Functions

A function accepts input arguments and produces output by executing valid R commands present in the function.

• Function name and file names need not to be the same.
• A file can have one or, more function definitions.
• Functions are created using the command function()

Syntax :

f = function(arguments){
      statements
      return(argument)
    }

Example :

We have already created a R-script file that consists of various custom function like volcylinder() , volsacylinder_mimo() etc. Now, in order to apply them, we need to call and load the function file and then use it.

Let’s calculate the volume of a cylinder that has a diameter of \(15 units\) and length of \(30 units\), by using the custom function volcylinder()

source("../User_Defined_Function_Files/Custom_Functions.R") #Invoking and loading the custom functions
v = volcylinder(15,30)
v

## [1] 5301.438

Passing Arguments to Functions

We can pass arguments to the function in the following ways :

• Passing the arguments in the same order as in the function definition.

v = volcylinder(15,30) #Here, dia = 15 & len = 30
v

## [1] 5301.438

• Passing the arguments in different order by specifying the argument name.

v = volcylinder(len = 30, dia = 15)
v

## [1] 5301.438

• Default values are used by the function if some or, all arguments are not passed.

v = volcylinder() #Here, dia = 5 & len = 10 has been taken as arguments
v

## [1] 1963.495

Lazy Function Evaluation

Functions are lazily evaluated, which means that if some arguments are missing, then, the function is still executed as long as the execution doesn’t involve these arguments

Example :

volume_case1 = function(dia, len, rad){
  vol = pi * dia/2 * len/4
  return(vol)
}

vol = volume_case1(len=22, dia=12)
vol

## [1] 103.6726

In the above case, even if we didn’t gave any value for the rad argument, the function executed correctly as the rad argument is not used anywhere.

But, in the below example; we will get an error because, the rad argument has been used in the function but, missing in our evaluation statement.

volume_case2 = function(dia, len, rad){
  vol = pi * dia/2 * len/4
  print(rad)
  return(vol)
}

vol = volume_case2(len=22, dia=12)
vol

MIMO Functions

Functions in R can take multiple input objects but, returns only one object as output.However, this is not a limitation because, list objects can also be returned by a function.

Example :

We have created a custom function called volsacylinder_mimo() to calculate both volume and surface area of a cylinder by taking diameter and length of the cylinder as input.

source("../User_Defined_Function_Files/Custom_Functions.R")
result = volsacylinder_mimo(dia = 12, len = 15)

result["Volume"] #Getting only volume

## $Volume
## [1] 1696.46

result["Surface Area"] #Getting only surface area

## $`Surface Area`
## [1] 565.4867

Inline Functions

Inline functions comes very handy when we have to find out the output of a complex polynomial equation for various input values

Example :

func = function(x){x^2+4*log(x)+5*x+2}

func(5)

## [1] 58.43775

func(13)

## [1] 246.2598

func(23)

## [1] 658.542

Looping Over Objects

There are few looping functions available in R that are pretty useful when working interactively on a command line.

Those functions are as follows :

• apply() : Apply a function over the margins of an array or, matrix.
• lapply() : Apply a function over a list or, vector.
• tapply() : Apply a function over a ragged array.
• mapply() : Multivariate version of lapply().
• xxply() : Function from plyr package.

1. apply() Function

Applies a given function over the margins of given array.

Syntax :

  apply(array, margins, function, ...)

Here, margins refer to the dimension of the array along which the function need to be applied.

• For rows, margin = 1
• For columns, margin = 2

Example :

K = matrix(1:9,3,3)
K

##      [,1] [,2] [,3]
## [1,]    1    4    7
## [2,]    2    5    8
## [3,]    3    6    9

apply(K,1,sum) #applying the sum function across the rows

## [1] 12 15 18

apply(K,2,sum) #applying the sum function across the columns

## [1]  6 15 24

2. lapply() Function

• Used to apply a function over a list.
• Always returns a list of the same length as the input list.

Syntax :

  lapply(list, function, ...)

Example :

Let’s take 2 matrices as the elements of a list and find their determinant in the output using in-built det function

R = matrix(1:9,3,3)
S = matrix(10:18,3,3)

MyList = list(R,S)

determinant_list = lapply(MyList, det)

determinant_list

## [[1]]
## [1] 0
## 
## [[2]]
## [1] 5.329071e-15

3. mapply() Function

• Multivariate version of lapply().
• A function can be applied over several lists simultaneously.

Syntax :

  mapply(function, list1,list2,list3 ...)

Example :

Let’s apply the custom function volcylinder() over a set of diameters and lengths

source("../User_Defined_Function_Files/Custom_Functions.R")

dia = list(1,2,3,4,5,6)
len = list(7,8,9,10,11,12)

vol = mapply(volcylinder,dia,len)

vol

## [1]   5.497787  25.132741  63.617251 125.663706 215.984495 339.292007

4. tapply() Function

Used to apply a function over subset of vectors given by a combination of factors.

Syntax :

  tapply(vector, factors, function ...)

Example :

Let’s apply the sum function to add the VALUES by ID

ID = c(1,1,1,1,2,2,2,3,3)
VALUES = c(1:9)

tapply(VALUES, ID, sum)

##  1  2  3 
## 10 18 17