1 “Hello R”

We will now start by writing our very first function, and then executing it.

CONTINUE TO ADVANCED EXCERCISE 2

1. Create a function (without any input) called “helloR” that prints “Hello World” when executed.

Create function

Hint:

# Remember the basic syntax for designing a function?
# If not, repeat this:

name_of_function <- function() {
  
}

Solution:

helloR <- function() {
  
  print("Hello World")

}

Execute function

solution:

helloR()

2. Well done, not that tricky right? Now lets ad some option to the function. If we provide a name as input, perhaps it can print “Hello NNN” ? Lets try!

Hint:

# Remember where we shoud put the input?

name_of_function <- function(input) {
  
}

Hint:

# Ahaaa, how to combine Hello and XXX?
# Perhaps this will give you a clue:

name <- "Andreas"
print(paste("Hello", name))

Solution:

#Define function

helloR <- function(name) {
  
  print(paste("Hello", name))

}

# Execute function

helloR("Andreas")
helloR("Malie")

3. Cool!!! We made it!!! Now we have a full function with input, and output. But, as we are going, lets define a default input, if no other input is given. Lets put your own name if no other input is given.

Hint:

# Remember how to define default inputs, no?

name_of_function <- function(input=Default) {
  
}

Solution:

#Define function

helloR <- function(name="Andreas") {
  
  print(paste("Hello", name))
}

# Execute function - try some different options:

helloR()
helloR("Andreas")
helloR("Malie")

Nice! We are done!

Now lets see if any of your mates need help - and the presentation will continue shortly!

2 Normalization function

Usually, we dont want R to just print things to the screen. We usually want to store the output as a new variable, that we can later use for other calculations.

1. Now, create a function that takes as input a vector of values (i.e a column from a data.frame) and returns a a vector where all the values has been normalized towards the mean (xi = xi/mean(x)). We can use the “Iris” dataset as example. The function can be called “normalizeR”

Hint 1:

# Lets repeat the syntax:

function_name <- function(input=default) {
  
  output <- "make something out of input"
  
  return(output)
}

Hint 2:

# What should we do with the input?
normalized <- iris$Sepal.Length / mean(iris$Sepal.Length)

Solution:

#Now, just put it together:

normalizeR <- function(inputvector) {
  
  normalized <- inputvector/mean(inputvector)
  
  return(normalized)
}

# Lets try the function out:

normalizeR(iris$Sepal.Length)
# Thets compare the output
boxplot(iris$Sepal.Length)
boxplot(normalizeR(iris$Sepal.Length))

2. Now, we would like to communicate a bit with the user. What happens if the user do not provide a vector? Make the function stop and provide an error message.

Hint 1:

# The stop function
stop("Write an error message here")

Hint 2:

# Do you remember the ifelse statements?

if (class(iris$Sepal.Length) != "numeric") {
  "Take some action"
}

Solution:

#Pay attention to the use of the braces and indentations:

normalizeR <- function(inputvector) {
  
  if (class(inputvector) != "numeric") {
    stop("Input is not a numeric vector")
    }
  
  normalized <- inputvector/mean(inputvector)
  
  return(normalized)
}


# Try your function:

normalizeR(iris$Sepal.Length)
normalizeR("Johansson")

3 Wrapper functions

Have you not always been annoyed by the default black color in Rs plot functions? Soo boring! Lets hot it up. Create a function that per default plots anything in red colors. Call the function redplot

Hint:

#This is how a plot would look like:

plot(x=iris$Sepal.Length, y=iris$Sepal.Width, col="red")

Solution:

redplot <- function(x, y, col="red") {
  plot(x=x, y=y, col=col)
}

But hey! What if the user wants to add i.e. a title on the x-axis? Leave roome in the formula for other arguments in the plot function:

Solution:

redplot <- function(x, y, col="red", ...) {
  plot(x=x, y=y, col=col, ...)
}


# Ore make it eaven nicer:

redplot <- function(..., col="red") {
  plot(..., col=col)
}

# Try it out

redplot(x=iris$Sepal.Length, y=iris$Sepal.Width)
redplot(x=iris$Sepal.Length, y=iris$Sepal.Width, xlab="Sepal Length", ylab="Sepal Width")

Its quite marvelous, is it not? See if you can use your function for other purposes.

CONTINUE TO ADVANCED EXCERCISE 2

4 Session Info

These packages were used during this session:

sessionInfo()

## R version 3.5.1 (2018-07-02)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.10
## 
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.8.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.8.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=sv_SE.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=sv_SE.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=sv_SE.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=sv_SE.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] compiler_3.5.1  backports_1.1.2 magrittr_1.5    rprojroot_1.3-2
##  [5] tools_3.5.1     htmltools_0.3.6 yaml_2.2.0      Rcpp_1.0.0     
##  [9] stringi_1.2.4   rmarkdown_1.10  knitr_1.20      stringr_1.3.1  
## [13] digest_0.6.18   evaluate_0.12