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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>Introduction to functions and R packages</title>
<meta charset="utf-8" />
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<body>
<textarea id="source">
class: center, middle, inverse, title-slide
.title[
# Introduction to functions and R packages
]
---
## Do One Thing and Do It Well
- Functions are minimal bits of **repeated code** that do one thing well
- Should be universal – applied to a variety of problems
- Scalability – should handle small and large tasks equally well
``` r
fahrenheit_to_celsius <- function(temp_F) {
temp_C <- (temp_F - 32) * 5 / 9
return(temp_C)
}
```
---
## Writing your functions
- Each function better be in a separate file, e.g., `temperature.R`
- Should contain code and documentation
- In a package, functions are placed in the `R` subfolder
``` r
fahrenheit_to_celsius <- function(temp_F) {
temp_C <- (temp_F - 32) * 5 / 9
return(temp_C)
}
```
---
## Functions
Functions are created using the `function()` directive
``` r
f <- function(<arguments>) {
# Do something interesting
# Return the result
}
```
The return value of a function is the last expression in the function body to be evaluated
---
## Arguments
- Functions have named arguments
- Arguments may have default values, be required, optional, or missing
- Arguments can be set by name, the order is not important
``` r
sd(x = mtx, na.rm = TRUE) # Equivalent to sd(na.rm = TRUE, x = mtx)
```
- Arguments can be matched positionally
``` r
sd(mtx, TRUE) # But changing order won't work. sd(TRUE, mtx) - wrong
```
- Always use the default order. Using names is recommended for clarity. Mix and match OK
---
## Message throughout the function
- `message("message")` will output “message” upon running unless `suppressMessages` is set to TRUE
- `warning("warning")` will output a warning with the message “warning” upon running unless `suppressWarnings` is set to TRUE
- `stop("error")` will terminate execution of a function and provide the message “error” upon exit. If the function is part of a larger script, will terminate running the entire script
---
## Recursive function: factorial
``` r
# fact1 calculates the factorial of a number x using a recursive approach
fact1 <- function(x) {
if (x == 1) return(1) else return(x * fact1(x - 1))
}
# fact2 calculates the factorial of a number x using a vectorized approach
fact2 <- function(x) {
prod(1:x)
}
# fact3 calculates the factorial of a number x using the gamma function
fact3 <- function(x) {
gamma(x + 1)
}
```
---
## Recursive function: factorial
``` r
system.time(for (i in 1:1e4) fact1(100))
```
```
## user system elapsed
## 0.329 0.009 0.339
```
``` r
system.time(for (i in 1:1e4) fact2(100))
```
```
## user system elapsed
## 0.012 0.000 0.011
```
``` r
system.time(for (i in 1:1e4) fact3(100))
```
```
## user system elapsed
## 0.007 0.000 0.008
```
---
## Recursive function: Fibonacci numbers
``` r
# fibR calculates the nth Fibonacci number using a recursive approach.
# The function calls itself with n-1 and n-2 until the base cases of
# n == 0 or n == 1 are reached. While simple and elegant, this method
# can be highly inefficient for large values of n due to redundant
# calculations, resulting in exponential time complexity.
fibR <- function(n) {
if (n == 0) return(0)
if (n == 1) return(1)
return (fibR(n - 1) + fibR(n - 2))
}
```
---
## Making Functions Available in the R Environment
- Copy-paste your function's code in the console
- If you saved your function in a file, source it with `source("path/to/my_functions.R")`
- If you open this file in RStudio, you can click the "Source" button
- Functions from other packages are made available by loading a package with `library(package_name)`
---
class: inverse, center, middle
# Packages
---
## DRY, don't repeat yourself
- If you're repeating the same lines of code in multiple places, you should turn those minimal repetitive tasks into functions – reuse your code
- A package is a collection of frequently used functions
- Package = easiest way to distribute code and data
- Package = easiest way to reuse other’s code
---
## Starting an R package using RStudio
Ideally, create packages from scratch as soon as you begin on a project
- RStudio -> File -> New project -> New Directory -> R Package
.center[<img src="img/new_project.png" height=400 >]
---
## Package made simple with usethis
`usethis` is a workflow package: it automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects
``` r
library(usethis)
# Create a new package
path <- file.path(tempdir(), "mypkg")
create_package(path)
```
- Most functions start with `use_*()` (e.g., `use_vignette()`, `use_mit_license()`)
- `usethis::create_package()` will create package's skeleton and the DESCRIPTION file
.small[https://usethis.r-lib.org/]
---
## `DESCRIPTION` - package's metadata
- **Package** - Name of the package
- **Type** - Type of package, usually "Package"
- **Title** - A short title for the package
- **Version** - Current version of the package
- **Author** - Author(s) of the package, including roles (aut, cre, ctb)
- **Maintainer** - Person responsible for package maintenance
- **Description** - A brief description of what the package does
- **License** - The license under which the package is distributed
- **Depends** - Specifies the R version and other packages
- **Imports** - Lists additional packages that are imported
- **Suggests** - Packages that are suggested but not required
- **Enhances** - Packages that are enhanced by this package
- **Encoding** - Character encoding used in the package
- **LazyData** - Indicates whether lazy-loading of data is used
- **RoxygenNote** - Version of roxygen2 used to generate the documentation
---
# Example of a DESCRIPTION File
```
Package: MyPackage
Type: Package
Title: A Brief Description of MyPackage
Version: 1.0.0
Author: John Doe [aut, cre], Jane Smith [ctb]
Maintainer: John Doe <[email protected]>
Description: This package provides tools for XYZ analysis.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: dplyr, ggplot2
Suggests: testthat, knitr
Enhances: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
```
---
## Starting an R package: `DESCRIPTION`
Edit the `DESCRIPTION` file
- Adjust _Title_, _Author_ and _role_, _Description_ (as verbose as you can)
- Add license (`usethis::use_mit_license()` and similar functions)
.small[http://r-pkgs.had.co.nz/description.html]
---
## Starting an R package: `DESCRIPTION`
- If some of your functions use functions from other packages, you should add `imports` (forced install) and/or `suggests` (suggested install) sections to the `DESCRIPTION` file
``` r
usethis::use_package("dplyr") # Adding dplyr to Imports
usethis::use_package("dplyr", type = "Suggests") # Adding dplyr to Suggests
```
- Functions from packages declared in the `DESCRIPTION` file should be used with the `::` sign, e.g., `dplyr::left_join()`
.small[http://r-pkgs.had.co.nz/description.html]
<!--
## Starting an R package: `DESCRIPTION`
Short-term: Keeps track of imports (dependencies)
Long-term: Help others find your package
``` r
Package: examplepackage
Type: Package
Title: What the Package Does (Title Case)
Version: 0.1.0
Authors@R: person("First", "Last", email = "[email protected]",
role = c("aut", "cre"))
Description: More about what it does (maybe more than one line)
Use four spaces when indenting paragraphs within the Description.
Depends: R (>= 4.0.0)
License: What license is it under?
Encoding: UTF-8
LazyData: true
```
-->
---
## Writing your first function
Create a file `cat_function.R` with the following content
``` r
cat_function <- function(love.cats = TRUE){
if(love.cats == TRUE){
print("I love cats!")
}
else {
print("I will love cats!")
}
}
```
cat_function is defined with one argument love.cats which defaults to TRUE
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