Fig3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats as st\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Baseline Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>ID</th>\n",
       "      <th>ACF_512</th>\n",
       "      <th>H</th>\n",
       "      <th>JSD</th>\n",
       "      <th>C</th>\n",
       "      <th>n_components</th>\n",
       "      <th>ACI</th>\n",
       "      <th>Hs</th>\n",
       "      <th>Ha</th>\n",
       "      <th>AEI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>journal.pone.0004065.s018.flac</td>\n",
       "      <td>[1.0, 0.3159691464939133, -0.19313433219221515...</td>\n",
       "      <td>0.846339</td>\n",
       "      <td>0.354606</td>\n",
       "      <td>0.300117</td>\n",
       "      <td>316</td>\n",
       "      <td>535.872117</td>\n",
       "      <td>0.844463</td>\n",
       "      <td>0.980452</td>\n",
       "      <td>0.827956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>journal.pone.0004065.s017.flac</td>\n",
       "      <td>[1.0, 0.9136246623305964, 0.7106019969300389, ...</td>\n",
       "      <td>0.716821</td>\n",
       "      <td>0.566582</td>\n",
       "      <td>0.406138</td>\n",
       "      <td>409</td>\n",
       "      <td>525.876161</td>\n",
       "      <td>0.713769</td>\n",
       "      <td>0.979878</td>\n",
       "      <td>0.699407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>journal.pone.0004065.s015.flac</td>\n",
       "      <td>[1.0, 0.06996709008426101, -0.9398546299007356...</td>\n",
       "      <td>0.704638</td>\n",
       "      <td>0.605776</td>\n",
       "      <td>0.426853</td>\n",
       "      <td>425</td>\n",
       "      <td>479.178002</td>\n",
       "      <td>0.704269</td>\n",
       "      <td>0.989265</td>\n",
       "      <td>0.696709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>journal.pone.0004065.s013.flac</td>\n",
       "      <td>[1.0, 0.857544569268467, 0.7808859927537377, 0...</td>\n",
       "      <td>0.618595</td>\n",
       "      <td>0.626243</td>\n",
       "      <td>0.387391</td>\n",
       "      <td>400</td>\n",
       "      <td>697.112265</td>\n",
       "      <td>0.613975</td>\n",
       "      <td>0.977368</td>\n",
       "      <td>0.600079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>journal.pone.0004065.s014.flac</td>\n",
       "      <td>[1.0, 0.0844259528093256, -0.9226459123449822,...</td>\n",
       "      <td>0.709295</td>\n",
       "      <td>0.593561</td>\n",
       "      <td>0.421010</td>\n",
       "      <td>424</td>\n",
       "      <td>469.874821</td>\n",
       "      <td>0.706308</td>\n",
       "      <td>0.989290</td>\n",
       "      <td>0.698744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               ID  \\\n",
       "0  journal.pone.0004065.s018.flac   \n",
       "1  journal.pone.0004065.s017.flac   \n",
       "2  journal.pone.0004065.s015.flac   \n",
       "3  journal.pone.0004065.s013.flac   \n",
       "4  journal.pone.0004065.s014.flac   \n",
       "\n",
       "                                             ACF_512         H       JSD  \\\n",
       "0  [1.0, 0.3159691464939133, -0.19313433219221515...  0.846339  0.354606   \n",
       "1  [1.0, 0.9136246623305964, 0.7106019969300389, ...  0.716821  0.566582   \n",
       "2  [1.0, 0.06996709008426101, -0.9398546299007356...  0.704638  0.605776   \n",
       "3  [1.0, 0.857544569268467, 0.7808859927537377, 0...  0.618595  0.626243   \n",
       "4  [1.0, 0.0844259528093256, -0.9226459123449822,...  0.709295  0.593561   \n",
       "\n",
       "          C n_components         ACI        Hs        Ha       AEI  \n",
       "0  0.300117          316  535.872117  0.844463  0.980452  0.827956  \n",
       "1  0.406138          409  525.876161  0.713769  0.979878  0.699407  \n",
       "2  0.426853          425  479.178002  0.704269  0.989265  0.696709  \n",
       "3  0.387391          400  697.112265  0.613975  0.977368  0.600079  \n",
       "4  0.421010          424  469.874821  0.706308  0.989290  0.698744  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lag = 512\n",
    "\n",
    "base = pd.read_pickle('./pkl_datasets/baseline_dataset_ACF_' + str(lag) + '.gzip')\n",
    "base.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = []\n",
    "for index, row in base.iterrows():\n",
    "    labels.append('$s_{'+(row['ID'].split('.'))[-2].split('0')[-1]+'}$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,3))\n",
    "plt.rc('font', size=16)\n",
    "plt.rc('axes', titlesize=16)\n",
    "\n",
    "plt.subplot(1,4,1)\n",
    "plt.bar(range(0,base.shape[0]),base['H'])\n",
    "plt.xticks(range(0,base.shape[0]),labels)\n",
    "plt.title('H')\n",
    "\n",
    "plt.subplot(1,4,2)\n",
    "plt.bar(range(0,base.shape[0]),base['C'])\n",
    "plt.xticks(range(0,base.shape[0]),labels)\n",
    "plt.title('EGCI')\n",
    "\n",
    "plt.subplot(1,4,3)\n",
    "plt.bar(range(base.shape[0]),base['AEI'])\n",
    "plt.xticks(range(0,base.shape[0]),labels)\n",
    "plt.title(r'$H_a$')\n",
    "\n",
    "plt.subplot(1,4,4)\n",
    "plt.bar(range(base.shape[0]),base['ACI'])\n",
    "plt.xticks(range(0,base.shape[0]),labels)\n",
    "plt.title('ACI')\n",
    "\n",
    "# plt.savefig('./figures/Fig3.eps', format=\"eps\", bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  },
  "toc": {
   "nav_menu": {
    "height": "49.1333px",
    "width": "252px"
   },
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}