plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Benchmark', 'Cycles_4GHz_cryocache', 'Instructions_4GHz_cryocache',\n",
      "       'IPC_4GHz_cryocache', 'Seconds_4GHz_cryocache',\n",
      "       'l1dAccesses_4GHz_cryocache', 'l1iAccesses_4GHz_cryocache',\n",
      "       'l2Accesses_4GHz_cryocache', 'l3Accesses_4GHz_cryocache',\n",
      "       'Frequency_4GHz_cryocache',\n",
      "       ...\n",
      "       'Frequency_50GHz_superl1l2l3', 'Cycles_100GHz_superl1l2l3',\n",
      "       'Instructions_100GHz_superl1l2l3', 'IPC_100GHz_superl1l2l3',\n",
      "       'Seconds_100GHz_superl1l2l3', 'l1dAccesses_100GHz_superl1l2l3',\n",
      "       'l1iAccesses_100GHz_superl1l2l3', 'l2Accesses_100GHz_superl1l2l3',\n",
      "       'l3Accesses_100GHz_superl1l2l3', 'Frequency_100GHz_superl1l2l3'],\n",
      "      dtype='object', length=181)\n"
     ]
    }
   ],
   "source": [
    "# data folders\n",
    "superconductingcorecryocache = \"superconductingcorecryocache/data/\"\n",
    "superconductingcorel1_cryol2l3 = \"superconductingcorel1_cryol2l3/data/\"\n",
    "superconductingcorel1l2_cryol3 = \"superconductingcorel1l2_cryol3/data/\"\n",
    "superconductingcorel1l2l3 = \"superconductingcorel1l2l3/data/\"\n",
    "\n",
    "def extract_data(folder, suffix=\"\", data=None):\n",
    "    for freq in [\"4GHz\", \"10GHz\", \"20GHz\", \"50GHz\", \"100GHz\"]:\n",
    "        df = pd.read_csv(folder + freq + \".csv\")\n",
    "        df[\"Frequency\"] = freq\n",
    "        df.rename(columns={'Unnamed: 0': 'Benchmark'}, inplace=True)\n",
    "        df.rename(columns=lambda col: f'{col}_{freq}_{suffix}' if col != \"Benchmark\" else col, inplace=True)\n",
    "        if data is None:\n",
    "            data = df\n",
    "        else:\n",
    "            data = data.merge(df, how=\"outer\", on=\"Benchmark\")\n",
    "    return data\n",
    "\n",
    "superconductingcorecryocache_data = extract_data(superconductingcorecryocache, \"cryocache\")\n",
    "superconductingcorel1_cryol2l3_data = extract_data(superconductingcorel1_cryol2l3, \"cryol2l3\")\n",
    "superconductingcorel1l2_cryol3_data = extract_data(superconductingcorel1l2_cryol3, \"cryol3\")\n",
    "superconductingcorel1l2l3_data = extract_data(superconductingcorel1l2l3, \"superl1l2l3\")\n",
    "\n",
    "data = superconductingcorecryocache_data.merge(superconductingcorel1_cryol2l3_data, how=\"outer\", on=\"Benchmark\")\n",
    "data = data.merge(superconductingcorel1l2_cryol3_data, how=\"outer\", on=\"Benchmark\")\n",
    "data = data.merge(superconductingcorel1l2l3_data, how=\"outer\", on=\"Benchmark\")\n",
    "\n",
    "print(data.columns)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate the speedup for each benchmark and frequency\n",
    "\n",
    "data[\"Speedup_10GHz_cryocache\"] = data[\"Seconds_4GHz_cryocache\"] / data[\"Seconds_10GHz_cryocache\"]\n",
    "data[\"Speedup_20GHz_cryocache\"] = data[\"Seconds_4GHz_cryocache\"] / data[\"Seconds_20GHz_cryocache\"]\n",
    "data[\"Speedup_50GHz_cryocache\"] = data[\"Seconds_4GHz_cryocache\"] / data[\"Seconds_50GHz_cryocache\"]\n",
    "data[\"Speedup_100GHz_cryocache\"] = data[\"Seconds_4GHz_cryocache\"] / data[\"Seconds_100GHz_cryocache\"]\n",
    "\n",
    "data[\"Speedup_10GHz_cryol2l3\"] = data[\"Seconds_4GHz_cryol2l3\"] / data[\"Seconds_10GHz_cryol2l3\"]\n",
    "data[\"Speedup_20GHz_cryol2l3\"] = data[\"Seconds_4GHz_cryol2l3\"] / data[\"Seconds_20GHz_cryol2l3\"]\n",
    "data[\"Speedup_50GHz_cryol2l3\"] = data[\"Seconds_4GHz_cryol2l3\"] / data[\"Seconds_50GHz_cryol2l3\"]\n",
    "data[\"Speedup_100GHz_cryol2l3\"] = data[\"Seconds_4GHz_cryol2l3\"] / data[\"Seconds_100GHz_cryol2l3\"]\n",
    "\n",
    "data[\"Speedup_10GHz_cryol3\"] = data[\"Seconds_4GHz_cryol3\"] / data[\"Seconds_10GHz_cryol3\"]\n",
    "data[\"Speedup_20GHz_cryol3\"] = data[\"Seconds_4GHz_cryol3\"] / data[\"Seconds_20GHz_cryol3\"]\n",
    "data[\"Speedup_50GHz_cryol3\"] = data[\"Seconds_4GHz_cryol3\"] / data[\"Seconds_50GHz_cryol3\"]\n",
    "data[\"Speedup_100GHz_cryol3\"] = data[\"Seconds_4GHz_cryol3\"] / data[\"Seconds_100GHz_cryol3\"]\n",
    "\n",
    "data[\"Speedup_10GHz_superl1l2l3\"] = data[\"Seconds_4GHz_superl1l2l3\"] / data[\"Seconds_10GHz_superl1l2l3\"]\n",
    "data[\"Speedup_20GHz_superl1l2l3\"] = data[\"Seconds_4GHz_superl1l2l3\"] / data[\"Seconds_20GHz_superl1l2l3\"]\n",
    "data[\"Speedup_50GHz_superl1l2l3\"] = data[\"Seconds_4GHz_superl1l2l3\"] / data[\"Seconds_50GHz_superl1l2l3\"]\n",
    "data[\"Speedup_100GHz_superl1l2l3\"] = data[\"Seconds_4GHz_superl1l2l3\"] / data[\"Seconds_100GHz_superl1l2l3\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract relevant columns for plotting\n",
    "speedup_columns = [col for col in data.columns if col.startswith(\"Speedup\")]\n",
    "\n",
    "# # frequency on the x-axis, speedup on the y-axis, different bars for different suffixes of configurations\n",
    "# for benchmark in data[\"Benchmark\"].unique():\n",
    "#     benchmark_data = data[data[\"Benchmark\"] == benchmark]\n",
    "#     benchmark_data = benchmark_data[speedup_columns]\n",
    "#     benchmark_data = benchmark_data.T\n",
    "#     benchmark_data.plot(kind=\"bar\")\n",
    "#     plt.title(benchmark)\n",
    "#     plt.show()\n",
    "#     plt.close()\n",
    "\n",
    "# I want to see how speedup of 100 GHz over 4 GHz changes with different configurations\n",
    "speedup_100GHz_over_4GHz = [col for col in speedup_columns if \"100GHz\" in col]\n",
    "speedup_100GHz_over_4GHz = data[speedup_100GHz_over_4GHz]\n",
    "speedup_100GHz_over_4GHz = speedup_100GHz_over_4GHz.T\n",
    "speedup_100GHz_over_4GHz.plot(kind=\"bar\")\n",
    "# legend labels, they are actually the Benchmark names\n",
    "plt.legend(data[\"Benchmark\"].unique())\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylabel(\"Speedup\")\n",
    "plt.xlabel(\"Configuration\")\n",
    "plt.title(\"Speedup of 100 GHz over 4 GHz\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "# xticklabelmap = {\n",
    "#     \"Speedup_100GHz_cryocache\": \"Super Core + CryoCache\",\n",
    "#     \"Speedup_100GHz_cryol2l3\": \"Super Core L1 + Cryo L2L3\",\n",
    "#     \"Speedup_100GHz_cryol3\": \"Super Core L1L2 + Cryo L3\",\n",
    "#     \"Speedup_100GHz_superl1l2l3\": \"Super Core Cache\"\n",
    "# }\n",
    "\n",
    "# average_speedup_per_suffix = {}\n",
    "# for suffix in data.columns:\n",
    "#     if suffix.startswith(\"Speedup\") and \"100GHz\" in suffix:\n",
    "#         suffix_speedup = data[suffix]\n",
    "#         average_speedup_per_suffix[suffix] = suffix_speedup.mean()\n",
    "\n",
    "# # Plotting the average speedup per suffix\n",
    "# plt.bar(average_speedup_per_suffix.keys(), average_speedup_per_suffix.values())\n",
    "# plt.xticks(rotation=45)\n",
    "# plt.xticks(range(len(average_speedup_per_suffix)), [xticklabelmap[col] for col in average_speedup_per_suffix.keys()])\n",
    "# plt.ylabel(\"Average Speedup\")\n",
    "# plt.xlabel(\"Configuration\")\n",
    "# plt.title(\"Average Speedup of 100 GHz over 4 GHz for Each Configuration\")\n",
    "# plt.show()\n",
    "\n",
    "def plot_average_speedup(freq):\n",
    "    xticklabelmap = {\n",
    "        f\"Speedup_{freq}_cryocache\": \"Super Core + CryoCache\",\n",
    "        f\"Speedup_{freq}_cryol2l3\": \"Super Core L1 + Cryo L2L3\",\n",
    "        f\"Speedup_{freq}_cryol3\": \"Super Core L1L2 + Cryo L3\",\n",
    "        f\"Speedup_{freq}_superl1l2l3\": \"Super Core Cache\"\n",
    "    }\n",
    "    average_speedup_per_suffix = {}\n",
    "    for suffix in data.columns:\n",
    "        if suffix.startswith(\"Speedup\") and freq in suffix:\n",
    "            suffix_speedup = data[suffix]\n",
    "            average_speedup_per_suffix[suffix] = suffix_speedup.mean()\n",
    "\n",
    "    # Plotting the average speedup per suffix\n",
    "    plt.bar(average_speedup_per_suffix.keys(), average_speedup_per_suffix.values())\n",
    "    plt.xticks(rotation=45)\n",
    "    plt.xticks(range(len(average_speedup_per_suffix)), [xticklabelmap[col] for col in average_speedup_per_suffix.keys()])\n",
    "    plt.ylabel(\"Average Speedup\")\n",
    "    plt.xlabel(\"Configuration\")\n",
    "    plt.title(f\"Average Speedup of {freq} over 4 GHz for Each Configuration\")\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_average_speedup(\"10GHz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_average_speedup(\"20GHz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_average_speedup(\"50GHz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Setwor0ALFy6c5ub9N2/eCAsLC+kWZXr+D+TKlUu4uromK4+IiFCpg6ioKGmZcv/f+vtWq0pQUJCwsrISv/7663evjFNqodm/f78AIGbOnKlS7unpKWQymXj06JFU9q1zY2rvl9pn6tevn7ReSnVz8eLFZMfJ5MmTpa4SX1P+v1bWecmSJUVcXJy0XHmM3L59O9V4w8PDBQDh7u6eps938+ZNAUD07t1bpXz06NECgMpxoTzW/P39pbL3798nu3OhPA9+fWvs69abt2/fCgMDA9GqVSuV9aZOnZqs9Tq9LUIAxNGjR5Otn1I9NWrUKNk5KrVbY1+3CKXnXKxsCZ0+fbrKPsuXLy8qVqyY7L2+RatGjW3ZsgV2dnaoW7cuAEAmk6F9+/bYvn075HI5AKBevXqwsbHBjh07pO1CQ0Nx4sQJtG/fXirbtWsXSpYsCWdnZ3z48EH6q1evHgDg9OnTKu9du3ZtlCpVKllMpqamKu8THh6OmjVr4saNG1L50aNHAQADBw5U2XbIkCEqr4UQ2LNnD1q0aAEhhEpcjRo1Qnh4uMp+vyaTyXDs2DHMnDkTuXLlwrZt2zBo0CAUKFAA7du3T3GYtzJr/zomZSvE3r17oVAo0K5dO5V47O3tUaxYMel7unnzJoKCgtCpUyd8/PhRWi86Ohr169eHv78/FAoF5HI5jh07hlatWiF//vzS+5YsWVK6uv8Z3/s8Kbl27Rrev3+PgQMHwsTERCpv1qwZnJ2d8ffff/90XN+iHHGSUqdHZTzKdWJjY9O0nnI02NdXj7dv34atra3K38ePH1XWqVq1Kk6cOJHsb8GCBd/8HBs3bsSKFSswb9486RhNiVwux/Hjx9GqVSsULlxYKndwcECnTp0QEBAgxd++fXskJCSotMIcP34cYWFh0vH8I8eNl5eXyrH7LePGjUPhwoXRu3fvNK2fVERERIpX8F27dlWpg3HjxiVbZ/ny5SnWQ7ly5VJ9v+joaLRu3Vo6/tPbGgh8OVb09fUxdOhQlfJRo0ZBCIEjR46olKd2bkxNwYIFU/xcSVvtktZNQkICPn78iKJFiyJnzpwqdblnzx64uLigdevWyd7n66k4evToodLyV7NmTQDAkydPUo1V+f/QwsIiTZ9NeZ4ZOXKkSvmoUaMAINm5pFSpUlIcwJeWuhIlSnwzptScPHkSiYmJ3/2d+RGFChVK8fyctJ6ULZi1a9fGkydPkrUgp8WPnIv79++v8rpmzZrp/v605taYXC7H9u3bUbduXTx9+lQqr1q1KhYuXIiTJ0+iYcOGMDAwgIeHB7Zu3Yq4uDgYGxtj7969SEhIUEmEgoKCEBgYCFtb2xTf7/379yqvCxUqlOJ6hw4dwsyZM3Hz5k2VkSRJD8Lnz59DT08v2T6+Hu0WEhKCsLAwrF69OtURCF/H9TVjY2NMnDgREydOxJs3b3D27FksWbIEO3fuhKGhITZv3qyyfrFixVReFylSBHp6etLcFEFBQRBCJFtPydDQUFoPQLJbGEmFh4cjLi4OsbGxKe6vRIkS30xY0uJ7nyclz58/l97/a87OzsmGN6ub8mSS0kgkZZO2ch1TU9M0rac8cUdFRamsV7RoUZw4cQLAl8Tl61tbAGBjY5PiiLhv3Wq9efMm+vfvj44dOyb7EfhaSEgIYmJiUvy+S5YsCYVCgeDgYJQuXRouLi5wdnbGjh070KtXLwBfbovZ2NhIFy0/ctykdjx/7dKlS9i0aRNOnjwJPb30XzdaWFgkqwMAmD59ujQC6Ndff01x2ypVqqR4uzRXrlwp3loCgD59+uDx48e4cOECcufOne54gS/Hg6OjY7Iff+XtWOXxopTW71IpR44c3x1xGRsbC29vb6xfvx6vXr2CEEJalvQH9vHjx/Dw8EjT+ya98AK+fI/AlwvY1FhaWgIAIiMj0/QeynP91+d2e3t75MyZM9l393VMyri+FdO33htI/rtibW0tfdYflVodnz9/HlOmTMHFixcRExOjsiw8PDzdIwHTey42MTFJ9hv+I9+f1iRCp06dwps3b7B9+3Zs37492fItW7agYcOGAIAOHTpg1apVOHLkCFq1aoWdO3fC2dkZLi4u0voKhQJly5bFokWLUny/fPnyqbxO6erx3LlzaNmyJWrVqoUVK1bAwcEBhoaGWL9+PbZu3Zruz6hQKAAAXbp0STWh+NbV4NccHBzQoUMHeHh4oHTp0ti5cyf8/Py++YP29VWUQqGATCbDkSNHUry6VF7tKmOfP38+XF1dU9y3ubl5uoYdpza5orL172f2kZU4ODgAAN68eZNs2Zs3b2BtbS21Ajk4OOD06dMQQqh8NuW2jo6OACBNk3Dnzh24u7tL65mbm0s/QupK8EJDQ+Hh4YHixYtjzZo1atlnUu3bt8esWbPw4cMHWFhY4MCBA+jYsaP0//hHjpu0tgaNHTsWNWvWRKFChaRkWpmEvHnzBi9evEjxx0zJ2dkZt27dQkJCgnTRkFI86rBkyRJs27YNmzdvTvUYzAhp/S7TY8iQIVi/fj2GDx+OX375RZpIsEOHDlJ9p1dqrWNJk6yvWVpawtHREXfu3EnXe6X1vPMjMalDes+tKdXx48ePUb9+fTg7O2PRokXIly8fjIyMcPjwYSxevPiH6yk9fqTFMyVakwgpO/4tX7482bK9e/di37598PX1hampKWrVqgUHBwfs2LEDbm5uOHXqlNRJS6lIkSK4desW6tev/8M/lnv27IGJiQmOHTumcrti/fr1KusVKFAACoUCT58+VWmxePTokcp6tra2sLCwgFwu/+4VU3oYGhqiXLlyCAoKkm5rKQUFBalk+48ePYJCoZA6PBYpUgRCCBQqVAjFixdP9T2UnYYtLS2/GbutrS1MTU2lFqSkHjx4oPJaeRXz9S29r6+qkvre50mJspP5gwcPpFaGpDEpl2cUJycn2NrapjiB3pUrV1R+1FxdXbFmzRoEBgaq3I5QdvhUrluzZk1YWVlh+/btmDBhwg+1ZqSFQqFA586dERYWhn/++UfqxPottra2MDMzS1bfAHD//n3o6empXIi0b98e06ZNw549e2BnZ4eIiAiV+ZIy6rgBgBcvXuD58+cpXhG3bNkSVlZW35xZvHnz5rh06RL27duHdu3aqTW2pM6dO4fRo0dj+PDh6Ny580/tq0CBAvjnn38QGRmp0iqknJA1o48HANi9eze8vLywcOFCqezz58/JvusiRYqkO0lJr+bNm2P16tW4ePEifvnll2+uqzzXBwUFqQxoePfuHcLCwjL0u1Pu+9GjRyr/Xz9+/JishSTpuTVp5+NvnVu/dvDgQcTFxeHAgQMqFwNfdysB0p4YaupcrBV9hGJjY7F37140b94cnp6eyf4GDx6MyMhIHDhwAACgp6cHT09PHDx4EJs2bUJiYqLKbTHgy+iiV69e4c8//0zx/aKjo78bl76+PmQymUoW/ezZs2QjzpT3VlesWKFSvnTp0mT78/DwwJ49e1I8uFOaZTipoKAgvHjxIll5WFgYLl68iFy5ciVrRvw6sVTG1KRJEwBAmzZtoK+vj2nTpiW7ShFCSP1LKlasiCJFimDBggUp3gpQxq6vr49GjRph//79KrEGBgbi2LFjKttYWlrCxsYG/v7+KuVff4/p+TwpqVSpEvLkyQNfX1+VFqsjR44gMDAwxdF96ubh4YFDhw4hODhYKjt58iQePnyItm3bSmXu7u4wNDRU+Q6EEPD19YWTk5M0ssXMzAxjx47FnTt3MH78+BSvMNVx1Tlt2jQcO3YM27ZtS/MtEn19fTRs2BB//fWXyi3Ld+/eYevWrXBzc5NuSQBfbsmULVsWO3bswI4dO+Dg4KAy+eDPHjffsnr1auzbt0/lT9nnYsGCBdiyZcs3tx8wYADs7OwwYsQIPHz4MNlyddTBmzdv0K5dO7i5uWH+/Pk/vb+mTZtCLpdj2bJlKuWLFy+GTCb75rGkLvr6+sm+m6VLlyZrsfDw8MCtW7eSjcYC1NeqMnbsWOTIkQO9e/fGu3fvki1//PgxlixZAuDLdwd8GSmVlPLOQ0aeS+rXrw8DAwOsXLlSpfzregT+d+Ga9NwaHR2NDRs2pPn9lK0xX9+2/LohAPhyOzQtjyLS1LlYK1qEDhw4gMjISLRs2TLF5dWqVYOtrS22bNkiJTzt27fH0qVLMWXKFJQtWzbZcOOuXbti586d6N+/P06fPo0aNWpALpfj/v372LlzJ44dO/bdacybNWuGRYsWoXHjxujUqRPev3+P5cuXo2jRovjvv/+k9SpWrAgPDw/4+Pjg48eP0vB55YkxabY8Z84cnD59GlWrVkWfPn1QqlQpfPr0CTdu3MA///yDT58+pRrPrVu30KlTJzRp0gQ1a9aEtbU1Xr16hQ0bNuD169fw8fFJ1pT49OlTtGzZEo0bN8bFixexefNmdOrUSbqNWKRIEcycORMTJkzAs2fP0KpVK1hYWODp06fYt28f+vbti9GjR0NPTw9r1qxBkyZNULp0afTo0QNOTk549eoVTp8+DUtLSxw8eBDAlx/Po0ePombNmhg4cCASExOxdOlSlC5dWuV7A74MRZ0zZw569+6NSpUqwd/fP8UflLR+npQYGhpi7ty56NGjB2rXro2OHTtKQzYLFiz4U48dWLZsGcLCwvD69WsAX66iXr58CeBL87/yHvpvv/2GXbt2oW7duhg2bBiioqIwf/58lC1bFj169JD2lzdvXgwfPhzz589HQkICKleujP379+PcuXPYsmWLSv2OHz8egYGBmD9/Po4fPw4PDw/kzZsXoaGhuHHjBnbt2oU8efKodEpMj9u3b2PGjBmoVasW3r9/n6z/WZcuXVLddubMmThx4gTc3NwwcOBAGBgYYNWqVYiLi8O8efOSrd++fXtMnjwZJiYm6NWrV7IWrp85br5Febs9KeUJvXbt2t89R1hbW2Pfvn1o0aIFXFxc0KFDB2mqj+DgYOzatQtAyn1F0mro0KEICQnB2LFjk3UbKFeuXLpvw7Vo0QJ169bFxIkT8ezZM7i4uOD48eP466+/MHz48J+eMiI8PDzZ/xUl5f+Z5s2bY9OmTbCyskKpUqVw8eJF/PPPP8n6PY0ZMwa7d+9G27Zt0bNnT1SsWBGfPn3CgQMH4Ovr+83jPq2KFCmCrVu3on379ihZsqTKzNIXLlzArl27pBmTXVxc4OXlhdWrVyMsLAy1a9fGlStXsGHDBrRq1eqbgwh+lp2dHYYNG4aFCxdK58Bbt27hyJEjsLGxUfmdadiwIfLnz49evXphzJgx0NfXx7p162Bra5vixXRKGjZsCCMjI7Ro0QL9+vVDVFQU/vzzT+TJkyfZbf6KFSti5cqVmDlzJooWLYo8efIka/EBMvZc/E3pGmOmIS1atBAmJiYiOjo61XW6d+8uDA0NpeGzCoVC5MuXL8VhoErx8fFi7ty5onTp0sLY2FjkypVLVKxYUUybNk2Eh4dL6+H/Jw1Lydq1a0WxYsWEsbGxcHZ2FuvXr09xaGJ0dLQYNGiQsLa2Fubm5qJVq1biwYMHAkCy2X3fvXsnBg0aJPLlyycMDQ2Fvb29qF+/vli9evU3v6d3796JOXPmiNq1awsHBwdhYGAgcuXKJerVqyd2796tsq4yxnv37glPT09hYWEhcuXKJQYPHpziBIR79uwRbm5uIkeOHCJHjhzC2dlZDBo0SDx48EBlvX///Ve0adNG5M6dWxgbG4sCBQqIdu3aiZMnT6qsd/bsWVGxYkVhZGSU6oSKQnwZntmrVy9hZWUlLCwsRLt27cT79+9THT6f1s+Tkh07dojy5csLY2NjYW1tneIkXukdPv+t4ehfTw53584d0bBhQ2FmZiZy5swpOnfuLN6+fZtsn3K5XMyePVuaQK506dJi8+bNqcawb98+0bRpU2FraysMDAxEzpw5hZubm5g/f74ICwtLFm9aJ1RUvk7t73tu3LghGjVqJMzNzYWZmZmoW7euuHDhQorrBgUFSftNaYJOIdJ23KhjduwfmULhzZs3YsyYMaJUqVLC1NRUmki0W7duKsOn07L/r4e8f2tIemoTKqa2L6XIyEgxYsQI4ejoKAwNDUWxYsW+OaFiWn0r1qT/Z0JDQ0WPHj2EjY2NMDc3F40aNRL3799PNjGgEEJ8/PhRDB48WDg5OUkT43p5eUm/BanV+bem50jJw4cPRZ8+fUTBggWFkZGRsLCwEDVq1BBLly5VmSwxISFBTJs2TRQqVEgYGhqKfPnyfXNCxZS+o6RDzdM6fF6IL9NjTJo0Sdjb2wtTU1NRr149ERgYKHLnzi369++vsv3169dF1apVhZGRkcifP79YtGjRNydUTMmBAwdEuXLlhImJiShYsKCYO3euWLduXbJ9vH37VjRr1kxYWFgIpGFCxbSci5UTKn7tR55QIBMig3tlUapu3ryJ8uXLY/PmzT99Xz+9pk6dimnTpiEkJERl0jFtld0+DxGROoSFhSFXrlyYOXNmsr6y9IVW9BHKDlJ6OrGPjw/09PQ08rBFIiLKXlL7nQGAOnXqZG4wWkQr+ghlB/PmzcP169dRt25dGBgY4MiRIzhy5Aj69u2bbKg+ERFReu3YsQN+fn7SozgCAgKwbds2NGzYEDVq1NB0eFkWE6FMUr16dZw4cQIzZsxAVFQU8ufPj6lTp7KpkoiI1KJcuXIwMDDAvHnzEBERIXWgnjlzpqZDy9LYR4iIiIh0FvsIERERkc5iIkREREQ6K9v3EVIoFHj9+jUsLCy04rlTRERE9GXW6sjISDg6OmbYY4IAHUiEXr9+zVFZREREWio4OBh58+bNsP1n+0RI+dDA4OBglecXERERUdYVERGBfPnyqTz8NyNk+0RIeTvM0tKSiRAREZGWyehuLewsTURERDqLiRARERHpLCZCREREpLOYCBEREZHOYiJEREREOouJEBEREeksJkJERESkszSaCPn7+6NFixZwdHSETCbD/v37k60TGBiIli1bwsrKCjly5EDlypXx4sWLzA+WiIiIsh2NJkLR0dFwcXHB8uXLU1z++PFjuLm5wdnZGWfOnMF///2HSZMmwcTEJJMjJSIiouxIJoQQmg4C+DJz5L59+9CqVSuprEOHDjA0NMSmTZt+eL8RERGwsrJCeHg4Z5YmIiLSEpn1+51l+wgpFAr8/fffKF68OBo1aoQ8efKgatWqKd4+SyouLg4REREqf0REREQpybKJ0Pv37xEVFYU5c+agcePGOH78OFq3bo02bdrg7NmzqW7n7e0NKysr6Y9PniciIqLUZNlbY69fv4aTkxM6duyIrVu3Suu1bNkSOXLkwLZt21LcT1xcHOLi4qTXyqfX8tYYERGR9sisW2NZ9unzNjY2MDAwQKlSpVTKS5YsiYCAgFS3MzY2hrGxcUaHR0RERNlAlr01ZmRkhMqVK+PBgwcq5Q8fPkSBAgU0FBURERFlJxptEYqKisKjR4+k10+fPsXNmzdhbW2N/PnzY8yYMWjfvj1q1aqFunXr4ujRozh48CDOnDmjuaCJiChLKjj+b02HoJOezWmm6RB+ikYToWvXrqFu3brS65EjRwIAvLy84Ofnh9atW8PX1xfe3t4YOnQoSpQogT179sDNzU1TIRMREVE2otFEqE6dOvheX+2ePXuiZ8+emRQRERER6ZIs20eIiIiIKKMxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnaTQR8vf3R4sWLeDo6AiZTIb9+/enum7//v0hk8ng4+OTafERERFR9qbRRCg6OhouLi5Yvnz5N9fbt28fLl26BEdHx0yKjIiIiHSBgSbfvEmTJmjSpMk313n16hWGDBmCY8eOoVmzZpkUGREREekCjSZC36NQKNC1a1eMGTMGpUuXTtM2cXFxiIuLk15HRERkVHhERESk5bJ0Z+m5c+fCwMAAQ4cOTfM23t7esLKykv7y5cuXgRESERGRNsuyidD169exZMkS+Pn5QSaTpXm7CRMmIDw8XPoLDg7OwCiJiIhIm2XZROjcuXN4//498ufPDwMDAxgYGOD58+cYNWoUChYsmOp2xsbGsLS0VPkjIiIiSkmW7SPUtWtXNGjQQKWsUaNG6Nq1K3r06KGhqIiIiCg70WgiFBUVhUePHkmvnz59ips3b8La2hr58+dH7ty5VdY3NDSEvb09SpQokdmhEhERUTak0UTo2rVrqFu3rvR65MiRAAAvLy/4+flpKCoiIiLSFRpNhOrUqQMhRJrXf/bsWcYFQ0RERDony3aWJiIiIspoTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZxloOgAiosxUcPzfmg5BZz2b00zTIRAlwxYhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdpdFEyN/fHy1atICjoyNkMhn2798vLUtISMC4ceNQtmxZ5MiRA46OjujWrRtev36tuYCJiIgoW9FoIhQdHQ0XFxcsX7482bKYmBjcuHEDkyZNwo0bN7B37148ePAALVu21ECkRERElB1pdGbpJk2aoEmTJikus7KywokTJ1TKli1bhipVquDFixfInz9/ZoRIRERE2ZhWPWIjPDwcMpkMOXPmTHWduLg4xMXFSa8jIiIyITIiIiLSRlrTWfrz588YN24cOnbsCEtLy1TX8/b2hpWVlfSXL1++TIySiIiItIlWJEIJCQlo164dhBBYuXLlN9edMGECwsPDpb/g4OBMipKIiIi0TZa/NaZMgp4/f45Tp059szUIAIyNjWFsbJxJ0REREZE2y9KJkDIJCgoKwunTp5E7d25Nh0RERETZiEYToaioKDx69Eh6/fTpU9y8eRPW1tZwcHCAp6cnbty4gUOHDkEul+Pt27cAAGtraxgZGWkqbCIiIsomNJoIXbt2DXXr1pVejxw5EgDg5eWFqVOn4sCBAwAAV1dXle1Onz6NOnXqZFaYRERElE1pNBGqU6cOhBCpLv/WMiIiIqKfpRWjxoiIiIgyAhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIinfVDidDJkyfRvHlzFClSBEWKFEHz5s3xzz//qDs2IiIiogyV7kRoxYoVaNy4MSwsLDBs2DAMGzYMlpaWaNq0KZYvX54RMRIRERFlCIP0bjB79mwsXrwYgwcPlsqGDh2KGjVqYPbs2Rg0aJBaAyQiIiLKKOluEQoLC0Pjxo2TlTds2BDh4eFqCYqIiIgoM6Q7EWrZsiX27duXrPyvv/5C8+bN1RIUERERUWZI962xUqVKYdasWThz5gx++eUXAMClS5dw/vx5jBo1Cn/88Ye07tChQ9UXKREREZGapTsRWrt2LXLlyoV79+7h3r17UnnOnDmxdu1a6bVMJmMiRERERFlauhOhp0+fZkQcRERERJmOEyoSERGRzkp3i1DPnj2/uXzdunU/HAwRERFRZkp3IhQaGqryOiEhAXfu3EFYWBjq1auntsCIiIiIMlq6E6GUhs4rFAoMGDAARYoUUUtQRERERJlBLX2E9PT0MHLkSCxevFgduyMiIiLKFGrrLP348WMkJiaqa3dEREREGS7dt8ZGjhyp8loIgTdv3uDvv/+Gl5eX2gIjIiIiymjpToT+/fdfldd6enqwtbXFwoULvzuijIiIiCgrSXcidPr06YyIg4iIiCjTaXRCRX9/f7Ro0QKOjo6QyWTYv3+/ynIhBCZPngwHBweYmpqiQYMGCAoK0kywRERElO2kqUWofPnykMlkadrhjRs30vzm0dHRcHFxQc+ePdGmTZtky+fNm4c//vgDGzZsQKFChTBp0iQ0atQI9+7dg4mJSZrfh4iIiCglaUqEWrVqJf378+fPWLFiBUqVKqXy9Pm7d+9i4MCB6XrzJk2aoEmTJikuE0LAx8cHv//+O9zd3QEAGzduhJ2dHfbv348OHTqk672IiIiIvpamRGjKlCnSv3v37o2hQ4dixowZydYJDg5WW2BPnz7F27dv0aBBA6nMysoKVatWxcWLF1NNhOLi4hAXFye9joiIUFtMRERElL2ku4/Qrl270K1bt2TlXbp0wZ49e9QSFAC8ffsWAGBnZ6dSbmdnJy1Libe3N6ysrKS/fPnyqS0mIiIiyl7SnQiZmpri/PnzycrPnz+fJfrtTJgwAeHh4dKfOlupiIiIKHtJ9/D54cOHY8CAAbhx4waqVKkCALh8+TLWrVuHSZMmqS0we3t7AMC7d+/g4OAglb979w6urq6pbmdsbAxjY2O1xUFERETZV7oTofHjx6Nw4cJYsmQJNm/eDAAoWbIk1q9fj3bt2qktsEKFCsHe3h4nT56UEp+IiAhcvnwZAwYMUNv7EBERke5KdyIEAO3atVNL0hMVFYVHjx5Jr58+fYqbN2/C2toa+fPnx/DhwzFz5kwUK1ZMGj7v6OioMoqNiIiI6Ef9UCIUFhaG3bt348mTJxg9ejSsra1x48YN2NnZwcnJKc37uXbtGurWrSu9Vj7HzMvLC35+fhg7diyio6PRt29fhIWFwc3NDUePHs0SfZGIiIhI+6U7Efrvv//QoEEDWFlZ4dmzZ+jduzesra2xd+9evHjxAhs3bkzzvurUqQMhRKrLZTIZpk+fjunTp6c3TCIiIqLvSveosZEjR6J79+4ICgpSaZlp2rQp/P391RocERERUUZKdyJ09epV9OvXL1m5k5PTN+f3ISIiIspq0p0IGRsbpzhb88OHD2Fra6uWoIiIiIgyQ7oToZYtW2L69OlISEgA8KUfz4sXLzBu3Dh4eHioPUAiIiKijJLuRGjhwoWIiopCnjx5EBsbi9q1a6No0aKwsLDArFmzMiJGIiIiogyR7lFjVlZWOHHiBAICAvDff/8hKioKFSpUUHk4KhEREZE2+KF5hADAzc0NlSpVgrGxMWQymTpjIiIiIsoU6b41plAoMGPGDDg5OcHc3BxPnz4FAEyaNAlr165Ve4BEREREGSXdidDMmTPh5+eHefPmwcjISCovU6YM1qxZo9bgiIiIiDJSuhOhjRs3YvXq1ejcuTP09fWlchcXF9y/f1+twRERERFlpHQnQq9evULRokWTlSsUCmlIPREREZE2SHciVKpUKZw7dy5Z+e7du1G+fHm1BEVERESUGdI9amzy5Mnw8vLCq1evoFAosHfvXjx48AAbN27EoUOHMiJGIiIiogyR7hYhd3d3HDx4EP/88w9y5MiByZMnIzAwEAcPHsSvv/6aETESERERZYgfmkeoZs2aOHHihLpjISIiIspUPzyh4rVr1xAYGAjgS7+hihUrqi0oIiIiosyQ7kTo5cuX6NixI86fP4+cOXMCAMLCwlC9enVs374defPmVXeMRERERBki3X2EevfujYSEBAQGBuLTp0/49OkTAgMDoVAo0Lt374yIkYiIiChDpLtF6OzZs7hw4QJKlCghlZUoUQJLly5FzZo11RocERERUUZKd4tQvnz5Upw4US6Xw9HRUS1BEREREWWGdCdC8+fPx5AhQ3Dt2jWp7Nq1axg2bBgWLFig1uCIiIiIMlK6b411794dMTExqFq1KgwMvmyemJgIAwMD9OzZEz179pTW/fTpk/oiJSIiIlKzdCdCPj4+GRAGERERUeZLdyLk5eWVEXEQERERZbo0J0KJiYmQy+UwNjaWyt69ewdfX19ER0ejZcuWcHNzy5AgiYiIiDJCmhOhPn36wMjICKtWrQIAREZGonLlyvj8+TMcHBywePFi/PXXX2jatGmGBUtERESkTmkeNXb+/Hl4eHhIrzdu3Ai5XI6goCDcunULI0eOxPz58zMkSCIiIqKMkOZE6NWrVyhWrJj0+uTJk/Dw8ICVlRWAL32H7t69q/4IiYiIiDJImhMhExMTxMbGSq8vXbqEqlWrqiyPiopSb3REREREGSjNiZCrqys2bdoEADh37hzevXuHevXqScsfP37MmaWJiIhIq6S5s/TkyZPRpEkT7Ny5E2/evEH37t3h4OAgLd+3bx9q1KiRIUESERERZYQ0J0K1a9fG9evXcfz4cdjb26Nt27Yqy11dXVGlShW1B0hERESUUdI1oWLJkiVRsmTJFJf17dtXLQERERERZZZ0P3SViIiIKLvI0omQXC7HpEmTUKhQIZiamqJIkSKYMWMGhBCaDo2IiIiygXQ/aywzzZ07FytXrsSGDRtQunRpXLt2DT169ICVlRWGDh2q6fCIiIhIy2XpROjChQtwd3dHs2bNAAAFCxbEtm3bcOXKFQ1HRkRERNnBD90aCwsLw5o1azBhwgR8+vQJAHDjxg28evVKrcFVr14dJ0+exMOHDwEAt27dQkBAAJo0aZLqNnFxcYiIiFD5IyIiIkpJuluE/vvvPzRo0ABWVlZ49uwZ+vTpA2tra+zduxcvXrzAxo0b1Rbc+PHjERERAWdnZ+jr60Mul2PWrFno3Llzqtt4e3tj2rRpaouBiIiIsq90twiNHDkS3bt3R1BQEExMTKTypk2bwt/fX63B7dy5E1u2bMHWrVtx48YNbNiwAQsWLMCGDRtS3WbChAkIDw+X/oKDg9UaExEREWUf6W4Runr1KlatWpWs3MnJCW/fvlVLUEpjxozB+PHj0aFDBwBA2bJl8fz5c3h7e8PLyyvFbYyNjWFsbKzWOIiIiCh7SneLkLGxcYr9bh4+fAhbW1u1BKUUExMDPT3VEPX19aFQKNT6PkRERKSb0p0ItWzZEtOnT0dCQgIAQCaT4cWLFxg3bhw8PDzUGlyLFi0wa9Ys/P3333j27Bn27duHRYsWoXXr1mp9HyIiItJN6U6EFi5ciKioKOTJkwexsbGoXbs2ihYtCgsLC8yaNUutwS1duhSenp4YOHAgSpYsidGjR6Nfv36YMWOGWt+HiIiIdFO6+whZWVnhxIkTCAgIwH///YeoqChUqFABDRo0UHtwFhYW8PHxgY+Pj9r3TURERPTDEyq6ubnBzc1NnbEQERERZap0J0J//PFHiuUymQwmJiYoWrQoatWqBX19/Z8OjoiIiCgjpTsRWrx4MUJCQhATE4NcuXIBAEJDQ2FmZgZzc3O8f/8ehQsXxunTp5EvXz61B0xERESkLunuLD179mxUrlwZQUFB+PjxIz5+/IiHDx+iatWqWLJkCV68eAF7e3uMGDEiI+IlIiIiUpt0twj9/vvv2LNnD4oUKSKVFS1aFAsWLICHhweePHmCefPmqX0oPREREZG6pbtF6M2bN0hMTExWnpiYKM0s7ejoiMjIyJ+PjoiIiCgDpTsRqlu3Lvr164d///1XKvv3338xYMAA1KtXDwBw+/ZtFCpUSH1REhEREWWAdCdCa9euhbW1NSpWrCg916tSpUqwtrbG2rVrAQDm5uZYuHCh2oMlIiIiUqd09xGyt7fHiRMncP/+fTx8+BAAUKJECZQoUUJap27duuqLkIiIiCiD/PCEis7OznB2dlZnLERERESZ6ocSoZcvX+LAgQN48eIF4uPjVZYtWrRILYERERERZbR0J0InT55Ey5YtUbhwYdy/fx9lypTBs2fPIIRAhQoVMiJGIiIiogyR7s7SEyZMwOjRo3H79m2YmJhgz549CA4ORu3atdG2bduMiJGIiIgoQ6Q7EQoMDES3bt0AAAYGBoiNjYW5uTmmT5+OuXPnqj1AIiIiooyS7kQoR44cUr8gBwcHPH78WFr24cMH9UVGRERElMHS3UeoWrVqCAgIQMmSJdG0aVOMGjUKt2/fxt69e1GtWrWMiJGIiIgoQ6Q7EVq0aBGioqIAANOmTUNUVBR27NiBYsWKccQYERERaZV0JUJyuRwvX75EuXLlAHy5Tebr65shgRERERFltHT1EdLX10fDhg0RGhqaUfEQERERZZp0d5YuU6YMnjx5khGxEBEREWWqdCdCM2fOxOjRo3Ho0CG8efMGERERKn9ERERE2iLdnaWbNm0KAGjZsiVkMplULoSATCaDXC5XX3REREREGSjdidDp06czIg4iIiKiTJfuRKh27doZEQcRERFRpkt3HyEAOHfuHLp06YLq1avj1atXAIBNmzYhICBArcERERERZaR0J0J79uxBo0aNYGpqihs3biAuLg4AEB4ejtmzZ6s9QCIiIqKM8kOjxnx9ffHnn3/C0NBQKq9RowZu3Lih1uCIiIiIMlK6E6EHDx6gVq1aycqtrKwQFhamjpiIiIiIMkW6EyF7e3s8evQoWXlAQAAKFy6slqCIiIiIMkO6E6E+ffpg2LBhuHz5MmQyGV6/fo0tW7Zg9OjRGDBgQEbESERERJQh0j18fvz48VAoFKhfvz5iYmJQq1YtGBsbY/To0RgyZEhGxEhERESUIdKdCMlkMkycOBFjxozBo0ePEBUVhVKlSsHc3Dwj4iMiIiLKMOm+NbZ582bExMTAyMgIpUqVQpUqVZgEERERkVZKdyI0YsQI5MmTB506dcLhw4cz/Nlir169QpcuXZA7d26YmpqibNmyuHbtWoa+JxEREemGdCdCb968wfbt2yGTydCuXTs4ODhg0KBBuHDhgtqDCw0NRY0aNWBoaIgjR47g3r17WLhwIXLlyqX29yIiIiLdk+4+QgYGBmjevDmaN2+OmJgY7Nu3D1u3bkXdunWRN29ePH78WG3BzZ07F/ny5cP69eulskKFCqlt/0RERKTbfuhZY0pmZmZo1KgRmjRpgmLFiuHZs2dqCuuLAwcOoFKlSmjbti3y5MmD8uXL488///zmNnFxcYiIiFD5IyIiIkrJDyVCMTEx2LJlC5o2bQonJyf4+PigdevWuHv3rlqDe/LkCVauXIlixYrh2LFjGDBgAIYOHYoNGzakuo23tzesrKykv3z58qk1JiIiIso+0n1rrEOHDjh06BDMzMzQrl07TJo0Cb/88ktGxAaFQoFKlSpJD3MtX7487ty5A19fX3h5eaW4zYQJEzBy5EjpdUREBJMhIiIiSlG6EyF9fX3s3LkTjRo1gr6+vsqyO3fuoEyZMmoLzsHBAaVKlVIpK1myJPbs2ZPqNsbGxjA2NlZbDKSbCo7/W9Mh6Kxnc5ppOgQi0iHpToS2bNmi8joyMhLbtm3DmjVrcP36dbUOp69RowYePHigUvbw4UMUKFBAbe9BREREuuuHO0v7+/vDy8sLDg4OWLBgAerVq4dLly6pMzaMGDECly5dwuzZs/Ho0SNs3boVq1evxqBBg9T6PkRERKSb0tUi9PbtW/j5+WHt2rWIiIhAu3btEBcXh/379ye7haUOlStXxr59+zBhwgRMnz4dhQoVgo+PDzp37qz29yIiIiLdk+ZEqEWLFvD390ezZs3g4+ODxo0bQ19fH76+vhkZnzRnEREREZG6pTkROnLkCIYOHYoBAwagWLFiGRkTERERUaZIcx+hgIAAREZGomLFiqhatSqWLVuGDx8+ZGRsRERERBkqzYlQtWrV8Oeff+LNmzfo168ftm/fDkdHRygUCpw4cQKRkZEZGScRERGR2qV71FiOHDnQs2dPBAQE4Pbt2xg1ahTmzJmDPHnyoGXLlhkRIxEREVGG+KlnjZUoUQLz5s3Dy5cvsW3bNnXFRERERJQpfioRUtLX10erVq1w4MABdeyOiIiIKFOoJREiIiIi0kZMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHSWViVCc+bMgUwmw/DhwzUdChEREWUDWpMIXb16FatWrUK5cuU0HQoRERFlE1qRCEVFRaFz5874888/kStXLk2HQ0RERNmEViRCgwYNQrNmzdCgQYPvrhsXF4eIiAiVPyIiIqKUGGg6gO/Zvn07bty4gatXr6ZpfW9vb0ybNi2DoyIiIqLsIEu3CAUHB2PYsGHYsmULTExM0rTNhAkTEB4eLv0FBwdncJRERESkrbJ0i9D169fx/v17VKhQQSqTy+Xw9/fHsmXLEBcXB319fZVtjI2NYWxsnNmhEhERkRbK0olQ/fr1cfv2bZWyHj16wNnZGePGjUuWBBERERGlR5ZOhCwsLFCmTBmVshw5ciB37tzJyomIiIjSK0v3ESIiIiLKSFm6RSglZ86c0XQIRERElE2wRYiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdFaWT4S8vb1RuXJlWFhYIE+ePGjVqhUePHig6bCIiIgoG8jyidDZs2cxaNAgXLp0CSdOnEBCQgIaNmyI6OhoTYdGREREWs5A0wF8z9GjR1Ve+/n5IU+ePLh+/Tpq1aqloaj+p+D4vzUdgs56NqeZpkMgIiItl+UToa+Fh4cDAKytrVNcHhcXh7i4OOl1REREpsRFRERE2ifL3xpLSqFQYPjw4ahRowbKlCmT4jre3t6wsrKS/vLly5fJURIREZG20KpEaNCgQbhz5w62b9+e6joTJkxAeHi49BccHJyJERIREZE20ZpbY4MHD8ahQ4fg7++PvHnzprqesbExjI2NMzEyIiIi0lZZPhESQmDIkCHYt28fzpw5g0KFCmk6JCIiIsomsnwiNGjQIGzduhV//fUXLCws8PbtWwCAlZUVTE1NNRwdERERabMs30do5cqVCA8PR506deDg4CD97dixQ9OhERERkZbL8i1CQghNh0BERETZVJZvESIiIiLKKEyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIiIiEhnMREiIiIincVEiIiIiHQWEyEiIiLSWUyEiIiISGcxESIiIiKdxUSIiIiIdBYTISIiItJZTISIiIhIZzERIiIiIp3FRIiIiIh0FhMhIiIi0llakQgtX74cBQsWhImJCapWrYorV65oOiQiIiLKBrJ8IrRjxw6MHDkSU6ZMwY0bN+Di4oJGjRrh/fv3mg6NiIiItFyWT4QWLVqEPn36oEePHihVqhR8fX1hZmaGdevWaTo0IiIi0nJZOhGKj4/H9evX0aBBA6lMT08PDRo0wMWLFzUYGREREWUHBpoO4Fs+fPgAuVwOOzs7lXI7Ozvcv38/xW3i4uIQFxcnvQ4PDwcAREREZEiMiriYDNkvfV9G1SnAetWkjKxXgHWrSazb7Cmj6lW5XyFEhuxfKUsnQj/C29sb06ZNS1aeL18+DURDGcnKR9MRUEZgvWZfrNvsKaPrNTIyElZWVhm2/yydCNnY2EBfXx/v3r1TKX/37h3s7e1T3GbChAkYOXKk9FqhUODTp0/InTs3ZDJZhsarTSIiIpAvXz4EBwfD0tJS0+GQGrFusyfWa/bFuk2ZEAKRkZFwdHTM0PfJ0omQkZERKlasiJMnT6JVq1YAviQ2J0+exODBg1PcxtjYGMbGxiplOXPmzOBItZelpSUPvGyKdZs9sV6zL9ZtchnZEqSUpRMhABg5ciS8vLxQqVIlVKlSBT4+PoiOjkaPHj00HRoRERFpuSyfCLVv3x4hISGYPHky3r59C1dXVxw9ejRZB2oiIiKi9MryiRAADB48ONVbYfRjjI2NMWXKlGS3EUn7sW6zJ9Zr9sW61SyZyOhxaURERERZVJaeUJGIiIgoIzERIiIiIp3FRIiIiIh0FhMhIiIi0llMhIhIqyUd78GxH9kL65YyAxMhynZSOmHyJJp9RUZGSg9blslkUCgUmg6J1IR1q1nK82Z2T0iZCFG2olAopGfKvXv3Di9fvgQAPmcum9q1axc6dOiAWrVqoVWrVvjw4QP09Hhayw5Yt5qV9FwaHh6O6OhoqSy7JUP8X0XZhhBCOlHOmDEDzZo1Q82aNVGpUiXs3r0bkZGRGo6Q1GndunXo0aMHateujZYtWyIsLAxTp06Vlme3k7UuYd1qlkKhkM6l8+fPh4eHB+rVq4fGjRsjODg4211YasXM0kRpoTw4p0+fjhUrVmD58uWoX78+6tSpgylTpsDV1RUWFhYajpLU4e+//8bkyZPh5+cHT09PAMDbt29hb2+Pz58/Q6FQwMzMTMNR0o9g3WqeMgmaOHEi/vzzT8yfPx8FCxZE165d0bx5c5w+fRrW1tYajlJ92CJE2YYQAh8+fMCxY8ewdOlSeHh44OrVq3j69CmGDh2KokWLso9BNvHixQu0b98ezZo1k8ru3buHTZs2oXLlyqhYsSLOnz8PgK0H2oZ1mzW8ePECx48fx+bNm+Hl5YXIyEhERESgf//+KklQtqgDQZSNvHz5UhQrVkxER0eLY8eOCXNzc7Fy5UohhBBRUVFi5cqV4sOHDxqOkn5WfHy8ePHihfS6a9euIn/+/GLfvn3i1KlTokuXLsLe3l6EhIRoMEr6EazbrOHff/8VefLkEUIIcfjwYWFubi58fX2FEEJERkaKpUuXioSEBE2GqDa8NUZaSwiR7F61k5MTbG1t0bFjR5w+fRo+Pj7o1asXgC+dpzdv3gwnJye0aNFCEyGTmhgaGiJfvnwAgJCQEDg5OcHf3x8FChQAAOTOnRsHDx7ErVu3UL9+fU2GSunEus18KZ1LixcvDldXV4waNQqrV6/GokWL0KdPHwDA8+fPcfDgQbi4uKBmzZqaCFmteGuMtNLXo8PCwsKkZV26dMG1a9dQr149KQmKjY3F0KFDYWpqiqZNm2oiZPpJIpVpEWxtbTFr1iwUKFBAuvUZGRmJ4sWLSz+olLWxbjUn6bk0Li4OsbGxAL58//b29li+fDm6d+8uJUGxsbEYO3YsDA0NUaNGDY3FrU58+jxple3bt6Nq1aooVKgQAGDSpEk4fvw4Xr9+jREjRqBDhw6wsLDAxIkT8ffff6No0aLIly8fHjx4gPDwcFy/fh2GhoaQy+XQ19fX8KehtHj58iXy5MkDIyOjFK9cAdUr2vj4eHh4eEBfXx979+7lkOssjHWrOefOnVNpzZk5cyYCAgLw6dMnjB8/Hm3atMHbt2/h6emJhIQElCtXDgULFsTx48cRGhoqnUuTjjDTVtodPemUgwcPokuXLvDz88OHDx+wceNGrFmzBn369IGnpycWLVqEadOmISwsDLNnz8aiRYtgamoKAPj1119x48YNGBoaIjExkUmQljh37hwaNmyIPXv2ID4+PtU5TGQyGeLi4nDmzBm4u7vj+fPn2LVrF/T09NhBPoti3WrO5s2bUbt2bWzduhXAlyHyy5YtQ4UKFVCkSBG0bdsW3t7esLe3x86dO9G4cWPcv38f165dQ4UKFVTOpdqeBAEcPk9apEWLFpg/fz4WLVoEMzMzfPjwAUuXLpWG2FaqVAkzZ87EjBkzMHr0aLi7u8Pd3V1lH3K5HAYG/G+vLapVqwZ7e3ssXrwYBgYGcHd3T7X14L///sPhw4dhaGgoXa0mJiayvrMo1q3mdOnSBffu3UPPnj1hZGSE6OhobN68GQ0aNAAAuLm5YciQIVAoFJg4cSKmTZuGadOmqewjO51Ls8enoGxPedIbMWIEEhIS8McffyAqKgqlSpWS1uncuTNkMhlmzJgBAwMD9OrVCxUrVlTZD1uCtIdCoYChoSGOHTuGli1bwtvbGwCkH8ykTfJRUVH4/Pkz+vTpg6JFi0Imk/GHMguTy+VS3bq7u7NuM5Ey0Zw9ezYSExPRoUMHWFtbo1q1atI6gwYNAgAMHToUBgYGGDx4MHLkyKGyn2x1Ls3sYWpE6SWXy5OVrVixQuTIkUP06NFDPH/+XGXZ1q1bRa5cucS8efMyK0RSo7dv34rg4GAREREhlcXHx4smTZqI8uXLi507d4rPnz9Ly969eydcXV1Fx44dpTKFQpGpMVP6JSYmCiFYt5kppXPpzJkzhUwmE4sWLUq2bMWKFUImk4lNmzZlRngaw0SIsrSkB+7SpUvF7NmzpddLliwRjo6OYvLkySI4OFhlu+PHj0snWtIeW7ZsEZUrVxYFCxYUDg4OYu/evdKypD+Yu3btEgkJCSIsLEzUqlVLlCxZUsTHx2swcvoRKSVDrNuMkfRcumXLFpXk5rfffhOGhoZiy5Ytybbbs2dPtpkvKDVMhEgrjB49WuTNm1dMmTJFPHv2TCpfuHChcHJySjEZEkIwGdIimzZtEhYWFsLX11f8888/YtCgQcLKykqlXpU/mBUqVBBr1qwRNWrUEM7OztIPZXY/YWdHXydDrNuMNXr0aJE/f37h4+MjXr58KZWPHz8+1WRIiOz9/TMRoixv+/btws7OTly5ckUqS3p1s3DhQpE/f34xbNgw8f79e02ESD/p9u3bomLFimL16tUq5aVLlxbLli0TQgjpBzE+Pl60aNFCyGQy4erqyh/KLC7prazUbmslTYZYtxlnzZo1ws7OTly6dCnF5ePHjxempqbizz//zOTINEv7x71Rtnf//n3UqlULlStXhlwuT7Z85MiR6N69O549ewYbGxsNREg/KyQkBAYGBqhbty6A/02wZ2Njg/fv3wOANP+ToaEh9uzZg99//x1Xr17lCKIsLOlkfUIIxMXFqSxX1rO+vr5Ut3v37sWkSZNYt2qk/J4vX76M1q1bo2rVqlJZ0ikIvL290a1bN2zatEkjcWoKJ1SkLG/IkCG4dOkSrly5Is01IpPJEB8fjxMnTkgPZ1SWi1QmZqOsLSAgAG5ubgC+TJxnZGSEjh07oly5cpgwYYK03sePH5E7d27pNX8os6akI78WLVqE8+fP48mTJ2jVqhVatWoFFxcXAKoTJn5dl6xb9WrdujWsrKzg5+enUh4fH49z585JjyzRtXMoW4Qoy0gtJy9Tpgw+fvyIw4cP4/Pnz9IBGh0dDW9vb+zatUtlH7p0AGcHyitSZRIkhIChoSGALz+EISEhUnnnzp1x+PBhle35Q5k1KZOg3377DbNnz0bx4sXRqFEjrFq1ClOmTMHx48cBQOV4/bouWbc/JrVzacGCBfHPP//gzZs3KuUfP37EunXrcO7cOQBIdXLL7IotQpQlJL16DAoKgqGhIfT19aXnCdWsWROfPn3CuHHj4Obmhvj4eIwaNQqfPn1CQEBA9prTQkek5Wrfw8MDhQsXxvz589GsWTPcvHkTz58/5w+klrhz5w5atWqF1atXo169egCAmzdvYsiQIbC1tYWvry/y5Mmj4Sizl6Tn0o8fP0KhUCB37tzQ09PD58+fUblyZRgZGWHLli2wtraGQqFAjx49EBUVhTNnzujkuZQtQqRxSQ/cqVOnokOHDqhRowa6d+8uNeGeO3cOxYoVw4IFC1C8eHF07NgRnz59gr+/v9S/gLTDsWPHpD5BqdVbYmIiAMDS0hLm5uZo3749Hj16hGfPnn1zO9Ksrx95oa+vj8+fP8PExATAl4kUXV1dsXTpUhw+fBj+/v6aCDPbSnounTFjBjw9PVGiRAmMGjUKR48ehYmJCf766y8YGBigTp06qFSpEpo2bYqQkBCcOnUK+vr6OvnYEl5WkcYpD9wpU6Zg5cqV2LBhA3Lnzo2FCxeiX79+iImJwcCBA7F//34EBgbiyZMnyJ07N6pUqQI9PT32I9AiHz9+xMSJE/Hp0ydcvXoVuXPnTvEBuMr6TEhIwLRp0+Di4oI7d+6w82wWpzyWb968CVdXV8hkMkRHR+Phw4eoXr261Hna1dUV5cqVw6NHjzQccfai/P4nTZoEX19fLFmyBEZGRli4cCEuXbqE2NhYtG7dGpcvX8bOnTvx+fNnmJmZoXXr1tDX19fdYytzB6kRpez8+fOiSpUqwt/fXwghxNGjR4WFhYVo3LixyJEjR7Jh1UopzZRKWZdCoRD+/v6idu3aonTp0iIkJEQIkfp8T3PnzhUFCxaUhk9zGHXWplAoxKlTp4RMJpPmf5o0aZIwNjYW//zzj7RedHS0KFOmjPD19dVUqNnWsWPHRMmSJcWFCxeEEEL4+/sLIyMjUalSJVGlShWxZ8+eFLfT5TnXmAiRRjx+/FhcvXpVvHjxQgghxJs3b8SUKVNEfHy8OH78uLCzsxOrVq0Sb968EdWqVRN6enpi8eLFmg2afopyDhmFQiECAgJEjRo1VJKhpEnO69evxciRI0VcXJy0HZMg7aBQKISbm5sYN26cSExMFK9fvxZ9+/YVMplMjBo1SkyZMkX8+uuvokyZMqxTNXj58qV48uSJlHg+ePBAmoH/8OHDwtraWqxbt07cvHlT2NnZiUqVKgk/Pz9NhpzlsLM0Zbrt27djxYoVMDU1RcOGDTFy5EjIZDLExsbC1NQUXbp0gZ2dHebOnQsDAwN0794dd+7cga2tLQ4fPsxRYdmAEAIXLlzAuHHjEBYWhtOnT8PW1hZCCISEhMDT0xMvX75EUFAQ9PX1ORowi/q6XhITE6Gnp4fffvsNAQEBCAgIAACEh4dj27Zt2LRpE8zMzODo6Ig1a9ZIc0PpYgddddi1axfWr18PIyMjeHp6Sg+eDg8Ph7GxMdq0aYNq1arh999/h56eHho0aICXL1+iUaNGWLJkiabDzzo0mYWR7lm3bp0wNzcXGzduFE+ePEm2PCoqSpQqVUqMGzdOCCFEZGSk8PT0FHv27FFpUSDtlVrL0MePH4VcLhdubm4qz5fi7c+s77///lNp3Xn//r2wtrYW3t7eKutFR0ervGaL0I9bu3atsLS0FGvXrhXXrl1Ltjw8PFyUKFFCephqeHi46NSpk9i+fTuPqa/oYK8o0pTLly9j+vTpWL58Obp27SqViyRXlTly5IC7uzs2b96MuLg4XLt2DbGxsXB3d+dkidlE0nqsXr065s6di/Hjx8PNzQ1mZmaIiYnBrVu32DE6C0s6Omn9+vVYvnw5TExMMG/ePOTLlw/58uXD4MGDceXKFXz8+BG5cuWCnp6eNHoM+HLcs25/zNmzZzFx4kQsX74cXbp0kcpFkkll4+Pj4ezsjNOnTyM+Ph6nTp1CREQE2rZtCz09PZU61HX8FijTKG9vNWzYUGWI5teJjZeXFzp27Ihr166hQIECuHjxojREnkmQdkhtCK6yPKVkyMzMDImJiUyCtIDyB9Tb2xtXrlzBhAkTkDdvXnTr1g1eXl7YunUrXFxccPr0ady/f19aP+kPL4/l9BNJHpVRuXJlNGvWTGXiQ+V3KpPJYGNjg8GDB0Mmk2H79u0wNDSEv78/k6AUsI8QZZpu3brh7t27uH79erJlyh/Fx48fw8zMDA4ODtJjFgBOta9Nkp5kHzx4ALlcDgsLC2lyzKR9QpJewf73338oW7Ysp0TIwpLW7V9//YWhQ4fi0KFDKFu2LADg5MmTuHLlCubOnYtWrVph48aNaNKkCbZt2wZLS0tNhp6tNG7cGHp6eslmWQf+d0w9e/YMOXPmRI4cORAXF4ccOXJAJpPx2EoBU0LKNHnz5sWnT5/w7NmzZMtkMhnkcjnmzJmDDRs2AICUBLEJXXsIIVQereDh4YFq1aqhVatWGDBgAACoTICZtGXIxcVFulplfWdNyro9cOAAzp07h549e6Js2bLSw1Tr16+PCRMm4MqVK6hUqRLq1KmDS5cu4fXr1wBSbymktEtMTIS5ubn0ncvl8mStQnFxcZgzZw6OHz8OQ0NDmJubQyaT8dhKBRMhyjS1atXC8+fPsXv3bpVy5UH88eNHfPjwAUWLFlVZziZ07aGsq3nz5mHVqlVYvHgx9u7di169emHv3r1o164dAEgjwZJuo8Qm+6wnOjoaYWFhAICwsDAMGzYMixYtkiZENDY2lpIchUKB4sWLY/DgwTh16hSKFi2KWbNmAWDdqoOBgQFatmyJ06dPY9euXdDX15eSHKWQkBC8evUK1tbWKtvy+08ZvxXKECld+TVu3Bj9+/fHhAkT8Mcff0gnVplMhtDQUPTq1QsRERFo3bp1JkdL6hQbG4tLly5h3Lhx+PXXX9GgQQP06dMHGzduhL+/P7y9vQEwwdUW+/btQ//+/VGrVi3cuXMHOXPmxLlz51C9enVcvXoVf//9N4AvP7JJWwSVj0nx8vLCx48fkZCQoLHPkN24ubmhQYMG6NmzJ/bt2wfgf0lOeHg4Bg4ciISEBOn5bvRtbCMjtUvaj+DixYsIDQ2Fra0typYti7lz5yImJgbDhw/HgQMHUKlSJYSFheHu3buIiorClStXpFsnnFtEO3w9kk9fXx8PHz6EjY2NVGZoaIh69eqhRYsW+Pfffzn6T0usW7cOv/32G6ZMmYI2bdqgTJkyUCgUyJs3L7Zu3YpWrVrBx8cHpqamqFevnsqtTuUtmOvXryM4OBgJCQkwNDTU8CfKHgoXLoxx48Zh+vTpaNu2Lfr27YuyZcvi06dPOHr0KCIiInDt2jV2jE4jJkKkdsqDbuzYsdi9ezeioqKQK1cu5MqVC4cOHYKfnx9q1KgBPz8/7Nq1C6VLl0bdunUxefJkGBgYsDOfllEmNKtWrULhwoXx66+/wsPDA+fOncPly5dRtWpVAF+SIScnJwQFBSEhIUHqA0ZZ05EjRzB69GgsW7YMnTp1ksqV/fny58+PvXv3onXr1pgzZw5kMhnq1q2rkuB++PAB0dHRWLduHczMzDTxMbIdZaJZv3595MqVC3/99RfWrVuH3bt3o0yZMihfvjwWLVrEc2k6cNQYZQhfX19MnDgRBw4cQN68efHgwQPMnDkTL168wNWrV2Fra4vY2FgIIVROkGwJ0k5v375FmzZt0KRJE0yaNAnnzp3D4MGDUaFCBfTo0QO1atVCeHg4PDw8ULBgQaxZs0bTIVMqlD8Jffv2BQCsWLEixZYc5bH6/PlzeHh4QC6XY+3atahQoYLKenFxcTA2Ns74wLORlFpxkraift2i+unTJ3z+/Bm5c+eWvmueS9OOiRCpnVwux9ChQyGTybBs2TKp/OHDh+jevTvy5cuHzZs3w8DAgLdHspFp06bB19cXDx48gKWlJY4fP45JkyYhIiIC+vr6MDExQXx8PK5fvw5DQ0PeHsvCEhMTUapUKXh5eWHixInJ6kr5+tOnT7C2tkZQUBBmz56NtWvX8jbMT0qaBN28eRNRUVFwdHSEk5NTmhNKHlvpw/+x9NO+zqX19fURGhqKGzduqJQXL14cLVq0QFBQEOLi4nigaqmv61s5FH7o0KHInz8/li9fDoVCgYYNG2Ljxo1YuHAhWrVqhb59++LGjRvSZIms/6zLwMAAenp6ePPmDYD/TXOgJJPJ8PHjRzRr1gz//fcfihUrhvXr10t9UujHJO1sPnHiRHh6eqJPnz6oXbs2RowYgTt37qRpPzy20oeJEP20pH1E5s6dCwBo0qQJPn/+jB07dqiMFilevDgUCgViYmI0Eiv9HIVCIdW3r68vAgMDER4eDgAwNzdH5cqVcfz4celkXqJECTRt2hQzZ85E3759YWBgALlczn4LWZhCoUBiYiJcXV1x+vRpXLp0CQCSDdH++PEjrKyskrVSsEXoxymPLR8fH6xduxbr1q1DYGAgWrRogW3btiEiIkLDEWZP/B9LahEVFYXTp0/j5s2bAICmTZvC3t4eq1atgp+fH8LDw/H27VusXr0aBQoUgK2trWYDpnRLerX64MED7Nu3D40aNULXrl2xY8cOGBoaYvLkyXj48CF8fX1T3Q/7LWRtenp6MDAwwLBhwxAUFIQ5c+ZIrbvK+o+MjMT48eNhZmaGYsWKaTLcbEGZYMrlciQmJuL8+fMYNWoUatWqhb/++gtbt26Ft7c3qlevjvj4eERHR2s44uyFfYRIbU6ePInGjRvj2LFjqFevHkJCQjBw4EDcv38fT548QfHixQEAV65cgaGhIYd1apGkdTVw4ECcO3cON2/exP79+3H58mUsXboUjRs3RtmyZREREYGwsDCsWrUKRkZGbKbXQsr63r59O7p06YJq1aqhbdu2aN68OS5cuIANGzbg/fv3uHHjBgwMDHgs/4Sk/Xlev34NR0dH1KxZE/Pnz4dCoUCjRo2wYMEC9OvXD/Hx8fD19YWrqytq1aql4cizDyZC9NOUB7JcLke3bt1gbm6OhQsXwtzcHNHR0Xj58iUuX74sPXBVX1+fwzq1VEhICIYMGYK+ffuqTNZ248YNHDlyBLt378atW7cAQHrMAmm3f/75B2PGjEFQUBBiYmJQtmxZlC1bFn5+ftKtTrby/ZikSVD//v1x5MgRPH/+HH379sXhw4cRGhoKX19fdO3aFcCX6Qjatm0LDw8PDB48WJOhZytMhChdkl75zZkzB7a2tnBzc0OJEiUAACtXrsTs2bNx9epV2Nvbp7gPnji108qVKzF37lwULFgQO3fuhI2NjTSbsLIzrUKhwNq1a7F582Y4OTlh/fr1MDEx0XTo9IOUdfvhwwfExcUhODgYRYsWRe7cufkATzV6/Pgxxo4di8GDB6Nu3br477//MGzYMLx79w63bt2CgYEBPn36hC5duiAiIgL+/v48h6oR2zIpXZRJ0Pnz56FQKDBp0iR0794dQ4YMwbt37zBgwACULVsWv//+e6r74AGsHR48eIDLly/D398fAGBjYwNra2vcv38fOXLkkJ4Sr7yiVSgU0NfXR9++fdG1a1f8999/iIqK0uRHoO/43nWwsm5tbGzg5OSEatWqwcbGhg/wVKONGzfC09MTYWFhUgtq6dKl0bdvX5iamsLJyQnVq1dHkyZNEBISgjNnzqg8uJh+HluEKE2StgSNGzcOS5YsQWRkJO7fv49bt25h2rRp0skyT548ePLkCTZv3gwbGxvOaaGFtm7dihUrVsDW1hZNmjRB37598fnzZ5w4cQIDBw5EsWLFcOrUKQCqLXzK/ydRUVFwdnbGxo0b+byjLER5LCY9nuVyOfT09FQej0GZIzExEUuXLoWfnx9CQ0Px4sULaZlCocCbN2+wa9cuJCYmwt7eHh07dmTXgowgiNLh2bNnYvz48eKff/5RKY+NjRWbN28W3bp1EzKZTMhkMvHHH39oKEr6GX5+fiJHjhxiy5Yt4vHjxyrL4uLixIEDB0SRIkVEkyZNpPKEhASV9Xx8fESuXLlEcHBwpsRMaRcXFyd+//13sXv3bpXyI0eOiIMHDwq5XK6hyLK/lL7byMhIsWbNGuHg4CDatGkjEhMThRBCKBSKFPehXE7qw1tjlGY7duxA4cKFsXv3bpX+P3K5HCYmJujcuTM2bNiAs2fPonfv3ti7dy/evn2rwYgpva5fv46pU6fCx8cHnTp1QuHChQF8aUkQQsDIyAiNGjXCokWL8OjRIzRv3hwAkl2dWlhY4MyZM8ibN2+mfwb6tg8fPuDhw4c4ePAgDh48CAA4dOgQmjZtivDwcI7+yiBJW+Fu376N27dvIygoCObm5ujatSumT5+Ox48fo3v37pDL5ZDJZCpzsCmxa4H68X88perGjRvYv38/Nm7cCAAoVKgQPD09ERwcLE2il5iYKB2Y4v/vstasWROdO3dGYGAggoODNRM8/ZD79+/D3t4eTZs2VSmXyWTSLRUjIyM0a9YMPj4+OHv2LEaPHp1sPz179kS5cuUyK2xKB0dHR3h7e8PIyAiHDx/GxIkT0alTJ6xZswadO3fWdHjZkkgyB9eECRPg7u6Opk2bonz58vjtt98QGhqK7t27Y+DAgbh37x569uwJuVye4jPeKANotkGKsqoNGzYIV1dX0aFDB+Hr6yuV//vvv6JRo0bCxsZGBAYGCiFUm2qTNueWK1dOrF27NvOCpp82fPhw4ezsnOIyZd0+fvxYBAQECIVCIc6dO8emei2jrK/Pnz+LX3/9VRgaGopBgwZJy1O7JUM/b9GiRcLGxkacOnVK3LhxQ2zYsEHkzJlT9O7dW0RGRoqYmBjh6+sr8ubNK6ZNm6bpcHUGe1tRMps3b8aAAQPg5+eHunXrwsbGRlrm6uqKuXPnYuLEiWjYsCGOHz8OZ2dnqcOssqPl2rVr8fjxY076pWWsrKzw6dMnREVFwdzcXKUjtHKuKF9fXzg4OKBGjRpwc3MDwCkRtInyGD137hwuXLiAatWqITo6Gn///TeaNWvGztIZQNm5+fz58/Dy8kLdunUBAOXLl4ednR3c3d1RtmxZDB06FJ07d4a9vb1025kyHm+NkYqHDx9izpw58Pb2Rtu2baUkSPx/HxEAcHFxwcyZM+Hi4oImTZrgzp07yX4Ey5Yti2vXrqFo0aKZ/hnox7Vv3x5RUVEYNWoUgC/9EZL2U4iMjMSDBw+QO3dule2YBGkPPT097N69G82bN8eqVauwbds2GBkZYffu3di9e7emw8s2nj9/jqtXryI+Ph4GBgaIj4/Hy5cvpUQzMTERiYmJaNSoEUaMGIF169YhMjIS5ubmcHd35xD5TMREiFQEBwcjPj4eDRs2VClX9hFRHpiurq5YuHAh7OzsMHny5GT7qVKlCpydnTMlZlIfJycn9O/fHxs2bJBmrlX2U3j79i26dOmC0NBQ9iXRYmFhYTh48CAWLVqEzp07w8nJCRMmTEB0dDTu37+v6fCyhR07dqBLly4YMGAAVqxYAQAwMjJC06ZNsW7dOty5cwcGBgZSUmRhYYHcuXPDwsJCZT+8wMgcnEeIVPj6+mLKlCl4+PAhrKysUlzn2bNn8Pf3R7du3fDw4UMULVqUI02ykefPn2Pu3LlYu3YtSpYsidq1ayMiIgL3799HfHw8Ll26BENDQ94O02IfPnxQae2VyWR48+YN7OzseCz/pPXr12PYsGFYvnw5atasiYIFC0rLHj16hNGjR+PZs2fYsGEDXFxcEBsbi1atWsHGxgZbtmzRXOA6jP/jSYW1tTVCQkLw5MkTAF+ab5MSQmDbtm3SlWPx4sWhp6cnPT2ZtF+BAgUwdepU7N27F/b29rh48SLCw8PRvHlzXL58GYaGhiqjBSlrSWnI9deS9vtTtko4ODjwWP5Jly5dwvTp07F06VJ07dpVSoKU32nRokUxatQoFC1aFJUrV0bFihVRuXJlvH79Gn5+fgC+P9s3qR9bhEhFVFQUqlWrBgMDA/j7+8PS0hIJCQnS7ZGYmBh07twZbm5uUj8Syt5iYmJgZmYmvWZLUNZ04MABHDhwAPfv30fjxo0xaNAg5MqVS9Nh6RRfX1/4+fnhr7/+gp2dncoykWTW7piYGBw8eBCvXr2CpaUlunfvDgMDA84YrSFsESIVZmZmGDJkCN68eYMGDRrgzZs3UhL06NEjeHp64vXr1xg+fLhmA6V0SXq98/UVf2rXQsrypEkQwH4LWdH69evRo0cPGBkZwcXFBTNmzMDs2bM1HZbOOX36NAwNDZMlQcD/Wt6ePHkCfX19tG/fHiNHjkTv3r1hYGAAuVzOJEhD+K2TRPz/pF89evTA58+fsXjxYhQuXBj16tVDVFQUYmNjoa+vj4CAAGlEA38UtYNMJsPnz59hYmICPT09JCQkSJ01Q0NDYW1tneI2lPX5+/tj2rRp+OOPP6RO7A0bNkSPHj3Qv39/FClSRMMR6o6iRYvi0qVLePLkiTQre1JyuRwjR45EtWrVMH78eJVlPJdqDluESJJ05uBBgwbhyJEjGD16NKysrFCyZEn0798fAQEB7COipdq1a4caNWoA+DISTCaTYf/+/fDw8MC7d+80HB39iMTERJw6dQrVq1eHu7s7gC8XNM7OzjA3N9dwdLqnTJkyCA4OxoEDBxAdHZ1s+cePH6Gvr49SpUppIDpKDfsIUTLiqydQJ31GDsA+ItrqxYsXaNiwIYoVK4aDBw/iyJEj8PDwwJIlS9CnTx9Nh0c/6N9//8XNmzfRo0cPqSwqKgrlypXDnj17UL58eQ1Gp3t69uyJnTt3Yv78+WjTpg3s7OygUCgQFhYGLy8vxMbG4tixYzyHZiFMhHRE0uQltUTm64SHsh9lMmRhYYEHDx5g6dKl8PLy0nRY9IO+vmhRiomJQbFixbBlyxbUqVMHALB48WI0adKE83upwdffu/JnVDkNwejRo7Ft2zbUq1cP9erVw6tXr3D37l2EhYXh6tWrnH4ii+Gvno7Q19dHTEyM1DQbHx8vHbxPnz4FACZB2ZgQAgqFAvnz58eoUaPw77//omDBglISxBlstYPymE36w5vSOomJiTAxMZGGyf/6669YunQpihUrlnnBZlMKhUL63h8+fAjgfxPOAl+mIdiyZQsWLFiAxMRE/PHHH3j69Cnc3Nxw7do1di3IgvjLp0NmzZoFW1tbvHnzBkZGRpDJZNi3bx+aNm2KwMBATYdHGUxPTw979+7FqFGjMGvWLMTGxqJly5YAviTKnD8m63vx4gWALz+83xrtp1AoYGpqivj4eLi7u+Ply5d48OAB61kNkj5FfuTIkan2rxs5ciROnjyJoKAgHD58GDNnzuTosKwqM57sSllHt27dhJ2dnRBCiDNnzggzMzOxatUqDUdFmeHAgQPCzMxM+Pr6CiGECA4OFiVKlBC//PKLhiOjtLh165YwMDAQa9askcpSe1J8dHS0KFy4sMiZM6coWrSoiI+PF0IIkZCQkCmxZkdJv+vz58+LqlWriitXrnxz3dTqh7IWtgjpmPXr18Pd3R05c+ZEs2bNsG7dOvTt21fTYVEmiIqKwrJly9CvXz8AQN68eXHs2DHky5ePrQRaIFeuXBg0aBDGjh2LjRs3Aki9Zejz58949+4d8ubNi8DAQOl2DFsifpzy1teff/6JdevWoXjx4qhcuXKK379yXU5BoR3YWVpHiP9/eryenh727duH9u3bw9TUFE+ePEHu3Ll5ktRB4jujAynrefXqFZYsWQJfX18sW7YM3bp1A6Bad+/fv8fHjx9hZmYGJycnzlisZoMGDcLKlSvh7OyMkydPwsHBQdMh0U/ikaFDlEmQl5cXli1bhvPnz6N06dK4efMm7O3tOYpBy6U3kfn6apVJUNalTGScnJwwdOhQAMDgwYMBAN26dVNJglq1aoWEhARcvXpVZVtKv5SOqeXLlyNPnjz4448/sHbtWvTr1w+2trYaipDUgUeHjpDJZDh58iQ6dOiApUuXom/fvujbty+8vLzg6OiIDx8+pDi7MGVtf/31F65evYpp06ZJHWGZ0GQPSes2aatO3rx5U0yG3r17B09PT4SFheHWrVvSfpgE/Zikx9KFCxeQkJCAmJgYNGnSBFOmTEFsbCz+/PNPmJmZoVu3bioPsiXtwiNEhzg5OWHz5s1o27atVLZhwwYUKVIEVlZWGoyMfsT+/fvRpk0bFC5cGDKZDFOnTmUylE2kVLepJUNDhgxBeHg4jhw5go8fP+LWrVvsE6QGSUeH7d+/X3pMTbFixbBnzx7MmTMHQggsXboUenp66NSpE/LkyaPhqOlHsI+QjkjLjyNvjWmPoKAgdO/eHVWrVoWBgQH8/f1Rr149zJgxg8mQlvte3SZNcF69eoXly5djzpw5KFasGO7cucMkSI18fHwwc+ZMHDlyBJUrV8bixYsxatQonDp1SpqocuzYsfjjjz/g5+eHDh06aDZg+iE8UrKBlH70vu4Im5YfRSZB2iNfvnxwc3ODh4cHypUrh+nTp+PUqVMAkGIyxMRIe3yvbpVz0ejr68PJyQk9evRAkSJF4OXlxY7Ranb37l3MmDEDlStXxt69ezFt2jSsXLkSderUQWRkJCwsLDBv3jwUKFBApaWdtAtbhLRc0h+4mzdvIioqCo6OjnBycoKxsbGGo6OMoExyExISYGhoCAAIDw/H3LlzcerUKdStWxezZs2Cnp4eQkNDkStXLg1HTGmVnrr9+PEjcufOrbI9kyD1SUxMRKVKldCvXz84OzujZcuWmD9/Pvr37w+5XI4ZM2agWLFi6Ny5s7QNW9W1Ey8RtZhyODwATJw4EZ6enujTpw9q166NESNG4M6dOxqOkDKCsqVP+UOZmJgIKysrjB8/HnXr1sXp06cxadIkvH79GrVr18bYsWM1GS6lQ3rqtm7duhgzZozK9kyCfkxK82gZGBigQ4cO2LFjB5o1a4ZFixahf//+AIDQ0FBcvXoV79+/V9mGSZB2YiKkxZQnTR8fH6xduxbr1q1DYGAgWrRogW3btiEiIkLDEVJmMDAwgEKhgKWlJX777TfUr18fx48fR5kyZSCXyzFz5kxNh0g/6Ht1O2vWLE2HqPWStqo/ePAA9+7dQ0JCAgCgQYMGePfuHcqXL4+KFSsCAF6+fAkvLy98+vRJ6rBO2o23xrSQ8sCVy+UQQqBjx46oUqUKxowZg7/++gteXl6YM2cO+vfvj/j4eCQkJCBHjhyaDpt+0OXLl+Ho6Ih8+fJ9cz3lbZVHjx6hUqVKKFmyJM6dO8d+I1kY6zbrmDBhAjZs2IDExEQYGhpizJgx6NevHy5duoShQ4dKyZGlpSUA4Pz583yKfDbBREjLJO0E/fr1azg6OqJmzZqYP38+FAoFGjVqhAULFqBfv36Ij4+Hr68vXF1dUatWLQ1HTuklhEBoaChsbGzg4eGBxYsXI2/evN/cJjQ0FO7u7tIwav5QZk2sW81L2hJ04MAB9O3bF6tXr0b+/PmxdetWHDhwAO7u7pg7dy7u37+PR48eITAwEM7OzmjatGmyEXykvViDWiRpEtS/f38cOXIEz58/R8mSJeHp6YnQ0FD4+vqia9euAICIiAjs27cPenp6TIS0kEwmg7W1Nfz9/dGkSROYmJjA29v7mz+YuXLlwi+//CI96Zon6qyJdat5yiRo/fr1+Pz5M0aPHo2WLVsCAFxdXWFvb49FixahSpUq8PDwgLOzM5o3by5tz6fIZyOZ9HBXUqNHjx6JNm3aiFOnTgkhvjyVuk6dOqJkyZIiPj5eKBQK8eHDB9G4cWNRvXp1kZiYqOGI6Ucp6+7ChQvC2NhYdOnSRQQHBydb7+3bt8LHx0d8/vxZKuOTxrM21q3mhYSEiMKFCwuZTCYGDRokhFD9bj09PcUvv/yiqfAok7CztJbZuHGjNI1+pUqVAAClS5dG3759YWpqCicnJ1SvXh1NmjRBSEgIzpw5A319fcjlcg1HTj9CWXe//PILTp8+jV27dmHChAkIDg6W1nn37h1atWoFHx8fabQRwBFEWR3rVrMUCgVsbGywb98+1KlTB4cPH8arV69gYGAgPVG+XLlyMDc3T/EJ85R98GjSIomJifj48SMUCgWCgoJgYWEB4MsJtX379qhVqxZ27dqFxMRE2Nvbo2PHjryPnQ18/YNZt25dAMDcuXNhaGiIdu3aISoqCg8fPoSenh4nT9QirFvNmD17NuLi4jBx4kSUK1cOS5cuRadOndC4cWPs2bMHtra2MDU1xYkTJ2Bvb5/sAcWUvbCzdBaW0kkvKioKO3bswKRJk/DLL79g586d0NfXTzaTtBJHNGQfyrq8ePEi6tWrh+bNmyM4OBjh4eH477//+GgFLca6zVzz58/HuHHjMHfuXAwbNgxGRka4e/cuunTpgufPn6NQoUIoW7Ysbty4gevXr8PQ0DDVcyxpPyZCWVTSJOj27dsAABMTExQrVgzx8fHYuHEjli1bhrJly8LPzw/6+voqs9GSdknLY1KA//1gXrp0CdWrV0fRokVx9+5d/lBmYaxbzUqtFW3FihUYPHgwvL29MWLECBgZGeHOnTsYMWIELl++jPPnz6Ns2bIAOGN3dsdEKAtKepKcMGECduzYgYSEBISGhmLo0KEYNmwYcufOjXXr1mHVqlUoU6YM1q1bx5YfLZXex6Qo1w8KCkKhQoU4gigLY91mHffu3UOpUqVUypYtW4ahQ4fC29sbw4cPh7GxMe7cuYNOnTpBT08PFy5cgJmZGW9JZnca6aJNabJo0SJhY2MjTp06JW7cuCE2bNggcubMKXr37i0iIyNFTEyM8PX1FXnz5hXTpk3TdLj0AxQKhfTv3377TRQpUkQ4OzuLvHnzigEDBojbt2+nuJ1cLpf+zRFEWRPrVrOSjrI7efKkkMlkYvPmzcnWmzdvnjA0NBTLli0TMTExQggh7ty5IypUqCDy588vIiMjMy1m0gwmQlmQ8uTn4eEhRo0apbLs6NGjwtjYWCxZskQIIURkZKTYv38/h8hrucWLFws7Oztx9uxZIYQQAwYMEDlz5hTnz5/XcGT0s1i3me/YsWNi3rx54vLly1LZ6NGjhampqdiyZYvKuoGBgcLS0lLIZDKxadMmqfzmzZuiRo0a4vHjx5kWN2kGE6Es4tmzZ+LKlSsiLi5OCCFEXFycqFq1qhg9erQQ4ktypEyQxo8fL1xcXERERITKPpgMaQ/lVX9iYqJISEgQnp6eYt68eUIIIfbv3y+srKzEypUrhRBf/i9ERUVpLFZKH9atZq1bt044OTmJAQMGiCtXrqgsGzt2rDA0NFRJhp48eSJ+++03sXPnzmQtcMrzMWVvTISygO3btws3NzdRsWJFsXjxYql82rRpwtraWmpCVyY6s2bNEvXq1dNEqKQGSW+ZvHr1SgghhJubm7h48aI4f/68MDc3F76+vkKILyfiJUuWSK0JlLWxbjVr27ZtwszMTOzYsUOEh4enuM6oUaOEnp6emDp1qti1a5do0aKFaN68ubSctyN1DxMhDVu3bp2wsLAQGzduFE+fPlVZFhQUJNzd3YWLi4u4efOmEEKImJgY0bBhQ9GpUycNREs/K+kPZb9+/UT+/PmFEEL06dNHODk5CTMzM7Fx40ZpnZCQEFGnTh2xdOnSTI+V0od1q1nv378XderUEcuWLVMpj4yMFJcvXxYXLlyQyubOnSvy5s0rnJ2dRa1atUR8fHxmh0tZCBMhDbp48aIoWLCg8PPzUylP2lnS399feHh4CENDQ1GhQgVRunRpUaZMGenATXryJe3Bx6RkX6xbzXj//r0oVaqU2Ldvn1S2YsUK4enpKWQymXB0dBRubm7SOfPZs2fi1atX0vmWLUG6i2MyNejmzZuws7ND48aNVcr19PSkIfQ1a9ZExYoVcfDgQbx69QqWlpbo3r07h9VqsY0bN2Lx4sWwtrZO9piUBQsWwMnJCUWKFIFcLodCocDFixelGYg5RULWxrrVrIiICPz999+wtLTEihUr8PDhQ7i5ueHYsWMIDw/HuHHjMGPGDEyePBn58+eXpilRKBQ8l+ow1rwGnT59GoaGhrCzs0u2THmAPnnyBE5OTmjfvr3Kcj75WDvxMSnZF+tWs2xtbeHn5wcPDw+cOnUKFhYW8PHxgYuLC3Lnzo3Q0FBYWlpCoVAAgMqElpwjSLdxQkUNmjhxIjZv3ozTp0+jcOHCyZbL5XJ4eHigWrVqGD9+vAYipJ/Fx6RkX6zbrCkkJARRUVEoVKiQSnloaCjc3d3RpUsX9O3bV0PRUVbENFiDypQpg+DgYBw4cADR0dHJln/8+BH6+vrJZkMl7fD1Y1Ju376NoKAgmJubo2vXrpg+fToeP36M7t27Qy6XQyaTISEhIdl++EOZ9bBusy5bW9tkSVBISAi6du2K+Ph49OrVS0ORUVbFFiEN69mzJ3bu3In58+ejTZs2sLOzg0KhQFhYGLy8vBAbG4tjx47xhKllBB+Tkm2xbrXHhw8fsGbNGgQEBOD9+/c4f/48DA0N2RJHKnhjOhN83SyuzD1lMhlmzZqFuLg4DBo0CHv27EG9evXw6tUr3L17F2FhYbh69So7U2ohZX0vXrwYa9aswc6dO5EzZ07cvn0bw4YNQ0hICBYvXoyuXbtCCIGZM2di1qxZmDx5soYjp+9h3WqPly9f4vz58yhatCj279/PQSaUIrYIZbCkTegPHz5E8eLFU1xv0aJFOHDgAO7fv48KFSqgQoUKmDp1Kg9cLaWsM09PTxQsWBALFiyQlh07dgzu7u6YN28ehg4diqioKJw8eRLNmzdnsqsFWLfaJSwsDFZWVpDJZLygpBQxEcokEyZMwO3bt7F27doUR4kBXzpOxsTESKNNlGU8cLXD8+fP8f79e7i4uMDIyAjx8fGoVasWatasifnz5yMxMREAYGBggAkTJuDIkSM4d+4c61sLsG61X2od1onYWTqDJM0vL1y4gNOnT2PKlCkpJkHKdfX09FROnAA7U2qLHTt2oEuXLhgwYABWrFgBADAyMkLTpk2xbt063LlzBwYGBtKJ2MLCArlz52Z9awHWbfbAJIhSw/stGUR50P3555+4fPkyihcvjsqVK6d4VaJ8zQNVO61fvx7Dhg3D8uXLUbNmTRQsWFBa1qlTJ9y4cQNdunTBhg0b4OLigtjYWJw9exb29vaaC5rShHVLlP3x1lgGGzRoEFauXAlnZ2ecPHkSDg4Omg6J1OjSpUvo2LEjpk6dCi8vL6k8ad+wc+fOYcmSJThw4ADKli2LuLg4yGQy3LhxA4aGhmyyz6JYt0S6gS1CapTSBGvLly9Hnjx58Mcff2Dt2rXo168fbG1tNRQhqRsfk5J9sW6JdAOPUjVJmgRduHABCQkJiImJQZMmTTBlyhTExsbizz//hJmZGbp16wYbGxsNR0zqwMekZF+sWyLdwCNVTZRJ0IQJE7B//37IZDJ8/vwZxYoVw549ezBnzhwIIbB06VLo6emhU6dOyJMnj4ajpp9VtGhRXLp0CU+ePEn1MSkjR45M8TEp7DybtbFuiXQDR42pkY+PD/78809s3LgR9+7dw5AhQ3DixAlcu3YNADB37ly0bdsW48ePx6lTpzQcLakDH5OSfbFuiXQDW4TU6O7du5gxYwYqV66MvXv3Ytq0aVi5ciXq1KmDyMhIWFhYYN68eShQoADatm2r6XBJDTp27IgTJ07g999/h7GxcbLHpPTq1QuxsbFo1qyZpkOldGLdEukGjhpTk8TERFSqVAn9+vWDs7MzWrZsifnz56N///6Qy+WYMWMGihUrhs6dO0vbcII17fGtx6S8efMGo0ePxrZt21CvXr0UH5PC5xtlXaxbIt3GW2M/QKFQJCszMDBAhw4dsGPHDjRr1gyLFi1C//79AQChoaG4evUq3r9/r7INT5zaQaFQSD+UDx8+BPDlR1JZ5uDggC1btmDBggVITEzEH3/8gadPn8LNzQ3Xrl2DoaEhEhMTWd9ZEOuWiNgilE5JR4c9ePAAcrkcxYoVg6GhIa5du4auXbvC2toaS5cuRYUKFfDy5Uv069cPnz59QkBAAE+YWoyPScm+WLdEuouJ0A+aMGECNmzYgMTERBgaGmLMmDHo168fLl26hKFDhyIhIQEAYGlpCQA4f/48m9C1TNJbJhcuXMDIkSOxdOlSVK5cOdV1OYGedmDdEpESO0unUdKWoAMHDmD9+vVYvXo18ufPj61bt8LX1xdv3rzB3LlzsWvXLjx69AiBgYFwdnZG06ZNoa+vzwnWtAwfk5J9sW6JSIm/ymmkTILWr1+Pz58/Y/To0WjZsiUAwNXVFfb29li0aBGqVKkCDw8PODs7o3nz5tL2nGBNe928eRPr1q2Ds7Mz3rx5w8ekZCOsWyJiZ+l0+PDhA2bOnIlBgwbh2bNnAL6MFgOAkSNH4pdffsHChQtT3Ja3w7RDSh3hly9fjilTpuDdu3dYu3YtQkJCNBAZ/SzWLRGlhE0UaaRQKGBjY4N9+/Zh+PDhOHz4MF69egUnJyepOb1cuXIIDw9nXwItxcekZF+sWyJKDROhNJg9ezbi4uIwceJElCtXDkuXLkWnTp3QuHFj7NmzB7a2tjA1NcWJEydgb2/PJEhL8TEp2RfrlohSJei75s2bJ2QymZg3b56Ii4sTQghx584d4erqKnLlyiUqVKggvLy8RNmyZUV8fLwQQgiFQqHJkOkHLV68WOTOnVtcuXJFCCHEokWLhEwmE6dPn5bWGTNmjDA2Nhbbtm3TUJT0I1i3RJQSJkJfkcvlKZYvX75cyGQyMWfOHCkZun37tmjQoIGwsLAQ//33n7RuQkJCpsRK6te7d2+xYsUKIYQQe/bsEVZWVsLX11cIIURERIS03rJly0RiYqJGYqQfw7olopRwHqFU3Lt3L9nDFJctW4ahQ4fC29sbw4cPh7GxMe7cuYNOnTpBT08PFy5cgJmZmUp/BNIefExK9sW6JaLU8Nf6/8XFxUn/PnXqFMqUKYMtW7aorDN48GDMnTsXkyZNwpo1axAbG4syZcpg27Zt0NfXR8mSJREVFcUkSAvwMSnZF+uWiNKDv9gAjh8/jj/++ANXrlwBANSrVw+jRo1Cnz59sHXrVpV1W7RoAVNTUwwZMgR79uwBAJQuXRrr1q1Dvnz5kp1MKev5+jEp9+7dk2YCb9CgAd69e4fy5cujYsWKAICXL1/Cy8sLnz59wtChQzUWN30f65aI0kvnb42tX78ekyZNQsuWLdGjRw+VKfbHjRuHxYsXw8/PD506dQIAPH36FGvWrIGrqytat26tMklifHw8jIyMMv0z0I/hY1KyL9YtEaWVTg+f3759OwYPHoz169ejcePG0klRae7cuZDL5ejatSuCgoJQunRpbNy4EUIIzJo1CwBUHpvBJChr42NSsi/WLRH9KJ1tEQoJCUG7du3g6emJQYMGSeVRUVG4d+8e5HI5fvnlFwDAvHnzsHTpUpibmyNPnjz4559/YGhoqKnQ6ScpH5MSHR2N0aNHS+WLFi3CokWLsGTJEnh4eCTbjq0FWR/rlojSS6cToTp16mDWrFlo1aoVAGDlypU4deoU9uzZAwcHBxQuXBj+/v6QyWR4/vw5DA0NYW9vDz09PV49aqkPHz6gatWqePr0KQYOHIhly5ap1GXbtm3x6tUrXLhwQcORUnqxbonoR+h0Z+mIiAj8/fffOHXqFDw9PbFy5UrY2tri2LFjWLJkCV6/fo0ZM2YAAPLnzw9HR0fo6elBoVAwCdJCSR+TUqdOHekxKQYGBlBeD5QrVw7m5ubQ0esDrcW6JaIfpbOJkK2tLfz8/LBr1y706dMHjx49go+PD2bMmIFff/0V9evXh6WlpTQUN+ljMzg8XvvMnj0b06ZNQ3x8vPSYFAsLCzRu3BgPHz5EWFgYPn/+jBMnTiBnzpx8TIoWYd0S0c/Q6WaN+vXrIygoCFFRUShUqFCy5RYWFnB0dNRAZKRuhoaG+P3332Fubo5hw4ahdOnS2Lp1K7p06YJq1aqhUKFCKFu2LMLCwnDy5EkA4MNztQTrloh+igZms87y3r9/L5o1ayaqVq3Kqfa1EB+Tkn2xbolI3XS2s3RKPnz4gDVr1iAgIADv37/n3CJajo9Jyb5Yt0SkLjwbJPHy5UucP38eRYsWxYULF2BoaIjExEQmQVqCj0nJvli3RJRhNN0kldWEhoYKhUIhhBC8LaZFjh07JubNmycuX74slY0ePVqYmpqKLVu2qKwbGBgoLC0thUwmE5s2bZLKb968KWrUqCEeP36caXHT97FuiSgj6XRn6ZTkzJkTwJfOlGwJ0g5JH5NSp04dqXz+/PnQ09ND9+7dAUB6TIqxsTEGDx4sPSZFycXFBadOneIM4VkI65aIMhoToVRwRIl24GNSsi/WLRFlBnaWJq3Fx6RkX6xbIsosbBEirfb+/Xs4OTlJr1N7TMrYsWPRvn17PiZFi7BuiSgzcPgEaTU+JiX7Yt0SUWbg2YK0lvIxKR4eHjh16hQsLCzg4+MDFxcX5M6dG6GhoXxMipZi3RJRZmEiRFqNj0nJvli3RJQZ2FmasqWQkBD06NEDHz58wPnz5zkVQjbCuiUidWKLEGUrKT0mRV9fn49JyQZYt0SUEXgznbIVPiYl+2LdElFG4K0xynbCwsJgZWUFmUzG1oJshnVLROrGRIiyLSEEZwjPpli3RKQuTISIiIhIZ7GPEBEREeksJkJERESks5gIERERkc5iIkREREQ6i4kQERER6SwmQkSU6YQQ6Nu3L6ytrSGTyXDz5k3UqVMHw4cP13Ro3+Tn54ecOXNqOgwiUiMOnyciFW/fvsWsWbPw999/49WrV8iTJw9cXV0xfPhw1K9fXy3vceTIEbi7u+PMmTMoXLgwbGxsEBERAUNDQ1hYWKjlPX5WwYIFMXz4cJXkLDY2FpGRkciTJ4/mAiMiteKzxohI8uzZM9SoUQM5c+bE/PnzUbZsWSQkJODYsWMYNGgQ7t+/r5b3efz4MRwcHFC9enWpzNraWi37/hYhBORyOQwMfuzUZ2pqClNTUzVHRUSaxFtjRCQZOHAgZDIZrly5Ag8PDxQvXhylS5fGyJEjcenSJQDAixcv4O7uDnNzc1haWqJdu3Z49+6dtI+pU6fC1dUVmzZtQsGCBWFlZYUOHTogMjISANC9e3cMGTIEL168gEwmQ8GCBQEg2a2xN2/eoFmzZjA1NUWhQoWwdetWFCxYED4+PgC+JG3K22pKYWFhkMlkOHPmDADgzJkzkMlkOHLkCCpWrAhjY2MEBATg8ePHcHd3h52dHczNzVG5cmX8888/0n7q1KmD58+fY8SIEZDJZNIs1indGlu5ciWKFCkCIyMjlChRAps2bVJZLpPJsGbNGrRu3RpmZmYoVqwYDhw48KNVRERqxkSIiAAAnz59wtGjRzFo0CDkyJEj2fKcOXNCoVDA3d0dnz59wtmzZ3HixAk8efIE7du3V1n38ePH2L9/Pw4dOoRDhw7h7NmzmDNnDgDg/9q5n5CoujCO49/pH05lOYuowEExpUYdFxX9GUELJowBIaFaJEgttKWCY0QI0dCihSgWIrXICFq0cKpVUNlU4KIRnIrqUhMlmg1EpMi0Se28i+jipG/52hS9zO+zmnPuwzPn3NUzZ557Ozs7CYVC5ObmkkgkGBgYmHM9dXV1vHv3jnv37tHb28uFCxd4//79gvZ2/Phxzpw5g2VZlJWVkUwmCQQC9PX1EYvF2Lt3L9XV1QwPDwMQDofJzc0lFAqRSCRIJBJz5r127RqNjY00Nzfz9OlTjh49ypEjR4hEIilxp06d4uDBgzx58oRAIEBtbS0fP35c0F5EJM2MiIgx5uHDhwYw4XD4X2Nu3bplFi9ebIaHh+25Z8+eGcBEo1FjjDEnT540y5cvNxMTE3ZMS0uL2b59uz3u6OgweXl5KbkrKytNY2OjMcYYy7IMYAYGBuzr8XjcAKajo8MYY8ybN28MYGKxmB0zNjZmABOJRIwxxkQiEQOY69ev/3T/JSUl5ty5c/Y4Ly/P/q5venp6zOrVq+2xz+cz9fX1KTEHDhwwgUDAHgOmtbXVHieTSQOYmzdv/nRNIvL76URIRICv/TM/Y1kWbrcbt9ttzxUXF5OTk4NlWfZcfn5+StPz+vXr/9NpzosXL1iyZAmbN2+25woLC3G5XPPOMdPWrVtTxslkkmAwiMfjIScnh5UrV2JZln0iNF+WZVFeXp4yV15ennIvAMrKyuzPK1asYNWqVQs+3RKR9FKztIgAUFRUhMPhSEtD9NKlS1PGDoeDL1++/HLemRYt+vo7bmYBNzk5OWfs93/1BYNBbt++TVtbG4WFhTidTvbv38/nz5/TusZv/sT9EJGF0YmQiABfn9qqqqqiq6uLT58+zbo+Pj6Ox+NhZGSEkZERe/758+eMj49TXFyctrVs3LiRqakpYrGYPffq1SvGxsbs8Zo1awBS+ndmNk7/SH9/P4cPH6ampgav18u6desYGhpKiVm2bBnT09M/zOPxeOjv75+VO533QkR+LxVCImLr6upienqabdu20dvbSzwex7Iszp49y86dO/H7/Xi9XmpraxkcHCQajVJXV0dlZeWsv59+xaZNm/D7/TQ0NBCNRonFYjQ0NOB0Ou0nuJxOJzt27LCboO/fv09ra+u88hcVFREOh3n06BGPHz/m0KFDs05o8vPzefDgAaOjo3z48GHOPC0tLVy6dInu7m7i8Tjt7e2Ew2GCweCv3QAR+WNUCImIraCggMHBQXbv3k1zczOlpaXs2bOHvr4+uru7cTgc3LhxA5fLRUVFBX6/n4KCAq5evZr2tVy+fJm1a9dSUVFBTU0N9fX1ZGdnk5WVZcdcvHiRqakptmzZQlNTE6dPn55X7vb2dlwuFz6fj+rqaqqqqlL6kQBCoRBDQ0Ns2LDBPn363r59++js7KStrY2SkhLOnz9PT08Pu3btWvC+ReTP0pulReR/4e3bt7jdbu7cuZO2N1yLiKgQEpG/0t27d0kmk3i9XhKJBMeOHWN0dJSXL1/Oaj4WEVkoPTUmIn+lyclJTpw4wevXr8nOzsbn83HlyhUVQSKSVjoREhERkYylZmkRERHJWCqEREREJGOpEBIREZGMpUJIREREMpYKIREREclYKoREREQkY6kQEhERkYylQkhEREQylgohERERyVj/AHXd6mKQgYKAAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_average_speedup(\"100GHz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Seconds'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:3790\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3789\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3790\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3791\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Seconds'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[172], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# plot average speedup for 100GHz for each configuration in one plot\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m superconductingcorecryocache_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSpeedup_100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43msuperconductingcorecryocache_data\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mSeconds\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m/\u001b[39m superconductingcorecryocache_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSeconds100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m      4\u001b[0m superconductingcorel1_cryol2l3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSpeedup_100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m superconductingcorel1_cryol2l3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSeconds\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m/\u001b[39m superconductingcorel1_cryol2l3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSeconds100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m      5\u001b[0m superconductingcorel1l2_cryol3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSpeedup_100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m superconductingcorel1l2_cryol3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSeconds\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m/\u001b[39m superconductingcorel1l2_cryol3_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSeconds100GHz\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/frame.py:3893\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3891\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   3892\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_getitem_multilevel(key)\n\u001b[0;32m-> 3893\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3894\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n\u001b[1;32m   3895\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m [indexer]\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:3797\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3792\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m   3793\u001b[0m         \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m   3794\u001b[0m         \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m   3795\u001b[0m     ):\n\u001b[1;32m   3796\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3797\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m   3798\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m   3799\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m   3800\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m   3801\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n\u001b[1;32m   3802\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Seconds'"
     ]
    }
   ],
   "source": [
    "# plot average speedup for 100GHz for each configuration in one plot\n",
    "\n",
    "superconductingcorecryocache_data['Speedup_100GHz'] = superconductingcorecryocache_data['Seconds'] / superconductingcorecryocache_data['Seconds100GHz']\n",
    "superconductingcorel1_cryol2l3_data['Speedup_100GHz'] = superconductingcorel1_cryol2l3_data['Seconds'] / superconductingcorel1_cryol2l3_data['Seconds100GHz']\n",
    "superconductingcorel1l2_cryol3_data['Speedup_100GHz'] = superconductingcorel1l2_cryol3_data['Seconds'] / superconductingcorel1l2_cryol3_data['Seconds100GHz']\n",
    "superconductingcorel1l2l3_data['Speedup_100GHz'] = superconductingcorel1l2l3_data['Seconds'] / superconductingcorel1l2l3_data['Seconds100GHz']\n",
    "\n",
    "superconductingcorecryocache_data['Speedup_10GHz'] = superconductingcorecryocache_data['Seconds'] / superconductingcorecryocache_data['Seconds10GHz']\n",
    "superconductingcorel1_cryol2l3_data['Speedup_10GHz'] = superconductingcorel1_cryol2l3_data['Seconds'] / superconductingcorel1_cryol2l3_data['Seconds10GHz']\n",
    "superconductingcorel1l2_cryol3_data['Speedup_10GHz'] = superconductingcorel1l2_cryol3_data['Seconds'] / superconductingcorel1l2_cryol3_data['Seconds10GHz']\n",
    "superconductingcorel1l2l3_data['Speedup_10GHz'] = superconductingcorel1l2l3_data['Seconds'] / superconductingcorel1l2l3_data['Seconds10GHz']\n",
    "\n",
    "superconductingcorecryocache_data['Speedup_20GHz'] = superconductingcorecryocache_data['Seconds'] / superconductingcorecryocache_data['Seconds20GHz']\n",
    "superconductingcorel1_cryol2l3_data['Speedup_20GHz'] = superconductingcorel1_cryol2l3_data['Seconds'] / superconductingcorel1_cryol2l3_data['Seconds20GHz']\n",
    "superconductingcorel1l2_cryol3_data['Speedup_20GHz'] = superconductingcorel1l2_cryol3_data['Seconds'] / superconductingcorel1l2_cryol3_data['Seconds20GHz']\n",
    "superconductingcorel1l2l3_data['Speedup_20GHz'] = superconductingcorel1l2l3_data['Seconds'] / superconductingcorel1l2l3_data['Seconds20GHz']\n",
    "\n",
    "superconductingcorecryocache_data['Speedup_50GHz'] = superconductingcorecryocache_data['Seconds'] / superconductingcorecryocache_data['Seconds50GHz']\n",
    "superconductingcorel1_cryol2l3_data['Speedup_50GHz'] = superconductingcorel1_cryol2l3_data['Seconds'] / superconductingcorel1_cryol2l3_data['Seconds50GHz']\n",
    "superconductingcorel1l2_cryol3_data['Speedup_50GHz'] = superconductingcorel1l2_cryol3_data['Seconds'] / superconductingcorel1l2_cryol3_data['Seconds50GHz']\n",
    "superconductingcorel1l2l3_data['Speedup_50GHz'] = superconductingcorel1l2l3_data['Seconds'] / superconductingcorel1l2l3_data['Seconds50GHz']\n",
    "\n",
    "# # Calculate average speedup for each configuration\n",
    "# average_speedup_100GHz = {\n",
    "#     'Superconducting Core Cryo Cache': superconductingcorecryocache_data['Speedup_100GHz'].mean(),\n",
    "#     'Superconducting Core L1 Cryo L2/L3': superconductingcorel1_cryol2l3_data['Speedup_100GHz'].mean(),\n",
    "#     'Superconducting Core L1/L2 Cryo L3': superconductingcorel1l2_cryol3_data['Speedup_100GHz'].mean(),\n",
    "#     'Superconducting Core L1/L2/L3': superconductingcorel1l2l3_data['Speedup_100GHz'].mean()\n",
    "# }\n",
    "\n",
    "# # Plotting\n",
    "# plt.figure(figsize=(10, 6))\n",
    "# plt.bar(average_speedup_100GHz.keys(), average_speedup_100GHz.values(), color='skyblue')\n",
    "# plt.title('Average Speedup for 100GHz for Each Configuration')\n",
    "# plt.xlabel('Configuration')\n",
    "# plt.ylabel('Average Speedup for 100GHz')\n",
    "# plt.xticks(rotation=45, ha='right')\n",
    "# plt.tight_layout()\n",
    "# plt.show()\n",
    "\n",
    "frequencies = [10, 20, 50, 100]\n",
    "\n",
    "# Calculate average speedup for each configuration and frequency\n",
    "average_speedup = {}\n",
    "for freq in frequencies:\n",
    "    speedup_key = f'Speedup_{freq}GHz'\n",
    "    average_speedup[f'{freq} GHz'] = [\n",
    "        superconductingcorecryocache_data[speedup_key].mean(),\n",
    "        superconductingcorel1_cryol2l3_data[speedup_key].mean(),\n",
    "        superconductingcorel1l2_cryol3_data[speedup_key].mean(),\n",
    "        superconductingcorel1l2l3_data[speedup_key].mean()\n",
    "    ]\n",
    "\n",
    "# Plotting\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "bar_width = 0.15\n",
    "index = np.arange(len(average_speedup['10 GHz']))\n",
    "\n",
    "for i, freq in enumerate(frequencies):\n",
    "    plt.bar(index + i * bar_width, average_speedup[f'{freq} GHz'], bar_width, label=f'{freq} GHz')\n",
    "\n",
    "plt.xlabel('Configuration')\n",
    "plt.ylabel('Average Speedup')\n",
    "plt.title('Average Speedup for Different Frequencies and Configurations')\n",
    "plt.xticks(index + bar_width * (len(frequencies) - 1) / 2, ['Superconducting Core Cryo Cache', 'Superconducting Core L1 Cryo L2/L3', 'Superconducting Core L1/L2 Cryo L3', 'Superconducting Core L1/L2/L3'], rotation=45, ha='right')\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "riscv-npb-lu-size-s-run: 0.9020676166526963, 23.006286836935168, 0.7924274672342333, 11.764522821576763\n",
      "riscv-npb-bt-size-s-run: 1.1339093881363849, 0.5977812757664343, 36.73361300471945, 107.04021937842779\n",
      "riscv-npb-is-size-s-run: 4.180851063829787, 14.088198757763974, 32.61111111111111, 1.4799043062200958\n",
      "riscv-gapbs-bfs-run: 0.9341588643914225, 5.129353233830845, 23.142993326978075, 38.58764940239044\n",
      "riscv-npb-ft-size-s-run: 3.5427603297425785, 0.6647563486616335, 8.712676056338028, 1.721346859486294\n",
      "riscv-gapbs-tc-run: 1.7901234567901234, 9.340900346287032, 11.643737166324435, 18.51792524790236\n",
      "riscv-npb-cg-size-s-run: 9.420917135961384, 1.508637236084453, 8.32873399715505, 4.878620689655173\n",
      "riscv-llvm-minisat-run: 1.3424479166666665, 71.40774719673801, 14.42133815551537, 212.92097264437692\n",
      "riscv-npb-lu-size-s-run: 0.9020676166526963, 0.6647563486616335, 32.61111111111111, 38.58764940239044\n",
      "riscv-npb-bt-size-s-run: 1.1339093881363849, 9.340900346287032, 23.142993326978075, 18.51792524790236\n",
      "riscv-npb-is-size-s-run: 4.180851063829787, 1.508637236084453, 0.7924274672342333, 4.878620689655173\n",
      "riscv-gapbs-bfs-run: 0.9341588643914225, 5.129353233830845, 8.712676056338028, 1.4799043062200958\n",
      "riscv-npb-ft-size-s-run: 3.5427603297425785, 71.40774719673801, 36.73361300471945, 212.92097264437692\n",
      "riscv-gapbs-tc-run: 1.7901234567901234, 0.5977812757664343, 14.42133815551537, 1.721346859486294\n",
      "riscv-npb-cg-size-s-run: 9.420917135961384, 23.006286836935168, 8.32873399715505, 107.04021937842779\n",
      "riscv-llvm-minisat-run: 1.3424479166666665, 14.088198757763974, 11.643737166324435, 11.764522821576763\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot speedup of 100GHz for each workload in one plot\n",
    "\n",
    "# superconductingcorecryocache_data['Speedup_100GHz'] = superconductingcorecryocache_data['Seconds'] / superconductingcorecryocache_data['Seconds100GHz']\n",
    "# superconductingcorel1_cryol2l3_data['Speedup_100GHz'] = superconductingcorel1_cryol2l3_data['Seconds'] / superconductingcorel1_cryol2l3_data['Seconds100GHz']\n",
    "# superconductingcorel1l2_cryol3_data['Speedup_100GHz'] = superconductingcorel1l2_cryol3_data['Seconds'] / superconductingcorel1l2_cryol3_data['Seconds100GHz']\n",
    "# superconductingcorel1l2l3_data['Speedup_100GHz'] = superconductingcorel1l2l3_data['Seconds'] / superconductingcorel1l2l3_data['Seconds100GHz']\n",
    "# first, rename Unnamed: 0 to Benchmark\n",
    "superconductingcorecryocache_data = superconductingcorecryocache_data.rename(columns={'Unnamed: 0': 'Benchmark'})\n",
    "superconductingcorel1_cryol2l3_data = superconductingcorel1_cryol2l3_data.rename(columns={'Unnamed: 0': 'Benchmark'})\n",
    "superconductingcorel1l2_cryol3_data = superconductingcorel1l2_cryol3_data.rename(columns={'Unnamed: 0': 'Benchmark'})\n",
    "superconductingcorel1l2l3_data = superconductingcorel1l2l3_data.rename(columns={'Unnamed: 0': 'Benchmark'})\n",
    "\n",
    "# print speedups of every benchmark\n",
    "for index, row in superconductingcorecryocache_data.iterrows():\n",
    "    print(f\"{row['Benchmark']}: {row['Speedup_100GHz']}, {superconductingcorel1_cryol2l3_data.iloc[index]['Speedup_100GHz']}, {superconductingcorel1l2_cryol3_data.iloc[index]['Speedup_100GHz']}, {superconductingcorel1l2l3_data.iloc[index]['Speedup_100GHz']}\")\n",
    "\n",
    "# merge all dataframes into one on the benchmark column\n",
    "\n",
    "# merge\n",
    "merged_data = superconductingcorecryocache_data.merge(superconductingcorel1_cryol2l3_data, on='Benchmark', suffixes=('_cryocache', '_l1_cryol2l3'))\n",
    "\n",
    "# Add suffix to superconductingcorel1l2_cryol3_data columns except Benchmark column\n",
    "superconductingcorel1l2_cryol3_data.rename(columns=lambda col: f'{col}_l1l2_cryol3' if col != 'Benchmark' else col, inplace=True)\n",
    "superconductingcorel1l2l3_data.rename(columns=lambda col: f'{col}_l1l2l3' if col != 'Benchmark' else col, inplace=True)\n",
    "\n",
    "merged_data = merged_data.merge(superconductingcorel1l2_cryol3_data, on='Benchmark')\n",
    "merged_data = merged_data.merge(superconductingcorel1l2l3_data, on='Benchmark')\n",
    "\n",
    "# print speedups of every benchmark\n",
    "for index, row in merged_data.iterrows():\n",
    "    print(f\"{row['Benchmark']}: {row['Speedup_100GHz_cryocache']}, {row['Speedup_100GHz_l1_cryol2l3']}, {row['Speedup_100GHz_l1l2_cryol3']}, {row['Speedup_100GHz_l1l2l3']}\")\n",
    "\n",
    "# Width of each bar group\n",
    "bar_width = 0.2\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "# Adjust x-coordinates for each group of bars\n",
    "x = np.arange(len(merged_data['Benchmark']))\n",
    "\n",
    "plt.bar(x - 1.5 * bar_width, merged_data['Speedup_100GHz_cryocache'], width=bar_width, label='Superconducting Core Cryo Cache')\n",
    "plt.bar(x - 0.5 * bar_width, merged_data['Speedup_100GHz_l1_cryol2l3'], width=bar_width, label='Superconducting Core L1 Cryo L2/L3')\n",
    "plt.bar(x + 0.5 * bar_width, merged_data['Speedup_100GHz_l1l2_cryol3'], width=bar_width, label='Superconducting Core L1/L2 Cryo L3')\n",
    "plt.bar(x + 1.5 * bar_width, merged_data['Speedup_100GHz_l1l2l3'], width=bar_width, label='Superconducting Core L1/L2/L3')\n",
    "\n",
    "# Add x-axis label and rotate labels for better readability\n",
    "plt.xlabel('Benchmark')\n",
    "plt.xticks(x, merged_data['Benchmark'], rotation=90)\n",
    "\n",
    "# Add y-axis label\n",
    "plt.ylabel('Speedup_100GHz')\n",
    "\n",
    "# Add legend\n",
    "plt.legend()\n",
    "\n",
    "# Show plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Speedup_10GHz'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:3790\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3789\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3790\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3791\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Speedup_10GHz'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[105], line 16\u001b[0m\n\u001b[1;32m     14\u001b[0m         average_speedup[config]\u001b[38;5;241m.\u001b[39mappend(superconductingcorecryocache_data[speedup_key]\u001b[38;5;241m.\u001b[39mmean())\n\u001b[1;32m     15\u001b[0m         average_speedup[config]\u001b[38;5;241m.\u001b[39mappend(superconductingcorel1_cryol2l3_data[speedup_key]\u001b[38;5;241m.\u001b[39mmean())\n\u001b[0;32m---> 16\u001b[0m         average_speedup[config]\u001b[38;5;241m.\u001b[39mappend(\u001b[43msuperconductingcorel1l2_cryol3_data\u001b[49m\u001b[43m[\u001b[49m\u001b[43mspeedup_key\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39mmean())\n\u001b[1;32m     17\u001b[0m         average_speedup[config]\u001b[38;5;241m.\u001b[39mappend(superconductingcorel1l2l3_data[speedup_key]\u001b[38;5;241m.\u001b[39mmean())\n\u001b[1;32m     19\u001b[0m \u001b[38;5;66;03m# Plotting\u001b[39;00m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/frame.py:3893\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3891\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   3892\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_getitem_multilevel(key)\n\u001b[0;32m-> 3893\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3894\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n\u001b[1;32m   3895\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m [indexer]\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:3797\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3792\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m   3793\u001b[0m         \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m   3794\u001b[0m         \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m   3795\u001b[0m     ):\n\u001b[1;32m   3796\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3797\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m   3798\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m   3799\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m   3800\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m   3801\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n\u001b[1;32m   3802\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Speedup_10GHz'"
     ]
    }
   ],
   "source": [
    "\n",
    "# Define the configurations\n",
    "configurations = ['Superconducting Core Cryo Cache', 'Superconducting Core L1 Cryo L2/L3', 'Superconducting Core L1/L2 Cryo L3', 'Superconducting Core L1/L2/L3']\n",
    "\n",
    "# Define the frequencies\n",
    "frequencies = [10, 20, 50, 100]\n",
    "\n",
    "# Initialize a dictionary to hold average speedup for each configuration\n",
    "average_speedup = {config: [] for config in configurations}\n",
    "\n",
    "# Calculate average speedup for each configuration and frequency\n",
    "for config in configurations:\n",
    "    for freq in frequencies:\n",
    "        speedup_key = f'Speedup_{freq}GHz'\n",
    "        average_speedup[config].append(superconductingcorecryocache_data[speedup_key].mean())\n",
    "        average_speedup[config].append(superconductingcorel1_cryol2l3_data[speedup_key].mean())\n",
    "        average_speedup[config].append(superconductingcorel1l2_cryol3_data[speedup_key].mean())\n",
    "        average_speedup[config].append(superconductingcorel1l2l3_data[speedup_key].mean())\n",
    "\n",
    "# Plotting\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "for config in configurations:\n",
    "    plt.plot(frequencies, average_speedup[config], marker='o', label=config)\n",
    "\n",
    "plt.xlabel('Frequency (GHz)')\n",
    "plt.ylabel('Average Speedup')\n",
    "plt.title('Average Speedup for Different Frequencies and Configurations')\n",
    "plt.xticks(frequencies)\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  }
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