Pre-process for high validity (>65% valid).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In this notebook we apply the following steps to prepare our data for classification:\n",
    "\n",
    "1. Remove data items with less than 3 seconds of total data\n",
    "2. Remove the last second of data to remove signs of intention to push the 'confused' button\n",
    "3. Remove data items with > 90% invalid rows (row is invalid if all features are negative)\n",
    "4. Replace negative feature values in remaining items with sentinel value of -1\n",
    "5. Split the remaining data items into 4\n",
    "6. Save data items in ./dataset/augmented/ directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import shutil\n",
    "import math\n",
    "import random\n",
    "\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "SAMPLES_PER_SECOND = 120 # hrz of tobii eye tracker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initial number of not_confused points:  5256\n",
      "initial number of confused points:  110\n",
      "initial number of pump and OE:  59\n"
     ]
    }
   ],
   "source": [
    "#load all paths to unaugmented data, get list of items, remove .DS_Store files\n",
    "confused_path = '../dataset/unaugmented/confused/'\n",
    "not_confused_path = '../dataset/unaugmented/not_confused/'\n",
    "pump_confused_path = '../dataset/unaugmented/confused_PUMP_OpenEnded/'\n",
    "\n",
    "confused_item_names = os.listdir(confused_path)\n",
    "not_confused_item_names = os.listdir(not_confused_path)\n",
    "pump_confused_item_names = os.listdir(pump_confused_path)\n",
    "\n",
    "if '.DS_Store' in confused_item_names:\n",
    "    confused_item_names.remove('.DS_Store')\n",
    "if '.DS_Store' in not_confused_item_names:\n",
    "    not_confused_item_names.remove('.DS_Store')\n",
    "if '.DS_Store' in pump_confused_item_names:\n",
    "    pump_confused_item_names.remove('.DS_Store')\n",
    "    \n",
    "print(\"initial number of not_confused points: \", len(not_confused_item_names))\n",
    "print(\"initial number of confused points: \", len(confused_item_names))\n",
    "print(\"initial number of pump and OE: \", len(pump_confused_item_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pump Confused\n",
      "\n",
      "too short:  107b_V-Open_Ended.pkl\n",
      "\n",
      "Not Confused\n",
      "\n",
      "too short:  100a_V-CDV-21.pkl\n",
      "too short:  100a_V-FE-24.pkl\n",
      "too short:  100a_V-RV-16.pkl\n",
      "too short:  100a_V-RV-20.pkl\n",
      "too short:  100a_V-SortOverall-23.pkl\n",
      "too short:  100a_V-SortTwoFactors-10.pkl\n",
      "too short:  100b_H-CDV-14.pkl\n",
      "too short:  100b_H-FE-15.pkl\n",
      "too short:  100b_H-RV-23.pkl\n",
      "too short:  100b_H-SortTwoFactors-11.pkl\n",
      "too short:  103a_H-FE-24.pkl\n",
      "too short:  103a_H-SortTwoFactors-6.pkl\n",
      "too short:  103b_V-CDV-5.pkl\n",
      "too short:  103b_V-RV-18.pkl\n",
      "too short:  104a_V-SortOverall-12.pkl\n",
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      "too short:  104a_V-SortOverall-22.pkl\n",
      "too short:  104b_H-FE-17.pkl\n",
      "too short:  104b_H-RV-24.pkl\n",
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      "too short:  105b_V-SortTwoFactors-23.pkl\n",
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      "too short:  127a_H-CDV-8.pkl\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "too short:  80b_H-CDV-9.pkl\n",
      "too short:  80b_H-FE-10.pkl\n",
      "too short:  80b_H-FE-16.pkl\n",
      "too short:  80b_H-FE-23.pkl\n",
      "too short:  80b_H-FE-6.pkl\n",
      "too short:  80b_H-RV-11.pkl\n",
      "too short:  80b_H-RV-14.pkl\n",
      "too short:  80b_H-RV-18.pkl\n",
      "too short:  80b_H-RV-2.pkl\n",
      "too short:  80b_H-RV-21.pkl\n",
      "too short:  80b_H-SortOverall-12.pkl\n",
      "too short:  80b_H-SortOverall-15.pkl\n",
      "too short:  80b_H-SortOverall-22.pkl\n",
      "too short:  80b_H-SortOverall-4.pkl\n",
      "too short:  80b_H-SortTwoFactors-20.pkl\n",
      "too short:  80b_H-SortTwoFactors-5.pkl\n",
      "too short:  80b_H-SortTwoFactors-8.pkl\n",
      "too short:  81a_H-SortOverall-17.pkl\n",
      "too short:  81b_V-CDV-8.pkl\n",
      "too short:  81b_V-FE-11.pkl\n",
      "too short:  81b_V-FE-17.pkl\n",
      "too short:  81b_V-RV-18.pkl\n",
      "too short:  81b_V-SortTwoFactors-22.pkl\n",
      "too short:  82a_V-FE-9.pkl\n",
      "too short:  82a_V-RV-2.pkl\n",
      "too short:  82a_V-RV-23.pkl\n",
      "too short:  82b_H-FE-10.pkl\n",
      "too short:  82b_H-RV-15.pkl\n",
      "too short:  83a_H-RV-20.pkl\n",
      "too short:  83b_V-CDV-21.pkl\n",
      "too short:  84b_H-CDV-11.pkl\n",
      "too short:  85b_V-CDV-17.pkl\n",
      "too short:  85b_V-FE-15.pkl\n",
      "too short:  85b_V-RV-14.pkl\n",
      "too short:  85b_V-SortOverall-6.pkl\n",
      "too short:  86a_V-CDV-15.pkl\n",
      "too short:  86a_V-RV-16.pkl\n",
      "too short:  86b_H-FE-15.pkl\n",
      "too short:  86b_H-RV-11.pkl\n",
      "too short:  86b_H-RV-17.pkl\n",
      "too short:  86b_H-RV-18.pkl\n",
      "too short:  86b_H-RV-23.pkl\n",
      "too short:  86b_H-RV-3.pkl\n",
      "too short:  86b_H-SortOverall-22.pkl\n",
      "too short:  87a_V-FE-9.pkl\n",
      "too short:  87a_V-RV-18.pkl\n",
      "too short:  87b_H-FE-8.pkl\n",
      "too short:  87b_H-SortOverall-22.pkl\n",
      "too short:  89a_V-CDV-23.pkl\n",
      "too short:  89a_V-FE-5.pkl\n",
      "too short:  89a_V-FE-8.pkl\n",
      "too short:  89a_V-RV-17.pkl\n",
      "too short:  89a_V-SortTwoFactors-16.pkl\n",
      "too short:  89b_H-FE-5.pkl\n",
      "too short:  89b_H-RV-22.pkl\n",
      "too short:  89b_H-SortOverall-9.pkl\n",
      "too short:  89b_H-SortTwoFactors-16.pkl\n",
      "too short:  8a_V-FE-11.pkl\n",
      "too short:  8a_V-RV-2.pkl\n",
      "too short:  8a_V-RV-24.pkl\n",
      "too short:  8b_H-CDV-6.pkl\n",
      "too short:  8b_H-RV-10.pkl\n",
      "too short:  8b_H-SortOverall-20.pkl\n",
      "too short:  8b_H-SortTwoFactors-14.pkl\n",
      "too short:  90a_H-RV-8.pkl\n",
      "too short:  90a_H-SortTwoFactors-9.pkl\n",
      "too short:  90b_V-CDV-17.pkl\n",
      "too short:  90b_V-CDV-22.pkl\n",
      "too short:  90b_V-FE-12.pkl\n",
      "too short:  90b_V-FE-23.pkl\n",
      "too short:  90b_V-RV-15.pkl\n",
      "too short:  90b_V-SortOverall-11.pkl\n",
      "too short:  90b_V-SortOverall-21.pkl\n",
      "too short:  91a_V-RV-16.pkl\n",
      "too short:  91a_V-RV-18.pkl\n",
      "too short:  91a_V-SortOverall-5.pkl\n",
      "too short:  91b_H-FE-21.pkl\n",
      "too short:  91b_H-RV-11.pkl\n",
      "too short:  91b_H-SortOverall-17.pkl\n",
      "too short:  91b_H-SortOverall-3.pkl\n",
      "too short:  92a_H-CDV-4.pkl\n",
      "too short:  92a_H-SortOverall-22.pkl\n",
      "too short:  92a_H-SortOverall-3.pkl\n",
      "too short:  92b_V-RV-18.pkl\n",
      "too short:  92b_V-SortTwoFactors-17.pkl\n",
      "too short:  93a_V-SortOverall-3.pkl\n",
      "too short:  93b_H-SortOverall-15.pkl\n",
      "too short:  94a_H-FE-17.pkl\n",
      "too short:  94a_H-FE-23.pkl\n",
      "too short:  94a_H-FE-9.pkl\n",
      "too short:  94a_H-RV-11.pkl\n",
      "too short:  94a_H-RV-14.pkl\n",
      "too short:  94a_H-RV-18.pkl\n",
      "too short:  94a_H-RV-24.pkl\n",
      "too short:  94a_H-RV-4.pkl\n",
      "too short:  94a_H-SortOverall-20.pkl\n",
      "too short:  94a_H-SortTwoFactors-10.pkl\n",
      "too short:  94b_V-CDV-15.pkl\n",
      "too short:  94b_V-CDV-21.pkl\n",
      "too short:  94b_V-CDV-6.pkl\n",
      "too short:  94b_V-CDV-8.pkl\n",
      "too short:  94b_V-FE-14.pkl\n",
      "too short:  94b_V-FE-5.pkl\n",
      "too short:  94b_V-FE-9.pkl\n",
      "too short:  94b_V-RV-10.pkl\n",
      "too short:  94b_V-RV-18.pkl\n",
      "too short:  94b_V-RV-24.pkl\n",
      "too short:  94b_V-SortOverall-23.pkl\n",
      "too short:  94b_V-SortTwoFactors-4.pkl\n",
      "too short:  95a_H-CDV-16.pkl\n",
      "too short:  95a_H-FE-8.pkl\n",
      "too short:  95a_H-RV-11.pkl\n",
      "too short:  96a_V-SortOverall-21.pkl\n",
      "too short:  96a_V-SortTwoFactors-12.pkl\n",
      "too short:  96a_V-SortTwoFactors-14.pkl\n",
      "too short:  96b_H-FE-20.pkl\n",
      "too short:  96b_H-FE-9.pkl\n",
      "too short:  96b_H-RV-6.pkl\n",
      "too short:  97a_H-CDV-12.pkl\n",
      "too short:  97a_H-FE-9.pkl\n",
      "too short:  97a_H-SortOverall-10.pkl\n",
      "too short:  97a_H-SortOverall-6.pkl\n",
      "too short:  97a_H-SortTwoFactors-24.pkl\n",
      "too short:  97b_V-FE-9.pkl\n",
      "too short:  97b_V-RV-15.pkl\n",
      "too short:  97b_V-RV-23.pkl\n",
      "too short:  98a_V-CDV-17.pkl\n",
      "too short:  98a_V-CDV-20.pkl\n",
      "too short:  98a_V-FE-21.pkl\n",
      "too short:  98a_V-RV-2.pkl\n",
      "too short:  98b_H-CDV-14.pkl\n",
      "too short:  98b_H-FE-9.pkl\n",
      "too short:  98b_H-SortOverall-3.pkl\n",
      "too short:  99a_H-CDV-11.pkl\n",
      "too short:  99a_H-CDV-16.pkl\n",
      "too short:  99a_H-FE-24.pkl\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "too short:  99b_V-CDV-20.pkl\n",
      "too short:  9a_H-FE-24.pkl\n",
      "too short:  9a_H-RV-22.pkl\n",
      "too short:  9b_V-CDV-10.pkl\n",
      "too short:  9b_V-RV-6.pkl\n",
      "too short:  9b_V-SortOverall-14.pkl\n",
      "too short:  9b_V-SortOverall-2.pkl\n",
      "too short:  9b_V-SortOverall-20.pkl\n",
      "\n",
      "Confused\n",
      "\n",
      "too short:  105b_V-RV-11.pkl\n",
      "too short:  132a_V-RV-18.pkl\n",
      "too short:  39b_V-SortTwoFactors-11.pkl\n",
      "too short:  39b_V-SortTwoFactors-21.pkl\n",
      "5425\n",
      "813\n",
      "\n",
      "excluding 808 not confused points \n",
      "excluding 4 confused points \n",
      "excluding 1 pump or OE points \n",
      "not_confused points remaining:  4448\n",
      "confused points remaining:  106\n",
      "pump or OE points remaining:  58\n"
     ]
    }
   ],
   "source": [
    "#1. Remove data items with less than 3 seconds of total data\n",
    "pump_names_exclude = []\n",
    "confused_names_exclude = []\n",
    "not_confused_names_exclude = []\n",
    "\n",
    "total = 0\n",
    "too_short = 0\n",
    "\n",
    "print(\"Pump Confused\\n\")\n",
    "\n",
    "for i in range(len(pump_confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/confused_PUMP_OpenEnded/'+pump_confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    if item.shape[0] < SAMPLES_PER_SECOND*3:\n",
    "        pump_names_exclude.append(pump_confused_item_names[i])\n",
    "        too_short+= 1\n",
    "        print(\"too short: \", pump_confused_item_names[i])\n",
    "    total+=1\n",
    "    f.close()\n",
    "    \n",
    "print(\"\\nNot Confused\\n\")\n",
    "    \n",
    "for i in range(len(not_confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/not_confused/'+not_confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    if item.shape[0] < SAMPLES_PER_SECOND*3:\n",
    "        not_confused_names_exclude.append(not_confused_item_names[i])\n",
    "        too_short+= 1\n",
    "        print(\"too short: \", not_confused_item_names[i])\n",
    "    total+=1\n",
    "    f.close()\n",
    "\n",
    "print(\"\\nConfused\\n\")\n",
    "        \n",
    "for i in range(len(confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/confused/'+confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    if item.shape[0] < SAMPLES_PER_SECOND*3:\n",
    "        confused_names_exclude.append(confused_item_names[i])\n",
    "        too_short+= 1\n",
    "        print(\"too short: \", confused_item_names[i])\n",
    "    total+=1\n",
    "    f.close()\n",
    "    \n",
    "print(total)\n",
    "print(too_short)\n",
    "print()\n",
    "print(\"excluding %d not confused points \"% len(not_confused_names_exclude))\n",
    "print(\"excluding %d confused points \"% len(confused_names_exclude))\n",
    "print(\"excluding %d pump or OE points \"% len(pump_names_exclude))\n",
    "\n",
    "print(\"not_confused points remaining: \", len(not_confused_item_names)-len(not_confused_names_exclude))\n",
    "print(\"confused points remaining: \", len(confused_item_names)-len(confused_names_exclude))\n",
    "print(\"pump or OE points remaining: \", len(pump_confused_item_names)-len(pump_names_exclude))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def percent_invalid_rows(df):\n",
    "    \"\"\" checks the % of invalid rows in a data item\n",
    "    \n",
    "    \"\"\"\n",
    "    # return # invalid and total rows (int,int)\n",
    "    total_rows = df.shape[0]\n",
    "    if total_rows == 0:\n",
    "        print(\"empty pkl\")\n",
    "        input()\n",
    "    # we define a row as invalid if all of the features named below contain invalid values\n",
    "    num_invalid = df[(df['ValidityLeft'] == 4.0) & (df['ValidityRight'] == 4.0)].shape[0]\n",
    "    return (num_invalid/total_rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fix_missing_eye(df):\n",
    "    \"\"\" items passed in must have only one of ValidityLeft or ValidityRight = 4.0\n",
    "    \n",
    "    \"\"\"\n",
    "    df = df.values\n",
    "    i_left = (df[:,6] == 4.0) & (df[:,13] == 0.0)#get indicies of rows with ValidityLeft = 4.0 (invalid)\n",
    "    i_right = (df[:,6] == 0.0) & (df[:,13] == 4.0)#get indicies of rows with ValidityRight = 4.0 (invalid)\n",
    "\n",
    "    df[i_left,0:7] = df[i_left,7:14]\n",
    "    df[i_right,7:14] = df[i_right,0:7]\n",
    "\n",
    "    df = pd.DataFrame(df)\n",
    "\n",
    "    return df\n",
    "\n",
    "def fix_invalid_rows(df):\n",
    "    \"\"\" Replace values corresponding to an invalid eye with -1 everywhere\n",
    "    \n",
    "    \"\"\"\n",
    "    df = df.values\n",
    "    i_left = (df[:,6] == 4.0) #get indicies of rows with ValidityLeft = 4.0 (invalid)\n",
    "    i_right = (df[:,13] == 4.0)#get indicies of rows with ValidityRight = 4.0 (invalid)\n",
    "\n",
    "    df[i_left,0:7] = -1.0\n",
    "    df[i_right,7:14] = -1.0\n",
    "\n",
    "    df = pd.DataFrame(df)\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Pump Confused\n",
      "\n",
      "110b_H-PUMP-7.pkl\n",
      "0.8394241417497231\n",
      "127b_V-PUMP-13.pkl\n",
      "0.6618625277161863\n",
      "132a_V-Open_Ended.pkl\n",
      "0.5139455782312925\n",
      "134a_V-Open_Ended.pkl\n",
      "0.39718035974720467\n",
      "141a_H-Open_Ended.pkl\n",
      "0.5514893617021277\n",
      "142a_V-Open_Ended.pkl\n",
      "0.6933848382423949\n",
      "143a_H-PUMP-1.pkl\n",
      "0.9528563505268997\n",
      "152a_V-PUMP-1.pkl\n",
      "0.9294377067254685\n",
      "152b_H-PUMP-1.pkl\n",
      "0.8515235457063712\n",
      "20a_V_Open_Ended.pkl\n",
      "0.6020186335403727\n",
      "24b_H_Open_Ended.pkl\n",
      "0.8349698535745047\n",
      "30a_V_Open_Ended.pkl\n",
      "0.7062193126022913\n",
      "33b_V-PUMP-7.pkl\n",
      "0.4772727272727273\n",
      "56b_H-PUMP-7.pkl\n",
      "0.545655783065855\n",
      "78a_V-PUMP-7.pkl\n",
      "0.9988907376594565\n",
      "82b_H-PUMP-7.pkl\n",
      "0.6760641238253179\n",
      "99b_V-PUMP-13.pkl\n",
      "0.9162072767364939\n",
      "9a_H_Open_Ended.pkl\n",
      "0.5284360189573459\n",
      "9b_V-PUMP-19.pkl\n",
      "0.9939293598233996\n",
      "9b_V-PUMP-7.pkl\n",
      "0.9944781888459415\n",
      "\n",
      "Not Confused\n",
      "\n",
      "100a_V-SortTwoFactors-14.pkl\n",
      "0.5314861460957179\n",
      "103b_V-SortOverall-23.pkl\n",
      "0.45732022762545266\n",
      "103b_V-SortTwoFactors-24.pkl\n",
      "0.7257597684515196\n",
      "105a_H-SortOverall-24.pkl\n",
      "0.4529463500439754\n",
      "105b_V-RV-18.pkl\n",
      "0.4090909090909091\n",
      "109a_H-CDV-15.pkl\n",
      "0.7614107883817427\n",
      "109a_H-FE-11.pkl\n",
      "0.3716216216216216\n",
      "109b_V-CDV-8.pkl\n",
      "0.5337349397590362\n",
      "109b_V-SortOverall-12.pkl\n",
      "0.496996996996997\n",
      "10b_H-CDV-17.pkl\n",
      "0.8123406425293218\n",
      "110a_V-CDV-17.pkl\n",
      "0.4317673378076063\n",
      "111a_H-CDV-16.pkl\n",
      "0.4195601851851852\n",
      "116a_V-CDV-11.pkl\n",
      "0.7048567870485679\n",
      "116a_V-CDV-23.pkl\n",
      "0.6040494938132733\n",
      "116a_V-FE-2.pkl\n",
      "0.6225165562913907\n",
      "116a_V-FE-20.pkl\n",
      "0.6061224489795919\n",
      "116a_V-RV-10.pkl\n",
      "0.55359765051395\n",
      "116a_V-RV-18.pkl\n",
      "0.669980879541109\n",
      "116a_V-RV-24.pkl\n",
      "0.7126373626373627\n",
      "116a_V-RV-4.pkl\n",
      "0.4869927159209157\n",
      "116a_V-SortOverall-12.pkl\n",
      "0.6475558237779119\n",
      "116a_V-SortOverall-15.pkl\n",
      "0.7067812798471824\n",
      "118a_V-CDV-17.pkl\n",
      "0.357630979498861\n",
      "118a_V-CDV-3.pkl\n",
      "0.40896664844177144\n",
      "118a_V-FE-8.pkl\n",
      "0.37373737373737376\n",
      "118a_V-RV-15.pkl\n",
      "0.3579295154185022\n",
      "118a_V-RV-23.pkl\n",
      "0.4272930648769575\n",
      "118a_V-RV-4.pkl\n",
      "0.36372093023255814\n",
      "118a_V-SortOverall-20.pkl\n",
      "0.5797224582271311\n",
      "118a_V-SortOverall-9.pkl\n",
      "0.5852534562211982\n",
      "118a_V-SortTwoFactors-10.pkl\n",
      "0.35282155566853074\n",
      "118a_V-SortTwoFactors-14.pkl\n",
      "0.48404701931150296\n",
      "122a_V-CDV-5.pkl\n",
      "0.3986983246956731\n",
      "122a_V-FE-12.pkl\n",
      "0.39282103134479274\n",
      "122a_V-RV-11.pkl\n",
      "0.35776311219173323\n",
      "122a_V-SortOverall-24.pkl\n",
      "0.5099403578528827\n",
      "122a_V-SortTwoFactors-10.pkl\n",
      "0.3887106184364061\n",
      "122a_V-SortTwoFactors-17.pkl\n",
      "0.3600352112676056\n",
      "123b_V-CDV-11.pkl\n",
      "0.4991158267020336\n",
      "123b_V-CDV-20.pkl\n",
      "0.38697068403908796\n",
      "123b_V-RV-18.pkl\n",
      "0.46830265848670755\n",
      "123b_V-RV-21.pkl\n",
      "0.5525902668759811\n",
      "123b_V-RV-4.pkl\n",
      "0.4106104651162791\n",
      "123b_V-SortOverall-14.pkl\n",
      "0.3898750821827745\n",
      "123b_V-SortOverall-22.pkl\n",
      "0.8043478260869565\n",
      "123b_V-SortOverall-6.pkl\n",
      "0.3576702214930271\n",
      "123b_V-SortOverall-8.pkl\n",
      "0.5115303983228512\n",
      "124a_H-CDV-16.pkl\n",
      "0.9964601769911504\n",
      "124a_H-CDV-22.pkl\n",
      "0.9690402476780186\n",
      "124a_H-CDV-9.pkl\n",
      "0.9974842767295597\n",
      "124a_H-FE-10.pkl\n",
      "1.0\n",
      "124a_H-FE-15.pkl\n",
      "0.9990074441687344\n",
      "124a_H-FE-20.pkl\n",
      "0.9348739495798319\n",
      "124a_H-FE-4.pkl\n",
      "0.9425981873111783\n",
      "124a_H-RV-24.pkl\n",
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      "97b_V-SortTwoFactors-14.pkl\n",
      "0.9981211836542978\n",
      "97b_V-SortTwoFactors-24.pkl\n",
      "0.996116504854369\n",
      "97b_V-SortTwoFactors-6.pkl\n",
      "0.9974236290025764\n",
      "97b_V-SortTwoFactors-8.pkl\n",
      "1.0\n",
      "98a_V-CDV-4.pkl\n",
      "0.9645833333333333\n",
      "98a_V-CDV-8.pkl\n",
      "0.7773109243697479\n",
      "98a_V-FE-12.pkl\n",
      "1.0\n",
      "98a_V-FE-16.pkl\n",
      "0.7908224076281287\n",
      "98a_V-FE-3.pkl\n",
      "0.8829008649367931\n",
      "98a_V-RV-10.pkl\n",
      "0.8478123018389346\n",
      "98a_V-RV-18.pkl\n",
      "0.8893280632411067\n",
      "98a_V-RV-23.pkl\n",
      "0.7788104089219331\n",
      "98a_V-SortOverall-11.pkl\n",
      "0.9153225806451613\n",
      "98a_V-SortOverall-15.pkl\n",
      "0.706\n",
      "98a_V-SortOverall-24.pkl\n",
      "0.9300833867864016\n",
      "98a_V-SortOverall-6.pkl\n",
      "0.907358390682901\n",
      "98a_V-SortTwoFactors-14.pkl\n",
      "0.7580893682588598\n",
      "98a_V-SortTwoFactors-22.pkl\n",
      "0.9096159399364713\n",
      "98a_V-SortTwoFactors-5.pkl\n",
      "0.939458413926499\n",
      "98a_V-SortTwoFactors-9.pkl\n",
      "0.8468271334792122\n",
      "98b_H-CDV-12.pkl\n",
      "0.5742574257425742\n",
      "98b_H-CDV-23.pkl\n",
      "0.9487750556792873\n",
      "98b_H-CDV-4.pkl\n",
      "0.5846329402814758\n",
      "98b_H-FE-17.pkl\n",
      "0.8231827111984283\n",
      "98b_H-FE-21.pkl\n",
      "0.8693586698337292\n",
      "98b_H-FE-5.pkl\n",
      "0.8033826638477801\n",
      "98b_H-RV-18.pkl\n",
      "0.6581818181818182\n",
      "98b_H-RV-20.pkl\n",
      "0.7329749103942652\n",
      "98b_H-RV-6.pkl\n",
      "0.6386986301369864\n",
      "98b_H-RV-8.pkl\n",
      "0.6915776986951364\n",
      "98b_H-SortOverall-11.pkl\n",
      "0.8477157360406091\n",
      "98b_H-SortOverall-15.pkl\n",
      "0.9478487614080835\n",
      "98b_H-SortOverall-22.pkl\n",
      "0.8937282229965157\n",
      "98b_H-SortTwoFactors-10.pkl\n",
      "0.834941050375134\n",
      "98b_H-SortTwoFactors-16.pkl\n",
      "0.7328767123287672\n",
      "98b_H-SortTwoFactors-2.pkl\n",
      "0.7600974930362117\n",
      "98b_H-SortTwoFactors-24.pkl\n",
      "0.753004005340454\n",
      "99a_H-CDV-22.pkl\n",
      "0.9980092899800929\n",
      "99a_H-FE-12.pkl\n",
      "0.9979919678714859\n",
      "99a_H-FE-5.pkl\n",
      "0.9187425860023725\n",
      "99a_H-RV-10.pkl\n",
      "0.9966777408637874\n",
      "99a_H-RV-14.pkl\n",
      "1.0\n",
      "99a_H-RV-18.pkl\n",
      "0.9951573849878934\n",
      "99a_H-RV-21.pkl\n",
      "0.9961685823754789\n",
      "99a_H-SortOverall-15.pkl\n",
      "0.9933665008291874\n",
      "99a_H-SortOverall-23.pkl\n",
      "0.9931237721021611\n",
      "99a_H-SortOverall-6.pkl\n",
      "0.9961013645224172\n",
      "99a_H-SortOverall-9.pkl\n",
      "0.9953846153846154\n",
      "99a_H-SortTwoFactors-17.pkl\n",
      "0.994478527607362\n",
      "99a_H-SortTwoFactors-20.pkl\n",
      "0.9973684210526316\n",
      "99a_H-SortTwoFactors-8.pkl\n",
      "0.9964881474978051\n",
      "99b_V-CDV-12.pkl\n",
      "0.9908136482939632\n",
      "99b_V-CDV-16.pkl\n",
      "0.995702005730659\n",
      "99b_V-CDV-6.pkl\n",
      "0.5\n",
      "99b_V-FE-10.pkl\n",
      "0.7038461538461539\n",
      "99b_V-FE-17.pkl\n",
      "1.0\n",
      "99b_V-RV-11.pkl\n",
      "0.742238946378175\n",
      "99b_V-RV-14.pkl\n",
      "0.9885844748858448\n",
      "99b_V-RV-18.pkl\n",
      "0.9976359338061466\n",
      "99b_V-RV-21.pkl\n",
      "0.45493562231759654\n",
      "99b_V-RV-3.pkl\n",
      "0.4068504594820384\n",
      "99b_V-SortOverall-22.pkl\n",
      "0.3886986301369863\n",
      "99b_V-SortOverall-9.pkl\n",
      "0.8906633906633906\n",
      "99b_V-SortTwoFactors-15.pkl\n",
      "0.9957044673539519\n",
      "99b_V-SortTwoFactors-23.pkl\n",
      "0.3699949315762798\n",
      "99b_V-SortTwoFactors-5.pkl\n",
      "0.9398496240601504\n",
      "99b_V-SortTwoFactors-8.pkl\n",
      "0.8158730158730159\n",
      "9a_H-CDV-9.pkl\n",
      "0.36020942408376966\n",
      "9b_V-CDV-15.pkl\n",
      "0.9584615384615385\n",
      "9b_V-CDV-22.pkl\n",
      "0.9981718464351006\n",
      "9b_V-CDV-4.pkl\n",
      "0.9955056179775281\n",
      "9b_V-FE-16.pkl\n",
      "0.9987146529562982\n",
      "9b_V-FE-23.pkl\n",
      "0.9974554707379135\n",
      "9b_V-FE-3.pkl\n",
      "0.9984251968503937\n",
      "9b_V-FE-9.pkl\n",
      "1.0\n",
      "9b_V-RV-11.pkl\n",
      "0.996734693877551\n",
      "9b_V-RV-18.pkl\n",
      "0.9977924944812362\n",
      "9b_V-RV-21.pkl\n",
      "0.9977810650887574\n",
      "9b_V-SortOverall-8.pkl\n",
      "0.9911699779249448\n",
      "9b_V-SortTwoFactors-12.pkl\n",
      "0.9964966913195796\n",
      "9b_V-SortTwoFactors-17.pkl\n",
      "0.9966887417218543\n",
      "9b_V-SortTwoFactors-24.pkl\n",
      "0.9975490196078431\n",
      "9b_V-SortTwoFactors-5.pkl\n",
      "0.8227459016393442\n",
      "\n",
      "Confused\n",
      "\n",
      "134a_V-CDV-11.pkl\n",
      "0.8785971223021583\n",
      "134a_V-CDV-3.pkl\n",
      "0.8546384222059897\n",
      "134a_V-RV-18.pkl\n",
      "0.8530721282279609\n",
      "134a_V-RV-21.pkl\n",
      "0.8349650349650349\n",
      "134a_V-SortTwoFactors-9.pkl\n",
      "0.6297136376523959\n",
      "22a_V-SortTwoFactors-12.pkl\n",
      "0.3940117853161331\n",
      "30a_V-SortTwoFactors-6.pkl\n",
      "0.6050531914893617\n",
      "31a_H-SortTwoFactors-24.pkl\n",
      "0.44335778321108393\n",
      "31a_H-SortTwoFactors-9.pkl\n",
      "0.46991676575505353\n",
      "33a_H-SortOverall-2.pkl\n",
      "0.42539184952978054\n",
      "34a_V-CDV-2.pkl\n",
      "0.8246471226927253\n",
      "34a_V-RV-9.pkl\n",
      "0.9581437670609645\n",
      "44a_V-RV-3.pkl\n",
      "0.928087986463621\n",
      "49a_H-FE-3.pkl\n",
      "0.9324499030381384\n",
      "52a_V-SortTwoFactors-11.pkl\n",
      "0.9925312550738756\n",
      "52a_V-SortTwoFactors-15.pkl\n",
      "0.9976771196283392\n",
      "59b_V-CDV-17.pkl\n",
      "0.995741056218058\n",
      "73a_H-CDV-3.pkl\n",
      "0.6776400171013254\n",
      "73a_H-CDV-8.pkl\n",
      "0.6615969581749049\n",
      "76a_V-SortTwoFactors-6.pkl\n",
      "0.690188091529891\n",
      "97a_H-RV-14.pkl\n",
      "0.3763856401911929\n",
      "\n",
      "5425.000000 points processed\n",
      "Number of invalid not_confused:  1323\n",
      "Number of invalid confused:  21\n",
      "Number of pump confused:  20\n",
      "\n",
      "total number of not_confused to exclued so far:  2131\n",
      "total number of confused to exclued so far:  25\n",
      "total number of pump or OE to exclued so far:  21\n"
     ]
    }
   ],
   "source": [
    "# 3. \n",
    "total = 0\n",
    "invalid_pump = 0\n",
    "invalid_not_confused = 0\n",
    "invalid_confused = 0\n",
    "\n",
    "print(\"\\nPump Confused\\n\")\n",
    "\n",
    "for i in range(len(pump_confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/confused_PUMP_OpenEnded/'+ pump_confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    if pump_confused_item_names[i] not in pump_names_exclude:\n",
    "        percent_inval = percent_invalid_rows(item)\n",
    "        if percent_inval > 0.35:\n",
    "                print(pump_confused_item_names[i])\n",
    "                print(percent_inval)\n",
    "                pump_names_exclude.append(pump_confused_item_names[i])\n",
    "                invalid_pump+=1\n",
    "    total+=1\n",
    "    f.close()\n",
    "\n",
    "print(\"\\nNot Confused\\n\")\n",
    "\n",
    "for i in range(len(not_confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/not_confused/'+ not_confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    \n",
    "    if not_confused_item_names[i] not in not_confused_names_exclude:\n",
    "        percent_inval = percent_invalid_rows(item)\n",
    "        if percent_inval > 0.35:\n",
    "            print(not_confused_item_names[i])\n",
    "            print(percent_inval)\n",
    "            not_confused_names_exclude.append(not_confused_item_names[i])\n",
    "            invalid_not_confused+=1\n",
    "    total+=1\n",
    "    f.close()\n",
    "      \n",
    "print(\"\\nConfused\\n\")\n",
    "\n",
    "for i in range(len(confused_item_names)):\n",
    "    f = open('../dataset/unaugmented/confused/'+ confused_item_names[i], 'rb')\n",
    "    item = pickle.load(f)\n",
    "    \n",
    "    if confused_item_names[i] not in confused_names_exclude:\n",
    "        percent_inval = percent_invalid_rows(item)\n",
    "        if percent_inval > 0.35:\n",
    "            print(confused_item_names[i])\n",
    "            print(percent_inval)\n",
    "            confused_names_exclude.append(confused_item_names[i])\n",
    "            invalid_confused+=1\n",
    "    total+=1\n",
    "    f.close()\n",
    "\n",
    "print()\n",
    "print(\"%f points processed\"% total)\n",
    "print(\"Number of invalid not_confused: \", invalid_not_confused)\n",
    "print(\"Number of invalid confused: \", invalid_confused)\n",
    "print(\"Number of pump confused: \", invalid_pump)\n",
    "\n",
    "print()\n",
    "\n",
    "print(\"total number of not_confused to exclued so far: \", len(not_confused_names_exclude))\n",
    "print(\"total number of confused to exclued so far: \", len(confused_names_exclude))\n",
    "print(\"total number of pump or OE to exclued so far: \", len(pump_names_exclude))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#2. Remove the last second of data to remove signs of intention to push the 'confused' button\n",
    "#4. Replace negative feature values in remaining items with sentinel value of -1\n",
    "#5. Split the remaining data items into 4\n",
    "#6. Save data items in ./dataset/augmented/ directory\n",
    "\n",
    "if os.path.exists('../dataset/augmented/confused_highly_valid/'):\n",
    "    shutil.rmtree('../dataset/augmented/confused_highly_valid/')\n",
    "if os.path.exists('../dataset/augmented/not_confused_highly_valid/'):\n",
    "    shutil.rmtree('../dataset/augmented/not_confused_highly_valid/')\n",
    "if os.path.exists('../dataset/augmented/pump_confused_highly_valid/'):\n",
    "    shutil.rmtree('../dataset/augmented/pump_confused_highly_valid/')\n",
    "            \n",
    "# Make new temp directories\n",
    "os.makedirs('../dataset/augmented/confused_highly_valid/')\n",
    "os.makedirs('../dataset/augmented/not_confused_highly_valid/')\n",
    "os.makedirs('../dataset/augmented/pump_confused_highly_valid/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove excluded items from list of items in each class\n",
    "for item in confused_names_exclude:\n",
    "    confused_item_names.remove(item)\n",
    "    \n",
    "for item in not_confused_names_exclude:\n",
    "    not_confused_item_names.remove(item)\n",
    "    \n",
    "for item in pump_names_exclude:\n",
    "    pump_confused_item_names.remove(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37a_H-SortTwoFactors-14.pkl\n",
      "35a_H-SortTwoFactors-22.pkl\n",
      "86a_V-FE-10.pkl\n",
      "103a_H-CDV-17.pkl\n",
      "12b_H-CDV-5.pkl\n",
      "9a_H-SortTwoFactors-12.pkl\n",
      "132b_H-CDV-6.pkl\n",
      "58a_V-SortTwoFactors-6.pkl\n",
      "145b_V-SortTwoFactors-10.pkl\n",
      "112a_V-SortTwoFactors-5.pkl\n",
      "103a_H-CDV-12.pkl\n",
      "129b_V-SortTwoFactors-23.pkl\n",
      "132a_V-SortOverall-9.pkl\n",
      "37a_H-SortTwoFactors-12.pkl\n",
      "74b_H-FE-12.pkl\n",
      "134b_H-CDV-4.pkl\n",
      "35a_H-SortTwoFactors-4.pkl\n",
      "105b_V-FE-20.pkl\n",
      "132b_H-SortOverall-9.pkl\n",
      "39a_H-SortTwoFactors-24.pkl\n",
      "1b_V-CDV-17.pkl\n",
      "58a_V-SortTwoFactors-23.pkl\n",
      "36a_V-SortTwoFactors-2.pkl\n",
      "121b_V-FE-2.pkl\n",
      "48a_V-SortTwoFactors-12.pkl\n",
      "111a_H-SortTwoFactors-3.pkl\n",
      "39b_V-RV-18.pkl\n",
      "132b_H-CDV-12.pkl\n",
      "143a_H-CDV-17.pkl\n",
      "133a_H-CDV-16.pkl\n",
      "39b_V-SortTwoFactors-17.pkl\n",
      "14a_V-SortTwoFactors-3.pkl\n",
      "50a_V-SortTwoFactors-22.pkl\n",
      "114a_V-SortTwoFactors-12.pkl\n",
      "141a_H-RV-18.pkl\n",
      "40a_V-SortTwoFactors-17.pkl\n",
      "132a_V-SortOverall-21.pkl\n",
      "6b_H-SortOverall-10.pkl\n",
      "132a_V-CDV-2.pkl\n",
      "39b_V-SortTwoFactors-3.pkl\n",
      "132b_H-CDV-16.pkl\n",
      "141a_H-SortTwoFactors-22.pkl\n",
      "137a_H-SortTwoFactors-2.pkl\n",
      "105a_H-RV-22.pkl\n",
      "86b_H-CDV-6.pkl\n",
      "130a_V-RV-10.pkl\n",
      "55b_V-CDV-11.pkl\n",
      "10a_V-CDV-2.pkl\n",
      "19b_V-RV-24.pkl\n",
      "8a_V-SortTwoFactors-10.pkl\n",
      "25a_H-RV-22.pkl\n",
      "122a_V-SortTwoFactors-4.pkl\n",
      "21b_V-SortTwoFactors-11.pkl\n",
      "58a_V-SortTwoFactors-14.pkl\n",
      "121a_H-SortTwoFactors-20.pkl\n",
      "63a_H-SortTwoFactors-5.pkl\n",
      "121a_H-CDV-9.pkl\n",
      "7a_H-SortTwoFactors-4.pkl\n",
      "32a_V-SortTwoFactors-11.pkl\n",
      "126a_V-SortTwoFactors-6.pkl\n",
      "8b_H-CDV-21.pkl\n",
      "142b_H-CDV-22.pkl\n",
      "142a_V-CDV-15.pkl\n",
      "134b_H-CDV-15.pkl\n",
      "131a_H-SortTwoFactors-12.pkl\n",
      "105a_H-FE-17.pkl\n",
      "131a_H-CDV-5.pkl\n",
      "3a_H-SortTwoFactors-11.pkl\n",
      "86a_V-SortTwoFactors-4.pkl\n",
      "105b_V-RV-5.pkl\n",
      "145b_V-SortTwoFactors-24.pkl\n",
      "137a_H-FE-4.pkl\n",
      "35a_H-SortTwoFactors-15.pkl\n",
      "39a_H-SortTwoFactors-17.pkl\n",
      "131b_V-SortTwoFactors-21.pkl\n",
      "11a_H-SortTwoFactors-5.pkl\n",
      "19b_V-SortTwoFactors-23.pkl\n",
      "121b_V-SortTwoFactors-11.pkl\n",
      "105a_H-RV-8.pkl\n",
      "37a_H-SortTwoFactors-5.pkl\n",
      "132a_V-SortTwoFactors-6.pkl\n",
      "82a_V-SortTwoFactors-4.pkl\n",
      "137b_V-FE-20.pkl\n",
      "39a_H-SortTwoFactors-10.pkl\n",
      "105b_V-FE-8.pkl\n"
     ]
    }
   ],
   "source": [
    "to_path = '../dataset/augmented/confused_highly_valid/'\n",
    "for name in confused_item_names:\n",
    "    print(name)\n",
    "    f = open(confused_path+name, 'rb')\n",
    "    item = pickle.load(f)\n",
    "    # replace remaining invalid values with -1\n",
    "    item = fix_missing_eye(item)\n",
    "    item = fix_invalid_rows(item)\n",
    "    item = item.replace({6:4.0, 13:4.0}, -1)\n",
    "    # remove last second\n",
    "    item = item.values[:-SAMPLES_PER_SECOND]\n",
    "    d1 = pd.DataFrame(item[0::4]).to_pickle(to_path+name.split('.')[0]+'-1.pkl')\n",
    "    d2 = pd.DataFrame(item[1::4]).to_pickle(to_path+name.split('.')[0]+'-2.pkl')\n",
    "    d3 = pd.DataFrame(item[2::4]).to_pickle(to_path+name.split('.')[0]+'-3.pkl')\n",
    "    d4 = pd.DataFrame(item[3::4]).to_pickle(to_path+name.split('.')[0]+'-4.pkl')\n",
    "    f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106b_H-CDV-9.pkl\n",
      "45b_V-RV-22.pkl\n",
      "79b_V-SortTwoFactors-21.pkl\n",
      "91a_V-FE-4.pkl\n",
      "54a_V-SortOverall-8.pkl\n",
      "39b_V-CDV-10.pkl\n",
      "63b_V-CDV-12.pkl\n",
      "38a_V-FE-17.pkl\n",
      "66b_H-RV-18.pkl\n",
      "111a_H-SortOverall-4.pkl\n",
      "85a_H-CDV-3.pkl\n",
      "62b_V-RV-15.pkl\n",
      "145b_V-RV-5.pkl\n",
      "105a_H-SortTwoFactors-2.pkl\n",
      "36b_H-SortTwoFactors-16.pkl\n",
      "122b_H-FE-15.pkl\n",
      "35b_V-SortTwoFactors-2.pkl\n",
      "105b_V-SortTwoFactors-3.pkl\n",
      "45b_V-SortOverall-3.pkl\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "93a_V-RV-9.pkl\n",
      "77b_V-SortTwoFactors-24.pkl\n",
      "12b_H-RV-18.pkl\n",
      "25b_V-RV-18.pkl\n",
      "121a_H-SortTwoFactors-2.pkl\n",
      "7b_V-FE-14.pkl\n",
      "114b_H-RV-16.pkl\n",
      "22b_H-FE-5.pkl\n",
      "84a_V-SortTwoFactors-9.pkl\n",
      "47a_H-SortOverall-11.pkl\n",
      "110a_V-SortOverall-10.pkl\n",
      "72a_V-RV-8.pkl\n",
      "107a_H-SortOverall-15.pkl\n",
      "138a_V-FE-12.pkl\n",
      "17b_V-CDV-20.pkl\n",
      "129a_H-RV-2.pkl\n",
      "142a_V-SortTwoFactors-16.pkl\n",
      "21b_V-SortOverall-9.pkl\n",
      "65b_V-SortOverall-9.pkl\n",
      "142b_H-FE-8.pkl\n",
      "116b_H-SortOverall-17.pkl\n",
      "16b_H-RV-11.pkl\n",
      "29a_H-SortOverall-10.pkl\n",
      "47b_V-RV-20.pkl\n",
      "64b_H-SortOverall-11.pkl\n",
      "64b_H-CDV-8.pkl\n",
      "126a_V-SortTwoFactors-23.pkl\n",
      "10a_V-SortTwoFactors-24.pkl\n",
      "90a_H-FE-10.pkl\n",
      "36b_H-FE-17.pkl\n",
      "65b_V-CDV-15.pkl\n",
      "21b_V-CDV-3.pkl\n",
      "87a_V-SortOverall-2.pkl\n",
      "84b_H-SortTwoFactors-9.pkl\n",
      "31b_V-RV-23.pkl\n",
      "8b_H-SortTwoFactors-23.pkl\n",
      "149a_H-RV-18.pkl\n",
      "4b_H-RV-15.pkl\n",
      "104b_H-SortTwoFactors-21.pkl\n",
      "2b_H-SortTwoFactors-17.pkl\n",
      "123b_V-CDV-5.pkl\n",
      "25b_V-FE-14.pkl\n",
      "12b_H-FE-14.pkl\n",
      "118a_V-FE-24.pkl\n",
      "67b_V-RV-17.pkl\n",
      "50b_H-RV-17.pkl\n",
      "75b_V-FE-3.pkl\n",
      "100a_V-FE-3.pkl\n",
      "133b_V-FE-14.pkl\n",
      "96b_H-SortOverall-8.pkl\n",
      "22b_H-RV-20.pkl\n",
      "77b_V-SortTwoFactors-6.pkl\n",
      "70b_H-FE-11.pkl\n",
      "100b_H-FE-20.pkl\n",
      "32b_H-RV-12.pkl\n",
      "137b_V-FE-20.pkl\n",
      "7b_V-RV-24.pkl\n",
      "106b_H-CDV-22.pkl\n",
      "55b_V-SortTwoFactors-5.pkl\n",
      "93a_V-FE-21.pkl\n",
      "128a_V-CDV-2.pkl\n",
      "7b_V-RV-18.pkl\n",
      "67a_H-CDV-17.pkl\n",
      "130b_H-RV-14.pkl\n",
      "112b_H-SortOverall-6.pkl\n",
      "75b_V-RV-16.pkl\n",
      "43b_V-SortOverall-2.pkl\n",
      "4a_V-RV-6.pkl\n",
      "139a_H-RV-4.pkl\n",
      "45a_H-RV-9.pkl\n",
      "72b_H-FE-22.pkl\n",
      "10a_V-CDV-11.pkl\n",
      "86a_V-CDV-3.pkl\n",
      "84a_V-SortTwoFactors-15.pkl\n",
      "137b_V-SortTwoFactors-10.pkl\n",
      "38b_H-CDV-12.pkl\n",
      "65b_V-RV-18.pkl\n",
      "82a_V-SortOverall-3.pkl\n",
      "52b_H-RV-18.pkl\n",
      "140b_H-CDV-2.pkl\n",
      "129b_V-SortTwoFactors-14.pkl\n",
      "141a_H-SortTwoFactors-9.pkl\n",
      "144a_V-SortTwoFactors-21.pkl\n",
      "46b_H-RV-22.pkl\n",
      "143b_V-FE-10.pkl\n",
      "105b_V-CDV-9.pkl\n",
      "144b_H-RV-18.pkl\n",
      "65b_V-RV-24.pkl\n",
      "33b_V-RV-10.pkl\n",
      "10b_H-RV-16.pkl\n",
      "3b_V-RV-4.pkl\n",
      "112a_V-SortOverall-16.pkl\n",
      "62b_V-CDV-11.pkl\n",
      "105b_V-FE-8.pkl\n",
      "93b_H-SortTwoFactors-20.pkl\n",
      "93b_H-SortOverall-9.pkl\n",
      "34b_H-FE-24.pkl\n",
      "64a_V-SortTwoFactors-21.pkl\n",
      "129a_H-CDV-24.pkl\n",
      "46b_H-SortTwoFactors-3.pkl\n",
      "77a_H-SortOverall-15.pkl\n",
      "86a_V-SortTwoFactors-22.pkl\n",
      "106a_V-SortOverall-11.pkl\n",
      "61b_H-SortOverall-24.pkl\n",
      "7a_H-CDV-21.pkl\n",
      "13b_V-FE-16.pkl\n",
      "90a_H-CDV-11.pkl\n",
      "72b_H-SortOverall-11.pkl\n",
      "45a_H-SortTwoFactors-16.pkl\n",
      "10a_V-SortOverall-4.pkl\n",
      "86b_H-FE-8.pkl\n",
      "58a_V-SortOverall-16.pkl\n",
      "67b_V-SortTwoFactors-14.pkl\n",
      "95a_H-SortTwoFactors-6.pkl\n",
      "116b_H-RV-18.pkl\n",
      "35a_H-SortOverall-3.pkl\n",
      "6b_H-RV-5.pkl\n",
      "121b_V-RV-18.pkl\n",
      "123a_H-SortOverall-16.pkl\n",
      "126b_H-FE-10.pkl\n"
     ]
    }
   ],
   "source": [
    "to_path = './dataset/augmented/not_confused_highly_valid/'\n",
    "for name in not_confused_item_names:\n",
    "    print(name)\n",
    "    f = open(not_confused_path+name, 'rb')\n",
    "    item = pickle.load(f)\n",
    "    # replace remaining invalid values with -1\n",
    "    item = fix_missing_eye(item)\n",
    "    item = fix_invalid_rows(item)\n",
    "\n",
    "    item = item.replace({6:4.0, 13:4.0}, -1)\n",
    "\n",
    "    # remove last second\n",
    "    item = item.values[:-SAMPLES_PER_SECOND]\n",
    "    d1 = pd.DataFrame(item[0::4]).to_pickle(to_path+name.split('.')[0]+'-1.pkl')\n",
    "    d2 = pd.DataFrame(item[1::4]).to_pickle(to_path+name.split('.')[0]+'-2.pkl')\n",
    "    d3 = pd.DataFrame(item[2::4]).to_pickle(to_path+name.split('.')[0]+'-3.pkl')\n",
    "    d4 = pd.DataFrame(item[3::4]).to_pickle(to_path+name.split('.')[0]+'-4.pkl')\n",
    "    f.close()"
   ]
  }
 ],
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