High resolution graphics with R

[This article was first published on mages' blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

For most purposes PDF or other vector graphic formats such as windows metafile and SVG work just fine. However, if I plot lots of points, say 100k, then those files can get quite large and bitmap formats like PNG can be the better option. I just have to be mindful of the resolution.

As an example I create the following plot: x Saving the plot as a PDF creates a 5.2 MB big file on my computer, while the PNG output is only 62 KB instead. Of course, the PNG doesn't look as crisp as the PDF file.
png("100kPoints72dpi.png", units = "px", width=400, height=400)
plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))
dev.off()

Hence, I increase the resolution to 150 dots per pixel.

png("100kHighRes150dpi.png", units="px", width=400, height=400, res=150)<br />plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))<br />dev.off()

This looks a bit odd. The file size is only 29 KB but the annotations look too big. Well, the file has only 400 x 400 pixels and the size of a pixel is fixed. Thus, I have to provide more pixels, or in other words increase the plot size. Doubling the width and height as I double the resolution makes sense.

png("100kHighRes150dpi2.png", units="px", width=800, height=800, res=150)<br />plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))<br />dev.off()

Next I increase the resolution further to 300 dpi and the graphic size to 1600 x 1600 pixels. The file is still very crisp. Of course the file size increased. Now it is 654 KB in size, yet sill only about 1/8 of the PDF and I can embed it in LaTeX as well.

png("100kHighRes300dpi.png", units="px", width=1600, height=1600, res=300)<br />plot(x, main="100,000 points", col=adjustcolor("black", alpha=0.2))<br />dev.off()

Note, you can click on the charts to access the original files of this post.

To leave a comment for the author, please follow the link and comment on their blog: mages' blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)