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Depending on what exactly your figures were/are, you might benefit from the viridis colour map, available in matplotlib and R (and probably in many other places
by quietbritishjim 3y ago
Depending on what exactly your figures were/are, you might benefit from the viridis colour map, available in matplotlib and R (and probably in many other places). It's colourful, so those without colour blindness get a richer display than if you used greyscale, and the colours chosen aren't too affected by most common forms of colour blindness. But for those that really can't see the colours, even if you literally just convert to monochrome, it still works. It also looks nice :-)
Here's a talk by the creators: https://www.youtube.com/watch?v=xAoljeRJ3lU https://www.youtube.com/watch?v=xAoljeRJ3lU
Here's a little article about it (with some R specifics): https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html https://cran.r-project.org/web/packages/viridis/vignettes/in...
- f33d5173 3y agoAm I wrong that in that article magma appears to do better? Particularly in the last two (red-blind and grayscale), it seems like viridis looks the same for large parts of the scale, while magma retains its distinction.
- quietbritishjim 3y agoI think it just won the poll [1] because it subjectively looks nicer. NJS, in that video, said something like: I don't care which wins, they're all so much better than the current situation. But magma is a good choice too and it's also available in matplotlib. [1] http://bids.github.io/colormap/ http://bids.github.io/colormap/