コード例 #1
0
ファイル: test_common.py プロジェクト: colour-science/colour
    def test_sRGB_to_XYZ(self):
        """Test :func:`colour.models.rgb.common.sRGB_to_XYZ` definition."""

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.70573936, 0.19248266, 0.22354169])),
            np.array([0.20654290, 0.12197943, 0.05137140]),
            decimal=7,
        )

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.25847003, 0.58276102, 0.29718877])),
            np.array([0.14222582, 0.23043727, 0.10496290]),
            decimal=7,
        )

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.09838967, 0.25404426, 0.65130925]),
                np.array([0.34570, 0.35850]),
            ),
            np.array([0.07819162, 0.06157356, 0.28099475]),
            decimal=7,
        )

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.00000000, 0.00000000, 0.00000000]),
                np.array([0.44757, 0.40745]),
            ),
            np.array([0.00000000, 0.00000000, 0.00000000]),
            decimal=7,
        )

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.60873814, 0.23259548, 0.43714892]),
                np.array([0.44757, 0.40745]),
                chromatic_adaptation_transform="Bradford",
            ),
            np.array([0.20654449, 0.12197792, 0.05137030]),
            decimal=7,
        )

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.45620520, 0.03081070, 0.04091953]),
                apply_cctf_decoding=False,
            ),
            np.array([0.20654291, 0.12197943, 0.05137141]),
            decimal=7,
        )
コード例 #2
0
ファイル: test_common.py プロジェクト: yixw/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.rgb.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.70573936, 0.19248266, 0.22354169])),
            np.array([0.20654290, 0.12197943, 0.05137140]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.25847003, 0.58276102, 0.29718877])),
            np.array([0.14222582, 0.23043727, 0.10496290]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.09838967, 0.25404426, 0.65130925]),
                np.array([0.34570, 0.35850])),
            np.array([0.07819162, 0.06157356, 0.28099475]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.00000000, 0.00000000, 0.00000000]),
                np.array([0.44757, 0.40745])),
            np.array([0.00000000, 0.00000000, 0.00000000]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.17498172, 0.38818743, 0.32159978]),
                chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.45620520, 0.03081070, 0.04091953]),
                apply_cctf_decoding=False),
            np.array([0.20654291, 0.12197943, 0.05137141]),
            decimal=7)
コード例 #3
0
ファイル: test_common.py プロジェクト: colour-science/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.rgb.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.70573936, 0.19248266, 0.22354169])),
            np.array([0.20654290, 0.12197943, 0.05137140]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.25847003, 0.58276102, 0.29718877])),
            np.array([0.14222582, 0.23043727, 0.10496290]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.09838967, 0.25404426, 0.65130925]),
                np.array([0.34570, 0.35850])),
            np.array([0.07819162, 0.06157356, 0.28099475]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.00000000, 0.00000000, 0.00000000]),
                np.array([0.44757, 0.40745])),
            np.array([0.00000000, 0.00000000, 0.00000000]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.17498172, 0.38818743, 0.32159978]),
                chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(
                np.array([0.45620520, 0.03081070, 0.04091953]),
                apply_decoding_cctf=False),
            np.array([0.20654291, 0.12197943, 0.05137141]),
            decimal=7)
コード例 #4
0
ファイル: tests_common.py プロジェクト: nick-shaw/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.rgb.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17498172, 0.38818743, 0.32159978])),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.96979222, 0.48891569, 0.30231574])),
            np.array([0.47097710, 0.34950000, 0.11301649]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.00000000, 0.00000000, 0.00000000]),
                        np.array([0.44757, 0.40745])),
            np.array([0.00000000, 0.00000000, 0.00000000]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.48222001, 0.31654775, 0.22070353]),
                        np.array([0.31270, 0.32900])),
            np.array([0.11805834, 0.10340000, 0.05150892]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17498172, 0.38818743, 0.32159978]),
                        chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.02583795, 0.12473949, 0.08439296]),
                        apply_decoding_cctf=False),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)
コード例 #5
0
ファイル: tests_common.py プロジェクト: brehm/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17501358, 0.38818795, 0.32161955])),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.96984378, 0.48883420, 0.30229060])),
            np.array([0.47097710, 0.34950000, 0.11301649]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.00000000, 0.00000000, 0.00000000]),
                        np.array([0.44757, 0.40745])),
            np.array([0., 0., 0.]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.48224885, 0.31651974, 0.22070513]),
                        np.array([0.31271, 0.32902])),
            np.array([0.1180583421, 0.10340000, 0.0515089229]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17501358, 0.38818795, 0.32161955]),
                        chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.02584654, 0.12473983, 0.08440360]),
                        apply_EOCF=False),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)
コード例 #6
0
ファイル: tests_common.py プロジェクト: scooperly/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17501358, 0.38818795, 0.32161955])),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.96984378, 0.48883420, 0.30229060])),
            np.array([0.47097710, 0.34950000, 0.11301649]),
            decimal=7)

        np.testing.assert_almost_equal(sRGB_to_XYZ(
            np.array([0.00000000, 0.00000000, 0.00000000]),
            np.array([0.44757, 0.40745])),
                                       np.array([0., 0., 0.]),
                                       decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.48224885, 0.31651974, 0.22070513]),
                        np.array([0.31271, 0.32902])),
            np.array([0.1180583421, 0.10340000, 0.0515089229]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17501358, 0.38818795, 0.32161955]),
                        chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.02584654, 0.12473983, 0.08440360]),
                        apply_EOCF=False),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)
コード例 #7
0
ファイル: tests_common.py プロジェクト: Nick-Shaw/colour
    def test_sRGB_to_XYZ(self):
        """
        Tests :func:`colour.models.rgb.common.sRGB_to_XYZ` definition.
        """

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17498172, 0.38818743, 0.32159978])),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.96979222, 0.48891569, 0.30231574])),
            np.array([0.47097710, 0.34950000, 0.11301649]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.00000000, 0.00000000, 0.00000000]),
                        np.array([0.44757, 0.40745])),
            np.array([0.00000000, 0.00000000, 0.00000000]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.48222001, 0.31654775, 0.22070353]),
                        np.array([0.31270, 0.32900])),
            np.array([0.11805834, 0.10340000, 0.05150892]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.17498172, 0.38818743, 0.32159978]),
                        chromatic_adaptation_method='Bradford'),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)

        np.testing.assert_almost_equal(
            sRGB_to_XYZ(np.array([0.02583795, 0.12473949, 0.08439296]),
                        apply_decoding_cctf=False),
            np.array([0.07049534, 0.10080000, 0.09558313]),
            decimal=7)
コード例 #8
0
ファイル: generate_plots.py プロジェクト: yixw/colour
def generate_documentation_plots(output_directory):
    """
    Generates documentation plots.

    Parameters
    ----------
    output_directory : unicode
        Output directory.
    """

    filter_warnings()

    colour_style()

    np.random.seed(0)

    # *************************************************************************
    # "README.rst"
    # *************************************************************************
    filename = os.path.join(output_directory,
                            'Examples_Colour_Automatic_Conversion_Graph.png')
    plot_automatic_colour_conversion_graph(filename)

    arguments = {
        'tight_layout':
        True,
        'transparent_background':
        True,
        'filename':
        os.path.join(output_directory,
                     'Examples_Plotting_Visible_Spectrum.png')
    }
    plt.close(
        plot_visible_spectrum('CIE 1931 2 Degree Standard Observer',
                              **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_Illuminant_F1_SD.png')
    plt.close(plot_single_illuminant_sd('FL1', **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Examples_Plotting_Blackbodies.png')
    blackbody_sds = [
        sd_blackbody(i, SpectralShape(0, 10000, 10))
        for i in range(1000, 15000, 1000)
    ]
    plt.close(
        plot_multi_sds(blackbody_sds,
                       y_label='W / (sr m$^2$) / m',
                       use_sds_colours=True,
                       normalise_sds_colours=True,
                       legend_location='upper right',
                       bounding_box=(0, 1250, 0, 2.5e15),
                       **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_Cone_Fundamentals.png')
    plt.close(
        plot_single_cmfs('Stockman & Sharpe 2 Degree Cone Fundamentals',
                         y_label='Sensitivity',
                         bounding_box=(390, 870, 0, 1.1),
                         **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_Luminous_Efficiency.png')
    plt.close(
        plot_multi_sds((sd_mesopic_luminous_efficiency_function(0.2),
                        PHOTOPIC_LEFS['CIE 1924 Photopic Standard Observer'],
                        SCOTOPIC_LEFS['CIE 1951 Scotopic Standard Observer']),
                       y_label='Luminous Efficiency',
                       legend_location='upper right',
                       y_tighten=True,
                       margins=(0, 0, 0, .1),
                       **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_BabelColor_Average.png')
    plt.close(
        plot_multi_sds(COLOURCHECKERS_SDS['BabelColor Average'].values(),
                       use_sds_colours=True,
                       title=('BabelColor Average - '
                              'Spectral Distributions'),
                       **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_ColorChecker_2005.png')
    plt.close(
        plot_single_colour_checker('ColorChecker 2005',
                                   text_parameters={'visible': False},
                                   **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Examples_Plotting_Chromaticities_Prediction.png')
    plt.close(
        plot_corresponding_chromaticities_prediction(2, 'Von Kries', 'Bianco',
                                                     **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Examples_Plotting_CCT_CIE_1960_UCS_Chromaticity_Diagram.png')
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(
            ['A', 'B', 'C'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Examples_Plotting_Chromaticities_CIE_1931_Chromaticity_Diagram.png')
    RGB = np.random.random((32, 32, 3))
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
            RGB,
            'ITU-R BT.709',
            colourspaces=['ACEScg', 'S-Gamut'],
            show_pointer_gamut=True,
            **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Examples_Plotting_CRI.png')
    plt.close(
        plot_single_sd_colour_rendering_index_bars(ILLUMINANTS_SDS['FL2'],
                                                   **arguments)[0])

    # *************************************************************************
    # Documentation
    # *************************************************************************
    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_CVD_Simulation_Machado2009.png')
    plt.close(plot_cvd_simulation_Machado2009(RGB, **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Colour_Checker.png')
    plt.close(plot_single_colour_checker('ColorChecker 2005', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Colour_Checkers.png')
    plt.close(
        plot_multi_colour_checkers(['ColorChecker 1976', 'ColorChecker 2005'],
                                   **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Single_SD.png')
    data = {
        500: 0.0651,
        520: 0.0705,
        540: 0.0772,
        560: 0.0870,
        580: 0.1128,
        600: 0.1360
    }
    sd = SpectralDistribution(data, name='Custom')
    plt.close(plot_single_sd(sd, **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Multi_SDS.png')
    data_1 = {
        500: 0.004900,
        510: 0.009300,
        520: 0.063270,
        530: 0.165500,
        540: 0.290400,
        550: 0.433450,
        560: 0.594500
    }
    data_2 = {
        500: 0.323000,
        510: 0.503000,
        520: 0.710000,
        530: 0.862000,
        540: 0.954000,
        550: 0.994950,
        560: 0.995000
    }
    spd1 = SpectralDistribution(data_1, name='Custom 1')
    spd2 = SpectralDistribution(data_2, name='Custom 2')
    plt.close(plot_multi_sds([spd1, spd2], **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Single_CMFS.png')
    plt.close(
        plot_single_cmfs('CIE 1931 2 Degree Standard Observer',
                         **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Multi_CMFS.png')
    cmfs = ('CIE 1931 2 Degree Standard Observer',
            'CIE 1964 10 Degree Standard Observer')
    plt.close(plot_multi_cmfs(cmfs, **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Illuminant_SD.png')
    plt.close(plot_single_illuminant_sd('A', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Illuminant_SDS.png')
    plt.close(plot_multi_illuminant_sds(['A', 'B', 'C'], **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Visible_Spectrum.png')
    plt.close(plot_visible_spectrum(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Lightness_Function.png')
    plt.close(plot_single_lightness_function('CIE 1976', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Lightness_Functions.png')
    plt.close(
        plot_multi_lightness_functions(['CIE 1976', 'Wyszecki 1963'],
                                       **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Luminance_Function.png')
    plt.close(plot_single_luminance_function('CIE 1976', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Luminance_Functions.png')
    plt.close(
        plot_multi_luminance_functions(['CIE 1976', 'Newhall 1943'],
                                       **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Blackbody_Spectral_Radiance.png')
    plt.close(
        plot_blackbody_spectral_radiance(3500,
                                         blackbody='VY Canis Major',
                                         **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Blackbody_Colours.png')
    plt.close(
        plot_blackbody_colours(SpectralShape(150, 12500, 50), **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Colour_Swatch.png')
    RGB = ColourSwatch(RGB=(0.45620519, 0.03081071, 0.04091952))
    plt.close(plot_single_colour_swatch(RGB, **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Colour_Swatches.png')
    RGB_1 = ColourSwatch(RGB=(0.45293517, 0.31732158, 0.26414773))
    RGB_2 = ColourSwatch(RGB=(0.77875824, 0.57726450, 0.50453169))
    plt.close(plot_multi_colour_swatches([RGB_1, RGB_2], **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Single_Function.png')
    plt.close(plot_single_function(lambda x: x**(1 / 2.2), **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Multi_Functions.png')
    functions = {
        'Gamma 2.2': lambda x: x**(1 / 2.2),
        'Gamma 2.4': lambda x: x**(1 / 2.4),
        'Gamma 2.6': lambda x: x**(1 / 2.6),
    }
    plt.close(plot_multi_functions(functions, **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Image.png')
    path = os.path.join(output_directory, 'Logo_Medium_001.png')
    plt.close(plot_image(read_image(str(path)), **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Corresponding_Chromaticities_Prediction.png')
    plt.close(
        plot_corresponding_chromaticities_prediction(1, 'Von Kries', 'CAT02',
                                                     **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Spectral_Locus.png')
    plt.close(
        plot_spectral_locus(spectral_locus_colours='RGB', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Chromaticity_Diagram_Colours.png')
    plt.close(plot_chromaticity_diagram_colours(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Chromaticity_Diagram.png')
    plt.close(plot_chromaticity_diagram(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Chromaticity_Diagram_CIE1931.png')
    plt.close(plot_chromaticity_diagram_CIE1931(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(plot_chromaticity_diagram_CIE1960UCS(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Chromaticity_Diagram_CIE1976UCS.png')
    plt.close(plot_chromaticity_diagram_CIE1976UCS(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_SDS_In_Chromaticity_Diagram.png')
    A = ILLUMINANTS_SDS['A']
    D65 = ILLUMINANTS_SDS['D65']
    plt.close(plot_sds_in_chromaticity_diagram([A, D65], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1931.png')
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1931([A, D65], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1960UCS([A, D65], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1976UCS.png')
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1976UCS([A, D65], **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Pointer_Gamut.png')
    plt.close(plot_pointer_gamut(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_RGB_Colourspaces_In_Chromaticity_Diagram.png')
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram(
            ['ITU-R BT.709', 'ACEScg', 'S-Gamut'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_RGB_Colourspaces_In_Chromaticity_Diagram_CIE1931.png')
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931(
            ['ITU-R BT.709', 'ACEScg', 'S-Gamut'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Colourspaces_In_'
        'Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS(
            ['ITU-R BT.709', 'ACEScg', 'S-Gamut'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Colourspaces_In_'
        'Chromaticity_Diagram_CIE1976UCS.png')
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS(
            ['ITU-R BT.709', 'ACEScg', 'S-Gamut'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Chromaticities_In_'
        'Chromaticity_Diagram.png')
    RGB = np.random.random((128, 128, 3))
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram(
            RGB, 'ITU-R BT.709', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Chromaticities_In_'
        'Chromaticity_Diagram_CIE1931.png')
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
            RGB, 'ITU-R BT.709', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Chromaticities_In_'
        'Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS(
            RGB, 'ITU-R BT.709', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Chromaticities_In_'
        'Chromaticity_Diagram_CIE1976UCS.png')
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS(
            RGB, 'ITU-R BT.709', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram.png')
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Ellipses_MacAdam1942_In_'
        'Chromaticity_Diagram_CIE1931.png')
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931(
            **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Ellipses_MacAdam1942_In_'
        'Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS(
            **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Ellipses_MacAdam1942_In_'
        'Chromaticity_Diagram_CIE1976UCS.png')
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS(
            **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Single_CCTF.png')
    plt.close(plot_single_cctf('ITU-R BT.709', **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Multi_CCTFs.png')
    plt.close(plot_multi_cctfs(['ITU-R BT.709', 'sRGB'], **arguments)[0])

    data = np.array([
        [
            None,
            np.array([0.95010000, 1.00000000, 1.08810000]),
            np.array([0.40920000, 0.28120000, 0.30600000]),
            np.array([
                [0.02495100, 0.01908600, 0.02032900],
                [0.10944300, 0.06235900, 0.06788100],
                [0.27186500, 0.18418700, 0.19565300],
                [0.48898900, 0.40749400, 0.44854600],
            ]),
            None,
        ],
        [
            None,
            np.array([0.95010000, 1.00000000, 1.08810000]),
            np.array([0.30760000, 0.48280000, 0.42770000]),
            np.array([
                [0.02108000, 0.02989100, 0.02790400],
                [0.06194700, 0.11251000, 0.09334400],
                [0.15255800, 0.28123300, 0.23234900],
                [0.34157700, 0.56681300, 0.47035300],
            ]),
            None,
        ],
        [
            None,
            np.array([0.95010000, 1.00000000, 1.08810000]),
            np.array([0.39530000, 0.28120000, 0.18450000]),
            np.array([
                [0.02436400, 0.01908600, 0.01468800],
                [0.10331200, 0.06235900, 0.02854600],
                [0.26311900, 0.18418700, 0.12109700],
                [0.43158700, 0.40749400, 0.39008600],
            ]),
            None,
        ],
        [
            None,
            np.array([0.95010000, 1.00000000, 1.08810000]),
            np.array([0.20510000, 0.18420000, 0.57130000]),
            np.array([
                [0.03039800, 0.02989100, 0.06123300],
                [0.08870000, 0.08498400, 0.21843500],
                [0.18405800, 0.18418700, 0.40111400],
                [0.32550100, 0.34047200, 0.50296900],
                [0.53826100, 0.56681300, 0.80010400],
            ]),
            None,
        ],
        [
            None,
            np.array([0.95010000, 1.00000000, 1.08810000]),
            np.array([0.35770000, 0.28120000, 0.11250000]),
            np.array([
                [0.03678100, 0.02989100, 0.01481100],
                [0.17127700, 0.11251000, 0.01229900],
                [0.30080900, 0.28123300, 0.21229800],
                [0.52976000, 0.40749400, 0.11720000],
            ]),
            None,
        ],
    ])
    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Constant_Hue_Loci.png')
    plt.close(plot_constant_hue_loci(data, 'IPT', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_Munsell_Value_Function.png')
    plt.close(plot_single_munsell_value_function('ASTM D1535', **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Multi_Munsell_Value_Functions.png')
    plt.close(
        plot_multi_munsell_value_functions(['ASTM D1535', 'McCamy 1987'],
                                           **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Single_SD_Rayleigh_Scattering.png')
    plt.close(plot_single_sd_rayleigh_scattering(**arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_The_Blue_Sky.png')
    plt.close(plot_the_blue_sky(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Colour_Quality_Bars.png')
    illuminant = ILLUMINANTS_SDS['FL2']
    light_source = LIGHT_SOURCES_SDS['Kinoton 75P']
    light_source = light_source.copy().align(SpectralShape(360, 830, 1))
    cqs_i = colour_quality_scale(illuminant, additional_data=True)
    cqs_l = colour_quality_scale(light_source, additional_data=True)
    plt.close(plot_colour_quality_bars([cqs_i, cqs_l], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Single_SD_Colour_Rendering_Index_Bars.png')
    illuminant = ILLUMINANTS_SDS['FL2']
    plt.close(
        plot_single_sd_colour_rendering_index_bars(illuminant, **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Multi_SDS_Colour_Rendering_Indexes_Bars.png')
    light_source = LIGHT_SOURCES_SDS['Kinoton 75P']
    plt.close(
        plot_multi_sds_colour_rendering_indexes_bars(
            [illuminant, light_source], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Single_SD_Colour_Quality_Scale_Bars.png')
    illuminant = ILLUMINANTS_SDS['FL2']
    plt.close(
        plot_single_sd_colour_quality_scale_bars(illuminant, **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Multi_SDS_Colour_Quality_Scales_Bars.png')
    light_source = LIGHT_SOURCES_SDS['Kinoton 75P']
    plt.close(
        plot_multi_sds_colour_quality_scales_bars([illuminant, light_source],
                                                  **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_Planckian_Locus.png')
    plt.close(plot_planckian_locus(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Planckian_Locus_CIE1931.png')
    plt.close(plot_planckian_locus_CIE1931(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_Planckian_Locus_CIE1960UCS.png')
    plt.close(plot_planckian_locus_CIE1960UCS(**arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram.png')
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram(['A', 'B', 'C'],
                                                     **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram_CIE1931.png')
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1931(['A', 'B', 'C'],
                                                             **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory,
        'Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram_CIE1960UCS.png')
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(
            ['A', 'B', 'C'], **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Colourspaces_Gamuts.png')
    plt.close(
        plot_RGB_colourspaces_gamuts(['ITU-R BT.709', 'ACEScg', 'S-Gamut'],
                                     **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Plotting_Plot_RGB_Colourspaces_Gamuts.png')
    plt.close(
        plot_RGB_colourspaces_gamuts(['ITU-R BT.709', 'ACEScg', 'S-Gamut'],
                                     **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Plotting_Plot_RGB_Scatter.png')
    plt.close(plot_RGB_scatter(RGB, 'ITU-R BT.709', **arguments)[0])

    filename = os.path.join(
        output_directory,
        'Plotting_Plot_Colour_Automatic_Conversion_Graph.png')
    plot_automatic_colour_conversion_graph(filename)

    # *************************************************************************
    # "tutorial.rst"
    # *************************************************************************
    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_Visible_Spectrum.png')
    plt.close(plot_visible_spectrum(**arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_Sample_SD.png')
    sample_sd_data = {
        380: 0.048,
        385: 0.051,
        390: 0.055,
        395: 0.060,
        400: 0.065,
        405: 0.068,
        410: 0.068,
        415: 0.067,
        420: 0.064,
        425: 0.062,
        430: 0.059,
        435: 0.057,
        440: 0.055,
        445: 0.054,
        450: 0.053,
        455: 0.053,
        460: 0.052,
        465: 0.052,
        470: 0.052,
        475: 0.053,
        480: 0.054,
        485: 0.055,
        490: 0.057,
        495: 0.059,
        500: 0.061,
        505: 0.062,
        510: 0.065,
        515: 0.067,
        520: 0.070,
        525: 0.072,
        530: 0.074,
        535: 0.075,
        540: 0.076,
        545: 0.078,
        550: 0.079,
        555: 0.082,
        560: 0.087,
        565: 0.092,
        570: 0.100,
        575: 0.107,
        580: 0.115,
        585: 0.122,
        590: 0.129,
        595: 0.134,
        600: 0.138,
        605: 0.142,
        610: 0.146,
        615: 0.150,
        620: 0.154,
        625: 0.158,
        630: 0.163,
        635: 0.167,
        640: 0.173,
        645: 0.180,
        650: 0.188,
        655: 0.196,
        660: 0.204,
        665: 0.213,
        670: 0.222,
        675: 0.231,
        680: 0.242,
        685: 0.251,
        690: 0.261,
        695: 0.271,
        700: 0.282,
        705: 0.294,
        710: 0.305,
        715: 0.318,
        720: 0.334,
        725: 0.354,
        730: 0.372,
        735: 0.392,
        740: 0.409,
        745: 0.420,
        750: 0.436,
        755: 0.450,
        760: 0.462,
        765: 0.465,
        770: 0.448,
        775: 0.432,
        780: 0.421
    }

    sd = SpectralDistribution(sample_sd_data, name='Sample')
    plt.close(plot_single_sd(sd, **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_SD_Interpolation.png')
    sd_copy = sd.copy()
    sd_copy.interpolate(SpectralShape(400, 770, 1))
    plt.close(
        plot_multi_sds([sd, sd_copy],
                       bounding_box=[730, 780, 0.25, 0.5],
                       **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_Sample_Swatch.png')
    sd = SpectralDistribution(sample_sd_data)
    cmfs = STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer']
    illuminant = ILLUMINANTS_SDS['D65']
    with domain_range_scale('1'):
        XYZ = sd_to_XYZ(sd, cmfs, illuminant)
        RGB = XYZ_to_sRGB(XYZ)
    plt.close(
        plot_single_colour_swatch(ColourSwatch('Sample', RGB),
                                  text_parameters={'size': 'x-large'},
                                  **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_Neutral5.png')
    patch_name = 'neutral 5 (.70 D)'
    patch_sd = COLOURCHECKERS_SDS['ColorChecker N Ohta'][patch_name]
    with domain_range_scale('1'):
        XYZ = sd_to_XYZ(patch_sd, cmfs, illuminant)
        RGB = XYZ_to_sRGB(XYZ)
    plt.close(
        plot_single_colour_swatch(ColourSwatch(patch_name.title(), RGB),
                                  text_parameters={'size': 'x-large'},
                                  **arguments)[0])

    arguments['filename'] = os.path.join(output_directory,
                                         'Tutorial_Colour_Checker.png')
    plt.close(
        plot_single_colour_checker(colour_checker='ColorChecker 2005',
                                   text_parameters={'visible': False},
                                   **arguments)[0])

    arguments['filename'] = os.path.join(
        output_directory, 'Tutorial_CIE_1931_Chromaticity_Diagram.png')
    xy = XYZ_to_xy(XYZ)
    plot_chromaticity_diagram_CIE1931(standalone=False)
    x, y = xy
    plt.plot(x, y, 'o-', color='white')
    # Annotating the plot.
    plt.annotate(patch_sd.name.title(),
                 xy=xy,
                 xytext=(-50, 30),
                 textcoords='offset points',
                 arrowprops=dict(arrowstyle='->',
                                 connectionstyle='arc3, rad=-0.2'))
    plt.close(
        render(standalone=True,
               limits=(-0.1, 0.9, -0.1, 0.9),
               x_tighten=True,
               y_tighten=True,
               **arguments)[0])

    # *************************************************************************
    # "basics.rst"
    # *************************************************************************
    arguments['filename'] = os.path.join(output_directory,
                                         'Basics_Logo_Small_001_CIE_XYZ.png')
    RGB = read_image(os.path.join(output_directory, 'Logo_Small_001.png'))[...,
                                                                           0:3]
    XYZ = sRGB_to_XYZ(RGB)
    plt.close(
        plot_image(XYZ, text_parameters={'text': 'sRGB to XYZ'},
                   **arguments)[0])
コード例 #9
0
def generate_documentation_plots(output_directory: str):
    """
    Generate documentation plots.

    Parameters
    ----------
    output_directory
        Output directory.
    """

    filter_warnings()

    colour_style()

    np.random.seed(0)

    # *************************************************************************
    # "README.rst"
    # *************************************************************************
    filename = os.path.join(
        output_directory, "Examples_Colour_Automatic_Conversion_Graph.png"
    )
    plot_automatic_colour_conversion_graph(filename)

    arguments = {
        "tight_layout": True,
        "transparent_background": True,
        "filename": os.path.join(
            output_directory, "Examples_Plotting_Visible_Spectrum.png"
        ),
    }
    plt.close(
        plot_visible_spectrum(
            "CIE 1931 2 Degree Standard Observer", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Illuminant_F1_SD.png"
    )
    plt.close(plot_single_illuminant_sd("FL1", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Blackbodies.png"
    )
    blackbody_sds = [
        sd_blackbody(i, SpectralShape(0, 10000, 10))
        for i in range(1000, 15000, 1000)
    ]
    plt.close(
        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),
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Cone_Fundamentals.png"
    )
    plt.close(
        plot_single_cmfs(
            "Stockman & Sharpe 2 Degree Cone Fundamentals",
            y_label="Sensitivity",
            bounding_box=(390, 870, 0, 1.1),
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Luminous_Efficiency.png"
    )
    plt.close(
        plot_multi_sds(
            (
                sd_mesopic_luminous_efficiency_function(0.2),
                SDS_LEFS_PHOTOPIC["CIE 1924 Photopic Standard Observer"],
                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),
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_BabelColor_Average.png"
    )
    plt.close(
        plot_multi_sds(
            SDS_COLOURCHECKERS["BabelColor Average"].values(),
            plot_kwargs={"use_sd_colours": True},
            title=("BabelColor Average - " "Spectral Distributions"),
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_ColorChecker_2005.png"
    )
    plt.close(
        plot_single_colour_checker(
            "ColorChecker 2005", text_kwargs={"visible": False}, **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Chromaticities_Prediction.png"
    )
    plt.close(
        plot_corresponding_chromaticities_prediction(
            2, "Von Kries", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Examples_Plotting_Chromaticities_CIE_1931_Chromaticity_Diagram.png",
    )
    RGB = np.random.random((32, 32, 3))
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
            RGB,
            "ITU-R BT.709",
            colourspaces=["ACEScg", "S-Gamut"],
            show_pointer_gamut=True,
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_CRI.png"
    )
    plt.close(
        plot_single_sd_colour_rendering_index_bars(
            SDS_ILLUMINANTS["FL2"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Colour_Rendition_Report.png"
    )
    plt.close(
        plot_single_sd_colour_rendition_report(
            SDS_ILLUMINANTS["FL2"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Plot_Visible_Spectrum_Section.png"
    )
    plt.close(
        plot_visible_spectrum_section(
            section_colours="RGB", section_opacity=0.15, **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Examples_Plotting_Plot_RGB_Colourspace_Section.png"
    )
    plt.close(
        plot_RGB_colourspace_section(
            "sRGB", section_colours="RGB", section_opacity=0.15, **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Examples_Plotting_CCT_CIE_1960_UCS_Chromaticity_Diagram.png",
    )
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(
            ["A", "B", "C"], **arguments
        )[0]
    )

    # *************************************************************************
    # Documentation
    # *************************************************************************
    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_CVD_Simulation_Machado2009.png"
    )
    plt.close(plot_cvd_simulation_Machado2009(RGB, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Colour_Checker.png"
    )
    plt.close(plot_single_colour_checker("ColorChecker 2005", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Colour_Checkers.png"
    )
    plt.close(
        plot_multi_colour_checkers(
            ["ColorChecker 1976", "ColorChecker 2005"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_SD.png"
    )
    data = {
        500: 0.0651,
        520: 0.0705,
        540: 0.0772,
        560: 0.0870,
        580: 0.1128,
        600: 0.1360,
    }
    sd = SpectralDistribution(data, name="Custom")
    plt.close(plot_single_sd(sd, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_SDS.png"
    )
    data_1 = {
        500: 0.004900,
        510: 0.009300,
        520: 0.063270,
        530: 0.165500,
        540: 0.290400,
        550: 0.433450,
        560: 0.594500,
    }
    data_2 = {
        500: 0.323000,
        510: 0.503000,
        520: 0.710000,
        530: 0.862000,
        540: 0.954000,
        550: 0.994950,
        560: 0.995000,
    }
    spd1 = SpectralDistribution(data_1, name="Custom 1")
    spd2 = SpectralDistribution(data_2, name="Custom 2")
    plt.close(plot_multi_sds([spd1, spd2], **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_CMFS.png"
    )
    plt.close(
        plot_single_cmfs("CIE 1931 2 Degree Standard Observer", **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_CMFS.png"
    )
    cmfs = (
        "CIE 1931 2 Degree Standard Observer",
        "CIE 1964 10 Degree Standard Observer",
    )
    plt.close(plot_multi_cmfs(cmfs, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Illuminant_SD.png"
    )
    plt.close(plot_single_illuminant_sd("A", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Illuminant_SDS.png"
    )
    plt.close(plot_multi_illuminant_sds(["A", "B", "C"], **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Visible_Spectrum.png"
    )
    plt.close(plot_visible_spectrum(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Lightness_Function.png"
    )
    plt.close(plot_single_lightness_function("CIE 1976", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Lightness_Functions.png"
    )
    plt.close(
        plot_multi_lightness_functions(
            ["CIE 1976", "Wyszecki 1963"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Luminance_Function.png"
    )
    plt.close(plot_single_luminance_function("CIE 1976", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Luminance_Functions.png"
    )
    plt.close(
        plot_multi_luminance_functions(
            ["CIE 1976", "Newhall 1943"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Blackbody_Spectral_Radiance.png"
    )
    plt.close(
        plot_blackbody_spectral_radiance(
            3500, blackbody="VY Canis Major", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Blackbody_Colours.png"
    )
    plt.close(
        plot_blackbody_colours(SpectralShape(150, 12500, 50), **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Colour_Swatch.png"
    )
    RGB = ColourSwatch((0.45620519, 0.03081071, 0.04091952))
    plt.close(plot_single_colour_swatch(RGB, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Colour_Swatches.png"
    )
    RGB_1 = ColourSwatch((0.45293517, 0.31732158, 0.26414773))
    RGB_2 = ColourSwatch((0.77875824, 0.57726450, 0.50453169))
    plt.close(plot_multi_colour_swatches([RGB_1, RGB_2], **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Function.png"
    )
    plt.close(plot_single_function(lambda x: x ** (1 / 2.2), **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Functions.png"
    )
    functions = {
        "Gamma 2.2": lambda x: x ** (1 / 2.2),
        "Gamma 2.4": lambda x: x ** (1 / 2.4),
        "Gamma 2.6": lambda x: x ** (1 / 2.6),
    }
    plt.close(plot_multi_functions(functions, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Image.png"
    )
    path = os.path.join(
        colour.__path__[0],
        "examples",
        "plotting",
        "resources",
        "Ishihara_Colour_Blindness_Test_Plate_3.png",
    )
    plt.close(plot_image(read_image(str(path)), **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Corresponding_Chromaticities_Prediction.png",
    )
    plt.close(
        plot_corresponding_chromaticities_prediction(
            1, "Von Kries", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Spectral_Locus.png"
    )
    plt.close(
        plot_spectral_locus(spectral_locus_colours="RGB", **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Chromaticity_Diagram_Colours.png"
    )
    plt.close(
        plot_chromaticity_diagram_colours(diagram_colours="RGB", **arguments)[
            0
        ]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Chromaticity_Diagram.png"
    )
    plt.close(plot_chromaticity_diagram(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Chromaticity_Diagram_CIE1931.png"
    )
    plt.close(plot_chromaticity_diagram_CIE1931(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Chromaticity_Diagram_CIE1960UCS.png"
    )
    plt.close(plot_chromaticity_diagram_CIE1960UCS(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Chromaticity_Diagram_CIE1976UCS.png"
    )
    plt.close(plot_chromaticity_diagram_CIE1976UCS(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_SDS_In_Chromaticity_Diagram.png"
    )
    A = SDS_ILLUMINANTS["A"]
    D65 = SDS_ILLUMINANTS["D65"]
    plt.close(plot_sds_in_chromaticity_diagram([A, D65], **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1931.png",
    )
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1931([A, D65], **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1960UCS.png",
    )
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1960UCS([A, D65], **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_SDS_In_Chromaticity_Diagram_CIE1976UCS.png",
    )
    plt.close(
        plot_sds_in_chromaticity_diagram_CIE1976UCS([A, D65], **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Pointer_Gamut.png"
    )
    plt.close(plot_pointer_gamut(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Colourspaces_In_Chromaticity_Diagram.png",
    )
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Colourspaces_In_Chromaticity_Diagram_CIE1931.png",
    )
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1931(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Colourspaces_In_"
        "Chromaticity_Diagram_CIE1960UCS.png",
    )
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1960UCS(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Colourspaces_In_"
        "Chromaticity_Diagram_CIE1976UCS.png",
    )
    plt.close(
        plot_RGB_colourspaces_in_chromaticity_diagram_CIE1976UCS(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Chromaticities_In_" "Chromaticity_Diagram.png",
    )
    RGB = np.random.random((128, 128, 3))
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram(
            RGB, "ITU-R BT.709", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Chromaticities_In_"
        "Chromaticity_Diagram_CIE1931.png",
    )
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
            RGB, "ITU-R BT.709", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Chromaticities_In_"
        "Chromaticity_Diagram_CIE1960UCS.png",
    )
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1960UCS(
            RGB, "ITU-R BT.709", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_RGB_Chromaticities_In_"
        "Chromaticity_Diagram_CIE1976UCS.png",
    )
    plt.close(
        plot_RGB_chromaticities_in_chromaticity_diagram_CIE1976UCS(
            RGB, "ITU-R BT.709", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Ellipses_MacAdam1942_In_Chromaticity_Diagram.png",
    )
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram(**arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Ellipses_MacAdam1942_In_"
        "Chromaticity_Diagram_CIE1931.png",
    )
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1931(**arguments)[
            0
        ]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Ellipses_MacAdam1942_In_"
        "Chromaticity_Diagram_CIE1960UCS.png",
    )
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1960UCS(
            **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Ellipses_MacAdam1942_In_"
        "Chromaticity_Diagram_CIE1976UCS.png",
    )
    plt.close(
        plot_ellipses_MacAdam1942_in_chromaticity_diagram_CIE1976UCS(
            **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_CCTF.png"
    )
    plt.close(plot_single_cctf("ITU-R BT.709", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_CCTFs.png"
    )
    plt.close(plot_multi_cctfs(["ITU-R BT.709", "sRGB"], **arguments)[0])

    data = np.array(
        [
            [
                None,
                np.array([0.95010000, 1.00000000, 1.08810000]),
                np.array([0.40920000, 0.28120000, 0.30600000]),
                np.array(
                    [
                        [0.02495100, 0.01908600, 0.02032900],
                        [0.10944300, 0.06235900, 0.06788100],
                        [0.27186500, 0.18418700, 0.19565300],
                        [0.48898900, 0.40749400, 0.44854600],
                    ]
                ),
                None,
            ],
            [
                None,
                np.array([0.95010000, 1.00000000, 1.08810000]),
                np.array([0.30760000, 0.48280000, 0.42770000]),
                np.array(
                    [
                        [0.02108000, 0.02989100, 0.02790400],
                        [0.06194700, 0.11251000, 0.09334400],
                        [0.15255800, 0.28123300, 0.23234900],
                        [0.34157700, 0.56681300, 0.47035300],
                    ]
                ),
                None,
            ],
            [
                None,
                np.array([0.95010000, 1.00000000, 1.08810000]),
                np.array([0.39530000, 0.28120000, 0.18450000]),
                np.array(
                    [
                        [0.02436400, 0.01908600, 0.01468800],
                        [0.10331200, 0.06235900, 0.02854600],
                        [0.26311900, 0.18418700, 0.12109700],
                        [0.43158700, 0.40749400, 0.39008600],
                    ]
                ),
                None,
            ],
            [
                None,
                np.array([0.95010000, 1.00000000, 1.08810000]),
                np.array([0.20510000, 0.18420000, 0.57130000]),
                np.array(
                    [
                        [0.03039800, 0.02989100, 0.06123300],
                        [0.08870000, 0.08498400, 0.21843500],
                        [0.18405800, 0.18418700, 0.40111400],
                        [0.32550100, 0.34047200, 0.50296900],
                        [0.53826100, 0.56681300, 0.80010400],
                    ]
                ),
                None,
            ],
            [
                None,
                np.array([0.95010000, 1.00000000, 1.08810000]),
                np.array([0.35770000, 0.28120000, 0.11250000]),
                np.array(
                    [
                        [0.03678100, 0.02989100, 0.01481100],
                        [0.17127700, 0.11251000, 0.01229900],
                        [0.30080900, 0.28123300, 0.21229800],
                        [0.52976000, 0.40749400, 0.11720000],
                    ]
                ),
                None,
            ],
        ]
    )
    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Constant_Hue_Loci.png"
    )
    plt.close(plot_constant_hue_loci(data, "IPT", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_Munsell_Value_Function.png"
    )
    plt.close(plot_single_munsell_value_function("ASTM D1535", **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Multi_Munsell_Value_Functions.png"
    )
    plt.close(
        plot_multi_munsell_value_functions(
            ["ASTM D1535", "McCamy 1987"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Single_SD_Rayleigh_Scattering.png"
    )
    plt.close(plot_single_sd_rayleigh_scattering(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_The_Blue_Sky.png"
    )
    plt.close(plot_the_blue_sky(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Colour_Quality_Bars.png"
    )
    illuminant = SDS_ILLUMINANTS["FL2"]
    light_source = SDS_LIGHT_SOURCES["Kinoton 75P"]
    light_source = light_source.copy().align(SpectralShape(360, 830, 1))
    cqs_i = colour_quality_scale(illuminant, additional_data=True)
    cqs_l = colour_quality_scale(light_source, additional_data=True)
    plt.close(plot_colour_quality_bars([cqs_i, cqs_l], **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Single_SD_Colour_Rendering_Index_Bars.png",
    )
    illuminant = SDS_ILLUMINANTS["FL2"]
    plt.close(
        plot_single_sd_colour_rendering_index_bars(illuminant, **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Multi_SDS_Colour_Rendering_Indexes_Bars.png",
    )
    light_source = SDS_LIGHT_SOURCES["Kinoton 75P"]
    plt.close(
        plot_multi_sds_colour_rendering_indexes_bars(
            [illuminant, light_source], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Single_SD_Colour_Quality_Scale_Bars.png",
    )
    illuminant = SDS_ILLUMINANTS["FL2"]
    plt.close(
        plot_single_sd_colour_quality_scale_bars(illuminant, **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Multi_SDS_Colour_Quality_Scales_Bars.png",
    )
    light_source = SDS_LIGHT_SOURCES["Kinoton 75P"]
    plt.close(
        plot_multi_sds_colour_quality_scales_bars(
            [illuminant, light_source], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Hull_Section_Colours.png"
    )
    vertices, faces, _outline = primitive_cube(1, 1, 1, 64, 64, 64)
    XYZ_vertices = RGB_to_XYZ(
        vertices["position"] + 0.5,
        RGB_COLOURSPACE_sRGB.whitepoint,
        RGB_COLOURSPACE_sRGB.whitepoint,
        RGB_COLOURSPACE_sRGB.matrix_RGB_to_XYZ,
    )
    hull = trimesh.Trimesh(XYZ_vertices, faces, process=False)
    plt.close(
        plot_hull_section_colours(hull, section_colours="RGB", **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Hull_Section_Contour.png"
    )
    plt.close(
        plot_hull_section_contour(hull, section_colours="RGB", **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Visible_Spectrum_Section.png"
    )
    plt.close(
        plot_visible_spectrum_section(
            section_colours="RGB", section_opacity=0.15, **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_RGB_Colourspace_Section.png"
    )
    plt.close(
        plot_RGB_colourspace_section(
            "sRGB", section_colours="RGB", section_opacity=0.15, **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_Planckian_Locus.png"
    )
    plt.close(
        plot_planckian_locus(planckian_locus_colours="RGB", **arguments)[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram.png",
    )
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram(
            ["A", "B", "C"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram_CIE1931.png",
    )
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1931(
            ["A", "B", "C"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Planckian_Locus_In_Chromaticity_Diagram_CIE1960UCS.png",
    )
    plt.close(
        plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(
            ["A", "B", "C"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Single_SD_Colour_Rendition_Report_Full.png",
    )
    plt.close(
        plot_single_sd_colour_rendition_report(
            SDS_ILLUMINANTS["FL2"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Single_SD_Colour_Rendition_Report_Intermediate.png",
    )
    plt.close(
        plot_single_sd_colour_rendition_report(
            SDS_ILLUMINANTS["FL2"], "Intermediate", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory,
        "Plotting_Plot_Single_SD_Colour_Rendition_Report_Simple.png",
    )
    plt.close(
        plot_single_sd_colour_rendition_report(
            SDS_ILLUMINANTS["FL2"], "Simple", **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_RGB_Colourspaces_Gamuts.png"
    )
    plt.close(
        plot_RGB_colourspaces_gamuts(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_RGB_Colourspaces_Gamuts.png"
    )
    plt.close(
        plot_RGB_colourspaces_gamuts(
            ["ITU-R BT.709", "ACEScg", "S-Gamut"], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Plotting_Plot_RGB_Scatter.png"
    )
    plt.close(plot_RGB_scatter(RGB, "ITU-R BT.709", **arguments)[0])

    filename = os.path.join(
        output_directory, "Plotting_Plot_Colour_Automatic_Conversion_Graph.png"
    )
    plot_automatic_colour_conversion_graph(filename)

    # *************************************************************************
    # "tutorial.rst"
    # *************************************************************************
    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_Visible_Spectrum.png"
    )
    plt.close(plot_visible_spectrum(**arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_Sample_SD.png"
    )
    sample_sd_data = {
        380: 0.048,
        385: 0.051,
        390: 0.055,
        395: 0.060,
        400: 0.065,
        405: 0.068,
        410: 0.068,
        415: 0.067,
        420: 0.064,
        425: 0.062,
        430: 0.059,
        435: 0.057,
        440: 0.055,
        445: 0.054,
        450: 0.053,
        455: 0.053,
        460: 0.052,
        465: 0.052,
        470: 0.052,
        475: 0.053,
        480: 0.054,
        485: 0.055,
        490: 0.057,
        495: 0.059,
        500: 0.061,
        505: 0.062,
        510: 0.065,
        515: 0.067,
        520: 0.070,
        525: 0.072,
        530: 0.074,
        535: 0.075,
        540: 0.076,
        545: 0.078,
        550: 0.079,
        555: 0.082,
        560: 0.087,
        565: 0.092,
        570: 0.100,
        575: 0.107,
        580: 0.115,
        585: 0.122,
        590: 0.129,
        595: 0.134,
        600: 0.138,
        605: 0.142,
        610: 0.146,
        615: 0.150,
        620: 0.154,
        625: 0.158,
        630: 0.163,
        635: 0.167,
        640: 0.173,
        645: 0.180,
        650: 0.188,
        655: 0.196,
        660: 0.204,
        665: 0.213,
        670: 0.222,
        675: 0.231,
        680: 0.242,
        685: 0.251,
        690: 0.261,
        695: 0.271,
        700: 0.282,
        705: 0.294,
        710: 0.305,
        715: 0.318,
        720: 0.334,
        725: 0.354,
        730: 0.372,
        735: 0.392,
        740: 0.409,
        745: 0.420,
        750: 0.436,
        755: 0.450,
        760: 0.462,
        765: 0.465,
        770: 0.448,
        775: 0.432,
        780: 0.421,
    }

    sd = SpectralDistribution(sample_sd_data, name="Sample")
    plt.close(plot_single_sd(sd, **arguments)[0])

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_SD_Interpolation.png"
    )
    sd_copy = sd.copy()
    sd_copy.interpolate(SpectralShape(400, 770, 1))
    plt.close(
        plot_multi_sds(
            [sd, sd_copy], bounding_box=[730, 780, 0.25, 0.5], **arguments
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_Sample_Swatch.png"
    )
    sd = SpectralDistribution(sample_sd_data)
    cmfs = MSDS_CMFS_STANDARD_OBSERVER["CIE 1931 2 Degree Standard Observer"]
    illuminant = SDS_ILLUMINANTS["D65"]
    with domain_range_scale("1"):
        XYZ = sd_to_XYZ(sd, cmfs, illuminant)
        RGB = XYZ_to_sRGB(XYZ)
    plt.close(
        plot_single_colour_swatch(
            ColourSwatch(RGB, "Sample"),
            text_kwargs={"size": "x-large"},
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_Neutral5.png"
    )
    patch_name = "neutral 5 (.70 D)"
    patch_sd = SDS_COLOURCHECKERS["ColorChecker N Ohta"][patch_name]
    with domain_range_scale("1"):
        XYZ = sd_to_XYZ(patch_sd, cmfs, illuminant)
        RGB = XYZ_to_sRGB(XYZ)
    plt.close(
        plot_single_colour_swatch(
            ColourSwatch(RGB, patch_name.title()),
            text_kwargs={"size": "x-large"},
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_Colour_Checker.png"
    )
    plt.close(
        plot_single_colour_checker(
            colour_checker="ColorChecker 2005",
            text_kwargs={"visible": False},
            **arguments,
        )[0]
    )

    arguments["filename"] = os.path.join(
        output_directory, "Tutorial_CIE_1931_Chromaticity_Diagram.png"
    )
    xy = XYZ_to_xy(XYZ)
    plot_chromaticity_diagram_CIE1931(standalone=False)
    x, y = xy
    plt.plot(x, y, "o-", color="white")
    # Annotating the plot.
    plt.annotate(
        patch_sd.name.title(),
        xy=xy,
        xytext=(-50, 30),
        textcoords="offset points",
        arrowprops=dict(arrowstyle="->", connectionstyle="arc3, rad=-0.2"),
    )
    plt.close(
        render(
            standalone=True,
            limits=(-0.1, 0.9, -0.1, 0.9),
            x_tighten=True,
            y_tighten=True,
            **arguments,
        )[0]
    )

    # *************************************************************************
    # "basics.rst"
    # *************************************************************************
    arguments["filename"] = os.path.join(
        output_directory, "Basics_Logo_Small_001_CIE_XYZ.png"
    )
    RGB = read_image(os.path.join(output_directory, "Logo_Small_001.png"))[
        ..., 0:3
    ]
    XYZ = sRGB_to_XYZ(RGB)
    plt.close(
        plot_image(XYZ, text_kwargs={"text": "sRGB to XYZ"}, **arguments)[0]
    )