1 / 29

R Packages

R Packages. Davor Cubranic SCARL, Dept. of Statistics. Warmup questions. Who here uses packages? Which ones? How do you know you ’ re using a package? Had to install it Had to load it What happens when you load it? Functions Data Help pages. So package is a bundle of “ stuff ”

simone
Download Presentation

R Packages

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. R Packages Davor Cubranic SCARL, Dept. of Statistics

  2. Warmup questions • Who here uses packages? • Which ones? • How do you know you’re using a package? • Had to install it • Had to load it • What happens when you load it? • Functions • Data • Help pages

  3. So package is a bundle of “stuff” • But, (next slide) • It’s a structured bundle of…

  4. What is a package? • Structured, standardized unit of: • R code • documentation • data • external code

  5. Why use packages (talking points) • Installation & administration is easy • Finding, installing, compiling, updating… • Validation • Package checks • Distribution mechanisms • CRAN, Bioconductor, Github • Documentation • Bundle examples, demos, tutorials • Organization • Especially useful for the programmers: • Self-contained (names) • Declare and enforce dependencies on other packages

  6. Why use packages • Installation & administration • Validation • Distribution • Documentation • Organization

  7. Knowing how packages work and how to use them effectively will make you more effective R analyst, even if you don’t develop new packages • But you should consider developing packages even if you don’t write the next ggplot • Packages for your own stuff: • Analyses you frequently repeat and/or share with others • Publication: create a package containing the publication as a vignette, and bundle the code and data with it

  8. Handling packages • Load with library(name) • Package-level help: • library(help=name) • Unload with detach(package:name) • You shouldn’t have to do this

  9. Handling packages with RStudio • See the packages tab in Rstudio • Checkmark to load • Some are already loaded!! • Click on the name for help

  10. What happens when you load a package? • When you start R you have an empty workspace • But there is also all this other “basic” R stuff (matrix, plot) • So it’s more like we have two boxes, your workspace and “core” R • Actually, it’s more like a whole bunch of boxes: see search()

  11. So what happens when you load? • New package gets inserted near the front of the list • It can pull additional packages (dependencies) • But notice that each package is its own bundle (box) • We’ll talk how you create these bundles next

  12. Structure • What makes package a package is that it follows a prescribed structure of files and directories • If you tell R to treat this as a package, it will • You can create it by hand, but we’ll use a shortcut: package.skeleton()

  13. package.skeleton() • Convenient for turning a set of existing functions and scripts into a package • Let’s do it with the anova.mlm code that we wrote earlier

  14. New project: • scdemoXX@vscarl1.stat.ubc.ca:~scdemo/pkg • source(‘anova.mlm.R’) • package.skeleton(“anovaMlm”, ls())

  15. DESCRIPTION • The only required part of a package • Name, author, license, etc.

  16. R/ • Directory for R code • package.skeleton creates one file per function • This is not a rule, you can put as many functions into a single file

  17. man/ • Help files

  18. NAMESPACE • Defines which objects are visible to the user and other functions • Public vs. private to the package • The default is to make everything visible that starts with a letter

  19. Command-line tools • Check • Install • Build

  20. INSTALL • Let’s install our package • R CMD INSTALL anova.mlm • Delete the “man” directory • (it’s optional and we’ll recreate it later) • Redo INSTALL • Restart R studio • library(“anova.mlm”)

  21. check • Really important!!! • Finds common errors, non-standard parts • CRAN requires no ERRORS or WARNINGS

  22. Optional contents • man/: documentation • data/: datasets • demo/: R code for demo purposes • inst/: other files to include in the package (PDFs, vignettes) • tests/: package test files • src/: C, C++, or Fortran source code • NEWS: history of changes to the package • LICENSE or LICENCE: package license

  23. DESCRIPTION • Depends: • packages used by this one • and loaded as part of its loading • i.e., visible to the user • Imports: • packages used by this one • but not loaded • i.e, not visible to the user • Suggests: • used in examples or vignettes • non-essential functionality

  24. NAMESPACE • exportPattern(“^[[:alpha:]]”) • export(anova.mlm, est.beta) • S3method(print, anova.mlm) • S3method(plot, anova.mlm) • import(MASS) • importFrom(MASS, lda)

  25. Documentation • Let’s re-generate the documentation files • promptPackage(“anova.mlm”) • prompt(anova.mlm)

  26. anova.mlm.Rd • Description: Compute a (generalized) analysis of variance table for one or more multivariate linear models. • Arguments: • object: an object of class '"mlm”’ • ...: further objects of class '"mlm"’. • force.int: Force intercept • Value: An object of class “anova” inheriting from class “matrix”

  27. Help files for methods • \usage{anova.mlm(…)} • For S3 methods: • \usage{\method{print}{anova.mlm}(….)}

  28. Vignettes • .rnw extension • Written in Sweave • similar to knitr • Latex + R code • Produces a PDF available in the installed package • vignette() • vignette(‘Sweave’)

  29. Help on writing packages • Lots of tutorials on the Web • many of them are not necessarily correct • NAMESPACES, Imports, etc. • Authoritative guide: Writing R Extensions • R-devel mailing list

More Related