GitHub - colour-science/colour: Colour Science for Python (original) (raw)
Colour is an open-sourcePython package providing a comprehensive number of algorithms and datasets for colour science.
It is freely available under theBSD-3-Clause terms.
Colour is an affiliated project of NumFOCUS, a 501(c)(3) nonprofit in the United States.
Table of Contents
- 1 Draft Release Notes
- 2 Sponsors
- 3 Features
- 3.1 Automatic Colour Conversion Graph - colour.graph
- 3.2 Chromatic Adaptation - colour.adaptation
- 3.3 Algebra - colour.algebra
- 3.4 Colour Appearance Models - colour.appearance
- 3.5 Colour Blindness - colour.blindness
- 3.6 Colour Correction - colour characterisation
- 3.7 ACES Input Transform - colour characterisation
- 3.8 Colorimetry - colour.colorimetry
- 3.9 Contrast Sensitivity Function - colour.contrast
- 3.10 Colour Difference - colour.difference
- 3.11 IO - colour.io
- 3.12 Colour Models - colour.models
- 3.13 Colour Notation Systems - colour.notation
- 3.14 Optical Phenomena - colour.phenomena
- 3.15 Light Quality - colour.quality
- 3.16 Spectral Up-Sampling & Recovery - colour.recovery
- 3.17 Correlated Colour Temperature Computation Methods - colour.temperature
- 3.18 Colour Volume - colour.volume
- 3.19 Geometry Primitives Generation - colour.geometry
- 3.20 Plotting - colour.plotting
- 4 User Guide
- 5 API Reference
- 6 See Also
- 7 Code of Conduct
- 8 Contact & Social
- 9 Thank You!
- 10 About
1 Draft Release Notes
The draft release notes of thedevelopbranch are available at thisurl.
2 Sponsors
We are grateful 💖 for the support of oursponsors. If you'd like to join them, please considerbecoming a sponsor on OpenCollective.
Gold Sponsors
Silver Sponsors
Nick Shaw |
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Bronze Sponsors
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CAVE Academy |
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Donations & Special Sponsors
JetBrains |
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Richard Lackey |
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Liam Collod |
Alex Mitchell |
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Frederic Savoir |
Howard Colin |
Christophe Brejon |
Mario Rokicki |
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3 Features
Most of the objects are available from the colour namespace:
3.1 Automatic Colour Conversion Graph - colour.graph
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"] colour.convert(sd, "Spectral Distribution", "sRGB", verbose={"mode": "Short"})
=============================================================================== * * * [ Conversion Path ] * * * * "sd_to_XYZ" --> "XYZ_to_sRGB" * * *
[ 0.49034776 0.30185875 0.23587685]
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"] illuminant = colour.SDS_ILLUMINANTS["FL2"] colour.convert( sd, "Spectral Distribution", "sRGB", sd_to_XYZ={"illuminant": illuminant}, )
[ 0.47924575 0.31676968 0.17362725]
3.2 Chromatic Adaptation - colour.adaptation
import colour
XYZ = [0.20654008, 0.12197225, 0.05136952] D65 = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["D65"] A = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["A"] colour.chromatic_adaptation(XYZ, colour.xy_to_XYZ(D65), colour.xy_to_XYZ(A))
[ 0.25331034 0.13765286 0.01543185]
import colour
sorted(colour.CHROMATIC_ADAPTATION_METHODS)
['CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Li 2025', 'Von Kries', 'Zhai 2018', 'vK20']
3.3 Algebra - colour.algebra
3.3.1 Kernel Interpolation
import colour
y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500] x = range(len(y)) colour.KernelInterpolator(x, y)([0.25, 0.75, 5.50])
[ 6.18062083 8.08238488 57.85783403]
3.3.2 Sprague (1880) Interpolation
import colour
y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500] x = range(len(y)) colour.SpragueInterpolator(x, y)([0.25, 0.75, 5.50])
[ 6.72951612 7.81406251 43.77379185]
3.4 Colour Appearance Models - colour.appearance
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_CIECAM02(J=34.434525727858997, C=67.365010921125915, h=22.279164147957076, s=62.814855853327131, Q=177.47124941102123, M=70.024939419291385, H=2.689608534423904, HC=None)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_CIECAM16(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_CIECAM16(J=33.880368498111686, C=69.444353357408033, h=19.510887327451748, s=64.03612114840314, Q=176.03752758512178, M=72.18638534116765, H=399.52975599115319, HC=None)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_CAM16(J=33.880368498111686, C=69.444353357408033, h=19.510887327451748, s=64.03612114840314, Q=176.03752758512178, M=72.18638534116765, H=399.52975599115319, HC=None)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_Hellwig2022(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_Hellwig2022(J=33.880368498111686, C=37.579419116276348, h=19.510887327451748, s=109.33343382561695, Q=45.34489577734751, M=49.577131618021212, H=399.52975599115319, HC=None, J_HK=39.41741758094139, Q_HK=52.755585941150315)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_Kim2009(XYZ, XYZ_w, L_A)
CAM_Specification_Kim2009(J=19.879918542450937, C=55.83905525087696, h=22.013388165090031, s=112.9797935493912, Q=36.309026130161513, M=46.346415858227871, H=2.3543198369639753, HC=None)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_sCAM(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_sCAM(J=42.550992142462782, C=40.419439198593302, h=20.904455433026421, Q=175.74578999778015, M=14.325369984981474, H=7.1106008503613021, HC=None, V=81.92545469934403, K=18.07454530065597, W=0.023675944970833029, D=99.976324055029167)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_ZCAM(XYZ, XYZ_w, L_A, Y_b)
CAM_Specification_ZCAM(J=38.347186278956357, C=21.121389892085183, h=33.711578931095183, s=81.444585609489536, Q=76.986725284523772, M=42.403805833900513, H=0.45779200212217158, HC=None, V=43.623590687423551, K=43.20894953152817, W=34.829588380192149)
3.5 Colour Blindness - colour.blindness
import colour
cmfs = colour.colorimetry.MSDS_CMFS_LMS["Stockman & Sharpe 2 Degree Cone Fundamentals"] colour.msds_cmfs_anomalous_trichromacy_Machado2009(cmfs, [15, 0, 0])[450]
[ 0.08912884 0.0870524 0.955393 ]
import colour
cmfs = colour.colorimetry.MSDS_CMFS_LMS["Stockman & Sharpe 2 Degree Cone Fundamentals"] primaries = colour.MSDS_DISPLAY_PRIMARIES["Apple Studio Display"] d_LMS = (15, 0, 0) colour.matrix_anomalous_trichromacy_Machado2009(cmfs, primaries, d_LMS)
[[-0.27774652 2.65150084 -1.37375432] [ 0.27189369 0.20047862 0.52762768] [ 0.00644047 0.25921579 0.73434374]]
3.6 Colour Correction - colour characterisation
import colour import numpy as np
RGB = [0.17224810, 0.09170660, 0.06416938] M_T = np.random.random((24, 3)) M_R = M_T + (np.random.random((24, 3)) - 0.5) * 0.5 colour.colour_correction(RGB, M_T, M_R)
[ 0.17960686 0.08935744 0.06766639] # (results will vary due to random inputs)
import colour
sorted(colour.COLOUR_CORRECTION_METHODS)
['Cheung 2004', 'Finlayson 2015', 'Vandermonde']
3.7 ACES Input Transform - colour characterisation
import colour
sensitivities = colour.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"] illuminant = colour.SDS_ILLUMINANTS["D55"] colour.matrix_idt(sensitivities, illuminant)
(array([[ 0.59368175, 0.30418373, 0.10213451], [ 0.0045798 , 1.14946005, -0.15403985], [ 0.03552214, -0.16312291, 1.12760078]]), array([ 1.58214188, 1. , 1.28910346]))
3.8 Colorimetry - colour.colorimetry
3.8.1 Spectral Computations
import colour
colour.sd_to_XYZ(colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"])
[ 36.94726204 32.62076174 13.0143849 ]
import colour
sorted(colour.SD_TO_XYZ_METHODS)
['ASTM E308', 'Integration', 'astm2015']
3.8.2 Multi-Spectral Computations
import colour
msds = [ [ [ 0.01367208, 0.09127947, 0.01524376, 0.02810712, 0.19176012, 0.04299992, ], [ 0.00959792, 0.25822842, 0.41388571, 0.22275120, 0.00407416, 0.37439537, ], [ 0.01791409, 0.29707789, 0.56295109, 0.23752193, 0.00236515, 0.58190280, ], ], [ [ 0.01492332, 0.10421912, 0.02240025, 0.03735409, 0.57663846, 0.32416266, ], [ 0.04180972, 0.26402685, 0.03572137, 0.00413520, 0.41808194, 0.24696727, ], [ 0.00628672, 0.11454948, 0.02198825, 0.39906919, 0.63640803, 0.01139849, ], ], [ [ 0.04325933, 0.26825359, 0.23732357, 0.05175860, 0.01181048, 0.08233768, ], [ 0.02484169, 0.12027161, 0.00541695, 0.00654612, 0.18603799, 0.36247808, ], [ 0.03102159, 0.16815442, 0.37186235, 0.08610666, 0.00413520, 0.78492409, ], ], [ [ 0.11682307, 0.78883040, 0.74468607, 0.83375293, 0.90571451, 0.70054168, ], [ 0.06321812, 0.41898224, 0.15190357, 0.24591440, 0.55301750, 0.00657664, ], [ 0.00305180, 0.11288624, 0.11357290, 0.12924391, 0.00195315, 0.21771573, ], ], ]
colour.msds_to_XYZ( msds, method="Integration", shape=colour.SpectralShape(400, 700, 60), )
[[[ 7.68544647 4.09414317 8.49324254] [ 17.12567298 27.77681821 25.52573685] [ 19.10280411 34.45851476 29.76319628]] [[ 18.03375827 8.62340812 9.71702574] [ 15.03110867 6.54001068 24.53208465] [ 37.68269495 26.4411103 10.66361816]] [[ 8.09532373 12.75333339 25.79613956] [ 7.09620297 2.79257389 11.15039854] [ 8.933163 19.39985815 17.14915636]] [[ 80.00969553 80.39810464 76.08184429] [ 33.27611427 24.38947838 39.34919287] [ 8.89425686 11.05185138 10.86767594]]]
import colour
sorted(colour.MSDS_TO_XYZ_METHODS)
['ASTM E308', 'Integration', 'astm2015']
3.8.3 Blackbody Spectral Radiance Computation
import colour
colour.sd_blackbody(5000)
[[ 360. 6654.27827064] [ 361. 6709.60527925] [ 362. 6764.82512152] ... [ 780. 10573.85196369]]
3.8.4 Dominant, Complementary Wavelength & Colour Purity Computation
import colour
xy = [0.54369557, 0.32107944] xy_n = [0.31270000, 0.32900000] colour.dominant_wavelength(xy, xy_n)
(array(616.0), array([ 0.68354746, 0.31628409]), array([ 0.68354746, 0.31628409]))
3.8.5 Lightness Computation
import colour
colour.lightness(12.19722535)
41.5278758447
import colour
sorted(colour.LIGHTNESS_METHODS)
['Abebe 2017', 'CIE 1976', 'Fairchild 2010', 'Fairchild 2011', 'Glasser 1958', 'Lstar1976', 'Wyszecki 1963']
3.8.6 Luminance Computation
import colour
colour.luminance(41.52787585)
12.1972253534
import colour
sorted(colour.LUMINANCE_METHODS)
['ASTM D1535', 'Abebe 2017', 'CIE 1976', 'Fairchild 2010', 'Fairchild 2011', 'Newhall 1943', 'astm2008', 'cie1976']
3.8.7 Whiteness Computation
import colour
XYZ = [95.00000000, 100.00000000, 105.00000000] XYZ_0 = [94.80966767, 100.00000000, 107.30513595] colour.whiteness(XYZ, XYZ_0)
[ 93.756 -1.33000001]
import colour
sorted(colour.WHITENESS_METHODS)
['ASTM E313', 'Berger 1959', 'CIE 2004', 'Ganz 1979', 'Stensby 1968', 'Taube 1960', 'cie2004']
3.8.8 Yellowness Computation
import colour
XYZ = [95.00000000, 100.00000000, 105.00000000] colour.yellowness(XYZ)
4.34
import colour
sorted(colour.YELLOWNESS_METHODS)
['ASTM D1925', 'ASTM E313', 'ASTM E313 Alternative']
3.8.9 Luminous Flux, Efficiency & Efficacy Computation
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"] colour.luminous_flux(sd)
23807.6555274
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"] colour.luminous_efficiency(sd)
0.199439356245
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"] colour.luminous_efficacy(sd)
136.217080315
3.9 Contrast Sensitivity Function - colour.contrast
import colour
colour.contrast_sensitivity_function(u=4, X_0=60, E=65)
358.511807899
import colour
sorted(colour.CONTRAST_SENSITIVITY_METHODS)
['Barten 1999']
3.10 Colour Difference - colour.difference
import colour
Lab_1 = [100.00000000, 21.57210357, 272.22819350] Lab_2 = [100.00000000, 426.67945353, 72.39590835] colour.delta_E(Lab_1, Lab_2)
94.0356490267
import colour
sorted(colour.DELTA_E_METHODS)
['CAM02-LCD', 'CAM02-SCD', 'CAM02-UCS', 'CAM16-LCD', 'CAM16-SCD', 'CAM16-UCS', 'CIE 1976', 'CIE 1994', 'CIE 2000', 'CMC', 'DIN99', 'HyAB', 'HyCH', 'ITP', 'cie1976', 'cie1994', 'cie2000']
3.11 IO - colour.io
3.11.1 Images
import colour
RGB = colour.read_image("Ishihara_Colour_Blindness_Test_Plate_3.png") RGB.shape
(276, 281, 3)
3.11.2 Spectral Images - Fichet et al. (2021)
import colour
components = colour.read_spectral_image_Fichet2021("Polarised.exr") list(components.keys())
['S0', 'S1', 'S2', 'S3']
3.11.3 Look Up Table (LUT) Data
import colour
LUT = colour.read_LUT("ACES_Proxy_10_to_ACES.cube") print(LUT)
LUT3x1D - ACES Proxy 10 to ACES
Dimensions : 2 Domain : [[0 0 0] [1 1 1]] Size : (32, 3)
import colour
RGB = [0.17224810, 0.09170660, 0.06416938] LUT.apply(RGB)
[ 0.00575674, 0.00181493, 0.00121419]
3.12 Colour Models - colour.models
3.12.1 CIE xyY Colourspace
import colour
colour.XYZ_to_xyY([0.20654008, 0.12197225, 0.05136952])
[ 0.54369557 0.32107944 0.12197225]
3.12.2 CIE L*a*b* Colourspace
import colour
colour.XYZ_to_Lab([0.20654008, 0.12197225, 0.05136952])
[ 41.52787529 52.63858304 26.92317922]
3.12.3 CIE L*u*v* Colourspace
import colour
colour.XYZ_to_Luv([0.20654008, 0.12197225, 0.05136952])
[ 41.52787529 96.83626054 17.75210149]
3.12.4 CIE 1960 UCS Colourspace
import colour
colour.XYZ_to_UCS([0.20654008, 0.12197225, 0.05136952])
[ 0.13769339 0.12197225 0.1053731 ]
3.12.5 CIE 1964 U*V*W* Colourspace
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] colour.XYZ_to_UVW(XYZ)
[ 94.55035725 11.55536523 40.54757405]
3.12.6 CAM02-LCD, CAM02-SCD, and CAM02-UCS Colourspaces - Luo, Cui and Li (2006)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 surround = colour.VIEWING_CONDITIONS_CIECAM02["Average"] specification = colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b, surround) JMh = [specification.J, specification.M, specification.h] colour.JMh_CIECAM02_to_CAM02UCS(JMh)
[ 47.16899898 38.72623785 15.8663383 ]
import colour
XYZ = [0.20654008, 0.12197225, 0.05136952] XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_CAM02UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)
[ 47.16899898 38.72623785 15.8663383 ]
3.12.7 CAM16-LCD, CAM16-SCD, and CAM16-UCS Colourspaces - Li et al. (2017)
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] XYZ_w = [95.05, 100.00, 108.88] L_A = 318.31 Y_b = 20.0 surround = colour.VIEWING_CONDITIONS_CAM16["Average"] specification = colour.XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b, surround) JMh = [specification.J, specification.M, specification.h] colour.JMh_CAM16_to_CAM16UCS(JMh)
[ 46.55542238 40.22460974 14.25288392]
import colour
XYZ = [0.20654008, 0.12197225, 0.05136952] XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100] L_A = 318.31 Y_b = 20.0 colour.XYZ_to_CAM16UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)
[ 46.55542238 40.22460974 14.25288392]
3.12.8 DIN99 Colourspace and DIN99b, DIN99c, DIN99d Refined Formulas
import colour
Lab = [41.52787529, 52.63858304, 26.92317922] colour.Lab_to_DIN99(Lab)
[ 53.22821988 28.41634656 3.89839552]
3.12.9 ICaCb Colourspace
import colour
colour.XYZ_to_ICaCb([0.20654008, 0.12197225, 0.05136952])
[ 0.06875297 0.05753352 0.02081548]
3.12.10 IgPgTg Colourspace
import colour
colour.XYZ_to_IgPgTg([0.20654008, 0.12197225, 0.05136952])
[ 0.42421258 0.18632491 0.10689223]
3.12.11 IPT Colourspace
import colour
colour.XYZ_to_IPT([0.20654008, 0.12197225, 0.05136952])
[ 0.38426191 0.38487306 0.18886838]
3.12.12 Jzazbz Colourspace
import colour
colour.XYZ_to_Jzazbz([0.20654008, 0.12197225, 0.05136952])
[ 0.00535048 0.00924302 0.00526007]
3.12.13 Hunter L,a,b Colour Scale
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] colour.XYZ_to_Hunter_Lab(XYZ)
[ 34.92452577 47.06189858 14.38615107]
3.12.14 Hunter Rd,a,b Colour Scale
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] colour.XYZ_to_Hunter_Rdab(XYZ)
[ 12.197225 57.12537874 17.46241341]
3.12.15 Oklab Colourspace
import colour
colour.XYZ_to_Oklab([0.20654008, 0.12197225, 0.05136952])
[ 0.51634019 0.154695 0.06289579]
3.12.16 OSA UCS Colourspace
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100] colour.XYZ_to_OSA_UCS(XYZ)
[-3.0049979 2.99713697 -9.66784231]
3.12.17 ProLab Colourspace
import colour
colour.XYZ_to_ProLab([0.51634019, 0.15469500, 0.06289579])
[ 59.8466286 115.0396354 20.12510352]
3.12.18 Ragoo and Farup (2021) Optimised IPT Colourspace
import colour
colour.XYZ_to_IPT_Ragoo2021([0.20654008, 0.12197225, 0.05136952])
[ 0.42248243 0.2910514 0.20410663]
3.12.19 Yrg Colourspace - Kirk (2019)
import colour
colour.XYZ_to_Yrg([0.20654008, 0.12197225, 0.05136952])
[ 0.13137801 0.49037645 0.37777388]
3.12.20 hdr-CIELAB Colourspace
import colour
colour.XYZ_to_hdr_CIELab([0.20654008, 0.12197225, 0.05136952])
[ 51.87002062 60.4763385 32.14551912]
3.12.21 hdr-IPT Colourspace
import colour
colour.XYZ_to_hdr_IPT([0.20654008, 0.12197225, 0.05136952])
[ 25.18261761 -22.62111297 3.18511729]
3.12.22 Y'CbCr Colour Encoding
import colour
colour.RGB_to_YCbCr([1.0, 1.0, 1.0])
[ 0.92156863 0.50196078 0.50196078]
3.12.23 YCoCg Colour Encoding
import colour
colour.RGB_to_YCoCg([0.75, 0.75, 0.0])
[ 0.5625 0.375 0.1875]
3.12.24 ICtCp Colour Encoding
import colour
colour.RGB_to_ICtCp([0.45620519, 0.03081071, 0.04091952])
[ 0.07351364 0.00475253 0.09351596]
3.12.25 HSV Colourspace
import colour
colour.RGB_to_HSV([0.45620519, 0.03081071, 0.04091952])
[ 0.99603944 0.93246304 0.45620519]
3.12.26 IHLS Colourspace
import colour
colour.RGB_to_IHLS([0.45620519, 0.03081071, 0.04091952])
[ 6.26236117 0.12197943 0.42539448]
3.12.27 Prismatic Colourspace
import colour
colour.RGB_to_Prismatic([0.25, 0.50, 0.75])
[ 0.75 0.16666667 0.33333333 0.5 ]
3.12.28 RGB Colourspace and Transformations
import colour
XYZ = [0.21638819, 0.12570000, 0.03847493] illuminant_XYZ = [0.34570, 0.35850] illuminant_RGB = [0.31270, 0.32900] chromatic_adaptation_transform = "Bradford" matrix_XYZ_to_RGB = [ [3.24062548, -1.53720797, -0.49862860], [-0.96893071, 1.87575606, 0.04151752], [0.05571012, -0.20402105, 1.05699594], ] colour.XYZ_to_RGB( XYZ, illuminant_XYZ, illuminant_RGB, matrix_XYZ_to_RGB, chromatic_adaptation_transform, )
[ 0.45595571 0.03039702 0.04087245]
3.12.29 RGB Colourspace Derivation
import colour
p = [0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700] w = [0.32168, 0.33767] colour.normalised_primary_matrix(p, w)
[[ 9.52552396e-01 0.00000000e+00 9.36786317e-05] [ 3.43966450e-01 7.28166097e-01 -7.21325464e-02] [ 0.00000000e+00 0.00000000e+00 1.00882518e+00]]
3.12.30 RGB Colourspaces
import colour
sorted(colour.RGB_COLOURSPACES)
['ACES2065-1', 'ACEScc', 'ACEScct', 'ACEScg', 'ACESproxy', 'ARRI Wide Gamut 3', 'ARRI Wide Gamut 4', 'Adobe RGB (1998)', 'Adobe Wide Gamut RGB', 'Apple RGB', 'Best RGB', 'Beta RGB', 'Blackmagic Wide Gamut', 'CIE RGB', 'CIE XYZ-D65 - Scene-referred', 'Cinema Gamut', 'ColorMatch RGB', 'DCDM XYZ', 'DCI-P3', 'DCI-P3-P', 'DJI D-Gamut', 'DRAGONcolor', 'DRAGONcolor2', 'DaVinci Wide Gamut', 'Display P3', 'Don RGB 4', 'EBU Tech. 3213-E', 'ECI RGB v2', 'ERIMM RGB', 'Ekta Space PS 5', 'F-Gamut', 'F-Gamut C', 'FilmLight E-Gamut', 'FilmLight E-Gamut 2', 'Gamma 1.8 Encoded Rec.709', 'Gamma 2.2 Encoded AP1', 'Gamma 2.2 Encoded AdobeRGB', 'Gamma 2.2 Encoded Rec.709', 'ITU-R BT.2020', 'ITU-R BT.470 - 525', 'ITU-R BT.470 - 625', 'ITU-R BT.709', 'ITU-T H.273 - 22 Unspecified', 'ITU-T H.273 - Generic Film', 'Linear AdobeRGB', 'Linear P3-D65', 'Linear Rec.2020', 'Linear Rec.709 (sRGB)', 'Max RGB', 'N-Gamut', 'NTSC (1953)', 'NTSC (1987)', 'P3-D65', 'PLASA ANSI E1.54', 'Pal/Secam', 'ProPhoto RGB', 'Protune Native', 'REDWideGamutRGB', 'REDcolor', 'REDcolor2', 'REDcolor3', 'REDcolor4', 'RIMM RGB', 'ROMM RGB', 'Russell RGB', 'S-Gamut', 'S-Gamut3', 'S-Gamut3.Cine', 'SMPTE 240M', 'SMPTE C', 'Sharp RGB', 'V-Gamut', 'Venice S-Gamut3', 'Venice S-Gamut3.Cine', 'Xtreme RGB', 'aces', 'adobe1998', 'g18_rec709_scene', 'g22_adobergb_scene', 'g22_ap1_scene', 'g22_rec709_scene', 'lin_adobergb_scene', 'lin_ap0_scene', 'lin_ap1_scene', 'lin_ciexyzd65_scene', 'lin_p3d65_scene', 'lin_rec2020_scene', 'lin_rec709_scene', 'prophoto', 'sRGB', 'sRGB Encoded AP1', 'sRGB Encoded P3-D65', 'sRGB Encoded Rec.709 (sRGB)', 'srgb_ap1_scene', 'srgb_p3d65_scene', 'srgb_rec709_scene']
3.12.31 OETFs
import colour
sorted(colour.OETFS)
['ARIB STD-B67', 'Blackmagic Film Generation 5', 'DaVinci Intermediate', 'ITU-R BT.2020', 'ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ', 'ITU-R BT.601', 'ITU-R BT.709', 'ITU-T H.273 IEC 61966-2', 'ITU-T H.273 Log', 'ITU-T H.273 Log Sqrt', 'SMPTE 240M']
3.12.32 EOTFs
import colour
sorted(colour.EOTFS)
['DCDM', 'DICOM GSDF', 'ITU-R BT.1886', 'ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ', 'ITU-T H.273 ST.428-1', 'SMPTE 240M', 'ST 2084', 'sRGB']
3.12.33 OOTFs
import colour
sorted(colour.OOTFS)
['ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ']
3.12.34 Log Encoding / Decoding
import colour
sorted(colour.LOG_ENCODINGS)
['ACEScc', 'ACEScct', 'ACESproxy', 'ARRI LogC3', 'ARRI LogC4', 'Apple Log Profile', 'Canon Log', 'Canon Log 2', 'Canon Log 3', 'Cineon', 'D-Log', 'ERIMM RGB', 'F-Log', 'F-Log2', 'Filmic Pro 6', 'L-Log', 'Log2', 'Log3G10', 'Log3G12', 'Mi-Log', 'N-Log', 'PLog', 'Panalog', 'Protune', 'REDLog', 'REDLogFilm', 'S-Log', 'S-Log2', 'S-Log3', 'T-Log', 'V-Log', 'ViperLog']
3.12.35 CCTFs Encoding / Decoding
import colour
sorted(colour.CCTF_ENCODINGS)
['ACEScc', 'ACEScct', 'ACESproxy', 'ARIB STD-B67', 'ARRI LogC3', 'ARRI LogC4', 'Apple Log Profile', 'Blackmagic Film Generation 5', 'Canon Log', 'Canon Log 2', 'Canon Log 3', 'Cineon', 'D-Log', 'DCDM', 'DICOM GSDF', 'DaVinci Intermediate', 'ERIMM RGB', 'F-Log', 'F-Log2', 'Filmic Pro 6', 'Gamma 2.2', 'Gamma 2.4', 'Gamma 2.6', 'ITU-R BT.1886', 'ITU-R BT.2020', 'ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ', 'ITU-R BT.601', 'ITU-R BT.709', 'ITU-T H.273 IEC 61966-2', 'ITU-T H.273 Log', 'ITU-T H.273 Log Sqrt', 'ITU-T H.273 ST.428-1', 'L-Log', 'Log2', 'Log3G10', 'Log3G12', 'Mi-Log', 'N-Log', 'PLog', 'Panalog', 'ProPhoto RGB', 'Protune', 'REDLog', 'REDLogFilm', 'RIMM RGB', 'ROMM RGB', 'S-Log', 'S-Log2', 'S-Log3', 'SMPTE 240M', 'ST 2084', 'T-Log', 'V-Log', 'ViperLog', 'sRGB']
3.12.36 Recommendation ITU-T H.273 Code points for Video Signal Type Identification
import colour
colour.COLOUR_PRIMARIES_ITUTH273.keys()
dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22, 23])
import colour
colour.models.describe_video_signal_colour_primaries(1)
=============================================================================== * * * Colour Primaries: 1 * * ------------------- * * * * Primaries : [[ 0.64 0.33] * * [ 0.3 0.6 ] * * [ 0.15 0.06]] * * Whitepoint : [ 0.3127 0.329 ] * * Whitepoint Name : D65 * * NPM : [[ 0.4123908 0.35758434 0.18048079] * * [ 0.21263901 0.71516868 0.07219232] * * [ 0.01933082 0.11919478 0.95053215]] * * NPM -1 : [[ 3.24096994 -1.53738318 -0.49861076] * * [-0.96924364 1.8759675 0.04155506] * * [ 0.05563008 -0.20397696 1.05697151]] * * FFmpeg Constants : ['AVCOL_PRI_BT709', 'BT709'] * * *
import colour
colour.TRANSFER_CHARACTERISTICS_ITUTH273.keys()
dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
import colour
colour.models.describe_video_signal_transfer_characteristics(1)
=============================================================================== * * * Transfer Characteristics: 1 * * --------------------------- * * * * Function : <function oetf_BT709 at 0x7f7b918776a0> * * FFmpeg Constants : ['AVCOL_TRC_BT709', 'BT709'] * * *
import colour
colour.MATRIX_COEFFICIENTS_ITUTH273.keys()
dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
import colour
colour.models.describe_video_signal_matrix_coefficients(1)
=============================================================================== * * * Matrix Coefficients: 1 * * ---------------------- * * * * Matrix Coefficients : [ 0.2126 0.0722] * * FFmpeg Constants : ['AVCOL_SPC_BT709', 'BT709'] * * *
3.13 Colour Notation Systems - colour.notation
3.13.1 Munsell Value
import colour
colour.munsell_value(12.23634268)
4.08244370765
import colour
sorted(colour.MUNSELL_VALUE_METHODS)
['ASTM D1535', 'Ladd 1955', 'McCamy 1987', 'Moon 1943', 'Munsell 1933', 'Priest 1920', 'Saunderson 1944', 'astm2008']
3.13.2 Munsell Colour
import colour
colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])
4.2YR 8.1/5.3
import colour
colour.munsell_colour_to_xyY("4.2YR 8.1/5.3")
[ 0.38736945 0.35751656 0.59362 ]
import colour
sorted(colour.XYY_TO_MUNSELL_COLOUR_METHODS)
['Centore 2014', 'ONNX']
3.14 Optical Phenomena - colour.phenomena
3.14.1 Rayleigh Scattering
import colour
colour.sd_rayleigh_scattering()
[[ 3.60000000e+02 5.60246579e-01] [ 3.61000000e+02 5.53748137e-01] [ 3.62000000e+02 5.47344692e-01] ... [ 7.80000000e+02 2.35336632e-02]]
3.14.2 CIE Standard General Sky
import colour import numpy as np
Relative luminance for CIE Standard General Sky Type 12 (Clear Sky)
colour.phenomena.sky_luminance_distribution_CIE2003( 12, np.radians(45), np.radians(180), np.radians(30), np.radians(0) )
0.4544524...
import colour import numpy as np
Traditional Overcast Sky (Type 16) at 45 degrees zenith angle
colour.phenomena.sky_luminance_distribution_overcast_CIE2003(np.radians(45))
0.8047378...
3.14.3 Prague Sky Model - Wilkie et al. (2021)
import colour import numpy as np from colour.phenomena.sky.wilkie2021 import ( SkyDataset_Wilkie2021, compute_sky_parameters_Wilkie2021, sky_radiance_Wilkie2021, )
dataset = SkyDataset_Wilkie2021() parameters = compute_sky_parameters_Wilkie2021( view_point=[0, 0, 0], view_direction=[0, 0, 1], sun_elevation=np.radians(30), sun_azimuth=0, visibility=50, albedo=0.5, ) sky_radiance_Wilkie2021(dataset, parameters, np.array([460, 540, 620]))
3.14.4 Thin Film Interference
import colour import numpy as np
Soap film (water, n=1.33) interference
R, T = colour.thin_film_tmm( n=[1.0, 1.33, 1.0], # [air, film, air] t=300, # 300 nm thickness wavelength=np.linspace(380, 780, 10), theta=0, # Normal incidence ) print(R[..., 0]) # s-polarisation reflectance
[[[0.01800269]] [[0.03176697]] [[0.0452849 ]] [[0.05812178]] [[0.06940598]] [[0.07834261]] [[0.08446072]] [[0.08770155]] [[0.08842705]] [[0.08732785]]]
3.15 Light Quality - colour.quality
3.15.1 Colour Fidelity Index
import colour
colour.colour_fidelity_index(colour.SDS_ILLUMINANTS["FL2"])
70.1208244014
import colour
sorted(colour.COLOUR_FIDELITY_INDEX_METHODS)
['ANSI/IES TM-30-18', 'CIE 2017']
3.15.2 Colour Quality Scale
import colour
colour.colour_quality_scale(colour.SDS_ILLUMINANTS["FL2"])
64.1118220157
import colour
sorted(colour.COLOUR_QUALITY_SCALE_METHODS)
['NIST CQS 7.4', 'NIST CQS 9.0']
3.15.3 Colour Rendering Index
import colour
colour.colour_rendering_index(colour.SDS_ILLUMINANTS["FL2"])
64.2337241217
import colour
sorted(colour.COLOUR_RENDERING_INDEX_METHODS)
['CIE 1995', 'CIE 2024']
3.15.4 Academy Spectral Similarity Index (SSI)
import colour
colour.spectral_similarity_index( colour.SDS_ILLUMINANTS["C"], colour.SDS_ILLUMINANTS["D65"] )
94.0
3.16 Spectral Up-Sampling & Recovery - colour.recovery
3.16.1 Reflectance Recovery
import colour
colour.XYZ_to_sd([0.20654008, 0.12197225, 0.05136952])
[[ 3.60000000e+02 8.42398617e-02] [ 3.65000000e+02 8.42355431e-02] [ 3.70000000e+02 8.42689564e-02] ... [ 7.80000000e+02 4.46952477e-01]]
import colour
sorted(colour.XYZ_TO_SD_METHODS)
['Gaussian', 'Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018', 'Smits 1999']
import colour
colour.XYZ_to_msds( [ [0.20654008, 0.12197225, 0.05136952], [0.14223761, 0.23042375, 0.10498415], [0.07820260, 0.06157595, 0.28106183], ] ).shape
(3, 421)
import colour
sorted(colour.XYZ_TO_MSDS_METHODS)
['Gaussian', 'Smits 1999']
3.16.2 Camera RGB Sensitivities Recovery
import colour
illuminant = colour.colorimetry.SDS_ILLUMINANTS["D65"] sensitivities = colour.characterisation.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"] reflectances = [ sd.copy().align(colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017) for sd in colour.SDS_COLOURCHECKERS["BabelColor Average"].values() ] reflectances = colour.colorimetry.sds_and_msds_to_msds(reflectances) RGB = colour.colorimetry.msds_to_XYZ( reflectances, method="Integration", cmfs=sensitivities, illuminant=illuminant, k=0.01, shape=colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017, ) colour.recovery.RGB_to_msds_camera_sensitivities_Jiang2013( RGB, illuminant, reflectances, colour.recovery.BASIS_FUNCTIONS_DYER2017, colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017, )
RGB_CameraSensitivities([[ 4.00000000e+02, 7.04378461e-03, 9.21260449e-03, -7.64080878e-03], [ 4.10000000e+02, -8.76715607e-03, 1.12726694e-02, 6.37434190e-03], [ 4.20000000e+02, 4.58126856e-02, 7.18000418e-02, 4.00001696e-01], ... [ 6.80000000e+02, 4.00195568e-02, 5.55512389e-03, 1.36794925e-03], [ 6.90000000e+02, -4.32240535e-03, 2.49731193e-03, 3.80303275e-04], [ 7.00000000e+02, -6.00395414e-03, 1.54678227e-03, 5.40394352e-04]], ['red', 'green', 'blue'], SpragueInterpolator, {}, Extrapolator, {'method': 'Constant', 'left': None, 'right': None})
3.17 Correlated Colour Temperature Computation Methods - colour.temperature
import colour
colour.uv_to_CCT([0.1978, 0.3122])
[ 6.50747479e+03 3.22334634e-03]
import colour
sorted(colour.UV_TO_CCT_METHODS)
['Krystek 1985', 'Ohno 2013', 'Planck 1900', 'Robertson 1968', 'ohno2013', 'robertson1968']
import colour
sorted(colour.XY_TO_CCT_METHODS)
['CIE Illuminant D Series', 'Hernandez 1999', 'Kang 2002', 'McCamy 1992', 'daylight', 'hernandez1999', 'kang2002', 'mccamy1992']
3.18 Colour Volume - colour.volume
import colour
colour.RGB_colourspace_volume_MonteCarlo(colour.RGB_COLOURSPACE_RGB["sRGB"])
821958.30000000005
3.19 Geometry Primitives Generation - colour.geometry
import colour
colour.primitive("Grid")
(array([ ([-0.5, 0.5, 0. ], [ 0., 1.], [ 0., 0., 1.], [ 0., 1., 0., 1.]), ([ 0.5, 0.5, 0. ], [ 1., 1.], [ 0., 0., 1.], [ 1., 1., 0., 1.]), ([-0.5, -0.5, 0. ], [ 0., 0.], [ 0., 0., 1.], [ 0., 0., 0., 1.]), ([ 0.5, -0.5, 0. ], [ 1., 0.], [ 0., 0., 1.], [ 1., 0., 0., 1.])], dtype=[('position', '<f8', (3,)), ('uv', '<f8', (2,)), ('normal', '<f8', (3,)), ('colour', '<f8', (4,))]), array([[0, 2, 1], [2, 3, 1]]), array([[0, 2], [2, 3], [3, 1], [1, 0]]))
import colour
sorted(colour.PRIMITIVE_METHODS)
['Cube', 'Grid']
import colour
colour.primitive_vertices("Quad MPL")
[[ 0. 0. 0.] [ 1. 0. 0.] [ 1. 1. 0.] [ 0. 1. 0.]]
3.20 Plotting - colour.plotting
Most of the objects are available from the colour.plotting namespace:
from colour.plotting import *
colour_style()
3.20.1 Visible Spectrum
from colour.plotting import *
plot_visible_spectrum("CIE 1931 2 Degree Standard Observer")
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'The Visible Spectrum - CIE 1931 2$^\circ$ Standard Observer'}, xlabel='Wavelength lambda\lambdalambda (nm)'>)
3.20.2 Spectral Distribution
from colour.plotting import *
plot_single_illuminant_sd("FL1")
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'Illuminant FL1 - CIE 1931 2$^\circ$ Standard Observer'}, xlabel='Wavelength lambda\lambdalambda (nm)', ylabel='Relative Power'>)
3.20.3 Blackbody
import colour from colour.plotting import *
blackbody_sds = [ colour.sd_blackbody(i, colour.SpectralShape(1, 10001, 10)) for i in range(1000, 15000, 1000) ] plot_multi_sds( blackbody_sds, y_label="W / (sr m$^2$) / m", plot_kwargs={"use_sd_colours": True, "normalise_sd_colours": True}, legend_location="upper right", bounding_box=(0, 1250, 0, 2.5e6), )
(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='Wavelength lambdalambdalambda (nm)', ylabel='W / (sr m$^2$) / m'>)
3.20.4 Colour Matching Functions
from colour.plotting import *
plot_single_cmfs( "Stockman & Sharpe 2 Degree Cone Fundamentals", y_label="Sensitivity", bounding_box=(390, 870, 0, 1.1), )
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'Stockman & Sharpe 2$^circ$ Cone Fundamentals - Colour Matching Functions'}, xlabel='Wavelength lambdalambdalambda (nm)', ylabel='Sensitivity'>)
3.20.5 Luminous Efficiency
import colour from colour.plotting import *
sd_mesopic_luminous_efficiency_function = ( colour.sd_mesopic_luminous_efficiency_function(0.2) ) plot_multi_sds( ( sd_mesopic_luminous_efficiency_function, colour.colorimetry.SDS_LEFS_PHOTOPIC["CIE 1924 Photopic Standard Observer"], colour.colorimetry.SDS_LEFS_SCOTOPIC["CIE 1951 Scotopic Standard Observer"], ), y_label="Luminous Efficiency", legend_location="upper right", y_tighten=True, margins=(0, 0, 0, 0.1), )
(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='Wavelength lambdalambdalambda (nm)', ylabel='Luminous Efficiency'>)
3.20.6 Colour Checker
import colour from colour.plotting import *
plot_multi_sds( list(colour.SDS_COLOURCHECKERS["BabelColor Average"].values()), plot_kwargs={ "use_sd_colours": True, }, title=("BabelColor Average - " "Spectral Distributions"), )
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'BabelColor Average - Spectral Distributions'}, xlabel='Wavelength lambdalambdalambda (nm)', ylabel='Spectral Distribution'>)
from colour.plotting import *
plot_single_colour_checker("ColorChecker 2005", text_kwargs={"visible": False})
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'ColorChecker 2005'}>)
3.20.7 Chromaticities Prediction
from colour.plotting import *
plot_corresponding_chromaticities_prediction( 2, "Von Kries", {"transform": "Bianco 2010"} )
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Corresponding Chromaticities Prediction - Von Kries - Experiment 2 - CIE 1976 UCS Chromaticity Diagram'}, xlabel="CIE u'", ylabel="CIE v'">)
3.20.8 Chromaticities
import numpy as np from colour.plotting import *
RGB = np.random.random((32, 32, 3)) plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931( RGB, "ITU-R BT.709", colourspaces=["ACEScg", "S-Gamut", "Pointer Gamut"], )
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'ACEScg, S-Gamut, ITU-R BT.709\nCIE 1931 2 Degree Standard Observer - CIE 1931 Chromaticity Diagram'}, xlabel='CIE x', ylabel='CIE y'>
3.20.9 Colour Rendering Index Bars
import colour from colour.plotting import *
plot_single_sd_colour_rendering_index_bars(colour.SDS_ILLUMINANTS["FL2"])
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Colour Rendering Index - FL2'}>)
3.20.10 ANSI/IES TM-30-18 Colour Rendition Report
import colour from colour.plotting import *
plot_single_sd_colour_rendition_report(colour.SDS_ILLUMINANTS["FL2"])
(<Figure size 827x1169 with 13 Axes>, <Axes: >)
3.20.11 Gamut Section
from colour.plotting import *
plot_visible_spectrum_section(section_colours="RGB", section_opacity=0.15)
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Visible Spectrum Section - 50.0% - CIE xyY - CIE 1931 2$^\circ$ Standard Observer'}, xlabel='x', ylabel='y'>)
from colour.plotting import *
plot_RGB_colourspace_section("sRGB", section_colours="RGB", section_opacity=0.15)
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'sRGB Section - 50.0% - CIE xyY'}, xlabel='x', ylabel='y'>)
3.20.12 Colour Temperature
from colour.plotting import *
plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(["A", "B", "C"])
(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'A, B, C Illuminants - Planckian Locus\nCIE 1960 UCS Chromaticity Diagram - CIE 1931 2 Degree Standard Observer'}, xlabel='CIE u', ylabel='CIE v'>)
3.20.13 Thin Film Interference
from colour.plotting import *
plot_thin_film_iridescence([1.0, 1.33, 1.0])
(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'Thin Film Iridescence (n=1.33, θ=0°)'}, xlabel='Thickness (nm)', ylabel=''>)
4 User Guide
4.1 Installation
Colour and its primary dependencies can be easily installed from thePython Package Indexby issuing this command in a shell:
$ pip install --user colour-science
The detailed installation procedure for the secondary dependencies is described in the Installation Guide.
Colour is also available for Anacondafrom Continuum Analytics via conda-forge:
$ conda install -c conda-forge colour-science
4.2 Tutorial
The static tutorialprovides an introduction to Colour. An interactive version is available viaGoogle Colab.
4.3 How-To
The Google Colab How-Toguide for Colour shows various techniques to solve specific problems and highlights some interesting use cases.
4.4 Contributing
If you would like to contribute to Colour, please refer to the followingContributing guide.
4.5 Changes
The changes are viewable on the Releases page.
4.6 Bibliography
The bibliography is available on the Bibliography page.
It is also viewable directly from the repository inBibTeXformat.
5 API Reference
The main technical reference for Colour is the API Reference:
6 See Also
6.1 Software
Python
- ColorAide by Muse, I.
- ColorPy by Kness, M.
- Colorspacious by Smith, N. J., et al.
- python-colormath by Taylor, G., et al.
Go
- go-colorful by Beyer, L., et al.
.NET
- Colourful by Pažourek, T., et al.
Julia
- Colors.jl by Holy, T., et al.
Matlab & Octave
- COLORLAB by Malo, J., et al.
- Psychtoolbox by Brainard, D., et al.
- The Munsell and Kubelka-Munk Toolbox by Centore, P.
7 Code of Conduct
The Code of Conduct, adapted from the Contributor Covenant 1.4, is available on the Code of Conduct page.
8 Contact & Social
The Colour Developers can be reached via different means:
9 Thank You!
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10 About
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