feature_importance.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import numpy as np\n",
    "from ecgdetectors import Detectors\n",
    "from time import time as time\n",
    "import seaborn as sns\n",
    "from hrvanalysis.hrvanalysis import remove_outliers, remove_ectopic_beats, interpolate_nan_values, get_time_domain_features, get_geometrical_features, get_frequency_domain_features, get_csi_cvi_features, get_poincare_plot_features, get_sampen\n",
    "from time import time as time\n",
    "import warnings\n",
    "import matplotlib.pyplot as plt\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "fs = 250\n",
    "\n",
    "#final fetures folder path\n",
    "finalfeats_path = \"FinalFeats/\"\n",
    "\n",
    "#R-peak files path\n",
    "\n",
    "vfdb_path = \"../vf2/finaldfs/final5sec.csv\"\n",
    "afdb_path = \"../af/hugedfrpeak5sec.csv\"\n",
    "challenge_path = \"../af2/finaldfs/2017final_normal_rpeak_L5_S1.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
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       "[787154 rows x 1251 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afdb"
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  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18751 rows × 1251 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    vf  0  1  2  3  4  5  6  7  8  ...  1240  1241  1242  1243  1244  1245  \\\n",
       "0    0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
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       "0    0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
       "0    0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0     0   \n",
       "\n",
       "    1246  1247  1248  1249  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
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       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "0      0     0     0     0  \n",
       "\n",
       "[18751 rows x 1251 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vfdb = pd.read_csv(vfdb_path,index_col=[0])\n",
    "vfdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "        af  0  1  2  3  4  5  6  7  8  ...  1240  1241  1242  1243  1244  \\\n",
       "0        0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0   \n",
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       "3        0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0   \n",
       "4        0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0   \n",
       "...     .. .. .. .. .. .. .. .. .. ..  ...   ...   ...   ...   ...   ...   \n",
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       "163592   0  0  0  0  0  0  0  0  0  0  ...     0     0     0     0     0   \n",
       "\n",
       "        1245  1246  1247  1248  1249  \n",
       "0          0     0     0     0     0  \n",
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       "2          0     0     0     0     0  \n",
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       "4          0     0     0     0     0  \n",
       "...      ...   ...   ...   ...   ...  \n",
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       "\n",
       "[163593 rows x 1251 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "challenge = pd.read_csv(challenge_path)\n",
    "challenge"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature Extraction Module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def featureExtraction(df, fs, label):\n",
    "    df1 = df[label].copy()\n",
    "    df.drop(columns = [label], inplace = True)\n",
    "    final = list()\n",
    "    for i in range(len(df)):\n",
    "        peaks = []\n",
    "        peaks = df.loc[i][df.loc[i] == 1].index.values\n",
    "        peaks = [int(x) for x in peaks]\n",
    "        peaks = [peaks[x+1] - peaks[x] for x in range(len(peaks) - 1)]\n",
    "        if (len(peaks) == 0 or len(peaks) == 1):\n",
    "            continue\n",
    "        time_domain_features = get_time_domain_features(250,peaks)\n",
    "#         geometrical_features = get_geometrical_features(peaks)\n",
    "        features = [time_domain_features]\n",
    "        new = {}\n",
    "        for x in features:\n",
    "            for y in x:\n",
    "                new[y] = x[y]\n",
    "        new\n",
    "        vf = df1.loc[i]\n",
    "        #single_window_df = pd.DataFrame(new.items(), columns = list(new.keys()))\n",
    "        single_window_df = pd.DataFrame(list(new.items()))\n",
    "        single_window_df = single_window_df.transpose()\n",
    "        columns = single_window_df.iloc[0]\n",
    "        single_window_df = single_window_df[1:]\n",
    "        single_window_df.columns = columns\n",
    "#         single_window_df.drop(columns = ['std_hr'], inplace = True)\n",
    "        single_window_df.insert(0, label, vf)\n",
    "        final.append(single_window_df)\n",
    "        del single_window_df\n",
    "    return pd.concat(final)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AFDB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "afdb_feats = featureExtraction(afdb, fs, 'af')\n",
    "afdb_feats.reset_index(drop = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
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       "      <td>0.254833</td>\n",
       "      <td>359.180415</td>\n",
       "      <td>416.666667</td>\n",
       "      <td>251.046025</td>\n",
       "      <td>71.633476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>176.500000</td>\n",
       "      <td>46.539231</td>\n",
       "      <td>67.747767</td>\n",
       "      <td>3.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>70.047127</td>\n",
       "      <td>0.396868</td>\n",
       "      <td>0.263678</td>\n",
       "      <td>357.667670</td>\n",
       "      <td>416.666667</td>\n",
       "      <td>251.046025</td>\n",
       "      <td>73.663194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>196.400000</td>\n",
       "      <td>44.892093</td>\n",
       "      <td>62.866426</td>\n",
       "      <td>3.0</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>63.227763</td>\n",
       "      <td>0.321934</td>\n",
       "      <td>0.228575</td>\n",
       "      <td>319.713024</td>\n",
       "      <td>405.405405</td>\n",
       "      <td>251.046025</td>\n",
       "      <td>69.708420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>192.000000</td>\n",
       "      <td>40.540104</td>\n",
       "      <td>40.449815</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>43.974424</td>\n",
       "      <td>0.229033</td>\n",
       "      <td>0.211146</td>\n",
       "      <td>324.803358</td>\n",
       "      <td>405.405405</td>\n",
       "      <td>256.410256</td>\n",
       "      <td>65.298039</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>769159</th>\n",
       "      <td>1</td>\n",
       "      <td>91.333333</td>\n",
       "      <td>42.371374</td>\n",
       "      <td>63.660775</td>\n",
       "      <td>7.0</td>\n",
       "      <td>63.636364</td>\n",
       "      <td>10.0</td>\n",
       "      <td>90.909091</td>\n",
       "      <td>63.842847</td>\n",
       "      <td>0.699009</td>\n",
       "      <td>0.463920</td>\n",
       "      <td>750.602431</td>\n",
       "      <td>1132.075472</td>\n",
       "      <td>285.714286</td>\n",
       "      <td>235.441064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>769160</th>\n",
       "      <td>1</td>\n",
       "      <td>91.538462</td>\n",
       "      <td>43.961376</td>\n",
       "      <td>71.516898</td>\n",
       "      <td>10.0</td>\n",
       "      <td>83.333333</td>\n",
       "      <td>12.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>71.523889</td>\n",
       "      <td>0.781353</td>\n",
       "      <td>0.480250</td>\n",
       "      <td>765.437060</td>\n",
       "      <td>1132.075472</td>\n",
       "      <td>285.714286</td>\n",
       "      <td>261.766781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>769161</th>\n",
       "      <td>1</td>\n",
       "      <td>84.857143</td>\n",
       "      <td>43.061418</td>\n",
       "      <td>66.222951</td>\n",
       "      <td>10.0</td>\n",
       "      <td>76.923077</td>\n",
       "      <td>12.0</td>\n",
       "      <td>92.307692</td>\n",
       "      <td>66.225140</td>\n",
       "      <td>0.780431</td>\n",
       "      <td>0.507458</td>\n",
       "      <td>821.298411</td>\n",
       "      <td>1132.075472</td>\n",
       "      <td>285.714286</td>\n",
       "      <td>255.114721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>769162</th>\n",
       "      <td>1</td>\n",
       "      <td>98.454545</td>\n",
       "      <td>53.359842</td>\n",
       "      <td>70.987393</td>\n",
       "      <td>9.0</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>71.083753</td>\n",
       "      <td>0.721996</td>\n",
       "      <td>0.541974</td>\n",
       "      <td>755.572381</td>\n",
       "      <td>1132.075472</td>\n",
       "      <td>285.714286</td>\n",
       "      <td>301.298392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>769163</th>\n",
       "      <td>1</td>\n",
       "      <td>89.769231</td>\n",
       "      <td>41.101812</td>\n",
       "      <td>57.086861</td>\n",
       "      <td>10.0</td>\n",
       "      <td>83.333333</td>\n",
       "      <td>10.0</td>\n",
       "      <td>83.333333</td>\n",
       "      <td>57.086922</td>\n",
       "      <td>0.635930</td>\n",
       "      <td>0.457861</td>\n",
       "      <td>781.512744</td>\n",
       "      <td>1132.075472</td>\n",
       "      <td>346.820809</td>\n",
       "      <td>268.553657</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>769164 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        af    mean_nni       sdnn       sdsd  nni_50    pnni_50  nni_20  \\\n",
       "0        0  175.166667  45.039612  60.945878     4.0  80.000000     4.0   \n",
       "1        0  175.166667  44.638175  67.354584     3.0  60.000000     3.0   \n",
       "2        0  176.500000  46.539231  67.747767     3.0  60.000000     3.0   \n",
       "3        0  196.400000  44.892093  62.866426     3.0  75.000000     3.0   \n",
       "4        0  192.000000  40.540104  40.449815     2.0  50.000000     2.0   \n",
       "...     ..         ...        ...        ...     ...        ...     ...   \n",
       "769159   1   91.333333  42.371374  63.660775     7.0  63.636364    10.0   \n",
       "769160   1   91.538462  43.961376  71.516898    10.0  83.333333    12.0   \n",
       "769161   1   84.857143  43.061418  66.222951    10.0  76.923077    12.0   \n",
       "769162   1   98.454545  53.359842  70.987393     9.0  90.000000     9.0   \n",
       "769163   1   89.769231  41.101812  57.086861    10.0  83.333333    10.0   \n",
       "\n",
       "           pnni_20      rmssd      cvsd     cvnni     mean_hr       max_hr  \\\n",
       "0        80.000000  64.143589  0.366186  0.257124  359.732339   431.654676   \n",
       "1        60.000000  69.092691  0.394440  0.254833  359.180415   416.666667   \n",
       "2        60.000000  70.047127  0.396868  0.263678  357.667670   416.666667   \n",
       "3        75.000000  63.227763  0.321934  0.228575  319.713024   405.405405   \n",
       "4        50.000000  43.974424  0.229033  0.211146  324.803358   405.405405   \n",
       "...            ...        ...       ...       ...         ...          ...   \n",
       "769159   90.909091  63.842847  0.699009  0.463920  750.602431  1132.075472   \n",
       "769160  100.000000  71.523889  0.781353  0.480250  765.437060  1132.075472   \n",
       "769161   92.307692  66.225140  0.780431  0.507458  821.298411  1132.075472   \n",
       "769162   90.000000  71.083753  0.721996  0.541974  755.572381  1132.075472   \n",
       "769163   83.333333  57.086922  0.635930  0.457861  781.512744  1132.075472   \n",
       "\n",
       "            min_hr      std_hr  \n",
       "0       251.046025   73.521467  \n",
       "1       251.046025   71.633476  \n",
       "2       251.046025   73.663194  \n",
       "3       251.046025   69.708420  \n",
       "4       256.410256   65.298039  \n",
       "...            ...         ...  \n",
       "769159  285.714286  235.441064  \n",
       "769160  285.714286  261.766781  \n",
       "769161  285.714286  255.114721  \n",
       "769162  285.714286  301.298392  \n",
       "769163  346.820809  268.553657  \n",
       "\n",
       "[769164 rows x 15 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afdb_feats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "afdb_feats2 = afdb_feats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    461691\n",
       "1    307473\n",
       "Name: af, dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afdb_feats.af.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0 = afdb_feats[afdb_feats['af'].eq(0)].sample(15000+3750)\n",
    "df1 = afdb_feats[afdb_feats['af'].eq(1)].sample(15000+3750)\n",
    "testdf0 = df0[df0['af'].eq(0)].sample(3750)\n",
    "testdf1 = df1[df1['af'].eq(1)].sample(3750)\n",
    "df0.drop(testdf0.index, inplace=True)\n",
    "df1.drop(testdf1.index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "afdb_train = pd.concat([df0,df1])\n",
    "afdb_test = pd.concat([testdf0, testdf1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0.drop(testdf0.index, inplace=True)\n",
    "df1.drop(testdf1.index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.2776"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train - 200k 0 200k 1\n",
    "test - 107473 0 107473 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "afd[finaldf1['af'].eq(0)].sample(200000).index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "107473"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "307473-200000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afdb_feats.isnull().any().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "afdb_feats.to_csv(finalfeats_path+'afdbfeats.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_corr(df, plotname):\n",
    "    s = df.select_dtypes(include='object').columns\n",
    "    df[s] = df[s].astype(\"float\")\n",
    "    corrmat = df.corr()\n",
    "    top_corr_features = corrmat.index\n",
    "    plt.subplots(figsize=(20,15))\n",
    "    g=sns.heatmap(df[top_corr_features].corr(),annot=True,cmap=sns.diverging_palette(20, 220, n=200))\n",
    "    plt.savefig(finalfeats_path+plotname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_corr(afdb_feats,'afdbHeatmap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2017 Challenge -AF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(162437, 15)"
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "challenge_feats.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = challenge_feats.iloc[:,1:]\n",
    "y = challenge_feats.iloc[:,:1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "challenge_feats = featureExtraction(challenge, fs, 'af')\n",
    "challenge_feats.reset_index(drop = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "challenge_feats.to_csv(finalfeats_path+'2017feats.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0 = challenge_feats[challenge_feats['af'].eq(0)].sample(15000+3750)\n",
    "df1 = challenge_feats[challenge_feats['af'].eq(1)].sample(15000+3750)\n",
    "testdf0 = df0[df0['af'].eq(0)].sample(3750)\n",
    "testdf1 = df1[df1['af'].eq(1)].sample(3750)\n",
    "df0.drop(testdf0.index, inplace=True)\n",
    "df1.drop(testdf1.index, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "challenge_train = pd.concat([df0,df1])\n",
    "challenge_test = pd.concat([testdf0, testdf1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    15000\n",
       "1    15000\n",
       "Name: af, dtype: int64"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "challenge_train.af.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_corr(challenge_feats,'2017Heatmap')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import f_classif\n",
    "from sklearn.feature_selection import SelectKBest\n",
    "f_score, f_p_value = f_classif(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 5.88843418313106e-280,\n",
       " 0.0]"
      ]
     },
     "execution_count": 398,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(f_p_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 1.103035087797857e-115,\n",
       " 0.0]"
      ]
     },
     "execution_count": 395,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(f_p_value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[166110.58432352,\n",
       " 329248.29915505706,\n",
       " 292564.6067323762,\n",
       " 1035803.3598970161,\n",
       " 937480.0081068721,\n",
       " 964317.2395459657,\n",
       " 726164.978830432,\n",
       " 275340.82134998566,\n",
       " 450012.62416186446,\n",
       " 545356.0015721533,\n",
       " 211654.9155191982,\n",
       " 321301.80928801716,\n",
       " 522.8620473111691,\n",
       " 409306.75643196347]"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(f_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [],
   "source": [
    "fs = SelectKBest(score_func=f_classif, k='all')\n",
    "# learn relationship from training data\n",
    "fs.fit(X, y)\n",
    "# transform train input data\n",
    "X_train_fs = fs.transform(X)\n",
    "# transform test input data\n",
    "# X_test_fs = fs.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature 0: 166110.584324\n",
      "Feature 1: 329248.299155\n",
      "Feature 2: 292564.606732\n",
      "Feature 3: 1035803.359897\n",
      "Feature 4: 937480.008107\n",
      "Feature 5: 964317.239546\n",
      "Feature 6: 726164.978830\n",
      "Feature 7: 275340.821350\n",
      "Feature 8: 450012.624162\n",
      "Feature 9: 545356.001572\n",
      "Feature 10: 211654.915519\n",
      "Feature 11: 321301.809288\n",
      "Feature 12: 522.862047\n",
      "Feature 13: 409306.756432\n",
      "['mean_nni', 'sdnn', 'sdsd', 'nni_50', 'pnni_50', 'nni_20', 'pnni_20', 'rmssd', 'cvsd', 'cvnni', 'mean_hr', 'max_hr', 'min_hr', 'std_hr']\n"
     ]
    }
   ],
   "source": [
    "x = []\n",
    "for i in range(len(fs.scores_)):\n",
    "\tprint('Feature %d: %f' % (i, fs.scores_[i]))\n",
    "#     x.append(fs.scores_[i])    \n",
    "# print(challenge_list)\n",
    "print(list(X.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_values = list(f_score)\n",
    "res = {}\n",
    "for key in list(X.columns):\n",
    "    for value in test_values:\n",
    "        res[key] = value\n",
    "        test_values.remove(value)\n",
    "        break  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'mean_nni': 166110.58432352,\n",
       " 'sdnn': 329248.29915505706,\n",
       " 'sdsd': 292564.6067323762,\n",
       " 'nni_50': 1035803.3598970161,\n",
       " 'pnni_50': 937480.0081068721,\n",
       " 'nni_20': 964317.2395459657,\n",
       " 'pnni_20': 726164.978830432,\n",
       " 'rmssd': 275340.82134998566,\n",
       " 'cvsd': 450012.62416186446,\n",
       " 'cvnni': 545356.0015721533,\n",
       " 'mean_hr': 211654.9155191982,\n",
       " 'max_hr': 321301.80928801716,\n",
       " 'min_hr': 522.8620473111691,\n",
       " 'std_hr': 409306.75643196347}"
      ]
     },
     "execution_count": 387,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sort_dict_by_value(d, reverse = False):\n",
    "    return dict(sorted(d.items(), key = lambda x: x[1], reverse = reverse))\n",
    "\n",
    "l = sort_dict_by_value(res, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd', 'std_hr', 'sdnn', 'max_hr', 'sdsd', 'rmssd', 'mean_hr', 'mean_nni', 'min_hr']\n",
      "[1035803.3598970161, 964317.2395459657, 937480.0081068721, 726164.978830432, 545356.0015721533, 450012.62416186446, 409306.75643196347, 329248.29915505706, 321301.80928801716, 292564.6067323762, 275340.82134998566, 211654.9155191982, 166110.58432352, 522.8620473111691]\n"
     ]
    }
   ],
   "source": [
    "print(list(l.keys()))\n",
    "print(list(l.values()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VFDB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'vfdb' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-b700ee9275d5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvfdb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mvfdb_feats\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfeatureExtraction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvfdb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'vf'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mvfdb_feats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdrop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'vfdb' is not defined"
     ]
    }
   ],
   "source": [
    "vfdb.reset_index(drop=True, inplace=True)\n",
    "vfdb_feats = featureExtraction(vfdb, fs, 'vf')\n",
    "vfdb_feats.reset_index(drop = True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vf</th>\n",
       "      <th>mean_nni</th>\n",
       "      <th>sdnn</th>\n",
       "      <th>sdsd</th>\n",
       "      <th>nni_50</th>\n",
       "      <th>pnni_50</th>\n",
       "      <th>nni_20</th>\n",
       "      <th>pnni_20</th>\n",
       "      <th>rmssd</th>\n",
       "      <th>median_nni</th>\n",
       "      <th>range_nni</th>\n",
       "      <th>cvsd</th>\n",
       "      <th>cvnni</th>\n",
       "      <th>mean_hr</th>\n",
       "      <th>max_hr</th>\n",
       "      <th>min_hr</th>\n",
       "      <th>std_hr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>25.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>22.0</td>\n",
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       "      <td>337.078652</td>\n",
       "      <td>300.0</td>\n",
       "      <td>14.099823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>198.2</td>\n",
       "      <td>14.567086</td>\n",
       "      <td>21.878928</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>198.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.113522</td>\n",
       "      <td>0.073497</td>\n",
       "      <td>304.040801</td>\n",
       "      <td>337.078652</td>\n",
       "      <td>273.972603</td>\n",
       "      <td>20.086207</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>199.2</td>\n",
       "      <td>14.720734</td>\n",
       "      <td>23.84717</td>\n",
       "      <td>3.0</td>\n",
       "      <td>75.0</td>\n",
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       "      <td>75.0</td>\n",
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       "      <td>20.381018</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>189.333333</td>\n",
       "      <td>26.665833</td>\n",
       "      <td>31.108841</td>\n",
       "      <td>4.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>32.930229</td>\n",
       "      <td>197.0</td>\n",
       "      <td>77.0</td>\n",
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       "      <td>196.0</td>\n",
       "      <td>32.930229</td>\n",
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       "      <td>0</td>\n",
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       "      <td>8.0</td>\n",
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       "      <td>100.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>109.509132</td>\n",
       "      <td>87.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.813187</td>\n",
       "      <td>0.428656</td>\n",
       "      <td>524.030108</td>\n",
       "      <td>705.882353</td>\n",
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       "    <tr>\n",
       "      <th>18432</th>\n",
       "      <td>0</td>\n",
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       "      <td>100.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>109.151271</td>\n",
       "      <td>139.5</td>\n",
       "      <td>112.0</td>\n",
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       "      <td>0.415505</td>\n",
       "      <td>503.915703</td>\n",
       "      <td>705.882353</td>\n",
       "      <td>304.568528</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>18433</th>\n",
       "      <td>0</td>\n",
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       "      <td>58.408506</td>\n",
       "      <td>108.179556</td>\n",
       "      <td>7.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>109.294491</td>\n",
       "      <td>139.5</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0.779979</td>\n",
       "      <td>0.416831</td>\n",
       "      <td>504.941695</td>\n",
       "      <td>705.882353</td>\n",
       "      <td>304.568528</td>\n",
       "      <td>196.864989</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18434 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "0      vf    mean_nni       sdnn        sdsd nni_50 pnni_50 nni_20 pnni_20  \\\n",
       "0       0       194.4   9.316652     7.53326    1.0    25.0    1.0    25.0   \n",
       "1       0       198.2  14.567086   21.878928    2.0    50.0    2.0    50.0   \n",
       "2       0       199.2  14.720734    23.84717    3.0    75.0    3.0    75.0   \n",
       "3       0  189.333333  26.665833   31.108841    4.0    80.0    4.0    80.0   \n",
       "4       0       196.0  32.930229   51.499903    4.0    80.0    4.0    80.0   \n",
       "...    ..         ...        ...         ...    ...     ...    ...     ...   \n",
       "18429   0      141.25  59.073199   109.12771    7.0   100.0    7.0   100.0   \n",
       "18430   0       135.0  58.111961  110.128831    8.0   100.0    8.0   100.0   \n",
       "18431   0  134.666667  57.725644  109.508847    8.0   100.0    8.0   100.0   \n",
       "18432   0      140.25  58.274596  108.055352    7.0   100.0    7.0   100.0   \n",
       "18433   0     140.125  58.408506  108.179556    7.0   100.0    7.0   100.0   \n",
       "\n",
       "0           rmssd median_nni range_nni      cvsd     cvnni     mean_hr  \\\n",
       "0        9.327379      198.0      22.0   0.04798  0.047925  309.246281   \n",
       "1            22.5      198.0      41.0  0.113522  0.073497  304.040801   \n",
       "2       23.858961      200.0      41.0  0.119774  0.073899  302.548041   \n",
       "3       32.930229      197.0      77.0  0.173927  0.140841  323.050953   \n",
       "4       52.790151      200.5      94.0  0.269338  0.168011  314.403427   \n",
       "...           ...        ...       ...       ...       ...         ...   \n",
       "18429  110.294411      141.0     113.0  0.780845  0.418217  501.537494   \n",
       "18430  110.128902       87.0     112.0   0.81577  0.430459  523.501399   \n",
       "18431  109.509132       87.0     112.0  0.813187  0.428656  524.030108   \n",
       "18432  109.151271      139.5     112.0  0.778262  0.415505  503.915703   \n",
       "18433  109.294491      139.5     112.0  0.779979  0.416831  504.941695   \n",
       "\n",
       "0          max_hr      min_hr      std_hr  \n",
       "0      337.078652       300.0   14.099823  \n",
       "1      337.078652  273.972603   20.086207  \n",
       "2      337.078652  273.972603   20.381018  \n",
       "3      422.535211  273.972603   48.210258  \n",
       "4      422.535211  254.237288   54.689186  \n",
       "...           ...         ...         ...  \n",
       "18429  705.882353  303.030303  196.229885  \n",
       "18430  705.882353  304.568528  194.813012  \n",
       "18431  705.882353  304.568528  194.227922  \n",
       "18432  705.882353  304.568528  195.833771  \n",
       "18433  705.882353  304.568528  196.864989  \n",
       "\n",
       "[18434 rows x 17 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vfdb_feats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "vfdb_feats.to_csv(finalfeats_path+'vfdbfeats.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_corr(vfdb_feats,'vfdbHeatmap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot only dependent variable corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "vfdb_feats = pd.read_csv(\"FinalFeats/vfdbfeats.csv\")\n",
    "afdb_feats = pd.read_csv(\"FinalFeats/afdbfeats.csv\")\n",
    "challenge_feats = pd.read_csv(\"FinalFeats/2017feats.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "vfdb_feats.drop(columns = ['median_nni','range_nni'], inplace = True)\n",
    "afdb_feats.drop(columns = ['median_nni','range_nni'], inplace = True)\n",
    "challenge_feats.drop(columns = ['median_nni','range_nni'], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pprint\n",
    "def get_best_corr(df, label, top_n=0):\n",
    "    s = df.select_dtypes(include='object').columns\n",
    "    df[s] = df[s].astype(\"float\")\n",
    "    corrmat = df.corr()\n",
    "#     print(corrmat[label])\n",
    "    required = corrmat[label]\n",
    "    if(top_n!=0):\n",
    "        pprint.pprint(corrmat.sort_values(by=label, key=abs, ascending = False)[label][1:top_n+1].to_dict())\n",
    "    else:\n",
    "        print(corrmat.sort_values(by=label, key=abs, ascending = False)[label].to_dict())\n",
    "#     top_corr_features = corrmat.index\n",
    "#     plt.subplots(figsize=(20,15))\n",
    "#     g=sns.heatmap(df[top_corr_features].corr(),annot=True,cmap=sns.diverging_palette(20, 220, n=200))\n",
    "#     plt.savefig(finalfeats_path+plotname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top 4 through 14 features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'max_hr': 0.5525932362348347,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008}\n",
      "2017:\n",
      "{'cvsd': 0.5286614180371076,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_50': 0.5813343453414543}\n"
     ]
    }
   ],
   "source": [
    "n = 4\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_50': 0.5813343453414543}\n"
     ]
    }
   ],
   "source": [
    "n = 6\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'sdsd': 0.45814532706766586}\n"
     ]
    }
   ],
   "source": [
    "n = 8\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'pnni_50': 0.3028604371898593,\n",
      " 'sdsd': 0.2844186217934457,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'max_hr': 0.5428138962553284,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'sdsd': 0.5249338060244614,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_20': 0.4446831098528145,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'sdsd': 0.45814532706766586,\n",
      " 'std_hr': 0.4423495381445425}\n"
     ]
    }
   ],
   "source": [
    "n = 10\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'pnni_20': 0.2606519305548472,\n",
      " 'pnni_50': 0.3028604371898593,\n",
      " 'sdnn': 0.23792385779624717,\n",
      " 'sdsd': 0.2844186217934457,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'max_hr': 0.5428138962553284,\n",
      " 'mean_hr': 0.4645368876928366,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'rmssd': 0.513429115641444,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'sdsd': 0.5249338060244614,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_20': 0.4446831098528145,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'rmssd': 0.4271152839245777,\n",
      " 'sdnn': 0.401229583807342,\n",
      " 'sdsd': 0.45814532706766586,\n",
      " 'std_hr': 0.4423495381445425}\n"
     ]
    }
   ],
   "source": [
    "n = 12\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'min_hr': 0.14315701677797643,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'pnni_20': 0.2606519305548472,\n",
      " 'pnni_50': 0.3028604371898593,\n",
      " 'rmssd': 0.23348994050468982,\n",
      " 'sdnn': 0.23792385779624717,\n",
      " 'sdsd': 0.2844186217934457,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'max_hr': 0.5428138962553284,\n",
      " 'mean_hr': 0.4645368876928366,\n",
      " 'mean_nni': -0.42143398129121584,\n",
      " 'min_hr': 0.026063761146766833,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'rmssd': 0.513429115641444,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'sdsd': 0.5249338060244614,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'mean_nni': -0.3182036306600463,\n",
      " 'min_hr': 0.08853654640533444,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_20': 0.4446831098528145,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'rmssd': 0.4271152839245777,\n",
      " 'sdnn': 0.401229583807342,\n",
      " 'sdsd': 0.45814532706766586,\n",
      " 'std_hr': 0.4423495381445425}\n"
     ]
    }
   ],
   "source": [
    "n = 14\n",
    "\n",
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf', n)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af', n)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af', n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'pnni_50': 0.3028604371898593,\n",
      " 'sdsd': 0.2844186217934457,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'max_hr': 0.5428138962553284,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'sdsd': 0.5249338060244614,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_20': 0.4446831098528145,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'sdsd': 0.45814532706766586,\n",
      " 'std_hr': 0.4423495381445425}\n"
     ]
    }
   ],
   "source": [
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf',10)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af',10)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af',10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top 14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VFDB:\n",
      "{'cvnni': 0.450890026219649,\n",
      " 'cvsd': 0.43745334691588983,\n",
      " 'max_hr': 0.5525932362348347,\n",
      " 'mean_hr': 0.5018688327087617,\n",
      " 'mean_nni': -0.35306595770834737,\n",
      " 'min_hr': 0.14315701677797643,\n",
      " 'nni_20': 0.5283437742438841,\n",
      " 'nni_50': 0.526132477107798,\n",
      " 'pnni_20': 0.2606519305548472,\n",
      " 'pnni_50': 0.3028604371898593,\n",
      " 'rmssd': 0.23348994050468982,\n",
      " 'sdnn': 0.23792385779624717,\n",
      " 'sdsd': 0.2844186217934457,\n",
      " 'std_hr': 0.5359121907575933}\n",
      "AFDB:\n",
      "{'cvnni': 0.6441051616682536,\n",
      " 'cvsd': 0.6075463152564952,\n",
      " 'max_hr': 0.5428138962553284,\n",
      " 'mean_hr': 0.4645368876928366,\n",
      " 'mean_nni': -0.42143398129121584,\n",
      " 'min_hr': 0.026063761146766833,\n",
      " 'nni_20': 0.7458485384650697,\n",
      " 'nni_50': 0.7575376492770757,\n",
      " 'pnni_20': 0.6968664648667948,\n",
      " 'pnni_50': 0.7411562783415008,\n",
      " 'rmssd': 0.513429115641444,\n",
      " 'sdnn': 0.5474941358848239,\n",
      " 'sdsd': 0.5249338060244614,\n",
      " 'std_hr': 0.5893393235920359}\n",
      "2017:\n",
      "{'cvnni': 0.4953699800471328,\n",
      " 'cvsd': 0.5286614180371076,\n",
      " 'max_hr': 0.4689975666537544,\n",
      " 'mean_hr': 0.44733408113519435,\n",
      " 'mean_nni': -0.3182036306600463,\n",
      " 'min_hr': 0.08853654640533444,\n",
      " 'nni_20': 0.6114214225684205,\n",
      " 'nni_50': 0.6851729543090167,\n",
      " 'pnni_20': 0.4446831098528145,\n",
      " 'pnni_50': 0.5813343453414543,\n",
      " 'rmssd': 0.4271152839245777,\n",
      " 'sdnn': 0.401229583807342,\n",
      " 'sdsd': 0.45814532706766586,\n",
      " 'std_hr': 0.4423495381445425}\n"
     ]
    }
   ],
   "source": [
    "print(\"VFDB:\",end=\"\\n\")\n",
    "get_best_corr(vfdb_feats,'vf',14)\n",
    "print(\"AFDB:\",end=\"\\n\")\n",
    "get_best_corr(afdb_feats,'af',14)\n",
    "print(\"2017:\",end=\"\\n\")\n",
    "get_best_corr(challenge_feats,'af',14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "d1 - afdb afdb df1\n",
    "d2 - 2017  df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Top 'n' features\n",
    "n = 4,6,8,10,12,14\n",
    "\n",
    "3 graph\n",
    "\n",
    "model running time \n",
    "total pipeline inf  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "d1 - 6\n",
    "d2 - 6\n",
    "\n",
    "\n",
    "d1 - 6 a/r    - top 6 best Sd1  abcd ef-12-13\n",
    "d2 - 6 a/r    - top 10 best   Sd2 abcd ef-9-10\n",
    "\n",
    "a r\n",
    "\n",
    "best \n",
    "\n",
    "t2 t3\n",
    "\n",
    "\n",
    "\n",
    "12 models model size and inference\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "no of features vs model size\n",
    "\"               vs inference time\n",
    "\n",
    "\n",
    "T1 - d1 - \n",
    "T2 - train d1 - Sd1 and Sd2\n",
    "\n",
    "d1 - top 4 -  abdf\n",
    "d2 - top 4 - abcd\n",
    "\n",
    "\n",
    "s1 s2\n",
    "\n",
    "s1 and s2 - abc\n",
    "s1 or s2 - \n",
    "\n",
    "\n",
    "T3 - train d2 -  \n",
    "T4 - d2 - \n",
    "\n",
    "\n",
    "top n festures vs model size\n",
    "\n",
    "\n",
    "12 + 4 models\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Balance dataset\n",
    "2. 12 csvs store\n",
    "3. Create folders and csv ----> numpy\n",
    "4. 12 models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "afdb_train\n",
    "afdb_test\n",
    "challenge_train\n",
    "challenge_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_top_feats(df, label, top_n=0):\n",
    "    s = df.select_dtypes(include='object').columns\n",
    "    df[s] = df[s].astype(\"float\")\n",
    "    corrmat = df.corr()\n",
    "    required = corrmat[label]\n",
    "    if(top_n!=0):\n",
    "        return(list(corrmat.sort_values(by=label, key=abs, ascending = False)[label][1:top_n+1].to_dict().keys()))\n",
    "    else:\n",
    "        return(list(corrmat.sort_values(by=label, key=abs, ascending = False)[label].to_dict().keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_topn_df(df, label, i):\n",
    "    features = get_top_feats(df, label, i)\n",
    "    features.insert(0,label)\n",
    "    return(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "def shuffler(df):\n",
    "    return df.reindex(np.random.permutation(df.index)).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_all_topn(dset_name, root_df, path, traindf, testdf):\n",
    "    n = [4,6,8,10,12,14]\n",
    "#     n = [8]\n",
    "    bonsai_path = path\n",
    "    for i in n:\n",
    "        path = bonsai_path\n",
    "        train = traindf.copy()\n",
    "        test = testdf.copy()\n",
    "        label = train.columns[0]\n",
    "        \n",
    "        features = get_topn_df(root_df, root_df.columns[0], i)\n",
    "        train = train[features] \n",
    "        test = test[features]\n",
    "        \n",
    "        top = pd.concat([train,test])\n",
    "        \n",
    "\n",
    "        top = shuffler(top)\n",
    "        \n",
    "#         train = train.to_numpy()\n",
    "#         test = test.to_numpy()\n",
    "        \n",
    "#         print(train.shape, test.shape)\n",
    "        \n",
    "        path = path + dset_name + '_top' + str(i) +'.csv'\n",
    "        top.to_csv(path, index=False)\n",
    "        \n",
    "#         os.mkdir(path)\n",
    "\n",
    "#         np.save(path + '/train.npy', train)\n",
    "#         np.save(path + '/test.npy', test)\n",
    "#         os.remove(path + '/train.npy')\n",
    "#         os.remove(path + '/test.npy')\n",
    "    \n",
    "        \n",
    "        print(path+\".....\"+\"Created\")\n",
    "#         print(top.isnull().sum())\n",
    "#         print(train.columns)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top4.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top6.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top8.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top10.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top12.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/AFDB_top14.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top4.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top6.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top8.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top10.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top12.csv.....Created\n",
      "../edgeml/examples/pytorch/Bonsai/final_features/2017_top14.csv.....Created\n"
     ]
    }
   ],
   "source": [
    "get_all_topn('AFDB', afdb_feats, '../edgeml/examples/pytorch/Bonsai/final_features/', afdb_train, afdb_test)\n",
    "get_all_topn('2017', challenge_feats, '../edgeml/examples/pytorch/Bonsai/final_features/', challenge_train, challenge_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Command history\n",
    "3)python bonsai_example2.py -dir 2017_top4/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top4.csv -kF 5 -e 100 -d 3\n",
    "1)python bonsai_example2.py -dir AFDB_top6/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top6.csv -kF 5 -e 100 -d 3\n",
    "2)python bonsai_example2.py -dir 2017_top6/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top6.csv -kF 5 -e 100 -d 3\n",
    "\n",
    "## Yet to run\n",
    "\n",
    "1)python bonsai_example2.py -dir AFDB_top8/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top8.csv -kF 5 -e 100 -d 3\n",
    "2)python bonsai_example2.py -dir 2017_top8/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top8.csv -kF 5 -e 100 -d 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "python bonsai_example2.py -dir AFDB_top4_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top4.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top4_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top4.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir AFDB_top6_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top6.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top6_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top6.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir AFDB_top8_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top8.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top8_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top8.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir AFDB_top10_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top10.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top10_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top10.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir AFDB_top12_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/AFDB_top12.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top12_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top12.csv -kF 5 -e 100 -d 1\n",
    "python bonsai_example2.py -dir 2017_top14_d1/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top14.csv -kF 5 -e 100 -d 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cd  /hdd/physio/edgeml/examples/pytorch/Bonsai/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python bonsai_example2.py -dir 2017_top4/ -df /hdd/physio/edgeml/examples/pytorch/Bonsai/final_features/2017_top4.csv -kF 5 -e 100 -d 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------4---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20'], dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd'], dtype='object')\n",
      "--------------------6---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd'], dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr'], dtype='object')\n",
      "--------------------8---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd',\n",
      "       'std_hr', 'sdnn'],\n",
      "      dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr', 'sdsd',\n",
      "       'mean_hr'],\n",
      "      dtype='object')\n",
      "--------------------10---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd',\n",
      "       'std_hr', 'sdnn', 'max_hr', 'sdsd'],\n",
      "      dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr', 'sdsd',\n",
      "       'mean_hr', 'pnni_20', 'std_hr'],\n",
      "      dtype='object')\n",
      "--------------------12---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd',\n",
      "       'std_hr', 'sdnn', 'max_hr', 'sdsd', 'rmssd', 'mean_hr'],\n",
      "      dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr', 'sdsd',\n",
      "       'mean_hr', 'pnni_20', 'std_hr', 'rmssd', 'sdnn'],\n",
      "      dtype='object')\n",
      "--------------------14---------------------\n",
      "AFDB\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd',\n",
      "       'std_hr', 'sdnn', 'max_hr', 'sdsd', 'rmssd', 'mean_hr', 'mean_nni',\n",
      "       'min_hr'],\n",
      "      dtype='object')\n",
      "2017\n",
      "Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr', 'sdsd',\n",
      "       'mean_hr', 'pnni_20', 'std_hr', 'rmssd', 'sdnn', 'mean_nni', 'min_hr'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "n = [4,6,8,10,12,14]\n",
    "for i in n:\n",
    "    print(\"--------------------\"+str(i)+\"---------------------\")\n",
    "    print(\"AFDB\")\n",
    "    print(get_topn_df(afdb_feats, afdb_feats.columns[0], i).columns)\n",
    "    print(\"2017\")\n",
    "    print(get_topn_df(challenge_feats, challenge_feats.columns[0], i).columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_top_feats(df, label, top_n=0):\n",
    "    s = df.select_dtypes(include='object').columns\n",
    "    df[s] = df[s].astype(\"float\")\n",
    "    corrmat = df.corr()\n",
    "    required = corrmat[label]\n",
    "    correlations = abs(corrmat.sort_values(by=label, key=abs, ascending = False)[label].values)\n",
    "    features = corrmat.sort_values(by=label, key=abs, ascending = False)[label].index[:top_n+1]\n",
    "    return(correlations, features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_topn(df, label, i):\n",
    "    corr_values,features = get_top_feats(df, label, i)\n",
    "#     features.insert(0,label)\n",
    "    return(corr_values,features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.        , 0.75753765, 0.74584854, 0.74115628, 0.69686646,\n",
       "        0.64410516, 0.60754632, 0.58933932, 0.54749414, 0.5428139 ,\n",
       "        0.52493381, 0.51342912, 0.46453689, 0.42143398, 0.02606376]),\n",
       " Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'pnni_20', 'cvnni', 'cvsd',\n",
       "        'std_hr', 'sdnn', 'max_hr', 'sdsd', 'rmssd', 'mean_hr', 'mean_nni',\n",
       "        'min_hr'],\n",
       "       dtype='object'))"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_topn(afdb_feats, 'af', 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.        , 0.68517295, 0.61142142, 0.58133435, 0.52866142,\n",
       "        0.49536998, 0.46899757, 0.45814533, 0.44733408, 0.44468311,\n",
       "        0.44234954, 0.42711528, 0.40122958, 0.31820363, 0.08853655]),\n",
       " Index(['af', 'nni_50', 'nni_20', 'pnni_50', 'cvsd', 'cvnni', 'max_hr', 'sdsd',\n",
       "        'mean_hr', 'pnni_20', 'std_hr', 'rmssd', 'sdnn', 'mean_nni', 'min_hr'],\n",
       "       dtype='object'))"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_topn(challenge_feats, 'af', 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['nni_50',\n",
       " 'nni_20',\n",
       " 'pnni_50',\n",
       " 'pnni_20',\n",
       " 'cvnni',\n",
       " 'cvsd',\n",
       " 'std_hr',\n",
       " 'sdnn',\n",
       " 'max_hr',\n",
       " 'sdsd',\n",
       " 'rmssd',\n",
       " 'mean_hr']"
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afdb_best = list(get_topn(afdb_feats, 'af', 12)[1][1:])\n",
    "afdb_best"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['nni_50',\n",
       " 'nni_20',\n",
       " 'pnni_50',\n",
       " 'cvsd',\n",
       " 'cvnni',\n",
       " 'max_hr',\n",
       " 'sdsd',\n",
       " 'mean_hr',\n",
       " 'pnni_20',\n",
       " 'std_hr',\n",
       " 'rmssd',\n",
       " 'sdnn',\n",
       " 'mean_nni',\n",
       " 'min_hr']"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "challenge_best = list(get_topn(challenge_feats, 'af', 14)[1][1:])\n",
    "challenge_best"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['af',\n",
       " 'nni_50',\n",
       " 'nni_20',\n",
       " 'pnni_50',\n",
       " 'cvsd',\n",
       " 'cvnni',\n",
       " 'max_hr',\n",
       " 'sdsd',\n",
       " 'mean_hr',\n",
       " 'pnni_20',\n",
       " 'std_hr',\n",
       " 'rmssd',\n",
       " 'sdnn']"
      ]
     },
     "execution_count": 322,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersection    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "intersection = [i for i in challenge_best if (i in afdb_best)]\n",
    "union = challenge_best"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [],
   "source": [
    "intersection.insert(0,'af')\n",
    "union.insert(0,'af')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(union)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13"
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(intersection)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "T2 - Train AFDB Test 2017\n",
    "\n",
    "UNION - Train afdb_union test 2017_union\n",
    "INTER - Train afdb_inter test 2017_inter\n",
    "\n",
    "T3 - Train 2017 Test AFDB\n",
    "\n",
    "UNION - Train 2017_union test afdb_union\n",
    "INTER - Train 2017_inter test afdb_inter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "afdb_final = pd.concat([afdb_train,afdb_test])\n",
    "afdb_final = shuffler(afdb_final)\n",
    "afdb_union = afdb_final[union].copy()\n",
    "afdb_inter = afdb_final[intersection].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [],
   "source": [
    "challenge_final = pd.concat([challenge_train,challenge_test])\n",
    "challenge_final = shuffler(challenge_final)\n",
    "challenge_union = challenge_final[union].copy()\n",
    "challenge_inter = challenge_final[intersection].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_t2u = \"../edgeml/examples/pytorch/Bonsai/T2_union/\"\n",
    "\n",
    "np.save(path_t2u + '/train.npy', afdb_union)\n",
    "np.save(path_t2u + '/test.npy', challenge_union)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_t2i = \"../edgeml/examples/pytorch/Bonsai/T2_inter/\"\n",
    "\n",
    "np.save(path_t2i + '/train.npy', afdb_inter)\n",
    "np.save(path_t2i + '/test.npy', challenge_inter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_t3u = \"../edgeml/examples/pytorch/Bonsai/T3_union/\"\n",
    "\n",
    "np.save(path_t3u + '/train.npy', challenge_union)\n",
    "np.save(path_t3u + '/test.npy', afdb_union)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_t3i = \"../edgeml/examples/pytorch/Bonsai/T3_inter/\"\n",
    "\n",
    "np.save(path_t3i + '/train.npy', challenge_inter)\n",
    "np.save(path_t3i + '/test.npy', afdb_inter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "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>af</th>\n",
       "      <th>nni_50</th>\n",
       "      <th>nni_20</th>\n",
       "      <th>pnni_50</th>\n",
       "      <th>cvsd</th>\n",
       "      <th>cvnni</th>\n",
       "      <th>max_hr</th>\n",
       "      <th>sdsd</th>\n",
       "      <th>mean_hr</th>\n",
       "      <th>pnni_20</th>\n",
       "      <th>std_hr</th>\n",
       "      <th>rmssd</th>\n",
       "      <th>sdnn</th>\n",
       "      <th>mean_nni</th>\n",
       "      <th>min_hr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.225140</td>\n",
       "      <td>0.168212</td>\n",
       "      <td>441.176471</td>\n",
       "      <td>39.382229</td>\n",
       "      <td>350.235404</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>54.972745</td>\n",
       "      <td>39.512023</td>\n",
       "      <td>29.521179</td>\n",
       "      <td>175.500000</td>\n",
       "      <td>276.497696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>77.777778</td>\n",
       "      <td>0.592026</td>\n",
       "      <td>0.348276</td>\n",
       "      <td>769.230769</td>\n",
       "      <td>72.937484</td>\n",
       "      <td>530.872923</td>\n",
       "      <td>88.888889</td>\n",
       "      <td>140.462121</td>\n",
       "      <td>72.937568</td>\n",
       "      <td>42.907653</td>\n",
       "      <td>123.200000</td>\n",
       "      <td>266.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.060426</td>\n",
       "      <td>0.039931</td>\n",
       "      <td>237.154150</td>\n",
       "      <td>14.764823</td>\n",
       "      <td>227.755862</td>\n",
       "      <td>66.666667</td>\n",
       "      <td>7.744858</td>\n",
       "      <td>15.937377</td>\n",
       "      <td>10.531698</td>\n",
       "      <td>263.750000</td>\n",
       "      <td>215.827338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006139</td>\n",
       "      <td>0.004341</td>\n",
       "      <td>226.415094</td>\n",
       "      <td>1.632993</td>\n",
       "      <td>225.567098</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.847997</td>\n",
       "      <td>1.632993</td>\n",
       "      <td>1.154701</td>\n",
       "      <td>266.000000</td>\n",
       "      <td>224.719101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.026067</td>\n",
       "      <td>0.021395</td>\n",
       "      <td>298.507463</td>\n",
       "      <td>5.315073</td>\n",
       "      <td>293.075411</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>5.573777</td>\n",
       "      <td>5.338539</td>\n",
       "      <td>4.381780</td>\n",
       "      <td>204.800000</td>\n",
       "      <td>285.714286</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37495</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.051791</td>\n",
       "      <td>0.048007</td>\n",
       "      <td>397.350993</td>\n",
       "      <td>8.117197</td>\n",
       "      <td>375.728557</td>\n",
       "      <td>83.333333</td>\n",
       "      <td>16.406254</td>\n",
       "      <td>8.286535</td>\n",
       "      <td>7.681146</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>346.820809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37496</th>\n",
       "      <td>1</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.307276</td>\n",
       "      <td>0.187848</td>\n",
       "      <td>483.870968</td>\n",
       "      <td>46.890232</td>\n",
       "      <td>404.372721</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>64.679734</td>\n",
       "      <td>46.898066</td>\n",
       "      <td>28.670231</td>\n",
       "      <td>152.625000</td>\n",
       "      <td>291.262136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37497</th>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>83.333333</td>\n",
       "      <td>0.174722</td>\n",
       "      <td>0.103537</td>\n",
       "      <td>431.654676</td>\n",
       "      <td>28.087660</td>\n",
       "      <td>373.700407</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>34.947059</td>\n",
       "      <td>28.304888</td>\n",
       "      <td>16.772994</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>314.136126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37498</th>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27.272727</td>\n",
       "      <td>0.166433</td>\n",
       "      <td>0.137534</td>\n",
       "      <td>697.674419</td>\n",
       "      <td>15.991217</td>\n",
       "      <td>633.309609</td>\n",
       "      <td>45.454545</td>\n",
       "      <td>67.855816</td>\n",
       "      <td>15.991475</td>\n",
       "      <td>13.214719</td>\n",
       "      <td>96.083333</td>\n",
       "      <td>451.127820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37499</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008254</td>\n",
       "      <td>0.006028</td>\n",
       "      <td>352.941176</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>350.205129</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.922056</td>\n",
       "      <td>1.414214</td>\n",
       "      <td>1.032796</td>\n",
       "      <td>171.333333</td>\n",
       "      <td>346.820809</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37500 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       af  nni_50  nni_20     pnni_50      cvsd     cvnni      max_hr  \\\n",
       "0       1     5.0     5.0  100.000000  0.225140  0.168212  441.176471   \n",
       "1       1     7.0     8.0   77.777778  0.592026  0.348276  769.230769   \n",
       "2       1     1.0     2.0   33.333333  0.060426  0.039931  237.154150   \n",
       "3       0     0.0     0.0    0.000000  0.006139  0.004341  226.415094   \n",
       "4       0     0.0     2.0    0.000000  0.026067  0.021395  298.507463   \n",
       "...    ..     ...     ...         ...       ...       ...         ...   \n",
       "37495   0     1.0     5.0   16.666667  0.051791  0.048007  397.350993   \n",
       "37496   1     7.0     7.0  100.000000  0.307276  0.187848  483.870968   \n",
       "37497   1     5.0     6.0   83.333333  0.174722  0.103537  431.654676   \n",
       "37498   1     3.0     5.0   27.272727  0.166433  0.137534  697.674419   \n",
       "37499   0     0.0     0.0    0.000000  0.008254  0.006028  352.941176   \n",
       "\n",
       "            sdsd     mean_hr     pnni_20      std_hr      rmssd       sdnn  \\\n",
       "0      39.382229  350.235404  100.000000   54.972745  39.512023  29.521179   \n",
       "1      72.937484  530.872923   88.888889  140.462121  72.937568  42.907653   \n",
       "2      14.764823  227.755862   66.666667    7.744858  15.937377  10.531698   \n",
       "3       1.632993  225.567098    0.000000    0.847997   1.632993   1.154701   \n",
       "4       5.315073  293.075411   50.000000    5.573777   5.338539   4.381780   \n",
       "...          ...         ...         ...         ...        ...        ...   \n",
       "37495   8.117197  375.728557   83.333333   16.406254   8.286535   7.681146   \n",
       "37496  46.890232  404.372721  100.000000   64.679734  46.898066  28.670231   \n",
       "37497  28.087660  373.700407  100.000000   34.947059  28.304888  16.772994   \n",
       "37498  15.991217  633.309609   45.454545   67.855816  15.991475  13.214719   \n",
       "37499   1.414214  350.205129    0.000000    1.922056   1.414214   1.032796   \n",
       "\n",
       "         mean_nni      min_hr  \n",
       "0      175.500000  276.497696  \n",
       "1      123.200000  266.666667  \n",
       "2      263.750000  215.827338  \n",
       "3      266.000000  224.719101  \n",
       "4      204.800000  285.714286  \n",
       "...           ...         ...  \n",
       "37495  160.000000  346.820809  \n",
       "37496  152.625000  291.262136  \n",
       "37497  162.000000  314.136126  \n",
       "37498   96.083333  451.127820  \n",
       "37499  171.333333  346.820809  \n",
       "\n",
       "[37500 rows x 15 columns]"
      ]
     },
     "execution_count": 321,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "challenge_union"
   ]
  }
 ],
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