A Better Default Colormap for Matplotlib | SciPy 2015 | Nathaniel Smith and Stéfan van der Walt By Enthought December 10, 2020 Data Science 51 data analytics, data science, data scientist, data scientists, data visualization, deep learning python, jupyter notebook, machine learning, matplotlib, neural networks python, nlp python, numpy python, python data, python pandas, python seaborn, python sklearn, tensor flow python, tips tricks python 40 Comments [ad_1] Complete SciPy 2015 Talk & Tutorial Playlist here: http://ow.ly/PHjEN Source [ad_2] Previous article Next article Comment List Enthought December 10, 2020 Thanks for not Anish Kapooring the colormap as Matlab did! Reply Enthought December 10, 2020 Would have been more convincing if he had tested the proposed colormap in some real data application. I have not seen anyone using a colormap for a photo before. Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 Where does the figure in 9:14 comes from? Reply Enthought December 10, 2020 These guys definitely know their business… Thanks for the excellent explanations! Reply Enthought December 10, 2020 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 Reply Enthought December 10, 2020 this guy is awsome. I wish I had this level of entertaining presentation skills. Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 August 2018 in the news: "New Map Scale Is More Readable by People Who Are Color Blind" – https://www.scientificamerican.com/article/end-of-the-rainbow-new-map-scale-is-more-readable-by-people-who-are-color-blind/ Reply Enthought December 10, 2020 Nerd programmer humour is alive and well in the new millennium! Reply Enthought December 10, 2020 Very cool talk, thanks a lot Reply Enthought December 10, 2020 Can't copyright a selection of colours. Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 The 'to brain' part is actually four dimensional, as some recent research has shown, the neurons in the retina 'transcode' the three dimensional data to four dimensional data to save bandwidth on the optic nerve. Unfortunately I can't find the paper on it anymore. 😐 Reply Enthought December 10, 2020 Very Informative Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 how about the divergent (or divergence) colormaps? I've been using blue-white-red for the whole time. Reply Enthought December 10, 2020 Very interesting talk. However, I have a question: what would be the "ideal" colormap for a person not being colorblind, and not having the need for a colormap that looks good printed in grey?? Reply Enthought December 10, 2020 Interesting! Reply Enthought December 10, 2020 great talk… Reply Enthought December 10, 2020 plt.style.use('ggplot') Reply Enthought December 10, 2020 This is a great talk! Very clear and useful, I will switch to the new colormap. Reply Enthought December 10, 2020 wow, great talk! interesting, informative, entertaining. Reply Enthought December 10, 2020 The colormap great, but the name… Inferno, Plasma, Magma, viridis? Please change it to Venom and get your shit together :P. Reply Enthought December 10, 2020 Like this talk? See more like it at the SciPy 2016 Conference, to be held July 11-17, 2016 in Austin, Texas. More details at the conference website: http://scipy2016.scipy.org. Reply Enthought December 10, 2020 Sounds like great work. And the talk is done really well. Thanks! Reply Enthought December 10, 2020 Well played. Reply Enthought December 10, 2020 It took me months to learn a lot of this color theory stuff, and he explains it super clear in 20 minutes and adds even more to my knowledge… AMAZING talk! Reply Enthought December 10, 2020 awesome! Reply Enthought December 10, 2020 Great presentation. Is there made a publication on the work? Reply Enthought December 10, 2020 Really don't know there are so many theories behind a colormap. Very informative. Thanks! Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 Great presentation !!!! Reply Enthought December 10, 2020 Congratulations, fantastic work and great talk!! Reply Enthought December 10, 2020 Can't wait to get my hands on viridis and see for myself Reply Enthought December 10, 2020 Surprising there is no mention of CubeHelix. Reply Enthought December 10, 2020 Heh. I also came across that lightning brain while looking for an image recently. Reply Enthought December 10, 2020 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. Reply Enthought December 10, 2020 Great talk and the work on colors is awesome! Reply Write a comment Cancel reply Save my name, email, and website in this browser for the next time I comment.