colour-science

Colour Science for Python

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Project links

Project description

https://raw.githubusercontent.com/colour-science/colour-branding/master/images/Colour_Logo_001.png

Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.

It is freely available under the BSD-3-Clause terms.

Colour is an affiliated project of NumFOCUS, a 501(c)(3) nonprofit in the United States.

1 Draft Release Notes

The draft release notes of the develop branch are available at this url.

2 Sponsors

We are grateful 💖 for the support of our sponsors. If you’d like to join them, please consider becoming a sponsor on OpenCollective.

3 Features

Most of the objects are available from the colour namespace:

import colour

3.1 Automatic Colour Conversion Graph - colour.graph

https://colour.readthedocs.io/en/develop/_static/Examples_Colour_Automatic_Conversion_Graph.png

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 Lab* Colourspace

import colour

colour.XYZ_to_Lab([0.20654008, 0.12197225, 0.05136952])

[ 41.52787529  52.63858304  26.92317922]

3.12.3 CIE Luv* 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 UVW* 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   ]

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 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)

['Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018', '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 $\\lambda$ (nm)'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Visible_Spectrum.png

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 $\\lambda$ (nm)', ylabel='Relative Power'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Illuminant_F1_SD.png

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 $lambda$ (nm)', ylabel='W / (sr m$^2$) / m'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Blackbodies.png

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 $lambda$ (nm)', ylabel='Sensitivity'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Cone_Fundamentals.png

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 $lambda$ (nm)', ylabel='Luminous Efficiency'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Luminous_Efficiency.png

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 $lambda$ (nm)', ylabel='Spectral Distribution'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_BabelColor_Average.png

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'}>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_ColorChecker_2005.png

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'">)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Chromaticities_Prediction.png

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'>

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Chromaticities_CIE_1931_Chromaticity_Diagram.png

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'}>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_CRI.png

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: >)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Colour_Rendition_Report.png

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'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Plot_Visible_Spectrum_Section.png

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'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Plot_RGB_Colourspace_Section.png

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'>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_CCT_CIE_1960_UCS_Chromaticity_Diagram.png

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=''>)

https://colour.readthedocs.io/en/develop/_static/Examples_Plotting_Thin_Film_Iridescence.png

4 User Guide

4.1 Installation

Colour and its primary dependencies can be easily installed from the Python Package Index by 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 Anaconda from Continuum Analytics via conda-forge:

$ conda install -c conda-forge colour-science

4.2 Tutorial

The static tutorial provides an introduction to Colour. An interactive version is available via Google Colab.

4.3 How-To

The Google Colab How-To guide 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 following Contributing 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 in BibTeX format.

5 API Reference

The main technical reference for Colour is the API Reference:

6 See Also

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-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.

9 About

Colour by Colour Developers
Copyright 2013 Colour Developers – colour-developers@colour-science.org
This software is released under terms of BSD-3-Clause: https://opensource.org/licenses/BSD-3-Clause
https://github.com/colour-science/colour

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Release history Release notifications | RSS feed

This version

0.4.7

Dec 6, 2025

0.4.6

Oct 11, 2024

0.4.5

Oct 10, 2024

0.4.4

Dec 17, 2023

0.4.3

Aug 26, 2023

0.4.2

Nov 29, 2022

0.4.1

Feb 25, 2022

0.4.0

Feb 20, 2022

0.3.16

Nov 27, 2020

0.3.15

Jan 25, 2020

0.3.14

Oct 26, 2019

0.3.13

Apr 20, 2019

0.3.12

Mar 23, 2019

0.3.11

Feb 18, 2018

0.3.10

Jul 12, 2017

0.3.9

Mar 12, 2017

0.3.8

Jul 9, 2016

0.3.7

Dec 13, 2015

0.3.6

Aug 9, 2015

0.3.5

May 6, 2015

0.3.4

Jan 27, 2015

0.3.3

Oct 28, 2014

0.3.2

Sep 3, 2014

0.3.1

Sep 2, 2014

0.3.0

Sep 2, 2014

0.2.1

Aug 9, 2014

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Project description

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

3.3.1 Kernel Interpolation

3.3.2 Sprague (1880) Interpolation

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

3.8.1 Spectral Computations

3.8.2 Multi-Spectral Computations

3.8.3 Blackbody Spectral Radiance Computation

3.8.4 Dominant, Complementary Wavelength & Colour Purity Computation

3.8.5 Lightness Computation

3.8.6 Luminance Computation

3.8.7 Whiteness Computation

3.8.8 Yellowness Computation

3.8.9 Luminous Flux, Efficiency & Efficacy Computation

3.9 Contrast Sensitivity Function - colour.contrast

3.10 Colour Difference - colour.difference

3.11 IO - colour.io

3.11.1 Images

3.11.2 Spectral Images - Fichet et al. (2021)

3.11.3 Look Up Table (LUT) Data

3.12 Colour Models - colour.models

3.12.1 CIE xyY Colourspace

3.12.2 CIE L*a*b* Colourspace

3.12.3 CIE L*u*v* Colourspace

3.12.4 CIE 1960 UCS Colourspace

3.12.5 CIE 1964 U*V*W* Colourspace

3.12.6 CAM02-LCD, CAM02-SCD, and CAM02-UCS Colourspaces - Luo, Cui and Li (2006)

3.12.7 CAM16-LCD, CAM16-SCD, and CAM16-UCS Colourspaces - Li et al. (2017)

3.12.8 DIN99 Colourspace and DIN99b, DIN99c, DIN99d Refined Formulas

3.12.9 ICaCb Colourspace

3.12.10 IgPgTg Colourspace

3.12.11 IPT Colourspace

3.12.12 Jzazbz Colourspace

3.12.13 Hunter L,a,b Colour Scale

3.12.14 Hunter Rd,a,b Colour Scale

3.12.15 Oklab Colourspace

3.12.16 OSA UCS Colourspace

3.12.17 ProLab Colourspace

3.12.18 Ragoo and Farup (2021) Optimised IPT Colourspace

3.12.19 Yrg Colourspace - Kirk (2019)

3.12.20 hdr-CIELAB Colourspace

3.12.21 hdr-IPT Colourspace

3.12.22 Y’CbCr Colour Encoding

3.12.23 YCoCg Colour Encoding

3.12.24 ICtCp Colour Encoding

3.12.25 HSV Colourspace

3.12.26 IHLS Colourspace

3.12.27 Prismatic Colourspace

3.12.28 RGB Colourspace and Transformations

3.12.29 RGB Colourspace Derivation

3.12.30 RGB Colourspaces

3.12.31 OETFs

3.12.32 EOTFs

3.12.33 OOTFs

3.12.34 Log Encoding / Decoding

3.12.35 CCTFs Encoding / Decoding

3.12.36 Recommendation ITU-T H.273 Code points for Video Signal Type Identification

3.13 Colour Notation Systems - colour.notation

3.13.1 Munsell Value

3.13.2 Munsell Colour

3.14 Optical Phenomena - colour.phenomena

3.14.1 Rayleigh Scattering

3.14.2 Thin Film Interference

3.12.2 CIE Lab* Colourspace

3.12.3 CIE Luv* Colourspace

3.12.5 CIE 1964 UVW* Colourspace