Random ta te ti

random_tateti.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Funciones para manipular el tablero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "from random import choice\n",
    "\n",
    "def random_move(board, who):\n",
    "    i, j = choice(get_available(board))\n",
    "    board[i][j] = who\n",
    "    \n",
    "def _get_diags(board):\n",
    "    return [board[0][0], board[1][1], board[2][2]], [board[0][2], board[1][1], board[2][0]]\n",
    "\n",
    "def player_won(board, who):\n",
    "    target_row = [who] * 3\n",
    "    return (\n",
    "        any(row==target_row for row in board) or # filas \n",
    "        any(list(row)==target_row for row in zip(*board)) or # columnas\n",
    "        any(row==target_row for row in _get_diags(board)) # diagonales\n",
    "    )\n",
    "\n",
    "empty = '-'\n",
    "def empty_board():\n",
    "    return [[empty] * 3 for _ in range(3)]\n",
    "\n",
    "def get_available(board):\n",
    "    return [(i, j) for i in range(3) for j in range(3) if board[i][j] is empty]\n",
    "\n",
    "def is_finished(board):\n",
    "    return not any(e is empty for row in board for e in row)\n",
    "\n",
    "def print_board(board):\n",
    "    [print(row) for row in board]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Funcion principal para simular una jugada random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import cycle\n",
    "\n",
    "def play():\n",
    "    board = empty_board()\n",
    "    player_iter = cycle('XO')\n",
    "    winner = None\n",
    "    while not is_finished(board):\n",
    "        who = next(player_iter)\n",
    "        random_move(board, who)\n",
    "        if player_won(board, who): \n",
    "            winner = who\n",
    "            break\n",
    "    return board, winner\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X\n",
      "['X', 'X', 'O']\n",
      "['X', 'O', 'O']\n",
      "['X', 'O', 'X']\n"
     ]
    }
   ],
   "source": [
    "board, winner = play()\n",
    "\n",
    "print(winner)\n",
    "print_board(board)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experimentos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "def experiment(n=1000):\n",
    "    ends = {'X': 0, 'O': 0, None: 0}\n",
    "    for _ in range(n):\n",
    "        _, winner = play()\n",
    "        ends[winner] += 1\n",
    "    return {k: v/n for k, v in ends.items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "experiments = pd.DataFrame([experiment() for _ in range(100)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11bb0b0a0>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "experiments.boxplot()"
   ]
  }
 ],
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   "language": "python",
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