{
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_population():\n",
    "    population = []\n",
    "    for i in range(N_POP):\n",
    "        arr = [random.randint(0,9) for j in range(10)]\n",
    "        population.append(arr)\n",
    "\n",
    "    return population\n",
    "\n",
    "def clac_score(x):\n",
    "    return sum(x)\n",
    "\n",
    "def evaluate(pop):\n",
    "    fitness = []\n",
    "    for p in pop:\n",
    "        if p[0] == -1:\n",
    "            fitness.append((clac_score(p[1]), p[1]))\n",
    "        else:\n",
    "            fitness.append(p)\n",
    "    fitness.sort()\n",
    "    fitness.reverse()\n",
    "    \n",
    "    return fitness\n",
    "\n",
    "def mutate(parent):\n",
    "    r = int(math.floor(random.random()*len(parent)))\n",
    "    child = copy.deepcopy(parent)\n",
    "    child[r] = (parent[r] + 1) % 2\n",
    "    \n",
    "    return child\n",
    "\n",
    "def crossover(parent1, parent2):\n",
    "    length = len(parent1)\n",
    "    r1 = int(math.floor(random.random()*length))\n",
    "    r2 = r1 + int(math.floor(random.random()*(length-r1)))\n",
    "        \n",
    "    child = copy.deepcopy(parent1)\n",
    "    child[r1:r2] = parent2[r1:r2]\n",
    "\n",
    "    return child"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import random\n",
    "import math\n",
    "import copy\n",
    "\n",
    "N_PARAM = 16\n",
    "N_POP = 500\n",
    "N_GEN = 20\n",
    "MUTATE_PROB = 0.2\n",
    "ELITE_RATE = 0.3\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def main():\n",
    "    pop =  [(-1, p) for p in get_population()]\n",
    "    \n",
    "    for g in range(N_GEN):\n",
    "        print(\"Generation: \" + str(g))\n",
    "        \n",
    "        # Get elites\n",
    "        fitness = evaluate(pop)\n",
    "        elites = fitness[:int(len(pop)*ELITE_RATE)]\n",
    "        \n",
    "        # Cross and mutate\n",
    "        pop = elites[:]\n",
    "        while len(pop) < N_POP:\n",
    "            if random.random() < MUTATE_PROB:\n",
    "                m = random.randint(0, len(elites)-1)\n",
    "                child = mutate(elites[m][1])\n",
    "            else:\n",
    "                c1 = random.randint(0, len(elites)-1)\n",
    "                c2 = random.randint(0, len(elites)-1)\n",
    "                child = crossover(elites[c1][1], elites[c2][1])\n",
    "            pop.append((-1, child))\n",
    "            \n",
    "        # Evaluate individual \n",
    "        fitness = evaluate(pop)\n",
    "        elites = fitness[:int(len(pop)*ELITE_RATE)]\n",
    "        \n",
    "        print(pop[0])\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation: 0\n",
      "(75, [9, 8, 9, 5, 7, 4, 8, 9, 8, 8])\n",
      "\n",
      "Generation: 1\n",
      "(76, [6, 9, 6, 7, 9, 6, 6, 9, 9, 9])\n",
      "\n",
      "Generation: 2\n",
      "(77, [9, 9, 9, 7, 8, 8, 9, 5, 8, 5])\n",
      "\n",
      "Generation: 3\n",
      "(80, [9, 8, 4, 7, 9, 9, 9, 9, 8, 8])\n",
      "\n",
      "Generation: 4\n",
      "(83, [9, 8, 7, 8, 8, 8, 8, 9, 9, 9])\n",
      "\n",
      "Generation: 5\n",
      "(87, [9, 8, 9, 9, 9, 9, 9, 9, 8, 8])\n",
      "\n",
      "Generation: 6\n",
      "(87, [9, 8, 9, 9, 9, 9, 9, 9, 8, 8])\n",
      "\n",
      "Generation: 7\n",
      "(88, [8, 9, 9, 9, 9, 9, 9, 9, 8, 9])\n",
      "\n",
      "Generation: 8\n",
      "(88, [9, 9, 9, 9, 9, 9, 8, 9, 8, 9])\n",
      "\n",
      "Generation: 9\n",
      "(88, [9, 9, 9, 9, 9, 9, 9, 9, 7, 9])\n",
      "\n",
      "Generation: 10\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 11\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 12\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 13\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 14\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 15\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 16\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 17\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 18\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n",
      "Generation: 19\n",
      "(90, [9, 9, 9, 9, 9, 9, 9, 9, 9, 9])\n",
      "\n"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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