Reproducible Research with knitr Thomas J. Leeper Department of - - PowerPoint PPT Presentation

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Reproducible Research with knitr Thomas J. Leeper Department of - - PowerPoint PPT Presentation

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Overview Activity Literate Programming knitr in Depth Wrapup Reproducible Research with knitr Thomas J. Leeper Department of Political Science and Government Aarhus University October 28, 2014 Overview Activity Literate Programming

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Overview Activity Literate Programming knitr in Depth Wrapup

Reproducible Research with knitr

Thomas J. Leeper

Department of Political Science and Government Aarhus University

October 28, 2014

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Overview Activity Literate Programming knitr in Depth Wrapup

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Teaching/Learning Approach

Hands-on practice Work independently to enhance your own workflow You will not learn everything today

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Outline for afternoon

A short activity History and philosophy of literate programming Work through basics together Independent project work Wrap up and move forward

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Think about your own workflow

Think about: How do I get outputs from my data? Draw a map or diagram of your workflow Include relevant steps and tools, such as:

Tables Figures In-text citations and reference list In-text analysis summaries Cross-referencing (tables, figures, sections) Document layout

Make notes about areas that are time-consuming and/or difficult

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Literate programming

Origins in computer program documentation Software source code should describe how to use that software Early tools

WEB by Donald Knuth (author of TeX) noweb by Norman Ramsey (1989)

Two operations to create two different outputs

Weave: Nice Documentation Tangle: Executable code

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Sweave

Released in 2002 by Friedrich Leisch1 Written for S (the language of R) Focused on creating articles Two operations to create two different outputs

SWeave: LaTeX document (and PDF) STangle: Executable R code

1Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis

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knitr

Released in 2012 by Yihui Xie2 Conceptual descendant of Sweave

Easier than Sweave Much more functionality and flexibility

Three operations to create two different outputs

knit: PDF (and LaTeX document) purl: Executable R code spin: PDF (from pure R code)

Also create various outputs from non-LaTeX input

2knitr Homepage

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How knitr Works3

3Image by Ari B. Friedman

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Workflows for knitr

Analysis Output Irreproducible R Copy-paste No knitr R Manual includes Finish in knitr R Load and knit All knitr knitr n/a

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Workflows for knitr4

4Image by Ari B. Friedman

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knitr Input

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PDF Output

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LaTeX Intermediary

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Code Chunks

Code chunks contain three parts Label

Used for referencing chunks

Options

Control chunk behavior and appearance

Contents

R code to be evaluated

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @

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Code Chunks: Anatomy

«a,eval=TRUE,echo=FALSE,results=’asis’»= a <- 1+1 a @ «a»= @

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Code Chunks: Options

echo eval results tidy and highlight warning and message

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Code Chunks: Options

Chunk options can be set for each chunk They can also be set globally in a document E.g., opts_chunk$set(echo = FALSE)

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Code Chunks: Inline Code

In addition to chunks, code can be written in-line Anything in \Sexpr{} is evaluated Useful for in-line reporting of analyses

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Code Externalization

Possible to externalize R code

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Code Externalization

Possible to externalize R code “Child” documents

knitr code chunks in separate file

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Child knitr Document

Child Document: child.Rnw <<>>= x <- 1:3 y <- 4:6 @ Parent Document: knitrdoc.Rnw <<a, child = ’child.Rnw’>>= @

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Code Externalization

Possible to externalize R code “Child” documents

knitr code chunks in separate file

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Code Externalization

Possible to externalize R code “Child” documents

knitr code chunks in separate file

Reading code from file

Code in specially formatted R script Code remains executable without knitr

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External R Script

R Script: analysis.R ## ---- a x <- 1:3 ## ---- b y <- 4:6 knitr Document: knitrdoc.Rnw <<>>= read_chunk(’analysis.R’) @ <<a>>= @

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Chunk Caching

knitr runs every chunk every time This is unnecessary if you’re making non-code changes Can be time-consuming The cache chunk option changes this

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Chunk Caching: How it Works

Set cache=TRUE to cache a chunk knitr stores the chunk and its results

Stored in .RData files in ./cache

Cached chunks are only run after changes

Substantive and non-substantive changes

Behavior depends on relations between chunks

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Chunk Caching: Chunk Dependencies

Cached chunks are only rerun if modified But chunks might depend on other chunks

B depends on cached A Cached B depends on A Cached B depends on cached A

Specify dependencies with dependson

Or: opts_chunk$set(cache=TRUE, autodep=TRUE)

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Figures

Two ways to include figures: Using knitr chunk options for figures

Handles lots of details automatically Takes work to customize

Manually using \includegraphics{}

Somewhat finer control Requires more LaTeX overhead

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Tables

LaTeX tables are tedious Doing them by-hand is irreproducible and a waste of time Lots of ways to create tables with knitr

kable xtable stargazer

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Porting a Project to knitr

Move existing R code into a knitr framework What code chunks and in-line expressions do you need How do you create tables and figures?

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Package Versioning

Reproducibility requires knowing software used to conduct analyses Including package names using library or require is not enough Your future self (and others) need to know package versions How do we handle that?

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Package Versioning: Do it Manually

Record versions and either:

Put these in a README Have knitr fail on wrong version

Manually install package version:

devtools repmis

Tedious

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Package Versioning: packrat

Package developed by RStudio Work in an isolated software environment Install packages into a local project directory Share your packrat directory as part of your reproducible directory

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Package Versioning: checkpoint

Package developed by Revolution Analytics Register a “checkpoint” (a date) for your analyses All packages are drawn from MRAN, a daily snapshot of the R package universe No need to store/share a large package directory

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Package Versioning: Virtual Machines

knitr connects analyses and output

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Package Versioning: Virtual Machines

knitr connects analyses and output packrat or checkpoint connect R and analyses

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Package Versioning: Virtual Machines

knitr connects analyses and output packrat or checkpoint connect R and analyses What about the connection between OS and R?

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Package Versioning: Virtual Machines

knitr connects analyses and output packrat or checkpoint connect R and analyses What about the connection between OS and R?

Virtual machines

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Package Versioning: Virtual Machines

knitr connects analyses and output packrat or checkpoint connect R and analyses What about the connection between OS and R?

Virtual machines Docker

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Wrapup

What questions/concerns do you have? How have today’s activities helped you think about your

  • wn reproducible workflow?
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Go Next Other Tools knitr Resources

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Things we probably didn’t cover

knitr’s spin function: Creates a PDF from an R script

Really useful for teaching assignments

Language engines: Embed non-R code

Python, Bash, Julia, FORTRAN, Stata(?)

rmarkdown: knit without using LaTeX markup

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Other Reproducible Research Tools

git: Version control GitHub and Bitbucket: Git cloud services

Good for collaboration5

pandoc: Command-line tool to convert documents between formats Tools for R package versioning

devtools repmis packrat checkpoint

5See “Collaborating with Git and Bitbucket”

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knitr Resources

knitr website CRAN Reproducible Research TaskView Dynamic Documents with R and knitr Reproducible Research with R and RStudio knitr Google Group knitr on StackOverflow

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