tornado.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3dSlAtsh43bx8+bLmzp2rZs2a2bgiPErS0tKUJ08eTZgwQa1bt9bvv/+ucePGKSkpydal4Qm3fv16BQYGSpL69++v559/XikpKTauCk86k8mkH374QY0aNdLZs2ctM/meZIRSyBFpaWkyDEMmk0lr1qxRhw4dtGbNGl27ds3WpSGXMwxDZrNZJUuWVNu2bfXyyy8rMDBQn332mSSCKVhHVFSUZs6cqdDQUFuXAjw0k8mk3bt3a9y4capSpYp8fX15HYVFxiyUsLAwJSQk6Pz581qwYIHGjx/PpXywqZCQEH366adq3ry5Vq1apdWrV8vJycnWZeEJd+vWLe3YsUPjxo1Tw4YNLa+hTzJCKWSrpUuXKjk5WQ4ODjKZTFq3bp26dOmi/v37q2/fvvLw8LB1icjlTCaT7O3t9d1332no0KGKjIxUcnKypk2bpokTJ1rG8AcVstN/n0/NmzdXo0aNtGbNGsXHx9uoKiB7JCUlac2aNVqzZo0OHTqkfPnyyWQy8ekuJN15T12/fr3q168vNzc3vf/++2rcuLHWrVunUaNGEUzBZj7//HOVKVNG27dvV69evVSxYkVbl4QnXHh4uMqVK6ctW7aoUqVKti7nkUEohWwzcuRIvf/++4qOjpYkxcXFafr06Ro/frwGDhwoFxcXRUVFacGCBVqzZo2Nq0VuduDAAfXo0UNvv/22goODtWfPHnXq1ElLly5ljSnkiIxL9vr27au4uDg99dRTevPNN/XVV1/p4MGDksQf8Hhsubi4qG/fvurdu7ciIyM1ZcoUSXdmyKSnp9u4OtiSYRhKTEzUggUL5Ovrq1GjRql///5avXq12rdvr40bN+qjjz7iUj5YXXJyshISElSpUiV16dJF3333nQICAhQTEyNJmV67eB2DtVSpUkXPP/+8Dhw4oEuXLtm6nEeGg60LQO5w4sQJLV26VEFBQSpdurSioqLk6ekpR0dHXb16VTExMZo8ebL27duns2fP6vz585o2bZqGDRtm69KRCx09elQlS5ZUly5d5ObmpiJFiuiDDz5QamqqZs6caVlzisUukR0Mw1BycrImTJigX3/9VQkJCWrUqJG6deumAQMGqFu3bgoLC5O7u7vlsmbgUZZxnl65ckUpKSkqUKCAKlSooGHDhiktLU2LFi2Si4uL/Pz8ZGdnp/T0dNnZ8Tnnk8hkMilPnjwym826efOmpd3R0VEff/yxwsLCFBQUpJs3b2rmzJnKmzev7YpFrnf3a5Gzs7Mk6auvvpIkDRo0SLNnz5YkdevWTYUKFZIkRUdHq3jx4jaoFk+ivHnzasWKFerQoYNGjx6tZ555RnXr1rV1WTbHbxDIFi4uLvL09NSZM2cUHBysjh076tixY6pVq5Z++uknFStWTGfOnFGPHj106NAh9evXTzt37uSTCWSL/57xVLx4cSUkJOjw4cOWttKlS8vX11dms1kjR460fNIP/FMZi6WaTCa5uLhoxowZKl26tG7cuKEjR46oWbNm8vb2VsWKFTV37lylpaURSOGRlxFI/ec//9FLL72kl156Sc8++6wmTZqk1NRU+fn5qX379lqwYIHlDzwCqSeX2WyW2WxWmTJldObMGV28eNHynmxnZ6emTZuqUKFCunr1quLi4mxcLXKzuwOpr7/+WkOHDtX48eP1zTffSLpzKV/btm01d+5cLVy4UEeOHFGLFi3UoUMHW5aNXCzjtTAsLEzz58/X7NmzFRISIicnJ33//feqWbOm2rdvr3379tm4UtvjtwhkC29vbzVv3lxz585Vnz599K9//UvVqlXTkCFDFBAQoO+++06rV69Wz5495ebmptjYWJUoUcLWZSOXMJlM2rlzp2XtnmLFiqlAgQJatmyZLl68aBmXP39+vfDCCxo7dqw6d+5sq3LxmDt79qwMw5CTk5N++uknbd26VTExMapXr5769euncuXK6c0331THjh01fPhw/fbbb1q0aJHOnDlj69KBv2UymbR582Z16dJF3bt31+7du9WxY0dNnDhRv/76qzw9PfXuu+/q9ddf1+TJkzVv3jxblwwryvgj6+7L8ezt7fXhhx8qMjJS7733ns6fP2/pu3Llirp166Yvv/yS2SjIURmB1PDhwzV06FCdPXtWmzdv1tChQ9WnTx9Jd4Kpdu3aaeHChWrbtq1u3bql7du327Js5GImk0mrVq1Sq1atFBISonXr1mngwIEaNmyY5WZgPj4+6tChg3799Vdbl2tbBvAPmM1mwzAMIz093UhNTTUMwzBWrlxpmEwmo0yZMsaCBQuMmJiYe7Y7f/68MXz4cKNQoULG4cOHrVozcq+4uDjDx8fHKF68uHHr1i3DMAxj6dKlRr58+YyBAwcaW7duNS5fvmyMGDHCeOmll4xr167ZuGI8rpKSkox69eoZpUqVMgzDMN5++22jcuXKRvfu3Y0//vjDiIiIMF555RVj+/bthmEYxk8//WR07tzZKFGihBEVFWXDyoG/ZzabDbPZbPTu3dsYPHiwYRiGcfHiRaN8+fJGv379Mo09c+aMMX78eOPkyZO2KBU2kJ6ebhiGYYSEhBhdu3Y1GjZsaEyYMMH47bffDMMwjP379xseHh5GvXr1jFdffdV48803DRcXF+P48eO2LBtPkO3btxuenp7Gzp07DcMwjNjYWOPf//63UaBAAcPX19cybvfu3cb27duNtLQ0wzAMy98ywMPKOKcMwzAOHz5slCxZ0pg3b55hGIbx22+/Ga6ursaQIUMsY1JSUoz69esbVapUMRITE61e76PCZBis9IusyZgee/z4cX3++ee6cOGCmjZtqueff16RkZH69ddfFRoaqt69e6tHjx7Knz+/JGndunVatWqVdu3apRUrVsjHx8e2B4JcJTw8XL6+vrp27Zr2798vNzc3LVu2TNOnT9eFCxfk6uqqmzdvavPmzapRo4aty8VjyjAM7dq1S/3791fRokW1bds2bdy4UXPnztXu3bu1aNEiLV++XAcOHNDevXuVN29eXblyRY6OjnJ3d7d1+YCFcdf6ZmlpaXJwcLC8v7dr1049evRQixYtVKlSJbVt21aBgYEymUxauXKlSpYsqeeff96yHZ4ca9euVefOnTV48GBJUkREhG7duqVZs2apTp06unDhggICAnT27Fk5ODjogw8+ULVq1WxcNZ4US5cu1YQJE3To0CHLmlLJyclavHixZs6cqWXLlt3z94fZbJa9vb0NqkVusnbtWrVu3VrOzs6W98aNGzda1hv9448/1LhxY7388suaP3++JGn//v2qUaOGUlJSdPnyZXl7e9v4KGzItpkYHjcZM6QiIiKMIkWKGO3atTPeeustw87OzpgzZ45lXO/evY3q1asbc+bMMeLi4gzDuPNp68qVK42zZ8/apHbkHhmf1v63/fv3GzVr1jSeeuopy3l36tQpIywszNiwYYNx7tw5a5aJXMpsNhu7d+82ypcvb9SvX9/SPmbMGKNcuXJGr169DCcnJ2PUqFGZPjEDHhUZr6HR0dGWti1bthg//vijYRh33sNr1apllC5d2hg4cKCRkpJiGIZhJCYmGm+88YYxadIkzu0n0IEDB4zKlSsbX375pWEYhnH16lXDw8PDeOqpp4waNWoYv/76q2EYf846yThvgJyW8ZoWGhpqFCtWzPj5558z9UdERBhubm7G1q1bbVEecrmIiAijXLlyRocOHYzk5GRL+5YtW4zWrVsbBw8eNLy9vY133nnH8t65Z88eY8iQIcYff/xhq7IfKawphQeW8QnqwYMHVb9+ffXt21dr1qzR0qVLNWDAAJ0+fVq3bt2SJC1cuFCNGzfWggULtGTJEt28eVOenp7q0KGDSpUqZeMjwePOZDJp165daty4caZFzn18fLRw4ULly5dPdevWVUJCgp566inVrl1brVu3lpeXlw2rxuMqOjo607X+dnZ2qlWrlpYuXaorV66oVq1aMgxDEydO1OzZs+Xm5qbU1FRt2LBBCQkJNqwcuJfx/zOkYmJi1LFjRw0cOFCrVq3Siy++qOTkZEnS4MGDZTKZZDKZ9Pnnn8vR0VGSNHHiRO3du1edOnViZsETIuM9Njk5WXny5FGdOnXUrVs3nT17VvXq1dPrr7+uzz//XDdv3tTgwYP166+/WmbPMYsOOeW/b5SUMevTy8tLTz31lBYvXqyDBw9a+osWLaoyZcrcc2McIDtUrFhRw4cPV1RUlLp27Wq5EY67u7vCw8NVp04dvfzyy/riiy8s751Lly7V8ePHVaBAAVuW/sjg8j1kyblz51SzZk01bdpUK1assLS/9dZbOnbsmJKSkuTl5aUBAwaoffv2GjhwoL7//nuNGTNGffv25c5TyDYbN25U//79VbFiRW3atEkmk8nyx9aSJUvUo0cPlSxZUkePHlW+fPlsXS4eU+fOnVONGjUUExOjxo0bq379+mrRooVq166t/PnzKywsTP369VNKSooOHTokk8mka9eu6ciRIypevLgqVKhg60MAMrl27Zo8PDx07do1/fvf/9ann36qy5cva+HCheratasMw1BKSoq++eYbTZ8+Xfb29qpZs6bi4uIUGhrKJdBPoP/85z/atWuXpk6dqujoaJUsWVJdu3aVJH311VdydHRUq1attHfvXj3zzDMKCQmRi4uLjatGbmXcdenx/PnzderUKd24cUP9+vVT3bp1tXnzZg0ePFhPP/20WrRoocqVK2vKlCmKiYnRnj17CNSRre6+/DMoKEiLFi1S2bJltXDhQjk5Oemrr75S7969NXHiRL322mtydnbWggULFBQUpB07dnB58/9jphSyxGw2q2zZskpOTtauXbskSdOmTdMPP/ygDh06aNiwYbpw4YKGDh2q06dPa+7cuWrXrp1atGhBIIUsy/gk7O67/GTk6C1atNCCBQt08eJFNWvWTOnp6ZZzzNvbW61bt1a1atV06dIl6xeOXCM9PV3e3t6qWLGi4uPjdfHiRbVp00aNGzdWt27ddObMGY0cOVJpaWlq1qyZDMOQh4eHGjZsSCCFR87KlSvl7e2tgwcPysPDQzVq1NCVK1fk7u6u3377TdKdGQfOzs7q0qWLvv32WzVq1EiGYejZZ5/V7t27CaSeEBnvv5GRkerXr5+qVq0qSSpZsqRu3bql33//Xc8995wcHR2VnJyskiVLauLEiVq+fDmBFHLM3b/rffjhhxo1apROnz6t/fv365VXXtG4cePUpEkTzZs3T05OThoxYoT8/PyUnp6u3bt3y97eXmaz2cZHgdwk466PoaGh2r9/v2JjY/XNN9+oV69eSk5OVs+ePeXv769Zs2apefPm6tixo0JCQrR161YCqbswUwpZduLECQ0ePFhOTk4qWrSovv/+e3399dd66aWXJElRUVEqU6aMPv/8c/n6+tq4WjzuLly4oPfff1/vvvuumjZtKunPS0nT0tK0ZcsWDRs2TIULF1ZISIjs7e01depUXbhwQbNnz1aePHlsfAR43J08eVLDhw9Xenq6Ro4cKU9PT/3yyy+aO3euUlNT9fvvv6tcuXL6/fff1a5dO61evdrWJQP3FRYWpo8++ki///67NmzYoIoVK2rXrl06fPiwAgMD1bhxY82dO9fWZcIGMt5XM/6VpN27dysyMlIHDx7U7NmzLX0JCQnq3LmzUlNT5efnp82bN2vNmjXavn27SpQoYeMjwZMgJiZG7777roYOHaq6detKkiZNmqR///vf6tatm4YPH66kpCTFxcUpNTVVJUqUkMlk4uYMyBEhISFq06aNpk2bJi8vL23dulW7du3SM888oyVLlsjZ2VmHDx/WzZs3lTdvXnl5ealIkSK2LvvRYoN1rJALHDt2zHjxxReNPHnyGNOnTzcM484igykpKcb58+eNZ5991li5cqWlHfinTp06ZdSvX99o06aNERoaamnPWHQ/JSXF2LRpk1G9enXDycnJqF27tpE3b17j4MGDtioZudDRo0eNli1bGi+++KKxd+9eS/uNGzeMJUuWGKNGjTJq1KhhuTU68ChZu3at5fuDBw8ar7zyiuHl5WUcPnzYMAzDuHLlijF9+nSjWrVqxqBBgyxjg4KCjE2bNhnp6em8l+diGe+nZ86cMb744gtjz549hmEYRp06dQyTyWQ0btw40+K9hmEYy5YtM5o0aWIUK1bMqFChghEeHm71uvFkmj9/vuHu7m7UqFHDOH78eKa+UaNGGUWLFjViYmLu2S7jPAeyS3p6upGcnGz861//Mt555x1Le3JyshEQEGBUqFDB6Nq16z2vn7gXM6Xwj506dUoDBgyQvb29Ro4cqYYNG0qSxo0bp2+++UY///zzk31rS2SbjNl5hmFo7NixatCggaQ/r+M2DENpaWkaO3asqlevrrp163LpFLLdiRMnNGjQIEnSyJEj1bhx40z9fAKLR9GBAwf00ksvKTw83HKzh/3792v8+PEKDw9XSEiIqlevrqtXr2rJkiVavHixSpcurapVq+rTTz/V0aNHVbFiRRsfBXJKxuynQ4cOqWPHjnr66afVq1cvtW3bVpLUpk0b/fzzz1q5cqVefPHFTK9xly5d0s2bN1WoUCEVK1bMVoeAXO7u2XuSFB4ersGDB+u3337T7t275ePjo5SUFDk5OSk+Pl6lSpXSl19+qQ4dOtiwajxJOnbsqISEBG3YsMHSlpaWph49emjZsmVq27atVq5cKScnJxtW+WhjTSn8Y+XKldPcuXNlGIYmT56s/fv365NPPtGnn36qVatWEUgh21SoUEFz5syRyWTSxIkTLeuZ2dvbKz09XcnJyRo7dqz++OMPtWvXjkAKOaJChQr6/PPPZTKZNHXqVP3yyy+Z+gmk8Kj55JNPdOjQIR07dkxeXl46cuSIJKlGjRqaMGGCateurVatWunQoUMqUqSIevTooQ8++EDJycnau3ev9u/fTyCVy9nZ2eno0aNq3LixXn/9dc2dO9cSSEnS+vXrVaNGDb377rvas2dPprueeXp6qkqVKgRSyDF3B1Lh4eGKjo5WrVq1NG/ePFWsWFE9e/ZUTEyM5Y/969evy83NTW5ubrYsG0+Q9PR01a1bV3FxcQoPD7e8Rjo4OKhhw4Z65plnlJ6eritXrti40kcbM6Xw0E6cOCE/Pz/t3btXN27c0O7du1WrVi1bl4Vc6H4zplJSUjR06FDNmzdP4eHh8vHxsXWZyOUyXvOuXbummTNnql69erYuCbjHxIkTNXPmTIWHh6ts2bK6dOmSSpUqpXfffVdz5syRdGfG1EcffaR9+/ZZZkylpqbK0dFR8fHxcnV1tfFRIKclJSWpW7duKlq0aKb1xFJTU3X+/Hnly5dPRYsWVevWrRUZGally5apXr16mWauADnh7kBq9OjR+vHHHzVmzBi1atVKzs7OOnjwoN5++23Z2dlpyJAhKly4sBYuXKgLFy4oPDycu+wh2xn/f+fHM2fOyDAMOTs7q2TJkvrjjz/UvHlzPf300xo7dqzq1KkjSfrggw9kMpk0evRoFShQwMbVP9p4R8FDq1ChgqZPn6569epp//79BFLIMf89Y+qnn37S2LFjFRQUpH379hFIwSoqVKigTz/9VF5eXizqi0dSUlKSfvvtN/Xr109ly5bVwYMHFRMTo8DAQAUFBenDDz+UdGfG1EcffaTatWvrlVdeUUREhBwdHSWJQOoJ4eDgoOjoaFWuXNnS9uOPP2r48OHy8fFRrVq19MYbb2jjxo2qWrWqXn75ZYWFhdmwYjwpMgKpjN/zJk2apGbNmsnFxUUmk0nPPvusli9fLicnJ73zzjvaunWr6tatq19//ZW77CFHmEwmrV69WvXr11fLli1Vp04drV+/XmXKlNHGjRt19OhRDR48WA0bNlT79u0VEBCgXr16EUg9AGZKIdtkfLoK5LSMmSq7du3S7du3tXv3btWsWdPWZeEJk7GGBfCoSUxMVOfOnZWSkqLGjRtr9OjRCgsLU7Vq1bR06VL17dtX77//vvz9/SVJERERGjJkiK5evar9+/fL0dHRctt15G5xcXF67rnn1LBhQw0dOlSrV6/W4sWLVa1aNTVq1Eiurq76+OOP1adPH40ZM0YtWrRQYGCgypcvb+vSkUvdPUPq999/V8eOHTV79my1bNlSN27c0MWLF7Vjxw499dRTatmypQ4ePKg+ffpIkn766SflzZtXycnJcnZ2tuVhIJfIiEpMJpMuXLigevXqacyYMSpZsqRCQkI0f/58BQcHq3v37jp//rx++OEH7du3T/ny5VO/fv309NNP2/gIHg+EUgAeS8eOHdPw4cM1ZcoUXvABPPEy/pC7+/K7MmXK6Pbt2xo2bJgmTpwo6U6YumzZsnuCqUOHDqlgwYKsB/kE2rZtm1q2bKmSJUsqJiZGn376qZo3b67y5csrNTVVbdu2VeHChfXtt9/aulTkcv+9qPm5c+fUtm1bffTRR/Lw8NDSpUu1a9cuJScnKzk5WZ988ok6deqkiIgIde7cWQULFtTmzZuVL18+Gx4FcoP/nmyxZcsWXbx4UYcPH7a8b6alpWn8+PHy9/dXcHCwunXrZhmfcTMmPBhWZQXwWKpUqZK+++47ZucBeOJl/CH3+++/a8GCBfr4448VGxurmJgYFSxYUIcPH9b+/ftVo0YNOTk56e2335YkDRgwQPHx8QoICFD16tVtfBSwlWbNmun06dO6cuWKSpcuLQ8PD0ufvb29ChQooHLlylkW8GU9KeSEn3/+WZLUuHFj9e3bV+7u7ho/frzc3NwsN1Ty9fXVtGnTVKNGDb3xxhu6fPmyJMnHx0f//ve/9dJLL+nVV1/V1q1bbXkoeMyNGjVK165d04IFCyTdCZ+WLFmib775JtOdlx0cHDRhwgRJUr9+/ZSWlqZevXpJ4nUyq5gpBQAA8JjKCKQOHDigWrVqacKECRo9erTS0tJ05swZ5c2bV/Xq1ZOPj48+/vhj1ahRQ9KdGVOLFi3S2LFjdejQIRUtWtTGR4JHTUpKiiZOnKjg4GD99NNP3NkWOcIwDMXHx6tOnToqVaqUChUqpJCQEG3btk01a9bUzZs3tWfPHuXPn1/169e3bFe/fn117txZgwYNsrQdPnxYLi4uKleunC0OBbnAr7/+KmdnZ9nb21vunGdnZ6fo6GhNmzZN8+fP18aNG9WsWTPLwudpaWkaNmyYli5dqlOnTil//vy2PozHDqEUAADAY+juQOr555/XkCFDNHnyZEt/xuUDkZGRatmypXx8fDRx4kTLTSFSUlKUmJjIIqy4xzfffKOwsDAtX75cGzdutISZQE65ceOGqlWrpsuXL2vBggWWGSd3S0hI0LVr19SvXz9FR0crLCxMDg4OlnAAeBgffPCBVqxYofDwcHl4eGjz5s1avHixvvzyS+XJk0fXrl3T0KFD9d133ykkJEQNGza0nHtms1kxMTEqUqSIrQ/jscS8MgAAgMeQnZ2djhw5orp162ro0KGZAqlly5bp9OnTMpvNqlq1qjZt2qSIiAhNmDBB+/btkyQ5OTkRSOEex44dU1BQkM6dO6ft27cTSCHHpaSk6OrVqypevLjKlSunVatWadu2bZb+tLQ0GYahBQsW6K233lJiYqL27t0rBwcHmc1mAik8tF9++UVBQUFatWqVPDw8dP36deXNm1fffvutBg0apMTERHl4eGjGjBnq0KGDWrVqpV27dslkMskwDNnb2xNIPQTWlAIAAHhMhYSEKDU1VbVr17a0+fv7a+TIkQoLC7PcGr1KlSravHmzatWqJRcXFy1atIi7U+G+KlWqpOXLl8vZ2ZnQEjnm7kXNnZycVLFiRYWHh+vChQtq3bq1/P39ZTKZ1LRpUzk43PmTdeDAgfL29la7du1kb2+vtLQ0Sx/wMFxcXOTl5aXY2FitXLlS3333nYKCgrR161a9+uqrSktL0/z581W4cGHNnDlTDg4OatiwoX755RfVq1fP1uU/9vi/GAAA4DH1/vvv69KlS3rjjTe0fv167d+/X9OnT9ePP/6oWrVqSZIlmKpcubL2798vk8lEIIW/xBpjyEl3B1JbtmxRVFSUSpQooQoVKqhcuXL67rvv1LFjR02fPl2pqalq0aKFGjZsqFdeeUUjRoyQdOfyZAIpZBdPT0+VLl1aI0eO1L59+7Ro0SK5urqqadOm+v777/Xqq69KkiWY8vf3l7OzswoWLGjbwnMJ1pQCAAB4DN29joqfn59mzZolBwcHbdy4Uc2bN79nPLeoBvAoGT58uJYtWyZnZ2c5ODgoISFBX3/9tRo3bqzjx4+rS5cuSk5OVkpKihwdHRUeHi4nJydbl41cJuO99JNPPtGIESNUvXp1zZo1S02bNrWM2bZtm1577TV16tRJn3/+ufLkyZMpXMXDIV4GAAB4jGT8An33OiozZsxQ/vz59fHHHysuLu6+2xFIAbC1jD/kv/76awUHB2vdunV6+umndeLECc2ZM0etWrXSli1b1KBBA61evVqbN29WQkKC+vfvLwcHBy7ZQ45JTEzU+PHjtX37dk2dOlXx8fF65ZVXJEnNmjXTDz/8oGbNmsnZ2VkBAQEEUtmImVIAAACPiYxAas+ePTpw4ICuX7+u559/Xo0bN5Z053K+efPm6euvv9abb75p42oB4I4ff/xRdevWlbu7u9LT0zVu3DgdO3ZMK1eutIyJjo7We++9pytXrmj16tVyd3fPtA9meyK7mM1m2dnZyWQyKSUlJdMMvGPHjql3797KmzevBg8erLZt21r6du7cqSJFiqhy5cq2KDvXIt4DAAB4TJhMJq1atUqtWrXStm3b9P3332vo0KF69913JUkzZ87UoEGD1KtXL3399dc2rhYApFu3bsnPz081a9bUzZs3ZWdnJ8MwFBERoYSEBMu44sWLq1WrVjp9+rSSk5Pv2Q+BFB5WZGSkEhMTZW9vL5PJpE2bNmnIkCHq2bOn9u7dq7i4OFWqVEnBwcFKSEjQnDlztH79esv2DRs2JJDKAYRSAAAAj7D09HTL95GRkXr//fc1bdo0/fvf/1ZQUJAiIyMzzSiYPn26unTpog8++EC3bt2yRckAYOHm5qaVK1eqSJEiql+/vm7cuKHWrVvL2dlZwcHBio2NtYytUKGC3NzcdPv2bRtWjNzou+++U8uWLbV69WpJ0o4dO9SmTRvFxsZq586d6tq1q7766itdv35dFStWVHBwsFJSUvTxxx/rxx9/tHH1uRuX7wEAADyC1q1bJx8fH3l5eVkuWwkJCdHo0aMVHh6uM2fOqGnTpmrZsqW++OILSdJvv/2mmjVrSpKuXLnCXdQA2FTGGlJpaWm6cOGC3njjDTk7O2vdunWaOHGitmzZog4dOujNN9+Uk5OT3n33XaWlpWnz5s2Z1s0DHpZhGHr11Vd17tw5jRw5Unv27FGFChUsM40HDBigXbt2qXv37urevbsKFy6sI0eOyM/PT1988YVKlSpl4yPIvZgpBQAA8IgJDw/XiBEjNGLECF26dMly2YrJZJKnp6f++OMPNWrUSC1bttS8efMkSbt27dKKFSt07tw5SSKQAmAz169flyTZ2dkpJSVFDg4OKl26tAoXLqxdu3bp5Zdf1tixY/Xqq6/qP//5j6pUqaJ27drp+vXr2rhxo0wmU6ZZosDDSElJkclk0g8//KCyZcvK399fP//8s7y9vS1j5s2bpxdeeEGLFi3S119/ratXr6pKlSr6/vvvCaRyGKEUAADAI6ZWrVp65513LJ/oXrp0SZJUtmxZbdu2TU899ZRef/11ffHFF5bAasWKFYqIiJCrq6stSwfwhNu5c6c6duyoHTt2SJJlEek33nhDFy5c0ObNm3X79m21bNlSfn5+2rFjh9avX6/AwED9+uuvcnR0VFpaGnc3w0O5O9TMOAcTEhK0Zs0aPf3009q/f7/Cw8OVkpJiGRcQEKCmTZtq+vTpWrFihdLT07nboxXwfzoAAMAjxGw2S5IGDx6sN954QydOnNCIESN07tw5VaxYUYsXL1aePHnk5uamkydPKjIyUsOHD9eSJUs0ffr0e+5YBQDWVLRoURmGIX9/f4WHh0uSOnbsqCNHjmj9+vVq3ry5li1bpuTkZDVp0kSJiYlq3bq16tevL3t7e5nNZoIAPDQ7OzudPHlS48ePl3RnTalWrVopNjZWX3/9tTp27Kjly5dr1apVSkpKsmw3e/Zsde7cWa1bt7bcoQ85izWlAAAAHiGGYWT6JXjevHn69ttvVa5cOU2dOlUlSpTQggULNHToUBUsWFD58+eXg4ODFi1apBo1atiwcgC448SJExo8eLDs7e0VGxur27dva/Xq1SpTpoxlzNGjR/Xiiy+qUaNGWrp0qe2KRa6Unp6u4OBg9evXT+3atdOaNWu0aNEidevWzTKmffv2OnXqlEaMGKHXX39dLi4uNqz4yUUoBQAA8IjICKS2b9+uo0eP6l//+pdcXV01d+5cLVu2TBUqVNDUqVPl6empM2fO6Ny5c3Jzc5OXl5eKFCli6/IBwOLEiRMaMGCAwsLC9OWXX+qNN96Q9Ofi55J09uxZeXl5WS5DBrKT2WxWv379FBwcrJdfflnr1q2TJCUlJVkCqPbt2+vs2bMaNGiQOnfuLGdnZ1uW/ETi8j0AAIBHhMlk0qpVq9S+fXudOHFCFy5ckCQNHDhQb7/9tuVSvvPnz6ts2bJq1KiRatSoQSAF4JFToUIFBQYGql69evrqq68UGhoq6c5lVRnr/ZQuXdpyyR6QE4oXL67OnTtrz549GjZsmCTJxcVFiYmJkqQ1a9bIw8NDCxYsUHJysi1LfWIxUwoAAOARsX//frVq1Ur+/v7q3r37PWtZzJ07VytXrlThwoU1b948FS9e3EaVAsCDybiUT5LGjBmjBg0a2LgiPGlu3bqlJUuWaNy4cerZs6emT59u6bty5YqKFi2qCxcuqGTJkjas8snFTCkAAAAb2Lt37z1tJ06cULly5dSuXTvLzIG77yA0cOBAvfrqq0pISOB26QAeCxUqVNCcOXNkb2+vIUOG6ODBg7YuCblUxnybw4cPa8OGDdqwYYOSk5Pl5uamTp06aeLEiVq0aJGGDh0qSRo/frzeeustxcfHE0jZEDOlAAAArCwkJERvv/22Tp8+nelueRMnTtS8efN06dIlSXfWw8hYa+XAgQMqX7688uXLpxs3bnCXPQCPlSNHjmjhwoX69NNPLWtKAdklY03GNWvWaOjQoXJwcFC+fPlkMpm0efNmFS5cWNevX9fq1as1ZMgQlS5dWtHR0dq0aZNq165t6/KfaIRSAAAANhAdHa3ixYtnumRg7969euuttzRkyBANGjRIJpNJZrNZZrNZ/fv3V8OGDdWzZ08bVw4AD+fuxc6Bf+J+59C2bdvUrl07ffbZZ+rdu7e2bt2qli1bqlKlStq8ebO8vLyUlJSk06dPa/fu3WrWrJnKli1royNABkIpAAAAK8r4NFeSTp06pQoVKmj+/Pnq16+fYmJiNGjQIF26dElt2rTR0KFDdeHCBS1YsEALFizQzz//rIoVK9r4CAAAsJ2MQOrChQsKDQ2V2WyWp6enduzYIScnJ40cOVIXL15U/fr19cILL+jEiRO6ceOGduzYIU9PT1uXj/9CKAUAAJDDMn6BTktLk4ODgyTp8uXLKlasmEaOHKnZs2fr888/V+/evXXu3DlNnjxZW7Zs0bVr11S2bFldvXpVP/zwg2rUqGHjIwEAwHYy3k8PHjyo9u3by8XFRcePH9fTTz+tatWqaeLEiSpYsKCaN2+uunXrKjAwUCtWrNBbb72lYsWKKTw8XCVKlLD1YeAuDrYuAAAAILezs7NTVFSUPvvsM82ePVurV6/WqFGjtG3bNk2dOlXOzs7q16+fDMNQnz599Mknn+jatWvatGmTypQpo6pVq6pUqVK2PgwAAGzm7kCqfv36GjhwoN577z2Fh4dr7ty5On78uBwcHPTLL78oT548GjFihCTJw8NDbdq0kb29vW7fvm3jo8B/I5QCAACwgnXr1ik0NFQtW7bU9u3bFRQUZPm09qOPPpIk9e/fXyaTSb1791b+/PnVv39/G1YMAMCjw87OTufOnVPz5s3Vpk0b+fv7S5JKlCihS5cuyc/PT0lJSYqOjtaBAwfk5eUlSdq6dauKFCmi+fPny9nZ2ZaHgPsglAIAAMhBGWtIDRgwQIcPH9b8+fPVuHFjderUSdKfd9jLCKYGDRqklJQUvfvuuzasGgCAR4/ZbFbZsmWVnJys0NBQvfDCC5KksmXLysXFRampqWrdurVmzJghLy8vVa9eXbt379bu3bsJpB5RrCkFAACQgzJCqU2bNmnZsmVydHTUsWPHVL58eU2dOlVFixbNtNbUiBEjtHDhQp06dUoFChSwcfUAADxaTpw4ocGDBys9PV2zZs2St7e3nnrqKfXs2VP+/v4yDENHjhzRokWLZGdnp+7du6tKlSq2Lhv/A6EUAABADtu5c6caN26sf//733rzzTc1Y8YMrVq1SpUrV9a0adNUpEgRSXfuxleuXDldu3ZNHh4eNq4aAIBH04kTJ/Tee+8pISFBBw8eVPfu3TVz5sxMd7iV/lyHCo8u/usAAADkoOPHj+vq1av65JNP9Oabb0qS/Pz81LFjRx07dkwffvihoqKiNH78eLVr1063bt0ikAIA4C9UqFBBs2fPlr29vfLnz6/27dtLkkwmkwzDUMbcGwKpRx9rSgEAAOSQc+fOqUGDBrp9+7ZlzaiUlBQ5OTnp/fffl6Ojo77++ms9//zzkqRVq1bJzc3NhhUDAPB4qFChgr744gsNGjRIU6ZMkb29vRo0aJBpphQefVy+BwAAkENu3LihJUuW6NNPP1WjRo307bffSvozmJKk33//XVFRUXr66adVunRpW5YLAMBj58SJE/Lz89O1a9c0c+ZM1atXz9YlIQsIpQAAAHLQ1atXtXLlSg0bNkwDBgzQ9OnTJUmpqalydHS0cXUAADz+jh49qrFjx+qzzz5TqVKlbF0OsoBQCgAAIBtkLK56+PBhRUVFKT09XS1atJCzs7OuX7+u5cuXa9y4cerZs6c+/fRTSXdubW1vb2/jygEAePzdPQsZjw9CKQAAgIeUEUitWbNGQ4cOlYODg/LlyyeTyaTNmzercOHClmDq448/1uuvv6558+bZumwAAACbYil6AACALEpPT8/02GQyadu2berevbtGjhypo0eP6pNPPlFERIReeOEFnT9/XoULF9Zbb72lDz74QD/++KOuXLkiPhsEAABPMmZKAQAAZEF6errs7Ox04cIFhYaGymw2y9PTUzt27JCTk5NGjhypixcvqn79+nrhhRd04sQJ3bhxQz///LNKlCihmJgYmUwmubu72/pQAAAAbIpQCgAA4AFlBFIHDx5U+/bt5eLiouPHj+vpp59WtWrVNHHiRBUsWFDNmzdX3bp1FRgYqBUrVuitt95S0aJF9dtvv6lEiRK2PgwAAIBHApfvAQAAPIC7A6n69eurY8eO2rx5s1avXq1ixYrp+PHjcnBw0C+//KI8efJoxIgRkiQPDw+1adNG9erV0+3bt218FAAAAI8OB1sXAAAA8Diws7PTuXPn1Lx5c7Vp00b+/v6SpBIlSujSpUvy8/NTUlKSoqOjdeDAAXl5eUmStm7dqiJFimj+/Plydna25SEAAAA8UpgpBQAA8IDMZrPKli2r5ORkhYaGWtrLli0rFxcXpaamqnXr1ipdurS8vLz04osvavbs2Xr//fcJpAAAAP4La0oBAABkwYkTJzR48GClp6dr1qxZ8vb21lNPPaWePXvK399fhmHoyJEjWrRokezs7NS9e3dVqVLF1mUDAAA8cgilAAAAsujEiRN67733lJCQoIMHD6p79+6aOXOmDMOQyWSyjMtYhwoAAAD34rckAACALKpQoYJmz54te3t75c+fX+3bt5ckmUwmGYahjM/8CKQAAAD+N2ZKAQAA/EMnT57UoEGDZBiGxo4dqwYNGti6JAAAgMcGH98BAAD8Q+XLl9ecOXPk6OioYcOG6ddff7V1SQAAAI8NQikAAICHUKFCBX366afy8vJSiRIlbF0OAADAY4PL9wAAALJBSkqKnJycbF0GAADAY4NQCgAAAAAAAFbH5XsAAAAAAACwOkIpAAAAAAAAWB2hFAAAAAAAAKyOUAoAAAAAAABWRygFAAAAAAAAqyOUAgAAAAAAgNURSgEAADwGfvrpJ5lMJt28edPWpVj06NFD7dq1s3UZAADgMUUoBQAA8Dd69Oghk8lk+SpcuLBatWqlgwcP2ro0AACAxxahFAAAwANo1aqVLl26pEuXLmnr1q1ycHBQ27ZtbV2WTZjNZqWnp9u6DAAA8JgjlAIAAHgAzs7OKl68uIoXLy4fHx+NGDFC586d09WrVyVJ586d05tvvqmCBQuqUKFCeu211/THH39Yts+41G369Ony9PRU4cKF5evrq9TUVMuY5ORkffjhh/L29pazs7PKly+voKCgTHWEh4erdu3ayps3r55//nkdO3bM0vfRRx/Jx8dHwcHBKlWqlFxdXTVgwACZzWZ98sknKl68uIoWLarJkydn2ueMGTNUvXp15cuXT97e3howYIDi4+Mt/YsWLVLBggX1/fffq2rVqnJ2dlZUVNQ9P6OwsDAVKVJE/v7+D/WzBgAATwZCKQAAgCyKj4/XN998o/Lly6tw4cJKTU1Vy5Yt5ebmpp07d2rXrl1ydXVVq1atlJKSYtlu+/btOnXqlLZv367Fixdr0aJFWrRokaW/W7duWrZsmebMmaMjR47oiy++kKura6bnHj16tD777DPt27dPDg4O6tWrV6b+U6dOaePGjQoJCdGyZcsUFBSkNm3a6Pz58/r555/l7++vMWPGaM+ePZZt7OzsNGfOHB0+fFiLFy/Wtm3bNHz48Ez7TUhIkL+/vxYuXKjDhw+raNGimfq3bdumF198UZMnT9aHH374sD9iAADwBHCwdQEAAACPg3Xr1lkCotu3b8vT01Pr1q2TnZ2dvv32W6Wnp2vhwoUymUySpK+++koFCxbUTz/9pJdeekmS5O7urrlz58re3l6VK1dWmzZttHXrVvXt21fHjx/XihUrtHnzZrVo0UKS9NRTT91Tx+TJk9W4cWNJ0ogRI9SmTRslJSXJxcVFkpSenq7g4GC5ubmpatWqatq0qY4dO6YNGzbIzs5OlSpVkr+/v7Zv367nnntOkjRkyBDL/suUKaNJkyapf//+mjdvnqU9NTVV8+bN07PPPntPTWvWrFG3bt20cOFCderU6WF/1AAA4AlBKAUAAPAAmjZtqvnz50uSbty4oXnz5ql169bau3evDhw4oJMnT8rNzS3TNklJSTp16pTl8dNPPy17e3vLY09PTx06dEiSFBERIXt7e0vg9L8888wzmbaXpCtXrqhUqVKS7oRKd9dRrFgx2dvby87OLlPblStXLI+3bNmiqVOn6ujRo4qLi1NaWpqSkpKUkJCgvHnzSpKcnJwyPXeGPXv2aN26dfruu++4Ex8AAMgSQikAAIAHkC9fPpUvX97yeOHChSpQoIC+/PJLxcfHq1atWlq6dOk92xUpUsTyvaOjY6Y+k8lkWTA8T548D1TH3fvImJV196Lj93uOv3reP/74Q23bttW7776ryZMnq1ChQgoNDVXv3r2VkpJiCaXy5Mljeb67lStXToULF1ZwcLDatGlzz3MBAAD8L6wpBQAA8A+YTCbZ2dkpMTFRNWvW1IkTJ1S0aFGVL18+01eBAgUeaH/Vq1dXenq6fv755xyuPLPw8HClp6frs88+U7169VSxYkVdvHjxgbf38PDQtm3bdPLkSb355puZFm4HAAD4K4RSAAAADyA5OVnR0dGKjo7WkSNHNGjQIMXHx+uVV15Rly5d5OHhoddee007d+7UmTNn9NNPP2nw4ME6f/78A+2/TJky6t69u3r16qW1a9da9rFixYocPa7y5csrNTVVn3/+uU6fPq2vv/5agYGBWdpH0aJFtW3bNh09elRvv/220tLScqhaAACQmxBKAQAAPICQkBB5enrK09NTzz33nMLCwrRy5Uo1adJEefPm1Y4dO1SqVCm9/vrrqlKlinr37q2kpCTlz5//gZ9j/vz56tixowYMGKDKlSurb9++un37dg4elfTss89qxowZ8vf3V7Vq1bR06VJNnTo1y/spXry4tm3bpkOHDqlLly4ym805UC0AAMhNTIZhGLYuAgAAAAAAAE8WZkoBAAAAAADA6gilAAAAAAAAYHWEUgAAAAAAALA6QikAAAAAAABYHaEUAAAAAAAArI5QCgAAAAAAAFZHKAUAAAAAAACrI5QCAAAAAACA1RFKAQAAAAAAwOoIpQAAAAAAAGB1hFIAAAAAAACwOkIpAAAAAAAAWN3/AdvAXetrRQHcAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Creating a dictionary to store the data\n",
    "data = {\n",
    "    'Algorithm': ['Bfs', 'Lud', 'Nw', 'ParticleFfilter', 'Srad', 'Hotspot', 'Pathfinder'],\n",
    "    'Java': [1.8844, 1.434, 0.1560, 0.1846, 0.5220, 79.4314, 0.0062],\n",
    "    'TornadoVM': [1.1482, 10.5903, 8.5883, 0.9217, 31.0169, 58.5059, 0.7790],\n",
    "    'OpenMP': [0.2191, 29.9380, 0.0050, 0.0139, 0.0287, 2.897, 0.0041]\n",
    "}\n",
    "\n",
    "# Converting the dictionary into a DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Setting the 'Algorithm' column as the index\n",
    "df.set_index('Algorithm', inplace=True)\n",
    "\n",
    "# Plotting the data with a logarithmic scale for y-axis\n",
    "ax = df.plot(kind='bar', figsize=(12, 8), rot=45, logy=True, color=['#1f77b4', '#ff7f0e', '#2ca02c'])\n",
    "ax.set_ylabel('Execution Time (seconds) [log scale]')\n",
    "ax.set_xlabel('Benchmark')\n",
    "# ax.set_title('Execution Time Comparison Among Java, TornadoVM, and OpenMP')\n",
    "\n",
    "# Adding text labels above the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f\"{p.get_height():.4f}\", (p.get_x() + p.get_width() / 2., p.get_height()), \n",
    "                ha='center', va='center', fontsize=9, color='black', rotation=0, xytext=(0, 5),\n",
    "                textcoords='offset points')\n",
    "\n",
    "plt.legend(title='Implementation')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Creating a dictionary to store the data\n",
    "data = {\n",
    "    'Algorithm': ['Bfs', 'Hotspot'],\n",
    "    'Java': [1.8844, 79.4314],\n",
    "    'TornadoVM': [1.1482, 58.5059],\n",
    "    'OpenMP': [0.2191, 2.897]\n",
    "}\n",
    "\n",
    "# Converting the dictionary into a DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Setting the 'Algorithm' column as the index\n",
    "df.set_index('Algorithm', inplace=True)\n",
    "\n",
    "# Plotting the data with a logarithmic scale for y-axis\n",
    "ax = df.plot(kind='bar', figsize=(6, 6), rot=45, logy=True, color=['#1f77b4', '#ff7f0e', '#2ca02c'])\n",
    "ax.set_ylabel('Execution Time (seconds) [log scale]')\n",
    "ax.set_xlabel('Benchmark')\n",
    "ax.set_title('Execution Time Comparison Among Java, TornadoVM, and OpenMP')\n",
    "\n",
    "# Adding text labels above the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f\"{p.get_height():.4f}\", (p.get_x() + p.get_width() / 2., p.get_height()), \n",
    "                ha='center', va='center', fontsize=9, color='black', rotation=0, xytext=(0, 5),\n",
    "                textcoords='offset points')\n",
    "\n",
    "plt.legend(title='Implementation')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a dictionary to store the data\n",
    "data = {\n",
    "    'Algorithm': [ 'Lud', 'Nw', 'ParticleFfilter', 'Srad', 'Pathfinder'],\n",
    "    'Java': [ 1.434, 0.1560, 0.1846, 0.5220,  0.0062],\n",
    "    'TornadoVM': [10.5903, 8.5883, 0.9217, 31.0169,  0.7790],\n",
    "    'OpenMP': [29.9380, 0.0050, 0.0139, 0.0287, 0.0041]\n",
    "}\n",
    "\n",
    "# Converting the dictionary into a DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Setting the 'Algorithm' column as the index\n",
    "df.set_index('Algorithm', inplace=True)\n",
    "\n",
    "# Plotting the data with a logarithmic scale for y-axis\n",
    "ax = df.plot(kind='bar', figsize=(12, 8), rot=45, logy=True, color=['#1f77b4', '#ff7f0e', '#2ca02c'])\n",
    "ax.set_ylabel('Execution Time (seconds) [log scale]')\n",
    "ax.set_xlabel('Benchmark')\n",
    "ax.set_title('Execution Time Comparison Among Java, TornadoVM, and OpenMP')\n",
    "\n",
    "# Adding text labels above the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f\"{p.get_height():.4f}\", (p.get_x() + p.get_width() / 2., p.get_height()), \n",
    "                ha='center', va='center', fontsize=9, color='black', rotation=0, xytext=(0, 5),\n",
    "                textcoords='offset points')\n",
    "\n",
    "plt.legend(title='Implementation')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data sizes and execution times\n",
    "data_sizes = ['16M', '8M', '4M', '2M', '1M', '512K', '256K', '128K']\n",
    "java_times = [1.8844, 0.8122, 0.3407, 0.1344, 0.0820, 0.0359, 0.0173, 0.0084]\n",
    "tornado_times = [1.1482, 0.6072, 0.3798, 0.2488, 0.1774, 0.1419, 0.1333, 0.1255]\n",
    "openmp_times = [0.2191, 0.0426, 0.0149, 0.0066, 0.0032, 0.0017, 0.0012, 0.0001]\n",
    "\n",
    "# Creating a DataFrame\n",
    "df = pd.DataFrame({\n",
    "    'Data Size': data_sizes,\n",
    "    'Java': java_times,\n",
    "    'TornadoVM': tornado_times,\n",
    "    'OpenMP': openmp_times\n",
    "})\n",
    "\n",
    "# Setting the 'Data Size' column as the index\n",
    "df.set_index('Data Size', inplace=True)\n",
    "\n",
    "# Plotting the data\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(df['Java'], label='Java', marker='o')\n",
    "plt.plot(df['TornadoVM'], label='TornadoVM', marker='s')\n",
    "plt.plot(df['OpenMP'], label='OpenMP', marker='^')\n",
    "\n",
    "# Adding labels and title\n",
    "plt.xlabel('Data Size')\n",
    "plt.ylabel('Execution Time (seconds)')\n",
    "# plt.title('Execution Time for BFS Algorithm Across Different Data Sizes')\n",
    "plt.legend()\n",
    "\n",
    "# Inverting x-axis to show larger datasets on the left\n",
    "plt.gca().invert_xaxis()\n",
    "\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import matplotlib.pyplot as plt\n",
    "# import numpy as np\n",
    "\n",
    "# # Data for RTX 4090\n",
    "# algorithms_4090 = ['bfs', 'lud', 'nw', 'particlefilter', 'srad', 'hotspot', 'pathfinder']\n",
    "# execution_time_4090_java = [0.0084, 1.434, 0.1560, 0.1846, 0.5220, 79.4314, 0.0062]\n",
    "# execution_time_4090_tornado = [0.1255, 10.5903, 8.5883, 0.9217, 31.0169, 58.5059, 0.7790]\n",
    "# execution_time_4090_openmp = [0.0001, 29.9380, 0.0050, 0.0139, 0.0287, 2.897, 0.0041]\n",
    "\n",
    "# # Data for QUADRO GP100\n",
    "# algorithms_gp100 = ['bfs', 'lud', 'nw', 'particlefilter', 'srad', 'hotspot', 'pathfinder']\n",
    "# execution_time_gp100_java = [2.308, 0.203, 0.376, 3.076, 0.00857, 0.00755, 0.0535, 0.206]\n",
    "# execution_time_gp100_tornado = [3.167, 16.851, 2.234, 57.393, 0.851, 1.025, 8.694, 22.235]\n",
    "# execution_time_gp100_openmp = [0.722, 0.044, 0.141, 116.546, 0.00156, 0.00132, 0.007, 0.00176]\n",
    "\n",
    "# # Creating bar chart\n",
    "# fig, ax = plt.subplots(figsize=(14, 8))\n",
    "# width = 0.25  # width of the bars\n",
    "\n",
    "# # Bars for RTX 4090\n",
    "# java_bars_4090 = ax.bar(np.arange(len(algorithms_4090)) - width, execution_time_4090_java, width, label='Java (RTX 4090)')\n",
    "# tornado_bars_4090 = ax.bar(np.arange(len(algorithms_4090)), execution_time_4090_tornado, width, label='Tornado (RTX 4090)')\n",
    "# openmp_bars_4090 = ax.bar(np.arange(len(algorithms_4090)) + width, execution_time_4090_openmp, width, label='OpenMP (RTX 4090)')\n",
    "\n",
    "# # Bars for QUADRO GP100\n",
    "# java_bars_gp100 = ax.bar(np.arange(len(algorithms_gp100)) - width, execution_time_gp100_java, width, label='Java (QUADRO GP100)', color='lightblue')\n",
    "# tornado_bars_gp100 = ax.bar(np.arange(len(algorithms_gp100)), execution_time_gp100_tornado, width, label='Tornado (QUADRO GP100)', color='orange')\n",
    "# openmp_bars_gp100 = ax.bar(np.arange(len(algorithms_gp100)) + width, execution_time_gp100_openmp, width, label='OpenMP (QUADRO GP100)', color='lightgreen')\n",
    "\n",
    "# ax.set_xlabel('Algorithm')\n",
    "# ax.set_ylabel('Execution Time (s)')\n",
    "# ax.set_title('Execution Time Comparison Between RTX 4090 and QUADRO GP100')\n",
    "# ax.set_xticks(np.arange(len(algorithms_4090 + algorithms_gp100)))\n",
    "# ax.set_xticklabels(algorithms_4090 + algorithms_gp100, rotation=45)\n",
    "# ax.legend()\n",
    "\n",
    "# plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Data for RTX 4090\n",
    "algorithms_4090 = ['bfs', 'lud', 'nw', 'particlefilter', 'srad', 'hotspot', 'pathfinder']\n",
    "execution_time_4090_tornado = [1.1482, 10.5903, 8.5883, 0.9217, 31.0169, 58.5059, 0.7790]\n",
    "\n",
    "# Data for QUADRO GP100\n",
    "algorithms_gp100 = ['bfs', 'lud', 'nw', 'particlefilter', 'srad', 'hotspot', 'pathfinder']\n",
    "execution_time_gp100_tornado = [3.5172, 57.3933, 38.6942, 2.234, 44.3431, 122.3213, 2.0133]\n",
    "\n",
    "# Creating bar chart\n",
    "fig, ax = plt.subplots(figsize=(14, 8))\n",
    "width = 0.35  # width of the bars\n",
    "\n",
    "indices = np.arange(len(algorithms_4090))  # the x locations for the groups\n",
    "\n",
    "# Bars for RTX 4090\n",
    "tornado_bars_4090 = ax.bar(indices - width/2, execution_time_4090_tornado, width, label='TornadoVM (RTX 4090)')\n",
    "\n",
    "# Bars for QUADRO GP100\n",
    "tornado_bars_gp100 = ax.bar(indices + width/2, execution_time_gp100_tornado, width, label='TornadoVM (QUADRO GP100)', color='orange')\n",
    "\n",
    "# Annotate each bar with its y-value above the bar\n",
    "for bar in tornado_bars_4090:\n",
    "    yval = bar.get_height()\n",
    "    ax.text(bar.get_x() + bar.get_width()/2, yval, f'{yval:.2f}', ha='center', va='bottom')\n",
    "\n",
    "for bar in tornado_bars_gp100:\n",
    "    yval = bar.get_height()\n",
    "    ax.text(bar.get_x() + bar.get_width()/2, yval, f'{yval:.2f}', ha='center', va='bottom')\n",
    "\n",
    "ax.set_xlabel('Benchmark')\n",
    "ax.set_ylabel('Execution Time (s)')\n",
    "# ax.set_title('Execution Time Comparison Between RTX 4090 and QUADRO GP100')\n",
    "ax.set_xticks(indices)\n",
    "ax.set_xticklabels(algorithms_4090, rotation=45)\n",
    "ax.legend()\n",
    "\n",
    "plt.show()\n"
   ]
  }
 ],
 "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}