notebooks/feature_results_visualization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json \n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath = \"../data/results/feature_data/Repro1/FP/1_1_cop_features.json\"\n",
    "\n",
    "with open(filepath) as json_data:\n",
    "    features = json.load(json_data)\n",
    "    time_features = features[\"time_features\"]\n",
    "    frequency_features = features[\"frequency_features\"]\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_features_df = pd.DataFrame(time_features,index=[0])\n",
    "frequency_features_df = pd.DataFrame(frequency_features,index=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mean distance</th>\n",
       "      <td>1.903751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean distance-ML</th>\n",
       "      <td>1.346155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean distance-AP</th>\n",
       "      <td>3.286983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rms distance</th>\n",
       "      <td>2.396578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rms distance-ML</th>\n",
       "      <td>1.694636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rms distance-AP</th>\n",
       "      <td>3.904998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Path length</th>\n",
       "      <td>181.617927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Path length-ML</th>\n",
       "      <td>108.561418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Path length-AP</th>\n",
       "      <td>122.514825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean velocity</th>\n",
       "      <td>9.080896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean velocity-ML</th>\n",
       "      <td>5.428071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean velocity-AP</th>\n",
       "      <td>6.125741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Range</th>\n",
       "      <td>6.339889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Range-ML</th>\n",
       "      <td>8.450483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Range-AP</th>\n",
       "      <td>19.412340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95% confidence circle area</th>\n",
       "      <td>58.048119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sway area</th>\n",
       "      <td>10.380762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean frequency</th>\n",
       "      <td>0.759169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean frequency-ML</th>\n",
       "      <td>0.712813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean frequency-AP</th>\n",
       "      <td>0.329447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fractal dimension-CC</th>\n",
       "      <td>1.670375</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     0\n",
       "Mean distance                 1.903751\n",
       "Mean distance-ML              1.346155\n",
       "Mean distance-AP              3.286983\n",
       "Rms distance                  2.396578\n",
       "Rms distance-ML               1.694636\n",
       "Rms distance-AP               3.904998\n",
       "Path length                 181.617927\n",
       "Path length-ML              108.561418\n",
       "Path length-AP              122.514825\n",
       "Mean velocity                 9.080896\n",
       "Mean velocity-ML              5.428071\n",
       "Mean velocity-AP              6.125741\n",
       "Range                         6.339889\n",
       "Range-ML                      8.450483\n",
       "Range-AP                     19.412340\n",
       "95% confidence circle area   58.048119\n",
       "Sway area                    10.380762\n",
       "Mean frequency                0.759169\n",
       "Mean frequency-ML             0.712813\n",
       "Mean frequency-AP             0.329447\n",
       "Fractal dimension-CC          1.670375"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_features_df.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Total power-RD</th>\n",
       "      <td>1.762535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total power-ML</th>\n",
       "      <td>6.344167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total power-AP</th>\n",
       "      <td>1.811480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peak frequency-RD</th>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peak frequency-ML</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peak frequency-AP</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50% power frequency-RD</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50% power frequency-ML</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50% power frequency-AP</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80% power frequency-RD</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80% power frequency-ML</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80% power frequency-AP</th>\n",
       "      <td>0.150000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               0\n",
       "Total power-RD          1.762535\n",
       "Total power-ML          6.344167\n",
       "Total power-AP          1.811480\n",
       "Peak frequency-RD       0.200000\n",
       "Peak frequency-ML       0.150000\n",
       "Peak frequency-AP       0.150000\n",
       "50% power frequency-RD  0.150000\n",
       "50% power frequency-ML  0.150000\n",
       "50% power frequency-AP  0.150000\n",
       "80% power frequency-RD  0.150000\n",
       "80% power frequency-ML  0.150000\n",
       "80% power frequency-AP  0.150000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequency_features_df.transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### To latex test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(frequency_features_df.to_latex(index=False))"
   ]
  },
  {
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}