{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Colour - Colour Science for Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import Image\n",
    "\n",
    "Image(filename=\"resources/images/Colour_Logo_Medium_001.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Colour](https://github.com/colour-science/colour/) is a **Python** colour science package implementing a comprehensive number of colour theory transformations and algorithms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from colour.plotting import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "colour_style();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1280x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_visible_spectrum();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is a companion guide and usage showcase. Most of the public API is available from the root `colour` namespace:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['domain_range_scale', 'get_domain_range_scale', 'set_domain_range_scale', 'CHROMATIC_ADAPTATION_METHODS', 'CHROMATIC_ADAPTATION_TRANSFORMS', 'CMCCAT2000_VIEWING_CONDITIONS', 'chromatic_adaptation', 'CubicSplineInterpolator', 'Extrapolator', 'KernelInterpolator', 'NearestNeighbourInterpolator', 'LinearInterpolator', 'NullInterpolator', 'PchipInterpolator', 'SpragueInterpolator', 'TABLE_INTERPOLATION_METHODS', 'kernel_cardinal_spline', 'kernel_lanczos', 'kernel_linear', 'kernel_nearest_neighbour', '...']\n"
     ]
    }
   ],
   "source": [
    "import colour\n",
    "\n",
    "print(colour.__all__[:20] + [\"...\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The notebook has been divided in different chapters dedicated to showcase the API:\n",
    "\n",
    "* Colorimetry\n",
    "    * [Spectrum](colorimetry/spectrum.ipynb)\n",
    "    * [Spectral Bandpass Dependence Correction](colorimetry/correction.ipynb)\n",
    "    * [Colour Matching Functions](colorimetry/cmfs.ipynb)\n",
    "    * [Dominant Wavelength & Purity](colorimetry/dominant_wavelength.ipynb)\n",
    "    * [Photometry](colorimetry/photometry.ipynb)\n",
    "    * [Luminous Efficiency Functions](colorimetry/lefs.ipynb)\n",
    "    * [Blackbody](colorimetry/blackbody.ipynb)\n",
    "    * [Illuminants](colorimetry/illuminants.ipynb)\n",
    "    * [Light Sources](colorimetry/light_sources.ipynb)\n",
    "    * [Lightness](colorimetry/lightness.ipynb)\n",
    "    * [Luminance](colorimetry/luminance.ipynb)\n",
    "    * [Whiteness](colorimetry/luminance.ipynb)\n",
    "* Colour Temperature\n",
    "    * [Correlated Colour Temperature](temperature/cct.ipynb)\n",
    "* Chromatic Adaptation\n",
    "    * [Chromatic Adaptation - Johannes Von Kries Hypothesis](adaptation/vonkries.ipynb)\n",
    "    * [Fairchild (1990) Chromatic Adaptation Model](adaptation/fairchild1990.ipynb)\n",
    "    * [CIE 1994 Chromatic Adaptation Model](adaptation/cie1994.ipynb)\n",
    "    * [CMCCAT2000 Chromatic Adaptation Model](adaptation/cmccat2000.ipynb)\n",
    "* [Corresponding Chromaticities Prediction](corresponding/prediction.ipynb)\n",
    "* Colour Models\n",
    "    * [CIE xyY](models/cie_xyy.ipynb)\n",
    "    * [CIE Lab](models/cie_lab.ipynb)\n",
    "    * [CIE Luv](models/cie_luv.ipynb)\n",
    "    * [CIE UCS](models/cie_ucs.ipynb)\n",
    "    * [CIE UVW](models/cie_uvw.ipynb)\n",
    "    * [IPT Colourspace](models/ipt.ipynb)\n",
    "    * [$IC_TC_P$ Colourspace](models/ictcp.ipynb)\n",
    "    * [Hunter Lab](models/hunter_lab.ipynb)    \n",
    "    * [Hunter Rdab](models/hunter_rdab.ipynb)    \n",
    "    * [RGB](models/rgb.ipynb)    \n",
    "    * [YCbCr Colour Encoding](models/ycbcr.ipynb)    \n",
    "    * [MacAdam (1942) Ellipses (Observer PGN)](models/macadam_ellipses.ipynb)    \n",
    "* Colour Difference\n",
    "    * [$\\Delta E_{ab}$](difference/delta_e.ipynb)\n",
    "* Colour Appearance Models\n",
    "    * [Nayatani (1995)](appearance/nayatani95.ipynb)\n",
    "    * [Hunt](appearance/hunt.ipynb)\n",
    "    * [RLAB](appearance/rlab.ipynb)\n",
    "    * [ATD (1995)](appearance/atd95.ipynb)\n",
    "    * [LLAB(l:c)](appearance/llab.ipynb)\n",
    "    * [CIECAM02](appearance/ciecam02.ipynb)\n",
    "    * [CAM16](appearance/cam16.ipynb)\n",
    "* Colour Notation Systems\n",
    "    * [Munsell Renotation System](notation/munsell.ipynb)\n",
    "* Characterisation\n",
    "    * [Colour Fitting](characterisation/fitting.ipynb)\n",
    "    * [Displays](characterisation/displays.ipynb)\n",
    "* Colourspace Volume Computation & Optimal Colour Stimuli\n",
    "    * [MacAdam Limits](volume/macadam_limits.ipynb)\n",
    "    * [Pointer's Gamut](volume/pointer_gamut.ipynb)\n",
    "    * [RGB Colourspace](volume/rgb.ipynb)    \n",
    "    * [Visible Spectrum](volume/spectrum.ipynb)    \n",
    "* Colour Quality\n",
    "    * [Colour Rendering Index](quality/cri.ipynb)\n",
    "* Contrast Sensitivity Function\n",
    "    * [Barten (1999)](contrast/barten1999.ipynb)\n",
    "* Optical Phenomena\n",
    "    * [Rayleigh Optical Depth](phenomena/rayleigh.ipynb)\n",
    "* [Automatic Conversion Graph](graph/conversion.ipynb)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}