{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "used_page = np.array([91.57, 89.7, 87.4, 83.88, 80.29, 75.65, 69.29]) # Taux de page utilisé\n",
    "miss_rate = np.array([74.49, 3.67, 3.38, 3.05, 2.73, 2.61, 2.4])  # Taux de miss\n",
    "\n",
    "reuse_distance = np.array([20, 49, 51, 58, 74, 76, 77]) # Reuse distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "memoire_A = used_page\n",
    "memoire_B = miss_rate\n",
    "\n",
    "numerical_indices = np.array([10, 20, 30, 40, 50, 60, 70])\n",
    "bar_width = 2  # Largeur des barres\n",
    "spacing = 1\n",
    "\n",
    "# Les étiquettes correspondant aux indices\n",
    "labels = [\"4Ko\", \"8Ko\", \"16Ko\", \"32Ko\", \"64Ko\", \"128Ko\", \"256Ko\"]\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "# Première série de barres pour le tableau A (en bleu)\n",
    "plt.bar(numerical_indices - bar_width / 2 - spacing / 2, memoire_A, color='blue', width=bar_width, label='Taux de page utilisé')\n",
    "\n",
    "# Deuxième série de barres pour le tableau B (en rouge)\n",
    "plt.bar(numerical_indices + bar_width / 2 + spacing / 2, memoire_B, color='red', width=bar_width, label='Taux de miss')\n",
    "\n",
    "plt.xlabel('Taille de page')  # Nommer l'axe des x\n",
    "#plt.ylabel('Taux de page utilisé (en %)')  # Nommer l'axe des y\n",
    "plt.xticks(numerical_indices, labels)  # Utiliser les étiquettes pour l'axe x\n",
    "\n",
    "for i in range(len(numerical_indices)):\n",
    "    plt.text(numerical_indices[i] - bar_width / 2 - spacing / 2, memoire_A[i], str(memoire_A[i])+'%', ha='center', va='bottom')\n",
    "    plt.text(numerical_indices[i] + bar_width / 2 + spacing, memoire_B[i], str(memoire_B[i])+'%', ha='center', va='bottom')\n",
    "\n",
    "plt.ylim(0, 100)\n",
    "plt.yticks(range(0, 101, 10))\n",
    "\n",
    "plt.legend()  # Afficher la légende\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig('atax-a.svg', format='svg')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAGoCAYAAABL+58oAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzt3Xu8XHV97//XGyIgNwVJOAFE1CJQoATYRSzWChhAVCBYFG9NERpsixXrKcX28ahotXIURE+Ph9OoaH7F4g+5CAdviYA3iuIGIpciUDGFYEyigqCo3D7nj1nBTdxJJglrz86a1/Px2I+Z+c5asz77m9mT93zXd62VqkKSJKlLNhp0AZIkSU81A44kSeocA44kSeocA44kSeocA44kSeocA44kSeqcVgNOkrcnuTXJLUkuSLJZkm2TLEhyZ3O7TZs1SJKk4dNawEmyI/BXwEhV7QVsDBwPnA5cWVW7Alc2jyVJkp4ybe+imgI8PckUYHPgh8DRwLzm+XnAMS3XIEmShsyUtl64qu5NchZwN/BLYH5VzU+yfVUtaZZZkmTaeOsnmQPMAdhiiy3233333dsqVZIkbSCuv/76H1fV1DUt11rAaebWHA08F7gf+GySN/a7flXNBeYCjIyM1OjoaCt1SpKkDUeS/+pnuTZ3Ub0M+EFVLa+qR4BLgD8AliaZDtDcLmuxBkmSNITaDDh3Awcm2TxJgEOB24DLgdnNMrOBy1qsQZIkDaE25+B8O8lFwA3Ao8CN9HY5bQlcmOREeiHouLZqkCRJw6m1gANQVe8C3rVS86/pjeZIkqRJ5vbbb+e1r33tE4/vuusu3vOe93Dttddy++23A3D//ffzzGc+k4ULFw6qzDVqNeBIkqQNy2677fZEcHnsscfYcccdmTVrFqeeeuoTy7zjHe/gGc94xqBK7IsBR5IkjevKK6/k+c9/Ps95znOeaKsqLrzwQq666qoBVrZmXotKkiSN6zOf+Qyve93rntT2jW98g+23355dd911QFX1x4AjSZJ+y8MPP8zll1/Occc9+VigCy644LdCz2RkwJEkdd7tt9/OjBkznvjZeuut+fCHPwzAP//zP7Pbbrux5557ctpppw240snji1/8Ivvttx/bb7/9E22PPvool1xyyZMmIU9WzsGRJHXeqibOXn311Vx22WXcdNNNbLrppixb5rlnVxhvpOYrX/kKu+++OzvttNOAquqfIziSpKEyduLsueeey+mnn86mm24KwLRp414eceg89NBDLFiwgGOPPfZJ7ePNyZmsDDiSpKEy9j/pO+64g2984xu88IUv5I/+6I/4zne+M+DqJofNN9+cn/zkJ791KPinPvUp3vKWtwyoqrXjLipJ0tBYMXH2/e9/P9CbU3LffffxrW99i+985zu85jWv4a677qJ3haFua/NXrGrvtfvlCI4kaWisPHF2p5124thjjyUJBxxwABtttBE//vGPB1ylngoGHEnS0Fh54uwxxxzzxAnr7rjjDh5++GG22267QZWnp5ABR5I0FMabOPvmN7+Zu+66i7322ovjjz+eefPmDcXuqWHgHBxJ0lBYMXF2rE022YTzzz9/QBWpTY7gSNIGbHUnsAM466yzSDJU80qSdn60YXEER5I2YKs6gR3APffcw4IFC9h5550HWaI0EK2N4CTZLcnCMT8PJDk1yRlJ7h3TfmRbNUjSMFn5ys9vf/vb+cAHPuCcEg2l1kZwqup2YAZAko2Be4FLgROAc6rqrLa2LUnDaOwJ7C6//HJ23HFH9tlnnwFXJQ3GRO2iOhT4flX9l98kJOmpN/YEdg899BDve9/7mD9//qDLkgZmoiYZHw9cMObxKUluSnJekm3GWyHJnCSjSUaXL18+MVVK0gZq7Ansvv/97/ODH/yAffbZh1122YXFixez33778aMf/WjQZUoTJtXy+ZSTbAL8ENizqpYm2R74MVDAPwLTq+rNq3uNkZGRGh0dbbVOSdqQHX/88Rx++OGccMIJv/XcLrvswujo6NCcwK6tHQWT4fIDT6UN9VINSa6vqpE1LTcRIzgvB26oqqUAVbW0qh6rqseBjwEHTEANktRZq7ryszTMJmIOzusYs3sqyfSqWtI8nAXcMgE1SFJnjXcCu7EWLVo0ccVIk0SrASfJ5sBM4OQxzR9IMoPeLqpFKz0nSZK03loNOFX1EPCsldre1OY2JamLnFcirR0v1SBJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjrHgCNJkjqntYCTZLckC8f8PJDk1CTbJlmQ5M7mdpu2apAkScOptYBTVbdX1YyqmgHsDzwEXAqcDlxZVbsCVzaPJUmSnjITtYvqUOD7VfVfwNHAvKZ9HnDMBNUgSZKGxEQFnOOBC5r721fVEoDmdtp4KySZk2Q0yejy5csnqExJktQFrQecJJsARwGfXZv1qmpuVY1U1cjUqVPbKU6SJHXSRIzgvBy4oaqWNo+XJpkO0Nwum4AaJEnSEJmIgPM6frN7CuByYHZzfzZw2QTUIEmShkirASfJ5sBM4JIxzWcCM5Pc2Tx3Zps1SJKk4TOlzRevqoeAZ63U9hN6R1VJkiS1wjMZS5KkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzjHgSJKkzmk14CR5ZpKLknwvyW1JXpTkjCT3JlnY/BzZZg2SJGn4TGn59T8CfKmq/jjJJsDmwOHAOVV1VsvbliRJQ6q1gJNka+AlwJ8CVNXDwMNJ2tqkJEkS0O4uqucBy4FPJrkxyceTbNE8d0qSm5Kcl2Sb8VZOMifJaJLR5cuXt1imJEnqmjYDzhRgP+DcqtoX+AVwOnAu8HxgBrAEOHu8latqblWNVNXI1KlTWyxTkiR1TZsBZzGwuKq+3Ty+CNivqpZW1WNV9TjwMeCAFmuQJElDqLWAU1U/Au5JslvTdCjwH0mmj1lsFnBLWzVIkqTh1PZRVG8FPt0cQXUXcALwP5PMAApYBJzccg2SJGnItBpwqmohMLJS85va3KYkSZJnMpYkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ3TasBJ8swkFyX5XpLbkrwoybZJFiS5s7ndps0aJEnS8Gl7BOcjwJeqandgH+A24HTgyqraFbiyeSxJkvSUaS3gJNkaeAnwCYCqeriq7geOBuY1i80DjmmrBkmSNJzaHMF5HrAc+GSSG5N8PMkWwPZVtQSguZ023spJ5iQZTTK6fPnyFsuUNBntsssu7L333syYMYORkREAFi5cyIEHHvhE23XXXTfgKiVNVm0GnCnAfsC5VbUv8AvWYndUVc2tqpGqGpk6dWpbNUqaxK6++moWLlzI6OgoAKeddhrvete7WLhwIe95z3s47bTTBlyhpMmqzYCzGFhcVd9uHl9EL/AsTTIdoLld1mINkjokCQ888AAAP/vZz9hhhx0GXJGkySpV1d6LJ98ATqqq25OcAWzRPPWTqjozyenAtlW12q9hIyMjteIbnKTh8NznPpdtttmGJJx88snMmTOH2267jcMPP5yq4vHHH+ff//3fec5znjPoUidE0s7rtvhfwMDYV/1pq5+g3b5Kcn1VjaxpuSntlQDAW4FPJ9kEuAs4gd6o0YVJTgTuBo5ruQZJG6BrrrmGHXbYgWXLljFz5kx23313LrroIs455xxe/epXc+GFF3LiiSfyla98ZdClSpqEWh3Beao4giMNtzPOOIMtt9ySf/zHf+T+++8nCVXFM57xjCd2WXWdoxL9s6/60/URHM9kLGnS+cUvfsGDDz74xP358+ez1157scMOO/C1r30NgKuuuopdd911kGVKmsTa3kUlSWtt6dKlzJo1C4BHH32U17/+9RxxxBFsueWWvO1tb+PRRx9ls802Y+7cuQOuVNJk5S4qSdoAuNulf/ZVf9xFJUmStIFxF5WkgdlQv0FKmvwcwZEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ1jwJEkSZ3TasBJsijJzUkWJhlt2s5Icm/TtjDJkW3WIEmShs9EXIvq4Kr68Upt51TVWROwbUmSNITcRSVJkjqn7YBTwPwk1yeZM6b9lCQ3JTkvyTbjrZhkTpLRJKPLly9vuUxJktQlbQecg6pqP+DlwF8meQlwLvB8YAawBDh7vBWram5VjVTVyNSpU1suU5IkdUmrAaeqftjcLgMuBQ6oqqVV9VhVPQ58DDigzRokSdLwaS3gJNkiyVYr7gOHAbckmT5msVnALW3VIEmShlObR1FtD1yaZMV2/q2qvpTkX5PMoDc/ZxFwcos1SJKkIdRawKmqu4B9xml/U1vblCRJAg8TlyRJHWTAkSRJnWPAkSRJnWPAkSbQLrvswt57782MGTMYGRkB4LOf/Sx77rknG220EaOjowOuUJK6YSKuRSVpjKuvvprtttvuicd77bUXl1xyCSef7AGFkvRUMeBIA7bHHnsMugRJ6hx3UUkTKAmHHXYY+++/P3Pnzh10OZLUWY7gSBPommuuYYcddmDZsmXMnDmT3XffnZe85CWDLkuSOscRHGkC7bDDDgBMmzaNWbNmcd111w24IknqJgOONEF+8Ytf8OCDDz5xf/78+ey1114DrkqSusmAI02QpUuX8uIXv5h99tmHAw44gFe84hUcccQRXHrppey0005ce+21vOIVr+Dwww8fdKmStMFLVQ26hjUaGRkpzw8idU/vWrzt2AA+2tZKW33VtX4C+6pfG+rfX5Lrq2pkTcs5yVhqgR+wkjRY7qLSU+Kxxx5j33335ZWvfCUA3/3ud3nRi17E3nvvzate9SoeeOCBAVcoSRomrQacJIuS3JxkYZLRpm3bJAuS3NncbtNmDZoYH/nIR550wrqTTjqJM888k5tvvplZs2bxwQ9+cIDVSZKGzUSM4BxcVTPG7C87HbiyqnYFrmweawO2ePFiPv/5z3PSSSc90Xb77bc/cX6XmTNncvHFFw+qPEnSEBrELqqjgXnN/XnAMQOoQU+hU089lQ984ANstNFv3k577bUXl19+OdC7mOQ999wzqPIkSUOo7YBTwPwk1yeZ07RtX1VLAJrbaeOtmGROktEko8uXL2+5TK2rK664gmnTprH//vs/qf28887jox/9KPvvvz8PPvggm2yyyYAqlCQNo7aPojqoqn6YZBqwIMn3+l2xquYCc6F3mHhbBWr9XHPNNVx++eV84Qtf4Fe/+hUPPPAAb3zjGzn//POZP38+AHfccQef//znB1ypJGmYtDqCU1U/bG6XAZcCBwBLk0wHaG6XtVmD2vX+97+fxYsXs2jRIj7zmc9wyCGHcP7557NsWe+f9fHHH+e9730vb3nLWwZcqSRpmLQWcJJskWSrFfeBw4BbgMuB2c1is4HL2qpBg3PBBRfwghe8gN13350ddtiBE044YdAlSZKGSGtnMk7yPHqjNtDbFfZvVfW+JM8CLgR2Bu4Gjquqn67utTyTsTY0nuivPxvqmVQHwfdU/+yr/myof38DP5NxVd0F7DNO+0+AQ9vartrjh4YkaUPhmYwlSVLnGHAkSVLnGHAkSVLnGHAkSVLnGHAkSVLnrDHgJNk+ySeSfLF5/LtJTmy/NEmSpHXTzwjOp4AvAzs0j+8ATm2rIEmSpPXVT8DZrqouBB4HqKpHgcdarUqSJGk99BNwftGcfbgAkhwI/KzVqiRJktZDP2cy/mt61496fpJrgKnAH7dalSRJ0npYY8CpqhuS/BGwGxDg9qp6pPXKJEmS1lE/R1H9JbBlVd1aVbcAWyb5i/ZLkyRJWjf9zMH5s6q6f8WDqroP+LP2SpIkSVo//QScjZLfXEc6ycbAJu2VJEmStH76CThfBi5McmiSQ4ALgC/1u4EkGye5MckVzeMzktybZGHzc+S6lS5JkjS+fo6i+lvgZODP6U0yng98fC228TbgNmDrMW3nVNVZa/EakiRJfevnKKrHgXObn7WSZCfgFcD76B1uLkmS1Lp+jqI6KMmCJHckuSvJD5Lc1efrfxg4jeYsyGOckuSmJOcl2WZti5YkSVqdfubgfAL4EPBi4PeBkeZ2tZK8ElhWVdev9NS5wPOBGcAS4OxVrD8nyWiS0eXLl/dRpiRJUk8/c3B+VlVfXIfXPgg4qplEvBmwdZLzq+qNKxZI8jHgivFWrqq5wFyAkZGRWoftS5KkIdXPCM7VST6Y5EVJ9lvxs6aVquqdVbVTVe0CHA9cVVVvTDJ9zGKzgFvWrXRJkqTx9TOC88LmdmRMWwGHrOM2P5BkRvMai+gdoSVJkvSU6ecoqoPXdyNV9VXgq839N63v60mSJK1OPyM4JHkFsCe9uTQAVNV72ipKkiRpffRzmPj/AV4LvJXeif6OA57Tcl2SJEnrrJ9Jxn9QVX8C3FdV7wZeBDy73bIkSZLWXT8B55fN7UNJdgAeAZ7bXkmSJEnrp585OFckeSbwQeAGekc/rc21qCRJkiZUPwHnA1X1a+Di5orgmwG/arcsSZKkddfPLqprV9ypql9X1c/GtkmSJE02qxzBSfLfgB2BpyfZl94RVABbA5tPQG2SJEnrZHW7qA4H/hTYid4FMVcEnAeBv2u3LEmSpHW3yoBTVfOAeUleXVUXT2BNkiRJ66WfOTg7Jdk6PR9PckOSw1qvTJIkaR31E3DeXFUPAIcB04ATgDNbrUqSJGk99BNwVsy9ORL4ZFV9d0ybJEnSpNNPwLk+yXx6AefLSbYCHm+3LEmSpHXXz4n+TgRmAHdV1UNJnkVvN5UkSdKktMoRnCS7N3dnNLfPS7IfvSuJ9xOMVrzOxklubM6CTJJtkyxIcmdzu826Fi9JkjSe1QWVdwB/Ru8cOCsr4JA+t/E24DZ6JwgEOB24sqrOTHJ68/hv+3wtSZKkNVrdeXD+rLk9eF1fPMlOwCuA9wF/3TQfDby0uT8P+CoGHEmS9BRa3aUajl3dilV1SR+v/2HgNGCrMW3bV9WS5jWWJJm2iu3PAeYA7Lzzzn1sSpIkqWd1u6he1dxOA/4AuKp5fDC9UZfVBpwkrwSWVdX1SV66toVV1VxgLsDIyEit7fqSJGl4rW4X1QkAzeTg310x6pJkOvDRPl77IOCoJEcCmwFbJzkfWJpkejN6Mx1Ytr6/hCRJ0lj9nAdnlxXhprEUeMGaVqqqd1bVTlW1C3A8cFVVvRG4HJjdLDYbuGztSpYkSVq9fg73/mqSLwMX0Dt66njg6vXY5pnAhUlOBO4GjluP15IkSfotaww4VXVKklnAS5qmuVV16dpspKq+Sm/eDlX1E+DQtStTkiSpf32dsK8JNGsVaiRJkgalnzk4kiRJGxQDjiRJ6py+Ak6SpyfZre1iJEmSngprDDhJXgUsBL7UPJ6R5PK2C5MkSVpX/YzgnAEcANwPUFULgV3aK0mSJGn99BNwHq2qn7VeiSRJ0lOkn8PEb0nyemDjJLsCfwX8e7tlSZIkrbt+RnDeCuwJ/Jre2YwfAE5tsyhJkqT10c+ZjB8C/h74+yQbA1tU1a9ar0ySJGkd9XMU1b8l2TrJFsCtwO1J/qb90iRJktZNP7uofreqHgCOAb4A7Ay8qdWqJEmS1kM/AedpSZ5GL+BcVlWP0LuquCRJ0qTUT8D5F2ARsAXw9STPoTfRWJIkaVJaY8Cpqv9ZVTtW1ZHV81/AwWtaL8lmSa5L8t0ktyZ5d9N+RpJ7kyxsfo58Cn4PSZKkJ6zxKKok/7CKp96zhlV/DRxSVT9vdnF9M8kXm+fOqaqz1qJOSZKkvvVzor9fjLm/GfBK4LY1rVRVBfy8efi05se5O5IkqXX9nAfn7LGPk5wF9HWxzea8OdcDvwN8tKq+neTlwClJ/gQYBd5RVfetdeWSJEmr0M8k45VtDjyvnwWr6rGqmgHsBByQZC/gXOD5wAxgCXD2eOsmmZNkNMno8uXL16FMSZI0rPo50d/NSW5qfm4Fbgc+sjYbqar7ga8CR1TV0ib4PA58jN6VysdbZ25VjVTVyNSpU9dmc5Ikacj1MwfnlWPuPwosrapH17RSkqnAI1V1f5KnAy8D/keS6VW1pFlsFnDL2hYtSZK0Ov3MwfmvJC8Gdq2qTybZLslWVfWDNaw6HZjXzMPZCLiwqq5I8q9JZtCbcLwIOHk9fwdJkqQn6ecw8XcBI8BuwCeBTYDzgYNWt15V3QTsO067l3mQJEmt6meS8SzgKJrDxavqh8BWbRYlSZK0PvoJOA8357QpgOaq4pIkSZNWPwHnwiT/AjwzyZ8BXwE+3m5ZkiRJ666fScZnJZlJ7wKbuwH/UFULWq9MkiRpHfVzmDhNoFkAvbMTJ3lDVX261cokSZLW0Sp3USXZOsk7k/yvJIel5xTgLuA1E1eiJEnS2lndCM6/AvcB1wInAX9D7xDxo6tq4QTUJkmStE5WF3CeV1V7AyT5OPBjYOeqenBCKpMkSVpHqzuK6pEVd6rqMeAHhhtJkrQhWN0Izj5JHmjuB3h68zhAVdXWrVcnSZK0DlYZcKpq44ksRJIk6anSz4n+JEmSNigGHEmS1DkGHEmS1DkGHEmS1DmtBZwkmyW5Lsl3k9ya5N1N+7ZJFiS5s7ndpq0aJEnScGpzBOfXwCFVtQ8wAzgiyYHA6cCVVbUrcGXzWJIk6SnTWsCpnp83D5/W/BRwNDCvaZ8HHNNWDZIkaTi1OgenufL4QmAZsKCqvg1sX1VLAJrbaatYd06S0SSjy5cvb7NMSZLUMa0GnKp6rKpmADsBByTZay3WnVtVI1U1MnXq1PaKlCRJnTMhR1FV1f3AV4EjgKVJpgM0t8smogZJkjQ82jyKamqSZzb3nw68DPgecDkwu1lsNnBZWzVIkqThtLqLba6v6cC8JBvTC1IXVtUVSa4FLkxyInA3cFyLNUiSpCHUWsCpqpuAfcdp/wlwaFvblSRJ8kzGkiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpc1oLOEmeneTqJLcluTXJ25r2M5Lcm2Rh83NkWzVIkqThNKXF134UeEdV3ZBkK+D6JAua586pqrNa3LYkSRpirQWcqloCLGnuP5jkNmDHtrYnSZK0woTMwUmyC7Av8O2m6ZQkNyU5L8k2q1hnTpLRJKPLly+fiDIlSVJHtB5wkmwJXAycWlUPAOcCzwdm0BvhOXu89apqblWNVNXI1KlT2y5TkiR1SKsBJ8nT6IWbT1fVJQBVtbSqHquqx4GPAQe0WYMkSRo+bR5FFeATwG1V9aEx7dPHLDYLuKWtGiRJ0nBq8yiqg4A3ATcnWdi0/R3wuiQzgAIWASe3WIMkSRpCbR5F9U0g4zz1hba2KUmSBJ7JWJIkdZABR5IkdY4BR5IkdY4BR5IkdY4BR5IkdY4BR5IkdY4BR5IkdY4BR5IkdY4BR5IkdY4BZxXuueceDj74YPbYYw/23HNPPvKRjwDw05/+lJkzZ7Lrrrsyc+ZM7rvvvgFXKkmSVmbAWYUpU6Zw9tlnc9ttt/Gtb32Lj370o/zHf/wHZ555Joceeih33nknhx56KGeeeeagS5UkSSsx4KzC9OnT2W+//QDYaqut2GOPPbj33nu57LLLmD17NgCzZ8/mc5/73CDLlCRJ4zDg9GHRokXceOONvPCFL2Tp0qVMnz4d6IWgZcuWDbg6SZK0MgPOGvz85z/n1a9+NR/+8IfZeuutB12OJEnqgwFnNR555BFe/epX84Y3vIFjjz0WgO23354lS5YAsGTJEqZNmzbIEiVJ0jhaCzhJnp3k6iS3Jbk1ydua9m2TLEhyZ3O7TVs1rI+q4sQTT2SPPfbgr//6r59oP+qoo5g3bx4A8+bN4+ijjx5UiZIkaRVSVe28cDIdmF5VNyTZCrgeOAb4U+CnVXVmktOBbarqb1f3WiMjIzU6OtpKnavyzW9+kz/8wz9k7733ZqONejnwn/7pn3jhC1/Ia17zGu6++2523nlnPvvZz7LttttOaG2DkrTzui29BQfKvupPW/0E9lW/utZPYF/1a0P9+0tyfVWNrGm5KW0VUFVLgCXN/QeT3AbsCBwNvLRZbB7wVWC1AWcQXvziF7Oq8HfllVdOcDWSJGlttBZwxkqyC7Av8G1g+yb8UFVLkow7iSXJHGAOwM4779xiba29dOfSviRJG4rWJxkn2RK4GDi1qh7od72qmltVI1U1MnXq1PYKlCRJndNqwEnyNHrh5tNVdUnTvLSZn7Nino4nkpEkSU+pNo+iCvAJ4Laq+tCYpy4HZjf3ZwOXtVWDJEkaTm3OwTkIeBNwc5KFTdvfAWcCFyY5EbgbOK7FGiRJ0hBq8yiqbwKrmsJ7aFvblSRJ8kzGkiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpcww4kiSpc1oLOEnOS7IsyS1j2s5Icm+Shc3PkW1tX5IkDa82R3A+BRwxTvs5VTWj+flCi9uXJElDqrWAU1VfB37a1utLkiStyiDm4JyS5KZmF9Y2q1ooyZwko0lGly9fPpH1SZKkDdxEB5xzgecDM4AlwNmrWrCq5lbVSFWNTJ06daLqkyRJHTChAaeqllbVY1X1OPAx4ICJ3L4kSRoOExpwkkwf83AWcMuqlpUkSVpXU9p64SQXAC8FtkuyGHgX8NIkM4ACFgEnt7V9SZI0vFoLOFX1unGaP9HW9iRJklbwTMaSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDiSJKlzDDgboz5fAAANOUlEQVSSJKlzDDiSJKlzDDiSJKlzWgs4Sc5LsizJLWPatk2yIMmdze02bW1fkiQNrzZHcD4FHLFS2+nAlVW1K3Bl81iSJOkp1VrAqaqvAz9dqfloYF5zfx5wTFvblyRJw2ui5+BsX1VLAJrbaataMMmcJKNJRpcvXz5hBUqSpA3fpJ1kXFVzq2qkqkamTp066HIkSdIGZKIDztIk0wGa22UTvH1JkjQEJjrgXA7Mbu7PBi6b4O1LkqQh0OZh4hcA1wK7JVmc5ETgTGBmkjuBmc1jSZKkp9SUtl64ql63iqcObWubkiRJMIknGUuSJK0rA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeocA44kSeqcKYPYaJJFwIPAY8CjVTUyiDokSVI3DSTgNA6uqh8PcPuSJKmj3EUlSZI6Z1ABp4D5Sa5PMme8BZLMSTKaZHT58uUTXJ4kSdqQDSrgHFRV+wEvB/4yyUtWXqCq5lbVSFWNTJ06deIrlCRJG6yBBJyq+mFzuwy4FDhgEHVIkqRumvCAk2SLJFutuA8cBtwy0XVIkqTuGsRRVNsDlyZZsf1/q6ovDaAOSZLUURMecKrqLmCfid6uJEkaHh4mLkmSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOseAI0mSOmcgASfJEUluT/KfSU4fRA2SJKm7JjzgJNkY+CjwcuB3gdcl+d2JrkOSJHXXIEZwDgD+s6ruqqqHgc8ARw+gDkmS1FFTBrDNHYF7xjxeDLxw5YWSzAHmNA9/nuT2CaitH9sBP+5nwaTlSiY3+6l/9lX/7Kv+2E/9s6/603c/Qet99Zx+FhpEwBnv167faqiaC8xtv5y1k2S0qkYGXcdkZz/1z77qn33VH/upf/ZVfzbEfhrELqrFwLPHPN4J+OEA6pAkSR01iIDzHWDXJM9NsglwPHD5AOqQJEkdNeG7qKrq0SSnAF8GNgbOq6pbJ7qO9TDpdptNUvZT/+yr/tlX/bGf+mdf9WeD66dU/db0F0mSpA2aZzKWJEmdY8CRJEmdY8AZR5KNk9yY5Irm8aeS/HFzf9vmuRMGW+VgJXl7kluT3JLkgiSb2U89Sc5LsizJLSu1v7W5RMmtST7QtL10xfusefzeJF9OsulE1z0IzfvmuiTfbfrl3U37B5N8L8lNSS5N8symfWj7K8kzk1zU9MttSV405rn/nqSSbNc8Hqp+Gu9vbjXvoaclmZfk5qYf3zlmnUVj+nD/JD9Isu/E/0btSPLsJFc3v/etSd7WtJ+R5N4kC5ufI8es83tJrm2WvznJZk37pO8rA8743gbctnJjkmfQmxw9t6o+OeFVTRJJdgT+Chipqr3oTRY/fszzw95PnwKOGNuQ5GB6Z+z+varaEzhr5ZWS/D1wEHBMVf16AuqcDH4NHFJV+wAzgCOSHAgsAPaqqt8D7gDeufKKQ9hfHwG+VFW7A/vQfEYleTYwE7h7vJWGpJ8+xUp/c6z6PXQcsGlV7Q3sD5ycZJexKyb5PeAi4LVVdWN7ZU+4R4F3VNUewIHAX465VNI5VTWj+fkCQJIpwPnAW5rPrZcCj4x9wcncVwaclSTZCXgF8PGVntoS+CLwb1V1brNsmm8JtzTJ9rUTXO4gTQGe3vwBbM5vzmU09P1UVV8HfrpS858DZ674D6aqlo19Msk7gCOBV1XVL5u2Q5tRsJubb6id+/ZdPT9vHj6t+amqml9Vjzbt36J3vqwnDFt/JdkaeAnwCYCqeriq7m+ePgc4jXFOmDos/TTe39xq3kMFbNF8dj0deBh4YMyqewCfA95UVdfBEyPSn2tGg77V/Ke+wamqJVV1Q3P/QXohecfVrHIYcFNVfbdZ5ydV9diY5yd1XxlwftuH6X1YPL5S+4eAb1bVOWPajqX3rXMf4GXAB5NMn5AqB6iq7qU3AnE3sAT4WVXNb562n8b3AuAPk3w7ydeS/P6Y5w4C3gK8fMV/9s0w8KfofSvam16g/PMJrnlCpLdLeCGwDFhQVd9eaZE30wvNKwxjfz0PWA58sgknH0+yRZKjgHtX/Ae0kmHsp1UZ+x66CPgFvc+uu4GzqmpsOLoMOKWqvjmm7d3Ajc1o0N8B/1/7JberGbXaF1jx93ZKE0rOS7JN0/YCoJrdmzckOW2ll5nUfWXAGSPJK4FlVXX9OE9fBRydZNqYthcDF1TVY1W1FPga8PvjrNspzZv/aOC5wA70vg29sXnafhrfFGAbesPCfwNcmDxxtZb/pHcJk8PGLL8b8IOquqN5PI/eN/jOad4XM+h9wz4gyV4rnmt2rzwKfHrMKsPYX1OA/YBzq2pfev9BnwH8PfAPq1hnGPvpt4zzHjoAeIzeZ9dzgXcked6YVb4CnJRk4zFtLwb+FaCqrgKe1eyK3yAl2RK4GDi1qh4AzgWeT++L6BLg7GbRKfR+9zc0t7OSHDrmpSZ1Xxlwnuwg4Kgki+hd5fyQJOc3z32G3pvgC0m2atqG9dJrL6P3Ibm8qh4BLgH+oHnOfhrfYuCSZpfMdfRGCLdrnltKbzfCOc1cHRjCPmt2uXyVZi5FktnAK4E31JNP2DWM/bUYWDxmdOsieoHnucB3m8+snYAbkvy3Zplh7KcnWcV76PX05jI90uwqvgYYe42lU5rb/z32pcZ5+Q3yJHJJnkYv3Hy6qi4BqKqlzReNx4GP0QuB0Hvffa2qflxVDwFfoPe+W2FS95UBZ4yqemdV7VRVu9CbNHtVVb1xzPMfBq4ELk3vMhNfB17bDLFPpfdN6LoBlD7R7gYOTLJ5MwpxKGMmZdtP4/occAhAkhcAmzDmyrzNN+pjgfOTzAC+B+yS5HeaRd5Eb+SrU5JMzW+Obnk6vfD8vSRHAH8LHNV8sD7JsPVXVf0IuCfJbk3TocANVTWtqnZpPrMWA/s1y65Yb6j6aazVvIfupvflNUm2oDeq+r0xzz8OvA7YLcl7mrav0xvFIMlLgR83Ix8blObz+hPAbVX1oTHtY6cMzAJWHI32ZeD3ms/6KcAfAf8xZtlJ3VeDuJr4Bq2q/jbJJ+kNwb0eeBHwXXoJ9bSxHy5dVVXfTnIRcAO9od8b6Z3G+1/GLDO0/ZTkAnpHG2yXZDHwLuA84Lz0DmN9GJhdVfWbvVRQVd9J77D6y4GDgROAzzYfLN8B/s+E/iITYzowrxni3gi4sKquSPKfwKbAgqaPvlVVbxm74hD211uBTzdfGu6i9/uu0TD00yr+5t7J+O+hjwKfpPefeIBPVtVNY1+vqn6d5Gjga0mW0tsd+MkkNwEPAbMn4vdqwUH0Qu3Nzbw36M2TeV0TgAtYBJwMUFX3JfkQvfdJAV+oqs+PfcHJ3FdeqkGSJHWOu6gkSVLnGHAkSVLnGHAkSVLnGHAkSVLnGHAkSVLnGHAkrVKSZ+U3Vxj+UZ58xeFNVrHOl5NslWRKkvubtt8Zc1jqutTx3iSnruv6koaP58GRtEpV9RN6p28nyRnAz6vqt66EvtI6hzfL+/kiaWAcwZG0TpL83yTXJ7k1yUlj2hevODvxKtabkuRDSa5L7+J+J61iuX9IcnuSBcCuY9p3bUaJrk/y9ebM0Cuv+94k85JcneTOJG9u2rdOclV6Fw68Kb3rz61Y591JvpdkQZL/f8WIUT/bkzT5+A1L0rqaXVU/TbI5MJrk4qq6r4/15tC7qO0BSTYFvpVkflXdvWKBJAcAr6Y3erQJsBC4tnl6LnBSVX0/yUHA/+LJF5RcYW9610jbmt41mj4P/BQ4uqoeTO+CsNcAVyQ5kN41i/ahd/bbddmepEnEgCNpXb09yVHN/Z3oXY14tI/1DgP2SHJ88/gZ9EZo7h6zzEuAi6vql8Avk/xfgGZk6EDg4jGXuVjV59jnqupXwK+SfJ3eFeznA/8jyYvpXUfn2Um2o3cF5M9V1a+BXye5Yh22J2kS8Q9V0lpL8jJ6IeTAqvplkm8Cm/W7OvAXVXXlGpYb7zoyoXfxvhl9bGfl9Qv4E3qBar+qerS5btFmrPoq22uzPUmTiHNwJK2LZwA/bcLNnvRGR/r1ZeAvVkxCTrJbelcSH+vrwLFJNkuyNb3dRzS7wJYkmdWsu1GSfVaxnWOSbNqM0PwhvdGlZ9DbPfZokpnAjs2y3wSOapbfCjhyHbYnaRIx4EhaF58HNk/yXeAfgG+vxbr/AtwJLGyurn4uK40mV9V1wKX0rkD/WXqBZ4Xjgbc0276VJvyM4zvAF+nNpXlXVS2ld3X7P0gyChzX1EFVXQt8CbgJuKhZ92druT1Jk4hXE5fUOUneS2/X0ofXYp0tq+rnSbagN6Izu6puaq1ISa1yDo4k9XwiyW705uScZ7iRNmyO4EiSpM5xDo4kSeocA44kSeocA44kSeocA44kSeocA44kSeqc/weJp8K9EjHTHgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reuse distance\n",
    "A = reuse_distance\n",
    "\n",
    "numerical_indices = [10, 20, 30, 40, 50, 60, 70]\n",
    "\n",
    "# Les étiquettes correspondant aux indices\n",
    "labels = [\"4Ko\", \"8Ko\", \"16Ko\", \"32Ko\", \"64Ko\", \"128Ko\", \"256Ko\"]\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "plt.bar(numerical_indices, A, color='blue', width=3)  # Largeur des bandes ajustée à 3\n",
    "plt.xlabel('Taille de page')  # Nommer l'axe des x\n",
    "plt.ylabel('Reuse distance')  # Nommer l'axe des y\n",
    "#plt.title('Histogramme de A en fonction de l\\'indice')  # Titre du graphique\n",
    "plt.xticks(numerical_indices, labels)  # Utiliser les étiquettes pour l'axe x\n",
    "\n",
    "for i in range(len(numerical_indices)):\n",
    "    plt.text(numerical_indices[i], A[i], str(A[i]), ha='center', va='bottom')\n",
    "\n",
    "plt.ylim(0, 80)\n",
    "plt.yticks(range(0, 81, 5))\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig('atax-b.svg', format='svg')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}