R - Function

Functions are stored as R objects with the class function

Functions can be:

• used as arguments of other functions
• nested

function( arglist ) expr
return(value)

#of

f <- function(arglist) {
   ## Body
}

where:

• arglist is a list of argument including the three dot argument.

Ex: arg1, arg2 = 1, arg3 = 'Nico', arg4 = NULL, …

Arguments can be matched positionally or by name.

Arguments mappings works as follow:

• an exact match on the name occurs. The matched argument are removed from the argument list.
• a partial match on the name occurs. The matched argument are removed from the argument list.
• a positional match occurs on the position (the remaining unnamed arguments taking their position number from the remaining argument list)

All the below function calls are equivalent:

mean(x=data,na.rm=FALSE)
mean(na.rm=FALSE,x=data)
mean(data,na.rm=FALSE)
mean(na.rm=FALSE,data)

To get the arguments of a function you can use the args function:

args(data.frame)

function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, 
    stringsAsFactors = default.stringsAsFactors()) 
NULL

Arguments to functions are evaluated lazily (ie only when needed).

• Argument is not used in the function

f = function(x, y) {
     return(x*2)
}
f(2)

[1] 4

• Argument is not called

f = function(x, y) {
     print(x)
     print(y)
}
f(2)

[1] 2
Error in print(y) : argument "y" is missing, with no default

The … argument indicates a variable number of arguments.

This special argument is used :

• when extending (wrapping) an existing function

myPlot = function(x, y, type = "l", ...) {
        plot(x, y, type = type, ...)
}

• when the number of arguments cannot be known in advance.
• by generic functions

The return value of a function is:

• returned by the return function
• of by the last expression in the body function to be evaluated.

f = function(x, y) {
     return(x*2)
}

is equivalent to:

f = function(x, y) {
     x*2
}

is equivalent to:

f = function(x, y) {
     return(x*2)
     x*4 # This statement will be skipped
}

Typically, a function is defined in the global environment, so that the values of free variables are just found in the user’s workspace

In this case the environment in which a function is defined is the body of another function! ????

Just use the question mark ? to obtain the documentation on a function

?data.frame

Use the str function

Example:

str(vector)
function (mode = "logical", length = 0L)  

where:

• function indicates that vector is a function
• (mode = “logical”, length = 0L) are the parameters of the function.

Just type the function:

Example with the function ddply from plyr

library(plyr)
> ddply
function (.data, .variables, .fun = NULL, ..., .progress = "none", 
    .inform = FALSE, .drop = TRUE, .parallel = FALSE, .paropts = NULL) 
{
    if (empty(.data)) 
        return(.data)
    .variables <- as.quoted(.variables)
    pieces <- splitter_d(.data, .variables, drop = .drop)
    ldply(.data = pieces, .fun = .fun, ..., .progress = .progress, 
        .inform = .inform, .parallel = .parallel, .paropts = .paropts)
}
<environment: namespace:plyr>

where:

• R - Namespace
• R - Environment (Scope)

To avoid the below message (function)

Error: could not find function "...."

load the package that contains the function

require(myPackage)

with R - Require or R - Library