Researched the origins and purposes of all the colormaps built into matplotlib, then added the info to the colormaps() docstring in pyplot.py
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Documenting the matplotlib colormaps
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| # https://github.com/matplotlib/matplotlib/issues/881 | |
| # Several of the ColorBrewer maps are "qualitative", meaning | |
| # they are just a group of colors that can be used together | |
| # for categories of data. So I remapped Accent to segments | |
| # instead of continuous: | |
| # Actually, these should be used with ListedColormap, and | |
| # the number of colors should depend on the number of | |
| # categories in the data, with colors removed from the | |
| # list in a certain order? | |
| _Accent_data = { | |
| 'blue': [ | |
| (0.0, 0.0, 0.49803921580314636), | |
| (0.125, 0.49803921580314636, 0.83137255907058716), | |
| (0.25, 0.83137255907058716, 0.52549022436141968), | |
| (0.375, 0.52549022436141968, 0.60000002384185791), | |
| (0.5, 0.60000002384185791, 0.69019609689712524), | |
| (0.625, 0.69019609689712524, 0.49803921580314636), | |
| (0.75, 0.49803921580314636, 0.090196080505847931), | |
| (0.875, 0.090196080505847931, 0.40000000596046448), | |
| (1.0, 0.40000000596046448, 0.0), | |
| ], | |
| 'green': [ | |
| (0.0, 0.0, 0.78823530673980713), | |
| (0.125, 0.78823530673980713, 0.68235296010971069), | |
| (0.25, 0.68235296010971069, 0.75294119119644165), | |
| (0.375, 0.75294119119644165, 1.0), | |
| (0.5, 1.0, 0.42352941632270813), | |
| (0.625, 0.42352941632270813, 0.0078431377187371254), | |
| (0.75, 0.0078431377187371254, 0.35686275362968445), | |
| (0.875, 0.35686275362968445, 0.40000000596046448), | |
| (1.0, 0.40000000596046448, 0.0), | |
| ], | |
| 'red': [ | |
| (0.0, 0.0, 0.49803921580314636), | |
| (0.125, 0.49803921580314636, 0.7450980544090271), | |
| (0.25, 0.7450980544090271, 0.99215686321258545), | |
| (0.375, 0.99215686321258545, 1.0), | |
| (0.5, 1.0, 0.21960784494876862), | |
| (0.625, 0.21960784494876862, 0.94117647409439087), | |
| (0.75, 0.94117647409439087, 0.74901962280273438), | |
| (0.875, 0.74901962280273438, 0.40000000596046448), | |
| (1.0, 0.40000000596046448, 0.0), | |
| ], | |
| } |
matplotlib provides a number of colormaps, a complete list of which can be found in cm._cmapnames.
You can set the colormap for an image, pcolor, scatter, etc, using a keyword argument:
imshow(X, cmap=cm.hot)
Additionally, for the "base" colormaps below, you can set the colormap post-hoc using the corresponding pylab interface function:
imshow(X) hot() jet()
In interactive mode, this will update the colormap allowing you to see which one works best for your data.
All colormaps can be reversed by appending _r: For instance,
gray_r is the reverse of gray.
There are 3 common color schemes used in visualization:
- Sequential schemes, for unipolar data that progresses from low to high
- Diverging schemes, for bipolar data that emphasizes positive or negative deviations from a central value
- Qualitative schemes, which don't have a relationship to magnitude
The base colormaps are:
Colormap Description autumn sequential increasing shades of red-orange-yellow bone sequential black-white color map with a tinge of blue, to emulate X-ray film cool sequential decreasing shades of cyan-magenta copper sequential increasing shades of black-copper flag repeating red-white-blue-black pattern gray simple sequential linearly-increasing black-to-white grayscale hot sequential black-red-yellow-white, to emulate blackbody radiation from an object at increasing temperatures hsv red-yellow-green-cyan-blue-pink-magenta, formed by changing the hue component in the HSV color space; meant to be used in plotting periodic data (that is, in which the maximum magnitude and the minimum magnitude are equivalent) jet blue-cyan-yellow-red, a variant of hsv; based on a fluid-jet simulation by NCSA [1] pink sequential increasing pastel black-pink-white, meant for sepia tone colorization of photographs prism repeating red-yellow-green-blue-purple-...-green pattern spring shades of magenta-yellow summer shades of green-yellow winter shades of blue-green spectral black-purple-blue-green-yellow-red-white spectrum
The next 7 palettes are from the Yorick scientific visualisation package, an evolution of the GIST package, both by David H. Munro:
Colormap Description gist_earth mapmaker's colors from dark blue deep ocean to green lowlands to brown highlands to white mountains gist_gray (identical to gray) gist_heat sequential red-orange-yellow-white, to emulate blackbody radiation from an iron bar as it grows hotter gist_ncar pseudo-spectral colormap from National Center for Atmospheric Research [2] gist_rainbow runs through the colors in spectral order at nearly constant intensity gist_stern "Stern special" color table from Interactive Data Language software gist_yarg (identical to gray_r)
The following 34 colormaps are based on the ColorBrewer color specifications and designs developed by Cynthia Brewer:
Diverging:
- BrBG
- PiYG
- PRGn
- PuOr
- RdBu
- RdGy
- RdYlBu
- RdYlGn
- Spectral
Sequential:
- Blues
- BuGn
- BuPu
- GnBu
- Greens
- Greys
- Oranges
- OrRd
- PuBu
- PuBuGn
- PuRd
- Purples
- RdPu
- Reds
- YlGn
- YlGnBu
- YlOrBr
- YlOrRd
Qualitative:
- Accent
- Dark2
- Paired
- Pastel1
- Pastel2
- Set1
- Set2
- Set3
Other miscellaneous schemes:
Colormap Description afmhot sequential black-orange-yellow-white blackbody spectrum, commonly used in atomic force microscopy binary (identical to gray_r) brg blue-red-green bwr diverging blue-white-red coolwarm diverging blue-gray-red, meant to avoid issues with 3D shading, color blindness, and ordering of colors [3] CMRmap "Default colormaps on color images often reproduce to confusing grayscale images. The proposed colormap maintains an aesthetically pleasing color image that automatically reproduces to a monotonic grayscale with discrete, quantifiable saturation levels." [4] cubehelix Unlike most other color schemes cubehelix was designed by D.A. Green to be monotonically increasing in terms of perceived brightness. Also, when printed on a black and white postscript printer, the scheme results in a greyscale with monotonically increasing brightness. This color scheme is named cubehelix because the r,g,b values produced can be visualised as a squashed helix around the diagonal in the r,g,b color cube. gnuplot gnuplot's traditional pm3d scheme (black-blue-red-yellow) gnuplot2 sequential color printable as gray (black-blue-violet-yellow-white) ocean green-blue-white rainbow purple-blue-green-yellow-orange-red seismic diverging blue-white-red terrain mapmaker's colors, blue-green-yellow-brown-white, originally from IGOR Pro
Footnotes
| [1] | Rainbow colormaps, jet in particular, are considered a poor choice for scientific visualization by many researchers: Rainbow Color Map (Still) Considered Harmful |
| [2] | Resembles "BkBlAqGrYeOrReViWh200" from Color Table Gallery |
| [3] | See Diverging Color Maps for Scientific Visualization by Kenneth Moreland. |
| [4] | See A Color Map for Effective Black-and-White Rendering of Color-Scale Images by Carey Rappaport |
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| From cm._cmapnames | |
| Copied from MATLAB: | |
| autumn | |
| bone | |
| cool | |
| copper | |
| flag | |
| gray | |
| hot | |
| hsv | |
| jet | |
| pink | |
| prism | |
| spring | |
| summer | |
| winter | |
| (Not copied from MATLAB: colorcube, lines, white) | |
| These were all added here https://github.com/matplotlib/matplotlib/commit/26ffb47e95d7d694a94bb101d17ebcd0622d15f7 | |
| spectral (Spectral is not the same! rename to nipy_spectral?) | |
| "Tim Leslie's spectral patch" | |
| https://github.com/matplotlib/matplotlib/commit/b64652d335d4318d1b1a332843837a0c17a4a202 | |
| added after "Spectral" | |
| from nipy | |
| http://sourceforge.net/mailarchive/message.php?msg_id=8931272 | |
| Only non-MATLAB colormap to have a post-hoc function | |
| Related to http://www.math.mcgill.ca/keith/surfstat/doc/SurfStat/spectral.html and http://www.mathworks.com/matlabcentral/fileexchange/4706-mia-2-4/content/mia24/Tools/spectralmni.m but none of these have the same endpoints | |
| "black-purple-blue-green-yellow-red-white" | |
| Copied from GIST/Yorick: | |
| # The next 7 palettes are from the Yorick scientific visalisation package, | |
| # an evolution of the GIST package, both by David H. Munro. | |
| descriptions here http://dhmunro.github.com/yorick-doc/manual/yorick_70.html http://projects.scipy.org/scipy/browser/trunk/Lib/xplt/gistdata?rev=685 | |
| These palettes tend to start with dark colors and progress toward lighter colors, except yarg and rainbow | |
| gist_earth "is loosely based on mapmaker's colors from dark blue deep ocean to green lowlands to brown highlands to white mountains" "dk blue - lt blue - dk green - yellow green - lt brown - white sort of like mapmakers colors from deep ocean to snow capped peak" | |
| gist_gray (identical to gray) | |
| gist_heat "a red-orange scale resembling the colors of an iron bar as it grows hotter" "dk red - red - orange - yellow - white color temperatures of hot iron bar" | |
| gist_ncar - resembles BkBlAqGrYeOrReViWh200 from National Center for Atmospheric Research | |
| http://www.ncl.ucar.edu/Document/Graphics/color_table_gallery.shtml | |
| gist_rainbow "runs through the colors in spectral order at nearly constant intensity" "colors in spectral order" | |
| gist_stern # red - dk blue - lt blue - gray green - white "Stern special" color table from IDL (c) Research Systems, Inc. | |
| gist_yarg (identical to gray_r and binary) | |
| sources here: https://github.com/dhmunro/yorick/tree/master/g | |
| no explanation of what ncar or stern are for | |
| 'Earlier versions of SkyView used the "Stern Special" color table by default, but we now default to more realistic if less colorful black and white images.' | |
| 'In appearance the most significant change is that by default images are now black and white. Users can select any of the old and many new color tables if desired but we feel that the black and white images most accurately reflect the intensity scaling. Some novice users were confused about the meaning of the colors in the old versions. The old system used the Stern Special color table.' | |
| In [4]: array_equal(cm.cmap_d['gist_gray'](arange(256)), cm.cmap_d['gray'](arange(256))) | |
| Out[4]: True | |
| ColorBrewer | |
| # 34 colormaps based on color specifications and designs | |
| # developed by Cynthia Brewer (http://colorbrewer.org). | |
| # The ColorBrewer palettes have been included under the terms | |
| # of an Apache-stype license (for details, see the file | |
| # LICENSE_COLORBREWER in the license directory of the matplotlib | |
| # source distribution). | |
| Added here https://github.com/matplotlib/matplotlib/commit/31c07815140e97becf2f2e037b8a214e263290b2 | |
| Categorizations here http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=RColorBrewer:ColorBrewer | |
| maxcolors category | |
| Diverging | |
| BrBG 11 div | |
| PiYG 11 div | |
| PRGn 11 div | |
| PuOr 11 div | |
| RdBu 11 div | |
| RdGy 11 div | |
| RdYlBu 11 div | |
| RdYlGn 11 div | |
| Spectral 11 div (not the same as spectral) | |
| Qualitative (these aren't supposed to be continuous! bug report?) | |
| Accent 8 qual | |
| Dark2 8 qual | |
| Paired 12 qual | |
| Pastel1 9 qual | |
| Pastel2 8 qual | |
| Set1 9 qual | |
| Set2 8 qual | |
| Set3 12 qual | |
| Sequential | |
| Blues 9 seq | |
| BuGn 9 seq | |
| BuPu 9 seq | |
| GnBu 9 seq | |
| Greens 9 seq | |
| Greys 9 seq | |
| Oranges 9 seq | |
| OrRd 9 seq | |
| PuBu 9 seq | |
| PuBuGn 9 seq | |
| PuRd 9 seq | |
| Purples 9 seq | |
| RdPu 9 seq | |
| Reds 9 seq | |
| YlGn 9 seq | |
| YlGnBu 9 seq | |
| YlOrBr 9 seq | |
| YlOrRd 9 seq | |
| cubehelix | |
| Unlike most other color schemes cubehelix was designed by D.A. Green to | |
| be monotonically increasing in terms of perceived brightness. | |
| Also, when printed on a black and white postscript printer, the scheme | |
| results in a greyscale with monotonically increasing brightness. | |
| This color scheme is named cubehelix because the r,g,b values produced | |
| can be visualised as a squashed helix around the diagonal in the | |
| r,g,b color cube. | |
| discussion http://sourceforge.net/mailarchive/message.php?msg_id=28065739 | |
| paper http://arxiv.org/abs/1108.5083 | |
| see cm.cubehelix() (no way to view the docstring?) | |
| coolwarm | |
| # This bipolar color map was generated from | |
| # "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland. | |
| # <http://www.cs.unm.edu/~kmorel/documents/ColorMaps/> | |
| Discussion about patch: | |
| http://sourceforge.net/mailarchive/message.php?msg_id=27816391 | |
| – The map yields images that are aesthetically pleasing. | |
| – The map has a maximal perceptual resolution. | |
| – Interference with the shading of 3D surfaces is minimal. | |
| – The map is not sensitive to vision deficiencies. | |
| – The order of the colors should be intuitively the same for all people. | |
| – The perceptual interpolation matches the underlying scalars of the map. | |
| http://www.cs.unm.edu/~kmorel/documents/ColorMaps/index.html | |
| CMRmap | |
| Default colormaps on color images often reproduce to confusing grayscale images. The proposed colormap maintains an aesthetically pleasing color image that automatically reproduces to a monotonic grayscale with discrete, quantifiable saturation levels. | |
| # Implementation of Carey Rappaport's CMRmap. | |
| # See `A Color Map for Effective Black-and-White Rendering of Color-Scale Images' by Carey Rappaport | |
| # http://www.mathworks.com/matlabcentral/fileexchange/2662-cmrmap-m | |
| misc others added at the same time | |
| afmhot - Used in atomic force microscopy? | |
| brg | |
| bwr | |
| gnuplot | |
| gnuplot2 | |
| ocean | |
| rainbow | |
| seismic | |
| terrain - from "a measurement program called 'Igor'" http://www.wavemetrics.com/products/igorpro/creatinggraphs/colortab.htm | |
| all added here: http://sourceforge.net/mailarchive/message.php?msg_id=23330302 | |
| seismic from here? http://soliton.vm.bytemark.co.uk/pub/cpt-city/gery/index.html http://www.mathworks.com/matlabcentral/fileexchange/30585-large-data-in-matlab-a-seismic-data-processing-case-study/content/migration/seismic.m | |
| afmhot, ocean, rainbow from here? http://gnuplot.sourceforge.net/docs_4.2/node216.html | |
| apparently AFM because heat is a common palette for atomic force microscopy? https://www.google.com/search?q=atomic+force+microscopy&tbm=isch "The color selection uses the HSB-color model where the color (H) is set in ° value. The color is selected by entering a number or by clicking a color in the color bar." | |
| binary | |
| identical to gray_r and gist_yarg | |
| In [8]: array_equal(cm.cmap_d['binary'](arange(256)), cm.cmap_d['gray_r'](arange(256))) | |
| Out[8]: True | |
| added here: https://github.com/matplotlib/matplotlib/commit/47af03d985d9729f3eedc41354fe11a22eff35c4 | |
| meant for barcodes? | |
| identify which are isoluminant/monotonic, sequential/diverging/cyclic/spectral, etc | |
| "sequential (quantitative) variables, discrete (qualitative) variables, and bipolar (diverging) variables" |
From http://ab-initio.mit.edu/wiki/index.php/Color_tables_in_h5topng
- autumn
- red-orange-yellow color map; based on colormap of the same name in Matlab
- bluered
- blue-white-red colorbar, useful for signed data in conjunction with -Z option to make white=0
- bone
- nearly grayscale (blackish to whitish) color map with a tinge of blue; based on colormap of the same name in Matlab, which suggests using it to add an "electronic" look to grayscale images
- colorcube
- enhanced color-cube color map; based on colormap of the same name in Matlab, basically designed to fill the RGB color space with an emphasis on a few pure colors
- cool
- cyan-magenta color map; based on colormap of the same name in Matlab
- copper
- black-copper color map; based on colormap of the same name in Matlab
- dkbluered
- dark blue-white-red colorbar, useful for signed data in conjunction with -Z option to make white=0; similar to bluered but shows a bit more dynamic range for the maxima/minima by darkening at the ends
- flag
- alternating red/white/blue/black color map; based on colormap of the same name in Matlab
- gray
- simple black-to-white grayscale color bar
- green
- white-green color map; useful for translucent overlays with -A
- hot
- black-red-yellow-white color map, useful for nonnegative "intensity" data — based on colormap of the same name in Matlab, loosely resembling the color of heated object at increasing temperatures
- hsv
- red-yellow-green-cyan-blue-pink-magenta color map formed by changing the hue component in the HSV color space; based on colormap of the same name in Matlab, who recommend it for used in plotting periodic data (that is, in which the maximum magnitude and the minimum magnitude are equivalent)
- jet
- blue-cyan-yellow-red color map (a variant of hsv; based on colormap of the same name in Matlab, who based it on a fluid-jet simulation by NCSA
- lines
- oscillating color map; based on colormap of the same name in Matlab (based on the Matlab plot-line colors)
- pink
- pastel black-pink-white color map; based on colormap of the same name in Matlab, used for Sepia tone colorization
- prism
- repeating red-yellow-green-blue-purple-...-green color map; based on colormap of the same name in Matlab
- spring
- magenta-yellow color map; based on colormap of the same name in Matlab
- summer
- green-yellow color map; based on colormap of the same name in Matlab
- vga
- Windows 4-bit color map; based on colormap of the same name in Matlab
- winter
- blue-green color map; based on colormap of the same name in Matlab
- yarg
- simple white-to-black grayscale color bar (the reverse of gray, and almost equivalent to using -gray or gray with -r); this is useful to make contour-like overlays with the -A option because its transparency scale (black is transparent) is the opposite of gray (white is transparent)
- yellow
- white-yellow color map; useful for translucent overlays with -A
From http://www.mathworks.com/help/techdoc/ref/colormap.html
- autumn
- varies smoothly from red, through orange, to yellow.
- bone
- is a grayscale colormap with a higher value for the blue component. This colormap is useful for adding an "electronic" look to grayscale images.
- colorcube
- contains as many regularly spaced colors in RGB color space as possible, while attempting to provide more steps of gray, pure red, pure green, and pure blue.
- cool
- consists of colors that are shades of cyan and magenta. It varies smoothly from cyan to magenta.
- copper
- varies smoothly from black to bright copper.
- flag
- consists of the colors red, white, blue, and black. This colormap completely changes color with each index increment.
- gray
- returns a linear grayscale colormap.
- hot
- varies smoothly from black through shades of red, orange, and yellow, to white.
- hsv
- varies the hue component of the hue-saturation-value color model. The colors begin with red, pass through yellow, green, cyan, blue, magenta, and return to red. The colormap is particularly appropriate for displaying periodic functions. hsv(m) is the same as hsv2rgb([h ones(m,2)]) where h is the linear ramp, h = (0:m–1)'/m.
- jet
- ranges from blue to red, and passes through the colors cyan, yellow, and orange. It is a variation of the hsv colormap. The jet colormap is associated with an astrophysical fluid jet simulation from the National Center for Supercomputer Applications. See Examples.
- lines
- produces a colormap of colors specified by the axes ColorOrder property and a shade of gray.
- pink
- contains pastel shades of pink. The pink colormap provides sepia tone colorization of grayscale photographs.
- prism
- repeats the six colors red, orange, yellow, green, blue, and violet.
- spring
- consists of colors that are shades of magenta and yellow.
- summer
- consists of colors that are shades of green and yellow.
- white
- is an all white monochrome colormap.
- winter
- consists of colors that are shades of blue and green.
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