Hands-off running: Automatically saving figures

Hands-off running: Automatically saving figures#

Say you have 53 figures and 23 tables, the latter created from 161 different specifications. That makes for a lot of work when re-running the code, if you haven’t automated the saving of said figures and tables.

Warning

We have seen instructions that tell the replicator to right-click and save the figures. While there is no substitute for comparing all these figures, that’s too much work!

TL;DR#

Save all figures using commands, rather than manually.
It’s easy.

Saving figures programmatically#

In order to be able to enable “hands-off running”, saving figures (and tables) automatically is important. I will show here a few simple examples for various statistical programming languages.

Stata

After having created the graph (”graph twoway”, “graph bar”, etc.), simply add “graph export "name_of_file.graph-extension", replace”. Many formats are available, as required by journal requirements.

sysuse auto
graph twoway (lfitci mpg disp) (scatter mpg disp)
graph export "path/to/figure1.png"

For more information, see https://www.stata.com/manuals/g-2graphexport.pdf.

R

Methods vary, but the two main ones are redefining the graphics device for the desired format, or using the ggsave wrapper. Examples for both, below.

attach(mtcars)
fit <- lm(mpg ~ disp)
png(filename=file.path("path","to","figure1.png"))
plot(fit)
dev.off()

(for more information, see help pages for “?png”, “?eps”, or “?pdf”)

library(ggplot2)
library(here)
figures <- here::here("figures")

ggp <- ggplot(mtcars,aes(mpg,disp)) + 
       geom_point()+ 
       stat_smooth(method = "lm",geom="smooth" )
ggsave(ggp,file.path(figures,"figure1.png"))

(for more information, see https://ggplot2.tidyverse.org/reference/ggsave.html)

Python

Need example

MATLAB

bar(x);
saveas(gcf,fullfile('path','to','figure1.png'))

Takeaways#

What this does#

This ensures

that your code runs without problem, after all the debugging.
that your code runs without manual intervention.
that you do not impose fallible and onerous work on replicators

What this does not do#

This does not ensure

that your code generates a log file that you can inspect, and that you could share with others.
that it will run on somebody else’s computer
- because it does not guarantee that all the software is there
- because it does not guarantee that all the directories for input or output are there
- because many intermediate files might be present that are not in the replication package
- because it does not guarantee that all the directory names are correctly adjusted everywhere in your code
that it actually produces all the outputs
- because some outputs might be present from test runs

What to do next#

To solve some of these problems, let’s go to the next step.