Reproducible: Difference between revisions
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# user system elapsed | # user system elapsed | ||
# 0.032 0.008 0.047 | # 0.032 0.008 0.047 | ||
</syntaxhighlight> | |||
: And be careful when it is used in simulation. | |||
: <syntaxhighlight lang='bash'> | |||
f <- function() { | |||
a <- rnorm(1e5) | |||
a | |||
} | |||
system.time(f1 <- f()) | |||
mf <- memoise::memoise(f) | |||
system.time(f2 <- mf()) | |||
system.time(f3 <- mf()) | |||
all.equal(f2, f3) # TRUE | |||
</syntaxhighlight> | </syntaxhighlight> | ||
* [https://cran.rstudio.com/web/packages/reproducible/index.html reproducible]: A Set of Tools that Enhance Reproducibility Beyond Package Management | * [https://cran.rstudio.com/web/packages/reproducible/index.html reproducible]: A Set of Tools that Enhance Reproducibility Beyond Package Management |
Revision as of 11:44, 1 July 2019
Rmarkdown
Rmarkdown package
packrat
Docker & Singularity
Misc
- digest: Create Compact Hash Digests of R Objects
- memoise: Memoisation of Functions. Need to understand how it works in order to take advantage. I modify the example from Efficient R by moving the data out of the function. The cache works in the 2nd call. I don't use benchmark() function since it performs the same operation each time (so favor memoise and mask some detail).
library(ggplot2) # mpg library(memoise) plot_mpg2 <- function(mpgdf, row_to_remove) { mpgdf = mpgdf[-row_to_remove,] plot(mpgdf$cty, mpgdf$hwy) lines(lowess(mpgdf$cty, mpgdf$hwy), col=2) } m_plot_mpg2 = memoise(plot_mpg2) system.time(m_plot_mpg2(mpg, 12)) # user system elapsed # 0.019 0.003 0.025 system.time(plot_mpg2(mpg, 12)) # user system elapsed # 0.018 0.003 0.024 system.time(m_plot_mpg2(mpg, 12)) # user system elapsed # 0.000 0.000 0.001 system.time(plot_mpg2(mpg, 12)) # user system elapsed # 0.032 0.008 0.047
- And be careful when it is used in simulation.
f <- function() { a <- rnorm(1e5) a } system.time(f1 <- f()) mf <- memoise::memoise(f) system.time(f2 <- mf()) system.time(f3 <- mf()) all.equal(f2, f3) # TRUE
- reproducible: A Set of Tools that Enhance Reproducibility Beyond Package Management