In IBAHCM/RPiR: Reproducible Programming in R

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Comparisons -- testing for equality and difference

These tests are essential for while loops, and other forms of flow control such as if statements. They allow us to test whether something is true, and change what lines of code are run depending on the outcome. There are the basic tests:

• a == b: is a equal to b? (TRUE if this is true, FALSE if this is false)
• a > b: is a greater than b?
• a < b: is a less than b?
• a >= b: is a greater than or equal to b?
• a <= b: is a less than or equal to b?
• a != b: is a different from b?

There are then three basic ways of changing or combining the above:

• (a < b) || (c == d): is either a less than b or c equal to d?
• (a < b) && (c == d): is both a less than b and c equal to d?
• !((a < b) && (c == d)): is the above not TRUE? TRUE if the above was FALSE and vice versa

Remember to use (lots of!) brackets to ensure you are combining things in the right order. These tests can be used in the while loops above to determine whether to continue through the next iteration of the loop, and in the if statements below, to determine what to do next.

We introduced these concepts in Lecture 7a. Comparisons are also covered in passing in R4DS, and by R Coder in a bit more depth here.

if (something) and if (something) { ... } else { ... } statements

The if command allow us to perform a test, and if the result is TRUE run a block of R code (in curly brackets { ... }). Optionally, if the test is FALSE, a different block of code can be run instead. This allows us to do a variety of things. To give a very simple example:

if (2 > 1) {
  print("Maths works!")
}

This prints "Maths works!" because the test is TRUE, so the code block that follows is run. Whereas:

if (2 >= 5) {
  print("At least 5.")
} else {
  print("Less than 5.")
}

This prints "Less than 5." because the test was false, so R continues to the code block after the else statement. If there is no else statement, then no code is run, so:

if (2 >= 5) {
  print("At least 5.")
}

does nothing. We use if and if ... else statements throughout the helper functions and the example code you've been provided with. For instance:

library(codetools)
library(RPiR)

if (length(findGlobals(plot_simple, merge = FALSE)$variables) != 0) {
  stop("Function plot_simple() may not use global variable(s): ",
       findGlobals(plot_simple, merge = FALSE)$variables)
}

This checks whether length(findGlobals(plot_simple, merge=FALSE)$variables) is non-zero, which is to say whether the variables element of what is returned by findGlobals(plot_simple, merge = FALSE) is not of length zero, i.e. whether there are any global variables in the function plot_simple. If there are, then the contents of the curly brackets are run, stop(...) is called, and the code stops running. In fact, plot_simple has no global variables, so the code block is not run.

In Practical 3-4 we provide a second example of an if statement, used to control code execution:

{R, eval = FALSE} if (first.graph) { plot_populations(final.populations, new.graph = TRUE, col = c(susceptibles = "green", infecteds = "red")) first.graph <- FALSE } else { plot_populations(final.populations, new.graph = FALSE, col = c(susceptibles = "green", infecteds = "red")) }

This code tests whether the variable first.graph is TRUE. If it is, the following code block is run, and it plots a graph into a new graphics window and sets first.graph to FALSE. In the practical, this code is run inside a loop, and the next (and every subsequent) time it runs, first.graph is already FALSE so the code block following the else statement is run, and a plot is superimposed on the existing graphics window.

We introduced these concepts in Lecture 5b. R Coder covers the basics of if statements here. R4DS seems to consider them too simple, but ironically they have a chapter in Advanced R; however, this contains a lot of advanced topics in flow control that are well beyond the scope of this course.

IBAHCM/RPiR documentation built on Jan. 12, 2023, 7:41 p.m.