manipulate_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from generate_dataset import Dataset\n",
    "\n",
    "dataset = Dataset.from_json(\"dataset.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19683: Total number of possible boards\n",
      "5478: Total number of boards in dataset\n",
      "765: Number of unique symmetry groups\n",
      "431: Number of decidable unique symmetry groups\n"
     ]
    }
   ],
   "source": [
    "# Possible\n",
    "total_possible_boards = 3**9\n",
    "\n",
    "# Reacheable\n",
    "total_reacheable_boards = len(dataset.boards)\n",
    "\n",
    "# Unique\n",
    "unique_symmetry_groups = set(board.category.symmetry_group for board in dataset.boards.values())\n",
    "total_unique_boards = len(unique_symmetry_groups)\n",
    "\n",
    "# Decidable\n",
    "decidable_symmetry_groups = set(\n",
    "    board.category.symmetry_group\n",
    "    for board in dataset.boards.values()\n",
    "    if board.category.choice_complexity[0] != 0\n",
    ")\n",
    "total_decidable_boards = len(decidable_symmetry_groups)\n",
    "\n",
    "# Print the results\n",
    "print(f\"{total_possible_boards}: Total number of possible boards\")\n",
    "print(f\"{total_reacheable_boards}: Total number of boards in dataset\")\n",
    "print(f\"{total_unique_boards}: Number of unique symmetry groups\")\n",
    "print(f\"{total_decidable_boards}: Number of decidable unique symmetry groups\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of filtered boards: 431\n",
      "Type of elements in filtered_boards: <class 'generate_dataset.Board'>\n"
     ]
    }
   ],
   "source": [
    "filtered_boards = []\n",
    "for symmetry_group in decidable_symmetry_groups:\n",
    "    # Get the first board from the symmetry group\n",
    "    first_string = symmetry_group.split('|')[0]\n",
    "    filtered_boards.append(dataset.boards[first_string])\n",
    "\n",
    "print(f\"Number of filtered boards: {len(filtered_boards)}\")\n",
    "print(f\"Type of elements in filtered_boards: {type(filtered_boards[0])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ranking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choice Complexity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{Fraction(1, 7): 2,\n",
       " Fraction(1, 5): 13,\n",
       " Fraction(1, 4): 6,\n",
       " Fraction(1, 3): 44,\n",
       " Fraction(2, 5): 13,\n",
       " Fraction(3, 7): 1,\n",
       " Fraction(1, 2): 93,\n",
       " Fraction(4, 7): 3,\n",
       " Fraction(3, 5): 19,\n",
       " Fraction(2, 3): 99,\n",
       " Fraction(5, 7): 2,\n",
       " Fraction(3, 4): 72,\n",
       " Fraction(4, 5): 46,\n",
       " Fraction(5, 6): 16,\n",
       " Fraction(6, 7): 1,\n",
       " Fraction(7, 8): 1}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from fractions import Fraction\n",
    "\n",
    "# Count unique decidable boards grouped by chance_complexity ratio\n",
    "chance_complexity_ratio_counts = {}\n",
    "\n",
    "for board in filtered_boards:\n",
    "    ratio = Fraction(board.category.choice_complexity[0], board.category.choice_complexity[1])\n",
    "    if ratio not in chance_complexity_ratio_counts:\n",
    "        chance_complexity_ratio_counts[ratio] = 0\n",
    "    chance_complexity_ratio_counts[ratio] += 1\n",
    "\n",
    "# Sort the dictionary by chance_complexity ratio\n",
    "sorted_chance_complexity_ratio_counts = dict(sorted(chance_complexity_ratio_counts.items()))\n",
    "\n",
    "sorted_chance_complexity_ratio_counts\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BfBQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Convert Fraction keys to strings for better readability\n",
    "choice_complexity_ratios = [str(ratio) for ratio in sorted_chance_complexity_ratio_counts.keys()]\n",
    "counts = list(sorted_chance_complexity_ratio_counts.values())\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "bars = plt.bar(choice_complexity_ratios, counts)\n",
    "plt.xlabel('Choice Complexity Ratio')\n",
    "plt.ylabel('Count')\n",
    "plt.title('Distribution of Choice Complexity')\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "\n",
    "# Add value labels on top of each bar\n",
    "for bar in bars:\n",
    "    height = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2., height,\n",
    "             f'{height}',\n",
    "             ha='center', va='bottom')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Depth Complexity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 252, 2: 79, 3: 51, 4: 24, 5: 17, 6: 8}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count unique decidable boards grouped by depth_complexity\n",
    "depth_complexity_counts = {}\n",
    "\n",
    "for board in filtered_boards:\n",
    "    depth = board.category.depth_complexity\n",
    "    if depth not in depth_complexity_counts:\n",
    "        depth_complexity_counts[depth] = 0\n",
    "    depth_complexity_counts[depth] += 1\n",
    "\n",
    "# Sort the dictionary by depth_complexity\n",
    "sorted_depth_complexity_counts = dict(sorted(depth_complexity_counts.items()))\n",
    "\n",
    "sorted_depth_complexity_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "depths = list(sorted_depth_complexity_counts.keys())\n",
    "counts = list(sorted_depth_complexity_counts.values())\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "bars = plt.bar(depths, counts)\n",
    "plt.xlabel('Depth Complexity')\n",
    "plt.ylabel('Count')\n",
    "plt.title('Distribution of Depth Complexity')\n",
    "plt.xticks(depths)\n",
    "\n",
    "# Add value labels on top of each bar\n",
    "for bar in bars:\n",
    "    height = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2., height,\n",
    "             f'{height}',\n",
    "             ha='center', va='bottom')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6CAYAAACI7Fo9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAffUlEQVR4nO2dfXRU5b3vv5nJ5BUOeZskVkl4SULRkECGepFa9TTcRLGoRQMcVy0ujxLIEgTvqV3tuVav4r13iZR1DB6gtljptSaovchZIkKhKKBYnZhAuBg8BRKChqRA3kwCM5Pv/SPONrwEMmTv/ezJ/n3W+q41mZns57d/+/edZ789z44AQAiCMKxxqA5AEATjEaMLgg0QowuCDRCjC4INEKMLgg0QowuCDRCjC4INEKMLgg0QowuCDRCjGwRJkHLT4WCRfBmLGF0QbIAYXRBsgBhdEGyAGF0QbIAYXRBsgBhdEGyAGF0QbIAYXRBsgBhdEGyAGF0QbIAYXRBsgBhdEGyAGF0QbIAYXRBsgBhdEGxApOoABOOJi4tDfn4+0tPTERMTAwDo6elBU1MTampq0NXVpThCwWjE6MOQuLg4zJkzB7fddhs8Hg8mTpwIp9N5ye8GAgEcOnQIXq8Xu3btQmVlJbq7u02OWDCaCMiz1wwhOFtKRESEaW1OmDABCxcuxIMPPoiEhATtfZ/Ph9raWhw7dkwzcWxsLMaMGYPc3Fy4XC7tu62trfj973+PNWvW4PDhw6bFriJfdoMi/RXEjLbcbjcrKyvZnz179rCsrIxTp05ldHT0gP8bHR3NqVOnsqysjHv27DlvGZWVlXS73cMuXzaVusZnz55tWiENpMLCQmZlZem+XLMKt6SkhM3NzSTJzs5Orl27lvn5+Ve9vPz8fK5du5adnZ0kyebmZpaUlBi+HkblKysri4WFhabV06Xkdrs5e/ZspTFAVcOzZ89mIBDggQMHlJm9qKiI3d3dPH78OFNTU3VdttFGj4uLY0VFhdbOtm3bmJGRodvyMzIyuG3bNm35FRUVjI2NNWx9jMhXamoqjx8/zu7ubhYVFZleX0CfyQ8cOMBAIKDa7GoaDiaApBKzB01OkuXl5bov30ijjxo1irt37yZJtre385FHHjEsTwsWLGB7eztJcvfu3Rw1apQh7RiVr/LycpJUYnbVNX6BlDWsLBFGmxwwrnDj4+P50UcfkSTr6+uZk5NjeL5ycnJYX19Pkvzwww8ZHx8fNvkC1JjdYiYnFDduekLMMDlgTOE6HA5u3bqVJHn06FGOHj3atO2UkZHBo0ePkiS3bt1Kh8Nh+Xz1l5lmt6DJCQsEYFpizDI5YEzhLlu2jCTZ1NTE8ePHm76dxo8fz6amJpLk0qVLLZ+vC2WG2S1qcsICAZiSIDNNDuhfuDk5Oezq6iJJ3nHHHcq208yZM0mSXV1dzM7Otmy+BpKRZrewyQkLBGB4osw2OaBv4TocDu7du5ckuX79euXb6ZVXXiHZd61er114s4wOGGN2i5ucsEAAhiZMhckBfQt37ty5JMnGxkbDznqHooSEBDY2NpIk586da7l8DUZ6mj0MTE5YIADDEqfK5IC+hfv++++TJEtLS5Vvm6BKS0tJkrt27bJcvgYrPcweJiYnLBCAIQlUaXJAv8LNzc0lSba1tRlyWetqNWLECLa1tZEkb7jhBsvkK1QNxexhZHLCAgHonkjVJgf0K9yXXnqJJPniiy8q3x4XKmiS1atXWyZfQ1mPUMweZiYnLBCArgm1gskB/Qr3xIkTJMm8vDzl2+JC5eXlkew7d2CVfF2tQjF7GJqcsEAAV9RgE2sVkwP6FG56ejpJ8syZM4yIiFC+HS5UREQEW1tbSZJpaWnK8zVUDcbsYWpywgIBDEpXSrCVTA7oU7h33nknSXLHjh3K12cg7dy5kyQ5c+ZM5fnSQ5czexibnLBAAIPWQIm2mskBfQr3V7/6FUny+eefV74+A2nFihUkySeffFJ5vvTSpcwe5iYnLBBASLow4SUlJZYzOaBP4W7YsIEkOX/+fOXrM5Dmz59PktywYYPyfOmp/mafM2dOuJucsEAAIau/2QOBgOVMDuhTuG+++SZJqh7HfFnde++9JMk33nhDeb70VtDswRoLY5MzLKd7bmlpwTPPPIPe3l44HA6cOnUKzzzzjOqwdCcysm/uTr/frziSgfH5fABw3rxzw4VnnnkGp06dgsPhQG9vL5599lm0tLSoDuuqCEujFxUVYcOGDZrJk5OTsXPnTrjdbtWh6crZs2cBANHR0YojGZj+00cPJ9xuN3bu3Ink5GTN7K+++iqKiopUh3ZVhJ3Ri4qK8PbbbyMmJgarV6/GxIkTUVtbi9zc3GFn9ra2NgCw9DqlpKQAANrb2xVHoh9Bk+fm5qK2thYTJ07E6tWrERMTg7fffjtsza78+GGwGujsuhXPiOpxzLl48WKS5Msvv6x8fQbSb3/7W5Lko48+qjxfeuhytaRyWiodpDyAQelKl9CsZnY9Cnf69OkkyaqqKuX5H0ifffYZSfKmm25Snq+hajA1FMZmVx7AFTXY6+RWMrsehRsXF0e/389z585ddm52VYqJiaHP56Pf7x/yDLGqjR5K7YSp2ZUHcFmFejOMVcyuV+FWV1eTJGfNmqV8W1yoWbNmkSSrq6stk6+r0dXUTBiaXXkAA+pq73izgtn1KtzHH3+cJLllyxbl2+NCvfvuuyTJZcuWWSZfoWootRJmZlcewCU11NtaVZtdr8JNSkrS5oobN26c8u0S1Pjx40n2zR2XmJhomXyZXSNhZHblAVwkve5dV2l2PQt3/fr1JMlVq1Yp3zZBrVq1iiT5u9/9znL5Mrs2wsTsygM4T3oPUFFldj0Ld/LkyQwEAvT5fCwoKFC+jTweD30+HwOBACdPnmy5fKmoiTAwu/IANBk1Ck2F2fUu3JUrV5Ik9+/fz6ioKGXbKCoqSsvlypUrLZsvFbVgcbMrD4CA8UNNzTa73oUbGxvLuro6kuTy5cuVbafly5eTJOvq6nR96KIZRjejBixsduUBmDae3EyzG1G406dP10ZS/eQnPzF9Oz3wwAMk+0ZzTZ8+3fL5UrXtLWp2tQGYPWmEWRvcqMINPpbJ5/PpNqf6YDR37lz6fD6S+j+Oych8mbnN+8uCZlfXuKqZYczY8EYW7tNPP631rEuWLDE8X0uWLNH2JJ566ilD2jAqXyqvvFjM7GoaLiwsVDozzIUFkJSUpOvyjd4V/fnPf661sW3bNmZkZOjeRmZmJrdv366188QTTxi2PkbkKykpSfmNU/3NXlhYaHr7/aSm4aysLB4/flzpzDBBs7/11lt0uVy6LttoowN9s7s0NzeTJNvb21lWVqbLGfmoqCiWlZWxvb2dJNnc3Mx7773X0HUxIl8ul4tvvfWW8nEP5eXlPH78OLOyspTFAIUNMzU1VeWKE+j71dfb5IB5l4tSUlJYWVmptdfU1MTly5df1bPTMzIy+Nxzz/HkyZPa8iorK5mSkmL4ehiVL5fLpfve2tXIArWuNgHDVWYZPajZs2drQ0ZJ0u/3c9euXVyxYgXnzZvH7OxsRkZGat+PjIxkdnY2582bxxUrVnDXrl30+/3a/3/22WemzlVndr5sKOUBDEupKtybbrqJf/jDH9jT08NL4fP5tLPnF9LT08MNGzZw2rRptsmXXRTxzQtBZ/pqFoiIiFDSflJSEqZNmwaPx4OpU6fC4/EgNTVVm8TR5/OhubkZXq8Xn376KbxeL/bt24fTp08riVd1voY7YnSDsGrhOp1OAEAgEFAcyflYNV/DhUjVAQjmYjWDC+YQdrPACoIQOmJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABgx6PHhwvLAiCdRjs+H3p0QXBBsgMMwYhM6aEhuTLWKRHFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsQVs9HT09Ph8fjgcfjQVZWFuLi4hAZGYmzZ8+ira0NBw4cgNfrRXV1Nbq6ulSHqxyHw4EJEybA4/GgoKAA6enpiImJAQD09PSgqakJVVVV8Hq9qKurQ29vr+KIBSOhlZWbm8uXXnqJJ06c4GDx+/2srq7m448/zsTERCVxBzG7XafTybvvvptbtmxhR0fHoHPW0dHBLVu28K677qLT6bRNvuwiS0484XA4UFJSgrKyMtxyyy3a+62trVoPdPDgQXR0dMDv9yM6OhputxtTpkyBx+NBbm4uXC4XAKC7uxsVFRV48cUXUV1dbdo6mD2RQnJyMkpLS1FaWoqMjAzt/WPHjsHr9cLr9eLo0aPo7u4GAMTGxmLs2LHaHtKYMWO0/2loaMC6deuwbt06nDp1ypT4ZeIJ41H+a9Nf2dnZ3LNnj/YL39bWxhdffJF5eXmMiIgY1DKio6M5a9YsbtmyRVtOIBDgypUrGRsba8p6mNlDlZSUsLm5WWuzrq6Ojz32GN1u96CX4Xa7+dhjj7Gurk5bTnNzM++7775hly+bSnkABECHw8Fly5axq6uLJNnY2MjS0lLGx8cPabnjxo3jqlWr6PP5NBNMnz7d8PUxo3Ddbjc3btyotbVjxw4WFhYO+gfxUoqIiGBhYSF37NihLXfjxo0h/WhYNV82l/IAGB8fz/fee0/b2OvXr2dCQoKubRQUFHD//v1a775s2TJD18nowp0yZQqbmppIku3t7VywYIHubSxYsIDt7e0kyaamJk6ZMiVs8yVSHMCoUaP40UcfacU0c+ZMw9qKiori8uXLtaJ6+umnDWvLyMKdPn06W1tbSZI7d+5kRkaGYeuRmZnJv/zlLyTJ1tZWw/aGxOiGS13jsbGx3L17N0ny6NGjHD9+vCntPvDAA9qu/BNPPGFIG0YV7pQpUzSTv/7663S5XIbny+VysaKiQjO7ET27GN1wqWs8WDz19fUcPXq0qW3PnTuXgUCAJHnvvffqvnwjCtftdmu76xUVFXQ4HKbly+FwaNurqalJ92N2MbrhUtNwSUmJdnyZk5OjJIYlS5aQ7Du7nJKSouuyjSjc4Im3nTt3mtKTXyiXy6XtxldWVlo+X3ro2oJ0Fj93Gx/e/k98rOZhLql6iA9tnccfrZrB/H+6Xnl8g5WS6+hutxsHDx6E2+3GggUL8PLLL5sdgsb27dsxY8YMbNy4EXPnztVtudT5unBJSQk2btyIjo4O5ObmoqGhQZflhkpmZiYOHDiAkSNHoqSkBG+++aYuy9U7X0PFGeVA0bO3Inf2dy/7vRXZa0yKaOiY/utSWVlJkty2bZvyX7rMzEztzPLs2bN1W66ePVRycrJ2ndyIs+uhqrS0VNsTSk5Otly+hqoIRwRnvzyTP/tiEf+lbiFv/9//yOtuvIZxybGMTYrhNfmpnL54Kh/+8/3KYw1B5jY4YcIEkmRnZ6ehZ4tDUVlZGUmyqqpKt2XqWbi//OUvSfZdJ1edq6CC19l/8YtfWC5fQ9X3Hp6smfy7d2Ypj0cnmdvgqlWrSJJr165VveKaoqKiePLkSZLktGnTdFmmXoXrdDpZX19PkiwsLFSeq6BmzJihnUjV46SgVYwePTKKj9U8zJ99sYjFz92mPB4dZV5jcXFxPHPmDEkyPz9f9Yqfp+eee44kuWHDBl2Wp1fh3nXXXSTJzz//fEh3vOmtiIgI7XbZWbNmWSZfQ9WUn+TyZ18s4s++WMTkLDUDooyQqePR58yZg4SEBOzduxc1NTVmNn1F1q1bh0AggDlz5iApKUl1OBoLFy4EAKxZs8ZSz6gniTVr+k5EBWMcDoy7tW9AUEdTJ07955lvP4gAIhzWOFF4NZhq9Ntuuw0A8Mc//tHMZgdFQ0MD9uzZg+joaEybNk11OAD6RvEFR+9ZMWfBmG655RY4HMNjDpP0vFQAwKm/9Zk8f971+Omm+/B47QL8t0OlKP3gARQ/dxsSx4xSGWbImLp1PB4PAOCvf/2rmc0Omk8++QTAt3GqZsKECYiPj8exY8fQ0tKiOpyLaG5uRn19PUaMGIGcnBzV4QyZyGgn4pJiAQDnOn24599vR9GztyLtBjecUU5EOCLwD9eMQN6ciZj/H3OQc/s4xREPHtNmmImLi8PEiRPh8/lw4MABs5oNCa/XCwCYOnWq4kj6CP7gBOOyIl6vF5mZmfB4PPj8889VhzMkokdGaa/H/WMmIqOcaPzkK3zwwj401bbAFReJ7BljcevPb0JsQgzufKEQZ461oeVzc8bsDwXTevT8/Hw4nU7U1tbi7NmzZjUbEkFDWaVHLygoAGB9owPWydmQ6HcMHhnlxMn/14KND27GiaomBM4F0NN6Fgfe/Bx/emQLegO9iIyOxPcf+57CgAePaUZPT08H0DfjiVU5evQoACA1NVVxJH0EcxaMy4oEY0tLS1McydDxdfnO+3vfmioEzl08j96X1Sdx5P2+OxPH/mA0nFFOU+IbCqYZPTgpYXAqIyvi9/vh9/vhcrngdKrfeOGQs/5TU4U75772wX/Wr/194tOvBvxu4yd9n0VGRyIx0/on5obHqVJB0AMCp4+0an/2tA98iNnT9u1nUSNcRkalC6YZvaenB4C1f/kjIyMRGRkJn8+HQCCgOpywyFkwNivvdYRC04Fvr27EJMQM+L3YxGjt9dmOc4bGpAemGb2pqQkAzptt1GqMHTsWQN9lIysQzFkwLisSjO3kyZOKI9GHL7Yf0V6PvvE7A35v9I3XAujb3T9zrM3wuIaKaUavqalBIBBAbm4uoqOjr/wPCrDa5ayqqioA1j6jbbWcDZWju49rN8vcVOZBZMzFV6BH/5fvYOwPRgMADr/3N/T6rf/gC9OM3tXVhUOHDsHlcmHSpElmNRsSwaL99NNPFUfSRzhcuhpuRmeA2PHsHvT6e5GSnYR5r92NMTdfh5iEaIy8ZgQKfjoJP157ByIcEeg+04O9//aJ6pAHhamPZPJ6vcjNzcWNN95oGTP153vf67smapWiraurQ2dnJ8aMGQO32225u+NSU1ORmZmJzs5OHD58WHU4ulG/txHv/fdd+K//4xZck5eKkldmXfSdr1u68H/LtqL9y04FEYaOqWfdd+3aBQC4//77zWx2UGRkZODmm2/G2bNnsW/fPtXhAAB6e3uxe/duANbMWTCmDz74YNg9t632rTq8evcbqP7jQbQ2tMHX48fZznNoqm3B3n/7BOvvqMBX1eF1XsK0oXIyTDV0BYep1tXVyTBV0VBkboMy8URosvrEE8eOHRtWE08MY5nbYE5ODkmZSioUWXEqqZ07d5IcnlNJDVOZ36hMDhmaZHJIkQ4yv1G3260V7iOPPKI0Adu3bydp/XnK+8+Dr3JPqP8Po55PWhWjGy41DcsDHEKXPMBBNASpa7z/I5nM7qXmzZsnj2QKQQ6HQzvkkkcyhaXUNS4PWQxd/R+yWFFRYdpDFoMmb21t5eTJk8MmXyJNagMYNWoUP/zwQ62nMPOxyU899ZRhbRlZuPLYZNFVSHkAjI+P59atW7WN/corrzAhIUHXNgoKCrh//36SZCAQ4LJlywxdJ6MLd8qUKdpufHt7uyFn40tLS7UTb01NTYY8LtmsfInUB0Cg7xhw6dKl7OrqIkk2NjaytLSUI0aMGNJyx40bx1WrVmm76nV1dYb1Sv1lRuG63W7tBB3Zd519xowZQ7qDLiIigjNmzNCuk5N9J970PlmpIl82l/IAzlN2djb37Nmjbfi2tjaWl5czLy9v0AUcExPDWbNm8d1339WWEwgE+MILLzA2NtaU9TCzcO+77z7tcmXwx2zp0qUhnTBLTU3l0qVLtdtayb6rEXpeQrNKvuwoJY9NvhIOhwMlJSVYtGgRbr31Vu39trY2VFVVwev1ora2Fp2dnfD5fIiJiUFKSgoKCgrg8XiQm5uLyMi+gXnd3d14/fXXUV5ejurqatPWgSY/Bjg5ORkLFizAwoULkZGRob1fX18Pr9cLr9eLo0ePnjfH29ixY+HxeODxeJCZman9T0NDA9auXYvf/OY3OHXKnKmMzc6XHVH+a3M53XDDDVy9ejUbGxs5WPx+P6urq7ls2TImJqp5fpaqHsrpdPKuu+7ili1b2NHRMeicdXR08J133uGsWbPodDptky+7yJI9+kCkpaVpPVB2djZiY2PhcrnQ09OD9vZ27N+/H16vFzU1Nejq6lIaqxV6KIfDgZycHC1naWlp583xdvLkSa23P3z4sNKhplbI13AmrIweTkjhhobky1hkumdBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAWJ0QbABYnRBsAFidEGwAYMephocRigIgnUY7LBe6dEFwQbIxBMGIRMphIbky1ikRxcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRhcEGyBGFwQbIEYXBBsgRg8z0tLSVIdgiRiE0BCjhxEPPvggjhw5guLiYmUxFBcX48iRI5g/f76yGITQEaOHEVOmTEFcXBw2bdqkxOzFxcXYtGkT4uLiUFBQYHr7wtCgSH8F0Xu55eXlJMnu7m4WFxebtj7FxcXs7u4mSZaXl4dNvkSalAcwLGVk4ZptdqNNbnS+RCAsEMCwlNGFa5bZzTC5Gfmyu8LmAQ5Lly5FQkLCoL9fXV2NTZs2GRbPlTDjgQTl5eV49NFH0dPTg3vuuQfvvfeerssPHpPHxMRg9erVWLx4sa7L74/VHuCQFh+PB/Py8IPRo3HtyJFwRETgq85O/KW+Hq/u34+mr79WHWJIRKoOwChOnjypOgTDCRrv0UcfxaZNm3Q1u5kmtxo/zMzEyhkzMCIq6rz3xycmYnxiIuZMnIhlf/4zPmhoUBRh6IRNj+5yua74az9nzhxkZWUhEAjg17/+Nb5W+KtrZg+ld8+uwuRW6dFz3W5U3HMPoiMj0dLVhZX79mFPYyN8vb2Ymp6Of5k2DWMTEvC1z4eSP/0JX5w+rTTeUFB+/KCH4uPj+eSTT/Lpp5/m/fffrzwes4859TpmN+uYXHW+BtJrd9/NLxYtYs3DD3N8QsJFnyfFxHD3Aw/wi0WL+MqPfqQ83sFq2FxHnzRpEpxOJ4C+43O7sXjxYqxevRoxMTFXfZ3dzrvrQN9x+Y3f+Q4A4E91dfhba+tF3znd04P1NTUAgJtHj8a4EM4bqWTYGD0/Px8A0N3djbq6OsXRqGEoZre7yQFgYnKy9vrjEycG/N7HX36pvS4aN87QmPRiWBg9LS0N11xzDQCgtrYWgUBAcUTquBqzi8n7+IfoaO11+9mzA36vrd9nk9xuQ2PSi2Fh9GBvDthzt/1CQjG7mPxbOs+d0173N/2FjOr32fjERENj0ouwN3pERAQmTZoEAGhpacGJy+xy2YnBmF1Mfj7/eeaM9jp4rH4p+n+WGBNjaEx6EfZGz8rKwsiRIwEANd+cJBH6uJzZxeQX09DejkN//zsAYPZ3v4sxo0Zd9J2E6Gj8c789yAuvtVuVsDd6cLe9t7dXjH4JLmV2MfnAvPDxx+glEe9y4bW778aPJ0xAalwckmJjMWPMGFT8+MdIHzEC3T4fAGjX/61OWN8ZFx0djQkTJgAAjhw5go6ODsURWZP+d9Bt3rwZABAVFSUmvwQfNDTg2T178K/f/z5S4+Px/A9/eNF31lVVYdq11yI/Le28E3NWJqx79NzcXLhcLgCy234lFi9ejM2bNyMqKgpRUVHYvHmzmHwA/k9tLe554w28eegQjre346zfjzM9Pdjd0ICH33kHL3z8MRK+OTb/qrNTcbSDI6x79OBue09PDw4dOqQ4GmtTXFyMoqIi7e+ioiIUFxfrPhBmuFB3+jR+sWvXJT+Ldjpx3TfnhQ60tJgY1dUTtj16UlISMjIyAAAHDx6E3+9XHJF1ufCYfKh30Nmd748eDaejzzrhMrAlbHv0/tfOZbd9YC534s2IUW924KffXM79sqMD74eJ0cO2R8/LywMAnD59Gg1hkmyzuZzJ9bg33o48Mnkyvn/ddQCA//Xhh+gNk7PuYWn0zMxMJH5zR5LcCXdpBnMJTcx+MdeOHInNJSV4MC8PE5KSMCo6Gu64ONw8ejT+/fbb8cRNNwEAXj94EFuPHFEc7eAJy133yZMnA+i7hrl//361wViQUK6TGzl5RbgyMSUF/5qScsnP/L29eKWmBs/v22dyVEMj7Izucrlw/fXXAwCOHTuG1ksMJbQzV3MzjJj9W/7e1YX/uXcvpl93HbISE5EUG4teEie//hofNjZi46FD+PzUKdVhXhXKB8UPR6mYSGGok0aomkpaVb5sJuUBDEuZXbh6zQyjyuxidMOlPIBhKTMLV+/pn1SYXYxuuJQHMCxlVuEaNceb2WYXoxsu5QEMS5lRuEZP5Gim2cXohkt5AMNSRheuWbO1mmV2MbrhUh7AsJSRhWv2lMxmmF2MbriUBzAsZVThqpp33Wizi9ENl/IAhqWMKFxVJg/KSLOL0Q2X8gCGpYwo3Ndee02ZyYMKmv21116zfL5E50l5AMNSRhRuZGQkH3roIeXr9tBDDzEyMtLy+RJ9q7B5yGK4QYs8NDBckHwZS1gOUxUEITTE6IJgA8TogmADxOiCYAPE6IJgA8TogmADxOiCYAPE6IJgA8TogmADxOiCYAPE6IJgA8TogmADxOiCYAPE6IJgA8TogmADxOiCYAPE6IJgA8TogmADxOiCYANkzjhBsAHSowuCDRCjC4INEKMLgg0QowuCDRCjC4INEKMLgg0QowuCDRCjC4INEKMLgg34//UebyJ4yIx3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 230x230 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Circle, Rectangle\n",
    "from IPython.display import display\n",
    "\n",
    "def display_tictactoe(board, size=230, moves_scores=None):\n",
    "    # Setup\n",
    "    fig, ax = plt.subplots(figsize=(size/100, size/100), dpi=100, facecolor='black')\n",
    "    ax.set_xlim(0, 3)\n",
    "    ax.set_ylim(0, 3)\n",
    "    ax.axis('off')\n",
    "    \n",
    "    # Style\n",
    "    bg_color = 'black'\n",
    "    line_color = 'white'\n",
    "    number_color = 'gray'\n",
    "    line_width = size / 160\n",
    "    \n",
    "    # Grid\n",
    "    for i in range(1, 3):\n",
    "        ax.axhline(y=i, color=line_color, linewidth=line_width)\n",
    "        ax.axvline(x=i, color=line_color, linewidth=line_width)\n",
    "    \n",
    "    # Symbols and scores\n",
    "    for i, mark in enumerate(board):\n",
    "        x, y = i % 3 + 0.5, 2 - (i // 3) + 0.5\n",
    "        a = 0.8\n",
    "        b = 0.27\n",
    "        if mark == 'X':\n",
    "            ax.plot([x-b*a, x+b*a], [y-b*a, y+b*a], color=line_color, linewidth=line_width)\n",
    "            ax.plot([x-b*a, x+b*a], [y+b*a, y-b*a], color=line_color, linewidth=line_width)\n",
    "        elif mark == 'O':\n",
    "            ax.add_artist(Circle((x, y), b, fill=False, color=line_color, linewidth=line_width))\n",
    "        else:\n",
    "            if moves_scores:\n",
    "                score = next((score for move, score in moves_scores if move == mark), None)\n",
    "                if score is not None:\n",
    "                    if score == 1:\n",
    "                        color = '#75db69'\n",
    "                    elif score == -1:\n",
    "                        color = '#db6969'\n",
    "                    else:\n",
    "                        color = 'gray'\n",
    "                else:\n",
    "                    color = number_color\n",
    "            else:\n",
    "                color = number_color\n",
    "            ax.text(x, y, str(mark), ha='center', va='center', color=color, fontsize=size/12)\n",
    "    \n",
    "    # Display\n",
    "    plt.tight_layout(pad=0)\n",
    "    fig.subplots_adjust(left=0, right=1, top=1, bottom=0)\n",
    "    display(fig)\n",
    "    plt.close()\n",
    "\n",
    "# Example usage\n",
    "board = ['X', 'O', 'X', 'O', 'O', 6, 7, 'X', 9]\n",
    "moves_scores = [(6, 1), (7, 0), (9, -1)]\n",
    "display_tictactoe(board, moves_scores=moves_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Manually adjustable index\n",
    "depth_complexity_index = 1  # Change this to select different depth complexities\n",
    "\n",
    "# Get the list of symmetry groups for the selected depth complexity\n",
    "symmetry_groups = set()\n",
    "for board in dataset.boards.values():\n",
    "    if board.category.depth_complexity == depth_complexity_index:\n",
    "        symmetry_groups.add(board.category.symmetry_group)\n",
    "\n",
    "print(f\"Depth Complexity: {depth_complexity_index}\")\n",
    "print(f\"Number of Symmetry Groups: {len(symmetry_groups)}\")\n",
    "\n",
    "# Calculate choice complexity ratio and sort symmetry groups\n",
    "symmetry_group_choice_ratios = []\n",
    "for symmetry_group in symmetry_groups:\n",
    "    for board in dataset.boards.values():\n",
    "        if board.category.depth_complexity == depth_complexity_index and board.category.symmetry_group == symmetry_group:\n",
    "            choice_complexity = board.category.choice_complexity\n",
    "            choice_ratio = choice_complexity[0] / choice_complexity[1]\n",
    "            symmetry_group_choice_ratios.append((symmetry_group, choice_ratio))\n",
    "            break\n",
    "\n",
    "# Sort symmetry groups by choice ratio (highest first)\n",
    "sorted_symmetry_groups = [sg for sg, _ in sorted(symmetry_group_choice_ratios, key=lambda x: x[1], reverse=True)]\n",
    "\n",
    "# Display the first board of the top 20 symmetry groups in the given depth_complexity, ordered by choice ratio (highest first)\n",
    "for symmetry_group in sorted_symmetry_groups[:20]:\n",
    "    print(f\"\\nSymmetry Group: {symmetry_group}\")\n",
    "    for board_hash, board in dataset.boards.items():\n",
    "        if board.category.depth_complexity == depth_complexity_index and board.category.symmetry_group == symmetry_group:\n",
    "            move_score_pairs = [(score.move, score.value) for score in board.scores if score.move is not None]\n",
    "            choice_ratio = board.category.choice_complexity[0] / board.category.choice_complexity[1]\n",
    "            print(f\"Choice Ratio: {choice_ratio:.2f}\")\n",
    "            display_tictactoe(board.state, size=200, moves_scores=move_score_pairs)\n",
    "            break  # Display only the first board of each symmetry group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: XOXOXOX89\n",
      "Depth Complexity: 0\n",
      "Choice Complexity: (0, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 123456789\n",
      "Depth Complexity: 0\n",
      "Choice Complexity: (0, 9)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 1234XOX8O\n",
      "Depth Complexity: 1\n",
      "Choice Complexity: (4, 5)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 123OXXO89\n",
      "Depth Complexity: 2\n",
      "Choice Complexity: (4, 5)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 12O456XOX\n",
      "Depth Complexity: 3\n",
      "Choice Complexity: (4, 5)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: X234O678X\n",
      "Depth Complexity: 4\n",
      "Choice Complexity: (2, 6)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 12345XO89\n",
      "Depth Complexity: 5\n",
      "Choice Complexity: (6, 7)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Board: 123O5X7X9\n",
      "Depth Complexity: 6\n",
      "Choice Complexity: (4, 6)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "examples = [\n",
    "    (0, \"XOXOXOX89\"),\n",
    "    (0, \"123456789\"),\n",
    "    (1, \"1234XOX8O\"),\n",
    "    (2, \"123OXXO89\"),\n",
    "    (3, \"12O456XOX\"),\n",
    "    (4, \"X234O678X\"),\n",
    "    (5, \"12345XO89\"),\n",
    "    (6, \"123O5X7X9\")\n",
    "]\n",
    "\n",
    "for depth, board_hash in examples:\n",
    "    board = dataset.boards[board_hash]\n",
    "    print(f\"\\nBoard: {board_hash}\")\n",
    "    print(f\"Depth Complexity: {board.category.depth_complexity}\")\n",
    "    print(f\"Choice Complexity: {board.category.choice_complexity}\")\n",
    "    move_score_pairs = [(score.move, score.value) for score in board.scores if score.move is not None]\n",
    "    display_tictactoe(board.state, size=200, moves_scores=move_score_pairs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of filtered boards: 431\n"
     ]
    }
   ],
   "source": [
    "from generate_dataset import Dataset\n",
    "\n",
    "dataset = Dataset.from_json(\"dataset.json\")\n",
    "\n",
    "def get_filtered_boards(dataset):\n",
    "    # Get unique, decidable symmetry groups\n",
    "    decidable_symmetry_groups = set(\n",
    "        board.category.symmetry_group\n",
    "        for board in dataset.boards.values()\n",
    "        if board.category.choice_complexity[0] != 0\n",
    "    )\n",
    "    \n",
    "    # Filter boards\n",
    "    filtered_boards = []\n",
    "    for symmetry_group in decidable_symmetry_groups:\n",
    "        # Get the first board from the symmetry group\n",
    "        first_string = symmetry_group.split('|')[0]\n",
    "        filtered_boards.append(dataset.boards[first_string])\n",
    "    \n",
    "    return filtered_boards\n",
    "\n",
    "# Get filtered boards\n",
    "filtered_boards = get_filtered_boards(dataset)\n",
    "print(f\"Number of filtered boards: {len(filtered_boards)}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of filtered boards after removing threat patterns: 68\n",
      "Number of removed boards with threat patterns: 363\n",
      "\n",
      "Removed boards:\n",
      "Board: 12O456XX9\n",
      "Choice Complexity: (5, 6)\n",
      "Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 1OOXOXXX9\n",
      "Choice Complexity: (1, 2)\n",
      "Depth Complexity: 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 123O5X7OX\n",
      "Choice Complexity: (2, 5)\n",
      "Depth Complexity: 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 123OOXXOX\n",
      "Choice Complexity: (2, 3)\n",
      "Depth Complexity: 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 1OOX5X7X9\n",
      "Choice Complexity: (2, 4)\n",
      "Depth Complexity: 1\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAANwAAADcCAYAAAAbWs+BAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAXA0lEQVR4nO2dfVBU97nHv8vuIu8gsivEAFHErAoqrk3ShNtoNJpYI7kt+NJR2kbFblobpzZOq4n03s4k03TSSf5oHMBkMvH2jproTSRXxySGO1atibxYY3yDlRSiKBJAUIQFfO4fuhs1vizLnud3DjyfmWdGWTjPw3N+H87uOef3OyYABEEQWAhRXYAgDCZEOEFgRIQTBEZEOEFgRIQTBEZEOEFgRIQTBEZEOEFgRIQTBEZEuD7idrvhdrtVl6Ec6UNgiHCCwIgIJwiMiHCCwIgIJwiMiHCCwIgIJwiMiHCCwIgIJwiMiHCCwIgIJwiMiHCCwIgIJwiMiHCCwIhFdQHC3TGZTEhPT4fT6URaWhrCwsIAAJ2dnXC73aioqEB1dTWIBv4So2FhYZg4cSImT54Mu92OIUOGoKenB+3t7fjiiy9QUVGB8+fPqy7zjpCE/+F2u8ntdmuex2q1Ul5eHu3atYsuXLhAd+PChQu0a9cuysvLI6vVOmD6AIDsdjv9/ve/p0OHDlF3d/dde1FXV0clJSU0efJk5ePl5jBd+4fgJ945YGlpaZpsPyYmBqtWrcKyZcuQlJSEK1eu4MiRI6ioqEBFRQWOHTuGS5cuAQAiIyMxduxYOJ1OOJ1OTJgwAQDQ0NCAkpISvPrqq2hra9OkTq37AACZmZn43e9+h9zcXISGhuLSpUsoLy/39aKurg4ejwcWiwXx8fGYNGkSnE4nHnjgAdxzzz0AgM8++wyvvfYaNm3apFmdfUW59UYKLf+yz5w5k+rq6oiIqKmpiV555RUaNWqU3z8/atQoeuWVV6ipqcn3l37mzJmG64PVaqXCwkLyeDxERPTPf/6TCgoKKDIy0q+fN5lMNH36dNq6dSv19PQQEdGOHTvo3nvvVT5+oIMCDBVaDLTw8HAqKSkhIqKuri5au3YthYWFBby9sLAwWrt2LXV1dRERUUlJCYWHh+u+DwBo3LhxVFVVRUREtbW1NGvWrH5tLyUlhUpLS4mIqLW1lfLz81WPIaXJDRfBHmgxMTG0Z88eIiI6ePAgjR8/PmjbzsjIoPLyciIi2rNnD8XExOi2DwDooYceoubmZiIieuONNygqKipo287Pz6eWlhYiIlq7dq3KMaQssSEjmAMtMjKS9u/fT0REGzduJIvFEvR6LRYLbdy4kYiI9u3b5/fbMs4+AKApU6ZQW1sbeTwemj9/vib7buTIkVRTU0NERGvWrFE1hpQkNWwEc6Bt376diIjeeustMplMmtVsMpnorbfeIiKi7du3664P9957LzU1NVF3dzfl5ORouv+SkpJ80i1evFjFGGJPaOgI1kBbsmSJ78O82WzWvG6z2Uw7duwgIqJnnnlGN30AQDt37iQioqVLl7Lsw5EjR1JLSwu1traqOJHCmqxPEZkQTuPmptNjLzxCP9n0NK08vJSer3bRT7fnKaspGAMtOTmZLly4QM3NzZSUlMRWe1JSEjU3NwdloAX7D0+wjrz+Rn5+PhER7dy5kzWvrm/tcsxJxw9fnQHnTydghDMJ1nCr6pKCwmuvvYaYmBg899xzaGhoYMvb0NCAlStXIjY2Fq+//jpb3tsRHx+Pv/zlL2hpacHy5ctZc7/zzjv48MMP8cQTT2D+/PmsuVkN70tk5Doo7+059G+rHqQxs0bRg8uzDH+Eu++++6i3t5f27t2r7HfYt28f9fb2UmpqqrI+AKBVq1YREdFzzz2npA8pKSnU09ND//jHPzjzqtnpgcT4H91veOFefvllIiJasGCBst9h4cKFRET00ksvKeuDyWSimpoaunjxIsXGxirrxbZt24iI2G4D0/VbyoFGaGgolixZgnPnzmHbtm3K6ti6dSsaGxuxdOlShIaGKqnh8ccfR1paGv72t7/hwoULSmoAgDfeeAMA4HK5WPKJcIxkZWXBZrNh8+bN8Hg8yurweDzYtGkTbDYbJk2apKSGWbNmAQA2btyoJL+X3bt348yZM5g5cyZLPhGOEafTCeDqDbWq+fzzzwF8WxM3TqcTPT09qKioUJLfCxHh4MGDSElJQUJCgub5RDhGvINb9SC7vgYVwplMJmRlZeHo0aO4fPkye/6b4eyFCMdIZmYmOjo6cPLkSdWl4OTJk+jo6EBmZiZ77tTUVMTExODQoUPsuW9FVVUVALD0QoRjJDo6Gi0tLbqYmX3lyhW0trYiOjqaPbc3Z3NzM3vuW9HS0gIALL0Q4RixWCzo6elRXYaP7u5uWK38NxNYLFdX9tBLL7q7uwGApRciHCNdXV0YMmSI6jJ8hIWFobOzkz1vV1cXACi7JHEz3n3C0QsRjpHGxkbYbDaEh4erLgXh4eFISEhQsuBOY2MjACAlJYU9963w1sHRCxGOkcrKSpjNZkycOFF1KZg0aRLMZrOSM6ZNTU2or69XdkniZjjPHotwjKg8FX8zqi9RVFRUIDk5GXa7XUn+6/FeEzx8+LDmuXS9LmV0YiTyP8jz/d8SagYAJKTH45ef/cz39eMf1mD3H/dyl9dnysvLAQBTp07FX//6V6W1PProowC+rYmb8vJyPP3005g6dSq2bNmipAYAiIqKgtPpxJEjR+QznMkcgoj4cF+ERl39kB1iufnrxpi2U11djaqqKuTk5GD48OHK6khMTEROTg4qKytRU1OjpIZ3330XAFBQUKAkv5dFixYhMjISmzdvZsup7E5tI0Z/75JfunSp8oVsXnjhBSIiWrJkibI+AKCPPvqIiIgcDoeyXhw+fJg6OzvJZrNx5VTzixo1+jvQIiIiqLW1lU6fPh3UVan8jaioKDp9+jS1tLRQRESEsj4AoJycHCIi2rBhg5J9OWvWLN8CTox5+X9RI0cwBtqLL77oWwqOu/7169cTEdGLL76ovA9ms9m3BuVjjz3G2ofo6Gj66quvyOPxUGZmJmdu3h1u9AjGQLNarUoG2vTp04mIqLKyst/PHwjWmiYTJ04kj8dDtbW1rEd87x+edevWcY8h1mSGj2APtPr6ekpOTta87uTkZKqvryePx0MTJkzQTR8AUGFhIRERbd68mUJCQjTvxYIFC3x/eLRYC/QuwZrM8BHMgbZixQoiIjpx4gSNGDFCs5pHjBhBJ06cICKiFStW6K4PVquVPv30UyIievPNNzWVLicnhzweD33zzTc0duxYFWOIPaGhI9grDv/hD3/wraOfkZER9HozMjKotraWiIgKCwt124eoqCg6cOCA70inxdvLZcuWUXd3N7W1tdGDDz6oagwpSWrY0GJN/dWrVxPR1Qd5rFmzJihvcywWyw0P9Fi9erXu+xAdHe070tXW1gbt8+0999zje6BHU1MTTZkyReUYUpbYkKHVU2NmzZrle1RVeXk5zZ49O6C3ViEhITR79mzfQzy0emSVVn2wWq20bt0636OqNmzYEPB1utjYWFq5cqXvIR47d+7UwyOrlCY3XGj5XLSYmBjfY6uIiE6dOkWrV6+m+++//47PHggJCSGHw0GrV6+mU6dO+X6+uLg4qE/M4eoDcPWkkvdMLhHR7t27ad68eWS32+/4c+Hh4ZSdnU3FxcV08eJFIrr6mKpgLO8ejJAnoPYRjid/ZmRkwOVyYfHixb5ZyO3t7aiqqsLRo0fR0dEBAIiIiMC4ceOQlZV1w/dt3LgR69evx5EjRzSrkaMPZrMZc+bMwbPPPnvDqlpff/217wmoXV1dsFqtGDp0KLKysjBu3DiYzVfvua2pqcH69evx9ttv62Z2uQjXRzgGmpfo6GjMmzcPDz/8MJxOJ8aPH++bLe2lp6cHX375JSoqKrB//35s2bIF7e3tmtfG2QcASE9PR15eHqZMmQKn03nLuXRtbW2orKxERUUFPvroI3z88ce6WM7iekS4PsI90K4nLCwMKSkpvgmsly9fRl1dnZJZ2yr7AAAJCQmw2WwICwtDd3c32tvbUVdXpzvBbkbX03OEG+ns7NTFil96oKmpCU1NTarL6DO6np4jCAMNEU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGPF7toD37vDBTnJyMgCgvr5ecSVqkT7ciL+zJuQIJwiMyHy4PqJ6HphekD4EhhzhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIEREU4QGBHhBIERduGys7PhcDhYc+bm5iIuLo41p+A/cXFxyM3NZc3pcDiQnZ3NmtML2/ON7XY7tbW1UUNDQ8APSu9rFBQUEBFRaWlpULan9bOtjRLB7ENpaSkRERUUFLDU7nA4qKGhgdra2shms3H3jndHeQXgkE6LXCJc8PvgFYBDOs5ctwn+ncUhnVY5RDht+sAhgg5kI6jaYVpKp+W2RTjt+qClEDqRjaByp2khhtZHTxFO2z5oIYaOZCOo3nHBFITjraoK4R5eMYWer3bdMSYuHMdak5Z9CKYgOpONLFBMcXExAKCoqAhlZWWYNm0ajh8/3uftFBQUoKioCGfPng14G3rnUlMHWr66cOvXGjuYq9GO48ePY9q0aSgrK0NRURGAb8dJX3A4HCgrK0NiYiKWL18e0Da0QLn1QP+OTpxnPlUe4Z780zTl+4mzD/05OuntyHZdKC/AF4GIwykbIMJx9yEQcXQsG0EHBdwQfRGIWzZAhFPRh74IpHPZCDoo4Dvhj0gqZAPUCpf/QS798NXpNO+dufT0+ifokZXfo2GjhyrZR9x98EckA8hG0EEBt4w7CaVKNkB/Zyl/e+IXNG3Nw2QKMQ34PtxJKIPIRtBBAbeNW4mlUjZAzUCbMH8sff+XTkqcYKfwoWFkDg2hhDHx9Ph//MAn3qOrHxrwfQBuLZaBZCPooIA7xvWCrVu3TqlsgP4ufD+wbBI9X+2i3xwtoJgR0YOiD9cLtm7dOiPJRtBBAXcNr3RERI2NjcpkA/QnnCnERL/4+2J6vtpFk/MzB00fHA4HNTY2+saFQWQjmYBqcOgKoeFwIwBgaGqs4mqEu6F74a6/g6SwsBA2mw1lZWXsk1j1TK+nFwAQYtH97gwK3jtIbDYbCgsLcfbsWRQVFaGgoEB1aX6h/DB7u5CTJv7Fz/53Pj1f7aKHXJMHfB/kpIlGIZcF/ItRU1N8ZyoTM/lmL8tlgYBDeQHfCbnw/W0MGz2UZv7xB2RzDLvxNRPIMWc0/bryGXq+2kX/XvQk6z6SC98Bh/ICbgi5tevGsI8d5juC/erzn1P++7m06L0f0a8O/tz39QX/nUNDokNZ95Pc2hVwKC/AF3Lz8ndjSHQoPeSaTD8qfpKW7f4J/bpqCf3mywJ6dv9P6ccls2nc3HT2u0w4+yA3L2sUMj3HWCHTcwIO5QUERRgu6UQ4nj4EQxidSqe2AFliwZghSywEHOqSyyJCxg1ZRCjgUJNYlskzdsgyeQEHf1JZCNb4IQvBBhy8CWWp84ERstR5wMGXzGazycM8BkjIwzwCDt4dlZ2dzX7/Y25uLsXFxQVlWyJc8PsQFxdHubm5rPU7HA7Kzs5m75vp2j8EP3G73QCAtLQ0xZWoRfoQGINjApUg6AQRThAYEeEEgRERThAYEeEEgRERThAYEeEEgRERThAYEeEEgRERThAYEeEEgRERThAYEeEEgRERThAYEeEEgRG/58N55z8NdpKTkwEA9fX1iitRi/ThRvydFyhHOEFgRGZ89xGZ6XwV6UNgyBFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEBgR4QSBERFOEXFxcSgtLYXD4WDL6XA4UFpairi4OLacwo2IcIqYMWMG5syZg7KyMhbpHA4HysrKMGfOHMyYMUPzfMLtIQn/w+12k9vtDsq2CgoKiIiooaGBHA6HZjU7HA5qaGggIqKCggLd9WGQhfICDBXBHmhaS6eFbFr0YRCF8gIMFVoMNK2k00o2rfowGMICnTIiOhr/t2iRX9974PRpLN6+XeOKtKO4uBgAUFRUhLKyMkybNg3Hjx/v1za9n9kSExOxfPlyX46BwBCzGYsyMjB79GiMiotDiMmEr9vbsevUKWyoqkJHT4/qEm+LboXr6ulBeUPDbV8PMZkwOTERAFB59ixXWZoRTOkGsmzxYWF4+6mnMDYhAVeI4G5pgae3F+nx8VgxZQrmjB6Nhe+/j28uX1Zd6m1RfpgNJLKTk6na5aJql4tSYmLY8mr9Vqq/by+1fBvJ2YfbRcns2VTtctGuhQtpVFyc7+vx4eH0zty5VO1y0Ttz57LX5W8Y9rJA7rVT6Z+fOYO6tjbF1QSP4uJiLF++HImJiX2+ZDCQj2wAkB4fj6mpqQCANWVlONXa6nut+fJl/PaTT3CpuxvfHzECD48YoajKO2NI4WJCQzHjvvsAAO/187OOHglEuoEuGwB8LykJAHD24kVU3OJjRGNHBw6eOQMAeCo9nbU2fzGkcE+lp2OIxYKLHg92DtCHjPRFusEgGwDEDhkCADh36dJtv+fsxYsAgKxrn+/1hiGF+/G1wbfD7Uanjs9I9Rd/pBsssgFAW1cXAGB4ZORtvycxKgoAkBobC7PJxFJXXzCccGPi45FptwMA3jt2THE12nMn6QaTbABwuLERwFWpsoYP/87rtogITLn2ttMSEoKo0FDW+vzBcMJ5j27ulhZUnTunuBoebiXdYJMNAL44fx6Hru3zPz32GBzDhvleGx4Zidcff/wGycIt+rvqpb+K7oAlJAQ5Y8YAALYNwJMld+L663R79uwBANhstkEjm5dVn3yC/8rJwci4OHyQl4fT7e3w9PYiNTYWJgDvHjuGvLFjAQAXPR61xd4CQx3hpqWmYlh4OHquXMH/nDypuhx2iouLUVhYCJvNBpvNhsLCwkElGwDUtbUh5913UVxVhdrWVtgjIpAQEYG99fVY8P772Pf11wCAS93duNjdrbja72KoI5z37eTf6+pwvqNDcTX8OBwOuFwu3/9dLhe2bNnS79vAjEZLZyf+fOAA/nzgwHdem5qSAgD48vx57rL8wjBHuGHh4fjBtedKD8Rrb3fj5s9sgV4cH+hMHzkSAPBxba3iSm6NYY5wT48ZA6vZjObLl/Hpv/6luhxW7nSCJJg3PBuduenpcAwbhtbOTt1+xjfMEc77dvKDkyfRc+WK4mr4uJNs/bkNzKg4ExORnZyMkOuusVlDQvCT8ePx0tSpAID/3LsXbTo8YQIY5Ag3wW5Henw8AGCrTv9yaYE/p/61mNqjZzLtdqx95BF0dHfjTHs7Ont7cV9sLKJCQ+Hp7UXhnj0ora5WXeZtMYRw3qPbF42NONHcrLgaHvpynW0wSffZ6dN479gxZCUmYnhkJKxmM85duoTS6mq8ffjwDTc06xXlUxaMFBzTUgKdYsO1RgpXHwZoKC/AUKH1QOvvfDYu6US4gEN5AYYKLQdasCaPckgnwgUcygswVGg10II9U1tr6US4gEN5AYYKLQaaVssiaCmdCBdwKC/AUBHsgab1GiRaSSfCBRzKCzBUBHOgcS34o4V0IlzAobwAQ0WwBhqXbN4ItnQiXGBhmFu7BhoJCQmIjIxkm8/mvQ0sMjISCQkJmucTbo0JV80T/MR9bdGitLS0fm/Lbrej8dqyAVzYbDacD8LUlWD2YTAhRziFcMsGICiyCYEjwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiM74FgRE5wgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCIyKcIDAiwgkCI/8P5v7kkAGx6y8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n"
     ]
    }
   ],
   "source": [
    "from typing import List\n",
    "from generate_dataset import Board\n",
    "\n",
    "\n",
    "def get_highest_scoring_moves(board: Board) -> List[int]:\n",
    "    highest_score = max(score.value for score in board.scores if score.move is not None)\n",
    "    return [score.move for score in board.scores if score.move is not None and score.value == highest_score]\n",
    "\n",
    "def get_lines_with_moves(moves: List[int]) -> List[List[int]]:\n",
    "    winning_lines = [\n",
    "        [0, 1, 2], [3, 4, 5], [6, 7, 8],  # Rows\n",
    "        [0, 3, 6], [1, 4, 7], [2, 5, 8],  # Columns\n",
    "        [0, 4, 8], [2, 4, 6]  # Diagonals\n",
    "    ]\n",
    "    return [line for line in winning_lines if any(move - 1 in line for move in moves)]\n",
    "\n",
    "def has_threat_pattern(board: Board, lines: List[List[int]]) -> bool:\n",
    "    for line in lines:\n",
    "        marks = [board.state[i] for i in line]\n",
    "        if marks.count('X') == 2 or marks.count('O') == 2:\n",
    "            return True\n",
    "    return False\n",
    "\n",
    "def filter_non_threat_boards(boards: List[Board]) -> List[Board]:\n",
    "    non_threat_boards = []\n",
    "    removed_boards = []\n",
    "    for board in boards:\n",
    "        highest_scoring_moves = get_highest_scoring_moves(board)\n",
    "        lines_with_moves = get_lines_with_moves(highest_scoring_moves)\n",
    "        if not has_threat_pattern(board, lines_with_moves):\n",
    "            non_threat_boards.append(board)\n",
    "        else:\n",
    "            removed_boards.append(board)\n",
    "    return non_threat_boards, removed_boards\n",
    "\n",
    "# Filter out boards with threat patterns\n",
    "filtered_boards, removed_boards = filter_non_threat_boards(filtered_boards)\n",
    "print(f\"Number of filtered boards after removing threat patterns: {len(filtered_boards)}\")\n",
    "print(f\"Number of removed boards with threat patterns: {len(removed_boards)}\")\n",
    "\n",
    "print(\"\\nRemoved boards:\")\n",
    "for board in removed_boards[:5]:\n",
    "    print(f\"Board: {Board.hash_board(board.state)}\")\n",
    "    print(f\"Choice Complexity: {board.category.choice_complexity}\")\n",
    "    print(f\"Depth Complexity: {board.category.depth_complexity}\")\n",
    "    move_score_pairs = [(score.move, score.value) for score in board.scores if score.move is not None]\n",
    "    display_tictactoe(board.state, size=200, moves_scores=move_score_pairs)\n",
    "    print(\"---\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of boards after removing those with center as highest scoring move: 42\n",
      "Number of removed boards with center as highest scoring move: 26\n",
      "\n",
      "Removed boards with center as highest scoring move:\n",
      "Board: 1OXX567XO\n",
      "Choice Complexity: (2, 4)\n",
      "Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 1234567X9\n",
      "Choice Complexity: (4, 8)\n",
      "Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 12345OX89\n",
      "Choice Complexity: (4, 7)\n",
      "Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 12O45XX89\n",
      "Choice Complexity: (3, 6)\n",
      "Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "Board: 12345O7X9\n",
      "Choice Complexity: (5, 7)\n",
      "Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n"
     ]
    }
   ],
   "source": [
    "# Filter out boards where one of the highest scoring moves is the center move\n",
    "center_move_boards = []\n",
    "non_center_move_boards = []\n",
    "\n",
    "for board in filtered_boards:\n",
    "    highest_scoring_moves = get_highest_scoring_moves(board)\n",
    "    if 5 in highest_scoring_moves:  # 5 represents the center move (1-indexed)\n",
    "        center_move_boards.append(board)\n",
    "    else:\n",
    "        non_center_move_boards.append(board)\n",
    "\n",
    "filtered_boards = non_center_move_boards\n",
    "\n",
    "print(f\"Number of boards after removing those with center as highest scoring move: {len(filtered_boards)}\")\n",
    "print(f\"Number of removed boards with center as highest scoring move: {len(center_move_boards)}\")\n",
    "\n",
    "print(\"\\nRemoved boards with center as highest scoring move:\")\n",
    "for board in center_move_boards[:5]:\n",
    "    print(f\"Board: {Board.hash_board(board.state)}\")\n",
    "    print(f\"Choice Complexity: {board.category.choice_complexity}\")\n",
    "    print(f\"Depth Complexity: {board.category.depth_complexity}\")\n",
    "    move_score_pairs = [(score.move, score.value) for score in board.scores if score.move is not None]\n",
    "    display_tictactoe(board.state, size=200, moves_scores=move_score_pairs)\n",
    "    print(\"---\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of selected boards: 50\n",
      "\n",
      "First 5 selected boards:\n",
      "\n",
      "1. Board: 12345XO89\n",
      "   Choice Complexity: (6, 7) (ratio: 0.86)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "2. Board: 12345XOX9\n",
      "   Choice Complexity: (5, 6) (ratio: 0.83)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "3. Board: 12OX5678X\n",
      "   Choice Complexity: (5, 6) (ratio: 0.83)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "4. Board: 123OOX7X9\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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FUlpaygcyhkeZ3kCgZs2aJa+//vqgjxy+ePGi1NfXS3Nz822PHK6qqpJ169aNq0cOL1myRPbu3Rt4M/Fra2sTl8slLpfrtkcOe71e2bNnjzzyyCPjZh7GW1m+/o+QEhMTg4KCgsCD5PPz85GUlITo6Gj09fXh0qVLgQfJV1ZW4syZM2q9+a8f07oXiM1mw6JFiwJzkZ2dHbgtQm9vL5xOZ2AuKioq0N7ertKX9jyMFyEZuFDGFe06zsPo8J4mRIoYOCJFDByRIgaOSBEDR6SIgSNSxMARKWLgiBQxcESKGDgiRQwckSIGjkjRsE9eDrenrBhl+vTpAIDz58+b3Im5OA83G+5J3NzCESni5TkjxMtSruM8jA63cESKGDgiRQwckSIGjkgRA0ekiIEjUsTAESli4IgUMXBEihg4IkUMHJEiBo5IEQNHpIiBI1LEwBEpYuCIFDFwJklJSUF5eTkcDofamA6HA+Xl5UhJSVEbk27GwJlk2bJlWL16NQ4fPqwSOofDgcOHD2P16tVYtmyZ4ePR0Ex/7nE4VTCfbb1+/XoREWlqahKHw2FYzw6HQ5qamkREZP369SE3DxOsTG8grCrYK5rRoTMibEbMwwQq0xsIqzJiRTMqdEaFzah5mAgVhRCVkpKCn/zkJ8P62XPnzuF3v/udsQ0ZqKysDADw9ttv4/DhwygqKsLJkyfHtEz/32x2ux0bNmwIjDEeRMVGovC5PNxXfC9sWSmwRFjQeeEKTn98FsfeqUH/VZ/ZLQ4pZAPn8/ngcrmGfN1isYyrm5EGM3TjOWzxtjg8+dvvIn1uKuSaoM3ZgQHvAKbMsWHxKwvhWH0v/rj2PVxt6zW71SGZvpkdTWVnZ8v27dtl+/btMnnyZLVxjf4oNdaPl0Z+jNSch6GqZGex/Oz0Rln38VqxZaUEvp9gi5cnf79GfnZ6ozz5+zXqfQ23wvawQGFhIQCgvr4eHR0dJncTPGVlZdiwYQPsdvuIDxmM5y0bAKTOsSFryUwAwP9uPoz2s+7Aa1fbe/Hhv/4V3p5+zHxwGmYunmZSl3cWloGLi4sLrIg1NTUmdxN8owndeA8bANyzaCoA4EpzNy5WNd/2ek/rVVyoaAQAzP3uHNXehissA5efn4+oqCh4PB7U1dWZ3Y4hRhK6iRA2AIibFAsAuNLSM+TPXGnuBgBkFtpVehqpsAyc/+NkbW0t+vv7Te7GOMMJ3UQJGwB4ujwAgKQM65A/k2RPBABMnjkJlkiLSl8jEXaBS09PR2ZmJoDx+XHyVncK3UQKGwA0fdEK4HqoMgszbnvdmpaAexZe/9gZERWB2MQY1f6GI+wC59+6Xb58eVwcDhiOwUI30cIGAM3HL6HxsxYAwKr/WIo0x5TAa4kZVnx3x3LE3BCyqPjQO+oVeh3dQUREBObPnw9gYmzdbnTjcbojR44AANLS0iZM2Pw+/Olf8dS734Ntdgr++f0n0HnxCga8A5g8cxJgAb7YdwLzn5gLAPB2e03u9nZhtYXLycmB1WrFtWvX8Pnnn5vdjrqysjJs27YNaWlpSEtLw7Zt2yZU2ADA7erC77+3D/8oq0H7OTcS0xNgTU3AuU/O449Pv4eG/7sAAPD29MPbHXp/34fVFs7/cfLMmTPo7u42uRt9DocDGzduDHy9ceNG7N27d8yngYWb3o4+HPnFURz5xdHbXpu9ZAYAoKX2knZbwxI2Wzir1Yp7770XwMT7OAncvoNktAfHx7s5j84GAJz+yzmTOxlc2GzhvvWtbyEyMhI9PT04deqU2e2outMOkmCe8BzuctfMQZpjCnrdffjyQGjORdhs4QoKCgAAX3zxBa5du2ZuM4ruFLaxnAYWrqYtsGPWQ9NhifjmGFtEdAQKnpmHla8vAQD87bVP4OkKvR0mQJhs4aZNm4b09HQAwGeffWZuM4qGs+vfiEt7Qpk9Px1Lt3wH3qv96Gq8Al/fACbPmoTYxBgMeAfwl21HcKL8tNltDiksAuffujU2NqKlpcXcZpSM5DjbRArd+X9cxPE/nUBmoR1JGVZEREeiu6UHJ8pPo+q3X9x0QnOoMv2ShXAqjctSRnuJjdY9UrTmYZyW6Q2EVRm9oo31ejat0DFwoy7TGwirMnJFC9bFoxqhY+BGXaY3EFZl1IoW7Cu1jQ4dAzfqMr2BsCojVjSjbotgZOgYuFGX6Q2EVQV7RTP6HiRGhY6BG3WZ3kBYVTBXNK0b/hgROgZu1GV6A2FVwVrRtMLmr2CHjoEbXYXNqV3jTWpqKqxWq9r1bP7TwKxWK1JTUw0fjwZnwfXk0TA5nU4AQHZ29piXlZ6ejtbW1jEvZyTS0tJw6dLYL10J5jxMJNzCmUg7bACCEjYaPQaOSBEDR6SIgSNSxMARKWLgiBQxcESKGDgiRQwckSIGjkgRA0ekiIEjUsTAESli4IgUMXBEihg4IkUMHJEiXvFNpIhbOCJFDByRIgaOSBEDR6SIgSNSxMARKWLgiBQxcESKGDgiRf8PJ7wugob/BFgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "5. Board: 1O3O5X7X9\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "6. Board: 12O45XXO9\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "7. Board: 12O456XOX\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "8. Board: 123OOXX89\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "9. Board: 12O45XX8O\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "10. Board: 123O5XXO9\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "11. Board: 1OXX5O7X9\n",
      "   Choice Complexity: (3, 4) (ratio: 0.75)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "12. Board: 12O45XXXO\n",
      "   Choice Complexity: (3, 4) (ratio: 0.75)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "13. Board: 12O45XXOX\n",
      "   Choice Complexity: (3, 4) (ratio: 0.75)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "14. Board: 1O3OXX7X9\n",
      "   Choice Complexity: (3, 4) (ratio: 0.75)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "15. Board: 12XO5X7XO\n",
      "   Choice Complexity: (3, 4) (ratio: 0.75)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "16. Board: 12O456X89\n",
      "   Choice Complexity: (5, 7) (ratio: 0.71)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "17. Board: 123O5X7X9\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "18. Board: 123456OXX\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "19. Board: 12OX567X9\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "20. Board: 123O5XX89\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "21. Board: 12O4X6X89\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "22. Board: 1OXXOO7X9\n",
      "   Choice Complexity: (2, 3) (ratio: 0.67)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "23. Board: 12XX5OOXO\n",
      "   Choice Complexity: (2, 3) (ratio: 0.67)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "24. Board: 1OXX5O7XO\n",
      "   Choice Complexity: (2, 3) (ratio: 0.67)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "25. Board: 12XX5OOOX\n",
      "   Choice Complexity: (2, 3) (ratio: 0.67)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "26. Board: 12OO5X78X\n",
      "   Choice Complexity: (3, 5) (ratio: 0.60)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "27. Board: 12XX5O7O9\n",
      "   Choice Complexity: (3, 5) (ratio: 0.60)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "28. Board: 123OXX7O9\n",
      "   Choice Complexity: (3, 5) (ratio: 0.60)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "29. Board: 12O4X6XO9\n",
      "   Choice Complexity: (3, 5) (ratio: 0.60)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "30. Board: 123456O8X\n",
      "   Choice Complexity: (4, 7) (ratio: 0.57)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "31. Board: 1234X6789\n",
      "   Choice Complexity: (4, 8) (ratio: 0.50)\n",
      "   Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "32. Board: 12XXOO7X9\n",
      "   Choice Complexity: (2, 4) (ratio: 0.50)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "33. Board: 1234OX7X9\n",
      "   Choice Complexity: (3, 6) (ratio: 0.50)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "34. Board: 1O3XOX7X9\n",
      "   Choice Complexity: (2, 4) (ratio: 0.50)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "35. Board: 123OXX789\n",
      "   Choice Complexity: (2, 6) (ratio: 0.33)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "36. Board: 1234OXX89\n",
      "   Choice Complexity: (2, 6) (ratio: 0.33)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "37. Board: 12X4O6X89\n",
      "   Choice Complexity: (2, 6) (ratio: 0.33)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "38. Board: 12O4OXX89\n",
      "   Choice Complexity: (1, 5) (ratio: 0.20)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "39. Board: 123OXX78O\n",
      "   Choice Complexity: (1, 5) (ratio: 0.20)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "40. Board: 12OX5O78X\n",
      "   Choice Complexity: (1, 5) (ratio: 0.20)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "41. Board: 1234O67X9\n",
      "   Choice Complexity: (1, 7) (ratio: 0.14)\n",
      "   Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "42. Board: 1234X67O9\n",
      "   Choice Complexity: (1, 7) (ratio: 0.14)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "43. Board: 12345678X\n",
      "   Choice Complexity: (7, 8) (ratio: 0.88)\n",
      "   Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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+KPxXXdWHWKSEheGv09KwPioKPgbD2O39Q0N4u6gIvy4qQvfgoNg8KtaD2Wwee/WyoKBgwquX3hAb4IVbuNGtm6OtTTw2lZZYrQgJCICPwYCG7m5ccjrR3t8Pf19fbI+PR8aSJapH9LiptnTeEtso5S+VTnfx9fHRzuzapVXk5Wm5KSlKZlBxWOCZ++7TKvLytKNPPKGlhIVNuO+xhATtUm6uVv7cc9pDy5bN6fUwuow/ZHDhwgXdvfR/q8WrtnCbo6MRbLFgyO3GvitXVI8jwmax4Pn0dADAT48du+mFkX3l5XizsBA+BgP+bu1aFSOKG93SXbx4EatWrUJ/fz+2bNmi+y0b4GW7lKO7k6eqquDs7VU8jYx77XZYTCb0DA7edAxu1MmRj/2NXbQIC0wmyfGU2bVr11hs/v7+2L17t+j76WbKa4ILtliwceRzpefDsbdRdxqQ2Wj00CT6Mf45W3p6+owPjqvgNcH9WXw8TEYjWvv6cKyyUvU4Yr4ZOai9wGSa8jjcxqVLAQCtfX1o6+8Xm02FG18gKSkpuaszUqR5TXCju5MHrlzBkNuteBo5l5ubUTpy4PuXDz6IlLCwCfc/lpCAvNRUAMD+Of68dqpXI+/2NDBJun23wHirQkMRZ7MBAPbOo93JUS8cPYrfbduGpQsX4oPsbDR0d6O5rw9LrFYE+fsDAArr6/HG2bOKJ/Wc273076m39sw2r9jCjW7dipuaUN7aqngaeRWtrXj0vffw3+fP45LTiXvMZiQGB0PD9fcCvnziBJ48cAB9c/Ssm+keZ/OWLZ3yYxPetPAd37LrYSZvsZG8RsoMFuUDeNXC4OTWw928n03H0SkfwKsWBiezHmbjzaM6jU75AF61MDjPr4fZfKe2DqNT/+B508LgPLsePHFZBJ1Fp/7B86aFwXluPXjyGiQ6ik79g+dNC4PzzHqQuOCPTqJT/+B508LgZn89SF5dS3V0XnHgm+a26OhosTePjj84Hh4eDovF4tHfdyOvu8SCaqousaA3s70e7HY7nE7nrPxb02E2m2GxWNAxxZXQPMUrzqWkuU8yNuD6lk7FeZbcpSQSxOCIBDE4IkEMjkgQgyMSxOCIBDE4IkEMjkgQgyMSxOCIBDE4IkEMjkgQgyMSxOCIBDE4IkEMjkgQ3/FNJIhbOCJBDI5IEIMjEsTgiAQxOCJBDI5IEIMjEsTgiAQxOCJB/w9CcfW9qq653gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "44. Board: 12XO567X9\n",
      "   Choice Complexity: (5, 6) (ratio: 0.83)\n",
      "   Depth Complexity: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "45. Board: 123456XOX\n",
      "   Choice Complexity: (5, 6) (ratio: 0.83)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "46. Board: 12345XXO9\n",
      "   Choice Complexity: (5, 6) (ratio: 0.83)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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JGhsbxWKxaBuH4dY7P/6xVNjt8qfVq2VyRETf7ZFBQfKHZcukwm6XPyxbpryvIZT2BgQYfuhUhg0Y+Yq2bt06ERHJzs7WNta/+tWvRERk7dq12sZhOJUYGSkVdrtU2O2SarPdcv9Yi0W+WrdOKux2SffgTqgRlvYG+mqooVMdNmDkK1pxcbE4nU6JiYnRNs42m02cTqcUFxdrG4fh1NMzZkiF3S5/WbNmwMf0bgG3ZGRoG9/blaGm55SXlyMjIwM1NTXYtm0bsrKyBnys2WzGrl27sHTpUuzbtw8rVqyA0+lU2O3QJSYmYtasWdizZw9qa2u19VFTU4M9e/Zg1qxZmDJlirY+hio8IAAAUHvjXNL+1LS1AQBm2WxKehoqQwUOGFzovDFsAJCWlgYAKCgo0NsIgEOHDgH4ridv0NLZCQCICQ4e8DG2Gyd7TwgPh6/JpKSvoTBc4IDbh85bwwYAqampAICioiLNnXzXQ29P3uBUXR2A66GaFRNzy/1WiwVpsbEAAD8fH4SYzUr7GwxDBg7oP3TeHDYAmD17NlwuF77++mvdreCrr76Cy+XyqsCV1Nfjqxsfxf958WIkR0X13RcTHIzfZWbeFLIgP+NN9zT8fLikpCQUFBTAZrPh1KlTmDlzptawjWQeWGlpKaKiohB7411Yt5qaGtTX1+Pee+8d8v/VNR/unrAwvP/TnyI2JAQ9IrjU2gqny4UJ4eEwAfhjeTmemDYNADDr3XfR1tWltL87MewWrld5eTmWLFmCjo4OzJw5E6dOnfK6LVuvgIAAdN74HmIEHR0dfZdr8BYXWlrw0507kXvyJM43NWGsxYJoiwVHqqrw1O7dOHrxIgDgaleX4cIGeMElFsxmMzZv3ozAwMC+0D377LPIzc3V3dqQdXd3IygoSHcbffz9/XHt2jXdbQxZY0cHth47hq3Hjt1yX8Y99wAAvqmvV93WoBh6C/fD72xz584d1CEDo2ptbcWYMWNgMsDeMx8fH0RERNx11z95ZNIkAMDn589r7qR/hg1cfztISkpKBn2czohKSkpgsVgwdepU3a1g6tSpsFgsKCkp0d2K2yxLTERyVBSaOjrwx7Iy3e30y5CBu93eyKEcHDcaI+2KN9IhiqFItdnwYHw8fL73KcHfxwdPz5iBzRkZAIDfHDmCFoN+xzfcd7jB7PrvDV1BQQG2bdsGAF7xna535Z43bx4++OADrb3MnTsXgPcF7t6xY5G9YAGudXXh29ZWdLhcmBgejhCzGU6XC28cPoz8igrdbd6W9vPLemuo50aqulzD92sk5xCazWapq6uTmpoaJed93q6P2tpaqaurG3YfumYLTIuKki0ZGXLgqaek+LnnpOT55+XPTz8tv3nooZtmDxi4tDfQtxIM50Rk1aEb6Yq2ZcsWERF56qmntI316tWrRURk8+bN2sZhFJf2BkZ81r/K0I10RZs4caK4XC45cuSItvE+evSouFwumTBhgrZxGMWltwF3TbFRFTp3rGi7du0SEZE1t5lm4ql65plnRERk165d2sdhlJa+hbt7PpuK0LljRRs/frw0NzfLlStXJDY2Vtl4x8XFSWNjozQ1Ncn48eO1j8MoLT0L9tTkUU+Hzl0r2tq1a0VEZP/+/eLr6+vx8fb19ZVPP/1URESee+45w4zDKCz1C/X0TG1Phs6dK9revXtFROS999677W8HjLRMJpO89957IiKyd+9ew43DKCu1C1R1WQRPhc6dK1pwcLAUFhaKiEheXp5bLnH+w/Lz85O8vDwRETl69OiILhzkqXEYZaVuYaqvQeKJ0Ll7RQsLC5PDhw+LyPUf8XDn5c5TUlL6ftTj8OHDbv0lHQZu2KVuYeHh4XL8+HFlF/wBvgvdpk2b3PJ8nljRgoKCJDc3V0Su/6BHdna2BAYGDvv5AgMDJTs7u++HPHJzcyXIzddqZOCGXWoXGB4ervwsC6vV6rbn8uSKtmTJkr6frGpoaJCtW7fK5MmTB/3/ExISZOvWrdLQ0CAiIpWVlZKZmemRXhm44ZXhZ3wbjadnOoeFheGVV15BVlZW38zwkpISFBUVoaioCKdPn+6bw2axWDB9+nSkpqYiNTW1b+Z2dXU1cnNz8eabb6KlpcUjffIXUIdPe+q9qVS9s/v5+cnKlSvlwIED0tzcLHfS3NwsBw4ckJUrV3pk54uucbjbilu4IdLxzm4ymTBlyhSkpqYiISGhb9Z4e3s7HA4HioqKcPbsWYioeym5hRsew03PoVuJCCoqKlBh8GkndGeGnIBKdLdi4IgUYuCIFGLgiBRi4IgUYuCIFGLgiBRi4IgUYuCIFGLgiBRi4IgUYuCIFGLgiBTi9BwihbiFI1KIgSNSiIEjUoiBI1KIgSNSiIEjUoiBI1KIgSNSiIEjUuj/AbZ5ELgjnqkfAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "47. Board: 12345XOXO\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "48. Board: 12345OOXX\n",
      "   Choice Complexity: (4, 5) (ratio: 0.80)\n",
      "   Depth Complexity: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "49. Board: 12345O7X9\n",
      "   Choice Complexity: (5, 7) (ratio: 0.71)\n",
      "   Depth Complexity: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n",
      "\n",
      "50. Board: 12345XX8O\n",
      "   Choice Complexity: (4, 6) (ratio: 0.67)\n",
      "   Depth Complexity: 4\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---\n"
     ]
    }
   ],
   "source": [
    "sorted_boards = sorted(\n",
    "    filtered_boards,\n",
    "    key=lambda board: (\n",
    "        board.category.choice_complexity[0] / board.category.choice_complexity[1],\n",
    "        board.category.depth_complexity\n",
    "    ),\n",
    "    reverse=True\n",
    ")\n",
    "\n",
    "sorted_center_move_boards = sorted(\n",
    "    center_move_boards,\n",
    "    key=lambda board: (\n",
    "        board.category.choice_complexity[0] / board.category.choice_complexity[1],\n",
    "        board.category.depth_complexity\n",
    "    ),\n",
    "    reverse=True\n",
    ")\n",
    "\n",
    "\n",
    "# Define the number of boards to select\n",
    "N = 50  # You can adjust this value as needed\n",
    "\n",
    "# Create a new list of selected boards\n",
    "selected_boards = []\n",
    "\n",
    "# Add boards from sorted_boards\n",
    "for board in sorted_boards:\n",
    "    selected_boards.append(board)\n",
    "    if len(selected_boards) >= N:\n",
    "        break\n",
    "\n",
    "# If we haven't reached N, add boards from sorted_center_move_boards\n",
    "if len(selected_boards) < N:\n",
    "    for board in sorted_center_move_boards:\n",
    "        if board not in selected_boards:\n",
    "            selected_boards.append(board)\n",
    "            if len(selected_boards) >= N:\n",
    "                break\n",
    "\n",
    "print(f\"Total number of selected boards: {len(selected_boards)}\")\n",
    "\n",
    "# Print information about the selected boards and display them\n",
    "print(\"\\nFirst 5 selected boards:\")\n",
    "for i, board in enumerate(selected_boards, 1):\n",
    "    choice_ratio = board.category.choice_complexity[0] / board.category.choice_complexity[1]\n",
    "    print(f\"\\n{i}. Board: {Board.hash_board(board.state)}\")\n",
    "    print(f\"   Choice Complexity: {board.category.choice_complexity} (ratio: {choice_ratio:.2f})\")\n",
    "    print(f\"   Depth Complexity: {board.category.depth_complexity}\")\n",
    "    \n",
    "    # Display the board using display_tictactoe\n",
    "    move_score_pairs = [(score.move, score.value) for score in board.scores if score.move is not None]\n",
    "    display_tictactoe(board.state, size=200, moves_scores=move_score_pairs)\n",
    "    print(\"---\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the top N variable\n",
    "top_n = len(selected_boards)  # Use all selected boards\n",
    "\n",
    "def count_depth_complexity(boards):\n",
    "    # Count the occurrences of each depth complexity\n",
    "    depth_complexity_counts = {}\n",
    "    for board in boards:\n",
    "        depth = board.category.depth_complexity\n",
    "        depth_complexity_counts[depth] = depth_complexity_counts.get(depth, 0) + 1\n",
    "    \n",
    "    return depth_complexity_counts\n",
    "\n",
    "# Count depth complexity for selected boards\n",
    "depth_counts = count_depth_complexity(selected_boards)\n",
    "\n",
    "# Visualize the distribution\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "bars = plt.bar(list(depth_counts.keys()), list(depth_counts.values()))\n",
    "plt.xlabel('Depth Complexity')\n",
    "plt.ylabel('Number of Boards')\n",
    "plt.title(f'Distribution of Depth Complexity in {top_n} Selected Boards')\n",
    "plt.xticks(list(depth_counts.keys()))  # Set x-axis ticks to integer values\n",
    "\n",
    "# Add the numbers on top of the bars\n",
    "for bar in bars:\n",
    "    height = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2., height,\n",
    "             f'{int(height)}',\n",
    "             ha='center', va='bottom')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created a new dataset with 50 boards and saved it to 'dataset_top50.json'\n"
     ]
    }
   ],
   "source": [
    "# Create a dictionary with hash values as keys and Board objects as values\n",
    "selected_boards_dict = {Board.hash_board(board.state): board for board in selected_boards}\n",
    "\n",
    "# Create a new Dataset object with the selected boards\n",
    "dataset_top50 = Dataset(boards=selected_boards_dict)\n",
    "\n",
    "# Save the new dataset to a JSON file\n",
    "dataset_top50.to_json(\"dataset_top50.json\")\n",
    "\n",
    "print(f\"Created a new dataset with {len(selected_boards)} boards and saved it to 'dataset_top50.json'\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}