simus/Simulations_du_jeu_de_151.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulons le jeu de *151* avec Python !\n",
    "\n",
    "## But :\n",
    "- Simuler numériquement le jeu de 151, qui est une variante à 3 dés du jeu appelé [5000](https://fr.wikipedia.org/wiki/5000),\n",
    "- Afin de trouver une stratégie *optimale*.\n",
    "\n",
    "## Comment ?\n",
    "- On va simuler des millions de parties (cf. [méthodes de Monte-Carlo](https://fr.wikipedia.org/wiki/Méthodes_de_Monte-Carlo)),\n",
    "- Afin de comparer différentes stratégies (aléatoires, s'arrêter au premier coup, s'arrêter après 3 coups, etc),\n",
    "- On les compare en fonction de leur gain *moyen*,\n",
    "- La meilleur stratégie sera celle qui apporte un gain moyen le plus élevé.\n",
    "\n",
    "## Résultats ?\n",
    "→ Lien vers les résultats obtenus."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "## Plans\n",
    "1. fonctions pour simuler un tirage (3 dés),\n",
    "2. puis simuler une une partie (affrontant deux stratégies, face à un total), plein de parties (total aléatoire),\n",
    "3. implémenter différentes stratégies,\n",
    "4. les comparer, faire des graphiques, et tirer des conclusions statistiquement valides (avec moyennes *et* écart-types)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "## 1. Simuler un tirage et une partie"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1. Simuler un tirage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dépendances :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.random as rn\n",
    "rn.seed(0)  # Pour obtenir les mêmes résultats\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(context=\"notebook\", style=\"darkgrid\", palette=\"hls\", font=\"sans-serif\", font_scale=1.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Première fonction : pour tirer trois dés, à 6 faces, indépendants."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def tirage(nb=1):\n",
    "    \"\"\" Renvoie un numpy array de taille (3,) si nb == 1, sinon (nb, 3).\"\"\"\n",
    "    if nb == 1:\n",
    "        return rn.randint(1, 7, 3)\n",
    "    else:\n",
    "        return rn.randint(1, 7, (nb, 3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testons là :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 6, 1])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tirage()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[4, 4, 4],\n",
       "       [2, 4, 6],\n",
       "       [3, 5, 1],\n",
       "       [1, 5, 3],\n",
       "       [2, 1, 2],\n",
       "       [6, 2, 6],\n",
       "       [1, 2, 5],\n",
       "       [4, 1, 4],\n",
       "       [6, 1, 3],\n",
       "       [4, 1, 2]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tirage(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2. Points d'un tirage\n",
    "Le jeu de *151* associe les points suivants, multiples de 50, aux tirages de 3 dés :\n",
    "\n",
    "- 200 pour un brelan de 2, 300 pour un brelan de 3, .., 600 pour un brelan de 6, 700 pour un brelan de 1,\n",
    "- 100 pour chaque 1, si ce n'est pas un brelan,\n",
    "- 50 pour chaque 5, si ce n'est pas un brelan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "COMPTE_SUITE = False  # Savoir si on implémente aussi la variante avec les suites\n",
    "\n",
    "def _points(valeurs, compte_suite=COMPTE_SUITE):\n",
    "    if valeurs[0] == valeurs[1] == valeurs[2]:  # Un brelan !\n",
    "        if valeurs[0] == 1:\n",
    "            return 700\n",
    "        else:\n",
    "            return 100 * valeurs[0]\n",
    "    else:            # Pas de brelan\n",
    "        # Code pour compter les suites :\n",
    "        bonus_suite = compte_suite and set(np.diff(np.sort(valeurs))) == {1}\n",
    "        return 100 * (np.sum(valeurs == 1) + bonus_suite) + 50 * np.sum(valeurs == 5)\n",
    "\n",
    "\n",
    "def points(valeurs, compte_suite=COMPTE_SUITE):\n",
    "    \"\"\" Calcule les points du tirage correspondant à valeurs.\n",
    "    \n",
    "    - si valeurs est de taille (3,), renvoie un seul entier,\n",
    "    - si valeurs est de taille (nb, 3), renvoie un tableau de points.\n",
    "    \"\"\"\n",
    "    if len(np.shape(valeurs)) > 1:\n",
    "        return np.array([_points(valeurs[i,:], compte_suite) for i in range(np.shape(valeurs)[0])])\n",
    "    else:\n",
    "        return _points(valeurs, compte_suite)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.1. Un seul tirage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testons ces fonctions :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "La valeur [4 6 4] donne     0 points.\n"
     ]
    }
   ],
   "source": [
    "valeurs = tirage()\n",
    "print(\"La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- La valeur [4 1 2] donne   100 points.\n",
      "- La valeur [2 2 1] donne   100 points.\n",
      "- La valeur [3 5 4] donne    50 points.\n",
      "- La valeur [4 3 5] donne    50 points.\n",
      "- La valeur [3 1 1] donne   200 points.\n",
      "- La valeur [5 6 6] donne    50 points.\n",
      "- La valeur [1 5 2] donne   150 points.\n",
      "- La valeur [5 2 3] donne    50 points.\n",
      "- La valeur [3 1 2] donne   100 points.\n",
      "- La valeur [2 2 2] donne   200 points.\n",
      "- La valeur [4 4 3] donne     0 points.\n",
      "- La valeur [4 1 4] donne   100 points.\n",
      "- La valeur [6 5 2] donne    50 points.\n",
      "- La valeur [3 5 4] donne    50 points.\n",
      "- La valeur [5 5 5] donne   500 points.\n",
      "- La valeur [4 5 5] donne   100 points.\n",
      "- La valeur [5 1 5] donne   200 points.\n",
      "- La valeur [4 3 6] donne     0 points.\n",
      "- La valeur [6 6 1] donne   100 points.\n",
      "- La valeur [2 6 2] donne     0 points.\n"
     ]
    }
   ],
   "source": [
    "for _ in range(20):\n",
    "    valeurs = tirage()\n",
    "    print(\"- La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testons quelques valeurs particulières :"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Les brelans :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- La valeur [1 1 1] donne   700 points.\n",
      "- La valeur [2 2 2] donne   200 points.\n",
      "- La valeur [3 3 3] donne   300 points.\n",
      "- La valeur [4 4 4] donne   400 points.\n",
      "- La valeur [5 5 5] donne   500 points.\n",
      "- La valeur [6 6 6] donne   600 points.\n"
     ]
    }
   ],
   "source": [
    "for valeur in range(1, 7):\n",
    "    valeurs = valeur * np.ones(3, dtype=int)\n",
    "    print(\"- La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Les 1 :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- La valeur [2 3 6] donne     0 points.\n",
      "- La valeur [1 3 6] donne   100 points.\n",
      "- La valeur [1 1 6] donne   200 points.\n"
     ]
    }
   ],
   "source": [
    "for valeurs in [np.array([2, 3, 6]), np.array([1, 3, 6]), np.array([1, 1, 6])]:\n",
    "    print(\"- La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Les 5 :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- La valeur [2 3 6] donne     0 points.\n",
      "- La valeur [5 3 6] donne    50 points.\n",
      "- La valeur [5 5 6] donne   100 points.\n"
     ]
    }
   ],
   "source": [
    "for valeurs in [np.array([2, 3, 6]), np.array([5, 3, 6]), np.array([5, 5, 6])]:\n",
    "    print(\"- La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "→ C'est bon, *tout* marche !\n",
    "\n",
    "*Note* : certaines variants du 151 accordent une valeur supplémentaire aux *suites* (non ordonnées) : [1, 2, 3] vaut 200, [2, 3, 4] vaut 100, et [3, 4, 5] et [4, 5, 6] vaut 150.\n",
    "Ce n'est pas difficile à intégrer dans notre fonction `points`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Testons quand même les suites :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- La valeur [1 2 3] donne   100 points.\n",
      "- La valeur [2 3 4] donne     0 points.\n",
      "- La valeur [3 4 5] donne    50 points.\n",
      "- La valeur [4 5 6] donne    50 points.\n"
     ]
    }
   ],
   "source": [
    "for valeurs in [np.array([1, 2, 3]), np.array([2, 3, 4]), np.array([3, 4, 5]), np.array([4, 5, 6])]:\n",
    "    print(\"- La valeur {} donne {:>5} points.\".format(valeurs, points(valeurs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.2. Plusieurs tirages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testons ces fonctions :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[4 1 6]\n",
      " [1 2 3]\n",
      " [5 3 1]\n",
      " [6 4 3]\n",
      " [3 6 1]\n",
      " [6 2 1]\n",
      " [3 3 4]\n",
      " [3 4 3]\n",
      " [2 3 4]\n",
      " [4 4 3]]\n",
      "[100 100 150   0 100 100   0   0   0   0]\n"
     ]
    }
   ],
   "source": [
    "valeurs = tirage(10)\n",
    "print(valeurs)\n",
    "print(points(valeurs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "#### 1.2.3. Moyenne d'un tirage, et quelques figures"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut faire quelques tests statistiques dès maintenant :"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Points moyens d'un tirage :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Pour     100 tirages, les tirages valent en moyenne 95.0 points.\n",
      "- Pour     100 tirages, les tirages valent en moyenne 100.0 points si on compte aussi les suites.\n",
      "- Pour    1000 tirages, les tirages valent en moyenne 81.2 points.\n",
      "- Pour    1000 tirages, les tirages valent en moyenne 98.0 points si on compte aussi les suites.\n",
      "- Pour   10000 tirages, les tirages valent en moyenne 85.05 points.\n",
      "- Pour   10000 tirages, les tirages valent en moyenne 97.3 points si on compte aussi les suites.\n",
      "- Pour  100000 tirages, les tirages valent en moyenne 85.817 points.\n",
      "- Pour  100000 tirages, les tirages valent en moyenne 96.6435 points si on compte aussi les suites.\n",
      "- Pour 1000000 tirages, les tirages valent en moyenne 85.32135 points.\n",
      "- Pour 1000000 tirages, les tirages valent en moyenne 96.55695 points si on compte aussi les suites.\n"
     ]
    }
   ],
   "source": [
    "def moyenneTirage(nb=1000):\n",
    "    return np.mean(points(tirage(nb), False))\n",
    "\n",
    "def moyenneTirage_avecSuite(nb=1000):\n",
    "    return np.mean(points(tirage(nb), True))\n",
    "\n",
    "for p in range(2, 7):\n",
    "    nb = 10 ** p\n",
    "    print(\"- Pour {:>7} tirages, les tirages valent en moyenne {:>4} points.\".format(nb, moyenneTirage(nb)))\n",
    "    print(\"- Pour {:>7} tirages, les tirages valent en moyenne {:>4} points si on compte aussi les suites.\".format(nb, moyenneTirage_avecSuite(nb)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ça semble converger vers 85 : en moyenne, un tirage vaut entre 50 et 100 points, plutôt du côté des 100.\n",
    "Et si on compte les suites, la valeur moyenne d'un tirage vaut plutôt 96 points (ça augmente comme prévu, mais ça augmente peu)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Moyenne et écart type :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Pour     100 tirages, les tirages valent en moyenne  79.00 +-  83.12 points.\n",
      "- Pour    1000 tirages, les tirages valent en moyenne  88.15 +-  92.42 points.\n",
      "- Pour   10000 tirages, les tirages valent en moyenne  86.97 +-  95.47 points.\n",
      "- Pour  100000 tirages, les tirages valent en moyenne  85.26 +-  92.53 points.\n",
      "- Pour 1000000 tirages, les tirages valent en moyenne  85.31 +-  92.73 points.\n"
     ]
    }
   ],
   "source": [
    "def moyenneStdTirage(nb=1000):\n",
    "    pts = points(tirage(nb))\n",
    "    return np.mean(pts), np.std(pts)\n",
    "\n",
    "for p in range(2, 7):\n",
    "    nb = 10 ** p\n",
    "    m, s = moyenneStdTirage(nb)\n",
    "    print(\"- Pour {:>7} tirages, les tirages valent en moyenne {:6.2f} +- {:>6.2f} points.\".format(nb, m, s))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Quelques courbes :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotPoints(nb=2000):\n",
    "    pts = np.sort(points(tirage(nb)))\n",
    "    m = np.mean(pts)\n",
    "    plt.figure()\n",
    "    plt.plot(pts, 'ro')\n",
    "    plt.title(\"Valeurs de {} tirages. Moyenne = {:.2f}\".format(nb, m))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BwbCxsQEANG3aFA8fPkRoaCgGDhyI+vXrv5ADJiIiIiJlM+oK8LZt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\n7ouZmaFevXo4f/48ACApKQmFhYVQq9U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8Xq+WLl0qj8ejnTt3aunSpSovL9fChQu79qgB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\nsBUCMAAAAGyFAAwAAABb+f/5rmTkdMzLMgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c04438b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPoints()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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j48OBAwdYuHAh586do1WrVnZTperUqQPcWD3DUf+npqaycuVKh7dOvtfuZtvu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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c04332438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPoints(10**5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WpKQkXL58GaampmjdujUAKE3jpO5BGRkZGYiJiYGurq7S7fTOnTtDFEW1dYqK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\nAAAACwjQAAAAgAUEaAAAAMCC/w9zXzWFdPFvOQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c3968fc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPoints(10**6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- On peut calculer la probabilité d'avoir un tirage valant 0 points :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def probaPoints(nb=1000, pt=0, compte_suite=COMPTE_SUITE):\n",
    "    pts = points(tirage(nb), compte_suite)\n",
    "    return np.sum(pts == pt) / float(nb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Pour     100 tirages, il y a une probabilité  16.00% d'avoir 0 point.\n",
      "- Pour     100 tirages, il y a une probabilité  28.00% d'avoir 0 point si on compte les suites.\n",
      "- Pour    1000 tirages, il y a une probabilité  27.00% d'avoir 0 point.\n",
      "- Pour    1000 tirages, il y a une probabilité  26.70% d'avoir 0 point si on compte les suites.\n",
      "- Pour   10000 tirages, il y a une probabilité  27.73% d'avoir 0 point.\n",
      "- Pour   10000 tirages, il y a une probabilité  24.11% d'avoir 0 point si on compte les suites.\n",
      "- Pour  100000 tirages, il y a une probabilité  27.90% d'avoir 0 point.\n",
      "- Pour  100000 tirages, il y a une probabilité  24.97% d'avoir 0 point si on compte les suites.\n",
      "- Pour 1000000 tirages, il y a une probabilité  27.81% d'avoir 0 point.\n",
      "- Pour 1000000 tirages, il y a une probabilité  25.00% d'avoir 0 point si on compte les suites.\n"
     ]
    }
   ],
   "source": [
    "for p in range(2, 7):\n",
    "    nb = 10 ** p\n",
    "    prob = probaPoints(nb, compte_suite=False)\n",
    "    print(\"- Pour {:>7} tirages, il y a une probabilité {:7.2%} d'avoir 0 point.\".format(nb, prob))\n",
    "    prob = probaPoints(nb, compte_suite=True)\n",
    "    print(\"- Pour {:>7} tirages, il y a une probabilité {:7.2%} d'avoir 0 point si on compte les suites.\".format(nb, prob))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Donc un tirage apporte 85 points en moyenne, mais il y a environ 28% de chance qu'un tirage rate.\n",
    "\n",
    "Si on compte les suites, un tirage apporte 97 points en moyenne, mais il y a environ 25% de chance qu'un tirage rate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- On peut faire le même genre de calcul pour les différentes valeurs de points possibles :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# valeursPossibles = list(set(points(tirage(10000))))\n",
    "valeursPossibles = [0, 50, 100, 150, 200, 250, 300, 400, 500, 600, 700]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "- Pour   10000 tirages :\n",
      "  - Il y a une probabilité  28.33% d'avoir   0 point.\n",
      "  - Il y a une probabilité  25.58% d'avoir   0 point si on compte les suites.\n",
      "  - Il y a une probabilité  22.47% d'avoir  50 points.\n",
      "  - Il y a une probabilité  16.68% d'avoir  50 points si on compte les suites.\n",
      "  - Il y a une probabilité  27.77% d'avoir 100 points.\n",
      "  - Il y a une probabilité  27.98% d'avoir 100 points si on compte les suites.\n",
      "  - Il y a une probabilité  10.70% d'avoir 150 points.\n",
      "  - Il y a une probabilité  16.49% d'avoir 150 points si on compte les suites.\n",
      "  - Il y a une probabilité   7.28% d'avoir 200 points.\n",
      "  - Il y a une probabilité   9.82% d'avoir 200 points si on compte les suites.\n",
      "  - Il y a une probabilité   1.19% d'avoir 250 points.\n",
      "  - Il y a une probabilité   1.19% d'avoir 250 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.42% d'avoir 300 points.\n",
      "  - Il y a une probabilité   0.42% d'avoir 300 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.50% d'avoir 400 points.\n",
      "  - Il y a une probabilité   0.50% d'avoir 400 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.41% d'avoir 500 points.\n",
      "  - Il y a une probabilité   0.41% d'avoir 500 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.49% d'avoir 600 points.\n",
      "  - Il y a une probabilité   0.49% d'avoir 600 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.44% d'avoir 700 points.\n",
      "  - Il y a une probabilité   0.44% d'avoir 700 points si on compte les suites.\n",
      "\n",
      "- Pour  100000 tirages :\n",
      "  - Il y a une probabilité  27.73% d'avoir   0 point.\n",
      "  - Il y a une probabilité  24.98% d'avoir   0 point si on compte les suites.\n",
      "  - Il y a une probabilité  22.68% d'avoir  50 points.\n",
      "  - Il y a une probabilité  16.95% d'avoir  50 points si on compte les suites.\n",
      "  - Il y a une probabilité  27.60% d'avoir 100 points.\n",
      "  - Il y a une probabilité  27.56% d'avoir 100 points si on compte les suites.\n",
      "  - Il y a une probabilité  10.98% d'avoir 150 points.\n",
      "  - Il y a une probabilité  16.71% d'avoir 150 points si on compte les suites.\n",
      "  - Il y a une probabilité   7.39% d'avoir 200 points.\n",
      "  - Il y a une probabilité  10.18% d'avoir 200 points si on compte les suites.\n",
      "  - Il y a une probabilité   1.34% d'avoir 250 points.\n",
      "  - Il y a une probabilité   1.34% d'avoir 250 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.45% d'avoir 300 points.\n",
      "  - Il y a une probabilité   0.45% d'avoir 300 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.44% d'avoir 400 points.\n",
      "  - Il y a une probabilité   0.44% d'avoir 400 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.44% d'avoir 500 points.\n",
      "  - Il y a une probabilité   0.44% d'avoir 500 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.49% d'avoir 600 points.\n",
      "  - Il y a une probabilité   0.49% d'avoir 600 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.46% d'avoir 700 points.\n",
      "  - Il y a une probabilité   0.46% d'avoir 700 points si on compte les suites.\n",
      "\n",
      "- Pour 1000000 tirages :\n",
      "  - Il y a une probabilité  27.87% d'avoir   0 point.\n",
      "  - Il y a une probabilité  25.08% d'avoir   0 point si on compte les suites.\n",
      "  - Il y a une probabilité  22.25% d'avoir  50 points.\n",
      "  - Il y a une probabilité  16.66% d'avoir  50 points si on compte les suites.\n",
      "  - Il y a une probabilité  27.70% d'avoir 100 points.\n",
      "  - Il y a une probabilité  27.72% d'avoir 100 points si on compte les suites.\n",
      "  - Il y a une probabilité  11.13% d'avoir 150 points.\n",
      "  - Il y a une probabilité  16.72% d'avoir 150 points si on compte les suites.\n",
      "  - Il y a une probabilité   7.37% d'avoir 200 points.\n",
      "  - Il y a une probabilité  10.14% d'avoir 200 points si on compte les suites.\n",
      "  - Il y a une probabilité   1.37% d'avoir 250 points.\n",
      "  - Il y a une probabilité   1.37% d'avoir 250 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.46% d'avoir 300 points.\n",
      "  - Il y a une probabilité   0.46% d'avoir 300 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.47% d'avoir 400 points.\n",
      "  - Il y a une probabilité   0.47% d'avoir 400 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.46% d'avoir 500 points.\n",
      "  - Il y a une probabilité   0.46% d'avoir 500 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.46% d'avoir 600 points.\n",
      "  - Il y a une probabilité   0.46% d'avoir 600 points si on compte les suites.\n",
      "  - Il y a une probabilité   0.46% d'avoir 700 points.\n",
      "  - Il y a une probabilité   0.46% d'avoir 700 points si on compte les suites.\n"
     ]
    }
   ],
   "source": [
    "for p in range(4, 7):\n",
    "    nb = 10 ** p\n",
    "    tirages = tirage(nb)\n",
    "    pts   = points(tirages, False)\n",
    "    pts_s = points(tirages, True)\n",
    "    print(\"\\n- Pour {:>7} tirages :\".format(nb))\n",
    "    for pt in valeursPossibles:\n",
    "        prob = np.sum(pts   == pt) / float(nb)\n",
    "        print(\"  - Il y a une probabilité {:7.2%} d'avoir {:3} point{}.\".format(prob, pt, 's' if pt > 0 else ''))\n",
    "        prob = np.sum(pts_s == pt) / float(nb)\n",
    "        print(\"  - Il y a une probabilité {:7.2%} d'avoir {:3} point{} si on compte les suites.\".format(prob, pt, 's' if pt > 0 else ''))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On devrait faire des histogrammes, mais j'ai la flemme...\n",
    "\n",
    "Ces quelques expériences montrent qu'on a :\n",
    "- une chance d'environ 2.5% d'avoir plus de 300 points (par un brelan),\n",
    "- une chance d'environ 9%   d'avoir entre 200 et 300 points,\n",
    "- une chance d'environ 11%  d'avoir 150 points,\n",
    "- une chance d'environ 27%  d'avoir 100 points,\n",
    "- une chance d'environ 22%  d'avoir 50  points,\n",
    "- une chance d'environ 28%  d'avoir 0   point.\n",
    "\n",
    "Autant de chance d'avoir 100 points que 0 ? Et oui !\n",
    "\n",
    "La variante comptant les suites augmente la chance d'avoir 200 points (de 7.5% à 10%), d'avoir 150 points (de 11% à 16%), et diminue la chance d'avoir 0 point, mais ne change pas vraiment le reste du jeu."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "### 1.3. Simuler des parties\n",
    "#### 1.3.1. Simuler une partie\n",
    "On va d'abord écrire une fonction qui prend deux joeurs, un total, et simule la partie, puis donne l'indice (0 ou 1) du joueur qui gagne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "DEBUG = False  # Par défaut, on n'affiche rien"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def unJeu(joueur, compte, total, debug=DEBUG):\n",
    "    accu = 0\n",
    "    if debug: print(\"  - Le joueur {.__name__} commence à jouer, son compte est {} et le total est {} ...\".format(joueur, compte, total))\n",
    "    t = tirage()\n",
    "    nbLance = 1\n",
    "    if points(t) == 0:\n",
    "        if debug: print(\"    - Hoho, ce tirage {} vallait 0 points, le joueur doit arrêter.\".format(t))\n",
    "        return 0, nbLance\n",
    "    if debug: print(\"    - Le joueur a obtenu {} ...\".format(t))\n",
    "    while compte + accu <= total and joueur(compte, accu, t, total):\n",
    "        accu += points(t)\n",
    "        t = tirage()\n",
    "        nbLance += 1\n",
    "        if debug: print(\"    - Le joueur a décidé de rejouer, accumulant {} points, et a ré-obtenu {} ...\".format(accu, t))\n",
    "        if points(t) == 0:\n",
    "            if debug: print(\"    - Hoho, ce tirage {} vallait 0 points, le joueur doit arrêter.\".format(t))\n",
    "            break\n",
    "    accu += points(t)\n",
    "    if compte + accu > total:\n",
    "        if debug: print(\"  - Le joueur a dépassé le total : impossible de marquer ! compte = {} + accu = {} > total = {} !\".format(compte, accu, total))\n",
    "        return 0, nbLance\n",
    "    else:\n",
    "        if accu > 0:\n",
    "            if debug: print(\"  - Le joueur peut marquer les {} points accumulés en {} lancés !\".format(accu, nbLance))\n",
    "        return accu, nbLance\n",
    "\n",
    "\n",
    "def unePartie(joueurs, total=1000, debug=DEBUG, i0=0):\n",
    "    assert len(joueurs) == 2, \"Erreur, seulement 2 joueurs sont acceptés !\"\n",
    "    comptes  = [0, 0]\n",
    "    nbCoups  = [0, 0]\n",
    "    nbLances = [0, 0]\n",
    "    scores   = [[0], [0]]\n",
    "    if debug: print(\"- Le joueur #{} va commencer ...\".format(i0))\n",
    "    i = i0\n",
    "    while max(comptes) != total:  # Tant qu'aucun joueur n'a gagné\n",
    "        nbCoups[i] += 1\n",
    "        if debug: print(\"- C'est au joueur #{} ({.__name__}) de jouer, son compte est {} et le total est {} ...\".format(i, joueurs[i], comptes[i], total))\n",
    "        accu, nbLance = unJeu(joueurs[i], comptes[i], total, debug)\n",
    "        nbLances[i] += nbLance\n",
    "        if accu > 0:\n",
    "            comptes[i] += accu\n",
    "            scores[i].append(comptes[i])  # Historique\n",
    "        if comptes[i] == total:\n",
    "            if debug: print(\"- Le joueur #{} ({.__name__}) a gagné en {} coups et {} lancés de dés !\".format(i, joueurs[i], nbCoups[i], nbLances[i]))\n",
    "            if debug: print(\"- Le joueur #{} ({.__name__}) a perdu, avec un score de {}, après {} coups et {} lancés de dés !\".format(i^1, joueurs[i^1], comptes[i^1], nbCoups[i^1], nbLances[i^1]))\n",
    "            return i, scores\n",
    "        i ^= 1  # 0 → 1, 1 → 0 (ou exclusif)\n",
    "\n",
    "# Note : on pourrait implémenter une partie à plus de 2 joueurs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "#### 1.3.2. Des stratégies\n",
    "\n",
    "On doit définir des stratégies, sous la forme de fonctions `joueur(compte, accu, t, total)`, qui renvoie `True` si elle doit continuer à jouer, ou `False` si elle doit marquer.\n",
    "\n",
    "D'abord, deux stratégies un peu stupides :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def unCoup(compte, accu, t, total):\n",
    "    \"\"\" Stratégie qui marque toujours au premier coup, peu importe le 1er tirage obtenu.\"\"\"\n",
    "    return False  # Marque toujours !\n",
    "\n",
    "def jusquauBout(compte, accu, t, total):\n",
    "    \"\"\" Stratégie qui ne marque que si elle peut gagner exactement .\"\"\"\n",
    "    if compte + accu + points(t) >= total:\n",
    "        return False  # Marque si elle peut gagner\n",
    "    else:\n",
    "        return True   # Continue à jouer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une autre stratégie, qui marche seulement si elle peut marquer plus de X points (100, 150 etc).\n",
    "C'est la version plus \"gourmande\" de `unCoup`, qui marque si elle a plus de 50 points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def auMoinsX(X):\n",
    "    def joueur(compte, accu, t, total):\n",
    "        \"\"\" Stratégie qui marque si elle a eu plus de {} points.\"\"\".format(X)\n",
    "        if accu + points(t) >= X:\n",
    "            return False  # Marque si elle a obtenu plus de X points\n",
    "        elif compte + accu + points(t) == total:\n",
    "            return False  # Marque si elle peut gagner\n",
    "        elif total - compte < X:\n",
    "            # S'il reste peu de points, marque toujours\n",
    "            # (sinon la stratégie d'accumuler plus de X points ne marche plus)\n",
    "            return False\n",
    "        else:\n",
    "            return True   # Continue de jouer, essaie d'obtenir X points\n",
    "    joueur.__name__ = \"auMoins{}\".format(X)  # Triche sur le nom\n",
    "    return joueur\n",
    "\n",
    "auMoins50  = auMoinsX(50)    # == unCoup, en fait\n",
    "auMoins100 = auMoinsX(100)\n",
    "auMoins150 = auMoinsX(150)\n",
    "auMoins200 = auMoinsX(200)   # Commence à devenir très audacieux\n",
    "auMoins250 = auMoinsX(250)\n",
    "auMoins300 = auMoinsX(300)   # Compètement fou, très peu de chance de marquer ça ou plus!\n",
    "auMoins350 = auMoinsX(350)\n",
    "auMoins400 = auMoinsX(400)\n",
    "auMoins450 = auMoinsX(450)\n",
    "auMoins500 = auMoinsX(500)\n",
    "auMoins550 = auMoinsX(550)\n",
    "auMoins600 = auMoinsX(600)\n",
    "auMoins650 = auMoinsX(650)\n",
    "auMoins700 = auMoinsX(700)\n",
    "# On pourrait continuer ...\n",
    "auMoins800 = auMoinsX(800)\n",
    "auMoins850 = auMoinsX(850)\n",
    "auMoins900 = auMoinsX(900)\n",
    "auMoins950 = auMoinsX(950)\n",
    "auMoins1000 = auMoinsX(1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une autre stratégie \"stupide\" : décider aléatoirement, selon une loi de Bernoulli, si elle continue ou si elle s'arrête."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def bernoulli(p=0.5):\n",
    "    def joueur(compte, accu, t, total):\n",
    "        \"\"\" Marque les points accumulés avec probabilité p = {} (Bernoulli).\"\"\".format(p)\n",
    "        return rn.random() > p\n",
    "    joueur.__name__ = \"bernoulli_{:.3g}\".format(p)\n",
    "    return joueur"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "#### 1.3.3. Quelques exemples\n",
    "Essayons de faire jouer deux stratégies face à l'autre."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Le joueur #0 va commencer ...\n",
      "- C'est au joueur #0 (unCoup) de jouer, son compte est 0 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 0 et le total est 200 ...\n",
      "    - Le joueur a obtenu [4 5 2] ...\n",
      "  - Le joueur peut marquer les 50 points accumulés en 1 lancés !\n",
      "- C'est au joueur #1 (unCoup) de jouer, son compte est 0 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 0 et le total est 200 ...\n",
      "    - Hoho, ce tirage [3 4 2] vallait 0 points, le joueur doit arrêter.\n",
      "- C'est au joueur #0 (unCoup) de jouer, son compte est 50 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 50 et le total est 200 ...\n",
      "    - Le joueur a obtenu [3 2 5] ...\n",
      "  - Le joueur peut marquer les 50 points accumulés en 1 lancés !\n",
      "- C'est au joueur #1 (unCoup) de jouer, son compte est 0 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 0 et le total est 200 ...\n",
      "    - Le joueur a obtenu [3 4 1] ...\n",
      "  - Le joueur peut marquer les 100 points accumulés en 1 lancés !\n",
      "- C'est au joueur #0 (unCoup) de jouer, son compte est 100 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 100 et le total est 200 ...\n",
      "    - Hoho, ce tirage [4 3 4] vallait 0 points, le joueur doit arrêter.\n",
      "- C'est au joueur #1 (unCoup) de jouer, son compte est 100 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 100 et le total est 200 ...\n",
      "    - Le joueur a obtenu [1 1 1] ...\n",
      "  - Le joueur a dépassé le total : impossible de marquer ! compte = 100 + accu = 700 > total = 200 !\n",
      "- C'est au joueur #0 (unCoup) de jouer, son compte est 100 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 100 et le total est 200 ...\n",
      "    - Hoho, ce tirage [4 3 4] vallait 0 points, le joueur doit arrêter.\n",
      "- C'est au joueur #1 (unCoup) de jouer, son compte est 100 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 100 et le total est 200 ...\n",
      "    - Le joueur a obtenu [1 5 1] ...\n",
      "  - Le joueur a dépassé le total : impossible de marquer ! compte = 100 + accu = 250 > total = 200 !\n",
      "- C'est au joueur #0 (unCoup) de jouer, son compte est 100 et le total est 200 ...\n",
      "  - Le joueur unCoup commence à jouer, son compte est 100 et le total est 200 ...\n",
      "    - Le joueur a obtenu [6 1 6] ...\n",
      "  - Le joueur peut marquer les 100 points accumulés en 1 lancés !\n",
      "- Le joueur #0 (unCoup) a gagné en 5 coups et 5 lancés de dés !\n",
      "- Le joueur #1 (unCoup) a perdu, avec un score de 100, après 4 coups et 4 lancés de dés !\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(0, [[0, 200], [0, 100]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joueurs = [unCoup, unCoup]\n",
    "total = 200\n",
    "\n",
    "unePartie(joueurs, total, True)\n",
    "unePartie(joueurs, total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, [[0, 50], [0, 100, 200]])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joueurs = [unCoup, jusquauBout]\n",
    "total = 200\n",
    "unePartie(joueurs, total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, [[0, 100, 200, 350, 400], [0, 100, 200, 350, 450, 500]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joueurs = [unCoup, auMoins100]\n",
    "total = 500\n",
    "unePartie(joueurs, total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0,\n",
       " [[0, 100, 150, 250, 400, 600, 700, 750, 900, 1000],\n",
       "  [0, 200, 300, 550, 750, 900, 950]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joueurs = [unCoup, auMoins200]\n",
    "total = 1000\n",
    "unePartie(joueurs, total)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "\n",
    "#### 1.3.4. Générer plusieurs parties\n",
    "On peut maintenant lancer plusieurs centaines de simulations de parties, sans afficher le déroulement de chaque parties.\n",
    "La fonction `unePartie` renvoie un tuple, `(i, comptes)`, où :\n",
    "- `i` est l'indice (0 ou 1) du joueur ayant gagné la partie,\n",
    "- et `comptes` est une liste contenant les deux historiques des points des deux joueurs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Par exemple, pour un `total = 500`, la sortie `(1, [[0, 100, 150, 250, 450], [0, 50, 450, 500]])` signifie :\n",
    "- le joueur 1 a gagné, après avoir marqué 50 points, puis 400, et enfin 50,\n",
    "- le joueur 2 a perdu, après avoir marqué 100 points, puis 50, puis 100, puis 200, mais a perdu avec 450 points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def desParties(nb, joueurs, total=1000, i0=0):\n",
    "    indices, historiques = [], []\n",
    "    for _ in range(nb):\n",
    "        i, h = unePartie(joueurs, total=total, i0=i0, debug=False)\n",
    "        indices.append(i)\n",
    "        historiques.append(h)\n",
    "    return indices, historiques"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Par exemple, on peut opposer le joueur pas courageux (`unCoup`) au joueur très gourmand (`jusquauBout`) sur 100 parties avec un total de 250 points :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def freqGain(indiceMoyen, i):\n",
    "    # (1^i) + ((-1)**(i==0)) * indiceMoyen\n",
    "    if i == 0:\n",
    "        return 1 - indiceMoyen\n",
    "    else:\n",
    "        return indiceMoyen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def afficheResultatsDesParties(nb, joueurs, total, indices, historiques):\n",
    "    indiceMoyen = np.mean(indices)\n",
    "    pointsFinaux = [np.mean(list(historiques[k][i][-1] for k in range(nb))) for i in [0, 1]]\n",
    "\n",
    "    print(\"Dans {} parties simulées, contre le total {} :\".format(nb, total))\n",
    "    for i in [0, 1]:\n",
    "        print(\" - le joueur {} ({.__name__:<11}) a gagné {:>5.2%} du temps, et a eu un score final moyen de {:>5g} points ...\".format(i, joueurs[i], freqGain(indiceMoyen, i), pointsFinaux[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dans 10000 parties simulées, contre le total 1000 :\n",
      " - le joueur 0 (unCoup     ) a gagné 12.11% du temps, et a eu un score final moyen de 553.635 points ...\n",
      " - le joueur 1 (jusquauBout) a gagné 87.89% du temps, et a eu un score final moyen de 977.425 points ...\n"
     ]
    }
   ],
   "source": [
    "nb = 10000\n",
    "joueurs = [unCoup, jusquauBout]\n",
    "total = 1000\n",
    "indices, historiques = desParties(nb, joueurs, total)\n",
    "afficheResultatsDesParties(nb, joueurs, total, indices, historiques)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dans 10000 parties simulées, contre le total 500 :\n",
      " - le joueur 0 (unCoup     ) a gagné 24.83% du temps, et a eu un score final moyen de 315.35 points ...\n",
      " - le joueur 1 (jusquauBout) a gagné 75.17% du temps, et a eu un score final moyen de 453.565 points ...\n"
     ]
    }
   ],
   "source": [
    "nb = 10000\n",
    "joueurs = [unCoup, jusquauBout]\n",
    "total = 500\n",
    "indices, historiques = desParties(nb, joueurs, total)\n",
    "afficheResultatsDesParties(nb, joueurs, total, indices, historiques)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dans 10000 parties simulées, contre le total 5000 :\n",
      " - le joueur 0 (unCoup     ) a gagné 0.04% du temps, et a eu un score final moyen de 1751.06 points ...\n",
      " - le joueur 1 (jusquauBout) a gagné 99.96% du temps, et a eu un score final moyen de 4999.95 points ...\n"
     ]
    }
   ],
   "source": [
    "nb = 10000\n",
    "joueurs = [unCoup, jusquauBout]\n",
    "total = 5000\n",
    "indices, historiques = desParties(nb, joueurs, total)\n",
    "afficheResultatsDesParties(nb, joueurs, total, indices, historiques)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Affichons une première courbe qui montrera la supériorité d'une stratégie face à la plus peureuse, en fonction du total."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plotResultatsDesParties(nb, joueurs, totaux):\n",
    "    N = len(totaux)\n",
    "    indicesMoyens = []\n",
    "    for total in totaux:\n",
    "        indices, _ = desParties(nb, joueurs, total)\n",
    "        indicesMoyens.append(np.mean(indices))\n",
    "    plt.figure()\n",
    "    plt.plot(totaux, indicesMoyens, 'ro')\n",
    "    plt.xlabel(\"Objectif (points totaux à atteindre)\")\n",
    "    plt.ylabel(\"Taux de victoire de 1 face à 0\")\n",
    "    plt.title(\"Taux de victoire du joueur 1 ({.__name__}) face au joueur 0 ({.__name__}),\\n pour {} parties simulees pour chaque total.\".format(joueurs[1], joueurs[0], nb))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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p6emIi4uTOj4MDAzwxRdflLm98pRuz6qUmppaJffvxX/JzZgxA7t27UJYWBiKiopgYWHB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\nIiIio8HChIiIiIzG/wOKmWNKoNedPgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5d8f940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb = 1000\n",
    "joueurs = [unCoup, jusquauBout]\n",
    "totaux = [50, 100, 150, 200, 250, 300, 350, 400, 450, 500]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tQ0ZGBtfvh36bqrV+/Xro6+vj+++/r+6s1BhPnjzBnTt30Lhx4zozvUFl1a9f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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c11223cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb = 1000\n",
    "joueurs = [unCoup, jusquauBout]\n",
    "totalMax = 2000\n",
    "totaux = list(range(50, totalMax + 50, 50))\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "D'autres comparaisons, entre stratégies gourmandes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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c1tbW+O677/DkyZNytyssLMTmzZvRu3dvmJmZoWvXrpgxY4Zi0/eTzxoFN3XU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\nRGRUWNwQERGRUWFxQ0REREbl/wFGMZvob2Uk0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c112234e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb = 5000\n",
    "joueurs = [auMoins100, auMoins200]\n",
    "totalMax = 1000\n",
    "totaux = list(range(50, totalMax + 50, 50))\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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+ffsyGxsbNnDgQHbmzBn29OlTbtm5c+cYY4xt3bqVOTs7MxsbGzZkyBAWFRXF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c11223cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb = 1000\n",
    "joueurs = [auMoins100, jusquauBout]\n",
    "totalMax = 2000\n",
    "totaux = list(range(50, totalMax + 50, 100))\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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q1KmwsbGBlZWVzBmHi4uL8eOPP6J///7g8/lwdnaWOVnetWvXMGbMGFhYWMDB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\nACEiIiK9+185hrJCLrMUUQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c11223cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb = 1000\n",
    "totalMax = 2000\n",
    "totaux = list(range(50, totalMax + 50, 50))\n",
    "\n",
    "joueurs = [unCoup, bernoulli(0.5)]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1dP369cOMGTPedTHqpZMnT8LMzEzlhU9J7aAAhNSIzMxM+Pj44Oeff5ZZ7K58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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c1725a240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "joueurs = [unCoup, bernoulli(0.1)]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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3Cs1LZbJ48WKcOnUKbm5uSseSqi5q166NTZs24ccff4S9vT169uxZ0VkqF4wx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c1725a240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "joueurs = [unCoup, bernoulli(0.25)]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WlpbModIJIdUHBSyEEEII0XjUhoUQQgghGo8CFlJhGGPYvn07bG1tMW3aNJlp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c0c127e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "joueurs = [unCoup, bernoulli(0.75)]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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m9jkqKgomJibQ1NTkwlRVVWFubs5VL0vz3Xff4dGjR9yvv4yMDNy9e1dqrQvw4UbZqlUr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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5c0c3e1b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "joueurs = [unCoup, bernoulli(0.9)]\n",
    "plotResultatsDesParties(nb, joueurs, totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "----\n",
    "## Évaluation en *self-play*\n",
    "Plutôt que de faire jouer une stratégie face à une autre, et d'utiliser le *taux de victoire* comme une mesure de performance (ce que j'ai fait plus haut), on peut chercher à mesure un autre taux de victoire.\n",
    "\n",
    "On peut laisser une stratégie jouer tout seule, et mesurer plutôt le *nombre de coup requis pour gagner*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def unePartieSeul(joueur, total=1000, debug=DEBUG):\n",
    "    compte   = 0\n",
    "    nbCoups  = 0\n",
    "    nbLances = 0\n",
    "    score   = [0]\n",
    "    if debug: print(\"Simulation pour le joueur ({.__name__}), le total à atteindre est {} :\".format(joueur, total))\n",
    "    while compte < total:  # Tant que joueur n'a pas gagné\n",
    "        nbCoups += 1\n",
    "        if debug: print(\" - Coup #{}, son compte est {} / {} ...\".format(nbCoups, compte, total))\n",
    "        accu, nbLance = unJeu(joueur, compte, total, debug)\n",
    "        nbLances += nbLance\n",
    "        if accu > 0:\n",
    "            compte += accu\n",
    "            score.append(compte)  # Historique\n",
    "        if compte == total:\n",
    "            if debug: print(\"- Le joueur ({.__name__}) a gagné en {} coups et {} lancés de dés !\".format(joueur, nbCoups, nbLances))\n",
    "            return score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testons ça avec la stratégie naïve `unCoup` :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Partie gagnée en 12 coups par le joueur (unCoup), avec le score [0, 200, 300, 350, 500, 550, 650, 700, 800, 850, 950, 1000] ...\n"
     ]
    }
   ],
   "source": [
    "h = unePartieSeul(unCoup, 1000)\n",
    "print(\"Partie gagnée en {} coups par le joueur ({.__name__}), avec le score {} ...\".format(len(h), unCoup, h))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Comme précédemment, on peut générer plusieurs simulations pour la même tâche, et obtenir ainsi une liste d'historiques de jeu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def desPartiesSeul(nb, joueur, total=1000, debug=False):\n",
    "    historique = []\n",
    "    for _ in range(nb):\n",
    "        h = unePartieSeul(joueur, total=total, debug=debug)\n",
    "        historique.append(h)\n",
    "    return historique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 100, 150, 250, 300, 400, 500, 550, 650, 800, 850, 950, 1000],\n",
       " [0, 100, 200, 300, 350, 400, 550, 650, 750, 800, 900, 950, 1000],\n",
       " [0, 150, 400, 450, 650, 750, 850, 950, 1000],\n",
       " [0, 100, 150, 250, 450, 850, 900, 1000]]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "desPartiesSeul(4, unCoup)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ce qui nous intéresse est uniquement le nombre de coups qu'une certaine stratégie va devoir jouer avant de gagner :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 6, 12, 11]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[len(l)-1 for l in desPartiesSeul(4, unCoup)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Avec un joli affichage et un calcul du nombre moyen de coups :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def afficheResultatsDesPartiesSeul(nb, joueur, total, historique):\n",
    "    nbCoupMoyens = np.mean([len(h) - 1 for h in historique])\n",
    "    print(\"Dans {} parties simulées, contre le total {}, le joueur ({.__name__}) a gagné en moyenne en {} coups ...\".format(nb, total, joueur, nbCoupMoyens))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dans 100 parties simulées, contre le total 1000, le joueur (unCoup) a gagné en moyenne en 9.56 coups ...\n"
     ]
    }
   ],
   "source": [
    "historique = desPartiesSeul(100, unCoup, 1000)\n",
    "afficheResultatsDesPartiesSeul(100, unCoup, 1000, historique)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comme précédemment, on peut afficher un graphique montrant l'évolution de ce nombre moyen de coups, disons pour $1000$ parties simulées, en fonction du total à atteindre.\n",
    "La courbe obtenue devrait être croissante, mais difficile de prévoir davantage son comportement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plotResultatsDesPartiesSeul(nb, joueur, totaux):\n",
    "    N = len(totaux)\n",
    "    nbCoupMoyens = []\n",
    "    for total in totaux:\n",
    "        historique = desPartiesSeul(nb, joueur, total)\n",
    "        nbCoupMoyens.append(np.mean([len(h) - 1 for h in historique]))\n",
    "    plt.figure()\n",
    "    plt.plot(totaux, nbCoupMoyens, 'ro')\n",
    "    plt.xlabel(\"Objectif (points totaux à atteindre)\")\n",
    "    plt.ylabel(\"Nombre moyen de coups joués avant de gagner\")\n",
    "    plt.title(\"Nombre moyen de coups requis par {.__name__}\\n pour {} parties simulées pour chaque total.\".format(joueur, nb))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "On va utiliser les mêmes paramètres de simulation que précédemment : $1000$ simulations pour chaque total, et des totaux allant de $50$ à $2000$ par pas de $50$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nb = 1000\n",
    "totalMax = 2000\n",
    "totaux = list(range(50, totalMax + 50, 50))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La courbe pour `unCoup` permet d'établir le comportement de la stratégie naïve, on pourra ensuite comparer les autres stratégies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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H+fPn4ePjg5SUFDg6Ola6PHUZr7UDVqxYAWtr6y/eTEj46d69O7egTbt27XD/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\nEkAIIYTUUJQEEEIIITXU/wHfxS7RqxdFAQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd9777f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, unCoup, totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Tient, pour `unCoup`, la courbe est linéaire dans le total. C'est assez logique, vue la stratégie utilisée !\n",
    "> On marque à chaque coup, donc le nombre de coups moyens est juste le total divisé par le score moyen.\n",
    "> On se rappelle que le score moyen en un tirage est d'environ $96$ points (avec suite), et en effet $2000 / 91 \\simeq 21$, ce qu'on lit sur la courbe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.833333333333332"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scoreMoyen = 96\n",
    "total = 2000\n",
    "total / scoreMoyen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Pour `jusquauBout` :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9PfHbb7+hWbNmcHNz436o3Lt3D0uWLEG/fv1w6dIlnDlzBnp6epg1axZSUlIA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\n2mIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5d66400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, jusquauBout, totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> On constate que cette stratégie `jusquauBout` gagne bien plus rapidement que la stratégie `unCoup` !"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Pour `auMoins200`, par exemple :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4o6KicOLECZHllJaWiv1AUVJSEnktjKk2hYWFaNOmjVg5YYzC9QPAqlWr4O3tLVKuvLxc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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5d56e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, auMoins200, totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Pour `bernoulli(0.5)`, par exemple :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WKS4uxsaNG/HLL7/g2LFjUFVVxS+//AIfHx94eHjgxIkT0NHRwaJFi2SOD8/X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\nJfH/AN+H4prs8W5mAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5d41470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, bernoulli(0.5), totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Pour `bernoulli(0.2)`, par exemple :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vx7x583Dw4EGoqalh3rx58Pf3h7e3Nw4fPgx9fX3Mnz9fYv/kfL1+/RqjRo1C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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5e1efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, bernoulli(0.2), totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Pour `bernoulli(0.8)`, par exemple :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2bt0KAFi/fj2OHDkidfsrV67Ejh07MGrUKERERGDJkiWIiIgQS4irVq1CbGws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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5bd5e18390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotResultatsDesPartiesSeul(nb, bernoulli(0.8), totaux)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "Ces comparaisons de différentes stratégies de Bernoulli permettent de conclure, comme on le présentait, que  la meilleure stratégie (parmi les quelques testées) est la stratégie `jusquauBout` !\n",
    "\n",
    "Toutes les courbes ci dessus montrent un comportement (presque) linéaire du nombre moyen de coups requis pour gagner en fonction du total.\n",
    "\n",
    "Ainsi, pour comparer différentes stratégies, on peut juste comparer leur nombre de coups moyen pour un certain total, disons $T = 2000$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def comparerStrategies(joueurs, nb=1000, total=2000):\n",
    "    resultats = []\n",
    "    for joueur in joueurs:\n",
    "        historique = desPartiesSeul(nb, joueur, total)\n",
    "        nbCoupMoyen = np.mean([len(h) - 1 for h in historique])\n",
    "        resultats.append((nbCoupMoyen, joueur.__name__))\n",
    "    # Trier les résultats permet de voir les meilleures stratégies en premier !\n",
    "    return sorted(resultats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(6.2400000000000002, 'jusquauBout'), (17.887, 'unCoup')]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joueurs = [unCoup, jusquauBout]\n",
    "comparerStrategies(joueurs, nb=nb, total=totalMax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On va comparer toutes les stratégies définies plus haut :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "joueurs = [unCoup, jusquauBout]\n",
    "joueurs += [auMoins50, auMoins100, auMoins150, auMoins200, auMoins250, auMoins300, auMoins350, auMoins400, auMoins450, auMoins500, auMoins550, auMoins600, auMoins650, auMoins700, auMoins800, auMoins850, auMoins900, auMoins950, auMoins1000]\n",
    "for p in range(0, 20 + 1):\n",
    "    joueurs.append(bernoulli(p/20.))\n",
    "\n",
    "# print([j.__name__ for j in joueurs])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pour le total 2000 et 1000 simulations ...\n",
      "- La stratégie classée # 0 / 42 est jusquauBout, avec un nombre moyen de coups = 6.3 ...\n",
      "- La stratégie classée # 1 / 42 est bernoulli_0, avec un nombre moyen de coups = 7.18 ...\n",
      "- La stratégie classée # 2 / 42 est bernoulli_0.05, avec un nombre moyen de coups = 7.65 ...\n",
      "- La stratégie classée # 3 / 42 est bernoulli_0.1, avec un nombre moyen de coups = 8.16 ...\n",
      "- La stratégie classée # 4 / 42 est auMoins550 , avec un nombre moyen de coups = 8.38 ...\n",
      "- La stratégie classée # 5 / 42 est auMoins500 , avec un nombre moyen de coups = 8.39 ...\n",
      "- La stratégie classée # 6 / 42 est auMoins450 , avec un nombre moyen de coups = 8.43 ...\n",
      "- La stratégie classée # 7 / 42 est auMoins400 , avec un nombre moyen de coups = 8.54 ...\n",
      "- La stratégie classée # 8 / 42 est auMoins650 , avec un nombre moyen de coups = 8.54 ...\n",
      "- La stratégie classée # 9 / 42 est bernoulli_0.15, avec un nombre moyen de coups = 8.55 ...\n",
      "- La stratégie classée #10 / 42 est auMoins600 , avec un nombre moyen de coups = 8.56 ...\n",
      "- La stratégie classée #11 / 42 est auMoins350 , avec un nombre moyen de coups = 8.72 ...\n",
      "- La stratégie classée #12 / 42 est auMoins700 , avec un nombre moyen de coups = 8.74 ...\n",
      "- La stratégie classée #13 / 42 est auMoins300 , avec un nombre moyen de coups = 8.98 ...\n",
      "- La stratégie classée #14 / 42 est bernoulli_0.2, avec un nombre moyen de coups = 9.12 ...\n",
      "- La stratégie classée #15 / 42 est auMoins800 , avec un nombre moyen de coups = 9.22 ...\n",
      "- La stratégie classée #16 / 42 est auMoins850 , avec un nombre moyen de coups = 9.37 ...\n",
      "- La stratégie classée #17 / 42 est auMoins900 , avec un nombre moyen de coups = 9.44 ...\n",
      "- La stratégie classée #18 / 42 est auMoins250 , avec un nombre moyen de coups = 9.6 ...\n",
      "- La stratégie classée #19 / 42 est bernoulli_0.25, avec un nombre moyen de coups = 9.7 ...\n",
      "- La stratégie classée #20 / 42 est auMoins950 , avec un nombre moyen de coups = 9.9 ...\n",
      "- La stratégie classée #21 / 42 est auMoins1000, avec un nombre moyen de coups = 10.1 ...\n",
      "- La stratégie classée #22 / 42 est bernoulli_0.3, avec un nombre moyen de coups = 10.3 ...\n",
      "- La stratégie classée #23 / 42 est auMoins200 , avec un nombre moyen de coups = 10.4 ...\n",
      "- La stratégie classée #24 / 42 est bernoulli_0.35, avec un nombre moyen de coups = 10.8 ...\n",
      "- La stratégie classée #25 / 42 est bernoulli_0.4, avec un nombre moyen de coups = 11.1 ...\n",
      "- La stratégie classée #26 / 42 est bernoulli_0.45, avec un nombre moyen de coups = 11.7 ...\n",
      "- La stratégie classée #27 / 42 est auMoins150 , avec un nombre moyen de coups = 11.8 ...\n",
      "- La stratégie classée #28 / 42 est bernoulli_0.5, avec un nombre moyen de coups = 12.2 ...\n",
      "- La stratégie classée #29 / 42 est bernoulli_0.55, avec un nombre moyen de coups = 12.8 ...\n",
      "- La stratégie classée #30 / 42 est bernoulli_0.6, avec un nombre moyen de coups = 13.3 ...\n",
      "- La stratégie classée #31 / 42 est bernoulli_0.65, avec un nombre moyen de coups = 14 ...\n",
      "- La stratégie classée #32 / 42 est bernoulli_0.7, avec un nombre moyen de coups = 14.5 ...\n",
      "- La stratégie classée #33 / 42 est auMoins100 , avec un nombre moyen de coups = 14.6 ...\n",
      "- La stratégie classée #34 / 42 est bernoulli_0.75, avec un nombre moyen de coups = 14.9 ...\n",
      "- La stratégie classée #35 / 42 est bernoulli_0.8, avec un nombre moyen de coups = 15.7 ...\n",
      "- La stratégie classée #36 / 42 est bernoulli_0.85, avec un nombre moyen de coups = 16.1 ...\n",
      "- La stratégie classée #37 / 42 est bernoulli_0.9, avec un nombre moyen de coups = 16.7 ...\n",
      "- La stratégie classée #38 / 42 est bernoulli_0.95, avec un nombre moyen de coups = 17.3 ...\n",
      "- La stratégie classée #39 / 42 est auMoins50  , avec un nombre moyen de coups = 17.7 ...\n",
      "- La stratégie classée #40 / 42 est unCoup     , avec un nombre moyen de coups = 17.7 ...\n",
      "- La stratégie classée #41 / 42 est bernoulli_1, avec un nombre moyen de coups = 17.8 ...\n"
     ]
    }
   ],
   "source": [
    "nb = 1000\n",
    "totalMax = 2000\n",
    "resultats = comparerStrategies(joueurs, nb=nb, total=totalMax)\n",
    "print(\"Pour le total {} et {} simulations ...\".format(totalMax, nb))\n",
    "for (i, (n, j)) in enumerate(resultats):\n",
    "    print(\"- La stratégie classée #{:2} / {} est {:<14}, avec un nombre moyen de coups = {:.3g} ...\".format(i, len(joueurs), j, n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pour le total 3000 et 2000 simulations ...\n",
      "- La stratégie classée # 0 / 42 est jusquauBout   , avec un nombre moyen de coups = 8.66 ...\n",
      "- La stratégie classée # 1 / 42 est bernoulli_0   , avec un nombre moyen de coups = 9.48 ...\n",
      "- La stratégie classée # 2 / 42 est bernoulli_0.05, avec un nombre moyen de coups = 10.3 ...\n",
      "- La stratégie classée # 3 / 42 est bernoulli_0.1 , avec un nombre moyen de coups = 11.2 ...\n",
      "- La stratégie classée # 4 / 42 est auMoins550    , avec un nombre moyen de coups = 11.4 ...\n",
      "- La stratégie classée # 5 / 42 est auMoins600    , avec un nombre moyen de coups = 11.4 ...\n",
      "- La stratégie classée # 6 / 42 est auMoins500    , avec un nombre moyen de coups = 11.4 ...\n",
      "- La stratégie classée # 7 / 42 est auMoins650    , avec un nombre moyen de coups = 11.5 ...\n",
      "- La stratégie classée # 8 / 42 est auMoins700    , avec un nombre moyen de coups = 11.6 ...\n",
      "- La stratégie classée # 9 / 42 est auMoins450    , avec un nombre moyen de coups = 11.6 ...\n",
      "- La stratégie classée #10 / 42 est auMoins800    , avec un nombre moyen de coups = 11.7 ...\n",
      "- La stratégie classée #11 / 42 est bernoulli_0.15, avec un nombre moyen de coups = 11.8 ...\n",
      "- La stratégie classée #12 / 42 est auMoins400    , avec un nombre moyen de coups = 11.9 ...\n",
      "- La stratégie classée #13 / 42 est auMoins850    , avec un nombre moyen de coups = 12 ...\n",
      "- La stratégie classée #14 / 42 est auMoins950    , avec un nombre moyen de coups = 12.1 ...\n",
      "- La stratégie classée #15 / 42 est auMoins900    , avec un nombre moyen de coups = 12.2 ...\n",
      "- La stratégie classée #16 / 42 est auMoins350    , avec un nombre moyen de coups = 12.3 ...\n",
      "- La stratégie classée #17 / 42 est auMoins1000   , avec un nombre moyen de coups = 12.5 ...\n",
      "- La stratégie classée #18 / 42 est bernoulli_0.2 , avec un nombre moyen de coups = 12.7 ...\n",
      "- La stratégie classée #19 / 42 est auMoins300    , avec un nombre moyen de coups = 12.8 ...\n",
      "- La stratégie classée #20 / 42 est bernoulli_0.25, avec un nombre moyen de coups = 13.4 ...\n",
      "- La stratégie classée #21 / 42 est auMoins250    , avec un nombre moyen de coups = 13.8 ...\n",
      "- La stratégie classée #22 / 42 est bernoulli_0.3 , avec un nombre moyen de coups = 14.4 ...\n",
      "- La stratégie classée #23 / 42 est auMoins200    , avec un nombre moyen de coups = 15.1 ...\n",
      "- La stratégie classée #24 / 42 est bernoulli_0.35, avec un nombre moyen de coups = 15.1 ...\n",
      "- La stratégie classée #25 / 42 est bernoulli_0.4 , avec un nombre moyen de coups = 15.9 ...\n",
      "- La stratégie classée #26 / 42 est bernoulli_0.45, avec un nombre moyen de coups = 16.8 ...\n",
      "- La stratégie classée #27 / 42 est auMoins150    , avec un nombre moyen de coups = 17.3 ...\n",
      "- La stratégie classée #28 / 42 est bernoulli_0.5 , avec un nombre moyen de coups = 17.7 ...\n",
      "- La stratégie classée #29 / 42 est bernoulli_0.55, avec un nombre moyen de coups = 18.6 ...\n",
      "- La stratégie classée #30 / 42 est bernoulli_0.6 , avec un nombre moyen de coups = 19.4 ...\n",
      "- La stratégie classée #31 / 42 est bernoulli_0.65, avec un nombre moyen de coups = 20.3 ...\n",
      "- La stratégie classée #32 / 42 est bernoulli_0.7 , avec un nombre moyen de coups = 21.3 ...\n",
      "- La stratégie classée #33 / 42 est auMoins100    , avec un nombre moyen de coups = 21.6 ...\n",
      "- La stratégie classée #34 / 42 est bernoulli_0.75, avec un nombre moyen de coups = 22 ...\n",
      "- La stratégie classée #35 / 42 est bernoulli_0.8 , avec un nombre moyen de coups = 22.9 ...\n",
      "- La stratégie classée #36 / 42 est bernoulli_0.85, avec un nombre moyen de coups = 23.8 ...\n",
      "- La stratégie classée #37 / 42 est bernoulli_0.9 , avec un nombre moyen de coups = 24.5 ...\n",
      "- La stratégie classée #38 / 42 est bernoulli_0.95, avec un nombre moyen de coups = 25.3 ...\n",
      "- La stratégie classée #39 / 42 est auMoins50     , avec un nombre moyen de coups = 26.2 ...\n",
      "- La stratégie classée #40 / 42 est unCoup        , avec un nombre moyen de coups = 26.4 ...\n",
      "- La stratégie classée #41 / 42 est bernoulli_1   , avec un nombre moyen de coups = 26.4 ...\n"
     ]
    }
   ],
   "source": [
    "nb = 2000\n",
    "totalMax = 3000\n",
    "resultats = comparerStrategies(joueurs, nb=nb, total=totalMax)\n",
    "print(\"Pour le total {} et {} simulations ...\".format(totalMax, nb))\n",
    "for (i, (n, j)) in enumerate(resultats):\n",
    "    print(\"- La stratégie classée #{:2} / {} est {:<14}, avec un nombre moyen de coups = {:.3g} ...\".format(i, len(joueurs), j, n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pour le total 5000 et 1000 simulations ...\n",
      "- La stratégie classée # 0 / 42 est jusquauBout   , avec un nombre moyen de coups = 13.2 ...\n",
      "- La stratégie classée # 1 / 42 est bernoulli_0   , avec un nombre moyen de coups = 14.2 ...\n",
      "- La stratégie classée # 2 / 42 est bernoulli_0.05, avec un nombre moyen de coups = 15.6 ...\n",
      "- La stratégie classée # 3 / 42 est auMoins650    , avec un nombre moyen de coups = 16.9 ...\n",
      "- La stratégie classée # 4 / 42 est bernoulli_0.1 , avec un nombre moyen de coups = 17 ...\n",
      "- La stratégie classée # 5 / 42 est auMoins850    , avec un nombre moyen de coups = 17.1 ...\n",
      "- La stratégie classée # 6 / 42 est auMoins800    , avec un nombre moyen de coups = 17.1 ...\n",
      "- La stratégie classée # 7 / 42 est auMoins700    , avec un nombre moyen de coups = 17.1 ...\n",
      "- La stratégie classée # 8 / 42 est auMoins600    , avec un nombre moyen de coups = 17.2 ...\n",
      "- La stratégie classée # 9 / 42 est auMoins1000   , avec un nombre moyen de coups = 17.3 ...\n",
      "- La stratégie classée #10 / 42 est auMoins900    , avec un nombre moyen de coups = 17.3 ...\n",
      "- La stratégie classée #11 / 42 est auMoins950    , avec un nombre moyen de coups = 17.4 ...\n",
      "- La stratégie classée #12 / 42 est auMoins500    , avec un nombre moyen de coups = 17.5 ...\n",
      "- La stratégie classée #13 / 42 est auMoins550    , avec un nombre moyen de coups = 17.6 ...\n",
      "- La stratégie classée #14 / 42 est auMoins450    , avec un nombre moyen de coups = 18 ...\n",
      "- La stratégie classée #15 / 42 est bernoulli_0.15, avec un nombre moyen de coups = 18.2 ...\n",
      "- La stratégie classée #16 / 42 est auMoins400    , avec un nombre moyen de coups = 18.5 ...\n",
      "- La stratégie classée #17 / 42 est auMoins350    , avec un nombre moyen de coups = 19.3 ...\n",
      "- La stratégie classée #18 / 42 est bernoulli_0.2 , avec un nombre moyen de coups = 19.7 ...\n",
      "- La stratégie classée #19 / 42 est auMoins300    , avec un nombre moyen de coups = 20.2 ...\n",
      "- La stratégie classée #20 / 42 est bernoulli_0.25, avec un nombre moyen de coups = 21.2 ...\n",
      "- La stratégie classée #21 / 42 est auMoins250    , avec un nombre moyen de coups = 22.1 ...\n",
      "- La stratégie classée #22 / 42 est bernoulli_0.3 , avec un nombre moyen de coups = 22.7 ...\n",
      "- La stratégie classée #23 / 42 est bernoulli_0.35, avec un nombre moyen de coups = 23.7 ...\n",
      "- La stratégie classée #24 / 42 est auMoins200    , avec un nombre moyen de coups = 24.7 ...\n",
      "- La stratégie classée #25 / 42 est bernoulli_0.4 , avec un nombre moyen de coups = 25.3 ...\n",
      "- La stratégie classée #26 / 42 est bernoulli_0.45, avec un nombre moyen de coups = 27.2 ...\n",
      "- La stratégie classée #27 / 42 est auMoins150    , avec un nombre moyen de coups = 28.3 ...\n",
      "- La stratégie classée #28 / 42 est bernoulli_0.5 , avec un nombre moyen de coups = 28.6 ...\n",
      "- La stratégie classée #29 / 42 est bernoulli_0.55, avec un nombre moyen de coups = 29.8 ...\n",
      "- La stratégie classée #30 / 42 est bernoulli_0.6 , avec un nombre moyen de coups = 31.4 ...\n",
      "- La stratégie classée #31 / 42 est bernoulli_0.65, avec un nombre moyen de coups = 33 ...\n",
      "- La stratégie classée #32 / 42 est bernoulli_0.7 , avec un nombre moyen de coups = 34.2 ...\n",
      "- La stratégie classée #33 / 42 est auMoins100    , avec un nombre moyen de coups = 35.5 ...\n",
      "- La stratégie classée #34 / 42 est bernoulli_0.75, avec un nombre moyen de coups = 36 ...\n",
      "- La stratégie classée #35 / 42 est bernoulli_0.8 , avec un nombre moyen de coups = 37.3 ...\n",
      "- La stratégie classée #36 / 42 est bernoulli_0.85, avec un nombre moyen de coups = 38.8 ...\n",
      "- La stratégie classée #37 / 42 est bernoulli_0.9 , avec un nombre moyen de coups = 40.5 ...\n",
      "- La stratégie classée #38 / 42 est bernoulli_0.95, avec un nombre moyen de coups = 41.6 ...\n",
      "- La stratégie classée #39 / 42 est auMoins50     , avec un nombre moyen de coups = 42.9 ...\n",
      "- La stratégie classée #40 / 42 est bernoulli_1   , avec un nombre moyen de coups = 43.1 ...\n",
      "- La stratégie classée #41 / 42 est unCoup        , avec un nombre moyen de coups = 43.2 ...\n"
     ]
    }
   ],
   "source": [
    "nb = 1000\n",
    "totalMax = 5000\n",
    "resultats = comparerStrategies(joueurs, nb=nb, total=totalMax)\n",
    "print(\"Pour le total {} et {} simulations ...\".format(totalMax, nb))\n",
    "for (i, (n, j)) in enumerate(resultats):\n",
    "    print(\"- La stratégie classée #{:2} / {} est {:<14}, avec un nombre moyen de coups = {:.3g} ...\".format(i, len(joueurs), j, n))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\implies$ la stratégie la plus efficace est en effet `jusquauBout` !"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Notons néanmoins que je n'ai testé que des stratégies très simples...\n",
    "> En particulier, celles considérées n'utilisent pas, dans leur prise de décision, le nombre de coups déja joué, ni le nombre de tirage courant."
   ]
  }
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