CIE 1931 color space.

cie_1931_color_space.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/Hasenpfote/fb262185313b0204893483add22d45a5/cie_1931_color_space.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "6aea5b40-8bee-46ca-bd17-ad1b9f4d2b25",
      "metadata": {
        "id": "6aea5b40-8bee-46ca-bd17-ad1b9f4d2b25"
      },
      "source": [
        "```python\n",
        "# Configure for google colab.\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "%cd \"drive/My Drive/Colab Notebooks/\"\n",
        "!pwd\n",
        "\n",
        "!pip install ipympl nb-mypy SciencePlots\n",
        "\n",
        "# Third-party Jupyter widgets\n",
        "from google.colab import output\n",
        "output.enable_custom_widget_manager()\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "c1c12b5c-bcd5-47f8-abad-f21a8c91ca63",
      "metadata": {
        "id": "c1c12b5c-bcd5-47f8-abad-f21a8c91ca63"
      },
      "source": [
        "[ipympl](https://github.com/matplotlib/ipympl)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9f3fcbef-24b4-45ad-a62f-26b9b1de1b7c",
      "metadata": {
        "id": "9f3fcbef-24b4-45ad-a62f-26b9b1de1b7c"
      },
      "outputs": [],
      "source": [
        "%matplotlib widget"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "4529a617-dc3a-4f71-b7ca-d2a598eee859",
      "metadata": {
        "id": "4529a617-dc3a-4f71-b7ca-d2a598eee859"
      },
      "source": [
        "[nb-mypy](https://pypi.org/project/nb-mypy/)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5ee2fc14-2b8d-4a5f-8221-2d5fa01f6e78",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5ee2fc14-2b8d-4a5f-8221-2d5fa01f6e78",
        "outputId": "d6cb877a-a13d-41c0-8de9-04f101203277"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Version 1.0.2\n",
            "INFO:nb-mypy:Version 1.0.2\n"
          ]
        }
      ],
      "source": [
        "%load_ext nb_mypy\n",
        "%nb_mypy On"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f004e296-3d8d-4647-a4bb-9d442b395376",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f004e296-3d8d-4647-a4bb-9d442b395376",
        "outputId": "4a46e3cb-5ca5-456e-dde8-689230dcfd3c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 3.7.15\n"
          ]
        }
      ],
      "source": [
        "!python --version"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9c012301-83f9-414e-a0b6-6239e4d40217",
      "metadata": {
        "id": "9c012301-83f9-414e-a0b6-6239e4d40217"
      },
      "outputs": [],
      "source": [
        "import functools\n",
        "import warnings\n",
        "\n",
        "import ipywidgets as widgets\n",
        "import matplotlib as mpl\n",
        "import matplotlib.patches as patches\n",
        "import matplotlib.patheffects as patheffects\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.ticker as ticker\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import scipy.integrate\n",
        "import scipy.interpolate\n",
        "import scipy.stats"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "41e4e142-d711-4cf8-a562-c06c107db1ee",
      "metadata": {
        "id": "41e4e142-d711-4cf8-a562-c06c107db1ee"
      },
      "outputs": [],
      "source": [
        "import types\n",
        "from dataclasses import InitVar, dataclass, field\n",
        "from typing import (\n",
        "    Any,\n",
        "    Dict,\n",
        "    Iterable,\n",
        "    Iterator,\n",
        "    List,\n",
        "    Optional,\n",
        "    Sequence,\n",
        "    Tuple,\n",
        "    Type,\n",
        "    Union,\n",
        ")\n",
        "\n",
        "import numpy.typing as npt"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "776ec7a6-bda3-4d09-a24c-da811c070e87",
      "metadata": {
        "id": "776ec7a6-bda3-4d09-a24c-da811c070e87"
      },
      "source": [
        "[SciencePlots](https://github.com/garrettj403/SciencePlots/)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "bb8b93c0-9833-407b-9bb4-abe16959a467",
      "metadata": {
        "id": "bb8b93c0-9833-407b-9bb4-abe16959a467"
      },
      "outputs": [],
      "source": [
        "try:\n",
        "    # pip install SciencePlots\n",
        "    plt.style.use(['science', 'grid', 'no-latex', 'notebook'])\n",
        "except OSError:\n",
        "    # plt.style.use('default')\n",
        "    plt.style.use('ggplot')"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "098ea86f-3df3-44fb-a12a-68b6159ebb3d",
      "metadata": {
        "id": "098ea86f-3df3-44fb-a12a-68b6159ebb3d"
      },
      "source": [
        "# Convenience modules"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "e02939da-674b-4a8c-a57b-e63b6f4a752b",
      "metadata": {
        "id": "e02939da-674b-4a8c-a57b-e63b6f4a752b"
      },
      "outputs": [],
      "source": [
        "Number = Union[int, float]\n",
        "\n",
        "\n",
        "def interval_of(distribution: npt.ArrayLike, unique: bool = True) -> npt.NDArray:\n",
        "    differences = np.abs(np.diff(distribution, n=1))\n",
        "    return np.unique(differences, axis=-1) if unique else differences\n",
        "\n",
        "\n",
        "def is_uniform(distribution: npt.ArrayLike) -> bool:\n",
        "    return interval_of(distribution).shape[-1] == 1\n",
        "\n",
        "\n",
        "def shape_of(distribution: npt.ArrayLike) -> npt.NDArray:\n",
        "    '''Returns the shape of a distribution.'''\n",
        "    interval = interval_of(distribution)\n",
        "    if interval.shape[-1] != 1:\n",
        "        warnings.warn(\n",
        "            'This distribution is non-uniform'\n",
        "            ' and therefore uses the minimum interval.',\n",
        "            RuntimeWarning,\n",
        "        )\n",
        "        interval = np.min(interval, axis=-1)\n",
        "    else:\n",
        "        interval = np.squeeze(interval, axis=-1)\n",
        "\n",
        "    start = np.min(distribution, axis=-1)\n",
        "    end = np.max(distribution, axis=-1)\n",
        "\n",
        "    return np.stack([start, end, interval], axis=-1)\n",
        "\n",
        "\n",
        "def range_of(\n",
        "    start: Number,\n",
        "    end: Number,\n",
        "    interval: Number,\n",
        "    dtype: Optional[Type[Union[float, np.floating]]] = None,\n",
        ") -> npt.NDArray:\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> range_of(380, 780, 10)\n",
        "    '''\n",
        "    if dtype is None:\n",
        "        dtype = float\n",
        "\n",
        "    assert np.issubdtype(dtype, np.floating)\n",
        "\n",
        "    num_samples = int(round((interval + end - start) / interval))\n",
        "\n",
        "    samples, effective_interval = np.linspace(\n",
        "        start, end, num_samples, retstep=True, dtype=dtype\n",
        "    )\n",
        "\n",
        "    if interval != effective_interval:\n",
        "        warnings.warn(\n",
        "            '{} is used instead of the specified shape {}'.format(\n",
        "                (start, end, effective_interval), (start, end, interval)\n",
        "            ),\n",
        "            RuntimeWarning,\n",
        "        )\n",
        "\n",
        "    return samples\n",
        "\n",
        "\n",
        "@dataclass(frozen=True)\n",
        "class SpectralShape:\n",
        "    start: Number\n",
        "    end: Number\n",
        "    interval: Number\n",
        "\n",
        "    def __iter__(self) -> Iterator[Number]:\n",
        "        return iter((self.start, self.end, self.interval))\n",
        "\n",
        "    @property\n",
        "    def boundaries(self) -> Tuple[Number, Number]:\n",
        "        return self.start, self.end\n",
        "\n",
        "    def range(\n",
        "        self, dtype: Optional[Type[Union[float, np.floating]]] = None\n",
        "    ) -> npt.NDArray:\n",
        "        if dtype is None:\n",
        "            dtype = float\n",
        "        return range_of(self.start, self.end, self.interval, dtype)\n",
        "\n",
        "\n",
        "@dataclass\n",
        "class SpectralDistribution:\n",
        "    wavelengths: npt.NDArray = field(init=False)\n",
        "    values: npt.NDArray = field(init=False)\n",
        "    interpolator: Type[scipy.interpolate.PPoly] = field(init=False)\n",
        "    interpolator_kwargs: Optional[Dict[str, Any]] = field(init=False)\n",
        "\n",
        "    data: InitVar[Union[npt.ArrayLike, 'SpectralDistribution']]\n",
        "    domain: InitVar[Optional[Union[npt.ArrayLike, SpectralShape]]] = None\n",
        "    copy: InitVar[bool] = True\n",
        "    kwargs: InitVar[Optional[Dict[str, Any]]] = None\n",
        "\n",
        "    def __post_init__(self, data, domain, copy, kwargs):\n",
        "        if isinstance(data, self.__class__):\n",
        "            self.wavelengths = np.array(data.wavelengths, copy=copy)\n",
        "            self.values = np.array(data.values, copy=copy)\n",
        "        else:\n",
        "            if isinstance(domain, SpectralShape):\n",
        "                self.wavelengths = domain.range()\n",
        "            else:\n",
        "                domain = np.asarray(domain)\n",
        "                assert domain.ndim == 1\n",
        "                self.wavelengths = np.array(domain, copy=copy)\n",
        "\n",
        "            data = np.asarray(data)\n",
        "            assert data.ndim == 1\n",
        "            self.values = np.array(data, copy=copy)\n",
        "\n",
        "        if kwargs is None:\n",
        "            kwargs = {}\n",
        "\n",
        "        self.interpolator = kwargs.get(\n",
        "            'interpolator', scipy.interpolate.Akima1DInterpolator\n",
        "        )\n",
        "        self.interpolator_kwargs = kwargs.get('interpolator_kwargs')\n",
        "\n",
        "    @property\n",
        "    def shape(self) -> SpectralShape:\n",
        "        return SpectralShape(*shape_of(self.wavelengths))\n",
        "\n",
        "    @property\n",
        "    def interp_fn(self) -> scipy.interpolate.PPoly:\n",
        "        if self.interpolator_kwargs is None:\n",
        "            kwargs = {}\n",
        "        else:\n",
        "            kwargs = self.interpolator_kwargs.copy()\n",
        "\n",
        "        kwargs['axis'] = -1\n",
        "        return self.interpolator(self.wavelengths, self.values, **kwargs)\n",
        "\n",
        "\n",
        "@dataclass\n",
        "class MultiSpectralDistributions:\n",
        "    wavelengths: npt.NDArray = field(init=False)\n",
        "    values: npt.NDArray = field(init=False)\n",
        "    interpolator: Type[scipy.interpolate.PPoly] = field(init=False)\n",
        "    interpolator_kwargs: Optional[Dict[str, Any]] = field(init=False)\n",
        "\n",
        "    data: InitVar[Union[npt.ArrayLike, 'MultiSpectralDistributions']]\n",
        "    domain: InitVar[Optional[Union[npt.ArrayLike, SpectralShape]]] = None\n",
        "    copy: InitVar[bool] = True\n",
        "    kwargs: InitVar[Optional[Dict[str, Any]]] = None\n",
        "\n",
        "    def __post_init__(self, data, domain, copy, kwargs):\n",
        "        if isinstance(data, self.__class__):\n",
        "            self.wavelengths = np.array(data.wavelengths, copy=copy)\n",
        "            self.values = np.array(data.values, copy=copy)\n",
        "        else:\n",
        "            if isinstance(domain, SpectralShape):\n",
        "                self.wavelengths = domain.range()\n",
        "            else:\n",
        "                domain = np.asarray(domain)\n",
        "                assert domain.ndim == 1\n",
        "                self.wavelengths = np.array(domain, copy=copy)\n",
        "\n",
        "            data = np.asarray(data)\n",
        "            assert data.ndim == 2\n",
        "            self.values = np.array(data, copy=copy)\n",
        "\n",
        "        if kwargs is None:\n",
        "            kwargs = {}\n",
        "\n",
        "        self.interpolator = kwargs.get(\n",
        "            'interpolator', scipy.interpolate.Akima1DInterpolator\n",
        "        )\n",
        "        self.interpolator_kwargs = kwargs.get('interpolator_kwargs')\n",
        "\n",
        "    @property\n",
        "    def num_dimensions(self) -> int:\n",
        "        return len(self.values)\n",
        "\n",
        "    @property\n",
        "    def shape(self) -> SpectralShape:\n",
        "        return SpectralShape(*shape_of(self.wavelengths))\n",
        "\n",
        "    @property\n",
        "    def interp_fn(self) -> scipy.interpolate.PPoly:\n",
        "        if self.interpolator_kwargs is None:\n",
        "            kwargs = {}\n",
        "        else:\n",
        "            kwargs = self.interpolator_kwargs.copy()\n",
        "\n",
        "        kwargs['axis'] = -1\n",
        "        return self.interpolator(self.wavelengths, self.values, **kwargs)\n",
        "\n",
        "    def to_sds(self) -> List[SpectralDistribution]:\n",
        "        kwargs = {\n",
        "            'interpolator': self.interpolator,\n",
        "            'interpolator_kwargs': self.interpolator_kwargs,\n",
        "        }\n",
        "        return [\n",
        "            SpectralDistribution(values, self.wavelengths, kwargs=kwargs)\n",
        "            for values in self.values\n",
        "        ]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4a3ae367-ea03-4a4d-b5dc-7fe1445070f4",
      "metadata": {
        "id": "4a3ae367-ea03-4a4d-b5dc-7fe1445070f4"
      },
      "outputs": [],
      "source": [
        "def minimum_shape_of(\n",
        "    various_sds: Sequence[\n",
        "        Union[\n",
        "            SpectralDistribution,\n",
        "            MultiSpectralDistributions,\n",
        "            Sequence[SpectralDistribution],\n",
        "        ]\n",
        "    ]\n",
        ") -> SpectralShape:\n",
        "\n",
        "    shapes = []\n",
        "    for one_of_them in various_sds:\n",
        "        if isinstance(one_of_them, (SpectralDistribution, MultiSpectralDistributions)):\n",
        "            shapes.append(tuple(one_of_them.shape))\n",
        "        else:\n",
        "            shapes += [tuple(sd.shape) for sd in one_of_them]\n",
        "\n",
        "    shapes = np.stack([shape for shape in shapes], axis=-1)\n",
        "    return SpectralShape(np.max(shapes[0]), np.min(shapes[1]), np.min(shapes[2]))\n",
        "\n",
        "\n",
        "def various_sds_to_msds(\n",
        "    various_sds: Sequence[\n",
        "        Union[\n",
        "            SpectralDistribution,\n",
        "            MultiSpectralDistributions,\n",
        "            Sequence[SpectralDistribution],\n",
        "        ]\n",
        "    ],\n",
        "    msds_kwargs: Optional[Dict[str, Any]] = None,\n",
        ") -> MultiSpectralDistributions:\n",
        "\n",
        "    shape = minimum_shape_of(various_sds)\n",
        "    wavelengths = shape.range()\n",
        "\n",
        "    temp = []\n",
        "    for one_of_them in various_sds:\n",
        "        if isinstance(one_of_them, (SpectralDistribution, MultiSpectralDistributions)):\n",
        "            temp.append(one_of_them.interp_fn(wavelengths))\n",
        "        else:\n",
        "            temp += [sd.interp_fn(wavelengths) for sd in one_of_them]\n",
        "\n",
        "    values = np.stack(temp, axis=0)\n",
        "\n",
        "    return MultiSpectralDistributions(values, wavelengths, kwargs=msds_kwargs)\n",
        "\n",
        "\n",
        "def various_sds_to_sds(\n",
        "    various_sds: Sequence[\n",
        "        Union[\n",
        "            SpectralDistribution,\n",
        "            MultiSpectralDistributions,\n",
        "            Sequence[SpectralDistribution],\n",
        "        ]\n",
        "    ]\n",
        ") -> List[SpectralDistribution]:\n",
        "\n",
        "    sds = []\n",
        "    for one_of_them in various_sds:\n",
        "        if isinstance(one_of_them, SpectralDistribution):\n",
        "            sds.append(one_of_them)\n",
        "        elif isinstance(one_of_them, MultiSpectralDistributions):\n",
        "            sds += one_of_them.to_sds()\n",
        "        else:\n",
        "            sds += one_of_them\n",
        "\n",
        "    return sds\n",
        "\n",
        "\n",
        "def synthesize(\n",
        "    sd_or_msds0: Union[SpectralDistribution, MultiSpectralDistributions],\n",
        "    sd_or_msds1: Union[SpectralDistribution, MultiSpectralDistributions],\n",
        "    sd_or_msds_kwargs: Optional[Dict[str, Any]] = None,\n",
        ") -> Union[SpectralDistribution, MultiSpectralDistributions]:\n",
        "\n",
        "    shape = minimum_shape_of([sd_or_msds0, sd_or_msds1])\n",
        "    wavelengths = shape.range()\n",
        "\n",
        "    interp_fn0 = sd_or_msds0.interp_fn\n",
        "    interp_fn1 = sd_or_msds1.interp_fn\n",
        "\n",
        "    if isinstance(sd_or_msds0, SpectralDistribution) \\\n",
        "       and isinstance(sd_or_msds1, SpectralDistribution):  # fmt: skip\n",
        "        values0 = interp_fn0(wavelengths)\n",
        "        values1 = interp_fn1(wavelengths)\n",
        "        values = values0 * values1\n",
        "        return SpectralDistribution(values, wavelengths, kwargs=sd_or_msds_kwargs)\n",
        "\n",
        "    elif isinstance(sd_or_msds0, SpectralDistribution) \\\n",
        "         and isinstance(sd_or_msds1, MultiSpectralDistributions):  # fmt: skip\n",
        "        values0 = interp_fn0(wavelengths)[np.newaxis, ...]\n",
        "        values1 = interp_fn1(wavelengths)\n",
        "        values = values0 * values1\n",
        "        return MultiSpectralDistributions(values, wavelengths, kwargs=sd_or_msds_kwargs)\n",
        "\n",
        "    elif isinstance(sd_or_msds0, MultiSpectralDistributions) \\\n",
        "         and isinstance(sd_or_msds1, SpectralDistribution):  # fmt: skip\n",
        "        values0 = interp_fn0(wavelengths)\n",
        "        values1 = interp_fn1(wavelengths)[np.newaxis, ...]\n",
        "        values = values0 * values1\n",
        "        return MultiSpectralDistributions(values, wavelengths, kwargs=sd_or_msds_kwargs)\n",
        "\n",
        "    elif isinstance(sd_or_msds0, MultiSpectralDistributions) \\\n",
        "         and isinstance(sd_or_msds1, MultiSpectralDistributions):  # fmt: skip\n",
        "        values0 = interp_fn0(wavelengths)\n",
        "        values1 = interp_fn1(wavelengths)\n",
        "        values = values0 * values1\n",
        "        return MultiSpectralDistributions(values, wavelengths, kwargs=sd_or_msds_kwargs)\n",
        "\n",
        "    else:\n",
        "        raise TypeError('Not a valid combination.')"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "ca33a9e1-b254-4d21-9d09-996a72195d1c",
      "metadata": {
        "id": "ca33a9e1-b254-4d21-9d09-996a72195d1c"
      },
      "source": [
        "Plotting"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "7d5f8757-9af9-46a2-97c9-dc842ad7a1ac",
      "metadata": {
        "id": "7d5f8757-9af9-46a2-97c9-dc842ad7a1ac"
      },
      "outputs": [],
      "source": [
        "def plot_sd(sd, shape, *, color=None, label=None, ax=None, backend_kwargs=None):\n",
        "    if ax is None:\n",
        "        if backend_kwargs is None:\n",
        "            backend_kwargs = {}\n",
        "\n",
        "        _, ax = plt.subplots(1, 1, **backend_kwargs)\n",
        "\n",
        "    wavelengths = shape.range()\n",
        "\n",
        "    ax.plot(\n",
        "        wavelengths, sd.interp_fn(wavelengths), linewidth=1, color=color, label=label\n",
        "    )\n",
        "    ec = ax.get_lines()[-1].get_color()\n",
        "    ax.scatter(\n",
        "        sd.wavelengths, sd.values, s=15, c='w', marker='o', edgecolor=ec, linewidth=0.75\n",
        "    )\n",
        "\n",
        "    ax.set_xlabel('Wavelength [nm]')\n",
        "\n",
        "    return ax\n",
        "\n",
        "\n",
        "def plot_various_sds(\n",
        "    various_sds, shape, *, colors=None, labels=None, ax=None, backend_kwargs=None\n",
        "):\n",
        "    if isinstance(various_sds, MultiSpectralDistributions):\n",
        "        sds = various_sds.to_sds()\n",
        "    else:\n",
        "        sds = various_sds_to_sds(various_sds)\n",
        "\n",
        "    num_sds = len(sds)\n",
        "\n",
        "    if colors is None:\n",
        "        colors = [None for _ in range(num_sds)]\n",
        "\n",
        "    if labels is None:\n",
        "        labels = [None for _ in range(num_sds)]\n",
        "\n",
        "    for sd, color, label in zip(sds, colors, labels):\n",
        "        ax = plot_sd(\n",
        "            sd,\n",
        "            shape,\n",
        "            color=color,\n",
        "            label=label,\n",
        "            ax=ax,\n",
        "            backend_kwargs=backend_kwargs,\n",
        "        )\n",
        "\n",
        "    return ax"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a51085c4-c3d6-4e07-ad64-d78197aff99a",
      "metadata": {
        "id": "a51085c4-c3d6-4e07-ad64-d78197aff99a"
      },
      "outputs": [],
      "source": [
        "def plot_colors(\n",
        "    colors, *, nrows_ncols, annotations=None, shape=None, ax=None, backend_kwargs=None\n",
        "):\n",
        "\n",
        "    num_colors = len(colors)\n",
        "    h, w = nrows_ncols\n",
        "    if num_colors <= w:\n",
        "        h, w = 1, num_colors\n",
        "    elif num_colors <= w * h:\n",
        "        h, w = np.ceil(num_colors / w).astype(int), w\n",
        "\n",
        "    if ax is None:\n",
        "        if backend_kwargs is None:\n",
        "            backend_kwargs = {}\n",
        "        _, ax = plt.subplots(1, 1, **backend_kwargs)\n",
        "\n",
        "    if (shape is None) or (shape == 'circle'):\n",
        "        patch_fn = lambda x, y, c: patches.Circle(\n",
        "            xy=(x + 0.5, y - 0.5), radius=0.45, fc=c\n",
        "        )\n",
        "        xlim = (0, w)\n",
        "        ylim = (-h, 0)\n",
        "    else:\n",
        "        patch_fn = lambda x, y, c: patches.Rectangle(\n",
        "            xy=(x + 0.1, y - 0.9), width=0.9, height=0.9, fc=color\n",
        "        )\n",
        "        xlim = (0, w + 0.1)\n",
        "        ylim = (-h, 0.1)\n",
        "\n",
        "    for i, color in enumerate(colors[0 : w * h]):\n",
        "        x, y = i % w, -(i // w)\n",
        "\n",
        "        patch = patch_fn(x, y, color)\n",
        "        ax.add_patch(patch)\n",
        "\n",
        "        if annotations is not None:\n",
        "            annotation = annotations[i]\n",
        "            ax.annotate(\n",
        "                annotation,\n",
        "                xy=(x + 0.5, y - 0.5),\n",
        "                color='w',\n",
        "                va='center',\n",
        "                ha='center',\n",
        "                path_effects=[patheffects.withStroke(linewidth=4, foreground='k')],\n",
        "            )\n",
        "\n",
        "    ax.set_xlim(*xlim)\n",
        "    ax.set_ylim(*ylim)\n",
        "    ax.set_facecolor('k')\n",
        "    ax.set_aspect('equal')\n",
        "    ax.axes.xaxis.set_visible(False)\n",
        "    ax.axes.yaxis.set_visible(False)\n",
        "\n",
        "    return ax\n",
        "\n",
        "\n",
        "def plot_colorbar(\n",
        "    color,\n",
        "    *,\n",
        "    align='center',\n",
        "    offset=0,\n",
        "    scale=1,\n",
        "    tick_label=None,\n",
        "    clip_path=None,\n",
        "    ax=None,\n",
        "    backend_kwargs=None\n",
        "):\n",
        "\n",
        "    num_colors = len(color)\n",
        "\n",
        "    start, end, interval = offset, offset + (num_colors - 1) * scale, scale\n",
        "\n",
        "    if clip_path is None:\n",
        "        lower, upper = start, end\n",
        "        if align == 'center':\n",
        "            half = 0.5 * interval\n",
        "            lower -= half\n",
        "            upper += half\n",
        "        else:\n",
        "            upper += interval\n",
        "\n",
        "        rect = np.vstack([(lower, 1), (lower, 0), (upper, 0), (upper, 1)])\n",
        "        clip_path = patches.Polygon(rect, facecolor=None, edgecolor=None)\n",
        "\n",
        "    vy = clip_path.get_path().vertices[..., 1]\n",
        "    py = clip_path.get_patch_transform().transform(vy)\n",
        "    bottom, top = np.min(py), np.max(py)\n",
        "\n",
        "    num_samples = int(round((interval + end - start) / interval))\n",
        "    x = np.linspace(start, end, num_samples, retstep=False)\n",
        "\n",
        "    if ax is None:\n",
        "        if backend_kwargs is None:\n",
        "            backend_kwargs = {}\n",
        "\n",
        "        _, ax = plt.subplots(1, 1, **backend_kwargs)\n",
        "\n",
        "    ax.add_patch(clip_path)\n",
        "\n",
        "    ax.bar(\n",
        "        x=x,\n",
        "        height=top - bottom,\n",
        "        width=interval,\n",
        "        bottom=bottom,\n",
        "        align=align,\n",
        "        color=color,\n",
        "        linewidth=0,\n",
        "        tick_label=tick_label,\n",
        "        clip_path=clip_path,\n",
        "    )\n",
        "\n",
        "    return ax\n",
        "\n",
        "\n",
        "def make_clip_path(fn, x, bottom=0):\n",
        "\n",
        "    arr = np.stack([x, fn(x)])\n",
        "    indices = np.argsort(arr[0])[..., ::-1]\n",
        "\n",
        "    x2 = np.take_along_axis(arr[0], indices, axis=-1)\n",
        "    y2 = np.take_along_axis(arr[1], indices, axis=-1)\n",
        "\n",
        "    x2 = np.append(x2, [np.min(x), np.max(x)])\n",
        "    y2 = np.append(y2, [bottom, bottom])\n",
        "\n",
        "    return patches.Polygon(np.stack([x2, y2], axis=-1), facecolor=None, edgecolor=None)\n",
        "\n",
        "\n",
        "def plot_gamma(compression, expansion, *, axes=None, backend_kwargs=None):\n",
        "\n",
        "    if axes is None:\n",
        "        if backend_kwargs is None:\n",
        "            backend_kwargs = {}\n",
        "\n",
        "        kwargs = backend_kwargs.copy()\n",
        "        kwargs['constrained_layout'] = True\n",
        "        fig, axes = plt.subplots(1, 2, **kwargs)\n",
        "        fig.set_constrained_layout_pads(hspace=0.1, wspace=0.1)\n",
        "    else:\n",
        "        fig = axes[0].get_figure()\n",
        "\n",
        "    ax = axes[0]\n",
        "    x = np.linspace(0, 1, 100)\n",
        "    comp_y = compression(x)\n",
        "    ax.plot(x, x, label='linear')\n",
        "    ax.plot(x, comp_y, label='compression', linestyle='--')\n",
        "    ax.plot(x, expansion(x), label='expansion', linestyle='--')\n",
        "    ax.set_aspect('equal')\n",
        "    ax.set_title('gamma curve')\n",
        "    ax.set_xlabel('input')\n",
        "    ax.set_ylabel('output')\n",
        "    ax.legend()\n",
        "\n",
        "    ax = axes[1]\n",
        "    ax.plot(x, comp_y, label='non-linear')\n",
        "    ax.plot(x, expansion(comp_y), label='expansion', linestyle='--')\n",
        "    ax.set_aspect('equal')\n",
        "    ax.set_title('gamma curve')\n",
        "    ax.set_xlabel('input')\n",
        "    ax.set_ylabel('output')\n",
        "    ax.legend()\n",
        "\n",
        "    return axes"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "1e8154a5-eee3-4697-8aba-9e34c4f5654d",
      "metadata": {
        "id": "1e8154a5-eee3-4697-8aba-9e34c4f5654d"
      },
      "source": [
        "# CIE 1931 color space\n",
        "- [CIE 1931 color space; en.wikipedia.org](https://en.wikipedia.org/wiki/CIE_1931_color_space)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "25cf76dc-b409-4587-bd93-cf912e0392b5",
      "metadata": {
        "id": "25cf76dc-b409-4587-bd93-cf912e0392b5"
      },
      "source": [
        "## CIE xy chromaticity diagram and the CIE xyY color space  \n",
        "- [CIE xy chromaticity diagram and the CIE xyY color space; en.wikipedia.org](https://en.wikipedia.org/wiki/CIE_1931_color_space#CIE_xy_chromaticity_diagram_and_the_CIE_xyY_color_space)  \n",
        "\n",
        "XYZ to xyY\n",
        "$$\n",
        "\\begin{aligned}\n",
        "x&=\\frac{X}{X + Y + Z}\\\\\n",
        "y&=\\frac{Y}{X + Y + Z}\\\\\n",
        "z&=\\frac{Z}{X + Y + Z}=1 - x - y\n",
        "\\end{aligned}\n",
        "$$\n",
        "\n",
        "xyY to XYZ\n",
        "$$\n",
        "\\begin{aligned}\n",
        "X&=Y \\frac{x}{y}\\\\\n",
        "Z&=Y \\frac{1 - x - y}{y}\n",
        "\\end{aligned}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "639ec3b0-afa3-4cb5-bccd-8d56fbc748ae",
      "metadata": {
        "id": "639ec3b0-afa3-4cb5-bccd-8d56fbc748ae"
      },
      "outputs": [],
      "source": [
        "def XYZ_to_xyY(XYZ):\n",
        "    assert np.issubdtype(XYZ.dtype, float)\n",
        "\n",
        "    X, Y = XYZ[..., 0], XYZ[..., 1]\n",
        "    s = np.sum(XYZ, axis=-1)\n",
        "    return np.stack([X / s, Y / s, Y], axis=-1)\n",
        "\n",
        "\n",
        "def xyY_to_XYZ(xyY):\n",
        "    assert np.issubdtype(xyY.dtype, float)\n",
        "\n",
        "    x, y, Y = xyY[..., 0], xyY[..., 1], xyY[..., 2]\n",
        "    X = Y * (x / y)\n",
        "    Z = Y * ((1 - x - y) / y)\n",
        "    return np.stack([X, Y, Z], axis=-1)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "6daa038d-870b-490b-85a3-25484402e23a",
      "metadata": {
        "id": "6daa038d-870b-490b-85a3-25484402e23a"
      },
      "source": [
        "## RGB/XYZ"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "b1cccffc-ddd6-47bc-8fe7-3a84b3c8eabf",
      "metadata": {
        "id": "b1cccffc-ddd6-47bc-8fe7-3a84b3c8eabf"
      },
      "source": [
        "RGB/XYZ Matrices  \n",
        "- [RGB/XYZ Matrices; www.brucelindbloom.com](http://www.brucelindbloom.com/index.html?WorkingSpaceInfo.html)  \n",
        "- [Calculating RGB↔XYZ matrix; mina86.com](https://mina86.com/2019/srgb-xyz-matrix/)\n",
        "\n",
        "$$\n",
        "C\n",
        "=\n",
        "\\left(\n",
        "\\begin{array}{ccc}\n",
        " \\frac{r_x}{r_y} & \\frac{g_x}{g_y} & \\frac{b_x}{b_y}\\\\\n",
        " 1 & 1 & 1\\\\\n",
        " \\frac{1 - r_x - r_y}{r_y} & \\frac{1 - g_x - g_y}{g_y} & \\frac{1 - b_x - b_y}{b_y}\n",
        "\\end{array}\n",
        "\\right)\n",
        "$$\n",
        "\n",
        "$$\n",
        "\\left(\n",
        "\\begin{array}{c}\n",
        " S_r\\\\\n",
        " S_g\\\\\n",
        " S_b\n",
        "\\end{array}\n",
        "\\right)\n",
        "=\n",
        "C^{-1}\n",
        "\\left(\n",
        "\\begin{array}{c}\n",
        " \\frac{w_x}{w_y}\\\\\n",
        " 1\\\\\n",
        " \\frac{1 - w_x - w_y}{w_y}\n",
        "\\end{array}\n",
        "\\right)\n",
        "$$\n",
        "\n",
        "$$\n",
        "\\left(\n",
        "\\begin{array}{c}\n",
        " X\\\\\n",
        " Y\\\\\n",
        " Z\n",
        "\\end{array}\n",
        "\\right)\n",
        "=\n",
        "M\n",
        "\\left(\n",
        "\\begin{array}{c}\n",
        " R\\\\\n",
        " G\\\\\n",
        " B\n",
        "\\end{array}\n",
        "\\right)\n",
        "$$\n",
        "\n",
        "$$\n",
        "\\begin{aligned}\n",
        "\\text{where}\\\\\n",
        "M\n",
        "&=\n",
        "C \\operatorname{diag}{(S_r, S_g, S_b)}\n",
        "\\end{aligned}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "eb1878b9-768f-4348-82a2-0bda9f757b04",
      "metadata": {
        "id": "eb1878b9-768f-4348-82a2-0bda9f757b04"
      },
      "outputs": [],
      "source": [
        "def make_rgb_to_xyz_matrix(r_xy, g_xy, b_xy, w_xy):\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> # sRGB D65\n",
        "    >>> r_xy = np.array([0.64000, 0.33000])\n",
        "    >>> g_xy = np.array([0.30000, 0.60000])\n",
        "    >>> b_xy = np.array([0.15000, 0.06000])\n",
        "    >>> w_xy = np.array([0.31271, 0.32902])\n",
        "    >>> make_rgb_to_xyz_matrix(r_xy, g_xy, b_xy, w_xy)\n",
        "    '''\n",
        "    assert np.issubdtype(r_xy.dtype, float)\n",
        "    assert np.issubdtype(g_xy.dtype, float)\n",
        "    assert np.issubdtype(b_xy.dtype, float)\n",
        "    assert np.issubdtype(w_xy.dtype, float)\n",
        "\n",
        "    def xy_to_XYZ(xy):\n",
        "        return np.array([xy[0], xy[1], 1 - xy[0] - xy[1]]) / xy[1]\n",
        "\n",
        "    XrYrZr = xy_to_XYZ(r_xy)\n",
        "    XgYgZg = xy_to_XYZ(g_xy)\n",
        "    XbYbZb = xy_to_XYZ(b_xy)\n",
        "    c = np.array([XrYrZr, XgYgZg, XbYbZb]).T\n",
        "\n",
        "    XwYwZw = xy_to_XYZ(w_xy)\n",
        "    SrSgSb = np.linalg.inv(c).dot(XwYwZw)\n",
        "\n",
        "    return c * SrSgSb"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "d1860269-1c87-4651-8a80-3e0dc7c27583",
      "metadata": {
        "id": "d1860269-1c87-4651-8a80-3e0dc7c27583"
      },
      "source": [
        "XYZ to RGB  \n",
        "- [XYZ to RGB; www.brucelindbloom.com](http://www.brucelindbloom.com/index.html?WorkingSpaceInfo.html)  \n",
        "- [RGB Working Space Information; www.brucelindbloom.com](http://www.brucelindbloom.com/index.html?WorkingSpaceInfo.html)  \n",
        "- [sRGB↔XYZ conversion; mina86.com](https://mina86.com/2019/srgb-xyz-conversion/)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8a7280b7-60ee-4105-a908-8d3e9ab37ff1",
      "metadata": {
        "id": "8a7280b7-60ee-4105-a908-8d3e9ab37ff1"
      },
      "outputs": [],
      "source": [
        "def make_srgb_to_xyz_matrix():\n",
        "    # linear-sRGB to XYZ\n",
        "    r_xy = np.array([0.64000, 0.33000])\n",
        "    g_xy = np.array([0.30000, 0.60000])\n",
        "    b_xy = np.array([0.15000, 0.06000])\n",
        "    w_xy = np.array([0.31271, 0.32902])  # D65\n",
        "\n",
        "    return make_rgb_to_xyz_matrix(r_xy, g_xy, b_xy, w_xy)\n",
        "\n",
        "\n",
        "def make_xyz_to_srgb_matrix():\n",
        "    # XYZ linear-sRGB\n",
        "    return np.linalg.inv(make_srgb_to_xyz_matrix())\n",
        "\n",
        "\n",
        "_xyz_to_rgb = make_xyz_to_srgb_matrix()\n",
        "_xyz_to_rgb.setflags(write=False)\n",
        "\n",
        "\n",
        "def xyz_to_rgb(xyz):\n",
        "    assert np.issubdtype(xyz.dtype, float)\n",
        "    return np.clip(_xyz_to_rgb.dot(xyz), 0, 1)\n",
        "\n",
        "\n",
        "def gamma_compression(rgb):\n",
        "    assert np.issubdtype(rgb.dtype, float)\n",
        "\n",
        "    cond = rgb <= 0.0031308\n",
        "    return np.piecewise(\n",
        "        rgb,\n",
        "        [cond, np.logical_not(cond)],\n",
        "        [lambda x: 12.92 * x, lambda x: 1.055 * (x ** (1 / 2.4)) - 0.055],\n",
        "    )\n",
        "\n",
        "\n",
        "def gamma_expansion(rgb):\n",
        "    assert np.issubdtype(rgb.dtype, float)\n",
        "\n",
        "    cond = rgb <= 0.04045\n",
        "    return np.piecewise(\n",
        "        rgb,\n",
        "        [cond, np.logical_not(cond)],\n",
        "        [lambda x: x / 12.92, lambda x: ((x + 0.055) / 1.055) ** 2.4],\n",
        "    )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c59758a5-671e-4000-8896-0f10a2661cd4",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377,
          "referenced_widgets": [
            "ee1fa13d14134c5f8e1a84cff0b1d92d",
            "e7df65d203794f8ca6099e021f62668c",
            "ede49cdbe7c54f3884ac8ad3ea3718d7",
            "6fe7cc31738d4655aa062844afc6072e"
          ]
        },
        "id": "c59758a5-671e-4000-8896-0f10a2661cd4",
        "outputId": "668968f4-29ef-49c5-e362-cb6bf0aa248c"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ],
            "image/png": 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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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' width=864.0/>\n",
              "            </div>\n",
              "        "
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ee1fa13d14134c5f8e1a84cff0b1d92d"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "axes = plot_gamma(\n",
        "    gamma_compression, gamma_expansion, backend_kwargs={'figsize': (12, 4)}\n",
        ")\n",
        "axes[0].legend(loc='upper left', bbox_to_anchor=(1.025, 1.0), borderaxespad=0)\n",
        "axes[1].legend(loc='upper left', bbox_to_anchor=(1.025, 1.0), borderaxespad=0)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "14c5c1db-e8a1-4912-88a3-f595dce9fb58",
      "metadata": {
        "id": "14c5c1db-e8a1-4912-88a3-f595dce9fb58"
      },
      "source": [
        "## CIE standard observer\n",
        "- [CIE standard observer; en.wikipedia.org](https://en.wikipedia.org/wiki/CIE_1931_color_space#CIE_standard_observer)\n",
        "\n",
        "piecewise-Gaussian function\n",
        "$$\n",
        "g(x; \\mu, \\sigma_{1}, \\sigma_{2})\n",
        "=\n",
        "\\begin{cases}\n",
        "\\exp{\\left(- \\frac{1}{2} \\frac{(x - \\mu)^2}{\\sigma_{1}^2} \\right)}, & x \\lt \\mu\\\\\n",
        "\\exp{\\left(- \\frac{1}{2} \\frac{(x - \\mu)^2}{\\sigma_{2}^2} \\right)}, & x \\ge \\mu\n",
        "\\end{cases}\n",
        "$$\n",
        "\n",
        "color matching functions\n",
        "$$\n",
        "\\begin{aligned}\n",
        "\\bar{x}(\\lambda)\n",
        "&=1.056 g(\\lambda; 599.8, 37.9, 31.0) + 0.362 g(\\lambda; 442.0, 16.0, 26.7) - 0.065 g(\\lambda; 501.1, 20.4, 26.2)\\\\\n",
        "\\\\\n",
        "\\bar{y}(\\lambda)\n",
        "&=0.821 g(\\lambda; 568.8, 46.9, 40.5) + 0.286 g(\\lambda; 530.9, 16.3, 31.1)\\\\\n",
        "\\\\\n",
        "\\bar{z}(\\lambda)\n",
        "&=1.217 g(\\lambda; 437.0, 11.8, 36.0) + 0.681 g(\\lambda; 459.0, 26.0, 13.8)\n",
        "\\end{aligned}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9b9f135c-b538-4987-a17e-a7fcc865b44f",
      "metadata": {
        "id": "9b9f135c-b538-4987-a17e-a7fcc865b44f"
      },
      "outputs": [],
      "source": [
        "def g(x, mu, sigma1, sigma2):\n",
        "    '''piecewise-Gaussian function.'''\n",
        "    assert (\n",
        "        isinstance(x, (np.generic, np.ndarray))\n",
        "        and np.issubdtype(x.dtype, float)\n",
        "        or isinstance(x, float)\n",
        "    )\n",
        "    assert np.issubdtype(np.dtype(type(mu)), float)\n",
        "    assert np.issubdtype(np.dtype(type(sigma1)), float)\n",
        "    assert np.issubdtype(np.dtype(type(sigma2)), float)\n",
        "\n",
        "    def gaussian(x, mu, sigma):\n",
        "        return np.exp(-0.5 * ((x - mu) ** 2) / (sigma**2))\n",
        "\n",
        "    cond = x < mu\n",
        "    return np.piecewise(\n",
        "        x,\n",
        "        [cond, np.logical_not(cond)],\n",
        "        [lambda x: gaussian(x, mu, sigma1), lambda x: gaussian(x, mu, sigma2)],\n",
        "    )\n",
        "\n",
        "\n",
        "def cie_cmfs(wavelength):\n",
        "    '''Returns values of the chromatic response of the observer.'''\n",
        "    assert (\n",
        "        isinstance(wavelength, (np.generic, np.ndarray))\n",
        "        and np.issubdtype(wavelength.dtype, float)\n",
        "        or isinstance(wavelength, float)\n",
        "    )\n",
        "\n",
        "    def x_bar(wavelength):\n",
        "        return 1.056 * g(wavelength, 599.8, 37.9, 31.0) \\\n",
        "               + 0.362 * g(wavelength, 442.0, 16.0, 26.7) \\\n",
        "               - 0.065 * g(wavelength, 501.1, 20.4, 26.2)  # fmt: skip\n",
        "\n",
        "    def y_bar(wavelength):\n",
        "        return 0.821 * g(wavelength, 568.8, 46.9, 40.5) \\\n",
        "               + 0.286 * g(wavelength, 530.9, 16.3, 31.1)  # fmt: skip\n",
        "\n",
        "    def z_bar(wavelength):\n",
        "        return 1.217 * g(wavelength, 437.0, 11.8, 36.0) \\\n",
        "               + 0.681 * g(wavelength, 459.0, 26.0, 13.8)  # fmt: skip\n",
        "\n",
        "    return np.stack([x_bar(wavelength), y_bar(wavelength), z_bar(wavelength)], axis=-1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ccc450fd-90fa-4bee-b1f9-66dac764b01d",
      "metadata": {
        "id": "ccc450fd-90fa-4bee-b1f9-66dac764b01d"
      },
      "outputs": [],
      "source": [
        "def msds_cmfs(shape=None):\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> msds = msds_cmfs(SpectralShape(380, 780, 10))\n",
        "    >>> values = msds.interp_fn(wavelength)\n",
        "    '''\n",
        "    if shape is None:\n",
        "        shape = SpectralShape(380, 780, 10)\n",
        "\n",
        "    wavelengths = shape.range()\n",
        "    values = np.stack([values for values in cie_cmfs(wavelengths).T], axis=0)\n",
        "\n",
        "    return MultiSpectralDistributions(values, wavelengths)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6e2f85ab-4db1-40d5-aec4-ec618edb8c2b",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521,
          "referenced_widgets": [
            "30c42403ddd745ea80937c2ce232be19",
            "88722c11430a4a00b410c0f55587e00c",
            "da6144fb2c5c447586111d5ef2837277",
            "06089d08c7fa4156a6de0a55e9bbc272"
          ]
        },
        "id": "6e2f85ab-4db1-40d5-aec4-ec618edb8c2b",
        "outputId": "fbe7830c-497d-4eb2-f95c-24d284ca183a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ],
            "image/png": 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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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' width=864.0/>\n",
              "            </div>\n",
              "        "
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "30c42403ddd745ea80937c2ce232be19"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "# for analysis\n",
        "def _cmfs_to_rgb(cmfs, shape):\n",
        "    values = np.stack([xyz_to_rgb(xyz) for xyz in cmfs.values.T], axis=-1)\n",
        "    interp_fn = scipy.interpolate.interp1d(cmfs.wavelengths, values, axis=-1)\n",
        "    x = shape.range()\n",
        "    y = np.clip(gamma_compression(interp_fn(x)), 0, 1)\n",
        "    return y.T\n",
        "\n",
        "\n",
        "def _plot_cmfs():\n",
        "    msds = msds_cmfs(SpectralShape(380, 780, 10))\n",
        "    start, end = msds.shape.boundaries\n",
        "    shape = SpectralShape(start, end, 1)\n",
        "    color = _cmfs_to_rgb(msds, shape)\n",
        "    sds = various_sds_to_sds(\n",
        "        [\n",
        "            msds,\n",
        "        ]\n",
        "    )\n",
        "    colors = ['r', 'g', 'b']\n",
        "    labels = [r'$\\bar{x}(\\lambda)$', r'$\\bar{y}(\\lambda)$', r'$\\bar{z}(\\lambda)$']\n",
        "\n",
        "    fig, axes = plt.subplot_mosaic(\n",
        "        [['a)', 'a)', 'b)'], ['a)', 'a)', 'c)'], ['a)', 'a)', 'd)']],\n",
        "        constrained_layout=True,\n",
        "        figsize=(12, 6),\n",
        "    )\n",
        "\n",
        "    fig.set_constrained_layout_pads(hspace=0.1, wspace=0.1)\n",
        "\n",
        "    ax = axes['a)']\n",
        "    ax = plot_various_sds(msds, shape, colors=['r', 'g', 'b'], labels=labels, ax=ax)\n",
        "    ax.set_title('CIE 1931 standard colorimetric observer')\n",
        "    ax.legend()\n",
        "    clip_path = make_clip_path(lambda x: np.zeros_like(x), [start, end], -0.05)\n",
        "    plot_colorbar(color, offset=start, scale=1, clip_path=clip_path, ax=ax)\n",
        "\n",
        "    keys = ['b)', 'c)', 'd)']\n",
        "    for key, sd, c, title in zip(keys, sds, colors, labels):\n",
        "        ax = axes[key]\n",
        "        ax = plot_sd(sd, shape, color=c, ax=ax)\n",
        "        ax.set_title(title)\n",
        "        clip_path = make_clip_path(lambda x: sd.interp_fn(x), sd.wavelengths)\n",
        "        plot_colorbar(color, offset=start, scale=1, clip_path=clip_path, ax=ax)\n",
        "\n",
        "\n",
        "_plot_cmfs()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "9f30b69a-740a-4630-a3e3-aa50edcd3ffd",
      "metadata": {
        "id": "9f30b69a-740a-4630-a3e3-aa50edcd3ffd"
      },
      "source": [
        "## Computing XYZ from spectral data"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "5bee8f31-9f4d-430f-ba54-260519d18701",
      "metadata": {
        "id": "5bee8f31-9f4d-430f-ba54-260519d18701"
      },
      "source": [
        "### Emissive case"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "2167063d-75d5-4669-ba54-e61cd358bd6c",
      "metadata": {
        "id": "2167063d-75d5-4669-ba54-e61cd358bd6c"
      },
      "source": [
        "#### Black-body radiation\n",
        "- [Planck's law; en.wikipedia.org](https://en.wikipedia.org/wiki/Planck's_law#The_law)\n",
        "\n",
        "$$\n",
        "B_{\\lambda}(\\lambda, T)\n",
        "=\\frac{2 h c^2}{\\lambda^5} \\frac{1}{\\exp{\\left(\\frac{h c}{\\lambda k T} \\right)} - 1}\n",
        "$$\n",
        "  \n",
        "$$\n",
        "B_{\\lambda}: [W sr^{-1} m^{-3}]\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fc73e72c-317f-4847-a3b9-d9fdef439abc",
      "metadata": {
        "id": "fc73e72c-317f-4847-a3b9-d9fdef439abc"
      },
      "outputs": [],
      "source": [
        "def planck_law(wavelength, temperature):\n",
        "    '''Returns the spectral radiance of a blackbody.'''\n",
        "    h = scipy.constants.h  # Plank's constant\n",
        "    c = scipy.constants.c  # Speed of light\n",
        "    k = scipy.constants.k  # Boltzmann constant\n",
        "\n",
        "    a = 2 * h * (c**2) / (wavelength**5)\n",
        "    b = 1 / (np.exp((h * c) / (wavelength * k * temperature)) - 1)\n",
        "    return a * b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "7fff9093-b0c4-4a1f-8deb-a1a909d55555",
      "metadata": {
        "id": "7fff9093-b0c4-4a1f-8deb-a1a909d55555"
      },
      "outputs": [],
      "source": [
        "def sd_blackbody(temperature, shape=None):\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> sd = sd_blackbody(6500., SpectralShape(380, 780, 10))\n",
        "    >>> spectral_radiance = sd.interp_fn(wavelength)\n",
        "    '''\n",
        "    assert np.issubdtype(np.dtype(type(temperature)), float)\n",
        "\n",
        "    if shape is None:\n",
        "        shape = SpectralShape(380, 780, 10)\n",
        "\n",
        "    wavelengths = shape.range()\n",
        "    values = planck_law(wavelengths * 1e-9, temperature) * 1e-9\n",
        "\n",
        "    return SpectralDistribution(values, wavelengths)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5cc218c5-7884-4586-b582-99a34061abac",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331,
          "referenced_widgets": [
            "b1a39989a9334b4c986df60ec092dd95",
            "102d0612863d4880a091ba9ad9c71a79",
            "161bed9522fb40b9bddf2ba5283846db",
            "cf83720a40c64445ba338670a11a8e1a",
            "3b4c3ff5d0324e398016ba0d624a054e"
          ]
        },
        "id": "5cc218c5-7884-4586-b582-99a34061abac",
        "outputId": "45674723-3742-47ae-cc1b-69baebfbbade"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "FloatSlider(value=6500.0, continuous_update=False, description='temperature', max=25000.0, min=500.0, step=500…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b1a39989a9334b4c986df60ec092dd95"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "cf83720a40c64445ba338670a11a8e1a"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "# for analysis\n",
        "def _plot_blackbody_sd():\n",
        "\n",
        "    shape0 = SpectralShape(100, 2000, 10)\n",
        "\n",
        "    _, ax = plt.subplots(1, 1, figsize=(16, 4))\n",
        "\n",
        "    output = widgets.Output()\n",
        "\n",
        "    @output.capture(clear_output=True, wait=True)\n",
        "    def on_value_change(temperature):\n",
        "        sd = sd_blackbody(temperature, shape0)\n",
        "\n",
        "        ax.clear()\n",
        "\n",
        "        start, end = sd.shape.boundaries\n",
        "        plot_sd(sd, SpectralShape(start, end, 1), color='k', ax=ax)\n",
        "\n",
        "        ax.vlines(\n",
        "            x=[380, 780],\n",
        "            ymin=0,\n",
        "            ymax=1,\n",
        "            color='r',\n",
        "            linestyle='-.',\n",
        "            transform=ax.get_xaxis_transform(),\n",
        "        )\n",
        "\n",
        "        ax.set_title('Black-body radiation {} K'.format(temperature))\n",
        "        ax.set_ylabel(r'Spectral radiance [$W\\cdot sr^{-1}\\cdot  m^{-2} nm^{-1}]$')\n",
        "\n",
        "        display(ax.figure)\n",
        "\n",
        "    fs0 = widgets.FloatSlider(\n",
        "        min=500, max=25000, step=500, value=6500, continuous_update=False\n",
        "    )\n",
        "\n",
        "    widgets.interactive(on_value_change, temperature=fs0)\n",
        "    display(fs0, output)\n",
        "    plt.close()\n",
        "    on_value_change(fs0.value)\n",
        "\n",
        "\n",
        "_plot_blackbody_sd()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "e1936543-99a8-4b1e-8328-ebda465db206",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 345,
          "referenced_widgets": [
            "90dc41f46e1d40ba9f61f916f1911fff",
            "9411f49d1dc442cb8d110bb46c24d556",
            "d6b811c16db44dcaa12a1b90272f4643",
            "9c96613f1f6e44caa9c6d7132c37a653",
            "d931c1690f814e8ba255866dd419464b"
          ]
        },
        "id": "e1936543-99a8-4b1e-8328-ebda465db206",
        "outputId": "95944a19-57f4-4302-eb7f-dbead43f53dd"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "FloatSlider(value=6500.0, continuous_update=False, description='temperature', max=25001.0, min=500.0, step=500…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "90dc41f46e1d40ba9f61f916f1911fff"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9c96613f1f6e44caa9c6d7132c37a653"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "# for analysis\n",
        "def _plot_integrand():\n",
        "\n",
        "    shape = SpectralShape(380, 780, 10)\n",
        "    cmfs_msds = msds_cmfs(shape)\n",
        "\n",
        "    fig, axes = plt.subplots(\n",
        "        1,\n",
        "        3,\n",
        "        subplot_kw={'xlabel': r'$\\lambda/nm$'},\n",
        "        figsize=(18, 4),\n",
        "        constrained_layout=True,\n",
        "    )\n",
        "\n",
        "    fig.set_constrained_layout_pads(hspace=0.1, wspace=0.1)\n",
        "\n",
        "    # cmfs values\n",
        "    ax = axes[2]\n",
        "    start, end = cmfs_msds.shape.boundaries\n",
        "    plot_various_sds(\n",
        "        cmfs_msds,\n",
        "        SpectralShape(start, end, 1),\n",
        "        colors=['r', 'g', 'b'],\n",
        "        labels=[r'$\\bar{x}(\\lambda)$', r'$\\bar{y}(\\lambda)$', r'$\\bar{z}(\\lambda)$'],\n",
        "        ax=ax,\n",
        "    )\n",
        "    ax.set_title('CIE 1931 standard colorimetric observer')\n",
        "\n",
        "    output = widgets.Output()\n",
        "\n",
        "    @output.capture(clear_output=True, wait=True)\n",
        "    def on_value_change(temperature):\n",
        "        blackbody_sd = sd_blackbody(temperature, shape)\n",
        "        msds = synthesize(blackbody_sd, cmfs_msds)\n",
        "\n",
        "        #\n",
        "        ax = axes[0]\n",
        "        ax.clear()\n",
        "        start, end = msds.shape.boundaries\n",
        "        plot_various_sds(\n",
        "            msds, SpectralShape(start, end, 1), colors=['r', 'g', 'b'], ax=ax\n",
        "        )\n",
        "        ax.set_ylabel(r'Spectral radiance [$W\\cdot sr^{-1}\\cdot  m^{-2} nm^{-1}]$')\n",
        "\n",
        "        # spectral radiances\n",
        "        ax = axes[1]\n",
        "        ax.clear()\n",
        "        start, end = blackbody_sd.shape.boundaries\n",
        "        plot_sd(blackbody_sd, SpectralShape(start, end, 1), color='k', ax=ax)\n",
        "        ax.set_title('Black-body radiation {} K'.format(temperature))\n",
        "        ax.set_ylabel(r'Spectral radiance [$W\\cdot sr^{-1}\\cdot  m^{-2} nm^{-1}]$')\n",
        "\n",
        "        display(fig)\n",
        "\n",
        "    fs0 = widgets.FloatSlider(\n",
        "        min=500, max=25001, step=500, value=6500, continuous_update=False\n",
        "    )\n",
        "\n",
        "    widgets.interactive(on_value_change, temperature=fs0)\n",
        "    display(fs0, output)\n",
        "    plt.close()\n",
        "    on_value_change(fs0.value)\n",
        "\n",
        "\n",
        "_plot_integrand()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "e43b7f25-cac6-45f3-8ca4-847cd234f67d",
      "metadata": {
        "id": "e43b7f25-cac6-45f3-8ca4-847cd234f67d"
      },
      "source": [
        "#### Visualizing color temperatures\n",
        "\n",
        "Computing XYZ From Spectral Data  \n",
        "- [Computing XYZ from spectral data; en.wikipedia.org](https://en.wikipedia.org/wiki/CIE_1931_color_space#Computing_XYZ_from_spectral_data)  \n",
        "$$\n",
        "\\begin{aligned}\n",
        "X\n",
        "&=\\int_{\\lambda} L_{e,\\Omega,\\lambda}(\\lambda) \\, \\bar{x}(\\lambda) \\, d\\lambda\\\\\n",
        "Y\n",
        "&=\\int_{\\lambda} L_{e,\\Omega,\\lambda}(\\lambda) \\, \\bar{y}(\\lambda) \\, d\\lambda\\\\\n",
        "Z\n",
        "&=\\int_{\\lambda} L_{e,\\Omega,\\lambda}(\\lambda) \\, \\bar{z}(\\lambda) \\, d\\lambda\n",
        "\\end{aligned}\n",
        "$$\n",
        "\n",
        "Data transformation pipeline\n",
        "$$\n",
        "\\text{XYZ} \\to \\text{linear rgb} \\to \\text{non-linear rgb}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "625a88a3-091b-440e-b275-3896ff6d6b99",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 809,
          "referenced_widgets": [
            "253ddce0eeea43849e494910463f278b",
            "f4bf0a4079b74ae7916e3f1dc7e5237a",
            "82a81c61bce848818e036ac9eb250076",
            "a2d3b0ef773c4f9ead5203b360fa0522"
          ]
        },
        "id": "625a88a3-091b-440e-b275-3896ff6d6b99",
        "outputId": "c63699c6-aa77-4297-a954-b054c1ecb85e"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ],
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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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' width=720.0/>\n",
              "            </div>\n",
              "        "
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "253ddce0eeea43849e494910463f278b"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "def emissive_case_example():\n",
        "    #\n",
        "    sample_size = 5000\n",
        "    temperatures = np.arange(500, 12001, 500, dtype=float)\n",
        "\n",
        "    shape = SpectralShape(380, 780, 10)\n",
        "    wl_min, wl_max = shape.boundaries\n",
        "\n",
        "    cmfs_msds = msds_cmfs(shape)\n",
        "\n",
        "    colors = []\n",
        "    for temperature in temperatures:\n",
        "        u = np.random.uniform(low=0, high=1, size=sample_size)\n",
        "        wl = wl_min + (wl_max - wl_min) * u\n",
        "\n",
        "        sd = sd_blackbody(temperature, shape)\n",
        "        msds = synthesize(sd, cmfs_msds)\n",
        "\n",
        "        XYZ = (wl_max - wl_min) * np.mean(msds.interp_fn(wl), axis=-1)\n",
        "        XYZ /= np.sum(XYZ)\n",
        "\n",
        "        colors.append(xyz_to_rgb(XYZ))\n",
        "\n",
        "    output_colors = [gamma_compression(color) for color in colors]\n",
        "\n",
        "    #\n",
        "    annotations = [\n",
        "        '{:4d}K'.format(temperature.astype(int)) for temperature in temperatures\n",
        "    ]\n",
        "    ax = plot_colors(\n",
        "        output_colors,\n",
        "        nrows_ncols=(4, 6),\n",
        "        annotations=annotations,\n",
        "        backend_kwargs={'figsize': (10, 10)},\n",
        "    )\n",
        "    ax.set_title('Color Temperatures')\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "emissive_case_example()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "398331bc-e84b-4c62-8287-8d9a57b8b04a",
      "metadata": {
        "id": "398331bc-e84b-4c62-8287-8d9a57b8b04a"
      },
      "source": [
        "### Reflective and transmissive cases"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "06018860-2e4f-4a78-81e5-f5c92daef90d",
      "metadata": {
        "id": "06018860-2e4f-4a78-81e5-f5c92daef90d"
      },
      "source": [
        "#### Macbeth color checker"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "85673f62-07e0-4f67-b549-0d564dce2431",
      "metadata": {
        "id": "85673f62-07e0-4f67-b549-0d564dce2431"
      },
      "source": [
        "##### Relative spectral power distribution (SPD) function of the standard illuminant D65\n",
        "- [Illuminant series D; en.wikipedia.org](https://en.wikipedia.org/wiki/Standard_illuminant#Illuminant_series_D)  \n",
        "- [Illuminant_D65; en.wikipedia.org](https://en.wikipedia.org/wiki/Illuminant_D65)  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8c8a9215-2bf7-42e8-81f7-61e8f6fb7cfe",
      "metadata": {
        "id": "8c8a9215-2bf7-42e8-81f7-61e8f6fb7cfe"
      },
      "outputs": [],
      "source": [
        "def T_to_xy(T):\n",
        "    '''Converts from the correlated color temperature of a CIE D-illuminant\n",
        "    to the chromaticity of that D-illuminant.\n",
        "    '''\n",
        "    assert (\n",
        "        isinstance(T, (np.generic, np.ndarray))\n",
        "        and np.issubdtype(T.dtype, float)\n",
        "        or isinstance(T, float)\n",
        "    )\n",
        "    assert np.all(T >= 4000) and np.all(T <= 25000)\n",
        "\n",
        "    def fn0(x):\n",
        "        return (\n",
        "            -4.6070 * (1e9 / (x**3))\n",
        "            + 2.9678 * (1e6 / (x**2))\n",
        "            + 0.09911 * (1e3 / x)\n",
        "            + 0.244063\n",
        "        )\n",
        "\n",
        "    def fn1(x):\n",
        "        return (\n",
        "            -2.0064 * (1e9 / (x**3))\n",
        "            + 1.9018 * (1e6 / (x**2))\n",
        "            + 0.24748 * (1e3 / x)\n",
        "            + 0.237040\n",
        "        )\n",
        "\n",
        "    cond = T <= 7000\n",
        "    xD = np.piecewise(T, [cond, np.logical_not(cond)], [fn0, fn1])\n",
        "\n",
        "    yD = -3.000 * (xD**2) + 2.870 * xD - 0.275\n",
        "\n",
        "    return np.stack([xD, yD], axis=-1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "43ae4b2e-3446-423e-af17-7371aeb6ba05",
      "metadata": {
        "id": "43ae4b2e-3446-423e-af17-7371aeb6ba05"
      },
      "outputs": [],
      "source": [
        "@functools.lru_cache(maxsize=1)\n",
        "def msds_CIE_illuminants_D_components():\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> msds = msds_CIE_illuminants_D_components()\n",
        "    >>> components = msds.interp_fn(wavelength)\n",
        "    '''\n",
        "    skiprows = lambda x: (x>0) and (x%2 == 0)\n",
        "    df = pd.read_csv('CIE_daylight_components.csv', index_col=0, skiprows=skiprows)\n",
        "    wavelengths = df.index.to_numpy()\n",
        "    S0 = df['S0(l)'].to_numpy()\n",
        "    S1 = df['S1(l)'].to_numpy()\n",
        "    S2 = df['S2(l)'].to_numpy()    \n",
        "    comps = np.stack([S0, S1, S2], axis=0)\n",
        "\n",
        "    return MultiSpectralDistributions(comps, wavelengths)\n",
        "\n",
        "\n",
        "msds_CIE_illuminants_D_components.cache_clear()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "66f13a6b-55a1-470c-ad4c-54983e362ecd",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 377,
          "referenced_widgets": [
            "c3e843be3d524cca9f1d4afc81ebb293",
            "d0dce17fc73f4ba089f8b27de88d7ea6",
            "3c738841f3f8433e8fc95166df1223f0",
            "a39f3585be3e43c39a41439863c531d1"
          ]
        },
        "id": "66f13a6b-55a1-470c-ad4c-54983e362ecd",
        "outputId": "ccdfbfa9-6e4b-4090-8725-f953602e6c82"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ],
            "image/png": 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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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' width=432.0/>\n",
              "            </div>\n",
              "        "
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c3e843be3d524cca9f1d4afc81ebb293"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "# for analysis\n",
        "msds = msds_CIE_illuminants_D_components()\n",
        "start, end = msds.shape.boundaries\n",
        "\n",
        "ax = plot_various_sds(\n",
        "    msds,\n",
        "    SpectralShape(start, end, 1),\n",
        "    colors=['b', 'g', 'r'],\n",
        "    labels=[r'$S_0(\\lambda)$', r'$S_1(\\lambda)$', r'$S_2(\\lambda)$'],\n",
        ")\n",
        "ax.set_title('CIE illuminants D components')\n",
        "ax.legend()\n",
        "del msds, start, end, ax"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fc17b2c0-2a14-468b-a19c-0baeaa953b00",
      "metadata": {
        "id": "fc17b2c0-2a14-468b-a19c-0baeaa953b00"
      },
      "outputs": [],
      "source": [
        "def sd_CIE_illuminant_D(T):\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> sd = sd_CIE_illuminant_D(6503.51)\n",
        "    >>> relative_power = sd.interp_fn(wavelength)\n",
        "    '''\n",
        "    assert np.issubdtype(np.dtype(type(T)), float)\n",
        "\n",
        "    msds = msds_CIE_illuminants_D_components()\n",
        "    comps = msds.values\n",
        "\n",
        "    S0, S1, S2 = comps[0], comps[1], comps[2]\n",
        "\n",
        "    xy = T_to_xy(T)\n",
        "    xD, yD = xy[..., 0], xy[..., 1]\n",
        "\n",
        "    M = 0.0241 + 0.2562 * xD - 0.7341 * yD\n",
        "\n",
        "    M1 = (-1.3515 - 1.7703 * xD + 5.9114 * yD) / M\n",
        "    M2 = (0.0300 - 31.4424 * xD + 30.0717 * yD) / M\n",
        "\n",
        "    S = S0 + M1 * S1 + M2 * S2\n",
        "\n",
        "    return SpectralDistribution(S, msds.wavelengths)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "02f70e0b-9784-4759-b76c-fac0259f52d9",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331,
          "referenced_widgets": [
            "abb24bd295ee40d7af72cca8e6247837",
            "423f3362c6754ad4b40e97788f9167ef",
            "b37bb7cfe01345aa9ec39682f6d3e7d0",
            "65a64b2e47ef4c82b62826fec4284db8",
            "f684a186f6af456e953abba911b04831",
            "4c0caac0a5fa4031968c55716dfaeb8d",
            "ac596d3beb5d40cbab41448c9e3b2863",
            "078f85a65b8348bd80b1e85f036e1a4e",
            "2ad819894b8b4cbeb7a84673cafad46a",
            "6002806b764b4459b6858722ed4635d2",
            "a7f0b75b11a3407bb7a88b2dd624e511",
            "ae804954b8474f8c96077d5791535d3e",
            "bd63f1eb99dd428aac2b9c0a4008d616"
          ]
        },
        "id": "02f70e0b-9784-4759-b76c-fac0259f52d9",
        "outputId": "478cdd5d-ab89-473d-a715-4132e6a2e00a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "FloatSlider(value=6503.51, continuous_update=False, description='temperature', max=25000.0, min=4000.0, step=0…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "abb24bd295ee40d7af72cca8e6247837"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
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              "version_minor": 0,
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      ],
      "source": [
        "# for analysis\n",
        "def _plot_CIE_illuminant_D_sd():\n",
        "\n",
        "    _, ax = plt.subplots(1, 1)\n",
        "\n",
        "    output = widgets.Output()\n",
        "\n",
        "    @output.capture(clear_output=True, wait=True)\n",
        "    def on_value_change(temperature):\n",
        "        sd = sd_CIE_illuminant_D(temperature)\n",
        "\n",
        "        ax.clear()\n",
        "\n",
        "        start, end = sd.shape.boundaries\n",
        "        plot_sd(\n",
        "            sd,\n",
        "            SpectralShape(start, end, 1),\n",
        "            color='k',\n",
        "            label='{:.2f} K'.format(temperature),\n",
        "            ax=ax,\n",
        "        )\n",
        "\n",
        "        ax.vlines(\n",
        "            x=[380, 780],\n",
        "            ymin=0,\n",
        "            ymax=1,\n",
        "            color='r',\n",
        "            linestyle='-.',\n",
        "            transform=ax.get_xaxis_transform(),\n",
        "        )\n",
        "\n",
        "        ax.set_title('CIE Standard Illuminant D')\n",
        "        ax.legend()\n",
        "\n",
        "        display(ax.figure)\n",
        "\n",
        "    fs0 = widgets.FloatSlider(\n",
        "        min=4000, max=25000, step=0.01, value=6503.51, continuous_update=False\n",
        "    )\n",
        "\n",
        "    widgets.interactive(on_value_change, temperature=fs0)\n",
        "    display(fs0, output)\n",
        "    plt.close()\n",
        "    on_value_change(fs0.value)\n",
        "\n",
        "\n",
        "_plot_CIE_illuminant_D_sd()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "bc11089d-39cb-4e40-b349-ca9c3b44cf4c",
      "metadata": {
        "id": "bc11089d-39cb-4e40-b349-ca9c3b44cf4c"
      },
      "outputs": [],
      "source": [
        "sd_CIE_illuminant_D65 = lambda: sd_CIE_illuminant_D(6503.51)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "2b90d425-44d7-49c4-9df4-c5eec348b470",
      "metadata": {
        "id": "2b90d425-44d7-49c4-9df4-c5eec348b470"
      },
      "source": [
        "##### The spectral reflectance data of the 24 colors in MCC  \n",
        "- [ColorChecker data; babelcolor.com](https://babelcolor.com/colorchecker-2.htm#xl_CCP2_data)  \n",
        "- [ColorChecker_RGB_and_spectra.xls; babelcolor.com](https://babelcolor.com/index_htm_files/ColorChecker_RGB_and_spectra.zip)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "95f32f4c-6281-401b-a607-6340b01e56f5",
      "metadata": {
        "id": "95f32f4c-6281-401b-a607-6340b01e56f5"
      },
      "outputs": [],
      "source": [
        "@functools.lru_cache(maxsize=1)\n",
        "def sds_MCC():\n",
        "    '''\n",
        "    Examples\n",
        "    --------\n",
        "    >>> sds = sds_MCC()\n",
        "    >>> spectral_reflectance = sds[idx].interp_fn(wavelength)\n",
        "    '''\n",
        "    df = pd.read_csv('BabelColor_spectral_data.csv', index_col=0, skiprows=1)\n",
        "\n",
        "    wavelengths_raw = df.columns[1:].values.astype(int).tolist()\n",
        "    wavelengths = wavelengths_raw + [\n",
        "        i for i in range(wavelengths_raw[-1] + 10, 781, 10)\n",
        "    ]\n",
        "    num_wavelengths, threshold = len(wavelengths), len(wavelengths_raw)\n",
        "\n",
        "    sds = []\n",
        "    for index, row in df.iterrows():\n",
        "        s = row[1:]\n",
        "        iterable = (s[i] if i < threshold else 0 for i in range(num_wavelengths))\n",
        "        values = np.fromiter(iterable, dtype=float)\n",
        "\n",
        "        sd = SpectralDistribution(values, wavelengths)\n",
        "\n",
        "        sds.append(sd)\n",
        "\n",
        "    return sds\n",
        "\n",
        "\n",
        "sds_MCC.cache_clear()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b34c6372-3f4f-415e-96a6-5c7d94ddb602",
      "metadata": {
        "colab": {
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          "referenced_widgets": [
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            "9f053b226db24eba81c9aa9f5f6cc113",
            "64cb1ef0492c46f5950be15feaebc737",
            "695efbec89534ecaaf7199ea8632b40a",
            "6e9849e001874f6387640726c4789a02",
            "e7bcd6ec647c4b7eb51c57af84228d47",
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        "outputId": "b50400af-0bb4-48e3-99d5-6c252ee08c6e"
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dropdown(description='Select data:', options=((' 0: dark skin', 0), (' 1: light skin', 1), (' 2: blue sky', 2)…"
            ],
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      ],
      "source": [
        "# for analysis\n",
        "def _plot_mcc_sds():\n",
        "\n",
        "    df = pd.read_csv('BabelColor_spectral_data.csv', index_col=0, skiprows=1)\n",
        "    color_names = df['Color name'].to_list()\n",
        "    del df\n",
        "\n",
        "    sds = sds_MCC()\n",
        "\n",
        "    _, ax = plt.subplots(1, 1)\n",
        "    ax.set_ylim(0, 1)\n",
        "\n",
        "    output = widgets.Output()\n",
        "\n",
        "    @output.capture(clear_output=True, wait=True)\n",
        "    def on_value_change(idx):\n",
        "        ax.clear()\n",
        "\n",
        "        start, end = sds[idx].shape.boundaries\n",
        "        plot_sd(sds[idx], SpectralShape(start, end, 1), color='k', ax=ax)\n",
        "        ax.vlines(\n",
        "            x=730,\n",
        "            ymin=0,\n",
        "            ymax=1,\n",
        "            colors='r',\n",
        "            linestyle='-.',\n",
        "            transform=ax.get_xaxis_transform(),\n",
        "        )\n",
        "        ax.set_title('{}'.format(color_names[idx]))\n",
        "\n",
        "        display(ax.figure)\n",
        "\n",
        "    options = [\n",
        "        ('{:2d}: {}'.format(i, color_name), i)\n",
        "        for i, color_name in enumerate(color_names)\n",
        "    ]\n",
        "\n",
        "    dd = widgets.Dropdown(options=options, value=0, description='Select data:')\n",
        "\n",
        "    widgets.interactive(on_value_change, idx=dd)\n",
        "    display(dd, output)\n",
        "    plt.close()\n",
        "    on_value_change(dd.value)\n",
        "\n",
        "\n",
        "_plot_mcc_sds()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f9f4dec5-15f0-4e3b-b709-f2513754fee2",
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          "height": 273,
          "referenced_widgets": [
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            "71b19bb81b5f420c8a942a8b352bf841",
            "ee198c2181344d9e8a6d88cf7b07f1d9"
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        "outputId": "0b3f535e-babb-489e-e130-9d71383e848c"
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dropdown(description='Select data:', options=((' 0: dark skin', 0), (' 1: light skin', 1), (' 2: blue sky', 2)…"
            ],
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
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              "version_minor": 0,
              "model_id": "71b19bb81b5f420c8a942a8b352bf841"
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          }
        }
      ],
      "source": [
        "# for analysis\n",
        "def _plot_integrand():\n",
        "\n",
        "    df = pd.read_csv('BabelColor_spectral_data.csv', index_col=0, skiprows=1)\n",
        "    color_names = df['Color name'].to_list()\n",
        "    del df\n",
        "\n",
        "    shape = SpectralShape(380, 780, 10)\n",
        "\n",
        "    MCC_sds = sds_MCC()\n",
        "    D65_spd = sd_CIE_illuminant_D65()\n",
        "    cmfs_msds = msds_cmfs(shape)\n",
        "\n",
        "    temp_msds = synthesize(D65_spd, cmfs_msds)\n",
        "\n",
        "    fig, axes = plt.subplots(\n",
        "        1,\n",
        "        4,\n",
        "        subplot_kw={'xlabel': r'$\\lambda/nm$'},\n",
        "        figsize=(16, 3),\n",
        "        constrained_layout=True,\n",
        "    )\n",
        "\n",
        "    fig.set_constrained_layout_pads(hspace=0.1, wspace=0.1)\n",
        "\n",
        "    # relative powers\n",
        "    ax = axes[2]\n",
        "    start, end = D65_spd.shape.boundaries\n",
        "    plot_sd(D65_spd, SpectralShape(start, end, 1), color='k', ax=ax)\n",
        "    ax.set_title('CIE standard illuminant D65')\n",
        "\n",
        "    # cmfs values\n",
        "    ax = axes[3]\n",
        "    start, end = cmfs_msds.shape.boundaries\n",
        "    plot_various_sds(\n",
        "        cmfs_msds,\n",
        "        SpectralShape(start, end, 1),\n",
        "        colors=['r', 'g', 'b'],\n",
        "        labels=[r'$\\bar{x}(\\lambda)$', r'$\\bar{y}(\\lambda)$', r'$\\bar{z}(\\lambda)$'],\n",
        "        ax=ax,\n",
        "    )\n",
        "    ax.set_title('CIE 1931 standard colorimetric observer')\n",
        "\n",
        "    output = widgets.Output()\n",
        "\n",
        "    @output.capture(clear_output=True, wait=True)\n",
        "    def on_value_change(idx):\n",
        "        msds = synthesize(MCC_sds[idx], temp_msds)\n",
        "\n",
        "        #\n",
        "        ax = axes[0]\n",
        "        ax.clear()\n",
        "        start, end = msds.shape.boundaries\n",
        "        plot_various_sds(\n",
        "            msds, SpectralShape(start, end, 1), colors=['r', 'g', 'b'], ax=ax\n",
        "        )\n",
        "\n",
        "        # spectral reflectances\n",
        "        ax = axes[1]\n",
        "        ax.clear()\n",
        "        start, end = MCC_sds[idx].shape.boundaries\n",
        "        plot_sd(MCC_sds[idx], SpectralShape(start, end, 1), color='k', ax=ax)\n",
        "        ax.set_title(color_names[idx])\n",
        "\n",
        "        display(fig)\n",
        "\n",
        "    options = [\n",
        "        ('{:2d}: {}'.format(i, color_name), i)\n",
        "        for i, color_name in enumerate(color_names)\n",
        "    ]\n",
        "\n",
        "    dd = widgets.Dropdown(options=options, value=0, description='Select data:')\n",
        "\n",
        "    widgets.interactive(on_value_change, idx=dd)\n",
        "    display(dd, output)\n",
        "    plt.close()\n",
        "    on_value_change(dd.value)\n",
        "\n",
        "\n",
        "_plot_integrand()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "eb222431-8d10-410f-8f03-299deba18440",
      "metadata": {
        "id": "eb222431-8d10-410f-8f03-299deba18440"
      },
      "source": [
        "#### Visualizing the color checker\n",
        "Computing XYZ from spectral data  \n",
        "- [Computing XYZ from spectral data; en.wikipedia.org](https://en.wikipedia.org/wiki/CIE_1931_color_space#Computing_XYZ_from_spectral_data) \n",
        "\n",
        "$$\n",
        "\\begin{aligned}\n",
        "X&=\\frac{1}{N} \\int_{\\lambda} S(\\lambda)\\,I(\\lambda)\\,\\bar{x}(\\lambda)\\,d\\lambda\\\\\n",
        "Y&=\\frac{1}{N} \\int_{\\lambda} S(\\lambda)\\,I(\\lambda)\\,\\bar{y}(\\lambda)\\,d\\lambda\\\\\n",
        "Z&=\\frac{1}{N} \\int_{\\lambda} S(\\lambda)\\,I(\\lambda)\\,\\bar{z}(\\lambda)\\,d\\lambda\\\\\n",
        "\\text{where}\\\\\n",
        "N&=\\int_{\\lambda} I(\\lambda)\\,\\bar{y}(\\lambda)\\,d\\lambda\n",
        "\\end{aligned}\n",
        "$$\n",
        "\n",
        "Data transformation pipeline\n",
        "$$\n",
        "\\text{XYZ} \\to \\text{linear rgb} \\to \\text{non-linear rgb}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5f61f3fd-bef4-4127-8835-3e9ff06fc2bf",
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
            ],
            "image/png": 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",
            "text/html": [
              "\n",
              "            <div style=\"display: inline-block;\">\n",
              "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
              "                    Figure\n",
              "                </div>\n",
              "                <img 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              "            </div>\n",
              "        "
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1e94dc7372644b00a97c20c23f71d0f2"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/d2e234f7cc04bf79/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "def reflective_and_transmissive_cases_example():\n",
        "    #\n",
        "    sample_size = 5000\n",
        "\n",
        "    MCC_sds = sds_MCC()\n",
        "    D65_spd = sd_CIE_illuminant_D65()\n",
        "\n",
        "    shape = SpectralShape(380, 780, 10)\n",
        "    cmfs_msds = msds_cmfs(shape)\n",
        "\n",
        "    temp_msds = synthesize(D65_spd, cmfs_msds)\n",
        "    sd = synthesize(D65_spd, cmfs_msds.to_sds()[1])\n",
        "\n",
        "    wl_min, wl_max = shape.boundaries\n",
        "\n",
        "    colors = []\n",
        "    for MCC_sd in MCC_sds:\n",
        "        u = np.random.uniform(low=0, high=1, size=sample_size)\n",
        "        wl = wl_min + (wl_max - wl_min) * u\n",
        "\n",
        "        msds = synthesize(MCC_sd, temp_msds)\n",
        "        s0 = np.sum(msds.interp_fn(wl), axis=-1)\n",
        "        s1 = np.sum(sd.interp_fn(wl), axis=-1)\n",
        "\n",
        "        XYZ = s0 / s1\n",
        "\n",
        "        colors.append(xyz_to_rgb(XYZ))\n",
        "\n",
        "    output_colors = [gamma_compression(color) for color in colors]\n",
        "\n",
        "    #\n",
        "    ax = plot_colors(output_colors, nrows_ncols=(4, 6), shape='rect')\n",
        "    ax.set_title('Macbeth Color Checker')\n",
        "\n",
        "\n",
        "reflective_and_transmissive_cases_example()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "97f3ba53-24db-4289-9969-1b1a88f8dedc",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "97f3ba53-24db-4289-9969-1b1a88f8dedc",
        "outputId": "4985f51b-5a1f-45d2-bfa4-7e55533eb93f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CacheInfo(hits=3, misses=1, maxsize=1, currsize=1)\n",
            "CacheInfo(hits=2, misses=1, maxsize=1, currsize=1)\n"
          ]
        }
      ],
      "source": [
        "print(msds_CIE_illuminants_D_components.cache_info())\n",
        "print(sds_MCC.cache_info())"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.15"
    },
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "ee1fa13d14134c5f8e1a84cff0b1d92d": {
          "model_module": "jupyter-matplotlib",
          "model_name": "MPLCanvasModel",
          "model_module_version": "^0.11",
          "state": {
            "_cursor": "default",
            "_data_url": 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        },
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            "_view_name": "StyleView",
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        "cf83720a40c64445ba338670a11a8e1a": {
          "model_module": "@jupyter-widgets/output",
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            "_view_module": "@jupyter-widgets/output",
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            "_view_name": "OutputView",
            "layout": "IPY_MODEL_3b4c3ff5d0324e398016ba0d624a054e",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "<Figure size 1152x288 with 1 Axes>",
                  "image/png": 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            "_view_name": "OutputView",
            "layout": "IPY_MODEL_d931c1690f814e8ba255866dd419464b",
            "msg_id": "",
            "outputs": [
              {
                "output_type": "display_data",
                "data": {
                  "text/plain": "<Figure size 1296x288 with 3 Axes>",
                  "image/png": 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

Required files

• CIE_daylight_components.csv
• BabelColor_spectral_data.csv