to several objects based on a factor — chop","title":"Split to several objects based on a factor — chop","text":"Rougher slicing accepts classifier ie column name $fac Momocs classes. Returns named (every level) list can lapply-ed combined. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split to several objects based on a factor — chop","text":"","code":"chop(.data, fac)"},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split to several objects based on a factor — chop","text":".data Coo Coe object fac column name $fac","code":""},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split to several objects based on a factor — chop","text":"named list Coo Coe objects","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/chop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split to several objects based on a factor — chop","text":"","code":"olea %>% filter(var == \"Aglan\") %>% # to have a balanced nb of 'view' chop(~view) %>% # split into a list of 2 npoly %>% # separately apply npoly # strict equivalent to lapply(npoly) combine %>% # recombine PCA %>% plot # an illustration of the 2 views #> 'nb.pts' missing and set to: 95 #> 'degree' missing and set to: 5 #> 'nb.pts' missing and set to: 91 #> 'degree' missing and set to: 5 #> will be deprecated soon, see ?plot_PCA # treated separately"},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate classification metrics on a confusion matrix — classification_metrics","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"cases, class correctness proportion correctly classified individuals enough, detailed metrics working classification.","code":""},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"","code":"classification_metrics(x)"},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"x table LDA object","code":""},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"list following components returned: accuracy fraction instances correctly classified macro_prf data.frame containing precision (fraction correct predictions certain class); recall, fraction instances class correctly predicted; f1 harmonic mean (weighted average) precision recall. macro_avg, just average three macro_prf indices ova list one-vs-confusion matrices class ova_sum single ova matrices kappa measure agreement predictions actual labels","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/classification_metrics.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate classification metrics on a confusion matrix — classification_metrics","text":"","code":"# some morphometrics on 'hearts' hearts %>% fgProcrustes(tol=1) %>% coo_slide(ldk=1) %>% efourier(norm=FALSE) %>% PCA() %>% # now the LDA and its summary LDA(~aut) %>% classification_metrics() #> iteration: 1 \tgain: 30322 #> iteration: 2 \tgain: 1.2498 #> iteration: 3 \tgain: 0.34194 #> 'nb.h' set to 7 (99% harmonic power) #> 11 PC retained #> $accuracy #> [1] 0.7666667 #> #> $macro_prf #> # A tibble: 8 × 3 #> precision recall f1 #> #> 1 0.839 0.867 0.852 #> 2 0.75 0.8 0.774 #> 3 0.542 0.433 0.481 #> 4 0.893 0.833 0.862 #> 5 0.893 0.833 0.862 #> 6 0.812 0.867 0.839 #> 7 0.871 0.9 0.885 #> 8 0.529 0.6 0.562 #> #> $macro_avg #> # A tibble: 1 × 3 #> avg_precision avg_recall avg_f1 #> #> 1 0.766 0.767 0.765 #> #> $ova #> $ova$ced #> classified #> actual ced others #> ced 26 4 #> others 5 205 #> #> $ova$jeya #> classified #> actual jeya others #> jeya 24 6 #> others 8 202 #> #> $ova$mat #> classified #> actual mat others #> mat 13 17 #> others 11 199 #> #> $ova$ponnu #> classified #> actual ponnu others #> ponnu 25 5 #> others 3 207 #> #> $ova$remi #> classified #> actual remi others #> remi 25 5 #> others 3 207 #> #> $ova$rom #> classified #> actual rom others #> rom 26 4 #> others 6 204 #> #> $ova$ruks #> classified #> actual ruks others #> ruks 27 3 #> others 4 206 #> #> $ova$vince #> classified #> actual vince others #> vince 18 12 #> others 16 194 #> #> #> $ova_sum #> classified #> actual relevant others #> relevant 184 56 #> others 56 1624 #> #> $kappa #> [1] 0.7333333 #>"},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":null,"dir":"Reference","previous_headings":"","what":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"Momocs uses colnamed matrices store (typically) Fourier coefficients Coe objects (typically OutCoe). arranged rank-wise: A1, A2, ..., , B1, ..., Bn, C1, ..., Cn, D1, ..., Dn. softwares may arrive A1, B1, C1, D1, ..., , Bn, Cn, Dn, functions helps go one format. short, function rearranges column order. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"","code":"coeff_rearrange(x, by = c(\"name\", \"rank\")[1])"},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"x matrix (colnames) character either \"name\" (A1, A2, ..) \"rank\" (A1, B1, ...)","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_rearrange.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rearrange a matrix of (typically Fourier) coefficients — coeff_rearrange","text":"","code":"m_name <- m_rank <- matrix(1:32, 2, 16) # this one is ordered by name colnames(m_name) <- paste0(rep(letters[1:4], each=4), 1:4) # this one is ordered by rank colnames(m_rank) <- paste0(letters[1:4], rep(1:4, each=4)) m_rank #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_rank %>% coeff_rearrange(by=\"name\") #> Warning: `arrange_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `arrange()` instead. #> ℹ See vignette('programming') for more help #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 9 17 25 3 11 19 27 5 13 21 29 7 15 23 31 #> [2,] 2 10 18 26 4 12 20 28 6 14 22 30 8 16 24 32 m_rank %>% coeff_rearrange(by=\"rank\") #no change #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name %>% coeff_rearrange(by=\"name\") # no change #> a1 a2 a3 a4 b1 b2 b3 b4 c1 c2 c3 c4 d1 d2 d3 d4 #> [1,] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 #> [2,] 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 m_name %>% coeff_rearrange(by=\"rank\") #> a1 b1 c1 d1 a2 b2 c2 d2 a3 b3 c3 d3 a4 b4 c4 d4 #> [1,] 1 9 17 25 3 11 19 27 5 13 21 29 7 15 23 31 #> [2,] 2 10 18 26 4 12 20 28 6 14 22 30 8 16 24 32"},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":null,"dir":"Reference","previous_headings":"","what":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"coeff_sel helps select given number harmonics returning indices arranged numeric vector. instance, harmonic coefficients arranged $coe slot Coe-objects way: \\(A_1, \\dots, A_n, B_1, \\dots, B_n, C_1, \\dots, C_n, D_1, \\dots, D-n\\) elliptical Fourier analysis (see efourier efourier) \\(C_n D_n\\) harmonic absent radii variation tangent angle approaches (see rfourier tfourier respectively). . function used internally might interest elwewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"","code":"coeff_sel(retain = 8, drop = 0, nb.h = 32, cph = 4)"},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"retain numeric. number harmonics retain. drop numeric. number harmonics drop nb.h numeric. maximum harmonic rank. cph numeric. Must set 2 rfourier tfourier used.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"coeff_sel returns indices can used select columns harmonic coefficient matrix. coeff_split returns named list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_sel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helps to select a given number of harmonics from a numerical vector. — coeff_sel","text":"","code":"bot.f <- efourier(bot, 32) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details coe <- bot.f$coe # the raw matrix coe #> A1 A2 A3 A4 A5 A6 #> brahma 1 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 1 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 1 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 1 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 1 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 1 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> franziskaner 1 0.007314669 0.09110003 0.01294912 0.023136784 0.010558958 #> grimbergen 1 0.009522713 0.08573641 0.01974880 0.012878126 0.008485338 #> guiness 1 0.009589570 0.08825041 0.02268926 0.017770767 0.010695823 #> hoegardeen 1 0.009598003 0.09186435 0.01393702 0.020136724 0.008952962 #> jupiler 1 0.008152360 0.09595083 0.01206957 0.023549986 0.007484692 #> kingfisher 1 0.007788546 0.09459391 0.01346605 0.024571428 0.009229773 #> latrappe 1 0.018476561 0.06035470 0.03974568 0.010493387 0.026379718 #> lindemanskriek 1 0.012406103 0.09289294 0.01773845 0.020632152 0.010949655 #> nicechouffe 1 0.015167563 0.09058037 0.02094971 0.020007417 0.014345165 #> pecheresse 1 0.008436476 0.09409400 0.01181167 0.022221176 0.007960411 #> sierranevada 1 0.015038107 0.08208708 0.02647382 0.013697543 0.013869924 #> tanglefoot 1 0.018782346 0.07275504 0.03848616 0.008439294 0.018172933 #> tauro 1 0.007333709 0.09536301 0.01149374 0.023043384 0.007093187 #> westmalle 1 0.009100416 0.09469091 0.01450202 0.023460557 0.009582984 #> amrut 1 0.004198631 0.09500128 0.02143863 0.026005715 0.011729658 #> ballantines 1 -0.000653116 0.05733309 0.03154946 0.017516836 0.034198742 #> bushmills 1 -0.004927807 0.08149528 0.01036776 0.023910616 0.017320375 #> chivas 1 0.021613712 0.08642271 0.04314511 0.008460823 0.014376414 #> dalmore 1 0.038669436 0.07265717 0.05680730 0.003277741 0.019363348 #> famousgrouse 1 0.003373189 0.08802317 0.02019928 0.025507211 0.016776448 #> glendronach 1 0.003257554 0.09526153 0.02074249 0.026167146 0.010932661 #> glenmorangie 1 0.008572527 0.09410920 0.02136020 0.024756735 0.011430941 #> highlandpark 1 -0.002122354 0.06989902 0.03612531 0.023554876 0.027350465 #> jackdaniels 1 0.008777794 0.08626120 0.02940216 0.019373419 0.015295504 #> jb 1 0.004384491 0.09517564 0.02460733 0.023505329 0.010741163 #> johnniewalker 1 0.002370576 0.08321025 0.01719991 0.022474617 0.017724976 #> magallan 1 -0.008648015 0.09924533 0.01455296 0.037258989 0.011586345 #> makersmark 1 0.016536161 0.10229688 0.03388156 0.008773613 0.010192259 #> oban 1 0.001652893 0.09909342 0.02127249 0.028337047 0.009671380 #> oldpotrero 1 0.022935601 0.09391465 0.03109455 0.009138035 0.012979620 #> redbreast 1 0.017769276 0.09281598 0.04425688 0.011246633 0.012792733 #> tamdhu 1 0.005270821 0.09375949 0.02020814 0.025073663 0.010943288 #> wildturkey 1 0.008605609 0.09229119 0.03228916 0.020978082 0.013010663 #> yoichi 1 -0.001738226 0.07733113 0.02843759 0.024035740 0.023420967 #> A7 A8 A9 A10 #> brahma 0.0031835706 0.005158502 -7.262824e-04 0.0047287291 #> caney 0.0035527091 0.007010166 1.214949e-03 0.0038734169 #> chimay -0.0047412879 0.007814037 -2.112661e-03 0.0022043011 #> corona 0.0055045888 0.007852411 8.767189e-04 0.0044201528 #> deusventrue 0.0025214510 0.011391904 -1.733965e-03 0.0062083192 #> duvel -0.0016871288 0.011025502 -1.042906e-04 0.0017042044 #> franziskaner 0.0045813399 0.006927102 -5.793922e-04 0.0045217266 #> grimbergen -0.0021957902 0.008213656 -1.577404e-03 0.0026346248 #> guiness -0.0015195731 0.008550727 2.093772e-04 0.0060163830 #> hoegardeen 0.0024034912 0.007507503 -1.234721e-03 0.0046892597 #> jupiler 0.0055270378 0.006597011 1.073131e-03 0.0041448892 #> kingfisher 0.0059527872 0.006778517 1.169809e-03 0.0044984721 #> latrappe -0.0057950372 0.005954999 -5.463098e-03 -0.0001140651 #> lindemanskriek 0.0033428880 0.008381096 -1.707332e-04 0.0050506285 #> nicechouffe 0.0026214920 0.010288304 -4.913646e-04 0.0065828560 #> pecheresse 0.0046954032 0.006669592 4.015144e-05 0.0042466561 #> sierranevada -0.0043828769 0.009275932 -1.465646e-03 0.0059555586 #> tanglefoot -0.0108560295 0.008370133 -2.988319e-03 0.0052185654 #> tauro 0.0052560957 0.006425077 9.461829e-04 0.0040141970 #> westmalle 0.0051463840 0.006848999 3.534839e-04 0.0042382642 #> amrut 0.0019176785 0.008515916 1.392307e-03 0.0089150426 #> ballantines 0.0045419501 0.014014932 -5.273138e-03 0.0006083616 #> bushmills 0.0095020099 0.012457087 -3.988679e-04 0.0048132802 #> chivas -0.0053775410 0.013797633 2.198119e-03 0.0031741809 #> dalmore -0.0072008170 0.012093037 5.368701e-03 0.0025492686 #> famousgrouse 0.0035195429 0.008617844 -1.621645e-03 0.0075384656 #> glendronach 0.0018504691 0.007851391 1.483976e-03 0.0086527932 #> glenmorangie 0.0023552959 0.007521806 1.103445e-03 0.0069834516 #> highlandpark -0.0024258364 0.003973480 -7.894105e-03 0.0013284975 #> jackdaniels -0.0047279969 0.008903250 -2.124758e-03 0.0090062900 #> jb -0.0015584637 0.008915452 4.097146e-04 0.0089915939 #> johnniewalker 0.0034197782 0.009945811 -3.913888e-03 0.0059350940 #> magallan 0.0095026108 0.003088506 1.575409e-03 0.0054824432 #> makersmark 0.0003303914 0.016520390 -1.901653e-03 0.0031138042 #> oban 0.0022492968 0.007479292 2.478319e-03 0.0090114539 #> oldpotrero 0.0015843674 0.012237947 -4.671411e-04 0.0023549220 #> redbreast -0.0046107656 0.015170859 3.884228e-03 0.0045806501 #> tamdhu 0.0013188307 0.006535142 1.700604e-04 0.0072170216 #> wildturkey -0.0038244377 0.010171775 1.641229e-03 0.0092477531 #> yoichi -0.0011328612 0.006117569 -8.008551e-03 0.0034639875 #> A11 A12 A13 A14 #> brahma -0.0013733386 0.0016363823 -2.308262e-03 -8.638239e-05 #> caney -0.0018777601 0.0011330555 -6.140388e-04 9.095865e-04 #> chimay -0.0012371979 -0.0018514226 4.671292e-04 -2.460672e-03 #> corona -0.0021742849 0.0026300698 -1.040704e-03 1.308265e-03 #> deusventrue -0.0007936789 0.0028680575 -3.667224e-05 4.628731e-04 #> duvel -0.0006045816 -0.0028942242 1.911167e-03 -1.075121e-03 #> franziskaner -0.0015947508 0.0021935018 -1.336804e-03 4.860914e-04 #> grimbergen -0.0035563564 -0.0004162333 -4.598763e-04 -6.524229e-04 #> guiness -0.0015222476 0.0005646464 -7.106716e-04 2.998013e-04 #> hoegardeen -0.0024579838 0.0023152691 -1.583256e-03 6.149144e-04 #> jupiler -0.0009974596 0.0023379940 -7.214137e-04 9.925517e-04 #> kingfisher -0.0004648420 0.0023788807 -4.654563e-04 7.413209e-04 #> latrappe 0.0015068375 -0.0015514855 2.342018e-03 -3.056608e-03 #> lindemanskriek -0.0009359325 0.0022848386 -6.636932e-04 3.522544e-04 #> nicechouffe -0.0007619565 0.0033654095 1.927898e-05 1.210854e-03 #> pecheresse -0.0013782823 0.0024185755 -1.351070e-03 7.509854e-04 #> sierranevada -0.0017933279 -0.0005349683 -1.031914e-03 -1.110401e-03 #> tanglefoot -0.0003179777 -0.0031166695 -6.330130e-04 -4.040699e-03 #> tauro -0.0010466330 0.0023514452 -6.553020e-04 1.065380e-03 #> westmalle -0.0004882420 0.0023217071 -3.503062e-04 3.148159e-04 #> amrut -0.0004155995 0.0028189180 -2.329164e-03 1.315932e-03 #> ballantines -0.0024674938 -0.0002274846 3.091761e-03 4.251026e-05 #> bushmills -0.0043970618 0.0017818484 -2.593370e-03 1.904341e-03 #> chivas -0.0016654883 -0.0026415175 2.038443e-03 -1.394657e-03 #> dalmore 0.0025922354 -0.0039822137 2.797073e-03 -1.626359e-03 #> famousgrouse 0.0001300206 0.0046515437 -1.163558e-03 2.084764e-04 #> glendronach -0.0002084792 0.0025405566 -2.450515e-03 8.307668e-04 #> glenmorangie -0.0001692272 0.0025838514 -1.298884e-03 1.028122e-03 #> highlandpark 0.0023214993 0.0028070218 3.398979e-03 -2.715598e-03 #> jackdaniels -0.0011544544 0.0013660407 -3.023216e-03 -1.495727e-03 #> jb -0.0026073348 0.0016289320 -3.506245e-03 1.398710e-03 #> johnniewalker -0.0026799451 0.0046998857 -7.408889e-04 1.724087e-03 #> magallan 0.0034410693 0.0056372281 7.595009e-04 1.320484e-03 #> makersmark -0.0037381840 0.0031052372 4.824121e-04 -7.739096e-04 #> oban -0.0000555700 0.0026159662 -2.336986e-03 1.677681e-03 #> oldpotrero 0.0002650070 0.0005717670 1.200764e-03 -1.479504e-03 #> redbreast -0.0017153754 -0.0017080604 2.956339e-03 -2.516789e-04 #> tamdhu -0.0004660552 0.0022520466 -2.360201e-03 1.825931e-04 #> wildturkey -0.0011040540 0.0003877287 -1.425560e-03 7.482844e-04 #> yoichi -0.0005670111 0.0040850862 1.536049e-03 -1.112175e-03 #> A15 A16 A17 A18 #> brahma -1.150816e-03 -3.765755e-04 -8.576746e-04 -0.0011152905 #> caney -4.470877e-04 -9.307845e-04 -6.102760e-04 -0.0008460017 #> chimay 1.560010e-05 -2.625393e-03 -6.111634e-04 -0.0014908027 #> corona -1.317478e-03 -5.180094e-04 -7.007916e-04 -0.0006290111 #> deusventrue 9.538496e-04 -6.759098e-04 7.618085e-04 -0.0011834834 #> duvel 2.113421e-03 -1.342867e-03 -5.580321e-04 -0.0007953381 #> franziskaner -8.169832e-04 -7.064707e-04 -4.330142e-04 -0.0013097566 #> grimbergen -4.937948e-04 -2.362703e-03 -7.577334e-04 -0.0016389273 #> guiness 9.445264e-04 -1.014837e-03 -3.870126e-04 -0.0018246820 #> hoegardeen -9.359774e-04 -6.806132e-04 -3.723940e-04 -0.0012041744 #> jupiler -6.500301e-04 -8.059191e-05 -3.572447e-04 -0.0005173527 #> kingfisher -4.322282e-04 -3.220011e-04 -1.490105e-04 -0.0007168806 #> latrappe -3.929165e-05 -2.305825e-03 -1.500329e-03 -0.0005806765 #> lindemanskriek -7.095128e-05 -5.265070e-04 9.090133e-05 -0.0011401438 #> nicechouffe 4.131153e-04 -1.060484e-05 4.958279e-04 -0.0004262323 #> pecheresse -1.039373e-03 -2.814305e-04 -7.590926e-04 -0.0008703985 #> sierranevada 1.197254e-03 -1.569161e-03 4.580294e-05 -0.0020229627 #> tanglefoot 1.578694e-03 -2.481082e-03 3.148731e-06 -0.0022741243 #> tauro -5.776374e-04 2.422874e-05 -2.473503e-04 -0.0004171947 #> westmalle -4.421245e-04 -7.338895e-04 1.612346e-05 -0.0007666637 #> amrut 4.652313e-04 1.135970e-03 3.402538e-04 -0.0011307959 #> ballantines 2.624766e-03 -1.653235e-03 -9.878081e-05 -0.0017287563 #> bushmills -1.332454e-04 1.113376e-03 1.602089e-04 -0.0006916012 #> chivas 1.116103e-03 -2.491530e-03 -9.913464e-04 -0.0011585308 #> dalmore 1.019313e-03 -9.423920e-04 -2.075399e-03 -0.0001835038 #> famousgrouse -1.222042e-03 -3.192907e-04 1.028735e-03 0.0001611504 #> glendronach 1.969121e-04 6.973513e-04 1.810040e-04 -0.0014310821 #> glenmorangie -4.077866e-05 2.974758e-04 2.699506e-05 -0.0009470779 #> highlandpark -1.096361e-03 -4.080900e-03 -8.356537e-04 -0.0007232859 #> jackdaniels 4.450744e-04 -7.898984e-04 8.654690e-04 -0.0026841687 #> jb 4.497643e-05 3.343889e-04 -1.017336e-03 -0.0020327924 #> johnniewalker -8.204066e-04 -1.173419e-03 -4.161162e-04 -0.0016445323 #> magallan -1.109793e-03 6.828727e-04 7.119352e-04 0.0013949777 #> makersmark -7.150888e-04 -2.119718e-03 4.641016e-04 -0.0020552953 #> oban 7.127703e-04 1.418921e-03 1.652713e-04 -0.0011940845 #> oldpotrero 6.516221e-04 -1.263670e-03 -3.276935e-04 -0.0007770829 #> redbreast 1.664233e-03 -2.352226e-03 -3.191507e-04 -0.0007444397 #> tamdhu -3.765004e-04 2.690095e-04 -2.278638e-05 -0.0013093652 #> wildturkey 2.107198e-03 -5.335998e-04 -5.539288e-07 -0.0025142726 #> yoichi -1.089887e-03 -3.844364e-03 -6.121975e-04 -0.0019437166 #> A19 A20 A21 A22 #> brahma -8.360520e-04 -1.095155e-03 -5.439578e-04 -0.0008608038 #> caney 2.301119e-05 -8.399357e-04 -5.178245e-04 -0.0009469597 #> chimay -1.119706e-03 -9.775433e-04 -1.256788e-03 -0.0002828775 #> corona -3.339722e-04 -1.281244e-03 -4.441549e-04 -0.0010768982 #> deusventrue 4.696431e-04 -8.906751e-04 -3.783424e-05 -0.0004364503 #> duvel -1.052150e-03 1.767706e-04 -1.315824e-03 0.0001575196 #> franziskaner -2.487242e-04 -1.440287e-03 -2.906736e-04 -0.0013413124 #> grimbergen -5.092226e-04 -1.388491e-03 -1.047057e-03 -0.0009030433 #> guiness -5.134258e-04 -9.406369e-04 -7.035895e-04 -0.0010718354 #> hoegardeen -3.030391e-05 -1.375411e-03 -1.083590e-04 -0.0012010324 #> jupiler -1.746120e-04 -7.555265e-04 -2.440347e-04 -0.0007606965 #> kingfisher -1.248337e-04 -9.013070e-04 -2.490120e-04 -0.0009173615 #> latrappe -1.798539e-03 1.557989e-04 -1.580709e-03 -0.0003042140 #> lindemanskriek -1.527305e-05 -1.022777e-03 -1.208019e-04 -0.0008309589 #> nicechouffe 3.237215e-04 -4.025861e-04 -3.535202e-05 -0.0003365178 #> pecheresse -6.085669e-04 -9.703236e-04 -4.706892e-04 -0.0008515637 #> sierranevada -3.026415e-04 -6.164256e-04 -4.048992e-04 -0.0002228167 #> tanglefoot -1.678775e-03 -6.763154e-04 -1.661378e-03 0.0002811837 #> tauro -1.242105e-04 -6.929686e-04 -1.750296e-04 -0.0006968736 #> westmalle 4.796447e-05 -9.153239e-04 -3.625213e-04 -0.0007776180 #> amrut -2.937597e-04 -1.042779e-03 4.676933e-04 -0.0005584716 #> ballantines -1.095479e-03 -5.664907e-04 -1.334292e-03 -0.0001309159 #> bushmills -4.243124e-04 -1.597220e-03 -3.746931e-04 -0.0012943033 #> chivas -1.143344e-03 -1.503350e-04 -1.506499e-03 -0.0005578037 #> dalmore -2.332470e-03 4.045078e-04 -1.415380e-03 -0.0005555167 #> famousgrouse 1.049511e-03 -9.742276e-04 -2.767390e-04 -0.0013519075 #> glendronach -3.271808e-04 -1.252161e-03 4.876743e-04 -0.0007595878 #> glenmorangie -6.036688e-05 -1.153601e-03 6.282828e-05 -0.0010084062 #> highlandpark 9.189143e-06 3.409179e-04 -1.179990e-03 -0.0003642734 #> jackdaniels -5.032865e-04 -2.133471e-03 1.457150e-04 -0.0007421376 #> jb -6.252763e-04 -1.068694e-03 2.480485e-04 -0.0012779648 #> johnniewalker 5.173429e-04 -1.616008e-03 3.050870e-04 -0.0017541528 #> magallan 1.070598e-03 2.807696e-05 -9.598212e-06 -0.0008434404 #> makersmark 2.630934e-04 -1.571250e-03 -3.711217e-04 -0.0014299088 #> oban -2.798357e-04 -9.061662e-04 7.605150e-04 -0.0005982398 #> oldpotrero -7.682701e-04 -3.189202e-04 -1.292703e-03 -0.0004288338 #> redbreast -4.639071e-04 -6.413198e-05 -1.338260e-03 -0.0002888724 #> tamdhu -7.332551e-04 -1.369532e-03 -2.418841e-04 -0.0008026583 #> wildturkey 1.454628e-04 -8.134531e-04 2.078593e-04 -0.0009947430 #> yoichi 5.982287e-04 -6.939296e-04 -3.599693e-04 -0.0010059628 #> A23 A24 A25 A26 #> brahma -5.735915e-04 -7.299627e-04 -5.033864e-04 -4.409200e-04 #> caney -3.939390e-04 -4.249811e-04 -3.278067e-04 -2.777037e-04 #> chimay -6.410642e-04 -3.497060e-04 -3.987327e-04 -3.797373e-04 #> corona -1.717514e-04 -8.503422e-04 -5.002657e-04 -6.613581e-04 #> deusventrue -2.719114e-04 -1.349406e-04 -4.678471e-04 -6.742999e-05 #> duvel -7.818289e-04 3.932732e-04 -9.314404e-06 -2.825668e-05 #> franziskaner -4.046305e-04 -1.021761e-03 -4.715859e-04 -6.988167e-04 #> grimbergen -7.620525e-04 -3.869953e-04 -6.922240e-04 -3.085118e-04 #> guiness -1.351687e-03 -8.291494e-04 -9.365808e-04 -3.617216e-04 #> hoegardeen -2.498091e-04 -8.130813e-04 -3.461347e-04 -4.976229e-04 #> jupiler -2.215773e-04 -5.697297e-04 -2.066056e-04 -4.092564e-04 #> kingfisher -3.967327e-04 -7.678531e-04 -5.048256e-04 -5.527247e-04 #> latrappe -1.006108e-03 -8.063068e-04 -1.898781e-04 -8.045060e-04 #> lindemanskriek -3.973242e-04 -5.696441e-04 -5.273803e-04 -3.157960e-04 #> nicechouffe -3.297171e-04 -2.842429e-04 -4.972024e-04 -2.750759e-04 #> pecheresse -4.105892e-04 -5.570638e-04 -2.828138e-04 -3.578320e-04 #> sierranevada -1.099662e-03 -1.387875e-04 -9.442991e-04 1.096631e-04 #> tanglefoot -1.635148e-03 -4.770303e-05 -1.168425e-03 -3.445467e-04 #> tauro -1.625056e-04 -5.661598e-04 -1.964170e-04 -4.236883e-04 #> westmalle -4.429987e-04 -3.005871e-04 -4.540035e-04 -1.575977e-04 #> amrut -7.244893e-05 -8.542750e-04 -5.559353e-04 -3.654990e-04 #> ballantines -1.390100e-03 -1.531693e-04 -8.488486e-04 -2.444936e-04 #> bushmills -7.789744e-05 -8.117072e-04 -1.020809e-04 -5.697088e-04 #> chivas -1.346262e-03 -5.894841e-04 -3.746380e-04 -6.807200e-04 #> dalmore -7.044950e-04 -1.289471e-03 5.765490e-05 -1.174635e-03 #> famousgrouse -5.212407e-04 -5.448013e-04 -3.704556e-04 -1.542122e-04 #> glendronach -1.149506e-04 -1.118511e-03 -6.721453e-04 -5.846057e-04 #> glenmorangie -2.822714e-04 -8.637078e-04 -6.676302e-04 -4.433941e-04 #> highlandpark -1.555117e-03 -4.896530e-04 -7.493971e-04 -2.547851e-04 #> jackdaniels -4.989083e-04 -7.889162e-04 -1.216612e-03 -2.005722e-04 #> jb -7.216180e-04 -1.498284e-03 -5.639723e-04 -6.661035e-04 #> johnniewalker -8.869808e-05 -1.130499e-03 -6.767161e-05 -5.211472e-04 #> magallan 1.136414e-04 -3.351403e-04 4.998842e-04 -1.129039e-04 #> makersmark -8.579604e-04 -2.116652e-04 -7.427828e-04 -2.690318e-04 #> oban 5.678546e-05 -1.123786e-03 -3.954051e-04 -5.501621e-04 #> oldpotrero -9.468502e-04 -4.171101e-04 -7.033424e-04 -7.954337e-04 #> redbreast -1.186983e-03 -3.016778e-04 -5.536010e-04 -4.264666e-04 #> tamdhu -3.844344e-04 -8.220193e-04 -7.701044e-04 -5.589579e-04 #> wildturkey -1.178700e-03 -7.132883e-04 -9.516387e-04 -4.435690e-05 #> yoichi -1.459839e-03 -7.921361e-04 -1.086323e-03 8.118876e-06 #> A27 A28 A29 A30 #> brahma -3.652079e-04 -2.976623e-04 -3.220750e-04 -2.405557e-04 #> caney -4.543725e-04 -1.340038e-04 -1.715288e-04 8.287078e-05 #> chimay 1.897326e-04 -3.220192e-04 1.012090e-04 -3.939649e-04 #> corona -5.628453e-04 -2.866408e-04 -6.301550e-04 -2.277373e-04 #> deusventrue -4.081023e-04 -6.793693e-06 -2.278672e-04 -1.602607e-04 #> duvel -4.501744e-05 -5.229843e-04 8.047695e-05 -3.443646e-04 #> franziskaner -4.854885e-04 -4.750621e-04 -4.823508e-04 -3.278401e-04 #> grimbergen -4.197697e-04 -1.283767e-04 -1.685585e-04 -1.590373e-04 #> guiness -6.925029e-04 -3.580901e-04 -5.165405e-04 -1.183717e-04 #> hoegardeen -4.969737e-04 -2.495808e-04 -4.912037e-04 -6.346919e-05 #> jupiler -2.483571e-04 -2.993651e-04 -1.920937e-04 -1.788899e-04 #> kingfisher -5.448135e-04 -4.650672e-04 -5.979427e-04 -3.497510e-04 #> latrappe 1.533756e-04 -5.493115e-04 5.599578e-05 -7.649463e-05 #> lindemanskriek -5.437426e-04 -1.937430e-04 -5.135849e-04 -9.406325e-05 #> nicechouffe -3.740962e-04 -2.387508e-04 -2.592933e-04 -3.671187e-04 #> pecheresse -2.370723e-04 -2.125326e-04 -1.635507e-04 -1.002369e-04 #> sierranevada -5.741030e-04 -3.442510e-05 -3.438660e-04 -1.891307e-04 #> tanglefoot -1.719313e-04 -4.589738e-04 3.812701e-04 -6.044718e-04 #> tauro -2.674869e-04 -3.421696e-04 -1.858056e-04 -2.076248e-04 #> westmalle -5.645719e-04 -1.247868e-04 -4.182225e-04 -4.248077e-05 #> amrut -3.710587e-04 -6.939239e-05 -6.261379e-04 -2.992623e-04 #> ballantines -3.251060e-04 -5.994957e-04 -2.757254e-04 -8.154587e-04 #> bushmills -2.720945e-04 -3.599923e-04 -3.414174e-04 -2.377839e-04 #> chivas -2.255766e-04 -8.637994e-04 -1.458373e-04 -3.882162e-04 #> dalmore -9.942863e-05 -7.848302e-04 -5.977677e-04 -2.299701e-04 #> famousgrouse -6.485656e-04 -2.158172e-04 -7.140961e-04 -1.036337e-04 #> glendronach -4.429512e-04 -1.668512e-04 -6.373005e-04 -3.195863e-04 #> glenmorangie -7.765482e-04 -2.094619e-04 -8.242601e-04 -2.409561e-04 #> highlandpark 9.675349e-05 -9.874542e-05 2.967982e-04 -2.470293e-04 #> jackdaniels -8.279356e-04 2.860995e-04 -6.585185e-04 1.297801e-04 #> jb -3.654559e-04 -6.181808e-04 -6.228425e-04 -5.440835e-04 #> johnniewalker -4.614923e-04 -4.769614e-04 -9.140300e-04 -3.536712e-04 #> magallan 1.930942e-04 -4.644705e-04 -1.875115e-04 -4.003883e-04 #> makersmark -1.422649e-03 -3.876731e-05 -4.450249e-04 2.762661e-04 #> oban -1.373020e-04 -1.436324e-04 -4.904222e-04 -3.352663e-04 #> oldpotrero -4.396750e-04 -5.793447e-04 -2.152387e-04 -5.552859e-04 #> redbreast -2.394329e-04 -7.978188e-04 -2.390723e-04 -5.929331e-04 #> tamdhu -6.472657e-04 -2.331427e-04 -4.991397e-04 -1.900026e-04 #> wildturkey -9.059420e-04 -3.046609e-04 -8.375680e-04 -3.434517e-04 #> yoichi -3.472393e-04 1.165942e-04 -2.819714e-04 -3.541959e-04 #> A31 A32 B1 B2 B3 #> brahma -1.974790e-04 -8.094538e-05 0 -1.900652e-04 3.306231e-04 #> caney -5.975848e-05 -7.681466e-06 0 5.012013e-04 -3.851293e-04 #> chimay 3.467138e-05 -3.425039e-05 0 1.843629e-04 4.196107e-04 #> corona -6.391514e-04 -7.778089e-05 0 -3.586724e-04 1.711055e-05 #> deusventrue -5.672855e-05 -9.370594e-05 0 1.774985e-04 -8.326845e-05 #> duvel 2.041590e-04 -1.384422e-04 0 -4.198782e-04 7.447638e-05 #> franziskaner -3.511246e-04 -1.887467e-04 0 -8.367911e-04 -3.508429e-04 #> grimbergen -1.034722e-04 -1.074542e-04 0 -4.478525e-04 -1.575351e-04 #> guiness -9.701532e-05 9.185850e-06 0 4.379065e-05 -3.284575e-04 #> hoegardeen -3.894108e-04 -1.449367e-05 0 -1.402306e-05 3.803656e-04 #> jupiler -1.358161e-04 -1.366520e-04 0 1.831345e-04 -1.827727e-04 #> kingfisher -4.164633e-04 -2.558914e-04 0 -1.644074e-04 -3.059412e-04 #> latrappe -6.701359e-05 2.760955e-04 0 2.164816e-04 1.803082e-04 #> lindemanskriek -2.873840e-04 2.669199e-06 0 4.100249e-04 2.208045e-04 #> nicechouffe -1.738180e-04 -3.703168e-04 0 5.495158e-04 -2.042167e-05 #> pecheresse -1.028221e-04 -5.676952e-05 0 2.181959e-04 -7.311833e-05 #> sierranevada -3.941502e-05 -1.245511e-04 0 -2.089826e-04 -3.847117e-04 #> tanglefoot 3.701320e-04 -3.628268e-04 0 2.257469e-04 -2.009399e-04 #> tauro -1.470322e-04 -2.627287e-04 0 1.762712e-04 -8.961804e-05 #> westmalle -1.340963e-04 -3.584753e-05 0 2.683034e-04 5.829510e-04 #> amrut -6.740665e-04 -1.263649e-04 0 3.259091e-04 3.840090e-04 #> ballantines -3.000458e-04 -5.620135e-04 0 -8.980074e-06 1.013064e-03 #> bushmills -3.951078e-04 -2.398475e-04 0 8.084328e-04 8.012671e-04 #> chivas -6.925496e-05 -8.800981e-06 0 6.073651e-04 3.070684e-04 #> dalmore -7.809275e-04 7.011618e-05 0 1.097768e-03 6.881659e-04 #> famousgrouse -4.672213e-04 -9.582100e-05 0 1.287495e-04 -1.324051e-04 #> glendronach -7.048583e-04 -1.975745e-04 0 4.149836e-04 1.394907e-04 #> glenmorangie -6.325151e-04 -2.741086e-04 0 8.773153e-05 -6.257124e-05 #> highlandpark -7.059637e-05 -2.569712e-04 0 -6.291662e-04 -7.091405e-04 #> jackdaniels -4.208486e-04 7.987137e-05 0 1.828207e-04 -5.854778e-04 #> jb -3.650894e-04 -2.691260e-04 0 5.770034e-04 1.295536e-04 #> johnniewalker -8.042786e-04 -1.053716e-04 0 1.610309e-03 1.521699e-03 #> magallan -1.549710e-04 -9.098292e-05 0 -1.110357e-03 -1.017379e-03 #> makersmark -5.759001e-04 -6.063122e-04 0 -2.272912e-03 -1.921977e-03 #> oban -6.414803e-04 -1.069347e-04 0 5.217373e-04 3.289690e-04 #> oldpotrero -3.440437e-04 -2.888371e-04 0 -4.566144e-04 2.434271e-04 #> redbreast 1.079718e-05 -2.434157e-04 0 1.568632e-04 1.213587e-04 #> tamdhu -4.031862e-04 -2.196594e-04 0 1.013117e-03 4.671170e-04 #> wildturkey -3.706899e-04 -3.840752e-04 0 9.489660e-04 9.344159e-04 #> yoichi -2.793226e-04 -3.702781e-04 0 2.371406e-04 3.337929e-04 #> B4 B5 B6 B7 #> brahma -5.191749e-04 1.067446e-04 -9.218905e-05 5.604686e-07 #> caney 3.333918e-04 -2.899903e-04 7.350207e-05 -4.952054e-04 #> chimay 3.227901e-04 -2.906714e-05 5.573360e-04 1.059517e-04 #> corona -5.501057e-04 -1.907425e-04 -4.256287e-04 -2.147013e-04 #> deusventrue -1.403373e-03 -3.240180e-04 -9.330047e-04 6.515692e-04 #> duvel -6.627095e-04 6.107940e-05 -4.746985e-04 2.450959e-04 #> franziskaner -6.983186e-04 -1.894199e-04 -5.170165e-04 5.988419e-05 #> grimbergen 1.554676e-04 5.257427e-05 1.132609e-04 -6.848791e-05 #> guiness -1.677242e-04 -5.817648e-04 -2.853668e-04 -5.620867e-04 #> hoegardeen 3.285812e-04 4.813766e-04 3.691213e-04 5.309204e-04 #> jupiler -4.540203e-05 -1.242456e-04 -5.198885e-05 -2.289954e-04 #> kingfisher -1.751841e-04 3.014782e-05 2.132220e-04 4.144846e-04 #> latrappe 5.468038e-04 2.303760e-04 5.053959e-04 2.603399e-04 #> lindemanskriek 2.791269e-04 -2.076986e-04 -1.312595e-04 -1.367999e-04 #> nicechouffe 2.492854e-04 2.171344e-04 2.155297e-04 1.621249e-04 #> pecheresse 2.879648e-04 3.072908e-05 1.503582e-04 2.875235e-05 #> sierranevada 2.254752e-04 -1.582761e-04 3.201773e-04 -2.506594e-04 #> tanglefoot -3.556495e-04 -4.589428e-04 -1.231722e-04 -1.030225e-04 #> tauro 8.045507e-05 4.030041e-05 1.942858e-04 7.124766e-05 #> westmalle 2.086425e-04 5.569697e-04 -1.481080e-04 2.680453e-04 #> amrut 2.692429e-04 2.370884e-04 4.975910e-05 1.929742e-04 #> ballantines -2.175286e-04 1.006239e-03 -2.063087e-04 6.874951e-04 #> bushmills 9.888621e-04 5.333749e-04 6.026329e-04 3.382499e-07 #> chivas 1.231654e-04 -3.404412e-05 8.988476e-05 1.476812e-04 #> dalmore 2.545366e-04 1.352642e-04 -1.253930e-04 2.101188e-04 #> famousgrouse -1.274614e-04 2.141211e-04 -1.073666e-04 1.188717e-05 #> glendronach 1.071609e-04 -2.016928e-04 -6.904446e-05 -1.327779e-04 #> glenmorangie 1.913928e-04 -9.675222e-05 1.480796e-04 -8.118855e-05 #> highlandpark -2.204109e-04 -5.021317e-04 3.287316e-04 -2.505046e-04 #> jackdaniels -7.969529e-04 -4.880520e-04 -1.903562e-04 3.092736e-04 #> jb -1.422141e-04 -2.056778e-04 -2.053789e-04 1.048725e-04 #> johnniewalker 1.140415e-03 1.505532e-04 2.156619e-04 -1.772208e-04 #> magallan -7.964354e-04 -6.143625e-04 -3.734865e-04 -1.291146e-04 #> makersmark -3.452843e-04 -1.437534e-04 4.289043e-04 -9.732915e-04 #> oban 3.351843e-04 4.359254e-05 1.826487e-05 -6.027186e-05 #> oldpotrero -2.060062e-04 3.778706e-05 -5.576392e-04 2.258336e-04 #> redbreast -1.087561e-04 -1.587376e-04 -9.420764e-05 -7.636860e-06 #> tamdhu 2.449976e-04 3.452581e-05 -1.344683e-04 1.407481e-04 #> wildturkey 2.048265e-04 1.038328e-04 7.988232e-06 2.379076e-04 #> yoichi 2.790195e-04 2.201285e-04 1.423493e-05 -5.626562e-05 #> B8 B9 B10 B11 #> brahma 6.268503e-06 -1.960132e-04 1.334431e-04 4.058288e-05 #> caney 8.536695e-05 -4.143363e-04 1.667420e-04 -3.134942e-04 #> chimay 6.209192e-04 1.441644e-04 1.715223e-04 5.930974e-05 #> corona -1.931107e-04 -3.048499e-04 -2.065499e-04 -2.244684e-04 #> deusventrue -8.354423e-04 2.287499e-05 -6.080012e-04 2.971827e-04 #> duvel -1.676532e-04 1.512500e-04 6.986965e-05 2.318703e-04 #> franziskaner -3.810484e-04 5.133436e-05 -3.407356e-04 5.681736e-05 #> grimbergen -9.289817e-05 2.532879e-05 1.655384e-04 3.086461e-04 #> guiness -1.496463e-04 -4.662246e-04 -1.905673e-04 -3.642220e-04 #> hoegardeen 3.462062e-04 4.557837e-04 4.205444e-04 3.080245e-04 #> jupiler -8.073101e-05 -2.203453e-04 -1.514837e-04 -1.572771e-04 #> kingfisher 1.324881e-05 1.991329e-04 1.802238e-04 2.681872e-04 #> latrappe 1.829641e-04 2.106651e-04 -1.447749e-04 2.756836e-04 #> lindemanskriek 4.871774e-05 -4.788973e-05 -2.120403e-04 -1.394498e-04 #> nicechouffe 1.463372e-04 2.488056e-04 8.034353e-05 2.586078e-04 #> pecheresse 2.759482e-04 1.481251e-05 1.433130e-04 -1.556835e-05 #> sierranevada 1.406542e-04 -1.888577e-04 6.806233e-05 -5.042849e-05 #> tanglefoot 5.673867e-06 -2.751261e-04 -3.002656e-04 -2.455063e-04 #> tauro 2.932668e-04 1.286768e-04 1.547277e-04 1.336644e-04 #> westmalle -1.539093e-04 4.586356e-04 1.799417e-05 3.301881e-04 #> amrut 1.570262e-04 2.548664e-04 1.115168e-04 7.490810e-06 #> ballantines -3.868333e-05 3.003380e-04 1.592670e-04 -5.079525e-05 #> bushmills 2.135771e-04 -2.019147e-04 1.348464e-04 -1.302260e-04 #> chivas 1.332194e-04 1.056333e-04 2.227781e-05 4.227956e-05 #> dalmore -4.021158e-06 2.679348e-04 -2.632871e-05 1.881627e-04 #> famousgrouse -2.566731e-04 2.195639e-04 -7.568478e-05 1.842423e-04 #> glendronach 2.453495e-05 -7.915842e-06 -1.865175e-05 -6.786263e-05 #> glenmorangie 1.557411e-04 -3.527084e-06 1.414448e-04 -9.027797e-06 #> highlandpark 3.870735e-04 -4.437162e-04 1.970082e-04 -4.866817e-04 #> jackdaniels -1.751848e-04 -3.777874e-05 -1.953733e-04 2.389926e-04 #> jb 1.396719e-04 1.902920e-04 -7.877557e-05 4.429623e-05 #> johnniewalker 5.133497e-04 1.719490e-04 5.339652e-04 -1.814410e-04 #> magallan -1.577770e-04 -1.006505e-04 -1.482048e-04 -8.058980e-06 #> makersmark -5.600587e-04 -7.200799e-04 4.777646e-04 2.581853e-04 #> oban 8.787835e-05 1.113193e-04 1.307306e-04 -2.483305e-05 #> oldpotrero -3.831452e-04 2.156873e-04 -5.679089e-04 2.063675e-04 #> redbreast 2.541246e-05 2.426826e-05 -8.753325e-05 -8.652635e-06 #> tamdhu -3.383952e-05 3.365051e-04 -1.785979e-04 -4.280721e-06 #> wildturkey 3.002663e-04 1.207047e-04 1.615231e-04 -7.004425e-06 #> yoichi -1.168653e-04 -8.227670e-05 5.854442e-05 8.229082e-05 #> B12 B13 B14 B15 #> brahma -1.917814e-04 -4.415768e-05 -1.760152e-06 2.542883e-05 #> caney 2.011956e-05 -2.220739e-04 9.710885e-05 -2.929034e-05 #> chimay -3.197006e-06 3.218682e-04 -2.136764e-04 2.996248e-04 #> corona -6.091420e-06 -1.616363e-04 -1.409505e-05 -3.036983e-04 #> deusventrue -2.794108e-04 -2.410553e-04 -5.766037e-06 -1.013081e-04 #> duvel 1.659893e-04 -2.147276e-05 -7.372516e-05 -1.697182e-05 #> franziskaner -2.140707e-04 1.309236e-04 -1.825897e-05 9.453212e-05 #> grimbergen 1.890428e-04 2.030487e-04 4.494496e-05 2.047563e-04 #> guiness -2.602631e-04 -1.363068e-04 -1.037229e-05 4.860333e-05 #> hoegardeen 2.814325e-04 1.153058e-04 7.690851e-05 -7.760464e-05 #> jupiler -1.151375e-04 -1.062093e-04 -1.414838e-04 -5.844711e-06 #> kingfisher 1.550433e-04 3.863328e-05 1.987871e-04 8.556756e-05 #> latrappe -1.942322e-04 3.505642e-04 -2.308454e-04 6.983853e-05 #> lindemanskriek -5.113408e-05 4.601614e-05 2.027442e-05 -3.838834e-05 #> nicechouffe 4.652882e-05 1.804172e-04 -1.750016e-04 2.230781e-04 #> pecheresse 1.587407e-04 -2.017244e-05 7.161075e-05 -1.571287e-04 #> sierranevada 3.125122e-05 4.681375e-05 -5.698779e-05 5.098577e-05 #> tanglefoot -9.215486e-05 2.005060e-05 -6.143058e-05 -1.075625e-04 #> tauro 1.226045e-04 1.507290e-04 8.074917e-05 1.647359e-04 #> westmalle 4.757341e-05 1.853084e-04 3.602525e-05 -1.202643e-06 #> amrut -9.179140e-05 -1.098218e-04 -7.874144e-05 -6.180094e-05 #> ballantines 3.235267e-04 -2.822891e-04 3.832439e-04 -3.134129e-04 #> bushmills 2.015409e-04 -9.005687e-05 1.551691e-04 -1.474612e-04 #> chivas -6.666931e-05 2.594754e-05 -1.465818e-04 -3.962153e-05 #> dalmore -9.894417e-05 1.384451e-04 -3.536678e-05 1.404756e-04 #> famousgrouse -7.211196e-05 3.016994e-05 -2.020980e-04 -1.375501e-04 #> glendronach -9.224044e-05 -7.327995e-05 -4.780469e-05 -6.055072e-05 #> glenmorangie 6.261072e-05 -3.298471e-05 8.810869e-05 7.353097e-05 #> highlandpark 1.369676e-04 -2.344619e-04 1.400952e-04 -7.669050e-05 #> jackdaniels 3.169089e-04 3.555232e-04 1.821979e-04 7.868212e-05 #> jb -5.463792e-05 1.038743e-04 -1.519486e-05 -1.559990e-05 #> johnniewalker -5.200179e-05 -4.843014e-04 -2.187679e-04 -2.056380e-04 #> magallan -1.072102e-04 1.704278e-05 -6.741317e-05 -2.205709e-05 #> makersmark 8.085419e-06 -3.964151e-04 -3.192971e-04 5.139474e-04 #> oban -6.805926e-05 -6.673682e-05 7.219949e-05 1.027476e-04 #> oldpotrero -3.604369e-04 2.247342e-04 -4.303685e-04 9.031801e-05 #> redbreast 1.217829e-04 9.014972e-05 1.107807e-04 -3.676530e-05 #> tamdhu -2.219702e-04 1.160413e-05 -4.931877e-05 5.098733e-05 #> wildturkey 2.260401e-05 5.912870e-06 2.723819e-05 2.216640e-05 #> yoichi 1.472054e-04 3.703653e-06 3.359119e-05 -7.624301e-05 #> B16 B17 B18 B19 #> brahma -1.024642e-04 -8.031982e-05 -7.433041e-05 2.949173e-05 #> caney 1.467454e-04 -1.500259e-05 8.962807e-05 1.017678e-04 #> chimay -4.160132e-04 2.173693e-04 -2.232850e-04 1.410948e-04 #> corona 1.562544e-04 -1.863667e-04 1.898815e-04 -3.051700e-04 #> deusventrue 2.687631e-04 -5.866990e-05 2.532389e-04 4.683303e-05 #> duvel 8.924870e-05 1.724312e-04 1.497399e-04 1.188058e-04 #> franziskaner 2.076190e-05 5.303781e-05 1.447445e-04 2.813898e-05 #> grimbergen 1.197492e-04 9.559379e-05 -1.078603e-04 -4.345587e-05 #> guiness -1.231218e-04 8.402517e-05 -5.232981e-05 1.549783e-04 #> hoegardeen 5.139144e-05 -1.331768e-04 -2.258407e-05 -2.391701e-04 #> jupiler -9.634201e-05 7.584032e-05 -2.484072e-05 1.230285e-04 #> kingfisher 1.629910e-04 1.538249e-05 6.406877e-05 -8.623734e-05 #> latrappe -3.333379e-04 -2.151666e-04 -1.793420e-04 -1.972264e-04 #> lindemanskriek 1.913674e-05 -2.214246e-05 6.308868e-05 1.058368e-04 #> nicechouffe -1.476434e-04 1.487541e-04 -3.189322e-04 7.671453e-05 #> pecheresse -1.502647e-05 -1.256547e-04 -2.111016e-05 -1.795287e-04 #> sierranevada -1.612513e-04 6.781737e-05 -1.868408e-04 1.545018e-04 #> tanglefoot -2.075450e-04 -6.190151e-05 7.110212e-05 1.907329e-04 #> tauro -2.608415e-05 7.036816e-05 -1.112206e-04 -2.070534e-07 #> westmalle 1.555977e-04 2.494345e-05 2.457638e-04 -3.753649e-05 #> amrut -5.808395e-05 -5.726583e-05 -4.347323e-05 -4.142367e-05 #> ballantines 2.695725e-04 -1.723254e-04 6.902277e-05 -2.491346e-05 #> bushmills 2.003848e-05 -1.361937e-04 -3.959514e-05 -8.151185e-05 #> chivas -8.163047e-05 6.400487e-05 2.496293e-05 3.670116e-07 #> dalmore 5.018616e-05 -2.426364e-05 1.517115e-05 -7.169745e-05 #> famousgrouse -5.272581e-05 2.433801e-05 7.999124e-05 1.472625e-05 #> glendronach -3.899954e-05 -1.372083e-04 -6.680409e-05 -1.191487e-04 #> glenmorangie 9.340889e-05 8.779820e-06 1.467657e-06 -4.863149e-05 #> highlandpark -5.506078e-05 -4.375426e-05 -1.601530e-04 1.023000e-05 #> jackdaniels 1.592122e-04 1.994958e-04 4.570234e-04 2.251557e-04 #> jb -1.185695e-04 -8.893584e-05 3.900650e-06 1.331244e-05 #> johnniewalker 1.378430e-04 1.149116e-04 3.109675e-04 2.515221e-04 #> magallan -1.015593e-04 -4.418979e-06 -3.238623e-05 3.993857e-05 #> makersmark 1.443085e-04 1.724064e-04 -5.251779e-04 1.746597e-04 #> oban 9.860858e-05 -4.593528e-05 -8.084187e-05 -5.853302e-05 #> oldpotrero -2.725407e-04 1.367096e-04 -1.893404e-04 -2.795346e-06 #> redbreast 1.181494e-04 -9.309777e-06 1.628999e-04 -2.745219e-05 #> tamdhu -4.983723e-05 -7.376290e-05 -1.044426e-04 -7.987732e-05 #> wildturkey -1.630103e-04 -3.611579e-06 -1.779304e-04 -3.570358e-05 #> yoichi 2.484339e-05 1.257615e-05 9.503541e-05 2.723700e-05 #> B20 B21 B22 B23 #> brahma -1.727433e-05 3.737724e-05 -9.462283e-06 -4.267458e-05 #> caney 1.631617e-04 1.508881e-04 1.414211e-04 1.088653e-04 #> chimay -3.610984e-05 -1.712342e-04 2.100688e-05 -3.082575e-04 #> corona 5.852024e-05 -1.892126e-04 1.439899e-04 -1.701985e-04 #> deusventrue 1.245832e-04 7.313250e-06 -1.170924e-04 1.347852e-04 #> duvel 1.101660e-04 -1.728305e-05 9.542637e-05 -1.277279e-04 #> franziskaner 1.795671e-04 6.095791e-06 1.990743e-04 7.411105e-06 #> grimbergen -5.951324e-05 -1.402638e-05 -1.801951e-04 -1.396215e-04 #> guiness -2.255777e-05 -1.319653e-05 -1.127083e-04 -8.149761e-05 #> hoegardeen -1.346868e-04 -3.083842e-04 -1.133545e-04 -2.005817e-04 #> jupiler -2.427445e-05 1.297878e-04 3.863779e-05 1.328010e-04 #> kingfisher 1.719032e-05 -8.315015e-05 -5.685565e-06 -4.528561e-05 #> latrappe 7.799543e-05 -1.931198e-04 5.065654e-05 -2.027860e-04 #> lindemanskriek 9.064003e-05 1.285962e-04 -7.498356e-05 9.866433e-05 #> nicechouffe -2.076616e-04 3.715694e-05 -1.897096e-04 -8.192524e-05 #> pecheresse -6.967807e-05 -1.204336e-04 -4.034586e-05 -8.286053e-05 #> sierranevada -1.253536e-04 2.231407e-04 -7.914671e-05 2.030511e-04 #> tanglefoot 1.265752e-04 3.645141e-05 8.153378e-05 1.463325e-04 #> tauro -1.673200e-04 -3.795493e-05 -2.216782e-04 -9.138492e-05 #> westmalle 1.513049e-04 -8.741209e-05 1.191689e-04 4.122166e-05 #> amrut -1.620938e-05 -4.241691e-05 -2.872726e-05 -7.706793e-05 #> ballantines -9.511720e-05 3.497929e-05 -1.525410e-04 3.344485e-05 #> bushmills -1.692696e-05 -1.985027e-05 -5.673431e-05 -4.245935e-05 #> chivas -3.520791e-05 -3.239497e-05 3.624818e-05 -7.905990e-05 #> dalmore 1.335714e-04 4.821092e-05 3.029999e-05 -2.866421e-05 #> famousgrouse 3.446106e-05 -9.287266e-05 -5.252847e-05 -1.166408e-04 #> glendronach -8.818028e-06 -5.284867e-05 -4.842191e-05 -1.083835e-04 #> glenmorangie -1.128407e-05 4.185137e-05 6.424851e-05 3.040985e-05 #> highlandpark -6.621924e-05 2.623244e-05 5.174724e-05 -4.722625e-05 #> jackdaniels 3.551884e-04 1.445123e-06 2.762319e-04 1.240702e-04 #> jb -2.384959e-06 -6.979310e-05 -8.136968e-05 -2.918739e-05 #> johnniewalker 2.572639e-04 2.352637e-04 2.062948e-04 1.853106e-04 #> magallan 8.388080e-05 2.286704e-05 8.619190e-05 -1.114752e-06 #> makersmark 1.772977e-04 4.534530e-04 -1.701385e-04 -2.389260e-04 #> oban 5.722186e-05 9.730784e-05 2.947083e-05 -4.596947e-05 #> oldpotrero -9.109679e-05 -1.485829e-05 8.622920e-05 -7.160617e-05 #> redbreast 1.465601e-04 -2.217205e-05 6.081711e-05 5.593471e-05 #> tamdhu -4.444590e-05 -9.622733e-05 -5.446212e-05 -7.968429e-05 #> wildturkey -6.312522e-05 -8.731978e-05 -9.045224e-05 -1.442588e-04 #> yoichi -6.770553e-06 -7.074253e-06 -3.277625e-05 3.448357e-05 #> B24 B25 B26 B27 #> brahma 3.357899e-05 1.692467e-05 1.346898e-04 1.323552e-05 #> caney 8.041007e-05 1.705793e-04 6.811154e-05 6.205877e-05 #> chimay 6.975068e-05 -3.230519e-04 2.772097e-05 -1.930852e-04 #> corona 2.066873e-05 -1.628616e-04 7.895544e-05 9.425535e-06 #> deusventrue -1.235701e-04 1.790799e-04 -1.724233e-04 1.249888e-04 #> duvel 7.759496e-05 -1.131994e-04 1.749479e-04 5.630411e-05 #> franziskaner 2.096840e-04 5.258363e-05 2.046122e-04 9.602614e-05 #> grimbergen -1.934331e-04 -5.077219e-05 -9.668195e-05 -1.152902e-05 #> guiness -3.540174e-05 -1.382297e-04 -7.048572e-05 -2.514223e-04 #> hoegardeen -1.012696e-04 -2.098450e-04 -1.981990e-04 -1.709484e-04 #> jupiler 4.995495e-05 9.924240e-05 3.292957e-05 6.028515e-05 #> kingfisher -4.338832e-05 2.094242e-06 -1.091127e-04 1.809903e-05 #> latrappe 4.481099e-05 -9.750492e-07 1.320075e-04 1.075270e-04 #> lindemanskriek -6.757003e-05 1.553763e-04 -7.707839e-05 5.131619e-05 #> nicechouffe -5.530183e-05 -1.113497e-04 1.000706e-04 -1.285347e-04 #> pecheresse 3.202237e-05 -8.922353e-07 7.525484e-05 6.328643e-06 #> sierranevada -3.979424e-05 2.215211e-04 6.707671e-05 1.786146e-04 #> tanglefoot 2.668517e-04 2.207476e-04 1.806422e-04 1.175903e-04 #> tauro -2.201592e-04 -1.334780e-04 -1.668332e-04 -1.334782e-04 #> westmalle 1.494564e-04 7.630565e-05 6.478230e-05 8.574062e-05 #> amrut -7.423616e-05 -9.642488e-05 -6.096081e-05 -5.130361e-05 #> ballantines -1.139455e-04 -5.063695e-06 -7.587876e-06 -8.630156e-05 #> bushmills -1.070090e-04 -5.351683e-05 -6.508694e-05 -4.250557e-05 #> chivas -6.203789e-05 -1.131152e-04 -2.118968e-05 -2.011372e-05 #> dalmore -1.052443e-04 1.314585e-04 6.223813e-05 8.974265e-05 #> famousgrouse 9.201751e-06 -3.069921e-05 6.168392e-05 -2.812213e-05 #> glendronach -9.443193e-05 -9.402038e-05 -6.862198e-05 -6.239359e-05 #> glenmorangie 8.064676e-06 -9.115729e-05 2.092771e-05 -6.525547e-06 #> highlandpark 1.656563e-04 -1.197451e-04 1.990472e-04 -1.607961e-04 #> jackdaniels 3.141428e-04 1.438902e-04 1.360127e-04 7.677775e-05 #> jb -5.981547e-06 3.209775e-05 -5.872919e-05 -4.055534e-05 #> johnniewalker 1.090105e-04 2.440030e-05 4.631195e-05 -6.158105e-05 #> magallan 4.078643e-05 -5.422248e-05 9.397643e-05 1.807366e-05 #> makersmark 7.660151e-05 2.869973e-04 3.123278e-04 -1.724480e-04 #> oban -8.787218e-05 1.336036e-05 6.898514e-05 1.098895e-04 #> oldpotrero 1.298368e-04 -1.188172e-04 1.233055e-04 -9.419603e-05 #> redbreast 1.608830e-05 1.972762e-05 -8.025162e-06 3.855603e-05 #> tamdhu -7.215626e-05 -5.300043e-05 -6.775627e-05 2.119539e-05 #> wildturkey -4.169666e-05 -8.994826e-05 2.380420e-05 -4.889098e-05 #> yoichi -1.328858e-05 3.447740e-05 -3.698146e-05 -2.869228e-05 #> B28 B29 B30 B31 #> brahma 9.806530e-05 -1.691212e-05 1.229728e-04 6.153001e-06 #> caney 4.057485e-05 3.928378e-05 3.848225e-05 5.608283e-05 #> chimay -2.670005e-05 2.629625e-05 -4.657436e-05 1.626961e-04 #> corona -1.115351e-05 1.797628e-05 -6.512991e-05 1.430262e-04 #> deusventrue -1.098118e-04 -7.708499e-06 -1.093334e-04 -1.335296e-04 #> duvel 8.996050e-05 -1.871001e-05 -1.512385e-04 -1.753386e-05 #> franziskaner 1.770497e-04 7.088446e-05 8.138285e-05 5.397908e-05 #> grimbergen -1.034470e-04 7.562129e-05 -2.509585e-05 1.318461e-04 #> guiness -1.343019e-05 -2.135015e-04 6.528218e-05 -2.138696e-04 #> hoegardeen -1.891331e-04 -2.027795e-05 -1.994452e-04 8.440574e-06 #> jupiler 3.698933e-05 4.153355e-05 -1.269451e-05 2.996676e-06 #> kingfisher -5.937101e-05 4.782661e-05 -4.637724e-05 -1.873467e-05 #> latrappe 3.127671e-05 6.155545e-05 1.090250e-05 1.042136e-04 #> lindemanskriek -7.184754e-05 1.818455e-05 -3.242323e-05 -4.990771e-05 #> nicechouffe 1.757105e-04 -2.027842e-04 2.059657e-04 -1.480986e-04 #> pecheresse 6.500181e-05 3.025513e-05 4.663718e-05 2.857271e-05 #> sierranevada 4.103579e-05 4.237471e-05 8.981611e-05 3.178064e-06 #> tanglefoot 1.359892e-04 1.424025e-04 9.431909e-05 5.521421e-05 #> tauro -1.277568e-04 -1.387930e-04 -9.102122e-05 -7.700952e-05 #> westmalle 1.603183e-05 4.180181e-05 6.597365e-05 1.291222e-04 #> amrut -3.381274e-05 -5.523538e-05 -5.099306e-05 -5.156172e-05 #> ballantines 7.017023e-05 -1.808696e-04 3.999426e-05 -1.901792e-04 #> bushmills -1.565836e-05 -2.836986e-05 -1.194452e-05 -5.279559e-05 #> chivas -4.979588e-05 -8.638138e-06 -7.040279e-05 4.772406e-05 #> dalmore -6.494053e-05 -9.744864e-05 6.715816e-05 3.921296e-05 #> famousgrouse 3.214914e-05 -1.031722e-05 8.491463e-05 5.581120e-05 #> glendronach -6.552423e-05 -4.747638e-05 -6.498987e-05 -2.314333e-05 #> glenmorangie 9.980637e-05 -2.982313e-05 5.485448e-05 -7.232008e-05 #> highlandpark 1.333362e-04 -1.101299e-04 5.583464e-05 3.249483e-05 #> jackdaniels 6.961363e-05 1.125400e-04 6.535658e-05 1.682956e-04 #> jb -1.163580e-04 1.168139e-05 -1.820077e-05 7.989656e-05 #> johnniewalker 1.843935e-04 -4.029596e-05 2.282147e-04 -1.093759e-04 #> magallan 1.905241e-04 -7.821211e-06 9.830610e-05 -1.616843e-05 #> makersmark -1.527610e-05 -1.083002e-05 2.667490e-04 5.665387e-05 #> oban -1.219200e-05 -3.906020e-05 -6.570052e-05 4.842028e-05 #> oldpotrero 1.395086e-04 -1.457807e-05 8.504515e-05 -1.657986e-05 #> redbreast 1.937056e-05 -3.090785e-05 1.655432e-05 -5.152611e-05 #> tamdhu -7.750763e-05 1.806773e-06 -1.030223e-04 -6.475153e-06 #> wildturkey 2.116661e-05 -3.808603e-05 2.629787e-06 1.485641e-06 #> yoichi -1.436536e-05 -6.982657e-06 4.571619e-05 -2.867356e-05 #> B32 C1 C2 C3 C4 #> brahma 1.217078e-04 0 -1.637571e-03 -3.936895e-03 5.408096e-03 #> caney 1.227213e-05 0 1.239828e-03 -2.845651e-04 3.757825e-04 #> chimay -4.552776e-05 0 -3.757608e-03 -1.797357e-03 -2.127924e-03 #> corona -4.547231e-05 0 -1.652864e-03 1.573302e-03 4.897281e-04 #> deusventrue 5.762098e-05 0 1.552775e-03 7.706329e-04 -1.416448e-03 #> duvel -1.615768e-04 0 2.872128e-04 -5.422392e-06 -7.785717e-04 #> franziskaner 5.143834e-05 0 -1.253868e-03 3.476506e-04 1.004621e-03 #> grimbergen -7.062906e-05 0 1.700875e-03 -1.452474e-04 4.332935e-04 #> guiness 7.815836e-05 0 -5.088378e-04 1.628258e-03 5.025916e-05 #> hoegardeen -2.171328e-04 0 -2.538102e-03 6.627214e-04 -1.481847e-03 #> jupiler -2.081774e-05 0 9.877198e-04 -8.223351e-05 1.286204e-04 #> kingfisher -3.244750e-05 0 8.355893e-04 -2.193322e-03 -9.853901e-04 #> latrappe 7.681797e-05 0 2.026476e-03 6.109498e-04 -1.518299e-04 #> lindemanskriek -4.318610e-05 0 -1.736348e-03 1.465734e-03 -1.513403e-03 #> nicechouffe 2.418090e-04 0 -5.467071e-04 2.799211e-04 -4.577128e-04 #> pecheresse 5.132538e-05 0 1.796104e-03 -3.206383e-04 -1.338857e-04 #> sierranevada 1.230683e-04 0 9.370620e-04 -7.543929e-04 2.972714e-04 #> tanglefoot -7.568911e-06 0 -7.405447e-04 3.028807e-04 6.337466e-04 #> tauro 7.872342e-07 0 1.122815e-04 -2.572009e-04 -8.133564e-04 #> westmalle 1.478645e-04 0 1.228197e-03 -2.741133e-04 9.140310e-05 #> amrut -2.042009e-05 0 4.658444e-04 -4.347520e-04 -3.326225e-05 #> ballantines -8.925358e-06 0 -5.591149e-04 1.469581e-03 -1.536579e-03 #> bushmills -2.889262e-05 0 -3.958316e-04 1.944836e-03 -7.053533e-05 #> chivas -7.474859e-05 0 -1.172232e-03 -1.218925e-03 -3.262755e-05 #> dalmore 8.076785e-05 0 6.958725e-04 -1.680610e-03 6.152298e-04 #> famousgrouse 1.145499e-04 0 7.115395e-05 8.468121e-04 -4.933730e-04 #> glendronach -4.912820e-05 0 -7.099606e-05 6.421159e-04 -4.706785e-04 #> glenmorangie 1.828692e-05 0 -8.919633e-06 -2.628346e-04 9.674043e-05 #> highlandpark -4.147565e-05 0 -1.617000e-03 5.528353e-04 -3.372340e-04 #> jackdaniels 6.663192e-06 0 5.328968e-04 -1.540810e-03 -5.769145e-04 #> jb -6.291564e-05 0 -2.505933e-03 -9.424246e-04 -8.780719e-04 #> johnniewalker 1.655345e-04 0 4.677592e-03 -4.233763e-04 -1.898993e-03 #> magallan 3.047713e-05 0 2.189543e-04 4.632813e-04 1.888985e-04 #> makersmark 1.662543e-05 0 1.698257e-03 -6.596354e-04 3.533379e-04 #> oban 5.922167e-05 0 6.795967e-07 1.085005e-06 -4.641661e-04 #> oldpotrero 5.577825e-05 0 -6.093255e-05 4.513517e-05 -4.902640e-04 #> redbreast 7.687024e-05 0 -1.468386e-03 1.265193e-04 -1.396525e-04 #> tamdhu -7.372278e-05 0 9.586941e-04 6.330302e-04 -2.779959e-04 #> wildturkey -4.151273e-05 0 -9.213008e-05 -1.129525e-03 -4.176692e-04 #> yoichi 3.983470e-06 0 5.380772e-05 -7.906572e-05 -7.656576e-04 #> C5 C6 C7 C8 #> brahma -1.259407e-03 -3.994402e-03 3.268582e-03 4.792269e-04 #> caney -4.017802e-05 4.699805e-04 2.518166e-04 6.300072e-04 #> chimay -4.663387e-04 -7.424827e-05 -8.096453e-05 9.946667e-04 #> corona 1.867708e-04 6.888736e-04 3.145355e-04 5.189042e-04 #> deusventrue 1.463377e-03 9.055123e-04 -2.834923e-04 -1.443910e-03 #> duvel 3.178998e-04 2.219253e-04 5.438377e-04 -3.518900e-06 #> franziskaner 1.054384e-03 2.433412e-04 9.526672e-04 8.662476e-04 #> grimbergen -6.417041e-04 -1.403671e-03 1.850428e-04 1.990252e-04 #> guiness 8.516115e-05 5.947385e-04 -3.856099e-04 2.426892e-04 #> hoegardeen -6.536099e-04 -5.091092e-04 -6.872483e-04 -4.089876e-04 #> jupiler 4.242307e-04 1.903101e-04 -1.512322e-04 3.486794e-04 #> kingfisher 1.200089e-03 4.039578e-05 -2.246083e-04 -6.682649e-04 #> latrappe -2.100725e-04 4.680496e-04 1.907268e-04 -1.386083e-04 #> lindemanskriek 2.721525e-04 -8.593526e-04 -1.905709e-04 1.402970e-04 #> nicechouffe -4.033887e-04 -3.674008e-04 -1.582921e-04 -3.898917e-04 #> pecheresse -3.165154e-04 -6.798663e-04 -1.857663e-04 -5.070674e-04 #> sierranevada 4.903049e-04 5.175725e-04 -5.450918e-04 -6.169308e-04 #> tanglefoot 6.556462e-04 1.058980e-03 8.585128e-04 5.745493e-04 #> tauro -4.748704e-04 -3.315681e-04 -4.564306e-04 -3.514821e-04 #> westmalle -4.491227e-04 -2.495132e-04 -7.270457e-05 -1.344863e-04 #> amrut 8.477464e-05 -1.080422e-04 2.126076e-04 -9.256970e-05 #> ballantines 6.528392e-04 -2.944984e-04 -5.656855e-04 1.789388e-04 #> bushmills 9.280815e-04 -4.013982e-04 -6.650163e-04 -5.644542e-04 #> chivas 1.300827e-04 -3.851168e-05 4.239507e-05 1.334791e-04 #> dalmore -2.964899e-04 -1.304289e-04 7.782306e-04 -4.877421e-04 #> famousgrouse 6.303902e-04 -1.322629e-04 -2.372041e-04 -2.550728e-05 #> glendronach -3.501431e-04 -2.525866e-04 3.742212e-04 1.133101e-04 #> glenmorangie -3.395833e-04 -4.246431e-04 -3.274667e-04 1.061570e-04 #> highlandpark 6.066669e-04 1.088092e-03 5.256719e-04 5.273203e-04 #> jackdaniels 1.023982e-03 9.323203e-04 1.214171e-03 5.898250e-04 #> jb 2.339479e-04 3.473492e-04 3.733691e-04 1.626720e-04 #> johnniewalker -8.686486e-04 -1.355694e-03 1.175580e-03 3.264915e-04 #> magallan 2.310078e-04 -1.038695e-04 -1.026307e-05 1.023165e-04 #> makersmark -5.037028e-04 -1.240866e-04 -7.956100e-05 -6.606345e-05 #> oban -3.076544e-04 -4.937905e-04 -1.310019e-05 -2.416906e-04 #> oldpotrero -5.717320e-04 -9.307817e-04 1.291075e-04 -5.512552e-04 #> redbreast -6.765261e-04 1.325618e-04 4.297985e-04 3.419357e-04 #> tamdhu -1.871447e-04 -1.524034e-04 6.923348e-05 -5.932353e-04 #> wildturkey -5.568095e-04 1.396939e-04 -3.130911e-04 -2.441291e-05 #> yoichi -1.807137e-04 -7.887244e-04 -4.647802e-04 -2.321719e-04 #> C9 C10 C11 C12 #> brahma -1.321861e-03 7.225736e-04 2.052451e-04 1.666890e-04 #> caney 4.837212e-04 -3.443095e-04 1.349160e-04 4.336526e-06 #> chimay -5.660053e-04 2.292011e-04 3.851391e-04 -2.066153e-05 #> corona 3.419355e-04 -4.427112e-05 5.053095e-04 2.703064e-04 #> deusventrue 5.149210e-05 4.983572e-04 -8.471361e-05 3.773608e-04 #> duvel 4.727181e-05 8.518990e-04 5.267156e-05 -7.761916e-06 #> franziskaner 4.052798e-04 2.307566e-04 5.425481e-04 8.822035e-04 #> grimbergen -4.235811e-04 -1.047152e-04 8.528320e-05 -4.862829e-04 #> guiness 2.578559e-05 -4.057230e-04 3.454914e-04 3.070080e-04 #> hoegardeen -2.093222e-04 -8.166019e-05 -5.849685e-04 -1.080950e-04 #> jupiler 3.426590e-04 1.476449e-04 3.134641e-04 2.698336e-04 #> kingfisher 1.267526e-04 2.565541e-04 -2.246671e-04 6.355569e-05 #> latrappe -4.351985e-06 -5.637614e-05 4.355069e-04 3.406179e-04 #> lindemanskriek -4.691485e-04 6.262551e-04 3.619995e-05 5.173449e-04 #> nicechouffe -2.084102e-04 4.207808e-04 7.211961e-05 -7.528575e-05 #> pecheresse -2.691263e-04 -5.693772e-04 -3.209598e-04 2.785471e-04 #> sierranevada 1.686643e-04 2.583335e-04 8.547137e-04 -1.139936e-04 #> tanglefoot 7.740523e-04 4.070373e-04 5.906937e-04 9.596081e-04 #> tauro -3.210499e-04 -2.265987e-04 5.213196e-05 1.560054e-07 #> westmalle 4.839335e-04 5.801730e-05 1.736045e-04 -1.456983e-04 #> amrut -1.864115e-04 -2.461486e-04 -3.925113e-04 -1.058934e-04 #> ballantines -5.195587e-04 3.044292e-04 -2.940957e-04 -8.254562e-05 #> bushmills -7.180710e-04 9.032786e-05 -3.120552e-04 3.338259e-04 #> chivas -3.525098e-05 -9.088640e-05 2.114664e-04 -4.123221e-05 #> dalmore 2.200639e-05 -1.248926e-04 -1.755355e-06 2.379108e-04 #> famousgrouse -3.212998e-04 3.215665e-04 -7.784050e-05 -5.945648e-04 #> glendronach 9.391914e-05 1.721023e-04 -5.496005e-04 -4.452810e-05 #> glenmorangie -1.452951e-05 2.274608e-05 8.210480e-05 2.227747e-04 #> highlandpark -1.043832e-04 2.593737e-04 7.274696e-06 -7.945600e-05 #> jackdaniels -6.541464e-05 8.873609e-04 3.142194e-04 5.911319e-04 #> jb -2.944987e-04 2.504811e-05 -2.127576e-05 -1.962938e-04 #> johnniewalker -8.111435e-05 -2.403699e-04 -1.403144e-03 -1.314933e-04 #> magallan 4.068423e-04 5.073294e-04 1.401801e-04 3.243760e-04 #> makersmark 4.971815e-04 6.070002e-04 1.442476e-05 -8.225582e-05 #> oban -1.976049e-04 -2.813942e-04 -2.577944e-04 -9.115022e-05 #> oldpotrero -5.682370e-04 1.529407e-07 -2.873197e-04 -1.840435e-04 #> redbreast -3.874401e-05 4.931648e-05 3.073398e-04 8.441133e-05 #> tamdhu -5.985664e-04 -4.647946e-04 -1.822017e-04 1.592463e-04 #> wildturkey 1.524887e-05 -6.414600e-04 2.874523e-04 -2.824274e-05 #> yoichi -2.834302e-04 1.556736e-04 -8.243757e-05 1.918715e-04 #> C13 C14 C15 C16 #> brahma -7.782826e-05 -1.930624e-05 3.379892e-04 -9.611430e-05 #> caney 5.571557e-05 1.585334e-04 -3.676568e-04 -2.424919e-04 #> chimay 2.069414e-04 -1.059161e-04 -5.895162e-05 -4.070464e-04 #> corona -3.358855e-05 3.794088e-04 7.431417e-05 7.851392e-04 #> deusventrue -2.738947e-04 7.547067e-04 2.411713e-04 2.337981e-04 #> duvel -2.899095e-04 1.153102e-04 4.201454e-04 -9.309399e-05 #> franziskaner 2.887549e-04 1.838704e-04 -1.076209e-04 -8.678411e-05 #> grimbergen -5.441140e-04 -1.117367e-04 8.398864e-05 4.536624e-06 #> guiness 1.002552e-04 4.035924e-04 4.794422e-04 -1.503013e-04 #> hoegardeen -6.620343e-04 -4.558427e-05 1.793707e-04 -2.548946e-04 #> jupiler 4.922288e-05 -5.590358e-08 1.921737e-04 -1.287978e-04 #> kingfisher -9.293274e-07 6.058292e-04 1.754447e-04 -1.321970e-04 #> latrappe 1.258799e-05 -4.563834e-04 -3.980325e-04 -3.632376e-05 #> lindemanskriek 3.942243e-05 1.639314e-04 3.621133e-04 2.603456e-05 #> nicechouffe 8.805995e-05 2.917660e-04 1.356673e-04 -1.709613e-04 #> pecheresse -4.861071e-04 -4.521904e-05 -4.938033e-05 1.569629e-04 #> sierranevada -2.667776e-04 5.072602e-05 -1.791841e-04 -7.011575e-05 #> tanglefoot 2.953027e-04 -9.831802e-06 -8.747989e-05 1.619364e-04 #> tauro -9.632911e-05 -9.375203e-05 -4.284123e-05 -2.047570e-04 #> westmalle -1.393513e-04 -1.584604e-04 -3.324221e-04 2.549518e-04 #> amrut 4.297953e-05 1.515928e-04 8.652384e-05 -1.182304e-04 #> ballantines 1.275977e-04 -1.152623e-04 -9.205056e-05 -4.163553e-09 #> bushmills -3.457626e-04 4.250469e-05 3.552076e-05 -5.053800e-04 #> chivas -1.777372e-04 -9.492327e-05 -2.055696e-04 5.817240e-05 #> dalmore 2.367824e-05 3.601473e-04 -1.802035e-04 -7.233793e-05 #> famousgrouse -5.629740e-04 1.716016e-04 4.970078e-04 1.638608e-04 #> glendronach -1.861826e-04 -2.166241e-04 -2.725060e-05 -2.919820e-04 #> glenmorangie 4.284188e-04 -3.059123e-04 1.548577e-07 5.323021e-05 #> highlandpark -5.202986e-05 -4.127667e-05 2.586090e-05 -1.032951e-04 #> jackdaniels 5.896938e-05 -4.375330e-04 4.011936e-04 2.314189e-04 #> jb -2.916919e-04 -5.900720e-04 -2.136720e-04 7.329517e-05 #> johnniewalker -1.479419e-04 3.073803e-04 3.149823e-04 3.938711e-04 #> magallan 1.154100e-04 2.200612e-04 3.321945e-04 7.696785e-05 #> makersmark 3.337325e-04 -1.068357e-05 4.436158e-04 1.721234e-04 #> oban -2.999197e-04 1.035791e-04 -1.810039e-04 -1.185358e-04 #> oldpotrero -5.099520e-04 -2.591210e-04 -1.489559e-04 -4.091994e-04 #> redbreast -1.790354e-04 -2.991022e-04 1.768442e-04 1.061400e-05 #> tamdhu 2.201204e-04 3.136042e-04 -7.139993e-05 -3.052562e-04 #> wildturkey -4.051933e-04 1.346852e-05 2.079652e-04 -1.649571e-04 #> yoichi -1.379502e-04 -2.627384e-04 2.209794e-04 4.497007e-05 #> C17 C18 C19 C20 #> brahma -2.462206e-05 4.542898e-05 2.594677e-04 1.484945e-04 #> caney -3.200717e-04 -2.643818e-04 1.448941e-04 -1.295417e-04 #> chimay 2.615626e-04 1.230016e-04 -2.602910e-04 4.566772e-04 #> corona 1.619221e-04 -1.010082e-04 -9.475160e-05 4.604978e-05 #> deusventrue 4.889298e-04 3.580373e-04 2.948538e-04 -2.065040e-05 #> duvel 2.191614e-04 8.201863e-05 5.854558e-06 -8.940682e-05 #> franziskaner -8.092666e-05 -6.457841e-05 -2.824789e-04 -3.859311e-04 #> grimbergen -3.961946e-04 3.650999e-05 3.213716e-04 1.180102e-04 #> guiness 2.115046e-04 1.749610e-04 -1.746358e-04 -1.581495e-04 #> hoegardeen 7.197760e-05 -2.012077e-04 -2.334965e-04 4.422896e-05 #> jupiler -2.008260e-05 -2.470511e-04 -1.663822e-04 -1.150708e-04 #> kingfisher -1.203436e-04 1.416556e-05 1.233551e-04 -1.424855e-04 #> latrappe -3.509800e-04 -3.539077e-04 -3.910480e-04 -1.488442e-04 #> lindemanskriek 4.564241e-04 6.139873e-05 2.472946e-04 -7.212713e-05 #> nicechouffe 2.088775e-05 -3.045093e-04 -4.116058e-05 9.187509e-05 #> pecheresse 3.099554e-04 -1.756667e-04 1.277428e-04 -9.767197e-05 #> sierranevada -2.374147e-04 1.934474e-04 3.562142e-04 -2.243221e-05 #> tanglefoot 2.693295e-04 -1.713949e-04 -4.543909e-05 -1.225435e-04 #> tauro -8.921517e-05 -3.763435e-05 2.081496e-05 5.772223e-05 #> westmalle -2.914399e-04 -1.082880e-04 -2.262683e-04 -1.303860e-04 #> amrut -2.450964e-04 -2.485646e-04 -1.839206e-04 -1.708371e-04 #> ballantines -1.568616e-04 -3.125000e-04 -5.701268e-05 -4.566974e-04 #> bushmills 4.389152e-04 1.152775e-04 -2.553003e-05 -2.255408e-04 #> chivas 7.206033e-05 -4.803968e-06 1.003524e-04 -5.006564e-05 #> dalmore -1.373879e-04 -3.425411e-04 1.887325e-04 -6.857783e-05 #> famousgrouse 1.098427e-04 3.769386e-04 -4.635939e-05 -4.732985e-04 #> glendronach 7.079193e-05 6.679345e-05 -1.471216e-05 -3.174342e-05 #> glenmorangie -2.887843e-04 3.663345e-06 8.615632e-05 1.443928e-04 #> highlandpark 4.361895e-05 -3.546641e-04 -2.543206e-04 -1.334150e-04 #> jackdaniels 6.397125e-04 3.132485e-04 -2.083165e-04 2.659526e-04 #> jb -1.357708e-05 6.999975e-06 1.014748e-04 1.390686e-04 #> johnniewalker 2.315024e-04 -7.245385e-04 -2.532287e-04 -1.843753e-04 #> magallan 2.912400e-04 2.959502e-04 2.326573e-04 2.930574e-04 #> makersmark -2.361525e-04 -2.818088e-05 4.879862e-04 3.105270e-05 #> oban -1.633058e-04 -9.438665e-05 1.228272e-04 3.653250e-05 #> oldpotrero 5.903880e-06 -3.358189e-04 1.091066e-04 3.691985e-04 #> redbreast -2.352497e-04 3.310177e-04 4.139320e-05 6.943862e-05 #> tamdhu -3.526671e-04 -1.708794e-04 -2.559883e-04 -1.303370e-04 #> wildturkey -1.566046e-04 3.186305e-04 -2.758046e-04 -4.246431e-05 #> yoichi 9.430638e-06 2.581787e-04 1.886038e-04 -4.095463e-05 #> C21 C22 C23 C24 #> brahma -2.357683e-04 -3.255489e-04 -3.888181e-05 1.601136e-04 #> caney 1.953747e-04 -2.101846e-04 -1.492333e-04 3.676434e-04 #> chimay -2.692597e-04 2.257056e-04 -1.397033e-05 -5.646081e-05 #> corona 1.999724e-04 6.189685e-05 -3.340597e-04 -1.953675e-04 #> deusventrue 1.591834e-04 -2.832760e-04 1.458864e-04 -8.427409e-05 #> duvel -2.955388e-04 -1.892748e-05 -2.437293e-04 -1.378691e-04 #> franziskaner -1.525330e-04 1.618032e-04 -5.139084e-05 -1.606879e-05 #> grimbergen 3.164260e-04 -1.221952e-05 1.167013e-04 3.467071e-04 #> guiness -3.339505e-04 -1.886574e-04 -2.230582e-04 -1.727871e-04 #> hoegardeen 1.874664e-04 1.600131e-04 1.958262e-04 -1.223848e-04 #> jupiler -1.957295e-04 1.587807e-04 -1.426824e-04 8.126834e-06 #> kingfisher -1.145588e-04 3.095102e-04 1.748363e-04 -2.958698e-05 #> latrappe -1.023105e-04 -4.186424e-04 -1.825023e-04 -3.951876e-05 #> lindemanskriek -1.380429e-04 -1.370311e-04 -1.728854e-04 1.500360e-04 #> nicechouffe -3.201139e-04 -4.944808e-04 -1.371930e-05 1.532805e-04 #> pecheresse 2.436237e-04 1.596311e-04 -2.128184e-04 3.576426e-04 #> sierranevada -1.687220e-05 -5.977664e-05 3.650123e-05 1.326880e-04 #> tanglefoot -3.427494e-04 -1.813205e-04 -4.801367e-05 5.543276e-06 #> tauro 9.933100e-05 7.064143e-05 2.098766e-04 6.374442e-05 #> westmalle 3.884283e-05 2.556888e-04 2.913800e-04 2.358729e-05 #> amrut -2.513723e-05 -4.865046e-05 6.915158e-05 9.554616e-05 #> ballantines -1.402023e-05 -1.177383e-04 -3.066781e-04 1.301059e-04 #> bushmills -1.016039e-04 -6.256814e-06 -2.782939e-05 -1.900221e-04 #> chivas -1.197585e-04 -2.656528e-05 -5.029721e-05 -7.452762e-05 #> dalmore 7.727193e-06 4.643119e-06 -1.397221e-04 1.462100e-04 #> famousgrouse -1.411842e-04 1.102486e-04 3.261561e-05 -1.482466e-04 #> glendronach 1.970525e-07 3.802927e-05 -1.079405e-04 -1.582899e-04 #> glenmorangie 8.129446e-05 3.967154e-05 -3.128011e-04 -1.635773e-05 #> highlandpark -1.802191e-04 -8.267955e-05 -1.275983e-04 1.323282e-04 #> jackdaniels -3.325901e-05 -3.256437e-05 -1.762269e-04 -5.790588e-04 #> jb -2.625235e-04 -1.667028e-04 -3.018992e-05 -5.868382e-05 #> johnniewalker -2.834732e-04 -4.393571e-04 -5.273623e-04 -5.014701e-04 #> magallan 6.945665e-05 -4.596990e-05 1.673075e-04 1.056113e-04 #> makersmark -5.032255e-04 -1.915835e-04 -7.805228e-05 2.830415e-04 #> oban 1.973869e-04 -5.481002e-05 1.739785e-05 8.027456e-05 #> oldpotrero 9.772372e-05 5.074158e-04 -1.364118e-04 1.254921e-04 #> redbreast 1.239392e-04 -8.674632e-05 1.488872e-04 -1.211999e-04 #> tamdhu 1.950283e-04 2.290251e-04 1.358859e-04 2.243632e-04 #> wildturkey 1.942568e-04 -2.562719e-04 1.268438e-04 1.317126e-04 #> yoichi -3.707432e-05 1.186764e-04 2.174843e-04 -1.334328e-04 #> C25 C26 C27 C28 #> brahma -2.168918e-04 5.311528e-06 -1.087851e-04 -1.129037e-04 #> caney 1.277543e-04 1.380997e-04 2.220567e-04 3.358853e-04 #> chimay -1.984526e-05 -2.262631e-04 9.411602e-05 -1.216533e-04 #> corona -1.099958e-04 -2.321293e-04 9.791988e-05 -3.093851e-04 #> deusventrue -3.818007e-04 -1.202012e-04 -8.165642e-05 -2.065725e-04 #> duvel 6.570113e-05 1.163622e-05 -1.505426e-04 -3.998066e-04 #> franziskaner 1.056867e-04 2.160659e-04 9.652675e-05 -1.456826e-04 #> grimbergen 1.243239e-04 2.355805e-04 1.329031e-04 2.166290e-04 #> guiness -3.127194e-04 -2.147014e-04 -9.180930e-05 6.054615e-06 #> hoegardeen -1.352939e-04 6.037898e-05 1.957805e-04 4.256147e-04 #> jupiler 1.463359e-04 -3.338668e-05 1.760442e-04 5.815076e-05 #> kingfisher 2.531356e-04 -2.597102e-04 -2.809453e-05 -1.026030e-04 #> latrappe 1.588111e-04 2.847210e-04 1.358552e-04 2.016904e-04 #> lindemanskriek 3.932121e-05 1.442253e-04 2.350166e-05 -2.638866e-05 #> nicechouffe -3.689553e-04 8.847560e-05 -7.805075e-05 -2.565099e-04 #> pecheresse 6.242504e-05 -2.132918e-04 -3.333979e-05 1.240727e-04 #> sierranevada -3.679124e-05 -9.493554e-05 -1.092878e-04 -2.741258e-05 #> tanglefoot -1.101320e-04 -2.362401e-04 -2.339105e-04 -1.321334e-04 #> tauro 8.184466e-05 6.090987e-05 -1.724211e-04 7.187784e-05 #> westmalle 1.390117e-04 -8.097500e-06 2.799535e-04 -2.956551e-05 #> amrut -9.040566e-06 1.628774e-04 4.928935e-05 1.955840e-04 #> ballantines -1.881555e-04 7.913061e-05 1.784297e-04 5.278585e-05 #> bushmills -1.882944e-04 2.576531e-04 1.135306e-04 7.203581e-05 #> chivas -1.217136e-05 1.459306e-04 -9.685215e-05 -2.166137e-04 #> dalmore -9.665762e-05 -1.115235e-05 -1.083964e-05 -1.765557e-04 #> famousgrouse 3.163937e-04 4.802734e-04 5.904108e-05 -6.039223e-05 #> glendronach -1.026367e-04 2.392065e-06 -6.767780e-05 4.176678e-05 #> glenmorangie 2.048456e-04 -1.662791e-04 2.088261e-04 1.762876e-04 #> highlandpark 1.294035e-04 1.854087e-04 1.168264e-04 2.134443e-05 #> jackdaniels -7.053449e-05 -2.075346e-04 -1.639481e-04 -1.499068e-04 #> jb 5.418975e-05 -8.534276e-05 -2.456867e-05 4.274040e-05 #> johnniewalker 1.110272e-04 3.863564e-04 5.023688e-04 4.238384e-04 #> magallan -1.464085e-04 8.875416e-05 -2.200694e-04 1.964866e-04 #> makersmark -5.747589e-05 -2.186057e-04 -4.321386e-04 -2.155324e-04 #> oban 1.759539e-04 1.294537e-04 -1.156101e-04 -1.182355e-04 #> oldpotrero 1.780324e-04 2.109986e-04 4.178527e-04 1.858207e-04 #> redbreast -1.305587e-04 -1.353161e-04 -5.952368e-05 -5.479947e-05 #> tamdhu 1.030517e-04 -1.192849e-04 -7.804091e-05 -1.508532e-04 #> wildturkey 1.934527e-04 3.215318e-04 1.288810e-06 7.522784e-05 #> yoichi -1.419941e-04 7.818576e-05 -1.276250e-05 1.358157e-04 #> C29 C30 C31 C32 #> brahma 5.059658e-05 -9.818126e-06 5.123235e-06 -1.428490e-04 #> caney 1.965508e-05 1.361109e-04 1.243089e-04 -1.336020e-04 #> chimay -9.070337e-05 -2.449328e-04 -6.708875e-05 4.022984e-05 #> corona 1.431245e-04 -2.173931e-04 -2.259074e-04 -2.787437e-04 #> deusventrue -1.783859e-04 -4.874278e-06 -3.212311e-04 -1.202210e-04 #> duvel -1.385701e-04 6.771122e-05 1.314672e-04 1.274480e-04 #> franziskaner -3.544520e-05 -1.570021e-04 4.143696e-05 -3.250007e-05 #> grimbergen 1.283964e-04 -1.619576e-04 -5.782503e-05 -7.440839e-05 #> guiness 1.623033e-04 1.124547e-04 1.457427e-04 2.620457e-04 #> hoegardeen 1.488354e-04 1.008707e-04 1.592857e-04 6.914513e-05 #> jupiler -1.025156e-04 -4.960354e-05 -5.397414e-05 1.393697e-05 #> kingfisher -2.551041e-04 -7.819386e-05 -4.231436e-04 1.136672e-05 #> latrappe 4.093292e-04 5.106237e-04 4.749064e-04 4.502392e-04 #> lindemanskriek -3.724973e-05 -8.158519e-05 -2.793628e-05 -2.304596e-04 #> nicechouffe -3.182117e-04 8.423888e-05 2.658457e-04 -1.540389e-04 #> pecheresse 1.880359e-04 1.197157e-04 2.589766e-04 3.113602e-04 #> sierranevada 1.574300e-05 -1.339857e-04 -3.371716e-05 2.780362e-05 #> tanglefoot -1.327847e-04 -1.552258e-04 -1.073922e-04 1.602931e-05 #> tauro -2.269286e-04 1.424808e-05 -1.177695e-05 4.677918e-05 #> westmalle 1.383318e-04 1.593729e-04 1.948654e-05 -1.302536e-04 #> amrut 1.270967e-04 -4.365482e-06 6.464597e-05 -1.148550e-04 #> ballantines 6.405210e-05 1.648409e-05 1.047806e-04 1.061185e-04 #> bushmills -8.378647e-05 2.595240e-05 -5.337516e-05 7.165584e-05 #> chivas 1.016956e-04 6.725272e-06 5.441987e-05 1.470306e-04 #> dalmore 1.881831e-04 1.517540e-04 7.488225e-05 2.682798e-05 #> famousgrouse -2.725213e-05 3.255800e-05 -5.556833e-05 -2.891368e-05 #> glendronach 3.820905e-05 2.432726e-05 6.797367e-05 -7.383064e-05 #> glenmorangie -2.481661e-04 -5.482361e-05 8.139003e-05 5.261718e-05 #> highlandpark 2.797181e-05 6.660466e-05 1.954252e-04 1.378264e-05 #> jackdaniels -1.941603e-04 -7.448475e-05 -1.546534e-04 -1.620665e-04 #> jb 1.500695e-04 1.005877e-04 -2.723725e-06 5.583773e-05 #> johnniewalker 5.239015e-05 4.615600e-05 1.840488e-04 4.954225e-04 #> magallan -2.830981e-05 -3.374251e-04 -1.457816e-05 1.537940e-04 #> makersmark 2.276041e-04 2.168941e-04 1.270890e-04 -8.071940e-05 #> oban -9.838630e-05 1.646660e-04 1.708445e-04 4.611304e-05 #> oldpotrero 2.634114e-04 1.184883e-05 1.039594e-04 1.387515e-04 #> redbreast -1.449013e-04 1.984628e-05 -1.465977e-04 -8.637397e-05 #> tamdhu -1.684881e-05 -1.183542e-04 2.023348e-04 2.682289e-04 #> wildturkey -5.207759e-05 -1.906513e-04 -1.833178e-04 -2.062892e-04 #> yoichi -1.389330e-05 -4.418834e-05 5.367797e-05 -6.039718e-05 #> D1 D2 D3 D4 D5 #> brahma 0.2937120 -0.04602927 0.05240292 -0.035768593 0.03999516 #> caney 0.3046235 -0.07069129 0.05062805 -0.011400633 0.04383297 #> chimay 0.4156841 -0.09356117 0.04692603 -0.019249436 0.03965332 #> corona 0.2745921 -0.05755121 0.05150878 -0.011252954 0.03689351 #> deusventrue 0.3149661 -0.11964363 0.05529900 0.007135060 0.03861865 #> duvel 0.4496172 -0.09170033 0.05080071 -0.024018306 0.03036868 #> franziskaner 0.3002734 -0.05637154 0.04411627 -0.030282997 0.03014850 #> grimbergen 0.3651919 -0.09065897 0.05082210 -0.010242594 0.04317369 #> guiness 0.3505997 -0.08196508 0.04422914 -0.022614638 0.04330972 #> hoegardeen 0.2945708 -0.06921001 0.05080275 -0.012677940 0.04146196 #> jupiler 0.2872499 -0.06835188 0.05058090 -0.011055591 0.04109503 #> kingfisher 0.3038732 -0.06930174 0.04366992 -0.021888850 0.03308585 #> latrappe 0.4672257 -0.08743553 0.04401705 -0.038810531 0.02809569 #> lindemanskriek 0.3008112 -0.08389446 0.04783652 -0.013888395 0.04157982 #> nicechouffe 0.3127453 -0.09102591 0.04393446 -0.019927059 0.03779695 #> pecheresse 0.2877918 -0.07053519 0.05180968 -0.009320568 0.04090001 #> sierranevada 0.3773035 -0.07825101 0.05234901 -0.021705236 0.03981425 #> tanglefoot 0.4079636 -0.09801072 0.04110270 -0.028374451 0.04305818 #> tauro 0.2869165 -0.06868727 0.05072815 -0.010829946 0.04098501 #> westmalle 0.2901614 -0.07168182 0.04932024 -0.012449351 0.03886788 #> amrut 0.2916508 -0.07148727 0.03950517 -0.025866432 0.04086520 #> ballantines 0.4617826 -0.07263052 0.04705459 -0.054513278 0.00386769 #> bushmills 0.3159155 -0.02993821 0.05271205 -0.040523047 0.01619821 #> chivas 0.4010304 -0.12319740 0.04665481 -0.003452339 0.05226216 #> dalmore 0.4148687 -0.14805699 0.04396881 -0.010373143 0.05369374 #> famousgrouse 0.3082730 -0.05984603 0.04245023 -0.038145717 0.02994654 #> glendronach 0.2880496 -0.06941189 0.04010808 -0.026119002 0.04146027 #> glenmorangie 0.2784428 -0.06974209 0.02918920 -0.025306813 0.04836028 #> highlandpark 0.4216191 -0.07914764 0.04537064 -0.044351756 0.02868104 #> jackdaniels 0.3474874 -0.08171102 0.04501412 -0.023326513 0.04362364 #> jb 0.2978504 -0.07724044 0.04167029 -0.021228975 0.04549082 #> johnniewalker 0.3097702 -0.04720860 0.04457306 -0.040162288 0.02378800 #> magallan 0.2790080 -0.04764937 0.01811567 -0.036589697 0.02988117 #> makersmark 0.3905990 -0.12195322 0.04665759 0.014950483 0.04867625 #> oban 0.2773362 -0.07277254 0.03313763 -0.023775433 0.04405146 #> oldpotrero 0.3550787 -0.13906787 0.05059907 0.008348999 0.04726562 #> redbreast 0.3884532 -0.13265717 0.04117925 -0.003816545 0.05332588 #> tamdhu 0.2956700 -0.06219547 0.04086923 -0.024902731 0.04397834 #> wildturkey 0.3186215 -0.08962249 0.03633236 -0.023651702 0.05160018 #> yoichi 0.3745590 -0.07064336 0.04209729 -0.040564238 0.03281077 #> D6 D7 D8 D9 #> brahma 1.156917e-02 1.544573e-02 0.0013278090 0.0017860170 #> caney 4.485691e-03 9.597789e-03 0.0016029758 0.0082459711 #> chimay 1.731744e-02 1.044446e-02 0.0104067305 0.0026404547 #> corona -4.664986e-03 9.465002e-03 0.0001838085 0.0120730321 #> deusventrue -8.770510e-04 1.356919e-02 0.0076757796 0.0034745699 #> duvel 1.486796e-02 7.642213e-03 0.0154756340 0.0060020330 #> franziskaner 1.266218e-03 1.748451e-02 0.0047455611 0.0067787344 #> grimbergen 7.100085e-03 6.253179e-03 0.0076965820 0.0090999349 #> guiness 9.543784e-03 9.549881e-03 0.0017249204 0.0017518501 #> hoegardeen 2.601196e-03 1.267815e-02 0.0028528664 0.0079320590 #> jupiler 2.215650e-03 1.160311e-02 0.0034969489 0.0080290760 #> kingfisher 2.046087e-03 1.149394e-02 0.0039224376 0.0069746627 #> latrappe 2.444196e-02 2.163781e-02 0.0204539980 -0.0001441159 #> lindemanskriek 2.496230e-03 1.222294e-02 0.0053531769 0.0062723553 #> nicechouffe 3.314725e-03 1.247704e-02 0.0066425182 0.0051531928 #> pecheresse 2.471297e-03 1.468476e-02 0.0056123765 0.0084044229 #> sierranevada 1.057630e-02 8.974816e-03 0.0026404084 0.0003673360 #> tanglefoot 1.902021e-02 1.046530e-02 0.0039430719 -0.0033493172 #> tauro 2.321158e-03 1.173141e-02 0.0034750116 0.0079425387 #> westmalle 1.786521e-03 1.515342e-02 0.0060316179 0.0079388255 #> amrut 6.369733e-03 1.572832e-02 -0.0038463793 0.0013700406 #> ballantines 4.344419e-03 1.645402e-02 0.0254142957 0.0095935791 #> bushmills -1.167929e-02 2.000745e-02 0.0117755165 0.0158424792 #> chivas 7.036241e-03 -4.363041e-03 0.0063540528 0.0079672331 #> dalmore 1.718407e-02 -6.837798e-03 0.0070735547 -0.0019258037 #> famousgrouse 4.059251e-03 2.229183e-02 0.0037608752 0.0010406075 #> glendronach 6.223170e-03 1.521132e-02 -0.0043261577 0.0013210684 #> glenmorangie 5.822448e-03 1.976818e-02 -0.0044147538 0.0033213121 #> highlandpark 1.979571e-02 2.717259e-02 0.0200795294 -0.0021232596 #> jackdaniels 1.186579e-02 1.329499e-02 -0.0005343742 -0.0016003714 #> jb 6.441694e-03 1.187397e-02 -0.0057652170 0.0017868329 #> johnniewalker 8.789822e-05 2.661158e-02 0.0128165570 0.0105593342 #> magallan 6.181261e-03 2.628647e-02 0.0002557046 0.0036531313 #> makersmark -5.885380e-03 -3.124763e-04 0.0123974490 0.0123986615 #> oban 7.290747e-03 1.526810e-02 -0.0064234752 0.0024990961 #> oldpotrero -1.263673e-03 9.106123e-06 0.0131403235 0.0062358607 #> redbreast 7.554115e-03 -5.549155e-03 0.0028962725 0.0066649976 #> tamdhu 7.609569e-03 1.817766e-02 -0.0043937269 0.0004398248 #> wildturkey 1.072078e-02 1.329394e-02 -0.0045720419 -0.0006442784 #> yoichi 1.665764e-02 2.932085e-02 0.0147708913 0.0009353830 #> D10 D11 D12 D13 #> brahma 0.006789017 0.0048196384 0.007143143 1.926114e-03 #> caney 0.011464283 0.0039468981 0.003663644 -7.807175e-04 #> chimay 0.012590865 0.0018154608 0.002625857 -8.084753e-04 #> corona 0.008346831 0.0027556006 0.002567053 5.432929e-04 #> deusventrue 0.006022626 0.0007085549 0.005811255 2.407200e-04 #> duvel 0.014318246 0.0021405582 -0.001168779 -3.377569e-03 #> franziskaner 0.007215285 0.0030768626 0.006498196 8.028161e-04 #> grimbergen 0.013935311 0.0016133249 0.001782113 -1.816164e-03 #> guiness 0.013609736 0.0052742301 0.006464424 -5.287655e-04 #> hoegardeen 0.007661150 0.0026973921 0.005420800 9.995327e-04 #> jupiler 0.007523271 0.0027339312 0.004363034 1.338460e-03 #> kingfisher 0.006826146 0.0028630395 0.005290393 2.293278e-03 #> latrappe 0.007468498 -0.0011091276 0.003570302 2.011317e-03 #> lindemanskriek 0.007494807 0.0009831097 0.006687031 1.442627e-03 #> nicechouffe 0.007804735 0.0010554318 0.006544953 1.205823e-03 #> pecheresse 0.006507851 0.0023044001 0.005130825 6.852104e-04 #> sierranevada 0.013424754 0.0060565295 0.007716962 -7.405564e-04 #> tanglefoot 0.012760316 0.0055315212 0.008787267 1.064633e-03 #> tauro 0.007452360 0.0026002512 0.004223806 1.378572e-03 #> westmalle 0.005389195 0.0009150318 0.004619774 1.262124e-03 #> amrut 0.008090140 0.0077694214 0.009648834 -1.144556e-03 #> ballantines 0.009641210 -0.0013505569 0.001193993 7.396074e-04 #> bushmills 0.012190958 0.0027373737 0.003932980 -3.732204e-03 #> chivas 0.019338356 0.0019726115 0.002305432 -2.020219e-03 #> dalmore 0.016575636 0.0049437344 0.004000701 5.545799e-03 #> famousgrouse 0.003906640 0.0019458696 0.010187413 3.371833e-03 #> glendronach 0.008581179 0.0087430642 0.009902698 -6.391147e-04 #> glenmorangie 0.007165778 0.0033642678 0.009454943 -1.032963e-03 #> highlandpark 0.003043362 -0.0045393480 0.006887804 5.658900e-03 #> jackdaniels 0.009896143 0.0071305091 0.011652937 1.190034e-03 #> jb 0.011312129 0.0089093269 0.008895351 -2.914444e-03 #> johnniewalker 0.004724823 -0.0013880745 0.003178167 -3.556457e-04 #> magallan -0.002901850 0.0030725685 0.006182579 4.129056e-03 #> makersmark 0.007706173 -0.0025568628 0.002741739 2.566683e-03 #> oban 0.007789470 0.0092615797 0.008856510 -4.461327e-04 #> oldpotrero 0.009884923 0.0004827760 0.006465018 2.203812e-03 #> redbreast 0.019010171 0.0030489037 0.003575003 -1.081990e-03 #> tamdhu 0.006990252 0.0067355151 0.011091059 -3.536949e-05 #> wildturkey 0.012225665 0.0056575767 0.009083087 -3.677090e-03 #> yoichi 0.001967838 -0.0043542059 0.006408266 2.324685e-03 #> D14 D15 D16 D17 #> brahma 0.0031275641 4.157794e-04 0.0019555535 9.890925e-04 #> caney 0.0037093445 1.744155e-03 0.0009874891 -4.753255e-04 #> chimay 0.0009166164 2.220375e-03 -0.0019270610 2.484912e-04 #> corona 0.0058977403 1.606741e-03 0.0024960621 -7.639544e-04 #> deusventrue 0.0033919410 1.559680e-04 0.0015420583 9.082901e-04 #> duvel -0.0029313189 2.502233e-03 0.0006963735 1.208427e-03 #> franziskaner 0.0041872022 9.225601e-04 0.0024966790 6.722121e-04 #> grimbergen 0.0019309787 1.956568e-03 0.0005450639 2.675718e-04 #> guiness 0.0018638986 2.692559e-03 0.0019352055 1.628688e-03 #> hoegardeen 0.0041552095 -1.065713e-04 0.0016889222 -3.166547e-04 #> jupiler 0.0033244959 9.848065e-05 0.0010603264 -6.525507e-05 #> kingfisher 0.0044673616 1.485094e-03 0.0023979578 6.894989e-04 #> latrappe -0.0008074752 1.664147e-03 -0.0021635248 7.689496e-04 #> lindemanskriek 0.0037615312 2.793989e-04 0.0016614073 1.352472e-03 #> nicechouffe 0.0038551513 1.311255e-03 0.0016680702 1.116012e-03 #> pecheresse 0.0025371633 -4.489783e-04 0.0008704132 -5.554931e-04 #> sierranevada 0.0005939006 1.474160e-03 0.0011437155 1.682900e-03 #> tanglefoot 0.0004785330 2.150301e-03 -0.0002248900 2.139070e-03 #> tauro 0.0033835451 1.001149e-04 0.0009107426 8.944532e-05 #> westmalle 0.0047945932 5.279402e-04 0.0014031914 -1.127039e-03 #> amrut 0.0006242293 -2.060446e-03 0.0027509103 2.295153e-03 #> ballantines 0.0026091729 2.944401e-03 0.0009597037 1.625268e-03 #> bushmills 0.0008108204 -1.658834e-03 0.0022376452 1.816720e-03 #> chivas -0.0003126890 3.062126e-03 0.0003784012 3.895628e-03 #> dalmore -0.0013721769 4.301123e-03 -0.0007346094 1.919821e-03 #> famousgrouse 0.0051280464 -2.095871e-03 -0.0014353739 -1.017602e-03 #> glendronach 0.0007605817 -2.608913e-03 0.0025423072 1.881103e-03 #> glenmorangie 0.0055043581 -3.529733e-04 0.0026449765 8.745923e-04 #> highlandpark 0.0046886634 2.790613e-03 -0.0028451046 -2.803900e-04 #> jackdaniels 0.0006010724 -1.874443e-03 -0.0001609028 1.721536e-03 #> jb 0.0006629365 -6.083868e-04 0.0040546060 2.647929e-03 #> johnniewalker 0.0052579368 -1.293010e-04 0.0022216234 -3.827680e-04 #> magallan 0.0055039424 -8.305055e-04 0.0012832388 -1.151480e-03 #> makersmark 0.0044651474 6.602691e-04 0.0009437839 -7.127560e-04 #> oban 0.0017261768 -1.145758e-03 0.0039396292 1.243568e-03 #> oldpotrero 0.0012186435 2.697974e-03 0.0002678611 1.879572e-03 #> redbreast 0.0008746647 3.392975e-03 0.0003544991 3.091612e-03 #> tamdhu 0.0033713850 -1.628121e-03 0.0024278166 1.560397e-03 #> wildturkey 0.0022983366 8.120105e-04 0.0033344198 2.666378e-03 #> yoichi 0.0060672149 1.801036e-03 0.0002647738 -5.632091e-05 #> D18 D19 D20 D21 #> brahma 6.293376e-04 3.896704e-04 -3.229345e-04 3.831138e-06 #> caney -7.645439e-04 -6.085621e-04 -3.245536e-04 -4.503156e-04 #> chimay -1.130345e-04 7.926418e-04 -1.780914e-04 -4.887150e-04 #> corona 1.024423e-03 8.842135e-05 4.313700e-04 -4.718718e-04 #> deusventrue -3.583324e-04 1.286906e-03 6.233120e-05 1.544907e-03 #> duvel -5.922990e-04 -1.333335e-04 4.815197e-04 -1.758102e-04 #> franziskaner 6.100396e-04 7.764117e-04 5.491195e-05 3.763780e-04 #> grimbergen -5.904705e-04 4.253926e-04 -2.173942e-04 5.361111e-04 #> guiness -6.191811e-04 -7.865923e-05 -7.407169e-04 -3.602892e-04 #> hoegardeen 5.654900e-04 3.283770e-05 -1.864209e-04 4.023209e-04 #> jupiler 3.689686e-04 -1.719041e-04 1.184231e-04 2.651784e-04 #> kingfisher 1.154506e-03 1.020985e-03 3.611220e-04 6.291875e-04 #> latrappe -2.088876e-03 -1.536620e-03 -1.005470e-03 -1.438940e-03 #> lindemanskriek -6.671207e-05 5.595716e-04 -6.809755e-04 2.883840e-04 #> nicechouffe -4.176123e-04 8.977287e-04 -5.825859e-04 2.514060e-04 #> pecheresse 2.960996e-04 -2.999634e-04 -5.143676e-04 5.298199e-04 #> sierranevada -1.402891e-03 -7.105184e-04 -1.406023e-03 -3.241741e-04 #> tanglefoot -4.466706e-04 1.003752e-03 -2.824955e-04 -4.366636e-04 #> tauro 5.077672e-04 -2.475905e-04 3.158794e-04 1.327427e-04 #> westmalle -4.447622e-04 3.776294e-04 4.195911e-04 8.484127e-04 #> amrut 2.150217e-03 1.310537e-03 5.423311e-04 1.191027e-03 #> ballantines -2.305305e-04 2.030836e-03 1.037686e-03 1.381778e-03 #> bushmills 1.883389e-03 1.671736e-03 1.085006e-03 1.129204e-03 #> chivas -7.487816e-04 -1.848059e-04 -7.542402e-04 -6.898937e-05 #> dalmore 1.853381e-03 -1.461692e-03 1.339406e-03 -6.406724e-04 #> famousgrouse 5.138360e-04 2.530545e-03 2.024220e-03 2.987046e-03 #> glendronach 2.040387e-03 1.241204e-03 4.021827e-04 1.360769e-03 #> glenmorangie 3.519697e-04 2.012743e-03 -9.903207e-04 1.364138e-03 #> highlandpark -2.634427e-03 -2.315674e-04 -8.854821e-04 -4.633894e-04 #> jackdaniels 6.015905e-04 9.398945e-04 -3.644850e-04 2.828080e-05 #> jb 9.951060e-04 8.239419e-04 -2.467022e-04 1.277872e-03 #> johnniewalker 1.083550e-03 1.030500e-03 1.236037e-03 2.082887e-03 #> magallan 2.235758e-03 1.613033e-03 2.732296e-03 1.761473e-03 #> makersmark -4.496665e-04 9.336664e-04 5.524012e-04 9.525012e-04 #> oban 2.228455e-03 -3.486102e-05 -4.580932e-05 6.453033e-04 #> oldpotrero -9.114012e-04 1.132774e-03 5.301941e-04 1.186192e-04 #> redbreast -1.950436e-04 9.281282e-04 -5.109409e-04 -7.237943e-06 #> tamdhu 9.609204e-04 1.925977e-03 -8.205987e-04 3.847804e-04 #> wildturkey -8.344240e-04 2.028382e-03 -1.207846e-03 1.686608e-03 #> yoichi -2.196066e-03 1.676181e-04 -1.415373e-03 1.009761e-03 #> D22 D23 D24 D25 #> brahma -6.023925e-04 -3.704707e-04 -8.677815e-04 -7.248682e-04 #> caney -1.173466e-03 -3.863544e-04 -1.351268e-03 -1.773197e-04 #> chimay -6.522348e-04 -7.978252e-04 -5.495898e-06 -1.800777e-03 #> corona -8.788427e-04 -4.830025e-05 -5.870134e-04 7.484502e-04 #> deusventrue 1.415082e-05 7.733248e-04 3.116257e-05 -6.374096e-04 #> duvel -2.941583e-04 -1.124154e-03 -1.118860e-03 -1.186668e-03 #> franziskaner -3.051374e-04 2.712854e-04 -3.334307e-04 6.527762e-05 #> grimbergen -3.660470e-04 -2.386308e-04 -7.363064e-04 -1.136209e-03 #> guiness -9.874371e-04 -2.115403e-04 -6.115358e-04 -1.042320e-03 #> hoegardeen -7.912932e-04 -6.136135e-05 -9.776025e-04 1.670660e-04 #> jupiler -5.807125e-04 -2.182125e-04 -5.863223e-04 -8.468729e-05 #> kingfisher -1.199056e-04 1.361850e-04 -3.033656e-04 -2.821181e-04 #> latrappe 4.653398e-04 -1.234463e-03 1.614692e-04 -4.335716e-04 #> lindemanskriek -7.295737e-04 4.368240e-06 -5.637679e-05 -1.888630e-04 #> nicechouffe -3.296172e-04 1.792659e-04 -2.905989e-04 -3.368342e-04 #> pecheresse -4.971391e-04 -1.135830e-05 -4.110029e-04 -2.045514e-04 #> sierranevada -6.684311e-04 -3.811855e-04 -4.383820e-04 -5.675429e-04 #> tanglefoot -9.195349e-05 -2.817236e-04 4.991349e-04 -3.507131e-04 #> tauro -7.745611e-04 1.012546e-04 -3.658760e-04 -1.334307e-04 #> westmalle -8.336006e-04 -5.476468e-05 -1.129115e-03 4.607603e-04 #> amrut 3.325703e-04 8.672648e-04 9.145089e-05 7.931481e-04 #> ballantines 6.627349e-04 -3.615268e-04 3.731327e-04 -2.763657e-04 #> bushmills 4.431144e-04 9.888128e-04 1.365332e-06 -1.032528e-04 #> chivas 1.495921e-03 -7.915520e-04 2.552716e-04 -1.400881e-03 #> dalmore 8.620998e-04 5.358565e-04 -2.205899e-04 8.854910e-04 #> famousgrouse 9.740031e-04 7.164023e-04 -5.641393e-04 -5.141442e-04 #> glendronach 6.069209e-04 1.250594e-03 3.418042e-04 8.590618e-04 #> glenmorangie -7.256586e-04 5.892879e-04 -1.846707e-04 -2.215014e-04 #> highlandpark 7.715184e-04 -1.223845e-04 8.942889e-04 -9.207978e-04 #> jackdaniels -7.403164e-05 5.163499e-04 2.071492e-05 2.953354e-04 #> jb 1.765633e-04 1.058650e-03 4.504999e-04 2.865430e-04 #> johnniewalker -8.526645e-05 8.983395e-04 -1.003037e-03 3.799430e-05 #> magallan 7.106320e-04 5.758546e-04 -6.188574e-04 2.465923e-04 #> makersmark -9.846482e-04 -2.252128e-04 -7.251905e-04 5.910814e-04 #> oban -1.589051e-04 1.386830e-03 1.430748e-04 6.763321e-04 #> oldpotrero 5.368851e-04 -3.892557e-04 8.146966e-04 -5.819797e-04 #> redbreast 1.204642e-03 -3.265974e-04 4.350358e-04 -4.717577e-04 #> tamdhu -1.558475e-03 -2.944087e-05 -3.153143e-04 9.049911e-05 #> wildturkey -2.598572e-05 8.017668e-04 7.628013e-04 -5.490242e-04 #> yoichi -5.700515e-05 5.679827e-04 1.700043e-04 -7.948749e-04 #> D26 D27 D28 D29 #> brahma -6.395018e-04 -4.053179e-04 -2.320532e-04 -3.997015e-04 #> caney -2.359438e-04 -2.059137e-04 -5.363116e-05 -5.687334e-04 #> chimay -1.367853e-03 -1.301151e-03 -1.233134e-03 -5.067907e-04 #> corona -5.900023e-04 4.867919e-04 -1.429390e-04 4.416367e-04 #> deusventrue -5.512986e-04 -9.265221e-04 -4.809160e-04 -5.674634e-04 #> duvel -6.434708e-04 -3.994538e-04 -2.003070e-04 -2.293221e-04 #> franziskaner -1.310487e-04 2.683871e-04 8.363468e-06 1.249318e-04 #> grimbergen -1.063777e-03 -1.567251e-03 -9.309061e-04 -1.203667e-03 #> guiness -4.237703e-04 -5.863080e-04 2.091300e-04 -1.398699e-04 #> hoegardeen -4.936265e-04 -3.031387e-04 -5.517384e-04 -6.863028e-04 #> jupiler -4.169136e-04 -2.806707e-04 -4.552180e-04 -5.632157e-04 #> kingfisher -5.282998e-04 -1.829135e-04 -5.253247e-04 -3.984768e-04 #> latrappe -2.182854e-05 6.079916e-04 -3.061676e-04 5.585698e-04 #> lindemanskriek -1.286669e-04 -3.587153e-04 -9.683567e-05 -3.789208e-04 #> nicechouffe -3.874500e-05 -6.006549e-04 1.047084e-04 4.153977e-05 #> pecheresse -4.871025e-04 -5.084450e-04 -6.217106e-04 -9.046258e-04 #> sierranevada -5.253493e-04 -9.103329e-04 -1.472245e-04 -6.919569e-04 #> tanglefoot -2.793185e-04 -9.121267e-04 -5.073682e-04 -7.915067e-04 #> tauro -3.810949e-04 -1.473809e-04 -5.954522e-04 -6.992086e-04 #> westmalle -3.036718e-05 4.895830e-05 -5.574292e-04 -1.059941e-03 #> amrut -6.925384e-05 -6.528198e-06 -7.195273e-04 -4.489611e-04 #> ballantines 5.806837e-04 -4.643040e-05 -1.345115e-04 -4.098110e-04 #> bushmills -9.920516e-04 -6.515162e-04 -9.939962e-04 -7.524942e-04 #> chivas -5.786515e-04 -5.643790e-04 -9.594352e-04 1.266319e-04 #> dalmore -2.071692e-04 9.919664e-05 -6.494984e-04 -8.782649e-04 #> famousgrouse -9.831707e-04 -2.574344e-04 3.023649e-04 1.759037e-04 #> glendronach -3.720452e-04 -6.702764e-04 -1.204797e-03 -6.332506e-04 #> glenmorangie 1.026999e-04 -4.035989e-04 8.014678e-04 -2.994170e-07 #> highlandpark -9.684691e-04 -1.380908e-03 -1.108075e-03 -2.124353e-04 #> jackdaniels -9.776790e-04 -7.222094e-04 -5.648930e-04 -6.747195e-04 #> jb -3.242447e-04 -6.974717e-04 -1.963078e-04 -2.453221e-05 #> johnniewalker -6.179291e-04 -4.241837e-04 -5.206066e-04 -8.604953e-04 #> magallan -1.348410e-04 3.236837e-04 3.675421e-04 4.734675e-04 #> makersmark -1.584742e-04 -7.659618e-04 -1.350651e-03 -1.228912e-03 #> oban -6.637215e-04 5.201189e-05 -4.165461e-04 8.882533e-05 #> oldpotrero -2.942613e-04 -5.427166e-04 -9.393213e-04 -4.784414e-04 #> redbreast 3.593234e-04 -1.693602e-04 -3.678528e-05 6.092724e-05 #> tamdhu 1.211206e-05 -7.018532e-04 1.418592e-05 -7.508705e-04 #> wildturkey 8.160391e-04 -5.939476e-04 2.147085e-04 -2.764873e-04 #> yoichi -4.611316e-04 -1.449003e-03 -3.131254e-04 -7.590933e-04 #> D30 D31 D32 #> brahma -3.902515e-04 -4.657627e-04 -4.591314e-04 #> caney -9.850469e-05 3.166971e-05 1.112523e-04 #> chimay -8.560520e-04 -4.323199e-04 9.946603e-05 #> corona 2.091023e-04 -7.157752e-05 -1.300100e-04 #> deusventrue 1.040810e-04 -8.204937e-04 -5.065759e-04 #> duvel -3.433012e-05 3.583444e-04 3.946036e-04 #> franziskaner -9.090693e-05 -3.654028e-04 -3.017993e-04 #> grimbergen -9.676903e-04 -7.092697e-04 -3.309973e-04 #> guiness -3.334034e-04 -4.702548e-05 1.426591e-04 #> hoegardeen -7.249966e-04 -8.858153e-04 -4.275584e-04 #> jupiler -5.485198e-04 -6.030643e-04 -3.822469e-04 #> kingfisher -4.201484e-04 -5.266630e-04 -1.660344e-04 #> latrappe -1.877748e-04 3.063740e-04 1.703602e-04 #> lindemanskriek -3.260925e-04 -2.780105e-04 -1.944023e-04 #> nicechouffe 3.820829e-04 -4.094818e-05 -2.591452e-05 #> pecheresse -5.103713e-04 -5.697029e-04 -3.993520e-04 #> sierranevada -2.174311e-04 -6.020258e-04 -5.489893e-04 #> tanglefoot -1.002316e-03 -1.046716e-03 -1.052470e-03 #> tauro -6.452311e-04 -5.544896e-04 -3.477609e-04 #> westmalle -4.824287e-04 -9.388615e-04 2.676913e-04 #> amrut -4.766425e-04 -6.277056e-04 -5.517415e-04 #> ballantines -4.625130e-04 -2.404349e-04 -7.489670e-04 #> bushmills -4.214640e-04 -1.678949e-04 1.042195e-04 #> chivas -9.372331e-04 -9.431970e-05 -5.353796e-04 #> dalmore -7.460785e-04 -1.279118e-03 -9.370873e-04 #> famousgrouse 1.304132e-04 -4.899982e-05 5.462999e-04 #> glendronach -3.515166e-04 -2.249163e-04 -1.682467e-04 #> glenmorangie 1.997467e-04 6.023239e-05 -2.466944e-04 #> highlandpark -3.607922e-04 2.362905e-04 -2.757210e-04 #> jackdaniels -2.447913e-04 -1.353065e-03 -5.253405e-04 #> jb -1.147366e-04 -3.104326e-04 -2.916444e-04 #> johnniewalker -6.281539e-04 -1.083614e-03 -2.760545e-04 #> magallan -3.536734e-04 -1.159514e-04 -4.591237e-04 #> makersmark 7.536380e-04 -2.134843e-04 1.025659e-04 #> oban 2.608163e-04 -3.330292e-04 -4.077367e-04 #> oldpotrero -5.492801e-04 -3.007036e-04 -1.206675e-03 #> redbreast -1.042452e-03 -4.929570e-04 -1.024011e-03 #> tamdhu -5.359179e-04 -4.648454e-04 1.256245e-04 #> wildturkey -4.068468e-04 -2.847724e-04 -5.372963e-04 #> yoichi -1.141095e-04 -2.989495e-04 -6.093731e-04 # if you want, say the first 8 harmonics but not the first one retain <- coeff_sel(retain=8, drop=1, nb.h=32, cph=4) head(coe[, retain]) #> A2 A3 A4 A5 A6 #> brahma 0.006766531 0.09348184 0.01374288 0.023818571 0.008592275 #> caney 0.007368844 0.09542847 0.01449765 0.022207326 0.006665955 #> chimay 0.016535135 0.07571705 0.02736989 0.009876978 0.014306122 #> corona 0.007486279 0.09616977 0.01220177 0.022887407 0.007281456 #> deusventrue 0.019627538 0.09281761 0.02230953 0.015264921 0.014857953 #> duvel 0.022177771 0.06895598 0.03354560 0.009316683 0.021131541 #> A7 A8 B2 B3 B4 #> brahma 0.003183571 0.005158502 -0.0001900652 3.306231e-04 -0.0005191749 #> caney 0.003552709 0.007010166 0.0005012013 -3.851293e-04 0.0003333918 #> chimay -0.004741288 0.007814037 0.0001843629 4.196107e-04 0.0003227901 #> corona 0.005504589 0.007852411 -0.0003586724 1.711055e-05 -0.0005501057 #> deusventrue 0.002521451 0.011391904 0.0001774985 -8.326845e-05 -0.0014033732 #> duvel -0.001687129 0.011025502 -0.0004198782 7.447638e-05 -0.0006627095 #> B5 B6 B7 B8 #> brahma 1.067446e-04 -9.218905e-05 5.604686e-07 6.268503e-06 #> caney -2.899903e-04 7.350207e-05 -4.952054e-04 8.536695e-05 #> chimay -2.906714e-05 5.573360e-04 1.059517e-04 6.209192e-04 #> corona -1.907425e-04 -4.256287e-04 -2.147013e-04 -1.931107e-04 #> deusventrue -3.240180e-04 -9.330047e-04 6.515692e-04 -8.354423e-04 #> duvel 6.107940e-05 -4.746985e-04 2.450959e-04 -1.676532e-04 #> C2 C3 C4 C5 #> brahma -0.0016375711 -3.936895e-03 0.0054080962 -1.259407e-03 #> caney 0.0012398277 -2.845651e-04 0.0003757825 -4.017802e-05 #> chimay -0.0037576080 -1.797357e-03 -0.0021279238 -4.663387e-04 #> corona -0.0016528639 1.573302e-03 0.0004897281 1.867708e-04 #> deusventrue 0.0015527752 7.706329e-04 -0.0014164476 1.463377e-03 #> duvel 0.0002872128 -5.422392e-06 -0.0007785717 3.178998e-04 #> C6 C7 C8 D2 D3 #> brahma -3.994402e-03 3.268582e-03 0.0004792269 -0.04602927 0.05240292 #> caney 4.699805e-04 2.518166e-04 0.0006300072 -0.07069129 0.05062805 #> chimay -7.424827e-05 -8.096453e-05 0.0009946667 -0.09356117 0.04692603 #> corona 6.888736e-04 3.145355e-04 0.0005189042 -0.05755121 0.05150878 #> deusventrue 9.055123e-04 -2.834923e-04 -0.0014439096 -0.11964363 0.05529900 #> duvel 2.219253e-04 5.438377e-04 -0.0000035189 -0.09170033 0.05080071 #> D4 D5 D6 D7 D8 #> brahma -0.03576859 0.03999516 0.011569168 0.015445729 0.0013278090 #> caney -0.01140063 0.04383297 0.004485691 0.009597789 0.0016029758 #> chimay -0.01924944 0.03965332 0.017317438 0.010444458 0.0104067305 #> corona -0.01125295 0.03689351 -0.004664986 0.009465002 0.0001838085 #> deusventrue 0.00713506 0.03861865 -0.000877051 0.013569192 0.0076757796 #> duvel -0.02401831 0.03036868 0.014867959 0.007642213 0.0154756340"},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"coeff_split returns named list coordinates vector harmonic coefficients. instance, harmonic coefficients arranged $coe slot Coe-objects way: \\(A_1, \\dots, A_n, B_1, \\dots, B_n, C_1, \\dots, C_n, D_1, \\dots, D-n\\) elliptical Fourier analysis (see efourier efourier) \\(C_n D_n\\) harmonic absent radii variation tangent angle approaches (see rfourier tfourier respectively). function used internally might interest elwewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"","code":"coeff_split(cs, nb.h = 8, cph = 4)"},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"cs vector harmonic coefficients. nb.h numeric. maximum harmonic rank. cph numeric. Must set 2 rfourier tfourier used.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"Returns named list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coeff_split.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Converts a numerical description of harmonic coefficients to a named list. — coeff_split","text":"","code":"coeff_split(1:128, nb.h=32, cph=4) # efourier #> $an #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 #> [26] 26 27 28 29 30 31 32 #> #> $bn #> [1] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 #> [26] 58 59 60 61 62 63 64 #> #> $cn #> [1] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 #> [26] 90 91 92 93 94 95 96 #> #> $dn #> [1] 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 #> [20] 116 117 118 119 120 121 122 123 124 125 126 127 128 #> coeff_split(1:64, nb.h=32, cph=2) # t/r fourier #> $an #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 #> [26] 26 27 28 29 30 31 32 #> #> $bn #> [1] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 #> [26] 58 59 60 61 62 63 64 #>"},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":null,"dir":"Reference","previous_headings":"","what":"Some color palettes — color_palettes","title":"Some color palettes — color_palettes","text":"Colors, colors, colors.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Some color palettes — color_palettes","text":"","code":"col_summer(n) col_summer2(n) col_spring(n) col_autumn(n) col_black(n) col_solarized(n) col_gallus(n) col_qual(n) col_heat(n) col_hot(n) col_cold(n) col_sari(n) col_india(n) col_bw(n) col_grey(n)"},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Some color palettes — color_palettes","text":"n number colors generate color palette","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Some color palettes — color_palettes","text":"colors (hexadecimal format)","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Some color palettes — color_palettes","text":"Among available color palettes, col_solarized based Solarized: https://ethanschoonover.com/solarized/; col_div, col_qual, col_heat, col_cold col_gallus based ColorBrewer2: https://colorbrewer2.org/.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_palettes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Some color palettes — color_palettes","text":"","code":"wheel <- function(palette, n=10){ op <- par(mar=rep(0, 4)) ; on.exit(par(op)) pie(rep(1, n), col=palette(n), labels=NA, clockwise=TRUE)} # Qualitative wheel(col_qual) wheel(col_solarized) wheel(col_summer) wheel(col_summer2) wheel(col_spring) wheel(col_autumn) # Divergent wheel(col_gallus) wheel(col_india) # Sequential wheel(col_heat) wheel(col_hot) wheel(col_cold) wheel(col_sari) wheel(col_bw) wheel(col_grey) # Black only for pubs wheel(col_black)"},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":null,"dir":"Reference","previous_headings":"","what":"Transparency helpers and palettes — col_transp","title":"Transparency helpers and palettes — col_transp","text":"ease transparency handling.","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transparency helpers and palettes — col_transp","text":"","code":"col_transp(n, col = \"#000000\", ceiling = 1) col_alpha(cols, transp = 0)"},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transparency helpers and palettes — col_transp","text":"n number colors generate col color hexadecimal format generate levels transparency ceiling maximal opacity (0 1) cols colors, provided hexadecimal values transp numeric 0 1, value transparency obtain","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transparency helpers and palettes — col_transp","text":"colors","code":""},{"path":"http://momx.github.io/Momocs/reference/color_transparency.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transparency helpers and palettes — col_transp","text":"","code":"x <- col_transp(10, col='#000000') x #> [1] \"#000000f0\" \"#0000001c\" \"#00000038\" \"#00000055\" \"#00000071\" \"#0000008d\" #> [7] \"#000000aa\" \"#000000c6\" \"#000000e2\" \"#000000ff\" barplot(1:10, col=x, main='a transparent black is grey') summer10 <- col_summer(10) summer10 #> [1] \"#4876FF\" \"#7094C6\" \"#99B28D\" \"#C2D155\" \"#EAEF1C\" \"#FFE805\" \"#FFBA0F\" #> [8] \"#FF8C1A\" \"#FF5E25\" \"#FF3030\" summer10.transp8 <- col_alpha(summer10, 0.8) summer10.transp8 #> [1] \"#4876FF32\" \"#7094C632\" \"#99B28D32\" \"#C2D15532\" \"#EAEF1C32\" \"#FFE80532\" #> [7] \"#FFBA0F32\" \"#FF8C1A32\" \"#FF5E2532\" \"#FF303032\" summer10.transp2 <- col_alpha(summer10, 0.8) summer10.transp2 #> [1] \"#4876FF32\" \"#7094C632\" \"#99B28D32\" \"#C2D15532\" \"#EAEF1C32\" \"#FFE80532\" #> [7] \"#FFBA0F32\" \"#FF8C1A32\" \"#FF5E2532\" \"#FF303032\" x <- 1:10 barplot(x, col=summer10.transp8) barplot(x/2, col=summer10.transp2, add=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":null,"dir":"Reference","previous_headings":"","what":"Combine several objects — combine","title":"Combine several objects — combine","text":"Combine Coo objects slicing, either manual using slice chop. Note Coo object, combines row-wise (ie, merges shapes c ) ; Coe combines column-wise (merges coefficients). latter case, Coe must number shapes (necessarily number coefficients). Also $fac first Coe retrieved. separate version may come point.","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Combine several objects — combine","text":"","code":"combine(...)"},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Combine several objects — combine","text":"... list (Coe), Opn(Coe), Ldk objects (class)","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Combine several objects — combine","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Combine several objects — combine","text":"Note order shapes coefficients checked, anything number rows merged.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/combine.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Combine several objects — combine","text":"","code":"w <- filter(bot, type==\"whisky\") b <- filter(bot, type==\"beer\") combine(w, b) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk # or, if you have many levels bot_s <- chop(bot, ~type) bot_s$whisky #> Out (outlines) #> - 20 outlines, 158 +/- 23 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows #> - also: $ldk # note that you can apply something (single function or a more # complex pipe) then combine everyone, since combine also works on lists # eg: # bot_s2 <- efourier(bot_s, 10) # equivalent to lapply(bot_s, efourier, 10) # bot_sf <- combine(bot_s2) # pipe style efourier(bot_s, 10) %>% combine() #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> An OutCoe object [ combined: efourier + efourier analyses ] #> -------------------- #> - $coe: 20 outlines described, and (total) 80 coefficients #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows"},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert complex to/from cartesian coordinates — complex","title":"Convert complex to/from cartesian coordinates — complex","text":"Convert complex /cartesian coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert complex to/from cartesian coordinates — complex","text":"","code":"cpx2coo(Z) coo2cpx(coo)"},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert complex to/from cartesian coordinates — complex","text":"Z coordinates expressed complex form coo coordinates expressed cartesian form","code":""},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert complex to/from cartesian coordinates — complex","text":"coordinates expressed cartesian/complex form","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/complex.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert complex to/from cartesian coordinates — complex","text":"","code":"shapes[4] %>% # from cartesian coo_sample(24) %>% coo2cpx() %T>% # to complex cpx2coo() # and back #> [1] 200+ 62i 205+ 43i 176+ 43i 146+ 44i 156+ 23i 186+ 20i 202+ 15i 172+ 9i #> [9] 143+ 16i 130+ 45i 135+ 74i 133+104i 142+134i 165+160i 191+182i 203+210i #> [17] 225+226i 239+204i 238+178i 237+150i 227+120i 221+ 91i 224+ 62i 219+ 45i"},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns coordinates — coo_align","title":"Aligns coordinates — coo_align","text":"Aligns coordinates along longer axis using var-cov matrix eigen values.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns coordinates — coo_align","text":"","code":"coo_align(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns coordinates — coo_align","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns coordinates — coo_align","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_align.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns coordinates — coo_align","text":"","code":"coo_plot(bot[1]) coo_plot(coo_align(bot[1])) # on a Coo b <- bot %>% slice(1:5) # for speed sake stack(coo_align(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes along their 'calliper length' — coo_aligncalliper","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"returns registered bookstein coordinates. See coo_bookstein.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"","code":"coo_aligncalliper(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_aligncalliper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes along their 'calliper length' — coo_aligncalliper","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(coo_aligncalliper(b)) b <- bot %>% slice(1:5) # for speed sake bot.al <- coo_aligncalliper(b) stack(bot.al)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes using their shortest radius — coo_alignminradius","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"returns slided first coordinate east. May used aligning strategy shapes clear 'invaginate' part.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"","code":"coo_alignminradius(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_alignminradius.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes using their shortest radius — coo_alignminradius","text":"","code":"b <- bot %>% slice(1:5) # for speed sake stack(coo_alignminradius(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":null,"dir":"Reference","previous_headings":"","what":"Aligns shapes along the x-axis — coo_alignxax","title":"Aligns shapes along the x-axis — coo_alignxax","text":"Align longest axis shape along x-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aligns shapes along the x-axis — coo_alignxax","text":"","code":"coo_alignxax(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aligns shapes along the x-axis — coo_alignxax","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aligns shapes along the x-axis — coo_alignxax","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Aligns shapes along the x-axis — coo_alignxax","text":"shapes upside-(mirror others), try redefining new starting point (eg coo_slidedirection) alignment step. may solve problem coo_calliper orders $arr.ind used coo_aligncalliper.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_alignxax.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Aligns shapes along the x-axis — coo_alignxax","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(coo_alignxax(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the angle of every edge of a shape — coo_angle_edges","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"Returns angle (radians) every edge shape,","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"","code":"coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1]) # S3 method for default coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1]) # S3 method for Coo coo_angle_edges(coo, method = c(\"atan2\", \"acos\")[1])"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"coo matrix list (x; y) coordinates Coo method 'atan2' ('acos') signed () angle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"numeric angles radians every edge.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"coo_thetapts deprecated removed future releases.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_angle_edges.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the angle of every edge of a shape — coo_angle_edges","text":"","code":"b <- coo_sample(bot[1], 64) coo_angle_edges(b) #> [1] -3.111523 -3.093172 -3.092305 3.081724 3.105229 3.077881 3.110353 #> [8] 3.046641 3.051196 3.135756 -3.074763 -3.017238 -2.926235 -2.628633 #> [15] -2.611156 -2.953906 -3.017238 -3.085049 -2.915581 -2.709056 -2.530867 #> [22] -2.927854 -3.086548 -3.100971 3.114884 -3.060821 3.116579 -3.106746 #> [29] 3.131759 3.116579 3.080363 3.030147 3.035444 3.141593 -3.051196 #> [36] -3.014394 -2.988492 -2.873097 -3.131789 2.993915 2.944112 -3.135728 #> [43] 3.113711 3.137875 -3.106026 3.106746 2.980423 -1.981456 -2.694480 #> [50] -3.062770 -2.583631 -2.029263 3.018319 3.023726 -3.109950 3.085522 #> [57] -3.087530 3.112543 2.978918 3.011861 3.087633 -2.957901 -2.916681 #> [64] -3.046946"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"Calculated using complex numbers returned radians minus first one (modulo 2*pi).","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"","code":"coo_angle_tangent(coo) # S3 method for default coo_angle_tangent(coo) # S3 method for Coo coo_angle_tangent(coo) coo_tangle(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"coo matrix coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"numeric, tangent angle along perimeter, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_angle_tangent.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the tangent angle along the perimeter of a\nshape — coo_angle_tangent","text":"","code":"b <- bot[1] phi <- coo_angle_tangent(b) phi2 <- coo_angle_tangent(coo_smooth(b, 2)) plot(phi, type='l') plot(phi2, type='l', col='red') # ta is very sensible to noise # on Coo bot %>% coo_angle_tangent #> $brahma #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $caney #> [1] 0.00000000 0.06226874 0.07482722 6.17098557 0.04973765 6.19585440 #> [7] 6.15845448 6.12105457 6.08365466 5.94658609 6.00885483 6.02141332 #> [13] 5.93405501 5.89665510 5.81167208 5.92152392 5.68478671 5.74705545 #> [19] 5.75961393 5.67225562 5.43746015 5.54749740 5.56005588 5.61331586 #> [25] 5.53521445 5.54752480 5.41045623 5.27338767 5.43532506 5.29825650 #> [31] 5.16118793 5.22345667 5.36591026 5.24832550 5.43300749 5.27125258 #> [37] 5.70474653 5.98185092 6.06880600 6.09653125 6.19140174 6.22285831 #> [43] 0.00000000 6.24578539 0.02486883 6.27065422 0.05494594 0.01233774 #> [49] 0.07266474 0.03526482 0.18097573 0.05452623 0.23276803 0.36301056 #> [55] 0.63366343 0.80375974 1.24653486 0.91207073 0.88384487 1.03466647 #> [61] 0.99726655 0.95986664 1.02213538 0.88506682 0.89762530 0.81026699 #> [67] 0.57547152 0.73546717 0.69806725 0.76033599 0.52359878 0.87732431 #> [73] 0.54846760 0.31367213 0.47366778 0.43626787 0.30820807 0.36146804 #> [79] 0.22439948 0.48406378 0.19930991 0.21186839 0.17446848 0.13706857 #> [85] 0.09966865 6.25479416 0.12453748 6.17098557 6.13358566 6.24581279 #> [91] 6.15845448 0.03526482 0.04544802 0.22671705 0.07444053 0.15191722 #> [97] 0.32561064 0.07711740 6.15071198 6.19274656 5.88412401 5.84672410 #> [103] 5.80460724 5.96371242 5.73452436 5.54749740 5.75745144 5.52265597 #> [109] 5.63414601 5.44785615 5.41045623 5.56127783 5.33565641 5.29825650 #> [115] 5.40974653 5.22345667 5.18605676 5.24832550 5.30865249 4.87646146 #> [121] 4.77913339 5.19645276 5.06132594 4.80714863 5.08425302 5.57609989 #> [127] 6.00234758 6.24578539 6.11065857 6.27065422 6.23325431 0.11006465 #> [133] 0.16672597 0.49891243 0.95304135 1.23419711 1.51513480 1.06167038 #> [139] 1.93029230 1.18426612 1.14686620 0.91207073 0.97239773 0.93499781 #> [145] 0.99726655 0.81097669 0.92246673 0.70521332 0.74799825 0.71059834 #> [151] 0.77286708 0.58657722 0.69806725 0.46327178 0.62326743 0.43697757 #> [157] 0.54846760 0.29239874 0.42370938 0.23887231 0.10741116 6.22179942 #> [163] 5.93251249 5.95912756 6.10959968 6.06842620 6.16619699 6.22285831 #> #> $chimay #> [1] 0.000000000 6.183372777 6.150128410 6.241239038 6.083639677 6.050395310 #> [7] 6.141505938 5.859551582 5.950662210 5.917417843 5.884173476 5.709032055 #> [13] 5.942039737 5.908795371 5.893093064 5.717951643 5.684707276 5.775817904 #> [19] 5.760115597 5.584974176 5.427374815 5.376588388 5.485241076 5.730296368 #> [25] 5.418752342 5.509862970 5.352263609 5.319019242 5.285774876 5.376885504 #> [31] 5.219286142 5.186041776 5.152797409 5.261450097 5.331287339 5.177419303 #> [37] 5.378590612 5.606825061 6.119235749 6.027235560 6.098868132 0.016854134 #> [43] 6.249253014 6.233550707 0.041476028 0.008231661 6.116275547 6.224928235 #> [49] 5.913384209 0.153553853 5.880216472 6.091950768 0.020499758 6.025462035 #> [55] 6.116572663 6.100870356 6.050083929 6.016839563 6.001137256 6.070974498 #> [61] 6.037730131 6.081257656 5.971241398 6.051789038 6.123421610 0.394994540 #> [67] 0.695548337 0.847651921 0.814407554 0.781163187 0.747918820 0.714674454 #> [73] 0.681430087 0.648185720 0.614941354 0.706051982 0.548452620 0.515208254 #> [79] 0.357608892 0.448719520 0.415475153 0.506585781 0.348986420 0.315742053 #> [85] 0.282497687 0.249253320 0.216008953 0.182764587 0.149520220 0.116275853 #> [91] 0.083031486 0.294765783 0.016542753 6.266483693 6.233239327 0.049361185 #> [97] 6.166750593 6.133506227 6.100261860 6.067017493 6.033773127 6.000528760 #> [103] 5.967284393 6.058395021 6.025150654 6.145850952 0.109720934 6.264710169 #> [109] 0.003779000 6.253719940 6.137956619 0.005149272 5.993611396 6.160195675 #> [115] 5.973243779 5.939999412 5.860633930 5.873510679 5.794145196 5.760900829 #> [121] 5.493240787 5.854787540 5.547375722 5.514131355 5.578932266 5.327018953 #> [127] 5.311316647 5.494945896 5.227285853 5.069686492 5.178339180 5.003197759 #> [133] 4.261327120 4.936709025 5.027819653 5.115198955 5.115275584 4.661834504 #> [139] 3.874431807 5.058993379 5.580056509 5.882779748 6.208306052 6.175061685 #> [145] 6.141817318 6.108572952 6.075328585 6.042084218 6.008839851 6.253895144 #> [151] 6.066706113 0.089569053 0.885173745 1.201536502 1.740485780 0.818761641 #> [157] 0.785517274 0.872896576 0.964007204 1.625501114 0.897518471 0.864274104 #> [163] 0.706674743 0.673430376 0.622643949 0.486317974 0.573697276 0.306037233 #> [169] 0.434167977 0.320019511 0.286775145 0.286851774 0.139815400 0.060449917 #> [175] 0.307742342 6.218390668 0.120629940 6.210657758 6.063159063 0.020896840 #> [181] 5.996670329 6.123801407 6.068821333 5.952435735 6.024068307 5.790995295 #> [187] 5.911458457 6.038127214 6.125506516 #> #> $corona #> [1] 0.000000000 0.093190192 6.280085533 0.095445119 6.230254910 6.181548048 #> [7] 6.132841185 6.084134322 6.035427459 5.986720596 5.938013733 5.889306870 #> [13] 5.840600008 5.791893145 5.743186282 5.694479419 5.645772556 5.597065693 #> [19] 5.548358831 5.821402522 5.450945105 5.402238242 5.353531379 5.304824516 #> [25] 5.256117653 5.404806350 5.158703928 5.200656952 5.524937811 6.100866371 #> [31] 0.054091936 6.164215386 0.253742423 0.105366907 0.056660045 0.007953182 #> [37] 0.139099819 0.015416395 0.041686093 0.255499953 0.626588922 1.286508331 #> [43] 1.049579963 1.189094606 1.140387743 1.041722484 1.042974017 0.994267154 #> [49] 0.945560292 0.896853429 0.848146566 0.799439703 0.750732840 0.702025977 #> [55] 0.653319114 0.604612252 0.555905389 0.507198526 0.458491663 0.409784800 #> [61] 0.361077937 0.312371075 0.263664212 0.214957349 0.166250486 0.026883736 #> [67] 0.121419822 0.020129897 6.254608342 0.064613226 0.195759863 0.022698006 #> [73] 0.317015084 0.191536329 6.196110346 5.913660302 5.864953439 5.816246576 #> [79] 5.767539713 5.718832851 5.769794640 5.621419125 5.721602210 5.524005399 #> [85] 5.672694096 5.568488728 5.575280370 5.238518061 5.429361033 5.498016271 #> [91] 5.380452919 5.229302203 5.085643634 4.848715265 5.279686702 5.030182932 #> [97] 5.431235682 0.129720339 0.081013476 0.032306613 6.266785058 0.271567707 #> [103] 1.748439146 1.210879929 1.162173066 1.729086092 1.262154900 1.163489642 #> [109] 0.701093565 1.116034312 0.801075400 1.018620586 0.870245071 0.599456306 #> [115] 0.772831345 0.728841428 0.556417326 0.626710756 0.677672546 0.628965683 #> [121] 0.580258820 0.531551957 0.285449535 0.434138232 0.004924992 6.239403436 #> [127] 6.064104446 6.173725084 6.120798837 #> #> $deusventrue #> [1] 0.00000000 6.22214668 6.18080993 6.23594696 6.17968595 6.11625336 #> [7] 6.21501833 6.19495497 6.13234484 6.16078710 6.07094474 6.22700355 #> [13] 6.18566681 6.14433006 6.10299332 6.06165657 6.02031983 6.08964030 #> [19] 6.13504189 5.89630959 5.90755591 5.81363610 5.88295657 5.83063126 #> [25] 5.78929451 5.70087218 5.70662102 5.66528428 5.52427888 5.68033769 #> [31] 5.63900095 0.01313872 0.29355253 0.22469980 0.46420077 0.41187546 #> [37] 0.48119594 0.38727613 0.28786522 0.25751705 0.31584895 0.27451221 #> [43] 0.23317546 0.19183872 0.25017063 0.20883388 0.06782848 0.36316656 #> [49] 0.64619816 1.05096696 1.21595411 1.33227243 1.28572740 1.24959894 #> [55] 1.20826219 1.10999222 1.22525735 0.96525166 1.09000080 1.10124712 #> [61] 0.95503343 1.01857363 0.87756823 0.93590014 0.67589445 0.85322665 #> [67] 0.81188990 0.52557449 0.72921641 0.68787966 0.85403914 0.60520617 #> [73] 0.66353808 0.67913456 0.67859150 0.71080604 0.68997924 0.73769208 #> [79] 0.68674024 0.69273654 0.73601867 0.51358927 0.65760048 0.44584005 #> [85] 0.53147609 0.37948212 0.27661179 0.26556880 0.15980522 0.15260155 #> [91] 0.07713172 6.16132522 6.13097705 6.14413176 6.03731499 6.05291147 #> [97] 6.07364179 5.81363610 5.66164213 5.73096261 5.68962586 5.64828912 #> [103] 5.60695237 5.56561563 5.62394753 5.37228491 5.29271544 5.40026864 #> [109] 5.41151496 5.31759515 5.49492735 5.07831979 5.48504171 5.97466645 #> [115] 0.10706565 6.25986463 0.31584895 0.47190777 0.61368184 0.91066872 #> [121] 1.52390274 1.77963021 1.27985414 1.33996435 1.93645770 1.22315778 #> [127] 1.64795003 1.62933664 1.49548128 1.34926759 1.30793085 1.26659410 #> [133] 1.22525735 0.96525166 1.52309024 0.90385156 0.95503343 0.79990468 #> [139] 0.87756823 0.78701019 0.64958473 0.65583109 0.61449434 0.30690555 #> [145] 0.52172018 0.39642287 0.32479236 0.31374938 0.27241263 0.15164139 #> [151] 0.15944538 0.16891234 #> #> $duvel #> [1] 0.00000000 0.05163389 0.01260790 1.54437823 6.21774121 5.98131966 #> [7] 6.13968922 6.10066322 6.06163723 1.31022225 5.98358524 5.94455924 #> [13] 5.90553325 5.86650725 5.82748125 1.07606628 5.74942926 5.71040327 #> [19] 5.67137727 5.63235128 5.59332528 0.84191030 5.51527329 5.47624729 #> [25] 5.43722130 5.39819530 0.64678033 5.22948342 5.28111731 5.24209132 #> [31] 5.46931737 5.59066682 0.41262435 5.87138550 6.23725129 0.20488648 #> [37] 0.16586048 0.12683449 0.17846838 0.04878249 6.20374819 0.06139039 #> [43] 6.21488981 6.26652371 6.22749771 6.18847171 6.14944572 6.11041972 #> [49] 6.16205361 6.03236773 5.99334174 6.13416924 6.00594963 6.07365931 #> [55] 5.83723775 5.79821176 6.10795677 0.37897450 0.54211730 0.74986529 #> [61] 0.80003291 5.56405578 0.81264081 0.77361481 0.73458882 0.69556282 #> [67] 0.65653682 5.32989981 0.57848483 0.53945884 0.50043284 0.46140685 #> [73] 5.13476983 0.38335485 0.34432886 0.30530286 0.26627687 0.22725087 #> [79] 4.90061386 0.14919888 0.11017289 0.07114689 0.03212089 6.27628021 #> [85] 4.66645788 6.19822821 6.15920222 6.21083611 6.08115023 6.13278412 #> [91] 4.43230191 6.06374089 6.19129829 6.23479125 0.06315567 4.23717193 #> [97] 0.11455324 6.15654376 6.03966127 5.83171777 5.71250693 4.00301596 #> [103] 5.62544617 5.76201234 5.88336179 5.84433579 6.00747859 3.76885998 #> [109] 5.91135628 5.76095104 5.60308470 5.36340583 5.14452633 3.53470401 #> [115] 4.71770333 4.93678846 5.25467440 4.85873646 3.33957403 4.69149086 #> [121] 5.12377516 5.46803331 5.75833348 6.01978465 3.10541805 6.11732483 #> [127] 6.16895872 6.22059261 0.23434891 0.35669803 2.87126208 0.79779215 #> [133] 0.95616171 1.44963982 0.96450827 0.92548228 2.63710611 1.20713728 #> [139] 1.33702879 0.84956314 0.64395375 2.44197613 0.56590176 0.18240185 #> [145] 0.01628675 0.21572910 0.32727882 2.20782015 0.21749145 0.26751504 #> [151] 0.42928595 0.30106634 0.35123396 1.97366418 0.01507085 6.04127195 #> [157] 5.95824921 6.10332168 6.11041680 1.73950821 6.23301769 #> #> $franziskaner #> [1] 0.00000000 6.23251446 6.18184361 6.13117276 6.08050191 6.02983106 #> [7] 6.17655577 5.92848936 5.87781851 5.82714766 5.77647681 5.72580597 #> [13] 5.67513512 5.62446427 5.57379342 5.52312257 5.47245172 5.42178087 #> [19] 5.37111002 5.32043917 5.26976832 5.21909747 5.06354968 5.11775577 #> [25] 5.11704332 5.11608273 5.28749378 5.75305360 6.07121890 6.09307021 #> [31] 6.23890445 5.92441464 6.13756275 6.18184361 0.06665640 6.12808501 #> [37] 6.22722662 6.21290339 0.02581043 0.43878719 0.84850663 0.96441918 #> [43] 0.92275710 1.06241479 0.91207529 0.86140444 0.81073359 0.76006274 #> [49] 0.70939189 0.65872104 0.60805019 0.55737934 0.50670849 0.45603764 #> [55] 0.40536679 0.35469594 0.30402510 0.25335425 0.20268340 0.15201255 #> [61] 0.10134170 0.05067085 0.00000000 6.23251446 6.18184361 6.13117276 #> [67] 6.08050191 6.02983106 5.97916021 5.97844776 6.14407056 5.97603761 #> [73] 6.04272886 5.98312968 5.94138717 5.88178798 5.84004547 5.81457936 #> [79] 5.76390851 5.74353142 5.60485320 5.61189597 5.50351150 5.51055427 #> [85] 5.31032368 5.21742443 5.20898198 5.01641408 4.91816012 4.59332182 #> [91] 5.01329148 4.81373068 4.81301823 6.23322691 6.05266096 6.18184361 #> [97] 6.22183265 6.18017056 1.21777343 1.41566118 0.86732938 1.47130840 #> [103] 1.11475868 1.06408783 0.66464598 0.81385619 0.91207529 0.60408072 #> [109] 0.72007370 0.42338792 0.43109223 0.46132548 0.24407123 0.23562879 #> [115] 0.21525170 0.13428709 0.12706714 0.15730038 0.07028191 6.24508276 #> [121] 0.15510029 6.23780230 6.24262995 0.05067085 #> #> $grimbergen #> [1] 0.000000000 6.130874904 6.278403913 6.228537363 6.178670813 6.128804263 #> [7] 6.078937713 6.128739816 5.888544726 6.029006716 5.879471513 5.829604963 #> [13] 5.779738413 5.729871863 5.680005313 5.630138763 5.580272213 5.530405663 #> [19] 5.480539112 5.430672562 5.380806012 5.378522566 5.380741565 5.321866249 #> [25] 5.459639471 5.806214204 5.966673528 6.265861669 0.089631132 0.031396576 #> [31] 0.169751531 0.029225094 0.022435328 0.020151881 6.253470638 0.015370487 #> [37] 0.050405731 6.245768043 0.062275925 0.069723584 0.314587140 0.843244804 #> [43] 0.944753698 0.858539527 0.951756270 0.992549607 0.942683057 0.892816507 #> [49] 0.842949957 0.702423520 0.643548205 0.693350307 0.643483757 0.593617207 #> [55] 0.543750657 0.493884107 0.444017557 0.394151007 0.344284457 0.294417907 #> [61] 0.344220009 0.194684806 0.144818256 0.094951706 0.045085156 0.042801710 #> [67] 6.228537363 0.075339006 0.151497827 0.295099128 0.333888459 0.306745270 #> [73] 0.145499478 0.001177992 5.929273615 5.977133973 5.777454966 5.770665200 #> [79] 5.827534323 5.722169267 5.879176666 5.725517776 5.610526062 5.672262807 #> [85] 5.472836517 5.460926412 5.330875015 5.039442758 4.624374758 5.347858761 #> [91] 5.310039821 3.930223399 5.073904116 6.104165835 0.020216329 0.070018431 #> [97] 0.020151881 6.253470638 6.203604088 6.253406191 0.842932605 1.560284404 #> [103] 1.911998394 1.008139177 0.994620248 1.860979257 1.092282707 1.042416157 #> [109] 0.795154048 0.754461552 0.712963007 0.609206776 0.595687847 0.563363357 #> [115] 0.495954747 0.552823870 0.593617207 0.496167554 0.493884107 0.063511180 #> [121] 0.030172050 5.952728822 5.966877249 6.028389942 6.097363737 6.149703905 #> #> $guiness #> [1] 0.000000000 6.248850961 6.214516615 6.180182269 6.145847923 6.111513577 #> [7] 6.077179232 6.167199880 5.884155545 6.098531188 5.939841848 5.905507502 #> [13] 5.871173156 5.836838810 5.802504464 5.768170118 5.733835772 5.699501426 #> [19] 5.665167080 5.630832734 5.596498388 5.562164042 5.527829696 5.610604095 #> [25] 5.459161005 5.424826659 5.390492313 5.356157967 5.321823621 5.009189616 #> [31] 5.253154929 5.218820583 5.184486237 5.150151891 5.334486491 5.205838194 #> [37] 5.479556629 5.798212671 5.961273885 5.894692656 6.235629133 6.124522896 #> [43] 0.004398803 6.253249764 6.232613191 6.184581072 6.274601721 6.240267375 #> [49] 6.205933029 6.171598683 6.199683147 6.102929991 6.179252866 6.034261299 #> [55] 6.244905616 0.041177970 6.162348928 6.141902578 0.222905371 0.454823074 #> [61] 0.522932582 0.688426881 1.012863205 0.978528859 0.944194513 0.909860167 #> [67] 0.875525821 0.965546470 1.051835793 0.772522784 0.738188438 0.703854092 #> [73] 0.669519746 0.635185400 0.600851054 0.566516708 0.532182362 0.497848016 #> [79] 0.463513670 0.429179324 0.176176032 0.360510632 0.326176286 0.291841940 #> [85] 0.257507595 0.223173249 0.188838903 0.154504557 0.120170211 0.085835865 #> [91] 0.051501519 6.175997486 6.266018134 6.231683788 6.197349442 6.163015096 #> [97] 6.128680750 5.816046745 6.060012059 6.270656376 6.115698361 6.201987684 #> [103] 6.261967289 0.163754337 0.129419991 0.197529499 0.287550147 0.088067124 #> [109] 6.107275643 5.927312916 5.772354902 5.891965220 5.689988437 5.669351864 #> [115] 5.635017518 5.593436922 5.686972495 5.549556540 5.497680134 5.449648015 #> [121] 5.429011442 5.455670052 5.454656702 5.201653410 5.291674059 5.274881773 #> [127] 5.209307593 5.342615685 5.256780528 4.995647334 4.175914825 4.648678984 #> [133] 5.016999291 5.076978897 4.752668140 5.377643862 5.705853754 6.046790231 #> [139] 6.257434548 6.223100202 6.188765856 6.271540254 6.120097164 6.210117813 #> [145] 0.326842480 0.945934475 1.394725794 1.236036454 1.142946285 2.043425813 #> [151] 1.133033416 0.390072798 1.206261779 1.030030378 0.878587288 0.961361686 #> [157] 0.802672346 0.647714331 0.747701427 0.824024303 0.544711294 0.631000616 #> [163] 0.476042602 0.562331924 0.527997578 0.373039564 0.583683881 0.364001585 #> [169] 0.404357968 0.235702180 0.201367834 0.053241481 6.153764608 6.006279281 #> [175] 5.917453478 5.969857471 6.004379615 6.025543774 6.049965251 6.201853745 #> [181] 6.125585953 0.193023686 0.144991567 #> #> $hoegardeen #> [1] 0.000000000 6.263129292 0.100037949 0.067482585 0.034927220 0.002371856 #> [7] 6.253001799 6.220446435 6.187891070 6.155335706 6.122780342 6.090224977 #> [13] 6.057669613 6.177763577 5.827410207 5.960003520 5.927448156 5.894892792 #> [19] 5.862337427 5.829782063 5.797226699 5.764671335 5.732115970 5.782701838 #> [25] 5.743777133 5.634449877 5.601894513 5.569339149 5.536783785 5.504228420 #> [31] 5.471673056 5.439117692 5.406562327 0.661617983 5.494100927 5.308896235 #> [37] 5.359482102 5.320557397 5.363879470 5.444926827 5.540910533 5.612910771 #> [43] 6.188157402 0.091085677 0.150859647 6.232388364 0.011599399 0.205842883 #> [49] 0.173287518 0.140732154 6.238712769 0.075621426 0.222919561 0.010510697 #> [55] 0.130604661 0.028541200 0.065493933 6.240246438 0.092712539 0.314525233 #> [61] 0.528042623 0.821517388 1.288308745 1.178981490 1.140056785 1.113870761 #> [67] 1.158087288 1.125531924 1.092976560 1.060421195 1.027865831 0.995310467 #> [73] 0.962755102 0.930199738 0.897644374 0.865089010 0.923193532 0.723206390 #> [79] 0.932571594 0.734867552 0.702312188 0.669756824 0.637201460 0.604646095 #> [85] 0.572090731 0.539535367 0.506980002 0.474424638 0.441869274 0.409313910 #> [91] 0.376758545 0.344203181 0.311647817 0.279092452 0.246537088 0.213981724 #> [97] 0.181426360 4.861259976 0.116315631 0.083760267 0.127976794 0.183798216 #> [103] 0.151242851 0.106188138 0.165962108 0.186927013 0.082671565 0.145067907 #> [109] 0.112512543 0.003185287 0.120442379 0.060269729 6.242224770 6.076319151 #> [115] 6.031264438 6.091038408 5.978653058 6.079447948 5.975192501 5.880986966 #> [121] 5.981781855 5.650727560 5.618172195 5.662388722 5.705710795 5.520506102 #> [127] 5.640600067 5.532167265 5.505981241 5.467056537 5.357729281 5.505027417 #> [133] 5.292618552 5.412712517 5.392656501 5.118180568 4.621977595 5.212982963 #> [139] 5.395785298 5.309709666 4.188021652 5.197015834 5.265563841 5.719907709 #> [145] 6.174251576 0.080237945 0.124454472 0.091899108 0.059343743 0.103560270 #> [151] 0.159381692 0.260176582 0.948263631 1.302214571 1.756558439 1.599648080 #> [157] 1.204548479 1.184492463 1.457235756 1.451884563 1.239475699 2.777716661 #> [163] 1.021715642 1.141809606 1.032482350 0.911550200 1.044143513 0.858938820 #> [169] 0.979032785 0.863336188 0.830780824 0.728717363 0.931952559 0.663606635 #> [175] 0.631051270 0.751145235 0.565940542 0.533385178 0.408500479 0.468274449 #> [181] 0.435719085 0.234062494 0.224758753 0.263903472 0.136396402 0.127092660 #> [187] 0.094537296 6.263159793 0.082946836 6.280056510 0.017836107 6.214945782 #> [193] 0.120932150 #> #> $jupiler #> [1] 0.000000000 0.035494062 0.066524698 0.026247869 6.269156347 6.228879518 #> [7] 6.188602689 6.148325860 6.031277140 6.067772203 6.027495374 5.987218545 #> [13] 5.875634251 5.906664887 5.866388058 5.826111229 5.714526936 5.745557571 #> [19] 5.633973278 5.665003914 5.624727085 5.584450256 5.544173427 5.432589133 #> [25] 5.386847878 5.423342940 5.346045995 5.414096747 5.444409508 5.339007516 #> [31] 5.363855850 5.524705907 5.746949802 5.963298364 6.226756021 0.009686739 #> [37] 0.056815509 0.085734959 0.110583293 0.005181301 0.106801526 0.143296589 #> [43] 0.168144923 0.127868094 0.172493059 0.248441322 0.384286667 0.566810992 #> [49] 0.784045742 1.104013060 1.048030716 1.092655681 1.122968442 1.153999078 #> [55] 1.113722249 1.002137955 1.033168591 0.992891762 0.952614933 0.912338104 #> [61] 0.872061275 0.831784447 0.791507618 0.674458898 0.710953960 0.670677131 #> [67] 0.630400302 0.518816008 0.549846644 0.432797924 0.469292987 0.287119103 #> [73] 0.541388657 0.277155035 0.308185671 0.267908842 0.227632013 0.116047719 #> [79] 0.147078355 0.142500639 0.219174026 0.168144923 0.197064373 0.172493059 #> [85] 0.183717041 0.143440212 0.123362656 0.127610836 0.022609725 0.002532169 #> [91] 6.158035049 6.048561942 6.019037386 6.037204562 5.927731455 5.972356419 #> [97] 5.705280743 5.806900968 5.701498976 5.584450256 5.615480892 5.575204063 #> [103] 5.540391660 5.494650405 5.454373576 5.419561174 5.373819918 5.262235625 #> [109] 5.298730687 4.838658026 5.141405138 5.253777638 5.060851480 4.793775803 #> [115] 5.207096671 5.545565657 6.006892882 6.203464815 0.035494062 0.066524698 #> [121] 0.103019760 0.264270699 0.611663448 1.043805933 1.364629415 1.895006773 #> [127] 1.056884291 1.173209339 1.596580119 1.234552735 1.087540234 1.077227186 #> [133] 1.042414784 1.002137955 0.956396700 0.850994708 0.881307468 0.770441050 #> [139] 0.872061275 0.760476982 0.649610563 0.524431941 0.639646495 0.392377472 #> [145] 0.477750974 0.379030140 0.271546985 0.282770967 0.126269046 0.085992217 #> [151] 0.090240397 0.005438559 6.248347038 0.041109994 6.232517661 6.259447158 #> #> $kingfisher #> [1] 0.00000000 0.07035394 0.03583095 0.00130795 6.24997026 6.21544726 #> [7] 1.46853529 6.14640127 6.11187828 6.27475084 5.94316363 6.13266428 #> [13] 5.97378629 5.93926330 5.90474030 5.87021730 5.83569431 1.08878233 #> [19] 5.76664831 5.73212532 5.69760232 5.66307933 5.62855633 5.59403333 #> [25] 5.55951034 5.52498734 5.49046434 0.74355237 5.42141835 5.38689536 #> [31] 5.35237236 5.31784936 5.28332637 5.46747232 5.21428038 5.29041460 #> [37] 5.34262994 5.43246194 0.36379941 5.42217177 5.79254056 6.00299623 #> [43] 6.04524512 6.22939107 6.14838995 6.20792818 0.08761544 6.11760881 #> [49] 0.01856945 6.26723176 0.16819240 6.19818577 0.09914641 0.06462341 #> [55] 0.10288827 0.19513280 0.12289186 0.54584371 0.78048820 5.92200180 #> [61] 0.95642087 0.92189788 0.90864827 1.07152083 0.92634061 1.00247484 #> [67] 0.96795184 0.93342885 0.70151029 0.86438285 5.54224884 0.99273242 #> [73] 0.76081387 0.72629087 0.69176787 0.65724488 0.62272188 0.58819889 #> [79] 0.55367589 0.62981011 0.48462990 5.16249588 0.41558390 0.38106091 #> [85] 0.34653791 0.31201492 0.27749192 0.24296892 0.20844593 0.17392293 #> [91] 0.13939993 0.10487694 4.78274292 0.03583095 0.00130795 0.16418051 #> [97] 6.21544726 0.09513452 0.06061153 0.02608853 0.15294064 0.05110377 #> [103] 4.43751296 6.17118185 6.23072009 6.12340925 6.25072368 6.03308987 #> [109] 6.01984026 6.08839887 6.02358211 5.80825954 6.12672693 4.05776000 #> [115] 5.79142889 5.85096713 5.72238290 5.73544301 5.55561000 5.61881391 #> [121] 5.60556430 5.45204101 5.53651831 5.48072193 3.67800704 5.43294932 #> [127] 5.37715294 5.14523438 5.11071139 5.29485734 5.23906095 5.00714240 #> [133] 4.55439507 5.22955320 3.33277708 4.57759362 5.12598421 5.72729964 #> [139] 6.23660910 0.01856945 6.26723176 6.23270876 0.01466911 0.46848007 #> [145] 1.30609357 2.95302412 1.56637375 1.21351315 1.37832746 1.35479303 #> [151] 1.10994416 1.07542117 1.14056682 0.88737488 1.07152083 0.81832889 #> [157] 2.57327117 0.77055628 0.93342885 0.79923720 0.66698730 0.61119091 #> [163] 0.59794130 0.66114521 0.52889531 0.27354354 2.22804120 0.52305323 #> [169] 0.36952994 0.13545156 0.40849567 0.28723434 0.06960052 0.41558390 #> [175] 6.24602189 0.14914235 0.11461936 1.84828825 6.20440368 0.01105037 #> [181] 6.16565144 0.13939993 #> #> $latrappe #> [1] 0.00000000 6.15384418 6.19078552 6.14458563 6.09838574 6.13532708 #> [7] 6.00598596 5.95978606 5.91358617 5.86738628 5.82118639 5.69821460 #> [13] 5.81192784 5.68258671 5.63638682 5.59018693 5.54398704 5.49778714 #> [19] 5.53472848 5.40538736 5.35918747 5.31298758 5.26678768 5.30372902 #> [25] 5.17438790 5.12818801 5.23463744 5.03578822 5.71623067 6.21568584 #> [31] 0.01965089 0.06182778 0.09239978 0.04619989 0.00000000 6.23698542 #> [37] 6.19078552 6.14458563 6.09838574 6.05218585 6.00598596 5.95978606 #> [43] 5.91358617 5.86738628 5.89795828 5.85812773 5.80555849 5.76572794 #> [49] 5.79504208 6.27591644 0.74845682 0.70862627 0.73919827 0.69299838 #> [55] 0.64679849 0.60059860 0.55439870 0.50819881 0.46199892 0.41579903 #> [61] 0.36959914 0.32339924 0.27719935 0.23099946 0.18479957 0.13859968 #> [67] 0.09239978 0.04619989 0.00000000 6.23698542 6.19078552 6.14458563 #> [73] 6.09838574 6.05218585 6.00598596 5.95978606 5.91358617 5.86738628 #> [79] 5.82118639 5.77498650 5.80555849 5.76572794 5.86318567 5.83516559 #> [85] 6.00763464 5.99172851 6.03958986 6.06108299 6.14458563 6.11965913 #> [91] 5.87233235 5.74866224 5.47288683 5.37316667 5.23463744 5.11892946 #> [97] 4.98958833 4.94338844 4.89718855 4.68583998 4.23805955 4.75858887 #> [103] 5.06115998 5.18064040 5.94580686 6.14458563 6.09838574 5.97541396 #> [109] 6.08912719 5.95978606 6.07873485 0.17220358 0.61485604 0.97193763 #> [115] 1.38357146 1.13534641 1.00382783 0.95456984 0.83159806 0.70862627 #> [121] 0.57404959 0.54034905 0.40181982 0.16819082 6.24958141 6.08912719 #> [127] 5.91633517 5.91358617 5.91083717 6.05492957 6.14587778 6.19243421 #> [133] 6.24118603 0.22174091 0.09239978 0.04619989 #> #> $lindemanskriek #> [1] 0.0000000000 0.2503515252 6.1760863615 0.0682944710 0.1432517756 #> [6] 0.1075518591 0.0094331326 0.1468092473 0.0004521096 6.2479375002 #> [11] 6.2122375837 6.1765376672 6.1408377507 6.1051378342 6.0694379176 #> [16] 6.0337380011 5.9980380846 5.9623381681 5.9266382516 5.8909383351 #> [21] 5.8552384185 5.8195385020 5.7838385855 5.7481386690 5.7124387525 #> [26] 5.6767388359 5.6410389194 5.6053390029 5.5696390864 5.5339391699 #> [31] 5.4982392534 5.4625393368 5.4268394203 5.3911395038 5.4660968085 #> [36] 5.5647183339 5.6057903086 5.8810886727 6.2248369327 0.0009034153 #> [41] 0.1071005534 0.1620605241 0.2330962802 0.1973963637 0.1689426972 #> [46] 0.2503515252 0.2146516087 0.1789516922 0.1432517756 0.2319068537 #> [51] 0.3168306057 0.1468092473 0.2315427768 0.2097308562 0.2508028309 #> [56] 0.2521230303 0.7261918388 0.8736027395 1.0352983829 1.1969940262 #> [61] 1.4830446641 1.0049705246 1.4329182171 1.1785493547 1.1428494382 #> [66] 1.1071495216 1.0714496051 1.0357496886 1.0000497721 0.9643498556 #> [71] 0.9286499390 0.8929500225 0.8572501060 0.8215501895 0.7858502730 #> [76] 0.7501503565 0.7144504399 0.6787505234 0.6430506069 0.6073506904 #> [81] 0.5716507739 0.5359508573 0.5002509408 0.5233068470 0.4288511078 #> [86] 0.2824939701 0.3574512748 0.3805071810 0.1616964472 0.2503515252 #> [91] 0.3317603532 0.3033066867 0.3882304388 0.3525305223 0.2571998926 #> [96] 0.3949226964 0.2191210554 0.3235228633 0.2151037183 0.1383310231 #> [101] 0.1794029979 0.2268443133 6.2441101167 0.5359508573 6.1223930792 #> [106] 0.0840446472 6.2126896933 6.2126888895 5.9795934131 6.1412890564 #> [111] 5.9081935800 5.9668076149 5.8367937470 5.8514110350 5.8597078653 #> [116] 5.6053390029 5.6802963076 5.5963579799 5.4982392534 5.4625393368 #> [121] 5.4268394203 5.5658117028 5.3554395873 5.3197396708 5.2840397542 #> [126] 5.1895840150 5.2126399212 4.9319613416 5.0168850936 5.1642959944 #> [131] 4.9454852606 5.2528092845 6.0568472886 0.0053728621 0.1039943875 #> [136] 0.1789516922 0.2020075984 0.3525305223 0.1962069372 0.4997996351 #> [141] 1.3401577692 1.7805271830 1.2548699402 1.1053780165 1.7313336387 #> [146] 1.3927488538 1.3570489373 1.0763703576 1.2856491042 1.2499491877 #> [151] 1.2142492712 1.0678921335 1.1428494382 0.9827945271 1.0714496051 #> [156] 0.9769938659 0.8893925509 0.8224528010 0.8179927179 0.7685950280 #> [161] 0.7465928848 0.6971951949 0.4640997186 0.5190596893 0.3556797697 #> [166] 0.4337718603 0.4243816610 0.2485800201 0.3266721107 0.2142003029 #> [171] 0.2552722777 0.1616661559 0.1838724447 0.0714006369 0.1124726116 #> [176] 0.0356999165 #> #> $nicechouffe #> [1] 0.000000000 0.007281689 6.140695807 0.045565652 6.161360448 6.118324933 #> [7] 6.199644411 6.156608896 6.113573380 5.959880643 6.086258171 5.984466832 #> [13] 5.941431317 5.898395801 5.855360285 5.812324769 5.769289253 5.726253738 #> [19] 5.683218222 5.640182706 5.597147190 5.554111674 5.511076159 5.468040643 #> [25] 5.425005127 5.381969611 5.338934095 5.295898580 5.252863064 5.454806211 #> [31] 5.488542587 5.642902631 6.049229981 6.249711141 0.037282325 0.239225473 #> [37] 0.196189957 0.042497220 0.110118925 0.067083410 0.024047894 6.264197685 #> [43] 6.221162169 6.178126653 0.070574776 0.213762101 0.105127413 0.281398598 #> [49] 0.731413980 0.743876969 1.102070252 1.121453547 1.078418031 1.035382515 #> [55] 0.992346999 0.949311483 1.016933189 0.800821642 0.820204936 0.777169420 #> [61] 0.844791126 0.691098389 0.648062873 0.605027357 0.561991841 0.518956325 #> [67] 0.475920810 0.432885294 0.514204773 0.346814262 0.303778746 0.015764567 #> [73] 0.217707715 0.419650862 0.131636683 0.147356990 0.169920646 0.126885130 #> [79] 0.204473283 0.101807054 0.118402252 0.152138627 0.032331220 0.047201909 #> [85] 0.106173311 6.160100262 6.184447242 6.214130955 6.171095439 6.128059924 #> [91] 6.012305179 5.807573216 5.998953376 5.955917860 5.785202342 5.729745104 #> [97] 5.592395637 5.542113871 5.381969611 5.557603041 5.420253574 5.311618886 #> [103] 5.209827548 5.166792032 5.234413737 5.080721001 4.530586980 4.870294974 #> [109] 5.237665895 5.019236158 5.485792907 6.034533562 6.225913722 0.024047894 #> [115] 0.105367372 0.525979466 1.143987119 1.564599212 1.134687978 1.521979076 #> [121] 1.404252831 1.250560094 1.096867357 1.164489062 1.121453547 0.859749085 #> [127] 1.035382515 0.881689778 0.949311483 0.687607022 0.746131707 0.695849942 #> [133] 0.455418866 0.489155241 0.405046947 0.369763214 0.386358411 0.222699227 #> [139] 0.273977662 0.117150139 0.154585635 0.050557164 6.271228899 0.085109801 #> [145] 6.265628879 6.255914359 #> #> $pecheresse #> [1] 0.00000000 0.11558369 0.17175377 0.07308851 6.25264841 0.02563318 #> [7] 6.26011162 6.21140476 6.16269790 6.11399103 6.06528417 5.91690866 #> [13] 5.96787045 5.91916358 5.87045672 5.82174986 5.77304299 5.72433613 #> [19] 5.67562927 5.62692241 5.46755832 5.52950868 5.48080182 5.43209495 #> [25] 5.48305674 5.53207679 5.65686565 6.05491255 6.20075765 0.09078998 #> [31] 0.22986799 0.11138213 0.28134421 0.23263735 0.18393048 0.23489227 #> [37] 0.19139370 0.32926669 0.52952253 0.69354745 1.08197926 1.41377877 #> [43] 1.25441469 1.26640665 1.26765818 1.07006137 1.17024446 1.12153759 #> [49] 1.07283073 1.02412387 0.97541700 0.82704149 0.87800328 0.82929642 #> [55] 0.66993233 0.84899143 0.63059277 0.43707340 0.58576210 0.53705524 #> [61] 0.48834838 0.43964151 0.39093465 0.34222779 0.39318958 0.35547128 #> [67] 0.34499715 0.24706899 0.35601719 0.25748284 0.21994869 0.20989660 #> [73] 0.16118974 0.10013782 0.05143096 6.24842697 6.21089282 6.09240696 #> [79] 6.10230638 5.95098023 5.99479199 5.85356650 5.69998270 5.84867140 #> [85] 5.65806748 5.60644517 5.60482390 5.45644839 5.51261846 5.11405600 #> [91] 4.89791736 5.51894465 4.89116352 5.06453856 5.40155179 6.03204515 #> [97] 0.01424085 0.14633356 0.20828391 0.15957705 0.32953913 0.73690427 #> [103] 1.12060518 1.48296287 1.59749629 1.31377721 1.33946694 1.73132552 #> [109] 1.18713467 1.24330475 1.08394067 1.04622237 1.09718416 0.99589424 #> [115] 0.80237488 0.95106357 0.74575483 0.75398119 0.58627404 0.46477933 #> [121] 0.55092738 0.44015345 0.31865874 0.29046182 0.30520558 0.17253815 #> [127] 0.14434123 0.10925750 0.09920541 #> #> $sierranevada #> [1] 0.000000000 6.247485391 1.499396494 6.176085558 6.140385641 6.104685725 #> [7] 1.356596828 6.033285892 5.997585975 1.249497078 5.926186142 5.890486225 #> [13] 5.854786309 1.106697412 5.783386476 5.747686559 0.999597663 5.676286726 #> [19] 5.640586810 0.892497913 5.569186977 5.533487060 5.497787144 0.749698247 #> [25] 5.426387311 5.473828626 0.642598497 5.319287561 5.283587645 5.164746496 #> [31] 0.499798831 5.176487895 5.293437307 0.392699082 5.234536823 5.561762677 #> [37] 6.136376864 0.249899416 0.049050822 0.013350905 0.142799666 0.030327858 #> [43] 0.071399833 0.035699917 0.000000000 6.247485391 6.211785474 6.176085558 #> [49] 6.140385641 6.104685725 6.152127040 6.033285892 6.162734652 6.114535387 #> [55] 5.926186142 5.890486225 6.176536863 5.819086392 0.285599332 0.713547025 #> [61] 0.916456431 5.676286726 0.775548501 0.892497913 5.569186977 0.986246757 #> [67] 0.785398163 0.749698247 5.426387311 0.678298414 0.642598497 5.319287561 #> [73] 0.571198664 0.535498748 0.499798831 5.176487895 0.428398998 0.392699082 #> [79] 5.069388146 0.321299249 0.285599332 0.249899416 4.926588479 0.178499583 #> [85] 0.225940898 4.819488730 0.071399833 0.035699917 0.000000000 4.676689064 #> [91] 6.211785474 6.176085558 4.569589314 6.104685725 6.068985808 4.462489565 #> [97] 6.074357866 6.045027290 6.091334819 4.319689899 0.004008777 0.063975534 #> [103] 4.212590149 0.093297539 0.131058267 6.071077846 4.069790483 5.688028125 #> [109] 5.721836305 3.962690734 5.580928376 5.545228459 5.579036639 3.819891067 #> [115] 5.599966141 5.484436239 3.712791318 5.400537057 5.457166475 5.421466558 #> [121] 3.569991652 5.331886910 5.152529377 3.462891902 5.242966976 4.613517392 #> [127] 3.355792153 5.212639117 4.436964317 4.972138058 3.212992487 5.730882620 #> [133] 6.118036630 3.105892737 6.135013583 6.176085558 6.223526873 2.963093071 #> [139] 6.234134485 0.424841527 2.855993321 0.822869585 1.754216662 0.856346691 #> [145] 2.713193655 1.286550912 1.147769387 2.606093906 0.754618999 0.784044246 #> [151] 0.629698898 2.463294240 0.691649319 0.655949403 2.356194490 0.597048918 #> [157] 0.630857098 0.513149736 2.213394824 0.530126690 0.488057432 2.106295075 #> [163] 0.334650154 0.311449586 1.999195325 6.281093269 6.011388186 5.948788930 #> [169] 1.856395659 5.966355505 5.998038085 1.749295909 6.273335645 6.225136379 #> [175] 0.236548510 1.606496243 #> #> $tanglefoot #> [1] 0.000000000 6.184656237 6.148545976 6.112435716 6.200680450 6.040215195 #> [7] 6.004104935 5.967994674 5.931884414 5.895774154 5.859663893 5.823553633 #> [13] 5.787443373 5.751333112 5.715222852 5.679112591 5.643002331 5.606892071 #> [19] 5.570781810 5.534671550 5.498561289 5.462451029 5.426340769 5.514585503 #> [25] 5.354120248 5.318009988 5.281899727 5.245789467 5.209679206 5.049213951 #> [31] 5.013103691 5.101348425 5.189593159 5.387898575 5.351788314 5.742305547 #> [37] 0.208408143 0.172297883 0.136187622 0.100077362 0.063967101 0.027856841 #> [43] 6.274931888 6.238821627 6.202711367 6.166601107 6.130490846 6.094380586 #> [49] 6.058270325 6.022160065 5.986049805 5.949939544 5.913829284 5.877719024 #> [55] 5.841608763 5.805498503 5.769388242 5.733277982 5.697167722 0.390069165 #> [61] 0.553787550 0.631469297 0.840337700 0.804227439 0.892472173 0.732006918 #> [67] 0.695896658 0.659786398 0.623676137 0.587565877 0.551455617 0.515345356 #> [73] 0.479235096 0.443124835 0.407014575 0.370904315 0.334794054 0.298683794 #> [79] 0.262573533 0.226463273 0.190353013 0.154242752 0.118132492 6.240852544 #> [85] 0.045911971 0.009801711 6.256876758 6.220766497 6.184656237 6.148545976 #> [91] 6.112435716 6.076325456 6.040215195 5.879749940 5.967994674 5.807529420 #> [97] 6.020129148 5.984018888 6.068532296 6.032422036 6.163743554 0.140663817 #> [103] 0.039428393 0.145215187 0.146125043 0.006426503 6.154921036 5.962208898 #> [109] 5.740750688 5.657431436 5.635209171 5.354120248 5.562988651 5.406254722 #> [115] 5.370144461 5.334034201 5.297923941 5.279355740 5.346327088 5.189593159 #> [121] 5.153482899 5.117372639 5.081262378 5.165775786 4.504180486 4.972931597 #> [127] 5.057445005 5.135126752 4.461946162 4.459156898 5.618572141 6.202711367 #> [133] 6.166601107 6.130490846 6.094380586 6.058270325 6.022160065 5.986049805 #> [139] 5.949939544 0.842669633 1.165330043 2.180869995 0.734338852 0.871651312 #> [145] 1.020889002 1.572781345 0.824313486 0.788203226 0.752092965 0.715982705 #> [151] 0.445456769 0.643762184 0.607651924 0.578787914 0.414807735 0.499321143 #> [157] 0.342587214 0.551455617 0.329997406 0.354880101 0.198146172 0.048243905 #> [163] 6.141700162 5.832581198 5.729902774 5.760360677 5.790818581 5.914939005 #> [169] 5.973780450 6.042547129 6.006436868 6.204742284 6.230568208 6.256876758 #> #> $tauro #> [1] 0.00000000 6.21162891 0.05748202 0.02137176 6.26844680 6.23233654 #> [7] 6.19622628 6.16011602 6.12400576 5.93524617 6.05178524 6.01567498 #> [13] 5.97956472 5.94345446 5.90734420 5.87123394 5.83512368 5.63386474 #> [19] 5.76290316 5.72679290 5.69068264 5.65457238 5.61846212 5.58235186 #> [25] 5.54624160 5.35748201 5.47402107 5.43791081 5.40180055 5.36569029 #> [31] 5.32958003 5.29346977 5.42250819 5.40110275 5.35028767 5.47077929 #> [37] 5.71846313 5.86220637 6.16538873 0.04722005 0.07623495 0.14320630 #> [43] 0.01871925 6.26579430 0.11164741 0.07553715 0.21928039 0.15596595 #> [49] 0.05034760 0.09624478 0.39433257 0.28550308 0.41076793 0.65519446 #> [55] 0.89471364 1.20208964 1.08397193 0.94675830 1.02425076 1.14078983 #> [61] 1.10467957 1.06856931 1.03245905 0.99634879 0.96023853 0.92412827 #> [67] 0.88801801 0.76876651 0.81579748 0.77968722 0.74357696 0.70746670 #> [73] 0.67135644 0.63524618 0.59913592 0.38317216 0.52691540 0.49080514 #> [79] 0.45469488 0.25343594 0.53512369 0.34636410 0.31025384 0.27414358 #> [85] 0.15489209 0.11878183 0.16581280 0.12970254 0.17673351 0.05748202 #> [91] 0.17402108 0.23024016 0.19412990 0.15801964 0.19868127 0.08579912 #> [97] 0.17188403 0.01357860 0.08126068 6.24581677 6.18843312 5.99800409 #> [103] 6.09803279 6.08010234 5.96416210 5.92805183 5.81745278 5.76745453 #> [109] 5.81972105 5.70160335 5.58235186 5.54624160 5.62956026 5.47402107 #> [115] 5.60305949 5.40180055 5.36569029 5.49472871 5.29346977 5.25735951 #> [121] 5.31190914 4.79034787 5.14902873 5.26556780 5.32178687 4.18873162 #> [127] 5.27083974 5.14833093 5.52036977 6.03464546 6.08217197 0.02850618 #> [133] 0.07553715 0.12256812 0.16846530 0.21218503 0.57459721 1.13104533 #> [139] 1.81017829 1.39356165 1.05895246 1.23819990 1.74887848 1.24912061 #> [145] 1.04786167 1.17690009 0.97564115 0.93953089 1.06856931 1.03245905 #> [151] 0.83120011 0.96023853 0.75897959 0.72286933 0.93504898 0.65064881 #> [157] 0.59983372 0.74357696 0.44121465 0.50620777 0.39026752 0.43398724 #> [163] 0.32748068 0.28193674 0.31095164 0.13294433 6.23812232 0.15567551 #> [169] 0.02461355 6.24466814 0.02916492 6.12642751 0.03677438 0.01316347 #> #> $westmalle #> [1] 0.000000000 0.186529069 6.250480580 0.097405873 6.277273760 0.008282678 #> [7] 6.246906387 6.202344789 6.157783191 6.113221593 6.068659995 6.024098397 #> [13] 5.979536799 6.045632423 5.890413603 5.845852006 5.801290408 5.756728810 #> [19] 5.712167212 5.667605614 5.623044016 5.702837413 5.533920820 5.489359222 #> [25] 5.444797624 5.400236026 5.472783173 5.435467825 5.207795410 5.741135749 #> [31] 6.241125859 6.163243265 6.240876838 0.086375599 0.068123719 0.067558868 #> [37] 0.197669469 0.211863694 0.108546273 0.181093420 0.264401740 0.314154094 #> [43] 0.289070551 0.505987769 0.626574849 1.300843250 1.077871153 1.153933224 #> [49] 1.233726620 1.130409200 1.144603425 1.100041827 1.055480229 1.010918631 #> [55] 0.966357033 0.921795435 0.877233837 0.832672239 0.788110641 0.743549043 #> [61] 0.698987445 0.654425847 0.609864250 0.565302652 0.520741054 0.476179456 #> [67] 0.431617858 0.387056260 0.283738839 0.542911727 0.312127289 0.208809868 #> [73] 0.281357015 0.364665336 0.260473024 0.275542140 0.183397438 0.160109227 #> [79] 0.218629237 0.174067639 0.052734150 0.041493548 6.232908265 5.712277337 #> [85] 6.029803147 0.048595106 6.068549870 6.268966935 5.858803005 5.806995157 #> [91] 5.923624474 5.717871962 5.556201619 5.574058831 5.467078423 5.546871820 #> [97] 5.377955227 5.333393629 5.288832031 5.046874874 5.199708836 5.329819437 #> [103] 4.788835085 5.128442852 5.485110053 6.057739847 0.219950268 6.261178417 #> [109] 0.130827072 0.260937673 0.446595662 0.873200329 1.399022012 1.478815409 #> [115] 1.524913698 1.279034992 1.469485610 1.411226239 1.256007419 1.211445822 #> [121] 1.042529229 1.122322626 1.077761028 0.908844435 0.988637832 0.819721239 #> [127] 0.782405891 0.609974375 0.635719241 0.520851179 0.330661201 0.271814860 #> [133] 0.694563859 0.587583451 0.240136984 0.374105260 0.167847215 0.087586504 #> [139] 0.179427511 6.185174841 0.151297271 #> #> $amrut #> [1] 0.00000000 6.25028905 6.21739279 6.18449653 6.15160027 6.11870402 #> [7] 6.08580776 6.05291150 6.02001524 5.98711898 5.95422273 5.92132647 #> [13] 5.88843021 5.85553395 5.82263769 5.78974143 5.75684518 5.72394892 #> [19] 5.69105266 5.65815640 5.62526014 5.59236389 5.55946763 5.52657137 #> [25] 5.49367511 5.46077885 5.42788260 5.39498634 5.36209008 5.32919382 #> [31] 5.29629756 5.26340130 5.23050505 5.19760879 4.96731697 5.03214762 #> [37] 5.09892001 5.16569241 5.23052306 5.09989989 5.16473054 5.77859271 #> [43] 6.00869118 6.14798574 6.20915072 6.27398136 6.24108511 6.20818885 #> [49] 6.27496124 6.24206498 6.20916873 6.17627247 6.14337621 6.11047995 #> [55] 6.07758369 6.14435609 6.11145983 6.07856357 6.23745546 0.13701560 #> [61] 0.50677400 0.93752535 0.90462909 1.06912839 0.93656348 1.00333587 #> [67] 1.07010827 1.03721201 0.90464710 0.87175084 0.83885458 0.80595832 #> [73] 0.77306207 0.74016581 0.60760090 0.67437329 0.64147703 0.60858078 #> [79] 0.57568452 0.54278826 0.50989200 0.47699574 0.44409949 0.41120323 #> [85] 0.37830697 0.34541071 0.31251445 0.27961819 0.24672194 0.21382568 #> [91] 0.18092942 0.14803316 0.11513690 0.08224065 0.04934439 0.01644813 #> [97] 6.26673718 6.23384092 6.20094466 6.16804840 6.13515215 6.10225589 #> [103] 6.06935963 6.03646337 6.00356711 5.97067085 5.83810594 5.90487834 #> [109] 6.06937764 6.21959220 6.26983717 0.03052750 0.11825491 0.20971365 #> [115] 0.28747461 6.22971088 5.98931839 5.99414009 5.64268815 5.51012324 #> [121] 5.47722698 5.34466207 5.31176581 5.37853821 5.44531060 5.31274569 #> [127] 5.69807376 5.44434874 5.31372557 5.28082931 5.24793305 5.49587452 #> [133] 5.27986744 4.85218007 4.81928381 5.18117867 5.05055550 4.91799059 #> [139] 4.98476299 4.95186673 4.71963317 4.78640556 4.85317796 5.50601121 #> [145] 5.93676256 6.12594820 6.19272060 6.15982434 6.22659673 0.10230331 #> [151] 0.38867622 1.31585033 1.28295407 1.25005781 1.11749290 1.18426529 #> [157] 1.15136904 1.01880412 1.08557652 1.05268026 1.13044122 1.08655640 #> [163] 0.95399149 0.72369967 0.59674218 0.85530271 0.62501089 0.78951020 #> [169] 0.24951543 0.62404903 0.59115277 0.65792516 0.62502890 0.69180130 #> [175] 0.55923639 0.42667148 0.17169332 0.08004124 6.17041716 5.78188502 #> [181] 5.91840181 5.95110472 6.03883213 6.08270776 6.22200232 6.28316730 #> [187] 0.06481264 0.32898059 0.09868877 0.06579252 0.03289626 #> #> $ballantines #> [1] 0.00000000 6.24014979 6.19711428 6.15407876 6.11104324 6.06800773 #> [7] 6.02497221 5.98193670 5.93890118 5.89586566 5.85283015 5.80979463 #> [13] 5.76675912 5.72372360 5.68068809 5.63765257 5.59461705 5.55158154 #> [19] 5.50854602 5.40309170 5.17749633 5.37943948 5.33640396 5.29336844 #> [25] 5.37468792 5.33165241 5.34960985 5.36620504 5.45869724 5.67865646 #> [31] 6.26003129 0.11234034 0.13124101 0.15062431 0.04516998 0.18890827 #> [37] 6.24228426 6.26166755 0.00201489 6.17559652 6.13256100 6.08952549 #> [43] 6.04648997 5.87909946 5.96041894 5.91738342 5.87434791 5.83131239 #> [49] 5.85069569 6.26438747 0.43121755 0.70180268 0.65876717 0.66331476 #> [55] 0.69331981 0.77463928 0.73160377 0.68856825 0.76988773 0.66906539 #> [61] 0.55946171 0.51642619 0.47339067 0.49277397 0.38731964 0.34428413 #> [67] 0.30124861 0.25821309 0.21517758 0.17214206 0.12910655 0.08607103 #> [73] 0.04303552 0.00000000 6.24014979 6.19711428 6.21649757 6.11104324 #> [79] 6.06800773 6.02497221 6.04435551 5.93890118 5.89586566 5.85283015 #> [85] 5.80979463 5.89111411 5.72372360 5.68068809 5.51329758 5.59461705 #> [91] 5.67593653 5.86731669 6.06779785 6.27444132 0.12663099 0.16036737 #> [97] 0.02238015 0.07429634 6.05926374 5.60088906 5.24558138 5.43696153 #> [103] 5.03515535 4.71382017 5.35397610 4.84362999 4.86301329 4.94433276 #> [109] 5.18183404 4.52281341 5.27887383 6.03328408 6.17559652 6.13256100 #> [115] 6.08952549 6.17904150 0.18391676 1.24802996 1.34689150 1.02940739 #> [121] 1.11892341 1.07588790 0.97043357 1.34858753 0.68617896 0.90374583 #> [127] 0.55782545 0.35402719 6.27242643 5.90764036 5.94137673 5.91652103 #> [133] 5.87348552 5.99068069 6.21160889 0.11462000 0.30600016 0.38731964 #> [139] 0.46863912 0.30124861 0.25821309 0.21517758 0.17214206 0.12910655 #> [145] 0.08607103 0.04303552 #> #> $bushmills #> [1] 0.00000000 6.18067856 6.14259865 1.39212975 6.06643882 6.02835891 #> [7] 6.05684717 6.01876725 1.20173020 5.87603927 5.83795936 5.79987945 #> [13] 1.04941056 5.79028779 5.68563971 5.64755980 5.60947989 0.85901100 #> [19] 5.59573888 5.42867200 5.58971178 5.41908034 0.66861145 5.34292052 #> [25] 5.36725941 5.26676069 0.51629180 5.12403271 5.09010215 5.04787289 #> [31] 4.95200614 0.32589225 4.93363315 5.09467294 5.10938945 5.37591891 #> [37] 0.13549269 5.79259549 6.14512262 6.23787010 6.26635836 6.22827845 #> [43] 6.19019853 6.15211862 6.17645752 6.07595880 6.03787889 6.06221779 #> [49] 5.96171907 5.99020732 5.88555925 6.09245800 0.15896295 0.70015986 #> [55] 0.95428246 5.69515969 1.01125896 1.03096588 1.00108251 5.54284005 #> [61] 0.91672615 0.82085941 0.71621134 0.61571261 5.35244049 0.60197160 #> [67] 0.56389169 0.52581178 0.48773187 5.16204094 0.41157205 0.37349214 #> [73] 0.27299342 0.23076415 4.97164138 0.22117249 0.18309258 0.14501267 #> [79] 4.81932174 0.06885285 0.03077294 6.27587833 6.17537961 4.62892219 #> [85] 6.09507044 6.12355869 6.08547878 6.04739887 4.43852263 5.97123905 #> [91] 5.93315914 5.89507922 4.28620299 5.75235124 5.71427133 5.74275958 #> [97] 5.70467967 4.09580343 5.62851985 5.59043994 5.48579186 5.51428012 #> [103] 3.90540388 5.43812029 5.33762157 5.49451200 5.78752817 3.71500432 #> [109] 6.00087202 6.10569621 6.02826654 3.56268468 5.88079926 5.43782756 #> [115] 5.14359627 4.54875359 3.37228512 4.96742035 4.86692163 4.82884172 #> [121] 4.85318062 3.18188557 4.78117015 4.61410326 5.55354286 3.02956593 #> [127] 6.00052714 6.09499876 6.05691885 6.15139047 2.83916637 0.24749641 #> [133] 1.33410728 1.09171150 1.04948224 2.64876682 1.03989058 1.00181067 #> [139] 0.96373076 1.28442152 2.45836726 0.84949102 0.37478395 0.05924050 #> [145] 2.30604762 6.07552960 6.15687861 6.22945592 0.20242527 2.11564806 #> [151] 0.38241683 0.46869191 0.43061200 0.39253209 1.92524851 0.31637227 #> [157] 0.27829236 0.24021245 1.77292886 0.22647144 0.19254088 0.08789280 #> [163] 0.04981289 1.58252931 6.25683838 #> #> $chivas #> [1] 0.0000000000 0.1291196729 0.2186774860 0.2974741250 0.2591620195 #> [6] 0.2208499139 0.2449566184 0.1442257029 0.1059135973 0.1263573145 #> [11] 0.0292893863 6.2741625879 6.2358504824 0.0387080642 6.1592262713 #> [16] 6.2315713870 6.0826020603 6.0442899547 6.0059778492 5.9676657437 #> [21] 5.9293536381 5.9497973553 5.8527294271 5.8144173216 5.8867624372 #> [26] 5.7377931105 5.6994810050 5.7855238940 5.6228567939 5.5845446884 #> [31] 5.4874767601 5.3835654828 5.7145870349 0.0102810137 0.4619262344 #> [36] 0.3973044117 0.4796159747 0.4485501192 0.5273467582 0.4890346527 #> [41] 0.3336138026 0.4124104416 0.3740983361 0.2251290094 0.2974741250 #> [46] 0.2591620195 0.2208499139 0.2412936311 0.1442257029 0.1646694201 #> [51] 0.1919564864 0.0292893863 0.0533960907 0.1713341211 0.0997010197 #> [56] 0.0003959587 0.2775714414 0.8116137645 1.0869223112 1.4106976134 #> [61] 1.2552767633 1.1545458478 1.1786525522 1.1403404467 1.1020283412 #> [66] 1.0637162356 0.9666483074 0.9870920246 0.9487799190 0.7861128190 #> [71] 0.8721557080 0.8338436024 0.7955314969 0.6948005814 0.7189072859 #> [76] 0.6805951803 0.6422830748 0.6039709693 0.5069030410 0.5273467582 #> [81] 0.4890346527 0.4507225471 0.4124104416 0.3740983361 0.3357862305 #> [86] 0.2387183023 0.3835170140 0.2208499139 0.4275164715 0.5029963731 #> [91] 0.5183240389 0.5746999962 0.6620382213 0.7763754441 0.7703102211 #> [96] 0.7663193969 0.8033361822 0.5886579210 0.3580160684 0.0060833107 #> [101] 5.8953206280 5.7226870806 5.8049986436 5.7666865381 5.7939736044 #> [106] 5.9387723161 6.0071958832 5.9827717736 5.8238359995 5.8465168494 #> [111] 5.8415257398 5.7698926384 5.6705875774 5.6250292219 5.1108377015 #> [116] 5.5556512608 5.3929841607 5.2303170606 5.3163599496 5.2780478441 #> [121] 5.3640907331 5.2014236330 5.1631115275 5.5884470310 0.1291196729 #> [126] 0.2770304078 0.1731191305 0.2591620195 0.2832687239 0.1825378084 #> [131] 0.2685806974 0.7261630833 1.4073071514 1.6000857131 1.5617736075 #> [136] 1.5234615020 1.3607944019 1.4468372910 1.5191824066 1.3702130799 #> [141] 1.3943197844 1.2935888688 1.1381680187 0.9719859946 0.9475618850 #> [146] 1.1403404467 0.7432576709 0.8187375725 0.9147469089 0.8017440746 #> [151] 0.9487799190 0.9692236362 0.9965107025 0.9581985970 0.9126402415 #> [156] 0.7572193914 0.3601366156 6.2371381468 6.1400702186 6.0351899493 #> [161] 5.9968778437 6.0554276619 6.1287188510 6.1596030241 #> #> $dalmore #> [1] 0.000000000 0.105091701 0.232547293 0.253660785 0.378272783 1.908532430 #> [7] 0.297199424 0.256662744 0.216126065 0.175589386 0.135052706 0.094516027 #> [13] 0.053979347 1.584238995 6.256091296 0.015510541 6.175017937 6.134481258 #> [19] 6.093944578 6.053407899 6.012871219 1.259945560 5.931797861 5.891261181 #> [25] 5.850724502 5.733415931 5.604502466 5.407363909 5.390078853 0.935652124 #> [31] 5.690645657 6.133696964 0.306943582 0.773505407 0.732968727 0.692432048 #> [37] 0.651895369 0.611358689 0.570822010 0.530285330 0.489748651 0.449211972 #> [43] 0.408675292 0.368138613 0.327601933 0.287065254 0.246528575 0.205991895 #> [49] 0.165455216 0.124918536 0.167523089 0.043845178 0.003308498 0.045913051 #> [55] 6.205420447 6.248024999 6.047575197 0.122375656 0.598069647 1.137698741 #> [61] 1.332952622 1.507773642 5.881127011 1.373180015 1.252813350 1.047127993 #> [67] 1.006591313 0.966054634 0.925517955 0.968122507 5.556833576 0.803907916 #> [73] 0.763371237 0.805975789 0.682297878 0.641761199 0.601224519 0.643829072 #> [79] 5.232540141 0.479614481 0.439077802 0.398541122 0.434776334 0.317467764 #> [85] 0.276931084 0.313166296 4.908246706 0.477071600 0.509575486 0.506655463 #> [91] 0.677212117 0.735121596 0.738035812 0.788159020 4.583953271 0.659876670 #> [97] 0.446186558 0.144745372 6.145252208 6.197044863 5.911529521 5.718343513 #> [103] 4.259659835 5.873060715 5.749382803 5.785618015 5.668309445 5.710913997 #> [109] 5.664007977 5.711848084 5.900953847 3.894829721 5.126590437 5.384552689 #> [115] 5.344016009 5.380251221 5.262942651 5.222405971 5.334518620 3.570536286 #> [121] 0.143428289 0.264729041 0.307333594 0.266796914 0.226260235 0.552897389 #> [127] 1.632841971 3.246242850 1.634909844 1.671145056 1.470695253 1.513299806 #> [133] 1.472763126 1.753977001 0.996898648 2.921949415 1.157967080 1.186938498 #> [139] 1.229543050 1.189006371 1.148469691 1.031161121 1.067396332 2.597655980 #> [145] 1.069464206 0.869014403 0.822108383 0.619734272 0.457002422 0.195636973 #> [151] 0.001155629 2.273362545 6.076675450 6.075829107 6.169403211 #> #> $famousgrouse #> [1] 0.000000000 6.141129757 6.103951146 6.066772535 1.317204943 5.992415312 #> [7] 5.955236701 5.918058089 5.880879478 5.843700867 5.806522256 5.769343644 #> [13] 1.019776053 5.694986422 5.657807810 5.620629199 5.583450588 5.546271977 #> [19] 5.509093365 5.471914754 0.722347162 5.397557531 5.360378920 5.323200309 #> [25] 5.286021698 5.248843086 5.211664475 0.462096883 5.137307252 5.100128641 #> [31] 4.844281084 5.025771419 4.988592807 4.951414196 5.273006255 0.164667993 #> [37] 5.427880966 6.014725407 6.044860672 0.015953548 6.064564684 6.224781633 #> [43] 6.187603021 6.150424410 6.113245799 6.076067187 6.038888576 6.001709965 #> [49] 5.964531354 6.038009963 5.890174131 6.050391080 6.034485854 0.002551494 #> [55] 0.470471390 0.794496534 0.954713483 0.917534872 5.592745241 1.040573209 #> [61] 0.805999038 0.966215986 0.731641815 0.694463204 0.657284593 0.620105981 #> [67] 5.295316350 0.545748759 0.508570147 0.471391536 0.434212925 0.397034314 #> [73] 0.359855702 5.035066071 0.285498480 0.248319868 0.211141257 0.173962646 #> [79] 0.136784035 0.099605423 0.062426812 4.737637181 0.206738535 6.234076285 #> [85] 6.196897674 5.941050117 6.122540452 6.085361840 6.048183229 4.440208291 #> [91] 5.973826006 5.936647395 5.899468784 5.862290173 5.825111561 5.787932950 #> [97] 5.750754339 4.142779401 5.676397116 5.857887451 5.799435453 6.123460598 #> [103] 6.034781175 6.217146400 3.882529122 6.260300823 5.886066730 5.586768278 #> [109] 5.304611003 5.267432392 5.032858221 5.514825724 3.585100231 5.582365556 #> [115] 5.621958836 5.155017945 4.907513460 4.970003502 4.932824890 5.020001274 #> [121] 3.287671341 4.710631835 4.784110445 4.965600780 4.709753223 4.672574611 #> [127] 5.344022272 3.027421062 6.131835104 5.897260933 6.276146828 6.020299270 #> [133] 0.408561624 1.344210289 0.837603786 2.729992172 1.122017234 1.084838622 #> [139] 1.047660011 1.010481400 0.973302789 0.936124177 1.096341126 2.432563281 #> [145] 0.627192784 0.676752511 0.089187952 0.308160723 0.478478338 0.857364233 #> [151] 2.172313002 0.564338064 0.527159453 0.109474465 6.092486429 5.913410763 #> [157] 5.876232152 6.160804095 1.874884112 6.131870152 6.154145200 6.278341699 #> [163] 0.155373340 0.118194729 0.191673339 0.043837506 1.577455222 6.252665591 #> [169] 6.215486980 #> #> $glendronach #> [1] 0.00000000 6.25129097 0.01935255 1.47511330 6.15560794 6.12371360 #> [7] 6.09181926 1.34753594 6.02803057 5.99613623 5.96424189 5.93234755 #> [13] 1.18806423 5.86855887 5.83666452 5.80477018 1.06048686 5.74098150 #> [19] 5.70908716 5.67719282 5.72843971 0.90101515 5.58150979 5.54961545 #> [25] 5.51772111 0.77343779 5.45393242 5.42203808 5.39014374 5.27510817 #> [31] 0.61396608 5.29446072 5.26256637 5.23067203 0.48638871 5.16688335 #> [37] 5.05184778 5.01995343 5.15434156 0.32691700 5.09055287 5.14066598 #> [43] 5.26537351 0.19933964 5.86262800 6.12023733 6.22169324 6.18979890 #> [49] 0.03986793 6.20801766 6.17612332 6.22737021 6.19547587 6.16358153 #> [55] 6.13168718 6.18293407 6.06789850 6.11914539 6.16925850 6.05535671 #> [61] 6.18529980 5.90842679 0.01997464 0.29426790 0.87355594 5.78084943 #> [67] 0.95342487 1.00467176 0.88963619 1.18586174 5.62137772 0.87709440 #> [73] 0.84520005 0.81330571 5.49380035 0.74951703 0.71762269 0.68572835 #> [79] 0.65383400 5.33432864 0.59004532 0.63492287 0.52625664 5.20675128 #> [85] 0.46246795 0.43057361 0.39867927 0.36678493 5.04727957 0.30299625 #> [91] 0.27110190 0.23920756 4.91970220 0.17541888 0.14352454 0.11163020 #> [97] 0.07973585 4.76023049 0.01594717 6.26723814 6.23534379 4.63265313 #> [103] 6.08841388 6.13966077 6.10776643 6.07587209 4.47318142 6.01208340 #> [109] 5.98018906 5.94829472 4.34560405 5.71935736 5.93575293 6.06569602 #> [115] 6.18361413 4.18613234 6.25310878 0.11221161 0.25411839 4.05855498 #> [121] 6.24095807 5.96035374 5.69881696 5.41863270 3.89908327 5.35484402 #> [127] 5.32294968 5.45733780 3.77150590 5.39354912 5.36165478 5.32976044 #> [133] 5.45970352 3.61203419 5.39591484 5.36402050 5.31394634 3.48445683 #> [139] 4.70160826 4.99146447 4.95957013 5.01081702 3.32498512 4.86388710 #> [145] 4.91513399 4.80009842 3.19740775 4.73630974 4.86956407 5.84852626 #> [151] 3.06983038 6.17952870 6.14763436 6.19251190 6.16698690 2.91035868 #> [157] 0.30360090 1.27577367 1.24387932 2.78278131 1.18009064 1.14819630 #> [163] 1.03316073 1.08440762 2.62330960 0.93747770 1.31047515 1.03997148 #> [169] 2.49573223 0.64806290 0.53939667 0.58427422 0.57055969 2.33626053 #> [175] 0.65042863 0.61853428 0.66978117 2.20868316 0.60599249 0.57409815 #> [181] 0.70735249 0.59345070 2.04921145 0.20154212 6.23416414 5.97117913 #> [187] 1.92163409 5.77327966 5.92673327 6.10593226 6.11165458 1.76216238 #> [193] 6.27750834 0.12757737 0.17882426 1.63458501 0.03189434 #> #> $glenmorangie #> [1] 0.00000000 0.02365423 1.50059314 6.17788053 6.20153475 6.22478608 #> [7] 1.36018676 6.03747415 6.00237256 6.02602678 1.21978039 6.02142277 #> [13] 5.86196618 5.88562041 1.07937401 5.75666140 5.72155980 5.74521403 #> [19] 0.93896764 5.73336377 5.64357224 5.54605184 0.79856126 5.47584865 #> [25] 5.50316586 5.52275420 0.65815489 5.33544227 5.30034068 5.32399491 #> [31] 0.51774851 5.19503590 5.09751549 4.74432633 0.37734213 4.61800236 #> [37] 4.95710912 5.15909853 0.23693576 5.73960000 6.03750744 6.12876484 #> [43] 0.09652938 6.22750435 6.12416355 6.21565409 6.23930831 6.26296254 #> [49] 6.11034930 6.20057170 6.09890194 6.18090909 6.08745457 6.17894511 #> [55] 5.95849556 0.02071504 6.22758499 0.42671110 5.81808919 1.01184279 #> [61] 1.09425284 1.49035275 5.67768281 1.23307711 0.95384647 0.79757024 #> [67] 5.53727644 0.78978586 0.75468427 0.59522768 5.39687006 0.59062366 #> [73] 0.61427789 0.45482130 5.25646369 0.45021729 0.41511569 0.43876992 #> [79] 5.11605731 0.36856674 0.33346514 0.18125480 4.97565093 0.16574155 #> [85] 0.19305877 0.04084843 4.83524456 0.08775398 6.27708188 0.01755080 #> [91] 4.69483818 6.16811411 6.19543132 6.16032973 4.55443181 5.96577155 #> [97] 6.05502495 6.01992335 4.41402543 6.07407516 6.14570924 6.16556842 #> [103] 4.27361906 6.24594095 6.21405478 0.05821264 4.13321268 6.27119476 #> [109] 6.17422532 6.13042829 3.99280631 5.72589660 5.73837811 5.63297005 #> [115] 3.85239993 5.44685049 5.35299307 5.31789148 3.71199355 5.37204328 #> [121] 5.21258669 5.17748510 3.57158718 5.10728191 5.07218032 5.09583455 #> [127] 3.43118080 4.96687554 4.86935513 4.61062091 3.29077443 4.94357791 #> [133] 4.85378638 4.75626597 3.15036805 5.65131445 6.16300170 6.18665592 #> [139] 3.00996168 6.11645274 6.14010696 0.69035946 2.86955530 1.26365738 #> [145] 1.11144704 1.19345419 2.72914893 1.35434167 1.08814941 1.05304782 #> [151] 2.58874255 0.86573588 0.94774304 0.91264144 2.44833617 0.84243825 #> [157] 0.74858084 0.77223507 2.30792980 0.70203188 0.66693028 0.63182869 #> [163] 2.16752342 0.31664684 0.18723129 0.20537087 2.02711705 6.19201497 #> [169] 6.15691338 5.98135462 1.88671067 6.00539874 6.08905388 6.15450226 #> [175] 1.74630430 6.16298929 6.15739942 0.01144737 1.60589792 #> #> $highlandpark #> [1] 0.000000000 6.246006696 1.496439104 6.171649473 6.134470862 6.097292251 #> [7] 1.347724659 6.022935028 5.914448952 6.019885270 1.199010214 5.802913118 #> [13] 5.913813863 5.799863360 1.050295769 5.725506138 5.688327527 0.938759935 #> [19] 5.613970304 5.576791693 5.539613081 0.790045490 5.465255859 5.428077248 #> [25] 5.390898636 0.641331045 5.316541414 5.208055338 5.242184191 0.492616600 #> [31] 5.096519504 5.130648357 0.381080766 5.461182921 6.095967481 6.209706299 #> [37] 0.232366321 6.251574168 0.086701633 0.049523022 0.083651875 6.118565238 #> [43] 0.009294653 6.255301349 6.218122737 6.180944126 6.215072980 6.106586904 #> [49] 6.140715757 6.103537146 6.066358535 5.957872458 6.062590902 6.025412290 #> [55] 5.988233679 5.809158013 5.983072735 0.280464542 0.843336144 5.660443568 #> [61] 0.982183441 0.873697365 5.548907734 0.941237197 0.762161531 0.724982920 #> [67] 5.400193289 0.721933162 0.613447086 0.576268475 5.251478844 0.501911252 #> [73] 0.464732641 0.427554030 5.102764399 0.353196807 0.316018196 4.991228565 #> [79] 0.241660973 0.204482362 0.167303751 4.842514120 0.092946528 0.055767917 #> [85] 0.018589306 4.693799675 6.227417390 6.190238779 6.153060168 4.545085230 #> [91] 6.078702945 6.041524334 6.004345723 4.396370784 5.929988500 5.892809889 #> [97] 4.284834951 5.818452666 5.709966590 5.672787979 4.136120505 5.811635276 #> [103] 6.096207219 0.137572542 3.987406060 0.237297316 0.366564398 0.329385787 #> [109] 3.838691615 6.114256599 5.487780048 3.727155781 5.118876442 5.294902350 #> [115] 5.397509607 3.578441336 5.253956106 5.146187905 5.037701829 3.429726891 #> [121] 4.685044948 4.926165995 4.888987384 3.281012446 4.814630161 5.075950482 #> [127] 3.169476612 5.779949285 6.094814988 6.128225967 3.020762167 6.196483674 #> [133] 6.159305063 0.045933338 2.872047722 0.478674620 1.226894172 1.331612616 #> [139] 2.723333277 1.186665803 1.149487192 2.611797443 1.145719559 0.966643893 #> [145] 0.787568228 2.463082998 0.644014726 0.746621983 0.709443372 2.314368552 #> [151] 0.706393614 0.205567394 5.838366741 2.165654107 5.613092090 5.752035653 #> [157] 2.054118274 5.710187298 6.036454405 0.004612279 1.905403828 0.226121425 #> [163] 0.331557744 0.294379132 1.756689383 0.220021910 0.111535834 0.074357223 #> [169] 1.607974938 #> #> $jackdaniels #> [1] 0.000000000 0.034883989 6.276181394 6.234293492 6.192405590 6.150517688 #> [7] 6.108629786 6.066741884 6.024853982 5.982966080 5.941078178 5.899190276 #> [13] 5.857302374 5.815414472 5.773526570 5.731638668 0.977361785 5.647862864 #> [19] 5.605974962 5.564087060 5.522199157 5.480311255 5.438423353 5.396535451 #> [25] 5.263987662 5.389531539 5.044072897 5.228983843 5.413894789 5.310356716 #> [31] 5.314413470 5.589506683 6.062266211 0.188495559 0.468358212 6.237878106 #> [37] 0.139603744 0.097715842 0.055827940 0.013940038 6.255237443 6.213349541 #> [43] 6.171461639 6.129573737 6.087685835 6.045797933 6.003910031 5.962022129 #> [49] 6.146933075 0.327876120 0.756795609 0.855282692 0.813394790 0.998305736 #> [55] 1.183216682 0.914529932 0.872642030 0.830754128 0.543887563 0.746978324 #> [61] 0.705090422 0.663202520 0.711974505 0.502654825 0.537538814 0.495650912 #> [67] 0.453763010 0.411875108 0.369987206 0.328099304 0.286211402 0.244323499 #> [73] 0.202435597 0.160547695 0.118659793 0.076771891 4.747272970 6.276181394 #> [79] 6.234293492 6.192405590 6.150517688 0.052243327 5.914092556 5.948082091 #> [85] 6.209764928 6.093727506 0.010796088 6.102281037 0.098958382 0.366399313 #> [91] 0.233851524 0.191963622 0.008178665 5.682746853 5.729235737 5.522199157 #> [97] 5.327661927 5.438423353 5.396535451 5.431419441 5.389531539 5.497670593 #> [103] 5.394132521 5.432074604 5.297857367 3.532523810 5.061432235 4.866895005 #> [109] 4.977656431 4.935768529 4.893880627 4.851992725 4.975253500 5.875365638 #> [115] 0.013940038 6.028438595 6.213349541 6.171461639 6.129573737 0.356155510 #> [121] 1.333408953 1.291521051 1.249633149 1.207745247 0.939058496 1.422468374 #> [127] 1.158853432 0.875044961 0.771506888 0.589244000 0.761880604 0.645843182 #> [133] 0.678104800 0.788866226 0.888875379 0.781862313 2.233998847 0.538173386 #> [139] 0.414278038 0.537538814 6.150039933 5.794948277 5.909662251 5.757117128 #> [145] 6.083210162 0.059412553 0.102426445 6.258822057 0.083775804 0.195431685 #> #> $jb #> [1] 0.0000000000 6.2470750468 6.1112961339 6.1748545260 6.2294041528 #> [6] 6.1026340052 6.0665237449 6.0304134845 5.9943032241 5.9581929637 #> [11] 5.9220827033 5.8859724429 5.8498621825 5.8137519222 5.7776416618 #> [16] 5.7891145047 5.7054211410 5.6693108806 5.6332006202 5.5970903598 #> [21] 5.5609800995 5.5248698391 5.4887595787 5.4526493183 5.4165390579 #> [26] 5.4710886847 5.2536586499 5.3082082768 5.3627579036 5.2359877560 #> [31] 5.1998774956 5.1637672352 5.0369970876 5.0915467144 5.0554364541 #> [36] 5.1099860809 5.4098434264 5.8568588308 6.0551642462 6.0969104753 #> [41] 0.0314342050 0.2146306455 0.1448252778 0.0180551302 6.2651301770 #> [46] 6.2290199166 6.1929096562 6.0571307433 6.1661124149 6.0845788751 #> [51] 6.0484686147 5.8149627944 6.0669079811 0.0374589034 0.1201889876 #> [56] 0.2594729478 0.7554391155 0.9034543118 1.0471975512 1.0110872908 #> [61] 1.1548305302 1.0295266572 0.9027565097 0.8666462493 0.8305359889 #> [66] 0.7944257285 0.7583154681 0.7222052077 0.6860949473 0.6499846869 #> [71] 0.6138744266 0.5777641662 0.5416539058 0.5055436454 0.4694333850 #> [76] 0.4333231246 0.3972128642 0.3611026039 0.4246609960 0.1982221959 #> [81] 0.3434317099 0.1690784590 0.2712111891 0.0537811543 0.1083307812 #> [86] 0.1198036240 0.0361102604 0.0000000000 6.2470750468 6.2109647864 #> [91] 6.1748545260 6.2384129181 6.1026340052 5.9758638577 5.9828303812 #> [96] 5.9943032241 5.8675330765 6.1019362031 6.2077229973 6.2764896757 #> [101] 0.2053075572 0.2798545180 0.3712538158 0.1600508939 6.1329584896 #> [106] 6.0137069973 5.5970903598 5.3635845396 5.4342099519 5.3980996915 #> [111] 5.4526493183 5.4165390579 5.4710886847 5.4349784243 5.4031599831 #> [116] 5.3627579036 5.3266476432 5.3972730554 5.3436207350 5.1752400781 #> [121] 5.0915467144 5.0554364541 5.0193261937 5.0781676396 4.7672521731 #> [126] 4.9109954125 4.9745538046 4.9806719463 4.8026646313 4.4077837007 #> [131] 5.1486684402 6.2197068976 6.2290199166 6.1929096562 6.1567993958 #> [136] 6.1682722387 6.0845788751 0.4087844163 1.4798228737 1.2139007178 #> [141] 1.1370889659 1.1916385927 1.1555283324 1.1194180720 1.0833078116 #> [146] 1.0471975512 1.0110872908 0.9749770304 0.8912836668 0.6365044605 #> [151] 0.6867927495 0.5642839397 0.6525286739 0.6676555809 0.5423517079 #> [156] 0.7857635998 0.5593247997 0.7937279264 0.6774328187 0.5416539058 #> [161] 0.5962035326 0.3697647325 0.0845521210 6.1136689539 5.8332543391 #> [166] 5.7751963840 5.8342523301 5.9071608435 6.1468564817 0.0006978021 #> [171] 6.2477728489 0.3057263410 0.1176438002 0.0361102604 #> #> $johnniewalker #> [1] 0.00000000 6.24578539 6.20838548 6.17098557 6.25794065 6.09618574 #> [7] 6.05878583 6.02138592 5.98398601 5.94658609 5.90918618 5.87178627 #> [13] 5.83438636 5.79698644 5.75958653 5.96716528 5.68478671 5.64738679 #> [19] 5.60998688 5.57258697 5.53518706 5.49778714 5.46038723 5.42298732 #> [25] 5.38558741 5.34818749 5.31078758 5.02840901 5.23598776 5.19858784 #> [31] 5.16118793 5.12378802 5.08638811 5.04898819 5.01158828 4.97418837 #> [37] 5.45593457 6.00653726 6.18780629 0.35717840 0.07479983 0.03739991 #> [43] 0.00000000 6.24578539 6.20838548 6.17098557 0.09537901 6.09618574 #> [49] 6.05878583 6.02138592 5.98398601 5.94658609 6.15416484 5.87178627 #> [55] 0.47849627 0.96024247 1.04719755 1.25477630 0.97239773 0.93499781 #> [61] 0.89759790 0.86019799 0.82279808 0.78539816 0.74799825 0.71059834 #> [67] 0.67319843 0.63579851 0.59839860 0.56099869 0.52359878 0.48619886 #> [73] 0.44879895 0.41139904 0.37399913 0.33659921 0.29919930 0.26179939 #> [79] 0.22439948 0.18699956 0.14959965 0.11219974 0.07479983 0.03739991 #> [85] 0.00000000 6.24578539 6.20838548 6.17098557 6.13358566 6.09618574 #> [91] 6.05878583 6.02138592 5.98398601 5.94658609 5.90918618 5.87178627 #> [97] 5.83438636 5.79698644 6.00456519 5.47720796 5.68478671 5.64738679 #> [103] 5.85496554 5.81756563 5.99883467 6.14128825 6.24578539 6.06648843 #> [109] 6.02908851 5.81183510 5.77443519 5.73703528 5.48096642 5.44356651 #> [115] 5.28554293 5.58743563 5.08638811 4.26359003 5.01158828 4.97418837 #> [121] 4.93678846 4.89938854 4.86198863 5.06956738 4.78718881 4.74978889 #> [127] 5.30039158 6.24578539 5.96340682 6.17098557 6.13358566 6.09618574 #> [133] 0.02057919 0.63425600 1.27159703 1.23419711 1.19679720 1.62304490 #> [139] 0.65834977 1.08459746 1.04719755 1.47344525 1.21737639 0.93499781 #> [145] 0.89759790 0.61521933 0.57781941 0.19739556 0.28435064 0.12259573 #> [151] 0.20955082 0.17215090 6.23808280 6.20068289 0.05995117 0.24122020 #> [157] 0.44879895 0.41139904 0.37399913 0.33659921 0.29919930 0.26179939 #> [163] 0.46937814 0.18699956 0.14959965 0.11219974 0.07479983 0.03739991 #> #> $magallan #> [1] 0.000000000 6.193200430 0.143753184 6.104077234 6.126083800 6.014954038 #> [7] 5.970392440 6.204130501 5.881269244 5.903275810 5.792146049 5.880135983 #> [13] 5.703022853 5.782816249 5.685207122 5.569338059 5.524776461 5.622111918 #> [19] 5.435653265 5.462399132 5.346530069 5.301968471 5.399303928 5.212845276 #> [25] 5.310180732 5.123722080 5.007853017 5.034598884 4.990037286 5.078027220 #> [31] 5.420060204 5.839146215 5.918939612 6.111226775 6.032861633 5.970602768 #> [37] 6.204340829 0.018490979 6.239572628 0.014269576 0.123415508 0.103239319 #> [43] 0.558613024 0.821249993 1.135459066 1.157465631 1.211484547 1.001774272 #> [49] 0.880440783 1.077799753 0.726192423 0.752220415 0.778966282 0.734404684 #> [55] 0.444864423 0.573974024 0.600719890 0.556158293 0.511596695 0.400466933 #> [61] 0.144173840 0.377911901 0.262042838 0.288788705 0.102330052 0.199665509 #> [67] 0.088535747 0.110542313 6.224811028 6.227832533 6.260042827 6.073584174 #> [73] 6.170919631 5.984460978 6.081796435 6.037234837 5.921365774 5.948111641 #> [79] 5.903550043 5.858988445 5.814426847 5.967260809 5.867200706 6.085633840 #> [85] 0.008690775 0.093831714 0.191167171 0.004708518 6.078183550 5.413372466 #> [91] 5.510707923 5.456800803 5.490781006 5.235126074 5.417363325 5.212571042 #> [97] 4.959544226 5.056879683 5.012318085 5.109653542 4.923194889 4.878633291 #> [103] 4.834071693 4.789510095 4.744948497 5.343888008 6.015528295 6.182060030 #> [109] 6.208805897 0.685809578 1.335986256 1.291424658 1.246863060 1.202301462 #> [115] 1.091171701 0.971281212 1.068616669 1.024055071 1.224472136 0.793034820 #> [121] 0.692974717 1.167559233 0.458223141 0.690117319 0.390373331 0.809459342 #> [127] 0.301250135 0.007101612 5.709914083 5.987103039 6.013848906 6.131723024 #> [133] 0.110652439 0.169172449 0.133956374 0.221946308 0.177384710 0.132823112 #> [139] 0.088261514 0.176251449 6.282323626 #> #> $makersmark #> [1] 0.000000000 0.161897338 0.186327271 2.249699824 0.432311942 0.381108205 #> [7] 0.430511776 0.536910609 0.698807947 2.036710492 0.353644051 0.461485884 #> [13] 0.359419499 0.465818331 1.859219381 0.252924832 0.444225458 0.253235853 #> [19] 0.217737631 0.308327504 1.646230049 0.111242965 0.087578510 6.252124363 #> [25] 0.075337888 1.468738938 6.145629697 6.110131475 0.002541279 6.191784359 #> [31] 6.003636808 1.255749606 6.143733697 6.264315976 6.228817754 6.193319532 #> [37] 1.078258496 6.076899808 0.387012565 0.839212297 0.936265607 0.900767385 #> [43] 0.865269163 0.829770941 0.794272719 0.758774497 0.723276275 0.687778053 #> [49] 0.652279831 0.616781609 0.581283386 0.545785164 0.652183997 0.474788720 #> [55] 0.439290498 0.403792276 0.579387387 0.851941946 1.589794278 0.261799388 #> [61] 1.475346938 1.329191495 1.465498657 1.463803978 0.084308277 1.487054850 #> [67] 1.584108160 1.337516605 1.360462388 1.477613494 6.154504252 1.406617050 #> [73] 1.218469499 1.124527272 1.300122383 5.977013142 1.096574407 1.193627717 #> [79] 0.947036162 1.122631273 0.945235996 5.764023809 1.016136607 0.753839537 #> [85] 0.945140163 0.756992612 5.586532699 0.838645497 0.955796603 0.767649052 #> [91] 1.075174771 1.063826442 5.373543367 1.119597533 1.245853568 1.469760420 #> [97] 1.434262198 5.196052256 1.398711895 0.761437835 1.162566773 1.127068551 #> [103] 0.377479630 4.983062924 0.163868256 0.199677499 0.230747441 0.270578110 #> [109] 4.805571813 0.190236143 0.022186389 0.139337495 0.272940499 6.198877030 #> [115] 4.592582481 6.127880586 6.245031692 6.123452305 6.021385919 4.415091371 #> [121] 6.082941008 6.047442785 5.879393031 5.772587344 5.879704052 4.202102038 #> [127] 5.737400143 5.701901921 5.666403699 5.828301036 4.024610928 5.701806087 #> [133] 6.135136775 0.498223949 0.741025386 0.705527164 3.811621595 0.634530720 #> [139] 0.599032498 0.885284830 1.470036094 1.836535310 3.598632263 1.992337714 #> [145] 1.804190163 1.921341270 1.674749714 3.421141152 1.814846604 1.976743941 #> [151] 1.532756826 1.708351937 1.406601666 3.208151820 1.601857271 1.489587158 #> [157] 1.530860827 1.353465550 3.030660710 1.357797997 1.256316406 1.353369717 #> [163] 1.120475935 1.140476218 2.817671377 1.211376828 0.964785273 1.140380384 #> [169] 1.365484554 2.640180267 0.807086870 0.038317133 5.973777186 0.584367111 #> [175] 0.230849661 2.427190934 6.153534852 #> #> $oban #> [1] 0.000000000 6.189327891 6.154226297 6.119124703 6.084023109 6.048921515 #> [7] 6.072575744 5.978718327 5.943616733 5.908515139 5.873413546 5.838311952 #> [13] 5.913867579 5.768108764 5.733007170 5.697905576 5.662803982 5.627702388 #> [19] 5.592600794 5.557499200 5.522397607 5.546051835 5.452194419 5.417092825 #> [25] 5.381991231 5.346889637 5.311788043 5.276686449 5.241584855 5.206483262 #> [31] 5.171381668 5.136280074 5.101178480 5.066076886 5.030975292 4.995873698 #> [37] 4.960772104 5.264963125 5.800322074 6.067492979 6.160071388 6.137391516 #> [43] 6.196603873 0.002671967 6.133646935 6.215654086 6.180552492 6.145450898 #> [49] 6.165847810 6.199602705 6.150803338 6.129399517 6.144615128 6.256591889 #> [55] 6.258510411 0.300282839 0.831096131 1.206400973 1.046944385 1.011842791 #> [61] 0.976741197 0.941639603 0.795880788 0.871436415 0.836334822 0.801233228 #> [67] 0.766131634 0.731030040 0.695928446 0.660826852 0.625725258 0.590623664 #> [73] 0.444864849 0.520420477 0.485318883 0.450217289 0.415115695 0.380014101 #> [79] 0.344912507 0.309810913 0.164052098 0.239607725 0.204506131 0.169404538 #> [85] 0.134302944 0.099201350 0.064099756 6.201526248 6.277081875 6.241980281 #> [91] 6.206878688 6.171777094 6.026018279 6.101573906 6.066472312 6.031370718 #> [97] 5.871914130 5.961167530 5.926065936 6.001621564 6.100841412 6.211368198 #> [103] 0.009572758 0.025971975 0.158913406 0.315119168 0.147466041 6.117250096 #> [109] 5.820028661 5.595446909 5.504846810 5.469745216 5.434643622 5.458297851 #> [115] 5.364440434 5.204983846 5.404894467 5.376244397 5.224034058 5.407601410 #> [121] 5.270939615 5.118729277 5.207982677 5.159183310 5.072180318 4.733344238 #> [127] 4.943221307 4.908119713 4.814262297 4.837916526 4.678459937 4.767713338 #> [133] 4.791367567 5.549476477 5.988226220 6.087446068 6.104245872 6.252255096 #> [139] 6.203455729 0.133282277 0.820249013 1.275104745 1.240003151 1.263657380 #> [145] 1.169799964 1.134698370 1.099596776 1.239167381 0.918736367 0.994291994 #> [151] 0.848533179 0.806980062 0.764632218 0.743228397 0.694429030 0.724926608 #> [157] 0.637923616 0.602822022 0.802732644 0.584520232 0.608174461 0.573072867 #> [163] 0.537971273 0.392212458 0.467768086 0.110915937 6.066087253 5.783478557 #> [169] 5.683251799 5.848803083 5.925680878 6.146471565 6.148390087 0.027498746 #> [175] 6.282828709 0.192307774 0.046548959 0.011447365 6.259531078 #> #> $oldpotrero #> [1] 0.00000000 6.20638390 6.15842066 0.03093063 0.10105941 0.15617777 #> [7] 0.20252848 0.33767605 0.23095698 0.18299373 0.13503049 0.20417598 #> [13] 0.03910399 6.27432605 6.22636281 6.23715538 6.13043631 6.08247307 #> [19] 6.03450982 6.04530240 5.93858333 5.89062008 5.84265683 5.79469359 #> [25] 5.74673034 5.80942431 6.00957452 0.18819469 0.42426404 0.57585618 #> [31] 0.38779121 0.58148989 0.53997817 0.49201492 0.43035390 0.44798982 #> [37] 0.45878240 0.41081915 0.36285591 0.37731147 0.58867997 0.34332116 #> [43] 0.49275348 0.46233229 0.58217493 0.73573945 1.22819571 1.61264024 #> [49] 1.33691102 1.40605652 1.35809327 1.19947281 1.26216678 1.21420353 #> [55] 1.16624029 1.11827704 1.01155797 1.02235055 0.97438730 0.92642405 #> [61] 0.87846081 0.70614257 0.78253432 0.73457107 0.68660782 0.63864458 #> [67] 0.59068133 0.76138703 0.83404745 0.96593770 0.90592685 1.01190826 #> [73] 0.90518920 0.89843971 0.79497796 0.82005528 0.59794809 0.18744061 #> [79] 0.33687292 0.18582807 0.09386807 6.15441794 6.21711191 6.05849144 #> [85] 6.06928402 5.96256495 6.02525892 5.86663846 5.81867521 5.88782071 #> [91] 5.72274872 5.67478547 5.75117722 5.46175023 5.40654074 5.48293248 #> [97] 5.79373991 5.20165804 5.33904274 6.15324955 0.42007005 0.48276402 #> [103] 0.43480078 0.51119253 0.44953151 1.25616270 1.81374412 2.12455154 #> [109] 1.39606707 1.79420937 1.73254835 1.69828288 1.41530742 1.47800139 #> [115] 1.21136920 1.38207490 1.33411165 1.28614840 1.23818516 1.19022191 #> [121] 1.03160144 1.03553960 1.04633217 0.87401393 0.83974846 0.65746377 #> [127] 0.43625486 0.56153728 0.25145419 0.10830210 0.07462359 #> #> $redbreast #> [1] 0.00000000 0.31063774 0.19199829 0.32869088 0.58464945 0.35175567 #> [7] 0.51365301 0.47815479 0.44265656 0.40715834 0.37166012 0.33616190 #> [13] 0.30066368 0.46256101 0.22966723 0.19416901 0.15867079 0.12317257 #> [19] 0.08767434 0.05217612 0.01667790 6.26436498 6.22886676 0.10757879 #> [25] 6.15787032 6.12237210 6.08687387 6.05137565 6.21327299 5.98037921 #> [31] 5.94488099 5.90938276 5.87388454 5.94904354 5.80288810 5.76738988 #> [37] 5.73189165 6.01814399 0.40808673 0.53250163 0.63253112 0.64461600 #> [43] 0.69585612 0.57361956 0.73551690 0.45504001 0.66452045 0.38404357 #> [49] 0.59352401 0.55802579 0.52252756 0.48702934 0.45153112 0.66101156 #> [55] 0.38053468 0.34503645 0.50693379 0.27404001 0.48352045 0.30271222 #> [61] 0.41252401 0.32944268 0.47705528 0.77988068 1.39895322 1.56085056 #> [67] 1.52535234 1.48985412 1.45435589 1.41885767 1.38335945 1.34786123 #> [73] 1.31236300 1.03188612 1.24136656 1.20586834 1.17037012 1.13487189 #> [79] 1.09937367 1.06387545 1.02837723 0.99287901 0.95738078 0.92188256 #> [85] 0.88638434 0.85088612 0.81538790 0.77988967 0.74439145 0.60922458 #> [91] 0.87079057 0.63789679 0.60239856 0.56690034 0.53140212 0.49590390 #> [97] 0.46040568 0.42490745 0.71115979 0.55130657 0.85883229 0.92641567 #> [103] 1.03281451 1.13921334 1.20679673 1.03697706 1.01517661 0.74466617 #> [109] 0.49807462 0.37943517 6.24661587 6.21111765 6.17561943 5.94272565 #> [115] 6.10462298 6.06912476 6.03362654 5.99812832 6.16002566 6.14580082 #> [121] 6.08902921 5.85613543 6.01803277 5.78513899 5.86029799 5.71414254 #> [127] 5.92362298 5.64314610 5.49699065 5.57214965 5.53665143 5.50115321 #> [133] 5.46565499 5.62755233 5.39465854 5.35916032 0.05267380 0.57577490 #> [139] 0.34288111 0.50477845 0.46928023 0.54443923 0.59567935 1.00628667 #> [145] 1.65310501 1.86258545 1.82708722 1.59419344 1.75609078 1.72059256 #> [151] 1.88248990 1.84699167 1.36911923 1.57859967 1.43244423 1.31020767 #> [157] 1.47210500 1.19162812 1.30143991 1.12063167 1.13271656 1.09721833 #> [163] 1.25911567 1.22361745 1.18811923 1.15262101 1.31451834 1.08162456 #> [169] 1.24352190 0.81323256 0.73015123 0.47598406 6.26002354 6.25576515 #> [175] 6.22026693 6.17107093 6.14927049 #> #> $tamdhu #> [1] 0.00000000 6.16765540 6.13195549 6.09625557 6.06055566 6.10162763 #> [7] 5.98915582 5.95345591 5.91775599 5.88205607 6.01150483 5.81065624 #> [13] 5.77495632 5.73925641 5.70355649 5.66785657 5.63215666 5.74910607 #> [19] 5.56075682 5.52505691 5.48935699 5.45365707 5.50109839 5.38225724 #> [25] 5.34655733 5.31085741 5.27515749 5.32259881 5.20375766 5.16805774 #> [31] 5.13235783 4.93150923 5.06095799 4.79845923 4.74457950 4.95385824 #> [37] 5.16313699 5.47046101 5.86589984 6.03308390 6.02440443 5.98870452 #> [43] 6.19161392 6.23905524 6.11661698 6.16765540 6.13195549 6.09625557 #> [49] 6.06055566 6.10799697 6.07229705 6.11860458 6.00089722 6.27684719 #> [55] 6.21352999 0.09420015 0.36782907 0.76061538 0.82601883 1.18226644 #> [61] 1.08491635 1.12904642 0.92819783 0.81266793 0.62431868 0.74126809 #> [67] 0.87071686 0.51721893 0.63416834 0.59846843 0.56276851 0.52706860 #> [73] 0.49136868 0.45566876 0.41996885 0.38426893 0.34856901 0.22972786 #> [79] 0.27716918 0.24146926 0.20576935 0.17006943 0.13436951 6.21670623 #> [85] 0.22811836 0.02726976 6.27475515 6.07390656 6.20335532 6.16765540 #> [91] 6.13195549 6.09625557 6.06055566 6.02485574 5.82400714 5.95345591 #> [97] 5.84098410 5.88205607 5.92312805 6.05563490 6.07345525 6.06100696 #> [103] 6.27028571 0.02817238 0.04370963 0.05108649 0.01038662 6.02440363 #> [109] 5.88414811 5.61880575 5.41795716 5.22960791 5.34655733 5.22771618 #> [115] 5.27515749 5.32259881 5.35640699 5.33320642 5.21549906 5.24930724 #> [121] 5.22610667 5.10202997 4.98955816 5.11900692 4.99493022 5.06231191 #> [127] 4.68160982 4.65840925 4.85849989 4.73965874 4.70395883 4.91323757 #> [133] 5.70400860 6.08451417 6.13195549 6.09625557 6.24040916 6.10162763 #> [139] 0.02772107 0.77741932 1.20536701 1.25280832 1.05719528 1.18140849 #> [145] 1.30754601 0.95009554 0.81131401 0.95546759 0.84299579 0.71891908 #> [151] 0.76853786 0.72952670 0.77696801 0.82440933 0.62242695 0.66986826 #> [157] 0.38918968 0.59846843 0.63954040 0.69221727 0.49136868 0.30301943 #> [163] 6.23950654 6.20380663 6.09133482 5.85823934 5.90465886 5.89585828 #> [169] 6.04143468 6.20827607 6.25240614 0.02189771 6.18100631 0.11041100 #> [175] 0.07471108 0.03901116 #> #> $wildturkey #> [1] 0.00000000 6.14248647 6.10852331 6.07456014 6.04059698 6.00663382 #> [7] 5.97267065 5.93870749 5.90474432 5.87078116 6.06361684 5.80285483 #> [13] 5.76889167 5.73492850 5.70096534 5.66700218 5.63303901 5.59907585 #> [19] 5.56511269 5.53114952 5.49718636 5.46322319 5.64035336 5.39529687 #> [25] 5.36133370 5.32737054 5.29340738 5.25944421 5.22548105 5.19151788 #> [31] 5.15755472 5.33468489 5.08962839 4.84457190 4.55805446 4.79034334 #> [37] 4.95377574 5.13090591 5.58058769 5.99027480 6.11041975 6.20210692 #> [43] 6.16814375 0.00364461 6.25286675 5.99210474 6.18494043 6.15097726 #> [49] 6.11701410 6.08305093 6.04908777 6.01512461 5.98116144 6.15829161 #> [55] 5.91323511 5.87927195 5.99795812 6.03814447 6.00418131 6.00402169 #> [61] 0.21166899 0.55821220 0.92914082 0.96648512 1.22838833 1.05405018 #> [67] 0.79328817 0.75932500 0.72536184 0.69139868 0.65743551 0.62347235 #> [73] 0.58950919 0.55554602 0.52158286 0.48761969 0.45365653 0.41969337 #> [79] 0.38573020 0.35176704 0.31780388 0.21253325 0.11732602 0.21591438 #> [85] 0.18195122 0.14798806 0.11402489 0.08006173 0.04609856 0.01213540 #> [91] 6.26135754 6.22739438 6.19343122 6.15946805 6.12550489 6.09154172 #> [97] 6.05757856 6.02361540 5.98965223 5.72889022 5.92172591 5.88776274 #> [103] 6.06489291 5.89114388 6.08437218 0.05672738 0.10073085 0.30562554 #> [109] 0.47398401 0.07068718 0.28170268 6.01177871 6.00810931 5.77870371 #> [115] 5.44624161 5.63907730 5.37831528 5.34435212 5.53718781 5.27642579 #> [121] 5.24246263 5.35039652 5.17453630 5.14057314 5.10660997 5.07264681 #> [127] 5.26548249 5.00472048 4.97075732 4.93679416 4.90283099 4.86886783 #> [133] 4.44011354 5.14396544 4.76697834 4.73301517 4.69905201 4.66508884 #> [139] 4.70243315 5.22595880 5.90719683 6.10003252 6.06606935 6.03210619 #> [145] 5.99814302 6.11682919 6.27324064 1.04196750 1.14990139 1.11593822 #> [151] 0.85517621 1.04801190 0.88149720 1.19117890 1.09877173 0.91215924 #> [157] 0.66710274 0.84423291 0.81026975 0.77630659 0.74234342 0.70838026 #> [163] 0.44761825 0.64045393 0.60649077 0.57252760 0.39666739 0.42782938 #> [169] 0.47063811 0.43667495 0.19161845 0.36874862 6.25079693 6.24098366 #> [175] 6.03089832 5.62002589 5.57729102 5.58598489 5.58534272 5.80889114 #> [181] 6.06796579 6.15965296 6.05154028 6.24437596 6.21041280 #> #> $yoichi #> [1] 0.00000000 6.23210250 6.18101969 6.12993689 6.07885408 6.16966832 #> [7] 5.97668846 5.92560566 5.87452285 5.82344004 5.77235723 5.72127443 #> [13] 5.67019162 5.61910881 5.56802600 5.51694320 5.46586039 5.41477758 #> [19] 5.36369477 5.24130450 5.32809732 5.21044635 5.15936354 5.10828074 #> [25] 5.05719793 5.34913906 6.03587132 6.26365250 0.07390956 0.02282675 #> [31] 0.03831211 6.14605961 6.21933180 6.16824899 6.11716618 6.13739084 #> [37] 6.01500057 6.03048592 5.98414242 6.05914771 6.21556113 0.39150192 #> [43] 0.99611474 0.94503194 0.89394913 0.84286632 0.79178351 0.74070071 #> [49] 0.62304974 0.63853509 0.58745228 0.53636948 0.48528667 0.43420386 #> [55] 0.38312106 0.33203825 0.28095544 0.16330447 0.17878983 0.12770702 #> [61] 0.07662421 0.02554140 6.25764390 6.20656110 6.08891012 6.10439548 #> [67] 6.05331267 6.00222987 5.95114706 5.83349609 5.84898144 5.79789864 #> [73] 5.81338399 5.82828455 6.04954200 6.05721502 6.20845384 0.19101021 #> [79] 0.29130285 6.21165446 5.54924670 5.28707056 5.23598776 5.18490495 #> [85] 5.13382214 5.15404680 4.96508836 4.78317816 4.92949091 4.81183994 #> [91] 4.82732530 4.91813954 5.85932885 6.10297615 6.19379039 6.14270759 #> [97] 6.09162478 6.23793753 0.75792407 1.15467991 1.24147273 1.05725360 #> [103] 1.07273895 1.28225854 0.97057334 0.85292237 0.86840773 0.81732492 #> [109] 0.76624211 0.64859114 0.25918471 6.03400894 5.71092702 5.87891268 #> [115] 6.06818963 6.20189044 0.14648632 0.23992868 0.25541404 0.20433123 #> [121] 0.15324842 0.10216561 0.11765097 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the area of a shape — coo_area","title":"Calculates the area of a shape — coo_area","text":"Calculates area (non-crossing) shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the area of a shape — coo_area","text":"","code":"coo_area(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the area of a shape — coo_area","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the area of a shape — coo_area","text":"numeric, area.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the area of a shape — coo_area","text":"Using area.poly gpc package good idea, licence impedes Momocs rely . function , gpc loaded: area.poly((coo, 'gpc.poly'))","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_area.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the area of a shape — coo_area","text":"","code":"coo_area(bot[1]) #> [1] 234515 # for the distribution of the area of the bottles dataset hist(sapply(bot$coo, coo_area), breaks=10)"},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots (lollipop) differences between two configurations — coo_arrows","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"Draws 'arrows' two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"","code":"coo_arrows(coo1, coo2, length = coo_centsize(coo1)/15, angle = 20, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"coo1 list matrix coordinates. coo2 list matrix coordinates. length length arrows. angle angle arrows ... optional parameters fed arrows.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_arrows.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots (lollipop) differences between two configurations — coo_arrows","text":"","code":"coo_arrows(coo_sample(olea[3], 50), coo_sample(olea[6], 50)) #> Warning: zero-length arrow is of indeterminate angle and so skipped title(\"Hi there !\")"},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":null,"dir":"Reference","previous_headings":"","what":"Register new baselines — coo_baseline","title":"Register new baselines — coo_baseline","text":"non-exact baseline registration t1 t2 coordinates, ldk1-th ldk2-th points. default returns Bookstein's coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register new baselines — coo_baseline","text":"","code":"coo_baseline(coo, ldk1, ldk2, t1, t2)"},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register new baselines — coo_baseline","text":"coo matrix (x; y) coordinates Coo object. ldk1 numeric id first point new baseline ldk2 numeric id second point new baseline t1 numeric (x; y) coordinates 1st point new baseline t2 numeric (x; y) coordinates 2nd point new baseline","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register new baselines — coo_baseline","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_baseline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register new baselines — coo_baseline","text":"","code":"h <- hearts %>% slice(1:5) # for speed sake stack(h) stack(coo_baseline(h, 2, 4, c(-1, 0), c(1, 1)))"},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":null,"dir":"Reference","previous_headings":"","what":"Register Bookstein's coordinates — coo_bookstein","title":"Register Bookstein's coordinates — coo_bookstein","text":"Registers new baseline shape, ldk1-th ldk2-th points set \\((x= -0.5; y=0)\\) \\((x= 0.5; y=0)\\), respectively.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Register Bookstein's coordinates — coo_bookstein","text":"","code":"coo_bookstein(coo, ldk1, ldk2)"},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Register Bookstein's coordinates — coo_bookstein","text":"coo matrix (x; y) coordinates Coo object. ldk1 numeric id first point new baseline (first, default) ldk2 numeric id second point new baseline (last, default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Register Bookstein's coordinates — coo_bookstein","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Register Bookstein's coordinates — coo_bookstein","text":", tries using $ldk slot. Also case Opn, landmark defined, first last point shape. Opn defines first landmark first point new shapes coo_slide.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_bookstein.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Register Bookstein's coordinates — coo_bookstein","text":"","code":"h <- hearts %>% slice(1:5) # for the sake of speed stack(h) stack(coo_bookstein(h, 2, 4)) h <- hearts[1] coo_plot(h) coo_plot(coo_bookstein(h, 20, 57), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates coordinates of the bounding box — coo_boundingbox","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"Calculates coordinates bounding box","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"","code":"coo_boundingbox(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"data.frame coordinates bounding box","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_boundingbox.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates coordinates of the bounding box — coo_boundingbox","text":"","code":"bot[1] %>% coo_boundingbox() #> # A tibble: 1 × 4 #> x0 x1 y0 y1 #> #> 1 33 316 14 1102 bot %>% coo_boundingbox() #> # A tibble: 40 × 4 #> x0 x1 y0 y1 #> * #> 1 33 316 14 1102 #> 2 51 312 26 1020 #> 3 48 291 11 654 #> 4 90 277 16 822 #> 5 36 323 53 939 #> 6 58 298 11 617 #> 7 54 268 5 870 #> 8 40 292 25 790 #> 9 67 297 17 759 #> 10 40 307 21 1069 #> # ℹ 30 more rows"},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the calliper length — coo_calliper","title":"Calculates the calliper length — coo_calliper","text":"Also called Feret's diameter, longest distance two points shape provided.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the calliper length — coo_calliper","text":"","code":"coo_calliper(coo, arr.ind = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the calliper length — coo_calliper","text":"coo matrix (x; y) coordinates Coo arr.ind logical, see .","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the calliper length — coo_calliper","text":"numeric, centroid size. arr.ind=TRUE, data_frame.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_calliper.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the calliper length — coo_calliper","text":"","code":"b <- bot[1] coo_calliper(b) #> [1] 1088.166 p <- coo_calliper(b, arr.ind=TRUE) p #> # A tibble: 1 × 2 #> length arr_ind #> #> 1 1088. p$length #> [1] 1088.166 ids <- p$arr_ind[[1]] coo_plot(b) segments(b[ids[1], 1], b[ids[1], 2], b[ids[2], 1], b[ids[2], 2], lty=2) # on a Coo bot %>% coo_sample(32) %>% # for speed sake coo_calliper() #> $brahma #> [1] 1087.768 #> #> $caney #> [1] 992.2107 #> #> $chimay #> [1] 644.5991 #> #> $corona #> [1] 806.6778 #> #> $deusventrue #> [1] 880.8053 #> #> $duvel #> [1] 606.7462 #> #> $franziskaner #> [1] 863.4501 #> #> $grimbergen #> [1] 766.5801 #> #> $guiness #> [1] 743.6162 #> #> $hoegardeen #> [1] 1046.608 #> #> $jupiler #> [1] 981.2747 #> #> $kingfisher #> [1] 717.4761 #> #> $latrappe #> [1] 746.2345 #> #> $lindemanskriek #> [1] 819.0562 #> #> $nicechouffe #> [1] 686.7001 #> #> $pecheresse #> [1] 927.4034 #> #> $sierranevada #> [1] 655.6706 #> #> $tanglefoot #> [1] 690.334 #> #> $tauro #> [1] 983.9842 #> #> $westmalle #> [1] 765.7114 #> #> $amrut #> [1] 864.1209 #> #> $ballantines #> [1] 711.5118 #> #> $bushmills #> [1] 882.1485 #> #> $chivas #> [1] 794.3198 #> #> $dalmore #> [1] 683.668 #> #> $famousgrouse #> [1] 607.8199 #> #> $glendronach #> [1] 821.1796 #> #> $glenmorangie #> [1] 986.0183 #> #> $highlandpark #> [1] 705.139 #> #> $jackdaniels #> [1] 798.2042 #> #> $jb #> [1] 1011.163 #> #> $johnniewalker #> [1] 337.8772 #> #> $magallan #> [1] 756.595 #> #> $makersmark #> [1] 858.3298 #> #> $oban #> [1] 858.7974 #> #> $oldpotrero #> [1] 596.5668 #> #> $redbreast #> [1] 425.3011 #> #> $tamdhu #> [1] 1007.425 #> #> $wildturkey #> [1] 1099.426 #> #> $yoichi #> [1] 714.077 #> bot %>% coo_sample(32) %>% # for speed sake coo_calliper(arr.ind=TRUE) #> # A tibble: 40 × 2 #> length arr_ind #> * #> 1 1088. #> 2 992. #> 3 645. #> 4 807. #> 5 881. #> 6 607. #> 7 863. #> 8 767. #> 9 744. #> 10 1047. #> # ℹ 30 more rows"},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns the distance between everypoints and the centroid — coo_centdist","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"every point shape, returns (centroid-points) distance.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"","code":"coo_centdist(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centdist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns the distance between everypoints and the centroid — coo_centdist","text":"","code":"b <- coo_sample(bot[1], 64) d <- coo_centdist(b) barplot(d, xlab=\"Points along the outline\", ylab=\"Distance to the centroid (pixels)\")"},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":null,"dir":"Reference","previous_headings":"","what":"Centers coordinates — coo_center","title":"Centers coordinates — coo_center","text":"Returns shape centered origin. two functions strictly equivalent.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Centers coordinates — coo_center","text":"","code":"coo_center(coo) coo_centre(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Centers coordinates — coo_center","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Centers coordinates — coo_center","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_center.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Centers coordinates — coo_center","text":"","code":"coo_plot(bot[1]) # same as coo_plot(coo_centre(bot[1])) # this coo_plot(coo_center(bot[1])) # on Coo objects b <- slice(bot, 1:5) # speed sake stack(slice(b, 1:5)) stack(coo_center(b))"},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate centroid coordinates — coo_centpos","title":"Calculate centroid coordinates — coo_centpos","text":"Returns (x; y) centroid coordinates shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate centroid coordinates — coo_centpos","text":"","code":"coo_centpos(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate centroid coordinates — coo_centpos","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate centroid coordinates — coo_centpos","text":"(x; y) coordinates centroid vector matrix.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centpos.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate centroid coordinates — coo_centpos","text":"","code":"b <- bot[1] coo_plot(b) xy <- coo_centpos(b) points(xy[1], xy[2], cex=2, col='blue') # on a Coo coo_centpos(bot) #> x y #> brahma 175.0580 543.8696 #> caney 182.7083 507.7560 #> chimay 169.0106 314.8095 #> corona 185.0155 407.2326 #> deusventrue 179.5592 467.2632 #> duvel 179.2484 287.1180 #> franziskaner 161.3548 423.2016 #> grimbergen 166.7460 394.8651 #> guiness 182.2022 372.0546 #> hoegardeen 173.2539 526.9275 #> jupiler 175.6026 510.9744 #> kingfisher 161.8407 365.2253 #> latrappe 176.0368 344.0147 #> lindemanskriek 163.9261 405.4034 #> nicechouffe 170.5548 338.1233 #> pecheresse 175.3023 489.5271 #> sierranevada 166.5795 333.5682 #> tanglefoot 174.5862 346.1724 #> tauro 175.5230 511.7644 #> westmalle 161.7943 383.0000 #> amrut 162.7225 420.5654 #> ballantines 174.2260 329.5000 #> bushmills 180.8303 432.3697 #> chivas 182.0244 405.7500 #> dalmore 176.4258 328.0452 #> famousgrouse 174.1065 299.2071 #> glendronach 173.2792 409.4365 #> glenmorangie 177.2514 493.9385 #> highlandpark 167.4852 346.6272 #> jackdaniels 182.8867 387.7600 #> jb 172.6149 509.0057 #> johnniewalker 174.4940 165.5655 #> magallan 167.2482 388.9149 #> makersmark 176.4802 402.7571 #> oban 176.5307 447.6536 #> oldpotrero 165.9160 284.7634 #> redbreast 176.8305 202.1977 #> tamdhu 173.7955 530.5625 #> wildturkey 173.7243 537.4973 #> yoichi 181.2764 361.1545"},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates centroid size — coo_centsize","title":"Calculates centroid size — coo_centsize","text":"Calculates centroid size","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates centroid size — coo_centsize","text":"","code":"coo_centsize(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates centroid size — coo_centsize","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates centroid size — coo_centsize","text":"numeric, centroid size.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates centroid size — coo_centsize","text":"function can used integrate size - meaningful - Coo objects. See also coo_length rescale.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_centsize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates centroid size — coo_centsize","text":"","code":"coo_centsize(bot[1]) #> [1] 364.1006 # on a Coo coo_centsize(bot) #> brahma caney chimay corona deusventrue #> 364.1006 332.6606 232.2377 267.1846 300.2182 #> duvel franziskaner grimbergen guiness hoegardeen #> 220.3785 289.6220 268.2272 256.6651 353.2312 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 325.0180 238.2959 275.5208 275.0680 230.9909 #> pecheresse sierranevada tanglefoot tauro westmalle #> 310.0406 230.7661 248.5782 325.6573 255.6335 #> amrut ballantines bushmills chivas dalmore #> 287.7783 259.1542 297.9153 283.8156 247.1982 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 204.7011 274.2665 328.5136 252.6141 274.6856 #> jb johnniewalker magallan makersmark oban #> 340.9851 114.5988 244.4261 297.1638 283.9853 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 208.3185 150.1516 337.8220 374.5002 249.7048 # add it to $fac mutate(bot, size=coo_centsize(bot)) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 40 × 3 #> type fake size #> #> 1 whisky a 364. #> 2 whisky a 333. #> 3 whisky a 232. #> 4 whisky a 267. #> 5 whisky a 300. #> 6 whisky a 220. #> # ℹ 34 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks shapes — coo_check","title":"Checks shapes — coo_check","text":"simple utility, used internally, mostly coo functions methods. Returns matrix coordinates, passed either list matrix coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks shapes — coo_check","text":"","code":"coo_check(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks shapes — coo_check","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks shapes — coo_check","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_check.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks shapes — coo_check","text":"","code":"#coo_check('Not a shape') #coo_check(iris) #coo_check(matrix(1:10, ncol=2)) #coo_check(list(x=1:5, y=6:10))"},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the (recursive) convex hull of a shape — coo_chull","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull returns ids points define convex hull shape. simple wrapper around chull, mainly used graphical functions.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"","code":"coo_chull(coo) # S3 method for default coo_chull(coo) # S3 method for Coo coo_chull(coo) coo_chull_onion(coo, close = TRUE) # S3 method for default coo_chull_onion(coo, close = TRUE) # S3 method for Coo coo_chull_onion(coo, close = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo matrix (x; y) coordinates Coo. close logical whether close onion rings (TRUE default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull returns matrix points defining convex hull shape; list Coo. coo_chull_onion returns list successive onions rings, list lists Coo.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"coo_chull_onion recursively find convex hull, remove , less 3 points left.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_chull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the (recursive) convex hull of a shape — coo_chull","text":"","code":"# coo_chull h <- coo_sample(hearts[4], 32) coo_plot(h) ch <- coo_chull(h) lines(ch, col='red', lty=2) bot %>% coo_chull #> $brahma #> [,1] [,2] #> [1,] 316 124 #> [2,] 316 113 #> [3,] 315 92 #> [4,] 311 71 #> [5,] 307 60 #> [6,] 290 40 #> [7,] 269 27 #> [8,] 259 24 #> [9,] 238 18 #> [10,] 217 16 #> [11,] 196 15 #> [12,] 164 14 #> [13,] 143 15 #> [14,] 111 19 #> [15,] 90 25 #> [16,] 80 29 #> [17,] 59 45 #> [18,] 47 66 #> [19,] 44 77 #> [20,] 40 98 #> [21,] 33 624 #> [22,] 33 645 #> [23,] 34 656 #> [24,] 105 1082 #> [25,] 120 1098 #> [26,] 131 1100 #> [27,] 173 1102 #> [28,] 183 1102 #> [29,] 205 1101 #> [30,] 226 1096 #> [31,] 232 1087 #> [32,] 307 681 #> [33,] 310 660 #> [34,] 311 629 #> #> $caney #> [,1] [,2] #> [1,] 312 392 #> [2,] 310 130 #> [3,] 305 89 #> [4,] 297 69 #> [5,] 291 60 #> [6,] 281 52 #> [7,] 263 42 #> [8,] 243 35 #> [9,] 213 29 #> [10,] 184 26 #> [11,] 164 26 #> [12,] 134 29 #> [13,] 124 31 #> [14,] 113 34 #> [15,] 94 42 #> [16,] 84 47 #> [17,] 75 53 #> [18,] 60 72 #> [19,] 55 91 #> [20,] 51 122 #> [21,] 51 253 #> [22,] 53 535 #> [23,] 55 555 #> [24,] 122 992 #> [25,] 126 1001 #> [26,] 144 1015 #> [27,] 154 1018 #> [28,] 164 1020 #> [29,] 195 1020 #> [30,] 215 1017 #> [31,] 235 1009 #> [32,] 243 1000 #> [33,] 245 990 #> [34,] 311 553 #> [35,] 312 523 #> #> $chimay #> [,1] [,2] #> [1,] 291 171 #> [2,] 291 56 #> [3,] 288 40 #> [4,] 284 33 #> [5,] 276 29 #> [6,] 268 26 #> [7,] 254 22 #> [8,] 238 18 #> [9,] 231 17 #> [10,] 208 14 #> [11,] 184 11 #> [12,] 155 11 #> [13,] 117 14 #> [14,] 109 15 #> [15,] 94 17 #> [16,] 86 20 #> [17,] 73 26 #> [18,] 63 40 #> [19,] 60 48 #> [20,] 57 64 #> [21,] 56 71 #> [22,] 52 148 #> [23,] 49 241 #> [24,] 48 348 #> [25,] 49 356 #> [26,] 115 640 #> [27,] 117 647 #> [28,] 125 651 #> [29,] 140 654 #> [30,] 194 654 #> [31,] 202 651 #> [32,] 208 646 #> [33,] 213 631 #> [34,] 284 364 #> [35,] 286 348 #> [36,] 290 248 #> #> $corona #> [,1] [,2] #> [1,] 276 111 #> [2,] 275 70 #> [3,] 271 39 #> [4,] 265 32 #> [5,] 246 23 #> [6,] 235 21 #> [7,] 205 17 #> [8,] 154 16 #> [9,] 123 25 #> [10,] 102 36 #> [11,] 97 46 #> [12,] 96 57 #> [13,] 94 87 #> [14,] 91 167 #> [15,] 90 395 #> [16,] 91 426 #> [17,] 144 815 #> [18,] 164 822 #> [19,] 216 822 #> [20,] 225 807 #> [21,] 229 786 #> [22,] 276 431 #> [23,] 277 391 #> #> $deusventrue #> [,1] [,2] #> [1,] 323 349 #> [2,] 323 319 #> [3,] 321 281 #> [4,] 318 232 #> [5,] 315 184 #> [6,] 313 165 #> [7,] 305 97 #> [8,] 300 78 #> [9,] 296 70 #> [10,] 287 63 #> [11,] 267 56 #> [12,] 228 53 #> [13,] 170 53 #> [14,] 122 56 #> [15,] 94 59 #> [16,] 65 70 #> [17,] 55 78 #> [18,] 49 108 #> [19,] 41 204 #> [20,] 36 271 #> [21,] 36 349 #> [22,] 41 379 #> [23,] 132 912 #> [24,] 134 922 #> [25,] 142 929 #> [26,] 162 937 #> [27,] 172 939 #> [28,] 191 939 #> [29,] 211 932 #> [30,] 225 919 #> [31,] 228 909 #> [32,] 315 406 #> [33,] 318 387 #> #> $duvel #> [,1] [,2] #> [1,] 298 65 #> [2,] 297 54 #> [3,] 295 43 #> [4,] 290 32 #> [5,] 282 21 #> [6,] 271 17 #> [7,] 228 12 #> [8,] 206 11 #> [9,] 163 11 #> [10,] 141 12 #> [11,] 86 18 #> [12,] 76 22 #> [13,] 66 32 #> [14,] 61 43 #> [15,] 58 54 #> [16,] 58 76 #> [17,] 59 272 #> [18,] 61 315 #> [19,] 63 337 #> [20,] 65 348 #> [21,] 135 595 #> [22,] 140 605 #> [23,] 149 611 #> [24,] 160 616 #> [25,] 171 617 #> [26,] 182 617 #> [27,] 193 616 #> [28,] 204 613 #> [29,] 215 606 #> [30,] 223 596 #> [31,] 226 586 #> [32,] 292 347 #> [33,] 295 336 #> [34,] 296 326 #> [35,] 297 315 #> [36,] 298 293 #> #> $franziskaner #> [,1] [,2] #> [1,] 268 79 #> [2,] 267 68 #> [3,] 265 48 #> [4,] 262 37 #> [5,] 246 19 #> [6,] 236 15 #> [7,] 215 10 #> [8,] 205 8 #> [9,] 175 5 #> [10,] 154 5 #> [11,] 133 7 #> [12,] 104 12 #> [13,] 94 15 #> [14,] 73 23 #> [15,] 63 32 #> [16,] 56 53 #> [17,] 55 63 #> [18,] 54 83 #> [19,] 54 480 #> [20,] 60 532 #> [21,] 120 867 #> [22,] 140 869 #> [23,] 151 870 #> [24,] 171 870 #> [25,] 202 867 #> [26,] 265 512 #> [27,] 266 492 #> #> $grimbergen #> [,1] [,2] #> [1,] 292 190 #> [2,] 290 107 #> [3,] 289 96 #> [4,] 282 65 #> [5,] 278 54 #> [6,] 258 39 #> [7,] 247 35 #> [8,] 237 32 #> [9,] 205 27 #> [10,] 184 25 #> [11,] 164 25 #> [12,] 122 27 #> [13,] 90 33 #> [14,] 70 40 #> [15,] 59 49 #> [16,] 51 59 #> [17,] 45 80 #> [18,] 43 101 #> [19,] 42 122 #> [20,] 40 320 #> [21,] 40 394 #> [22,] 44 425 #> [23,] 110 771 #> [24,] 121 789 #> [25,] 131 790 #> [26,] 194 790 #> [27,] 204 789 #> [28,] 215 785 #> [29,] 288 431 #> [30,] 290 420 #> [31,] 291 389 #> [32,] 292 326 #> #> $guiness #> [,1] [,2] #> [1,] 295 61 #> [2,] 292 53 #> [3,] 287 45 #> [4,] 280 36 #> [5,] 272 30 #> [6,] 239 21 #> [7,] 231 19 #> [8,] 214 18 #> [9,] 190 17 #> [10,] 157 17 #> [11,] 140 19 #> [12,] 116 22 #> [13,] 99 27 #> [14,] 86 36 #> [15,] 79 43 #> [16,] 73 56 #> [17,] 70 73 #> [18,] 67 418 #> [19,] 138 743 #> [20,] 141 751 #> [21,] 149 756 #> [22,] 157 757 #> [23,] 182 759 #> [24,] 206 759 #> [25,] 214 757 #> [26,] 221 752 #> [27,] 225 746 #> [28,] 294 431 #> [29,] 297 415 #> [30,] 297 406 #> #> $hoegardeen #> [,1] [,2] #> [1,] 307 262 #> [2,] 307 111 #> [3,] 304 61 #> [4,] 298 50 #> [5,] 285 38 #> [6,] 274 32 #> [7,] 262 29 #> [8,] 211 23 #> [9,] 187 21 #> [10,] 174 21 #> [11,] 124 23 #> [12,] 111 26 #> [13,] 86 32 #> [14,] 74 35 #> [15,] 62 41 #> [16,] 56 52 #> [17,] 51 64 #> [18,] 48 75 #> [19,] 46 88 #> [20,] 44 113 #> [21,] 42 139 #> [22,] 40 265 #> [23,] 40 531 #> [24,] 108 1037 #> [25,] 110 1049 #> [26,] 118 1062 #> [27,] 131 1066 #> [28,] 143 1068 #> [29,] 156 1069 #> [30,] 194 1069 #> [31,] 207 1068 #> [32,] 220 1064 #> [33,] 229 1055 #> [34,] 233 1042 #> [35,] 235 1032 #> [36,] 304 540 #> [37,] 305 527 #> #> $jupiler #> [,1] [,2] #> [1,] 290 176 #> [2,] 289 135 #> [3,] 288 121 #> [4,] 286 107 #> [5,] 280 80 #> [6,] 271 66 #> [7,] 259 55 #> [8,] 245 47 #> [9,] 231 42 #> [10,] 218 39 #> [11,] 190 35 #> [12,] 177 34 #> [13,] 163 34 #> [14,] 136 37 #> [15,] 122 39 #> [16,] 108 42 #> [17,] 95 46 #> [18,] 81 52 #> [19,] 67 64 #> [20,] 58 77 #> [21,] 53 91 #> [22,] 51 105 #> [23,] 48 132 #> [24,] 47 146 #> [25,] 54 501 #> [26,] 55 515 #> [27,] 125 989 #> [28,] 131 1002 #> [29,] 145 1013 #> [30,] 159 1017 #> [31,] 172 1018 #> [32,] 186 1018 #> [33,] 200 1017 #> [34,] 213 1014 #> [35,] 227 1007 #> [36,] 236 994 #> [37,] 239 981 #> [38,] 294 518 #> [39,] 295 490 #> [40,] 295 395 #> #> $kingfisher #> [,1] [,2] #> [1,] 258 151 #> [2,] 258 141 #> [3,] 256 102 #> [4,] 255 83 #> [5,] 253 73 #> [6,] 249 55 #> [7,] 244 45 #> [8,] 235 35 #> [9,] 216 27 #> [10,] 206 24 #> [11,] 188 20 #> [12,] 169 18 #> [13,] 159 18 #> [14,] 140 20 #> [15,] 130 22 #> [16,] 112 27 #> [17,] 104 31 #> [18,] 94 37 #> [19,] 85 46 #> [20,] 81 56 #> [21,] 78 65 #> [22,] 76 75 #> [23,] 75 84 #> [24,] 73 103 #> [25,] 71 316 #> [26,] 71 384 #> [27,] 73 413 #> [28,] 123 729 #> [29,] 132 735 #> [30,] 142 736 #> [31,] 171 736 #> [32,] 181 735 #> [33,] 189 729 #> [34,] 192 719 #> [35,] 253 384 #> [36,] 255 365 #> #> $latrappe #> [,1] [,2] #> [1,] 326 53 #> [2,] 325 40 #> [3,] 324 28 #> [4,] 313 19 #> [5,] 288 15 #> [6,] 276 14 #> [7,] 251 12 #> [8,] 238 11 #> [9,] 76 11 #> [10,] 63 12 #> [11,] 51 14 #> [12,] 38 18 #> [13,] 30 27 #> [14,] 28 52 #> [15,] 27 89 #> [16,] 25 239 #> [17,] 25 451 #> [18,] 28 464 #> [19,] 111 724 #> [20,] 118 737 #> [21,] 130 745 #> [22,] 142 747 #> [23,] 167 748 #> [24,] 205 747 #> [25,] 217 744 #> [26,] 230 721 #> [27,] 234 710 #> [28,] 318 477 #> [29,] 321 465 #> [30,] 324 452 #> [31,] 325 440 #> [32,] 326 427 #> #> $lindemanskriek #> [,1] [,2] #> [1,] 275 67 #> [2,] 274 59 #> [3,] 271 50 #> [4,] 267 43 #> [5,] 256 30 #> [6,] 248 27 #> [7,] 239 24 #> [8,] 231 22 #> [9,] 214 18 #> [10,] 197 15 #> [11,] 189 14 #> [12,] 146 14 #> [13,] 129 16 #> [14,] 113 18 #> [15,] 96 22 #> [16,] 87 25 #> [17,] 79 29 #> [18,] 71 34 #> [19,] 60 49 #> [20,] 57 58 #> [21,] 55 66 #> [22,] 54 75 #> [23,] 53 362 #> [24,] 54 395 #> [25,] 55 404 #> [26,] 119 810 #> [27,] 123 827 #> [28,] 131 831 #> [29,] 147 834 #> [30,] 164 835 #> [31,] 172 835 #> [32,] 181 834 #> [33,] 189 832 #> [34,] 205 823 #> [35,] 207 814 #> [36,] 269 411 #> [37,] 270 403 #> [38,] 272 386 #> #> $nicechouffe #> [,1] [,2] #> [1,] 267 157 #> [2,] 267 64 #> [3,] 266 48 #> [4,] 262 40 #> [5,] 258 33 #> [6,] 250 28 #> [7,] 226 19 #> [8,] 217 17 #> [9,] 150 17 #> [10,] 116 18 #> [11,] 108 20 #> [12,] 100 23 #> [13,] 84 34 #> [14,] 80 41 #> [15,] 77 50 #> [16,] 75 58 #> [17,] 74 269 #> [18,] 75 311 #> [19,] 77 336 #> [20,] 135 683 #> [21,] 138 692 #> [22,] 153 702 #> [23,] 161 703 #> [24,] 170 703 #> [25,] 186 701 #> [26,] 194 698 #> [27,] 199 691 #> [28,] 205 665 #> [29,] 261 350 #> [30,] 263 334 #> [31,] 266 300 #> #> $pecheresse #> [,1] [,2] #> [1,] 290 355 #> [2,] 286 164 #> [3,] 280 87 #> [4,] 272 67 #> [5,] 256 52 #> [6,] 246 46 #> [7,] 226 40 #> [8,] 207 38 #> [9,] 187 36 #> [10,] 138 36 #> [11,] 109 41 #> [12,] 89 48 #> [13,] 81 53 #> [14,] 65 68 #> [15,] 58 86 #> [16,] 56 96 #> [17,] 54 116 #> [18,] 54 165 #> [19,] 56 310 #> [20,] 58 428 #> [21,] 61 476 #> [22,] 63 495 #> [23,] 124 940 #> [24,] 128 948 #> [25,] 143 960 #> [26,] 161 964 #> [27,] 191 964 #> [28,] 209 962 #> [29,] 219 959 #> [30,] 232 950 #> [31,] 237 933 #> [32,] 288 471 #> [33,] 290 451 #> #> $sierranevada #> [,1] [,2] #> [1,] 275 95 #> [2,] 275 83 #> [3,] 272 58 #> [4,] 268 46 #> [5,] 257 35 #> [6,] 245 31 #> [7,] 208 27 #> [8,] 196 26 #> [9,] 122 26 #> [10,] 109 27 #> [11,] 85 31 #> [12,] 72 37 #> [13,] 65 49 #> [14,] 63 61 #> [15,] 61 74 #> [16,] 59 382 #> [17,] 63 407 #> [18,] 118 658 #> [19,] 123 669 #> [20,] 133 677 #> [21,] 145 679 #> [22,] 157 680 #> [23,] 169 680 #> [24,] 182 679 #> [25,] 194 677 #> [26,] 206 669 #> [27,] 268 403 #> [28,] 270 391 #> [29,] 271 379 #> [30,] 272 366 #> #> $tanglefoot #> [,1] [,2] #> [1,] 298 64 #> [2,] 294 48 #> [3,] 291 40 #> [4,] 286 32 #> [5,] 62 32 #> [6,] 56 38 #> [7,] 50 54 #> [8,] 48 70 #> [9,] 47 383 #> [10,] 47 391 #> [11,] 48 407 #> [12,] 49 415 #> [13,] 130 704 #> [14,] 133 712 #> [15,] 213 712 #> [16,] 220 707 #> [17,] 295 425 #> [18,] 299 409 #> [19,] 301 393 #> #> $tauro #> [,1] [,2] #> [1,] 295 398 #> [2,] 290 132 #> [3,] 288 119 #> [4,] 282 84 #> [5,] 277 73 #> [6,] 266 60 #> [7,] 254 52 #> [8,] 232 41 #> [9,] 220 39 #> [10,] 184 34 #> [11,] 160 34 #> [12,] 123 39 #> [13,] 112 41 #> [14,] 100 44 #> [15,] 77 55 #> [16,] 67 65 #> [17,] 58 78 #> [18,] 54 90 #> [19,] 50 113 #> [20,] 48 125 #> [21,] 48 198 #> [22,] 52 405 #> [23,] 54 503 #> [24,] 59 538 #> [25,] 124 980 #> [26,] 132 1003 #> [27,] 144 1012 #> [28,] 156 1015 #> [29,] 168 1017 #> [30,] 180 1018 #> [31,] 192 1018 #> [32,] 204 1017 #> [33,] 215 1013 #> [34,] 228 1007 #> [35,] 236 995 #> [36,] 241 973 #> [37,] 293 532 #> [38,] 295 496 #> #> $westmalle #> [,1] [,2] #> [1,] 258 105 #> [2,] 257 80 #> [3,] 255 64 #> [4,] 252 41 #> [5,] 246 35 #> [6,] 232 25 #> [7,] 224 22 #> [8,] 207 16 #> [9,] 199 14 #> [10,] 182 12 #> [11,] 157 11 #> [12,] 149 11 #> [13,] 132 14 #> [14,] 123 16 #> [15,] 107 20 #> [16,] 98 24 #> [17,] 74 38 #> [18,] 70 45 #> [19,] 68 87 #> [20,] 67 145 #> [21,] 66 244 #> [22,] 66 344 #> [23,] 67 369 #> [24,] 70 394 #> [25,] 117 761 #> [26,] 127 773 #> [27,] 134 776 #> [28,] 151 779 #> [29,] 159 779 #> [30,] 182 776 #> [31,] 197 768 #> [32,] 201 760 #> [33,] 254 389 #> [34,] 256 372 #> [35,] 259 339 #> #> $amrut #> [,1] [,2] #> [1,] 269 74 #> [2,] 268 54 #> [3,] 264 34 #> [4,] 257 25 #> [5,] 248 20 #> [6,] 228 14 #> [7,] 198 11 #> [8,] 129 11 #> [9,] 99 14 #> [10,] 89 16 #> [11,] 79 19 #> [12,] 69 24 #> [13,] 60 32 #> [14,] 58 42 #> [15,] 55 62 #> [16,] 54 72 #> [17,] 54 82 #> [18,] 55 501 #> [19,] 56 511 #> [20,] 124 864 #> [21,] 134 871 #> [22,] 144 874 #> [23,] 154 875 #> [24,] 174 875 #> [25,] 184 874 #> [26,] 193 871 #> [27,] 200 864 #> [28,] 269 513 #> #> $ballantines #> [,1] [,2] #> [1,] 313 107 #> [2,] 313 67 #> [3,] 312 59 #> [4,] 309 44 #> [5,] 303 20 #> [6,] 298 12 #> [7,] 284 4 #> [8,] 268 3 #> [9,] 118 3 #> [10,] 95 4 #> [11,] 79 5 #> [12,] 71 6 #> [13,] 55 11 #> [14,] 49 19 #> [15,] 43 34 #> [16,] 41 42 #> [17,] 38 58 #> [18,] 35 82 #> [19,] 35 121 #> [20,] 36 483 #> [21,] 38 499 #> [22,] 41 507 #> [23,] 133 704 #> [24,] 141 708 #> [25,] 156 710 #> [26,] 188 710 #> [27,] 204 707 #> [28,] 208 701 #> [29,] 304 508 #> [30,] 307 500 #> [31,] 309 484 #> #> $bushmills #> [,1] [,2] #> [1,] 291 60 #> [2,] 290 45 #> [3,] 284 29 #> [4,] 269 18 #> [5,] 253 14 #> [6,] 238 13 #> [7,] 176 11 #> [8,] 130 11 #> [9,] 115 12 #> [10,] 100 15 #> [11,] 85 25 #> [12,] 77 40 #> [13,] 74 56 #> [14,] 72 71 #> [15,] 68 564 #> [16,] 68 656 #> [17,] 70 672 #> [18,] 132 881 #> [19,] 147 891 #> [20,] 162 893 #> [21,] 193 893 #> [22,] 208 891 #> [23,] 221 881 #> [24,] 290 676 #> [25,] 292 661 #> #> $chivas #> [,1] [,2] #> [1,] 332 316 #> [2,] 329 77 #> [3,] 327 69 #> [4,] 322 61 #> [5,] 305 53 #> [6,] 272 47 #> [7,] 240 45 #> [8,] 223 44 #> [9,] 198 43 #> [10,] 166 43 #> [11,] 133 44 #> [12,] 100 46 #> [13,] 83 48 #> [14,] 75 49 #> [15,] 50 55 #> [16,] 36 67 #> [17,] 34 75 #> [18,] 29 379 #> [19,] 29 412 #> [20,] 31 429 #> [21,] 33 437 #> [22,] 135 828 #> [23,] 142 833 #> [24,] 158 835 #> [25,] 183 836 #> [26,] 191 836 #> [27,] 216 834 #> [28,] 224 832 #> [29,] 232 816 #> [30,] 330 431 #> [31,] 332 423 #> [32,] 333 398 #> #> $dalmore #> [,1] [,2] #> [1,] 325 63 #> [2,] 323 50 #> [3,] 314 40 #> [4,] 302 36 #> [5,] 228 34 #> [6,] 49 34 #> [7,] 40 39 #> [8,] 33 50 #> [9,] 32 62 #> [10,] 42 334 #> [11,] 44 346 #> [12,] 47 359 #> [13,] 136 701 #> [14,] 149 706 #> [15,] 186 706 #> [16,] 198 705 #> [17,] 210 702 #> [18,] 310 347 #> [19,] 311 334 #> #> $famousgrouse #> [,1] [,2] #> [1,] 254 58 #> [2,] 254 39 #> [3,] 252 29 #> [4,] 247 21 #> [5,] 238 16 #> [6,] 229 14 #> [7,] 219 12 #> [8,] 210 11 #> [9,] 143 11 #> [10,] 124 13 #> [11,] 114 16 #> [12,] 106 19 #> [13,] 100 28 #> [14,] 97 36 #> [15,] 96 370 #> [16,] 96 389 #> [17,] 98 399 #> [18,] 146 611 #> [19,] 153 617 #> [20,] 172 619 #> [21,] 192 617 #> [22,] 198 610 #> [23,] 246 410 #> [24,] 250 391 #> #> $glendronach #> [,1] [,2] #> [1,] 275 90 #> [2,] 274 66 #> [3,] 273 54 #> [4,] 270 41 #> [5,] 260 32 #> [6,] 249 27 #> [7,] 237 24 #> [8,] 213 21 #> [9,] 189 19 #> [10,] 153 19 #> [11,] 129 21 #> [12,] 105 25 #> [13,] 92 29 #> [14,] 80 37 #> [15,] 76 49 #> [16,] 74 61 #> [17,] 72 85 #> [18,] 72 495 #> [19,] 74 507 #> [20,] 134 832 #> [21,] 145 839 #> [22,] 157 840 #> [23,] 170 841 #> [24,] 194 841 #> [25,] 206 836 #> [26,] 273 500 #> [27,] 274 488 #> #> $glenmorangie #> [,1] [,2] #> [1,] 298 76 #> [2,] 297 59 #> [3,] 284 44 #> [4,] 252 32 #> [5,] 236 29 #> [6,] 202 26 #> [7,] 187 25 #> [8,] 153 25 #> [9,] 136 26 #> [10,] 103 31 #> [11,] 86 36 #> [12,] 70 43 #> [13,] 57 55 #> [14,] 54 72 #> [15,] 53 518 #> [16,] 53 550 #> [17,] 54 567 #> [18,] 133 998 #> [19,] 142 1010 #> [20,] 159 1011 #> [21,] 176 1011 #> [22,] 192 1011 #> [23,] 209 1010 #> [24,] 222 1001 #> [25,] 298 574 #> [26,] 300 558 #> [27,] 300 524 #> #> $highlandpark #> [,1] [,2] #> [1,] 295 55 #> [2,] 293 41 #> [3,] 282 29 #> [4,] 268 26 #> [5,] 226 20 #> [6,] 170 16 #> [7,] 128 16 #> [8,] 86 21 #> [9,] 73 24 #> [10,] 59 29 #> [11,] 46 36 #> [12,] 40 50 #> [13,] 39 469 #> [14,] 40 483 #> [15,] 117 705 #> [16,] 128 716 #> [17,] 142 720 #> [18,] 170 722 #> [19,] 184 721 #> [20,] 198 719 #> [21,] 211 712 #> [22,] 291 487 #> [23,] 293 473 #> #> $jackdaniels #> [,1] [,2] #> [1,] 301 68 #> [2,] 295 42 #> [3,] 290 29 #> [4,] 280 20 #> [5,] 267 17 #> [6,] 100 17 #> [7,] 87 18 #> [8,] 75 25 #> [9,] 68 37 #> [10,] 65 51 #> [11,] 60 76 #> [12,] 60 89 #> [13,] 63 414 #> [14,] 64 453 #> [15,] 65 466 #> [16,] 70 493 #> [17,] 137 802 #> [18,] 150 810 #> [19,] 189 810 #> [20,] 215 807 #> [21,] 227 801 #> [22,] 296 480 #> [23,] 301 454 #> #> $jb #> [,1] [,2] #> [1,] 305 102 #> [2,] 305 81 #> [3,] 303 70 #> [4,] 295 49 #> [5,] 285 41 #> [6,] 274 35 #> [7,] 264 31 #> [8,] 242 29 #> [9,] 106 29 #> [10,] 85 31 #> [11,] 74 35 #> [12,] 63 40 #> [13,] 54 47 #> [14,] 44 69 #> [15,] 43 80 #> [16,] 40 595 #> [17,] 44 617 #> [18,] 123 1030 #> [19,] 131 1036 #> [20,] 163 1037 #> [21,] 195 1037 #> [22,] 217 1036 #> [23,] 221 1027 #> [24,] 300 608 #> [25,] 302 597 #> #> $johnniewalker #> [,1] [,2] #> [1,] 218 24 #> [2,] 218 20 #> [3,] 217 12 #> [4,] 214 8 #> [5,] 206 7 #> [6,] 178 6 #> [7,] 146 5 #> [8,] 142 6 #> [9,] 138 8 #> [10,] 134 15 #> [11,] 132 211 #> [12,] 132 239 #> [13,] 154 337 #> [14,] 158 342 #> [15,] 162 343 #> [16,] 174 343 #> [17,] 186 342 #> [18,] 188 339 #> [19,] 215 240 #> [20,] 217 232 #> #> $magallan #> [,1] [,2] #> [1,] 241 57 #> [2,] 238 49 #> [3,] 227 35 #> [4,] 220 32 #> [5,] 205 26 #> [6,] 192 23 #> [7,] 170 20 #> [8,] 155 20 #> [9,] 120 29 #> [10,] 114 32 #> [11,] 99 42 #> [12,] 95 49 #> [13,] 93 64 #> [14,] 75 441 #> [15,] 75 484 #> [16,] 77 499 #> [17,] 79 513 #> [18,] 140 766 #> [19,] 150 778 #> [20,] 164 779 #> [21,] 171 779 #> [22,] 185 776 #> [23,] 194 764 #> [24,] 254 516 #> [25,] 258 494 #> [26,] 258 450 #> [27,] 257 414 #> #> $makersmark #> [,1] [,2] #> [1,] 328 144 #> [2,] 323 103 #> [3,] 321 88 #> [4,] 318 75 #> [5,] 314 60 #> [6,] 299 18 #> [7,] 285 10 #> [8,] 271 7 #> [9,] 228 5 #> [10,] 82 5 #> [11,] 67 7 #> [12,] 53 17 #> [13,] 33 71 #> [14,] 30 85 #> [15,] 25 127 #> [16,] 13 267 #> [17,] 11 296 #> [18,] 8 353 #> [19,] 8 367 #> [20,] 10 381 #> [21,] 16 408 #> [22,] 126 840 #> [23,] 134 851 #> [24,] 149 856 #> [25,] 207 856 #> [26,] 221 852 #> [27,] 228 842 #> [28,] 343 386 #> [29,] 345 358 #> [30,] 345 343 #> [31,] 343 315 #> #> $oban #> [,1] [,2] #> [1,] 275 74 #> [2,] 270 57 #> [3,] 262 50 #> [4,] 254 47 #> [5,] 245 44 #> [6,] 228 41 #> [7,] 220 40 #> [8,] 203 38 #> [9,] 185 37 #> [10,] 160 37 #> [11,] 134 39 #> [12,] 126 40 #> [13,] 117 42 #> [14,] 100 46 #> [15,] 92 49 #> [16,] 83 56 #> [17,] 77 73 #> [18,] 72 517 #> [19,] 74 534 #> [20,] 75 542 #> [21,] 138 879 #> [22,] 146 894 #> [23,] 154 897 #> [24,] 171 899 #> [25,] 188 898 #> [26,] 197 897 #> [27,] 205 895 #> [28,] 213 888 #> [29,] 279 535 #> [30,] 280 526 #> [31,] 280 500 #> #> $oldpotrero #> [,1] [,2] #> [1,] 271 93 #> [2,] 269 41 #> [3,] 266 32 #> [4,] 259 26 #> [5,] 250 21 #> [6,] 233 15 #> [7,] 224 12 #> [8,] 207 8 #> [9,] 191 7 #> [10,] 165 7 #> [11,] 148 8 #> [12,] 122 11 #> [13,] 105 13 #> [14,] 88 18 #> [15,] 79 22 #> [16,] 66 33 #> [17,] 63 41 #> [18,] 62 50 #> [19,] 58 205 #> [20,] 57 248 #> [21,] 58 256 #> [22,] 130 588 #> [23,] 139 601 #> [24,] 156 603 #> [25,] 182 603 #> [26,] 191 602 #> [27,] 198 596 #> [28,] 273 256 #> [29,] 273 204 #> #> $redbreast #> [,1] [,2] #> [1,] 255 78 #> [2,] 254 27 #> [3,] 253 22 #> [4,] 245 15 #> [5,] 240 13 #> [6,] 231 11 #> [7,] 217 9 #> [8,] 207 8 #> [9,] 189 7 #> [10,] 160 7 #> [11,] 146 8 #> [12,] 137 9 #> [13,] 123 11 #> [14,] 118 12 #> [15,] 114 13 #> [16,] 109 15 #> [17,] 104 18 #> [18,] 101 27 #> [19,] 100 50 #> [20,] 98 107 #> [21,] 97 163 #> [22,] 97 205 #> [23,] 98 214 #> [24,] 154 428 #> [25,] 158 431 #> [26,] 163 432 #> [27,] 172 433 #> [28,] 181 433 #> [29,] 191 432 #> [30,] 199 427 #> [31,] 255 214 #> [32,] 256 172 #> #> $tamdhu #> [,1] [,2] #> [1,] 304 106 #> [2,] 302 94 #> [3,] 299 83 #> [4,] 289 71 #> [5,] 278 64 #> [6,] 253 54 #> [7,] 229 51 #> [8,] 205 49 #> [9,] 155 49 #> [10,] 120 51 #> [11,] 108 52 #> [12,] 84 60 #> [13,] 73 64 #> [14,] 60 72 #> [15,] 52 84 #> [16,] 49 96 #> [17,] 44 613 #> [18,] 47 638 #> [19,] 49 650 #> [20,] 116 1038 #> [21,] 122 1050 #> [22,] 134 1054 #> [23,] 158 1057 #> [24,] 183 1057 #> [25,] 207 1055 #> [26,] 218 1049 #> [27,] 221 1037 #> [28,] 301 638 #> [29,] 302 625 #> #> $wildturkey #> [,1] [,2] #> [1,] 333 76 #> [2,] 333 63 #> [3,] 327 49 #> [4,] 316 38 #> [5,] 301 34 #> [6,] 275 28 #> [7,] 262 26 #> [8,] 220 23 #> [9,] 122 23 #> [10,] 81 26 #> [11,] 55 30 #> [12,] 41 34 #> [13,] 28 40 #> [14,] 18 52 #> [15,] 15 66 #> [16,] 15 625 #> [17,] 20 651 #> [18,] 120 1113 #> [19,] 134 1118 #> [20,] 147 1120 #> [21,] 203 1120 #> [22,] 216 1117 #> [23,] 224 1106 #> [24,] 326 648 #> [25,] 330 620 #> #> $yoichi #> [,1] [,2] #> [1,] 290 48 #> [2,] 280 35 #> [3,] 273 32 #> [4,] 258 29 #> [5,] 244 28 #> [6,] 229 27 #> [7,] 200 26 #> [8,] 156 26 #> [9,] 134 27 #> [10,] 104 29 #> [11,] 90 32 #> [12,] 75 40 #> [13,] 70 54 #> [14,] 69 120 #> [15,] 68 421 #> [16,] 68 472 #> [17,] 69 487 #> [18,] 72 501 #> [19,] 136 721 #> [20,] 144 735 #> [21,] 159 738 #> [22,] 203 738 #> [23,] 210 737 #> [24,] 225 730 #> [25,] 291 496 #> [26,] 293 481 #> [27,] 294 466 #> [28,] 294 437 #> coo_chull_onion #> function (coo, close = TRUE) #> { #> UseMethod(\"coo_chull_onion\") #> } #> #> x <- bot %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details all_whisky_points <- x %>% as_df() %>% filter(type==\"whisky\") %>% select(PC1, PC2) #> `retain` is too ambitious. All axes returned plot(x, ~type, eig=FALSE) #> will be deprecated soon, see ?plot_PCA peeling_the_whisky_onion <- all_whisky_points %>% as.matrix %>% coo_chull_onion() # you may need to par(xpd=NA) to ensure all segments # even those outside the graphical window are drawn peeling_the_whisky_onion$coo %>% lapply(coo_draw) #> [[1]] #> NULL #> #> [[2]] #> NULL #> #> [[3]] #> NULL #> # simulated data xy <- replicate(2, rnorm(50)) coo_plot(xy, poly=FALSE) xy %>% coo_chull_onion() %$% coo %>% lapply(polygon, col=\"#00000022\") #> [[1]] #> NULL #> #> [[2]] #> NULL #> #> [[3]] #> NULL #> #> [[4]] #> NULL #> #> [[5]] #> NULL #> #> [[6]] #> NULL #> #> [[7]] #> NULL #>"},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the Haralick's circularity of a shape — coo_circularity","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"coo_circularity calculates 'circularity measure'. Also called 'compactness' 'shape factor' sometimes. coo_circularityharalick calculates Haralick's circularity less sensible digitalization noise coo_circularity. coo_circularitynorm calculates 'circularity', also called compactness shape factor, normalized unit circle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"","code":"coo_circularity(coo) # S3 method for default coo_circularity(coo) # S3 method for Coo coo_circularity(coo) coo_circularityharalick(coo) # S3 method for default coo_circularityharalick(coo) # S3 method for Coo coo_circularityharalick(coo) coo_circularitynorm(coo) # S3 method for default coo_circularitynorm(coo) # S3 method for Coo coo_circularitynorm(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"numeric single shapes, list Coo corresponding circularity measurement.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_circularity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the Haralick's circularity of a shape — coo_circularity","text":"","code":"# coo_circularity bot[1] %>% coo_circularity() #> [1] 26.26463 bot %>% slice(1:5) %>% # for speed sake only coo_circularity #> $brahma #> [1] 26.26463 #> #> $caney #> [1] 25.60553 #> #> $chimay #> [1] 20.83278 #> #> $corona #> [1] 27.61134 #> #> $deusventrue #> [1] 25.75573 #> # coo_circularityharalick bot[1] %>% coo_circularityharalick() #> [1] 2.320493 bot %>% slice(1:5) %>% # for speed sake only coo_circularityharalick #> $brahma #> [1] 2.320493 #> #> $caney #> [1] 2.374045 #> #> $chimay #> [1] 2.935174 #> #> $corona #> [1] 2.261573 #> #> $deusventrue #> [1] 2.397828 #> # coo_circularitynorm bot[1] %>% coo_circularitynorm() #> [1] 2.090073 bot %>% slice(1:5) %>% # for speed sake only coo_circularitynorm #> $brahma #> [1] 2.090073 #> #> $caney #> [1] 2.037623 #> #> $chimay #> [1] 1.65782 #> #> $corona #> [1] 2.197241 #> #> $deusventrue #> [1] 2.049576 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":null,"dir":"Reference","previous_headings":"","what":"Closes/uncloses shapes — coo_close","title":"Closes/uncloses shapes — coo_close","text":"Returns closed shape (un)closed shapes. See also coo_unclose. Returns unclosed shape (un)closed shapes. See also coo_close.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Closes/uncloses shapes — coo_close","text":"","code":"coo_close(coo) coo_unclose(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Closes/uncloses shapes — coo_close","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Closes/uncloses shapes — coo_close","text":"matrix (x; y) coordinates, Coo object. matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_close.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Closes/uncloses shapes — coo_close","text":"","code":"x <- (matrix(1:10, ncol=2)) x2 <- coo_close(x) x3 <- coo_unclose(x2) x #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x) #> [1] FALSE x2 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 #> [6,] 1 6 coo_is_closed(x2) #> [1] TRUE x3 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x3) #> [1] FALSE x <- (matrix(1:10, ncol=2)) x2 <- coo_close(x) x3 <- coo_unclose(x2) x #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x) #> [1] FALSE x2 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 #> [6,] 1 6 coo_is_closed(x2) #> [1] TRUE x3 #> [,1] [,2] #> [1,] 1 6 #> [2,] 2 7 #> [3,] 3 8 #> [4,] 4 9 #> [5,] 5 10 coo_is_closed(x3) #> [1] FALSE"},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the convexity of a shape — coo_convexity","title":"Calculates the convexity of a shape — coo_convexity","text":"Calculated using ratio eigen values (inertia axis)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the convexity of a shape — coo_convexity","text":"","code":"coo_convexity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the convexity of a shape — coo_convexity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the convexity of a shape — coo_convexity","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the convexity of a shape — coo_convexity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_convexity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the convexity of a shape — coo_convexity","text":"","code":"coo_convexity(bot[1]) #> [1] 0.8003675 bot %>% slice(1:3) %>% # for speed sake only coo_convexity() #> $brahma #> [1] 0.8003675 #> #> $caney #> [1] 0.9409434 #> #> $chimay #> [1] 0.9454935 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":null,"dir":"Reference","previous_headings":"","what":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"Useful shapes aligned along x-axis (e.g. bilateral symmetry) one wants retain just lower side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"","code":"coo_down(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_down","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"shapes \"sliced\" along x-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_down.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"coo_down\nRetains coordinates with negative y-coordinates — coo_down","text":"","code":"b <- coo_alignxax(bot[1]) coo_plot(b) coo_draw(coo_down(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":null,"dir":"Reference","previous_headings":"","what":"Adds a shape to the current plot — coo_draw","title":"Adds a shape to the current plot — coo_draw","text":"coo_draw simply coo_plot plot.new=FALSE, ie adds shape active plot.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Adds a shape to the current plot — coo_draw","text":"","code":"coo_draw(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Adds a shape to the current plot — coo_draw","text":"coo list matrix coordinates. ... optional parameters coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Adds a shape to the current plot — coo_draw","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_draw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Adds a shape to the current plot — coo_draw","text":"","code":"b1 <- bot[4] b2 <- bot[5] coo_plot(b1) coo_draw(b2, border='red') # all coo_plot arguments will work for coo_draw"},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":null,"dir":"Reference","previous_headings":"","what":"Draw radii to the current plot — coo_draw_rads","title":"Draw radii to the current plot — coo_draw_rads","text":"Given shape, centroid-points radii drawn using segments can passed options","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draw radii to the current plot — coo_draw_rads","text":"","code":"coo_draw_rads(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draw radii to the current plot — coo_draw_rads","text":"coo shape ... arguments feed segments","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draw radii to the current plot — coo_draw_rads","text":"drawing last plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_draw_rads.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draw radii to the current plot — coo_draw_rads","text":"","code":"shp <- shapes[4] %>% coo_sample(24) %T>% coo_plot coo_draw_rads(shp, col=col_summer(24))"},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate abscissa and ordinate on a shape — coo_dxy","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"simple wrapper calculate dxi - dx1 dyi - dx1.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"","code":"coo_dxy(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"coo matrix (list) (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"data.frame two components dx dy single shapes list data.frames Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_dxy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate abscissa and ordinate on a shape — coo_dxy","text":"","code":"coo_dxy(coo_sample(bot[1], 12)) #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 26 -200 #> 3 5 -411 #> 4 106 -546 #> 5 279 -448 #> 6 268 -259 #> 7 258 -38 #> 8 259 152 #> 9 203 351 #> 10 168 540 #> 11 73 441 #> 12 45 220 bot %>% slice(1:5) %>% coo_sample(12) %>% # for readability and speed only coo_dxy() #> $brahma #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 26 -200 #> 3 5 -411 #> 4 106 -546 #> 5 279 -448 #> 6 268 -259 #> 7 258 -38 #> 8 259 152 #> 9 203 351 #> 10 168 540 #> 11 73 441 #> 12 45 220 #> #> $caney #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -192 #> 3 0 -373 #> 4 91 -507 #> 5 251 -436 #> 6 258 -244 #> 7 258 -73 #> 8 219 109 #> 9 193 299 #> 10 182 474 #> 11 76 392 #> 12 58 211 #> #> $chimay #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 3 -131 #> 3 7 -254 #> 4 99 -320 #> 5 227 -304 #> 6 242 -185 #> 7 239 -54 #> 8 209 83 #> 9 163 204 #> 10 145 321 #> 11 65 265 #> 12 49 145 #> #> $corona #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -155 #> 3 3 -298 #> 4 73 -409 #> 5 184 -346 #> 6 185 -201 #> 7 185 -46 #> 8 155 106 #> 9 145 246 #> 10 125 396 #> 11 53 309 #> 12 33 171 #> #> $deusventrue #> # A tibble: 12 × 2 #> dx dy #> #> 1 0 0 #> 2 -38 -171 #> 3 -28 -334 #> 4 86 -427 #> 5 231 -384 #> 6 245 -209 #> 7 234 -47 #> 8 168 123 #> 9 151 294 #> 10 137 451 #> 11 56 347 #> 12 57 197 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the eccentricity of a shape — coo_eccentricity","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"coo_eccentricityeigen uses ratio eigen values (inertia axes coordinates). coo_eccentricityboundingbox uses width/length ratio (see coo_lw).","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"","code":"coo_eccentricityeigen(coo) # S3 method for default coo_eccentricityeigen(coo) # S3 method for Coo coo_eccentricityeigen(coo) coo_eccentricityboundingbox(coo) # S3 method for default coo_eccentricityboundingbox(coo) # S3 method for Coo coo_eccentricityboundingbox(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"numeric single shapes, list Coo.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_eccentricity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the eccentricity of a shape — coo_eccentricity","text":"","code":"# coo_eccentricityeigen bot[1] %>% coo_eccentricityeigen() #> [1] 0.09292547 bot %>% slice(1:3) %>% # for speed sake only coo_eccentricityeigen() #> $brahma #> [1] 0.09292547 #> #> $caney #> [1] 0.100634 #> #> $chimay #> [1] 0.1813198 #> # coo_eccentricityboundingbox bot[1] %>% coo_eccentricityboundingbox() #> [1] 0.2555899 bot %>% slice(1:3) %>% # for speed sake only coo_eccentricityboundingbox() #> $brahma #> [1] 0.2555899 #> #> $caney #> [1] 0.2617262 #> #> $chimay #> [1] 0.3744498 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the elongation of a shape — coo_elongation","title":"Calculates the elongation of a shape — coo_elongation","text":"Calculates elongation shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the elongation of a shape — coo_elongation","text":"","code":"coo_elongation(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the elongation of a shape — coo_elongation","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the elongation of a shape — coo_elongation","text":"coo matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the elongation of a shape — coo_elongation","text":"numeric, eccentricity bounding box","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_elongation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the elongation of a shape — coo_elongation","text":"","code":"coo_elongation(bot[1]) #> [1] 0.7444101 # on Coo # for speed sake bot %>% slice(1:3) %>% coo_elongation #> $brahma #> [1] 0.7444101 #> #> $caney #> [1] 0.7382738 #> #> $chimay #> [1] 0.6255502 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract coordinates from a shape — coo_extract","title":"Extract coordinates from a shape — coo_extract","text":"Extract ids coordinates single shape Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract coordinates from a shape — coo_extract","text":"","code":"coo_extract(coo, ids)"},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract coordinates from a shape — coo_extract","text":"coo either matrix (x; y) coordinates Coo object. ids integer, ids points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract coordinates from a shape — coo_extract","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract coordinates from a shape — coo_extract","text":"probably make sense Coo objects number coordinates homologous, typically Ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_extract.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract coordinates from a shape — coo_extract","text":"","code":"coo_extract(bot[1], c(3, 9, 12)) # or : #> [,1] [,2] #> [1,] 40 529 #> [2,] 57 414 #> [3,] 63 361 bot[1] %>% coo_extract(c(3, 9, 12)) #> [,1] [,2] #> [1,] 40 529 #> [2,] 57 414 #> [3,] 63 361"},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":null,"dir":"Reference","previous_headings":"","what":"Flips shapes — coo_flipx","title":"Flips shapes — coo_flipx","text":"coo_flipx flips shapes x-axis; coo_flipy y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flips shapes — coo_flipx","text":"","code":"coo_flipx(coo) coo_flipy(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flips shapes — coo_flipx","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Flips shapes — coo_flipx","text":"matrix (x; y) coordinates","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_flip.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flips shapes — coo_flipx","text":"","code":"cat <- shapes[4] cat <- coo_center(cat) coo_plot(cat) coo_draw(coo_flipx(cat), border=\"red\") coo_draw(coo_flipy(cat), border=\"blue\") #' # to flip an entire Coo: shapes2 <- shapes shapes$coo <- lapply(shapes2$coo, coo_flipx)"},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":null,"dir":"Reference","previous_headings":"","what":"Forces shapes to close — coo_force2close","title":"Forces shapes to close — coo_force2close","text":"exotic function distribute distance first last points unclosed shapes, become closed. May useful (?) e.g. t/rfourier methods reconstructed shapes may closed.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Forces shapes to close — coo_force2close","text":"","code":"coo_force2close(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Forces shapes to close — coo_force2close","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Forces shapes to close — coo_force2close","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_force2close.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Forces shapes to close — coo_force2close","text":"","code":"b <- coo_sample(bot[1], 64) b <- b[1:40,] coo_plot(b) coo_draw(coo_force2close(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":null,"dir":"Reference","previous_headings":"","what":"Interpolates coordinates — coo_interpolate","title":"Interpolates coordinates — coo_interpolate","text":"Interpolates n coordinates 'among existing points'' existing points, along perimeter coordinates provided keeping first point","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Interpolates coordinates — coo_interpolate","text":"","code":"coo_interpolate(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Interpolates coordinates — coo_interpolate","text":"coo matrix (x; y) coordinates Coo object. n integer, number fo points interpolate.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Interpolates coordinates — coo_interpolate","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_interpolate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Interpolates coordinates — coo_interpolate","text":"","code":"b5 <- bot %>% slice(1:5) # for speed sake stack(b5) stack(coo_scale(b5)) stack(b5) stack(coo_interpolate(coo_sample(b5, 12), 120)) coo_plot(bot[1]) coo_plot(coo_interpolate(coo_sample(bot[1], 12), 120))"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":null,"dir":"Reference","previous_headings":"","what":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"Take shape, segment starting centroid particular angle, point nearest segment intersects shape?","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"","code":"coo_intersect_angle(coo, angle = 0) coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for default coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Coo coo_intersect_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4])"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"coo matrix (x; y) coordinates Coo object. angle numeric angle radians (0 default). direction character one \"\", \"left\", \"\", \"right\" (\"right\" default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"numeric id nearest point list Coo See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"shapes always centered operation. need simple direction (, left, , right)ward, use coo_intersect_direction need find intersection relies coordinates 1000.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_angle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Nearest intersection between a shape and a segment specified with an angle — coo_intersect_angle","text":"","code":"coo <- bot[1] %>% coo_center %>% coo_scale coo_plot(coo) coo %>% coo_intersect_angle(pi/7) %>% coo[., , drop=FALSE] %>% points(col=\"red\") # many angles coo_plot(coo) sapply(seq(0, pi, pi/12), function(x) coo %>% coo_intersect_angle(x)) -> ids coo[ids, ] %>% points(col=\"blue\") coo %>% coo_intersect_direction(\"down\") %>% coo[.,, drop=FALSE] %>% points(col=\"orange\")"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":null,"dir":"Reference","previous_headings":"","what":"Nearest intersection between a shape and a segment — coo_intersect_segment","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"Take shape, intersecting segment, point nearest segment intersects shape? time, centering makes sense.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"","code":"coo_intersect_segment(coo, seg, center = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"coo matrix (x; y) coordinates Coo object. seg 2x2 matrix defining starting ending points; list numeric length 4. center logical whether center shape (TRUE default)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"numeric id nearest point, list Coo. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_intersect_segment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Nearest intersection between a shape and a segment — coo_intersect_segment","text":"","code":"coo <- bot[1] %>% coo_center %>% coo_scale seg <- c(0, 0, 2, 2) # passed as a numeric of length(4) coo_plot(coo) segments(seg[1], seg[2], seg[3], seg[4]) coo %>% coo_intersect_segment(seg) %T>% print %>% # prints on the console and draw it coo[., , drop=FALSE] %>% points(col=\"red\") #> [1] 79 # on Coo bot %>% slice(1:3) %>% # for the sake of speed coo_center %>% coo_intersect_segment(matrix(c(0, 0, 1000, 1000), ncol=2, byrow=TRUE)) #> $brahma #> [1] 79 #> #> $caney #> [1] 96 #> #> $chimay #> [1] 110 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":null,"dir":"Reference","previous_headings":"","what":"Test if shapes are closed — coo_is_closed","title":"Test if shapes are closed — coo_is_closed","text":"Returns TRUE/FALSE whether last coordinate shapes first one.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Test if shapes are closed — coo_is_closed","text":"","code":"coo_is_closed(coo) is_open(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Test if shapes are closed — coo_is_closed","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Test if shapes are closed — coo_is_closed","text":"single vector logical.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_is_closed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Test if shapes are closed — coo_is_closed","text":"","code":"coo_is_closed(matrix(1:10, ncol=2)) #> [1] FALSE coo_is_closed(coo_close(matrix(1:10, ncol=2))) #> [1] TRUE coo_is_closed(bot) #> brahma caney chimay corona deusventrue #> FALSE FALSE FALSE FALSE FALSE #> duvel franziskaner grimbergen guiness hoegardeen #> FALSE FALSE FALSE FALSE FALSE #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> FALSE FALSE FALSE FALSE FALSE #> pecheresse sierranevada tanglefoot tauro westmalle #> FALSE FALSE FALSE FALSE FALSE #> amrut ballantines bushmills chivas dalmore #> FALSE FALSE FALSE FALSE FALSE #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> FALSE FALSE FALSE FALSE FALSE #> jb johnniewalker magallan makersmark oban #> FALSE FALSE FALSE FALSE FALSE #> oldpotrero redbreast tamdhu wildturkey yoichi #> FALSE FALSE FALSE FALSE FALSE coo_is_closed(coo_close(bot)) #> brahma caney chimay corona deusventrue #> TRUE TRUE TRUE TRUE TRUE #> duvel franziskaner grimbergen guiness hoegardeen #> TRUE TRUE TRUE TRUE TRUE #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> TRUE TRUE TRUE TRUE TRUE #> pecheresse sierranevada tanglefoot tauro westmalle #> TRUE TRUE TRUE TRUE TRUE #> amrut ballantines bushmills chivas dalmore #> TRUE TRUE TRUE TRUE TRUE #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> TRUE TRUE TRUE TRUE TRUE #> jb johnniewalker magallan makersmark oban #> TRUE TRUE TRUE TRUE TRUE #> oldpotrero redbreast tamdhu wildturkey yoichi #> TRUE TRUE TRUE TRUE TRUE"},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":null,"dir":"Reference","previous_headings":"","what":"Jitters shapes — coo_jitter","title":"Jitters shapes — coo_jitter","text":"simple wrapper around jitter.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Jitters shapes — coo_jitter","text":"","code":"coo_jitter(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Jitters shapes — coo_jitter","text":"coo matrix (x; y) coordinates Coo object. ... additional parameter jitter","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Jitters shapes — coo_jitter","text":"matrix (x; y) coordinates Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_jitter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Jitters shapes — coo_jitter","text":"","code":"b <-bot[1] coo_plot(b, zoom=0.2) coo_draw(coo_jitter(b, amount=3), border=\"red\") # for a Coo example, see \\link{get_pairs}"},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines landmarks interactively — coo_ldk","title":"Defines landmarks interactively — coo_ldk","text":"Allows interactively define nb.ldk number landarks shape. Used facilities acquire/manipulate data.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines landmarks interactively — coo_ldk","text":"","code":"coo_ldk(coo, nb.ldk, close = FALSE, points = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines landmarks interactively — coo_ldk","text":"coo matrix list (x; y) coordinates. nb.ldk integer, number landmarks define close logical whether close (typically outlines) points logical whether display points","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines landmarks interactively — coo_ldk","text":"numeric corresponds closest ids, shape, cliked points.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines landmarks interactively — coo_ldk","text":"","code":"if (FALSE) { b <- bot[1] coo_ldk(b, 3) # run this, and click 3 times coo_ldk(bot, 2) # this also works on Out }"},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with negative x-coordinates — coo_left","title":"Retains coordinates with negative x-coordinates — coo_left","text":"Useful shapes aligned along y-axis (e.g. bilateral symmetry) one wants retain just lower side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with negative x-coordinates — coo_left","text":"","code":"coo_left(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with negative x-coordinates — coo_left","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_left","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with negative x-coordinates — coo_left","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with negative x-coordinates — coo_left","text":"shapes \"sliced\" along y-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_left.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with negative x-coordinates — coo_left","text":"","code":"b <- coo_center(bot[1]) coo_plot(b) coo_draw(coo_left(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the length of a shape — coo_length","title":"Calculates the length of a shape — coo_length","text":"Nothing coo_lw(coo)[1].","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the length of a shape — coo_length","text":"","code":"coo_length(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the length of a shape — coo_length","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the length of a shape — coo_length","text":"length (pixels) shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the length of a shape — coo_length","text":"function can used integrate size - meaningful - Coo objects. See also coo_centsize rescale.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the length of a shape — coo_length","text":"","code":"coo_length(bot[1]) #> [1] 1087.831 coo_length(bot) #> brahma caney chimay corona deusventrue #> 1087.8309 994.1615 643.8746 805.9889 886.0715 #> duvel franziskaner grimbergen guiness hoegardeen #> 606.0107 865.0272 765.0962 742.1752 1048.1058 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 984.2303 718.3227 737.3475 821.1190 686.2766 #> pecheresse sierranevada tanglefoot tauro westmalle #> 928.6771 654.2412 680.6856 984.3941 768.0226 #> amrut ballantines bushmills chivas dalmore #> 864.0899 707.8465 882.0460 793.0187 672.0897 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 608.2238 822.0508 986.0991 705.9991 793.1392 #> jb johnniewalker magallan makersmark oban #> 1008.1334 337.7117 759.0041 851.3161 862.0016 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 596.0958 426.0429 1008.3194 1097.1657 712.1001 mutate(bot, size=coo_length(bot)) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 40 × 3 #> type fake size #> #> 1 whisky a 1088. #> 2 whisky a 994. #> 3 whisky a 644. #> 4 whisky a 806. #> 5 whisky a 886. #> 6 whisky a 606. #> # ℹ 34 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":null,"dir":"Reference","previous_headings":"","what":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"Tests shapes (likely) developping clockwise anticlockwise","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"","code":"coo_likely_clockwise(coo) # S3 method for default coo_likely_clockwise(coo) # S3 method for Coo coo_likely_clockwise(coo) coo_likely_anticlockwise(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"single vector logical.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_likely_clockwise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tests if shapes are (likely) developping clockwise or anticlockwise — coo_likely_clockwise","text":"","code":"shapes[4] %>% coo_sample(64) %>% coo_plot() #clockwise cat shapes[4] %>% coo_likely_clockwise() #> [1] TRUE shapes[4] %>% coo_rev() %>% coo_likely_clockwise() #> [1] FALSE # on Coo shapes %>% coo_likely_clockwise %>% `[`(4) #> cat #> TRUE"},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots sets of shapes. — coo_listpanel","title":"Plots sets of shapes. — coo_listpanel","text":"coo_listpanel plots list shapes passed list coordinates. Mainly used panel.Coo functions. used outside latter, shapes must \"templated\", see coo_template. want reorder shapes according factor, use arrange.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots sets of shapes. — coo_listpanel","text":"","code":"coo_listpanel( coo.list, dim, byrow = TRUE, fromtop = TRUE, cols, borders, poly = TRUE, points = FALSE, points.pch = 3, points.cex = 0.2, points.col = \"#333333\", ... )"},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots sets of shapes. — coo_listpanel","text":"coo.list list coordinates dim vector form (nb.row, nb.cols) specify panel display. missing, shapes arranged square. byrow logical. Whether draw successive shape row col. fromtop logical. Whether display shapes top plotting region. cols vector colors fill shapes. borders vector colors draw shape borders. poly logical whether use polygon lines draw shapes. mainly use outlines open outlines. points logical poly set FALSE whether add points points.pch points TRUE, pch points points.cex points TRUE, cex points points.col points TRUE, col points ... additional arguments feed generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots sets of shapes. — coo_listpanel","text":"Returns (invisibly) data.frame position shapes can used sophisticated plotting design.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_listpanel.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots sets of shapes. — coo_listpanel","text":"","code":"coo_listpanel(bot$coo) # equivalent to panel(bot)"},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots (lollipop) differences between two configurations — coo_lolli","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"Draws 'lollipops' two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"","code":"coo_lolli(coo1, coo2, pch = NA, cex = 0.5, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"coo1 list matrix coordinates. coo2 list matrix coordinates. pch pch points (default NA) cex cex points ... optional parameters fed points segments.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_lolli.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots (lollipop) differences between two configurations — coo_lolli","text":"","code":"coo_lolli(coo_sample(olea[3], 50), coo_sample(olea[6], 50)) title(\"A nice title !\")"},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates length and width of a shape — coo_lw","title":"Calculates length and width of a shape — coo_lw","text":"Returns length width shape based iniertia axis .e. alignment x-axis. length defined range along x-axis; width range y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates length and width of a shape — coo_lw","text":"","code":"coo_lw(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates length and width of a shape — coo_lw","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates length and width of a shape — coo_lw","text":"vector two numeric: length width.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_lw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates length and width of a shape — coo_lw","text":"","code":"coo_lw(bot[1]) #> [1] 1087.8309 278.0386"},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":null,"dir":"Reference","previous_headings":"","what":"Counts coordinates — coo_nb","title":"Counts coordinates — coo_nb","text":"Returns number coordinates, single shape Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Counts coordinates — coo_nb","text":"","code":"coo_nb(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Counts coordinates — coo_nb","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Counts coordinates — coo_nb","text":"either single numeric vector numeric","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_nb.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Counts coordinates — coo_nb","text":"","code":"# single shape coo_nb(bot[1]) #> [1] 138 # Coo object coo_nb(bot) #> brahma caney chimay corona deusventrue #> 138 168 189 129 152 #> duvel franziskaner grimbergen guiness hoegardeen #> 161 124 126 183 193 #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> 156 182 136 176 146 #> pecheresse sierranevada tanglefoot tauro westmalle #> 129 176 174 174 141 #> amrut ballantines bushmills chivas dalmore #> 191 146 165 164 155 #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> 169 197 179 169 150 #> jb johnniewalker magallan makersmark oban #> 174 168 141 177 179 #> oldpotrero redbreast tamdhu wildturkey yoichi #> 131 177 176 185 123"},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":null,"dir":"Reference","previous_headings":"","what":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"Shape analysis deals curve fitting, whether \\(x(t)\\) \\(y(t)\\) positions along curvilinear abscissa /radius/tangent angle variation. functions mainly intended (self-)teaching Fourier-based methods.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"","code":"coo_oscillo( coo, method = c(\"efourier\", \"rfourier\", \"tfourier\", \"all\")[4], shape = TRUE, nb.pts = 12 )"},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"coo list matrix coordinates. method character among c('efourier', 'rfourier', 'tfourier', ''). '' default shape logical whether plot original shape nb.pts integer. number reference points, sampled equidistantly along curvilinear abscissa added oscillo curves.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"plotted values","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_oscillo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Momocs' 'oscilloscope' for Fourier-based approaches — coo_oscillo","text":"","code":"coo_oscillo(shapes[4]) #> [1] 0.00000000 4.70353942 3.90929170 3.90044215 3.89159259 4.66814120 #> [7] 3.87389348 3.07964576 6.21238885 6.20353930 6.19468974 6.18584018 #> [13] 6.17699063 5.38274291 6.15929151 6.15044196 6.14159240 5.34734468 #> [19] 6.12389329 5.32964557 5.32079601 4.52654829 5.30309689 4.50884917 #> [25] 4.49999962 4.49115006 3.69690234 4.47345095 3.67920323 2.88495551 #> [31] 3.66150411 2.86725639 2.85840684 2.84955728 2.84070772 2.83185817 #> [37] 2.82300861 2.81415905 2.80530950 3.58185810 2.78761038 2.77876083 #> [43] 2.76991127 2.76106171 2.75221216 2.74336260 2.73451304 2.72566349 #> [49] 2.71681393 2.70796437 2.69911482 2.69026526 2.68141570 2.67256614 #> [55] 2.66371659 2.65486703 2.64601747 1.85176975 3.41371652 1.83407064 #> [61] 2.61061925 2.60176969 2.59292013 2.58407058 2.57522102 2.56637146 #> [67] 2.55752191 2.54867235 2.53982279 2.53097324 2.52212368 2.51327412 #> [73] 2.50442457 2.49557501 2.48672545 2.47787590 2.46902634 2.46017678 #> [79] 2.45132723 2.44247767 2.43362811 2.42477856 2.41592900 2.40707944 #> [85] 2.39822988 2.38938033 2.38053077 2.37168121 2.36283166 1.56858394 #> [91] 2.34513254 2.33628299 2.32743343 3.88938020 3.88053064 3.87168109 #> [97] 3.07743337 3.85398197 3.84513242 3.83628286 3.82743330 3.81858375 #> [103] 4.59513235 3.80088463 3.79203508 4.56858368 4.55973413 3.76548641 #> [109] 4.54203501 4.53318546 5.30973406 4.51548634 4.50663679 5.28318539 #> [115] 4.48893767 5.26548628 4.47123856 5.24778717 5.23893761 4.44468989 #> [121] 5.22123849 5.21238894 4.41814122 5.19468982 5.18584027 5.17699071 #> [127] 5.16814115 4.37389343 5.15044204 5.14159248 5.13274293 5.12389337 #> [133] 5.11504381 5.10619426 5.09734470 5.08849514 4.29424742 5.07079603 #> [139] 5.06194647 5.05309692 5.04424736 5.03539780 5.02654825 5.80309685 #> [145] 5.00884913 4.99999958 4.99115002 4.98230046 4.97345091 4.96460135 #> [151] 4.95575179 5.73230040 4.93805268 4.92920312 4.92035356 4.91150401 #> [157] 4.90265445 5.67920306 4.88495534 4.87610578 4.86725622 4.85840667 #> [163] 4.84955711 4.84070755 4.83185800 4.82300844 4.81415888 4.80530933 #> [169] 4.79645977 4.00221205 3.99336249 3.19911477 2.40486705 2.39601750 #> [175] 1.60176978 2.37831838 1.58407066 2.36061927 1.56637155 2.34292016 #> [181] 1.54867243 1.53982288 2.31637148 1.52212376 1.51327421 2.28982281 #> [187] 1.49557509 1.48672554 2.26327414 1.46902642 1.46017687 1.45132731 #> [193] 2.22787592 1.43362820 1.42477864 1.41592908 2.19247769 1.39822997 #> [199] 0.60398225 2.16592902 1.37168130 1.36283174 1.35398219 1.34513263 #> [205] 1.33628307 1.32743352 1.31858396 1.30973440 1.30088485 1.29203529 #> [211] 1.28318573 1.27433617 1.26548662 1.25663706 1.24778750 1.23893795 #> [217] 1.23008839 1.22123883 1.21238928 0.41814156 1.19469016 1.18584061 #> [223] 1.17699105 1.16814149 0.37389377 1.15044238 1.14159282 0.34734510 #> [229] 1.12389371 1.11504415 0.32079643 1.09734504 0.30309732 1.07964593 #> [235] 0.28539821 1.06194681 0.26769909 0.25884954 1.03539814 0.24115042 #> [241] 0.23230087 0.22345131 0.21460175 0.20575219 0.19690264 0.18805308 #> [247] 5.67699067 0.17035397 5.65929155 0.15265485 5.64159244 0.13495574 #> [253] 5.62389333 5.61504377 0.10840707 5.59734466 5.58849510 5.57964554 #> [259] 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 5.52654820 #> [265] 5.51769865 5.50884909 5.49999953 4.70575181 5.48230042 5.47345086 #> [271] 4.67920314 5.45575175 5.44690219 4.65265447 5.42920308 5.42035352 #> [277] 4.62610580 4.61725625 5.39380485 5.38495529 5.37610574 4.58185802 #> [283] 5.35840662 6.13495523 4.55530935 5.33185795 5.32300840 5.31415884 #> [289] 5.30530928 6.08185789 4.50221201 6.06415878 5.26991106 5.26106150 #> [295] 5.25221194 5.24336239 6.01991099 4.44026511 6.00221188 5.20796416 #> [301] 5.19911460 5.19026505 5.18141549 5.17256593 5.16371638 5.94026498 #> [307] 5.14601726 4.35176954 5.12831815 5.11946859 5.89601720 5.10176948 #> [313] 5.09291992 5.08407036 5.07522081 5.06637125 5.05752169 5.04867214 #> [319] 5.03982258 5.03097302 5.02212347 5.01327391 5.00442435 4.99557480 #> [325] 4.98672524 4.97787568 4.96902613 4.96017657 4.95132701 4.94247746 #> [331] 4.93362790 4.13938018 4.91592879 5.69247739 4.11283151 4.88938012 #> [337] 4.88053056 4.87168100 4.86283145 4.06858373 4.84513233 4.83628278 #> [343] 4.04203506 4.81858366 4.80973410 4.01548638 4.79203499 3.99778727 #> [349] 4.77433588 3.98008816 4.75663676 3.96238904 4.73893765 3.94468993 #> [355] 4.72123854 3.92699082 4.70353942 3.90929170 4.68584031 3.89159259 #> [361] 4.66814120 3.87389348 4.65044208 3.85619436 3.84734481 3.83849525 #> [367] 4.61504386 3.82079614 3.81194658 4.58849519 3.79424747 3.78539791 #> [373] 3.77654835 3.76769880 3.75884924 3.74999968 3.74115012 3.73230057 #> [379] 3.72345101 3.71460145 2.92035373 3.69690234 2.90265462 3.67920323 #> [385] 2.88495551 2.87610595 3.65265456 2.85840684 2.84955728 3.62610589 #> [391] 2.83185817 2.82300861 3.59955722 3.59070766 2.79645994 3.57300855 #> [397] 2.77876083 3.55530943 3.54645988 2.75221216 3.52876076 3.51991121 #> [403] 3.51106165 3.50221209 3.49336254 3.48451298 3.47566342 4.25221203 #> [409] 3.45796431 3.44911475 4.22566336 3.43141564 4.20796424 3.41371652 #> [415] 4.19026513 4.18141557 4.17256602 4.16371646 4.15486690 4.14601735 #> [421] 4.92256595 3.34292007 4.11946868 4.11061912 4.10176956 3.30752184 #> [427] 4.08407045 4.07522089 3.28097317 4.05752178 3.26327406 4.03982267 #> [433] 4.03097311 3.23672539 3.22787583 4.00442444 3.21017672 3.98672533 #> [439] 3.19247761 3.18362805 3.17477849 3.16592893 3.15707938 2.36283166 #> [445] 3.13938026 3.13053071 2.33628299 3.11283159 2.31858387 3.09513248 #> [451] 3.08628292 3.07743337 3.85398197 3.84513242 3.05088470 3.82743330 #> [457] 3.03318558 3.80973419 3.01548647 3.00663691 3.78318552 2.98893780 #> [463] 2.98008824 3.75663685 2.96238913 2.95353957 2.15929185 2.93584046 #> [469] 2.14159274 1.34734502 1.33849546 1.32964590 0.53539818 0.52654863 #> [475] 0.51769907 1.29424768 5.99778710 0.49115040 0.48230084 1.25884945 #> [481] 0.46460173 0.45575217 0.44690262 0.43805306 0.42920350 0.42035395 #> [487] 0.41150439 0.40265483 0.39380528 1.95575205 1.94690249 1.15265477 #> [493] 1.92920338 1.92035382 1.12610610 1.90265471 1.10840699 1.88495559 #> [499] 1.09070787 1.86725648 1.07300876 0.27876104 1.05530964 1.04646009 #> [505] 0.25221237 1.02876097 1.01991142 1.01106186 1.78761047 1.77876091 #> [511] 0.98451319 1.76106180 0.96681408 0.95796452 0.16371680 0.94026541 #> [517] 0.14601769 5.63495527 0.12831857 0.11946902 5.60840660 0.10176990 #> [523] 0.09292035 5.58185793 5.57300838 5.56415882 5.55530926 5.54645971 #> [529] 5.53761015 5.52876059 4.73451287 5.51106148 5.50221192 4.70796420 #> [535] 5.48451281 5.47566325 6.25221186 6.24336230 6.23451274 6.22566319 #> [541] 6.21681363 6.20796407 6.19911452 0.69247782 5.39601724 0.67477870 #> [547] 6.16371629 6.15486673 6.14601718 6.13716762 0.63053092 5.33407034 #> [553] 0.61283181 6.10176939 6.09291984 6.08407028 6.07522072 6.06637117 #> [559] 6.05752161 0.55088491 5.25442433 6.03097294 6.02212338 6.01327383 #> [565] 6.00442427 0.49778757 5.20132699 5.97787560 5.96902604 5.96017649 #> [571] 5.95132693 5.94247737 5.93362781 5.92477826 5.13053054 5.90707914 #> [577] 5.89822959 5.10398187 5.88053047 5.87168092 5.07743320 5.85398180 #> [583] 5.05973408 5.05088453 5.82743313 5.03318541 5.02433586 5.80088446 #> [589] 5.00663674 4.99778719 5.77433579 4.98008807 4.97123852 5.74778712 #> [595] 5.73893757 4.94468985 4.93584029 5.71238890 5.70353934 4.90929162 #> [601] 5.68584023 5.67699067 5.66814111 4.87389339 5.65044200 5.64159244 #> [607] 5.63274288 5.62389333 4.82964561 5.60619421 5.59734466 5.58849510 #> [613] 5.57964554 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 #> [619] 5.52654820 5.51769865 5.50884909 5.49999953 5.49114998 5.48230042 #> [625] 5.47345086 5.46460131 5.45575175 5.44690219 5.43805264 5.42920308 #> [631] 5.42035352 5.41150397 5.40265441 5.39380485 5.38495529 5.37610574 #> [637] 5.36725618 5.35840662 5.34955707 5.34070751 5.33185795 5.32300840 #> [643] 6.09955700 5.30530928 5.29645973 5.28761017 5.27876061 5.26991106 #> [649] 5.26106150 6.03761011 0.53097341 6.01991099 0.51327429 0.50442474 #> [655] 0.49557518 5.98451277 0.47787607 0.46902651 5.95796410 5.16371638 #> [661] 5.94026498 4.36061910 5.13716771 4.34291999 4.33407043 4.32522087 #> [667] 5.88716764 4.30752176 5.86946853 4.28982264 4.28097309 4.27212353 #> [673] 3.47787581 4.25442442 3.46017670 3.45132714 3.44247758 3.43362803 #> [679] 3.42477847 3.41592891 3.40707936 3.39822980 3.38938024 2.59513252 #> [685] 3.37168113 2.57743341 2.56858385 2.55973430 2.55088474 2.54203518 #> [691] 2.53318563 1.73893791 2.51548651 2.50663696 1.71238924 2.48893784 #> [697] 1.69469012 2.47123873 1.67699101 2.45353961 1.65929189 1.65044234 #> [703] 2.42699094 1.63274322 1.62389367 3.18584044 4.74778721 4.73893765 #> [709] 4.73008809 3.93584037 coo_oscillo(shapes[4], 'efourier') #> # A tibble: 710 × 2 #> dx dy #> #> 1 0 0 #> 2 0 -1 #> 3 -1 -2 #> 4 -2 -3 #> 5 -3 -4 #> 6 -3 -5 #> 7 -4 -6 #> 8 -5 -6 #> 9 -4 -6 #> 10 -3 -6 #> # ℹ 700 more rows coo_oscillo(shapes[4], 'rfourier') #> [1] 34.28884 35.22856 35.85539 36.52625 37.23875 38.21062 38.96933 #> [8] 38.77938 38.96933 39.18390 39.42267 39.68521 39.97105 41.22840 #> [15] 41.55177 41.89653 42.26213 43.56815 43.96536 45.28850 46.61700 #> [22] 47.52337 48.85250 49.75835 50.66774 51.58049 52.10667 53.03236 #> [29] 53.60027 53.25618 53.87744 53.57247 53.28452 53.01388 52.76080 #> [36] 52.52555 52.30835 52.10945 51.92905 52.75589 52.61573 52.49424 #> [43] 52.39157 52.30782 52.24307 52.19741 52.17088 52.16351 52.17531 #> [50] 52.20626 52.25633 52.32548 52.41361 52.52064 52.64645 52.79090 #> [57] 52.95385 52.15376 53.33453 52.57829 52.81768 53.07484 53.34950 #> [64] 53.64141 53.95027 54.27580 54.61770 54.97567 55.34939 55.73855 #> [71] 56.14283 56.56190 56.99543 57.44311 57.90459 58.37955 58.86768 #> [78] 59.36863 59.88210 60.40775 60.94528 61.49438 62.05473 62.62604 #> [85] 63.20800 63.80033 64.40274 65.01495 65.63669 65.49870 66.14613 #> [92] 66.80226 67.46682 68.21363 68.96685 69.72627 71.13586 71.90019 #> [99] 72.67024 73.44584 74.22680 75.01296 75.20000 76.00241 76.80946 #> [106] 77.04407 77.30385 78.13586 78.43027 78.74899 78.23153 78.58924 #> [113] 78.97065 78.49288 78.91279 78.46017 78.91827 78.49116 78.07453 #> [120] 78.58580 78.19525 77.81559 78.37960 78.02647 77.68461 77.35417 #> [127] 77.03530 77.68226 77.39058 77.11077 76.84296 76.58726 76.34381 #> [134] 76.11273 75.89411 75.68808 76.47732 76.29908 76.13356 75.98084 #> [141] 75.84100 75.71411 75.60023 74.50394 74.41509 74.33959 74.27748 #> [148] 74.22879 74.19355 74.17177 74.16347 73.16873 73.18765 73.22022 #> [155] 73.26643 73.32625 73.39964 72.49103 72.59283 72.70824 72.83719 #> [162] 72.97963 73.13546 73.30460 73.48696 73.68244 73.89094 74.11235 #> [169] 74.34655 75.56127 76.78281 77.74913 78.46964 79.20886 78.98907 #> [176] 79.76109 79.56797 80.37176 80.20506 81.03955 80.89895 80.77048 #> [183] 81.64820 81.54545 81.45484 82.37383 82.30844 82.25515 83.21339 #> [190] 83.18473 83.16808 83.16346 84.17077 84.18996 84.22102 84.26394 #> [197] 85.31688 85.38267 84.46363 85.54918 85.64983 85.76202 85.88571 #> [204] 86.02085 86.16738 86.32525 86.49439 86.67474 86.86623 87.06878 #> [211] 87.28232 87.50677 87.74204 87.98805 88.24470 88.51191 88.78958 #> [218] 89.07761 89.37590 88.73531 89.05721 89.38914 89.73098 90.08263 #> [225] 89.51415 89.88890 90.27317 89.75049 90.15753 90.57379 90.09726 #> [232] 90.53589 90.09246 90.55320 90.14314 90.62570 90.24922 89.89341 #> [239] 90.41049 90.08863 89.78789 89.50849 89.25062 89.01448 88.80024 #> [246] 88.60805 87.81833 87.65822 86.88289 86.75564 85.99543 85.90180 #> [253] 85.15746 84.41839 84.37043 83.64833 82.93200 82.22159 81.51725 #> [260] 80.81915 80.12746 79.44232 78.76392 78.09244 77.42804 76.77093 #> [267] 76.12127 74.71205 74.07134 73.43866 72.03249 71.40975 70.79566 #> [274] 69.39357 68.79056 68.19688 66.80013 65.40412 64.82571 64.25765 #> [281] 63.70023 62.31502 61.77244 62.09459 60.72216 60.21507 59.72041 #> [288] 59.23851 58.76967 59.20961 57.87245 58.35344 57.94651 57.55407 #> [295] 57.17643 56.81388 57.40838 56.13523 56.77207 56.47780 56.19977 #> [302] 55.93825 55.69346 55.46561 55.25493 56.04473 55.87204 54.72776 #> [309] 54.58755 54.46535 55.35682 55.27252 55.20620 55.15793 55.12777 #> [316] 55.11574 55.12184 55.14609 55.18844 55.24887 55.32730 55.42367 #> [323] 55.53789 55.66983 55.81938 55.98640 56.17072 56.37218 56.59060 #> [330] 56.82578 57.07752 56.38515 56.67414 57.92981 57.30013 57.63660 #> [337] 57.98837 58.35516 58.73668 58.21890 58.63543 59.06595 58.61935 #> [344] 59.08386 59.56152 59.18629 59.69666 59.37283 59.91499 59.64267 #> [351] 60.21563 59.99470 60.59734 60.42747 61.05860 60.93927 61.59763 #> [358] 61.52813 62.21241 62.19185 62.90071 62.92807 63.66015 63.73427 #> [365] 63.83964 63.97610 64.75812 64.93887 65.14982 65.96342 66.21642 #> [372] 66.49855 66.80942 67.14865 67.51580 67.91043 68.33204 68.78016 #> [379] 69.25426 69.75382 69.35679 69.89854 69.53111 70.11432 69.77669 #> [386] 69.45182 70.09278 69.79804 69.51644 70.21380 69.96247 69.72457 #> [393] 70.47665 71.24886 71.05751 71.86523 71.70342 72.54532 73.40480 #> [400] 73.28734 74.17868 75.08608 76.00895 76.94676 77.89895 78.86500 #> [407] 79.84441 80.84432 81.83670 82.84134 83.84129 84.85755 85.85730 #> [414] 86.88451 87.88397 88.88344 89.88292 90.88241 91.88191 92.88142 #> [421] 93.85554 94.88048 95.88002 96.87957 97.87913 98.91293 99.91216 #> [428] 100.91141 101.95369 102.95256 104.00323 105.00164 106.00008 107.05821 #> [435] 108.12447 109.12184 110.19536 111.19213 112.27258 113.36038 114.45531 #> [442] 115.55717 116.66577 116.78900 117.91146 119.04014 119.18609 120.32775 #> [449] 120.48874 121.64283 122.80236 123.96718 124.95013 125.93335 127.10095 #> [456] 128.08327 129.25466 130.23609 131.41112 132.59082 133.57020 134.75326 #> [463] 135.94073 136.91806 138.10864 139.30341 139.52852 140.73255 140.96957 #> [470] 140.24449 139.52997 138.82618 137.86237 136.89909 135.93634 135.25082 #> [477] 134.01247 133.05137 132.09086 131.41572 130.45849 129.50191 128.54599 #> [484] 127.59074 126.63619 125.68234 124.72922 123.77683 122.82521 123.13732 #> [491] 123.45675 122.84000 123.17644 123.52005 122.93616 123.29667 122.73616 #> [498] 123.11350 122.57662 122.97072 122.45772 121.54514 121.05088 120.57119 #> [505] 119.66929 119.20920 118.76418 118.33438 118.80149 119.27516 118.88086 #> [512] 119.37097 119.00220 118.64915 117.79197 117.46081 116.61205 115.23423 #> [519] 114.38642 113.54110 112.16122 111.31696 110.47530 109.09331 107.71215 #> [526] 106.33186 104.95248 103.57404 102.19657 100.82012 100.29919 98.92667 #> [533] 97.55533 97.04779 95.68088 94.31537 93.44900 92.58533 91.72442 #> [540] 90.86637 90.01124 89.15913 88.31012 88.00439 86.62177 86.33323 #> [547] 85.50294 84.67632 83.85348 83.03453 82.80597 81.40876 81.20026 #> [554] 80.40404 79.61241 78.82552 78.04351 77.26653 76.49472 76.37761 #> [561] 74.96730 74.21201 73.46257 72.71916 71.98197 71.94094 70.52699 #> [568] 69.80962 69.09928 68.39618 67.70055 67.01262 66.33263 65.66083 #> [575] 64.24875 63.58639 62.93294 61.52327 60.88054 60.24755 58.84152 #> [582] 58.22071 56.81733 55.41450 54.80961 53.41022 52.01162 51.42505 #> [589] 50.03093 48.63796 48.07263 46.68550 45.30004 44.75958 44.23513 #> [596] 42.86379 41.49533 41.00231 40.52797 39.18002 38.73500 38.31093 #> [603] 37.90850 36.60071 36.23449 35.89241 35.57516 35.28341 34.05109 #> [610] 33.80538 33.58765 33.39846 33.23829 33.10756 33.00662 32.93576 #> [617] 32.89515 32.88491 32.90508 32.95559 33.03631 33.14701 33.28740 #> [624] 33.45711 33.65568 33.88261 34.13735 34.41925 34.72768 35.06193 #> [631] 35.42126 35.80492 36.21214 36.64213 37.09410 37.56726 38.06082 #> [638] 38.57399 39.10600 39.65610 40.22354 40.80759 42.20611 42.80984 #> [645] 43.42821 44.06059 44.70640 45.36507 46.03603 47.44904 48.18901 #> [652] 49.60118 50.34924 51.10592 51.87084 53.27926 54.05043 54.82898 #> [659] 56.23445 56.86510 58.27294 58.15749 58.81854 58.75524 58.72594 #> [666] 58.73069 60.14474 60.18261 61.59580 61.66523 61.76697 61.90086 #> [673] 61.27762 61.46141 60.86654 60.28239 59.70928 59.14752 58.59744 #> [680] 58.05937 57.53366 57.02063 56.52065 55.15875 54.67832 53.32563 #> [687] 51.97622 50.63034 49.28829 47.95039 46.61700 45.71452 44.38155 #> [694] 43.05376 42.14616 40.81915 39.91086 38.58472 37.67564 36.35049 #> [701] 35.44054 34.53556 33.20556 32.29988 31.39993 30.97074 31.88281 #> [708] 32.80000 33.72190 34.28884 coo_oscillo(shapes[4], 'tfourier') #> [1] 0.00000000 4.70353942 3.90929170 3.90044215 3.89159259 4.66814120 #> [7] 3.87389348 3.07964576 6.21238885 6.20353930 6.19468974 6.18584018 #> [13] 6.17699063 5.38274291 6.15929151 6.15044196 6.14159240 5.34734468 #> [19] 6.12389329 5.32964557 5.32079601 4.52654829 5.30309689 4.50884917 #> [25] 4.49999962 4.49115006 3.69690234 4.47345095 3.67920323 2.88495551 #> [31] 3.66150411 2.86725639 2.85840684 2.84955728 2.84070772 2.83185817 #> [37] 2.82300861 2.81415905 2.80530950 3.58185810 2.78761038 2.77876083 #> [43] 2.76991127 2.76106171 2.75221216 2.74336260 2.73451304 2.72566349 #> [49] 2.71681393 2.70796437 2.69911482 2.69026526 2.68141570 2.67256614 #> [55] 2.66371659 2.65486703 2.64601747 1.85176975 3.41371652 1.83407064 #> [61] 2.61061925 2.60176969 2.59292013 2.58407058 2.57522102 2.56637146 #> [67] 2.55752191 2.54867235 2.53982279 2.53097324 2.52212368 2.51327412 #> [73] 2.50442457 2.49557501 2.48672545 2.47787590 2.46902634 2.46017678 #> [79] 2.45132723 2.44247767 2.43362811 2.42477856 2.41592900 2.40707944 #> [85] 2.39822988 2.38938033 2.38053077 2.37168121 2.36283166 1.56858394 #> [91] 2.34513254 2.33628299 2.32743343 3.88938020 3.88053064 3.87168109 #> [97] 3.07743337 3.85398197 3.84513242 3.83628286 3.82743330 3.81858375 #> [103] 4.59513235 3.80088463 3.79203508 4.56858368 4.55973413 3.76548641 #> [109] 4.54203501 4.53318546 5.30973406 4.51548634 4.50663679 5.28318539 #> [115] 4.48893767 5.26548628 4.47123856 5.24778717 5.23893761 4.44468989 #> [121] 5.22123849 5.21238894 4.41814122 5.19468982 5.18584027 5.17699071 #> [127] 5.16814115 4.37389343 5.15044204 5.14159248 5.13274293 5.12389337 #> [133] 5.11504381 5.10619426 5.09734470 5.08849514 4.29424742 5.07079603 #> [139] 5.06194647 5.05309692 5.04424736 5.03539780 5.02654825 5.80309685 #> [145] 5.00884913 4.99999958 4.99115002 4.98230046 4.97345091 4.96460135 #> [151] 4.95575179 5.73230040 4.93805268 4.92920312 4.92035356 4.91150401 #> [157] 4.90265445 5.67920306 4.88495534 4.87610578 4.86725622 4.85840667 #> [163] 4.84955711 4.84070755 4.83185800 4.82300844 4.81415888 4.80530933 #> [169] 4.79645977 4.00221205 3.99336249 3.19911477 2.40486705 2.39601750 #> [175] 1.60176978 2.37831838 1.58407066 2.36061927 1.56637155 2.34292016 #> [181] 1.54867243 1.53982288 2.31637148 1.52212376 1.51327421 2.28982281 #> [187] 1.49557509 1.48672554 2.26327414 1.46902642 1.46017687 1.45132731 #> [193] 2.22787592 1.43362820 1.42477864 1.41592908 2.19247769 1.39822997 #> [199] 0.60398225 2.16592902 1.37168130 1.36283174 1.35398219 1.34513263 #> [205] 1.33628307 1.32743352 1.31858396 1.30973440 1.30088485 1.29203529 #> [211] 1.28318573 1.27433617 1.26548662 1.25663706 1.24778750 1.23893795 #> [217] 1.23008839 1.22123883 1.21238928 0.41814156 1.19469016 1.18584061 #> [223] 1.17699105 1.16814149 0.37389377 1.15044238 1.14159282 0.34734510 #> [229] 1.12389371 1.11504415 0.32079643 1.09734504 0.30309732 1.07964593 #> [235] 0.28539821 1.06194681 0.26769909 0.25884954 1.03539814 0.24115042 #> [241] 0.23230087 0.22345131 0.21460175 0.20575219 0.19690264 0.18805308 #> [247] 5.67699067 0.17035397 5.65929155 0.15265485 5.64159244 0.13495574 #> [253] 5.62389333 5.61504377 0.10840707 5.59734466 5.58849510 5.57964554 #> [259] 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 5.52654820 #> [265] 5.51769865 5.50884909 5.49999953 4.70575181 5.48230042 5.47345086 #> [271] 4.67920314 5.45575175 5.44690219 4.65265447 5.42920308 5.42035352 #> [277] 4.62610580 4.61725625 5.39380485 5.38495529 5.37610574 4.58185802 #> [283] 5.35840662 6.13495523 4.55530935 5.33185795 5.32300840 5.31415884 #> [289] 5.30530928 6.08185789 4.50221201 6.06415878 5.26991106 5.26106150 #> [295] 5.25221194 5.24336239 6.01991099 4.44026511 6.00221188 5.20796416 #> [301] 5.19911460 5.19026505 5.18141549 5.17256593 5.16371638 5.94026498 #> [307] 5.14601726 4.35176954 5.12831815 5.11946859 5.89601720 5.10176948 #> [313] 5.09291992 5.08407036 5.07522081 5.06637125 5.05752169 5.04867214 #> [319] 5.03982258 5.03097302 5.02212347 5.01327391 5.00442435 4.99557480 #> [325] 4.98672524 4.97787568 4.96902613 4.96017657 4.95132701 4.94247746 #> [331] 4.93362790 4.13938018 4.91592879 5.69247739 4.11283151 4.88938012 #> [337] 4.88053056 4.87168100 4.86283145 4.06858373 4.84513233 4.83628278 #> [343] 4.04203506 4.81858366 4.80973410 4.01548638 4.79203499 3.99778727 #> [349] 4.77433588 3.98008816 4.75663676 3.96238904 4.73893765 3.94468993 #> [355] 4.72123854 3.92699082 4.70353942 3.90929170 4.68584031 3.89159259 #> [361] 4.66814120 3.87389348 4.65044208 3.85619436 3.84734481 3.83849525 #> [367] 4.61504386 3.82079614 3.81194658 4.58849519 3.79424747 3.78539791 #> [373] 3.77654835 3.76769880 3.75884924 3.74999968 3.74115012 3.73230057 #> [379] 3.72345101 3.71460145 2.92035373 3.69690234 2.90265462 3.67920323 #> [385] 2.88495551 2.87610595 3.65265456 2.85840684 2.84955728 3.62610589 #> [391] 2.83185817 2.82300861 3.59955722 3.59070766 2.79645994 3.57300855 #> [397] 2.77876083 3.55530943 3.54645988 2.75221216 3.52876076 3.51991121 #> [403] 3.51106165 3.50221209 3.49336254 3.48451298 3.47566342 4.25221203 #> [409] 3.45796431 3.44911475 4.22566336 3.43141564 4.20796424 3.41371652 #> [415] 4.19026513 4.18141557 4.17256602 4.16371646 4.15486690 4.14601735 #> [421] 4.92256595 3.34292007 4.11946868 4.11061912 4.10176956 3.30752184 #> [427] 4.08407045 4.07522089 3.28097317 4.05752178 3.26327406 4.03982267 #> [433] 4.03097311 3.23672539 3.22787583 4.00442444 3.21017672 3.98672533 #> [439] 3.19247761 3.18362805 3.17477849 3.16592893 3.15707938 2.36283166 #> [445] 3.13938026 3.13053071 2.33628299 3.11283159 2.31858387 3.09513248 #> [451] 3.08628292 3.07743337 3.85398197 3.84513242 3.05088470 3.82743330 #> [457] 3.03318558 3.80973419 3.01548647 3.00663691 3.78318552 2.98893780 #> [463] 2.98008824 3.75663685 2.96238913 2.95353957 2.15929185 2.93584046 #> [469] 2.14159274 1.34734502 1.33849546 1.32964590 0.53539818 0.52654863 #> [475] 0.51769907 1.29424768 5.99778710 0.49115040 0.48230084 1.25884945 #> [481] 0.46460173 0.45575217 0.44690262 0.43805306 0.42920350 0.42035395 #> [487] 0.41150439 0.40265483 0.39380528 1.95575205 1.94690249 1.15265477 #> [493] 1.92920338 1.92035382 1.12610610 1.90265471 1.10840699 1.88495559 #> [499] 1.09070787 1.86725648 1.07300876 0.27876104 1.05530964 1.04646009 #> [505] 0.25221237 1.02876097 1.01991142 1.01106186 1.78761047 1.77876091 #> [511] 0.98451319 1.76106180 0.96681408 0.95796452 0.16371680 0.94026541 #> [517] 0.14601769 5.63495527 0.12831857 0.11946902 5.60840660 0.10176990 #> [523] 0.09292035 5.58185793 5.57300838 5.56415882 5.55530926 5.54645971 #> [529] 5.53761015 5.52876059 4.73451287 5.51106148 5.50221192 4.70796420 #> [535] 5.48451281 5.47566325 6.25221186 6.24336230 6.23451274 6.22566319 #> [541] 6.21681363 6.20796407 6.19911452 0.69247782 5.39601724 0.67477870 #> [547] 6.16371629 6.15486673 6.14601718 6.13716762 0.63053092 5.33407034 #> [553] 0.61283181 6.10176939 6.09291984 6.08407028 6.07522072 6.06637117 #> [559] 6.05752161 0.55088491 5.25442433 6.03097294 6.02212338 6.01327383 #> [565] 6.00442427 0.49778757 5.20132699 5.97787560 5.96902604 5.96017649 #> [571] 5.95132693 5.94247737 5.93362781 5.92477826 5.13053054 5.90707914 #> [577] 5.89822959 5.10398187 5.88053047 5.87168092 5.07743320 5.85398180 #> [583] 5.05973408 5.05088453 5.82743313 5.03318541 5.02433586 5.80088446 #> [589] 5.00663674 4.99778719 5.77433579 4.98008807 4.97123852 5.74778712 #> [595] 5.73893757 4.94468985 4.93584029 5.71238890 5.70353934 4.90929162 #> [601] 5.68584023 5.67699067 5.66814111 4.87389339 5.65044200 5.64159244 #> [607] 5.63274288 5.62389333 4.82964561 5.60619421 5.59734466 5.58849510 #> [613] 5.57964554 5.57079599 5.56194643 5.55309687 5.54424732 5.53539776 #> [619] 5.52654820 5.51769865 5.50884909 5.49999953 5.49114998 5.48230042 #> [625] 5.47345086 5.46460131 5.45575175 5.44690219 5.43805264 5.42920308 #> [631] 5.42035352 5.41150397 5.40265441 5.39380485 5.38495529 5.37610574 #> [637] 5.36725618 5.35840662 5.34955707 5.34070751 5.33185795 5.32300840 #> [643] 6.09955700 5.30530928 5.29645973 5.28761017 5.27876061 5.26991106 #> [649] 5.26106150 6.03761011 0.53097341 6.01991099 0.51327429 0.50442474 #> [655] 0.49557518 5.98451277 0.47787607 0.46902651 5.95796410 5.16371638 #> [661] 5.94026498 4.36061910 5.13716771 4.34291999 4.33407043 4.32522087 #> [667] 5.88716764 4.30752176 5.86946853 4.28982264 4.28097309 4.27212353 #> [673] 3.47787581 4.25442442 3.46017670 3.45132714 3.44247758 3.43362803 #> [679] 3.42477847 3.41592891 3.40707936 3.39822980 3.38938024 2.59513252 #> [685] 3.37168113 2.57743341 2.56858385 2.55973430 2.55088474 2.54203518 #> [691] 2.53318563 1.73893791 2.51548651 2.50663696 1.71238924 2.48893784 #> [697] 1.69469012 2.47123873 1.67699101 2.45353961 1.65929189 1.65044234 #> [703] 2.42699094 1.63274322 1.62389367 3.18584044 4.74778721 4.73893765 #> [709] 4.73008809 3.93584037 #tfourier is prone to high-frequency noise but smoothing can help coo_oscillo(coo_smooth(shapes[4], 10), 'tfourier') #> [1] 0.000000000 6.210281146 6.150339598 6.110870956 6.093957661 6.111051488 #> [7] 6.210841936 0.294826636 1.163080415 1.662325460 1.784906858 1.788459018 #> [13] 1.754364939 1.713694996 1.673686879 1.624391221 1.550688278 1.445544249 #> [19] 1.313650160 1.165054644 1.007403085 0.842241873 0.665533492 0.472501809 #> [25] 0.264958204 0.052746323 6.128257112 5.926985109 5.730762152 5.541624953 #> [31] 5.365867883 5.211467073 5.086389730 4.997097511 4.946510695 4.933000642 #> [37] 4.949742414 4.982955751 5.012460904 5.019029243 4.994585130 4.946466089 #> [43] 4.891849750 4.846153200 4.815140738 4.796127011 4.783744124 4.773987623 #> [49] 4.764958775 4.755946140 4.746333644 4.734694607 4.718307666 4.693917249 #> [55] 4.660156421 4.620031964 4.580677444 4.549991613 4.533287434 4.532292499 #> [61] 4.545279217 4.566934623 4.589359967 4.605421681 4.612112985 4.610800812 #> [67] 4.604740736 4.596653165 4.587948567 4.579116176 4.570267573 4.561418016 #> [73] 4.552568459 4.543718902 4.534869346 4.526019789 4.517170232 4.508320675 #> [79] 4.499471119 4.490620608 4.481752932 4.472741250 4.462985703 4.450603765 #> [85] 4.431608816 4.400770190 4.356068458 4.305424656 4.269520989 4.277135048 #> [91] 4.360538895 4.555194318 4.871254402 5.215038283 5.459664874 5.595213464 #> [97] 5.672103286 5.734294873 5.805171782 5.888871809 5.977816468 6.062603219 #> [103] 6.138686968 6.207147740 6.271367481 0.051070155 0.115529390 0.185002608 #> [109] 0.260266970 0.335648438 0.401580810 0.452499558 0.490752929 0.523002507 #> [115] 0.554570991 0.586753235 0.617247615 0.642073315 0.658350204 0.667047287 #> [121] 0.673606828 0.685132162 0.705052388 0.728633438 0.744734811 0.745801344 #> [127] 0.737404131 0.735346616 0.751874045 0.784845872 0.819132998 0.837128874 #> [133] 0.828297388 0.792765360 0.741689130 0.694623805 0.671233403 0.681431950 #> [139] 0.721943628 0.781107907 0.846153540 0.905318763 0.945847189 0.956185340 #> [145] 0.933520844 0.889053044 0.844590615 0.821054584 0.826911372 0.853852015 #> [151] 0.881659563 0.890921047 0.876241385 0.849987814 0.832106250 0.832287770 #> [157] 0.840824651 0.837648250 0.809803659 0.760803413 0.706008449 0.660112883 #> [163] 0.628012512 0.604377441 0.577183265 0.530156087 0.444950680 0.304766283 #> [169] 0.096072698 6.087754031 5.700461201 5.247258666 4.831451596 4.527523880 #> [175] 4.329498082 4.206491595 4.131062373 4.081089105 4.040449748 4.001478231 #> [181] 3.964579062 3.933656583 3.910945742 3.895211705 3.883184677 3.871266154 #> [187] 3.856146033 3.835553787 3.810038382 3.783889856 3.762402266 3.746921155 #> [193] 3.733416217 3.716285917 3.692075007 3.659767668 3.620829826 3.580502872 #> [199] 3.545836696 3.519458457 3.496862828 3.471910466 3.443688053 3.416538164 #> [205] 3.394773009 3.379129831 3.367634796 3.358040420 3.349046858 3.340179182 #> [211] 3.331310551 3.322298870 3.312543323 3.300160435 3.281145755 3.250115199 #> [217] 3.204257486 3.148748834 3.097182990 3.062798448 3.047139365 3.037836547 #> [223] 3.019070901 2.985270415 2.943990251 2.906371786 2.877162870 2.853033116 #> [229] 2.827294741 2.795605917 2.758775379 2.721017676 2.685491706 2.651638374 #> [235] 2.616756113 2.579249488 2.539266926 2.496642604 2.450285176 2.400599692 #> [241] 2.350909726 2.304563353 2.260820580 2.214420252 2.159471987 2.094718182 #> [247] 2.026085459 1.963248210 1.911995985 1.870137442 1.831022284 1.789478413 #> [253] 1.743510198 1.691608789 1.631150303 1.561569503 1.488650289 1.423172645 #> [259] 1.373787829 1.341690659 1.321606928 1.305654435 1.285571657 1.253491627 #> [265] 1.204250793 1.139519444 1.069263427 1.006648871 0.960120128 0.930025733 #> [271] 0.911026560 0.895946158 0.877978420 0.852313020 0.819389902 0.787791876 #> [277] 0.771357046 0.780349343 0.814054366 0.861526357 0.910083692 0.952417749 #> [283] 0.985608592 1.008800661 1.025873144 1.046448905 1.078707071 1.120695586 #> [289] 1.160889837 1.187477232 1.195902397 1.189182194 1.174564489 1.160112567 #> [295] 1.151279870 1.148175732 1.145840851 1.137610074 1.119048880 1.090947700 #> [301] 1.060659306 1.039140171 1.032285551 1.032745212 1.022979818 0.991476068 #> [307] 0.948086298 0.920008639 0.927148777 0.961284686 0.992101349 0.993873732 #> [313] 0.963915071 0.918406903 0.876060289 0.845934321 0.827081727 0.814716958 #> [319] 0.804962365 0.795950684 0.787083007 0.778231543 0.769363866 0.760353139 #> [325] 0.750614758 0.738375872 0.720105828 0.691716549 0.652608187 0.609790908 #> [331] 0.575970900 0.560292070 0.560253479 0.563707517 0.558656949 0.539780722 #> [337] 0.506825021 0.461757288 0.409794503 0.359637805 0.318856196 0.288830724 #> [343] 0.264555711 0.238816280 0.207252588 0.171067996 0.135611940 0.106165474 #> [349] 0.084689231 0.069773360 0.058688066 0.049228656 0.040263124 0.031399834 #> [355] 0.022548751 0.013684699 0.004705453 6.278316778 6.266646228 6.249714189 #> [361] 6.223378486 6.185711060 6.140814149 6.098429160 6.068030924 6.052616099 #> [367] 6.047041546 6.041070135 6.024843229 5.993927011 5.951419573 5.905757611 #> [373] 5.865459482 5.834682028 5.812125954 5.792458593 5.768502704 5.733457862 #> [379] 5.683206435 5.618467189 5.545329001 5.472432994 5.406413214 5.350205499 #> [385] 5.304888721 5.271062496 5.248378331 5.235801685 5.233541784 5.243796693 #> [391] 5.267701445 5.300728508 5.332712334 5.354453431 5.364377855 5.368534497 #> [397] 5.374741784 5.387390003 5.407383871 5.434201642 5.465689493 5.497519401 #> [403] 5.525769644 5.550355985 5.574942842 5.603203498 5.635133193 5.667217292 #> [409] 5.696503292 5.724011803 5.754170455 5.792492400 5.844118816 5.911952780 #> [415] 5.993258931 6.078066848 6.152989261 6.206858374 6.232226877 6.224754148 #> [421] 6.185255417 6.122244570 6.049372258 5.978525675 5.915552103 5.861307526 #> [427] 5.814628320 5.774712015 5.742004258 5.716275508 5.693379276 5.666055366 #> [433] 5.630481863 5.590829982 5.554144579 5.520973706 5.483347333 5.432738889 #> [439] 5.368764431 5.298373235 5.228480361 5.162317644 5.101305142 5.047172969 #> [445] 5.001770639 4.967325726 4.949028929 4.955822231 4.995559376 5.068649008 #> [451] 5.166128839 5.271169312 5.361943901 5.418816242 5.434261089 5.415787999 #> [457] 5.378749340 5.337253926 5.300066779 5.270326801 5.245798899 5.219095373 #> [463] 5.178948961 5.113005498 5.010509821 4.861906973 4.655872417 4.383607566 #> [469] 4.061035875 3.739006861 3.460013884 3.228975398 3.035724811 2.875726521 #> [475] 2.751418620 2.667347672 2.626605417 2.625083548 2.645200476 2.660136888 #> [481] 2.649921973 2.613646664 2.566698627 2.528381069 2.513356521 2.534150830 #> [487] 2.608723363 2.760815486 2.995303110 3.253844542 3.450019278 3.556829435 #> [493] 3.594254480 3.588553531 3.560325237 3.523018039 3.480988947 3.429095667 #> [499] 3.357730619 3.262973502 3.155419447 3.057566270 2.990178713 2.963327724 #> [505] 2.978269071 3.031263380 3.113254441 3.206490718 3.283579186 3.315652213 #> [511] 3.286439739 3.198490398 3.065780988 2.901072469 2.710327869 2.499825577 #> [517] 2.288736611 2.106853050 1.972716007 1.880608795 1.808217671 1.732016385 #> [523] 1.641441083 1.543848642 1.454766713 1.383471012 1.328109195 1.280445960 #> [529] 1.233298003 1.186051865 1.145835795 1.124395250 1.133998381 1.185203040 #> [535] 1.284655334 1.429095439 1.597639355 1.755997591 1.877909670 1.959627909 #> [541] 2.012852441 2.050062384 2.076448107 2.091254469 2.093166224 2.083874267 #> [547] 2.068528701 2.053935597 2.045086040 2.041980966 2.039645151 2.031397576 #> [553] 2.012695022 1.983859410 1.950961917 1.922825350 1.903874767 1.888886160 #> [559] 1.867115865 1.834104119 1.799091522 1.778085405 1.777842081 1.787473253 #> [565] 1.787246136 1.766366858 1.731953827 1.700820006 1.683021524 1.673232227 #> [571] 1.656126033 1.618934077 1.560828846 1.493152222 1.431106120 1.383899161 #> [577] 1.350760265 1.323321861 1.290847550 1.246070449 1.189727078 1.130361772 #> [583] 1.078468381 1.040047045 1.014823673 0.998771530 0.987568410 0.978706955 #> [589] 0.972097548 0.969825211 0.974911598 0.988572657 1.007325669 1.023813218 #> [595] 1.033242798 1.039315778 1.051423155 1.075752154 1.109940476 1.145106149 #> [601] 1.172013529 1.186848625 1.193363408 1.198926850 1.206369621 1.210402157 #> [607] 1.204972412 1.194030025 1.191273604 1.207820260 1.241670290 1.279478888 #> [613] 1.307637488 1.320968930 1.322284497 1.316968271 1.309024705 1.300337273 #> [619] 1.291505836 1.282657232 1.273807676 1.264958119 1.256108562 1.247259005 #> [625] 1.238409449 1.229559892 1.220710335 1.211860778 1.203011222 1.194161665 #> [631] 1.185312108 1.176462551 1.167613948 1.158782511 1.150095079 1.142151512 #> [637] 1.136835287 1.138149900 1.151463248 1.179461633 1.216397766 1.246996075 #> [643] 1.254805029 1.235032721 1.201996315 1.185517450 1.218031010 1.321091442 #> [649] 1.494393247 1.707858148 1.913968285 2.077528885 2.185390609 2.236504708 #> [655] 2.234154703 2.181616267 2.077397918 1.913965611 1.684446939 1.396172930 #> [661] 1.083379564 0.801165397 0.594838371 0.479858466 0.448502322 0.476558403 #> [667] 0.519940898 0.523261974 0.451098963 0.310029503 0.136270603 6.245725890 #> [673] 6.083883304 5.933308298 5.794794776 5.675631097 5.583900424 5.519806626 #> [679] 5.472922363 5.426039551 5.361978088 5.270595236 5.153649901 5.024269044 #> [685] 4.899718114 4.792550346 4.706581487 4.638154755 4.579941168 4.525357287 #> [691] 4.471842191 4.420780288 4.374056983 4.331365078 4.291374762 4.253868124 #> [697] 4.218994007 4.185218958 4.150165899 4.114424239 4.084166694 4.070249157 #> [703] 4.087829504 4.167359978 4.411768752 5.183594717 6.047475358 0.033827928 #> [709] 0.090954159 0.064865507"},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates perimeter and variations — coo_perim","title":"Calculates perimeter and variations — coo_perim","text":"coo_perim calculates perimeter; coo_perimpts calculates euclidean distance every points shape; coo_perimcum calculates cumulative sum.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates perimeter and variations — coo_perim","text":"","code":"coo_perimpts(coo) # S3 method for default coo_perimpts(coo) # S3 method for Coo coo_perimpts(coo) coo_perimcum(coo) # S3 method for default coo_perimcum(coo) # S3 method for Coo coo_perimcum(coo) coo_perim(coo) # S3 method for default coo_perim(coo) # S3 method for Coo coo_perim(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates perimeter and variations — coo_perim","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates perimeter and variations — coo_perim","text":"numeric distance every point list .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_perim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates perimeter and variations — coo_perim","text":"","code":"# for speed sake b1 <- coo_sample(bot[1], 12) b5 <- bot %>% slice(1:5) %>% coo_sample(12) # coo_perim coo_perim(b1) #> [1] 2140.62 coo_perim(b5) #> brahma caney chimay corona deusventrue #> 2140.620 1942.307 1354.083 1555.883 1768.427 # coo_perimpts coo_perimpts(b1) #> [1] 201.6829 212.0424 168.6001 198.8291 189.3198 221.2261 190.0026 206.7293 #> [9] 192.2134 137.2079 222.7667 b5 %>% coo_perimpts() #> $brahma #> [1] 201.6829 212.0424 168.6001 198.8291 189.3198 221.2261 190.0026 206.7293 #> [9] 192.2134 137.2079 222.7667 #> #> $caney #> [1] 192.0000 181.0000 161.9784 175.0457 192.1276 171.0000 186.1317 191.7707 #> [9] 175.3454 134.0149 181.8928 #> #> $chimay #> [1] 131.03435 123.06502 113.22544 128.99612 119.94165 131.03435 140.24621 #> [8] 129.44883 118.37652 97.65244 121.06197 #> #> $corona #> [1] 155.0000 143.0315 131.2288 127.6323 145.0034 155.0000 154.9322 140.3567 #> [9] 151.3275 112.9292 139.4417 #> #> $deusventrue #> [1] 175.1713 163.3065 147.1224 151.2415 175.5591 162.3730 182.3623 171.8430 #> [9] 157.6230 131.8218 150.0033 #> # coo_perimcum b1 %>% coo_perimcum() #> [1] 0.0000 201.6829 413.7254 582.3255 781.1546 970.4744 1191.7005 #> [8] 1381.7032 1588.4324 1780.6459 1917.8537 2140.6204 b5 %>% coo_perimcum() #> $brahma #> [1] 0.0000 201.6829 413.7254 582.3255 781.1546 970.4744 1191.7005 #> [8] 1381.7032 1588.4324 1780.6459 1917.8537 2140.6204 #> #> $caney #> [1] 0.0000 192.0000 373.0000 534.9784 710.0241 902.1517 1073.1517 #> [8] 1259.2833 1451.0540 1626.3994 1760.4143 1942.3072 #> #> $chimay #> [1] 0.0000 131.0343 254.0994 367.3248 496.3209 616.2626 747.2969 #> [8] 887.5431 1016.9920 1135.3685 1233.0209 1354.0829 #> #> $corona #> [1] 0.0000 155.0000 298.0315 429.2603 556.8926 701.8960 856.8960 #> [8] 1011.8282 1152.1849 1303.5124 1416.4416 1555.8833 #> #> $deusventrue #> [1] 0.0000 175.1713 338.4778 485.6002 636.8417 812.4008 974.7739 #> [8] 1157.1361 1328.9791 1486.6021 1618.4239 1768.4272 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a single shape — coo_plot","title":"Plots a single shape — coo_plot","text":"simple wrapper around plot plotting shapes. Widely used Momocs graphical functions, methods, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a single shape — coo_plot","text":"","code":"coo_plot( coo, xlim, ylim, border = \"#333333\", col = NA, lwd = 1, lty = 1, points = FALSE, first.point = TRUE, cex.first.point = 0.5, centroid = TRUE, xy.axis = TRUE, pch = 1, cex = 0.5, main = NA, poly = TRUE, plot.new = TRUE, plot = TRUE, zoom = 1, ... ) ldk_plot(coo, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a single shape — coo_plot","text":"coo list matrix coordinates. xlim coo_plot called coo missing, vector length 2 specifying ylim ploting area. ylim coo_plot called coo missing, vector length 2 specifying ylim ploting area. border color shape border. col color fill shape polygon. lwd lwd drawing shapes. lty lty drawing shapes. points logical. Whether display points. missing number points < 100, points plotted. first.point logical whether plot first point. cex.first.point numeric size first point centroid logical. Whether display centroid. xy.axis logical. Whether draw xy axis. pch pch points. cex cex points. main character. title plot. poly logical whether use polygon lines draw shape, just points. words, whether shape considered configuration landmarks (eg closed outline). plot.new logical whether plot new frame. plot logical whether plot something just create empty plot. zoom numeric take distances. ... arguments use coo_plot methods. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a single shape — coo_plot","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a single shape — coo_plot","text":"","code":"b <- bot[1] coo_plot(b) coo_plot(bot[2], plot.new=FALSE) # equivalent to coo_draw(bot[2]) coo_plot(b, zoom=2) coo_plot(b, border='blue') coo_plot(b, first.point=FALSE, centroid=FALSE) coo_plot(b, points=TRUE, pch=20) coo_plot(b, xy.axis=FALSE, lwd=2, col='#F2F2F2')"},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate coordinates range — coo_range","title":"Calculate coordinates range — coo_range","text":"coo_range simply returns range, coo_range_enlarge enlarges k proportion. coo_diffrange return amplitude (ie diff coo_range)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate coordinates range — coo_range","text":"","code":"coo_range(coo) # S3 method for default coo_range(coo) # S3 method for Coo coo_range(coo) coo_range_enlarge(coo, k) # S3 method for default coo_range_enlarge(coo, k = 0) # S3 method for Coo coo_range_enlarge(coo, k = 0) # S3 method for list coo_range_enlarge(coo, k = 0) coo_diffrange(coo) # S3 method for default coo_diffrange(coo) # S3 method for Coo coo_diffrange(coo) # S3 method for list coo_diffrange(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate coordinates range — coo_range","text":"coo matrix (x; y) coordinates Coo object. k numeric proportion enlarge ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate coordinates range — coo_range","text":"matrix range (min, max) x (x, y)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_range.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate coordinates range — coo_range","text":"","code":"bot[1] %>% coo_range # single shape #> x y #> min 33 14 #> max 316 1102 bot %>% coo_range # Coo object #> x y #> min 8 3 #> max 345 1120 bot[1] %>% coo_range_enlarge(1/50) # single shape #> x y #> min 27.34 -7.76 #> max 321.66 1123.76 bot %>% coo_range_enlarge(1/50) # Coo object #> x y #> min 1.26 -19.34 #> max 351.74 1142.34"},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the rectangularity of a shape — coo_rectangularity","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"Calculates rectangularity shape","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"","code":"coo_rectangularity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rectangularity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the rectangularity of a shape — coo_rectangularity","text":"","code":"coo_rectangularity(bot[1]) #> [1] 0.7753614 bot %>% slice(1:3) %>% # for speed sake only coo_rectangularity #> $brahma #> [1] 0.7753614 #> #> $caney #> [1] 0.7772434 #> #> $chimay #> [1] 0.7695281 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the rectilinearity of a shape — coo_rectilinearity","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"proposed Zunic Rosin (see ). May need testing/review.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"","code":"coo_rectilinearity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"Zunic J, Rosin PL. 2003. Rectilinearity measurements polygons. IEEE Transactions Pattern Analysis Machine Intelligence 25: 1193-1200.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"numeric single shape, list Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"due laborious nature algorithm (nb.pts^2), implementation, may long compute.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rectilinearity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the rectilinearity of a shape — coo_rectilinearity","text":"","code":"bot[1] %>% coo_sample(32) %>% # for speed sake only coo_rectilinearity #> [1] 0.3539899 bot %>% slice(1:3) %>% coo_sample(32) %>% # for speed sake only coo_rectilinearity #> $brahma #> [1] 0.3539899 #> #> $caney #> [1] 0.3751378 #> #> $chimay #> [1] 0.3597856 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":null,"dir":"Reference","previous_headings":"","what":"Reverses coordinates — coo_rev","title":"Reverses coordinates — coo_rev","text":"Returns reverse suite coordinates, .e. change shape's orientation","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reverses coordinates — coo_rev","text":"","code":"coo_rev(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reverses coordinates — coo_rev","text":"coo matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reverses coordinates — coo_rev","text":"matrix (x; y) coordinates Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rev.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reverses coordinates — coo_rev","text":"","code":"b <- coo_sample(bot[1], 4) b #> [,1] [,2] #> [1,] 37 561 #> [2,] 143 15 #> [3,] 295 523 #> [4,] 205 1101 coo_rev(b) #> [,1] [,2] #> [1,] 205 1101 #> [2,] 295 523 #> [3,] 143 15 #> [4,] 37 561"},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with positive x-coordinates — coo_right","title":"Retains coordinates with positive x-coordinates — coo_right","text":"Useful shapes aligned along y-axis (e.g. bilateral symmetry) one wants retain just upper side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with positive x-coordinates — coo_right","text":"","code":"coo_right(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with positive x-coordinates — coo_right","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_right","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with positive x-coordinates — coo_right","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with positive x-coordinates — coo_right","text":"shapes \"sliced\" along y-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_right.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with positive x-coordinates — coo_right","text":"","code":"b <- coo_center(bot[1]) coo_plot(b) coo_draw(coo_right(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":null,"dir":"Reference","previous_headings":"","what":"Rotates coordinates — coo_rotate","title":"Rotates coordinates — coo_rotate","text":"Rotates coordinates 'theta' angle (radians) trigonometric direction (anti-clockwise). provided, assumed centroid size. involves three steps: centering current position, dividing coordinates 'scale', translating original position.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rotates coordinates — coo_rotate","text":"","code":"coo_rotate(coo, theta = 0)"},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rotates coordinates — coo_rotate","text":"coo either matrix (x; y) coordinates, Coo object. theta numericthe angle (radians) rotate shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rotates coordinates — coo_rotate","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rotate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rotates coordinates — coo_rotate","text":"","code":"coo_plot(bot[1]) coo_plot(coo_rotate(bot[1], pi/2)) # on Coo b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_rotate(b, pi/2))"},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":null,"dir":"Reference","previous_headings":"","what":"Rotates shapes with a custom center — coo_rotatecenter","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"rotates shape 'theta' angles (radians) (x; y) 'center'.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"","code":"coo_rotatecenter(coo, theta, center = c(0, 0))"},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"coo matrix (x; y) coordinates Coo object. theta numeric angle (radians) rotate shapes. center numeric (x; y) position center","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_rotatecenter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rotates shapes with a custom center — coo_rotatecenter","text":"","code":"b <- bot[1] coo_plot(b) coo_draw(coo_rotatecenter(b, -pi/2, c(200, 200)), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots differences as (colored) segments aka a ruban — coo_ruban","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"Useful display differences shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"","code":"coo_ruban(coo, dev, palette = col_heat, normalize = TRUE, ...)"},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"coo shape, typically mean shape dev numeric vector distances anythinh relevant palette color palette use palette normalize logical whether normalize (TRUE default) distances ... parameters fed segments, eg lwd (see examples)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_ruban.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots differences as (colored) segments aka a ruban — coo_ruban","text":"","code":"ms <- MSHAPES(efourier(bot , 10), \"type\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details b <- ms$shp$beer w <- ms$shp$whisky # we obtain the mean shape, then euclidean distances between points m <- MSHAPES(list(b, w)) d <- edm(b, w) # First plot coo_plot(m, plot=FALSE) coo_draw(b) coo_draw(w) coo_ruban(m, d, lwd=5) #Another example coo_plot(m, plot=FALSE) coo_ruban(m, d, palette=col_summer2, lwd=5) #If you want linewidth rather than color coo_plot(m, plot=FALSE) coo_ruban(m, d, palette=col_black)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample coordinates (among points) — coo_sample","title":"Sample coordinates (among points) — coo_sample","text":"Sample n coordinates among existing points.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample coordinates (among points) — coo_sample","text":"","code":"coo_sample(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample coordinates (among points) — coo_sample","text":"coo either matrix (x; y) coordinates Opn object. n integer, number fo points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample coordinates (among points) — coo_sample","text":"matrix (x; y) coordinates, Opn object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Sample coordinates (among points) — coo_sample","text":"Opn methods (pointless Ldk), $ldk component defined, changed accordingly multiplying ids n number coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_sample.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample coordinates (among points) — coo_sample","text":"","code":"b <- bot[1] stack(bot) stack(coo_sample(bot, 24)) coo_plot(b) coo_plot(coo_sample(b, 24))"},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample a proportion of coordinates (among points) — coo_sample_prop","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"simple wrapper around coo_sample","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"","code":"coo_sample_prop(coo, prop = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"coo either matrix (x; y) coordinates Opn object. prop numeric, proportion points sample","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"matrix (x; y) coordinates, Opn object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"coo_sample $ldk component defined, changed accordingly multiplying ids n number coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_sample_prop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample a proportion of coordinates (among points) — coo_sample_prop","text":"","code":"# single shape bot[1] %>% coo_nb() #> [1] 138 bot[1] %>% coo_sample_prop(0.5) %>% coo_nb() #> [1] 69"},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":null,"dir":"Reference","previous_headings":"","what":"Samples coordinates (regular radius) — coo_samplerr","title":"Samples coordinates (regular radius) — coo_samplerr","text":"Samples n coordinates regular angle.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Samples coordinates (regular radius) — coo_samplerr","text":"","code":"coo_samplerr(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Samples coordinates (regular radius) — coo_samplerr","text":"coo matrix (x; y) coordinates Coo object. n integer, number points sample.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Samples coordinates (regular radius) — coo_samplerr","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Samples coordinates (regular radius) — coo_samplerr","text":"design, function samples among existing points, using coo_interpolate prior may useful homogeneous angles. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_samplerr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Samples coordinates (regular radius) — coo_samplerr","text":"","code":"stack(bot) bot <- coo_center(bot) stack(coo_samplerr(bot, 12)) coo_plot(bot[1]) coo_plot(rr <- coo_samplerr(bot[1], 12)) cpos <- coo_centpos(bot[1]) segments(cpos[1], cpos[2], rr[, 1], rr[, 2]) # Sometimes, interpolating may be useful: shp <- hearts[1] %>% coo_center # given a shp, draw segments from each points on it, to its centroid draw_rads <- function(shp, ...){ segments(shp[, 1], shp[, 2], coo_centpos(shp)[1], coo_centpos(shp)[2], ...) } # calculate the sd of argument difference in successive points, # in other words a proxy for the homogeneity of angles sd_theta_diff <- function(shp) shp %>% complex(real=.[, 1], imaginary=.[, 2]) %>% Arg %>% `[`(-1) %>% diff %>% sd # no interpolation: all points are sampled from existing points but the # angles are not equal shp %>% coo_plot(points=TRUE, main=\"no interpolation\") shp %>% coo_samplerr(64) %T>% draw_rads(col=\"red\") %>% sd_theta_diff #> [1] 0.03301767 # with interpolation: much more homogeneous angles shp %>% coo_plot(points=TRUE) shp %>% coo_interpolate(360) %>% coo_samplerr(64) %T>% draw_rads(col=\"blue\") %>% sd_theta_diff #> [1] 0.00696334"},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates all scalar descriptors of shape — coo_scalars","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"See examples full list.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"","code":"coo_scalars(coo, rectilinearity = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"coo matrix (x; y) coordinates Coo rectilinearity logical whether include rectilinearity using coo_rectilinearity","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"data_frame","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"coo_rectilinearity particularly optimized, takes around 30 times time include calculate others thus includedby default. default.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_scalars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates all scalar descriptors of shape — coo_scalars","text":"","code":"df <- bot %>% coo_scalars() # pass bot %>% coo_scalars(TRUE) if you want rectilinearity colnames(df) %>% cat(sep=\"\\n\") # all scalars used #> area #> calliper #> centsize #> circularity #> circularityharalick #> circularitynorm #> convexity #> eccentricityboundingbox #> eccentricityeigen #> elongation #> length #> perim #> rectangularity #> solidity #> width # a PCA on all these descriptors TraCoe(coo_scalars(bot), fac=bot$fac) %>% PCA %>% plot_PCA(~type)"},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":null,"dir":"Reference","previous_headings":"","what":"Scales coordinates — coo_scale","title":"Scales coordinates — coo_scale","text":"coo_scale scales coordinates 'scale' factor. provided, assumed centroid size. involves three steps: centering current position, dividing coordinates 'scale', pushing back original position. coo_scalex applies scaling (shrinking) parallel x-axis, coo_scaley y axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Scales coordinates — coo_scale","text":"","code":"coo_scale(coo, scale) # S3 method for default coo_scale(coo, scale = coo_centsize(coo)) # S3 method for Coo coo_scale(coo, scale) coo_scalex(coo, scale = 1) # S3 method for default coo_scalex(coo, scale = 1) # S3 method for Coo coo_scalex(coo, scale = 1) coo_scaley(coo, scale = 1) # S3 method for default coo_scaley(coo, scale = 1) # S3 method for Coo coo_scaley(coo, scale = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Scales coordinates — coo_scale","text":"coo matrix (x; y) coordinates Coo object. scale scaling factor, default, centroid size coo_scale; 1 scalex scaley.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Scales coordinates — coo_scale","text":"single shape Coo object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_scale.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Scales coordinates — coo_scale","text":"","code":"# on a single shape b <- bot[1] %>% coo_center %>% coo_scale coo_plot(b, lwd=2) coo_draw(coo_scalex(b, 1.5), bor=\"blue\") coo_draw(coo_scaley(b, 0.5), bor=\"red\") # this also works on Coo objects: b <- slice(bot, 5) # for speed sake stack(b) b %>% coo_center %>% coo_scale %>% stack b %>% coo_center %>% coo_scaley(0.5) %>% stack #equivalent to: #b %>% coo_center %>% coo_scalex(2) %>% stack"},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":null,"dir":"Reference","previous_headings":"","what":"Shears shapes — coo_shearx","title":"Shears shapes — coo_shearx","text":"coo_shearx applies shear mapping matrix (x; y) coordinates (list), parallel x-axis (.e. x' = x + ky; y' = y + kx). coo_sheary parallel y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Shears shapes — coo_shearx","text":"","code":"coo_shearx(coo, k) coo_sheary(coo, k)"},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Shears shapes — coo_shearx","text":"coo matrix (x; y) coordinates Coo object. k numeric shear factor","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Shears shapes — coo_shearx","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_shear.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Shears shapes — coo_shearx","text":"","code":"coo <- coo_template(shapes[11]) coo_plot(coo) coo_draw(coo_shearx(coo, 0.5), border=\"blue\") coo_draw(coo_sheary(coo, 0.5), border=\"red\")"},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":null,"dir":"Reference","previous_headings":"","what":"Slices shapes between successive coordinates — coo_slice","title":"Slices shapes between successive coordinates — coo_slice","text":"Takes shape n coordinates. pass function least two ids (<= n), shape open corresponding coordinates slices returned list","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slices shapes between successive coordinates — coo_slice","text":"","code":"coo_slice(coo, ids, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slices shapes between successive coordinates — coo_slice","text":"coo matrix (x; y) coordinates Coo object. ids numeric length >= 2, slice shape(s) ldk numeric id ldk use ids, Opn. provided, ids ignored.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slices shapes between successive coordinates — coo_slice","text":"list shapes list Opn","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slices shapes between successive coordinates — coo_slice","text":"","code":"h <- slice(hearts, 1:5) # speed purpose only # single shape, a list of matrices is returned sh <- coo_slice(h[1], c(12, 24, 36, 48)) coo_plot(sh[[1]]) panel(Opn(sh)) # on a Coo, a list of Opn is returned # makes no sense if shapes are not normalized first sh2 <- coo_slice(h, c(12, 24, 36, 48)) panel(sh2[[1]]) # Use coo_slice with `ldk` instead: # hearts as an example x <- h %>% fgProcrustes(tol=1) #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224 # 4 landmarks stack(x) x$ldk[1:5] #> [[1]] #> [1] 65 56 50 19 #> #> [[2]] #> [1] 69 60 52 21 #> #> [[3]] #> [1] 68 60 51 21 #> #> [[4]] #> [1] 69 59 53 23 #> #> [[5]] #> [1] 71 61 54 21 #> # here we slice y <- coo_slice(x, ldk=1:4) # plotting stack(y[[1]]) stack(y[[2]]) # new ldks from tipping points, new ldks from angle olea %>% slice(1:5) %>% # for the sake of speed def_ldk_tips %>% def_ldk_angle(0.75*pi) %>% def_ldk_angle(0.25*pi) %>% coo_slice(ldk =1:4) -> oleas oleas[[1]] %>% stack oleas[[2]] %>% stack # etc. # domestic operations y[[3]] %>% coo_area() #> shp1 shp2 shp3 shp4 shp5 #> 0.001684956 0.007028829 0.010968094 0.009962128 0.016920135 # shape analysis of a slice y[[1]] %>% coo_bookstein() %>% npoly %>% PCA %>% plot(~aut) #> 'nb.pts' missing and set to: 31 #> 'degree' missing and set to: 5 #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates — coo_slide","title":"Slides coordinates — coo_slide","text":"Slides coordinates id-th point become first one.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates — coo_slide","text":"","code":"coo_slide(coo, id, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates — coo_slide","text":"coo matrix (x; y) coordinates Coo object. id numeric id point become new first point. See details method Coo objects. ldk numeric id ldk use id, ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates — coo_slide","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Slides coordinates — coo_slide","text":"Coo objects, particular Opn three different ways coo_sliding available: ldk passed single id passed: id-th points within shapes become first points. $ldk slided accordingly. ldk passed vector ids matching length Coo: every shape, id-th point used id-th point. $ldk slided accordingly. single ldk passed: ldk-th ldk used slide every shape. id (also) passed, ignored message. See examples.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slide.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates — coo_slide","text":"","code":"h <- hearts %>% slice(1:5) # for speed sake stack(h) # set the first landmark as the starting point stack(coo_slide(h, ldk=1)) # set the 50th point as the starting point (everywhere) stack(coo_slide(h, id=50)) # set the id-random-th point as the starting point (everywhere) set.seed(123) # just for the reproducibility id_random <- sample(x=min(sapply(h$coo, nrow)), size=length(h), replace=TRUE) stack(coo_slide(h, id=id_random))"},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates in a particular direction — coo_slidedirection","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"Shapes centered , according direction, point northwards, southwards, eastwards westwards centroid, becomes first point coo_slide. 'right' possibly sensible option (default), since 0 radians points eastwards, relatively origin. followed coo_untiltx cases remove rotationnal dephasing/bias.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"","code":"coo_slidedirection( coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4], center, id )"},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"coo matrix (x; y) coordinates Coo object. direction character one \"\", \"left\", \"\", \"right\" (\"right\" default) center logical whether center sliding id numeric whether return id point slided shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slidedirection.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates in a particular direction — coo_slidedirection","text":"","code":"b <- coo_rotate(bot[1], pi/6) # dummy example just to make it obvious coo_plot(b) # not the first point coo_plot(coo_slidedirection(b, \"up\")) coo_plot(coo_slidedirection(b, \"right\")) coo_plot(coo_slidedirection(b, \"left\")) coo_plot(coo_slidedirection(b, \"down\")) # on Coo objects b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_slidedirection(b, \"right\")) # This should be followed by a [coo_untiltx] in most (if not all) cases stack(coo_slidedirection(b, \"right\") %>% coo_untiltx)"},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":null,"dir":"Reference","previous_headings":"","what":"Slides coordinates using the widest gap — coo_slidegap","title":"Slides coordinates using the widest gap — coo_slidegap","text":"slicing shape using two landmarks, functions coo_up, open curve obtained rank points make wrong/artefactual results. widest gap > 5 * median gaps, couple coordinates forming widest gap used starting ending points. switch helps deal open curves. Examples self-speaking. Use force=TRUE bypass check","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Slides coordinates using the widest gap — coo_slidegap","text":"","code":"coo_slidegap(coo, force)"},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Slides coordinates using the widest gap — coo_slidegap","text":"coo matrix (x; y) coordinates Coo object. force logical whether use widest gap, check, real gap","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Slides coordinates using the widest gap — coo_slidegap","text":"matrix (x; y) coordinates Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_slidegap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Slides coordinates using the widest gap — coo_slidegap","text":"","code":"cat <- coo_center(shapes[4]) coo_plot(cat) # we only retain the bottom of the cat cat_down <- coo_down(cat, slidegap=FALSE) # see? the segment on the x-axis coorespond to the widest gap. coo_plot(cat_down) # that's what we meant coo_plot(coo_slidegap(cat_down))"},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Smoothes coordinates — coo_smooth","title":"Smoothes coordinates — coo_smooth","text":"Smoothes coordinates using simple moving average. May useful remove digitization noise, mainly outlines open outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Smoothes coordinates — coo_smooth","text":"","code":"coo_smooth(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Smoothes coordinates — coo_smooth","text":"coo matrix (x; y) coordinates Coo object. n integer number smoothing iterations","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Smoothes coordinates — coo_smooth","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_smooth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Smoothes coordinates — coo_smooth","text":"","code":"b5 <- slice(bot, 1:5) # for speed sake stack(b5) stack(coo_smooth(b5, 10)) coo_plot(b5[1]) coo_plot(coo_smooth(b5[1], 30))"},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":null,"dir":"Reference","previous_headings":"","what":"Smoothes coordinates on curves — coo_smoothcurve","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"Smoothes coordinates using simple moving average let first last points unchanged. May useful remove digitization noise curves.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"","code":"coo_smoothcurve(coo, n)"},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"coo matrix (x; y) coordinates Coo object. n integer specify number smoothing iterations","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_smoothcurve.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Smoothes coordinates on curves — coo_smoothcurve","text":"","code":"o <- olea[1] coo_plot(o, border='grey50', points=FALSE) coo_draw(coo_smooth(o, 24), border='blue', points=FALSE) coo_draw(coo_smoothcurve(o, 24), border='red', points=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the solidity of a shape — coo_solidity","title":"Calculates the solidity of a shape — coo_solidity","text":"Calculated using ratio shape area convex hull area.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the solidity of a shape — coo_solidity","text":"","code":"coo_solidity(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the solidity of a shape — coo_solidity","text":"Rosin PL. 2005. Computing global shape measures. Handbook Pattern Recognition Computer Vision. 177-196.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the solidity of a shape — coo_solidity","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the solidity of a shape — coo_solidity","text":"numeric single shape, list Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_solidity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the solidity of a shape — coo_solidity","text":"","code":"coo_solidity(bot[1]) #> [1] 0.8932612 bot %>% slice(1:3) %>% # for speed sake only coo_solidity #> $brahma #> [1] 0.8932612 #> #> $caney #> [1] 0.9201334 #> #> $chimay #> [1] 0.9279237 #>"},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the total absolute curvature of a shape — coo_tac","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"Calculated using sum absolute value second derivative smooth.spline prediction defined point.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"","code":"coo_tac(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"Siobhan Braybrook.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"coo matrix (x; y) coordinates Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"numeric single shape Coo","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_tac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the total absolute curvature of a shape — coo_tac","text":"","code":"coo_tac(bot[1]) #> [1] 67.85005 bot %>% slice(1:3) %>% # for speed sake only coo_tac #> brahma caney chimay #> 67.85005 34.81994 46.61054"},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":null,"dir":"Reference","previous_headings":"","what":"'Templates' shapes — coo_template","title":"'Templates' shapes — coo_template","text":"coo_template returns shape centered origin inscribed size-side square. coo_template_relatively biggest shape (prod(coo_diffrange)) size=size consequently defined single shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"'Templates' shapes — coo_template","text":"","code":"coo_template(coo, size) # S3 method for default coo_template(coo, size = 1) # S3 method for list coo_template(coo, size = 1) # S3 method for Coo coo_template(coo, size = 1) coo_template_relatively(coo, size = 1) # S3 method for list coo_template_relatively(coo, size = 1) # S3 method for Coo coo_template_relatively(coo, size = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"'Templates' shapes — coo_template","text":"coo list matrix coordinates. size numeric. Indicates length side 'inscribing' shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"'Templates' shapes — coo_template","text":"Returns matrix (x; y)coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"'Templates' shapes — coo_template","text":"See coo_listpanel illustration function. morphospaces functions also take profit function. May useful develop graphical functions.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_template.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"'Templates' shapes — coo_template","text":"","code":"coo <- bot[1] coo_plot(coo_template(coo), xlim=c(-1, 1), ylim=c(-1, 1)) rect(-0.5, -0.5, 0.5, 0.5) s <- 0.01 coo_plot(coo_template(coo, s)) rect(-s/2, -s/2, s/2, s/2)"},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":null,"dir":"Reference","previous_headings":"","what":"Translates coordinates — coo_trans","title":"Translates coordinates — coo_trans","text":"Translates coordinates 'x' 'y' value","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translates coordinates — coo_trans","text":"","code":"coo_trans(coo, x = 0, y = 0)"},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translates coordinates — coo_trans","text":"coo matrix (x; y) coordinates Coo object. x numeric translation along x-axis. y numeric translation along y-axis.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Translates coordinates — coo_trans","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trans.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translates coordinates — coo_trans","text":"","code":"coo_plot(bot[1]) coo_plot(coo_trans(bot[1], 50, 100)) # on Coo b <- bot %>% slice(1:5) # for speed sake stack(b) stack(coo_trans(b, 50, 100))"},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims both ends coordinates from shape — coo_trim","title":"Trims both ends coordinates from shape — coo_trim","text":"Removes trim coordinates ends shape, ie top bottom shape matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims both ends coordinates from shape — coo_trim","text":"","code":"coo_trim(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims both ends coordinates from shape — coo_trim","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims both ends coordinates from shape — coo_trim","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims both ends coordinates from shape — coo_trim","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trim(1) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.453100 0.08999 #> [2,] -0.371800 0.17700 #> [3,] -0.269700 0.24720 #> [4,] -0.177400 0.28280 #> [5,] -0.084940 0.30470 #> [6,] 0.007775 0.30940 #> [7,] 0.100600 0.30720 #> [8,] 0.193600 0.28790 #> [9,] 0.287000 0.24450 #> [10,] 0.373900 0.17700"},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims bottom coordinates from shape — coo_trimbottom","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"Removes trim coordinates bottom shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"","code":"coo_trimbottom(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trimbottom.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims bottom coordinates from shape — coo_trimbottom","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trimbottom(4) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720"},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":null,"dir":"Reference","previous_headings":"","what":"Trims top coordinates from shape — coo_trimtop","title":"Trims top coordinates from shape — coo_trimtop","text":"Removes trim coordinates top shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Trims top coordinates from shape — coo_trimtop","text":"","code":"coo_trimtop(coo, trim = 1)"},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Trims top coordinates from shape — coo_trimtop","text":"coo matrix (x; y) coordinates Coo object. trim numeric, number coordinates trim","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Trims top coordinates from shape — coo_trimtop","text":"trimmed shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_trimtop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Trims top coordinates from shape — coo_trimtop","text":"","code":"olea[1] %>% coo_sample(12) %T>% print() %T>% ldk_plot() %>% coo_trimtop(4) %T>% print() %>% points(col=\"red\") #> [,1] [,2] #> [1,] -0.500000 0.00000 #> [2,] -0.453100 0.08999 #> [3,] -0.371800 0.17700 #> [4,] -0.269700 0.24720 #> [5,] -0.177400 0.28280 #> [6,] -0.084940 0.30470 #> [7,] 0.007775 0.30940 #> [8,] 0.100600 0.30720 #> [9,] 0.193600 0.28790 #> [10,] 0.287000 0.24450 #> [11,] 0.373900 0.17700 #> [12,] 0.443800 0.09201 #> [,1] [,2] #> [1,] -0.177400 0.28280 #> [2,] -0.084940 0.30470 #> [3,] 0.007775 0.30940 #> [4,] 0.100600 0.30720 #> [5,] 0.193600 0.28790 #> [6,] 0.287000 0.24450 #> [7,] 0.373900 0.17700 #> [8,] 0.443800 0.09201"},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":null,"dir":"Reference","previous_headings":"","what":"Truss measurement — coo_truss","title":"Truss measurement — coo_truss","text":"method calculate shapes Coo truss measurements, pairwise combinations euclidean distances","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Truss measurement — coo_truss","text":"","code":"coo_truss(x)"},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Truss measurement — coo_truss","text":"x shape Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Truss measurement — coo_truss","text":"named numeric matrix","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Truss measurement — coo_truss","text":"Mainly implemented historical/didactical reasons.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_truss.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Truss measurement — coo_truss","text":"","code":"# example on a single shape cat <- coo_sample(shapes[4], 6) coo_truss(cat) #> 1-2 1-3 1-4 1-5 1-6 2-3 2-4 2-5 #> 58.79626 73.24616 92.45539 165.89454 63.97656 14.76482 111.87940 214.40616 #> 2-6 3-4 3-5 3-6 4-5 4-6 5-6 #> 120.20815 118.00424 225.44179 133.68620 123.90722 86.14523 106.01887 # example on wings dataset tx <- coo_truss(wings) txp <- PCA(tx, scale. = TRUE, center=TRUE, fac=wings$fac) plot(txp, 1) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"Rotationnal biases appear coo_slidedirection (friends). Typically useful outline analysis phasing matters. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"","code":"coo_untiltx(coo, id, ldk)"},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"coo matrix (x; y) coordinates Coo object. id numeric id point become new first point. See details method Coo objects. ldk numeric id ldk use id, ","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"matrix (x; y) coordinates, Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"Coo objects, particular Opn two different ways coo_sliding available: ldk passed id passed: id-th points within shapes become first points. single ldk passed: ldk-th ldk used slide every shape. id (also) passed, id ignored message.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_untiltx.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes rotation so that the centroid and a given point are parallel to the x-axis — coo_untiltx","text":"","code":"# on a single shape bot[1] %>% coo_center %>% coo_align %>% coo_sample(12) %>% coo_slidedirection(\"right\") %T>% coo_plot() %>% # the first point is not on the x-axis coo_untiltx() %>% coo_draw(border=\"red\") # this (red) one is # on an Out # prepare bot prebot <- bot %>% coo_center %>% coo_scale %>% coo_align %>% coo_slidedirection(\"right\") prebot %>% stack # some dephasing remains prebot %>% coo_slidedirection(\"right\") %>% coo_untiltx() %>% stack # much better # _here_ there is no change but the second, untilted, is correct prebot %>% efourier(8, norm=FALSE) %>% PCA %>% plot_PCA(~type) prebot %>% coo_untiltx %>% efourier(8, norm=FALSE) %>% PCA %>% plot_PCA(~type) # an example using ldks: # the landmark #2 is on the x-axis hearts %>% slice(1:5) %>% fgProcrustes(tol=1e-3) %>% # for speed sake coo_center %>% coo_untiltx(ldk=2) %>% stack #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224"},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":null,"dir":"Reference","previous_headings":"","what":"Retains coordinates with positive y-coordinates — coo_up","title":"Retains coordinates with positive y-coordinates — coo_up","text":"Useful shapes aligned along x-axis (e.g. bilateral symmetry) one wants retain just upper side.","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retains coordinates with positive y-coordinates — coo_up","text":"","code":"coo_up(coo, slidegap = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retains coordinates with positive y-coordinates — coo_up","text":"coo matrix (x; y) coordinates Coo object. slidegap logical whether apply coo_slidegap coo_down","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retains coordinates with positive y-coordinates — coo_up","text":"matrix (x; y) coordinates Coo object (returned Opn)","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Retains coordinates with positive y-coordinates — coo_up","text":"shapes \"sliced\" along x-axis, usually results open curves thus huge/artefactual gaps points neighboring axis. usually solved coo_slidegap. See examples . Also, apply coo_left/right//object, obtain Opn object, done automatically.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_up.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retains coordinates with positive y-coordinates — coo_up","text":"","code":"b <- coo_alignxax(bot[1]) coo_plot(b) coo_draw(coo_up(b), border='red')"},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the width of a shape — coo_width","title":"Calculates the width of a shape — coo_width","text":"Nothing coo_lw(coo)[2].","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the width of a shape — coo_width","text":"","code":"coo_width(coo)"},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the width of a shape — coo_width","text":"coo matrix (x; y) coordinates Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the width of a shape — coo_width","text":"width (pixels) shape","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/coo_width.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the width of a shape — coo_width","text":"","code":"coo_width(bot[1]) #> [1] 278.0386"},{"path":"http://momx.github.io/Momocs/reference/d.html","id":null,"dir":"Reference","previous_headings":"","what":"A wrapper to calculates euclidean distances between two points — d","title":"A wrapper to calculates euclidean distances between two points — d","text":"main advantage ed method can passed different objects used combination measure. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A wrapper to calculates euclidean distances between two points — d","text":"","code":"d(x, id1, id2)"},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"A wrapper to calculates euclidean distances between two points — d","text":"x Ldk (typically), matrix id1 id 1st row id2 id 2nd row","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A wrapper to calculates euclidean distances between two points — d","text":"numeric","code":""},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"A wrapper to calculates euclidean distances between two points — d","text":"objects, first get_ldk.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A wrapper to calculates euclidean distances between two points — d","text":"","code":"# single shape d(wings[1], 1, 4) #> [1] 0.7581273 # Ldk object d(wings, 1, 4) #> AN1 AN2 AN3 AN4 AN5 AN6 AN7 AN8 #> 0.7581273 0.7281573 0.7127928 0.7185018 0.7367129 0.7124015 0.7285464 0.7301814 #> AN9 AN10 AN11 TO12 WY13 WY14 WY15 WY16 #> 0.7091337 0.7087522 0.7100063 0.6994695 0.7257983 0.7250806 0.7227536 0.7176631 #> UR17 UR18 UR19 UR20 CA21 CA22 CA23 CA24 #> 0.7207639 0.7269677 0.7153795 0.7397394 0.7373042 0.7172436 0.7223663 0.7182525 #> CA25 CA26 CA27 OR28 MA29 MA30 MA31 PS32 #> 0.7317102 0.7172721 0.7127463 0.7244861 0.7335012 0.7238598 0.7424106 0.7366003 #> PS33 PS34 PS35 PS36 PS37 PS38 PS39 PS40 #> 0.7262568 0.7315960 0.7233414 0.7278607 0.7262419 0.7331013 0.7087411 0.7163488 #> PS41 PS42 PS43 AE44 AE45 AE46 AE47 AE48 #> 0.7085592 0.7134963 0.7062850 0.7233241 0.7080950 0.7261707 0.7100848 0.7421942 #> AE49 AE50 AE51 AE52 AE53 AE54 AE55 AE56 #> 0.7115717 0.7248944 0.7230917 0.7144437 0.7182977 0.7168990 0.7175543 0.7165161 #> AE57 AE58 AE59 AE60 AE61 AE62 AE63 AE64 #> 0.7404125 0.7154040 0.7448661 0.7261959 0.7224206 0.7360905 0.7335780 0.7318912 #> AE65 AE66 AE67 AE68 AE69 AE70 AE71 AE72 #> 0.7151047 0.7147967 0.7145111 0.7210058 0.7222862 0.7212556 0.7302622 0.7216666 #> AE73 AE74 AE75 AE76 AE77 AE78 AE79 AE80 #> 0.7437503 0.7436207 0.7327989 0.7092307 0.7315643 0.7322983 0.7398728 0.7173188 #> AE81 AE82 AE83 AE84 AE85 AE86 AE87 AE88 #> 0.6992811 0.7286847 0.7241596 0.7290020 0.7136496 0.7222001 0.7283568 0.7341570 #> AE89 AE90 AE91 AE92 AE93 AE94 AE95 AE96 #> 0.7213378 0.7293730 0.7198584 0.7149219 0.7354247 0.7296066 0.7157059 0.6982300 #> AE97 AE98 AE99 AE100 CX101 CX102 CX103 CX104 #> 0.7382611 0.7261058 0.7145814 0.7133695 0.7205058 0.7340288 0.7172196 0.7235002 #> CX105 CX106 CX107 CX108 CX109 CX110 CX111 CX112 #> 0.7186017 0.7191322 0.7077697 0.7256004 0.7205312 0.7205628 0.7171014 0.7182613 #> CX113 CX114 CX115 CX116 CX117 CX118 CX119 CX120 #> 0.7299714 0.7094558 0.6976466 0.7216434 0.7297104 0.7277296 0.7383755 0.7150724 #> CX121 CX122 CX123 CX124 CX125 DE126 DE127 #> 0.7217969 0.7252883 0.7075976 0.7231878 0.7190234 0.7001547 0.7128613 # Out object d(hearts, 2, 4) #> shp1 shp2 shp3 shp4 shp5 shp6 shp7 shp8 #> 0.7631146 0.7182864 0.8451851 0.8524332 0.6289745 0.7469257 0.7650846 0.5290089 #> shp9 shp10 shp11 shp12 shp13 shp14 shp15 shp16 #> 0.6103333 0.6236372 0.7429723 0.6348490 0.7671199 0.6810554 0.6338818 0.6853828 #> shp17 shp18 shp19 shp20 shp21 shp22 shp23 shp24 #> 0.6238002 0.8866637 0.6208528 0.5822941 0.5880879 0.8852956 0.7346886 0.7203612 #> shp25 shp26 shp27 shp28 shp29 shp30 shp31 shp32 #> 0.6834542 0.6683383 0.6815803 0.6992615 0.8837326 0.6694748 0.9143077 0.7462901 #> shp33 shp34 shp35 shp36 shp37 shp38 shp39 shp40 #> 0.8324069 0.8263567 0.7156152 0.7400215 0.8636179 0.7327721 0.7302947 0.8022611 #> shp41 shp42 shp43 shp44 shp45 shp46 shp47 shp48 #> 0.7876690 0.6702961 0.7657328 0.7114349 0.8160898 0.8514524 0.7864097 0.8544094 #> shp49 shp50 shp51 shp52 shp53 shp54 shp55 shp56 #> 0.8540897 0.7362736 0.7839997 0.7141854 0.7881206 0.7844670 0.7976090 0.7780533 #> shp57 shp58 shp59 shp60 shp61 shp62 shp63 shp64 #> 0.7790919 0.7977559 0.8113749 0.7159091 0.7119202 0.6425247 0.8280741 0.7699237 #> shp65 shp66 shp67 shp68 shp69 shp70 shp71 shp72 #> 0.9112877 0.7542011 0.8073623 0.8916280 0.7638459 0.7394304 0.7120199 0.8475767 #> shp73 shp74 shp75 shp76 shp77 shp78 shp79 shp80 #> 0.8467397 0.7998835 0.9270539 0.7642246 0.8594367 0.7209088 0.7989868 0.7535296 #> shp81 shp82 shp83 shp84 shp85 shp86 shp87 shp88 #> 0.8750936 0.9212785 0.8739192 0.7410993 0.7711573 0.9040280 0.8445564 0.8595617 #> shp89 shp90 shp91 shp92 shp93 shp94 shp95 shp96 #> 0.7544551 0.8765394 0.7649132 0.8566908 0.8672661 0.8905499 0.8167811 0.6780182 #> shp97 shp98 shp99 shp100 shp101 shp102 shp103 shp104 #> 0.7720006 0.9065548 0.8954063 0.8858552 0.8706311 0.8762412 0.9093137 0.9002444 #> shp105 shp106 shp107 shp108 shp109 shp110 shp111 shp112 #> 0.9036831 0.8292070 0.8859845 0.8851778 0.8619118 0.9206441 0.8397867 0.8692543 #> shp113 shp114 shp115 shp116 shp117 shp118 shp119 shp120 #> 0.8671550 0.7668184 0.8522446 0.7407808 0.7615372 0.7884933 0.9120387 0.8496588 #> shp121 shp122 shp123 shp124 shp125 shp126 shp127 shp128 #> 0.7128952 0.8452803 0.7808519 0.8506531 0.8119996 0.7727404 0.7854347 0.8393396 #> shp129 shp130 shp131 shp132 shp133 shp134 shp135 shp136 #> 0.8445801 0.7802361 0.7640858 0.8662670 0.7090051 0.8541041 0.7161086 0.7619554 #> shp137 shp138 shp139 shp140 shp141 shp142 shp143 shp144 #> 0.7454238 0.8066868 0.8413141 0.7679260 0.8279943 0.7932280 0.8050323 0.8471870 #> shp145 shp146 shp147 shp148 shp149 shp150 shp151 shp152 #> 0.7967146 0.8006016 0.8237974 0.8582077 0.9160836 0.8401398 0.7995380 0.6738980 #> shp153 shp154 shp155 shp156 shp157 shp158 shp159 shp160 #> 0.7307879 0.7278767 0.8359675 0.8280149 0.8104836 0.7733338 0.8047466 0.6754903 #> shp161 shp162 shp163 shp164 shp165 shp166 shp167 shp168 #> 0.7218993 0.6596433 0.8148563 0.6368536 0.7098642 0.7902415 0.7481063 0.7169491 #> shp169 shp170 shp171 shp172 shp173 shp174 shp175 shp176 #> 0.7126700 0.7845322 0.7388734 0.7834291 0.6949870 0.6693791 0.6995516 0.6978463 #> shp177 shp178 shp179 shp180 shp181 shp182 shp183 shp184 #> 0.7198900 0.7878513 0.8469718 0.7758912 0.7731482 0.6759113 0.7120142 0.6643103 #> shp185 shp186 shp187 shp188 shp189 shp190 shp191 shp192 #> 0.7535931 0.7760557 0.7520940 0.7106488 0.6974563 0.7151895 0.8647945 0.7771309 #> shp193 shp194 shp195 shp196 shp197 shp198 shp199 shp200 #> 0.7450503 0.6718839 0.7454927 0.5912441 0.7118493 0.7229153 0.8140886 0.8216331 #> shp201 shp202 shp203 shp204 shp205 shp206 shp207 shp208 #> 0.7815022 0.6470323 0.6373149 0.5962023 0.6925027 0.7957830 0.6756185 0.7093084 #> shp209 shp210 shp211 shp212 shp213 shp214 shp215 shp216 #> 0.6560775 0.7320395 0.7869578 0.7326762 0.7769385 0.8253959 0.6940959 0.7130844 #> shp217 shp218 shp219 shp220 shp221 shp222 shp223 shp224 #> 0.6848838 0.8305747 0.7472713 0.7586330 0.8380628 0.7593495 0.6286220 0.7498917 #> shp225 shp226 shp227 shp228 shp229 shp230 shp231 shp232 #> 0.7584135 0.7930154 0.7907987 0.7237335 0.8102214 0.8092945 0.7134718 0.8471743 #> shp233 shp234 shp235 shp236 shp237 shp238 shp239 shp240 #> 0.7870556 0.8002813 0.7853021 0.8028798 0.7940435 0.8044962 0.6784667 0.7779515"},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"Data: Outline coordinates Apodemus (wood mouse) mandibles","code":""},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"object 64 coordinates 30 wood molar outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_apodemus.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of Apodemus (wood mouse) mandibles — apodemus","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. Journal Biogeography 30:1617-1628. see https://onlinelibrary.wiley.com/doi/full/10.1046/j.1365-2699.2003.00932.x","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of beer and whisky bottles. — bot","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"Data: Outline coordinates beer whisky bottles.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"object containing outlines coordinates grouping factor 20 beer 20 whisky bottles","code":""},{"path":"http://momx.github.io/Momocs/reference/data_bot.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of beer and whisky bottles. — bot","text":"Images grabbed internet prepared package's authors. particular choice made dimension original images brands cited .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Data: Landmark semilandmark coordinates cereal glumes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Ldk object 21 configurations landmarks semi-landmarks (4 partitions) sampled cereal glumes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_chaff.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Landmark and semilandmark coordinates on cereal glumes — chaff","text":"Research support provided European Research Council (Evolutionary Origins Agriculture (grant . 269830-EOA) PI: Glynis Jones, Dept Archaeology, Sheffield, UK. Data collected Emily Forster.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates from an experimental charring on cereal grains — charring","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"Data: Outline coordinates experimental charring cereal grains","code":""},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"object 18 grains, 3 views , 2 cereal species, charred different temperatures 6 hours (0C (charring), 230C 260C).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_charring.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates from an experimental charring on cereal grains — charring","text":"Research support provided European Research Council (Evolutionary Origins Agriculture (grant . 269830-EOA) PI: Glynis Jones, Dept Archaeology, Sheffield, UK. Data collected Emily Forster.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Measurement of iris flowers — flower","title":"Data: Measurement of iris flowers — flower","text":"Data: Measurement iris flowers","code":""},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Measurement of iris flowers — flower","text":"TraCoe object 150 measurements 4 variables (petal + sepal) x (length x width) 3 species iris. dataset classical iris formatted Momocs.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_flower.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Measurement of iris flowers — flower","text":"see iris","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of hand-drawn hearts — hearts","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"Data: Outline coordinates hand-drawn hearts","code":""},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"object outline coordinates 240 hand-drawn hearts 8 different persons, 4 landmarks.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_hearts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of hand-drawn hearts — hearts","text":"thank fellows Ecology Department French Institute Pondicherry drawn hearts, smoothed, scaled, centered, downsampled 80 coordinates per outline.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of 360 molars — molars","title":"Data: Outline coordinates of 360 molars — molars","text":"Courtesy Julien Corny Florent Detroit.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of 360 molars — molars","text":"object containing 79 equilinearly spaced (x; y) coordinates 360 crown outlines, modern human molars, along type ($type) - 90 first upper molars (UM1), 90 second upper molars (UM2), 90 first lower molars (LM1), 90 second lower molars (LM2) - individual (ind) come (data 360 molars taken 180 individuals).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_molars.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of 360 molars — molars","text":"Corny, J., & Detroit, F. (2014). Technical Note: Anatomic identification isolated modern human molars: testing Procrustes aligned outlines standardization procedure elliptic fourier analysis. American Journal Physical Anthropology, 153(2), 314-22. doi:10.1002/ajpa.22428 see https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.22428","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of mosquito wings. — mosquito","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"Data: Outline coordinates mosquito wings.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"object 126 mosquito wing outlines outlines used Rohlf Archie (1984). Note links defined quite approximate.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mosquito.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of mosquito wings. — mosquito","text":"Rohlf F, Archie J. 1984. comparison Fourier methods description wing shape mosquitoes (Diptera: Culicidae). Systematic Biology: 302-317.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of mouse molars — mouse","title":"Data: Outline coordinates of mouse molars — mouse","text":"Data: Outline coordinates mouse molars","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of mouse molars — mouse","text":"object 64 coordinates 30 wood molar outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_mouse.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of mouse molars — mouse","text":"Renaud S, Dufour AB, Hardouin EA, Ledevin R, Auffray JC (2015): upon multivariate analyses: tell several stories biological evolution. PLoS One 10:1-18 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132801","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of North Sea fishes — nsfishes","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"Data: Outline coordinates North Sea fishes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"object containing outlines coordinates 218 fishes North Sea along taxonomical cofactors.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_nsfishes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of North Sea fishes — nsfishes","text":"Caillon F, Frelat R, Mollmann C, Bonhomme V (submitted)","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Configuration of landmarks of oak leaves — oak","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Viscosi Cardini (2001).","code":""},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Ldk object containing 11 (x; y) landmarks 176 oak leaves wings, ","code":""},{"path":"http://momx.github.io/Momocs/reference/data_oak.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Configuration of landmarks of oak leaves — oak","text":"Viscosi, V., & Cardini, . (2011). Leaf morphology, taxonomy geometric morphometrics: simplified protocol beginners. PloS One, 6(10), e25630. doi:10.1371/journal.pone.0025630","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of olive seeds open outlines. — olea","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"Data: Outline coordinates olive seeds open outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"Opn object outline coordinates olive seeds.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_olea.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of olive seeds open outlines. — olea","text":"thank Jean-Frederic Terral Sarah Ivorra (UMR CBAE, Montpellier, France) allowing us share data. can look original paper: Terral J-F, Alonso N, Capdevila RB , Chatti N, Fabre L, Fiorentino G, Marinval P, Jorda GP, Pradat B, Rovira N, et al. 2004. Historical biogeography olive domestication (Olea europaea L.) revealed geometrical morphometry applied biological archaeological material. Journal Biogeography 31: 63-77.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of various shapes — shapes","title":"Data: Outline coordinates of various shapes — shapes","text":"Data: Outline coordinates various shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of various shapes — shapes","text":"object outline coordinates various shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_shapes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of various shapes — shapes","text":"Borrowed default shapes (c) Adobe Photoshop. send jail.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"Data: Outline coordinates cephalic outlines trilobite","code":""},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"object 64 coordinates 50 cephalic outlines different ontogenetic stages trilobite.","code":""},{"path":"http://momx.github.io/Momocs/reference/data_trilo.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Outline coordinates of cephalic outlines of trilobite — trilo","text":"Arranged : https://folk.universitetetioslo./ (used ohammer website seems deprecated now). original data included 51 outlines 5 ontogenetic stages, one just single outline thas removed.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":null,"dir":"Reference","previous_headings":"","what":"Data: Landmarks coordinates of mosquito wings — wings","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Data: Landmarks coordinates mosquito wings","code":""},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Ldk object containing 18 (x; y) landmarks 127 mosquito wings, ","code":""},{"path":"http://momx.github.io/Momocs/reference/data_wings.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data: Landmarks coordinates of mosquito wings — wings","text":"Rohlf Slice 1990.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines new landmarks on Out and Opn objects — def_ldk","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Helps define landmarks Coo object. number landmarks must specified rows indices correspond nearest points clicked every outlines stored $ldk slot Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"","code":"def_ldk(Coo, nb.ldk, close, points)"},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Coo Opn object nb.ldk number landmarks define every shape close logical whether close (typically outlines) points logical whether display points","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"Opn object landmarks defined","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines new landmarks on Out and Opn objects — def_ldk","text":"","code":"if (FALSE) { bot <- bot[1:5] # to make it shorter to try # click on 3 points, 5 times. # Don't forget to save the object returned by def_ldk... bot2 <- def_ldk(bot, 3) stack(bot2) bot2$ldk }"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":null,"dir":"Reference","previous_headings":"","what":"Add new landmarks based on angular positions — def_ldk_angle","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"wrapper coo_intersect_angle coo_intersect_direction Opn objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"","code":"def_ldk_angle(coo, angle) def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for default def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Out def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4]) # S3 method for Opn def_ldk_direction(coo, direction = c(\"down\", \"left\", \"up\", \"right\")[4])"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"coo Opn object angle numeric angle radians (0 default). direction character one \"\", \"left\", \"\", \"right\" (\"right\" default)","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"existing ldk preserved.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_ldk_angle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add new landmarks based on angular positions — def_ldk_angle","text":"","code":"# adds a new landmark towards south east hearts %>% slice(1:5) %>% # for speed purpose only def_ldk_angle(-pi/6) %>% stack() # on Out and towards NW and NE here olea %>% slice(1:5) %>% #for speed purpose only def_ldk_angle(3*pi/4) %>% def_ldk_angle(pi/4) %>% stack"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":null,"dir":"Reference","previous_headings":"","what":"Define tips as new landmarks — def_ldk_tips","title":"Define tips as new landmarks — def_ldk_tips","text":"Opn objects, can used coo_slice. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define tips as new landmarks — def_ldk_tips","text":"","code":"def_ldk_tips(coo)"},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define tips as new landmarks — def_ldk_tips","text":"coo Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define tips as new landmarks — def_ldk_tips","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Define tips as new landmarks — def_ldk_tips","text":"existing ldk preserved.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_ldk_tips.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define tips as new landmarks — def_ldk_tips","text":"","code":"is_ldk(olea) # no ldk for olea #> [1] FALSE olea %>% slice(1:3) %>% #for the sake of speed def_ldk_tips %>% def_ldk_angle(3*pi/4) %>% def_ldk_angle(pi/4) %T>% stack %>% coo_slice(ldk=1:4) -> oleas stack(oleas[[1]]) stack(oleas[[2]]) # etc."},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines links between landmarks — def_links","title":"Defines links between landmarks — def_links","text":"Works Ldk objects, 2-cols matrices, 3-dim arrays (MSHAPES turns matrix).","code":""},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines links between landmarks — def_links","text":"","code":"def_links(x, nb.ldk)"},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines links between landmarks — def_links","text":"x Ldk, matric array nb.ldk numeric iterative procedure stopped user click top graphical window.","code":""},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines links between landmarks — def_links","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_links.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines links between landmarks — def_links","text":"","code":"if (FALSE) { wm <- MSHAPES(wings) links <- def_links(wm, 3) # click to define pairs of landmarks ldk_links(wm, links) }"},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":null,"dir":"Reference","previous_headings":"","what":"Defines sliding landmarks matrix — def_slidings","title":"Defines sliding landmarks matrix — def_slidings","text":"Defines sliding landmarks matrix","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defines sliding landmarks matrix — def_slidings","text":"","code":"def_slidings(Coo, slidings)"},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defines sliding landmarks matrix — def_slidings","text":"Coo Ldk object slidings matrix, numeric list numeric. See Details","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Defines sliding landmarks matrix — def_slidings","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Defines sliding landmarks matrix — def_slidings","text":"$slidings Ldk must 'valid' matrix: containing ids coordinates, none lower 1 higher number coordinates $coo. slidings matrix contains 3 columns (, slide, ). inspired geomorph compatible . matrix can passed directly slidings argument matrix. course, strictly equivalent Ldk$slidings <- slidings. slidings can also passed \"partition(s)\", sliding landmarks identified ids (row number) consecutive $coo. single partition can passed either numeric (eg 4:12), points 5 11 must considered sliding landmarks (4 12 fixed); list numeric. See examples .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/def_slidings.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Defines sliding landmarks matrix — def_slidings","text":"","code":"#waiting for a sliding dataset..."},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Discrete cosinus transform — dfourier","title":"Discrete cosinus transform — dfourier","text":"Calculates discrete cosine transforms, introduced Dommergues colleagues, shape (mainly open outlines).","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Discrete cosinus transform — dfourier","text":"","code":"dfourier(coo, nb.h) # S3 method for default dfourier(coo, nb.h) # S3 method for Opn dfourier(coo, nb.h) # S3 method for list dfourier(coo, nb.h) # S3 method for Coo dfourier(coo, nb.h)"},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Discrete cosinus transform — dfourier","text":"coo matrix (list) (x; y) coordinates nb.h numeric number harmonics calculate","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Discrete cosinus transform — dfourier","text":"list following components: harmonic coefficients bn B harmonic coefficients mod modules points arg arguments points","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Discrete cosinus transform — dfourier","text":"method poorly tested Momocs considered experimental. Yet improved factor 10, method still long execute. improved releases painful right now. also explains progress bar. Shapes aligned performing dct transform. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Discrete cosinus transform — dfourier","text":"Dommergues, C. H., Dommergues, J.-L., & Verrecchia, E. P. (2007). Discrete Cosine Transform, Fourier-related Method Morphometric Analysis Open Contours. Mathematical Geology, 39(8), 749-763. doi:10.1007/s11004-007-9124-6 Many thanks Remi Laffont translation R).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Discrete cosinus transform — dfourier","text":"","code":"o <- olea %>% slice(1:5) # for the sake of speed od <- dfourier(o) #> 'nb.h' not provided and set to 12 #> od #> An OpnCoe object [ discrete cosine tansform analysis ] #> -------------------- #> - $coe: 5 open outlines described #> # A tibble: 5 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 op <- PCA(od) plot(op, 1) #> will be deprecated soon, see ?plot_PCA # dfourier and inverse dfourier o <- olea[1] o <- coo_bookstein(o) coo_plot(o) o.dfourier <- dfourier(o, nb.h=12) o.dfourier #> $an #> [1] -3.11820730 -0.13206715 -0.24781390 -0.09660325 -0.06788311 -0.06691169 #> [7] -0.03519719 -0.06016120 -0.02071002 -0.06544994 -0.01169704 -0.06810722 #> #> $bn #> [1] 0.032926049 -0.914830858 0.005334948 -0.268975696 -0.006644877 #> [6] -0.101625518 0.003834764 -0.049467452 0.003042230 -0.028964333 #> [11] -0.002260202 -0.022833346 #> #> $mod #> [1] 3.11838113 0.92431446 0.24787132 0.28579733 0.06820756 0.12167547 #> [7] 0.03540548 0.07788709 0.02093227 0.07157253 0.01191341 0.07183283 #> #> $phi #> [1] 3.131034 -1.714168 3.120068 -1.915601 -3.044016 -2.153064 3.033070 #> [8] -2.453432 2.995739 -2.724958 -2.950716 -2.818113 #> o.i <- dfourier_i(o.dfourier) o.i <- coo_bookstein(o.i) coo_draw(o.i, border='red') #future calibrate_reconstructions o <- olea[1] h.range <- 2:13 coo <- list() for (i in seq(along=h.range)){ coo[[i]] <- dfourier_i(dfourier(o, nb.h=h.range[i]))} names(coo) <- paste0('h', h.range) panel(Opn(coo), borders=col_india(12), names=TRUE) title('Discrete Cosine Transforms')"},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Investe discrete cosinus transform — dfourier_i","title":"Investe discrete cosinus transform — dfourier_i","text":"Calculates inverse discrete cosine transforms (see dfourier), given list B harmonic coefficients, typically produced dfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Investe discrete cosinus transform — dfourier_i","text":"","code":"dfourier_i(df, nb.h, nb.pts = 60)"},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Investe discrete cosinus transform — dfourier_i","text":"df list $$B components, containing harmonic coefficients. nb.h custom number harmonics use nb.pts numeric number pts shape reconstruction","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Investe discrete cosinus transform — dfourier_i","text":"matrix (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Investe discrete cosinus transform — dfourier_i","text":"core functions far. implemented Opn method soon.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Investe discrete cosinus transform — dfourier_i","text":"Dommergues, C. H., Dommergues, J.-L., & Verrecchia, E. P. (2007). Discrete Cosine Transform, Fourier-related Method Morphometric Analysis Open Contours. Mathematical Geology, 39(8), 749-763. doi:10.1007/s11004-007-9124-6 Many thanks Remi Laffont translation R).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Investe discrete cosinus transform — dfourier_i","text":"","code":"# dfourier and inverse dfourier o <- olea[1] o <- coo_bookstein(o) coo_plot(o) o.dfourier <- dfourier(o, nb.h=12) o.dfourier #> $an #> [1] -3.11820730 -0.13206715 -0.24781390 -0.09660325 -0.06788311 -0.06691169 #> [7] -0.03519719 -0.06016120 -0.02071002 -0.06544994 -0.01169704 -0.06810722 #> #> $bn #> [1] 0.032926049 -0.914830858 0.005334948 -0.268975696 -0.006644877 #> [6] -0.101625518 0.003834764 -0.049467452 0.003042230 -0.028964333 #> [11] -0.002260202 -0.022833346 #> #> $mod #> [1] 3.11838113 0.92431446 0.24787132 0.28579733 0.06820756 0.12167547 #> [7] 0.03540548 0.07788709 0.02093227 0.07157253 0.01191341 0.07183283 #> #> $phi #> [1] 3.131034 -1.714168 3.120068 -1.915601 -3.044016 -2.153064 3.033070 #> [8] -2.453432 2.995739 -2.724958 -2.950716 -2.818113 #> o.i <- dfourier_i(o.dfourier) o.i <- coo_bookstein(o.i) coo_draw(o.i, border='red') o <- olea[1] h.range <- 2:13 coo <- list() for (i in seq(along=h.range)){ coo[[i]] <- dfourier_i(dfourier(o, nb.h=h.range[i]))} names(coo) <- paste0('h', h.range) panel(Opn(coo), borders=col_india(12), names=TRUE) title('Discrete Cosine Transforms')"},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draws 'dfourier' shapes — dfourier_shape","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"Calculates shapes based 'Discrete cosine transforms' given harmonic coefficients (see dfourier) can generate random 'dfourier' shapes. Mainly intended generate shapes /understand dfourier works.","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"","code":"dfourier_shape(A, B, nb.h, nb.pts = 60, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"vector harmonic coefficients B vector harmonic coefficients nb.h /B provided, number harmonics generate nb.pts /B provided, number points use reconstruct shapes alpha power coefficient associated (usually decreasing) amplitude harmonic coefficients (see efourier_shape) plot logical whether plot shape","code":""},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"list shapes plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draws 'dfourier' shapes — dfourier_shape","text":"","code":"# some signatures panel(coo_align(Opn(replicate(48, dfourier_shape(alpha=0.5, nb.h=6))))) # some worms panel(coo_align(Opn(replicate(48, dfourier_shape(alpha=2, nb.h=6)))))"},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":null,"dir":"Reference","previous_headings":"","what":"Dissolve Coe objects — dissolve","title":"Dissolve Coe objects — dissolve","text":"opposite combine, typically used . Note $fac slot may wrong since combine...well combines... $fac. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Dissolve Coe objects — dissolve","text":"","code":"dissolve(x, retain)"},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Dissolve Coe objects — dissolve","text":"x Coe object retain partition id retain. name partitions named (see x$method) eg chop","code":""},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Dissolve Coe objects — dissolve","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/dissolve.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Dissolve Coe objects — dissolve","text":"","code":"data(bot) w <- filter(bot, type==\"whisky\") b <- filter(bot, type==\"beer\") wf <- efourier(w, 10) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bf <- efourier(b, 10) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details wbf <- combine(wf, bf) dissolve(wbf, 1) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows dissolve(wbf, 2) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 14 more rows # or using chop (yet combine here makes no sense) bw <- bot %>% chop(~type) %>% lapply(efourier, 10) %>% combine #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bw %>% dissolve(1) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows bw %>% dissolve(2) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 20 outlines described, 10 harmonics #> # A tibble: 20 × 2 #> type fake #> #> 1 beer c #> 2 beer c #> 3 beer c #> 4 beer c #> 5 beer c #> 6 beer c #> # ℹ 14 more rows"},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr drawers for shape plots — drawers","title":"grindr drawers for shape plots — drawers","text":"Useful drawers building custom shape plots using grindr approach. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr drawers for shape plots — drawers","text":"","code":"draw_polygon( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_outline( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_outlines( coo, f, col = par(\"fg\"), fill = NA, lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_points( coo, f, col = par(\"fg\"), cex = 1/2, pch = 20, transp = 0, pal = pal_qual, ... ) draw_landmarks( coo, f, col = par(\"fg\"), cex = 1/2, pch = 20, transp = 0, pal = pal_qual, ... ) draw_lines( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_centroid( coo, f, col = par(\"fg\"), pch = 3, cex = 0.5, transp = 0, pal = pal_qual, ... ) draw_curve( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_curves( coo, f, col = par(\"fg\"), lwd = 1, lty = 1, transp = 0, pal = pal_qual, ... ) draw_firstpoint( coo, f, label = \"^\", col = par(\"fg\"), cex = 3/4, transp = 0, pal = pal_qual, ... ) draw_axes(coo, col = \"#999999\", lwd = 1/2, ...) draw_ticks(coo, col = \"#333333\", cex = 3/4, lwd = 3/4, ...) draw_labels(coo, labels = 1:nrow(coo), cex = 1/2, d = 1/20, ...) draw_links( coo, f, links, col = \"#99999955\", lwd = 1/2, lty = 1, transp = 0, pal = pal_qual, ... ) draw_title( coo, main = \"\", sub = \"\", cex = c(1, 3/4), font = c(2, 1), padding = 1/200, ... )"},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr drawers for shape plots — drawers","text":"coo matrix 2 columns (x, y) coordinates f optionnal factor specification feed. See examples vignettes. col color (hexadecimal) draw components fill color (hexadecimal) draw components lwd draw components lty draw components transp numeric transparency (default:0, min:0, max:1) pal palette use col/border/etc. provided. See [palettes] ... additional options feed core functions drawer cex draw components ((c(2, 1) default) draw_title) pch draw components label indicate first point labels character name labels draw (defaut 1:nrow(coo)) d numeric proportion d(centroid-each_point) add centrifugating landmarks links matrix links use draw segments landmarks. See wings$ldk example main character title (empty default) sub character subtitle (empty default) font numeric feed text (c(2, 1) default) padding numeric fraction graphical window (1/200 default)","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr drawers for shape plots — drawers","text":"drawing layer","code":""},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"grindr drawers for shape plots — drawers","text":"approach (soon) replace coo_plot friends versions. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/drawers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"grindr drawers for shape plots — drawers","text":"","code":"bot[1] %>% paper_grid() %>% draw_polygon() olea %>% paper_chess %>% draw_lines(~var) hearts[240] %>% paper_white() %>% draw_outline() %>% coo_sample(24) %>% draw_landmarks %>% draw_labels() %>% draw_links(links=replicate(2, sample(1:24, 8))) bot %>% paper_grid() %>% draw_outlines() %>% draw_title(\"Alcohol abuse \\nis dangerous for health\", \"Drink responsibly\")"},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean distance between two points. — ed","title":"Calculates euclidean distance between two points. — ed","text":"ed simply calculates euclidean distance two points defined (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean distance between two points. — ed","text":"","code":"ed(pt1, pt2)"},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean distance between two points. — ed","text":"pt1 (x; y) coordinates first point. pt2 (x; y) coordinates second point.","code":""},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean distance between two points. — ed","text":"Returns euclidean distance two points.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean distance between two points. — ed","text":"","code":"ed(c(0,1), c(1,0)) #> [1] 1.414214"},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean intermediate between two points. — edi","title":"Calculates euclidean intermediate between two points. — edi","text":"edi simply calculates coordinates points relative distance r pt1-pt2 defined (x; y) coordinates. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean intermediate between two points. — edi","text":"","code":"edi(pt1, pt2, r = 0.5)"},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean intermediate between two points. — edi","text":"pt1 \\((x; y)\\) coordinates first point. pt2 \\((x; y)\\) coordinates second point. r relative distance pt1 pt2.","code":""},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean intermediate between two points. — edi","text":"returns \\((x; y)\\) interpolated coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean intermediate between two points. — edi","text":"","code":"edi(c(0,1), c(1,0), r = 0.5) #> [1] 0.5 0.5"},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates euclidean distance every pairs of points in two matrices. — edm","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"edm returns euclidean distances points \\(1 -> n\\) two 2-col matrices dimension. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"","code":"edm(m1, m2)"},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"m1 first matrix coordinates. m2 second matrix coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"Returns vector euclidean distances pairwise coordinates two matrices.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"one wishes align two (shapes) Procrustes surimposition may provide better solution.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates euclidean distance every pairs of points in two matrices. — edm","text":"","code":"x <- matrix(1:10, nc=2) edm(x, x) #> [1] 0 0 0 0 0 edm(x, x+1) #> [1] 1.414214 1.414214 1.414214 1.414214 1.414214"},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"edm_nearest calculates shortest euclidean distance found every point one matrix among second. words, m1, m2 n rows, result shortest distance first point m1 point m2 , n times. function used internally may interest analyses.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"","code":"edm_nearest(m1, m2, full = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"m1 first list matrix coordinates. m2 second list matrix coordinates. full logical. Whether returns condensed version results.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"full TRUE, returns list two components: d every point m1 shortest distance found point m2, pos (m2) row indices points. Otherwise returns d numeric vector shortest distances.","code":""},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"far function quite time consumming since performs \\( n \\times n \\) euclidean distance computation. one wishes align two (shapes) Procrustes surimposition may provide better solution.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/edm_nearest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the shortest euclidean distance found for every point of one\nmatrix among those of a second. — edm_nearest","text":"","code":"x <- matrix(1:10, nc=2) edm_nearest(x, x+rnorm(10)) #> [1] 0.9276974 0.2276210 1.3132366 0.3104909 1.5710566 edm_nearest(x, x+rnorm(10), full=TRUE) #> $d #> [1] 1.2055581 1.0015449 1.1344017 1.1321094 0.5926906 #> #> $pos #> [1] 1 1 3 5 5 #>"},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Elliptical Fourier transform (and its normalization) — efourier","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"efourier computes Elliptical Fourier Analysis (Transforms EFT) matrix (list) (x; y) coordinates. efourier_norm normalizes Fourier coefficients. Read Details carefully.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"","code":"efourier(x, ...) # S3 method for default efourier(x, nb.h, smooth.it = 0, ...) # S3 method for Out efourier(x, nb.h, smooth.it = 0, norm = TRUE, start = FALSE, ...) # S3 method for list efourier(x, ...) efourier_norm(ef, start = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"x list matrix coordinates object ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform. norm whether normalize coefficients using efourier_norm start logical. efourier whether consider first point homologous; efourier_norm whether conserve position first point outline. ef list a_n, b_n, c_n d_n Fourier coefficients, typically returned efourier","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"efourier, list components: , bn, cn, dn harmonic coefficients, plus ao co. latter named a0 c0 Claude (2008) (intentionnaly) propagated error. efourier_norm, list components: , B, C, D harmonic coefficients, plus size, magnitude semi-major axis first fitting ellipse, theta angle, radians, starting semi-major axis first fitting ellipse, psi orientation first fitting ellipse, ao , , lnef concatenation coefficients.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"maths behind see paper JSS. Normalization coefficients long matter trouble, newcomers. two ways normalizing outlines: first, far used, use \"numerical\" alignment, directly matrix coefficients. coefficients first harmonic consumed process harmonics higher rank normalized terms size rotation. sometimes referred using \"first ellipse\", harmonics define ellipse plane, first one mother ellipses, others \"roll\" along. approach really convenient done easily software (option) Momocs . default option efourier. pitfall: shapes prone bad aligments among first ellipses, result poorly (even ) \"homologous\" coefficients. shapes particularly prone either (least roughly) circular /strong bilateral symmetry. can try use stack Coe object returned efourier. Also, perhaps explicitely, morphospace usually show mirroring symmetry, typically visible calculated couple components (usually first two). see upside-(180 degrees rotated) shapes morphospace, seriously consider aligning shapes efourier step, performing latter norm = FALSE. pitfall explains (quite annoying) message passing efourier just . several options align shapes, using control points (landmarks), far time consuming (less reproducible) possibly best one alignment tricky automate. can also try Procrustes alignment (see fgProcrustes) calliper length (see coo_aligncalliper), etc. also make first point homologous either coo_slide coo_slidedirection minimize subsequent problems. dedicate (day) vignette paper problem.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"Directly borrowed Claude (2008). Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Elliptical Fourier transform (and its normalization) — efourier","text":"","code":"# single shape coo <- bot[1] coo_plot(coo) ef <- efourier(coo, 12) # same but silent efourier(coo, 12, norm=TRUE) #> $an #> [1] -143.1142910 5.2925309 22.9922936 -11.3596452 -14.9412217 #> [6] -5.4200881 5.7177112 0.4509076 0.3107020 -3.1633079 #> [11] 0.2814646 3.4927761 #> #> $bn #> [1] -13.8501141 -21.8994092 11.4235084 13.5870435 -12.6401807 2.5050679 #> [7] 5.1968464 -0.5366171 -1.0431706 1.0823659 2.3427969 0.1022387 #> #> $cn #> [1] 64.44753053 -3.15375656 -17.96822626 5.76052596 7.17390949 #> [6] -2.98410094 -1.20013013 1.18299684 -0.36305436 -0.46782525 #> [11] 0.67134872 0.08954658 #> #> $dn #> [1] -484.90299209 -1.04774048 42.07408510 3.40654863 -9.19128141 #> [6] -2.99359284 0.96722479 2.22582484 0.02026172 -2.26134728 #> [11] -0.04679906 0.80569603 #> #> $ao #> [1] 349.02 #> #> $co #> [1] 1080.921 #> # inverse EFT efi <- efourier_i(ef) coo_draw(efi, border='red', col=NA) # on Out bot %>% slice(1:5) %>% efourier #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 5 outlines described, 10 harmonics #> # A tibble: 5 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a"},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse elliptical Fourier transform — efourier_i","title":"Inverse elliptical Fourier transform — efourier_i","text":"efourier_i uses inverse elliptical Fourier transformation calculate shape, given list Fourier coefficients, typically obtained computed efourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse elliptical Fourier transform — efourier_i","text":"","code":"efourier_i(ef, nb.h, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse elliptical Fourier transform — efourier_i","text":"ef list. list containing \\(a_n\\), \\(b_n\\), \\(c_n\\) \\(d_n\\) Fourier coefficients, returned efourier. nb.h integer. number harmonics use. specified, length(ef$) used. nb.pts integer. number points calculate.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse elliptical Fourier transform — efourier_i","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse elliptical Fourier transform — efourier_i","text":"See efourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse elliptical Fourier transform — efourier_i","text":"Directly borrowed Claude (2008), also called iefourier .","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse elliptical Fourier transform — efourier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse elliptical Fourier transform — efourier_i","text":"","code":"coo <- bot[1] coo_plot(coo) ef <- efourier(coo, 12) ef #> $an #> [1] -143.1142910 5.2925309 22.9922936 -11.3596452 -14.9412217 #> [6] -5.4200881 5.7177112 0.4509076 0.3107020 -3.1633079 #> [11] 0.2814646 3.4927761 #> #> $bn #> [1] -13.8501141 -21.8994092 11.4235084 13.5870435 -12.6401807 2.5050679 #> [7] 5.1968464 -0.5366171 -1.0431706 1.0823659 2.3427969 0.1022387 #> #> $cn #> [1] 64.44753053 -3.15375656 -17.96822626 5.76052596 7.17390949 #> [6] -2.98410094 -1.20013013 1.18299684 -0.36305436 -0.46782525 #> [11] 0.67134872 0.08954658 #> #> $dn #> [1] -484.90299209 -1.04774048 42.07408510 3.40654863 -9.19128141 #> [6] -2.99359284 0.96722479 2.22582484 0.02026172 -2.26134728 #> [11] -0.04679906 0.80569603 #> #> $ao #> [1] 349.02 #> #> $co #> [1] 1080.921 #> efi <- efourier_i(ef) coo_draw(efi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'efourier' shapes. — efourier_shape","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"efourier_shape calculates 'Fourier elliptical shape' given Fourier coefficients (see Details) can generate 'efourier' shapes. Mainly intended generate shapes /understand efourier works.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"","code":"efourier_shape(an, bn, cn, dn, nb.h, nb.pts = 60, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. cn numeric. \\(c_n\\) Fourier coefficients calculate shape. dn numeric. \\(d_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"list components: x vector x-coordinates y vector y-coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"efourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See efourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp. Ferson S, Rohlf FJ, Koehn RK. 1985. Measuring shape variation two-dimensional outlines. Systematic Biology 34: 59-68.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/efourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'efourier' shapes. — efourier_shape","text":"","code":"ef <- efourier(bot[1], 24) efourier_shape(ef$an, ef$bn, ef$cn, ef$dn) # equivalent to efourier_i(ef) #> x y #> [1,] -139.292006 52.55414 #> [2,] -136.616807 10.69211 #> [3,] -131.350271 -30.94211 #> [4,] -125.199336 -72.07640 #> [5,] -118.953152 -113.78248 #> [6,] -113.609682 -155.07182 #> [7,] -110.814096 -196.99594 #> [8,] -110.406802 -238.82588 #> [9,] -114.448576 -280.46843 #> [10,] -121.291958 -321.87890 #> [11,] -128.793705 -362.93618 #> [12,] -133.799480 -404.68963 #> [13,] -133.459946 -446.39242 #> [14,] -121.381226 -485.99486 #> [15,] -90.225043 -512.97786 #> [16,] -49.878625 -523.21089 #> [17,] -8.353210 -526.12066 #> [18,] 33.911396 -525.08469 #> [19,] 74.759609 -519.43972 #> [20,] 113.051448 -502.25491 #> [21,] 136.285584 -468.52283 #> [22,] 141.399365 -427.41134 #> [23,] 140.746409 -385.31652 #> [24,] 138.719031 -343.56495 #> [25,] 136.547192 -301.87577 #> [26,] 132.884166 -259.94004 #> [27,] 128.335128 -218.62173 #> [28,] 123.859620 -176.68909 #> [29,] 118.283114 -135.32263 #> [30,] 115.872309 -93.60856 #> [31,] 116.738256 -51.46991 #> [32,] 121.746650 -10.34707 #> [33,] 130.044438 31.28459 #> [34,] 135.215555 72.30011 #> [35,] 135.968480 114.36171 #> [36,] 127.773756 155.43284 #> [37,] 110.008193 192.61949 #> [38,] 91.059514 230.59227 #> [39,] 78.417823 270.00689 #> [40,] 72.336775 311.64758 #> [41,] 67.126887 353.28501 #> [42,] 63.718346 394.51271 #> [43,] 58.801472 437.18028 #> [44,] 54.675788 477.22927 #> [45,] 57.783825 520.56987 #> [46,] 46.279411 554.26720 #> [47,] 8.173233 561.94185 #> [48,] -37.145543 559.89637 #> [49,] -64.096831 541.62656 #> [50,] -64.927840 500.81669 #> [51,] -64.170645 459.21723 #> [52,] -69.796352 417.94924 #> [53,] -72.732679 375.54798 #> [54,] -77.369097 334.76587 #> [55,] -80.882096 292.41632 #> [56,] -87.983533 251.76743 #> [57,] -103.969321 212.65038 #> [58,] -121.348549 174.68203 #> [59,] -136.478064 135.92288 #> [60,] -141.748300 94.09730 efourier_shape() # is autonomous #> x y #> [1,] -0.15480069 -1.973007909 #> [2,] -0.22809026 -1.818420231 #> [3,] -0.27032753 -1.617424063 #> [4,] -0.29533144 -1.379645958 #> [5,] -0.31810038 -1.115840290 #> [6,] -0.35332863 -0.837066371 #> [7,] -0.41396840 -0.553906111 #> [8,] -0.50997009 -0.275789459 #> [9,] -0.64731572 -0.010481905 #> [10,] -0.82743225 0.236229469 #> [11,] -1.04703483 0.460635732 #> [12,] -1.29840910 0.660997728 #> [13,] -1.57010032 0.837256167 #> [14,] -1.84793879 0.990604033 #> [15,] -2.11630003 1.122977481 #> [16,] -2.35947761 1.236527684 #> [17,] -2.56303702 1.333135713 #> [18,] -2.71502309 1.414025714 #> [19,] -2.80690968 1.479519099 #> [20,] -2.83420662 1.528955598 #> [21,] -2.79667422 1.560787525 #> [22,] -2.69813421 1.572833685 #> [23,] -2.54590625 1.562660872 #> [24,] -2.34993539 1.528046001 #> [25,] -2.12170552 1.467461982 #> [26,] -1.87305376 1.380526662 #> [27,] -1.61500882 1.268356875 #> [28,] -1.35677236 1.133778649 #> [29,] -1.10494596 0.981359078 #> [30,] -0.86308017 0.817243778 #> [31,] -0.63158802 0.648804395 #> [32,] -0.40802730 0.484121281 #> [33,] -0.18771750 0.331344943 #> [34,] 0.03537770 0.197994496 #> [35,] 0.26759916 0.090260326 #> [36,] 0.51448708 0.012380671 #> [37,] 0.77974312 -0.033842603 #> [38,] 1.06437497 -0.049334829 #> [39,] 1.36612060 -0.037808467 #> [40,] 1.67922192 -0.005575404 #> [41,] 1.99458198 0.038882082 #> [42,] 2.30030138 0.085552509 #> [43,] 2.58255024 0.123698665 #> [44,] 2.82669741 0.142757057 #> [45,] 3.01859091 0.133256549 #> [46,] 3.14586632 0.087675830 #> [47,] 3.19915458 0.001163238 #> [48,] 3.17306813 -0.127946593 #> [49,] 3.06686342 -0.297867638 #> [50,] 2.88470784 -0.503375634 #> [51,] 2.63551577 -0.736101825 #> [52,] 2.33235949 -0.985084971 #> [53,] 1.99150137 -1.237536583 #> [54,] 1.63113051 -1.479755629 #> [55,] 1.26991586 -1.698116048 #> [56,] 0.92550660 -1.880044476 #> [57,] 0.61311653 -2.014907112 #> [58,] 0.34432245 -2.094733481 #> [59,] 0.12618734 -2.114720168 #> [60,] -0.03921072 -2.073477807 panel(Out(a2l(replicate(100, efourier_shape(nb.h=6, alpha=2.5, plot=FALSE))))) # Bubble family"},{"path":"http://momx.github.io/Momocs/reference/export.html","id":null,"dir":"Reference","previous_headings":"","what":"Exports Coe objects and shapes — export","title":"Exports Coe objects and shapes — export","text":"Writes .txt .xls whatever readable single shape, Coe, PCA object, along individual names $fac.","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Exports Coe objects and shapes — export","text":"","code":"export(x, file, sep, dec)"},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Exports Coe objects and shapes — export","text":"x Coe PCA object file filenames data.txt default sep field separator string feed write.table). (default tab) tab default dec string feed write.table) (default \".\") default.","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Exports Coe objects and shapes — export","text":"external file","code":""},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Exports Coe objects and shapes — export","text":"simple wrapper around write.table. Default parameters write .txt file, readable foreign programs. default parameters, numbers use dots decimal points, considered character chain Excel many countries (locale versions). can solved using dec=',' examples . looking file, specified file, getwd() help. mention everytime use function, cowardly run R Excel 'statistics' , innocent adorable kitten probably murdered somewhere. Use R!","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/export.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Exports Coe objects and shapes — export","text":"","code":"# Will write (and remove) files on your working directory! if (FALSE) { bf <- efourier(bot, 6) # Export Coe (here Fourier coefficients) export(bf) # data.txt which can be opened by every software including MS Excel # If you come from a country that uses comma as decimal separator (not recommended, but...) export(bf, dec=',') export(bf, file='data.xls', dec=',') # Export PCA scores bf %>% PCA %>% export() # for shapes (matrices) # export(bot[1], file='bot1.txt') # remove these files from your machine file.remove(\"coefficients.txt\", \"data.xls\", \"scores.txt\") }"},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Procrustes alignment between two shapes — fProcrustes","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"Directly borrowed Claude (2008), called fPsup function.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"","code":"fProcrustes(coo1, coo2)"},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"coo1 configuration matrix superimposed onto centered preshape coo2. coo2 reference configuration matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"list components: coo1 superimposed centered preshape coo1 onto centered preshape coo2 coo2 centered preshape coo2 rotation rotation matrix scale scale parameter DF full Procrustes distance coo1 coo2.","code":""},{"path":"http://momx.github.io/Momocs/reference/fProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Full Procrustes alignment between two shapes — fProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":null,"dir":"Reference","previous_headings":"","what":"Brew and serve fac from Momocs object — fac_dispatcher","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"Ease various specifications fac specification passed Momocs objects. Intensively used (internally).","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"","code":"fac_dispatcher(x, fac)"},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"x Momocs object (Coo, Coe, PCA, etc.) fac specification extract fac","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"prepared factor (numeric). See examples","code":""},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"fac can : factor, passed fly column id $fac column name fac; found, return NULL message formula form: ~column_name ($fac, quotes). expresses concise way. Also allows interacting fly. See examples. NULL returns NULL, message","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fac_dispatcher.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Brew and serve fac from Momocs object — fac_dispatcher","text":"","code":"bot <- mutate(bot, s=rnorm(40), fake=factor(rep(letters[1:4], 10))) # factor, on the fly fac_dispatcher(bot, factor(rep(letters[1:4], 10))) #> [1] a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b c d a b #> [39] c d #> Levels: a b c d # column id fac_dispatcher(bot, 1) #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # column name fac_dispatcher(bot, \"type\") #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # same, numeric case fac_dispatcher(bot, \"s\") #> s1 s2 s3 s4 s5 s6 #> 1.708650899 -0.759601384 0.972369565 -1.031840383 0.768586627 0.301285060 #> s7 s8 s9 s10 s11 s12 #> 0.424560581 0.006571057 0.741297749 1.559007487 -0.417168752 -0.420322963 #> s13 s14 s15 s16 s17 s18 #> 0.697185864 -0.210961609 1.541085498 0.284831960 0.321961376 -1.068526069 #> s19 s20 s21 s22 s23 s24 #> 1.425715862 1.199570200 -1.678036407 1.828806163 -0.535208856 -0.835660641 #> s25 s26 s27 s28 s29 s30 #> -0.758469900 -1.324129902 0.788467471 -1.376718465 -1.070395242 -0.986740931 #> s31 s32 s33 s34 s35 s36 #> 0.536586184 -0.445206584 -0.003501437 -0.623814095 0.460846925 -0.577520120 #> s37 s38 s39 s40 #> 1.687608566 0.025660517 -0.590307162 1.382021803 # formula interface fac_dispatcher(bot, ~type) #> type1 type2 type3 type4 type5 type6 type7 type8 type9 type10 type11 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky whisky #> type12 type13 type14 type15 type16 type17 type18 type19 type20 type21 type22 #> whisky whisky whisky whisky whisky whisky whisky whisky whisky beer beer #> type23 type24 type25 type26 type27 type28 type29 type30 type31 type32 type33 #> beer beer beer beer beer beer beer beer beer beer beer #> type34 type35 type36 type37 type38 type39 type40 #> beer beer beer beer beer beer beer #> Levels: beer whisky # formula interface + interaction on the fly fac_dispatcher(bot, ~type+fake) #> [1] whisky_a whisky_b whisky_c whisky_d whisky_a whisky_b whisky_c whisky_d #> [9] whisky_a whisky_b whisky_c whisky_d whisky_a whisky_b whisky_c whisky_d #> [17] whisky_a whisky_b whisky_c whisky_d beer_a beer_b beer_c beer_d #> [25] beer_a beer_b beer_c beer_d beer_a beer_b beer_c beer_d #> [33] beer_a beer_b beer_c beer_d beer_a beer_b beer_c beer_d #> Levels: beer_a beer_b beer_c beer_d whisky_a whisky_b whisky_c whisky_d # when passing NULL or non existing column fac_dispatcher(42, NULL) #> NULL fac_dispatcher(bot, \"loser\") #> not a valid column specification, returning NULL #> NULL"},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Generalized Procrustes alignment between shapes — fgProcrustes","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Directly borrowed Claude (2008), called fgpa2 function.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"","code":"fgProcrustes(x, tol, coo)"},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"x array, list configurations, , Opn Ldk object tol numeric stop iterations coo logical, working Opn, whether use $coo rather $ldk","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"list components: rotated array superimposed configurations iterationnumber number iterations Q convergence criterion Qi full list Q Qd difference successive Q interproc.dist minimal sum squared norms pairwise differences shapes superimposed sample mshape mean shape configuration cent.size vector centroid sizes. , Opn Ldk object.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"performed Opn object, try use $ldk slot, landmarks previousy defined, (message) $coo slot, case, shapes must number coordinates (coo_sample may help).","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Slightly less optimized procGPA shapes package (~20% machine). optimized performance last thing improve! Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fgProcrustes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Full Generalized Procrustes alignment between shapes — fgProcrustes","text":"","code":"# on Ldk w <- wings %>% slice(1:5) # for the sake of speed stack(w) fgProcrustes(w, tol=0.1) %>% stack() #> iteration: 1 \tgain: 77.967 #> iteration: 2 \tgain: 0.00039082 # on Out h <- hearts %>% slice(1:5) # for the sake of speed stack(h) fgProcrustes(h) %>% stack() #> iteration: 1 \tgain: 8.1326 #> iteration: 2 \tgain: 0.00031224 #> iteration: 3 \tgain: 4.8293e-05 #> iteration: 4 \tgain: 1.0158e-06 #> iteration: 5 \tgain: 4.1771e-05 #> iteration: 6 \tgain: 7.9575e-06 #> iteration: 7 \tgain: 9.2944e-06 #> iteration: 8 \tgain: 3.1971e-07 #> iteration: 9 \tgain: 5.6429e-06 #> iteration: 10 \tgain: 3.6475e-06 #> iteration: 11 \tgain: 1.0455e-06 #> iteration: 12 \tgain: 4.6442e-08 #> iteration: 13 \tgain: 3.9276e-07 #> iteration: 14 \tgain: 5.6006e-07 #> iteration: 15 \tgain: 3.5497e-07 #> iteration: 16 \tgain: 2.2619e-08 #> iteration: 17 \tgain: 1.6228e-07 #> iteration: 18 \tgain: 1.662e-07 #> iteration: 19 \tgain: 8.6435e-08 #> iteration: 20 \tgain: 6.7107e-09 #> iteration: 21 \tgain: 3.6428e-08 #> iteration: 22 \tgain: 4.0699e-08 #> iteration: 23 \tgain: 2.2641e-08 #> iteration: 24 \tgain: 2.0915e-09 #> iteration: 25 \tgain: 9.3406e-09 #> iteration: 26 \tgain: 1.0441e-08 #> iteration: 27 \tgain: 5.8207e-09 #> iteration: 28 \tgain: 6.1735e-10 #> iteration: 29 \tgain: 2.312e-09 #> iteration: 30 \tgain: 2.6457e-09 #> iteration: 31 \tgain: 1.502e-09 #> iteration: 32 \tgain: 1.793e-10 #> iteration: 33 \tgain: 5.7701e-10 #> iteration: 34 \tgain: 6.7226e-10 #> iteration: 35 \tgain: 3.8692e-10 #> iteration: 36 \tgain: 5.1135e-11"},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"Directly wrapped around geomorph::gpagen.","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"","code":"fgsProcrustes(x)"},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"See ?gpagen geomorph package","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"x Ldk object $slidings","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"list","code":""},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"Landmarks methods less tested Momocs. Keep mind features still experimental help welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/fgsProcrustes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Full Generalized Procrustes alignment between shapes with sliding landmarks — fgsProcrustes","text":"","code":"ch <- chaff %>% slice(1:5) # for the sake of speed chaffp <- fgsProcrustes(ch) #> #> Performing GPA #> | | | 0% | |======= | 10% #> Singular BE matrix; using generalized inverse | |============== | 20% #> Singular BE matrix; using generalized inverse | |===================== | 30% #> Singular BE matrix; using generalized inverse | |============================ | 40% #> Singular BE matrix; using generalized inverse | |=================================== | 50% #> Singular BE matrix; using generalized inverse | |========================================== | 60% #> Singular BE matrix; using generalized inverse | |================================================= | 70% #> Singular BE matrix; using generalized inverse | |======================================================== | 80% #> Singular BE matrix; using generalized inverse | |=============================================================== | 90% #> Singular BE matrix; using generalized inverse | |======================================================================| 100% #> #> Making projections... Finished! chaffp #> An LdkCoe [full Generalized Procrustes] object with: #> -------------------- #> - $coo: 5 configuration of landmarks (172 +/- 0 coordinates) #> # A tibble: 5 × 3 #> id taxa centsize #> #> 1 571 tax1 1343. #> 2 572 tax1 1279. #> 3 573 tax1 1232. #> 4 581 tax1 1296. #> 5 582 tax1 1274. chaffp %>% PCA() %>% plot(\"taxa\") #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset based on conditions — filter","title":"Subset based on conditions — filter","text":"Return shapes matching conditions, $fac. See examples ?dplyr::filter.","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset based on conditions — filter","text":"","code":"filter(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset based on conditions — filter","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset based on conditions — filter","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset based on conditions — filter","text":"dplyr verbs maintained. probbaly filter PCA objects. latter calculated using individuals filtering may lead false conclusions. want highlith individuals, see examples plot_PCA.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/filter.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset based on conditions — filter","text":"","code":"olea #> Opn (curves) #> - 210 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk # we retain on dorsal views filter(olea, view==\"VD\") #> Opn (curves) #> - 120 curves, 100 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 120 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VD O11 #> 3 Aglan cult VD O12 #> 4 Aglan cult VD O13 #> 5 Aglan cult VD O14 #> 6 Aglan cult VD O15 #> # ℹ 114 more rows #> - also: $ldk # only dorsal views and Aglan+PicMa varieties filter(olea, view==\"VD\", var %in% c(\"Aglan\", \"PicMa\")) #> Opn (curves) #> - 60 curves, 100 +/- 2 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 60 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VD O11 #> 3 Aglan cult VD O12 #> 4 Aglan cult VD O13 #> 5 Aglan cult VD O14 #> 6 Aglan cult VD O15 #> # ℹ 54 more rows #> - also: $ldk # we create an id column and retain the 120 first shapes olea %>% mutate(id=1:length(olea)) %>% filter(id > 120) #> Opn (curves) #> - 90 curves, 99 +/- 4 coords (in $coo) #> - 5 classifiers (in $fac): #> # A tibble: 90 × 5 #> var domes view ind id #> #> 1 PicMa cult VD O24 121 #> 2 PicMa cult VL O24 122 #> 3 PicMa cult VD O25 123 #> 4 PicMa cult VL O25 124 #> 5 PicMa cult VD O26 125 #> 6 PicMa cult VL O26 126 #> # ℹ 84 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":null,"dir":"Reference","previous_headings":"","what":"Flips PCA axes — flip_PCaxes","title":"Flips PCA axes — flip_PCaxes","text":"Simply multiply -1, corresponding scores rotation vectors PCA objects. PC orientation arbitrary, may help better display.","code":""},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Flips PCA axes — flip_PCaxes","text":"","code":"flip_PCaxes(x, axs)"},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Flips PCA axes — flip_PCaxes","text":"x PCA object axs numeric PC(s) flip","code":""},{"path":"http://momx.github.io/Momocs/reference/flip_PCaxes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Flips PCA axes — flip_PCaxes","text":"","code":"bp <- bot %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bp %>% plot #> will be deprecated soon, see ?plot_PCA bp %>% flip_PCaxes(1) %>% plot() #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates convex hull area/volume of PCA scores — get_chull_area","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"May useful compare shape diversity. Expressed PCA units compared within PCA.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"","code":"get_chull_area(x, fac, xax = 1, yax = 2) get_chull_volume(x, fac, xax = 1, yax = 2, zax = 3)"},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"x PCA object fac (optionnal) column name ID $fac slot. xax first PC axis use (1 default) yax second PC axis (2 default) zax third PC axis (3 default volume)","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"fac provided global area/volume returned; otherwise named list every level fac","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"get_chull_area calculated using coo_chull followed coo_area; get_chull_volume calculated using geometry::convexhulln","code":""},{"path":"http://momx.github.io/Momocs/reference/get_chull_area.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates convex hull area/volume of PCA scores — get_chull_area","text":"","code":"bp <- PCA(efourier(bot, 12)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details get_chull_area(bp) #> [1] 0.01968577 get_chull_area(bp, 1) #> $beer #> [1] 0.01802331 #> #> $whisky #> [1] 0.008768242 #> get_chull_volume(bp) #> [1] 0.0005563784 get_chull_volume(bp, 1) #> $beer #> [1] 0.0004506466 #> #> $whisky #> [1] 0.0001181342 #>"},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieves landmarks coordinates — get_ldk","title":"Retrieves landmarks coordinates — get_ldk","text":"See Details different behaviors implemented.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieves landmarks coordinates — get_ldk","text":"","code":"get_ldk(Coo)"},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieves landmarks coordinates — get_ldk","text":"Coo , Opn Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieves landmarks coordinates — get_ldk","text":"list shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieves landmarks coordinates — get_ldk","text":"Different behaviors depending class object: Ldk: retrieves landmarks. Ldk slidings defined: retrieves fixed landmarks, sliding ones. See also get_slidings. landmarks $ldk $coo, . Opn: .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/get_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieves landmarks coordinates — get_ldk","text":"","code":"# Out example ldk.h <- get_ldk(hearts) stack(Ldk(ldk.h)) # on Ldk (no slidings) get_ldk(wings) # equivalent to wings$coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> [7,] 0.2311 -0.0228 #> [8,] 0.2040 -0.0452 #> [9,] 0.1282 -0.0742 #> [10,] 0.0424 -0.0966 #> [11,] -0.0674 -0.1108 #> [12,] -0.4102 -0.0163 #> [13,] -0.3140 0.0318 #> [14,] -0.1768 0.0341 #> [15,] 0.0715 0.0509 #> [16,] -0.0540 0.0238 #> [17,] 0.0575 -0.0059 #> [18,] -0.1401 -0.0240 #> #> $AN2 #> [,1] [,2] #> [1,] -0.4814 0.0135 #> [2,] -0.0058 0.0780 #> [3,] 0.2345 0.0644 #> [4,] 0.2460 0.0467 #> [5,] 0.2487 0.0281 #> [6,] 0.2430 0.0115 #> [7,] 0.2316 -0.0039 #> [8,] 0.1956 -0.0305 #> [9,] 0.1462 -0.0545 #> [10,] 0.0483 -0.0866 #> [11,] -0.0520 -0.1047 #> [12,] -0.4016 -0.0250 #> [13,] -0.3868 0.0166 #> [14,] -0.1808 0.0229 #> [15,] 0.0484 0.0405 #> [16,] -0.0519 0.0164 #> [17,] 0.0623 -0.0047 #> [18,] -0.1444 -0.0286 #> #> $AN3 #> [,1] [,2] #> [1,] -0.4622 0.0159 #> [2,] 0.0089 0.0689 #> [3,] 0.2404 0.0545 #> [4,] 0.2501 0.0424 #> [5,] 0.2600 0.0230 #> [6,] 0.2541 0.0039 #> [7,] 0.2369 -0.0105 #> [8,] 0.1957 -0.0305 #> [9,] 0.1249 -0.0480 #> [10,] 0.0146 -0.0720 #> [11,] -0.0758 -0.0865 #> [12,] -0.4104 -0.0200 #> [13,] -0.3919 0.0190 #> [14,] -0.1724 0.0182 #> [15,] 0.0577 0.0344 #> [16,] -0.0468 0.0115 #> [17,] 0.0766 -0.0079 #> [18,] -0.1602 -0.0162 #> #> $AN4 #> [,1] [,2] #> [1,] -0.4534 -0.0028 #> [2,] -0.0318 0.0738 #> [3,] 0.2423 0.0808 #> [4,] 0.2627 0.0559 #> [5,] 0.2654 0.0322 #> [6,] 0.2579 0.0143 #> [7,] 0.2426 0.0018 #> [8,] 0.1851 -0.0313 #> [9,] 0.1191 -0.0581 #> [10,] 0.0203 -0.0847 #> [11,] -0.0919 -0.0957 #> [12,] -0.3862 -0.0289 #> [13,] -0.4051 -0.0072 #> [14,] -0.1536 0.0150 #> [15,] 0.0617 0.0436 #> [16,] -0.0549 0.0217 #> [17,] 0.0705 -0.0031 #> [18,] -0.1507 -0.0273 #> #> $AN5 #> [,1] [,2] #> [1,] -0.4926 -0.0212 #> [2,] -0.0260 0.0708 #> [3,] 0.2347 0.0679 #> [4,] 0.2398 0.0584 #> [5,] 0.2415 0.0355 #> [6,] 0.2337 0.0187 #> [7,] 0.2163 0.0010 #> [8,] 0.1920 -0.0171 #> [9,] 0.1271 -0.0443 #> [10,] 0.0427 -0.0699 #> [11,] -0.0516 -0.1016 #> [12,] -0.4242 -0.0505 #> [13,] -0.3970 -0.0018 #> [14,] -0.1374 0.0154 #> [15,] 0.0762 0.0457 #> [16,] -0.0313 0.0170 #> [17,] 0.0880 0.0037 #> [18,] -0.1318 -0.0278 #> #> $AN6 #> [,1] [,2] #> [1,] -0.4614 0.0567 #> [2,] -0.0091 0.0684 #> [3,] 0.2335 0.0345 #> [4,] 0.2499 0.0171 #> [5,] 0.2553 -0.0019 #> [6,] 0.2522 -0.0176 #> [7,] 0.2383 -0.0356 #> [8,] 0.2030 -0.0524 #> [9,] 0.1296 -0.0691 #> [10,] 0.0155 -0.0785 #> [11,] -0.0965 -0.0805 #> [12,] -0.4053 0.0196 #> [13,] -0.3907 0.0522 #> [14,] -0.1607 0.0403 #> [15,] 0.0703 0.0371 #> [16,] -0.0577 0.0258 #> [17,] 0.0801 -0.0118 #> [18,] -0.1463 -0.0042 #> #> $AN7 #> [,1] [,2] #> [1,] -0.4742 -0.0161 #> [2,] -0.0633 0.0656 #> [3,] 0.2206 0.0937 #> [4,] 0.2490 0.0720 #> [5,] 0.2576 0.0483 #> [6,] 0.2512 0.0232 #> [7,] 0.2388 0.0116 #> [8,] 0.1871 -0.0273 #> [9,] 0.1484 -0.0449 #> [10,] 0.0230 -0.0882 #> [11,] -0.0575 -0.1054 #> [12,] -0.3916 -0.0478 #> [13,] -0.3805 -0.0085 #> [14,] -0.1604 0.0119 #> [15,] 0.0647 0.0470 #> [16,] -0.0449 0.0135 #> [17,] 0.0903 -0.0072 #> [18,] -0.1585 -0.0414 #> #> $AN8 #> [,1] [,2] #> [1,] -0.4698 0.0224 #> [2,] 0.0525 0.0771 #> [3,] 0.2450 0.0501 #> [4,] 0.2603 0.0333 #> [5,] 0.2587 0.0166 #> [6,] 0.2552 0.0071 #> [7,] 0.2373 -0.0083 #> [8,] 0.1808 -0.0319 #> [9,] 0.1008 -0.0546 #> [10,] 0.0155 -0.0807 #> [11,] -0.0922 -0.0907 #> [12,] -0.4082 -0.0124 #> [13,] -0.3919 0.0228 #> [14,] -0.1604 0.0248 #> [15,] 0.0494 0.0383 #> [16,] -0.0575 0.0160 #> [17,] 0.0660 -0.0107 #> [18,] -0.1416 -0.0192 #> #> $AN9 #> [,1] [,2] #> [1,] -0.4652 -0.0110 #> [2,] -0.0017 0.0759 #> [3,] 0.2246 0.0759 #> [4,] 0.2405 0.0587 #> [5,] 0.2500 0.0443 #> [6,] 0.2509 0.0258 #> [7,] 0.2406 0.0057 #> [8,] 0.2009 -0.0214 #> [9,] 0.1389 -0.0475 #> [10,] 0.0284 -0.0790 #> [11,] -0.0450 -0.0979 #> [12,] -0.3999 -0.0458 #> [13,] -0.3968 -0.0077 #> [14,] -0.1886 0.0090 #> [15,] 0.0561 0.0424 #> [16,] -0.0683 0.0081 #> [17,] 0.0793 -0.0046 #> [18,] -0.1449 -0.0309 #> #> $AN10 #> [,1] [,2] #> [1,] -0.4496 0.0335 #> [2,] 0.0012 0.0701 #> [3,] 0.2502 0.0412 #> [4,] 0.2591 0.0249 #> [5,] 0.2598 0.0083 #> [6,] 0.2540 -0.0054 #> [7,] 0.2376 -0.0184 #> [8,] 0.1914 -0.0377 #> [9,] 0.1255 -0.0551 #> [10,] 0.0201 -0.0796 #> [11,] -0.0594 -0.0904 #> [12,] -0.4083 -0.0007 #> [13,] -0.3931 0.0279 #> [14,] -0.1805 0.0303 #> [15,] 0.0520 0.0405 #> [16,] -0.0622 0.0241 #> [17,] 0.0662 -0.0066 #> [18,] -0.1640 -0.0070 #> #> $AN11 #> [,1] [,2] #> [1,] -0.4586 0.0314 #> [2,] -0.0040 0.0707 #> [3,] 0.2412 0.0445 #> [4,] 0.2514 0.0284 #> [5,] 0.2543 0.0140 #> [6,] 0.2504 -0.0032 #> [7,] 0.2330 -0.0248 #> [8,] 0.1846 -0.0433 #> [9,] 0.1228 -0.0565 #> [10,] 0.0319 -0.0713 #> [11,] -0.0718 -0.0806 #> [12,] -0.4071 -0.0050 #> [13,] -0.3992 0.0249 #> [14,] -0.1819 0.0293 #> [15,] 0.0809 0.0402 #> [16,] -0.0575 0.0224 #> [17,] 0.0888 -0.0103 #> [18,] -0.1592 -0.0105 #> #> $TO12 #> [,1] [,2] #> [1,] -0.4577 0.0257 #> [2,] -0.0119 0.0557 #> [3,] 0.2215 0.0519 #> [4,] 0.2416 0.0411 #> [5,] 0.2510 0.0217 #> [6,] 0.2488 0.0035 #> [7,] 0.2333 -0.0147 #> [8,] 0.1951 -0.0385 #> [9,] 0.1154 -0.0580 #> [10,] 0.0081 -0.0710 #> [11,] -0.0986 -0.0839 #> [12,] -0.4056 0.0000 #> [13,] -0.3814 0.0248 #> [14,] -0.1579 0.0201 #> [15,] 0.1630 0.0365 #> [16,] -0.0686 0.0122 #> [17,] 0.0985 -0.0115 #> [18,] -0.1947 -0.0157 #> #> $WY13 #> [,1] [,2] #> [1,] -0.4704 0.0144 #> [2,] 0.0120 0.0897 #> [3,] 0.2333 0.0707 #> [4,] 0.2545 0.0505 #> [5,] 0.2624 0.0302 #> [6,] 0.2601 0.0070 #> [7,] 0.2429 -0.0154 #> [8,] 0.2026 -0.0363 #> [9,] 0.1108 -0.0668 #> [10,] 0.0149 -0.0885 #> [11,] -0.1081 -0.1035 #> [12,] -0.4161 -0.0288 #> [13,] -0.3559 0.0268 #> [14,] -0.1632 0.0253 #> [15,] 0.0432 0.0414 #> [16,] -0.0244 0.0162 #> [17,] 0.0478 -0.0092 #> [18,] -0.1462 -0.0237 #> #> $WY14 #> [,1] [,2] #> [1,] -0.4693 -0.0651 #> [2,] 0.0093 0.0766 #> [3,] 0.2223 0.0934 #> [4,] 0.2417 0.0771 #> [5,] 0.2472 0.0550 #> [6,] 0.2427 0.0420 #> [7,] 0.2263 0.0193 #> [8,] 0.1913 -0.0059 #> [9,] 0.1359 -0.0363 #> [10,] 0.0587 -0.0694 #> [11,] -0.0426 -0.0967 #> [12,] -0.4065 -0.0824 #> [13,] -0.4097 -0.0476 #> [14,] -0.1541 0.0086 #> [15,] 0.0189 0.0479 #> [16,] -0.0264 0.0211 #> [17,] 0.0566 0.0022 #> [18,] -0.1423 -0.0397 #> #> $WY15 #> [,1] [,2] #> [1,] -0.4673 0.0220 #> [2,] -0.0277 0.0745 #> [3,] 0.2456 0.0517 #> [4,] 0.2553 0.0369 #> [5,] 0.2618 0.0159 #> [6,] 0.2593 0.0014 #> [7,] 0.2409 -0.0152 #> [8,] 0.1932 -0.0402 #> [9,] 0.1261 -0.0584 #> [10,] 0.0266 -0.0732 #> [11,] -0.1079 -0.0788 #> [12,] -0.4005 -0.0119 #> [13,] -0.3871 0.0193 #> [14,] -0.1765 0.0251 #> [15,] 0.0456 0.0363 #> [16,] -0.0333 0.0174 #> [17,] 0.0724 -0.0072 #> [18,] -0.1266 -0.0156 #> #> $WY16 #> [,1] [,2] #> [1,] -0.4598 0.0418 #> [2,] 0.0208 0.0737 #> [3,] 0.2401 0.0484 #> [4,] 0.2577 0.0265 #> [5,] 0.2626 0.0063 #> [6,] 0.2574 -0.0081 #> [7,] 0.2337 -0.0255 #> [8,] 0.1831 -0.0458 #> [9,] 0.1230 -0.0605 #> [10,] 0.0175 -0.0749 #> [11,] -0.1034 -0.0821 #> [12,] -0.4151 0.0095 #> [13,] -0.4040 0.0348 #> [14,] -0.1433 0.0285 #> [15,] 0.0435 0.0364 #> [16,] -0.0406 0.0177 #> [17,] 0.0610 -0.0099 #> [18,] -0.1344 -0.0169 #> #> $UR17 #> [,1] [,2] #> [1,] -0.4690 0.0256 #> [2,] 0.0188 0.0844 #> [3,] 0.2381 0.0519 #> [4,] 0.2517 0.0352 #> [5,] 0.2540 0.0131 #> [6,] 0.2459 -0.0122 #> [7,] 0.2249 -0.0331 #> [8,] 0.1799 -0.0516 #> [9,] 0.1157 -0.0621 #> [10,] 0.0257 -0.0784 #> [11,] -0.1524 -0.0905 #> [12,] -0.4012 -0.0015 #> [13,] -0.3796 0.0340 #> [14,] -0.1482 0.0442 #> [15,] 0.1153 0.0437 #> [16,] -0.0745 0.0274 #> [17,] 0.0942 -0.0158 #> [18,] -0.1395 -0.0142 #> #> $UR18 #> [,1] [,2] #> [1,] -0.4999 0.0214 #> [2,] 0.0533 0.0868 #> [3,] 0.2081 0.0713 #> [4,] 0.2263 0.0548 #> [5,] 0.2358 0.0361 #> [6,] 0.2391 0.0128 #> [7,] 0.2206 -0.0235 #> [8,] 0.1792 -0.0512 #> [9,] 0.1168 -0.0693 #> [10,] 0.0343 -0.0924 #> [11,] -0.1419 -0.1106 #> [12,] -0.4192 -0.0064 #> [13,] -0.3695 0.0241 #> [14,] -0.1232 0.0410 #> [15,] 0.1380 0.0543 #> [16,] -0.0694 0.0134 #> [17,] 0.0825 -0.0252 #> [18,] -0.1111 -0.0373 #> #> $UR19 #> [,1] [,2] #> [1,] -0.4668 -0.0044 #> [2,] -0.0334 0.0689 #> [3,] 0.2229 0.0664 #> [4,] 0.2464 0.0514 #> [5,] 0.2598 0.0307 #> [6,] 0.2588 0.0141 #> [7,] 0.2389 -0.0053 #> [8,] 0.1792 -0.0283 #> [9,] 0.1107 -0.0468 #> [10,] 0.0349 -0.0718 #> [11,] -0.1502 -0.0893 #> [12,] -0.3964 -0.0316 #> [13,] -0.3764 0.0077 #> [14,] -0.1537 0.0238 #> [15,] 0.1411 0.0493 #> [16,] -0.0807 0.0116 #> [17,] 0.0985 -0.0159 #> [18,] -0.1336 -0.0306 #> #> $UR20 #> [,1] [,2] #> [1,] -0.4873 0.0122 #> [2,] -0.0175 0.0784 #> [3,] 0.2357 0.0725 #> [4,] 0.2514 0.0514 #> [5,] 0.2567 0.0255 #> [6,] 0.2527 0.0058 #> [7,] 0.2371 -0.0142 #> [8,] 0.1959 -0.0388 #> [9,] 0.1245 -0.0612 #> [10,] 0.0397 -0.0783 #> [11,] -0.1466 -0.1012 #> [12,] -0.4242 -0.0296 #> [13,] -0.3325 0.0165 #> [14,] -0.1271 0.0308 #> [15,] 0.0840 0.0459 #> [16,] -0.0807 0.0177 #> [17,] 0.0600 -0.0103 #> [18,] -0.1219 -0.0230 #> #> $CA21 #> [,1] [,2] #> [1,] -0.4829 0.0300 #> [2,] 0.0117 0.0938 #> [3,] 0.2398 0.0578 #> [4,] 0.2544 0.0325 #> [5,] 0.2518 0.0092 #> [6,] 0.2446 -0.0074 #> [7,] 0.2271 -0.0243 #> [8,] 0.1758 -0.0524 #> [9,] 0.1062 -0.0728 #> [10,] 0.0065 -0.0876 #> [11,] -0.0936 -0.0955 #> [12,] -0.4021 0.0090 #> [13,] -0.3899 0.0343 #> [14,] -0.1648 0.0403 #> [15,] 0.0951 0.0433 #> [16,] -0.0210 0.0206 #> [17,] 0.0735 -0.0094 #> [18,] -0.1321 -0.0214 #> #> $CA22 #> [,1] [,2] #> [1,] -0.4683 0.0225 #> [2,] 0.0446 0.0866 #> [3,] 0.2237 0.0673 #> [4,] 0.2486 0.0447 #> [5,] 0.2543 0.0291 #> [6,] 0.2566 0.0081 #> [7,] 0.2350 -0.0205 #> [8,] 0.1694 -0.0470 #> [9,] 0.1025 -0.0648 #> [10,] 0.0227 -0.0858 #> [11,] -0.0900 -0.0984 #> [12,] -0.4127 -0.0165 #> [13,] -0.3935 0.0185 #> [14,] -0.1948 0.0288 #> [15,] 0.0637 0.0464 #> [16,] -0.0261 0.0189 #> [17,] 0.0842 -0.0124 #> [18,] -0.1198 -0.0254 #> #> $CA23 #> [,1] [,2] #> [1,] -0.4625 0.0195 #> [2,] 0.0534 0.0874 #> [3,] 0.2472 0.0558 #> [4,] 0.2595 0.0425 #> [5,] 0.2608 0.0208 #> [6,] 0.2517 0.0033 #> [7,] 0.2317 -0.0116 #> [8,] 0.1701 -0.0391 #> [9,] 0.1081 -0.0590 #> [10,] 0.0151 -0.0825 #> [11,] -0.0976 -0.0988 #> [12,] -0.4123 -0.0236 #> [13,] -0.3980 0.0148 #> [14,] -0.1728 0.0274 #> [15,] 0.0480 0.0493 #> [16,] -0.0277 0.0244 #> [17,] 0.0489 -0.0032 #> [18,] -0.1236 -0.0275 #> #> $CA24 #> [,1] [,2] #> [1,] -0.4473 0.0502 #> [2,] -0.0237 0.0884 #> [3,] 0.2454 0.0522 #> [4,] 0.2706 0.0277 #> [5,] 0.2719 0.0059 #> [6,] 0.2623 -0.0133 #> [7,] 0.2396 -0.0313 #> [8,] 0.1828 -0.0538 #> [9,] 0.1047 -0.0703 #> [10,] 0.0191 -0.0914 #> [11,] -0.0813 -0.1033 #> [12,] -0.3940 0.0049 #> [13,] -0.3814 0.0464 #> [14,] -0.2018 0.0488 #> [15,] 0.0482 0.0441 #> [16,] -0.0358 0.0232 #> [17,] 0.0524 -0.0112 #> [18,] -0.1317 -0.0173 #> #> $CA25 #> [,1] [,2] #> [1,] -0.4681 0.0445 #> [2,] 0.0566 0.0841 #> [3,] 0.2515 0.0503 #> [4,] 0.2635 0.0318 #> [5,] 0.2617 0.0109 #> [6,] 0.2493 -0.0113 #> [7,] 0.2229 -0.0326 #> [8,] 0.1654 -0.0584 #> [9,] 0.1050 -0.0713 #> [10,] 0.0084 -0.0877 #> [11,] -0.1085 -0.0962 #> [12,] -0.4064 0.0035 #> [13,] -0.3850 0.0391 #> [14,] -0.1688 0.0396 #> [15,] 0.0717 0.0458 #> [16,] -0.0227 0.0245 #> [17,] 0.0439 -0.0054 #> [18,] -0.1404 -0.0113 #> #> $CA26 #> [,1] [,2] #> [1,] -0.4654 0.0045 #> [2,] -0.0237 0.0591 #> [3,] 0.2298 0.0652 #> [4,] 0.2506 0.0472 #> [5,] 0.2565 0.0359 #> [6,] 0.2547 0.0191 #> [7,] 0.2406 0.0016 #> [8,] 0.1958 -0.0240 #> [9,] 0.1348 -0.0499 #> [10,] 0.0377 -0.0837 #> [11,] -0.0598 -0.1028 #> [12,] -0.4078 -0.0288 #> [13,] -0.3939 0.0037 #> [14,] -0.1667 0.0187 #> [15,] 0.0639 0.0422 #> [16,] -0.0479 0.0175 #> [17,] 0.0514 0.0013 #> [18,] -0.1504 -0.0267 #> #> $CA27 #> [,1] [,2] #> [1,] -0.4544 0.0221 #> [2,] -0.0074 0.0855 #> [3,] 0.2360 0.0679 #> [4,] 0.2578 0.0500 #> [5,] 0.2686 0.0258 #> [6,] 0.2677 0.0018 #> [7,] 0.2525 -0.0206 #> [8,] 0.2016 -0.0483 #> [9,] 0.1010 -0.0702 #> [10,] 0.0270 -0.0886 #> [11,] -0.0571 -0.0967 #> [12,] -0.3962 -0.0166 #> [13,] -0.3685 0.0227 #> [14,] -0.1830 0.0288 #> [15,] 0.0186 0.0402 #> [16,] -0.0344 0.0185 #> [17,] 0.0542 -0.0106 #> [18,] -0.1840 -0.0120 #> #> $OR28 #> [,1] [,2] #> [1,] -0.4653 -0.0153 #> [2,] -0.0530 0.0713 #> [3,] 0.1996 0.0886 #> [4,] 0.2548 0.0643 #> [5,] 0.2654 0.0462 #> [6,] 0.2632 0.0168 #> [7,] 0.2399 -0.0084 #> [8,] 0.1881 -0.0358 #> [9,] 0.1297 -0.0542 #> [10,] 0.0436 -0.0796 #> [11,] -0.0329 -0.0978 #> [12,] -0.4176 -0.0393 #> [13,] -0.3934 -0.0092 #> [14,] -0.1727 0.0196 #> [15,] 0.0655 0.0490 #> [16,] -0.0419 0.0247 #> [17,] 0.0323 -0.0041 #> [18,] -0.1054 -0.0366 #> #> $MA29 #> [,1] [,2] #> [1,] -0.4624 0.0319 #> [2,] 0.0361 0.0848 #> [3,] 0.2647 0.0476 #> [4,] 0.2711 0.0332 #> [5,] 0.2686 0.0142 #> [6,] 0.2536 -0.0028 #> [7,] 0.2181 -0.0254 #> [8,] 0.1662 -0.0468 #> [9,] 0.1179 -0.0599 #> [10,] 0.0245 -0.0808 #> [11,] -0.0732 -0.0968 #> [12,] -0.3969 -0.0034 #> [13,] -0.3870 0.0305 #> [14,] -0.1745 0.0310 #> [15,] 0.0578 0.0444 #> [16,] -0.0471 0.0241 #> [17,] 0.0261 -0.0030 #> [18,] -0.1635 -0.0226 #> #> $MA30 #> [,1] [,2] #> [1,] -0.4740 0.0220 #> [2,] 0.0024 0.0831 #> [3,] 0.2327 0.0713 #> [4,] 0.2492 0.0529 #> [5,] 0.2556 0.0308 #> [6,] 0.2491 0.0089 #> [7,] 0.2318 -0.0089 #> [8,] 0.1827 -0.0386 #> [9,] 0.1087 -0.0608 #> [10,] 0.0389 -0.0882 #> [11,] -0.0529 -0.1136 #> [12,] -0.4112 -0.0271 #> [13,] -0.3980 0.0168 #> [14,] -0.1748 0.0275 #> [15,] 0.0599 0.0415 #> [16,] -0.0157 0.0171 #> [17,] 0.0480 -0.0105 #> [18,] -0.1324 -0.0244 #> #> $MA31 #> [,1] [,2] #> [1,] -0.4831 -0.0136 #> [2,] 0.0024 0.0861 #> [3,] 0.2431 0.0843 #> [4,] 0.2554 0.0625 #> [5,] 0.2540 0.0326 #> [6,] 0.2405 0.0126 #> [7,] 0.2165 -0.0073 #> [8,] 0.1757 -0.0319 #> [9,] 0.1188 -0.0525 #> [10,] 0.0420 -0.0831 #> [11,] -0.0576 -0.1092 #> [12,] -0.4031 -0.0419 #> [13,] -0.3856 -0.0059 #> [14,] -0.1916 0.0145 #> [15,] 0.0674 0.0531 #> [16,] -0.0285 0.0259 #> [17,] 0.0642 -0.0014 #> [18,] -0.1304 -0.0246 #> #> $PS32 #> [,1] [,2] #> [1,] -0.4955 0.0422 #> [2,] 0.0429 0.0871 #> [3,] 0.2268 0.0616 #> [4,] 0.2411 0.0429 #> [5,] 0.2455 0.0159 #> [6,] 0.2386 -0.0002 #> [7,] 0.2212 -0.0235 #> [8,] 0.1736 -0.0527 #> [9,] 0.1042 -0.0675 #> [10,] 0.0273 -0.0890 #> [11,] -0.0741 -0.1126 #> [12,] -0.4098 0.0008 #> [13,] -0.4000 0.0326 #> [14,] -0.1689 0.0341 #> [15,] 0.0781 0.0438 #> [16,] -0.0248 0.0224 #> [17,] 0.0790 -0.0106 #> [18,] -0.1054 -0.0273 #> #> $PS33 #> [,1] [,2] #> [1,] -0.4870 -0.0111 #> [2,] 0.0401 0.0939 #> [3,] 0.2165 0.0943 #> [4,] 0.2332 0.0825 #> [5,] 0.2471 0.0502 #> [6,] 0.2408 0.0188 #> [7,] 0.2241 -0.0047 #> [8,] 0.1764 -0.0367 #> [9,] 0.1146 -0.0632 #> [10,] 0.0050 -0.0961 #> [11,] -0.0748 -0.1175 #> [12,] -0.4034 -0.0539 #> [13,] -0.4011 -0.0029 #> [14,] -0.1615 0.0180 #> [15,] 0.0824 0.0556 #> [16,] -0.0144 0.0217 #> [17,] 0.0784 -0.0062 #> [18,] -0.1164 -0.0428 #> #> $PS34 #> [,1] [,2] #> [1,] -0.4862 0.0842 #> [2,] 0.0260 0.0865 #> [3,] 0.2370 0.0326 #> [4,] 0.2426 0.0203 #> [5,] 0.2407 0.0011 #> [6,] 0.2355 -0.0171 #> [7,] 0.2093 -0.0424 #> [8,] 0.1746 -0.0611 #> [9,] 0.1018 -0.0804 #> [10,] 0.0167 -0.0920 #> [11,] -0.0894 -0.1024 #> [12,] -0.4233 0.0207 #> [13,] -0.3944 0.0698 #> [14,] -0.1543 0.0526 #> [15,] 0.0847 0.0385 #> [16,] 0.0040 0.0209 #> [17,] 0.0815 -0.0175 #> [18,] -0.1069 -0.0145 #> #> $PS35 #> [,1] [,2] #> [1,] -0.4698 0.0229 #> [2,] 0.0008 0.0769 #> [3,] 0.2413 0.0565 #> [4,] 0.2534 0.0372 #> [5,] 0.2562 0.0211 #> [6,] 0.2530 0.0045 #> [7,] 0.2392 -0.0150 #> [8,] 0.1969 -0.0380 #> [9,] 0.1006 -0.0591 #> [10,] 0.0087 -0.0818 #> [11,] -0.0851 -0.0980 #> [12,] -0.4069 -0.0163 #> [13,] -0.3909 0.0199 #> [14,] -0.1716 0.0275 #> [15,] 0.0642 0.0463 #> [16,] -0.0269 0.0213 #> [17,] 0.0729 -0.0090 #> [18,] -0.1360 -0.0167 #> #> $PS36 #> [,1] [,2] #> [1,] -0.4781 0.0434 #> [2,] 0.0151 0.0861 #> [3,] 0.2315 0.0588 #> [4,] 0.2497 0.0340 #> [5,] 0.2522 0.0097 #> [6,] 0.2468 -0.0098 #> [7,] 0.2262 -0.0268 #> [8,] 0.1710 -0.0504 #> [9,] 0.1161 -0.0662 #> [10,] 0.0229 -0.0872 #> [11,] -0.0725 -0.0919 #> [12,] -0.4162 -0.0013 #> [13,] -0.3934 0.0423 #> [14,] -0.1805 0.0383 #> [15,] 0.0727 0.0398 #> [16,] -0.0165 0.0185 #> [17,] 0.0770 -0.0152 #> [18,] -0.1238 -0.0220 #> #> $PS37 #> [,1] [,2] #> [1,] -0.4831 0.0333 #> [2,] 0.0053 0.0903 #> [3,] 0.2195 0.0586 #> [4,] 0.2431 0.0411 #> [5,] 0.2528 0.0130 #> [6,] 0.2449 -0.0048 #> [7,] 0.2233 -0.0224 #> [8,] 0.1825 -0.0408 #> [9,] 0.1059 -0.0670 #> [10,] 0.0350 -0.0854 #> [11,] -0.0632 -0.1019 #> [12,] -0.4102 -0.0103 #> [13,] -0.4019 0.0322 #> [14,] -0.1665 0.0331 #> [15,] 0.0750 0.0390 #> [16,] -0.0117 0.0188 #> [17,] 0.0926 -0.0086 #> [18,] -0.1432 -0.0182 #> #> $PS38 #> [,1] [,2] #> [1,] -0.4868 0.0376 #> [2,] 0.0145 0.0744 #> [3,] 0.2315 0.0576 #> [4,] 0.2463 0.0390 #> [5,] 0.2527 0.0143 #> [6,] 0.2466 0.0000 #> [7,] 0.2285 -0.0178 #> [8,] 0.1868 -0.0382 #> [9,] 0.1200 -0.0602 #> [10,] 0.0140 -0.0828 #> [11,] -0.0960 -0.0979 #> [12,] -0.4053 -0.0083 #> [13,] -0.3932 0.0282 #> [14,] -0.1530 0.0252 #> [15,] 0.0769 0.0365 #> [16,] -0.0236 0.0192 #> [17,] 0.0819 -0.0094 #> [18,] -0.1417 -0.0175 #> #> $PS39 #> [,1] [,2] #> [1,] -0.4681 0.0267 #> [2,] 0.0193 0.0801 #> [3,] 0.2274 0.0661 #> [4,] 0.2402 0.0517 #> [5,] 0.2490 0.0300 #> [6,] 0.2487 0.0093 #> [7,] 0.2388 -0.0078 #> [8,] 0.1901 -0.0408 #> [9,] 0.1154 -0.0649 #> [10,] 0.0358 -0.0930 #> [11,] -0.0922 -0.1143 #> [12,] -0.4119 -0.0207 #> [13,] -0.3901 0.0205 #> [14,] -0.1749 0.0280 #> [15,] 0.0685 0.0439 #> [16,] -0.0261 0.0209 #> [17,] 0.0726 -0.0088 #> [18,] -0.1425 -0.0269 #> #> $PS40 #> [,1] [,2] #> [1,] -0.4708 0.0327 #> [2,] 0.0546 0.0803 #> [3,] 0.2318 0.0604 #> [4,] 0.2454 0.0473 #> [5,] 0.2528 0.0247 #> [6,] 0.2488 0.0056 #> [7,] 0.2253 -0.0160 #> [8,] 0.1810 -0.0400 #> [9,] 0.1072 -0.0659 #> [10,] 0.0325 -0.0918 #> [11,] -0.0733 -0.1075 #> [12,] -0.4125 -0.0175 #> [13,] -0.3964 0.0257 #> [14,] -0.1769 0.0264 #> [15,] 0.0782 0.0456 #> [16,] -0.0320 0.0199 #> [17,] 0.0493 -0.0081 #> [18,] -0.1450 -0.0218 #> #> $PS41 #> [,1] [,2] #> [1,] -0.4681 0.0007 #> [2,] -0.0003 0.0884 #> [3,] 0.2120 0.0925 #> [4,] 0.2365 0.0755 #> [5,] 0.2530 0.0482 #> [6,] 0.2547 0.0290 #> [7,] 0.2428 0.0031 #> [8,] 0.2044 -0.0260 #> [9,] 0.1192 -0.0625 #> [10,] 0.0515 -0.0936 #> [11,] -0.0682 -0.1217 #> [12,] -0.3970 -0.0443 #> [13,] -0.3857 0.0009 #> [14,] -0.1914 0.0123 #> [15,] 0.0543 0.0404 #> [16,] -0.0266 0.0088 #> [17,] 0.0521 -0.0126 #> [18,] -0.1431 -0.0391 #> #> $PS42 #> [,1] [,2] #> [1,] -0.4716 0.0113 #> [2,] -0.0361 0.0801 #> [3,] 0.2011 0.0886 #> [4,] 0.2403 0.0590 #> [5,] 0.2478 0.0350 #> [6,] 0.2418 0.0160 #> [7,] 0.2306 -0.0017 #> [8,] 0.1874 -0.0304 #> [9,] 0.1155 -0.0642 #> [10,] 0.0496 -0.0922 #> [11,] -0.0430 -0.1309 #> [12,] -0.4147 -0.0391 #> [13,] -0.3963 0.0063 #> [14,] -0.1871 0.0211 #> [15,] 0.0941 0.0519 #> [16,] -0.0092 0.0184 #> [17,] 0.0798 0.0003 #> [18,] -0.1300 -0.0296 #> #> $PS43 #> [,1] [,2] #> [1,] -0.4650 0.0189 #> [2,] 0.0777 0.0958 #> [3,] 0.2329 0.0615 #> [4,] 0.2406 0.0500 #> [5,] 0.2516 0.0248 #> [6,] 0.2474 0.0028 #> [7,] 0.2232 -0.0239 #> [8,] 0.1751 -0.0467 #> [9,] 0.0905 -0.0670 #> [10,] 0.0085 -0.0866 #> [11,] -0.0910 -0.1106 #> [12,] -0.4048 -0.0239 #> [13,] -0.3877 0.0175 #> [14,] -0.2037 0.0338 #> [15,] 0.0961 0.0522 #> [16,] -0.0197 0.0285 #> [17,] 0.0797 -0.0070 #> [18,] -0.1514 -0.0198 #> #> $AE44 #> [,1] [,2] #> [1,] -0.4725 0.0516 #> [2,] -0.0143 0.0813 #> [3,] 0.2422 0.0488 #> [4,] 0.2507 0.0382 #> [5,] 0.2559 0.0186 #> [6,] 0.2537 -0.0002 #> [7,] 0.2367 -0.0236 #> [8,] 0.1749 -0.0518 #> [9,] 0.1033 -0.0718 #> [10,] 0.0238 -0.0987 #> [11,] -0.0727 -0.1095 #> [12,] -0.4000 0.0036 #> [13,] -0.3912 0.0449 #> [14,] -0.1666 0.0384 #> [15,] 0.0829 0.0420 #> [16,] -0.0183 0.0225 #> [17,] 0.0560 -0.0095 #> [18,] -0.1445 -0.0249 #> #> $AE45 #> [,1] [,2] #> [1,] -0.4700 0.0329 #> [2,] 0.0211 0.0740 #> [3,] 0.2225 0.0573 #> [4,] 0.2380 0.0445 #> [5,] 0.2463 0.0264 #> [6,] 0.2464 0.0056 #> [7,] 0.2289 -0.0202 #> [8,] 0.1914 -0.0426 #> [9,] 0.1183 -0.0646 #> [10,] 0.0281 -0.0876 #> [11,] -0.0840 -0.0974 #> [12,] -0.4163 -0.0049 #> [13,] -0.4033 0.0281 #> [14,] -0.1798 0.0299 #> [15,] 0.0811 0.0398 #> [16,] -0.0269 0.0163 #> [17,] 0.0871 -0.0149 #> [18,] -0.1289 -0.0229 #> #> $AE46 #> [,1] [,2] #> [1,] -0.4763 0.0541 #> [2,] 0.0198 0.0823 #> [3,] 0.2385 0.0565 #> [4,] 0.2495 0.0309 #> [5,] 0.2487 0.0119 #> [6,] 0.2414 -0.0050 #> [7,] 0.2247 -0.0242 #> [8,] 0.1859 -0.0439 #> [9,] 0.1116 -0.0648 #> [10,] 0.0350 -0.0872 #> [11,] -0.0774 -0.1079 #> [12,] -0.4132 -0.0092 #> [13,] -0.3855 0.0404 #> [14,] -0.1809 0.0317 #> [15,] 0.0706 0.0405 #> [16,] -0.0278 0.0176 #> [17,] 0.0771 -0.0100 #> [18,] -0.1416 -0.0136 #> #> $AE47 #> [,1] [,2] #> [1,] -0.4650 0.0251 #> [2,] 0.0340 0.0867 #> [3,] 0.2201 0.0688 #> [4,] 0.2449 0.0413 #> [5,] 0.2502 0.0272 #> [6,] 0.2497 0.0056 #> [7,] 0.2334 -0.0178 #> [8,] 0.2017 -0.0396 #> [9,] 0.1236 -0.0666 #> [10,] 0.0180 -0.0880 #> [11,] -0.1076 -0.1018 #> [12,] -0.4067 -0.0178 #> [13,] -0.3950 0.0173 #> [14,] -0.1924 0.0277 #> [15,] 0.0536 0.0477 #> [16,] -0.0110 0.0214 #> [17,] 0.0727 -0.0081 #> [18,] -0.1240 -0.0291 #> #> $AE48 #> [,1] [,2] #> [1,] -0.4816 -0.0101 #> [2,] -0.0088 0.0787 #> [3,] 0.2519 0.0669 #> [4,] 0.2576 0.0565 #> [5,] 0.2584 0.0363 #> [6,] 0.2483 0.0188 #> [7,] 0.2217 -0.0046 #> [8,] 0.1745 -0.0324 #> [9,] 0.1081 -0.0580 #> [10,] 0.0173 -0.0796 #> [11,] -0.1134 -0.0967 #> [12,] -0.3990 -0.0323 #> [13,] -0.3859 -0.0026 #> [14,] -0.1730 0.0227 #> [15,] 0.0797 0.0444 #> [16,] -0.0026 0.0194 #> [17,] 0.0714 -0.0012 #> [18,] -0.1245 -0.0260 #> #> $AE49 #> [,1] [,2] #> [1,] -0.4629 0.0336 #> [2,] 0.0171 0.0795 #> [3,] 0.2194 0.0704 #> [4,] 0.2486 0.0437 #> [5,] 0.2537 0.0236 #> [6,] 0.2519 0.0026 #> [7,] 0.2329 -0.0160 #> [8,] 0.2020 -0.0353 #> [9,] 0.1282 -0.0616 #> [10,] 0.0354 -0.0929 #> [11,] -0.0687 -0.1047 #> [12,] -0.4003 -0.0198 #> [13,] -0.3796 0.0241 #> [14,] -0.2303 0.0291 #> [15,] 0.0574 0.0373 #> [16,] -0.0315 0.0182 #> [17,] 0.0682 -0.0090 #> [18,] -0.1416 -0.0229 #> #> $AE50 #> [,1] [,2] #> [1,] -0.4796 0.0445 #> [2,] 0.0328 0.0897 #> [3,] 0.2322 0.0526 #> [4,] 0.2452 0.0328 #> [5,] 0.2481 0.0158 #> [6,] 0.2460 -0.0086 #> [7,] 0.2302 -0.0294 #> [8,] 0.1887 -0.0480 #> [9,] 0.0998 -0.0674 #> [10,] 0.0049 -0.0882 #> [11,] -0.0920 -0.0998 #> [12,] -0.4136 -0.0102 #> [13,] -0.3879 0.0401 #> [14,] -0.1660 0.0347 #> [15,] 0.0839 0.0398 #> [16,] -0.0172 0.0234 #> [17,] 0.0791 -0.0039 #> [18,] -0.1344 -0.0181 #> #> $AE51 #> [,1] [,2] #> [1,] -0.4677 0.0660 #> [2,] -0.0018 0.1009 #> [3,] 0.2411 0.0573 #> [4,] 0.2545 0.0301 #> [5,] 0.2548 0.0037 #> [6,] 0.2473 -0.0135 #> [7,] 0.2332 -0.0313 #> [8,] 0.1707 -0.0620 #> [9,] 0.1136 -0.0767 #> [10,] 0.0222 -0.1042 #> [11,] -0.0559 -0.1135 #> [12,] -0.3919 0.0170 #> [13,] -0.3774 0.0620 #> [14,] -0.2083 0.0434 #> [15,] 0.0839 0.0383 #> [16,] -0.0297 0.0210 #> [17,] 0.0527 -0.0203 #> [18,] -0.1415 -0.0183 #> #> $AE52 #> [,1] [,2] #> [1,] -0.4727 0.0471 #> [2,] 0.0132 0.0814 #> [3,] 0.2200 0.0560 #> [4,] 0.2417 0.0392 #> [5,] 0.2517 0.0124 #> [6,] 0.2487 -0.0071 #> [7,] 0.2247 -0.0342 #> [8,] 0.1889 -0.0556 #> [9,] 0.1234 -0.0757 #> [10,] 0.0366 -0.0924 #> [11,] -0.0722 -0.1071 #> [12,] -0.4056 0.0170 #> [13,] -0.3994 0.0442 #> [14,] -0.1945 0.0406 #> [15,] 0.0769 0.0411 #> [16,] -0.0155 0.0201 #> [17,] 0.0568 -0.0137 #> [18,] -0.1228 -0.0132 #> #> $AE53 #> [,1] [,2] #> [1,] -0.4807 0.0159 #> [2,] -0.0202 0.0827 #> [3,] 0.2179 0.0740 #> [4,] 0.2367 0.0518 #> [5,] 0.2462 0.0284 #> [6,] 0.2410 0.0037 #> [7,] 0.2272 -0.0130 #> [8,] 0.1851 -0.0385 #> [9,] 0.1207 -0.0622 #> [10,] 0.0321 -0.0902 #> [11,] -0.0706 -0.1060 #> [12,] -0.4145 -0.0256 #> [13,] -0.3957 0.0149 #> [14,] -0.1793 0.0264 #> [15,] 0.0928 0.0493 #> [16,] -0.0085 0.0226 #> [17,] 0.0943 -0.0077 #> [18,] -0.1245 -0.0265 #> #> $AE54 #> [,1] [,2] #> [1,] -0.4692 0.0562 #> [2,] 0.0113 0.0832 #> [3,] 0.2364 0.0432 #> [4,] 0.2471 0.0269 #> [5,] 0.2512 0.0092 #> [6,] 0.2441 -0.0114 #> [7,] 0.2197 -0.0333 #> [8,] 0.1746 -0.0524 #> [9,] 0.1010 -0.0710 #> [10,] 0.0188 -0.0892 #> [11,] -0.0895 -0.1013 #> [12,] -0.4180 0.0126 #> [13,] -0.3956 0.0506 #> [14,] -0.1724 0.0422 #> [15,] 0.1044 0.0406 #> [16,] -0.0057 0.0242 #> [17,] 0.0756 -0.0119 #> [18,] -0.1337 -0.0188 #> #> $AE55 #> [,1] [,2] #> [1,] -0.4647 0.0148 #> [2,] 0.0328 0.0689 #> [3,] 0.2379 0.0568 #> [4,] 0.2523 0.0430 #> [5,] 0.2595 0.0223 #> [6,] 0.2578 0.0052 #> [7,] 0.2412 -0.0121 #> [8,] 0.2027 -0.0352 #> [9,] 0.1038 -0.0530 #> [10,] 0.0136 -0.0693 #> [11,] -0.1152 -0.0897 #> [12,] -0.3986 -0.0184 #> [13,] -0.3831 0.0119 #> [14,] -0.1813 0.0216 #> [15,] 0.0656 0.0390 #> [16,] -0.0403 0.0181 #> [17,] 0.0736 -0.0065 #> [18,] -0.1577 -0.0176 #> #> $AE56 #> [,1] [,2] #> [1,] -0.4643 0.0376 #> [2,] -0.0249 0.0706 #> [3,] 0.2336 0.0638 #> [4,] 0.2522 0.0424 #> [5,] 0.2586 0.0186 #> [6,] 0.2564 -0.0016 #> [7,] 0.2379 -0.0220 #> [8,] 0.1841 -0.0415 #> [9,] 0.1089 -0.0615 #> [10,] 0.0300 -0.0845 #> [11,] -0.0898 -0.0983 #> [12,] -0.4106 -0.0060 #> [13,] -0.3895 0.0278 #> [14,] -0.1702 0.0248 #> [15,] 0.0759 0.0394 #> [16,] -0.0150 0.0170 #> [17,] 0.0744 -0.0099 #> [18,] -0.1477 -0.0166 #> #> $AE57 #> [,1] [,2] #> [1,] -0.4828 0.0392 #> [2,] -0.0177 0.0874 #> [3,] 0.2484 0.0501 #> [4,] 0.2576 0.0349 #> [5,] 0.2591 0.0166 #> [6,] 0.2516 -0.0050 #> [7,] 0.2218 -0.0278 #> [8,] 0.1684 -0.0531 #> [9,] 0.1035 -0.0670 #> [10,] 0.0279 -0.0888 #> [11,] -0.0751 -0.1052 #> [12,] -0.3931 -0.0032 #> [13,] -0.3969 0.0420 #> [14,] -0.1688 0.0401 #> [15,] 0.0818 0.0463 #> [16,] -0.0094 0.0226 #> [17,] 0.0521 -0.0059 #> [18,] -0.1285 -0.0232 #> #> $AE58 #> [,1] [,2] #> [1,] -0.4712 0.0489 #> [2,] 0.0625 0.0804 #> [3,] 0.2222 0.0592 #> [4,] 0.2441 0.0367 #> [5,] 0.2491 0.0157 #> [6,] 0.2467 -0.0018 #> [7,] 0.2327 -0.0224 #> [8,] 0.1965 -0.0425 #> [9,] 0.1163 -0.0686 #> [10,] 0.0347 -0.0930 #> [11,] -0.0869 -0.1097 #> [12,] -0.4093 0.0021 #> [13,] -0.3883 0.0349 #> [14,] -0.1725 0.0325 #> [15,] 0.0504 0.0387 #> [16,] -0.0392 0.0198 #> [17,] 0.0675 -0.0162 #> [18,] -0.1555 -0.0148 #> #> $AE59 #> [,1] [,2] #> [1,] -0.4829 -0.0110 #> [2,] -0.0098 0.0702 #> [3,] 0.2305 0.0864 #> [4,] 0.2584 0.0618 #> [5,] 0.2570 0.0425 #> [6,] 0.2426 0.0193 #> [7,] 0.2192 0.0022 #> [8,] 0.1676 -0.0241 #> [9,] 0.1095 -0.0453 #> [10,] 0.0244 -0.0772 #> [11,] -0.0597 -0.0994 #> [12,] -0.4056 -0.0417 #> [13,] -0.4000 -0.0105 #> [14,] -0.1811 0.0104 #> [15,] 0.0829 0.0435 #> [16,] -0.0125 0.0117 #> [17,] 0.0856 -0.0066 #> [18,] -0.1262 -0.0320 #> #> $AE60 #> [,1] [,2] #> [1,] -0.4763 0.0391 #> [2,] 0.0399 0.0951 #> [3,] 0.2294 0.0748 #> [4,] 0.2498 0.0509 #> [5,] 0.2521 0.0178 #> [6,] 0.2452 -0.0041 #> [7,] 0.2200 -0.0252 #> [8,] 0.1877 -0.0446 #> [9,] 0.1021 -0.0731 #> [10,] 0.0172 -0.1043 #> [11,] -0.1109 -0.1183 #> [12,] -0.3956 -0.0066 #> [13,] -0.3835 0.0327 #> [14,] -0.1856 0.0394 #> [15,] 0.0696 0.0482 #> [16,] -0.0140 0.0210 #> [17,] 0.0847 -0.0112 #> [18,] -0.1318 -0.0316 #> #> $AE61 #> [,1] [,2] #> [1,] -0.4617 0.0257 #> [2,] -0.0363 0.0805 #> [3,] 0.2449 0.0659 #> [4,] 0.2606 0.0389 #> [5,] 0.2588 0.0255 #> [6,] 0.2505 0.0054 #> [7,] 0.2316 -0.0157 #> [8,] 0.1783 -0.0465 #> [9,] 0.1121 -0.0690 #> [10,] 0.0320 -0.0931 #> [11,] -0.0929 -0.1131 #> [12,] -0.4029 -0.0125 #> [13,] -0.3868 0.0196 #> [14,] -0.1833 0.0295 #> [15,] 0.0735 0.0539 #> [16,] -0.0217 0.0250 #> [17,] 0.0709 -0.0047 #> [18,] -0.1278 -0.0153 #> #> $AE62 #> [,1] [,2] #> [1,] -0.4899 -0.0062 #> [2,] 0.0120 0.0676 #> [3,] 0.2322 0.0679 #> [4,] 0.2437 0.0543 #> [5,] 0.2506 0.0304 #> [6,] 0.2433 0.0098 #> [7,] 0.2302 -0.0042 #> [8,] 0.1901 -0.0281 #> [9,] 0.1227 -0.0547 #> [10,] 0.0281 -0.0743 #> [11,] -0.0746 -0.0870 #> [12,] -0.4098 -0.0256 #> [13,] -0.3979 -0.0004 #> [14,] -0.1563 0.0184 #> [15,] 0.0717 0.0423 #> [16,] -0.0308 0.0153 #> [17,] 0.0716 -0.0061 #> [18,] -0.1369 -0.0194 #> #> $AE63 #> [,1] [,2] #> [1,] -0.4755 0.0458 #> [2,] 0.0115 0.0887 #> [3,] 0.2387 0.0626 #> [4,] 0.2580 0.0351 #> [5,] 0.2607 0.0113 #> [6,] 0.2531 -0.0061 #> [7,] 0.2338 -0.0283 #> [8,] 0.1817 -0.0528 #> [9,] 0.0846 -0.0718 #> [10,] 0.0053 -0.0886 #> [11,] -0.0847 -0.0995 #> [12,] -0.3990 -0.0003 #> [13,] -0.3796 0.0437 #> [14,] -0.1870 0.0389 #> [15,] 0.0760 0.0427 #> [16,] -0.0087 0.0158 #> [17,] 0.0698 -0.0190 #> [18,] -0.1387 -0.0180 #> #> $AE64 #> [,1] [,2] #> [1,] -0.4869 0.0242 #> [2,] -0.0225 0.0761 #> [3,] 0.2350 0.0677 #> [4,] 0.2443 0.0560 #> [5,] 0.2491 0.0389 #> [6,] 0.2493 0.0173 #> [7,] 0.2331 -0.0081 #> [8,] 0.1806 -0.0367 #> [9,] 0.1241 -0.0617 #> [10,] 0.0381 -0.0926 #> [11,] -0.0605 -0.1162 #> [12,] -0.3956 -0.0361 #> [13,] -0.3832 0.0226 #> [14,] -0.1822 0.0248 #> [15,] 0.0825 0.0473 #> [16,] -0.0211 0.0178 #> [17,] 0.0552 -0.0041 #> [18,] -0.1393 -0.0370 #> #> $AE65 #> [,1] [,2] #> [1,] -0.4734 0.0418 #> [2,] 0.0120 0.0760 #> [3,] 0.2281 0.0557 #> [4,] 0.2417 0.0392 #> [5,] 0.2475 0.0208 #> [6,] 0.2471 0.0067 #> [7,] 0.2335 -0.0141 #> [8,] 0.1969 -0.0382 #> [9,] 0.1173 -0.0641 #> [10,] 0.0343 -0.0854 #> [11,] -0.1142 -0.0941 #> [12,] -0.4119 -0.0102 #> [13,] -0.3943 0.0260 #> [14,] -0.1705 0.0265 #> [15,] 0.0578 0.0328 #> [16,] -0.0101 0.0157 #> [17,] 0.0916 -0.0131 #> [18,] -0.1334 -0.0221 #> #> $AE66 #> [,1] [,2] #> [1,] -0.4733 0.0634 #> [2,] 0.0375 0.0889 #> [3,] 0.2215 0.0532 #> [4,] 0.2409 0.0342 #> [5,] 0.2528 0.0053 #> [6,] 0.2475 -0.0172 #> [7,] 0.2245 -0.0341 #> [8,] 0.1735 -0.0584 #> [9,] 0.0939 -0.0720 #> [10,] 0.0066 -0.0898 #> [11,] -0.1113 -0.1010 #> [12,] -0.4122 0.0161 #> [13,] -0.3891 0.0520 #> [14,] -0.1736 0.0397 #> [15,] 0.1103 0.0418 #> [16,] -0.0110 0.0195 #> [17,] 0.0908 -0.0196 #> [18,] -0.1295 -0.0220 #> #> $AE67 #> [,1] [,2] #> [1,] -0.4745 -0.0048 #> [2,] -0.0180 0.0739 #> [3,] 0.2023 0.0863 #> [4,] 0.2362 0.0689 #> [5,] 0.2474 0.0435 #> [6,] 0.2454 0.0244 #> [7,] 0.2370 0.0076 #> [8,] 0.1946 -0.0248 #> [9,] 0.1253 -0.0550 #> [10,] 0.0461 -0.0881 #> [11,] -0.0717 -0.1084 #> [12,] -0.4133 -0.0474 #> [13,] -0.4007 -0.0074 #> [14,] -0.1827 0.0092 #> [15,] 0.0698 0.0415 #> [16,] -0.0069 0.0150 #> [17,] 0.0830 -0.0029 #> [18,] -0.1193 -0.0316 #> #> $AE68 #> [,1] [,2] #> [1,] -0.4682 0.0363 #> [2,] 0.0162 0.0848 #> [3,] 0.2220 0.0626 #> [4,] 0.2528 0.0392 #> [5,] 0.2574 0.0164 #> [6,] 0.2491 -0.0044 #> [7,] 0.2243 -0.0272 #> [8,] 0.1727 -0.0476 #> [9,] 0.1078 -0.0619 #> [10,] 0.0231 -0.0810 #> [11,] -0.0979 -0.0994 #> [12,] -0.4090 -0.0105 #> [13,] -0.3968 0.0310 #> [14,] -0.1951 0.0358 #> [15,] 0.0985 0.0423 #> [16,] -0.0013 0.0195 #> [17,] 0.0729 -0.0110 #> [18,] -0.1284 -0.0248 #> #> $AE69 #> [,1] [,2] #> [1,] -0.4863 0.0295 #> [2,] 0.0127 0.0793 #> [3,] 0.2191 0.0650 #> [4,] 0.2358 0.0459 #> [5,] 0.2457 0.0240 #> [6,] 0.2417 0.0087 #> [7,] 0.2301 -0.0121 #> [8,] 0.1995 -0.0360 #> [9,] 0.1184 -0.0630 #> [10,] 0.0296 -0.0845 #> [11,] -0.0793 -0.1054 #> [12,] -0.4148 -0.0143 #> [13,] -0.3983 0.0188 #> [14,] -0.1556 0.0227 #> [15,] 0.0775 0.0426 #> [16,] -0.0229 0.0174 #> [17,] 0.0789 -0.0132 #> [18,] -0.1320 -0.0255 #> #> $AE70 #> [,1] [,2] #> [1,] -0.4737 0.0113 #> [2,] 0.0050 0.0868 #> [3,] 0.2235 0.0796 #> [4,] 0.2462 0.0555 #> [5,] 0.2500 0.0330 #> [6,] 0.2454 0.0145 #> [7,] 0.2256 -0.0071 #> [8,] 0.1972 -0.0254 #> [9,] 0.1149 -0.0624 #> [10,] 0.0369 -0.0947 #> [11,] -0.0880 -0.1198 #> [12,] -0.4060 -0.0291 #> [13,] -0.3921 0.0033 #> [14,] -0.1731 0.0192 #> [15,] 0.0698 0.0518 #> [16,] -0.0206 0.0244 #> [17,] 0.0761 -0.0092 #> [18,] -0.1368 -0.0317 #> #> $AE71 #> [,1] [,2] #> [1,] -0.4874 -0.0215 #> [2,] -0.0026 0.0984 #> [3,] 0.2117 0.0955 #> [4,] 0.2368 0.0724 #> [5,] 0.2441 0.0511 #> [6,] 0.2405 0.0297 #> [7,] 0.2309 0.0125 #> [8,] 0.1885 -0.0225 #> [9,] 0.1217 -0.0534 #> [10,] 0.0463 -0.0908 #> [11,] -0.0510 -0.1233 #> [12,] -0.3904 -0.0572 #> [13,] -0.3866 -0.0109 #> [14,] -0.2039 0.0073 #> [15,] 0.0774 0.0526 #> [16,] -0.0172 0.0150 #> [17,] 0.0720 -0.0079 #> [18,] -0.1308 -0.0471 #> #> $AE72 #> [,1] [,2] #> [1,] -0.4795 0.0247 #> [2,] 0.0091 0.0831 #> [3,] 0.2254 0.0679 #> [4,] 0.2418 0.0477 #> [5,] 0.2478 0.0260 #> [6,] 0.2434 0.0069 #> [7,] 0.2229 -0.0137 #> [8,] 0.1698 -0.0435 #> [9,] 0.1011 -0.0675 #> [10,] 0.0302 -0.0889 #> [11,] -0.0886 -0.1022 #> [12,] -0.4144 -0.0192 #> [13,] -0.3939 0.0218 #> [14,] -0.1871 0.0307 #> [15,] 0.1069 0.0493 #> [16,] -0.0070 0.0188 #> [17,] 0.0938 -0.0142 #> [18,] -0.1216 -0.0280 #> #> $AE73 #> [,1] [,2] #> [1,] -0.4812 0.0565 #> [2,] -0.0083 0.0817 #> [3,] 0.2518 0.0414 #> [4,] 0.2618 0.0231 #> [5,] 0.2579 0.0073 #> [6,] 0.2441 -0.0147 #> [7,] 0.2224 -0.0303 #> [8,] 0.1684 -0.0514 #> [9,] 0.0983 -0.0710 #> [10,] 0.0396 -0.0905 #> [11,] -0.0744 -0.1091 #> [12,] -0.3931 0.0040 #> [13,] -0.3867 0.0503 #> [14,] -0.1847 0.0468 #> [15,] 0.0925 0.0426 #> [16,] -0.0247 0.0228 #> [17,] 0.0492 -0.0054 #> [18,] -0.1331 -0.0041 #> #> $AE74 #> [,1] [,2] #> [1,] -0.4993 0.0324 #> [2,] 0.0385 0.0888 #> [3,] 0.2101 0.0738 #> [4,] 0.2442 0.0458 #> [5,] 0.2478 0.0201 #> [6,] 0.2385 -0.0078 #> [7,] 0.2092 -0.0311 #> [8,] 0.1675 -0.0509 #> [9,] 0.1004 -0.0700 #> [10,] 0.0204 -0.0891 #> [11,] -0.0874 -0.1027 #> [12,] -0.4197 -0.0120 #> [13,] -0.3998 0.0311 #> [14,] -0.1515 0.0383 #> [15,] 0.0957 0.0439 #> [16,] 0.0090 0.0234 #> [17,] 0.0858 -0.0101 #> [18,] -0.1094 -0.0239 #> #> $AE75 #> [,1] [,2] #> [1,] -0.4930 0.0009 #> [2,] 0.0098 0.0850 #> [3,] 0.2238 0.0734 #> [4,] 0.2375 0.0589 #> [5,] 0.2455 0.0384 #> [6,] 0.2455 0.0211 #> [7,] 0.2315 -0.0059 #> [8,] 0.1734 -0.0333 #> [9,] 0.1027 -0.0571 #> [10,] 0.0428 -0.0851 #> [11,] -0.0623 -0.1083 #> [12,] -0.4081 -0.0362 #> [13,] -0.3975 0.0072 #> [14,] -0.1826 0.0205 #> [15,] 0.0913 0.0498 #> [16,] -0.0073 0.0133 #> [17,] 0.0610 -0.0098 #> [18,] -0.1140 -0.0327 #> #> $AE76 #> [,1] [,2] #> [1,] -0.4792 0.0348 #> [2,] 0.0304 0.0869 #> [3,] 0.2140 0.0581 #> [4,] 0.2300 0.0414 #> [5,] 0.2386 0.0231 #> [6,] 0.2373 0.0049 #> [7,] 0.2247 -0.0140 #> [8,] 0.1851 -0.0421 #> [9,] 0.1217 -0.0651 #> [10,] 0.0216 -0.0856 #> [11,] -0.0886 -0.1011 #> [12,] -0.4228 -0.0215 #> [13,] -0.3953 0.0281 #> [14,] -0.1876 0.0300 #> [15,] 0.1045 0.0452 #> [16,] -0.0007 0.0172 #> [17,] 0.0934 -0.0135 #> [18,] -0.1271 -0.0268 #> #> $AE77 #> [,1] [,2] #> [1,] -0.4881 0.0362 #> [2,] 0.0112 0.0821 #> [3,] 0.2292 0.0667 #> [4,] 0.2434 0.0459 #> [5,] 0.2498 0.0225 #> [6,] 0.2441 0.0014 #> [7,] 0.2256 -0.0232 #> [8,] 0.1860 -0.0492 #> [9,] 0.1195 -0.0705 #> [10,] 0.0140 -0.0947 #> [11,] -0.0906 -0.1020 #> [12,] -0.4026 -0.0068 #> [13,] -0.3875 0.0336 #> [14,] -0.1753 0.0313 #> [15,] 0.0810 0.0459 #> [16,] -0.0129 0.0188 #> [17,] 0.0793 -0.0134 #> [18,] -0.1262 -0.0247 #> #> $AE78 #> [,1] [,2] #> [1,] -0.4808 0.0257 #> [2,] 0.0119 0.0828 #> [3,] 0.2359 0.0674 #> [4,] 0.2512 0.0466 #> [5,] 0.2487 0.0253 #> [6,] 0.2389 0.0053 #> [7,] 0.2190 -0.0150 #> [8,] 0.1791 -0.0401 #> [9,] 0.1275 -0.0625 #> [10,] 0.0294 -0.0893 #> [11,] -0.0727 -0.1060 #> [12,] -0.4010 -0.0194 #> [13,] -0.4092 0.0233 #> [14,] -0.1771 0.0352 #> [15,] 0.0698 0.0404 #> [16,] -0.0148 0.0155 #> [17,] 0.0663 -0.0123 #> [18,] -0.1222 -0.0228 #> #> $AE79 #> [,1] [,2] #> [1,] -0.4854 -0.0160 #> [2,] 0.0061 0.0899 #> [3,] 0.2144 0.0921 #> [4,] 0.2502 0.0634 #> [5,] 0.2546 0.0396 #> [6,] 0.2495 0.0239 #> [7,] 0.2275 0.0048 #> [8,] 0.1833 -0.0226 #> [9,] 0.1243 -0.0512 #> [10,] 0.0498 -0.0852 #> [11,] -0.0740 -0.1218 #> [12,] -0.3882 -0.0466 #> [13,] -0.3775 -0.0073 #> [14,] -0.2143 0.0109 #> [15,] 0.0727 0.0477 #> [16,] -0.0267 0.0160 #> [17,] 0.0627 -0.0037 #> [18,] -0.1292 -0.0337 #> #> $AE80 #> [,1] [,2] #> [1,] -0.4770 0.0323 #> [2,] 0.0028 0.0796 #> [3,] 0.2192 0.0600 #> [4,] 0.2403 0.0375 #> [5,] 0.2502 0.0177 #> [6,] 0.2468 0.0028 #> [7,] 0.2361 -0.0172 #> [8,] 0.1945 -0.0413 #> [9,] 0.1137 -0.0629 #> [10,] 0.0326 -0.0831 #> [11,] -0.0776 -0.1016 #> [12,] -0.4146 -0.0084 #> [13,] -0.3839 0.0274 #> [14,] -0.2006 0.0291 #> [15,] 0.0822 0.0417 #> [16,] -0.0149 0.0200 #> [17,] 0.0785 -0.0103 #> [18,] -0.1282 -0.0233 #> #> $AE81 #> [,1] [,2] #> [1,] -0.4625 0.0125 #> [2,] 0.0122 0.0972 #> [3,] 0.2143 0.0808 #> [4,] 0.2348 0.0651 #> [5,] 0.2503 0.0410 #> [6,] 0.2534 0.0207 #> [7,] 0.2349 -0.0058 #> [8,] 0.1980 -0.0317 #> [9,] 0.1238 -0.0673 #> [10,] 0.0546 -0.1022 #> [11,] -0.0467 -0.1261 #> [12,] -0.4013 -0.0416 #> [13,] -0.3820 0.0075 #> [14,] -0.2137 0.0199 #> [15,] 0.0583 0.0513 #> [16,] -0.0247 0.0182 #> [17,] 0.0494 -0.0079 #> [18,] -0.1531 -0.0316 #> #> $AE82 #> [,1] [,2] #> [1,] -0.4883 -0.0152 #> [2,] -0.0164 0.0892 #> [3,] 0.2108 0.0868 #> [4,] 0.2351 0.0724 #> [5,] 0.2480 0.0471 #> [6,] 0.2410 0.0243 #> [7,] 0.2141 -0.0064 #> [8,] 0.1917 -0.0298 #> [9,] 0.1307 -0.0653 #> [10,] 0.0442 -0.0980 #> [11,] -0.0780 -0.1146 #> [12,] -0.3971 -0.0369 #> [13,] -0.3903 -0.0044 #> [14,] -0.1827 0.0154 #> [15,] 0.0974 0.0553 #> [16,] -0.0215 0.0170 #> [17,] 0.0864 -0.0036 #> [18,] -0.1253 -0.0333 #> #> $AE83 #> [,1] [,2] #> [1,] -0.4668 0.0570 #> [2,] 0.0029 0.0886 #> [3,] 0.2390 0.0506 #> [4,] 0.2567 0.0261 #> [5,] 0.2587 0.0026 #> [6,] 0.2436 -0.0248 #> [7,] 0.2192 -0.0429 #> [8,] 0.1795 -0.0629 #> [9,] 0.1235 -0.0753 #> [10,] 0.0217 -0.0877 #> [11,] -0.0879 -0.0963 #> [12,] -0.4110 0.0186 #> [13,] -0.3814 0.0537 #> [14,] -0.1887 0.0495 #> [15,] 0.0936 0.0451 #> [16,] -0.0185 0.0264 #> [17,] 0.0418 -0.0133 #> [18,] -0.1261 -0.0149 #> #> $AE84 #> [,1] [,2] #> [1,] -0.4812 0.0442 #> [2,] 0.0448 0.0968 #> [3,] 0.2255 0.0617 #> [4,] 0.2478 0.0425 #> [5,] 0.2591 0.0180 #> [6,] 0.2498 -0.0017 #> [7,] 0.2289 -0.0281 #> [8,] 0.1867 -0.0532 #> [9,] 0.1105 -0.0763 #> [10,] 0.0286 -0.0992 #> [11,] -0.0938 -0.1047 #> [12,] -0.3920 0.0044 #> [13,] -0.3772 0.0462 #> [14,] -0.1932 0.0398 #> [15,] 0.0649 0.0383 #> [16,] -0.0299 0.0180 #> [17,] 0.0600 -0.0188 #> [18,] -0.1393 -0.0281 #> #> $AE85 #> [,1] [,2] #> [1,] -0.4611 0.0127 #> [2,] 0.0154 0.0912 #> [3,] 0.2370 0.0709 #> [4,] 0.2518 0.0454 #> [5,] 0.2528 0.0309 #> [6,] 0.2509 0.0117 #> [7,] 0.2381 -0.0070 #> [8,] 0.1968 -0.0369 #> [9,] 0.1009 -0.0629 #> [10,] 0.0191 -0.0904 #> [11,] -0.0797 -0.1074 #> [12,] -0.4117 -0.0313 #> [13,] -0.3981 0.0050 #> [14,] -0.1649 0.0262 #> [15,] 0.0475 0.0479 #> [16,] -0.0288 0.0249 #> [17,] 0.0693 -0.0046 #> [18,] -0.1354 -0.0264 #> #> $AE86 #> [,1] [,2] #> [1,] -0.4746 -0.0102 #> [2,] -0.0048 0.0982 #> [3,] 0.2290 0.0868 #> [4,] 0.2432 0.0694 #> [5,] 0.2495 0.0465 #> [6,] 0.2450 0.0269 #> [7,] 0.2298 0.0018 #> [8,] 0.1892 -0.0311 #> [9,] 0.1274 -0.0604 #> [10,] 0.0578 -0.0941 #> [11,] -0.0414 -0.1274 #> [12,] -0.3930 -0.0612 #> [13,] -0.3824 0.0085 #> [14,] -0.1932 0.0158 #> [15,] 0.0533 0.0491 #> [16,] -0.0299 0.0185 #> [17,] 0.0498 -0.0022 #> [18,] -0.1549 -0.0351 #> #> $AE87 #> [,1] [,2] #> [1,] -0.4700 0.0346 #> [2,] 0.0075 0.0853 #> [3,] 0.2372 0.0643 #> [4,] 0.2583 0.0437 #> [5,] 0.2639 0.0246 #> [6,] 0.2569 -0.0012 #> [7,] 0.2319 -0.0174 #> [8,] 0.1824 -0.0420 #> [9,] 0.1036 -0.0660 #> [10,] 0.0394 -0.0887 #> [11,] -0.0630 -0.1144 #> [12,] -0.3993 -0.0161 #> [13,] -0.3864 0.0292 #> [14,] -0.1710 0.0321 #> [15,] 0.0501 0.0412 #> [16,] -0.0248 0.0161 #> [17,] 0.0472 -0.0097 #> [18,] -0.1638 -0.0155 #> #> $AE88 #> [,1] [,2] #> [1,] -0.4789 0.0466 #> [2,] 0.0268 0.0831 #> [3,] 0.2438 0.0371 #> [4,] 0.2548 0.0207 #> [5,] 0.2559 0.0020 #> [6,] 0.2477 -0.0151 #> [7,] 0.2317 -0.0271 #> [8,] 0.1799 -0.0469 #> [9,] 0.1011 -0.0651 #> [10,] 0.0353 -0.0829 #> [11,] -0.0892 -0.0917 #> [12,] -0.4086 0.0069 #> [13,] -0.4010 0.0471 #> [14,] -0.1455 0.0405 #> [15,] 0.0471 0.0396 #> [16,] -0.0206 0.0232 #> [17,] 0.0565 -0.0062 #> [18,] -0.1368 -0.0116 #> #> $AE89 #> [,1] [,2] #> [1,] -0.4690 0.0593 #> [2,] 0.0698 0.0872 #> [3,] 0.2319 0.0416 #> [4,] 0.2512 0.0188 #> [5,] 0.2517 -0.0043 #> [6,] 0.2471 -0.0202 #> [7,] 0.2183 -0.0396 #> [8,] 0.1770 -0.0567 #> [9,] 0.1112 -0.0710 #> [10,] 0.0155 -0.0877 #> [11,] -0.1024 -0.0898 #> [12,] -0.4069 0.0179 #> [13,] -0.3957 0.0535 #> [14,] -0.1706 0.0430 #> [15,] 0.0837 0.0418 #> [16,] -0.0302 0.0247 #> [17,] 0.0648 -0.0124 #> [18,] -0.1475 -0.0060 #> #> $AE90 #> [,1] [,2] #> [1,] -0.4802 -0.0309 #> [2,] -0.0233 0.0907 #> [3,] 0.2213 0.0933 #> [4,] 0.2414 0.0753 #> [5,] 0.2467 0.0519 #> [6,] 0.2403 0.0348 #> [7,] 0.2267 0.0144 #> [8,] 0.1900 -0.0138 #> [9,] 0.1237 -0.0532 #> [10,] 0.0422 -0.0917 #> [11,] -0.0573 -0.1295 #> [12,] -0.4019 -0.0754 #> [13,] -0.3867 -0.0167 #> [14,] -0.1757 0.0123 #> [15,] 0.0683 0.0591 #> [16,] -0.0120 0.0220 #> [17,] 0.0642 0.0026 #> [18,] -0.1275 -0.0454 #> #> $AE91 #> [,1] [,2] #> [1,] -0.4779 0.0343 #> [2,] -0.0051 0.0874 #> [3,] 0.2188 0.0711 #> [4,] 0.2418 0.0494 #> [5,] 0.2468 0.0277 #> [6,] 0.2444 0.0099 #> [7,] 0.2258 -0.0153 #> [8,] 0.1875 -0.0437 #> [9,] 0.1220 -0.0740 #> [10,] 0.0300 -0.1010 #> [11,] -0.0978 -0.1141 #> [12,] -0.4076 -0.0196 #> [13,] -0.3892 0.0245 #> [14,] -0.1812 0.0342 #> [15,] 0.0914 0.0433 #> [16,] -0.0160 0.0187 #> [17,] 0.0841 -0.0124 #> [18,] -0.1180 -0.0206 #> #> $AE92 #> [,1] [,2] #> [1,] -0.4656 0.0404 #> [2,] 0.0042 0.0833 #> [3,] 0.2235 0.0551 #> [4,] 0.2493 0.0348 #> [5,] 0.2565 0.0143 #> [6,] 0.2524 -0.0079 #> [7,] 0.2341 -0.0255 #> [8,] 0.1980 -0.0432 #> [9,] 0.1148 -0.0632 #> [10,] 0.0300 -0.0813 #> [11,] -0.0854 -0.1019 #> [12,] -0.4114 -0.0068 #> [13,] -0.3884 0.0291 #> [14,] -0.1832 0.0313 #> [15,] 0.0617 0.0390 #> [16,] -0.0179 0.0219 #> [17,] 0.0760 -0.0099 #> [18,] -0.1484 -0.0095 #> #> $AE93 #> [,1] [,2] #> [1,] -0.4952 -0.0307 #> [2,] -0.0084 0.0880 #> [3,] 0.2071 0.0946 #> [4,] 0.2316 0.0816 #> [5,] 0.2467 0.0549 #> [6,] 0.2453 0.0383 #> [7,] 0.2234 0.0091 #> [8,] 0.1754 -0.0252 #> [9,] 0.1271 -0.0547 #> [10,] 0.0341 -0.0909 #> [11,] -0.0819 -0.1079 #> [12,] -0.3926 -0.0640 #> [13,] -0.3841 -0.0171 #> [14,] -0.1796 0.0081 #> [15,] 0.1004 0.0557 #> [16,] -0.0091 0.0132 #> [17,] 0.0923 -0.0063 #> [18,] -0.1324 -0.0468 #> #> $AE94 #> [,1] [,2] #> [1,] -0.4698 0.0335 #> [2,] -0.0216 0.0792 #> [3,] 0.2474 0.0542 #> [4,] 0.2598 0.0366 #> [5,] 0.2638 0.0178 #> [6,] 0.2596 -0.0003 #> [7,] 0.2374 -0.0203 #> [8,] 0.1819 -0.0429 #> [9,] 0.1096 -0.0649 #> [10,] 0.0342 -0.0885 #> [11,] -0.0859 -0.0998 #> [12,] -0.3934 -0.0067 #> [13,] -0.3849 0.0245 #> [14,] -0.1768 0.0324 #> [15,] 0.0505 0.0429 #> [16,] -0.0276 0.0247 #> [17,] 0.0610 -0.0049 #> [18,] -0.1454 -0.0177 #> #> $AE95 #> [,1] [,2] #> [1,] -0.4671 0.0312 #> [2,] -0.0061 0.0664 #> [3,] 0.2297 0.0527 #> [4,] 0.2486 0.0341 #> [5,] 0.2520 0.0135 #> [6,] 0.2493 0.0015 #> [7,] 0.2372 -0.0153 #> [8,] 0.1981 -0.0390 #> [9,] 0.1311 -0.0586 #> [10,] 0.0390 -0.0802 #> [11,] -0.0883 -0.0946 #> [12,] -0.4060 -0.0092 #> [13,] -0.3842 0.0282 #> [14,] -0.1979 0.0305 #> [15,] 0.0683 0.0382 #> [16,] -0.0176 0.0225 #> [17,] 0.0693 -0.0105 #> [18,] -0.1554 -0.0115 #> #> $AE96 #> [,1] [,2] #> [1,] -0.4496 0.0251 #> [2,] 0.0418 0.0929 #> [3,] 0.2379 0.0655 #> [4,] 0.2481 0.0523 #> [5,] 0.2581 0.0299 #> [6,] 0.2557 0.0055 #> [7,] 0.2381 -0.0173 #> [8,] 0.1991 -0.0432 #> [9,] 0.1126 -0.0703 #> [10,] 0.0403 -0.0928 #> [11,] -0.0848 -0.1123 #> [12,] -0.3990 -0.0242 #> [13,] -0.3887 0.0212 #> [14,] -0.1800 0.0272 #> [15,] 0.0494 0.0466 #> [16,] -0.0371 0.0209 #> [17,] 0.0319 -0.0083 #> [18,] -0.1738 -0.0188 #> #> $AE97 #> [,1] [,2] #> [1,] -0.4752 0.0313 #> [2,] -0.0129 0.0794 #> [3,] 0.2411 0.0647 #> [4,] 0.2630 0.0408 #> [5,] 0.2667 0.0187 #> [6,] 0.2589 0.0001 #> [7,] 0.2373 -0.0218 #> [8,] 0.1823 -0.0483 #> [9,] 0.1101 -0.0685 #> [10,] 0.0322 -0.0905 #> [11,] -0.0857 -0.1034 #> [12,] -0.3916 -0.0011 #> [13,] -0.3707 0.0294 #> [14,] -0.1594 0.0302 #> [15,] 0.0684 0.0464 #> [16,] -0.0400 0.0168 #> [17,] 0.0472 -0.0064 #> [18,] -0.1714 -0.0179 #> #> $AE98 #> [,1] [,2] #> [1,] -0.4805 0.0310 #> [2,] 0.0152 0.0817 #> [3,] 0.2335 0.0515 #> [4,] 0.2456 0.0339 #> [5,] 0.2510 0.0165 #> [6,] 0.2463 -0.0020 #> [7,] 0.2240 -0.0203 #> [8,] 0.1898 -0.0367 #> [9,] 0.1122 -0.0542 #> [10,] 0.0281 -0.0775 #> [11,] -0.0741 -0.0984 #> [12,] -0.4098 -0.0139 #> [13,] -0.3935 0.0240 #> [14,] -0.1848 0.0289 #> [15,] 0.0663 0.0398 #> [16,] -0.0167 0.0198 #> [17,] 0.0885 -0.0078 #> [18,] -0.1409 -0.0163 #> #> $AE99 #> [,1] [,2] #> [1,] -0.4590 0.0473 #> [2,] -0.0082 0.0763 #> [3,] 0.2412 0.0497 #> [4,] 0.2554 0.0312 #> [5,] 0.2586 0.0137 #> [6,] 0.2549 -0.0042 #> [7,] 0.2314 -0.0258 #> [8,] 0.1965 -0.0468 #> [9,] 0.1246 -0.0728 #> [10,] 0.0303 -0.0900 #> [11,] -0.0930 -0.1030 #> [12,] -0.3969 0.0077 #> [13,] -0.3798 0.0425 #> [14,] -0.2065 0.0362 #> [15,] 0.0579 0.0396 #> [16,] -0.0358 0.0229 #> [17,] 0.0666 -0.0084 #> [18,] -0.1383 -0.0161 #> #> $AE100 #> [,1] [,2] #> [1,] -0.4465 0.0572 #> [2,] 0.0411 0.0848 #> [3,] 0.2502 0.0521 #> [4,] 0.2663 0.0287 #> [5,] 0.2668 0.0076 #> [6,] 0.2608 -0.0132 #> [7,] 0.2354 -0.0369 #> [8,] 0.1695 -0.0604 #> [9,] 0.0920 -0.0708 #> [10,] 0.0016 -0.0921 #> [11,] -0.1146 -0.0914 #> [12,] -0.4002 0.0082 #> [13,] -0.3877 0.0479 #> [14,] -0.1849 0.0425 #> [15,] 0.0621 0.0415 #> [16,] -0.0326 0.0214 #> [17,] 0.0604 -0.0142 #> [18,] -0.1397 -0.0129 #> #> $CX101 #> [,1] [,2] #> [1,] -0.4675 0.0358 #> [2,] 0.0076 0.0890 #> [3,] 0.2398 0.0591 #> [4,] 0.2530 0.0387 #> [5,] 0.2530 0.0160 #> [6,] 0.2435 -0.0025 #> [7,] 0.2281 -0.0208 #> [8,] 0.1904 -0.0450 #> [9,] 0.1145 -0.0676 #> [10,] 0.0441 -0.0922 #> [11,] -0.0861 -0.1011 #> [12,] -0.4050 -0.0034 #> [13,] -0.4006 0.0308 #> [14,] -0.1777 0.0344 #> [15,] 0.0503 0.0428 #> [16,] -0.0234 0.0200 #> [17,] 0.0666 -0.0124 #> [18,] -0.1306 -0.0216 #> #> $CX102 #> [,1] [,2] #> [1,] -0.4888 0.0420 #> [2,] 0.0310 0.0749 #> [3,] 0.2320 0.0461 #> [4,] 0.2452 0.0355 #> [5,] 0.2490 0.0209 #> [6,] 0.2463 -0.0001 #> [7,] 0.2282 -0.0249 #> [8,] 0.1735 -0.0509 #> [9,] 0.1146 -0.0649 #> [10,] 0.0404 -0.0844 #> [11,] -0.0664 -0.1011 #> [12,] -0.4162 0.0110 #> [13,] -0.3960 0.0379 #> [14,] -0.1586 0.0274 #> [15,] 0.0461 0.0383 #> [16,] -0.0118 0.0157 #> [17,] 0.0706 -0.0104 #> [18,] -0.1394 -0.0132 #> #> $CX103 #> [,1] [,2] #> [1,] -0.4607 0.0433 #> [2,] -0.0028 0.0881 #> [3,] 0.2367 0.0578 #> [4,] 0.2565 0.0380 #> [5,] 0.2685 0.0039 #> [6,] 0.2615 -0.0101 #> [7,] 0.2378 -0.0312 #> [8,] 0.1889 -0.0549 #> [9,] 0.1104 -0.0715 #> [10,] 0.0204 -0.0899 #> [11,] -0.0858 -0.0956 #> [12,] -0.3957 -0.0012 #> [13,] -0.3755 0.0427 #> [14,] -0.1941 0.0420 #> [15,] 0.0460 0.0436 #> [16,] -0.0207 0.0213 #> [17,] 0.0641 -0.0091 #> [18,] -0.1553 -0.0172 #> #> $CX104 #> [,1] [,2] #> [1,] -0.4740 0.0362 #> [2,] 0.0148 0.0902 #> [3,] 0.2410 0.0524 #> [4,] 0.2495 0.0367 #> [5,] 0.2536 0.0150 #> [6,] 0.2499 -0.0044 #> [7,] 0.2304 -0.0224 #> [8,] 0.1789 -0.0498 #> [9,] 0.1190 -0.0697 #> [10,] 0.0377 -0.0896 #> [11,] -0.0732 -0.1019 #> [12,] -0.3990 -0.0067 #> [13,] -0.3906 0.0306 #> [14,] -0.1890 0.0359 #> [15,] 0.0466 0.0460 #> [16,] -0.0228 0.0254 #> [17,] 0.0727 -0.0101 #> [18,] -0.1455 -0.0140 #> #> $CX105 #> [,1] [,2] #> [1,] -0.4668 0.0618 #> [2,] 0.0094 0.0873 #> [3,] 0.2422 0.0529 #> [4,] 0.2512 0.0324 #> [5,] 0.2543 0.0050 #> [6,] 0.2490 -0.0107 #> [7,] 0.2352 -0.0310 #> [8,] 0.1858 -0.0570 #> [9,] 0.1074 -0.0749 #> [10,] 0.0270 -0.0931 #> [11,] -0.0583 -0.1068 #> [12,] -0.4072 0.0148 #> [13,] -0.3952 0.0506 #> [14,] -0.1745 0.0392 #> [15,] 0.0449 0.0349 #> [16,] -0.0158 0.0211 #> [17,] 0.0501 -0.0115 #> [18,] -0.1385 -0.0147 #> #> $CX106 #> [,1] [,2] #> [1,] -0.4715 0.0348 #> [2,] 0.0383 0.0970 #> [3,] 0.2271 0.0693 #> [4,] 0.2476 0.0416 #> [5,] 0.2507 0.0204 #> [6,] 0.2462 0.0005 #> [7,] 0.2329 -0.0169 #> [8,] 0.1895 -0.0447 #> [9,] 0.1317 -0.0662 #> [10,] 0.0419 -0.0952 #> [11,] -0.0667 -0.1140 #> [12,] -0.4058 -0.0158 #> [13,] -0.3849 0.0256 #> [14,] -0.1853 0.0312 #> [15,] 0.0307 0.0462 #> [16,] -0.0225 0.0202 #> [17,] 0.0530 -0.0107 #> [18,] -0.1530 -0.0232 #> #> $CX107 #> [,1] [,2] #> [1,] -0.4590 0.0148 #> [2,] 0.0363 0.0863 #> [3,] 0.2260 0.0699 #> [4,] 0.2480 0.0478 #> [5,] 0.2538 0.0260 #> [6,] 0.2493 0.0091 #> [7,] 0.2424 -0.0048 #> [8,] 0.1848 -0.0373 #> [9,] 0.1359 -0.0516 #> [10,] 0.0476 -0.0813 #> [11,] -0.0687 -0.1059 #> [12,] -0.4071 -0.0230 #> [13,] -0.3946 0.0101 #> [14,] -0.2028 0.0189 #> [15,] 0.0294 0.0402 #> [16,] -0.0230 0.0168 #> [17,] 0.0519 -0.0071 #> [18,] -0.1502 -0.0288 #> #> $CX108 #> [,1] [,2] #> [1,] -0.4555 0.0398 #> [2,] 0.0470 0.0891 #> [3,] 0.2562 0.0561 #> [4,] 0.2701 0.0390 #> [5,] 0.2680 0.0145 #> [6,] 0.2584 -0.0016 #> [7,] 0.2320 -0.0199 #> [8,] 0.1668 -0.0458 #> [9,] 0.1151 -0.0631 #> [10,] 0.0296 -0.0835 #> [11,] -0.0592 -0.0990 #> [12,] -0.3938 -0.0068 #> [13,] -0.3848 0.0315 #> [14,] -0.2053 0.0334 #> [15,] 0.0194 0.0418 #> [16,] -0.0607 0.0127 #> [17,] 0.0395 -0.0129 #> [18,] -0.1427 -0.0254 #> #> $CX109 #> [,1] [,2] #> [1,] -0.4667 0.0415 #> [2,] 0.0338 0.0789 #> [3,] 0.2422 0.0496 #> [4,] 0.2538 0.0348 #> [5,] 0.2566 0.0152 #> [6,] 0.2470 -0.0006 #> [7,] 0.2342 -0.0169 #> [8,] 0.1996 -0.0404 #> [9,] 0.1256 -0.0646 #> [10,] 0.0298 -0.0862 #> [11,] -0.0508 -0.0996 #> [12,] -0.4027 -0.0035 #> [13,] -0.3905 0.0319 #> [14,] -0.1961 0.0325 #> [15,] 0.0087 0.0352 #> [16,] -0.0277 0.0175 #> [17,] 0.0499 -0.0075 #> [18,] -0.1466 -0.0177 #> #> $CX110 #> [,1] [,2] #> [1,] -0.4672 0.0148 #> [2,] -0.0006 0.0759 #> [3,] 0.2450 0.0556 #> [4,] 0.2527 0.0457 #> [5,] 0.2575 0.0260 #> [6,] 0.2521 0.0083 #> [7,] 0.2378 -0.0110 #> [8,] 0.1833 -0.0363 #> [9,] 0.1208 -0.0568 #> [10,] 0.0466 -0.0793 #> [11,] -0.0694 -0.0989 #> [12,] -0.4047 -0.0193 #> [13,] -0.3958 0.0109 #> [14,] -0.1872 0.0241 #> [15,] 0.0241 0.0417 #> [16,] -0.0231 0.0205 #> [17,] 0.0664 -0.0083 #> [18,] -0.1382 -0.0136 #> #> $CX111 #> [,1] [,2] #> [1,] -0.4677 0.0403 #> [2,] 0.0196 0.0881 #> [3,] 0.2339 0.0595 #> [4,] 0.2494 0.0417 #> [5,] 0.2516 0.0225 #> [6,] 0.2500 0.0040 #> [7,] 0.2268 -0.0213 #> [8,] 0.1892 -0.0451 #> [9,] 0.1276 -0.0688 #> [10,] 0.0479 -0.0954 #> [11,] -0.0531 -0.1165 #> [12,] -0.4007 -0.0060 #> [13,] -0.3897 0.0315 #> [14,] -0.1988 0.0346 #> [15,] 0.0346 0.0453 #> [16,] -0.0262 0.0179 #> [17,] 0.0552 -0.0111 #> [18,] -0.1495 -0.0211 #> #> $CX112 #> [,1] [,2] #> [1,] -0.4564 0.0647 #> [2,] 0.0275 0.0924 #> [3,] 0.2515 0.0403 #> [4,] 0.2605 0.0205 #> [5,] 0.2628 -0.0063 #> [6,] 0.2530 -0.0233 #> [7,] 0.2335 -0.0405 #> [8,] 0.1908 -0.0613 #> [9,] 0.0918 -0.0767 #> [10,] 0.0060 -0.0898 #> [11,] -0.0921 -0.0952 #> [12,] -0.3958 0.0241 #> [13,] -0.3816 0.0571 #> [14,] -0.1921 0.0501 #> [15,] 0.0472 0.0384 #> [16,] -0.0190 0.0215 #> [17,] 0.0587 -0.0154 #> [18,] -0.1462 -0.0008 #> #> $CX113 #> [,1] [,2] #> [1,] -0.4751 0.0569 #> [2,] 0.0052 0.0783 #> [3,] 0.2519 0.0382 #> [4,] 0.2542 0.0256 #> [5,] 0.2513 0.0055 #> [6,] 0.2471 -0.0123 #> [7,] 0.2233 -0.0291 #> [8,] 0.1824 -0.0469 #> [9,] 0.1096 -0.0678 #> [10,] 0.0453 -0.0893 #> [11,] -0.0698 -0.1008 #> [12,] -0.4007 0.0165 #> [13,] -0.3929 0.0455 #> [14,] -0.1801 0.0341 #> [15,] 0.0579 0.0377 #> [16,] -0.0185 0.0201 #> [17,] 0.0591 -0.0086 #> [18,] -0.1500 -0.0037 #> #> $CX114 #> [,1] [,2] #> [1,] -0.4516 0.0474 #> [2,] 0.0362 0.0865 #> [3,] 0.2354 0.0643 #> [4,] 0.2578 0.0385 #> [5,] 0.2614 0.0162 #> [6,] 0.2522 -0.0055 #> [7,] 0.2305 -0.0240 #> [8,] 0.1886 -0.0484 #> [9,] 0.1193 -0.0725 #> [10,] 0.0389 -0.1026 #> [11,] -0.0797 -0.1136 #> [12,] -0.4040 0.0051 #> [13,] -0.3864 0.0390 #> [14,] -0.1879 0.0325 #> [15,] 0.0302 0.0375 #> [16,] -0.0300 0.0176 #> [17,] 0.0510 -0.0096 #> [18,] -0.1620 -0.0084 #> #> $CX115 #> [,1] [,2] #> [1,] -0.4523 0.0176 #> [2,] 0.0035 0.0833 #> [3,] 0.2144 0.0768 #> [4,] 0.2443 0.0558 #> [5,] 0.2566 0.0296 #> [6,] 0.2542 0.0105 #> [7,] 0.2407 -0.0070 #> [8,] 0.2163 -0.0307 #> [9,] 0.1366 -0.0594 #> [10,] 0.0410 -0.0894 #> [11,] -0.0903 -0.1067 #> [12,] -0.4030 -0.0281 #> [13,] -0.3952 0.0062 #> [14,] -0.1757 0.0183 #> [15,] 0.0380 0.0414 #> [16,] -0.0322 0.0175 #> [17,] 0.0617 -0.0073 #> [18,] -0.1585 -0.0283 #> #> $CX116 #> [,1] [,2] #> [1,] -0.4638 0.0562 #> [2,] 0.0597 0.0945 #> [3,] 0.2388 0.0506 #> [4,] 0.2573 0.0282 #> [5,] 0.2573 0.0022 #> [6,] 0.2492 -0.0153 #> [7,] 0.2263 -0.0375 #> [8,] 0.1867 -0.0609 #> [9,] 0.1100 -0.0799 #> [10,] 0.0215 -0.0950 #> [11,] -0.0765 -0.1068 #> [12,] -0.4073 0.0138 #> [13,] -0.3775 0.0529 #> [14,] -0.1544 0.0461 #> [15,] 0.0437 0.0430 #> [16,] -0.0265 0.0239 #> [17,] 0.0387 -0.0080 #> [18,] -0.1834 -0.0080 #> #> $CX117 #> [,1] [,2] #> [1,] -0.4699 0.0301 #> [2,] 0.0096 0.0909 #> [3,] 0.2565 0.0431 #> [4,] 0.2598 0.0340 #> [5,] 0.2595 0.0158 #> [6,] 0.2551 0.0034 #> [7,] 0.2364 -0.0176 #> [8,] 0.2000 -0.0399 #> [9,] 0.1255 -0.0658 #> [10,] 0.0271 -0.0897 #> [11,] -0.0544 -0.1021 #> [12,] -0.3901 -0.0085 #> [13,] -0.3751 0.0295 #> [14,] -0.1805 0.0350 #> [15,] 0.0155 0.0443 #> [16,] -0.0440 0.0198 #> [17,] 0.0343 -0.0054 #> [18,] -0.1652 -0.0169 #> #> $CX118 #> [,1] [,2] #> [1,] -0.4717 0.0591 #> [2,] 0.0228 0.0912 #> [3,] 0.2401 0.0542 #> [4,] 0.2557 0.0372 #> [5,] 0.2604 0.0132 #> [6,] 0.2551 -0.0035 #> [7,] 0.2380 -0.0238 #> [8,] 0.1861 -0.0494 #> [9,] 0.1134 -0.0730 #> [10,] 0.0372 -0.0981 #> [11,] -0.0711 -0.1055 #> [12,] -0.4021 -0.0079 #> [13,] -0.3762 0.0492 #> [14,] -0.1826 0.0340 #> [15,] 0.0230 0.0341 #> [16,] -0.0235 0.0166 #> [17,] 0.0383 -0.0098 #> [18,] -0.1430 -0.0179 #> #> $CX119 #> [,1] [,2] #> [1,] -0.4823 0.0484 #> [2,] 0.0239 0.0839 #> [3,] 0.2381 0.0493 #> [4,] 0.2559 0.0323 #> [5,] 0.2612 0.0093 #> [6,] 0.2540 -0.0136 #> [7,] 0.2274 -0.0340 #> [8,] 0.1855 -0.0536 #> [9,] 0.1077 -0.0661 #> [10,] 0.0256 -0.0857 #> [11,] -0.0909 -0.0937 #> [12,] -0.4008 0.0051 #> [13,] -0.3850 0.0448 #> [14,] -0.1620 0.0341 #> [15,] 0.0659 0.0387 #> [16,] -0.0253 0.0186 #> [17,] 0.0440 -0.0063 #> [18,] -0.1428 -0.0115 #> #> $CX120 #> [,1] [,2] #> [1,] -0.4575 0.0294 #> [2,] 0.0270 0.0921 #> [3,] 0.2328 0.0739 #> [4,] 0.2574 0.0451 #> [5,] 0.2623 0.0192 #> [6,] 0.2555 -0.0027 #> [7,] 0.2341 -0.0226 #> [8,] 0.1904 -0.0453 #> [9,] 0.1083 -0.0686 #> [10,] 0.0369 -0.0939 #> [11,] -0.0767 -0.1056 #> [12,] -0.4021 -0.0155 #> [13,] -0.3876 0.0264 #> [14,] -0.1826 0.0346 #> [15,] 0.0479 0.0459 #> [16,] -0.0293 0.0198 #> [17,] 0.0432 -0.0130 #> [18,] -0.1598 -0.0193 #> #> $CX121 #> [,1] [,2] #> [1,] -0.4785 0.0252 #> [2,] -0.0091 0.0782 #> [3,] 0.2140 0.0670 #> [4,] 0.2430 0.0459 #> [5,] 0.2600 0.0218 #> [6,] 0.2575 0.0084 #> [7,] 0.2420 -0.0185 #> [8,] 0.2009 -0.0467 #> [9,] 0.1466 -0.0688 #> [10,] 0.0406 -0.0924 #> [11,] -0.0734 -0.1098 #> [12,] -0.3879 -0.0101 #> [13,] -0.3856 0.0271 #> [14,] -0.1764 0.0262 #> [15,] 0.0299 0.0448 #> [16,] -0.0162 0.0209 #> [17,] 0.0502 -0.0023 #> [18,] -0.1576 -0.0167 #> #> $CX122 #> [,1] [,2] #> [1,] -0.4806 0.0049 #> [2,] 0.0172 0.0810 #> [3,] 0.2174 0.0773 #> [4,] 0.2429 0.0558 #> [5,] 0.2512 0.0339 #> [6,] 0.2482 0.0140 #> [7,] 0.2267 -0.0067 #> [8,] 0.1961 -0.0262 #> [9,] 0.1269 -0.0542 #> [10,] 0.0394 -0.0811 #> [11,] -0.0736 -0.1045 #> [12,] -0.4104 -0.0276 #> [13,] -0.3947 0.0023 #> [14,] -0.1550 0.0162 #> [15,] 0.0567 0.0419 #> [16,] -0.0242 0.0153 #> [17,] 0.0737 -0.0086 #> [18,] -0.1579 -0.0338 #> #> $CX123 #> [,1] [,2] #> [1,] -0.4703 -0.0009 #> [2,] 0.0011 0.0805 #> [3,] 0.2146 0.0747 #> [4,] 0.2348 0.0585 #> [5,] 0.2453 0.0350 #> [6,] 0.2442 0.0149 #> [7,] 0.2372 -0.0030 #> [8,] 0.2186 -0.0235 #> [9,] 0.1342 -0.0582 #> [10,] 0.0391 -0.0843 #> [11,] -0.0726 -0.1051 #> [12,] -0.4090 -0.0371 #> [13,] -0.3966 -0.0061 #> [14,] -0.1624 0.0193 #> [15,] 0.0557 0.0467 #> [16,] -0.0272 0.0190 #> [17,] 0.0718 -0.0052 #> [18,] -0.1583 -0.0251 #> #> $CX124 #> [,1] [,2] #> [1,] -0.4725 0.0441 #> [2,] 0.0318 0.0808 #> [3,] 0.2382 0.0419 #> [4,] 0.2504 0.0237 #> [5,] 0.2492 0.0019 #> [6,] 0.2414 -0.0135 #> [7,] 0.2276 -0.0298 #> [8,] 0.1945 -0.0472 #> [9,] 0.1219 -0.0661 #> [10,] 0.0311 -0.0885 #> [11,] -0.0963 -0.0840 #> [12,] -0.4066 0.0093 #> [13,] -0.3944 0.0425 #> [14,] -0.1724 0.0390 #> [15,] 0.0667 0.0418 #> [16,] -0.0108 0.0205 #> [17,] 0.0548 -0.0049 #> [18,] -0.1546 -0.0115 #> #> $CX125 #> [,1] [,2] #> [1,] -0.4697 0.0196 #> [2,] 0.0007 0.0850 #> [3,] 0.2228 0.0760 #> [4,] 0.2485 0.0540 #> [5,] 0.2548 0.0319 #> [6,] 0.2511 0.0132 #> [7,] 0.2366 -0.0097 #> [8,] 0.1950 -0.0372 #> [9,] 0.1279 -0.0620 #> [10,] 0.0443 -0.0943 #> [11,] -0.0773 -0.1149 #> [12,] -0.3987 -0.0131 #> [13,] -0.3908 0.0161 #> [14,] -0.1816 0.0213 #> [15,] 0.0376 0.0408 #> [16,] -0.0073 0.0137 #> [17,] 0.0592 -0.0103 #> [18,] -0.1531 -0.0300 #> #> $DE126 #> [,1] [,2] #> [1,] -0.4620 0.0204 #> [2,] 0.0082 0.0893 #> [3,] 0.2061 0.0797 #> [4,] 0.2374 0.0529 #> [5,] 0.2457 0.0306 #> [6,] 0.2482 0.0060 #> [7,] 0.2341 -0.0151 #> [8,] 0.2064 -0.0363 #> [9,] 0.1421 -0.0635 #> [10,] 0.0572 -0.0906 #> [11,] -0.0335 -0.1073 #> [12,] -0.4127 -0.0169 #> [13,] -0.4018 0.0111 #> [14,] -0.1876 0.0241 #> [15,] 0.0279 0.0403 #> [16,] -0.0425 0.0145 #> [17,] 0.0729 -0.0123 #> [18,] -0.1460 -0.0269 #> #> $DE127 #> [,1] [,2] #> [1,] -0.4570 0.0468 #> [2,] -0.0090 0.0753 #> [3,] 0.2381 0.0463 #> [4,] 0.2556 0.0275 #> [5,] 0.2614 0.0064 #> [6,] 0.2515 -0.0129 #> [7,] 0.2287 -0.0278 #> [8,] 0.1883 -0.0456 #> [9,] 0.1180 -0.0624 #> [10,] 0.0408 -0.0818 #> [11,] -0.0823 -0.0867 #> [12,] -0.4025 0.0048 #> [13,] -0.3888 0.0415 #> [14,] -0.2028 0.0371 #> [15,] 0.0490 0.0347 #> [16,] -0.0422 0.0204 #> [17,] 0.1004 -0.0180 #> [18,] -0.1473 -0.0057 #> # on Ldk (slidings) get_ldk(chaff) #> $shp1 #> x y #> ScarTop 697 977 #> ScarRight 766 991 #> ScarBottom 704 1046 #> ScarLeft 629 1008 #> RofScar 818 981 #> LofScar 567 1017 #> GInsL 594 1077 #> GInsR 809 1044 #> GJoinL 645 950 #> GJoinR 731 926 #> LTop 541 962 #> RTop 835 911 #> #> $shp2 #> x y #> ScarTop 677 964 #> ScarRight 748 992 #> ScarBottom 677 1039 #> ScarLeft 603 985 #> RofScar 803 994 #> LofScar 551 984 #> GInsL 575 1051 #> GInsR 784 1041 #> GJoinL 642 949 #> GJoinR 715 947 #> LTop 541 949 #> RTop 822 955 #> #> $shp3 #> x y #> ScarTop 684 981 #> ScarRight 748 1006 #> ScarBottom 683 1047 #> ScarLeft 620 1006 #> RofScar 808 1009 #> LofScar 566 1007 #> GInsL 594 1082 #> GInsR 788 1064 #> GJoinL 629 957 #> GJoinR 727 953 #> LTop 551 956 #> RTop 823 960 #> #> $shp4 #> x y #> ScarTop 750 1035 #> ScarRight 820 1056 #> ScarBottom 748 1104 #> ScarLeft 681 1058 #> RofScar 880 1058 #> LofScar 626 1059 #> GInsL 646 1114 #> GInsR 845 1137 #> GJoinL 714 984 #> GJoinR 799 1015 #> LTop 611 985 #> RTop 888 1018 #> #> $shp5 #> x y #> ScarTop 740 1067 #> ScarRight 802 1091 #> ScarBottom 739 1136 #> ScarLeft 674 1093 #> RofScar 862 1092 #> LofScar 604 1095 #> GInsL 636 1173 #> GInsR 829 1165 #> GJoinL 697 1054 #> GJoinR 777 1040 #> LTop 594 1052 #> RTop 874 1044 #> #> $shp6 #> x y #> ScarTop 784 903 #> ScarRight 841 921 #> ScarBottom 782 954 #> ScarLeft 720 914 #> RofScar 919 928 #> LofScar 663 913 #> GInsL 704 994 #> GInsR 886 983 #> GJoinL 751 888 #> GJoinR 828 897 #> LTop 654 887 #> RTop 928 905 #> #> $shp7 #> x y #> ScarTop 766 1041 #> ScarRight 841 1055 #> ScarBottom 768 1108 #> ScarLeft 688 1063 #> RofScar 892 1055 #> LofScar 631 1065 #> GInsL 664 1102 #> GInsR 873 1085 #> GJoinL 707 1006 #> GJoinR 824 992 #> LTop 601 1008 #> RTop 921 997 #> #> $shp8 #> x y #> ScarTop 822 1134 #> ScarRight 895 1149 #> ScarBottom 823 1201 #> ScarLeft 747 1159 #> RofScar 951 1146 #> LofScar 688 1161 #> GInsL 721 1201 #> GInsR 920 1188 #> GJoinL 755 1112 #> GJoinR 879 1114 #> LTop 665 1118 #> RTop 964 1121 #> #> $shp9 #> x y #> ScarTop 772 1041 #> ScarRight 829 1054 #> ScarBottom 767 1104 #> ScarLeft 695 1049 #> RofScar 893 1061 #> LofScar 638 1052 #> GInsL 661 1094 #> GInsR 859 1110 #> GJoinL 711 1007 #> GJoinR 822 1015 #> LTop 619 1005 #> RTop 912 1026 #> #> $shp10 #> x y #> ScarTop 824 978 #> ScarRight 875 1013 #> ScarBottom 821 1047 #> ScarLeft 752 1012 #> RofScar 980 1017 #> LofScar 652 1014 #> GInsL 722 1133 #> GInsR 940 1111 #> GJoinL 760 977 #> GJoinR 873 971 #> LTop 640 981 #> RTop 991 985 #> #> $shp11 #> x y #> ScarTop 773 1004 #> ScarRight 832 1022 #> ScarBottom 777 1060 #> ScarLeft 716 1030 #> RofScar 927 1019 #> LofScar 605 1040 #> GInsL 679 1167 #> GInsR 878 1140 #> GJoinL 716 1002 #> GJoinR 861 965 #> LTop 594 1012 #> RTop 945 973 #> #> $shp12 #> x y #> ScarTop 792 986 #> ScarRight 849 992 #> ScarBottom 795 1044 #> ScarLeft 732 1003 #> RofScar 951 987 #> LofScar 636 1014 #> GInsL 700 1159 #> GInsR 899 1119 #> GJoinL 749 983 #> GJoinR 856 969 #> LTop 630 995 #> RTop 959 970 #> #> $shp13 #> x y #> ScarTop 753 1244 #> ScarRight 830 1265 #> ScarBottom 759 1322 #> ScarLeft 678 1288 #> RofScar 940 1259 #> LofScar 566 1306 #> GInsL 634 1413 #> GInsR 884 1392 #> GJoinL 674 1242 #> GJoinR 822 1213 #> LTop 550 1254 #> RTop 952 1220 #> #> $shp14 #> x y #> ScarTop 754 1113 #> ScarRight 819 1149 #> ScarBottom 749 1179 #> ScarLeft 678 1137 #> RofScar 943 1169 #> LofScar 572 1128 #> GInsL 643 1254 #> GInsR 850 1287 #> GJoinL 673 1099 #> GJoinR 831 1115 #> LTop 561 1099 #> RTop 956 1129 #> #> $shp15 #> x y #> ScarTop 742 1127 #> ScarRight 805 1151 #> ScarBottom 740 1182 #> ScarLeft 672 1154 #> RofScar 910 1158 #> LofScar 557 1157 #> GInsL 654 1279 #> GInsR 830 1270 #> GJoinL 658 1118 #> GJoinR 814 1098 #> LTop 543 1113 #> RTop 922 1115 #> #> $shp16 #> x y #> ScarTop 821 1105 #> ScarRight 886 1110 #> ScarBottom 831 1167 #> ScarLeft 763 1140 #> RofScar 985 1101 #> LofScar 656 1167 #> GInsL 715 1240 #> GInsR 954 1184 #> GJoinL 732 1098 #> GJoinR 899 1045 #> LTop 635 1118 #> RTop 1001 1049 #> #> $shp17 #> x y #> ScarTop 829 1103 #> ScarRight 898 1123 #> ScarBottom 825 1162 #> ScarLeft 754 1115 #> RofScar 1004 1134 #> LofScar 661 1109 #> GInsL 703 1199 #> GInsR 958 1215 #> GJoinL 747 1081 #> GJoinR 917 1103 #> LTop 651 1080 #> RTop 1010 1122 #> #> $shp18 #> x y #> ScarTop 763 1102 #> ScarRight 826 1107 #> ScarBottom 774 1158 #> ScarLeft 701 1126 #> RofScar 924 1094 #> LofScar 615 1140 #> GInsL 659 1226 #> GInsR 878 1229 #> GJoinL 695 1110 #> GJoinR 828 1080 #> LTop 612 1123 #> RTop 927 1077 #> #> $shp19 #> x y #> ScarTop 653 1169 #> ScarRight 724 1197 #> ScarBottom 653 1254 #> ScarLeft 569 1202 #> RofScar 830 1210 #> LofScar 439 1212 #> GInsL 523 1311 #> GInsR 775 1297 #> GJoinL 539 1141 #> GJoinR 728 1124 #> LTop 405 1151 #> RTop 873 1128 #> #> $shp20 #> x y #> ScarTop 600 1155 #> ScarRight 663 1197 #> ScarBottom 592 1232 #> ScarLeft 525 1187 #> RofScar 781 1208 #> LofScar 405 1187 #> GInsL 460 1289 #> GInsR 716 1289 #> GJoinL 500 1114 #> GJoinR 667 1128 #> LTop 372 1118 #> RTop 812 1149 #> #> $shp21 #> x y #> ScarTop 612 1193 #> ScarRight 677 1228 #> ScarBottom 610 1269 #> ScarLeft 543 1228 #> RofScar 773 1230 #> LofScar 429 1228 #> GInsL 482 1289 #> GInsR 734 1299 #> GJoinL 527 1167 #> GJoinR 665 1147 #> LTop 403 1169 #> RTop 799 1161 #> get_ldk(chaff) %>% Ldk %>% fgProcrustes(tol=0.1) %>% stack #> iteration: 1 \tgain: 1448.7 #> iteration: 2 \tgain: 0.027479"},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"paired individuals, .e. treatment repeated measures, coded coded $fac, methods allows retrieve corresponding PC/LD scores, coefficients Coe objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"","code":"get_pairs(x, fac, range)"},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"x Coe, PCA LDA object. fac factor column name id corresponding pairing factor. range numeric range coefficients Coe, PC (LD) axes return scores.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"list components x1 coefficients/scores corresponding first level fac provided; x2 thing second level; fac corresponding fac.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get paired individual on a Coe, PCA or LDA objects — get_pairs","text":"","code":"bot2 <- bot1 <- coo_scale(coo_center(coo_sample(bot, 60))) bot1$fac$session <- factor(rep(\"session1\", 40)) # we simulate an measurement error bot2 <- coo_jitter(bot1, amount=0.01) bot2$fac$session <- factor(rep(\"session2\", 40)) botc <- combine(bot1, bot2) botcf <- efourier(botc, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # we gonna plot the PCA with the two measurement sessions and the two types botcp <- PCA(botcf) plot(botcp, \"type\", col=col_summer(2), pch=rep(c(1, 20), each=40), eigen=FALSE) #> will be deprecated soon, see ?plot_PCA bot.pairs <- get_pairs(botcp, fac = \"session\", range=1:2) segments(bot.pairs$session1[, 1], bot.pairs$session1[, 2], bot.pairs$session2[, 1], bot.pairs$session2[, 2], col=col_summer(2)[bot.pairs$fac$type])"},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts sliding landmarks coordinates — get_slidings","title":"Extracts sliding landmarks coordinates — get_slidings","text":"Ldk object.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts sliding landmarks coordinates — get_slidings","text":"","code":"get_slidings(Coo, partition)"},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts sliding landmarks coordinates — get_slidings","text":"Coo Ldk object partition numeric one(s) get.","code":""},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts sliding landmarks coordinates — get_slidings","text":"list list(s) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/get_slidings.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts sliding landmarks coordinates — get_slidings","text":"","code":"# for each example below a list with partition containign shapes is returned # extracts the first partition get_slidings(chaff, 1) %>% names() #> [1] \"partition1\" # the first and the fourth get_slidings(chaff, c(1, 4)) %>% names() #> [1] \"partition1\" \"partition4\" # all of them get_slidings(chaff) %>% names #> [1] \"partition1\" \"partition2\" \"partition3\" \"partition4\" # here we want to see it get_slidings(chaff, 1)[[1]] %>% Ldk %>% stack"},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":null,"dir":"Reference","previous_headings":"","what":"Harmonic contribution to shape — hcontrib","title":"Harmonic contribution to shape — hcontrib","text":"Calculates contribution harmonics shape. amplitude every coefficients given harmonic multiplied coefficients provided resulting shapes reconstructed plotted. Naturally, works Fourier-based methods.","code":""},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Harmonic contribution to shape — hcontrib","text":"","code":"hcontrib(Coe, ...) # S3 method for OutCoe hcontrib( Coe, id, harm.r, amp.r = c(0, 0.5, 1, 2, 5, 10), main = \"Harmonic contribution to shape\", xlab = \"Harmonic rank\", ylab = \"Amplification factor\", ... )"},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Harmonic contribution to shape — hcontrib","text":"Coe Coe object (either OutCoe (soon) OpnCoe) ... additional parameter pass coo_draw id id particular shape, otherwise working meanshape harm.r range harmonics explore contributions amp.r vector numeric multiplying coefficients main title plot xlab title x-axis ylab title y-axis","code":""},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Harmonic contribution to shape — hcontrib","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/harm.contrib.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Harmonic contribution to shape — hcontrib","text":"","code":"data(bot) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details hcontrib(bot.f) #> no 'id' provided, working on the meanshape hcontrib(bot.f, harm.r=3:10, amp.r=1:8, col=\"grey20\", main=\"A huge panel\") #> no 'id' provided, working on the meanshape"},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"Given list , bn (eventually cn dn), returns harmonic power.","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"","code":"harm_pow(xf)"},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"xf list , bn (cn, dn) components, typically e/r/tfourier passed coo_","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"Returns vector harmonic power","code":""},{"path":"http://momx.github.io/Momocs/reference/harm_pow.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates harmonic power given a list from e/t/rfourier — harm_pow","text":"","code":"ef <- efourier(bot[1], 24) rf <- efourier(bot[1], 24) harm_pow(ef) #> H1 H2 H3 H4 H5 H6 #> 1.299790e+05 2.593195e+02 1.376114e+03 1.792188e+02 2.594795e+02 2.675959e+01 #> H7 H8 H9 H10 H11 H12 #> 3.103764e+01 3.422527e+00 6.584799e-01 8.255293e+00 3.010409e+00 6.433551e+00 #> H13 H14 H15 H16 H17 H18 #> 1.082413e+00 1.171377e+00 1.929022e-01 4.769194e-01 2.059250e-01 1.971375e-01 #> H19 H20 H21 H22 H23 H24 #> 1.099667e-01 1.586647e-01 4.222544e-02 1.447763e-01 5.618937e-02 1.570677e-01 harm_pow(rf) #> H1 H2 H3 H4 H5 H6 #> 1.299790e+05 2.593195e+02 1.376114e+03 1.792188e+02 2.594795e+02 2.675959e+01 #> H7 H8 H9 H10 H11 H12 #> 3.103764e+01 3.422527e+00 6.584799e-01 8.255293e+00 3.010409e+00 6.433551e+00 #> H13 H14 H15 H16 H17 H18 #> 1.082413e+00 1.171377e+00 1.929022e-01 4.769194e-01 2.059250e-01 1.971375e-01 #> H19 H20 H21 H22 H23 H24 #> 1.099667e-01 1.586647e-01 4.222544e-02 1.447763e-01 5.618937e-02 1.570677e-01 plot(cumsum(harm_pow(ef)[-1]), type='o', main='Cumulated harmonic power without the first harmonic', ylab='Cumulated harmonic power', xlab='Harmonic rank')"},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a .jpg image — img_plot","title":"Plots a .jpg image — img_plot","text":"simple image plotter. provided path, reads .jpg plots . provided imagematrix, ask choose interactively .jpeg image.","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a .jpg image — img_plot","text":"","code":"img_plot(img) img_plot0(img)"},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a .jpg image — img_plot","text":"img matrix image, obtained readJPEG.","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a .jpg image — img_plot","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/img_plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots a .jpg image — img_plot","text":"img_plot used import functions import_jpg1; img_plot0 job preserves par plots axes.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outlines coordinates from an image silhouette — import_Conte","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Provided image 'mask' (.e. black pixels white background), point form start algorithm, returns (x; y) coordinates outline.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"","code":"import_Conte(img, x)"},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"img matrix binary image mask. x numeric (x; y) coordinates starting point within shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"matrix (x; y) coordinates outline points.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Used internally import_jpg1 may useful purposes.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"Note function deprecated Momocs Momacs Momit fully operationnal. image single shape, may want try imager::highlight function. Momocs may use point.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_Conte.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Extract outlines coordinates from an image silhouette — import_Conte","text":"original algorithm due : Pavlidis, T. (1982). Algorithms graphics image processing. Computer science press. detailed : Rohlf, F. J. (1990). overview image processing analysis techniques morphometrics. Proceedings Michigan Morphometrics Workshop. Special Publication . 2 (pp. 47-60). University Michigan Museum Zoology: Ann Arbor. translated R : Claude, J. (2008). Morphometrics R. (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":null,"dir":"Reference","previous_headings":"","what":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"Helps read .txt files created StereoMorph (x; y) coordinates Momocs objects. Can applied 'curves' 'ldk' text files.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"","code":"import_StereoMorph_curve1(path) import_StereoMorph_curve(path, names) import_StereoMorph_ldk1(path) import_StereoMorph_ldk(path, names)"},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"path toward single file folder containing .txt files produced StereoMorph names feed lf_structure","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"list class Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"*1 functions import single .txt file. counterpart ('1') work path indicates folder, .e. 'curves' 'ldk'. return list Opn Ldk objects, respectively. Please hesitate contact particular case need something.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_StereoMorph.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import files creates by StereoMorph into Momocs — import_StereoMorph_curve1","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outline coordinates from multiple .jpg files — import_jpg","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"function used import outline coordinates built around import_jpg1.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"","code":"import_jpg( jpg.paths = .lf.auto(), auto.notcentered = TRUE, fun.notcentered = NULL, threshold = 0.5 )"},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"jpg.paths vector paths corresponding .jpg files import. provided (NULL), switches automatic version. See Details . auto.notcentered logical TRUE random locations used . one (assumed) within shape (black pixel); FALSE locator called, click point within shape. fun.notcentered NULL default. shapes centered random pick black pixel satisfactory. See import_jpg1 help examples. threshold threshold value use binarize images. , pixels turned 1, 0.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"list matrices (x; y) coordinates can passed ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"see import_jpg1 important informations outlines extracted, import_Conte algorithm . jpg.paths provided (NULL), select .jpg file folder contains files. outlines imported .","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"Note function deprecated Momocs Momacs Momit fully operationnal. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_jpg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract outline coordinates from multiple .jpg files — import_jpg","text":"","code":"# \\donttest{ lf <- list.files('/foo/jpegs', full.names=TRUE) coo <- import_jpg(lf) #> Extracting 0.jpg outlines... #> Done in 0 secs Out(coo) #> empty Out coo <- import_jpg() #> Warning: unable to translate 'd' to a wide string #> Warning: input string 1 is invalid #> Extracting 0.jpg outlines... #> Done in 0 secs # }"},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract outline coordinates from a single .jpg file — import_jpg1","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"Used import outline coordinates .jpg files. function used single images wrapped import_jpg. relies import_Conte","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"","code":"import_jpg1( jpg.path, auto.notcentered = TRUE, fun.notcentered = NULL, threshold = 0.5, ... )"},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"jpg.path vector paths corresponding .jpg files import, obtained list.files. auto.notcentered logical TRUE random locations used one (assumed) within shape (corresponds black pixel) middle point black; FALSE locator called, click point within shape. fun.notcentered NULL default can accept function , passed imagematrix returns numeric length two corresponds starting point imagematrix Conte algorithm. instruction wraps , function may wrong proposing starting position. See examples quick example. threshold threshold value use binarize images. , pixels turned 1, 0. ... arguments passed read.table, eg. 'skip', 'dec', etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"matrix (x; y) coordinates can passed ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"jpegs can provided either RVB 8-bit greylevels monochrome. function binarizes pixels values using 'threshold' argument. try start apply import_Conte algorithm center image 'looking' downwards first black/white 'frontier' pixels. point first outlines. latter may useful align manually images want retain information consequent morphometric analyses. point center image within shape, .e. 'white' two choices defined 'auto.notcentered' argument. TRUE, random starting points tried 'black' within shape; FALSE asked click point within shape. pixels borders white, functions adds 2-pixel border white pixels; otherwise import_Conte fail return error. Finally, remember images working directory, list.files must called argument full.names=TRUE! Note use fun.notcentered argument probably leads serious headaches probably imply dissection functions: import_Conte, img_plot import_jpg ","code":""},{"path":"http://momx.github.io/Momocs/reference/import_jpg1.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract outline coordinates from a single .jpg file — import_jpg1","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":null,"dir":"Reference","previous_headings":"","what":"Import a tps file — import_tps","title":"Import a tps file — import_tps","text":"returns list coordinates, curves, scale","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import a tps file — import_tps","text":"","code":"import_tps(tps.path, curves = TRUE) tps2coo(tps, curves = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import a tps file — import_tps","text":"tps.path lines, typically readLines, describing single shape tps-like format. need manually build Coo object : eg (coo=your_list$coo). curves logical whether read curves, tps lines single tps file tps2coo used import_tps may useful data import. provided lines (eg readLines) tps-like description (\"LM\", \"CURVES\", etc.) returns list coordinates, curves, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import a tps file — import_tps","text":"list components: coo matrix coordinates; cur list matrices; scale scale numeric.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_tps.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import a tps file — import_tps","text":"Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":null,"dir":"Reference","previous_headings":"","what":"Import coordinates from a .txt file — import_txt","title":"Import coordinates from a .txt file — import_txt","text":"wrapper around read.table can used import outline/landmark coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Import coordinates from a .txt file — import_txt","text":"","code":"import_txt(txt.paths = .lf.auto(), ...)"},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Import coordinates from a .txt file — import_txt","text":"txt.paths vector paths corresponding .txt files import. provided (NULL), switches automatic version, just import_jpg. See Details . ... arguments passed read.table, eg. 'skip', 'dec', etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Import coordinates from a .txt file — import_txt","text":"list matrix(ces) (x; y) coordinates can passed , Opn Ldk.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Import coordinates from a .txt file — import_txt","text":"Columns named .txt files. can tune using ... argument. Define read.table arguments allow import single file, pass function, ie .txt file header (eg ('x', 'y')), forget header=TRUE.","code":""},{"path":"http://momx.github.io/Momocs/reference/import_txt.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Import coordinates from a .txt file — import_txt","text":"Note function deprecated Momocs Momacs Momit fully operationnal. Silent message progress bars () options(\"verbose\"=FALSE).","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":null,"dir":"Reference","previous_headings":"","what":"Graphical inspection of shapes — inspect","title":"Graphical inspection of shapes — inspect","text":"Allows plot shapes, individually, Coo (, Opn Ldk) objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graphical inspection of shapes — inspect","text":"","code":"inspect(x, id, ...)"},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graphical inspection of shapes — inspect","text":"x Coo object id id shape plot, provided random shape plotted. passed '' shapes plotted, one one. ... arguments passed coo_plot","code":""},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graphical inspection of shapes — inspect","text":"interactive plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/inspect.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graphical inspection of shapes — inspect","text":"","code":"if (FALSE) { inspect(bot, 5) inspect(bot) inspect(bot, 5, pch=3, points=TRUE) # an example of '...' use }"},{"path":"http://momx.github.io/Momocs/reference/is.html","id":null,"dir":"Reference","previous_headings":"","what":"Class and component testers — is","title":"Class and component testers — is","text":"Class testers test classes object given class. instance is_PCA PCA object (classes PCA prcomp) return TRUE. Component testers check there_is particular component (eg $fac, etc.) object.","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Class and component testers — is","text":"","code":"is_Coo(x) is_PCA(x) is_LDA(x) is_Out(x) is_Opn(x) is_Ldk(x) is_Coe(x) is_OutCoe(x) is_OpnCoe(x) is_LdkCoe(x) is_TraCoe(x) is_shp(x) is_fac(x) is_ldk(x) is_slidings(x) is_links(x)"},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Class and component testers — is","text":"x object test","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Class and component testers — is","text":"logical","code":""},{"path":"http://momx.github.io/Momocs/reference/is.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Class and component testers — is","text":"","code":"is_Coo(bot) #> [1] TRUE is_Out(bot) #> [1] TRUE is_Ldk(bot) #> [1] FALSE is_ldk(hearts) # mind the capitals! #> [1] TRUE"},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":null,"dir":"Reference","previous_headings":"","what":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"Returns TRUE/FALSE whether sd angles successive radii /thesh","code":""},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"","code":"is_equallyspacedradii(coo, thres)"},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"coo matrix (x; y) coordinates Coo object. thres numeric threshold (arbitrarily pi/90, eg 2 degrees, default)","code":""},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"single vector logical. NA returned, coordinates likely identical, least x y.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/is_equallyspacedradii.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tests if coordinates likely have equally spaced radii — is_equallyspacedradii","text":"","code":"bot[1] %>% is_equallyspacedradii #> [1] NA bot[1] %>% coo_samplerr(36) %>% is_equallyspacedradii #> [1] NA # higher tolerance but wrong bot[1] %>% coo_samplerr(36) %>% is_equallyspacedradii(thres=5*2*pi/360) #> [1] NA # coo_interpolate is a better option bot[1] %>% coo_interpolate(1200) %>% coo_samplerr(36) %>% is_equallyspacedradii #> [1] NA # Coo method bot %>% coo_interpolate(360) %>% coo_samplerr(36) %>% is_equallyspacedradii #> brahma caney chimay corona deusventrue #> NA NA NA NA NA #> duvel franziskaner grimbergen guiness hoegardeen #> NA NA NA NA NA #> jupiler kingfisher latrappe lindemanskriek nicechouffe #> NA NA NA NA NA #> pecheresse sierranevada tanglefoot tauro westmalle #> NA NA NA NA NA #> amrut ballantines bushmills chivas dalmore #> NA NA NA NA NA #> famousgrouse glendronach glenmorangie highlandpark jackdaniels #> NA NA NA NA NA #> jb johnniewalker magallan makersmark oban #> NA NA NA NA NA #> oldpotrero redbreast tamdhu wildturkey yoichi #> NA NA NA NA NA"},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr layers for multivariate plots — layers","title":"grindr layers for multivariate plots — layers","text":"Useful layers building custom mutivariate plots using cheapbabi approach. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr layers for multivariate plots — layers","text":"","code":"layer_frame(x, center_origin = TRUE, zoom = 0.9) layer_axes(x, col = \"#999999\", lwd = 1/2, ...) layer_ticks(x, col = \"#333333\", cex = 3/4, lwd = 3/4, ...) layer_grid(x, col = \"#999999\", lty = 3, grid = 3, ...) layer_box(x, border = \"#e5e5e5\", ...) layer_fullframe(x, ...) layer_points(x, pch = 20, cex = 4/log1p(nrow(x$xy)), transp = 0, ...) layer_ellipses(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_ellipsesfilled(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_ellipsesaxes(x, conf = 0.5, lwd = 1, alpha = 0, ...) layer_chull(x, ...) layer_chullfilled(x, alpha = 0.8, ...) layer_stars(x, alpha = 0.5, ...) layer_delaunay(x, ...) layer_density( x, levels_density = 20, levels_contour = 4, alpha = 1/3, n = 200, density = TRUE, contour = TRUE ) layer_labelpoints( x, col = par(\"fg\"), cex = 2/3, font = 1, abbreviate = FALSE, ... ) layer_labelgroups( x, col = par(\"fg\"), cex = 3/4, font = 2, rect = TRUE, alpha = 1/4, abbreviate = FALSE, ... ) layer_rug(x, size = 1/200, ...) layer_histogram_2(x, freq = FALSE, breaks, split = FALSE, transp = 0) layer_density_2(x, bw, split = FALSE, rug = TRUE, transp = 0) layer_title(x, title = \"\", cex = 3/4, ...) layer_axesnames(x, cex = 3/4, name = \"Axis\", ...) layer_eigen(x, nb_max = 5, cex = 1/2, ...) layer_axesvar(x, cex = 3/4, ...) layer_legend(x, probs = seq(0, 1, 0.25), cex = 3/4, ...)"},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr layers for multivariate plots — layers","text":"x list, typically returned plot_PCA center_origin logical whether center origin (default TRUE) zoom numeric change zoom (default 0.9) col color (hexadecimal) use drawing components lwd linewidth drawing components ... additional options feed core functions layer cex use drawing components lty linetype drawing components grid numeric number grid draw border color (hexadecimal) use draw border pch use drawing components transp transparency use (min: 0 defaut:0 max:1) conf numeric 0 1 confidence ellipses alpha numeric 0 1 transparency components levels_density numeric number levels use feed MASS::kde2d levels_contour numeric number levels use feed graphics::contour n numeric number grid points feed MASS::kde2d density logical whether draw density estimate contour logical whether draw contour lines font feed text abbreviate logical whether abbreviate names rect logical whether draw rectangle names size numeric fraction graphical window (default: 1/200) freq logicalto feed[hist] (default:FALSE`) breaks feed hist (default: calculated pooled values) split logical whether split two distributions two plots bw feed density (default: stats::bw.nrd0) rug logical whether add rug (default: TRUE) title add plot (default \"\") name use axes (default \"Axis\") nb_max numeric number eigen values display (default 5) probs numeric sequence feed stats::quantile indicate draw ticks legend labels","code":""},{"path":"http://momx.github.io/Momocs/reference/layers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr layers for multivariate plots — layers","text":"drawing layer","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":null,"dir":"Reference","previous_headings":"","what":"Morphospace layers — layers_morphospace","title":"Morphospace layers — layers_morphospace","text":"Used internally plot_PCA, plot_LDA, etc. may useful elsewhere.","code":""},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Morphospace layers — layers_morphospace","text":"","code":"layer_morphospace_PCA( x, position = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb = 12, nr = 6, nc = 5, rotate = 0, size = 0.9, col = \"#999999\", flipx = FALSE, flipy = FALSE, draw = TRUE ) layer_morphospace_LDA( x, position = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb = 12, nr = 6, nc = 5, rotate = 0, size = 0.9, col = \"#999999\", flipx = FALSE, flipy = FALSE, draw = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Morphospace layers — layers_morphospace","text":"x layered PCA LDA. Typically, object returned plot_PCA plot_LDA position one range, full, circle, xy, range_axes, full_axes feed morphospace_positions (default: range) nb numeric total number shapes position=\"circle\" (default: 12) nr numeric number rows position shapes (default: 6) nc numeric number columns position shapes (default 5) rotate numeric angle (radians) rotate shapes displayed morphospace (default: 0) size numeric size use feed coo_template (default: 0.9) col color draw shapes (default: #999999) flipx logical whether flip shapes x-axis (default: FALSE) flipy logical whether flip shapes y-axis (default: FALSE) draw logical whether draw shapes (default: TRUE)","code":""},{"path":"http://momx.github.io/Momocs/reference/layers_morphospace.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Morphospace layers — layers_morphospace","text":"drawing layer","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks 'ldk' shapes — ldk_check","title":"Checks 'ldk' shapes — ldk_check","text":"simple utility, used internally, mostly Ldk methods, graphical functions, notably l2a. Returns array landmarks arranged (nb.ldk) x (x; y) x (nb.shapes), passed either list, matrix array coordinates. list provided, checks number landmarks consistent.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks 'ldk' shapes — ldk_check","text":"","code":"ldk_check(ldk)"},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks 'ldk' shapes — ldk_check","text":"ldk matrix (x; y) coordinates, list, array.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks 'ldk' shapes — ldk_check","text":"array (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_check.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks 'ldk' shapes — ldk_check","text":"","code":"#coo_check('Not a shape') #coo_check(matrix(1:10, ncol=2)) #coo_check(list(x=1:5, y=6:10))"},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws convex hulls around landmark positions — ldk_chull","title":"Draws convex hulls around landmark positions — ldk_chull","text":"wrapper uses coo_chull","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws convex hulls around landmark positions — ldk_chull","text":"","code":"ldk_chull(ldk, col = \"grey40\", lty = 1)"},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws convex hulls around landmark positions — ldk_chull","text":"ldk array (list) landmarks col color drawing convex hull lty lty drawing convex hulls","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws convex hulls around landmark positions — ldk_chull","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_chull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws convex hulls around landmark positions — ldk_chull","text":"","code":"coo_plot(MSHAPES(wings)) ldk_chull(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws confidence ellipses for landmark positions — ldk_confell","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"Draws confidence ellipses landmark positions","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"","code":"ldk_confell( ldk, conf = 0.5, col = \"grey40\", ell.lty = 1, ax = TRUE, ax.lty = 2 )"},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"ldk array (list) landmarks conf confidence level (normal quantile, 0.5 default) col color ellipse ell.lty lty ellipse ax logical whether draw ellipses axes ax.lty lty ellipses axes","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_confell.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws confidence ellipses for landmark positions — ldk_confell","text":"","code":"coo_plot(MSHAPES(wings)) ldk_confell(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws kernel density contours around landmark — ldk_contour","title":"Draws kernel density contours around landmark — ldk_contour","text":"Using kde2d MASS package.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws kernel density contours around landmark — ldk_contour","text":"","code":"ldk_contour(ldk, nlevels = 5, grid.nb = 50, col = \"grey60\")"},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws kernel density contours around landmark — ldk_contour","text":"ldk array (list) landmarks nlevels number contour lines grid.nb grid.nb col color drawing contour lines","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws kernel density contours around landmark — ldk_contour","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_contour.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws kernel density contours around landmark — ldk_contour","text":"","code":"coo_plot(MSHAPES(wings)) ldk_contour(wings$coo)"},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":null,"dir":"Reference","previous_headings":"","what":"Add landmarks labels — ldk_labels","title":"Add landmarks labels — ldk_labels","text":"Add landmarks labels","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add landmarks labels — ldk_labels","text":"","code":"ldk_labels(ldk, d = 0.05, cex = 2/3, ...)"},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add landmarks labels — ldk_labels","text":"ldk matrix (x; y) coordinates: plot labels d far coordinates, (centroid-landmark) segment cex cex label ... additional parameters fed text","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add landmarks labels — ldk_labels","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/ldk_labels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add landmarks labels — ldk_labels","text":"","code":"coo_plot(wings[1]) ldk_labels(wings[1]) # closer and smaller coo_plot(wings[1]) ldk_labels(wings[1], d=0.05, cex=0.5)"},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws links between landmarks — ldk_links","title":"Draws links between landmarks — ldk_links","text":"Cosmetics useful visualize shape variation.","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws links between landmarks — ldk_links","text":"","code":"ldk_links(ldk, links, ...)"},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws links between landmarks — ldk_links","text":"ldk matrix (x; y) coordinates links matrix links. first column starting-id, second column ending-id (id= number coordinate) ... additional parameters fed segments","code":""},{"path":"http://momx.github.io/Momocs/reference/ldk_links.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws links between landmarks — ldk_links","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":null,"dir":"Reference","previous_headings":"","what":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"filenames consistently named character serating factors, every individual including belonging levels, e.g.: 001_speciesI_siteA_ind1_dorsalview 002_speciesI_siteA_ind2_lateralview etc., function returns data.frame can passed , Opn, Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"","code":"lf_structure(lf, names = character(), split = \"_\", trim.extension = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"lf list (names used, except list import_tps case names(lf$coo) used) list filenames, characters, typically obtained list.files. Alternatively, path folder containing files. Actually, lf length 1 (single character), function assumes path list.files . names names groups, vector characters length corresponds number groups. split character, spliting factor used file names. trim.extension logical. Whether remove last characters filenames, typically extension, e.g. '.jpg'.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"data.frame , every individual, corresponding level every group.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":"number groups must consistent across filenames.","code":""},{"path":"http://momx.github.io/Momocs/reference/lf_structure.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"bind_db.Coe <- bind_db.Coo\nExtracts structure from filenames — lf_structure","text":", view, good practice 'store' grouping structure filenames, course mandatory. Note also can: ) import_jpg save list, say 'foo'; ii) pass 'names(foo)' lf_structure. See Momocs' vignette illustration. Note function deprecated Momocs Momacs Momit fully operationnal.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates links (all pairwise combinations) between landmarks — links_all","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"Creates links (pairwise combinations) landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"","code":"links_all(coo)"},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"coo matrix (list) (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"matrix can passed ldk_links, etc. columns row ids original shape.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_all.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates links (all pairwise combinations) between landmarks — links_all","text":"","code":"w <- wings[1] coo_plot(w) links <- links_all(w) ldk_links(w, links)"},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"Creates links (Delaunay triangulation) landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"","code":"links_delaunay(coo)"},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"coo matrix (list) (x; y) coordinates","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"matrix can passed ldk_links, etc. columns row ids original shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"uses delaunayn geometry package.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/links_delaunay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates links (Delaunay triangulation) between landmarks — links_delaunay","text":"","code":"w <- wings[1] coo_plot(w, poly=FALSE) links <- links_delaunay(w) ldk_links(w, links)"},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":null,"dir":"Reference","previous_headings":"","what":"Measures shape descriptors — measure","title":"Measures shape descriptors — measure","text":"Calculates shape descriptors Coo objects. function returns scalar fed coordinates can passed naturally Momocs (pick apropos(\"coo_\")). Functions without arguments (eg coo_area) passed without brackets functions arguments (eg d) passed \"entirely\". See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Measures shape descriptors — measure","text":"","code":"measure(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Measures shape descriptors — measure","text":"x Coo object, list shapes, shape matrix. ... list functions. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Measures shape descriptors — measure","text":"TraCoe object, raw data.frame","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/measure.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Measures shape descriptors — measure","text":"","code":"bm <- measure(bot, coo_area, coo_perim) bm #> A TraCoe object -------------------- #> - $coe: 40 shapes described with 2 variables #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows bm$coe #> # A tibble: 40 × 2 #> area perim #> #> 1 234515 2482. #> 2 201056. 2269. #> 3 119460. 1578. #> 4 119568. 1817. #> 5 165736. 2066. #> 6 114015 1487. #> 7 149503 1954. #> 8 147642. 1826. #> 9 130178. 1751. #> 10 219548 2399. #> # ℹ 30 more rows # how to use arguments, eg with the d() function measure(wings, coo_area, d(1, 3), d(4, 5)) #> A TraCoe object -------------------- #> - $coe: 127 shapes described with 3 variables #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows # alternatively, to get a data_frame measure(bot$coo, coo_area, coo_perim) #> # A tibble: 40 × 2 #> area perim #> #> 1 234515 2482. #> 2 201056. 2269. #> 3 119460. 1578. #> 4 119568. 1817. #> 5 165736. 2066. #> 6 114015 1487. #> 7 149503 1954. #> 8 147642. 1826. #> 9 130178. 1751. #> 10 219548 2399. #> # ℹ 30 more rows # and also, to get a data_frame (one row) measure(bot[1], coo_area, coo_perim) #> # A tibble: 1 × 2 #> area perim #> #> 1 234515 2482."},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"Calculates nice positions plane drawing shapes","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"","code":"morphospace_positions( xy, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], nb.shp = 12, nr.shp = 6, nc.shp = 5, circle.r.shp )"},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"xy matrix points typically PCA multivariate method morphospace can calculated pos.shp shapes positionned: range xy, full extent plane, circle rosewind, xy values provided, range_axes range xy axes, full_axes thing (0.85) range axes. can also directly pass matrix (data.frame) columns named (\"x\", \"y\"). nb.shp total number shapes nr.shp number rows position shapes nc.shp number cols position shapes circle.r.shp circle, radius","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"data.frame positions","code":""},{"path":"http://momx.github.io/Momocs/reference/morphospace_positions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates nice positions on a plane for drawing shapes — morphospace_positions","text":"See plot.PCA self-speaking examples","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots mosaics of shapes. — mosaic_engine","title":"Plots mosaics of shapes. — mosaic_engine","text":"soon replace panel. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots mosaics of shapes. — mosaic_engine","text":"","code":"mosaic_engine( coo_list, dim, asp = 1, byrow = TRUE, fromtop = TRUE, sample = 60, relatively = FALSE, template_size = 0.92 ) mosaic(x, ...) # S3 method for Out mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_outlines, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... ) # S3 method for Opn mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_curves, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... ) # S3 method for Ldk mosaic( x, f, relatively = FALSE, pal = pal_qual, sample = 60, paper_fun = paper_white, draw_fun = draw_landmarks, legend = TRUE, dim = NA, asp = 1, byrow = TRUE, fromtop = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots mosaics of shapes. — mosaic_engine","text":"coo_list list shapes dim numeric length 2, desired dimensions rows columns asp numeric yx ratio used calculate dim (1 default). byrow logical whether order shapes rows fromtop logical whether order shapes top sample numeric number points coo_sample relatively logical TRUE use coo_template_relatively , FALSE(default) coo_template. words, whether preserve size . template_size numeric feed coo_template(_relatively). useful add padding around shapes default value (0.95) lowered. x Coo object ... additional arguments feed main drawer number shapes > 1000 (default: 64). non-numeric (eg FALSE) sample. f factor specification feed fac_dispatcher pal one palettes paper_fun papers function (default: paper) draw_fun one drawers pile.list legend logical whether draw legend (improved versions)","code":""},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots mosaics of shapes. — mosaic_engine","text":"list templated translated shapes","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/mosaic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots mosaics of shapes. — mosaic_engine","text":"","code":"# On Out --- bot %>% mosaic bot %>% mosaic(~type) # As with other grindr functions you can continue the pipe bot %>% mosaic(~type, asp=0.5) %>% draw_firstpoint # On Opn ---- same grammar olea %>% mosaic(~view+var, paper_fun=paper_dots) # On Ldk mosaic(wings, ~group, pal=pal_qual_Dark2, pch=3) # On Out with different sizes # would work on other Coo too shapes2 <- shapes sizes <- runif(30, 1, 2) shapes2 %>% mosaic(relatively=FALSE) shapes2 %>% mosaic(relatively=TRUE) %>% draw_centroid()"},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":null,"dir":"Reference","previous_headings":"","what":"Add new variables — mutate","title":"Add new variables — mutate","text":"Add new variables $fac. See examples ?dplyr::mutate.","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add new variables — mutate","text":"","code":"mutate(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add new variables — mutate","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add new variables — mutate","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add new variables — mutate","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/mutate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add new variables — mutate","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk mutate(olea, id=factor(1:length(olea))) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 5 classifiers (in $fac): #> # A tibble: 210 × 5 #> var domes view ind id #> #> 1 Aglan cult VD O10 1 #> 2 Aglan cult VL O10 2 #> 3 Aglan cult VD O11 3 #> 4 Aglan cult VL O11 4 #> 5 Aglan cult VD O12 5 #> 6 Aglan cult VL O12 6 #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate natural polynomial fits on open outlines — npoly","title":"Calculate natural polynomial fits on open outlines — npoly","text":"Calculates natural polynomial coefficients, linear model fit (see lm), matrix (x; y) coordinates Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate natural polynomial fits on open outlines — npoly","text":"","code":"npoly(x, ...) # S3 method for default npoly(x, degree, ...) # S3 method for Opn npoly( x, degree, baseline1 = c(-0.5, 0), baseline2 = c(0.5, 0), nb.pts = 120, ... ) # S3 method for list npoly(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate natural polynomial fits on open outlines — npoly","text":"x matrix (list) (x; y) coordinates Opn object ... useless degree polynomial degree fit (Intercept also returned) baseline1 numeric \\((x; y)\\) coordinates first baseline default \\((x= -0.5; y=0)\\) baseline2 numeric \\((x; y)\\) coordinates second baseline default \\((x= 0.5; y=0)\\) nb.pts number points sample calculate polynomials","code":""},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate natural polynomial fits on open outlines — npoly","text":"applied single shape, list components: coeff coefficients (including intercept) ortho whether orthogonal natural polynomials fitted degree degree fit (retrieved coeff though) baseline1 first baseline point (far first point) baseline2 second baseline point (far last point) r2 r2 fit mod raw lm model otherwise, OpnCoe object.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/npoly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate natural polynomial fits on open outlines — npoly","text":"","code":"data(olea) o <- olea[1] op <- opoly(o, degree=4) op #> $coeff #> (Intercept) x1 x2 x3 x4 #> 0.20937101 0.01991936 -0.95319289 -0.03075138 -0.11975200 #> #> $ortho #> [1] TRUE #> #> $degree #> [1] 4 #> #> $baseline1 #> [1] -0.5 0.0 #> #> $baseline2 #> [1] 0.5 0.0 #> #> $r2 #> [1] 0.9986415 #> #> $mod #> #> Call: #> lm(formula = coo[, 2] ~ x) #> #> Coefficients: #> (Intercept) x1 x2 x3 x4 #> 0.20937 0.01992 -0.95319 -0.03075 -0.11975 #> #> # shape reconstruction opi <- opoly_i(op) coo_plot(o) coo_draw(opi, border=\"red\") # R2 for degree 1 to 10 r <- numeric() for (i in 1:10) { r[i] <- npoly(o, degree=i)$r2 } plot(2:10, r[2:10], type='b', pch=20, col='red', main='R2 / degree')"},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate orthogonal polynomial fits on open outlines — opoly","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"Calculates orthogonal polynomial coefficients, linear model fit (see lm), matrix (x; y) coordinates Opn object","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"","code":"opoly(x, ...) # S3 method for default opoly(x, degree, ...) # S3 method for Opn opoly( x, degree, baseline1 = c(-0.5, 0), baseline2 = c(0.5, 0), nb.pts = 120, ... ) # S3 method for list opoly(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"x matrix (list) (x; y) coordinates ... useless degree polynomial degree fit (Intercept also returned) baseline1 numeric \\((x; y)\\) coordinates first baseline default \\((x= -0.5; y=0)\\) baseline2 numeric \\((x; y)\\) coordinates second baseline default \\((x= 0.5; y=0)\\) nb.pts number points sample calculate polynomials","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"list components applied single shape: coeff coefficients (including intercept) ortho whether orthogonal natural polynomials fitted degree degree fit (retrieved coeff though) baseline1 first baseline point (far first point) baseline2 second baseline point (far last point) r2 r2 fit mod raw lm model otherwise OpnCoe object.","code":""},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"Orthogonal polynomials sometimes called Legendre's polynomials. preferred natural polynomials since adding degree change lower orders coefficients.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/opoly.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate orthogonal polynomial fits on open outlines — opoly","text":"","code":"data(olea) o <- olea[1] op <- opoly(o, degree=4) op #> $coeff #> (Intercept) x1 x2 x3 x4 #> 0.20937101 0.01991936 -0.95319289 -0.03075138 -0.11975200 #> #> $ortho #> [1] TRUE #> #> $degree #> [1] 4 #> #> $baseline1 #> [1] -0.5 0.0 #> #> $baseline2 #> [1] 0.5 0.0 #> #> $r2 #> [1] 0.9986415 #> #> $mod #> #> Call: #> lm(formula = coo[, 2] ~ x) #> #> Coefficients: #> (Intercept) x1 x2 x3 x4 #> 0.20937 0.01992 -0.95319 -0.03075 -0.11975 #> #> # shape reconstruction opi <- opoly_i(op) coo_plot(o) coo_draw(opi) lines(opi, col='red') # R2 for degree 1 to 10 r <- numeric() for (i in 1:10) { r[i] <- opoly(o, degree=i)$r2 } plot(2:10, r[2:10], type='b', pch=20, col='red', main='R2 / degree')"},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":null,"dir":"Reference","previous_headings":"","what":"Partial Procrustes alignment between two shapes — pProcrustes","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"Directly borrowed Claude (2008), called pPsup .","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"","code":"pProcrustes(coo1, coo2)"},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"coo1 Configuration matrix superimposed onto centered preshape coo2. coo2 Reference configuration matrix.","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"list components coo1 superimposed centered preshape coo1 onto centered preshape coo2 coo2 centered preshape coo2 rotation rotation matrix DP partial Procrustes distance coo1 coo2 rho trigonometric Procrustes distance.","code":""},{"path":"http://momx.github.io/Momocs/reference/pProcrustes.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Partial Procrustes alignment between two shapes — pProcrustes","text":"Claude, J. (2008). Morphometrics R. Analysis (p. 316). Springer.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":null,"dir":"Reference","previous_headings":"","what":"Color palettes — palettes","title":"Color palettes — palettes","text":"colorblind friendly RColorBrewer palettes recreated without number colors limitation transparency support thanks pal_alpha can used alone. Also, viridis palettes (see package CRAN), yet color ramps borrowed Momocs depend . Also, pal_qual_solarized based Solarized: https://ethanschoonover.com/solarized/ pal_seq_grey shades grey grey10 grey90.","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Color palettes — palettes","text":"","code":"pal_alpha(cols, transp = 0) pal_manual(cols, transp = 0) pal_qual_solarized(n, transp = 0) pal_seq_grey(n, transp = 0) pal_div_BrBG(n, transp = 0) pal_div_PiYG(n, transp = 0) pal_div_PRGn(n, transp = 0) pal_div_PuOr(n, transp = 0) pal_div_RdBu(n, transp = 0) pal_div_RdYlBu(n, transp = 0) pal_qual_Dark2(n, transp = 0) pal_qual_Paired(n, transp = 0) pal_qual_Set2(n, transp = 0) pal_seq_Blues(n, transp = 0) pal_seq_BuGn(n, transp = 0) pal_seq_BuPu(n, transp = 0) pal_seq_GnBu(n, transp = 0) pal_seq_Greens(n, transp = 0) pal_seq_Greys(n, transp = 0) pal_seq_Oranges(n, transp = 0) pal_seq_OrRd(n, transp = 0) pal_seq_PuBu(n, transp = 0) pal_seq_PuBuGn(n, transp = 0) pal_seq_PuRd(n, transp = 0) pal_seq_Purples(n, transp = 0) pal_seq_RdPu(n, transp = 0) pal_seq_Reds(n, transp = 0) pal_seq_YlGn(n, transp = 0) pal_seq_YlGnBu(n, transp = 0) pal_seq_YlOrBr(n, transp = 0) pal_seq_YlOrRd(n, transp = 0) pal_seq_magma(n, transp = 0) pal_seq_inferno(n, transp = 0) pal_seq_plasma(n, transp = 0) pal_seq_viridis(n, transp = 0) pal_qual(n, transp = 0) pal_seq(n, transp = 0) pal_div(n, transp = 0)"},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Color palettes — palettes","text":"cols color(s) hexadecimal values transp numeric 0 1 (0, eg opaque, default) n numeric number colors","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Color palettes — palettes","text":"palette function","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Color palettes — palettes","text":"Default color palettes currently: pal_qual=pal_qual_Set2 pal_seq=pal_seq_viridis pal_div=pal_div_RdBu","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Color palettes — palettes","text":"RColorBrewer palettes happy n lower 3 given number palette. case, functions create color palette colorRampPalette return colors even .","code":""},{"path":"http://momx.github.io/Momocs/reference/palettes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Color palettes — palettes","text":"","code":"pal_div_BrBG(5) %>% barplot(rep(1, 5), col=.) pal_div_BrBG(5, 0.5) %>% barplot(rep(1, 5), col=.)"},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Family picture of shapes — panel","title":"Family picture of shapes — panel","text":"Plots outlines, side side, Coo (, Opn Ldk) objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family picture of shapes — panel","text":"","code":"panel(x, ...) # S3 method for Out panel( x, dim, cols, borders, fac, palette = col_summer, coo_sample = 120, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col, ... ) # S3 method for Opn panel( x, cols, borders, fac, palette = col_summer, coo_sample = 120, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col, ... ) # S3 method for Ldk panel( x, cols, borders, fac, palette = col_summer, names = NULL, cex.names = 0.6, points = TRUE, points.pch = 3, points.cex = 0.2, points.col = \"#333333\", ... )"},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family picture of shapes — panel","text":"x Coo object plot. ... additional arguments feed generic plot dim coo_listpanel: numeric length 2 specifying dimensions panel cols vector colors drawing outlines. Either single value length exactly equal number coordinates. borders vector colors drawing borders. Either single value length exactly equals number coordinates. fac factor within $fac slot colors palette color palette coo_sample NULL number point per shape display (plot quickly) names whether plot names . TRUE uses shape names, something fac_dispatcher cex.names cex names points logical (Ldk) whether draw points points.pch (Ldk) pch points points.cex (Ldk) cex points points.col (Ldk) col points","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family picture of shapes — panel","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Family picture of shapes — panel","text":"want reorder shapes according factor, use arrange.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/panel.Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family picture of shapes — panel","text":"","code":"panel(mosquito, names=TRUE, cex.names=0.5) panel(olea) panel(bot, c(4, 10)) # an illustration of the use of fac panel(bot, fac='type', palette=col_spring, names=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":null,"dir":"Reference","previous_headings":"","what":"grindr papers for shape plots — papers","title":"grindr papers for shape plots — papers","text":"Papers use drawers building custom shape plots using grindr approach. See examples vignettes.","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"grindr papers for shape plots — papers","text":"","code":"paper(coo, ...) paper_white(coo) paper_grid(coo, grid = c(10, 5), cols = c(\"#ffa500\", \"#e5e5e5\"), ...) paper_chess(coo, n = 50, col = \"#E5E5E5\") paper_dots(coo, pch = 20, n = 50, col = \"#7F7F7F\")"},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"grindr papers for shape plots — papers","text":"coo single shape Coo object ... arguments feed plotting function within paper function grid numeric length 2 (roughly) specify number majors lines, number minor lines within two major ones cols colors (hexadecimal preferred) use grid drawing n numeric number squares chessboard col color (hexadecimal) use chessboard drawing pch use dots","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"grindr papers for shape plots — papers","text":"drawing layer","code":""},{"path":"http://momx.github.io/Momocs/reference/papers.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"grindr papers for shape plots — papers","text":"approach (soon) replace coo_plot friends versions. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":null,"dir":"Reference","previous_headings":"","what":"Permutes and breed Coe (and others) objects — perm","title":"Permutes and breed Coe (and others) objects — perm","text":"methods applies permutations column-wise coe Coe object relies function can used matrix. Coe object, uses sample every column (row) (without) replacement.","code":""},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Permutes and breed Coe (and others) objects — perm","text":"","code":"perm(x, ...) # S3 method for default perm(x, margin = 2, size, replace = TRUE, ...) # S3 method for Coe perm(x, size, replace = TRUE, ...)"},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Permutes and breed Coe (and others) objects — perm","text":"x object permute ... useless margin numeric whether 1 2 (rows columns) size numeric required size final object, size default. replace logical, whether use sample replacement","code":""},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Permutes and breed Coe (and others) objects — perm","text":"Coe object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/perm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Permutes and breed Coe (and others) objects — perm","text":"","code":"m <- matrix(1:12, nrow=3) m #> [,1] [,2] [,3] [,4] #> [1,] 1 4 7 10 #> [2,] 2 5 8 11 #> [3,] 3 6 9 12 perm(m, margin=2, size=5) #> [,1] [,2] [,3] [,4] #> [1,] 3 4 9 11 #> [2,] 1 6 8 12 #> [3,] 3 5 7 11 #> [4,] 1 6 9 12 #> [5,] 3 4 8 12 perm(m, margin=1, size=10) #> [,1] [,2] [,3] #> [1,] 1 2 9 #> [2,] 10 8 3 #> [3,] 10 5 3 #> [4,] 10 11 6 #> [5,] 1 5 9 #> [6,] 4 5 9 #> [7,] 1 8 6 #> [8,] 7 11 3 #> [9,] 7 2 12 #> [10,] 4 8 3 bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.m <- perm(bot.f, 80) bot.m #> An OutCoe object [ elliptical Fourier analysis ] #> -------------------- #> - $coe: 80 outlines described, 12 harmonics #> # A tibble: 0 × 0"},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":null,"dir":"Reference","previous_headings":"","what":"Graphical pile of shapes — pile","title":"Graphical pile of shapes — pile","text":"Pile shapes graphical window. Useful check normalization terms size, position, rotation, first point, etc. , essentially, shortcut around paper + drawers grindr family.","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Graphical pile of shapes — pile","text":"","code":"pile(coo, f, sample, subset, pal, paper_fun, draw_fun, transp, ...) # S3 method for default pile( coo, f, sample, subset, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for list pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for array pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_landmarks, transp = 0, ... ) # S3 method for Out pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_outlines, transp = 0, ... ) # S3 method for Opn pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_curves, transp = 0, ... ) # S3 method for Ldk pile( coo, f, sample = 64, subset = 1000, pal = pal_qual, paper_fun = paper, draw_fun = draw_landmarks, transp = 0, ... )"},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Graphical pile of shapes — pile","text":"coo single shape Coo object f factor specification sample numeric number points coo_sample number shapes > 1000 (default: 64). non-numeric (eg FALSE) sample. subset numeric draw number (randomly chosen) shapes number shapes > 1000 (default: 1000) non-numeric (eg FALSE) sample. pal palette among palettes (default: pal_qual) paper_fun papers function (default: paper) draw_fun one drawers pile.list transp numeric transparency (default:adjusted, min:0, max=0) ... arguments feed core drawer, depending object","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Graphical pile of shapes — pile","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Graphical pile of shapes — pile","text":"Large Coo sampled, terms number shapes points drawn.","code":""},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Graphical pile of shapes — pile","text":"variation plot called stack Momocs 1.2.5","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/pile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Graphical pile of shapes — pile","text":"","code":"# all Coo are supported with sensible defaults pile(bot) # outlines pile(olea, ~var, pal=pal_qual_Dark2, paper_fun=paper_grid) # curves pile(wings) # landmarks # you can continue the pipe with compatible drawers pile(bot, trans=0.9) %>% draw_centroid # if you are not happy with this, build your own ! # eg see Momocs::pile.Out (no quotes) my_pile <- function(x, col_labels=\"red\", transp=0.5){ x %>% paper_chess(n=100) %>% draw_landmarks(transp=transp) %>% draw_labels(col=col_labels) } # using it wings %>% my_pile(transp=3/4) # and as gridr functions propagate, you can even continue: wings %>% my_pile() %>% draw_centroid(col=\"blue\", cex=5) # method on lists bot$coo %>% pile # it can be tuned when we have a list of landmarks with: wings$coo %>% pile(draw_fun=draw_landmarks) # or on arrays (turn for draw_landmarks) wings$coo %>% l2a %>% #we now have an array pile"},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots Linear Discriminant Analysis — plot.LDA","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Momocs' LDA plotter many graphical options.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"","code":"# S3 method for LDA plot( x, fac = x$fac, xax = 1, yax = 2, points = TRUE, col = \"#000000\", pch = 20, cex = 0.5, palette = col_solarized, center.origin = FALSE, zoom = 1, xlim = NULL, ylim = NULL, bg = par(\"bg\"), grid = TRUE, nb.grids = 3, morphospace = FALSE, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], amp.shp = 1, size.shp = 1, nb.shp = 12, nr.shp = 6, nc.shp = 5, rotate.shp = 0, flipx.shp = FALSE, flipy.shp = FALSE, pts.shp = 60, border.shp = col_alpha(\"#000000\", 0.5), lwd.shp = 1, col.shp = col_alpha(\"#000000\", 0.95), stars = FALSE, ellipses = FALSE, conf.ellipses = 0.5, ellipsesax = TRUE, conf.ellipsesax = c(0.5, 0.9), lty.ellipsesax = 1, lwd.ellipsesax = sqrt(2), chull = FALSE, chull.lty = 1, chull.filled = FALSE, chull.filled.alpha = 0.92, density = FALSE, lev.density = 20, contour = FALSE, lev.contour = 3, n.kde2d = 100, delaunay = FALSE, loadings = FALSE, labelspoints = FALSE, col.labelspoints = par(\"fg\"), cex.labelspoints = 0.6, abbreviate.labelspoints = TRUE, labelsgroups = TRUE, cex.labelsgroups = 0.8, rect.labelsgroups = FALSE, abbreviate.labelsgroups = FALSE, color.legend = FALSE, axisnames = TRUE, axisvar = TRUE, unit = FALSE, eigen = TRUE, rug = TRUE, title = substitute(x), box = TRUE, old.par = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"x object class \"LDA\", typically obtained LDA fac name column id $fac slot, formula combining colum names $fac slot (cf. examples). factor numeric length can also passed fly. xax first PC axis yax second PC axis points logical whether plot points col color points (either global, every level fac every individual, see examples) pch pch points (either global, every level fac every individual, see examples) cex size points palette palette center.origin logical whether center plot onto origin zoom keep distances xlim numeric length two ; provided along ylim, x y lims use ylim numeric length two ; provided along xlim, x y lims use bg color background grid logical whether draw grid nb.grids many morphospace logical whether add morphological space pos.shp passed morphospace_positions, one \"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\". directly matrix positions. See morphospace_positions amp.shp amplification factor shape deformation size.shp size shapes nb.shp (pos.shp=\"circle\") number shapes compass nr.shp (pos.shp=\"full\" \"range) number shapes per row nc.shp (pos.shp=\"full\" \"range) number shapes per column rotate.shp angle radians rotate shapes (several methods, vector angles) flipx.shp , whether apply coo_flipx flipy.shp , whether apply coo_flipy pts.shp number points fro drawing shapes border.shp border color shapes lwd.shp line width shapes col.shp color shapes stars logical whether draw \"stars\" ellipses logical whether draw confidence ellipses conf.ellipses numeric quantile (bivariate gaussian) confidence ellipses ellipsesax logical whether draw ellipse axes conf.ellipsesax one numeric, quantiles (bivariate gaussian) ellipses axes lty.ellipsesax yes, lty draw axes lwd.ellipsesax yes, one numeric line widths chull logical whether draw convex hull chull.lty yes, linetype chull.filled logical whether add filled convex hulls chull.filled.alpha numeric alpha transparency density whether add 2d density kernel estimation (based kde2d) lev.density yes, number levels plot (image) contour whether add contour lines based 2d density kernel lev.contour yes, (approximate) number lines draw n.kde2d number bins kde2d, ie 'smoothness' density kernel delaunay logical whether add delaunay 'mesh' points loadings logical whether add loadings every variables labelspoints TRUE rownames used labels, colname $fac can also passed col.labelspoints color labels, otherwise inherited fac cex.labelspoints cex labels abbreviate.labelspoints logical whether abbreviate labelsgroups logical whether add labels groups cex.labelsgroups ifyes, numeric size labels rect.labelsgroups logical whether add rectangle behind groups names abbreviate.labelsgroups logical, whether abbreviate group names color.legend logical whether add (cheap) color legend numeric fac axisnames logical whether add PC names axisvar logical whether draw variance explain unit logical whether add plane unit eigen logical whether draw plot eigen values rug logical whether add rug margins title character name plot box whether draw box around plotting region old.par whether restore old par. Set FALSE want reuse graphical window. ... useless , just fit generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Widely inspired \"layers\" philosophy behind graphical functions ade4 R package.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots Linear Discriminant Analysis — plot.LDA","text":"Morphospaces deprecated far. 99% code shared plot.PCA waiting general rewriting multivariate plotter. See https://github.com/vbonhomme/Momocs/issues/121","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots Principal Component Analysis — plot.PCA","title":"Plots Principal Component Analysis — plot.PCA","text":"Momocs' PCA plotter morphospaces many graphical options.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots Principal Component Analysis — plot.PCA","text":"","code":"# S3 method for PCA plot( x, fac, xax = 1, yax = 2, points = TRUE, col = \"#000000\", pch = 20, cex = 0.5, palette = col_solarized, center.origin = FALSE, zoom = 1, xlim = NULL, ylim = NULL, bg = par(\"bg\"), grid = TRUE, nb.grids = 3, morphospace = TRUE, pos.shp = c(\"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\")[1], amp.shp = 1, size.shp = 1, nb.shp = 12, nr.shp = 6, nc.shp = 5, rotate.shp = 0, flipx.shp = FALSE, flipy.shp = FALSE, pts.shp = 60, border.shp = col_alpha(\"#000000\", 0.5), lwd.shp = 1, col.shp = col_alpha(\"#000000\", 0.95), stars = FALSE, ellipses = FALSE, conf.ellipses = 0.5, ellipsesax = FALSE, conf.ellipsesax = c(0.5, 0.9), lty.ellipsesax = 1, lwd.ellipsesax = sqrt(2), chull = FALSE, chull.lty = 1, chull.filled = TRUE, chull.filled.alpha = 0.92, density = FALSE, lev.density = 20, contour = FALSE, lev.contour = 3, n.kde2d = 100, delaunay = FALSE, loadings = FALSE, labelspoints = FALSE, col.labelspoints = par(\"fg\"), cex.labelspoints = 0.6, abbreviate.labelspoints = TRUE, labelsgroups = TRUE, cex.labelsgroups = 0.8, rect.labelsgroups = FALSE, abbreviate.labelsgroups = FALSE, color.legend = FALSE, axisnames = TRUE, axisvar = TRUE, unit = FALSE, eigen = TRUE, rug = TRUE, title = substitute(x), box = TRUE, old.par = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots Principal Component Analysis — plot.PCA","text":"x PCA, typically obtained PCA fac name column id $fac slot, formula combining colum names $fac slot (cf. examples). factor numeric length can also passed fly. xax first PC axis yax second PC axis points logical whether plot points col color points (either global, every level fac every individual, see examples) pch pch points (either global, every level fac every individual, see examples) cex size points palette palette center.origin logical whether center plot onto origin zoom keep distances xlim numeric length two ; provided along ylim, x y lims use ylim numeric length two ; provided along xlim, x y lims use bg color background grid logical whether draw grid nb.grids many morphospace logical whether add morphological space pos.shp passed morphospace_positions, one \"range\", \"full\", \"circle\", \"xy\", \"range_axes\", \"full_axes\". directly matrix positions. See morphospace_positions amp.shp amplification factor shape deformation size.shp size shapes nb.shp (pos.shp=\"circle\") number shapes compass nr.shp (pos.shp=\"full\" \"range) number shapes per row nc.shp (pos.shp=\"full\" \"range) number shapes per column rotate.shp angle radians rotate shapes (several methods, vector angles) flipx.shp , whether apply coo_flipx flipy.shp , whether apply coo_flipy pts.shp number points fro drawing shapes border.shp border color shapes lwd.shp line width shapes col.shp color shapes stars logical whether draw \"stars\" ellipses logical whether draw confidence ellipses conf.ellipses numeric quantile (bivariate gaussian) confidence ellipses ellipsesax logical whether draw ellipse axes conf.ellipsesax one numeric, quantiles (bivariate gaussian) ellipses axes lty.ellipsesax yes, lty draw axes lwd.ellipsesax yes, one numeric line widths chull logical whether draw convex hull chull.lty yes, linetype chull.filled logical whether add filled convex hulls chull.filled.alpha numeric alpha transparency density whether add 2d density kernel estimation (based kde2d) lev.density yes, number levels plot (image) contour whether add contour lines based 2d density kernel lev.contour yes, (approximate) number lines draw n.kde2d number bins kde2d, ie 'smoothness' density kernel delaunay logical whether add delaunay 'mesh' points loadings logical whether add loadings every variables labelspoints TRUE rownames used labels, colname $fac can also passed col.labelspoints color labels, otherwise inherited fac cex.labelspoints cex labels abbreviate.labelspoints logical whether abbreviate labelsgroups logical whether add labels groups cex.labelsgroups ifyes, numeric size labels rect.labelsgroups logical whether add rectangle behind groups names abbreviate.labelsgroups logical, whether abbreviate group names color.legend logical whether add (cheap) color legend numeric fac axisnames logical whether add PC names axisvar logical whether draw variance explain unit logical whether add plane unit eigen logical whether draw plot eigen values rug logical whether add rug margins title character name plot box whether draw box around plotting region old.par whether restore old par. Set FALSE want reuse graphical window. ... useless , just fit generic plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots Principal Component Analysis — plot.PCA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plots Principal Component Analysis — plot.PCA","text":"Widely inspired \"layers\" philosophy behind graphical functions ade4 R package.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots Principal Component Analysis — plot.PCA","text":"NAs $fac handled quite experimentally. importantly, early 2018, plan complete rewrite plot.PCA multivariate plotters.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot.PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots Principal Component Analysis — plot.PCA","text":"","code":"# \\donttest{ bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot.p <- PCA(bot.f) ### Morphospace options plot(bot.p, pos.shp=\"full\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"range\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"xy\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"circle\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"range_axes\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, pos.shp=\"full_axes\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA ### Passing factors to plot.PCA # 3 equivalent methods plot(bot.p, \"type\") #> will be deprecated soon, see ?plot_PCA plot(bot.p, 1) #> will be deprecated soon, see ?plot_PCA plot(bot.p, ~type) #> will be deprecated soon, see ?plot_PCA # let's create a dummy factor of the correct length # and another added to the $fac with mutate # and a numeric of the correct length f <- factor(rep(letters[1:2], 20)) z <- factor(rep(LETTERS[1:2], 20)) bot %<>% mutate(cs=coo_centsize(.), z=z) bp <- bot %>% efourier %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) # so bp contains type, cs (numeric) and z; not f # yet f can be passed on the fly plot(bp, f) #> will be deprecated soon, see ?plot_PCA # numeric fac are allowed plot(bp, \"cs\", cex=3, color.legend=TRUE) #> will be deprecated soon, see ?plot_PCA # formula allows combinations of factors plot(bp, ~type+z) #> will be deprecated soon, see ?plot_PCA ### other morphometric approaches works the same # open curves op <- npoly(olea, 5) #> 'nb.pts' missing and set to: 91 op.p <- PCA(op) op.p #> A PCA object #> -------------------- #> - 210 shapes #> - $method: [ npoly analysis ] #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, mod, baseline1, baseline2, cuts. plot(op.p, ~ domes + var, morpho=TRUE) # use of formula #> will be deprecated soon, see ?plot_PCA # landmarks wp <- fgProcrustes(wings, tol=1e-4) #> iteration: 1 \tgain: 53084 #> iteration: 2 \tgain: 0.1323 #> iteration: 3 \tgain: 0.056732 #> iteration: 4 \tgain: 0.00012401 #> iteration: 5 \tgain: 0.038609 #> iteration: 6 \tgain: 0.018221 #> iteration: 7 \tgain: 0.0014165 #> iteration: 8 \tgain: 6.1489e-06 wpp <- PCA(wp) wpp #> A PCA object #> -------------------- #> - 127 shapes #> - $method: [ procrustes analysis ] #> # A tibble: 127 × 1 #> group #> #> 1 AN #> 2 AN #> 3 AN #> 4 AN #> 5 AN #> 6 AN #> # ℹ 121 more rows #> - All components: sdev, rotation, center, scale, x, eig, fac, mshape, method, cuts, links. plot(wpp, 1) #> will be deprecated soon, see ?plot_PCA ### Cosmetic options # window plot(bp, 1, zoom=2) #> will be deprecated soon, see ?plot_PCA plot(bp, zoom=0.5) #> will be deprecated soon, see ?plot_PCA plot(bp, center.origin=FALSE, grid=FALSE) #> will be deprecated soon, see ?plot_PCA # colors plot(bp, col=\"red\") # globally #> will be deprecated soon, see ?plot_PCA plot(bp, 1, col=c(\"#00FF00\", \"#0000FF\")) # for every level #> will be deprecated soon, see ?plot_PCA # a color vector of the right length plot(bp, 1, col=rep(c(\"#00FF00\", \"#0000FF\"), each=20)) #> will be deprecated soon, see ?plot_PCA # a color vector of the right length, mixign Rcolor names (not a good idea though) plot(bp, 1, col=rep(c(\"#00FF00\", \"forestgreen\"), each=20)) #> will be deprecated soon, see ?plot_PCA # ellipses plot(bp, 1, conf.ellipsesax=2/3) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, ellipsesax=FALSE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, ellipsesax=TRUE, ellipses=TRUE) #> will be deprecated soon, see ?plot_PCA # stars plot(bp, 1, stars=TRUE, ellipsesax=FALSE) #> will be deprecated soon, see ?plot_PCA # convex hulls plot(bp, 1, chull=TRUE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, chull.lty=3) #> will be deprecated soon, see ?plot_PCA # filled convex hulls plot(bp, 1, chull.filled=TRUE) #> will be deprecated soon, see ?plot_PCA plot(bp, 1, chull.filled.alpha = 0.8, chull.lty =1) # you can omit chull.filled=TRUE #> will be deprecated soon, see ?plot_PCA # density kernel plot(bp, 1, density=TRUE, contour=TRUE, lev.contour=10) #> will be deprecated soon, see ?plot_PCA # delaunay plot(bp, 1, delaunay=TRUE) #> will be deprecated soon, see ?plot_PCA # loadings flower %>% PCA %>% plot(1, loadings=TRUE) #> will be deprecated soon, see ?plot_PCA # point/group labelling plot(bp, 1, labelspoint=TRUE) # see options for abbreviations #> will be deprecated soon, see ?plot_PCA plot(bp, 1, labelsgroup=TRUE) # see options for abbreviations #> will be deprecated soon, see ?plot_PCA # clean axes, no rug, no border, random title plot(bp, axisvar=FALSE, axisnames=FALSE, rug=FALSE, box=FALSE, title=\"random\") #> will be deprecated soon, see ?plot_PCA # no eigen plot(bp, eigen=FALSE) # eigen cause troubles to graphical window #> will be deprecated soon, see ?plot_PCA # eigen may causes troubles to the graphical window. you can try old.par = TRUE # }"},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a cross-validation table as an heatmap — plot_CV","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"Either frequencies (percentages) plus marginal sums, values heatmaps. Used Momocs plotting cross-validation tables may used table (likely freq=FALSE).","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"","code":"plot_CV( x, freq = FALSE, rm0 = FALSE, pc = FALSE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... ) # S3 method for default plot_CV( x, freq = FALSE, rm0 = FALSE, pc = FALSE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... ) # S3 method for LDA plot_CV( x, freq = TRUE, rm0 = TRUE, pc = TRUE, fill = TRUE, labels = TRUE, axis.size = 10, axis.x.angle = 45, cell.size = 2.5, signif = 2, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"x (cross-validation table) LDA object freq logical whether display frequencies (within actual class) counts rm0 logical whether remove zeros pc logical whether multiply proportion 100, ie display percentages fill logical whether fill cell according count/freq labels logical whether add text labels cells axis.size numeric adjust axis labels axis.x.angle numeric rotate x-axis labels cell.size numeric adjust text labels cells signif numeric round frequencies using signif ... useless ","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"ggplot object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_CV.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a cross-validation table as an heatmap — plot_CV","text":"","code":"h <- hearts %>% fgProcrustes(0.01) %>% coo_slide(ldk=2) %T>% stack %>% efourier(6, norm=FALSE) %>% LDA(~aut) #> iteration: 1 \tgain: 30322 #> iteration: 2 \tgain: 1.2498 #> iteration: 3 \tgain: 0.34194 #> iteration: 4 \tgain: 0.0062954 h %>% plot_CV() #> Warning: The `` argument of `guides()` cannot be `FALSE`. Use \"none\" instead as #> of ggplot2 3.3.4. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . h %>% plot_CV(freq=FALSE, rm0=FALSE, fill=FALSE) # you can customize the returned gg with some ggplot2 functions h %>% plot_CV(labels=FALSE, fill=TRUE, axis.size=5) + ggplot2::ggtitle(\"A confusion matrix\") # or build your own using the prepared data_frame: df <- h %>% plot_CV() %$% data df #> # A tibble: 34 × 4 #> actual predicted n actual2 #> #> 1 ced ced 0.77 ced #> 2 ced mat 0.1 ced #> 3 ced rom 0.067 ced #> 4 ced vince 0.067 ced #> 5 jeya jeya 0.87 jeya #> 6 jeya ponnu 0.067 jeya #> 7 jeya vince 0.067 jeya #> 8 mat ced 0.033 mat #> 9 mat jeya 0.1 mat #> 10 mat mat 0.47 mat #> # ℹ 24 more rows # you can even use it as a cross-table plotter bot$fac %>% table %>% plot_CV()"},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots a cross-correlation table — plot_CV2","title":"Plots a cross-correlation table — plot_CV2","text":"contingency/confusion table. simple graphic representation based variable width /color arrows segments, based relative frequencies.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots a cross-correlation table — plot_CV2","text":"","code":"plot_CV2(x, ...) # S3 method for LDA plot_CV2(x, ...) # S3 method for table plot_CV2( x, links.FUN = arrows, col = TRUE, col0 = \"black\", col.breaks = 5, palette = col_heat, lwd = TRUE, lwd0 = 5, gap.dots = 0.2, pch.dots = 20, gap.names = 0.25, cex.names = 1, legend = TRUE, ... )"},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots a cross-correlation table — plot_CV2","text":"x LDA object, table squared matrix ... useless . links.FUN function draw links: eg segments (default), arrows, etc. col logical whether vary color links col0 color default link (col = FALSE) col.breaks number different colors palette color palette, eg col_summer, col_hot, etc. lwd logical whether vary width links lwd0 width default link (lwd = FALSE) gap.dots numeric set space dots links pch.dots pch dots gap.names numeric set space dots group names cex.names cex names legend logical whether add legend","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots a cross-correlation table — plot_CV2","text":"ggplot2 object","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Plots a cross-correlation table — plot_CV2","text":"freq=FALSE, fill colors weighted within actual classes displayed classes sizes balanced.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_CV2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots a cross-correlation table — plot_CV2","text":"","code":"# Below various table that you can try. We will use the last one for the examples. #pure random a <- sample(rep(letters[1:4], each=10)) b <- sample(rep(letters[1:4], each=10)) tab <- table(a, b) # veryhuge + some structure a <- sample(rep(letters[1:10], each=10)) b <- sample(rep(letters[1:10], each=10)) tab <- table(a, b) diag(tab) <- round(runif(10, 10, 20)) tab <- matrix(c(8, 3, 1, 0, 0, 2, 7, 1, 2, 3, 3, 5, 9, 1, 1, 1, 1, 2, 7, 1, 0, 9, 1, 4, 5), 5, 5, byrow=TRUE) tab <- as.table(tab) # good prediction tab <- matrix(c(8, 1, 1, 0, 0, 1, 7, 1, 0, 0, 1, 2, 9, 1, 0, 1, 1, 1, 7, 1, 0, 0, 0, 1, 8), 5, 5, byrow=TRUE) tab <- as.table(tab) plot_CV2(tab) plot_CV2(tab, arrows) # if you prefer arrows plot_CV2(tab, lwd=FALSE, lwd0=1, palette=col_india) # if you like india but not lwds plot_CV2(tab, col=FALSE, col0='pink') # only lwd plot_CV2(tab, col=FALSE, lwd0=10, cex.names=2) # if you're getting old plot_CV2(tab, col=FALSE, lwd=FALSE) # pretty but useless plot_CV2(tab, col.breaks=2) # if you think it's either good or bad plot_CV2(tab, pch=NA) # if you do not like dots plot_CV2(tab, gap.dots=0) # if you want to 'fill the gap' plot_CV2(tab, gap.dots=1) # or not #trilo examples trilo.f <- efourier(trilo, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details trilo.l <- LDA(PCA(trilo.f), 'onto') #> 8 PC retained trilo.l #> * Cross-validation table ($CV.tab): #> classified #> actual a b c d #> a 0 5 2 0 #> b 3 12 1 0 #> c 0 3 11 4 #> d 0 0 3 6 #> #> * Class accuracy ($CV.ce): #> a b c d #> 0.0000000 0.7500000 0.6111111 0.6666667 #> #> * Leave-one-out cross-validation ($CV.correct): (58% - 29/50): plot_CV2(trilo.l) # olea example op <- opoly(olea, 5) #> 'nb.pts' missing and set to 91 opl <- LDA(PCA(op), 'var') #> 4 PC retained plot_CV2(opl)"},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":null,"dir":"Reference","previous_headings":"","what":"LDA plot using grindr layers — plot_LDA","title":"LDA plot using grindr layers — plot_LDA","text":"Quickly vizualise LDA objects build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"LDA plot using grindr layers — plot_LDA","text":"","code":"plot_LDA( x, axes = c(1, 2), palette = pal_qual, points = TRUE, points_transp = 1/4, morphospace = FALSE, morphospace_position = \"range\", chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", center_origin = TRUE, zoom = 0.9, eigen = TRUE, box = TRUE, iftwo_layer = layer_histogram_2, iftwo_split = FALSE, axesnames = TRUE, axesvar = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"LDA plot using grindr layers — plot_LDA","text":"x LDA object axes numeric length two select PCs use (c(1, 2) default) palette color palette use col_summer default points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) morphospace logical whether draw using layer_morphospace_PCA morphospace_position feed layer_morphospace_PCA (default: \"range\") chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") center_origin logical whether center origin zoom numeric zoom level frame (default: 0.9) eigen logical whether draw using layer_eigen box logical whether draw using layer_box iftwo_layer function (quotes) drawing LD1 two levels. far, one layer_histogram_2 (default) layer_density_2 iftwo_split feed split argument layer_histogram_2 layer_density_2 axesnames logical whether draw using layer_axesnames axesvar logical whether draw using layer_axesvar","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"LDA plot using grindr layers — plot_LDA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"LDA plot using grindr layers — plot_LDA","text":"approach replace plot.LDA. part grindr approach may packaged point. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_LDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"LDA plot using grindr layers — plot_LDA","text":"","code":"### First prepare an LDA object # Some outlines with bot bl <- bot %>% # cheap alignement before efourier coo_align() %>% coo_center %>% coo_slidedirection(\"left\") %>% # add a fake column mutate(fake=sample(letters[1:5], 40, replace=TRUE)) %>% # EFT efourier(6, norm=FALSE) %>% # LDA LDA(~fake) #> factor passed was a character, and coerced to a factor. bl %>% plot_LDA %>% layer_morphospace_LDA #> * layer_morphospace_LDA is back, but experimental # Below inherited from plot_PCA and to adapt here. #plot_PCA(bp) #plot_PCA(bp, ~type) #plot_PCA(bp, ~fake) # Some curves with olea #op <- olea %>% #mutate(s=coo_area(.)) %>% #filter(var != \"Cypre\") %>% #chop(~view) %>% lapply(opoly, 5, nb.pts=90) %>% #combine %>% PCA #op$fac$s %<>% as.character() %>% as.numeric() #op %>% plot_PCA(title=\"hi there!\") ### Now we can play with layers # and for instance build a custom plot # it should start with plot_PCA() #my_plot <- function(x, ...){ #x %>% # plot_PCA(...) %>% # layer_points %>% # layer_ellipsesaxes %>% # layer_rug # } # and even continue after this function # op %>% my_plot(~var, axes=c(1, 3)) %>% # layer_title(\"hi there!\") %>% # layer_stars() # You get the idea."},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":null,"dir":"Reference","previous_headings":"","what":"Pairwise comparison of a list of shapes — plot_MSHAPES","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"\"Confusion matrix\" list shapes. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"","code":"plot_MSHAPES(x, draw_fun, size, palette)"},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"x list shapes (eg returned MSHAPES) draw_fun one draw_outline, draw_curves, draw_landmarks. result MSHAPES passed, detected based $Coe, otherwise default draw_curves. size numeric shrinking factor shapes (coo_template; 3/4 default) palette palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"Directly inspired Chitwood et al. (2016) New Phytologist","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_MSHAPES.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Pairwise comparison of a list of shapes — plot_MSHAPES","text":"","code":"x <- bot %>% efourier(6) %>% MSHAPES(~type) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # custom colors x %>% plot_MSHAPES(palette=pal_manual(c(\"darkgreen\", \"orange\"))) # also works on list of shapes, eg: leaves <- shapes %>% slice(grep(\"leaf\", names(shapes))) %$% coo class(leaves) #> [1] \"list\" leaves %>% plot_MSHAPES() # or shapes %>% # subset and degrade slice(1:12) %>% coo_sample(60) %$% # grab the coo coo %>% plot_MSHAPES()"},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":null,"dir":"Reference","previous_headings":"","what":"NMDS plot unsing grindr layers — plot_NMDS","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"Quickly vizualise MDS NMDS objects build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"","code":"plot_NMDS( x, f = NULL, axes = c(1, 2), points = TRUE, points_transp = 1/4, chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", box = TRUE, axesnames = TRUE, palette = pal_qual ) plot_MDS( x, f = NULL, axes = c(1, 2), points = TRUE, points_transp = 1/4, chull = TRUE, chullfilled = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", box = TRUE, axesnames = TRUE, palette = pal_qual )"},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"x result MDS NMDS f factor specification feed fac_dispatcher axes numeric length two select PCs use (c(1, 2) default) points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") box logical whether draw using layer_box axesnames logical whether draw using layer_axesnames palette color palette use col_summer default","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_NMDS.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"NMDS plot unsing grindr layers — plot_NMDS","text":"","code":"### First prepare an NMDS object x <- bot %>% efourier %>% NMDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) #> 'comm' has negative data: 'autotransform', 'noshare' and 'wascores' set to FALSE #> Warning: results may be meaningless because data have negative entries #> in method “bray” #> Run 0 stress 0.07227125 #> Run 1 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 5.165599e-06 max resid 1.848616e-05 #> ... Similar to previous best #> Run 2 stress 0.07227125 #> ... New best solution #> ... Procrustes: rmse 1.848561e-06 max resid 7.686046e-06 #> ... Similar to previous best #> Run 3 stress 0.1610098 #> Run 4 stress 0.07227125 #> ... Procrustes: rmse 6.814352e-06 max resid 2.80386e-05 #> ... Similar to previous best #> Run 5 stress 0.07227125 #> ... Procrustes: rmse 8.042268e-06 max resid 3.293377e-05 #> ... Similar to previous best #> Run 6 stress 0.07227125 #> ... Procrustes: rmse 2.510741e-06 max resid 7.634959e-06 #> ... Similar to previous best #> Run 7 stress 0.1660041 #> Run 8 stress 0.07227125 #> ... Procrustes: rmse 1.181586e-06 max resid 3.464235e-06 #> ... Similar to previous best #> Run 9 stress 0.1642555 #> Run 10 stress 0.07227125 #> ... Procrustes: rmse 5.427893e-06 max resid 2.018695e-05 #> ... Similar to previous best #> Run 11 stress 0.07227125 #> ... Procrustes: rmse 1.396985e-06 max resid 6.777242e-06 #> ... Similar to previous best #> Run 12 stress 0.07227125 #> ... Procrustes: rmse 5.297107e-06 max resid 2.060719e-05 #> ... Similar to previous best #> Run 13 stress 0.07227125 #> ... Procrustes: rmse 5.87307e-06 max resid 2.1449e-05 #> ... Similar to previous best #> Run 14 stress 0.1660723 #> Run 15 stress 0.07227125 #> ... Procrustes: rmse 8.005086e-06 max resid 3.40387e-05 #> ... Similar to previous best #> Run 16 stress 0.07227125 #> ... Procrustes: rmse 4.941503e-06 max resid 1.943066e-05 #> ... Similar to previous best #> Run 17 stress 0.1591579 #> Run 18 stress 0.07227125 #> ... Procrustes: rmse 1.363299e-06 max resid 5.158787e-06 #> ... Similar to previous best #> Run 19 stress 0.07227125 #> ... Procrustes: rmse 5.783015e-06 max resid 2.420838e-05 #> ... Similar to previous best #> Run 20 stress 0.07227125 #> ... Procrustes: rmse 3.842551e-06 max resid 1.520619e-05 #> ... Similar to previous best #> *** Best solution repeated 14 times plot_NMDS(x) #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet plot_NMDS(x, ~type) %>% layer_stars() %>% layer_labelpoints() #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet ### Same on MDS object x <- bot %>% efourier %>% MDS #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) plot_MDS(x) #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet plot_MDS(x, ~type) %>% layer_stars() %>% layer_labelpoints() #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet"},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":null,"dir":"Reference","previous_headings":"","what":"PCA plot using grindr layers — plot_PCA","title":"PCA plot using grindr layers — plot_PCA","text":"Quickly vizualise PCA objects friends build customs plots using layers. See examples.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PCA plot using grindr layers — plot_PCA","text":"","code":"plot_PCA( x, f = NULL, axes = c(1, 2), palette = NULL, points = TRUE, points_transp = 1/4, morphospace = TRUE, morphospace_position = \"range\", chull = TRUE, chullfilled = FALSE, labelpoints = FALSE, labelgroups = FALSE, legend = TRUE, title = \"\", center_origin = TRUE, zoom = 0.9, eigen = TRUE, box = TRUE, axesnames = TRUE, axesvar = TRUE )"},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PCA plot using grindr layers — plot_PCA","text":"x PCA object f factor specification feed fac_dispatcher axes numeric length two select PCs use (c(1, 2) default) palette color palette use col_summer default points logical whether draw layer_points points_transp numeric feed layer_points (default:0.25) morphospace logical whether draw using layer_morphospace_PCA morphospace_position feed layer_morphospace_PCA (default: \"range\") chull logical whether draw layer_chull chullfilled logical whether draw layer_chullfilled labelpoints logical whether draw layer_labelpoints labelgroups logical whether draw layer_labelgroups legend logical whether draw layer_legend title character specified, fee layer_title (default \"\") center_origin logical whether center origin zoom numeric zoom level frame (default: 0.9) eigen logical whether draw using layer_eigen box logical whether draw using layer_box axesnames logical whether draw using layer_axesnames axesvar logical whether draw using layer_axesvar","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"PCA plot using grindr layers — plot_PCA","text":"plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"PCA plot using grindr layers — plot_PCA","text":"approach replace plot.PCA (plot.lda versions. part grindr approach may packaged point. comments welcome.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_PCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PCA plot using grindr layers — plot_PCA","text":"","code":"### First prepare two PCA objects. # Some outlines with bot bp <- bot %>% mutate(fake=sample(letters[1:5], 40, replace=TRUE)) %>% efourier(6) %>% PCA #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details plot_PCA(bp) plot_PCA(bp, ~type) plot_PCA(bp, ~fake) #> factor passed was a character, and coerced to a factor. # Some curves with olea op <- olea %>% mutate(s=coo_area(.)) %>% filter(var != \"Cypre\") %>% chop(~view) %>% opoly(5, nb.pts=90) %>% combine %>% PCA op$fac$s %<>% as.character() %>% as.numeric() op %>% plot_PCA(title=\"hi there!\") ### Now we can play with layers # and for instance build a custom plot # it should start with plot_PCA() my_plot <- function(x, ...){ x %>% plot_PCA(...) %>% layer_points %>% layer_ellipsesaxes %>% layer_rug } # and even continue after this function op %>% my_plot(~var, axes=c(1, 3)) %>% layer_title(\"hi there!\") # grindr allows (almost nice) tricks like highlighting: # bp %>% .layerize_PCA(~fake) %>% # layer_frame %>% layer_axes() %>% # layer_morphospace_PCA() -> x # highlight <- function(x, ..., col_F=\"#CCCCCC\", col_T=\"#FC8D62FF\"){ # args <- list(...) # x$colors_groups <- c(col_F, col_T) # x$colors_rows <- c(col_F, col_T)[(x$f %in% args)+1] # x # } # x %>% highlight(\"a\", \"b\") %>% layer_points() # You get the idea."},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":null,"dir":"Reference","previous_headings":"","what":"Draws colored segments from a matrix of coordinates. — plot_devsegments","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"Given matrix (x; y) coordinates, draws segments every points defined row matrix uses color display information.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"","code":"plot_devsegments(coo, cols, lwd = 1)"},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"coo matrix coordinates. cols vector color length = nrow(coo). lwd lwd use drawing segments.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"drawing last plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_devsegments.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Draws colored segments from a matrix of coordinates. — plot_devsegments","text":"","code":"# we load some data guinness <- coo_sample(bot[9], 100) # we calculate the diff between 48 harm and one with 6 harm. out.6 <- efourier_i(efourier(guinness, nb.h=6), nb.pts=120) # we calculate deviations, you can also try 'edm' dev <- edm_nearest(out.6, guinness) / coo_centsize(out.6) # we prepare the color scale d.cut <- cut(dev, breaks=20, labels=FALSE, include.lowest=TRUE) cols <- paste0(col_summer(20)[d.cut], 'CC') # we draw the results coo_plot(guinness, main='Guiness fitted with 6 harm.', points=FALSE) par(xpd=NA) plot_devsegments(out.6, cols=cols, lwd=4) coo_draw(out.6, lty=2, points=FALSE, col=NA) par(xpd=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":null,"dir":"Reference","previous_headings":"","what":"Silhouette plot — plot_silhouette","title":"Silhouette plot — plot_silhouette","text":"used, far, KMEDOIDS.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Silhouette plot — plot_silhouette","text":"","code":"plot_silhouette(x, palette = pal_qual)"},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Silhouette plot — plot_silhouette","text":"x object returned KMEDOIDS palette one palettes","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Silhouette plot — plot_silhouette","text":"ggplot plot","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_silhouette.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Silhouette plot — plot_silhouette","text":"","code":"olea %>% opoly(5) %>% KMEDOIDS(4) %>% plot_silhouette(pal_qual_solarized) #> 'nb.pts' missing and set to 91"},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots confusion matrix of sample sizes within $fac — plot_table","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"utility plots confusion matrix sample size (barplot) every object $fac. Useful visually large sample sizes, (un)balanced designs, etc.","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"","code":"plot_table(x, fac1, fac2 = fac1, rm0 = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"x object $fac slot (Coo, Coe, PCA, etc.) fac1 name id first factor fac2 name id second factor rm0 logical whether print zeros","code":""},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"ggplot2 object","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/plot_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots confusion matrix of sample sizes within $fac — plot_table","text":"","code":"plot_table(olea, \"var\") #> Warning: `select_()` was deprecated in dplyr 0.7.0. #> ℹ Please use `select()` instead. #> ℹ The deprecated feature was likely used in the Momocs package. #> Please report the issue at . plot_table(olea, \"domes\", \"var\") gg <- plot_table(olea, \"domes\", \"var\", rm0 = TRUE) gg library(ggplot2) gg + coord_equal() gg + scale_fill_gradient(low=\"green\", high = \"red\") #> Scale for fill is already present. #> Adding another scale for fill, which will replace the existing scale. gg + coord_flip()"},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates shape from a polynomial model — opoly_i","title":"Calculates shape from a polynomial model — opoly_i","text":"Returns matrix (x; y) coordinates passed list obtained opoly npoly.","code":""},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates shape from a polynomial model — opoly_i","text":"","code":"opoly_i(pol, nb.pts = 120, reregister = TRUE) npoly_i(pol, nb.pts = 120, reregister = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates shape from a polynomial model — opoly_i","text":"pol pol list created npoly opoly nb.pts number points predict. default (higher) number points original shape. reregister logical whether reregister shape original baseline.","code":""},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates shape from a polynomial model — opoly_i","text":"matrix (x; y) coordinates.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/poly_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates shape from a polynomial model — opoly_i","text":"","code":"data(olea) o <- olea[5] coo_plot(o) for (i in 2:7){ x <- opoly_i(opoly(o, i)) coo_draw(x, border=col_summer(7)[i], points=FALSE) }"},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":null,"dir":"Reference","previous_headings":"","what":"","title":"","text":"Basically wrapper around predict.lda package MASS. Uses LDA model classify new data.","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"","text":"","code":"reLDA(newdata, LDA) # S3 method for default reLDA(newdata, LDA) # S3 method for PCA reLDA(newdata, LDA) # S3 method for Coe reLDA(newdata, LDA)"},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"","text":"newdata use, PCA Coe object LDA LDA object","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"","text":"list components (?predict.lda ). class factor classification posterior posterior probabilities classes x scores test cases res data.frame results CV.tab confusion matrix results CV.correct proportion diagonal CV.tab newdata data used calculate passed predict.lda","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"","text":"Uses number PC axis LDA object provided. probably use rePCA conjunction reLDA get 'homologous' scores.","code":""},{"path":"http://momx.github.io/Momocs/reference/reLDA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"","text":"","code":"# We select the first 10 individuals in bot, # for whisky and beer bottles. It will be our referential. bot1 <- slice(bot, c(1:10, 21:30)) # Same thing for the other 10 individuals. # It will be our unknown dataset on which we want # to calculate classes. bot2 <- slice(bot, c(11:20, 31:40)) # We calculate efourier on these two datasets bot1.f <- efourier(bot1, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bot2.f <- efourier(bot2, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # Here we obtain our LDA model: first, a PCA, then a LDA bot1.p <- PCA(bot1.f) bot1.l <- LDA(bot1.p, \"type\") #> 6 PC retained # we redo the same PCA since we worked with scores bot2.p <- rePCA(bot1.p, bot2.f) # we finally \"predict\" with the model obtained before bot2.l <- reLDA(bot2.p, bot1.l) bot2.l #> $class #> [1] whisky whisky whisky whisky beer whisky whisky beer whisky whisky #> [11] beer beer beer whisky beer whisky beer beer beer beer #> Levels: beer whisky #> #> $posterior #> beer whisky #> jupiler 1.588583e-05 9.999841e-01 #> kingfisher 9.172746e-02 9.082725e-01 #> latrappe 2.276644e-02 9.772336e-01 #> lindemanskriek 5.840887e-03 9.941591e-01 #> nicechouffe 7.031244e-01 2.968756e-01 #> pecheresse 1.773492e-06 9.999982e-01 #> sierranevada 2.144720e-04 9.997855e-01 #> tanglefoot 9.372426e-01 6.275742e-02 #> tauro 1.183763e-05 9.999882e-01 #> westmalle 1.157018e-04 9.998843e-01 #> jb 9.975581e-01 2.441892e-03 #> johnniewalker 8.473188e-01 1.526812e-01 #> magallan 1.000000e+00 3.192177e-09 #> makersmark 1.093923e-01 8.906077e-01 #> oban 9.999880e-01 1.199656e-05 #> oldpotrero 2.425202e-02 9.757480e-01 #> redbreast 9.999820e-01 1.795276e-05 #> tamdhu 8.589367e-01 1.410633e-01 #> wildturkey 9.999905e-01 9.478960e-06 #> yoichi 9.744921e-01 2.550790e-02 #> #> $x #> LD1 #> jupiler 2.9341875 #> kingfisher 0.6087998 #> latrappe 0.9982650 #> lindemanskriek 1.3640608 #> nicechouffe -0.2289504 #> pecheresse 3.5163722 #> sierranevada 2.2430113 #> tanglefoot -0.7179197 #> tauro 3.0122943 #> westmalle 2.4069164 #> jb -1.5965434 #> johnniewalker -0.4550552 #> magallan -5.1945591 #> makersmark 0.5568188 #> oban -3.0087530 #> oldpotrero 0.9810760 #> redbreast -2.9017076 #> tamdhu -0.4796867 #> wildturkey -3.0712994 #> yoichi -0.9673275 #> #> $newdata #> PC1 PC2 PC3 PC4 #> jupiler 0.047558323 -0.0009556964 -1.132936e-02 -0.0038135827 #> kingfisher 0.031019804 0.0092893037 -5.639726e-03 0.0006984167 #> latrappe -0.140467542 0.0368452619 8.204030e-03 -0.0074130929 #> lindemanskriek 0.028727335 -0.0093711139 -6.350860e-03 0.0040530566 #> nicechouffe 0.014137615 -0.0087352325 -1.464619e-03 0.0102437348 #> pecheresse 0.046019149 -0.0022071144 -1.263256e-02 -0.0019483303 #> sierranevada -0.045574138 0.0101119946 -4.587309e-03 -0.0139742083 #> tanglefoot -0.083848693 0.0019607973 1.265634e-02 -0.0086813906 #> tauro 0.047804962 -0.0010302173 -1.166643e-02 -0.0038315686 #> westmalle 0.043104213 -0.0006618641 -9.661507e-03 0.0013659528 #> jb 0.033826795 -0.0043832070 8.789680e-03 -0.0012973929 #> johnniewalker 0.027546559 0.0433572509 -5.503569e-07 0.0080407513 #> magallan 0.062757370 0.0344623824 1.994348e-02 0.0054305457 #> makersmark -0.066073754 -0.0410683917 -2.500513e-02 -0.0028195062 #> oban 0.056001340 -0.0017415641 1.469954e-02 0.0024240694 #> oldpotrero -0.039446859 -0.0560097481 -1.838963e-02 0.0143275711 #> redbreast -0.070467008 -0.0453726482 1.443590e-03 0.0008230393 #> tamdhu 0.040245919 0.0099990120 8.849077e-03 -0.0054926858 #> wildturkey 0.009047941 -0.0118958979 1.825586e-02 -0.0002205672 #> yoichi -0.041919333 0.0374066929 1.388610e-02 0.0020851880 #> PC5 PC6 #> jupiler 0.0005273680 -0.003411272 #> kingfisher -0.0025505108 -0.000645225 #> latrappe 0.0014020218 -0.011164248 #> lindemanskriek -0.0005455535 -0.004342575 #> nicechouffe -0.0031229185 -0.005062708 #> pecheresse 0.0030349867 -0.005659553 #> sierranevada -0.0050825894 -0.003254912 #> tanglefoot -0.0051466484 -0.003608419 #> tauro 0.0011495431 -0.003297832 #> westmalle 0.0015195495 -0.004960376 #> jb -0.0020355558 0.003538980 #> johnniewalker -0.0046821155 -0.006875580 #> magallan 0.0055312084 0.011826574 #> makersmark 0.0039534995 0.017991125 #> oban 0.0001554770 0.005786238 #> oldpotrero 0.0023407200 0.001001825 #> redbreast -0.0038050474 0.012566253 #> tamdhu -0.0011719141 0.000222802 #> wildturkey -0.0020315441 0.003880876 #> yoichi 0.0105600234 -0.004531973 #>"},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":null,"dir":"Reference","previous_headings":"","what":"","title":"","text":"Basically reapply rotation new Coe object.","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"","text":"","code":"rePCA(PCA, Coe)"},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"","text":"PCA PCA object Coe Coe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"","text":"Quite experimental. Dimensions matrices methods must match.","code":""},{"path":"http://momx.github.io/Momocs/reference/rePCA.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"","text":"","code":"b <- filter(bot, type==\"beer\") w <- filter(bot, type==\"whisky\") bf <- efourier(b, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bp <- PCA(bf) wf <- efourier(w, 8) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details # and we use the \"beer\" PCA on the whisky coefficients wp <- rePCA(bp, wf) plot(wp) #> will be deprecated soon, see ?plot_PCA plot(bp, eig=FALSE) #> will be deprecated soon, see ?plot_PCA points(wp$x[, 1:2], col=\"red\", pch=4)"},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":null,"dir":"Reference","previous_headings":"","what":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Helps reorder retain landmarks simply changing order recorded Coo objects. Note Opn objects, rearranges $ldk component. Ldk, rearranges $coo directly.","code":""},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"","code":"rearrange_ldk(Coo, new_ldk_ids)"},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Coo appropriate Coo object (typically Ldk) landmarks inside new_ldk_ids vector numeric ldk retain right order (see )","code":""},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rearrange_ldk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rearrange, (select and reorder) landmarks to retain — rearrange_ldk","text":"","code":"# Out example hearts %>% slice(1) %T>% stack %$% ldk #> [[1]] #> [1] 65 56 50 19 #> hearts %>% rearrange_ldk(c(4, 1)) %>% slice(1) %T>%stack %$% ldk #> [[1]] #> [1] 19 65 #> # Ldk example wings %>% slice(1) %T>% stack %$% coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] -0.0777 0.0832 #> [3,] 0.2231 0.0861 #> [4,] 0.2641 0.0462 #> [5,] 0.2645 0.0261 #> [6,] 0.2471 0.0003 #> [7,] 0.2311 -0.0228 #> [8,] 0.2040 -0.0452 #> [9,] 0.1282 -0.0742 #> [10,] 0.0424 -0.0966 #> [11,] -0.0674 -0.1108 #> [12,] -0.4102 -0.0163 #> [13,] -0.3140 0.0318 #> [14,] -0.1768 0.0341 #> [15,] 0.0715 0.0509 #> [16,] -0.0540 0.0238 #> [17,] 0.0575 -0.0059 #> [18,] -0.1401 -0.0240 #> wings %>% rearrange_ldk(c(1, 3, 12:15)) %>% slice(1) %T>% stack %$% coo #> $AN1 #> [,1] [,2] #> [1,] -0.4933 0.0130 #> [2,] 0.2231 0.0861 #> [3,] -0.4102 -0.0163 #> [4,] -0.3140 0.0318 #> [5,] -0.1768 0.0341 #> [6,] 0.0715 0.0509 #>"},{"path":"http://momx.github.io/Momocs/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. magrittr %$%, %<>%, %>%, %T>%","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":null,"dir":"Reference","previous_headings":"","what":"Rename columns by name — rename","title":"Rename columns by name — rename","text":"Rename variables, $fac. See examples dplyr::rename.","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rename columns by name — rename","text":"","code":"rename(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rename columns by name — rename","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rename columns by name — rename","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rename columns by name — rename","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rename.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rename columns by name — rename","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk rename(olea, variety=var, domesticated=domes) # rename var column #> Opn (curves) #> - 210 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> variety domesticated view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":null,"dir":"Reference","previous_headings":"","what":"Rescale coordinates from pixels to real length units — rescale","title":"Rescale coordinates from pixels to real length units — rescale","text":"time, (x, y) coordinates recorded pixels. want mm, cm, etc. need convert rescale . functions job two cases: ) either homogeneous rescaling factor, e.g. pictures taken using magnification ii) various magnifications. Details section","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rescale coordinates from pixels to real length units — rescale","text":"","code":"rescale(x, scaling_factor, scale_mapping, magnification_col, ...)"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rescale coordinates from pixels to real length units — rescale","text":"x Coo object scaling_factor numeric homogeneous scaling factor. (x, y) coordinates scale scale_mapping either data.frame path read data.frame. MUST contain three columns order: magnification found $fac, column \"magnification_col\", pixels, real length unit. Column names matter must specified, read.table reads header=TRUE Every different magnification level found $fac, column \"magnification_col\" must row. magnification_col name id $fac column look magnification levels every image ... additional arguments (besides header=TRUE) pass read.table 'scale_mapping' path","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rescale coordinates from pixels to real length units — rescale","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Rescale coordinates from pixels to real length units — rescale","text":") case straightforward, 1cm 500pix long pictures, just call rescale(your_Coo, scaling_factor=1/500) coordinates cm. ii) second case subtle. First need code Coo object, fac slot, column named, say \"mag\", magnification. Imagine 4 magnifications: 0.5, 1, 2 5, indicate magnification, many pixels stands many units real world. information passed data.frame, built externally R, must look like : . , optical reasons, ratio pix/real_unit, linear function magnification. shapes centered apply (single different) scaling_factor.","code":"mag pix cm 0.5 1304 10 1 921 10 2 816 5 5 1020 5"},{"path":"http://momx.github.io/Momocs/reference/rescale.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Rescale coordinates from pixels to real length units — rescale","text":"function simple quite complex detail. Feel free contact problem . can just access code (type rescale) reply .","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Radii variation Fourier transform (equally spaced radii) — rfourier","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"rfourier computes radii variation Fourier analysis matrix list coordinates points equally spaced radii.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"","code":"rfourier(x, ...) # S3 method for default rfourier(x, nb.h, smooth.it = 0, norm = FALSE, ...) # S3 method for Out rfourier(x, nb.h = 40, smooth.it = 0, norm = TRUE, thres = pi/90, ...) # S3 method for list rfourier(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"x list matrix coordinates object ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform. norm logical. Whether scale outlines mean length radii used equals 1. thres numeric tolerance feed is_equallyspacedradii","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"list following components: vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients ao ao harmonic coefficient. r vector radii lengths.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"see JSS paper maths behind. methods objects tests coordinates equally spaced radii using is_equallyspacedradii. message printed case.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"Silent message progress bars () options(\"verbose\"=FALSE). Directly borrowed Claude (2008), called fourier1 .","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radii variation Fourier transform (equally spaced radii) — rfourier","text":"","code":"data(bot) coo <- coo_center(bot[1]) # centering is almost mandatory for rfourier family coo_plot(coo) rf <- rfourier(coo, 12) rf #> $an #> [1] 9.216460e-15 -4.745309e+02 8.327818e-01 2.719483e+02 -1.430955e+01 #> [6] -1.110619e+02 2.489911e+01 -1.011701e+00 -1.771458e+01 5.542552e+01 #> [11] 6.786737e-01 -5.902187e+01 #> #> $bn #> [1] 1.054744e-13 -1.108663e+01 -5.032796e+01 1.187178e+01 1.332257e+02 #> [6] 4.068663e+00 -1.709325e+02 -1.013725e+01 1.391797e+02 1.085760e+01 #> [11] -7.449979e+01 -2.355442e+00 #> #> $ao #> [1] 669.1267 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- rfourier_i(rf) coo_draw(rfi, border='red', col=NA) # Out method bot %>% rfourier() #> some shapes seem(s) to have some identical coordinates #> 'nb.h' not provided and set to 60 (99% harmonic power) #> An OutCoe object [ radii variation (equally spaced radii) analysis ] #> -------------------- #> - $coe: 40 outlines described, 60 harmonics #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows"},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse radii variation Fourier transform — rfourier_i","title":"Inverse radii variation Fourier transform — rfourier_i","text":"rfourier_i uses inverse radii variation (equally spaced radii) transformation calculate shape, given list Fourier coefficients, typically obtained computed rfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse radii variation Fourier transform — rfourier_i","text":"","code":"rfourier_i(rf, nb.h, nb.pts = 120)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse radii variation Fourier transform — rfourier_i","text":"rf list ao, bn components, typically returned rfourier. nb.h integer. number harmonics calculate/use. nb.pts integer. number points calculate.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse radii variation Fourier transform — rfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. angle vector angles used. r vector radii calculated.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse radii variation Fourier transform — rfourier_i","text":"See JSS paper maths behind.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse radii variation Fourier transform — rfourier_i","text":"Directly borrowed Claude (2008), called ifourier1 .","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse radii variation Fourier transform — rfourier_i","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse radii variation Fourier transform — rfourier_i","text":"","code":"data(bot) coo <- coo_center(bot[1]) # centering is almost mandatory for rfourier family coo_plot(coo) rf <- rfourier(coo, 12) rf #> $an #> [1] 9.216460e-15 -4.745309e+02 8.327818e-01 2.719483e+02 -1.430955e+01 #> [6] -1.110619e+02 2.489911e+01 -1.011701e+00 -1.771458e+01 5.542552e+01 #> [11] 6.786737e-01 -5.902187e+01 #> #> $bn #> [1] 1.054744e-13 -1.108663e+01 -5.032796e+01 1.187178e+01 1.332257e+02 #> [6] 4.068663e+00 -1.709325e+02 -1.013725e+01 1.391797e+02 1.085760e+01 #> [11] -7.449979e+01 -2.355442e+00 #> #> $ao #> [1] 669.1267 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- rfourier_i(rf) coo_draw(rfi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'rfourier' shapes. — rfourier_shape","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"rfourier_shape calculates 'Fourier radii variation shape' given Fourier coefficients (see Details) can generate 'rfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"","code":"rfourier_shape(an, bn, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"rfourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See rfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'rfourier' shapes. — rfourier_shape","text":"","code":"data(bot) rf <- rfourier(bot[1], 24) rfourier_shape(rf$an, rf$bn) # equivalent to rfourier_i(rf) #> x y #> [1,] -504.032401 0.000000e+00 #> [2,] 152.277511 1.213684e+01 #> [3,] 123.922985 1.988014e+01 #> [4,] -405.769720 -9.869758e+01 #> [5,] -299.257786 -9.855215e+01 #> [6,] -64.033528 -2.689724e+01 #> [7,] -297.588603 -1.538718e+02 #> [8,] -247.659860 -1.541471e+02 #> [9,] 34.115634 2.520344e+01 #> [10,] -81.118036 -7.054630e+01 #> [11,] -96.952489 -9.889967e+01 #> [12,] 181.738917 2.175623e+02 #> [13,] 320.377819 4.522104e+02 #> [14,] 650.392457 1.092799e+03 #> [15,] 1019.781679 2.072239e+03 #> [16,] 766.774556 1.932160e+03 #> [17,] 840.274273 2.733288e+03 #> [18,] 1733.216439 7.797650e+03 #> [19,] 1683.030508 1.201390e+04 #> [20,] 472.998568 7.920093e+03 #> [21,] -3.693822 1.857488e+02 #> [22,] 193.709205 -1.942018e+03 #> [23,] 21.862735 -1.208644e+02 #> [24,] 53.714265 -2.031549e+02 #> [25,] 370.520921 -1.054083e+03 #> [26,] 216.540448 -4.880980e+02 #> [27,] 135.732670 -2.501862e+02 #> [28,] 466.908353 -7.179336e+02 #> [29,] 411.781716 -5.348072e+02 #> [30,] 235.560214 -2.602254e+02 #> [31,] 517.224029 -4.872563e+02 #> [32,] 572.278421 -4.590422e+02 #> [33,] 346.348891 -2.351772e+02 #> [34,] 534.117025 -3.036705e+02 #> [35,] 679.577570 -3.178066e+02 #> [36,] 455.098727 -1.702117e+02 #> [37,] 529.331468 -1.512772e+02 #> [38,] 725.483690 -1.461831e+02 #> [39,] 545.014188 -6.533097e+01 #> [40,] 512.204019 -2.037956e+01 #> [41,] 711.685148 2.831651e+01 #> [42,] 599.323333 7.184102e+01 #> [43,] 487.280383 9.818574e+01 #> [44,] 648.008281 1.851938e+02 #> [45,] 605.439186 2.264407e+02 #> [46,] 453.428917 2.120475e+02 #> [47,] 549.059655 3.121661e+02 #> [48,] 558.226691 3.790460e+02 #> [49,] 404.964997 3.248349e+02 #> [50,] 430.145214 4.052228e+02 #> [51,] 461.416259 5.097305e+02 #> [52,] 334.454312 4.343772e+02 #> [53,] 303.642443 4.668906e+02 #> [54,] 326.758921 6.022910e+02 #> [55,] 236.290598 5.326163e+02 #> [56,] 176.846385 5.031047e+02 #> [57,] 171.184806 6.474451e+02 #> [58,] 109.884528 6.074778e+02 #> [59,] 51.833348 5.196517e+02 #> [60,] 12.809119 6.441236e+02 #> [61,] -38.593591 6.462278e+02 #> [62,] -72.750399 5.193108e+02 #> [63,] -133.044116 5.985585e+02 #> [64,] -196.546600 6.393370e+02 #> [65,] -198.662349 5.006002e+02 #> [66,] -256.653752 5.215311e+02 #> [67,] -347.381274 5.836753e+02 #> [68,] -324.847387 4.585191e+02 #> [69,] -354.756103 4.246838e+02 #> [70,] -474.501207 4.840310e+02 #> [71,] -445.049745 3.870485e+02 #> [72,] -429.185843 3.170675e+02 #> [73,] -566.188571 3.524040e+02 #> [74,] -546.614528 2.826337e+02 #> [75,] -483.371296 2.030398e+02 #> [76,] -622.486699 2.049985e+02 #> [77,] -607.488016 1.477626e+02 #> [78,] -514.459992 8.253138e+01 #> [79,] -692.324999 5.517977e+01 #> [80,] -504.032401 1.234523e-13 rfourier_shape() # not very interesting #> x y #> [1,] -1.70783049 0.000000e+00 #> [2,] -1.42387492 -1.134858e-01 #> [3,] -1.12842604 -1.810258e-01 #> [4,] -0.83525063 -2.031626e-01 #> [5,] -0.55314503 -1.821628e-01 #> [6,] -0.28573344 -1.200222e-01 #> [7,] -0.03274864 -1.693308e-02 #> [8,] 0.20762473 1.292287e-01 #> [9,] 0.43605675 3.221435e-01 #> [10,] 0.64983694 5.651467e-01 #> [11,] 0.84177670 8.586828e-01 #> [12,] 1.00061227 1.197848e+00 #> [13,] 1.11285389 1.570783e+00 #> [14,] 1.16562637 1.958503e+00 #> [15,] 1.14977127 2.336383e+00 #> [16,] 1.06240688 2.677111e+00 #> [17,] 0.90828491 2.954516e+00 #> [18,] 0.69959955 3.147462e+00 #> [19,] 0.45430408 3.242938e+00 #> [20,] 0.19336079 3.237717e+00 #> [21,] -0.06240765 3.138252e+00 #> [22,] -0.29514415 2.958947e+00 #> [23,] -0.49188023 2.719276e+00 #> [24,] -0.64526044 2.440466e+00 #> [25,] -0.75311265 2.142507e+00 #> [26,] -0.81720368 1.842037e+00 #> [27,] -0.84168817 1.551423e+00 #> [28,] -0.83175975 1.278941e+00 #> [29,] -0.79285960 1.029737e+00 #> [30,] -0.73054609 8.070406e-01 #> [31,] -0.65086608 6.131551e-01 #> [32,] -0.56087882 4.498982e-01 #> [33,] -0.46892701 3.184099e-01 #> [34,] -0.38434108 2.185159e-01 #> [35,] -0.31647156 1.479989e-01 #> [36,] -0.27319902 1.021793e-01 #> [37,] -0.25928964 7.410219e-02 #> [38,] -0.27507300 5.542650e-02 #> [39,] -0.31587991 3.786459e-02 #> [40,] -0.37249857 1.482096e-02 #> [41,] -0.43263981 -1.721386e-02 #> [42,] -0.48312454 -5.791225e-02 #> [43,] -0.51230209 -1.032276e-01 #> [44,] -0.51213827 -1.463636e-01 #> [45,] -0.47949724 -1.793370e-01 #> [46,] -0.41635659 -1.947105e-01 #> [47,] -0.32897716 -1.870389e-01 #> [48,] -0.22631518 -1.536721e-01 #> [49,] -0.11813866 -9.476267e-02 #> [50,] -0.01334510 -1.257189e-02 #> [51,] 0.08113017 8.962521e-02 #> [52,] 0.16063793 2.086307e-01 #> [53,] 0.22244168 3.420336e-01 #> [54,] 0.26492212 4.883117e-01 #> [55,] 0.28673533 6.463225e-01 #> [56,] 0.28627059 8.144022e-01 #> [57,] 0.26160815 9.894390e-01 #> [58,] 0.21096982 1.166311e+00 #> [59,] 0.13345744 1.337968e+00 #> [60,] 0.02975436 1.496238e+00 #> [61,] -0.09753442 1.633159e+00 #> [62,] -0.24410623 1.742492e+00 #> [63,] -0.40474725 1.820937e+00 #> [64,] -0.57446280 1.868642e+00 #> [65,] -0.74957661 1.888824e+00 #> [66,] -0.92838875 1.886525e+00 #> [67,] -1.11108727 1.866866e+00 #> [68,] -1.29882939 1.833286e+00 #> [69,] -1.49218159 1.786313e+00 #> [70,] -1.68934733 1.723276e+00 #> [71,] -1.88473800 1.639109e+00 #> [72,] -2.06840699 1.528067e+00 #> [73,] -2.22666734 1.385910e+00 #> [74,] -2.34389910 1.211941e+00 #> [75,] -2.40520955 1.010307e+00 #> [76,] -2.39933834 7.901548e-01 #> [77,] -2.32108398 5.645699e-01 #> [78,] -2.17260957 3.485372e-01 #> [79,] -1.96325086 1.564753e-01 #> [80,] -1.70783049 4.182978e-16 rfourier_shape(nb.h=12) # better #> x y #> [1,] 3.17350221 0.000000e+00 #> [2,] 2.82968114 2.255316e-01 #> [3,] 2.43948432 3.913502e-01 #> [4,] 2.06536164 5.023692e-01 #> [5,] 1.74268302 5.739037e-01 #> [6,] 1.47564178 6.198424e-01 #> [7,] 1.24842809 6.455149e-01 #> [8,] 1.04054160 6.476482e-01 #> [9,] 0.83709685 6.184180e-01 #> [10,] 0.63206684 5.496925e-01 #> [11,] 0.42754983 4.361367e-01 #> [12,] 0.23216062 2.779229e-01 #> [13,] 0.05887461 8.310097e-02 #> [14,] -0.07873057 -1.322843e-01 #> [15,] -0.17140187 -3.482958e-01 #> [16,] -0.21769695 -5.485646e-01 #> [17,] -0.22348979 -7.269792e-01 #> [18,] -0.19763895 -8.891673e-01 #> [19,] -0.14677845 -1.047742e+00 #> [20,] -0.07253700 -1.214591e+00 #> [21,] 0.02774197 -1.395042e+00 #> [22,] 0.15824615 -1.586486e+00 #> [23,] 0.32205629 -1.780433e+00 #> [24,] 0.51961489 -1.965257e+00 #> [25,] 0.74804094 -2.128078e+00 #> [26,] 1.00099083 -2.256307e+00 #> [27,] 1.26941847 -2.339827e+00 #> [28,] 1.54350539 -2.373345e+00 #> [29,] 1.81487968 -2.357100e+00 #> [30,] 2.07741451 -2.294938e+00 #> [31,] 2.32588321 -2.191122e+00 #> [32,] 2.55405607 -2.048687e+00 #> [33,] 2.75500192 -1.870696e+00 #> [34,] 2.92452011 -1.662726e+00 #> [35,] 3.06492303 -1.433321e+00 #> [36,] 3.18450875 -1.191040e+00 #> [37,] 3.29071918 -9.404522e-01 #> [38,] 3.38068991 -6.812003e-01 #> [39,] 3.43662398 -4.119489e-01 #> [40,] 3.43105716 -1.365148e-01 #> [41,] 3.33973942 1.328815e-01 #> [42,] 3.15355628 3.780175e-01 #> [43,] 2.88139811 5.805943e-01 #> [44,] 2.54314959 7.268048e-01 #> [45,] 2.15980801 8.077911e-01 #> [46,] 1.74916782 8.180039e-01 #> [47,] 1.32926781 7.557509e-01 #> [48,] 0.92374397 6.272389e-01 #> [49,] 0.56104073 4.500281e-01 #> [50,] 0.26536741 2.499921e-01 #> [51,] 0.04586366 5.066599e-02 #> [52,] -0.10657467 -1.384153e-01 #> [53,] -0.21116372 -3.246923e-01 #> [54,] -0.28370198 -5.229272e-01 #> [55,] -0.32811803 -7.396021e-01 #> [56,] -0.33890179 -9.641311e-01 #> [57,] -0.31062985 -1.174846e+00 #> [58,] -0.24514106 -1.355220e+00 #> [59,] -0.15025456 -1.506367e+00 #> [60,] -0.03270006 -1.644366e+00 #> [61,] 0.10654541 -1.784042e+00 #> [62,] 0.26942175 -1.923201e+00 #> 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0.8523405308 1.610035e-02 #> [253,] 0.7339562151 2.311176e-02 #> [254,] 0.6070058016 2.676834e-02 #> [255,] 0.4716608340 2.675388e-02 #> [256,] 0.3281356702 2.276096e-02 #> [257,] 0.1766873280 1.449337e-02 #> [258,] 0.0176150845 1.668473e-03 #> [259,] -0.1487401725 -1.598046e-02 #> [260,] -0.3219968412 -3.870196e-02 #> [261,] -0.5017337489 -6.672411e-02 #> [262,] -0.6874915390 -1.002524e-01 #> [263,] -0.8787742964 -1.394678e-01 #> [264,] -1.0750514062 -1.845244e-01 #> [265,] -1.2757596359 -2.355482e-01 #> [266,] -1.4803054332 -2.926349e-01 #> [267,] -1.6880674276 -3.558488e-01 #> [268,] -1.8983991234 -4.252210e-01 #> [269,] -2.1106317703 -5.007487e-01 #> [270,] -2.3240773954 -5.823941e-01 #> [271,] -2.5380319828 -6.700832e-01 #> [272,] -2.7517787794 -7.637059e-01 #> [273,] -2.9645917117 -8.631154e-01 #> [274,] -3.1757388921 -9.681279e-01 #> [275,] -3.3844861954 -1.078523e+00 #> [276,] -3.5901008841 -1.194044e+00 #> [277,] -3.7918552610 -1.314399e+00 #> [278,] -3.9890303282 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-4.640957e+00 #> [305,] -5.7302997090 -4.693309e+00 #> [306,] -5.6362205080 -4.736073e+00 #> [307,] -5.5324419493 -4.768996e+00 #> [308,] -5.4194698055 -4.791870e+00 #> [309,] -5.2978431877 -4.804534e+00 #> [310,] -5.1681314720 -4.806871e+00 #> [311,] -5.0309310732 -4.798816e+00 #> [312,] -4.8868620859 -4.780348e+00 #> [313,] -4.7365648154 -4.751499e+00 #> [314,] -4.5806962193 -4.712346e+00 #> [315,] -4.4199262834 -4.663017e+00 #> [316,] -4.2549343536 -4.603689e+00 #> [317,] -4.0864054489 -4.534584e+00 #> [318,] -3.9150265759 -4.455973e+00 #> [319,] -3.7414830713 -4.368169e+00 #> [320,] -3.5664549920 -4.271531e+00 #> [321,] -3.3906135775 -4.166459e+00 #> [322,] -3.2146178059 -4.053391e+00 #> [323,] -3.0391110633 -3.932804e+00 #> [324,] -2.8647179495 -3.805208e+00 #> [325,] -2.6920412365 -3.671144e+00 #> [326,] -2.5216590002 -3.531185e+00 #> [327,] -2.3541219405 -3.385924e+00 #> [328,] -2.1899509060 -3.235982e+00 #> [329,] -2.0296346383 -3.081995e+00 #> [330,] -1.8736277460 -2.924614e+00 #> [331,] -1.7223489218 -2.764504e+00 #> [332,] -1.5761794099 -2.602335e+00 #> [333,] -1.4354617320 -2.438783e+00 #> [334,] -1.3004986772 -2.274524e+00 #> [335,] -1.1715525591 -2.110228e+00 #> [336,] -1.0488447423 -1.946562e+00 #> [337,] -0.9325554379 -1.784179e+00 #> [338,] -0.8228237665 -1.623718e+00 #> [339,] -0.7197480838 -1.465800e+00 #> [340,] -0.6233865647 -1.311026e+00 #> [341,] -0.5337580368 -1.159971e+00 #> [342,] -0.4508430560 -1.013182e+00 #> [343,] -0.3745852119 -8.711775e-01 #> [344,] -0.3048926515 -7.344407e-01 #> [345,] -0.2416398079 -6.034202e-01 #> [346,] -0.1846693177 -4.785269e-01 #> [347,] -0.1337941121 -3.601316e-01 #> [348,] -0.0887996638 -2.485638e-01 #> [349,] -0.0494463715 -1.441101e-01 #> [350,] -0.0154720622 -4.701310e-02 #> [351,] 0.0134054074 4.252949e-02 #> [352,] 0.0374854712 1.243654e-01 #> [353,] 0.0570821171 1.983879e-01 #> [354,] 0.0725211136 2.645363e-01 #> [355,] 0.0841372209 3.227948e-01 #> [356,] 0.0922714074 3.731929e-01 #> [357,] 0.0972680931 4.158035e-01 #> [358,] 0.0994724381 4.507425e-01 #> [359,] 0.0992276988 4.781669e-01 #> [360,] 0.0968726680 4.982736e-01 #> [361,] 0.0927392197 5.112970e-01 #> [362,] 0.0871499740 5.175069e-01 #> [363,] 0.0804160985 5.172066e-01 #> [364,] 0.0728352630 5.107299e-01 #> [365,] 0.0646897580 4.984384e-01 #> [366,] 0.0562447922 4.807189e-01 #> [367,] 0.0477469784 4.579800e-01 #> [368,] 0.0394230163 4.306493e-01 #> [369,] 0.0314785819 3.991701e-01 #> [370,] 0.0240974266 3.639978e-01 #> [371,] 0.0174406929 3.255972e-01 #> [372,] 0.0116464470 2.844384e-01 #> [373,] 0.0068294301 2.409941e-01 #> [374,] 0.0030810269 1.957358e-01 #> [375,] 0.0004694488 1.491308e-01 #> [376,] -0.0009598730 1.016390e-01 #> [377,] -0.0011836908 5.370944e-02 #> [378,] -0.0002001469 5.777811e-03 #> [379,] 0.0019722053 -4.173675e-02 #> [380,] 0.0052955579 -8.843425e-02 #> [381,] 0.0097141677 -1.339364e-01 #> [382,] 0.0151558267 -1.778890e-01 #> [383,] 0.0215334678 -2.199639e-01 #> [384,] 0.0287468917 -2.598611e-01 #> [385,] 0.0366845972 -2.973105e-01 #> [386,] 0.0452256982 -3.320731e-01 #> [387,] 0.0542419100 -3.639424e-01 #> [388,] 0.0635995851 -3.927453e-01 #> [389,] 0.0731617813 -4.183428e-01 #> [390,] 0.0827903424 -4.406302e-01 #> [391,] 0.0923479727 -4.595377e-01 #> [392,] 0.1017002861 -4.750298e-01 #> [393,] 0.1107178119 -4.871055e-01 #> [394,] 0.1192779386 -4.957969e-01 #> [395,] 0.1272667785 -5.011692e-01 #> [396,] 0.1345809348 -5.033190e-01 #> [397,] 0.1411291575 -5.023730e-01 #> [398,] 0.1468338708 -4.984867e-01 #> [399,] 0.1516325589 -4.918424e-01 #> [400,] 0.1554789968 -4.826475e-01 #> [401,] 0.1583443157 -4.711320e-01 #> [402,] 0.1602178907 -4.575464e-01 #> [403,] 0.1611080441 -4.421595e-01 #> [404,] 0.1610425565 -4.252554e-01 #> [405,] 0.1600689790 -4.071311e-01 #> [406,] 0.1582547442 -3.880940e-01 #> [407,] 0.1556870729 -3.684587e-01 #> [408,] 0.1524726756 -3.485441e-01 #> [409,] 0.1487372509 -3.286714e-01 #> [410,] 0.1446247831 -3.091602e-01 #> [411,] 0.1402966432 -2.903264e-01 #> [412,] 0.1359305000 -2.724793e-01 #> [413,] 0.1317190495 -2.559187e-01 #> [414,] 0.1278685704 -2.409329e-01 #> [415,] 0.1245973187 -2.277954e-01 #> [416,] 0.1221337714 -2.167632e-01 #> [417,] 0.1207147347 -2.080744e-01 #> [418,] 0.1205833303 -2.019462e-01 #> [419,] 0.1219868758 -1.985731e-01 #> [420,] 0.1251746763 -1.981249e-01 #> [421,] 0.1303957451 -2.007457e-01 #> [422,] 0.1378964703 -2.065525e-01 #> [423,] 0.1479182489 -2.156342e-01 #> [424,] 0.1606951045 -2.280504e-01 #> [425,] 0.1764513113 -2.438315e-01 #> [426,] 0.1953990416 -2.629782e-01 #> [427,] 0.2177360577 -2.854609e-01 #> [428,] 0.2436434683 -3.112207e-01 #> [429,] 0.2732835666 -3.401690e-01 #> [430,] 0.3067977706 -3.721887e-01 #> [431,] 0.3443046826 -4.071349e-01 #> [432,] 0.3858982853 -4.448357e-01 #> [433,] 0.4316462915 -4.850940e-01 #> [434,] 0.4815886611 -5.276885e-01 #> [435,] 0.5357363014 -5.723759e-01 #> [436,] 0.5940699617 -6.188922e-01 #> [437,] 0.6565393349 -6.669551e-01 #> [438,] 0.7230623754 -7.162661e-01 #> [439,] 0.7935248421 -7.665126e-01 #> [440,] 0.8677800724 -8.173707e-01 #> [441,] 0.9456489928 -8.685073e-01 #> [442,] 1.0269203697 -9.195827e-01 #> [443,] 1.1113513010 -9.702536e-01 #> [444,] 1.1986679491 -1.020175e+00 #> [445,] 1.2885665117 -1.069005e+00 #> [446,] 1.3807144290 -1.116402e+00 #> [447,] 1.4747518185 -1.162036e+00 #> [448,] 1.5702931325 -1.205583e+00 #> [449,] 1.6669290275 -1.246731e+00 #> [450,] 1.7642284357 -1.285184e+00 #> [451,] 1.8617408256 -1.320661e+00 #> [452,] 1.9589986377 -1.352900e+00 #> [453,] 2.0555198811 -1.381659e+00 #> [454,] 2.1508108725 -1.406721e+00 #> [455,] 2.2443691025 -1.427890e+00 #> [456,] 2.3356862074 -1.444999e+00 #> [457,] 2.4242510296 -1.457907e+00 #> [458,] 2.5095527440 -1.466500e+00 #> [459,] 2.5910840309 -1.470694e+00 #> [460,] 2.6683442720 -1.470437e+00 #> [461,] 2.7408427500 -1.465704e+00 #> [462,] 2.8081018272 -1.456504e+00 #> [463,] 2.8696600830 -1.442874e+00 #> [464,] 2.9250753866 -1.424882e+00 #> [465,] 2.9739278858 -1.402627e+00 #> [466,] 3.0158228871 -1.376237e+00 #> [467,] 3.0503936105 -1.345868e+00 #> [468,] 3.0773037961 -1.311704e+00 #> [469,] 3.0962501455 -1.273953e+00 #> [470,] 3.1069645794 -1.232850e+00 #> [471,] 3.1092162952 -1.188653e+00 #> [472,] 3.1028136086 -1.141638e+00 #> [473,] 3.0876055668 -1.092103e+00 #> [474,] 3.0634833183 -1.040361e+00 #> [475,] 3.0303812321 -9.867403e-01 #> [476,] 2.9882777541 -9.315820e-01 #> [477,] 2.9371959947 -8.752358e-01 #> [478,] 2.8772040430 -8.180593e-01 #> [479,] 2.8084150020 -7.604142e-01 #> [480,] 2.7309867450 -7.026646e-01 #> [481,] 2.6451213919 -6.451738e-01 #> [482,] 2.5510645094 -5.883018e-01 #> [483,] 2.4491040361 -5.324030e-01 #> [484,] 2.3395689420 -4.778231e-01 #> [485,] 2.2228276275 -4.248973e-01 #> [486,] 2.0992860718 -3.739474e-01 #> [487,] 1.9693857436 -3.252796e-01 #> [488,] 1.8336012848 -2.791826e-01 #> [489,] 1.6924379826 -2.359253e-01 #> [490,] 1.5464290467 -1.957551e-01 #> [491,] 1.3961327068 -1.588961e-01 #> [492,] 1.2421291512 -1.255476e-01 #> [493,] 1.0850173244 -9.588280e-02 #> [494,] 0.9254116045 -7.004754e-02 #> [495,] 0.7639383824 -4.815950e-02 #> [496,] 0.6012325644 -3.030744e-02 #> [497,] 0.4379340204 -1.655068e-02 #> [498,] 0.2746840012 -6.918859e-03 #> [499,] 0.1121215474 -1.411859e-03 #> [500,] -0.0491200860 1.203095e-17 # Butterflies of the vignette' cover panel(Out(a2l(replicate(100, rfourier_shape(nb.h=6, alpha=0.4, nb.pts=200, plot=FALSE)))))"},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"obtained efourier, otherwise message returned. rm_asym sets B C coefficients 0; rm_sym sets D coefficients 0.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"","code":"rm_asym(OutCoe) # S3 method for default rm_asym(OutCoe) # S3 method for OutCoe rm_asym(OutCoe) rm_sym(OutCoe) # S3 method for default rm_sym(OutCoe) # S3 method for OutCoe rm_sym(OutCoe)"},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"OutCoe OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"OutCoe object","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":": first mention, two applications. Iwata, H., Niikura, S., Matsuura, S., Takano, Y., & Ukai, Y. (1998). Evaluation variation root shape Japanese radish (Raphanus sativus L.) based image analysis using elliptic Fourier descriptors. Euphytica, 102, 143-149. Iwata, H., Nesumi, H., Ninomiya, S., Takano, Y., & Ukai, Y. (2002). Evaluation Genotype x Environment Interactions Citrus Leaf Morphology Using Image Analysis Elliptic Fourier Descriptors. Breeding Science, 52(2), 89-94. doi:10.1270/jsbbs.52.89 Yoshioka, Y., Iwata, H., Ohsawa, R., & Ninomiya, S. (2004). Analysis petal shape variation Primula sieboldii elliptic fourier descriptors principal component analysis. Annals Botany, 94(5), 657-64. doi:10.1093/aob/mch190","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_asym.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes asymmetric and symmetric variation on OutCoe objects — rm_asym","text":"","code":"botf <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details botSym <- rm_asym(botf) boxplot(botSym) botSymp <- PCA(botSym) plot(botSymp) #> will be deprecated soon, see ?plot_PCA plot(botSymp, amp.shp=5) #> will be deprecated soon, see ?plot_PCA # Asymmetric only botAsym <- rm_sym(botf) boxplot(botAsym) botAsymp <- PCA(botAsym) plot(botAsymp) #> will be deprecated soon, see ?plot_PCA # strange shapes because the original shape was mainly symmetric and would need its # symmetric (eg its average) for a proper reconstruction. Should only be used like that: plot(botAsymp, morpho=FALSE) #> will be deprecated soon, see ?plot_PCA"},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":null,"dir":"Reference","previous_headings":"","what":"Removes harmonics from Coe objects — rm_harm","title":"Removes harmonics from Coe objects — rm_harm","text":"Useful drop harmonics Coe objects. work Fourier-based approached since looks [-D][1-drop] pattern.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Removes harmonics from Coe objects — rm_harm","text":"","code":"rm_harm(x, drop = 1)"},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Removes harmonics from Coe objects — rm_harm","text":"x Coe object drop numeric number harmonics drop","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Removes harmonics from Coe objects — rm_harm","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_harm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Removes harmonics from Coe objects — rm_harm","text":"","code":"data(bot) bf <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) colnames(rm_harm(bf, 1)$coe) #> [1] \"A2\" \"A3\" \"A4\" \"A5\" \"A6\" \"A7\" \"A8\" \"A9\" \"B2\" \"B3\" \"B4\" \"B5\" \"B6\" \"B7\" \"B8\" #> [16] \"B9\" \"C2\" \"C3\" \"C4\" \"C5\" \"C6\" \"C7\" \"C8\" \"C9\" \"D2\" \"D3\" \"D4\" \"D5\" \"D6\" \"D7\" #> [31] \"D8\" \"D9\""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove shapes with missing data in fac — rm_missing","title":"Remove shapes with missing data in fac — rm_missing","text":"row (within given column specified) containing NA $fac corresponding shapes $coo, lines $coe objects also dropped.","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove shapes with missing data in fac — rm_missing","text":"","code":"rm_missing(x, by)"},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove shapes with missing data in fac — rm_missing","text":"x object NA column $fac objects complete views","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove shapes with missing data in fac — rm_missing","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_missing.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove shapes with missing data in fac — rm_missing","text":"","code":"bot$fac$type[3] <- NA bot$fac$fake[9] <- NA bot %>% length() #> [1] 40 bot %>% rm_missing() %>% length #> [1] 38 bot %>% rm_missing(\"fake\") %>% length() #> [1] 39"},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove shapes with incomplete slices — rm_uncomplete","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"Imagine take three views every object study. , can slice, filter chop entire dataset, morphometrics , want combine . forgotten one view, impossible obtain, one objects, combine work. function helps remove ugly ducklings. See examples","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"","code":"rm_uncomplete(x, id, by)"},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"x object remove uncomplete \"\" id objects, within $fac slot column $fac objects complete views","code":""},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rm_uncomplete.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove shapes with incomplete slices — rm_uncomplete","text":"","code":"# we load olea data(olea) # we select the var Aglan since it is the only one complete ol <- filter(olea, var == \"Aglan\") # everything seems fine table(ol$view, ol$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 # indeed rm_uncomplete(ol, id=\"ind\", by=\"view\") #> all ids have 2 slices #> Opn (curves) #> - 60 curves, 98 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 60 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 54 more rows #> - also: $ldk # we mess the ol object by removing a single shape ol.pb <- slice(ol, -1) table(ol.pb$view, ol.pb$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 1 1 1 1 1 1 1 1 1 1 1 #> VL 1 1 1 1 1 1 1 1 1 1 1 # the counterpart has been removed with a notice ol.ok <- rm_uncomplete(ol.pb, \"ind\", \"view\") #> those shapes did not have 2 slices and has been removed: O10 # now you can combine them table(ol.ok$view, ol.ok$ind) #> #> O1 O10 O11 O12 O13 O14 O15 O16 O17 O18 O19 O2 O20 O21 O22 O23 O24 O25 O26 #> VD 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> VL 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #> #> O27 O28 O29 O3 O30 O4 O5 O6 O7 O8 O9 #> VD 0 0 0 0 0 0 0 0 0 0 0 #> VL 0 0 0 0 0 0 0 0 0 0 0"},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":null,"dir":"Reference","previous_headings":"","what":"Renames levels on Momocs objects — rw_fac","title":"Renames levels on Momocs objects — rw_fac","text":"rw_fac stands 'rewriting rule'. Typically useful correct typos import, merge levels within covariates. Drops levels silently.","code":""},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Renames levels on Momocs objects — rw_fac","text":"","code":"rw_fac(x, fac, from, to)"},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Renames levels on Momocs objects — rw_fac","text":"x Momocs object fac id name $fac column look (fac_dispatcher yet supported) level(s) renamed; passed single several characters name used rename /levels","code":""},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Renames levels on Momocs objects — rw_fac","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/rw_fac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Renames levels on Momocs objects — rw_fac","text":"","code":"# single renaming rw_fac(bot, \"type\", \"whisky\", \"agua_de_fuego\")$type # 1 instead of \"type\" is fine too #> type1 type2 type3 type4 type5 #> beer beer beer beer beer #> type6 type7 type8 type9 type10 #> beer beer beer beer beer #> type11 type12 type13 type14 type15 #> beer beer beer beer beer #> type16 type17 type18 type19 type20 #> beer beer beer beer beer #> type21 type22 type23 type24 type25 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type26 type27 type28 type29 type30 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type31 type32 type33 type34 type35 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> type36 type37 type38 type39 type40 #> agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego agua_de_fuego #> Levels: agua_de_fuego beer # several renaming bot2 <- mutate(bot, fake=factor(rep(letters[1:4], 10))) rw_fac(bot2, \"fake\", c(\"a\", \"e\"), \"ae\")$fake #> fake1 fake2 fake3 fake4 fake5 fake6 fake7 fake8 fake9 fake10 fake11 #> ae ae b c ae ae b c ae ae b #> fake12 fake13 fake14 fake15 fake16 fake17 fake18 fake19 fake20 fake21 fake22 #> c ae ae b c ae ae b c ae ae #> fake23 fake24 fake25 fake26 fake27 fake28 fake29 fake30 fake31 fake32 fake33 #> b c ae ae b c ae ae b c ae #> fake34 fake35 fake36 fake37 fake38 fake39 fake40 #> ae b c ae ae b c #> Levels: ae b c"},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample a fraction of shapes — sample_frac","title":"Sample a fraction of shapes — sample_frac","text":"Sample fraction shapes Momocs object. See examples ?dplyr::sample_n.","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample a fraction of shapes — sample_frac","text":"","code":"sample_frac(tbl, size, replace, fac, ...)"},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample a fraction of shapes — sample_frac","text":"tbl Momocs object (Coo, Coe) size numeric (0 < numeric <= 1) fraction shapes select replace logical whether sample done ot without replacement fac column name $fac defined; size applied within levels factor ... additional arguments dplyr::sample_frac maintain generic compatibility","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample a fraction of shapes — sample_frac","text":"Momocs object class","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Sample a fraction of shapes — sample_frac","text":"resulting fraction rounded ceiling.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sample_frac.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample a fraction of shapes — sample_frac","text":"","code":"# samples 50% of the bottles no matter their type sample_frac(bot, 0.5) #> Out (outlines) #> - 20 outlines, 158 +/- 22 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 20 × 2 #> type fake #> #> 1 beer d #> 2 whisky a #> 3 beer c #> 4 beer d #> 5 beer d #> 6 beer d #> # ℹ 14 more rows #> - also: $ldk # 80% bottles of beer and of whisky table(sample_frac(bot, 0.8, fac=\"type\")$fac) #> fake #> type a b c d #> beer 0 0 7 9 #> whisky 10 6 0 0 # bootstrap the same number of bootles of each type but with replacement table(names(sample_frac(bot, 1, replace=TRUE))) #> #> amrut bushmills caney chimay chivas #> 1 2 1 1 2 #> corona dalmore deusventrue glendronach glenmorangie #> 1 1 2 2 1 #> grimbergen guiness highlandpark hoegardeen jackdaniels #> 1 2 2 1 1 #> kingfisher latrappe lindemanskriek magallan makersmark #> 1 1 3 2 1 #> nicechouffe redbreast tamdhu westmalle wildturkey #> 1 1 1 1 2 #> yoichi #> 5"},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":null,"dir":"Reference","previous_headings":"","what":"Sample n shapes — sample_n","title":"Sample n shapes — sample_n","text":"Sample n shapes Momocs object. See examples ?dplyr::sample_n.","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sample n shapes — sample_n","text":"","code":"sample_n(tbl, size, replace, fac, ...)"},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sample n shapes — sample_n","text":"tbl Momocs object (Coo, Coe) size numeric many shapes sample replace logical whether sample done ot without replacement fac column name $fac defined; size applied within levels factor ... additional arguments dplyr::sample_n maintain generic compatibility","code":""},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sample n shapes — sample_n","text":"Momocs object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sample_n.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sample n shapes — sample_n","text":"","code":"# samples 5 bottles no matter their type sample_n(bot, 5) #> Out (outlines) #> - 5 outlines, 165 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 5 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky b #> 4 whisky a #> 5 whisky a #> - also: $ldk # 5 bottles of beer and of whisky table(sample_n(bot, 5, fac=\"type\")$type) #> #> beer whisky #> 5 5 # many repetitions table(names(sample_n(bot, 400, replace=TRUE))) #> #> amrut ballantines brahma bushmills caney #> 9 8 8 10 11 #> chimay chivas corona dalmore deusventrue #> 14 9 16 17 6 #> duvel famousgrouse franziskaner glendronach glenmorangie #> 11 13 11 14 11 #> grimbergen guiness highlandpark hoegardeen jackdaniels #> 8 7 9 9 8 #> jb johnniewalker jupiler kingfisher latrappe #> 11 10 11 14 14 #> lindemanskriek magallan makersmark nicechouffe oban #> 7 17 6 4 7 #> oldpotrero pecheresse redbreast sierranevada tamdhu #> 10 10 14 9 10 #> tanglefoot tauro westmalle wildturkey yoichi #> 6 4 7 12 8"},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":null,"dir":"Reference","previous_headings":"","what":"How many axes to retain this much of variance or trace ? — scree","title":"How many axes to retain this much of variance or trace ? — scree","text":"set functions around PCA/LDA eigen/trace. scree calculates proportion cumulated proportion; scree_min returns minimal number axis use retain given proportion; scree_plot displays screeplot.","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"How many axes to retain this much of variance or trace ? — scree","text":"","code":"scree(x, nax) # S3 method for PCA scree(x, nax) # S3 method for LDA scree(x, nax) scree_min(x, prop) scree_plot(x, nax)"},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"How many axes to retain this much of variance or trace ? — scree","text":"x PCA object nax numeric range axes consider. default scree_min, display 0.99 scree_plot prop numeric many axes enough gather proportion variance. Default 1, axes returned defaut 1: axis returned","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"How many axes to retain this much of variance or trace ? — scree","text":"scree returns data.frame, scree_min numeric, scree_plot ggplot.","code":""},{"path":"http://momx.github.io/Momocs/reference/scree.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"How many axes to retain this much of variance or trace ? — scree","text":"","code":"# On PCA bp <- PCA(efourier(bot)) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) scree(bp) #> # A tibble: 40 × 3 #> axis proportion cumsum #> #> 1 1 0.761 0.761 #> 2 2 0.170 0.931 #> 3 3 0.0294 0.960 #> 4 4 0.0135 0.974 #> 5 5 0.00860 0.982 #> 6 6 0.00719 0.990 #> 7 7 0.00306 0.993 #> 8 8 0.00190 0.994 #> 9 9 0.00159 0.996 #> 10 10 0.00122 0.997 #> # ℹ 30 more rows scree_min(bp, 0.99) #> [1] 7 scree_min(bp, 1) #> [1] 37 scree_plot(bp) scree_plot(bp, 1:5) # on LDA, it uses svd bl <- LDA(PCA(opoly(olea)), \"var\") #> 'nb.pts' missing and set to 91 #> 'degree' missing and set to 5 #> 4 PC retained scree(bl) #> # A tibble: 3 × 3 #> axis proportion cumsum #> #> 1 1 0.913 0.913 #> 2 2 0.0603 0.973 #> 3 3 0.0268 1"},{"path":"http://momx.github.io/Momocs/reference/select.html","id":null,"dir":"Reference","previous_headings":"","what":"Select columns by name — select","title":"Select columns by name — select","text":"Select variables name, $fac. Selected variables can also renamed fly. See examples ?dplyr::select.","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select columns by name — select","text":"","code":"select(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select columns by name — select","text":".data Coo, Coe, PCA object ... comma separated list unquoted expressions","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select columns by name — select","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Select columns by name — select","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/select.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select columns by name — select","text":"","code":"olea #> Opn (curves) #> - 210 curves, 98 +/- 3 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk select(olea, var, view) # drops domes and ind #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 210 × 2 #> var view #> #> 1 Aglan VD #> 2 Aglan VL #> 3 Aglan VD #> 4 Aglan VL #> 5 Aglan VD #> 6 Aglan VL #> # ℹ 204 more rows #> - also: $ldk select(olea, variety=var, domesticated_status=domes, view) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 210 × 3 #> variety domesticated_status view #> #> 1 Aglan cult VD #> 2 Aglan cult VL #> 3 Aglan cult VD #> 4 Aglan cult VL #> 5 Aglan cult VD #> 6 Aglan cult VL #> # ℹ 204 more rows #> - also: $ldk # combine with filter with magrittr pipes # only dorsal views, and 'var' and 'domes' columns filter(olea, view==\"VD\") %>% select(var, domes) #> Opn (curves) #> - 120 curves, 99 +/- 3 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 120 × 2 #> var domes #> #> 1 Aglan cult #> 2 Aglan cult #> 3 Aglan cult #> 4 Aglan cult #> 5 Aglan cult #> 6 Aglan cult #> # ℹ 114 more rows #> - also: $ldk head(olea$fac) #> # A tibble: 6 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 # select some columns select(olea, domes, view) #> Opn (curves) #> - 210 curves, 98 +/- 3 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 210 × 2 #> domes view #> #> 1 cult VD #> 2 cult VL #> 3 cult VD #> 4 cult VL #> 5 cult VD #> 6 cult VL #> # ℹ 204 more rows #> - also: $ldk # remove some columns select(olea, -ind) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 3 classifiers (in $fac): #> # A tibble: 210 × 3 #> var domes view #> #> 1 Aglan cult VD #> 2 Aglan cult VL #> 3 Aglan cult VD #> 4 Aglan cult VL #> 5 Aglan cult VD #> 6 Aglan cult VL #> # ℹ 204 more rows #> - also: $ldk # rename on the fly and select some columns select(olea, foo=domes) #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 210 × 1 #> foo #> #> 1 cult #> 2 cult #> 3 cult #> 4 cult #> 5 cult #> 6 cult #> # ℹ 204 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"sfourier computes radii variation Fourier analysis matrix list coordinates points equally spaced aong curvilinear abscissa.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"","code":"sfourier(x, nb.h) # S3 method for default sfourier(x, nb.h) # S3 method for Out sfourier(x, nb.h) # S3 method for list sfourier(x, nb.h)"},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"x list matrix coordinates object nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"list following components: vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients ao ao harmonic coefficient r vector radii lengths","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"implementation still quite experimental (Dec. 2016)","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"Renaud S, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Radii variation Fourier transform (equally spaced curvilinear abscissa) — sfourier","text":"","code":"molars[4] %>% coo_center %>% coo_scale %>% coo_interpolate(1080) %>% coo_slidedirection(\"right\") %>% coo_sample(360) %T>% coo_plot(zoom=2) %>% sfourier(16) %>% sfourier_i() %>% coo_draw(bor=\"red\", points=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse radii variation Fourier transform — sfourier_i","title":"Inverse radii variation Fourier transform — sfourier_i","text":"sfourier_i uses inverse radii variation (equally spaced curvilinear abscissa) transformation calculate shape, given list Fourier coefficients, typically obtained computed sfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse radii variation Fourier transform — sfourier_i","text":"","code":"sfourier_i(rf, nb.h, nb.pts = 120, dtheta = FALSE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse radii variation Fourier transform — sfourier_i","text":"rf list ao, bn components, typically returned sfourier. nb.h integer. number harmonics calculate/use. nb.pts integer. number points calculate. dtheta logical. Whether use dtheta correction method. FALSE default. TRUE, tries correct angular difference reconstructed points; otherwise equal angles used.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse radii variation Fourier transform — sfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. angle vector angles used. r vector radii calculated.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse radii variation Fourier transform — sfourier_i","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse radii variation Fourier transform — sfourier_i","text":"","code":"coo <- coo_center(bot[1]) # centering is almost mandatory for sfourier family coo_plot(coo) rf <- sfourier(coo, 12) rf #> $an #> [1] 4.604028e-03 -2.999389e-01 -9.402145e-04 1.149290e-02 7.204731e-03 #> [6] -9.029436e-03 -3.801153e-04 -3.509909e-03 3.066128e-03 -1.605563e-04 #> [11] -5.282196e-05 -2.663480e-03 #> #> $bn #> [1] -5.890572e-03 3.958517e-02 -7.064423e-03 -2.988931e-03 1.291082e-02 #> [6] 2.814025e-03 -1.504084e-03 5.682629e-04 5.198896e-03 -3.561684e-05 #> [11] -1.358067e-03 2.234144e-03 #> #> $ao #> [1] 334.5633 #> #> $r #> [1] 139.1167 135.1134 135.8741 136.8427 141.0323 143.5802 151.2095 162.8116 #> [9] 175.5101 182.5204 198.0176 214.4721 223.4262 241.8735 260.7074 269.7883 #> [17] 289.8301 310.0117 320.9760 342.0111 363.0862 373.1664 393.9569 415.7375 #> [25] 436.2997 445.8192 465.8759 484.9159 494.7304 512.1917 523.5711 525.7951 #> [33] 528.7641 528.6261 529.8403 529.9849 528.9630 529.2840 529.5332 529.6230 #> [41] 526.6029 525.3373 516.8135 501.5361 492.0222 473.0432 453.3357 442.8940 #> [49] 422.7064 402.9506 393.5883 373.2914 353.4743 342.9622 323.7894 303.5315 #> [57] 283.8734 274.5648 254.3851 234.8608 225.9056 207.4851 188.9917 179.2651 #> [65] 163.2102 148.4020 142.2876 131.8906 124.2115 121.7441 122.3408 126.4329 #> [73] 133.8555 138.8126 149.4057 160.3977 165.1035 178.0327 190.2983 196.3891 #> [81] 207.9233 218.2629 225.0539 239.8685 256.5975 274.7171 283.4915 303.0400 #> [89] 323.0170 333.5460 353.5262 373.8148 383.4986 404.8965 425.3750 435.1409 #> [97] 455.5781 476.1955 487.0166 508.4428 526.8989 546.1072 554.4755 557.9344 #> [105] 558.1869 558.1342 557.6074 557.8729 556.8590 542.6716 524.9317 515.3814 #> [113] 494.2988 473.6200 462.7267 442.2440 421.9866 401.6471 390.8306 370.6053 #> [121] 350.7010 341.4100 321.0176 301.2409 290.9421 272.0980 254.7364 246.6077 #> [129] 230.9259 217.6545 212.0765 201.6712 191.0722 180.1960 174.3784 163.0992 #> [137] 152.9502 148.4252 #> rfi <- sfourier_i(rf) coo_draw(rfi, border='red', col=NA)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draw 'sfourier' shapes. — sfourier_shape","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"sfourier_shape calculates 'Fourier radii variation shape' given Fourier coefficients (see Details) can generate 'sfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"","code":"sfourier_shape(an, bn, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"sfourier_shape can used specifying nb.h alpha. coefficients sampled uniform distribution \\((-\\pi ; \\pi)\\) amplitude divided \\(harmonicrank^alpha\\). alpha lower 1, consecutive coefficients thus increase. See sfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"Renaud S, Pale JRM, Michaux JR (2003): Adaptive latitudinal trends mandible shape Apodemus wood mice. J Biogeogr 30:1617-1628.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/sfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draw 'sfourier' shapes. — sfourier_shape","text":"","code":"rf <- sfourier(bot[1], 24) sfourier_shape(rf$an, rf$bn) # equivalent to sfourier_i(rf) #> x y #> [1,] -0.290097233 0.000000e+00 #> [2,] -0.271959700 -2.167576e-02 #> [3,] -0.246484918 -3.954193e-02 #> [4,] -0.217733972 -5.296062e-02 #> [5,] -0.189896582 -6.253711e-02 #> [6,] -0.161756328 -6.794564e-02 #> [7,] -0.129280368 -6.684598e-02 #> [8,] -0.093457131 -5.816908e-02 #> [9,] -0.056911599 -4.204430e-02 #> [10,] -0.020498051 -1.782664e-02 #> [11,] 0.012003787 1.224487e-02 #> [12,] 0.037674640 4.510087e-02 #> [13,] 0.059580159 8.409685e-02 #> [14,] 0.077938313 1.309531e-01 #> [15,] 0.087952301 1.787227e-01 #> [16,] 0.089723461 2.260901e-01 #> [17,] 0.084960971 2.763655e-01 #> [18,] 0.070321004 3.163705e-01 #> [19,] 0.046429512 3.314256e-01 #> [20,] 0.019913853 3.334462e-01 #> [21,] -0.006649182 3.343630e-01 #> [22,] -0.031682610 3.176318e-01 #> [23,] -0.049327516 2.726987e-01 #> [24,] -0.057930387 2.191009e-01 #> [25,] -0.060592889 1.723788e-01 #> [26,] -0.056570309 1.275136e-01 #> [27,] -0.044606160 8.221929e-02 #> [28,] -0.026786000 4.118703e-02 #> [29,] -0.003378834 4.388307e-03 #> [30,] 0.025798149 -2.849944e-02 #> [31,] 0.058618676 -5.522233e-02 #> [32,] 0.094446012 -7.575806e-02 #> [33,] 0.130822044 -8.883054e-02 #> [34,] 0.161850879 -9.201979e-02 #> [35,] 0.189408545 -8.857751e-02 #> [36,] 0.220645564 -8.252378e-02 #> [37,] 0.252775395 -7.224049e-02 #> [38,] 0.279699320 -5.635869e-02 #> [39,] 0.302648329 -3.627852e-02 #> [40,] 0.317717406 -1.264133e-02 #> [41,] 0.314194975 1.250118e-02 #> [42,] 0.292885334 3.510823e-02 #> [43,] 0.262693915 5.293215e-02 #> [44,] 0.225005085 6.430404e-02 #> [45,] 0.180944070 6.767500e-02 #> [46,] 0.137869807 6.447525e-02 #> [47,] 0.097568618 5.547232e-02 #> [48,] 0.056393859 3.829245e-02 #> [49,] 0.016752301 1.343754e-02 #> [50,] -0.016789374 -1.581660e-02 #> [51,] -0.044589066 -4.925793e-02 #> [52,] -0.067069580 -8.710755e-02 #> [53,] -0.083178505 -1.278980e-01 #> [54,] -0.093570208 -1.724712e-01 #> [55,] -0.097166720 -2.190209e-01 #> [56,] -0.090346447 -2.570238e-01 #> [57,] -0.073587369 -2.783178e-01 #> [58,] -0.051890843 -2.868696e-01 #> [59,] -0.028919129 -2.899267e-01 #> [60,] -0.005779918 -2.906509e-01 #> [61,] 0.017359802 -2.906800e-01 #> [62,] 0.040168810 -2.867352e-01 #> [63,] 0.059710443 -2.686342e-01 #> [64,] 0.071446661 -2.324054e-01 #> [65,] 0.074293397 -1.872085e-01 #> [66,] 0.069720055 -1.416741e-01 #> [67,] 0.057052553 -9.586057e-02 #> [68,] 0.036028165 -5.085343e-02 #> [69,] 0.009821433 -1.175738e-02 #> [70,] -0.020089825 2.049331e-02 #> [71,] -0.055257428 4.805599e-02 #> [72,] -0.094037716 6.947178e-02 #> [73,] -0.132851358 8.268862e-02 #> [74,] -0.171860865 8.886274e-02 #> [75,] -0.210848274 8.856668e-02 #> [76,] -0.245371280 8.080615e-02 #> [77,] -0.272295567 6.623194e-02 #> [78,] -0.290646288 4.662644e-02 #> [79,] -0.297232987 2.369010e-02 #> [80,] -0.290097233 7.105333e-17 sfourier_shape() # not very interesting #> x y #> [1,] -0.945118007 0.000000e+00 #> [2,] -1.089655560 -8.684786e-02 #> [3,] -1.224220418 -1.963935e-01 #> [4,] -1.343537389 -3.267959e-01 #> [5,] -1.442069318 -4.749051e-01 #> [6,] -1.515125904 -6.364277e-01 #> [7,] -1.559856027 -8.065425e-01 #> [8,] -1.575773677 -9.807844e-01 #> [9,] -1.564617563 -1.155885e+00 #> [10,] -1.529566340 -1.330225e+00 #> [11,] -1.474053174 -1.503658e+00 #> [12,] -1.400572047 -1.676645e+00 #> [13,] -1.309892716 -1.848902e+00 #> [14,] -1.200988990 -2.017920e+00 #> [15,] -1.071767042 -2.177875e+00 #> [16,] -0.920422241 -2.319330e+00 #> [17,] -0.747034817 -2.429994e+00 #> [18,] -0.554907030 -2.496498e+00 #> [19,] -0.351185770 -2.506853e+00 #> [20,] -0.146498336 -2.453031e+00 #> [21,] 0.046394820 -2.333025e+00 #> [22,] 0.214638297 -2.151842e+00 #> [23,] 0.347504343 -1.921118e+00 #> [24,] 0.438218807 -1.657405e+00 #> [25,] 0.484901075 -1.379480e+00 #> [26,] 0.490363516 -1.105315e+00 #> [27,] 0.460828661 -8.494120e-01 #> [28,] 0.403923046 -6.210854e-01 #> [29,] 0.326508157 -4.240570e-01 #> [30,] 0.232951810 -2.573439e-01 #> [31,] 0.124314258 -1.171115e-01 #> [32,] -0.001340897 1.075575e-03 #> [33,] -0.147624087 1.002394e-01 #> [34,] -0.317886999 1.807336e-01 #> [35,] -0.513251749 2.400238e-01 #> [36,] -0.731178192 2.734684e-01 #> [37,] -0.964983613 2.757819e-01 #> [38,] -1.204450247 2.426936e-01 #> [39,] -1.437343375 1.722947e-01 #> [40,] -1.651408292 6.570619e-02 #> [41,] -1.836292173 -7.306234e-02 #> [42,] -1.984880367 -2.379280e-01 #> [43,] -2.093730023 -4.218812e-01 #> [44,] -2.162566216 -6.180382e-01 #> [45,] -2.193090184 -8.202390e-01 #> [46,] -2.187549211 -1.023014e+00 #> [47,] -2.147572924 -1.220996e+00 #> [48,] -2.073675643 -1.408063e+00 #> [49,] -1.965592490 -1.576662e+00 #> [50,] -1.823330567 -1.717688e+00 #> [51,] -1.648565296 -1.821184e+00 #> [52,] -1.445874819 -1.877850e+00 #> [53,] -1.223327227 -1.881028e+00 #> [54,] -0.992112686 -1.828689e+00 #> [55,] -0.765194301 -1.724804e+00 #> [56,] -0.555254267 -1.579625e+00 #> [57,] -0.372444248 -1.408637e+00 #> [58,] -0.222539419 -1.230271e+00 #> [59,] -0.106013852 -1.062835e+00 #> [60,] -0.018321147 -9.213033e-01 #> [61,] 0.048656444 -8.147245e-01 #> [62,] 0.104343507 -7.448305e-01 #> [63,] 0.156966287 -7.061831e-01 #> [64,] 0.211445246 -6.878001e-01 #> [65,] 0.268211852 -6.758548e-01 #> [66,] 0.323221424 -6.567994e-01 #> [67,] 0.369109956 -6.201842e-01 #> [68,] 0.397141945 -5.605622e-01 #> [69,] 0.399402278 -4.781304e-01 #> [70,] 0.370649888 -3.780940e-01 #> [71,] 0.309378472 -2.690586e-01 #> [72,] 0.217877577 -1.609604e-01 #> [73,] 0.101379497 -6.310007e-02 #> [74,] -0.033373044 1.725594e-02 #> [75,] -0.179667239 7.546911e-02 #> [76,] -0.332009446 1.093380e-01 #> [77,] -0.486653324 1.183713e-01 #> [78,] -0.641391147 1.028941e-01 #> [79,] -0.794775929 6.334533e-02 #> [80,] -0.945118007 2.314871e-16 sfourier_shape(nb.h=12) # better #> x y #> [1,] -3.73028216 0.000000e+00 #> [2,] -3.79081371 -3.021359e-01 #> [3,] -3.74114732 -6.001673e-01 #> [4,] -3.61177769 -8.785124e-01 #> [5,] -3.43507276 -1.131245e+00 #> [6,] -3.22637825 -1.355238e+00 #> [7,] -2.98195669 -1.541857e+00 #> [8,] -2.69374968 -1.676629e+00 #> [9,] -2.36746422 -1.749000e+00 #> [10,] -2.02848468 -1.764122e+00 #> [11,] -1.71086482 -1.745226e+00 #> [12,] -1.43868404 -1.722270e+00 #> [13,] -1.21456649 -1.714350e+00 #> [14,] -1.02323427 -1.719254e+00 #> [15,] -0.84545308 -1.717996e+00 #> [16,] -0.67059890 -1.689812e+00 #> [17,] -0.49955732 -1.624986e+00 #> [18,] -0.33920388 -1.526061e+00 #> [19,] -0.19602476 -1.399275e+00 #> [20,] -0.07446420 -1.246861e+00 #> [21,] 0.02125625 -1.068899e+00 #> [22,] 0.08706282 -8.728423e-01 #> [23,] 0.12298195 -6.798846e-01 #> [24,] 0.13720637 -5.189339e-01 #> [25,] 0.14417303 -4.101533e-01 #> [26,] 0.15553796 -3.505940e-01 #> [27,] 0.17054532 -3.143538e-01 #> [28,] 0.17457563 -2.684332e-01 #> [29,] 0.14836597 -1.926924e-01 #> [30,] 0.08076147 -8.921790e-02 #> [31,] -0.02595140 2.444779e-02 #> [32,] -0.16280016 1.305870e-01 #> [33,] -0.32648936 2.216922e-01 #> [34,] -0.52516205 2.985792e-01 #> [35,] -0.77085296 3.604918e-01 #> [36,] -1.06420436 3.980237e-01 #> [37,] -1.38501767 3.958232e-01 #> [38,] -1.69830982 3.422051e-01 #> [39,] -1.97268399 2.364661e-01 #> [40,] -2.19714866 8.742009e-02 #> [41,] -2.38344487 -9.483244e-02 #> [42,] -2.55272406 -3.059956e-01 #> [43,] -2.71784631 -5.476390e-01 #> [44,] -2.87509273 -8.216706e-01 #> [45,] -3.01006409 -1.125796e+00 #> [46,] -3.11033755 -1.454559e+00 #> [47,] -3.17270089 -1.803829e+00 #> [48,] -3.19899367 -2.172175e+00 #> [49,] -3.18554363 -2.555223e+00 #> [50,] -3.11700723 -2.936409e+00 #> [51,] -2.97140412 -3.282536e+00 #> [52,] -2.73341309 -3.550058e+00 #> [53,] -2.40622080 -3.699884e+00 #> [54,] -2.01370848 -3.711722e+00 #> [55,] -1.59238058 -3.589343e+00 #> [56,] -1.17931764 -3.355004e+00 #> [57,] -0.80341929 -3.038645e+00 #> [58,] -0.48285695 -2.669392e+00 #> [59,] -0.22670844 -2.272850e+00 #> [60,] -0.03722754 -1.872036e+00 #> [61,] 0.08884098 -1.487592e+00 #> [62,] 0.15903666 -1.135244e+00 #> [63,] 0.18276462 -8.222485e-01 #> [64,] 0.16785204 -5.459978e-01 #> [65,] 0.11761273 -2.963670e-01 #> [66,] 0.02989255 -6.074290e-02 #> [67,] -0.10145958 1.704739e-01 #> [68,] -0.28309891 3.995915e-01 #> [69,] -0.51751306 6.195225e-01 #> [70,] -0.79872291 8.147643e-01 #> [71,] -1.11093808 9.661547e-01 #> [72,] -1.43263632 1.058382e+00 #> [73,] -1.74574192 1.086575e+00 #> [74,] -2.04499551 1.057390e+00 #> [75,] -2.34006808 9.829441e-01 #> [76,] -2.64618338 8.714462e-01 #> [77,] -2.96731752 7.217568e-01 #> [78,] -3.28344281 5.267408e-01 #> [79,] -3.55279054 2.831649e-01 #> [80,] -3.73028216 9.136556e-16 sfourier_shape(nb.h=6, alpha=0.4, nb.pts=500) #> x y #> [1,] -4.627376537 0.000000e+00 #> [2,] -4.433329065 -5.582545e-02 #> [3,] -4.224758345 -1.064150e-01 #> [4,] -4.002543436 -1.512667e-01 #> [5,] -3.767629800 -1.899219e-01 #> [6,] -3.521024150 -2.219692e-01 #> [7,] -3.263788935 -2.470472e-01 #> [8,] -2.997036513 -2.648476e-01 #> [9,] -2.721923035 -2.751171e-01 #> [10,] -2.439642077 -2.776596e-01 #> [11,] -2.151418074 -2.723378e-01 #> [12,] -1.858499581 -2.590742e-01 #> [13,] -1.562152419 -2.378520e-01 #> [14,] -1.263652728 -2.087150e-01 #> [15,] -0.964280000 -1.717679e-01 #> [16,] -0.665310099 -1.271752e-01 #> [17,] -0.368008349 -7.516038e-02 #> [18,] -0.073622700 -1.600461e-02 #> [19,] 0.216622959 4.995549e-02 #> [20,] 0.501535323 1.223299e-01 #> [21,] 0.779957967 2.006780e-01 #> [22,] 1.050777396 2.845114e-01 #> [23,] 1.312928801 3.732977e-01 #> [24,] 1.565401492 4.664638e-01 #> [25,] 1.807243971 5.634001e-01 #> [26,] 2.037568623 6.634647e-01 #> [27,] 2.255555987 7.659880e-01 #> [28,] 2.460458599 8.702773e-01 #> [29,] 2.651604365 9.756215e-01 #> [30,] 2.828399466 1.081296e+00 #> [31,] 2.990330767 1.186570e+00 #> [32,] 3.136967724 1.290706e+00 #> [33,] 3.267963782 1.392973e+00 #> [34,] 3.383057253 1.492643e+00 #> [35,] 3.482071683 1.589005e+00 #> [36,] 3.564915697 1.681362e+00 #> [37,] 3.631582343 1.769040e+00 #> [38,] 3.682147928 1.851395e+00 #> [39,] 3.716770372 1.927811e+00 #> [40,] 3.735687085 1.997711e+00 #> [41,] 3.739212390 2.060557e+00 #> [42,] 3.727734519 2.115855e+00 #> [43,] 3.701712184 2.163158e+00 #> [44,] 3.661670782 2.202072e+00 #> [45,] 3.608198236 2.232254e+00 #> [46,] 3.541940509 2.253418e+00 #> [47,] 3.463596839 2.265338e+00 #> [48,] 3.373914701 2.267845e+00 #> [49,] 3.273684558 2.260832e+00 #> [50,] 3.163734428 2.244255e+00 #> [51,] 3.044924295 2.218130e+00 #> [52,] 2.918140422 2.182539e+00 #> [53,] 2.784289581 2.137621e+00 #> [54,] 2.644293265 2.083581e+00 #> [55,] 2.499081894 2.020679e+00 #> [56,] 2.349589075 1.949237e+00 #> [57,] 2.196745937 1.869630e+00 #> [58,] 2.041475583 1.782289e+00 #> [59,] 1.884687703 1.687693e+00 #> [60,] 1.727273364 1.586370e+00 #> [61,] 1.570100018 1.478893e+00 #> [62,] 1.414006763 1.365873e+00 #> [63,] 1.259799875 1.247959e+00 #> [64,] 1.108248641 1.125831e+00 #> [65,] 0.960081515 1.000197e+00 #> [66,] 0.815982618 8.717886e-01 #> [67,] 0.676588603 7.413547e-01 #> [68,] 0.542485892 6.096580e-01 #> [69,] 0.414208305 4.774694e-01 #> [70,] 0.292235085 3.455634e-01 #> [71,] 0.176989328 2.147129e-01 #> [72,] 0.068836826 8.568446e-02 #> [73,] -0.031914693 -4.076659e-02 #> [74,] -0.125015907 -1.639010e-01 #> [75,] -0.210275850 -2.830002e-01 #> [76,] -0.287561464 -3.973705e-01 #> [77,] -0.356796774 -5.063479e-01 #> [78,] -0.417961694 -6.093015e-01 #> [79,] -0.471090475 -7.056376e-01 #> [80,] -0.516269827 -7.948032e-01 #> [81,] -0.553636720 -8.762891e-01 #> [82,] -0.583375898 -9.496328e-01 #> [83,] -0.605717121 -1.014421e+00 #> [84,] -0.620932169 -1.070293e+00 #> [85,] -0.629331624 -1.116939e+00 #> [86,] -0.631261470 -1.154105e+00 #> [87,] -0.627099534 -1.181595e+00 #> [88,] -0.617251795 -1.199267e+00 #> [89,] -0.602148591 -1.207036e+00 #> [90,] -0.582240768 -1.204875e+00 #> [91,] -0.557995780 -1.192811e+00 #> [92,] -0.529893781 -1.170930e+00 #> [93,] -0.498423747 -1.139369e+00 #> [94,] -0.464079635 -1.098320e+00 #> [95,] -0.427356630 -1.048023e+00 #> [96,] -0.388747489 -9.887688e-01 #> [97,] -0.348739018 -9.208941e-01 #> [98,] -0.307808706 -8.447780e-01 #> [99,] -0.266421528 -7.608402e-01 #> [100,] -0.225026950 -6.695371e-01 #> [101,] -0.184056148 -5.713584e-01 #> [102,] -0.143919460 -4.668239e-01 #> [103,] -0.105004083 -3.564786e-01 #> [104,] -0.067672028 -2.408900e-01 #> [105,] -0.032258349 -1.206429e-01 #> [106,] 0.000930360 3.663704e-03 #> [107,] 0.031617179 1.314216e-01 #> [108,] 0.059555797 2.620170e-01 #> [109,] 0.084531157 3.948349e-01 #> [110,] 0.106359826 5.292628e-01 #> [111,] 0.124890076 6.646951e-01 #> [112,] 0.140001702 8.005368e-01 #> [113,] 0.151605574 9.362071e-01 #> [114,] 0.159642930 1.071143e+00 #> [115,] 0.164084435 1.204802e+00 #> [116,] 0.164929016 1.336668e+00 #> [117,] 0.162202475 1.466249e+00 #> [118,] 0.155955923 1.593086e+00 #> [119,] 0.146264033 1.716749e+00 #> [120,] 0.133223137 1.836846e+00 #> [121,] 0.116949199 1.953017e+00 #> [122,] 0.097575667 2.064943e+00 #> [123,] 0.075251245 2.172341e+00 #> [124,] 0.050137591 2.274971e+00 #> [125,] 0.022406980 2.372629e+00 #> [126,] -0.007760058 2.465155e+00 #> [127,] -0.040177094 2.552427e+00 #> [128,] -0.074654133 2.634364e+00 #> [129,] -0.110999897 2.710924e+00 #> [130,] -0.149024040 2.782103e+00 #> [131,] -0.188539275 2.847934e+00 #> [132,] -0.229363393 2.908485e+00 #> [133,] -0.271321155 2.963859e+00 #> [134,] -0.314246041 3.014189e+00 #> [135,] -0.357981845 3.059637e+00 #> [136,] -0.402384096 3.100393e+00 #> [137,] -0.447321296 3.136673e+00 #> [138,] -0.492675970 3.168710e+00 #> [139,] -0.538345508 3.196760e+00 #> [140,] -0.584242813 3.221092e+00 #> [141,] -0.630296726 3.241990e+00 #> [142,] -0.676452245 3.259746e+00 #> [143,] -0.722670536 3.274659e+00 #> [144,] -0.768928722 3.287031e+00 #> [145,] -0.815219480 3.297166e+00 #> [146,] -0.861550426 3.305363e+00 #> [147,] -0.907943314 3.311917e+00 #> [148,] -0.954433052 3.317116e+00 #> [149,] -1.001066541 3.321233e+00 #> [150,] -1.047901360 3.324532e+00 #> [151,] -1.095004306 3.327258e+00 #> [152,] -1.142449802 3.329639e+00 #> [153,] -1.190318193 3.331882e+00 #> [154,] -1.238693949 3.334174e+00 #> [155,] -1.287663792 3.336676e+00 #> [156,] -1.337314765 3.339528e+00 #> [157,] -1.387732261 3.342839e+00 #> [158,] -1.438998042 3.346696e+00 #> [159,] -1.491188260 3.351156e+00 #> [160,] -1.544371493 3.356251e+00 #> [161,] -1.598606842 3.361983e+00 #> [162,] -1.653942074 3.368329e+00 #> [163,] -1.710411865 3.375238e+00 #> [164,] -1.768036130 3.382633e+00 #> [165,] -1.826818484 3.390412e+00 #> [166,] -1.886744835 3.398450e+00 #> [167,] -1.947782128 3.406598e+00 #> [168,] -2.009877256 3.414689e+00 #> [169,] -2.072956149 3.422533e+00 #> [170,] -2.136923057 3.429927e+00 #> [171,] -2.201660027 3.436652e+00 #> [172,] -2.267026591 3.442474e+00 #> [173,] -2.332859667 3.447151e+00 #> [174,] -2.398973676 3.450435e+00 #> [175,] -2.465160879 3.452068e+00 #> [176,] -2.531191939 3.451794e+00 #> [177,] -2.596816695 3.449354e+00 #> [178,] -2.661765154 3.444494e+00 #> [179,] -2.725748693 3.436964e+00 #> [180,] -2.788461461 3.426521e+00 #> [181,] -2.849581979 3.412935e+00 #> [182,] -2.908774916 3.395985e+00 #> [183,] -2.965693039 3.375468e+00 #> [184,] -3.019979320 3.351197e+00 #> [185,] -3.071269177 3.323005e+00 #> [186,] -3.119192842 3.290745e+00 #> [187,] -3.163377841 3.254293e+00 #> [188,] -3.203451545 3.213552e+00 #> [189,] -3.239043804 3.168446e+00 #> [190,] -3.269789615 3.118929e+00 #> [191,] -3.295331819 3.064983e+00 #> [192,] -3.315323806 3.006617e+00 #> [193,] -3.329432188 2.943869e+00 #> [194,] -3.337339447 2.876805e+00 #> [195,] -3.338746512 2.805523e+00 #> [196,] -3.333375252 2.730147e+00 #> [197,] -3.320970870 2.650830e+00 #> [198,] -3.301304172 2.567752e+00 #> [199,] -3.274173686 2.481120e+00 #> [200,] -3.239407629 2.391167e+00 #> [201,] -3.196865687 2.298148e+00 #> [202,] -3.146440608 2.202341e+00 #> [203,] -3.088059580 2.104048e+00 #> [204,] -3.021685390 2.003584e+00 #> [205,] -2.947317354 1.901284e+00 #> [206,] -2.864991998 1.797499e+00 #> [207,] -2.774783494 1.692590e+00 #> [208,] -2.676803843 1.586927e+00 #> [209,] -2.571202796 1.480890e+00 #> [210,] -2.458167516 1.374862e+00 #> [211,] -2.337921982 1.269229e+00 #> [212,] -2.210726134 1.164378e+00 #> [213,] -2.076874767 1.060692e+00 #> [214,] -1.936696174 9.585491e-01 #> [215,] -1.790550564 8.583193e-01 #> [216,] -1.638828235 7.603634e-01 #> [217,] -1.481947546 6.650295e-01 #> [218,] -1.320352681 5.726511e-01 #> [219,] -1.154511226 4.835452e-01 #> [220,] -0.984911582 3.980103e-01 #> [221,] -0.812060220 3.163244e-01 #> [222,] -0.636478812 2.387439e-01 #> [223,] -0.458701243 1.655015e-01 #> [224,] -0.279270541 9.680565e-02 #> [225,] -0.098735734 3.283887e-02 #> [226,] 0.082351332 -2.624263e-02 #> [227,] 0.263439206 -8.030977e-02 #> [228,] 0.443980029 -1.292610e-01 #> [229,] 0.623432721 -1.730224e-01 #> [230,] 0.801266107 -2.115477e-01 #> [231,] 0.976961978 -2.448184e-01 #> [232,] 1.150018056 -2.728425e-01 #> [233,] 1.319950846 -2.956548e-01 #> [234,] 1.486298345 -3.133153e-01 #> [235,] 1.648622604 -3.259088e-01 #> [236,] 1.806512109 -3.335429e-01 #> [237,] 1.959583970 -3.363477e-01 #> [238,] 2.107485904 -3.344731e-01 #> [239,] 2.249897996 -3.280880e-01 #> [240,] 2.386534221 -3.173782e-01 #> [241,] 2.517143730 -3.025445e-01 #> [242,] 2.641511868 -2.838008e-01 #> [243,] 2.759460944 -2.613717e-01 #> [244,] 2.870850727 -2.354911e-01 #> [245,] 2.975578676 -2.063994e-01 #> [246,] 3.073579898 -1.743418e-01 #> [247,] 3.164826842 -1.395657e-01 #> [248,] 3.249328723 -1.023190e-01 #> [249,] 3.327130692 -6.284809e-02 #> [250,] 3.398312748 -2.139530e-02 #> [251,] 3.462988412 2.180249e-02 #> [252,] 3.521303171 6.651593e-02 #> [253,] 3.573432693 1.125248e-01 #> [254,] 3.619580855 1.596199e-01 #> [255,] 3.659977569 2.076038e-01 #> [256,] 3.694876447 2.562932e-01 #> [257,] 3.724552310 3.055188e-01 #> [258,] 3.749298571 3.551275e-01 #> [259,] 3.769424505 4.049823e-01 #> [260,] 3.785252431 4.549631e-01 #> [261,] 3.797114832 5.049672e-01 #> [262,] 3.805351432 5.549097e-01 #> [263,] 3.810306249 6.047228e-01 #> [264,] 3.812324661 6.543565e-01 #> [265,] 3.811750493 7.037775e-01 #> [266,] 3.808923154 7.529688e-01 #> [267,] 3.804174856 8.019294e-01 #> [268,] 3.797827914 8.506726e-01 #> [269,] 3.790192174 8.992255e-01 #> [270,] 3.781562572 9.476275e-01 #> [271,] 3.772216846 9.959287e-01 #> [272,] 3.762413426 1.044189e+00 #> [273,] 3.752389504 1.092476e+00 #> [274,] 3.742359318 1.140863e+00 #> [275,] 3.732512645 1.189428e+00 #> [276,] 3.723013520 1.238250e+00 #> [277,] 3.713999198 1.287412e+00 #> [278,] 3.705579358 1.336990e+00 #> [279,] 3.697835550 1.387062e+00 #> [280,] 3.690820904 1.437697e+00 #> [281,] 3.684560088 1.488959e+00 #> [282,] 3.679049519 1.540900e+00 #> [283,] 3.674257826 1.593565e+00 #> [284,] 3.670126556 1.646983e+00 #> [285,] 3.666571124 1.701171e+00 #> [286,] 3.663481986 1.756129e+00 #> [287,] 3.660726033 1.811841e+00 #> [288,] 3.658148195 1.868273e+00 #> [289,] 3.655573232 1.925372e+00 #> [290,] 3.652807708 1.983065e+00 #> [291,] 3.649642117 2.041258e+00 #> [292,] 3.645853154 2.099837e+00 #> [293,] 3.641206113 2.158667e+00 #> [294,] 3.635457372 2.217592e+00 #> [295,] 3.628356972 2.276435e+00 #> [296,] 3.619651246 2.335000e+00 #> [297,] 3.609085484 2.393070e+00 #> [298,] 3.596406612 2.450409e+00 #> [299,] 3.581365857 2.506766e+00 #> [300,] 3.563721386 2.561871e+00 #> [301,] 3.543240883 2.615441e+00 #> [302,] 3.519704048 2.667179e+00 #> [303,] 3.492905004 2.716779e+00 #> [304,] 3.462654575 2.763923e+00 #> [305,] 3.428782438 2.808289e+00 #> [306,] 3.391139102 2.849548e+00 #> [307,] 3.349597726 2.887372e+00 #> [308,] 3.304055742 2.921431e+00 #> [309,] 3.254436270 2.951399e+00 #> [310,] 3.200689328 2.976956e+00 #> [311,] 3.142792800 2.997792e+00 #> [312,] 3.080753184 3.013605e+00 #> [313,] 3.014606088 3.024111e+00 #> [314,] 2.944416478 3.029039e+00 #> [315,] 2.870278686 3.028141e+00 #> [316,] 2.792316158 3.021188e+00 #> [317,] 2.710680960 3.007976e+00 #> [318,] 2.625553034 2.988330e+00 #> [319,] 2.537139220 2.962102e+00 #> [320,] 2.445672038 2.929173e+00 #> [321,] 2.351408260 2.889461e+00 #> [322,] 2.254627259 2.842915e+00 #> [323,] 2.155629168 2.789522e+00 #> [324,] 2.054732853 2.729304e+00 #> [325,] 1.952273723 2.662321e+00 #> [326,] 1.848601387 2.588674e+00 #> [327,] 1.744077187 2.508499e+00 #> [328,] 1.639071619 2.421975e+00 #> [329,] 1.533961667 2.329317e+00 #> [330,] 1.429128070 2.230778e+00 #> [331,] 1.324952549 2.126652e+00 #> [332,] 1.221815014 2.017265e+00 #> [333,] 1.120090768 1.902982e+00 #> [334,] 1.020147745 1.784200e+00 #> [335,] 0.922343796 1.661348e+00 #> [336,] 0.827024043 1.534883e+00 #> [337,] 0.734518334 1.405291e+00 #> [338,] 0.645138807 1.273083e+00 #> [339,] 0.559177600 1.138791e+00 #> [340,] 0.476904708 1.002964e+00 #> [341,] 0.398566021 8.661696e-01 #> [342,] 0.324381551 7.289846e-01 #> [343,] 0.254543865 5.919958e-01 #> [344,] 0.189216744 4.557947e-01 #> [345,] 0.128534065 3.209738e-01 #> [346,] 0.072598937 1.881230e-01 #> [347,] 0.021483077 5.782568e-02 #> [348,] -0.024773551 -6.934495e-02 #> [349,] -0.066162841 -1.928298e-01 #> [350,] -0.102708380 -3.120876e-01 #> [351,] -0.134465034 -4.265987e-01 #> [352,] -0.161518265 -5.358683e-01 #> [353,] -0.183983198 -6.394304e-01 #> [354,] -0.202003441 -7.368507e-01 #> [355,] -0.215749669 -8.277298e-01 #> [356,] -0.225417978 -9.117059e-01 #> [357,] -0.231228029 -9.884580e-01 #> [358,] -0.233420990 -1.057708e+00 #> [359,] -0.232257302 -1.119221e+00 #> [360,] -0.228014273 -1.172813e+00 #> [361,] -0.220983540 -1.218343e+00 #> [362,] -0.211468397 -1.255725e+00 #> [363,] -0.199781029 -1.284918e+00 #> [364,] -0.186239670 -1.305936e+00 #> [365,] -0.171165703 -1.318842e+00 #> [366,] -0.154880737 -1.323751e+00 #> [367,] -0.137703676 -1.320828e+00 #> [368,] -0.119947813 -1.310286e+00 #> [369,] -0.101917969 -1.292390e+00 #> [370,] -0.083907703 -1.267447e+00 #> [371,] -0.066196621 -1.235813e+00 #> [372,] -0.049047805 -1.197883e+00 #> [373,] -0.032705378 -1.154094e+00 #> [374,] -0.017392248 -1.104919e+00 #> [375,] -0.003308021 -1.050866e+00 #> [376,] 0.009372866 -9.924735e-01 #> [377,] 0.020502798 -9.303053e-01 #> [378,] 0.029962396 -8.649498e-01 #> [379,] 0.037661667 -7.970141e-01 #> [380,] 0.043540906 -7.271203e-01 #> [381,] 0.047571307 -6.559008e-01 #> [382,] 0.049755300 -5.839945e-01 #> [383,] 0.050126593 -5.120419e-01 #> [384,] 0.048749926 -4.406810e-01 #> [385,] 0.045720529 -3.705422e-01 #> [386,] 0.041163292 -3.022446e-01 #> [387,] 0.035231645 -2.363908e-01 #> [388,] 0.028106155 -1.735634e-01 #> [389,] 0.019992857 -1.143202e-01 #> [390,] 0.011121318 -5.919034e-02 #> [391,] 0.001742456 -8.670729e-03 #> [392,] -0.007873869 3.677790e-02 #> [393,] -0.017441487 7.673421e-02 #> [394,] -0.026660735 1.108194e-01 #> [395,] -0.035221452 1.387000e-01 #> [396,] -0.042806122 1.600905e-01 #> [397,] -0.049093143 1.747553e-01 #> [398,] -0.053760193 1.825106e-01 #> [399,] -0.056487671 1.832260e-01 #> [400,] -0.056962178 1.768255e-01 #> [401,] -0.054880017 1.632880e-01 #> [402,] -0.049950676 1.426479e-01 #> [403,] -0.041900270 1.149949e-01 #> [404,] -0.030474909 8.047325e-02 #> [405,] -0.015443962 3.928130e-02 #> [406,] 0.003396802 -8.330104e-03 #> [407,] 0.026222243 -6.205918e-02 #> [408,] 0.053175058 -1.215553e-01 #> [409,] 0.084363200 -1.864212e-01 #> [410,] 0.119857537 -2.562160e-01 #> [411,] 0.159689775 -3.304580e-01 #> [412,] 0.203850648 -4.086285e-01 #> [413,] 0.252288427 -4.901746e-01 #> [414,] 0.304907735 -5.745141e-01 #> [415,] 0.361568698 -6.610389e-01 #> [416,] 0.422086443 -7.491195e-01 #> [417,] 0.486230956 -8.381099e-01 #> [418,] 0.553727293 -9.273516e-01 #> [419,] 0.624256173 -1.016179e+00 #> [420,] 0.697454933 -1.103923e+00 #> [421,] 0.772918855 -1.189917e+00 #> [422,] 0.850202861 -1.273503e+00 #> [423,] 0.928823565 -1.354032e+00 #> [424,] 1.008261682 -1.430874e+00 #> [425,] 1.087964768 -1.503418e+00 #> [426,] 1.167350287 -1.571081e+00 #> [427,] 1.245808989 -1.633307e+00 #> [428,] 1.322708566 -1.689576e+00 #> [429,] 1.397397580 -1.739407e+00 #> [430,] 1.469209627 -1.782357e+00 #> [431,] 1.537467710 -1.818031e+00 #> [432,] 1.601488808 -1.846081e+00 #> [433,] 1.660588581 -1.866207e+00 #> [434,] 1.714086213 -1.878166e+00 #> [435,] 1.761309336 -1.881767e+00 #> [436,] 1.801599004 -1.876876e+00 #> [437,] 1.834314694 -1.863415e+00 #> [438,] 1.858839286 -1.841367e+00 #> [439,] 1.874583988 -1.810772e+00 #> [440,] 1.880993174 -1.771726e+00 #> [441,] 1.877549095 -1.724387e+00 #> [442,] 1.863776434 -1.668967e+00 #> [443,] 1.839246654 -1.605735e+00 #> [444,] 1.803582132 -1.535012e+00 #> [445,] 1.756460015 -1.457173e+00 #> [446,] 1.697615797 -1.372639e+00 #> [447,] 1.626846559 -1.281880e+00 #> [448,] 1.544013874 -1.185407e+00 #> [449,] 1.449046324 -1.083772e+00 #> [450,] 1.341941624 -9.775617e-01 #> [451,] 1.222768332 -8.673937e-01 #> [452,] 1.091667110 -7.539138e-01 #> [453,] 0.948851551 -6.377897e-01 #> [454,] 0.794608527 -5.197074e-01 #> [455,] 0.629298075 -4.003658e-01 #> [456,] 0.453352805 -2.804720e-01 #> [457,] 0.267276829 -1.607361e-01 #> [458,] 0.071644204 -4.186650e-02 #> [459,] -0.132903085 7.543553e-02 #> [460,] -0.345657620 1.904806e-01 #> [461,] -0.565849492 3.025960e-01 #> [462,] -0.792649690 4.111309e-01 #> [463,] -1.025173911 5.154605e-01 #> [464,] -1.262486771 6.149909e-01 #> [465,] -1.503606402 7.091629e-01 #> [466,] -1.747509396 7.974565e-01 #> [467,] -1.993136078 8.793942e-01 #> [468,] -2.239396075 9.545447e-01 #> [469,] -2.485174143 1.022526e+00 #> [470,] -2.729336218 1.083007e+00 #> [471,] -2.970735659 1.135712e+00 #> [472,] -3.208219638 1.180420e+00 #> [473,] -3.440635644 1.216971e+00 #> [474,] -3.666838049 1.245260e+00 #> [475,] -3.885694707 1.265244e+00 #> [476,] -4.096093533 1.276938e+00 #> [477,] -4.296949032 1.280420e+00 #> [478,] -4.487208720 1.275823e+00 #> [479,] -4.665859408 1.263341e+00 #> [480,] -4.831933307 1.243224e+00 #> [481,] -4.984513904 1.215777e+00 #> [482,] -5.122741581 1.181357e+00 #> [483,] -5.245818935 1.140372e+00 #> [484,] -5.353015765 1.093276e+00 #> [485,] -5.443673693 1.040568e+00 #> [486,] -5.517210379 9.827848e-01 #> [487,] -5.573123322 9.205018e-01 #> [488,] -5.610993200 8.543250e-01 #> [489,] -5.630486731 7.848879e-01 #> [490,] -5.631359050 7.128469e-01 #> [491,] -5.613455564 6.388764e-01 #> [492,] -5.576713280 5.636637e-01 #> [493,] -5.521161607 4.879042e-01 #> [494,] -5.446922605 4.122960e-01 #> [495,] -5.354210692 3.375352e-01 #> [496,] -5.243331809 2.643103e-01 #> [497,] -5.114682038 1.932973e-01 #> [498,] -4.968745690 1.251549e-01 #> [499,] -4.806092870 6.051937e-02 #> [500,] -4.627376537 1.133380e-15 # Butterflies of the vignette' cover panel(Out(a2l(replicate(100, sfourier_shape(nb.h=6, alpha=0.4, nb.pts=200, plot=FALSE)))))"},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset based on positions — slice","title":"Subset based on positions — slice","text":"Select rows position, based $fac. See examples ?dplyr::slice.","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset based on positions — slice","text":"","code":"slice(.data, ...)"},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset based on positions — slice","text":".data Coo, Coe, PCA object ... logical conditions","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset based on positions — slice","text":"Momocs object class.","code":""},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset based on positions — slice","text":"dplyr verbs maintained.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/slice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset based on positions — slice","text":"","code":"olea #> Opn (curves) #> - 210 curves, 99 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 210 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 204 more rows #> - also: $ldk slice(olea, 1) # if you only want the coordinates, try bot[1] #> Opn (curves) #> - 1 curves, 99 +/- NA coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 1 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> - also: $ldk slice(olea, 1:20) #> Opn (curves) #> - 20 curves, 99 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 20 × 4 #> var domes view ind #> #> 1 Aglan cult VD O10 #> 2 Aglan cult VL O10 #> 3 Aglan cult VD O11 #> 4 Aglan cult VL O11 #> 5 Aglan cult VD O12 #> 6 Aglan cult VL O12 #> # ℹ 14 more rows #> - also: $ldk slice(olea, 21:30) #> Opn (curves) #> - 10 curves, 100 +/- 4 coords (in $coo) #> - 4 classifiers (in $fac): #> # A tibble: 10 × 4 #> var domes view ind #> #> 1 Aglan cult VD O1 #> 2 Aglan cult VL O1 #> 3 Aglan cult VD O20 #> 4 Aglan cult VL O20 #> 5 Aglan cult VD O21 #> 6 Aglan cult VL O21 #> # ℹ 4 more rows #> - also: $ldk"},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts partitions of sliding coordinates — slidings_scheme","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"Helper function deduces (likely reminder) partition scheme $slidings Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"","code":"slidings_scheme(Coo)"},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"Coo Ldk object","code":""},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"list two components: n number partition; id position. NULL slidings defined","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/slidings_scheme.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts partitions of sliding coordinates — slidings_scheme","text":"","code":"# no slidings defined a NULL is returned with a message slidings_scheme(wings) #> no sliding defined #> NULL # slidings defined slidings_scheme(chaff) #> $n #> [1] 4 #> #> $id #> start end #> partition1 13 52 #> partition2 53 92 #> partition3 93 132 #> partition4 133 172 #>"},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":null,"dir":"Reference","previous_headings":"","what":"Family picture of shapes — stack","title":"Family picture of shapes — stack","text":"Plots outlines, graph, Coo (, Opn Ldk) object.","code":""},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Family picture of shapes — stack","text":"","code":"# S3 method for Coo stack( x, cols, borders, fac, palette = col_summer, coo_sample = 120, points = FALSE, first.point = TRUE, centroid = TRUE, ldk = TRUE, ldk_pch = 3, ldk_col = \"#FF000055\", ldk_cex = 0.5, ldk_links = FALSE, ldk_confell = FALSE, ldk_contour = FALSE, ldk_chull = FALSE, ldk_labels = FALSE, xy.axis = TRUE, title = substitute(x), ... ) # S3 method for Ldk stack( x, cols, borders, first.point = TRUE, centroid = TRUE, ldk = TRUE, ldk_pch = 20, ldk_col = col_alpha(\"#000000\", 0.5), ldk_cex = 0.3, meanshape = FALSE, meanshape_col = \"#FF0000\", ldk_links = FALSE, ldk_confell = FALSE, ldk_contour = FALSE, ldk_chull = FALSE, ldk_labels = FALSE, slidings = TRUE, slidings_pch = \"\", xy.axis = TRUE, title = substitute(x), ... )"},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Family picture of shapes — stack","text":"x Coo object plot. cols vector colors drawing outlines. Either single value length exactly equals number coordinates. borders vector colors drawing borders. Either single value length exactly equals number coordinates. fac factor within $fac slot colors palette color palette use fac provided coo_sample NULL number point per shape display (plot quickly) points logical whether draw points first.point logical whether draw first point centroid logical whether draw centroid ldk logical. Whether display landmarks (). ldk_pch pch landmarks ldk_col color landmarks ldk_cex cex landmarks ldk_links logical whether draw links (mean shape) ldk_confell logical whether draw conf ellipses ldk_contour logical whether draw contour lines ldk_chull logical whether draw convex hull ldk_labels logical whether draw landmark labels xy.axis whether draw x y axes title title plot. name Coo default ... arguments passed coo_plot meanshape logical whether add meanshape related stuff () meanshape_col color everything meanshape slidings logical whether draw slidings semi landmarks slidings_pch pch semi landmarks","code":""},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Family picture of shapes — stack","text":"plot","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/stack.Coo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Family picture of shapes — stack","text":"","code":"# \\donttest{ stack(bot) bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details stack(bot.f) #> Warning: non-vector elements will be ignored #> [1] ind #> <0 rows> (or 0-length row.names) stack(mosquito, borders='#1A1A1A22', first.point=FALSE) stack(hearts) stack(hearts, ldk=FALSE) stack(hearts, borders='#1A1A1A22', ldk=TRUE, ldk_col=col_summer(4), ldk_pch=20) stack(hearts, fac=\"aut\", palette=col_sari) chaffal <- fgProcrustes(chaff) #> iteration: 1 \tgain: 75173 #> iteration: 2 \tgain: 0.037814 #> iteration: 3 \tgain: 0.0090566 #> iteration: 4 \tgain: 0.00034224 #> iteration: 5 \tgain: 0.0069657 #> iteration: 6 \tgain: 0.002451 #> iteration: 7 \tgain: 0.0006129 #> iteration: 8 \tgain: 4.8815e-05 #> iteration: 9 \tgain: 0.00046668 #> iteration: 10 \tgain: 0.00018849 #> iteration: 11 \tgain: 2.4521e-05 #> iteration: 12 \tgain: 2.9766e-06 #> iteration: 13 \tgain: 2.4553e-05 #> iteration: 14 \tgain: 6.3825e-06 #> iteration: 15 \tgain: 5.1105e-06 #> iteration: 16 \tgain: 8.2596e-07 #> iteration: 17 \tgain: 2.8678e-06 #> iteration: 18 \tgain: 2.0472e-06 #> iteration: 19 \tgain: 6.5232e-07 #> iteration: 20 \tgain: 1.1298e-07 #> iteration: 21 \tgain: 1.3908e-07 #> iteration: 22 \tgain: 2.8327e-07 #> iteration: 23 \tgain: 2.1788e-07 #> iteration: 24 \tgain: 4.5583e-08 #> iteration: 25 \tgain: 7.0497e-08 #> iteration: 26 \tgain: 8.9792e-08 #> iteration: 27 \tgain: 5.538e-08 #> iteration: 28 \tgain: 1.2621e-08 #> iteration: 29 \tgain: 1.503e-08 #> iteration: 30 \tgain: 2.2108e-08 #> iteration: 31 \tgain: 1.4865e-08 #> iteration: 32 \tgain: 3.7216e-09 #> iteration: 33 \tgain: 3.8289e-09 #> iteration: 34 \tgain: 5.7787e-09 #> iteration: 35 \tgain: 3.9287e-09 #> iteration: 36 \tgain: 1.0587e-09 #> iteration: 37 \tgain: 9.2591e-10 #> iteration: 38 \tgain: 1.4847e-09 #> iteration: 39 \tgain: 1.039e-09 #> iteration: 40 \tgain: 2.9925e-10 #> iteration: 41 \tgain: 2.2588e-10 #> iteration: 42 \tgain: 3.8255e-10 #> iteration: 43 \tgain: 2.7403e-10 #> iteration: 44 \tgain: 8.3666e-11 stack(chaffal, slidings=FALSE) stack(chaffal, meanshape=TRUE, meanshape_col=\"blue\") # }"},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":null,"dir":"Reference","previous_headings":"","what":"Subsetize various Momocs objects — subsetize","title":"Subsetize various Momocs objects — subsetize","text":"Subsetize wrapper around dplyr's verbs used directly.","code":""},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subsetize various Momocs objects — subsetize","text":"","code":"subsetize(x, subset, ...)"},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subsetize various Momocs objects — subsetize","text":"x Coo Coe object. subset logical taken $fac slot, indices. See examples. ... useless maintains consistence generic subset.","code":""},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subsetize various Momocs objects — subsetize","text":"subsetted object class","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/subset.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subsetize various Momocs objects — subsetize","text":"","code":"# Do not use subset directly"},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":null,"dir":"Reference","previous_headings":"","what":"Calcuates symmetry indices on OutCoe objects — symmetry","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"OutCoe objects obtained efourier, calculates several indices matrix coefficients: AD, sum absolute values harmonic coefficients D; BC thing B C; amp sum absolute value harmonic coefficients sym ratio AD amp. See references details.","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"","code":"symmetry(OutCoe)"},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"OutCoe efourier objects","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"matrix 4 colums described .","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"call symmetry bilateral symmetry. comparing coefficients resulting efourier, AD responsible amplitude Fourier functions, BC phase, results plane fitted/reconstructed shapes symmetry. long shapes aligned along bilateral symmetry axis, can use approach coined Iwata et al., implemented Momocs.","code":""},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":": first mention, two applications. Iwata, H., Niikura, S., Matsuura, S., Takano, Y., & Ukai, Y. (1998). Evaluation variation root shape Japanese radish (Raphanus sativus L.) based image analysis using elliptic Fourier descriptors. Euphytica, 102, 143-149. Iwata, H., Nesumi, H., Ninomiya, S., Takano, Y., & Ukai, Y. (2002). Evaluation Genotype x Environment Interactions Citrus Leaf Morphology Using Image Analysis Elliptic Fourier Descriptors. Breeding Science, 52(2), 89-94. doi:10.1270/jsbbs.52.89 Yoshioka, Y., Iwata, H., Ohsawa, R., & Ninomiya, S. (2004). Analysis petal shape variation Primula sieboldii elliptic fourier descriptors principal component analysis. Annals Botany, 94(5), 657-64. doi:10.1093/aob/mch190","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/symmetry.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calcuates symmetry indices on OutCoe objects — symmetry","text":"","code":"bot.f <- efourier(bot, 12) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details res <- symmetry(bot.f) hist(res[, 'sym'])"},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":null,"dir":"Reference","previous_headings":"","what":"Tangent angle Fourier transform — tfourier","title":"Tangent angle Fourier transform — tfourier","text":"tfourier computes tangent angle Fourier analysis matrix list coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tangent angle Fourier transform — tfourier","text":"","code":"tfourier(x, ...) # S3 method for default tfourier(x, nb.h, smooth.it = 0, norm = FALSE, ...) # S3 method for Out tfourier(x, nb.h = 40, smooth.it = 0, norm = TRUE, ...) # S3 method for list tfourier(x, ...)"},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tangent angle Fourier transform — tfourier","text":"x list matrix coordinates ... useless nb.h integer. number harmonics use. missing, 12 used shapes; 99 percent harmonic power objects, messages. smooth.integer. number smoothing iterations perform norm logical. Whether scale register new coordinates first point used sent origin.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tangent angle Fourier transform — tfourier","text":"list following components: ao ao harmonic coefficient vector \\(a_{1->n}\\) harmonic coefficients bn vector \\(b_{1->n}\\) harmonic coefficients phi vector variation tangent angle t vector distance along perimeter expressed radians perimeter numeric. perimeter outline thetao numeric. first tangent angle x1 x-coordinate first point y1 y-coordinate first point.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Tangent angle Fourier transform — tfourier","text":"Silent message progress bars () options(\"verbose\"=FALSE). Directly borrowed Claude (2008), called fourier2 .","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Tangent angle Fourier transform — tfourier","text":"Zahn CT, Roskies RZ. 1972. Fourier Descriptors Plane Closed Curves. IEEE Transactions Computers C-21: 269-281. Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tangent angle Fourier transform — tfourier","text":"","code":"coo <- bot[1] coo_plot(coo) tf <- tfourier(coo, 12) tf #> $ao #> [1] 7.733739 #> #> $an #> [1] 0.04522478 -0.37556233 0.02768553 0.94117330 -0.39901487 -0.77638246 #> [7] -0.57686667 0.04409017 -0.76045376 -0.46366388 -0.60869408 -0.14084193 #> #> $bn #> [1] 0.008457058 2.526564125 -0.554083930 0.313312077 -0.288987146 #> [6] 0.032821965 -0.226300468 0.409651090 -0.021830547 0.015586993 #> [11] 0.414880500 0.677636372 #> #> $phi #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $t #> [1] 0.00000000 0.04553033 0.09106066 0.13659098 0.18212131 0.22765164 #> [7] 0.27318197 0.31871230 0.36424263 0.40977295 0.45530328 0.50083361 #> [13] 0.54636394 0.59189427 0.63742460 0.68295492 0.72848525 0.77401558 #> [19] 0.81954591 0.86507624 0.91060657 0.95613689 1.00166722 1.04719755 #> [25] 1.09272788 1.13825821 1.18378854 1.22931886 1.27484919 1.32037952 #> [31] 1.36590985 1.41144018 1.45697051 1.50250083 1.54803116 1.59356149 #> [37] 1.63909182 1.68462215 1.73015248 1.77568280 1.82121313 1.86674346 #> [43] 1.91227379 1.95780412 2.00333445 2.04886477 2.09439510 2.13992543 #> [49] 2.18545576 2.23098609 2.27651642 2.32204674 2.36757707 2.41310740 #> [55] 2.45863773 2.50416806 2.54969839 2.59522871 2.64075904 2.68628937 #> [61] 2.73181970 2.77735003 2.82288036 2.86841068 2.91394101 2.95947134 #> [67] 3.00500167 3.05053200 3.09606233 3.14159265 3.18712298 3.23265331 #> [73] 3.27818364 3.32371397 3.36924430 3.41477462 3.46030495 3.50583528 #> [79] 3.55136561 3.59689594 3.64242627 3.68795659 3.73348692 3.77901725 #> [85] 3.82454758 3.87007791 3.91560823 3.96113856 4.00666889 4.05219922 #> [91] 4.09772955 4.14325988 4.18879020 4.23432053 4.27985086 4.32538119 #> [97] 4.37091152 4.41644185 4.46197217 4.50750250 4.55303283 4.59856316 #> [103] 4.64409349 4.68962382 4.73515414 4.78068447 4.82621480 4.87174513 #> [109] 4.91727546 4.96280579 5.00833611 5.05386644 5.09939677 5.14492710 #> [115] 5.19045743 5.23598776 5.28151808 5.32704841 5.37257874 5.41810907 #> [121] 5.46363940 5.50916973 5.55470005 5.60023038 5.64576071 5.69129104 #> [127] 5.73682137 5.78235170 5.82788202 5.87341235 5.91894268 5.96447301 #> [133] 6.01000334 6.05553367 6.10106399 6.14659432 6.19212465 6.23765498 #> #> $perimeter #> [1] 2513.886 #> #> $thetao #> [1] -1.508378 #> #> $x1 #> [1] 37 #> #> $y1 #> [1] 561 #> tfi <- tfourier_i(tf) coo_draw(tfi, border='red', col=NA) # the outline is not closed... coo_draw(tfourier_i(tf, force2close=TRUE), border='blue', col=NA) # we force it to close."},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":null,"dir":"Reference","previous_headings":"","what":"Inverse tangent angle Fourier transform — tfourier_i","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"tfourier_i uses inverse tangent angle Fourier transformation calculate shape, given list Fourier coefficients, typically obtained computed tfourier.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"","code":"tfourier_i( tf, nb.h, nb.pts = 120, force2close = FALSE, rescale = TRUE, perim = 2 * pi, thetao = 0 )"},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"tf list ao, bn components, typically returned tfourier nb.h integer. number harmonics calculate/use nb.pts integer. number points calculate force2close logical. Whether force outlines calculated close (see coo_force2close). rescale logical. Whether rescale points calculated perimeter equals perim. perim perimeter length rescale shapes. thetao numeric. Radius angle reference (radians)","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"list components: x vector x-coordinates. y vector y-coordinates. phi vector interpolated changes tangent angle. angle vector position perimeter (radians).","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"See tfourier mathematical background.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"Directly borrowed Claude (2008), called ifourier2 .","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"Zahn CT, Roskies RZ. 1972. Fourier Descriptors Plane Closed Curves. IEEE Transactions Computers C-21: 269-281. Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier_i.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Inverse tangent angle Fourier transform — tfourier_i","text":"","code":"tfourier(bot[1], 24) #> $ao #> [1] 7.733739 #> #> $an #> [1] 0.0452247795 -0.3755623338 0.0276855331 0.9411732992 -0.3990148731 #> [6] -0.7763824605 -0.5768666699 0.0440901651 -0.7604537570 -0.4636638848 #> [11] -0.6086940781 -0.1408419257 -0.2906453466 0.1360186290 -0.2905320818 #> [16] -0.0013913889 0.0999975983 0.2531539067 -0.2409440735 -0.0107735036 #> [21] -0.0386305555 -0.0238992918 -0.1631252535 -0.0004085881 #> #> $bn #> [1] 0.008457058 2.526564125 -0.554083930 0.313312077 -0.288987146 #> [6] 0.032821965 -0.226300468 0.409651090 -0.021830547 0.015586993 #> [11] 0.414880500 0.677636372 0.197011887 0.180444429 0.433515510 #> [16] 0.237573437 0.107717915 0.027571558 0.054653201 -0.170505441 #> [21] 0.130595490 -0.014178384 -0.048221455 -0.127039009 #> #> $phi #> [1] 0.00000000 0.03394792 6.12970584 6.22607257 6.18054224 6.19051042 #> [7] 6.13580603 5.99700591 5.99842093 5.99084704 5.86041492 5.81488459 #> [13] 5.76506244 5.62887223 5.58334190 5.53781157 5.39732954 5.35179921 #> [19] 5.22136709 5.16746875 5.12193843 5.06723404 5.07720222 5.03804123 #> [25] 5.03308691 5.08250829 5.03697796 5.17966914 5.21216935 5.41953309 #> [31] 5.77457625 5.99961627 6.05629266 6.19411028 6.06367816 6.15041823 #> [37] 6.20005411 6.10694068 6.10899345 6.11083173 6.24864935 6.21627616 #> [43] 0.15041122 0.41687566 0.72706839 0.84208756 0.93719564 0.93924841 #> [49] 0.94130119 0.84818776 0.80265743 0.85207881 0.75917987 0.75672633 #> [55] 0.62053611 0.71690284 0.62442716 0.58361378 0.52907469 0.53478153 #> [61] 0.44702280 0.39677552 0.39819054 0.39061666 0.21281593 0.16728561 #> [67] 0.07417217 6.26424405 6.21871372 6.07886944 5.99538267 5.94148434 #> [73] 5.89595401 5.85879168 5.85121780 5.90000142 6.00172285 5.85652387 #> [79] 5.95289060 6.03171526 6.08391184 6.21482206 6.12821895 6.02776111 #> [85] 5.90179053 5.77058090 5.73820771 5.54311764 5.45064197 5.40081982 #> [91] 5.40652666 5.31405098 5.27323760 5.21869850 5.17746000 5.13664661 #> [97] 5.13334469 5.04086901 4.99104686 4.62111347 5.01682255 4.60719411 #> [103] 5.30626827 6.00978848 6.15257805 6.15247100 6.15452378 6.10899345 #> [109] 6.19573352 0.50480943 1.60303743 0.87544326 1.21632143 1.02825629 #> [115] 1.03030907 0.88982703 0.79735136 0.79876638 0.84818776 0.70770572 #> [121] 0.61523005 0.51420121 0.66606644 0.52558441 0.48434590 0.34125395 #> [127] 0.16219458 0.14695801 6.24944229 6.18612024 6.12136151 6.11662487 #> [133] 6.17219791 6.26019663 0.02904262 0.07417217 0.07622495 0.08278017 #> #> $t #> [1] 0.00000000 0.04553033 0.09106066 0.13659098 0.18212131 0.22765164 #> [7] 0.27318197 0.31871230 0.36424263 0.40977295 0.45530328 0.50083361 #> [13] 0.54636394 0.59189427 0.63742460 0.68295492 0.72848525 0.77401558 #> [19] 0.81954591 0.86507624 0.91060657 0.95613689 1.00166722 1.04719755 #> [25] 1.09272788 1.13825821 1.18378854 1.22931886 1.27484919 1.32037952 #> [31] 1.36590985 1.41144018 1.45697051 1.50250083 1.54803116 1.59356149 #> [37] 1.63909182 1.68462215 1.73015248 1.77568280 1.82121313 1.86674346 #> [43] 1.91227379 1.95780412 2.00333445 2.04886477 2.09439510 2.13992543 #> [49] 2.18545576 2.23098609 2.27651642 2.32204674 2.36757707 2.41310740 #> [55] 2.45863773 2.50416806 2.54969839 2.59522871 2.64075904 2.68628937 #> [61] 2.73181970 2.77735003 2.82288036 2.86841068 2.91394101 2.95947134 #> [67] 3.00500167 3.05053200 3.09606233 3.14159265 3.18712298 3.23265331 #> [73] 3.27818364 3.32371397 3.36924430 3.41477462 3.46030495 3.50583528 #> [79] 3.55136561 3.59689594 3.64242627 3.68795659 3.73348692 3.77901725 #> [85] 3.82454758 3.87007791 3.91560823 3.96113856 4.00666889 4.05219922 #> [91] 4.09772955 4.14325988 4.18879020 4.23432053 4.27985086 4.32538119 #> [97] 4.37091152 4.41644185 4.46197217 4.50750250 4.55303283 4.59856316 #> [103] 4.64409349 4.68962382 4.73515414 4.78068447 4.82621480 4.87174513 #> [109] 4.91727546 4.96280579 5.00833611 5.05386644 5.09939677 5.14492710 #> [115] 5.19045743 5.23598776 5.28151808 5.32704841 5.37257874 5.41810907 #> [121] 5.46363940 5.50916973 5.55470005 5.60023038 5.64576071 5.69129104 #> [127] 5.73682137 5.78235170 5.82788202 5.87341235 5.91894268 5.96447301 #> [133] 6.01000334 6.05553367 6.10106399 6.14659432 6.19212465 6.23765498 #> #> $perimeter #> [1] 2513.886 #> #> $thetao #> [1] -1.508378 #> #> $x1 #> [1] 37 #> #> $y1 #> [1] 561 #> tfourier_shape() #> x y #> [1,] 0.09561277 -0.004814825 #> [2,] 0.17323630 0.012512711 #> [3,] 0.24247674 0.051646046 #> [4,] 0.29748929 0.109085359 #> [5,] 0.33385352 0.179819356 #> [6,] 0.34893838 0.257909706 #> [7,] 0.34202693 0.337142828 #> [8,] 0.31420461 0.411651714 #> [9,] 0.26805270 0.476425605 #> [10,] 0.20721414 0.527653777 #> [11,] 0.13590836 0.562883614 #> [12,] 0.05846627 0.581004809 #> [13,] -0.02106025 0.582095153 #> [14,] -0.09918242 0.567175968 #> [15,] -0.17314294 0.537927066 #> [16,] -0.24097751 0.496404468 #> [17,] -0.30149084 0.444792525 #> [18,] -0.35417340 0.385208942 #> [19,] -0.39908549 0.319569319 #> [20,] -0.43673077 0.249508712 #> [21,] -0.46793577 0.176352003 #> [22,] -0.49374533 0.101122207 #> [23,] -0.51533859 0.024575573 #> [24,] -0.53396545 -0.052746453 #> [25,] -0.55090089 -0.130456468 #> [26,] -0.56741250 -0.208257641 #> [27,] -0.58473615 -0.285882037 #> [28,] -0.60405502 -0.363034076 #> [29,] -0.62647771 -0.439341866 #> [30,] -0.65301277 -0.514318839 #> [31,] -0.68453815 -0.587338057 #> [32,] -0.72176597 -0.657621374 #> [33,] -0.76520472 -0.724245173 #> [34,] -0.81512229 -0.786163607 #> [35,] -0.87151466 -0.842248868 #> [36,] -0.93408535 -0.891346370 #> [37,] -1.00224041 -0.932340801 #> [38,] -1.07510266 -0.964227287 #> [39,] -1.15154679 -0.986180670 #> [40,] -1.23025448 -0.997615508 #> [41,] -1.30978610 -0.998229998 #> [42,] -1.38866314 -0.988028677 #> [43,] -1.46545414 -0.967321231 #> [44,] -1.53885612 -0.936697614 #> [45,] -1.60776454 -0.896982570 #> [46,] -1.67132626 -0.849175003 #> [47,] -1.72897228 -0.794379083 #> [48,] -1.78042991 -0.733734485 #> [49,] -1.82571635 -0.668352569 #> [50,] -1.86511718 -0.599264002 #> [51,] -1.89915498 -0.527381571 #> [52,] -1.92855271 -0.453480087 #> [53,] -1.95419642 -0.378193596 #> [54,] -1.97710051 -0.302028917 #> [55,] -1.99837709 -0.225393658 #> [56,] -2.01920947 -0.148636458 #> [57,] -2.04082810 -0.072096988 #> [58,] -2.06448584 0.003836979 #> [59,] -2.09142827 0.078668531 #> [60,] -2.12285438 0.151730528 #> [61,] -2.15986277 0.222129640 #> [62,] -2.20337967 0.288702417 #> [63,] -2.25406724 0.349992107 #> [64,] -2.31221382 0.404256561 #> [65,] -2.37761297 0.449518103 #> [66,] -2.44944361 0.483665071 #> [67,] -2.52616994 0.504610845 #> [68,] -2.60548492 0.510509188 #> [69,] -2.68432347 0.500014501 #> [70,] -2.75896986 0.472563240 #> [71,] -2.82527534 0.428640136 #> [72,] -2.87898770 0.369983183 #> [73,] -2.91617419 0.299677983 #> [74,] -2.93369646 0.222098182 #> [75,] -2.92967593 0.142665876 #> [76,] -2.90387517 0.067433061 #> [77,] -2.85792168 0.002518250 #> [78,] -2.79531652 -0.046535279 #> [79,] -2.72120119 -0.075389641 #> [80,] -2.64189714 -0.081433142"},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates and draws 'tfourier' shapes. — tfourier_shape","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"tfourier_shape calculates 'Fourier tangent angle shape' given Fourier coefficients (see Details) can generate 'tfourier' shapes.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"","code":"tfourier_shape(an, bn, ao = 0, nb.h, nb.pts = 80, alpha = 2, plot = TRUE)"},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"numeric. \\(a_n\\) Fourier coefficients calculate shape. bn numeric. \\(b_n\\) Fourier coefficients calculate shape. ao ao Harmonic coefficient. nb.h integer. number harmonics use. nb.pts integer. number points calculate. alpha numeric. power coefficient associated (usually decreasing) amplitude Fourier coefficients (see Details). plot logical. Whether plot shape.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"matrix (x; y) coordinates.","code":""},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"Claude, J. (2008) Morphometrics R, Use R! series, Springer 316 pp.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tfourier_shape.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates and draws 'tfourier' shapes. — tfourier_shape","text":"","code":"tf <- tfourier(bot[1], 24) tfourier_shape(tf$an, tf$bn) # equivalent to rfourier_i(rf) #> x y #> [1,] -0.068536123 0.03816985 #> [2,] 0.010421770 0.02861438 #> [3,] -0.063790622 0.05721817 #> [4,] -0.140579972 0.07793172 #> [5,] -0.183238239 0.14505793 #> [6,] -0.247181702 0.19235370 #> [7,] -0.320133871 0.22403393 #> [8,] -0.368197883 0.28740195 #> [9,] -0.418456077 0.34904422 #> [10,] -0.483991433 0.39410832 #> [11,] -0.527015593 0.46100060 #> [12,] -0.558482563 0.53404501 #> [13,] -0.615378810 0.58961904 #> [14,] -0.666002527 0.65096148 #> [15,] -0.703250243 0.72123426 #> [16,] -0.768466384 0.76675910 #> [17,] -0.843721723 0.79249409 #> [18,] -0.920086430 0.81472216 #> [19,] -0.990492372 0.77772677 #> [20,] -1.035089701 0.71187289 #> [21,] -1.107991534 0.68007700 #> [22,] -1.173409209 0.63484224 #> [23,] -1.172271234 0.55531639 #> [24,] -1.245117865 0.52339423 #> [25,] -1.169306190 0.54744097 #> [26,] -1.166890972 0.46794366 #> [27,] -1.134401707 0.39534818 #> [28,] -1.068636587 0.35062006 #> [29,] -1.007856315 0.29932275 #> [30,] -0.955597746 0.23936695 #> [31,] -0.898595892 0.18390125 #> [32,] -0.832707879 0.13935435 #> [33,] -0.769939719 0.09050956 #> [34,] -0.718591641 0.02977217 #> [35,] -0.653105984 -0.01536412 #> [36,] -0.579711689 -0.04600613 #> [37,] -0.541356302 -0.11568052 #> [38,] -0.489158357 -0.17568911 #> [39,] -0.526675851 -0.10555999 #> [40,] -0.483094002 -0.17209027 #> [41,] -0.411233403 -0.20617413 #> [42,] -0.384991638 -0.28125426 #> [43,] -0.346581120 -0.35089827 #> [44,] -0.281483742 -0.39659277 #> [45,] -0.223918101 -0.45147312 #> [46,] -0.163346561 -0.50301673 #> [47,] -0.086698985 -0.52424890 #> [48,] -0.009264515 -0.54240265 #> [49,] 0.061119622 -0.57943951 #> [50,] 0.129392040 -0.62023819 #> [51,] 0.196505793 -0.66291605 #> [52,] 0.256624481 -0.71498715 #> [53,] 0.315395180 -0.76857503 #> [54,] 0.379092808 -0.81620137 #> [55,] 0.442596932 -0.86408541 #> [56,] 0.501564226 -0.91745689 #> [57,] 0.558878373 -0.97259983 #> [58,] 0.616862632 -1.02703770 #> [59,] 0.683127662 -1.07102180 #> [60,] 0.761505112 -1.05750770 #> [61,] 0.789105491 -0.98291631 #> [62,] 0.836639557 -0.91914980 #> [63,] 0.850183366 -0.99752212 #> [64,] 0.787935223 -0.94801632 #> [65,] 0.760460379 -0.87337860 #> [66,] 0.699791505 -0.82194959 #> [67,] 0.638226839 -0.77159636 #> [68,] 0.596708767 -0.70375901 #> [69,] 0.552733618 -0.63748804 #> [70,] 0.492705339 -0.58531274 #> [71,] 0.437325328 -0.52822763 #> [72,] 0.414799359 -0.45195026 #> [73,] 0.364582422 -0.39027438 #> [74,] 0.378601540 -0.46856307 #> [75,] 0.344461362 -0.39672921 #> [76,] 0.268368346 -0.37358815 #> [77,] 0.341471182 -0.34225716 #> [78,] 0.264568188 -0.36254472 #> [79,] 0.260420375 -0.28311896 #> [80,] 0.189614910 -0.24689408 tfourier_shape() #> x y #> [1,] 0.001516715 0.05327275 #> [2,] 0.015779539 0.13151742 #> [3,] 0.030251198 0.20972373 #> [4,] 0.045538391 0.28777472 #> [5,] 0.062199796 0.36554395 #> [6,] 0.080739961 0.44288681 #> [7,] 0.101603447 0.51963556 #> [8,] 0.125169341 0.59559808 #> [9,] 0.151746433 0.67056016 #> [10,] 0.181569435 0.74429105 #> [11,] 0.214796683 0.81655173 #> [12,] 0.251509688 0.88710534 #> [13,] 0.291714820 0.95572897 #> [14,] 0.335347235 1.02222610 #> [15,] 0.382276925 1.08643872 #> [16,] 0.432316607 1.14825850 #> [17,] 0.485230944 1.20763635 #> [18,] 0.540746428 1.26458972 #> [19,] 0.598561178 1.31920758 #> [20,] 0.658353875 1.37165269 #> [21,] 0.719791053 1.42216139 #> [22,] 0.782532121 1.47104098 #> [23,] 0.846231576 1.51866487 #> [24,] 0.910538094 1.56546580 #> [25,] 0.975090367 1.61192718 #> [26,] 1.039509789 1.65857259 #> [27,] 1.103390319 1.70595332 #> [28,] 1.166286114 1.75463365 #> [29,] 1.227697771 1.80517338 #> [30,] 1.287058321 1.85810712 #> [31,] 1.343720418 1.91391987 #> [32,] 1.396946475 1.97301845 #> [33,] 1.445903783 2.03569889 #> [34,] 1.489666884 2.10211009 #> [35,] 1.527229520 2.17221504 #> [36,] 1.557528380 2.24575166 #> [37,] 1.579480384 2.32219618 #> [38,] 1.592034458 2.40073312 #> [39,] 1.594237457 2.48023660 #> [40,] 1.585312261 2.55926822 #> [41,] 1.564744045 2.63609662 #> [42,] 1.532368623 2.70874295 #> [43,] 1.488454817 2.77505458 #> [44,] 1.433771343 2.83280728 #> [45,] 1.369628237 2.87983193 #> [46,] 1.297883552 2.91415912 #> [47,] 1.220908256 2.93417060 #> [48,] 1.141505884 2.93874434 #> [49,] 1.062788251 2.92737817 #> [50,] 0.988013858 2.90027751 #> [51,] 0.920400814 2.85839515 #> [52,] 0.862930169 2.80341533 #> [53,] 0.818157940 2.73768023 #> [54,] 0.788054092 2.66406356 #> [55,] 0.773884313 2.58580199 #> [56,] 0.776145825 2.50630016 #> [57,] 0.794562342 2.42892776 #> [58,] 0.828136648 2.35682768 #> [59,] 0.875253046 2.29275194 #> [60,] 0.933817055 2.23893825 #> [61,] 1.001416873 2.19703455 #> [62,] 1.075490376 2.16807299 #> [63,] 1.153482821 2.15248985 #> [64,] 1.232983360 2.15018335 #> [65,] 1.311832391 2.16059902 #> [66,] 1.388195950 2.18283104 #> [67,] 1.460607221 2.21572881 #> [68,] 1.527978325 2.25799925 #> [69,] 1.589587611 2.30829788 #> [70,] 1.645048769 2.36530416 #> [71,] 1.694268193 2.42777898 #> [72,] 1.737396454 2.49460419 #> [73,] 1.774778736 2.56480548 #> [74,] 1.806907834 2.63756108 #> [75,] 1.834382083 2.71219901 #> [76,] 1.857869426 2.78818586 #> [77,] 1.878077959 2.86510966 #> [78,] 1.895732549 2.94265946 #> [79,] 1.911556753 3.02060335 #> [80,] 1.926258977 3.09876664 tfourier_shape(nb.h=6, alpha=0.4, nb.pts=500) #> x y #> [1,] -0.002108631 -0.01142224 #> [2,] -0.002501370 -0.02400767 #> [3,] -0.001880612 -0.03658391 #> [4,] -0.000235429 -0.04906752 #> [5,] 0.002435011 -0.06137264 #> [6,] 0.006121025 -0.07341260 #> [7,] 0.010802278 -0.08510161 #> [8,] 0.016447951 -0.09635655 #> [9,] 0.023017214 -0.10709862 #> [10,] 0.030460003 -0.11725500 #> [11,] 0.038718070 -0.12676034 #> [12,] 0.047726285 -0.13555803 #> [13,] 0.057414131 -0.14360122 #> [14,] 0.067707341 -0.15085360 #> [15,] 0.078529617 -0.15728987 #> [16,] 0.089804362 -0.16289588 #> [17,] 0.101456362 -0.16766852 #> [18,] 0.113413364 -0.17161534 #> [19,] 0.125607495 -0.17475387 #> [20,] 0.137976476 -0.17711088 #> [21,] 0.150464609 -0.17872140 #> [22,] 0.163023508 -0.17962766 #> [23,] 0.175612571 -0.17987805 #> [24,] 0.188199205 -0.17952609 #> [25,] 0.200758787 -0.17862936 #> [26,] 0.213274414 -0.17724866 #> [27,] 0.225736438 -0.17544723 #> [28,] 0.238141825 -0.17329001 #> [29,] 0.250493362 -0.17084322 #> [30,] 0.262798730 -0.16817392 #> [31,] 0.275069481 -0.16534976 #> [32,] 0.287319934 -0.16243881 #> [33,] 0.299566006 -0.15950949 #> [34,] 0.311824005 -0.15663048 #> [35,] 0.324109401 -0.15387072 #> [36,] 0.336435595 -0.15129931 #> [37,] 0.348812707 -0.14898537 #> [38,] 0.361246402 -0.14699779 #> [39,] 0.373736791 -0.14540487 #> [40,] 0.386277437 -0.14427376 #> [41,] 0.398854497 -0.14366977 #> [42,] 0.411446043 -0.14365552 #> [43,] 0.424021608 -0.14428985 #> [44,] 0.436541994 -0.14562670 #> [45,] 0.448959372 -0.14771379 #> [46,] 0.461217720 -0.15059131 #> [47,] 0.473253593 -0.15429063 #> [48,] 0.484997259 -0.15883305 #> [49,] 0.496374148 -0.16422875 #> [50,] 0.507306617 -0.17047602 #> [51,] 0.517715948 -0.17756073 #> [52,] 0.527524516 -0.18545625 #> [53,] 0.536658044 -0.19412376 #> [54,] 0.545047831 -0.20351305 #> [55,] 0.552632860 -0.21356365 #> [56,] 0.559361680 -0.22420650 #> [57,] 0.565193974 -0.23536587 #> [58,] 0.570101738 -0.24696161 #> [59,] 0.574070028 -0.25891150 #> [60,] 0.577097246 -0.27113374 #> [61,] 0.579194980 -0.28354932 #> [62,] 0.580387426 -0.29608429 #> [63,] 0.580710458 -0.30867169 #> [64,] 0.580210428 -0.32125332 #> [65,] 0.578942782 -0.33378090 #> [66,] 0.576970590 -0.34621704 #> [67,] 0.574363104 -0.35853566 #> [68,] 0.571194404 -0.37072198 #> [69,] 0.567542236 -0.38277225 #> [70,] 0.563487083 -0.39469294 #> [71,] 0.559111504 -0.40649978 #> [72,] 0.554499769 -0.41821640 #> [73,] 0.549737758 -0.42987275 #> [74,] 0.544913126 -0.44150332 #> [75,] 0.540115641 -0.45314511 #> [76,] 0.535437656 -0.46483544 #> [77,] 0.530974607 -0.47660950 #> [78,] 0.526825428 -0.48849779 #> [79,] 0.523092770 -0.50052337 #> [80,] 0.519882881 -0.51269891 #> [81,] 0.517305016 -0.52502376 #> [82,] 0.515470246 -0.53748092 #> [83,] 0.514489542 -0.55003422 #> [84,] 0.514471047 -0.56262576 #> [85,] 0.515516483 -0.57517384 #> [86,] 0.517716714 -0.58757167 #> [87,] 0.521146550 -0.59968709 #> [88,] 0.525858973 -0.61136358 #> [89,] 0.531879072 -0.62242276 #> [90,] 0.539198072 -0.63266871 #> [91,] 0.547767920 -0.64189395 #> [92,] 0.557496962 -0.64988725 #> [93,] 0.568247269 -0.65644302 #> [94,] 0.579834122 -0.66137172 #> [95,] 0.592028072 -0.66451096 #> [96,] 0.604559851 -0.66573642 #> [97,] 0.617128167 -0.66497179 #> [98,] 0.629410174 -0.66219699 #> [99,] 0.641074135 -0.65745365 #> [100,] 0.651793556 -0.65084750 #> [101,] 0.661261840 -0.64254697 #> [102,] 0.669206437 -0.63277811 #> [103,] 0.675401403 -0.62181592 #> [104,] 0.679677420 -0.60997266 #> [105,] 0.681928498 -0.59758396 #> [106,] 0.682114907 -0.58499378 #> [107,] 0.680262169 -0.57253928 #> [108,] 0.676456337 -0.56053666 #> [109,] 0.670836064 -0.54926902 #> [110,] 0.663582217 -0.53897684 #> [111,] 0.654905955 -0.52985162 #> [112,] 0.645036211 -0.52203271 #> [113,] 0.634207485 -0.51560730 #> [114,] 0.622648728 -0.51061306 #> [115,] 0.610573885 -0.50704299 #> [116,] 0.598174478 -0.50485167 #> [117,] 0.585614369 -0.50396235 #> [118,] 0.573026679 -0.50427430 #> [119,] 0.560512676 -0.50566962 #> [120,] 0.548142331 -0.50801947 #> [121,] 0.535956240 -0.51118908 #> [122,] 0.523968541 -0.51504165 #> [123,] 0.512170530 -0.51944099 #> [124,] 0.500534721 -0.52425297 #> [125,] 0.489019154 -0.52934600 #> [126,] 0.477571821 -0.53459059 #> [127,] 0.466135158 -0.53985842 #> [128,] 0.454650578 -0.54502094 #> [129,] 0.443063052 -0.54994806 #> [130,] 0.431325750 -0.55450689 #> [131,] 0.419404746 -0.55856113 #> [132,] 0.407283721 -0.56197112 #> [133,] 0.394968576 -0.56459493 #> [134,] 0.382491745 -0.56629079 #> [135,] 0.369915957 -0.56692069 #> [136,] 0.357337087 -0.56635567 #> [137,] 0.344885689 -0.56448219 #> [138,] 0.332726775 -0.56120988 #> [139,] 0.321057428 -0.55647981 #> [140,] 0.310101919 -0.55027303 #> [141,] 0.300104155 -0.54261850 #> [142,] 0.291317498 -0.53359952 #> [143,] 0.283992284 -0.52335801 #> [144,] 0.278361630 -0.51209556 #> [145,] 0.274626457 -0.50007076 #> [146,] 0.272940836 -0.48759254 #> [147,] 0.273398923 -0.47500933 #> [148,] 0.276024756 -0.46269461 #> [149,] 0.280766008 -0.45102980 #> [150,] 0.287492512 -0.44038549 #> [151,] 0.295999944 -0.43110266 #> [152,] 0.306018542 -0.42347542 #> [153,] 0.317226259 -0.41773657 #> [154,] 0.329265267 -0.41404747 #> [155,] 0.341760448 -0.41249258 #> [156,] 0.354338320 -0.41307940 #> [157,] 0.366644877 -0.41574321 #> [158,] 0.378361032 -0.42035612 #> [159,] 0.389214654 -0.42673939 #> [160,] 0.398988640 -0.43467768 #> [161,] 0.407524855 -0.44393404 #> [162,] 0.414724200 -0.45426441 #> [163,] 0.420543388 -0.46543063 #> [164,] 0.424989183 -0.47721121 #> [165,] 0.428111009 -0.48940963 #> [166,] 0.429992784 -0.50185977 #> [167,] 0.430744760 -0.51442885 #> [168,] 0.430495992 -0.52701795 #> [169,] 0.429387899 -0.53956065 #> [170,] 0.427569155 -0.55202016 #> [171,] 0.425192036 -0.56438529 #> [172,] 0.422410135 -0.57666570 #> [173,] 0.419377309 -0.58888655 #> [174,] 0.416247586 -0.60108294 #> [175,] 0.413175701 -0.61329403 #> [176,] 0.410317926 -0.62555700 #> [177,] 0.407832766 -0.63790087 #> [178,] 0.405881126 -0.65034026 #> [179,] 0.404625544 -0.66286906 #> [180,] 0.404228078 -0.67545433 #> [181,] 0.404846527 -0.68803069 #> [182,] 0.406628741 -0.70049548 #> [183,] 0.409704904 -0.71270549 #> [184,] 0.414177929 -0.72447576 #> [185,] 0.420112297 -0.73558119 #> [186,] 0.427522044 -0.74576170 #> [187,] 0.436358881 -0.75473152 #> [188,] 0.446501744 -0.76219272 #> [189,] 0.457749287 -0.76785311 #> [190,] 0.469816892 -0.77144757 #> [191,] 0.482339680 -0.77276172 #> [192,] 0.494882596 -0.77165606 #> [193,] 0.506958073 -0.76808813 #> [194,] 0.518050962 -0.76213036 #> [195,] 0.527649444 -0.75398074 #> [196,] 0.535279762 -0.74396448 #> [197,] 0.540541754 -0.73252513 #> [198,] 0.543141751 -0.72020493 #> [199,] 0.542919276 -0.70761535 #> [200,] 0.539864452 -0.69539998 #> [201,] 0.534123851 -0.68419316 #> [202,] 0.525993794 -0.67457810 #> [203,] 0.515901498 -0.66704864 #> [204,] 0.504375878 -0.66197840 #> [205,] 0.492010966 -0.65960013 #> [206,] 0.479425663 -0.65999683 #> [207,] 0.467223760 -0.66310501 #> [208,] 0.455957927 -0.66872891 #> [209,] 0.446100612 -0.67656348 #> [210,] 0.438023807 -0.68622332 #> [211,] 0.431988473 -0.69727420 #> [212,] 0.428143312 -0.70926428 #> [213,] 0.426531705 -0.72175227 #> [214,] 0.427104949 -0.73433077 #> [215,] 0.429739668 -0.74664358 #> [216,] 0.434257236 -0.75839683 #> [217,] 0.440443280 -0.76936406 #> [218,] 0.448065724 -0.77938631 #> [219,] 0.456890287 -0.78836820 #> [220,] 0.466692836 -0.79627119 #> [221,] 0.477268369 -0.80310532 #> [222,] 0.488436766 -0.80892031 #> [223,] 0.500045641 -0.81379692 #> [224,] 0.511970771 -0.81783901 #> [225,] 0.524114613 -0.82116682 #> [226,] 0.536403406 -0.82391141 #> [227,] 0.548783310 -0.82621037 #> [228,] 0.561215938 -0.82820461 #> [229,] 0.573673589 -0.83003604 #> [230,] 0.586134395 -0.83184588 #> [231,] 0.598577552 -0.83377333 #> [232,] 0.610978787 -0.83595430 #> [233,] 0.623306164 -0.83852003 #> [234,] 0.635516378 -0.84159540 #> [235,] 0.647551648 -0.84529669 #> [236,] 0.659337383 -0.84972881 #> [237,] 0.670780778 -0.85498199 #> [238,] 0.681770502 -0.86112798 #> [239,] 0.692177644 -0.86821590 #> [240,] 0.701858022 -0.87626808 #> [241,] 0.710655912 -0.88527609 #> [242,] 0.718409155 -0.89519750 #> [243,] 0.724955505 -0.90595355 #> [244,] 0.730139942 -0.91742826 #> [245,] 0.733822593 -0.92946924 #> [246,] 0.735886755 -0.94189045 #> [247,] 0.736246485 -0.95447686 #> [248,] 0.734853191 -0.96699109 #> [249,] 0.731700665 -0.97918162 #> [250,] 0.726828117 -0.99079219 #> [251,] 0.720320890 -1.00157195 #> [252,] 0.712308702 -1.01128545 #> [253,] 0.702961483 -1.01972208 #> [254,] 0.692483056 -1.02670419 #> [255,] 0.681103074 -1.03209336 #> [256,] 0.669067787 -1.03579459 #> [257,] 0.656630248 -1.03775797 #> [258,] 0.644040618 -1.03797807 #> [259,] 0.631537164 -1.03649117 #> [260,] 0.619338444 -1.03337052 #> [261,] 0.607637044 -1.02872031 #> [262,] 0.596595093 -1.02266865 #> [263,] 0.586341602 -1.01536022 #> [264,] 0.576971545 -1.00694897 #> [265,] 0.568546501 -0.99759130 #> [266,] 0.561096561 -0.98744016 #> [267,] 0.554623200 -0.97664003 #> [268,] 0.549102776 -0.96532314 #> [269,] 0.544490327 -0.95360680 #> [270,] 0.540723423 -0.94159191 #> [271,] 0.537725823 -0.92936237 #> [272,] 0.535410781 -0.91698546 #> [273,] 0.533683915 -0.90451289 #> [274,] 0.532445562 -0.89198237 #> [275,] 0.531592646 -0.87941974 #> [276,] 0.531020085 -0.86684121 #> [277,] 0.530621809 -0.85425596 #> [278,] 0.530291482 -0.84166874 #> [279,] 0.529923029 -0.82908258 #> [280,] 0.529411080 -0.81650143 #> [281,] 0.528651442 -0.80393282 #> [282,] 0.527541696 -0.79139026 #> [283,] 0.525982022 -0.77889568 #> [284,] 0.523876323 -0.76648144 #> [285,] 0.521133697 -0.75419221 #> [286,] 0.517670309 -0.74208633 #> [287,] 0.513411637 -0.73023682 #> [288,] 0.508295074 -0.71873169 #> [289,] 0.502272813 -0.70767368 #> [290,] 0.495314891 -0.69717918 #> [291,] 0.487412261 -0.68737634 #> [292,] 0.478579699 -0.67840232 #> [293,] 0.468858353 -0.67039965 #> [294,] 0.458317700 -0.66351185 #> [295,] 0.447056714 -0.65787825 #> [296,] 0.435204029 -0.65362842 #> [297,] 0.422916946 -0.65087618 #> [298,] 0.410379171 -0.64971368 #> [299,] 0.397797234 -0.65020571 #> [300,] 0.385395646 -0.65238467 #> [301,] 0.373410891 -0.65624639 #> [302,] 0.362084473 -0.66174725 #> [303,] 0.351655298 -0.66880271 #> [304,] 0.342351713 -0.67728743 #> [305,] 0.334383602 -0.68703712 #> [306,] 0.327934909 -0.69785200 #> [307,] 0.323156973 -0.70950183 #> [308,] 0.320163022 -0.72173226 #> [309,] 0.319024073 -0.73427220 #> [310,] 0.319766469 -0.74684185 #> [311,] 0.322371111 -0.75916106 #> [312,] 0.326774422 -0.77095759 #> [313,] 0.332870930 -0.78197484 #> [314,] 0.340517297 -0.79197886 #> [315,] 0.349537559 -0.80076419 #> [316,] 0.359729272 -0.80815853 #> [317,] 0.370870249 -0.81402588 #> [318,] 0.382725564 -0.81826837 #> [319,] 0.395054502 -0.82082660 #> [320,] 0.407617192 -0.82167868 #> [321,] 0.420180664 -0.82083821 #> [322,] 0.432524164 -0.81835119 #> [323,] 0.444443587 -0.81429230 #> [324,] 0.455754963 -0.80876057 #> [325,] 0.466296973 -0.80187485 #> [326,] 0.475932513 -0.79376907 #> [327,] 0.484549387 -0.78458775 #> [328,] 0.492060198 -0.77448156 #> [329,] 0.498401565 -0.76360341 #> [330,] 0.503532789 -0.75210481 #> [331,] 0.507434072 -0.74013287 #> [332,] 0.510104440 -0.72782774 #> [333,] 0.511559463 -0.71532054 #> [334,] 0.511828878 -0.70273186 #> [335,] 0.510954212 -0.69017073 #> [336,] 0.508986463 -0.67773388 #> [337,] 0.505983905 -0.66550556 #> [338,] 0.502010062 -0.65355751 #> [339,] 0.497131870 -0.64194930 #> [340,] 0.491418052 -0.63072881 #> [341,] 0.484937714 -0.61993286 #> [342,] 0.477759157 -0.60958803 #> [343,] 0.469948897 -0.59971144 #> [344,] 0.461570887 -0.59031164 #> [345,] 0.452685922 -0.58138950 #> [346,] 0.443351209 -0.57293903 #> [347,] 0.433620088 -0.56494826 #> [348,] 0.423541880 -0.55739995 #> [349,] 0.413161848 -0.55027239 #> [350,] 0.402521259 -0.54354000 #> [351,] 0.391657518 -0.53717397 #> [352,] 0.380604375 -0.53114277 #> [353,] 0.369392188 -0.52541267 #> [354,] 0.358048219 -0.51994809 #> [355,] 0.346596981 -0.51471203 #> [356,] 0.335060595 -0.50966634 #> [357,] 0.323459176 -0.50477202 #> [358,] 0.311811233 -0.49998949 #> [359,] 0.300134071 -0.49527874 #> [360,] 0.288444209 -0.49059960 #> [361,] 0.276757783 -0.48591189 #> [362,] 0.265090965 -0.48117558 #> [363,] 0.253460357 -0.47635104 #> [364,] 0.241883386 -0.47139918 #> [365,] 0.230378680 -0.46628166 #> [366,] 0.218966425 -0.46096117 #> [367,] 0.207668700 -0.45540162 #> [368,] 0.196509773 -0.44956847 #> [369,] 0.185516375 -0.44342906 #> [370,] 0.174717912 -0.43695291 #> [371,] 0.164146643 -0.43011219 #> [372,] 0.153837784 -0.42288207 #> [373,] 0.143829554 -0.41524122 #> [374,] 0.134163142 -0.40717229 #> [375,] 0.124882583 -0.39866238 #> [376,] 0.116034558 -0.38970361 #> [377,] 0.107668080 -0.38029354 #> [378,] 0.099834094 -0.37043576 #> [379,] 0.092584960 -0.36014026 #> [380,] 0.085973843 -0.34942390 #> [381,] 0.080054001 -0.33831073 #> [382,] 0.074877974 -0.32683223 #> [383,] 0.070496704 -0.31502749 #> [384,] 0.066958575 -0.30294325 #> [385,] 0.064308412 -0.29063375 #> [386,] 0.062586451 -0.27816050 #> [387,] 0.061827305 -0.26559185 #> [388,] 0.062058966 -0.25300243 #> [389,] 0.063301849 -0.24047236 #> [390,] 0.065567931 -0.22808640 #> [391,] 0.068860011 -0.21593282 #> [392,] 0.073171098 -0.20410228 #> [393,] 0.078483991 -0.19268648 #> [394,] 0.084771028 -0.18177684 #> [395,] 0.091994062 -0.17146301 #> [396,] 0.100104636 -0.16183151 #> [397,] 0.109044392 -0.15296427 #> [398,] 0.118745680 -0.14493730 #> [399,] 0.129132386 -0.13781946 #> [400,] 0.140120928 -0.13167136 #> [401,] 0.151621420 -0.12654438 #> [402,] 0.163538958 -0.12247996 #> [403,] 0.175775005 -0.11950904 #> [404,] 0.188228826 -0.11765174 #> [405,] 0.200798940 -0.11691726 #> [406,] 0.213384553 -0.11730400 #> [407,] 0.225886932 -0.11879991 #> [408,] 0.238210688 -0.12138298 #> [409,] 0.250264941 -0.12502196 #> [410,] 0.261964339 -0.12967721 #> [411,] 0.273229922 -0.13530161 #> [412,] 0.283989809 -0.14184165 #> [413,] 0.294179715 -0.14923847 #> [414,] 0.303743287 -0.15742903 #> [415,] 0.312632273 -0.16634717 #> [416,] 0.320806528 -0.17592469 #> [417,] 0.328233881 -0.18609236 #> [418,] 0.334889871 -0.19678091 #> [419,] 0.340757371 -0.20792181 #> [420,] 0.345826128 -0.21944808 #> [421,] 0.350092233 -0.23129492 #> [422,] 0.353557540 -0.24340024 #> [423,] 0.356229060 -0.25570513 #> [424,] 0.358118331 -0.26815414 #> [425,] 0.359240806 -0.28069556 #> [426,] 0.359615239 -0.29328155 #> [427,] 0.359263110 -0.30586818 #> [428,] 0.358208071 -0.31841545 #> [429,] 0.356475449 -0.33088723 #> [430,] 0.354091776 -0.34325110 #> [431,] 0.351084379 -0.35547823 #> [432,] 0.347481014 -0.36754318 #> [433,] 0.343309547 -0.37942367 #> [434,] 0.338597684 -0.39110039 #> [435,] 0.333372746 -0.40255670 #> [436,] 0.327661484 -0.41377850 #> [437,] 0.321489931 -0.42475389 #> [438,] 0.314883297 -0.43547301 #> [439,] 0.307865883 -0.44592783 #> [440,] 0.300461033 -0.45611190 #> [441,] 0.292691106 -0.46602026 #> [442,] 0.284577463 -0.47564917 #> [443,] 0.276140481 -0.48499607 #> [444,] 0.267399571 -0.49405939 #> [445,] 0.258373212 -0.50283846 #> [446,] 0.249078990 -0.51133344 #> [447,] 0.239533647 -0.51954524 #> [448,] 0.229753125 -0.52747547 #> [449,] 0.219752622 -0.53512643 #> [450,] 0.209546636 -0.54250105 #> [451,] 0.199149017 -0.54960294 #> [452,] 0.188573012 -0.55643634 #> [453,] 0.177831306 -0.56300619 #> [454,] 0.166936061 -0.56931815 #> [455,] 0.155898946 -0.57537863 #> [456,] 0.144731171 -0.58119481 #> [457,] 0.133443505 -0.58677476 #> [458,] 0.122046301 -0.59212742 #> [459,] 0.110549511 -0.59726269 #> [460,] 0.098962704 -0.60219150 #> [461,] 0.087295079 -0.60692582 #> [462,] 0.075555483 -0.61147874 #> [463,] 0.063752430 -0.61586453 #> [464,] 0.051894127 -0.62009866 #> [465,] 0.039988500 -0.62419784 #> [466,] 0.028043242 -0.62818006 #> [467,] 0.016065863 -0.63206459 #> [468,] 0.004063753 -0.63587203 #> [469,] -0.007955728 -0.63962427 #> [470,] -0.019985155 -0.64334450 #> [471,] -0.032016912 -0.64705719 #> [472,] -0.044043052 -0.65078803 #> [473,] -0.056055133 -0.65456389 #> [474,] -0.068044026 -0.65841274 #> [475,] -0.079999708 -0.66236355 #> [476,] -0.091911031 -0.66644615 #> [477,] -0.103765470 -0.67069109 #> [478,] -0.115548859 -0.67512944 #> [479,] -0.127245112 -0.67979258 #> [480,] -0.138835946 -0.68471191 #> [481,] -0.150300593 -0.68991855 #> [482,] -0.161615540 -0.69544297 #> [483,] -0.172754277 -0.70131458 #> [484,] -0.183687084 -0.70756125 #> [485,] -0.194380867 -0.71420883 #> [486,] -0.204799045 -0.72128052 #> [487,] -0.214901527 -0.72879630 #> [488,] -0.224644766 -0.73677230 #> [489,] -0.233981928 -0.74522006 #> [490,] -0.242863174 -0.75414590 #> [491,] -0.251236071 -0.76355025 #> [492,] -0.259046144 -0.77342699 #> [493,] -0.266237563 -0.78376289 #> [494,] -0.272753971 -0.79453710 #> [495,] -0.278539437 -0.80572082 #> [496,] -0.283539532 -0.81727704 #> [497,] -0.287702482 -0.82916052 #> [498,] -0.290980393 -0.84131793 #> [499,] -0.293330497 -0.85368823 #> [500,] -0.294716374 -0.86620328 panel(Out(a2l(replicate(100, coo_force2close(tfourier_shape(nb.h=6, alpha=2, nb.pts=200, plot=FALSE)))))) # biological shapes"},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":null,"dir":"Reference","previous_headings":"","what":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"Given list files (lf) includes matching filenames .jpg (black masks) .txt (landmark positions .txt), returns $ldk defined. Typically useful use ImageJ define landmarks outlines.","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"","code":"tie_jpg_txt(lf)"},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"lf list filenames","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"object","code":""},{"path":"http://momx.github.io/Momocs/reference/tie_jpg_txt.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Binds .jpg outlines from .txt landmarks taken on them — tie_jpg_txt","text":"optimized (images read twice). Please hesitate contact particular case need something.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":null,"dir":"Reference","previous_headings":"","what":"Thin Plate Splines for 2D data — tps2d","title":"Thin Plate Splines for 2D data — tps2d","text":"tps2d core function Thin Plate Splines. used internally TPS graphical functions.tps_apply function arguments properly named (maintain tps2d historical reasons) want apply trasnformation grid.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Thin Plate Splines for 2D data — tps2d","text":"","code":"tps2d(grid0, fr, to) tps_apply(fr, to, new)"},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Thin Plate Splines for 2D data — tps2d","text":"grid0 matrix coordinates calculate deformations fr reference shape target shape new shape apply shp1->shp2 calibrated tps trasnformation","code":""},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Thin Plate Splines for 2D data — tps2d","text":"shape.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps2d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Thin Plate Splines for 2D data — tps2d","text":"","code":"shapes <- shapes %>% coo_scale() %>% coo_center() %>% coo_slidedirection(\"up\") %>% coo_sample(64) leaf1 <- shapes[14] leaf2 <- shapes[15] # tps grid on the two leafs2 tps_grid(leaf1, leaf2) # apply the (leaf1 -> leaf2) tps trasnformation onto leaf1 # (that thus get closer to leaf2) tps_apply(leaf1, leaf2, leaf1) %>% coo_draw(bor=\"purple\")"},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation 'vector field' using Thin Plate Splines — tps_arr","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"tps_arr(ows) calculates deformations two configurations illustrate using arrows.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"","code":"tps_arr( fr, to, amp = 1, grid = TRUE, over = 1.2, palette = col_summer, arr.nb = 200, arr.levels = 100, arr.len = 0.1, arr.ang = 20, arr.lwd = 0.75, arr.col = \"grey50\", poly = TRUE, shp = TRUE, shp.col = rep(NA, 2), shp.border = col_qual(2), shp.lwd = c(2, 2), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr grid whether calculate plot changes across graphical window TRUE just within starting shape (FALSE) numeric indicates much thin plate splines extends shapes palette color palette included Momocs produced colorRampPalette arr.nb numeric number arrows calculate arr.levels numeric. number levels color arrows arr.len numeric length arrows arr.ang numeric angle arrows' heads arr.lwd numeric lwd drawing arrows arr.col palette used color arrows poly whether draw polygons (outlines) points (landmarks) shp logical. whether draw shapes shp.col two colors filling shapes shp.border two colors drawing borders shp.lwd two lwd drawing shapes shp.lty two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"Nothing.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_arr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation 'vector field' using Thin Plate Splines — tps_arr","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_arr(fr, to, arr.nb=200, palette=col_sari, amp=3) tps_arr(fr, to, arr.nb=200, palette=col_sari, amp=3, grid=FALSE)"},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation grids using Thin Plate Splines — tps_grid","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"tps_grid calculates plots deformation grids two configurations.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"","code":"tps_grid( fr, to, amp = 1, over = 1.2, grid.size = 15, grid.col = \"grey80\", poly = TRUE, shp = TRUE, shp.col = rep(NA, 2), shp.border = col_qual(2), shp.lwd = c(1, 1), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr numeric indicates much thin plate splines extends shapes grid.size numeric specify number grid cells longer axis outlines grid.col color drawing grid poly whether draw polygons (outlines) points (landmarks) shp logical. Whether draw shapes shp.col Two colors filling shapes shp.border Two colors drawing borders shp.lwd Two lwd drawing shapes shp.lty Two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"Nothing","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_grid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation grids using Thin Plate Splines — tps_grid","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_grid(fr, to, amp=3, grid.size=10)"},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":null,"dir":"Reference","previous_headings":"","what":"Deformation isolines using Thin Plate Splines. — tps_iso","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"tps_iso calculates deformations two configurations map without isolines.","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"","code":"tps_iso( fr, to, amp = 1, grid = FALSE, over = 1.2, palette = col_spring, iso.nb = 1000, iso.levels = 12, cont = TRUE, cont.col = \"black\", poly = TRUE, shp = TRUE, shp.border = col_qual(2), shp.lwd = c(2, 2), shp.lty = c(1, 1), legend = TRUE, legend.text, ... )"},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr grid whether calculate plot changes across graphical window TRUE just within starting shape (FALSE) numeric indicates much thin plate splines extends shapes palette color palette included Momocs produced colorRampPalette iso.nb numeric. number points use calculation deformation iso.levels numeric. number levels mapping deformations cont logical. Whether draw contour lines cont.col color drawing contour lines poly whether draw polygons (outlines) points (landmarks) shp logical. Whether draw shapes shp.border Two colors drawing borders shp.lwd Two lwd drawing shapes shp.lty Two lty fro drawing shapes legend logical whether plot legend legend.text text legend ... additional arguments feed coo_draw","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"returned value","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_iso.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deformation isolines using Thin Plate Splines. — tps_iso","text":"","code":"botF <- efourier(bot) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x <- MSHAPES(botF, 'type', nb.pts=80)$shp fr <- x$beer to <- x$whisky tps_iso(fr, to, iso.nb=200, amp=3) tps_iso(fr, to, iso.nb=200, amp=3, grid=TRUE)"},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":null,"dir":"Reference","previous_headings":"","what":"Vanilla Thin Plate Splines — tps_raw","title":"Vanilla Thin Plate Splines — tps_raw","text":"tps_raw calculates deformation grids returns position sampled points .","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vanilla Thin Plate Splines — tps_raw","text":"","code":"tps_raw(fr, to, amp = 1, over = 1.2, grid.size = 15)"},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vanilla Thin Plate Splines — tps_raw","text":"fr reference \\((x; y)\\) coordinates target \\((x; y)\\) coordinates amp amplification factor differences fr numeric indicates much thin plate splines extends shapes grid.size numeric specify number grid cells longer axis outlines","code":""},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vanilla Thin Plate Splines — tps_raw","text":"list two components: grid xy coordinates sampled points along grid; dim dimension grid.","code":""},{"path":[]},{"path":"http://momx.github.io/Momocs/reference/tps_raw.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vanilla Thin Plate Splines — tps_raw","text":"","code":"# \\donttest{ ms <- MSHAPES(efourier(bot, 10), \"type\") #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details b <- ms$shp$beer w <- ms$shp$whisky g <- tps_raw(b, w) ldk_plot(g$grid) # a wavy plot ldk_plot(g$grid, pch=NA) cols_ids <- 1:g$dim[1] for (i in 1:g$dim[2]) lines(g$grid[cols_ids + (i-1)*g$dim[1], ]) # }"},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":null,"dir":"Reference","previous_headings":"","what":"Validates Coo objects — verify","title":"Validates Coo objects — verify","text":"validation S3 objects, method (cheap) attempt checking Coo objects, , Opn Ldk objects.","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validates Coo objects — verify","text":"","code":"verify(Coo)"},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validates Coo objects — verify","text":"Coo Coo object","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validates Coo objects — verify","text":"Coo object.","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Validates Coo objects — verify","text":"Implemented morphometric methods handling verbs. see checked, try eg Momocs:::verify.Coo","code":""},{"path":"http://momx.github.io/Momocs/reference/verify.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Validates Coo objects — verify","text":"","code":"verify(bot) #> Out (outlines) #> - 40 outlines, 162 +/- 21 coords (in $coo) #> - 2 classifiers (in $fac): #> # A tibble: 40 × 2 #> type fake #> #> 1 whisky a #> 2 whisky a #> 3 whisky a #> 4 whisky a #> 5 whisky a #> 6 whisky a #> # ℹ 34 more rows #> - also: $ldk bot[12] <- NA # you would not use try, but here we cope with R CMD CHECK standards plop <- try(verify(bot), silent=TRUE) class(plop) #> [1] \"try-error\" verify(hearts) #> Out (outlines) #> - 240 outlines, 80 +/- 0 coords (in $coo) #> - 1 classifiers (in $fac): #> # A tibble: 240 × 1 #> aut #> #> 1 ced #> 2 ced #> 3 ced #> 4 ced #> 5 ced #> 6 ced #> # ℹ 234 more rows #> - also: $ldk hearts$ldk[[4]] <- c(1, 2) # same remark plop2 <- try(verify(hearts), silent=TRUE) class(plop2) #> [1] \"try-error\""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify outliers — which_out","title":"Identify outliers — which_out","text":"simple wrapper around dnorm helps identify outliers. particular, may useful Coe object (case PCA first calculated) also Ldk detecting possible outliers freshly digitized/imported datasets.","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify outliers — which_out","text":"","code":"which_out(x, conf, nax, ...)"},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify outliers — which_out","text":"x object, either Coe numeric search outliers conf confidence dnorm (1e-3 default) nax number axes retain (Coe), <1 retain enough axes retain proportion variance ... additional parameters passed PCA (Coe)","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify outliers — which_out","text":"vector indices","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Identify outliers — which_out","text":"experimental. dnorm parameters used median(x), sd(x)","code":""},{"path":"http://momx.github.io/Momocs/reference/which_out.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify outliers — which_out","text":"","code":"# on a numeric x <- rnorm(10) x[4] <- 99 which_out(x) #> [1] 4 # on a Coe bf <- bot %>% efourier(6) #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details bf$coe[c(1, 6), 1] <- 5 which_out(bf) #> [1] 1 6 # on Ldk w_no <- w_ok <- wings w_no$coo[[2]][1, 1] <- 2 w_no$coo[[6]][2, 2] <- 2 which_out(w_ok, conf=1e-12) # with low conf, no outliers #> [1] NA which_out(w_no, conf=1e-12) # as expected #> found 127 possible outliers #> # A tibble: 2 × 4 #> shape id row coordinate #> #> 1 AN2 2 1 x #> 2 AN6 6 2 y # a way to illustrate, filter outliers # conf has been chosen deliberately low to show some outliers x_f <- bot %>% efourier #> 'norm=TRUE' is used and this may be troublesome. See ?efourier #Details #> 'nb.h' set to 10 (99% harmonic power) x_p <- PCA(x_f) # which are outliers (conf is ridiculously low here) which_out(x_p$x[, 1], 0.5) #> duvel latrappe ballantines #> 6 13 22 cols <- rep(\"black\", nrow(x_p$x)) outliers <- which_out(x_p$x[, 1], 0.5) cols[outliers] <- \"red\" plot(x_p, col=cols) #> will be deprecated soon, see ?plot_PCA # remove them for Coe, rePCA, replot x_f %>% slice(-outliers) %>% PCA %>% plot #> Error in eval(e, Coe$fac, parent.frame()): object 'outliers' not found # or directly with which_out.Coe # which relies on a PCA outliers <- x_f %>% which_out(0.5, nax=0.95) %>% na.omit() x_f %>% slice(-outliers) %>% PCA %>% plot #> Error in eval(e, Coe$fac, parent.frame()): object 'outliers' not found"},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-141","dir":"Changelog","previous_headings":"","what":"Momocs 1.4.1","title":"Momocs 1.4.1","text":"Removed rgeos dependency Momocs can resurect CRAN","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-140","dir":"Changelog","previous_headings":"","what":"Momocs 1.4.0","title":"Momocs 1.4.0","text":"CRAN release: 2022-04-04 Fixed several minor bugs, mostly plotting. coo_slide duplicated initial point cases. Now fixed. coo_likely_clockwise (friends) now uses complex numbers much robust. removed annoying messages. slice(…, 1) now returns matrix $coe, numeric ([,,drop=FALSE]) ’m currently academia ’m looking funding develop MomX. plan give time 2022 ideas, either directly hiring consulting, ring bell!","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-133","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.3","title":"Momocs 1.3.3","text":"plot_PCA plot_LDA consistently work within eg pdf(). Thanks Bill fof pointing . (214) coo_shearx/y return Coo. Fixed.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-132","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.2","title":"Momocs 1.3.2","text":"CRAN release: 2020-10-06 Turned remaining return return() please R CMD check as_df now uses tibble verbs everywhere printing Coo faster now price sampling 100 shapes calculate mean number coordinates sd. Removed (quite) annoying startup message. time MomX 2021 anyway","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-131","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.1","title":"Momocs 1.3.1","text":"Changed dplyr::as_data_frame tibble::as_tibble","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-130","dir":"Changelog","previous_headings":"","what":"Momocs 1.3.0","title":"Momocs 1.3.0","text":"CRAN release: 2020-04-15 version last major one released CRAN. Momocs now retired longer maintained. See momx.github.io. April 15, 2020 satisifies available testing approaches. new multivariate method: KMEDOIDS top cluster::pam. Added plot_silhouette go friend. Now depends cluster. new multivariate method: NMDS top vegan::metaMDS; use plot_NMDS plot vegan::stressplot Shepard plot. Now depends vegan. new multivariate method: MDS top cmdscale; use plot_MDS plot . mshapes now MSHAPES stick capitalized “multivariate” methods. mshapes now just announces future deprecation. MSHAPES now just returns data_frame PCs LDs used PCA LDA objects. Consequently, plot_MSHAPES new method plotting . Works lists result MSHAPES. plot_CV refreshed, better now plotting either small big matrices. fac_dispatcher supports NULL eases lot multivariate plots (notably Momecs side) new handling method rm_missing deal missing data $fac boxplot methods Coe refreshed hist methods Coe deprecated coo_plot longer method gains cex.first.point argument new method: coo_scalars gather scalar descriptors shape TraCoe class properly data_frameize fac build TraCoe() CLUST methods rewrote now wraps around dendextend. Consequently released ape dependency. morphometrics methods now accepts lists elegant working chop+combine LDA methods partly rewritten now handles constant collinear variables dropping storing returned list morphospace LDAs (finally) back, yet still quite experimental. coo_untiltx now removes (residual) rotational biases coo_slidedirection used . plot_LDA now . Pretty much plot_PCA (expected yet nice). .layerize_LDA internal prepare previous new vignettes: Momocs_coo Momocs_FAQ; others refreshed. morphospace_position chullfilled plot_PCA now properly working verify replaces validate avoid conflict shiny::validate (Momecs) subsetize now exported () def_ldk gains close points argument printing Coo errors due forgotten data.frame rather data_frame Coo builders gain .data.frame method, notably ease compatibility Momit as_df now returns useful data_frame everywhere gain retain argument deprecated coo_angle_edge1 friends, now coo_angle_edges see 1.2.9. fixed minor bugs (see GitHub history commits)","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-129","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.9","title":"Momocs 1.2.9","text":"CRAN release: 2018-03-22","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"preamble-1-2-9","dir":"Changelog","previous_headings":"","what":"Preamble","title":"Momocs 1.2.9","text":"Started general review Momocs (including #184) prepare MomX. convenience, changes stack 1.2.5 GitHub appear, end, 1.9.0 CRAN reflect proximity 2.0 huge quantity changes since 1.2 Moved everything github.com/MomX/Momocs ongoing complete review code ongoing complete review manual pages: lots grouping, better graphics dead (aka grindr): pipe-friendly base layers biplots shape drawing cartesian coordinates. used replace multivariate plotters (eg plot.PCA), family pictures (eg stack replace pile remove annoying conflict utils::stack, panel) single shape plotters (eg ldk_plot, coo_plot). strategy faster, much generic ease development maintenance compared previous Momocs graphs. vignette details grindr rationale use.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"new-1-2-9","dir":"Changelog","previous_headings":"","what":"New","title":"Momocs 1.2.9","text":"new functions: andnow andnow_method class tells object, classes supported function/method. new coo_* methods: coo_range, coo_range_enlarge, coo_diffrange, coo_template_relatively. latter prepare ground proper size handling, notably morphospaces. Many coo functions ported methods now supporting .Coo directly: coo_angle_edges, coo_angle_tangent, coo_boundingbox, coo_calliper, coo_chull, coo_chull_onion, coo_circularity, coo_circularityharalick, coo_circularity_norm, coo_convexity, coo_dxy, coo_eccentricityboundingbox, coo_eccentricityeigen, coo_elongation, coo_intersect_angle, coo_intersect_direction, coo_intersect_segment, coo_perim, coo_perimcum, coo_perimpts, coo_rectangularity, coo_rectilinearity, coo_scalex, coo_scaley, coo_solidity, coo_truss. Palettes now colorblind-friendly RColorBrewer , state art, virids palettes. See also pal_manual, pal_qual_solarized pal_seq_grey. dispatch_fac now behind fac arguments fgProcrustes now accepts lists efourier default norm=TRUE now messages wrong may dplyr::tibble() everywhere pertinent","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"deprecated-1-2-9","dir":"Changelog","previous_headings":"","what":"Deprecated","title":"Momocs 1.2.9","text":".* aliases is_* methods Deprecated classify calibrate_*(..., method) renamed calibrate_*_method. See ?calibrate_reconstructions friends. Deprecated plot3.PCA (replaced versions) Ntable now splitted plot_table + table coo_tangle now coo_angle_tangent coo_theta3 now coo_angle_edges truss now coo_truss method plot.Coo now inspect pos.shapes now morphospace_positions is_closed deprecated, now coo_is_closed; is_open now coo_is_open, comply coo_* friends naming scheme is_clockwise deprecated, now coo_likely_clockwise; is_anticlockwise now coo_likely_anticlockwise. Better reflect incertainty gather coo_* friends Deprecated table (poor shortcut anyway avoid boring startup message) Deprecated stack2 panel2 rewriting Deprecated as_Out, efourier_i.OutCoe anyway. Consequently deprecated panel.OutCoe method additionnaly Coe method. May back versions. non-exported functions (ie internals) now homegeneously begin ., eg ..error (try Momocs:::. + complete list). previously exported functions now internals (function_foo renamed .function_foo): .coo_angle_edge1, .vecs_param, .refactor NEWS now decent NEWS file Online doc moved [http://momx.github.io/Momocs/]","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"dependencies-1-2-9","dir":"Changelog","previous_headings":"","what":"Dependencies","title":"Momocs 1.2.9","text":"Released reshape2, plyr dependencies Now depends RColorBrewer, progress Proper indications external functions ::. nice side effect remove annoying messages attaching Momocs. Another removal importFrom.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"breaking-changes-1-2-9","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"Momocs 1.2.9","text":"Besides deprecated/renamed functions breaking changes. Future breaking changes announced within concerned functions.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"minor-1-2-9","dir":"Changelog","previous_headings":"","what":"Minor","title":"Momocs 1.2.9","text":"Waiting cleaner fix, subset now subsetize… Fixed bug LDA retain=1 (#e7704eb) Messages homogeneity Internals lightened verbosity progress bar now handled via options(\"verbose\") Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-124-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.4 (GitHub)","title":"Momocs 1.2.4 (GitHub)","text":"New functions/methods: coo_intersect_segment, coo_intersect_direction, coo_intersect_angle, def_ldk_direction, def_ldk_angle, def_ldk, def_ldk_tips, coo_sample_prop coo_slice.Opn now supports ldk argument. Now depends rgeos intersecting methods. Lightened nsfishes charring comply R CMD CHECK. Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-123-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.3 (GitHub)","title":"Momocs 1.2.3 (GitHub)","text":"Built R 3.4.3 coo_slice now suports ldk argument Various minor bugs fixes, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-122-cran--github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.2 (CRAN + GitHub)","title":"Momocs 1.2.2 (CRAN + GitHub)","text":"CRAN release: 2017-09-28 MANOVA_PW now returns p-values New dataset nsfishes minor debugging, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-121-github","dir":"Changelog","previous_headings":"","what":"Momocs 1.2.1 (GitHub)","title":"Momocs 1.2.1 (GitHub)","text":"Introduced testing testthat Minor debugging, see GitHub","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-116-github--cran","dir":"Changelog","previous_headings":"","what":"Momocs 1.1.6 (GitHub + CRAN)","title":"Momocs 1.1.6 (GitHub + CRAN)","text":"CRAN release: 2017-04-17 sfourier family implementation new datasets: apodemus mouse","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-110-github--cran","dir":"Changelog","previous_headings":"","what":"Momocs 1.1.0 (GitHub + CRAN)","title":"Momocs 1.1.0 (GitHub + CRAN)","text":"CRAN release: 2016-10-25 plot2.PCA deprecated due ggplot2 2.2.0 breaking changes minor changes can followed GitHub commits","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-10-cran--github","dir":"Changelog","previous_headings":"","what":"Momocs 1.0 (CRAN + GitHub)","title":"Momocs 1.0 (CRAN + GitHub)","text":"Release CRAN replaces now completely obsolete 0.2.6 (one JSS paper. consists last version pushed CRAN.","code":""},{"path":"http://momx.github.io/Momocs/news/index.html","id":"momocs-09-github","dir":"Changelog","previous_headings":"","what":"Momocs 0.9 (Github)","title":"Momocs 0.9 (Github)","text":"Started routinely use GitHub (NEWS) complete rewriting package, inclusion new morphometrics approches (open outlines, configuration landmarks, global shape descriptors). New design classes , Opn Ldk handle (closed) outlines, open outlines configuration landmarks. Coo becomes “super class” encompassing three others. S4 -> S3 rewriting. Maybe less orthodox much easy understand, code, extend probably required Momocs step. Renaming functions/methods consistent scheme New/partial rewriting multivariate methods: MANOVA, MANOVA_PW, LDA, KMEANS, CLUST. Graphics refreshed: panel, stack, plot.PCA New datasets: chaff, flowers, oak, olea, molars, shapes, wings, General review helpfiles Many issues fixed, see GitHub Momocs speed dating: tutorial vignette (see browseVignette(\"Momocs\") available","code":""}]