Merge branch 'master' of https://github.com/GotelliLab/Bio381

Lectures/ControlStructures_I.Rmd

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+---
+title: 'Control Structures I'
+author: "Nicholas J. Gotelli"
+date: "7 March 2024"
+output:
+  html_document: 
+    highlight: tango
+    theme: united
+    keep_md: yes
+  pdf_document: default
+---
+### Logical operators
+
+```{r, eval=FALSE}
+# Simple inequalities
+5 > 3
+5 < 3
+5 >= 5
+5 <= 5
+5 == 3
+5 != 3
+
+# use & for AND
+FALSE & FALSE
+FALSE & TRUE
+TRUE & TRUE
+5 > 3 & 1!=2
+1==2 & 1!=2
+
+# use | for OR
+FALSE | FALSE
+FALSE | TRUE
+TRUE | TRUE
+1==2 | 1!=2
+
+# works with vectors
+
+1:5 > 3
+
+a <- 1:10
+b <- 10:1
+
+a > 4 & b > 4
+
+# use "long form" to evaluate left to write until a the first true/false is evaluated
+
+# evaluates all elements and gives a vector of results
+a < 4 & b > 4
+
+# evaluates until the first logical result is created
+a < 4 && b > 4
+
+# similar format for "long form" for OR
+
+# vector result
+a < 4 | b > 4
+
+# single result
+a < 4 || b > 4
+
+
+# xor for exclusive or testing of vectors
+# works for (TRUE FALSE) but not (FALSE FALSE) or (TRUE TRUE)
+xor(FALSE,FALSE)
+xor(FALSE,TRUE)
+xor(TRUE,TRUE)
+a <- c(0,0,1)
+b <- c(0,1,1)
+xor(a,b)
+
+# compare with a | b
+# works for (TRUE FALSE) or (TRUE TRUE)
+a | b
+```
+### Set Operations
+```{r, eval=FALSE}
+# boolean algebra on sets of atomic vectors (logical,numeric, character strings)
+
+a <- 1:7
+b <- 5:10
+
+# union to get all elements
+union(a,b)
+
+# intersect to get common elements
+intersect(a,b)
+
+# setdiff to get distinct elements in a
+setdiff(a,b)
+
+setdiff(b,a)
+
+# setequal to check for identical elements
+setequal(a,b)
+
+# more generally, to compare any two objects
+z <- matrix(1:12,nrow=4,byrow=TRUE)
+z1 <- matrix(1:12,nrow=4,byrow=FALSE)
+
+# This just compares element by element
+z==z1
+
+# Use identical for entire structures
+identical(z,z1)
+z1 <- z
+identical(z,z1)
+
+# most useful for if statements is %in% or is.element
+# these two are equivalent, but I prefer the %in% for readability
+d <- 12
+d %in% union(a,b)
+is.element(d,union(a,b))
+
+# check for partial matching with vector comparisons
+
+d <- c(10,12)
+d %in% union(a,b)
+d %in% a
+```
+
+
+
+### `If` statements
+
+```
+if (condition) {expression1}
+
+if (condition) {expression1} else {expression2}
+
+if (condition1) {expression1} else
+if (condition2) {expression2} else
+```
+* note that final unspecified `else` captures rest of the (unspecified) conditions
+* `else` statement must appear on the same line as the expression
+* typically enclose multiple statements in brackets `{}` for compound expression
+
+```{r, eval=FALSE}
+z <- signif(runif(1),digits=2)
+print(z)
+z > 0.5
+if (z > 0.5) cat(z, "is a bigger than average number","\n")
+
+if (z > 0.8) cat(z,"is a large number","\n") else 
+if (z < 0.2) cat(z,"is a small number","\n") else
+   {cat(z,"is a number of typical size","\n")
+    cat("z^2 =",z^2,"\n")}
+
+# if statement requires a single logical value. With a vector,
+# it will assign TRUE/FALSE based on very first element only.
+
+z <- 1:10
+
+# this does not do anything
+if (z > 7) print(z)
+
+# probably not what you want 
+if (z < 7) print(z)
+
+# use subsetting!
+print(z[z < 7])
+
+   
+```
+
+# `ifelse` to fill vectors
+```
+ifelse(test,yes,no)
+
+test is an object that can be coerced to a logical yes/no
+yes return values for true elements of test
+no return vales for false elements of test
+```
+Suppose we have an insect population in which each female lays, on average, 10.2 eggs, following a Poisson distribution with $\lambda = 10.2$. However, there is a 35% chance of parasitism, in which case no eggs are laid. Here is the distribution of eggs laid for 1000 individuals:
+```{r, eval=FALSE}
+tester <- runif(1000) # start with random uniform elements
+eggs <- ifelse(tester>0.35,rpois(n=1000,lambda=10.2),0)
+hist(eggs)
+```
+
+Suppose we have a vector of p values (say from a simulation), and we want to create a vector to highlight the significant ones for plotting purposes.
+
+```{r}
+pVals <- runif(1000)
+z <- ifelse(pVals<=0.025,"lowerTail","nonSig")
+z[pVals>=0.975] <- "upperTail"
+table(z)
+```
+
+Here is how I would probably do this
+```{r}
+z1 <- rep("nonSig",1000)
+z1[pVals<=0.025] <- "lowerTail"
+z1[pVals>=0.975] <- "upperTail"
+table(z1)
+```
+
+