Add missing conditional execution of 'ggrepel'

An object was created in a chunk run only with 'ggrepel' available, but used in unprotected chunks. In addition found additional unprotected chunks calling 'ggrepel'.

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: ggpp
 Type: Package
 Title: Grammar Extensions to 'ggplot2'
-Version: 0.5.8
-Date: 2024-06-26
+Version: 0.5.8-1
+Date: 2024-06-30
 Authors@R:
     c(
     person("Pedro J.", "Aphalo", email = "pedro.aphalo@helsinki.fi", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3385-972X")),

NEWS.md

@@ -6,10 +6,12 @@ editor_options:
     wrap: 72
 ---
 
-# ggpp 0.5.8
+# ggpp 0.5.8-1
 
 -  Fix wrong test for availability of 'gginnards' in examples (reported by
 _Joshua Ulrich_ in issue #53).
+-  Add to vignette _Combining repulsion and nudging_ three missing tests for 
+availability of package 'ggrepel'.
 -  Revise `position_nudge_to()` to support expansion and contraction of the
 range within which to spread the positions.
 

vignettes/nudge-examples.R

@@ -55,13 +55,14 @@ ggplot(df, aes(x, y, label = l)) +
               hjust = "left") +
   expand_limits(x = 2.3)
 
-## ----eval=eval_ggrepel--------------------------------------------------------
+## -----------------------------------------------------------------------------
 ## Example data frame where each species' principal components have been computed.
 df1 <- data.frame(
   Species = paste("Species",1:5),
   PC1     = c(-4, -3.5, 1, 2, 3),
   PC2     = c(-1, -1, 0, -0.5, 0.7)) 
 
+## ----eval=eval_ggrepel--------------------------------------------------------
 ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
   geom_hline(aes(yintercept = 0), linewidth = .2) +
   geom_vline(aes(xintercept = 0), linewidth = .2) +
@@ -78,7 +79,7 @@ ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
   coord_fixed() +
   theme(legend.position = "none")
 
-## -----------------------------------------------------------------------------
+## ----eval=eval_ggrepel--------------------------------------------------------
 ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
   geom_hline(aes(yintercept = 0), linewidth = .2) +
   geom_vline(aes(xintercept = 0), linewidth = .2) +
@@ -350,14 +351,11 @@ ggplot(data = d, aes(x, y, label = lab, colour = group)) +
     geom_point()
 
 ## -----------------------------------------------------------------------------
-library(ggplot2)
-library(ggpp)
-library(ggrepel)
 syms = c(letters[1:5], LETTERS[1:5], 0:9)
 labs = do.call(paste0, expand.grid(syms, syms))
 dset = data.frame(x=rnorm(1e3), y=rnorm(1e3), label=sample(labs, 1e3, replace=TRUE))
 
-## -----------------------------------------------------------------------------
+## ----eval=eval_ggrepel--------------------------------------------------------
 ggplot(dset, aes(x=x, y=y, label = label)) +
   geom_point(colour = "grey85") +
   stat_dens2d_filter(geom = "text_repel",
@@ -466,7 +464,7 @@ ggplot(df, aes(x, yy)) +
                box.padding = 0,
                min.segment.length = 0)
 
-## -----------------------------------------------------------------------------
+## ----eval=eval_ggrepel--------------------------------------------------------
 ggplot(df, aes(x, yy)) +
   geom_point() +
   stat_smooth(method = "lm", 

vignettes/nudge-examples.Rmd

@@ -243,16 +243,18 @@ respective default justification approaches.
 
 ---
 
-A usually more problematic example is the labeling of loadings in PCA
+A usually more problematic example is the labelling of loadings in PCA
 and similar biplots.
 
-```{r, eval=eval_ggrepel}
+```{r}
 ## Example data frame where each species' principal components have been computed.
 df1 <- data.frame(
   Species = paste("Species",1:5),
   PC1     = c(-4, -3.5, 1, 2, 3),
   PC2     = c(-1, -1, 0, -0.5, 0.7)) 
+```
 
+```{r, eval=eval_ggrepel}
 ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
   geom_hline(aes(yintercept = 0), linewidth = .2) +
   geom_vline(aes(xintercept = 0), linewidth = .2) +
@@ -273,7 +275,7 @@ ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
 The use of `position_nudge_center()` together with repulsion, shown above,
 results a much better plot than using only repulsion.
 
-```{r}
+```{r, eval=eval_ggrepel}
 ggplot(df1, aes(x=PC1, y = PC2, label = Species, colour = Species)) +
   geom_hline(aes(yintercept = 0), linewidth = .2) +
   geom_vline(aes(xintercept = 0), linewidth = .2) +
@@ -696,15 +698,12 @@ GitHub by Michael Schubert, made possible by parameter `keep.these` added for
 this and similar use cases.
 
 ```{r}
-library(ggplot2)
-library(ggpp)
-library(ggrepel)
 syms = c(letters[1:5], LETTERS[1:5], 0:9)
 labs = do.call(paste0, expand.grid(syms, syms))
 dset = data.frame(x=rnorm(1e3), y=rnorm(1e3), label=sample(labs, 1e3, replace=TRUE))
 ```
 
-```{r}
+```{r, eval=eval_ggrepel}
 ggplot(dset, aes(x=x, y=y, label = label)) +
   geom_point(colour = "grey85") +
   stat_dens2d_filter(geom = "text_repel",
@@ -909,7 +908,7 @@ Nudging plus repulsion, shown next, will be compared to
 alternatives. In this case we assume no linking segments are desired as
 there is enough space for the data labels to remain near the observations.
 
-```{r}
+```{r, eval=eval_ggrepel}
 ggplot(df, aes(x, yy)) +
   geom_point() +
   stat_smooth(method = "lm",