# -*- coding: utf-8 -*-
from setuptools import setup

package_dir = \
{'': '.'}

packages = \
['colour',
 'colour.adaptation',
 'colour.adaptation.datasets',
 'colour.adaptation.tests',
 'colour.algebra',
 'colour.algebra.coordinates',
 'colour.algebra.coordinates.tests',
 'colour.algebra.tests',
 'colour.appearance',
 'colour.appearance.tests',
 'colour.biochemistry',
 'colour.biochemistry.tests',
 'colour.blindness',
 'colour.blindness.datasets',
 'colour.blindness.tests',
 'colour.characterisation',
 'colour.characterisation.datasets',
 'colour.characterisation.datasets.cameras',
 'colour.characterisation.datasets.cameras.dslr',
 'colour.characterisation.datasets.colour_checkers',
 'colour.characterisation.datasets.displays',
 'colour.characterisation.datasets.displays.crt',
 'colour.characterisation.datasets.displays.lcd',
 'colour.characterisation.tests',
 'colour.colorimetry',
 'colour.colorimetry.datasets',
 'colour.colorimetry.datasets.illuminants',
 'colour.colorimetry.datasets.light_sources',
 'colour.colorimetry.tests',
 'colour.constants',
 'colour.continuous',
 'colour.continuous.tests',
 'colour.contrast',
 'colour.contrast.tests',
 'colour.corresponding',
 'colour.corresponding.datasets',
 'colour.corresponding.tests',
 'colour.difference',
 'colour.difference.tests',
 'colour.examples',
 'colour.examples.adaptation',
 'colour.examples.algebra',
 'colour.examples.appearance',
 'colour.examples.blindness',
 'colour.examples.characterisation',
 'colour.examples.colorimetry',
 'colour.examples.contrast',
 'colour.examples.corresponding',
 'colour.examples.difference',
 'colour.examples.graph',
 'colour.examples.io',
 'colour.examples.models',
 'colour.examples.notation',
 'colour.examples.phenomena',
 'colour.examples.plotting',
 'colour.examples.quality',
 'colour.examples.recovery',
 'colour.examples.temperature',
 'colour.examples.volume',
 'colour.graph',
 'colour.graph.tests',
 'colour.io',
 'colour.io.luts',
 'colour.io.luts.tests',
 'colour.io.tests',
 'colour.models',
 'colour.models.datasets',
 'colour.models.rgb',
 'colour.models.rgb.datasets',
 'colour.models.rgb.tests',
 'colour.models.rgb.transfer_functions',
 'colour.models.rgb.transfer_functions.tests',
 'colour.models.tests',
 'colour.notation',
 'colour.notation.datasets',
 'colour.notation.datasets.munsell',
 'colour.notation.tests',
 'colour.phenomena',
 'colour.phenomena.tests',
 'colour.plotting',
 'colour.plotting.datasets',
 'colour.plotting.tests',
 'colour.quality',
 'colour.quality.datasets',
 'colour.quality.tests',
 'colour.recovery',
 'colour.recovery.datasets',
 'colour.recovery.tests',
 'colour.temperature',
 'colour.temperature.tests',
 'colour.utilities',
 'colour.utilities.tests',
 'colour.volume',
 'colour.volume.datasets',
 'colour.volume.tests']

package_data = \
{'': ['*'],
 'colour.appearance.tests': ['fixtures/*'],
 'colour.examples.io': ['resources/*'],
 'colour.examples.plotting': ['resources/*'],
 'colour.io.luts.tests': ['resources/cinespace/*',
                          'resources/iridas_cube/*',
                          'resources/resolve_cube/*',
                          'resources/sony_spi1d/*',
                          'resources/sony_spi3d/*'],
 'colour.io.tests': ['resources/*']}

install_requires = \
['imageio', 'scipy', 'six']

extras_require = \
{'development': ['biblib-simple',
                 'coverage',
                 'coveralls',
                 'flake8',
                 'invoke',
                 'jupyter',
                 'mock',
                 'nbformat>=4,<5',
                 'nose',
                 'pre-commit',
                 'pytest',
                 'restructuredtext-lint',
                 'sphinx',
                 'sphinx_rtd_theme',
                 'sphinxcontrib-bibtex',
                 'toml',
                 'twine',
                 'yapf==0.23'],
 'graphviz': ['pygraphviz'],
 'optional': ['networkx', 'pandas'],
 'plotting': ['backports.functools_lru_cache', 'matplotlib'],
 'read-the-docs': ['mock',
                   'networkx',
                   'numpy',
                   'pygraphviz',
                   'sphinxcontrib-bibtex']}

setup_kwargs = {
    'name': 'colour-science',
    'version': '0.3.15',
    'description': 'Colour Science for Python',
    'long_description': '..  image:: https://raw.githubusercontent.com/colour-science/colour-branding/master/images/Colour_Logo_Medium_001.png\n\n.. start-badges\n\n|NumFOCUS| |actions| |coveralls| |codacy| |version| |zenodo|\n\n.. |NumFOCUS| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat-square&colorA=E1523D&colorB=007D8A\n    :target: http://numfocus.org\n    :alt: Powered by NumFOCUS\n.. |actions| image:: https://img.shields.io/github/workflow/status/colour-science/colour/Continuous%20Integration?label=actions&logo=github&style=flat-square\n    :target: https://github.com/colour-science/colour/actions\n    :alt: Develop Build Status\n.. |coveralls| image:: http://img.shields.io/coveralls/colour-science/colour/develop.svg?style=flat-square\n    :target: https://coveralls.io/r/colour-science/colour\n    :alt: Coverage Status\n.. |codacy| image:: https://img.shields.io/codacy/grade/7d0d61f8e7294533b27ae00ee6f50fb2/develop.svg?style=flat-square\n    :target: https://www.codacy.com/app/colour-science/colour\n    :alt: Code Grade\n.. |version| image:: https://img.shields.io/pypi/v/colour-science.svg?style=flat-square\n    :target: https://pypi.org/project/colour-science\n    :alt: Package Version\n.. |zenodo| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.3627408-blue.svg?style=flat-square\n    :target: https://dx.doi.org/10.5281/zenodo.3627408\n    :alt: DOI\n\n.. end-badges\n\n`Colour <https://github.com/colour-science/colour>`__ is an open-source\n`Python <https://www.python.org/>`__ package providing a comprehensive number of\nalgorithms and datasets for colour science.\n\nIt is freely available under the\n`New BSD License <https://opensource.org/licenses/BSD-3-Clause>`__ terms.\n\n**Colour** is an affiliated project of `NumFOCUS <https://numfocus.org/>`__, a\n501(c)(3) nonprofit in the United States.\n\n.. contents:: **Table of Contents**\n    :backlinks: none\n    :depth: 3\n\n.. sectnum::\n\nDraft Release Notes\n-------------------\n\nThe draft release notes of the\n`develop <https://github.com/colour-science/colour/tree/develop>`__\nbranch are available at this\n`url <https://gist.github.com/KelSolaar/4a6ebe9ec3d389f0934b154fec8df51d>`__.\n\nSponsors\n--------\n\nWe are grateful 💖 for the support of our\n`sponsors <https://github.com/colour-science/colour/blob/develop/SPONSORS.rst>`__.\nIf you\'d like to join them, please consider\n`becoming a sponsor on OpenCollective <https://opencollective.com/colour-science>`__.\n\n\n\nFeatures\n--------\n\n**Colour** features a rich dataset and collection of objects, please see the\n`features <https://www.colour-science.org/features/>`__ page for more\ninformation.\n\nInstallation\n------------\n\n**Colour** can be easily installed from the\n`Python Package Index <https://pypi.org/project/colour-science/>`__\nby issuing this command in a shell:\n\n.. code-block:: bash\n\n    $ pip install colour-science\n\n**Colour** is also available for `Anaconda <https://www.continuum.io/downloads>`__\nfrom *Continuum Analytics* via `conda-forge <https://conda-forge.org/>`__:\n\n.. code-block:: bash\n\n    $ conda install -c conda-forge colour-science\n\nThe detailed installation procedure is described in the\n`Installation Guide <https://www.colour-science.org/installation-guide/>`__.\n\nDocumentation\n-------------\n\nTutorial\n~~~~~~~~\n\nThe `static tutorial <https://colour.readthedocs.io/en/develop/tutorial.html>`__\nprovides an introduction to **Colour**. An interactive version is available via\n`Google Colab <https://colab.research.google.com/notebook#fileId=1Im9J7or9qyClQCv5sPHmKdyiQbG4898K&offline=true&sandboxMode=true>`__.\n\nHow-To Guide\n~~~~~~~~~~~~\n\nThe `How-To <https://colab.research.google.com/notebook#fileId=1NRcdXSCshivkwoU2nieCvC3y14fx1X4X&offline=true&sandboxMode=true>`__\nguide for **Colour** shows various techniques to solve specific problems and\nhighlights some interesting use cases.\n\nAPI Reference\n~~~~~~~~~~~~~\n\nThe main technical reference for **Colour** and its API is the\n`Colour Manual <https://colour.readthedocs.io/en/latest/manual.html>`__.\n\nJupyter Notebooks\n~~~~~~~~~~~~~~~~~\n\n`Jupyter Notebooks <http://nbviewer.jupyter.org/github/colour-science/colour-notebooks/blob/master/notebooks/colour.ipynb>`__\nare available and designed to provide an historical perspective of colour\nscience via **Colour** usage.\n\nExamples\n~~~~~~~~\n\nMost of the objects are available from the ``colour`` namespace:\n\n.. code-block:: python\n\n    >>> import colour\n\nAutomatic Colour Conversion Graph - ``colour.graph``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nStarting with version *0.3.14*, **Colour** implements an automatic colour\nconversion graph enabling easier colour conversions.\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Colour_Automatic_Conversion_Graph.png\n\n.. code-block:: python\n\n    >>> sd = colour.COLOURCHECKERS_SDS[\'ColorChecker N Ohta\'][\'dark skin\']\n    >>> convert(sd, \'Spectral Distribution\', \'sRGB\', verbose={\'mode\': \'Short\'})\n\n::\n\n    ===============================================================================\n    *                                                                             *\n    *   [ Conversion Path ]                                                       *\n    *                                                                             *\n    *   "sd_to_XYZ" --> "XYZ_to_sRGB"                                             *\n    *                                                                             *\n    ===============================================================================\n    array([ 0.45675795,  0.30986982,  0.24861924])\n\n.. code-block:: python\n\n    >>> illuminant = colour.ILLUMINANTS_SDS[\'FL2\']\n    >>> convert(sd, \'Spectral Distribution\', \'sRGB\', sd_to_XYZ={\'illuminant\': illuminant})\n    array([ 0.47924575,  0.31676968,  0.17362725])\n\nChromatic Adaptation - ``colour.adaptation``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008, 0.12197225, 0.05136952]\n    >>> D65 = colour.ILLUMINANTS[\'CIE 1931 2 Degree Standard Observer\'][\'D65\']\n    >>> A = colour.ILLUMINANTS[\'CIE 1931 2 Degree Standard Observer\'][\'A\']\n    >>> colour.chromatic_adaptation(\n    ...     XYZ, colour.xy_to_XYZ(D65), colour.xy_to_XYZ(A))\n    array([ 0.2533053 ,  0.13765138,  0.01543307])\n    >>> sorted(colour.CHROMATIC_ADAPTATION_METHODS.keys())\n    [\'CIE 1994\', \'CMCCAT2000\', \'Fairchild 1990\', \'Von Kries\']\n\nAlgebra - ``colour.algebra``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nKernel Interpolation\n********************\n\n.. code-block:: python\n\n    >>> y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500]\n    >>> x = range(len(y))\n    >>> colour.KernelInterpolator(x, y)([0.25, 0.75, 5.50])\n    array([  6.18062083,   8.08238488,  57.85783403])\n\nSprague (1880) Interpolation\n****************************\n\n.. code-block:: python\n\n    >>> y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500]\n    >>> x = range(len(y))\n    >>> colour.SpragueInterpolator(x, y)([0.25, 0.75, 5.50])\n    array([  6.72951612,   7.81406251,  43.77379185])\n\nColour Appearance Models - ``colour.appearance``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]\n    >>> XYZ_w = [95.05, 100.00, 108.88]\n    >>> L_A = 318.31\n    >>> Y_b = 20.0\n    >>> colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b)\n    CIECAM02_Specification(J=34.434525727858997, C=67.365010921125915, h=22.279164147957076, s=62.814855853327131, Q=177.47124941102123, M=70.024939419291385, H=2.689608534423904, HC=None)\n\nColour Blindness - ``colour.blindness``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> import colour\n    >>> cmfs = colour.LMS_CMFS[\'Stockman & Sharpe 2 Degree Cone Fundamentals\']\n    >>> colour.anomalous_trichromacy_cmfs_Machado2009(cmfs, np.array([15, 0, 0]))[450]\n    array([ 0.08912884,  0.0870524 ,  0.955393  ])\n    >>> primaries = colour.DISPLAYS_RGB_PRIMARIES[\'Apple Studio Display\']\n    >>> d_LMS = (15, 0, 0)\n    >>> colour.anomalous_trichromacy_matrix_Machado2009(cmfs, primaries, d_LMS)\n    array([[-0.27774652,  2.65150084, -1.37375432],\n           [ 0.27189369,  0.20047862,  0.52762768],\n           [ 0.00644047,  0.25921579,  0.73434374]])\n\nColour Correction - ``colour characterisation``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> import numpy as np\n    >>> RGB = [0.17224810, 0.09170660, 0.06416938]\n    >>> M_T = np.random.random((24, 3))\n    >>> M_R = M_T + (np.random.random((24, 3)) - 0.5) * 0.5\n    >>> colour.colour_correction(RGB, M_T, M_R)\n    array([ 0.15205429,  0.08974029,  0.04141435])\n    >>> sorted(colour.COLOUR_CORRECTION_METHODS.keys())\n    [\'Cheung 2004\', \'Finlayson 2015\', \'Vandermonde\']\n\nColorimetry - ``colour.colorimetry``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nSpectral Computations\n*********************\n\n.. code-block:: python\n\n    >>> colour.sd_to_XYZ(colour.LIGHT_SOURCES_SDS[\'Neodimium Incandescent\'])\n    array([ 36.94726204,  32.62076174,  13.0143849 ])\n    >>> sorted(colour.SPECTRAL_TO_XYZ_METHODS.keys())\n    [\'ASTM E308\', \'Integration\', \'astm2015\']\n\n\nMulti-Spectral Computations\n***************************\n\n.. code-block:: python\n\n    >>> msds = np.array([\n    ...     [[0.01367208, 0.09127947, 0.01524376, 0.02810712, 0.19176012, 0.04299992],\n    ...      [0.00959792, 0.25822842, 0.41388571, 0.22275120, 0.00407416, 0.37439537],\n    ...      [0.01791409, 0.29707789, 0.56295109, 0.23752193, 0.00236515, 0.58190280]],\n    ...     [[0.01492332, 0.10421912, 0.02240025, 0.03735409, 0.57663846, 0.32416266],\n    ...      [0.04180972, 0.26402685, 0.03572137, 0.00413520, 0.41808194, 0.24696727],\n    ...      [0.00628672, 0.11454948, 0.02198825, 0.39906919, 0.63640803, 0.01139849]],\n    ...     [[0.04325933, 0.26825359, 0.23732357, 0.05175860, 0.01181048, 0.08233768],\n    ...      [0.02484169, 0.12027161, 0.00541695, 0.00654612, 0.18603799, 0.36247808],\n    ...      [0.03102159, 0.16815442, 0.37186235, 0.08610666, 0.00413520, 0.78492409]],\n    ...     [[0.11682307, 0.78883040, 0.74468607, 0.83375293, 0.90571451, 0.70054168],\n    ...      [0.06321812, 0.41898224, 0.15190357, 0.24591440, 0.55301750, 0.00657664],\n    ...      [0.00305180, 0.11288624, 0.11357290, 0.12924391, 0.00195315, 0.21771573]],\n    ... ])\n    >>> colour.multi_sds_to_XYZ(msds, cmfs, illuminant, method=\'Integration\',\n    ...                         shape=colour.SpectralShape(400, 700, 60)))\n    [[[  9.73192501   5.02105851   3.22790699]\n      [ 16.08032168  24.47303359  10.28681006]\n      [ 17.73513774  29.61865582  12.10713449]]\n     [[ 25.69298792  11.72611193   3.70187275]\n      [ 18.51208526   8.03720984   9.30361825]\n      [ 48.55945054  32.30885571   4.09223401]]\n     [[  5.7743232   10.10692925  10.08461311]\n      [  8.81306527   3.65394599   4.20783881]\n      [  8.06007398  15.87077693   7.02551086]]\n     [[ 90.88877129  81.82966846  29.86765971]\n      [ 38.64801062  26.70860262  15.08396538]\n      [  8.77151115  10.56330761   4.28940206]]]\n    >>> sorted(colour.MULTI_SPECTRAL_TO_XYZ_METHODS.keys())\n    [\'ASTM E308\', \'Integration\', \'astm2015\']\n\nBlackbody Spectral Radiance Computation\n***************************************\n\n.. code-block:: python\n\n    >>> colour.sd_blackbody(5000)\n    SpectralDistribution([[  3.60000000e+02,   6.65427827e+12],\n                          [  3.61000000e+02,   6.70960528e+12],\n                          [  3.62000000e+02,   6.76482512e+12],\n                          ...\n                          [  7.78000000e+02,   1.06068004e+13],\n                          [  7.79000000e+02,   1.05903327e+13],\n                          [  7.80000000e+02,   1.05738520e+13]],\n                         interpolator=SpragueInterpolator,\n                         interpolator_args={},\n                         extrapolator=Extrapolator,\n                         extrapolator_args={\'right\': None, \'method\': \'Constant\', \'left\': None})\n\nDominant, Complementary Wavelength & Colour Purity Computation\n**************************************************************\n\n.. code-block:: python\n\n    >>> xy = [0.54369557, 0.32107944]\n    >>> xy_n = [0.31270000, 0.32900000]\n    >>> colour.dominant_wavelength(xy, xy_n)\n    (array(616.0),\n     array([ 0.68354746,  0.31628409]),\n     array([ 0.68354746,  0.31628409]))\n\nLightness Computation\n*********************\n\n.. code-block:: python\n\n    >>> colour.lightness(12.19722535)\n    41.527875844653451\n    >>> sorted(colour.LIGHTNESS_METHODS.keys())\n    [\'CIE 1976\',\n     \'Fairchild 2010\',\n     \'Fairchild 2011\',\n     \'Glasser 1958\',\n     \'Lstar1976\',\n     \'Wyszecki 1963\']\n\nLuminance Computation\n*********************\n\n.. code-block:: python\n\n    >>> colour.luminance(41.52787585)\n    12.197225353400775\n    >>> sorted(colour.LUMINANCE_METHODS.keys())\n    [\'ASTM D1535\',\n     \'CIE 1976\',\n     \'Fairchild 2010\',\n     \'Fairchild 2011\',\n     \'Newhall 1943\',\n     \'astm2008\',\n     \'cie1976\']\n\nWhiteness Computation\n*********************\n\n.. code-block:: python\n\n    >>> XYZ = [95.00000000, 100.00000000, 105.00000000]\n    >>> XYZ_0 = [94.80966767, 100.00000000, 107.30513595]\n    >>> colour.whiteness(XYZ, XYZ_0)\n    array([ 93.756     ,  -1.33000001])\n    >>> sorted(colour.WHITENESS_METHODS.keys())\n    [\'ASTM E313\',\n     \'Berger 1959\',\n     \'CIE 2004\',\n     \'Ganz 1979\',\n     \'Stensby 1968\',\n     \'Taube 1960\',\n     \'cie2004\']\n\nYellowness Computation\n**********************\n\n.. code-block:: python\n\n    >>> XYZ = [95.00000000, 100.00000000, 105.00000000]\n    >>> colour.yellowness(XYZ)\n    11.065000000000003\n    >>> sorted(colour.YELLOWNESS_METHODS.keys())\n    [\'ASTM D1925\', \'ASTM E313\']\n\nLuminous Flux, Efficiency & Efficacy Computation\n************************************************\n\n.. code-block:: python\n\n    >>> sd = colour.LIGHT_SOURCES_SDS[\'Neodimium Incandescent\']\n    >>> colour.luminous_flux(sd)\n    23807.655527367202\n    >>> sd = colour.LIGHT_SOURCES_SDS[\'Neodimium Incandescent\']\n    >>> colour.luminous_efficiency(sd)\n    0.19943935624521045\n    >>> sd = colour.LIGHT_SOURCES_SDS[\'Neodimium Incandescent\']\n    >>> colour.luminous_efficacy(sd)\n    136.21708031547874\n\nContrast Sensitivity Function - ``colour.contrast``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> colour.contrast_sensitivity_function(u=4, X_0=60, E=65)\n    358.51180789884984\n    >>> sorted(colour.CONTRAST_SENSITIVITY_METHODS.keys())\n    [\'Barten 1999\']\n\n\nColour Difference - ``colour.difference``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> Lab_1 = [100.00000000, 21.57210357, 272.22819350]\n    >>> Lab_2 = [100.00000000, 426.67945353, 72.39590835]\n    >>> colour.delta_E(Lab_1, Lab_2)\n    94.035649026659485\n    >>> sorted(colour.DELTA_E_METHODS.keys())\n    [\'CAM02-LCD\',\n     \'CAM02-SCD\',\n     \'CAM02-UCS\',\n     \'CAM16-LCD\',\n     \'CAM16-SCD\',\n     \'CAM16-UCS\',\n     \'CIE 1976\',\n     \'CIE 1994\',\n     \'CIE 2000\',\n     \'CMC\',\n     \'DIN99\',\n     \'cie1976\',\n     \'cie1994\',\n     \'cie2000\']\n\nIO - ``colour.io``\n^^^^^^^^^^^^^^^^^^\n\nImages\n******\n\n.. code-block:: python\n\n    >>> RGB = colour.read_image(\'Ishihara_Colour_Blindness_Test_Plate_3.png\')\n    >>> RGB.shape\n    (276, 281, 3)\n\nLook Up Table (LUT) Data\n************************\n\n.. code-block:: python\n\n    >>> LUT = colour.read_LUT(\'ACES_Proxy_10_to_ACES.cube\')\n    >>> print(LUT)\n\n::\n\n    LUT3x1D - ACES Proxy 10 to ACES\n    -------------------------------\n    Dimensions : 2\n    Domain     : [[0 0 0]\n                  [1 1 1]]\n    Size       : (32, 3)\n\n.. code-block:: python\n\n    >>> RGB = [0.17224810, 0.09170660, 0.06416938]\n    >>> LUT.apply(RGB)\n    array([ 0.00575674,  0.00181493,  0.00121419])\n\nColour Models - ``colour.models``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nCIE xyY Colourspace\n*******************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_xyY([0.20654008, 0.12197225, 0.05136952])\n    array([ 0.54369557,  0.32107944,  0.12197225])\n\nCIE L*a*b* Colourspace\n**********************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_Lab([0.20654008, 0.12197225, 0.05136952])\n    array([ 41.52787529,  52.63858304,  26.92317922])\n\nCIE L*u*v* Colourspace\n**********************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_Luv([0.20654008, 0.12197225, 0.05136952])\n    array([ 41.52787529,  96.83626054,  17.75210149])\n\nCIE 1960 UCS Colourspace\n************************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_UCS([0.20654008, 0.12197225, 0.05136952])\n    array([ 0.13769339,  0.12197225,  0.1053731 ])\n\nCIE 1964 U*V*W* Colourspace\n***************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> colour.XYZ_to_UVW(XYZ)\n    array([ 94.55035725,  11.55536523,  40.54757405])\n\nHunter L,a,b Colour Scale\n*************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> colour.XYZ_to_Hunter_Lab(XYZ)\n    array([ 34.92452577,  47.06189858,  14.38615107])\n\nHunter Rd,a,b Colour Scale\n**************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> colour.XYZ_to_Hunter_Rdab(XYZ)\n    array([ 12.197225  ,  57.12537874,  17.46241341])\n\nCAM02-LCD, CAM02-SCD, and CAM02-UCS Colourspaces - Luo, Cui and Li (2006)\n*************************************************************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> XYZ_w = [95.05, 100.00, 108.88]\n    >>> L_A = 318.31\n    >>> Y_b = 20.0\n    >>> surround = colour.CIECAM02_VIEWING_CONDITIONS[\'Average\']\n    >>> specification = colour.XYZ_to_CIECAM02(\n            XYZ, XYZ_w, L_A, Y_b, surround)\n    >>> JMh = (specification.J, specification.M, specification.h)\n    >>> colour.JMh_CIECAM02_to_CAM02UCS(JMh)\n    array([ 47.16899898,  38.72623785,  15.8663383 ])\n\nCAM16-LCD, CAM16-SCD, and CAM16-UCS Colourspaces - Li et al. (2017)\n*******************************************************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> XYZ_w = [95.05, 100.00, 108.88]\n    >>> L_A = 318.31\n    >>> Y_b = 20.0\n    >>> surround = colour.CAM16_VIEWING_CONDITIONS[\'Average\']\n    >>> specification = colour.XYZ_to_CAM16(\n            XYZ, XYZ_w, L_A, Y_b, surround)\n    >>> JMh = (specification.J, specification.M, specification.h)\n    >>> colour.JMh_CAM16_to_CAM16UCS(JMh)\n    array([ 46.55542238,  40.22460974,  14.25288392]\n\nIPT Colourspace\n***************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_IPT([0.20654008, 0.12197225, 0.05136952])\n    array([ 0.38426191,  0.38487306,  0.18886838])\n\nDIN99 Colourspace\n*****************\n\n.. code-block:: python\n\n    >>> Lab = [41.52787529, 52.63858304, 26.92317922]\n    >>> colour.Lab_to_DIN99(Lab)\n    array([ 53.22821988,  28.41634656,   3.89839552])\n\nhdr-CIELAB Colourspace\n**********************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_hdr_CIELab([0.20654008, 0.12197225, 0.05136952])\n    array([ 51.87002062,  60.4763385 ,  32.14551912])\n\nhdr-IPT Colourspace\n*******************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_hdr_IPT([0.20654008, 0.12197225, 0.05136952])\n    array([ 25.18261761, -22.62111297,   3.18511729])\n\nOSA UCS Colourspace\n*******************\n\n.. code-block:: python\n\n    >>> XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952* 100]\n    >>> colour.XYZ_to_OSA_UCS(XYZ)\n    array([-3.0049979 ,  2.99713697, -9.66784231])\n\nJzAzBz Colourspace\n******************\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_JzAzBz([0.20654008, 0.12197225, 0.05136952])\n    array([ 0.00535048,  0.00924302,  0.00526007])\n\nY\'CbCr Colour Encoding\n**********************\n\n.. code-block:: python\n\n    >>> colour.RGB_to_YCbCr([1.0, 1.0, 1.0])\n    array([ 0.92156863,  0.50196078,  0.50196078])\n\nYCoCg Colour Encoding\n*********************\n\n.. code-block:: python\n\n    >>> colour.RGB_to_YCoCg([0.75, 0.75, 0.0])\n    array([ 0.5625,  0.375 ,  0.1875])\n\nICTCP Colour Encoding\n*********************\n\n.. code-block:: python\n\n    >>> colour.RGB_to_ICTCP([0.45620519, 0.03081071, 0.04091952])\n    array([ 0.07351364,  0.00475253,  0.09351596])\n\nHSV Colourspace\n***************\n\n.. code-block:: python\n\n    >>> colour.RGB_to_HSV([0.45620519, 0.03081071, 0.04091952])\n    array([ 0.99603944,  0.93246304,  0.45620519])\n\nPrismatic Colourspace\n*********************\n\n.. code-block:: python\n\n    >>> colour.RGB_to_Prismatic([0.25, 0.50, 0.75])\n    array([ 0.75      ,  0.16666667,  0.33333333,  0.5       ])\n\nRGB Colourspace and Transformations\n***********************************\n\n.. code-block:: python\n\n    >>> XYZ = [0.21638819, 0.12570000, 0.03847493]\n    >>> illuminant_XYZ = [0.34570, 0.35850]\n    >>> illuminant_RGB = [0.31270, 0.32900]\n    >>> chromatic_adaptation_transform = \'Bradford\'\n    >>> XYZ_to_RGB_matrix = [\n             [3.24062548, -1.53720797, -0.49862860],\n             [-0.96893071, 1.87575606, 0.04151752],\n             [0.05571012, -0.20402105, 1.05699594]]\n    >>> colour.XYZ_to_RGB(\n             XYZ,\n             illuminant_XYZ,\n             illuminant_RGB,\n             XYZ_to_RGB_matrix,\n             chromatic_adaptation_transform)\n    array([ 0.45595571,  0.03039702,  0.04087245])\n\nRGB Colourspace Derivation\n**************************\n\n.. code-block:: python\n\n    >>> p = [0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700]\n    >>> w = [0.32168, 0.33767]\n    >>> colour.normalised_primary_matrix(p, w)\n    array([[  9.52552396e-01,   0.00000000e+00,   9.36786317e-05],\n           [  3.43966450e-01,   7.28166097e-01,  -7.21325464e-02],\n           [  0.00000000e+00,   0.00000000e+00,   1.00882518e+00]])\n\nRGB Colourspaces\n****************\n\n.. code-block:: python\n\n    >>> sorted(colour.RGB_COLOURSPACES.keys())\n    [\'ACES2065-1\',\n     \'ACEScc\',\n     \'ACEScct\',\n     \'ACEScg\',\n     \'ACESproxy\',\n     \'ALEXA Wide Gamut\',\n     \'Adobe RGB (1998)\',\n     \'Adobe Wide Gamut RGB\',\n     \'Apple RGB\',\n     \'Best RGB\',\n     \'Beta RGB\',\n     \'CIE RGB\',\n     \'Cinema Gamut\',\n     \'ColorMatch RGB\',\n     \'DCDM XYZ\',\n     \'DCI-P3\',\n     \'DCI-P3+\',\n     \'Display P3\',\n     \'DJI D-Gamut\',\n     \'DRAGONcolor\',\n     \'DRAGONcolor2\',\n     \'Don RGB 4\',\n     \'ECI RGB v2\',\n     \'ERIMM RGB\',\n     \'Ekta Space PS 5\',\n     \'F-Gamut\',\n     \'FilmLight E-Gamut\',\n     \'ITU-R BT.2020\',\n     \'ITU-R BT.470 - 525\',\n     \'ITU-R BT.470 - 625\',\n     \'ITU-R BT.709\',\n     \'Max RGB\',\n     \'NTSC (1953)\',\n     \'NTSC (1987)\',\n     \'P3-D65\',\n     \'Pal/Secam\',\n     \'ProPhoto RGB\',\n     \'Protune Native\',\n     \'REDWideGamutRGB\',\n     \'REDcolor\',\n     \'REDcolor2\',\n     \'REDcolor3\',\n     \'REDcolor4\',\n     \'RIMM RGB\',\n     \'ROMM RGB\',\n     \'Russell RGB\',\n     \'S-Gamut\',\n     \'S-Gamut3\',\n     \'S-Gamut3.Cine\',\n     \'SMPTE 240M\',\n     \'SMPTE C\',\n     \'Sharp RGB\',\n     \'V-Gamut\',\n     \'Xtreme RGB\',\n     \'aces\',\n     \'adobe1998\',\n     \'prophoto\',\n     \'sRGB\']\n\nOETFs\n*****\n\n.. code-block:: python\n\n    >>> sorted(colour.OETFS.keys())\n    [\'ARIB STD-B67\',\n     \'ITU-R BT.2020\',\n     \'ITU-R BT.2100 HLG\',\n     \'ITU-R BT.2100 PQ\',\n     \'ITU-R BT.601\',\n     \'ITU-R BT.709\',\n     \'SMPTE 240M\']\n\nOETFs Inverse\n*************\n\n.. code-block:: python\n\n    >>> sorted(colour.OETF_INVERSES.keys())\n    [\'ARIB STD-B67\',\n     \'ITU-R BT.2100 HLD\',\n     \'ITU-R BT.2100 PQ\',\n     \'ITU-R BT.601\',\n     \'ITU-R BT.709\']\n\nEOTFs\n*****\n\n.. code-block:: python\n\n    >>> sorted(colour.EOTFS.keys())\n    [\'DCDM\',\n     \'DICOM GSDF\',\n     \'ITU-R BT.1886\',\n     \'ITU-R BT.2020\',\n     \'ITU-R BT.2100 HLG\',\n     \'ITU-R BT.2100 PQ\',\n     \'SMPTE 240M\',\n     \'ST 2084\',\n     \'sRGB\']\n\nEOTFs Inverse\n*************\n\n.. code-block:: python\n\n    >>> sorted(colour.EOTF_INVERSES.keys())\n    [\'DCDM\',\n     \'DICOM GSDF\',\n     \'ITU-R BT.1886\',\n     \'ITU-R BT.2100 HLG\',\n     \'ITU-R BT.2100 PQ\',\n     \'ST 2084\',\n     \'sRGB\']\n\nOOTFs\n*****\n\n.. code-block:: python\n\n    >>> sorted(colour.OOTFS.keys())\n    [\'ITU-R BT.2100 HLG\', \'ITU-R BT.2100 PQ\']\n\nOOTFs Inverse\n*************\n\n.. code-block:: python\n\n    >>> sorted(colour.OOTF_INVERSES.keys())\n    [\'ITU-R BT.2100 HLG\', \'ITU-R BT.2100 PQ\']\n\nLog Encoding / Decoding\n***********************\n\n.. code-block:: python\n\n    >>> sorted(colour.LOG_ENCODINGS.keys())\n    [\'ACEScc\',\n     \'ACEScct\',\n     \'ACESproxy\',\n     \'ALEXA Log C\',\n     \'Canon Log\',\n     \'Canon Log 2\',\n     \'Canon Log 3\',\n     \'Cineon\',\n     \'D-Log\',\n     \'ERIMM RGB\',\n     \'F-Log\',\n     \'Filmic Pro 6\',\n     \'Log3G10\',\n     \'Log3G12\',\n     \'PLog\',\n     \'Panalog\',\n     \'Protune\',\n     \'REDLog\',\n     \'REDLogFilm\',\n     \'S-Log\',\n     \'S-Log2\',\n     \'S-Log3\',\n     \'T-Log\',\n     \'V-Log\',\n     \'ViperLog\']\n\nCCTFs Encoding / Decoding\n*************************\n\n.. code-block:: python\n\n    >>> sorted(colour.CCTF_ENCODINGS.keys())\n    [\'ACEScc\',\n     \'ACEScct\',\n     \'ACESproxy\',\n     \'ALEXA Log C\',\n     \'ARIB STD-B67\',\n     \'Canon Log\',\n     \'Canon Log 2\',\n     \'Canon Log 3\',\n     \'Cineon\',\n     \'D-Log\',\n     \'DCDM\',\n     \'DICOM GSDF\',\n     \'ERIMM RGB\',\n     \'F-Log\',\n     \'Filmic Pro 6\',\n     \'Gamma 2.2\',\n     \'Gamma 2.4\',\n     \'Gamma 2.6\',\n     \'ITU-R BT.1886\',\n     \'ITU-R BT.2020\',\n     \'ITU-R BT.2100 HLG\',\n     \'ITU-R BT.2100 PQ\',\n     \'ITU-R BT.601\',\n     \'ITU-R BT.709\',\n     \'Log3G10\',\n     \'Log3G12\',\n     \'PLog\',\n     \'Panalog\',\n     \'ProPhoto RGB\',\n     \'Protune\',\n     \'REDLog\',\n     \'REDLogFilm\',\n     \'RIMM RGB\',\n     \'ROMM RGB\',\n     \'S-Log\',\n     \'S-Log2\',\n     \'S-Log3\',\n     \'SMPTE 240M\',\n     \'ST 2084\',\n     \'T-Log\',\n     \'V-Log\',\n     \'ViperLog\',\n     \'sRGB\']\n\nColour Notation Systems - ``colour.notation``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nMunsell Value\n*************\n\n.. code-block:: python\n\n    >>> colour.munsell_value(12.23634268)\n    4.0824437076525664\n    >>> sorted(colour.MUNSELL_VALUE_METHODS.keys())\n    [\'ASTM D1535\',\n     \'Ladd 1955\',\n     \'McCamy 1987\',\n     \'Moon 1943\',\n     \'Munsell 1933\',\n     \'Priest 1920\',\n     \'Saunderson 1944\',\n     \'astm2008\']\n\nMunsell Colour\n**************\n\n.. code-block:: python\n\n    >>> colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])\n    \'4.2YR 8.1/5.3\'\n    >>> colour.munsell_colour_to_xyY(\'4.2YR 8.1/5.3\')\n    array([ 0.38736945,  0.35751656,  0.59362   ])\n\nOptical Phenomena - ``colour.phenomena``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> colour.rayleigh_scattering_sd()\n    SpectralDistribution([[  3.60000000e+02,   5.99101337e-01],\n                          [  3.61000000e+02,   5.92170690e-01],\n                          [  3.62000000e+02,   5.85341006e-01],\n                          ...\n                          [  7.78000000e+02,   2.55208377e-02],\n                          [  7.79000000e+02,   2.53887969e-02],\n                          [  7.80000000e+02,   2.52576106e-02]],\n                         interpolator=SpragueInterpolator,\n                         interpolator_args={},\n                         extrapolator=Extrapolator,\n                         extrapolator_args={\'right\': None, \'method\': \'Constant\', \'left\': None})\n\nLight Quality - ``colour.quality``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nColour Rendering Index\n**********************\n\n.. code-block:: python\n\n    >>> colour.colour_quality_scale(colour.ILLUMINANTS_SDS[\'FL2\'])\n    64.017283509280588\n    >>> colour.COLOUR_QUALITY_SCALE_METHODS\n    (\'NIST CQS 7.4\', \'NIST CQS 9.0\')\n\nColour Quality Scale\n********************\n\n.. code-block:: python\n\n    >>> colour.colour_rendering_index(colour.ILLUMINANTS_SDS[\'FL2\'])\n    64.151520202968015\n\nAcademy Spectral Similarity Index (SSI)\n***************************************\n\n.. code-block:: python\n\n    >>> colour.spectral_similarity_index(colour.ILLUMINANTS_SDS[\'C\'], colour.ILLUMINANTS_SDS[\'D65\'])\n    94.0\n\nSpectral Up-sampling & Reflectance Recovery - ``colour.recovery``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> colour.XYZ_to_sd([0.20654008, 0.12197225, 0.05136952])\n    SpectralDistribution([[  3.60000000e+02,   7.73462151e-02],\n                          [  3.65000000e+02,   7.73632975e-02],\n                          [  3.70000000e+02,   7.74299705e-02],\n                          ...\n                          [  8.20000000e+02,   3.93126353e-01],\n                          [  8.25000000e+02,   3.93158148e-01],\n                          [  8.30000000e+02,   3.93163548e-01]],\n                         interpolator=SpragueInterpolator,\n                         interpolator_args={},\n                         extrapolator=Extrapolator,\n                         extrapolator_args={\'right\': None, \'method\': \'Constant\', \'left\': None})\n\n    >>> sorted(colour.REFLECTANCE_RECOVERY_METHODS.keys())\n    [\'Meng 2015\', \'Smits 1999\']\n\nCorrelated Colour Temperature Computation Methods - ``colour.temperature``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> colour.uv_to_CCT([0.1978, 0.3122])\n    array([  6.50751282e+03,   3.22335875e-03])\n    >>> sorted(colour.UV_TO_CCT_METHODS.keys())\n    [\'Krystek 1985\', \'Ohno 2013\', \'Robertson 1968\', \'ohno2013\', \'robertson1968\']\n    >>> sorted(colour.XY_TO_CCT_METHODS.keys())\n    [\'CIE Illuminant D Series\', \'Hernandez 1999\', \'Kang 2002\', \'McCamy 1992\', \'daylight\', \'hernandez1999\', \'kang2002\', \'mccamy1992\']\n\nColour Volume - ``colour.volume``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code-block:: python\n\n    >>> colour.RGB_colourspace_volume_MonteCarlo(colour.RGB_COLOURSPACE[\'sRGB\'])\n    821958.30000000005\n\nPlotting - ``colour.plotting``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nMost of the objects are available from the ``colour.plotting`` namespace:\n\n.. code-block:: python\n\n    >>> from colour.plotting import *\n    >>> colour_style()\n\nVisible Spectrum\n****************\n\n.. code-block:: python\n\n    >>> plot_visible_spectrum(\'CIE 1931 2 Degree Standard Observer\')\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Visible_Spectrum.png\n\nSpectral Distribution\n*********************\n\n.. code-block:: python\n\n    >>> plot_single_illuminant_sd(\'FL1\')\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Illuminant_F1_SD.png\n\nBlackbody\n*********\n\n.. code-block:: python\n\n    >>> blackbody_sds = [\n    ...     colour.sd_blackbody(i, colour.SpectralShape(0, 10000, 10))\n    ...     for i in range(1000, 15000, 1000)\n    ... ]\n    >>> plot_multi_sds(\n    ...     blackbody_sds,\n    ...     y_label=\'W / (sr m$^2$) / m\',\n    ...     use_sds_colours=True,\n    ...     normalise_sds_colours=True,\n    ...     legend_location=\'upper right\',\n    ...     bounding_box=(0, 1250, 0, 2.5e15))\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Blackbodies.png\n\nColour Matching Functions\n*************************\n\n.. code-block:: python\n\n    >>> plot_single_cmfs(\n    ...     \'Stockman & Sharpe 2 Degree Cone Fundamentals\',\n    ...     y_label=\'Sensitivity\',\n    ...     bounding_box=(390, 870, 0, 1.1))\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Cone_Fundamentals.png\n\nLuminous Efficiency\n*******************\n\n.. code-block:: python\n\n    >>> sd_mesopic_luminous_efficiency_function = (\n    ...     colour.sd_mesopic_luminous_efficiency_function(0.2))\n    >>> plot_multi_sds(\n    ...     (sd_mesopic_luminous_efficiency_function,\n    ...      colour.PHOTOPIC_LEFS[\'CIE 1924 Photopic Standard Observer\'],\n    ...      colour.SCOTOPIC_LEFS[\'CIE 1951 Scotopic Standard Observer\']),\n    ...     y_label=\'Luminous Efficiency\',\n    ...     legend_location=\'upper right\',\n    ...     y_tighten=True,\n    ...     margins=(0, 0, 0, .1))\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Luminous_Efficiency.png\n\nColour Checker\n**************\n\n.. code-block:: python\n\n    >>> from colour.characterisation.dataset.colour_checkers.sds import (\n    ...     COLOURCHECKER_INDEXES_TO_NAMES_MAPPING)\n    >>> plot_multi_sds(\n    ...     [\n    ...         colour.COLOURCHECKERS_SDS[\'BabelColor Average\'][value]\n    ...         for key, value in sorted(\n    ...             COLOURCHECKER_INDEXES_TO_NAMES_MAPPING.items())\n    ...     ],\n    ...     use_sds_colours=True,\n    ...     title=(\'BabelColor Average - \'\n    ...            \'Spectral Distributions\'))\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_BabelColor_Average.png\n\n.. code-block:: python\n\n    >>> plot_single_colour_checker(\'ColorChecker 2005\', text_parameters={\'visible\': False})\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_ColorChecker_2005.png\n\nChromaticities Prediction\n*************************\n\n.. code-block:: python\n\n    >>> plot_corresponding_chromaticities_prediction(2, \'Von Kries\', \'Bianco\')\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Chromaticities_Prediction.png\n\nColour Temperature\n******************\n\n.. code-block:: python\n\n    >>> plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS([\'A\', \'B\', \'C\'])\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_CCT_CIE_1960_UCS_Chromaticity_Diagram.png\n\n\nChromaticities\n**************\n\n.. code-block:: python\n\n    >>> import numpy as np\n    >>> RGB = np.random.random((32, 32, 3))\n    >>> plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(\n    ...     RGB, \'ITU-R BT.709\', colourspaces=[\'ACEScg\', \'S-Gamut\', \'Pointer Gamut\'])\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_Chromaticities_CIE_1931_Chromaticity_Diagram.png\n\nColour Rendering Index\n**********************\n\n.. code-block:: python\n\n    >>> plot_single_sd_colour_rendering_index_bars(\n    ...     colour.ILLUMINANTS_SDS[\'FL2\'])\n\n..  image:: https://colour.readthedocs.io/en/develop/_images/Examples_Plotting_CRI.png\n\nContributing\n------------\n\nIf you would like to contribute to **Colour**, please refer to the following\n`Contributing <https://www.colour-science.org/contributing/>`__ guide.\n\nChanges\n-------\n\nThe changes are viewable on the `Releases <https://github.com/colour-science/colour/releases>`__ page.\n\nBibliography\n------------\n\nThe bibliography is available on the `Bibliography <https://www.colour-science.org/bibliography/>`__ page.\n\nIt is also viewable directly from the repository in\n`BibTeX <https://github.com/colour-science/colour/blob/develop/BIBLIOGRAPHY.bib>`__\nformat.\n\nSee Also\n--------\n\nHere is a list of notable colour science packages sorted by languages:\n\n**Python**\n\n- `Colorio <https://github.com/nschloe/colorio/>`__  by Schlömer, N.\n- `ColorPy <http://markkness.net/colorpy/ColorPy.html>`__ by Kness, M.\n- `Colorspacious <https://colorspacious.readthedocs.io/>`__ by Smith, N. J., et al.\n- `python-colormath <https://python-colormath.readthedocs.io/>`__ by Taylor, G., et al.\n\n**Go**\n\n- `go-colorful <https://github.com/lucasb-eyer/go-colorful/>`__  by Beyer, L., et al.\n\n**.NET**\n\n- `Colourful <https://github.com/tompazourek/Colourful>`__ by Pažourek, T., et al.\n\n**Julia**\n\n- `Colors.jl <https://github.com/JuliaGraphics/Colors.jl>`__ by Holy, T., et al.\n\n**Matlab & Octave**\n\n- `COLORLAB <https://www.uv.es/vista/vistavalencia/software/colorlab.html>`__ by Malo, J., et al.\n- `Psychtoolbox <http://psychtoolbox.org/>`__ by Brainard, D., et al.\n- `The Munsell and Kubelka-Munk Toolbox <http://www.munsellcolourscienceforpainters.com/MunsellAndKubelkaMunkToolbox/MunsellAndKubelkaMunkToolbox.html>`__ by Centore, P.\n\nCode of Conduct\n---------------\n\nThe *Code of Conduct*, adapted from the `Contributor Covenant 1.4 <https://www.contributor-covenant.org/version/1/4/code-of-conduct.html>`__,\nis available on the `Code of Conduct <https://www.colour-science.org/code-of-conduct/>`__ page.\n\n\n\nAbout\n-----\n\n| **Colour** by Colour Developers\n| Copyright © 2013-2020 – Colour Developers – `colour-developers@colour-science.org <colour-developers@colour-science.org>`__\n| This software is released under terms of New BSD License: https://opensource.org/licenses/BSD-3-Clause\n| `https://github.com/colour-science/colour <https://github.com/colour-science/colour>`__\n',
    'author': 'Colour Developers',
    'author_email': 'colour-developers@colour-science.org',
    'maintainer': 'Colour Developers',
    'maintainer_email': 'colour-developers@colour-science.org',
    'url': 'https://www.colour-science.org/',
    'package_dir': package_dir,
    'packages': packages,
    'package_data': package_data,
    'install_requires': install_requires,
    'extras_require': extras_require,
    'python_requires': '>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*',
}


setup(**setup_kwargs)
