colour-science/colour - Githubissues

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.. |NumFOCUS| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat-square&colorA=E1523D&colorB=007D8A :target: http://numfocus.org :alt: Powered by NumFOCUS .. |actions| image:: https://img.shields.io/github/actions/workflow/status/colour-science/colour/.github/workflows/continuous-integration-quality-unit-tests.yml?branch=develop&style=flat-square :target: https://github.com/colour-science/colour/actions :alt: Develop Build Status .. |coveralls| image:: http://img.shields.io/coveralls/colour-science/colour/develop.svg?style=flat-square :target: https://coveralls.io/r/colour-science/colour :alt: Coverage Status .. |codacy| image:: https://img.shields.io/codacy/grade/1f3b8d3bba7440ba9ebc1170589628b1/develop.svg?style=flat-square :target: https://app.codacy.com/gh/colour-science/colour :alt: Code Grade .. |version| image:: https://img.shields.io/pypi/v/colour-science.svg?style=flat-square :target: https://pypi.org/project/colour-science :alt: Package Version .. |zenodo| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.10396329-blue.svg?style=flat-square :target: https://dx.doi.org/10.5281/zenodo.10396329 :alt: DOI

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Colour <https://github.com/colour-science/colour> is an open-source Python <https://www.python.org> package providing a comprehensive number of algorithms and datasets for colour science.

It is freely available under the BSD-3-Clause <https://opensource.org/licenses/BSD-3-Clause>__ terms.

Colour is an affiliated project of NumFOCUS <https://numfocus.org>__, a 501(c)(3) nonprofit in the United States.

.. contents:: Table of Contents :backlinks: none :depth: 2

.. sectnum::

Draft Release Notes

The draft release notes of the develop <https://github.com/colour-science/colour/tree/develop> branch are available at this url <https://gist.github.com/KelSolaar/4a6ebe9ec3d389f0934b154fec8df51d>.

Features

Most of the objects are available from the colour namespace:

.. code-block:: python

import colour

Automatic Colour Conversion Graph - colour.graph


Starting with version *0.3.14*, **Colour** implements an automatic colour
conversion graph enabling easier colour conversions.

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

.. code-block:: python

    sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"]
    colour.convert(sd, "Spectral Distribution", "sRGB", verbose={"mode": "Short"})

.. code-block:: text

    ===============================================================================
    *                                                                             *
    *   [ Conversion Path ]                                                       *
    *                                                                             *
    *   "sd_to_XYZ" --> "XYZ_to_sRGB"                                             *
    *                                                                             *
    ===============================================================================
    array([ 0.45675795,  0.30986982,  0.24861924])

.. code-block:: python

    illuminant = colour.SDS_ILLUMINANTS["FL2"]
    colour.convert(
        sd,
        "Spectral Distribution",
        "sRGB",
        sd_to_XYZ={"illuminant": illuminant},
    )

.. code-block:: text

    array([ 0.47924575,  0.31676968,  0.17362725])

Chromatic Adaptation - ``colour.adaptation``

.. code-block:: python

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))

.. code-block:: text

array([ 0.2533053 ,  0.13765138,  0.01543307])

.. code-block:: python

sorted(colour.CHROMATIC_ADAPTATION_METHODS)

.. code-block:: text

['CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Von Kries', 'Zhai 2018', 'vK20']

Algebra - colour.algebra


Kernel Interpolation
********************

.. code-block:: python

    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])

.. code-block:: text

    array([  6.18062083,   8.08238488,  57.85783403])

Sprague (1880) Interpolation
****************************

.. code-block:: python

    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])

.. code-block:: text

    array([  6.72951612,   7.81406251,  43.77379185])

Colour Appearance Models - ``colour.appearance``

.. code-block:: python

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)

.. code-block:: text

CAM_Specification_CIECAM02(J=34.434525727858997, C=67.365010921125943, h=22.279164147957065, s=62.81485585332716, Q=177.47124941102123, M=70.024939419291414, H=2.6896085344238898, HC=None)

.. code-block:: python

colour.XYZ_to_CIECAM16(XYZ, XYZ_w, L_A, Y_b)

.. code-block:: text

CAM_Specification_CIECAM16(J=34.434525727858997, C=67.365010921125943, h=22.279164147957065, s=62.81485585332716, Q=177.47124941102123, M=70.024939419291414, H=2.6896085344238898, HC=None)

.. code-block:: python

colour.XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b)

.. code-block:: text

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)

.. code-block:: python

colour.XYZ_to_Hellwig2022(XYZ, XYZ_w, L_A)

.. code-block:: text

CAM_Specification_Hellwig2022(J=33.880368498111686, C=40.347043294550311, h=19.510887327451748, s=117.38555017188679, Q=45.34489577734751, M=53.228355383108031, H=399.52975599115319, HC=None)

.. code-block:: python

colour.XYZ_to_Kim2009(XYZ, XYZ_w, L_A)

.. code-block:: text

CAM_Specification_Kim2009(J=19.879918542450902, C=55.839055250876946, h=22.013388165090046, s=112.97979354939129, Q=36.309026130161449, M=46.346415858227864, H=2.3543198369639931, HC=None)

.. code-block:: python

colour.XYZ_to_ZCAM(XYZ, XYZ_w, L_A, Y_b)

.. code-block:: text

CAM_Specification_ZCAM(J=38.347186278956357, C=21.12138989208518, h=33.711578931095197, s=81.444585609489536, Q=76.986725284523772, M=42.403805833900506, H=0.45779200212219573, HC=None, V=43.623590687423544, K=43.20894953152817, W=34.829588380192149)

Colour Blindness - colour.blindness


.. code-block:: python

    import numpy as np

    cmfs = colour.LMS_CMFS["Stockman & Sharpe 2 Degree Cone Fundamentals"]
    colour.msds_cmfs_anomalous_trichromacy_Machado2009(cmfs, np.array([15, 0, 0]))[450]

.. code-block:: text

    array([ 0.08912884,  0.0870524 ,  0.955393  ])

.. code-block:: python

    primaries = colour.MSDS_DISPLAY_PRIMARIES["Apple Studio Display"]
    d_LMS = (15, 0, 0)
    colour.matrix_anomalous_trichromacy_Machado2009(cmfs, primaries, d_LMS)

.. code-block:: text

    array([[-0.27774652,  2.65150084, -1.37375432],
           [ 0.27189369,  0.20047862,  0.52762768],
           [ 0.00644047,  0.25921579,  0.73434374]])

Colour Correction - ``colour characterisation``

.. code-block:: python

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)

.. code-block:: text

array([ 0.1806237 ,  0.07234791,  0.07848845])

.. code-block:: python

sorted(colour.COLOUR_CORRECTION_METHODS)

.. code-block:: text

['Cheung 2004', 'Finlayson 2015', 'Vandermonde']

ACES Input Transform - colour characterisation


.. code-block:: python

    sensitivities = colour.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"]
    illuminant = colour.SDS_ILLUMINANTS["D55"]
    colour.matrix_idt(sensitivities, illuminant)

.. code-block:: text

    (array([[ 0.59368175,  0.30418371,  0.10213454],
           [ 0.00457979,  1.14946003, -0.15403982],
           [ 0.03552213, -0.16312291,  1.12760077]]), array([ 1.58214188,  1.        ,  1.28910346]))

Colorimetry - ``colour.colorimetry``

Spectral Computations

.. code-block:: python

colour.sd_to_XYZ(colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"])

.. code-block:: text

array([ 36.94726204,  32.62076174,  13.0143849 ])

.. code-block:: python

sorted(colour.SPECTRAL_TO_XYZ_METHODS)

.. code-block:: text

['ASTM E308', 'Integration', 'astm2015']

Multi-Spectral Computations

.. code-block:: python

msds = np.array(
    [
        [
            [
                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),
)

.. code-block:: text

array([[[  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]]])

.. code-block:: python

sorted(colour.MSDS_TO_XYZ_METHODS)

.. code-block:: text

['ASTM E308', 'Integration', 'astm2015']

Blackbody Spectral Radiance Computation

.. code-block:: python

colour.sd_blackbody(5000)

.. code-block:: text

SpectralDistribution([[  3.60000000e+02,   6.65427827e+12],
                      [  3.61000000e+02,   6.70960528e+12],
                      [  3.62000000e+02,   6.76482512e+12],
                      ...
                      [  7.78000000e+02,   1.06068004e+13],
                      [  7.79000000e+02,   1.05903327e+13],
                      [  7.80000000e+02,   1.05738520e+13]],
                     interpolator=SpragueInterpolator,
                     interpolator_args={},
                     extrapolator=Extrapolator,
                     extrapolator_args={'right': None, 'method': 'Constant', 'left': None})

Dominant, Complementary Wavelength & Colour Purity Computation

.. code-block:: python

xy = [0.54369557, 0.32107944]
xy_n = [0.31270000, 0.32900000]
colour.dominant_wavelength(xy, xy_n)

.. code-block:: text

(array(616.0),
 array([ 0.68354746,  0.31628409]),
 array([ 0.68354746,  0.31628409]))

Lightness Computation

.. code-block:: python

colour.lightness(12.19722535)

.. code-block:: text

41.527875844653451

.. code-block:: python

sorted(colour.LIGHTNESS_METHODS)

.. code-block:: text

['Abebe 2017',
 'CIE 1976',
 'Fairchild 2010',
 'Fairchild 2011',
 'Glasser 1958',
 'Lstar1976',
 'Wyszecki 1963']

Luminance Computation

.. code-block:: python

colour.luminance(41.52787585)

.. code-block:: text

12.197225353400775

.. code-block:: python

sorted(colour.LUMINANCE_METHODS)

.. code-block:: text

['ASTM D1535',
 'CIE 1976',
 'Fairchild 2010',
 'Fairchild 2011',
 'Newhall 1943',
 'astm2008',
 'cie1976']

Whiteness Computation

.. code-block:: python

XYZ = [95.00000000, 100.00000000, 105.00000000]
XYZ_0 = [94.80966767, 100.00000000, 107.30513595]
colour.whiteness(XYZ, XYZ_0)

.. code-block:: text

array([ 93.756     ,  -1.33000001])

.. code-block:: python

sorted(colour.WHITENESS_METHODS)

.. code-block:: text

['ASTM E313',
 'Berger 1959',
 'CIE 2004',
 'Ganz 1979',
 'Stensby 1968',
 'Taube 1960',
 'cie2004']

Yellowness Computation

.. code-block:: python

XYZ = [95.00000000, 100.00000000, 105.00000000]
colour.yellowness(XYZ)

.. code-block:: text

4.3400000000000034

.. code-block:: python

sorted(colour.YELLOWNESS_METHODS)

.. code-block:: text

['ASTM D1925', 'ASTM E313', 'ASTM E313 Alternative']

Luminous Flux, Efficiency & Efficacy Computation

.. code-block:: python

sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_flux(sd)

.. code-block:: text

23807.655527367202

.. code-block:: python

sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficiency(sd)

.. code-block:: text

0.19943935624521045

.. code-block:: python

sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficacy(sd)

.. code-block:: text

136.21708031547874

Contrast Sensitivity Function - colour.contrast


.. code-block:: python

    colour.contrast_sensitivity_function(u=4, X_0=60, E=65)

.. code-block:: text

    358.51180789884984

.. code-block:: python

    sorted(colour.CONTRAST_SENSITIVITY_METHODS)

.. code-block:: text

    ['Barten 1999']

Colour Difference - ``colour.difference``

.. code-block:: python

Lab_1 = [100.00000000, 21.57210357, 272.22819350]
Lab_2 = [100.00000000, 426.67945353, 72.39590835]
colour.delta_E(Lab_1, Lab_2)

.. code-block:: text

94.035649026659485

.. code-block:: python

sorted(colour.DELTA_E_METHODS)

.. code-block:: text

['CAM02-LCD',
 'CAM02-SCD',
 'CAM02-UCS',
 'CAM16-LCD',
 'CAM16-SCD',
 'CAM16-UCS',
 'CIE 1976',
 'CIE 1994',
 'CIE 2000',
 'CMC',
 'DIN99',
 'ITP',
 'cie1976',
 'cie1994',
 'cie2000']

IO - colour.io


Images
******

.. code-block:: python

    RGB = colour.read_image("Ishihara_Colour_Blindness_Test_Plate_3.png")
    RGB.shape

.. code-block:: text

    (276, 281, 3)

Spectral Images - Fichet et al. (2021)
**************************************

.. code-block:: python

    components = colour.read_spectral_image_Fichet2021("Polarised.exr")
    list(components.keys())

.. code-block:: text

    ['S0', 'S1', 'S2', 'S3']

Look Up Table (LUT) Data
************************

.. code-block:: python

    LUT = colour.read_LUT("ACES_Proxy_10_to_ACES.cube")
    print(LUT)

.. code-block:: text

    LUT3x1D - ACES Proxy 10 to ACES
    -------------------------------
    Dimensions : 2
    Domain     : [[0 0 0]
                  [1 1 1]]
    Size       : (32, 3)

.. code-block:: python

    RGB = [0.17224810, 0.09170660, 0.06416938]
    LUT.apply(RGB)

.. code-block:: text

    array([ 0.00575674,  0.00181493,  0.00121419])

Colour Models - ``colour.models``

CIE xyY Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.54369557,  0.32107944,  0.12197225])

CIE Lab* Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 41.52787529,  52.63858304,  26.92317922])

CIE Luv* Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 41.52787529,  96.83626054,  17.75210149])

CIE 1960 UCS Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.13769339,  0.12197225,  0.1053731 ])

CIE 1964 UVW* Colourspace

.. code-block:: python

XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_UVW(XYZ)

.. code-block:: text

array([ 94.55035725,  11.55536523,  40.54757405])

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

.. code-block:: python

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)

.. code-block:: text

array([ 47.16899898,  38.72623785,  15.8663383 ])

.. code-block:: python

XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
colour.XYZ_to_CAM02UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)

.. code-block:: text

array([ 47.16899898,  38.72623785,  15.8663383 ])

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

.. code-block:: python

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)

.. code-block:: text

array([ 46.55542238,  40.22460974,  14.25288392])

.. code-block:: python

XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
colour.XYZ_to_CAM16UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)

.. code-block:: text

array([ 46.55542238,  40.22460974,  14.25288392])

DIN99 Colourspace and DIN99b, DIN99c, DIN99d Refined Formulas

.. code-block:: python

Lab = [41.52787529, 52.63858304, 26.92317922]
colour.Lab_to_DIN99(Lab)

.. code-block:: text

array([ 53.22821988,  28.41634656,   3.89839552])

ICaCb Colourspace

.. code-block:: python

XYZ_to_ICaCb(np.array([0.20654008, 0.12197225, 0.05136952]))

.. code-block:: text

array([ 0.06875297,  0.05753352,  0.02081548])

IgPgTg Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.42421258,  0.18632491,  0.10689223])

IPT Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.38426191,  0.38487306,  0.18886838])

Jzazbz Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.00535048,  0.00924302,  0.00526007])

hdr-CIELAB Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 51.87002062,  60.4763385 ,  32.14551912])

hdr-IPT Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 25.18261761, -22.62111297,   3.18511729])

Hunter L,a,b Colour Scale

.. code-block:: python

XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Lab(XYZ)

.. code-block:: text

array([ 34.92452577,  47.06189858,  14.38615107])

Hunter Rd,a,b Colour Scale

.. code-block:: python

XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Rdab(XYZ)

.. code-block:: text

array([ 12.197225  ,  57.12537874,  17.46241341])

Oklab Colourspace

.. code-block:: python

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

.. code-block:: text

array([ 0.51634019,  0.154695  ,  0.06289579])

OSA UCS Colourspace

.. code-block:: python

XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_OSA_UCS(XYZ)

.. code-block:: text

array([-3.0049979 ,  2.99713697, -9.66784231])

ProLab Colourspace

.. code-block:: python

colour.XYZ_to_ProLab([0.51634019, 0.15469500, 0.06289579])

.. code-block:: text

array([1.24610688, 2.39525236, 0.41902126])

Ragoo and Farup (2021) Optimised IPT Colourspace

.. code-block:: python

colour.XYZ_to_IPT_Ragoo2021([0.20654008, 0.12197225, 0.05136952])

.. code-block:: text

array([ 0.42248243,  0.2910514 ,  0.20410663])

Yrg Colourspace - Kirk (2019)

.. code-block:: python

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

.. code-block:: text

array([ 0.13137801,  0.49037645,  0.37777388])

Y'CbCr Colour Encoding

.. code-block:: python

colour.RGB_to_YCbCr([1.0, 1.0, 1.0])

.. code-block:: text

array([ 0.92156863,  0.50196078,  0.50196078])

YCoCg Colour Encoding

.. code-block:: python

colour.RGB_to_YCoCg([0.75, 0.75, 0.0])

.. code-block:: text

array([ 0.5625,  0.375 ,  0.1875])

ICtCp Colour Encoding

.. code-block:: python

colour.RGB_to_ICtCp([0.45620519, 0.03081071, 0.04091952])

.. code-block:: text

array([ 0.07351364,  0.00475253,  0.09351596])

HSV Colourspace

.. code-block:: python

colour.RGB_to_HSV([0.45620519, 0.03081071, 0.04091952])

.. code-block:: text

array([ 0.99603944,  0.93246304,  0.45620519])

IHLS Colourspace

.. code-block:: python

colour.RGB_to_IHLS([0.45620519, 0.03081071, 0.04091952])

.. code-block:: text

array([ 6.26236117,  0.12197943,  0.42539448])

Prismatic Colourspace

.. code-block:: python

colour.RGB_to_Prismatic([0.25, 0.50, 0.75])

.. code-block:: text

array([ 0.75      ,  0.16666667,  0.33333333,  0.5       ])

RGB Colourspace and Transformations

.. code-block:: python

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,
)

.. code-block:: text

array([ 0.45595571,  0.03039702,  0.04087245])

RGB Colourspace Derivation

.. code-block:: python

p = [0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700]
w = [0.32168, 0.33767]
colour.normalised_primary_matrix(p, w)

.. code-block:: text

array([[  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]])

RGB Colourspaces

.. code-block:: python

sorted(colour.RGB_COLOURSPACES)

.. code-block:: text

['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',
 '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',
 'FilmLight E-Gamut',
 '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',
 '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',
 'prophoto',
 'sRGB']

OETFs

.. code-block:: python

sorted(colour.OETFS)

.. code-block:: text

['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']

EOTFs

.. code-block:: python

sorted(colour.EOTFS)

.. code-block:: text

['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']

OOTFs

.. code-block:: python

sorted(colour.OOTFS)

.. code-block:: text

['ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ']

Log Encoding / Decoding

.. code-block:: python

sorted(colour.LOG_ENCODINGS)

.. code-block:: text

['ACEScc',
 'ACEScct',
 'ACESproxy',
 'Apple Log Profile',
 'ARRI LogC3',
 'ARRI LogC4',
 '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',
 'N-Log',
 'PLog',
 'Panalog',
 'Protune',
 'REDLog',
 'REDLogFilm',
 'S-Log',
 'S-Log2',
 'S-Log3',
 'T-Log',
 'V-Log',
 'ViperLog']

CCTFs Encoding / Decoding

.. code-block:: python

sorted(colour.CCTF_ENCODINGS)

.. code-block:: text

['ACEScc',
 'ACEScct',
 'ACESproxy',
 'Apple Log Profile',
 'ARRI LogC3',
 'ARRI LogC4',
 'ARIB STD-B67',
 'Canon Log',
 'Canon Log 2',
 'Canon Log 3',
 'Cineon',
 'D-Log',
 'DCDM',
 'DICOM GSDF',
 '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',
 'Log2',
 'Log3G10',
 'Log3G12',
 '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']

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

.. code-block:: python

colour.COLOUR_PRIMARIES_ITUTH273.keys()

.. code-block:: text

dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22, 23])

.. code-block:: python

colour.models.describe_video_signal_colour_primaries(1)

.. code-block:: text

===============================================================================
*                                                                             *
*   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']                           *
*                                                                             *
===============================================================================

.. code-block:: python

colour.TRANSFER_CHARACTERISTICS_ITUTH273.keys()

.. code-block:: text

dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])

.. code-block:: python

colour.models.describe_video_signal_transfer_characteristics(1)

.. code-block:: text

===============================================================================
*                                                                             *
*   Transfer Characteristics: 1                                               *
*   ---------------------------                                               *
*                                                                             *
*   Function         : <function oetf_BT709 at 0x165bb3550>                   *
*   FFmpeg Constants : ['AVCOL_TRC_BT709', 'BT709']                           *
*                                                                             *
===============================================================================

.. code-block:: python

colour.MATRIX_COEFFICIENTS_ITUTH273.keys()

.. code-block:: text

dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])

.. code-block:: python

colour.models.describe_video_signal_matrix_coefficients(1)

.. code-block:: text

===============================================================================
*                                                                             *
*   Matrix Coefficients: 1                                                    *
*   ----------------------                                                    *
*                                                                             *
*   Matrix Coefficients : [ 0.2126  0.0722]                                   *
*   FFmpeg Constants    : ['AVCOL_SPC_BT709', 'BT709']                        *
*                                                                             *
===============================================================================

Colour Notation Systems - colour.notation


Munsell Value
*************

.. code-block:: python

    colour.munsell_value(12.23634268)

.. code-block:: text

    4.0824437076525664

.. code-block:: python

    sorted(colour.MUNSELL_VALUE_METHODS)

.. code-block:: text

    ['ASTM D1535',
     'Ladd 1955',
     'McCamy 1987',
     'Moon 1943',
     'Munsell 1933',
     'Priest 1920',
     'Saunderson 1944',
     'astm2008']

Munsell Colour
**************

.. code-block:: python

    colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])

.. code-block:: text

    '4.2YR 8.1/5.3'

.. code-block:: python

    colour.munsell_colour_to_xyY("4.2YR 8.1/5.3")

.. code-block:: text

    array([ 0.38736945,  0.35751656,  0.59362   ])

Optical Phenomena - ``colour.phenomena``

.. code-block:: python

colour.rayleigh_scattering_sd()

.. code-block:: text

SpectralDistribution([[  3.60000000e+02,   5.99101337e-01],
                      [  3.61000000e+02,   5.92170690e-01],
                      [  3.62000000e+02,   5.85341006e-01],
                      ...
                      [  7.78000000e+02,   2.55208377e-02],
                      [  7.79000000e+02,   2.53887969e-02],
                      [  7.80000000e+02,   2.52576106e-02]],
                     interpolator=SpragueInterpolator,
                     interpolator_args={},
                     extrapolator=Extrapolator,
                     extrapolator_args={'right': None, 'method': 'Constant', 'left': None})

Light Quality - colour.quality


Colour Fidelity Index
*********************

.. code-block:: python

    colour.colour_fidelity_index(colour.SDS_ILLUMINANTS["FL2"])

.. code-block:: text

    70.120825477833037

.. code-block:: python

    sorted(colour.COLOUR_FIDELITY_INDEX_METHODS)

.. code-block:: text

    ['ANSI/IES TM-30-18', 'CIE 2017']

Colour Quality Scale
********************

.. code-block:: python

    colour.colour_quality_scale(colour.SDS_ILLUMINANTS["FL2"])

.. code-block:: text

    64.111703163816699

.. code-block:: python

    sorted(colour.COLOUR_QUALITY_SCALE_METHODS)

.. code-block:: text

    ['NIST CQS 7.4', 'NIST CQS 9.0']

Colour Rendering Index
**********************

.. code-block:: python

    colour.colour_rendering_index(colour.SDS_ILLUMINANTS["FL2"])

.. code-block:: text

    64.233724121664807

Academy Spectral Similarity Index (SSI)
***************************************

.. code-block:: python

    colour.spectral_similarity_index(
        colour.SDS_ILLUMINANTS["C"], colour.SDS_ILLUMINANTS["D65"]
    )

.. code-block:: text

    94.0

Spectral Up-Sampling & Recovery - ``colour.recovery``

Reflectance Recovery

.. code-block:: python

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

.. code-block:: text

SpectralDistribution([[  3.60000000e+02,   8.40144095e-02],
                      [  3.65000000e+02,   8.41264236e-02],
                      [  3.70000000e+02,   8.40057597e-02],
                      ...
                      [  7.70000000e+02,   4.46743012e-01],
                      [  7.75000000e+02,   4.46817187e-01],
                      [  7.80000000e+02,   4.46857696e-01]],
                     SpragueInterpolator,
                     {},
                     Extrapolator,
                     {'method': 'Constant', 'left': None, 'right': None})

.. code-block:: python

sorted(colour.REFLECTANCE_RECOVERY_METHODS)

.. code-block:: text

['Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018', 'Smits 1999']

Camera RGB Sensitivities Recovery

.. code-block:: python

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.characterisation.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,
)

.. code-block:: text

RGB_CameraSensitivities([[  4.00000000e+02,   7.22815777e-03,   9.22506480e-03,
                           -9.88368972e-03],
                         [  4.10000000e+02,  -8.50457609e-03,   1.12777480e-02,
                            3.86248655e-03],
                         [  4.20000000e+02,   4.58191132e-02,   7.15520948e-02,
                            4.04068293e-01],
                         ...
                         [  6.80000000e+02,   4.08276173e-02,   5.55290476e-03,
                            1.39907862e-03],
                         [  6.90000000e+02,  -3.71437574e-03,   2.50935640e-03,
                            3.97652622e-04],
                         [  7.00000000e+02,  -5.62256563e-03,   1.56433970e-03,
                            5.84726936e-04]],
                        ['red', 'green', 'blue'],
                        SpragueInterpolator,
                        {},
                        Extrapolator,
                        {'method': 'Constant', 'left': None, 'right': None})

Correlated Colour Temperature Computation Methods - colour.temperature


.. code-block:: python

    colour.uv_to_CCT([0.1978, 0.3122])

.. code-block:: text

    array([  6.50751282e+03,   3.22335875e-03])

.. code-block:: python

    sorted(colour.UV_TO_CCT_METHODS)

.. code-block:: text

    ['Krystek 1985', 'Ohno 2013', 'Planck 1900', 'Robertson 1968', 'ohno2013', 'robertson1968']

.. code-block:: python

    sorted(colour.XY_TO_CCT_METHODS)

.. code-block:: text

    ['CIE Illuminant D Series',
     'Hernandez 1999',
     'Kang 2002',
     'McCamy 1992',
     'daylight',
     'hernandez1999',
     'kang2002',
     'mccamy1992']

Colour Volume - ``colour.volume``

.. code-block:: python

colour.RGB_colourspace_volume_MonteCarlo(colour.RGB_COLOURSPACE_RGB["sRGB"])

.. code-block:: text

821958.30000000005

Geometry Primitives Generation - colour.geometry


.. code-block:: python

    colour.primitive("Grid")

.. code-block:: text

 (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', '<f4', (3,)), ('uv', '<f4', (2,)), ('normal', '<f4', (3,)), ('colour', '<f4', (4,))]), array([[0, 2, 1],
           [2, 3, 1]], dtype=uint32), array([[0, 2],
           [2, 3],
           [3, 1],
           [1, 0]], dtype=uint32))

.. code-block:: python

    sorted(colour.PRIMITIVE_METHODS)

.. code-block:: text

    ['Cube', 'Grid']

.. code-block:: python

    colour.primitive_vertices("Quad MPL")

.. code-block:: text

    array([[ 0.,  0.,  0.],
           [ 1.,  0.,  0.],
           [ 1.,  1.,  0.],
           [ 0.,  1.,  0.]])
    sorted(colour.PRIMITIVE_VERTICES_METHODS)
    ['Cube MPL', 'Grid MPL', 'Quad MPL', 'Sphere']

Plotting - ``colour.plotting``

Most of the objects are available from the colour.plotting namespace:

.. code-block:: python

from colour.plotting import *

colour_style()

Visible Spectrum

.. code-block:: python

plot_visible_spectrum("CIE 1931 2 Degree Standard Observer")

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

Spectral Distribution

.. code-block:: python

plot_single_illuminant_sd("FL1")

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

Blackbody

.. code-block:: python

blackbody_sds = [
    colour.sd_blackbody(i, colour.SpectralShape(0, 10000, 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),
)

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

Colour Matching Functions

.. code-block:: python

plot_single_cmfs(
    "Stockman & Sharpe 2 Degree Cone Fundamentals",
    y_label="Sensitivity",
    bounding_box=(390, 870, 0, 1.1),
)

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

Luminous Efficiency

.. code-block:: python

sd_mesopic_luminous_efficiency_function = (
    colour.sd_mesopic_luminous_efficiency_function(0.2)
)
plot_multi_sds(
    (
        sd_mesopic_luminous_efficiency_function,
        colour.PHOTOPIC_LEFS["CIE 1924 Photopic Standard Observer"],
        colour.SCOTOPIC_LEFS["CIE 1951 Scotopic Standard Observer"],
    ),
    y_label="Luminous Efficiency",
    legend_location="upper right",
    y_tighten=True,
    margins=(0, 0, 0, 0.1),
)

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

Colour Checker

.. code-block:: python

from colour.characterisation.dataset.colour_checkers.sds import (
    COLOURCHECKER_INDEXES_TO_NAMES_MAPPING,
)

plot_multi_sds(
    [
        colour.SDS_COLOURCHECKERS["BabelColor Average"][value]
        for key, value in sorted(COLOURCHECKER_INDEXES_TO_NAMES_MAPPING.items())
    ],
    plot_kwargs={
        "use_sd_colours": True,
    },
    title=("BabelColor Average - " "Spectral Distributions"),
)

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

.. code-block:: python

plot_single_colour_checker("ColorChecker 2005", text_kwargs={"visible": False})

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

Chromaticities Prediction

.. code-block:: python

plot_corresponding_chromaticities_prediction(2, "Von Kries", "Bianco 2010")

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

Chromaticities

.. code-block:: python

import numpy as np

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"],
)

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

Colour Rendering Index Bars

.. code-block:: python

plot_single_sd_colour_rendering_index_bars(colour.SDS_ILLUMINANTS["FL2"])

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

ANSI/IES TM-30-18 Colour Rendition Report

.. code-block:: python

plot_single_sd_colour_rendition_report(colour.SDS_ILLUMINANTS["FL2"])

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

Gamut Section

.. code-block:: python

plot_visible_spectrum_section(section_colours="RGB", section_opacity=0.15)

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

.. code-block:: python

plot_RGB_colourspace_section("sRGB", section_colours="RGB", section_opacity=0.15)

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

Colour Temperature

.. code-block:: python

plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(["A", "B", "C"])

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

User Guide

Installation


**Colour** and its primary dependencies can be easily installed from the
`Python Package Index <https://pypi.org/project/colour-science>`__
by issuing this command in a shell:

.. code-block:: bash

    $ pip install --user colour-science

The detailed installation procedure for the secondary dependencies is
described in the `Installation Guide <https://www.colour-science.org/installation-guide>`__.

**Colour** is also available for `Anaconda <https://www.anaconda.com/download>`__
from *Continuum Analytics* via `conda-forge <https://conda-forge.org>`__:

.. code-block:: bash

    $ conda install -c conda-forge colour-science

Tutorial

The static tutorial <https://colour.readthedocs.io/en/develop/tutorial.html> provides an introduction to Colour. An interactive version is available via Google Colab <https://colab.research.google.com/notebook#fileId=1Im9J7or9qyClQCv5sPHmKdyiQbG4898K&offline=true&sandboxMode=true>.

How-To


The `Google Colab How-To <https://colab.research.google.com/notebook#fileId=1NRcdXSCshivkwoU2nieCvC3y14fx1X4X&offline=true&sandboxMode=true>`__
guide for **Colour** shows various techniques to solve specific problems and
highlights some interesting use cases.

Contributing

If you would like to contribute to Colour, please refer to the following Contributing <https://www.colour-science.org/contributing>__ guide.

Changes


The changes are viewable on the `Releases <https://github.com/colour-science/colour/releases>`__ page.

Bibliography

The bibliography is available on the Bibliography <https://www.colour-science.org/bibliography>__ page.

It is also viewable directly from the repository in BibTeX <https://github.com/colour-science/colour/blob/develop/BIBLIOGRAPHY.bib>__ format.

API Reference

The main technical reference for Colour is the API Reference:

Release <https://colour.readthedocs.io/en/master/reference.html>__.
Develop <https://colour.readthedocs.io/en/latest/reference.html>__.