{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Colour 0.3.8 - Computational Changes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[colour-science.org](http://colour-science.org) - July 9, 2016"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spectral Computations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section illustrates some of the computational differences to expect when using the new **ASTM E308–15** compliant spectral code of *Colour 0.3.8*.\n",
    "\n",
    "In the following example, the overall $\\Delta E_{2000}$ colour difference mean between *Colour 0.3.7* and *Colour 0.3.8* spectral computations is **0.005** (0.01 standard deviation)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>41.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.005400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.014937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.001047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.002432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.004388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.096603</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Overall - ΔE\n",
       "count     41.000000\n",
       "mean       0.005400\n",
       "std        0.014937\n",
       "min        0.000011\n",
       "25%        0.001047\n",
       "50%        0.002432\n",
       "75%        0.004388\n",
       "max        0.096603"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas\n",
    "\n",
    "import colour\n",
    "\n",
    "colour.filter_warnings(True, False)\n",
    "\n",
    "delta_E = colour.delta_E_CIE2000\n",
    "\n",
    "\n",
    "def spectral_to_XYZ(spd,\n",
    "                    cmfs=colour.STANDARD_OBSERVERS_CMFS.get(\n",
    "                        'CIE 1931 2 Degree Standard Observer'),\n",
    "                    illuminant=None):\n",
    "    shape = cmfs.shape\n",
    "    if spd.shape != cmfs.shape:\n",
    "        spd = spd.clone().zeros(shape)\n",
    "\n",
    "    if illuminant is None:\n",
    "        illuminant = colour.ones_spd(shape)\n",
    "    else:\n",
    "        if illuminant.shape != cmfs.shape:\n",
    "            illuminant = illuminant.clone().zeros(shape)\n",
    "\n",
    "    spd = spd.values\n",
    "    x_bar, y_bar, z_bar = (cmfs.x_bar.values,\n",
    "                           cmfs.y_bar.values,\n",
    "                           cmfs.z_bar.values)\n",
    "    illuminant = illuminant.values\n",
    "\n",
    "    x_products = spd * x_bar * illuminant\n",
    "    y_products = spd * y_bar * illuminant\n",
    "    z_products = spd * z_bar * illuminant\n",
    "\n",
    "    normalising_factor = 100 / np.sum(y_bar * illuminant)\n",
    "\n",
    "    XYZ = np.array([normalising_factor * np.sum(x_products),\n",
    "                    normalising_factor * np.sum(y_products),\n",
    "                    normalising_factor * np.sum(z_products)])\n",
    "\n",
    "    return XYZ\n",
    "\n",
    "\n",
    "XYZ_0_3_7 = []\n",
    "XYZ_0_3_8 = []\n",
    "for spd in colour.ILLUMINANTS_RELATIVE_SPDS.values():\n",
    "    XYZ_0_3_7.append(spectral_to_XYZ(spd) * spd.shape.interval / 100)\n",
    "    XYZ_0_3_8.append(colour.spectral_to_XYZ(spd) / 100)\n",
    "\n",
    "d_E = delta_E(\n",
    "    colour.XYZ_to_Lab(XYZ_0_3_7),\n",
    "    colour.XYZ_to_Lab(XYZ_0_3_8))\n",
    "\n",
    "pandas.DataFrame({'Overall - ΔE': d_E}).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Colour Difference - $\\Delta E$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`colour.delta_E_CIE1994` definition signature has changed and the `textiles` argument now default to `False`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(88.335553057506502, 83.779225500887094)\n"
     ]
    }
   ],
   "source": [
    "Lab_1 = np.array([100.00000000, 21.57210357, 272.22819350])\n",
    "Lab_2 = np.array([100.00000000, 426.67945353, 72.39590835])\n",
    "\n",
    "DE_0_3_7 = colour.delta_E_CIE1994(Lab_1, Lab_2, textiles=True)\n",
    "DE_0_3_8 = colour.delta_E_CIE1994(Lab_1, Lab_2, textiles=False)\n",
    "\n",
    "print(DE_0_3_7, DE_0_3_8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Colourspace Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section illustrates colour differences occuring as a result of *D50* and *D65* illuminants chromaticity coordinates changes (CIE 1931 2° Standard Observer) and *Adobe RGB 1998*, *Prophoto RGB*, and *sRGB* colourspaces normalised primary matrices updates. \n",
    "\n",
    "Those alterations are the result of [a decision to better comply](https://github.com/colour-science/colour/issues/220) with the cited RGB colourspaces specifications (even if it means using a rounded less precise dataset).\n",
    "\n",
    "> Note: Almost all the RGB colourspaces and various other objects defined in *Colour* are using the *D50* or *D65* illuminants chromaticity coordinates, thus some minor numerical differences between *Colour 0.3.7* and *Colour 0.3.8* are expected for those objects.\n",
    "\n",
    "RGB values of a X-Rite ColorChecker 2005 are computed in various *RGB* colourspace models using *Colour 0.3.7* and *Colour 0.3.8* dataset. Colour differences of the output values are taken: the overall $\\Delta E_{2000}$ colour difference mean is **0.006** (0.002 standard deviation) and reaches **0.03** (0.01 standard deviation) with high dynamic range values (Luminance → 10000).\n",
    "\n",
    "*CIE Lab* conversions only accounting for illuminants chromaticity coordinates changes have an overall $\\Delta E_{2000}$ colour difference mean of **0.006** (0.003 standard deviation) and reaches **0.03** (0.03 standard deviation) with high dynamic range values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RGB Colourspaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    * Adobe RGB (1998) 1 - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * Adobe RGB (1998) 2 - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
      "    * ProPhoto RGB 1 - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * ProPhoto RGB 2 - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
      "    * sRGB 1 - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * sRGB 2 - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, chromatic adaptation from D50 to D65\n",
      "    \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adobe RGB (1998) 1 - ΔE</th>\n",
       "      <th>Adobe RGB (1998) 2 - ΔE</th>\n",
       "      <th>ProPhoto RGB 1 - ΔE</th>\n",
       "      <th>ProPhoto RGB 2 - ΔE</th>\n",
       "      <th>sRGB 1 - ΔE</th>\n",
       "      <th>sRGB 2 - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.004170</td>\n",
       "      <td>0.005795</td>\n",
       "      <td>0.006563</td>\n",
       "      <td>0.003545</td>\n",
       "      <td>0.006663</td>\n",
       "      <td>0.010531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.002809</td>\n",
       "      <td>0.002609</td>\n",
       "      <td>0.003042</td>\n",
       "      <td>0.002023</td>\n",
       "      <td>0.004106</td>\n",
       "      <td>0.004785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.001299</td>\n",
       "      <td>0.002380</td>\n",
       "      <td>0.003275</td>\n",
       "      <td>0.001292</td>\n",
       "      <td>0.000892</td>\n",
       "      <td>0.003563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.001998</td>\n",
       "      <td>0.003640</td>\n",
       "      <td>0.004191</td>\n",
       "      <td>0.001911</td>\n",
       "      <td>0.003877</td>\n",
       "      <td>0.007242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.003279</td>\n",
       "      <td>0.005360</td>\n",
       "      <td>0.005582</td>\n",
       "      <td>0.002900</td>\n",
       "      <td>0.005870</td>\n",
       "      <td>0.009160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.005507</td>\n",
       "      <td>0.007173</td>\n",
       "      <td>0.008309</td>\n",
       "      <td>0.005370</td>\n",
       "      <td>0.007110</td>\n",
       "      <td>0.012594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.011429</td>\n",
       "      <td>0.012182</td>\n",
       "      <td>0.012422</td>\n",
       "      <td>0.008152</td>\n",
       "      <td>0.017947</td>\n",
       "      <td>0.022735</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Adobe RGB (1998) 1 - ΔE  Adobe RGB (1998) 2 - ΔE  ProPhoto RGB 1 - ΔE  \\\n",
       "count                24.000000                24.000000            24.000000   \n",
       "mean                  0.004170                 0.005795             0.006563   \n",
       "std                   0.002809                 0.002609             0.003042   \n",
       "min                   0.001299                 0.002380             0.003275   \n",
       "25%                   0.001998                 0.003640             0.004191   \n",
       "50%                   0.003279                 0.005360             0.005582   \n",
       "75%                   0.005507                 0.007173             0.008309   \n",
       "max                   0.011429                 0.012182             0.012422   \n",
       "\n",
       "       ProPhoto RGB 2 - ΔE  sRGB 1 - ΔE  sRGB 2 - ΔE  \n",
       "count            24.000000    24.000000    24.000000  \n",
       "mean              0.003545     0.006663     0.010531  \n",
       "std               0.002023     0.004106     0.004785  \n",
       "min               0.001292     0.000892     0.003563  \n",
       "25%               0.001911     0.003877     0.007242  \n",
       "50%               0.002900     0.005870     0.009160  \n",
       "75%               0.005370     0.007110     0.012594  \n",
       "max               0.008152     0.017947     0.022735  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name, data, illuminant = colour.COLOURCHECKERS['ColorChecker 2005']\n",
    "XYZ = np.asarray([colour.xyY_to_XYZ(np.array([x, y, Y]))\n",
    "                  for index, name, x, y, Y in data])\n",
    "# X, Y, Z = colour.tsplit(XYZ)\n",
    "# XYZ_HDR = colour.tstack((X, Y * 10000, Z))\n",
    "XYZ_HDR = XYZ * 10000\n",
    "\n",
    "D50_0_3_7 = np.array([0.34567, 0.35850])\n",
    "D50_0_3_8 = np.array([0.34570, 0.35850])\n",
    "D65_0_3_7 = np.array([0.31271, 0.32902])\n",
    "D65_0_3_8 = np.array([0.31270, 0.32900])\n",
    "\n",
    "sRGB_XYZ_TO_RGB_MATRIX_0_3_7 = np.linalg.inv(np.array(\n",
    "    [[0.41238656, 0.35759149, 0.18045049],\n",
    "     [0.21263682, 0.71518298, 0.0721802],\n",
    "     [0.01933062, 0.11919716, 0.95037259]]))\n",
    "\n",
    "sRGB_XYZ_TO_RGB_MATRIX_0_3_8 = np.linalg.inv(np.array(\n",
    "    [[0.4124, 0.3576, 0.1805],\n",
    "     [0.2126, 0.7152, 0.0722],\n",
    "     [0.0193, 0.1192, 0.9505]]))\n",
    "\n",
    "PROPHOTO_XYZ_to_RGB_MATRIX_0_3_7 = np.linalg.inv(np.array(\n",
    "    [[7.97667235e-01, 1.35192231e-01, 3.13525290e-02],\n",
    "     [2.88037454e-01, 7.11876883e-01, 8.56626476e-05],\n",
    "     [0.00000000e+00, 0.00000000e+00, 8.25188285e-01]]))\n",
    "\n",
    "PROPHOTO_XYZ_to_RGB_MATRIX_0_3_8 = np.linalg.inv(np.array(\n",
    "    [[0.7977, 0.1352, 0.0313],\n",
    "     [0.2880, 0.7119, 0.0001],\n",
    "     [0.0000, 0.0000, 0.8249]]))\n",
    "\n",
    "ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_7 = np.linalg.inv(np.array(\n",
    "    [[0.57666809, 0.18556195, 0.1881985],\n",
    "     [0.29734449, 0.62737611, 0.0752794],\n",
    "     [0.02703132, 0.07069027, 0.99117879]]))\n",
    "\n",
    "ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_8 = np.linalg.inv(np.array(\n",
    "    [[0.57667, 0.18556, 0.18823],\n",
    "     [0.29734, 0.62736, 0.07529],\n",
    "     [0.02703, 0.07069, 0.99134]]))\n",
    "\n",
    "RGB_to_XYZ = lambda x: colour.RGB_to_XYZ(\n",
    "    x,\n",
    "    D65_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    np.linalg.inv(sRGB_XYZ_TO_RGB_MATRIX_0_3_8))\n",
    "\n",
    "# sRGB 1 - ΔE\n",
    "RGB_0_3_7__1 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__1 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__1 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__1)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__1)))\n",
    "\n",
    "# sRGB 2 - ΔE\n",
    "RGB_0_3_7__2 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__2 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__2 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__2)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__2)))\n",
    "\n",
    "# Prophoto 1 - ΔE\n",
    "RGB_0_3_7__3 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_7,\n",
    "    D50_0_3_7,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__3 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_8,\n",
    "    D50_0_3_8,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__3 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__3)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__3)))\n",
    "\n",
    "# Prophoto 2 - ΔE\n",
    "RGB_0_3_7__4 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_7,\n",
    "    D50_0_3_7,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__4 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_8,\n",
    "    D50_0_3_8,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__4 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__4)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__4)))\n",
    "\n",
    "# Adobe RGB (1998) 1 - ΔE\n",
    "RGB_0_3_7__5 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__5 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D65_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__5 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__5)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__5)))\n",
    "\n",
    "# Adobe RGB (1998) 2 - ΔE\n",
    "RGB_0_3_7__6 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__6 = colour.XYZ_to_RGB(\n",
    "    XYZ,\n",
    "    D50_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__6 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__6)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__6)))\n",
    "\n",
    "print(\n",
    "    \"\"\"\n",
    "    * Adobe RGB (1998) 1 - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * Adobe RGB (1998) 2 - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
    "    * ProPhoto RGB 1 - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * ProPhoto RGB 2 - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
    "    * sRGB 1 - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * sRGB 2 - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, chromatic adaptation from D50 to D65\n",
    "    \"\"\")\n",
    "\n",
    "results = {'sRGB 1 - ΔE': d_E__1,\n",
    "           'sRGB 2 - ΔE': d_E__2,\n",
    "           'ProPhoto RGB 1 - ΔE': d_E__3,\n",
    "           'ProPhoto RGB 2 - ΔE': d_E__4,\n",
    "           'Adobe RGB (1998) 1 - ΔE': d_E__5,\n",
    "           'Adobe RGB (1998) 2 - ΔE': d_E__6}\n",
    "results_dataframe = pandas.DataFrame(results)\n",
    "results_dataframe.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.006211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.002467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.003545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.004576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.006179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.006638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.010531</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Overall - ΔE\n",
       "count      6.000000\n",
       "mean       0.006211\n",
       "std        0.002467\n",
       "min        0.003545\n",
       "25%        0.004576\n",
       "50%        0.006179\n",
       "75%        0.006638\n",
       "max        0.010531"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.DataFrame({'Overall - ΔE': np.squeeze(\n",
    "            results_dataframe.describe()[1:2].values)}).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    * Adobe RGB (1998) 1 - HDR - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * Adobe RGB (1998) 2 - HDR - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
      "    * ProPhoto RGB 1 - HDR - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * ProPhoto RGB 2 - HDR - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
      "    * sRGB 1 - HDR - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
      "    * sRGB 2 - HDR - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, chromatic adaptation from D50 to D65\n",
      "    \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adobe RGB (1998) 1 - HDR - ΔE</th>\n",
       "      <th>Adobe RGB (1998) 2 - HDR - ΔE</th>\n",
       "      <th>ProPhoto RGB 1 - HDR - ΔE</th>\n",
       "      <th>ProPhoto RGB 2 - HDR - ΔE</th>\n",
       "      <th>sRGB 1 - HDR - ΔE</th>\n",
       "      <th>sRGB 2 - HDR - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.026184</td>\n",
       "      <td>0.017442</td>\n",
       "      <td>0.020993</td>\n",
       "      <td>0.015517</td>\n",
       "      <td>0.048194</td>\n",
       "      <td>0.030479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.035712</td>\n",
       "      <td>0.010542</td>\n",
       "      <td>0.024208</td>\n",
       "      <td>0.013827</td>\n",
       "      <td>0.067167</td>\n",
       "      <td>0.020316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.001960</td>\n",
       "      <td>0.004145</td>\n",
       "      <td>0.007118</td>\n",
       "      <td>0.001833</td>\n",
       "      <td>0.001322</td>\n",
       "      <td>0.005232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.005259</td>\n",
       "      <td>0.008038</td>\n",
       "      <td>0.010060</td>\n",
       "      <td>0.003494</td>\n",
       "      <td>0.008221</td>\n",
       "      <td>0.015646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.007359</td>\n",
       "      <td>0.014469</td>\n",
       "      <td>0.014516</td>\n",
       "      <td>0.012635</td>\n",
       "      <td>0.014617</td>\n",
       "      <td>0.023240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.029524</td>\n",
       "      <td>0.024952</td>\n",
       "      <td>0.018783</td>\n",
       "      <td>0.020148</td>\n",
       "      <td>0.044347</td>\n",
       "      <td>0.049502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.132952</td>\n",
       "      <td>0.037742</td>\n",
       "      <td>0.120340</td>\n",
       "      <td>0.048273</td>\n",
       "      <td>0.203857</td>\n",
       "      <td>0.070433</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Adobe RGB (1998) 1 - HDR - ΔE  Adobe RGB (1998) 2 - HDR - ΔE  \\\n",
       "count                      24.000000                      24.000000   \n",
       "mean                        0.026184                       0.017442   \n",
       "std                         0.035712                       0.010542   \n",
       "min                         0.001960                       0.004145   \n",
       "25%                         0.005259                       0.008038   \n",
       "50%                         0.007359                       0.014469   \n",
       "75%                         0.029524                       0.024952   \n",
       "max                         0.132952                       0.037742   \n",
       "\n",
       "       ProPhoto RGB 1 - HDR - ΔE  ProPhoto RGB 2 - HDR - ΔE  \\\n",
       "count                  24.000000                  24.000000   \n",
       "mean                    0.020993                   0.015517   \n",
       "std                     0.024208                   0.013827   \n",
       "min                     0.007118                   0.001833   \n",
       "25%                     0.010060                   0.003494   \n",
       "50%                     0.014516                   0.012635   \n",
       "75%                     0.018783                   0.020148   \n",
       "max                     0.120340                   0.048273   \n",
       "\n",
       "       sRGB 1 - HDR - ΔE  sRGB 2 - HDR - ΔE  \n",
       "count          24.000000          24.000000  \n",
       "mean            0.048194           0.030479  \n",
       "std             0.067167           0.020316  \n",
       "min             0.001322           0.005232  \n",
       "25%             0.008221           0.015646  \n",
       "50%             0.014617           0.023240  \n",
       "75%             0.044347           0.049502  \n",
       "max             0.203857           0.070433  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sRGB 1 - HDR - ΔE\n",
    "RGB_0_3_7__1 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__1 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__1 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__1)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__1)))\n",
    "\n",
    "# sRGB 2 - HDR - ΔE\n",
    "RGB_0_3_7__2 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__2 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    sRGB_XYZ_TO_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__2 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__2)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__2)))\n",
    "\n",
    "# Prophoto 1 - HDR - ΔE\n",
    "RGB_0_3_7__3 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_7,\n",
    "    D50_0_3_7,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__3 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_8,\n",
    "    D50_0_3_8,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__3 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__3)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__3)))\n",
    "\n",
    "# Prophoto 2 - HDR - ΔE\n",
    "RGB_0_3_7__4 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_7,\n",
    "    D50_0_3_7,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__4 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_8,\n",
    "    D50_0_3_8,\n",
    "    PROPHOTO_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__4 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__4)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__4)))\n",
    "\n",
    "# Adobe RGB (1998) 1 - HDR - ΔE\n",
    "RGB_0_3_7__5 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__5 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D65_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__5 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__5)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__5)))\n",
    "\n",
    "# Adobe RGB (1998) 2 - HDR - ΔE\n",
    "RGB_0_3_7__6 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_7,\n",
    "    D65_0_3_7,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_7)\n",
    "\n",
    "RGB_0_3_8__6 = colour.XYZ_to_RGB(\n",
    "    XYZ_HDR,\n",
    "    D50_0_3_8,\n",
    "    D65_0_3_8,\n",
    "    ADOBE_RGB_1998_XYZ_to_RGB_MATRIX_0_3_8)\n",
    "\n",
    "d_E__6 = delta_E(\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_7__6)),\n",
    "    colour.XYZ_to_Lab(RGB_to_XYZ(RGB_0_3_8__6)))\n",
    "\n",
    "print(\n",
    "    \"\"\"\n",
    "    * Adobe RGB (1998) 1 - HDR - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * Adobe RGB (1998) 2 - HDR - ΔE: Conversion to Adobe RGB (1998) v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
    "    * ProPhoto RGB 1 - HDR - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * ProPhoto RGB 2 - HDR - ΔE: Conversion to ProPhoto RGB v0.3.7 vs v0.3.8, chromatic adaptation from D65 to D50\n",
    "    * sRGB 1 - HDR - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, no chromatic adaptation\n",
    "    * sRGB 2 - HDR - ΔE: Conversion to sRGB v0.3.7 vs v0.3.8, chromatic adaptation from D50 to D65\n",
    "    \"\"\")\n",
    "\n",
    "results = {'sRGB 1 - HDR - ΔE': d_E__1,\n",
    "           'sRGB 2 - HDR - ΔE': d_E__2,\n",
    "           'ProPhoto RGB 1 - HDR - ΔE': d_E__3,\n",
    "           'ProPhoto RGB 2 - HDR - ΔE': d_E__4,\n",
    "           'Adobe RGB (1998) 1 - HDR - ΔE': d_E__5,\n",
    "           'Adobe RGB (1998) 2 - HDR - ΔE': d_E__6}\n",
    "results_dataframe = pandas.DataFrame(results)\n",
    "results_dataframe.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall - HDR - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.026468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.011996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.015517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.018330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.023588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.029405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.048194</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Overall - HDR - ΔE\n",
       "count            6.000000\n",
       "mean             0.026468\n",
       "std              0.011996\n",
       "min              0.015517\n",
       "25%              0.018330\n",
       "50%              0.023588\n",
       "75%              0.029405\n",
       "max              0.048194"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.DataFrame({'Overall - HDR - ΔE': np.squeeze(\n",
    "            results_dataframe.describe()[1:2].values)}).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CIE Lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    * CIE Lab 1 - ΔE: D50\n",
      "    * CIE Lab 1 - ΔE: D65\n",
      "    \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CIE Lab 1 - ΔE</th>\n",
       "      <th>CIE Lab 2 - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.007691</td>\n",
       "      <td>0.003701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.004800</td>\n",
       "      <td>0.001690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.002643</td>\n",
       "      <td>0.001431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.005097</td>\n",
       "      <td>0.002529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.006238</td>\n",
       "      <td>0.003214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.008135</td>\n",
       "      <td>0.004475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.021485</td>\n",
       "      <td>0.007566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       CIE Lab 1 - ΔE  CIE Lab 2 - ΔE\n",
       "count       24.000000       24.000000\n",
       "mean         0.007691        0.003701\n",
       "std          0.004800        0.001690\n",
       "min          0.002643        0.001431\n",
       "25%          0.005097        0.002529\n",
       "50%          0.006238        0.003214\n",
       "75%          0.008135        0.004475\n",
       "max          0.021485        0.007566"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_E__1 = delta_E(\n",
    "    colour.XYZ_to_Lab(XYZ, D50_0_3_7),\n",
    "    colour.XYZ_to_Lab(XYZ, D50_0_3_8))\n",
    "\n",
    "d_E__2 = delta_E(\n",
    "    colour.XYZ_to_Lab(XYZ, D65_0_3_7),\n",
    "    colour.XYZ_to_Lab(XYZ, D65_0_3_8))\n",
    "\n",
    "print(\n",
    "    \"\"\"\n",
    "    * CIE Lab 1 - ΔE: D50\n",
    "    * CIE Lab 1 - ΔE: D65\n",
    "    \"\"\")\n",
    "\n",
    "results = {'CIE Lab 1 - ΔE': d_E__1,\n",
    "           'CIE Lab 2 - ΔE': d_E__2}\n",
    "results_dataframe = pandas.DataFrame(results)\n",
    "results_dataframe.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.005696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.002821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.003701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.004699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.005696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.006694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.007691</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Overall - ΔE\n",
       "count      2.000000\n",
       "mean       0.005696\n",
       "std        0.002821\n",
       "min        0.003701\n",
       "25%        0.004699\n",
       "50%        0.005696\n",
       "75%        0.006694\n",
       "max        0.007691"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.DataFrame({'Overall - ΔE': np.squeeze(\n",
    "            results_dataframe.describe()[1:2].values)}).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    * CIE Lab 1 - HDR - ΔE: D50\n",
      "    * CIE Lab 1 - HDR - ΔE: D65\n",
      "    \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CIE Lab 1 - ΔE</th>\n",
       "      <th>CIE Lab 2 - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.054747</td>\n",
       "      <td>0.012313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.076240</td>\n",
       "      <td>0.009439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.004040</td>\n",
       "      <td>0.002047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.011649</td>\n",
       "      <td>0.005269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.015807</td>\n",
       "      <td>0.007352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.065657</td>\n",
       "      <td>0.018146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.257200</td>\n",
       "      <td>0.028689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       CIE Lab 1 - ΔE  CIE Lab 2 - ΔE\n",
       "count       24.000000       24.000000\n",
       "mean         0.054747        0.012313\n",
       "std          0.076240        0.009439\n",
       "min          0.004040        0.002047\n",
       "25%          0.011649        0.005269\n",
       "50%          0.015807        0.007352\n",
       "75%          0.065657        0.018146\n",
       "max          0.257200        0.028689"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_E__1 = delta_E(\n",
    "    colour.XYZ_to_Lab(XYZ_HDR, D50_0_3_7),\n",
    "    colour.XYZ_to_Lab(XYZ_HDR, D50_0_3_8))\n",
    "\n",
    "d_E__2 = delta_E(\n",
    "    colour.XYZ_to_Lab(XYZ_HDR, D65_0_3_7),\n",
    "    colour.XYZ_to_Lab(XYZ_HDR, D65_0_3_8))\n",
    "\n",
    "print(\n",
    "    \"\"\"\n",
    "    * CIE Lab 1 - HDR - ΔE: D50\n",
    "    * CIE Lab 1 - HDR - ΔE: D65\n",
    "    \"\"\")\n",
    "\n",
    "results = {'CIE Lab 1 - ΔE': d_E__1,\n",
    "           'CIE Lab 2 - ΔE': d_E__2}\n",
    "results_dataframe = pandas.DataFrame(results)\n",
    "results_dataframe.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall - HDR - ΔE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.033530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.030005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.012313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.022922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.033530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.044138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.054747</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Overall - HDR - ΔE\n",
       "count            2.000000\n",
       "mean             0.033530\n",
       "std              0.030005\n",
       "min              0.012313\n",
       "25%              0.022922\n",
       "50%              0.033530\n",
       "75%              0.044138\n",
       "max              0.054747"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.DataFrame({'Overall - HDR - ΔE': np.squeeze(\n",
    "            results_dataframe.describe()[1:2].values)}).describe()"
   ]
  }
 ],
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