{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ab5cd7d1-1a57-46fc-8282-dae0a6cc2944",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import random\n",
    "import pandas as pd\n",
    "import itertools\n",
    "from joblib import Parallel, delayed\n",
    "import os.path\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3d1ad0b9-f6a8-4e98-84aa-6e02e4279954",
   "metadata": {},
   "outputs": [],
   "source": [
    "SEED = 42\n",
    "np.random.seed(SEED)\n",
    "random.seed(SEED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a92c6772-6609-41a8-a3d1-4d640b69a864",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 596 ms, sys: 151 ms, total: 747 ms\n",
      "Wall time: 746 ms\n"
     ]
    }
   ],
   "source": [
    "objective_result_file = \"./objective_grid-search_multi-core.csv\"\n",
    "results_df = None\n",
    "\n",
    "if not os.path.isfile(objective_result_file):\n",
    "    print(\"Run `02-objective_multi-core_gridsearch.ipynb`\")\n",
    "else:\n",
    "    results_df = pd.read_csv(objective_result_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "45d7f86f-edee-4fc5-835f-1e311ab2e411",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Objective</th>\n",
       "      <th>Optimal TTL</th>\n",
       "      <th>db_object_count</th>\n",
       "      <th>cache_size</th>\n",
       "      <th>c_f (Miss Cost)</th>\n",
       "      <th>c_delta (Refresh Cost)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.715000</td>\n",
       "      <td>[inf -0. -0. inf -0. -0. inf -0. -0. -0.]</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.730000</td>\n",
       "      <td>[-0. -0. -0. inf inf -0. -0. -0. inf -0.]</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.940000</td>\n",
       "      <td>[-0. inf -0. -0. -0. inf -0. -0. -0. -0.]</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.550000</td>\n",
       "      <td>[inf -0. inf -0. -0. -0. -0. -0. -0. -0.]</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.622740</td>\n",
       "      <td>[-0.         -0.         -0.         -0.      ...</td>\n",
       "      <td>10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32719</th>\n",
       "      <td>12506.666667</td>\n",
       "      <td>[1.09861229 0.54930614 1.09861229 1.09861229 1...</td>\n",
       "      <td>500</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32720</th>\n",
       "      <td>16130.000000</td>\n",
       "      <td>[0.1732868  0.69314718 0.07701635 0.69314718 0...</td>\n",
       "      <td>500</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32721</th>\n",
       "      <td>46486.000000</td>\n",
       "      <td>[5.10825624e-01 5.10825624e-01 8.51376040e-02 ...</td>\n",
       "      <td>500</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32722</th>\n",
       "      <td>29780.000000</td>\n",
       "      <td>[0.07438118 0.22314355 0.22314355 0.22314355 0...</td>\n",
       "      <td>500</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>50.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32723</th>\n",
       "      <td>15316.000000</td>\n",
       "      <td>[0.10536052 0.10536052 0.10536052 0.10536052 0...</td>\n",
       "      <td>500</td>\n",
       "      <td>500.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32724 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Objective                                        Optimal TTL  \\\n",
       "0          0.715000          [inf -0. -0. inf -0. -0. inf -0. -0. -0.]   \n",
       "1          0.730000          [-0. -0. -0. inf inf -0. -0. -0. inf -0.]   \n",
       "2          0.940000          [-0. inf -0. -0. -0. inf -0. -0. -0. -0.]   \n",
       "3          1.550000          [inf -0. inf -0. -0. -0. -0. -0. -0. -0.]   \n",
       "4          9.622740  [-0.         -0.         -0.         -0.      ...   \n",
       "...             ...                                                ...   \n",
       "32719  12506.666667  [1.09861229 0.54930614 1.09861229 1.09861229 1...   \n",
       "32720  16130.000000  [0.1732868  0.69314718 0.07701635 0.69314718 0...   \n",
       "32721  46486.000000  [5.10825624e-01 5.10825624e-01 8.51376040e-02 ...   \n",
       "32722  29780.000000  [0.07438118 0.22314355 0.22314355 0.22314355 0...   \n",
       "32723  15316.000000  [0.10536052 0.10536052 0.10536052 0.10536052 0...   \n",
       "\n",
       "       db_object_count  cache_size  c_f (Miss Cost)  c_delta (Refresh Cost)  \n",
       "0                   10         1.0              0.1                    0.01  \n",
       "1                   10         1.0              0.1                    0.02  \n",
       "2                   10         1.0              0.1                    0.04  \n",
       "3                   10         1.0              0.1                    0.05  \n",
       "4                   10         1.0              0.1                    0.07  \n",
       "...                ...         ...              ...                     ...  \n",
       "32719              500       500.0             10.0                   15.00  \n",
       "32720              500       500.0             10.0                   20.00  \n",
       "32721              500       500.0             10.0                   25.00  \n",
       "32722              500       500.0             10.0                   50.00  \n",
       "32723              500       500.0             10.0                  100.00  \n",
       "\n",
       "[32724 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8624c964-a9e9-4e51-9090-503c37ed113d",
   "metadata": {},
   "outputs": [],
   "source": [
    "c_delta = results_df[\"c_delta (Refresh Cost)\"]\n",
    "c_f = results_df[\"c_f (Miss Cost)\"]\n",
    "\n",
    "db_object_count = results_df[\"db_object_count\"]\n",
    "cache_size = results_df[\"cache_size\"]\n",
    "\n",
    "c_ratio = pd.DataFrame(c_delta/c_f, columns=['c_delta/c_f'])\n",
    "nb = pd.DataFrame(db_object_count/cache_size, columns=['n/b'])\n",
    "objectives = pd.DataFrame(results_df[\"Objective\"], columns=['Objective'])\n",
    "\n",
    "df = objectives.merge(nb, left_index=True, right_index=True).merge(c_ratio, left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ee992ea0-da3e-47a8-bcbb-7a17a7472d07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "scatter = plt.scatter(df['c_delta/c_f'], df['Objective'], s=df['n/b'] * 10, c=df['n/b'], cmap='viridis', alpha=0.6)\n",
    "\n",
    "# Adding color bar to represent 'n/b' values\n",
    "plt.colorbar(scatter, label='n/b')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('c_delta/c_f')\n",
    "plt.ylabel('Objective')\n",
    "plt.title('Objective vs. c_delta/c_f with n/b as size and color')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae1a71af-85bd-414b-8c95-f51cc0afed34",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "graphs",
   "language": "python",
   "name": "graphs"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}