A Better Default Colormap for Matplotlib | SciPy 2015 | Nathaniel Smith and Stéfan van der Walt

[pleaserespond]

Pedantic note: sRGB is like that not just because "cathode ray tubes worked like that", the reason is that human eyes are more sensitive to differences in dim light than in bright light, so the sRGB curve gives you more precision on the low end and less on the high end. If we switched to 16-bit floats per channel, then you could use a linear RGB colour space (and float encoding automatically gives you more precision for smaller values), but at the cost of doubling our memory requirements. Back in the day we were lucky to have enough space even for 8 bits per channel and sometimes had to quantise down to 5/6/5 bits for red, green and blue channel respectively (6 for green because your eyes are most sensitive to green). So sRGB follows CRTs because the curve for CRTs was already optimised for use in memory-restricted scenarios (like desktop and laptop PCs until about 5 years ago, or TV signal bandwidth back in the day). If you want to save yourself pain and have the memory for it, by all means use 16 or even 32 bit floats per channel in linear RGB for your rendering calculations, then convert the image to sRGB as a final display step.

[foadsf]

this guy is awsome. I wish I had this level of entertaining presentation skills.

[MrCk]

Really don't know there are so many theories behind a colormap. Very informative. Thanks!

[VictorHCandido]

This talk is amazing! There's lots of high level content and the jokes killed me every time! Please, do more talks on anything, lol. TYVM

[HeltonMoraes]

These guys definitely know their business... Thanks for the excellent explanations!

[nathanielsmith]

ERRATA: I just realized that in the diagrams showing the XYZ colorspace at around 6:00 in the video, the labels on the "X" and "Y" axes are accidentally swapped -- the one going up should be labeled "Y", and the one going down and to the right should be labeled "X". My apologies if this confused anyone.

[edwnx]

kinda wish they had more time to the full presentation. i'm a graphic designer and also a nerd and it's very interesting hearing the reasoning behind the color choices.

[Ljk]

Nerd programmer humour is alive and well in the new millennium!

[benjaminblumer]

Sounds like great work. And the talk is done really well. Thanks!

[MrSirCorion]

Great talk and the work on colors is awesome!

[xdazamx]

Such a good presentation on what one would probably consider a dry topic. From a colourblind perspective, thanks for considering the 4.5% of us who often do really stupid things to be able to tell, often unsucessefully, what on earth we're looking at.

[jabelsjabels]

wow, great talk! interesting, informative, entertaining.

[uuadad]

I like the colour map being such that green-red colour perception is not an issue. All too often I cannot discriminate.  The 'viridis' one looks fine to me.

[gogyoo]

Just here to say I like "tag10" for classification tasks.

[alucard]

The colormap great, but the name... Inferno, Plasma, Magma, viridis? Please change it to Venom and get your shit together :P.

[Ryan-srzv]

Blue yellow dress: Actually measuring the raw RGB reveals that there is a difference in the YouTube image at least. 100 136 250 vs. 129 145 183

[alantesla]

Great presentation. Is there made a publication on the work?

[sailawayteam]

Great presentation indeed! But this case also shows that perfect in theory does not necessarily mean perfect in reality. I think matlab did better job even if their map isn't "perfect" in theory. Viridis produces unbelievanle sickly colors. And what value is there to argue that a color map is good or bad by using them in photographs or paintings? Photographs are not height maps, not by any means.

[adammaj]

Why multicolor gradient if the data is od one type? IMHo monochrome gradient would be better as default

[josephbarranco]

Any thoughts on the best "default" diverging color maps? In theory, one would use a diverging color map if there is a special value (say zero) in the data and you want to have separate colors for values on either side. For example, if I was doing a simulation of convection and was plotting the vertical velocity, I may want positive (upward) velocities with a reddish color map and downward (negative) velocities with a blueish color map. The main disadvantage is that printing out in gray essentially takes the absolute value of the data (not quite, but close enough) and so you preserve magnitude of velocity, but lose all info on sign. All of this, of course, is avoided with a sequential color map (like viridis), but then there isn't the instant recognition that upward (positive) and downward (negative) are different. As Kenneth Moreland states: "The middle point serves as much to highlight the two extremes as it does to highlight itself. In effect, the divergent color map allows us to quickly identify whether values are near extrema and which extrema they are near." But maybe the printing to gray issue should be a more dominant concern.