Functions

First Function

• write functions in a text file ( R script)

add2 <- function(x,y){
  x+y
} ## didn't have to do anything to return, R returns the last expression
add2(3,5)

## [1] 8

Take a vector of numbers, return subset based on a condition

above10 <- function(x){
  use <- x> 10 ##return logical vector
  x[use] ##return this
}
above <- function(x,n){
  use <- x > n
  x[use]
}

x<- 1:20
above(x,15)

## [1] 16 17 18 19 20

above <- function(x, n = 10){ ## set default value to 10 
use <- x > n
x[use]
}

Calculate the mean of each column in matrix or data frame

columnmean <-function(y){ # y is a data fram or matrix
  nc <- ncol(y)
  means <-numeric(nc) #empty vector = num columns to store means
  for(i in 1:nc){
    means[i] <- mean(y[ , i])

  }
  means # return
}
d<- data.frame( col1=1:4, col2 = 5:8, col3 = c(NA, NA, 4, 6) )
d

##   col1 col2 col3
## 1    1    5   NA
## 2    2    6   NA
## 3    3    7    4
## 4    4    8    6

columnmean(d)

## [1] 2.5 6.5  NA

#can't calculate mean where we have NA's in column

#rewrite the fn to remove NA's before calculting mean

columnmean <-function(y, removeNA = TRUE){ # y is a data fram or matrix
  nc <- ncol(y)
  means <-numeric(nc) #empty vector = num columns to store means
  for(i in 1:nc){
    means[i] <- mean(y[ , i], na.rm = removeNA)

  }
  means # return
}
columnmean(d)

## [1] 2.5 6.5 5.0

columnmean(d, FALSE)

## [1] 2.5 6.5  NA

Functions Part1

Functions are R objects of class 'function'
The return value is the last expression in the function to be evaluated.

Functions have names argument which may have default values.
Formal Arguments : included in definition. formals function returns list of formal arguments.

Argument Matching

R functions arguments can be matched positionally or by name. So the following calls to sd are all equivalent

mydata <- rnorm(100)
sd(mydata)

## [1] 1.053673

sd(x=mydata)

## [1] 1.053673

sd(x=mydata, na.rm = FALSE) #when name your arguments, you don't have to use them in order

## [1] 1.053673

sd(na.rm = FALSE, x=mydata)

## [1] 1.053673

sd(na.rm = FALSE, mydata)

## [1] 1.053673

args(lm)

## function (formula, data, subset, weights, na.action, method = "qr", 
##     model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, 
##     contrasts = NULL, offset, ...) 
## NULL

#lm(data = mydata, formula=y-x, model=FALSE, subset=1:100)  
#lm(y-x, mydata, 1:100, model = FALSE) # if you don't overide defaulst, they will be used from the args defitinition 

Functions Part 2

Lazy evaluation

f<- function(a,b){
  a^2
}
f(2) #fn never uses the value b, a is positionally matched to a

## [1] 4

The "..." Argument

The ... argument indicate a variable number of arguments that are usually passed on to other functions.
... is often used when extending another function and you don’t want to copy the entire argument list of the original function

myplot <- function(x, y, type = "l", ...) {
 plot(x, y, type = type, ...)
}

The ... argument is also necessary when the number of arguments passed to the function cannot be known in advance.

args(paste)

## function (..., sep = " ", collapse = NULL) 
## NULL

args(cat) # here the '...' is the set of R objects (we don't know how many ) that will be concatenated.

## function (..., file = "", sep = " ", fill = FALSE, labels = NULL, 
##     append = FALSE) 
## NULL

Any arguments that appear after ... on the argument list must be named explicitly and cannot be partially matched.

args(paste)

## function (..., sep = " ", collapse = NULL) 
## NULL

paste("a", "b", sep =":")

## [1] "a:b"