R functions

• Write your own R functions by Jenny Bryan:
  • part 1: bare bone basics
  • part 2: generalize for multiple uses
  • part 3: missing values (NA) and pass through (...)
• linear regression function in detail
• split-apply-combine the function to all countries

miscellaneous notes:

• functional programming (prequel to functions)
• anonymous function, function closure
• stopifnot() and if() {stop()}
• turning interactive code into a function
• return() values and invisible()

A simple function has a name, possibly one or more arguments, and a body.

calcGCPct <- function(xSeq) {
  length(which(xSeq %in% c("C","G"))) / length(xSeq)
}

mySeq <- sample(c("A","C","G","T"), 1000, replace = TRUE)

calcGCPct(mySeq)

## [1] 0.519

calcGCPct(mySeq[1:100])

## [1] 0.56

Notes about arguments

• order: full names, abbreviated names, order
• assignment: = vs. <-
• elipsis (...) for arbitrary additional arguments
• defaults
• use arguments to avoid cut and paste
• sensible conventions for argument names
  • mean something to you
  • match use in functions you call

makeVector <- function(aa, ab, ba) { c(aa, ab, ba) }
makeVector(1, 2, 3)

## [1] 1 2 3

makeVector(1, 2, aa = 3)

## [1] 3 1 2

makeVector(1, ab = 3,a = 2)

## [1] 2 3 1

makeAlphanumericSample <- function( alphabet, 
                                    seqLength = 1000, 
                                    useProbabilities = NULL) {
  if(is.null(useProbabilities)) 
    useProbabilities <- rep(1/length(alphabet), length(alphabet))
  sample(alphabet, seqLength, replace=TRUE, prob=useProbabilities)
}

makeDNASample <- function(...){
  makeAlphanumericSample(c("A","C","G","T"), ...)
}

makeDNASample(seqLength = 100)

##   [1] "A" "G" "A" "C" "A" "G" "G" "C" "A" "C" "C" "C" "A" "C" "A" "T" "C"
##  [18] "C" "G" "C" "C" "C" "A" "C" "C" "A" "A" "A" "C" "T" "G" "A" "G" "C"
##  [35] "T" "C" "C" "T" "A" "G" "G" "G" "A" "A" "T" "C" "C" "C" "T" "G" "C"
##  [52] "A" "A" "G" "T" "T" "T" "C" "A" "T" "G" "T" "T" "T" "G" "G" "G" "A"
##  [69] "T" "C" "A" "T" "T" "A" "C" "C" "A" "A" "T" "T" "G" "C" "C" "C" "C"
##  [86] "C" "G" "A" "A" "C" "A" "T" "T" "T" "C" "A" "A" "T" "G" "G"

makeDNASample(seqLength = 100, 
              useProbabilities = c(0,.5,.5,0))

##   [1] "G" "C" "G" "G" "C" "C" "C" "G" "G" "C" "C" "C" "C" "G" "C" "C" "C"
##  [18] "C" "G" "C" "G" "C" "C" "G" "C" "G" "C" "G" "C" "C" "G" "C" "C" "C"
##  [35] "G" "C" "G" "G" "G" "G" "G" "G" "G" "C" "C" "C" "C" "C" "C" "C" "G"
##  [52] "C" "G" "G" "C" "C" "C" "C" "C" "C" "C" "G" "G" "C" "G" "G" "C" "G"
##  [69] "C" "C" "G" "C" "G" "C" "G" "C" "C" "C" "G" "C" "C" "C" "C" "G" "C"
##  [86] "C" "C" "C" "C" "C" "G" "C" "G" "G" "C" "G" "G" "C" "G" "G"

Notes about return values:

• returns last evaluated expression.
• thus only one object, but object can be a list of objects
• Hadley Wickham suggests reserving “return(expr)” for early returns.

The following returns NULL:

testFunction <- function(){}
testFunction()

## NULL

testFunction <- function(x) 5+7
testFunction()

## [1] 12

testFunction <- function(x) { 5+7; 13 }
testFunction()

## [1] 13

testFunction <- function(x){
  if(missing(x)) 
    return(0)
  x^2
}
testFunction()

## [1] 0

testFunction(4)

## [1] 16

Notes about scope

• R looks first in the local environment for a variable
• if not found, it looks at the environment of the calling function
• can force use of Global environment by using <–

testFunction <- function(x){ 
  y <- 5
  x + y 
}
rm(y)

## Warning in rm(y): object 'y' not found

testFunction(2)

## [1] 7

y

## Error: object 'y' not found

y <- 2
testFunction(2)

## [1] 7

y

## [1] 2

testFunction <- function(x) {
  v1 <- x + y
  y <- 10
  v1 + y
}
y<-2
testFunction(4)

## [1] 16

testFunction <- function(x){
  y <<- 5
  x + y
}
rm(y)
testFunction(2)

## [1] 7

y

## [1] 5