ColourTSP.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from colormath.color_objects import LabColor, XYZColor, sRGBColor\n",
    "from colormath.color_conversions import convert_color\n",
    "from colormath.color_diff import delta_e_cie2000\n",
    "\n",
    "from tsp_solver.greedy import solve_tsp\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "colours_length = 1000\n",
    "colours = []\n",
    "\n",
    "for i in range(colours_length):\n",
    "    colours.append (\n",
    "        [\n",
    "            random.random(),\n",
    "            random.random(),\n",
    "            random.random()\n",
    "        ]\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plot_colours(colours):\n",
    "    height = 50\n",
    "\n",
    "    im = np.zeros((height, len(colours), 3))\n",
    "\n",
    "    for idx, col in enumerate(colours):\n",
    "        im[:, idx, :] = col\n",
    "\n",
    "    fig, axes = plt.subplots(1, figsize=(16, 12))\n",
    "    axes.imshow(im, interpolation='nearest')\n",
    "    axes.axis('off')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fed1fef5208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_colours(colours)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cie_colours = []\n",
    "\n",
    "for i in range(colours_length):\n",
    "    rgb = sRGBColor(*colours[i])\n",
    "    xyz = convert_color(rgb, XYZColor)\n",
    "    lab = convert_color(xyz, LabColor)\n",
    "    cie_colours.append(lab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "D = np.zeros((colours_length, colours_length))\n",
    "\n",
    "for i in range(colours_length):\n",
    "    for j in range(0, i):\n",
    "        delta_e = delta_e_cie2000(cie_colours[i], cie_colours[j])\n",
    "        D[i, j] = delta_e\n",
    "        D[j, i] = delta_e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "path = solve_tsp(D)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sorted_colours = []\n",
    "\n",
    "for i in range(colours_length):\n",
    "    sorted_colours.append(colours[path[i]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fed1f914128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_colours(sorted_colours)"
   ]
  }
 ],
 "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": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}