tools/1_extract_performance_and_other_features_from_logs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook extracts and exports various measures of task behaviour from the log data of the JUSThink Dialogue and Actions Corpus, at varying granularities of the activity (i.e. Corpus, Task, Attempt, and Turn Levels).\n",
    "\n",
    "In later notebooks, we focus one feature to estimate the task performance: (minimum) error.\n",
    "\n",
    "We define the granularities as follows:\n",
    "1. Corpus Level:  The whole collection of temporal team action data (logs) for all teams\n",
    "1. Task level: The complete time that a team participates in the activity\n",
    "2. Attempt level: The duration of the team constructing a solution and submitting it together\n",
    "3. Turn level: The duration where one of the participants is in figurative view, and the other is in abstract view\n",
    "\n",
    "Note that the levels Task, Attempt and Turn are time granularities for a team."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib as pl\n",
    "import networkx as nx\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from scipy import stats\n",
    "from scipy.stats import pearsonr\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from read_utils import read_tables, read_network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import read_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.family'] = \"serif\"\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.max_colwidth', 200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define paths."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inputs.\n",
    "data_dir = pl.Path('../data')\n",
    "network_file = data_dir.joinpath('metadata/network.json')\n",
    "logs_dir = data_dir.joinpath('logs')\n",
    "\n",
    "# Outputs.\n",
    "processed_data_dir = pl.Path('../processed_data')\n",
    "output_dir = processed_data_dir.joinpath('log_features')\n",
    "\n",
    "# Create output directories if they do not exist.\n",
    "for folder in [output_dir]:\n",
    "    if not folder.exists():\n",
    "        folder.mkdir(parents=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "code_folding": []
   },
   "source": [
    "## Load data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load logs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading log files from ../data/logs.\n",
      "log 39 files found.\n",
      "File justhink19_log_06 belongs to team  6\n",
      "File justhink19_log_07 belongs to team  7\n",
      "File justhink19_log_08 belongs to team  8\n",
      "File justhink19_log_09 belongs to team  9\n",
      "File justhink19_log_10 belongs to team 10\n",
      "File justhink19_log_11 belongs to team 11\n",
      "File justhink19_log_12 belongs to team 12\n",
      "File justhink19_log_14 belongs to team 14\n",
      "File justhink19_log_15 belongs to team 15\n",
      "File justhink19_log_16 belongs to team 16\n",
      "File justhink19_log_17 belongs to team 17\n",
      "File justhink19_log_18 belongs to team 18\n",
      "File justhink19_log_19 belongs to team 19\n",
      "File justhink19_log_20 belongs to team 20\n",
      "File justhink19_log_21 belongs to team 21\n",
      "File justhink19_log_22 belongs to team 22\n",
      "File justhink19_log_23 belongs to team 23\n",
      "File justhink19_log_25 belongs to team 25\n",
      "File justhink19_log_26 belongs to team 26\n",
      "File justhink19_log_27 belongs to team 27\n",
      "File justhink19_log_28 belongs to team 28\n",
      "File justhink19_log_29 belongs to team 29\n",
      "File justhink19_log_30 belongs to team 30\n",
      "File justhink19_log_31 belongs to team 31\n",
      "File justhink19_log_32 belongs to team 32\n",
      "File justhink19_log_33 belongs to team 33\n",
      "File justhink19_log_34 belongs to team 34\n",
      "File justhink19_log_35 belongs to team 35\n",
      "File justhink19_log_36 belongs to team 36\n",
      "File justhink19_log_37 belongs to team 37\n",
      "File justhink19_log_38 belongs to team 38\n",
      "File justhink19_log_39 belongs to team 39\n",
      "File justhink19_log_40 belongs to team 40\n",
      "File justhink19_log_41 belongs to team 41\n",
      "File justhink19_log_42 belongs to team 42\n",
      "File justhink19_log_44 belongs to team 44\n",
      "File justhink19_log_45 belongs to team 45\n",
      "File justhink19_log_46 belongs to team 46\n",
      "File justhink19_log_47 belongs to team 47\n",
      "Log of  6 contains  100 events\n",
      "Log of  7 contains  420 events\n",
      "Log of  8 contains  263 events\n",
      "Log of  9 contains  266 events\n",
      "Log of 10 contains  300 events\n",
      "Log of 11 contains  343 events\n",
      "Log of 12 contains  386 events\n",
      "Log of 14 contains  166 events\n",
      "Log of 15 contains  322 events\n",
      "Log of 16 contains  171 events\n",
      "Log of 17 contains  126 events\n",
      "Log of 18 contains  147 events\n",
      "Log of 19 contains  252 events\n",
      "Log of 20 contains  146 events\n",
      "Log of 21 contains  188 events\n",
      "Log of 22 contains  247 events\n",
      "Log of 23 contains  394 events\n",
      "Log of 25 contains  142 events\n",
      "Log of 26 contains  205 events\n",
      "Log of 27 contains  221 events\n",
      "Log of 28 contains  142 events\n",
      "Log of 29 contains  226 events\n",
      "Log of 30 contains  307 events\n",
      "Log of 31 contains  201 events\n",
      "Log of 32 contains  221 events\n",
      "Log of 33 contains  156 events\n",
      "Log of 34 contains  196 events\n",
      "Log of 35 contains  286 events\n",
      "Log of 36 contains  210 events\n",
      "Log of 37 contains  180 events\n",
      "Log of 38 contains  289 events\n",
      "Log of 39 contains  182 events\n",
      "Log of 40 contains  233 events\n",
      "Log of 41 contains  113 events\n",
      "Log of 42 contains  140 events\n",
      "Log of 44 contains  357 events\n",
      "Log of 45 contains  129 events\n",
      "Log of 46 contains  138 events\n",
      "Log of 47 contains  246 events\n"
     ]
    }
   ],
   "source": [
    "log_dfs = read_tables(logs_dir, form='log')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combine the log tables into a corpus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_df = pd.concat(log_dfs.values(), ignore_index=True)\n",
    "data_df.insert(2, 'corpus_no', 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network read from ../data/metadata/network.json: 10 nodes, 20 edges\n"
     ]
    }
   ],
   "source": [
    "network = read_network(network_file)\n",
    "print('Network read from {}: {} nodes, {} edges'.format(\n",
    "    network_file, network.number_of_nodes(), network.number_of_edges()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualize the network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 432x288 with 1 Axes>, <AxesSubplot:>)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_network(G, labels=None):\n",
    "    x_values = nx.get_node_attributes(G, 'x')\n",
    "    y_values = nx.get_node_attributes(G, 'y')\n",
    "\n",
    "    pos = {u: (x_values[u], y_values[u]) for u in G.nodes()}\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "\n",
    "    if labels is None:\n",
    "        labels = {u: '{}-{}'.format(u, d['label'].split()[-1])\n",
    "                  for u, d in G.nodes(data=True)}\n",
    "\n",
    "    nx.draw(G,\n",
    "            pos=pos,\n",
    "            with_labels=True,\n",
    "            labels=labels,\n",
    "            nodelist=[u for u in G.nodes()],\n",
    "            ax=ax)\n",
    "\n",
    "    labels = nx.get_edge_attributes(G, 'cost')\n",
    "    nx.draw_networkx_edge_labels(G, pos, edge_labels=labels)\n",
    "    ax.margins(0.1)\n",
    "\n",
    "    return fig, ax\n",
    "\n",
    "\n",
    "draw_network(network)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find the optimal solutions.\n",
    "i.e. minimum spanning trees."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Find a minimum spanning tree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MST found, 10 nodes, 9 edges, cost = 22\n"
     ]
    },
    {
     "data": {
      "image/png": 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eRsLSMciUKhSP2b3jgQGti2olr1mzhry8PHx8fLCxsWHgwIHFujMMgViRVsPk5eXRvXt3XnjhBWbMmKHvcIxWq1atWLFiBQEBoq5FVatt9UdES7eGqVOnDps3b2bVqlX8/PPP+g7HaIkuhuozIdAbtVLx9BNLoVYqGB/oXckRVS2RdGsgJycnfvzxR8aOHculS5f0HY5REkm3+tS2Gsci6dZQbdu25csvv+Tll18mLS1N3+EYHZF0q1d564+YqhSEBzczyoJPIunWYKNGjSI4OJihQ4dSUGB8a9T1SSyQqH7lqT8SEdbBKBMuiIG0Gk+r1dK7d2/at2/P7Nmz9R2O0bh16xatWrWq9tVKQpFH649ciLpGekoSY/r3rhE1jkXSrQWSk5Np27YtP/30E61atdJ3OEZBkiQsLCxITEzEyspK3+HUavv372fGjBkGN9+2okT3Qi3g4ODAX3/9JVaqlYNMJsPLy4tr14yvXmtN07BhwxpVwlQk3VrC1tZWV9mpNDk5Obz33ntkZmZWY1SGTQymGQZXV1fu3LlDTk6OvkOpFCLp1nIPepfUajU5OTmMHj1azxEZDpF0DYNCoaBBgwbExMToO5RKIZJuLSeTyXRbqyxevBitViuKvfyPSLqGoyZ1MYikWwtJklTso9rUqVN56623AMRuCY8QSddweHl51Zika7j1z4Qq89dff5GTk0Pnzp0BmDlzJs2aNePmzZvk5eURHh6u5wgNg5irazhES1cwasnJyYwdO5aMjAwAYmNj8fHxYfbs2WzcuBFPT089R2gYXF1duXfvnhhcNAANGzasMTNJREu3FgoKCuL48eMMHTqUvn37cv36dXr27ImPj4++QzMocrlc98v+uPqwQvUQLV3B6E2fPp0ePXpw9epVPD09GTZsmL5DMkiiX9cwPEi6NWEtl2jp1mKTJk3SfV9YWIhWq0WlUukxIsMjkq5hsLKywszMjDt37lCvXj19h/NMREtXAIqSbu/evTl69Ki+QzEoIukajprSxSCSrgCAUqlk8uTJDBo0iFu3buk7HIMhkq7hqCmDaSLpCjr9+vXjjTfeYMCAAeTm5uo7HIMgkq7hEC1doUaaNm0aLi4uTJgwoUYMWjwrNzc37ty5Q3b2k3ejFapeTVkgIZKuUIxcLmf16tUcO3aMb7/9Vt/h6J1SqcTd3b1G/LIbu5rS0hWzF4QSLC0t+fnnn+ncuTPNmzena9eu+g5JryZNmoSZmZm+w6j1akqfrihiLjzW7t27GTVqFCdOnMDNzU3f4eiNmEpnGAoKCjAzMyMtLQ1TU1N9h1NhontBeKzevXszefJkXn311VrdpykSrmFQKBS4u7sbfYlHkXSFJ3rvvfdo1KgRYWFhYmBN0LuaMJgmkq7wRDKZjFWrVnHhwgUWLlyo73CEWq4mDKaJpCs8lZmZGT/99BNffPEF+/bt03c4evP3lv6tW7c4fvy4nqKpnWrCYJpIukKZeHh48P333zN8+HBu3Lih73Cq1erVqzl06BAymQx4mHwLCgp4++23jb6P0ZiIlq5Qqzz//PNMmzaNV155pVbVmJ0zZw5jxoxh7ty5ZGZmIpPJyMvLw83NDWdnZy5duqTvEGsNkXSFWuett96iVatWjBkzptYMrPXt25fBgweTkZFBSEgIe/bsoU6dOgDY2Nhw7949PUdYezRs2JAbN24Y9XtPJF2hXGQyGcuWLePGjRt88cUX+g6nWlhZWWFpaclnn31GSEgIS5YsoX379nTr1o309HS6deum7xBrDUtLS8zNzUlKStJ3KBUmVqQJ5aZWq/nxxx9p164d/v7+9OnTB4C7mlw2n4rn8u100nPysVIraepkxaA2rthZmOg56opr06YNBw8eBCA0NJTu3btz8+ZNsrOz6dSpE2q1Ws8R1i4PBtOcnJz0HUqFiBVpQoX98ccf9O/fn//7+Td+vZbLwahkAHLzC3XnqJVyJCCwiQPju3nj72atn2CfQXZ2NmlpaTg7O+s7FAF47bXX6NOnD6GhofoOpUJE0hWeSdiXa9lzxwKZsg5PeiPJZKBWKggPbsrwDh7VFZ5QA3388ccolUqmT5+u71AqRPTpChW27lgMhzPs4SkJF0CSIFtbwKwdkaw7FlMd4VW6mJiYWjVrw1AZ+wwGkXSFYoYPH46zszNWVlY0btyYlStXlnreyk3bCO3YkCtz+nNz/kDiF48g7fD6pz5/traQWTsucy4+rZIjr3pjx47l8OHD+g6j1hNJV6hR/vnPfxITE0N6ejq//vorH330EadOnSpx3s9nElBY2tJgymYaTNlMveFz0ZzbQ1bU0/dYy8kvYOmB4rsxFBQUVNprqCpiFwnDYOyr0kTSFYrx9fXFxKRopoFMJkMmk5V4g9/V5HI2Lq3YYyprJ0zqN0N7N073mDYljqSNHxG3cAgJy8eRGVnUSpQk+P7LfzL6H2EEBwdjbm7O/v378fDwYN68efj5+VG3bl1CQkLIycmp2hdcDt7e3ly9elXfYdR6Li4upKamkpWVpe9QKkQkXaGE8ePHY2ZmRtOmTXF2diY4OLjY8c2n4ktco01NIDf+EnVcmgBQmJdD0saPMffphuvb63F46QNS93xL3t2bums2bvye8PBwMjIy6NKlCwCbNm1i165d3Lhxg3PnzrF69eqqe6HlJFq6hkGhUODh4WG0y69F0hVKWLp0KRkZGRw+fJj+/fvrWr4PXL6djragkIKMVG4uCOHmV4O4tXwcdVyaoHbzASD72gmUdR2x8OuJTK6gjpMXZk06kXX5DwAKCiU8W3ejc+fOyOVy3VzXt99+GxcXF2xtbXnxxRc5c+ZMtb72J2nUqJFIugbCmPt1xeIIoVQKhYIuXbqwbt06vv32W3bu3KkbRGoz7ENAicLSFtcJ3wFQmJNJyp6l3N22AIeXPyD//h1yb0Vxc0HIwyctLMC8+fO6f6rqOpS476MT3s3MzAxqO/iGDRsSGxtLfn4+SqX41dEnY+7XFe8c4Yny8/O5du0aO3fu1D32bsRprvyyq9h5crU55j6B3P2laGmw0soBdYPm1Bvy+WOfW60yrrefWq3G0dGRuLg4PD099R1OrWbMLV3RvSDo3Llzh40bN6LRaCgoKGD37t18//339OjRo9h5TZ2sUCmKv3UK87LJijyEyr4BAKZebdGmJqC58DtSQT5SQT65iVG6gTaFXIadRZ3qeWGVSPTrGgZj3kHCuJoaQpWSyWR8++23vPHGGxQWFuLu7s7ChQt56aWXip03sI0rs1ZS1Kc7f2DRtQoVJvWbYP/SewDITcyoF/IZ935fyb3fVoIkoXL0xLbHP3TP08zJsvpeXCV5kHR79uyp71BqNWNu6YplwEKFhK09yd7IJCr07pEKqZN8mU1v9aRly5aVHVqVmjt3LklJScyfP1/fodRqGo0GR0dHXX1jYyK6F4QKmRDojVqpqNC1pnWUhLZ2pFevXrz//vtGtbRWdC8YBgsLCywtLUlMTNR3KOWm96R7V5PLsoPXeDfiNGO++5N3I06z7OA1UjS5+g5NeAJ/N2vCg5tiqirfW8hUJSc8uBkfTxjJhQsXSExMxNfXlx07dlRRpJVLLJAwHMbaxaC37oWzcWksORBdY8sB1hbrjsUwa8dlcvILntjV8KQqY3v37uXNN9+kdevWfP311wZdQjEzMxN7e3s0Gg0KRcVa+kLlGD58OL169WLEiBH6DqVc9NLSXXcshiErjrE3Monc/MJiCRcg53+P7bmUxJAVx4y2KlVtMLyDBxFhHejtUw8TpRy1svhbSq2UY6KU09unHhFhHUot69izZ0/Onz9Po0aN8PPz49tvv6WwsLDEeYbA3NwcW1tbEhIS9B1KrSdaumVU1DKKJFtb9l8qU5WcZrd2Y5Zzl3Xr1lVhdEUOHDjA8OHDiY8vudxVeLwUTS6b/4rncmIG6TlarNQqmjpbMrB12XeOuHjxImFhYRQWFrJ8+XJatGhRxVGXX7du3Zg+fTrdu3fXdyi12urVq/n9999Zs2aNvkMpl3K3dD08PHSjhg+sXLmSwMDAp157Ni6NWTsulyvhQlE5wENX73IvK6+84QJF/3MerO0Xqo6dhQnjunqxIKQlq0a2ZUFIS8Z19SrXVj2+vr4cPnyY0aNH0717d6ZOnWpwhU3EYJphMNZVaRXqXigoKODrr78u93VLDkSTk1+xEn75hYVEJWVU6FrBuMjlcsLCwjh//jyxsbG0aNGC3bt36zssHZF0DYOxdi9UKOm+//77zJs3j7S0tFKPX758mZ49e2Jra0uTJk3YtGkTdzVFe2glrptKxtmHv0Cac/u4ve4D3b/zkmN15QDjvhnO/SObig5IcPuehpDXhmFpaYmvry8nT57UXTdnzhy8vLywtLTEx8eHn376CYDIyEjeeOMNjh49ioWFBdbW1gDk5uby3nvv0aBBA+rVq8cbb7xBdnZ2RX4cQhVxcnLi+++/Z/Hixbz55pu89tprBrELrEi6hsHFxYWsrCyj+72tUNINCAggMDCQefPmlTiWmZlJz549ee2113TLSsePH8+iLfuf+ryFuVnc2fgRpp6tcZ24hvrjlqP28H/43FHHcWjZnbS0NF566SUmTpyoO+bl5cXhw4e5f/8+06dPZ/jw4SQmJtKsWTOWLVtGx44d0Wg0uj8UU6dOJSoqijNnzhAdHU1CQgIzZ86syI9DqGJ9+vThwoULuLm50aJFC1asWPHEgbbc3KqdbiiSrmGQy+WkpqZSp45xLSev8OyFmTNnsmjRIpKTk4s9vm3bNjw8PBg9ejRKpZJWrVoxYMAAdm/7ucQshb/LvvYncnMbrNr3R6asg9zEDJP/1WcFMHH1QeXeBoVCQWhoKGfPntUdGzRoEC4uLsjlckJCQmjUqBEnTpwo9T6SJLF8+XIWLFiAra0tlpaWTJs2jY0bN1b0xyFUMTMzM7744gv27dvHqlWrOHbsGI8bA548eTKTJ09+7PFn5eXlRXR0tMHOsKhNFAqF0U3de2LS7dOnDxYWFlhYWLB+ffH9r5o3b06/fv2YM2dOscdjY2M5fvw41tbWuq/169eTllI8OZcmPz0Zlc3j97JXWNiQnqMFin4Jc3JyyM/PB2DNmjW0bNlSd88LFy5w9+7dUp8nOTmZrKws2rRpozs/KCioxB8QwfD4+fnx3//+l7Zt2z52+Wd4eDgajYa2bdty4cKFSo/BysrKaFdDCfr3xKS7c+dONBoNGo2GYcOGlTj+6aefsmLFimJzFt3c3OjWrRtpaWm6L41GQ9C4j4puWEeNpH348a8g857ue6WVA/lpT+6zs1KrSjwWGxvL2LFjWbx4MSkpKaSlpdG8eXNdS+fvv5z29vaYmppy8eJFXYz3799Ho9E88d6CYVAoFKhUJd8HD7i4uLB8+XK6devGkSNHqiQGUdBcqKhnWhzh7e1NSEgI33zzje6xfv36ERUVxdq1a9FqtWi1Wv7880/q5t7BRClH5diQrCtHKNTmoL13C825PbprTb3aUqBJJf3PX5DytRTmZpF768rDYGUymjqXrEz1oOiFg0NRUez//Oc/xVo49erVIz4+nry8oilncrmcsWPHMmnSJO7cuQNAQkKCQY2QCxXzww8/0K9fP06cOMGOHTuws7OrkvuIfl2hop55Rdonn3xSbM6upaUle/bsYePGjbi4uODk5MSHH35IoLcNAFZtX0amUBG/KJSUbQsw9wl8GIyJGY5DPiM7+jjxi4aTsDyMnNhzxe43sLVriRh8fHyYMmUKHTt2pF69epw/f57OnTvrjnfv3h1fX1+cnJywt7cH4IsvvsDb25sOHTpgZWXFCy+8wJUrV0o8t2D4Hu1bHTRoELa2tsycOZNJkyYRFBRUJfcUSdew/L3/PikpiXPnzj3mbP2q1hVpz1IOUCaD3j71WDY8oPIDE4zajRs3qF+/vm4U++jRoyxatIgNGzZU2T03btzIli1b+OGHH6rsHsLTrVmzBm9vbzp16gQUJV+ZTEZsbCxDhgxh06ZNuLm56TnK4qq19sKzlANUKxWMD/Su5IgEYydJEtu3bycwMJDIyEgADh8+TLNmzXQt4KpoV4iWrmH47LPPGDVqFF9//TW5ubnIZDLy8vJwd3fHzs7OID+9VuvOEQ/KAVak9kJ4cFP8XK2rLjjBKMlkMiZOnIi5uTmDBg2iYcOGqNVqJk2ahFwuJzc3l61bt2Jvb1+mpepl9WDa2IOWlaAfffr0wdLSkoSEBIYMGcKUKVN0S/5tbW0fO4NJn6p9u54HVaaetRygIDxq9OjRDBw4kPPnz9OqVStMTU0BMDExwdTUlBEjRtCjRw/mzZtXKYNrNjY2mJiYcOfOHerVq/fMzydUjIWFBY6OjrzzzjssW7aM2bNno9FokMlk2NraFhvbMRR6q6d7Lj6NpQei2X8lGRlF5RwfkLS5qE1Neb6JA+MDvUULV3hmGRkZfPzxx2zcuJG5c+cSGhr6zC3UDh06MG/ePFFMSY9++OEHTp8+zb/+9S8Arl+/zrVr19BqtXTt2hULCws9R1iS3vdIK60c4L7N3zFzdDCvBovN/4TKdfLkScLCwrCxsWHZsmU0atSows8VGhpKjx49GDVqVOUFKJSLRqMhIyPDoAvf/53edwN+UA7wUZ9e/oU/ftslkq5Q6QICAjhx4gSLFi2iY8eOvPvuu3zwwQcVWr8vBtP0z8LCArVajUajMchWbWn0vkdaafr06cOuXbv0HYZQQymVSiZNmsSpU6c4fvw4LVu25PDhw+V+HpF0DUN6ejqDBg3SdxhlZpBJNyAggDt37nDz5k19hyLUYO7u7vz666989tlnDB06lLFjx5Kamlrm60XSNQzW1tYcOHDAaHaVNsikK5fL6dWrl2jtClVOJpMxYMAALl68iImJCb6+vmzYsKFMc3ttnd2Js2gidrLWM7lcjqenJzdu3NB3KGWi94G0x1m3bh1btmzRFSMXhOpw/PhxwsLCcHJyYunSpXh5eZU459GdrHNyspEpH25HJHay1o9+/foxduxYXn75ZX2H8lQG2dIF6NWrF/v379cVqRGE6tC+fXtOnjzJCy+8QPv27Zk9ezZarVZ3/O87WT+acEHsZK0vXl5eRrN1j8EmXUdHRxo1alRlpfkE4XFUKhXvv/8+f/75J4cOHaJ169YcOXLkkZ2sn7yoB0CSIFtbwKwdkSLxVgNj2i/NYJMuQFBQkOjXFZ7Z4sWLCQgIwMTE5Klzaj08PNi3bx8Anp6e7Nixg48//phB497jk5/PVmgn61k7LnMuPq2C0QtlIZJuJenTpw87d+7UdxiCkXNxceGjjz5izJgx5b5WJpMxePBgek2aT2EFf11y8gtYeuDpsxwe7IIilJ9IupWkXbt2xMXFcevWLX2HIhix/v3788orr1S45sJdTS4/fv0J9w4/3LIqJ/Yc8UtGApAZeYib8wfqvmK/fIXb66cCIOVrSf1tFasmBOPoWHzX6QMHDuDq6soXX3yBk5MTo0ePZsaMGQwePJgRI0aUuuu1UDpPT09iYmKMYt86g066SqWSnj17ii4GQa82n4p/4nHzZl1pMGUzDaZsxnXiGpTWTpj7dAPg3oHVaFMT8Bi7mPA1e0rsOn379m1SU1OJjY1l+fLlAPz6668MGTKk1F2vhdKZmZlhY2NjFA00g066IPp1Bf27fDudgsKnz6yUpELu/vol6gYtsGzVB0mS0JzdhU2PsWhV5sTcl0rsOi2Xy/n000911dAAunTpQnBwcKm7XguPZyxdDEaRdPft2yf6u4RK96Tdrh+VnlO2917awTUU5mVj+8I4AAqz7iNpc0lc/S43F4SwdPRzJXaddnBwQK1WF3seJ6eHO2L/fddr4fGMJenqveDN0zg7O9OgQQOOHz9ukLUxBeNV1kFaK7USWR01kjZH99iju1gDZF46SOalQziPWoBMUfRrJTezQqY0weUfS1Ba2vNqy/osCGlZ7DpRAL3yGEvSNfiWLohZDMKzyc/PJycnh4KCAgoKCp7actRqteTk5Oi+GtmbYebkRfa1UxRkZ1CguUf6yV915+fdvkbq3n/jOOAjFGZ1dY/LZHIs/Htx77eVKHPTaepsKXadrkJeXl5cu3ZN32E8lVEkXdGvKzyLzz//HFNTU+bMmcO6deswNTXl888/f+z5wcHBmJqa6r6u7f4PVn7dqePoScK3Y0iK+Bjzps/pzs+6eozCHA23132gm8GQtGk6ADbPj0Zp40zs/01iUh8/set0FTKWlq7B1l54lFarxcHBgStXroitUQS9eKadrIHGZlnErPsIS0tL3nvvPQYOHIhSafC9e0YlMTGRli1bkpSUpO9QnsgoWroqlYru3buzZ88efYci1FLPtJO1SsGXo3sSGRnJ9OnT+fbbb/H29mbhwoVkZGRUcqS1l5OTExkZGWg0Gn2H8kRGkXRB9OsK+vVgJ2tTVfl+ZR7dyVoul/Piiy9y8OBBNm3axNGjR/Hw8ODDDz8kISGhiiKvPWQymVGUeDSapBsUFMSePXsoKCjQdyhCLTW8gwfhwc0wVSl42qQDmQxMVQrCg5uVupN1u3btiIiI4OTJk+Tm5tKiRQtGjhzJuXPnqib4WsIYBtOMJum6ubnh5OQklkQKejW8gwcRYR3o7VMPuVSAguLLTtVKOSZKOb196hER1qHUhPsoT09PFi5cyLVr12jWrBlBQUH06tWLPXv2lKmQulCcMQymGcVA2gPvv/8+5ubmzJgxQ9+hCALPB71Iy/5vQN36up2smzpbMrC1K3YWJk9/glLk5uayceNG5s2bh0wm47333mPIkCEV2jizNvrmm2+Iiopi8eLF+g7lsYwq6f7222+Eh4dz7NgxfYci1HKSJGFvb8+FCxeqZPtvSZLYs2cP8+bNIzIykrfeeotx48ZhbW1d6feqSbZt28bSpUvZsWOHvkN5LKPpXoCiNemRkZHcvXtX36EItVx8fDwqlapKEi4UDQr17t2bvXv3sm3bNi5evEjDhg2ZNGkSMTExVXLPmqBhw4aiT7cymZiY0K1bN/bu3avvUIRa7vTp07Rs2bJa7tWyZUvWrFnDuXPnUKlUtGnThiFDhojxjVJ4enoSGxtr0APuRpV0QUwdEwzDmTNnaNWqVbXe09XVlblz53Ljxg3atWvHgAEDCAwMZNu2bUZRR7Y6mJqaYmdnZ9AlHo0u6QYFBbF7927xJhP06vTp09WedB+wsrJi8uTJREdHM27cOKZPn46vry8rVqwgJyfn6U9Qwxn6DAajS7qenp7Y2Nhw+vRpfYdSIXc1uSw7eI13I04z5rs/eTfiNMsOXiNFk6vv0IRyOHPmTLV1LzyOSqVi6NChnDx5kqVLl/LLL7/g4eHBZ599VqvHPQw96Rrl4u8HBXDatGmj71DK7GxcGksORHMwqqiWam7+w5a6WnmbBfuiCGziwPhu3vi7WespSqEs7t27x927d/H29tZ3KEDRoNvzzz/P888/z6VLl/jqq69o3LgxQ4cOZdKkSQYTZ3Ux9AUSRtfSBePr1113LIYhK46xNzKJ3PzCYgkXIOd/j+25lMSQFcfElt0G7uzZs/j5+SGXG96vj4+PDytXruTSpUvY2trSsWNH+vfvz5EjR/QdWrUx9Jau4b1ryqBr166cPXuWe/fuPf1kPVt3LIZZOyLJ1hY8tUKVJEG2toBZOyJF4jVg+uzPLSsnJyc+++wzYmJi6NGjB6GhoXTs2JEtW7YY9Mh+ZRBJtwqYmpry3HPPsW/fPn2H8kRn49KYteMy2dqyDfrdXj+VjLO7ydYWMmvHZc7Fpz32XA8PD4N//TWVIfTnlpW5uTkTJkwgKiqK999/n3nz5tG4cWOWLFlCZmbmE69dtWqVbrNMYyKSbhWpaGHzwMBA1Gq1bm+sJk2aPPZcmUxGdHR0mZ63tCS45EA0OfkVa1Xk5Bew9EDZ7i1UL2No6f6dQqGgf//+HD16lLVr1/Lbb7/RoUMHtFrtY6/x9PRk+/bttGjRgi1btlRjtM+mXr16ZGZmGmzZTKNNun369GHXrl0VKgqyePFiNBoNGo2myqr439XkcjAquUxFryVJQpIK//YY7L+SLGY1GJicnByuXr2Kr6+vvkOpsE6dOvHjjz9y6NChJ57XvXt3fvnlF+bPn8/WrVurKbpnJ5PJDLq1a7RJ19vbG7Vazfnz56vlfjNmzGDw4MGMGDECS0tLfH19dSuCQkNDuXnzJi+++CIWFhbMnTuXzafiyY6/zO2173FzQQi3Vk0kJ/Zh2b7b66dy7+Aabq99n7j5A8hPu13sftp7icSvnYp7fSfs7e0ZNmwYaWlppcYWGRmJp6cn33//PVC0/rxly5ZYW1vTqVOnYuUCPTw8mDdvHn5+ftStW5eQkBAxt7McLl68SKNGjUrs4GuMbGxsUKlUjz2+ePFikpOTOXbsGBqNhtxc42kAiKRbBWQyWYVnMfzzn//E3t6ezp07c+DAgTJf9+uvvzJkyBDS0tJ46aWXmDhxIgBr166lQYMGbN26FY1GwwcffMDJS9EkbJxO3U4huL37PTbdXyf5p9kUZN3XPV/mxf3YBk3EbfIPKK0c/3Y3CYsOgxi9ZDeRkZHExcWVWl3tr7/+onfv3ixatIihQ4dy+vRpxowZw7///W9SUlIYN24cL730UrFfmE2bNrFr1y5u3LjBuXPnWL16dTl+erVby5YtjWrmTEVptVqioqJo0qQJ8fHxTJkyBROTilVO0weRdKvIyJEjyz2g8cUXX3D9+nUSEhIICwvjxRdfLPOcvi5duhAcHIxCoSA0NJSzZ88+9twz+7di6hWAqVdbZDI5pp6tqOPsTfa1h+vlLZr3oI6DOzK5Qrdt9wMqGxdMPVuRVSDDwcGByZMnc/DgwWLnHD58mJdeeok1a9bQr18/AJYvX864ceNo3749CoWCkSNHYmJiUqwy29tvv42Liwu2tra8+OKLnDlzpkyvXyjqG61fv76+w6gyD/44q1QqvvnmG6ZOnYqvry8dO3bUc2TlY8hJ1ygXRzwQEBBQ7j7d9u3b674fOXIk33//PTt27GDZsmXExsYCsHPnTp577rkS1zo5Oem+NzMz023lXdoGg3lpd8i8/AdZ0ScePliYj7qBn+6fCiv7x8ZZkHmP1H3Lifj3ZX54K4fCwkJsbGyKnbNs2TK6detGYGCg7rHY2Fi+++47Fi1a9DCWvLxia9H//joMeZ26UH0kSeLIkSO4u7vTsGFDoOgT5YP5yHl5edy7d88oNof18vIy2PKORt3SffQN8SzPIUkSFy9e1A2ulZZwy/I8j2ro0QCrFt1pMCni4deULdTtOOjRix77fPcOrkEukzFzzU7S09NZt25diT8wy5Yt4+bNm0yaNEn3mJubG+Hh4aSlpem+srKyGDp0aLlfk1D7REZGEhQUxMSJE5k3bx6///47jRs3BiApKYlmzZoRGhpq8J+ODLnEo1En3fJKS0tj9+7duhbq+vXrOXToEEFBQc/83PXq1Sv2cebTyW+QefUE2ddPIRUWIOXnkRN7jvz0sq2Jl/KykZR1WPHRG0yZMoWZM2eWOMfS0pJdu3Zx6NAhpk6dCsDYsWNZtmwZx48fR5IkMjMz2b59u8FOnxEMh0wmY/z48Zw6dQpnZ2dSUlKYOXMmvXr1Aor+oF+/fp0WLVrQr18/evbsye7duw1yWyEPDw9u3rxpkAtBalXS1Wq1fPTRRzg4OGBvb8+iRYv4+eefdX/Jn8U///lPPv/8c6ytrZk3bx7+Tb3p995X3D/6A/HfDCN+ySjST/wIUtkWSlh3GYppejyxURdZs2YN0dHR3Llzh3/961/F/oJbW1uzd+9edu7cyccff0xAQAArVqxg4sSJ2NjY4O3tLQbKKuj06dN88803bN68GSh6/1y/fr3Gz/awtLQkPDyc2bNn07Zt22Kf4qytrfnggw+4fv06oaGhfPDBB/j5+bF69WqDmt2gVquxt7c3yF2WjWq7nrKSJInY2FhOnTrFgAED9BbH2bg0hqw4Rra2/H9tTVUKIsI64OdqDUBBQQF//PEHERERbNmyBTc3N0JCQhg8eDDu7u6VHLmQnJzMa6+9pmvd9ejRg5MnT+Lp6UmdOnUIDw+nbt26+g5T7yRJYt++fcybN48LFy7othX6+/iDPnTt2pWZM2cWG/MwBEbf0i2trq5MJkOpVDJnzhy9loD0d7MmPLgppqry/ZhNVXLCg5vqEi4UjZp369aNpUuXkpCQwBdffMHVq1dp06YNHTp0YMGCBcTHx1fyK6i9Tpw4gYWFBf/3f//H1KlT2bBhA3PmzGHo0KEkJSWxZMkSfYdoEGQyma6bYefOnURGRuLl5cW7776r922FvLy8DHIGg9En3VmzZvHmm28WG4HPycnB1dWVPn366D4a6svwDh6EBzfDVKV40rgZUDSuZqpSEB7c7IlbdyuVSnr06MHy5ctJTExkxowZnDt3Dj8/P5577jkWL17M7du3H3u98HTHjh3Dw8MDgOvXrxMYGEizZs1o3749L7/8MhcvXtRvgAbIz8+P7777jvPnz6NWqwkICCAkJIQTJ048/eIqYKiDaUafdFNTU9myZQuTJ0/mnXfe4fjx47rVQtbW1gbRkT68gwcRYR3o7VMPE6UctbL4j12tlGOilNPbpx4RYR2emHD/TqVSERQUxH/+8x8SExP58MMPOX78OM2aNaN79+4sW7aM5OTkSn5FNV/Pnj0JDQ0FYPz48Xz11Ve6Y/v27aNt27b6Cs3g1a9fnzlz5nDjxg06duzI4MGD6dq1K7/++mu17vhiqHN1jb5P96+//iI8PJyffvqJhQsX8vvvv1NQUICNjQ2xsbEsX77coIqTpGhy2fxXPJcTM0jP0WKlVtHU2ZKBrV2xs6i8FT/Z2dns2rWLiIgIdu7cSfv27QkJCeHVV1/F1ta20u5T2+Tn5/P2228zatQo2rVrp+9wjEJ+fj5btmzhyy+/JCMjgylTphAaGoqpqWmV3vfo0aO8++67HD9+vErvU15Gn3QBGjVqxOnTp7GwsCAlJYX9+/djYWGBv79/lW2RbUweTBvbtGkTe/fupXPnzoSEhPDKK6+IwaBy0mq15ObmYm5uXmJutvBkkiRx6NAh5s2bx4kTJxg/fjzjx4/HwcGhSu6XlJRE8+bNDe6TXo1IuvPmzSMoKIjmzZvrOxSDl5GRwdatW4mIiGD//v08//zzhISE8OKLL2Jpaanv8AxWTk4OcrmcOnXq6DuUGiEyMpIFCxbwww8/MGTIECZNmlQpUzcfJUkSlpaW3Lp1Cysrq0p97mdh9H26UFRLwNfXl5ycHLFL8FNYWlry2muv8csvv3Dz5k369+/P+vXrcXV1ZeDAgfzwww9kZWXpO0yD8+KLL5KUlKTvMGqMZs2asXz5ci5fvoyDgwNdunThlVde4Y8//qi0xRaGWuKxRiTdOnXqIJPJ2Lp1Kxs2bNB3OEbD2tqakSNHsn37dm7cuEGfPn1YsWIFzs7ODBkyhJ9++qnMCwGetguBMcvIyODIkSOiq6oK1KtXj5kzZxITE0Pv3r0ZPXo0HTt2ZPPmzZUyCC6SbhWTyWQi6VaQra0tr7/+Onv27CE6OprAwEAWLVqEs7MzoaGhbNu2jby8vFKvLSws5KeffsLPz4+hQ4c+tTi2sTl37hy+vr6lFjYSKoeZmRlvvvkmly9f5sMPP2ThwoU0atSIRYsWodFoKvScdzW55DcKZNnZbMZ89yfvRpxm2cFret8YoEb06T6QlpZGgwYNSEpKqvKR0dri9u3bbN68mYiICC5evMj58+dLlDbMy8vjzp07ZGdnc/ToUX744QcWLFhQY7b+XrJkCWfPnjXK/cKM2dGjR5k/fz4HDx4kLCyMiRMnlunTxtm4NJYciOZgVDL5+fkUPNK2VCvlSEBgEwfGd/PG38266l7AY9Solq61tTX+/v4l6s4KFefk5MTEiRM5fPgwFy9eLLWsX506dXB1daVRo0aMGDGCxMREXZnMmsAY90SrCR50Mxw7doz79+/j6+vLmDFjnrgwZd2xGIasOMbeyCRy8wuLJVyAnPxCcvML2XMpiSErjull1+0alXSh4htWCk/n7Oxc6kfs/Px83fcnTpzA2dm5WM1eY2dMu//WRF5eXixevJirV6/i5eXFCy+8QHBwML///nuxQbd1x2KYtSOSbG3BU/cmlCTI1hYwa0dktSfeGtW9AEWLJYYOHVplG04KxRUWFupqGn/11Vf89ttvdO7cmWnTpuk5ssqh1WqpW7cuycnJmJub6zucGi0yMpIJEyZw6tQpHBwc+PLLL3n11VdLnPdgmX9qaioymQy1Wo13U1+SnNpj0qIXMll5a50ULy5V1WpcS7dly5akpaUZ3IhlTSWXyzl58iS9e/fm+PHjzJgxQ1fbF4qS1smTJw2y5mpZXL58mQYNGoiEW8Xy8/N5+eWX6devH6mpqSxfvpzhw4cTFRVV4ly1Wo2FhQW7du1i69attGnThlsWjbj7302k7Pim3PfOyS9g6YHoyngZZVLjkq5cLhddDNWkoKCAd999l/79+zN8+HAiIiJo27Ztsd08oqOjee211/Dy8mLq1KmcPn3aqBKw6M+tHpcvX+bWrVtMmjQJhUJB9+7d6dy5M2vXrn3sNXK5nODgYH7csRfrLq/h8PKHZJ7/jbzkGACyov/k1v+9zc2vBhG/ZBRph9frrk3aNJ30U0XbyksS7L+STPMWfvz4448AHDlyhLZt21K3bl3atm3LkSNHdNeuXr2ahg0bYmlpiaenJ+vXP3zesqhxSRdEv251atq0KQ0bNmT58uVMnDiRS5cuFTverFkzrly5wpYtW5DJZAwYMIAmTZrw8ccfc/78eYNPwGfOnBFJV08kSeLChQtPPW/zqXjkcjkmLk1QWNmTG1f0HpSrTLDvNxm3SRE4DppOxumdZEUdBcC8WVeyLj2c2piXfJPrMTH07duX1NRU+vbty9tvv01KSgqTJ0+mb9++pKSkkJmZydtvv83OnTt187fL299fI5Nur169OHDggEFVsq+JFAoFb7zxBgcOHGDDhg00aNCAy5cvl0ikMpmMVq1aMXv2bK5du8b69evJzs6mb9+++Pr68umnn3L58mU9vYonO336tBhEqwZNmjTB0dGRL7/8Eq1Wy549ezh48GCZVkdevp1Obn7RSlSFhS2FOUVbU6nd/ajj6IFMJqeOoyfmPl3JuVmUxM0adyTvznXy798BIPXc73gGdMfExITt27fTqFEjQkNDUSqVDB06lKZNm7J1a1HLWC6Xc+HCBbKzs3F2dsbX17dcr7VGJl07Ozt8fHz4448/9B1KreHm5sYHH3xA//79n1gIRiaT0bZtW+bNm0dMTAwrV67k3r179OjRA39/f/71r38RHV19/WtPIkmSmLlQTVQqFT///DPbt2/HycmJ+fPnM3jwYF1dbAsLCywsLEr9KJ+e83D2TEFGCnJ1UQ2R3FtXuL3hn8R9/Ro3Fwwm4/ROCrPTAZCbmGHq1ZbMyKLWbtalgzRo1xOAW7duldiNxd3dnYSEBMzNzYmIiGDZsmU4OzvTt2/fcjcYamTSBejTpw87d+7UdxjCE8jlcjp16sTChQuJi4tj0aJFJCQk0LlzZ9q0acPcuXP1uvtAbGwsZmZmODo66i2G2sTPz4+DBw+SkpLC7t27uX79Ou3atWPnzp26nbqHDRtW4jorddE0xtzEKAoyUjBx9QHg7q9fYubdHtcJq2kwaROWrfoADz+FmTfrSualg+QmRCIVaGnSsiMALi4uJeaZ37x5U7coqHfv3uzdu5fExESaNm3K2LFjy/U6a2zSFf26xkUul9O1a1eWLFlCQkICc+fOJTo6mrZt2+ptOyLRn1u9zp07R05ODllZWcybN4/ExERGjRr11OvcLWVob/zJ3V/mYu4bSB1HDwAK87KRm1oiU9Yh99YVMi8VXzRl6tWWgvt3SDu8HiufrjSrX1TmNDg4mKioKDZs2EB+fj4RERFcunSJfv36kZSUxC+//EJmZiYmJiZYWFgUGzguixqbdAMCAkhKSiIuLk7foQjl9Oh2RLdu3eLTTz/l/Pnz+Pv706VLFxYtWlQt2xGJ/tzqtXbtWpydnXF0dOS3335j7969mJg8vrD/g3Kk04d2I/WPCKzavoJd33d1x217vUna4XXc/GoQ9/+7EfOmXYpdL1OqMG3SiZyYM1g2D2Rga1egqHty27ZtzJ8/Hzs7O+bOncu2bduwt7ensLCQr776ChcXF2xtbTl48CDffvttuV5njVsc8ahhw4YRGBhY7ua/YJjy8vLYs2cPERERbNu2jZYtWxISEsKAAQMqpRD2XU0um0/Fc/l2Ouk5+fx17L909vVg5qg+lbqrh1D5wtaeZG9k0lNXopVGJoPePvVYNjyg8gMr7X41OemuXbuWn376STf3Tqg5cnJyim1H1K5dOwYPHkz//v3LvR3RowVSAN1IOEAdhQyZTKbXAinC052NS2PIimNka8tfDrK6V6TV6KR7584dGjduTHJyMiqVSt/hCFUkKytLtx3Rnj17yrUdUdF6/cvk5D95vb5MBmqlgvDgpuXaOFSoPg9rL5R9IwNTlfypu29Xthrbpwvg6OiIt7d3sdUkQs1jZmbGoEGD+OGHH0hISCA0NJSffvqJBg0a8PLLL7NhwwYyMjJKXGcsBVKEshnewYPw4GaYqhQ8bfs6mayohVvdCRdqeNKFoqljYhZDzXD16lXUajXDhw8v9fi//vUvnJycGDt2LPv27aOgoIBdu3YxbNgwHB0dGTBgAJs2bSIzM5OzcWnM2nG5XK0igGxtIbN2XOZcfFq5458xY0aJ2AMDA1m5cmW5n0so3fAOHkSEdaC3Tz1MlHLUyuIpTq2UY6KU09unHhFhHfTyqaXGJ92goCAxX7eGmDBhAm3btn3s8WnTpunmcz74ev/99/Hx8SEqKoq+ffuyatUq6tevz6gvvydHm//Y5wKQCkvvH6zuAilC+fi5WrNseABHPuzOpJ6NebVlfXo0deTVlvWZ1LMxRz7szrLhAdXWh1uCVMNptVrJxsZGSkhI0HcowjP4/vvvpUGDBknTp0+Xhg0bVqZrtm/fLllaWkqXLl3SPZaQkCD1DAqW5KZWkqJuPcnmhTDJfeo2yX3qNqlu56GSWZNOkrlvoCSrYyrZ9nlLMnFrLll1CpFM6jeVZCq1ZOrVVnJ9Z4Nk6RsoWVhaSgEBAdKNGzd0z//2229Lrq6ukqWlpdS6dWvp0KFDkiRJ0s6dOyWVSiUplUrJ3Nxc8vPzk6ZNmybJ5XLJxMREMjc3lyZMmFCpPzPBMNX4lq5SqeSFF15g9+7d+g5FqKD09HQ++eQTvvrqqzJfExMTQ2hoKCtWrKBZs2ZAUe3fF198ERPnRni9u5Z6Q2eR8ecvZF8/pbsu6+pxzJp0xm1SBOY+gUWPXTqEXb8puE74jvy029xe8x51/Xvyxc9/0qxZMz799FPd9W3btuXMmTOkpqby2muvMWjQIHJycggKCmLatGmEhISg0Wg4e/Yss2bN4rnnnmPx4sVoNBoWL15cOT8wwaDV+KQLol/X2H388ce8/vrruLq6lun83NxcBg4cyLBhwwgJCdE9/ueff5KcnIxX75HkSQpU1k5YtOxNZuRh3TkmLk0xa9wRmUyOXFU0N9fC7wVUNs7I1eaoG7ZBaeOMooE/V5OzGTRoEKdPn9ZdP3z4cOzs7FAqlUyZMoXc3FxRUF8oplZsb9q7d2+mTJlCfn6+2NHVyJw5c4Z9+/YVS2wP+Pr66tbI79y5k+eeew6Ad955B5VKxfz584udf+XKFW7dusWSUV0okP43vC0V6tbqAyis7EvcR25urftepjJBYVb07/QcLaZ2psV2q503bx6rVq3i1q1byGQy0tPTuXv3boVeu1Az1YoM5OLiQoMGDThx4gSdOnXSdzhCORw4cICYmBgaNGgAgEajoaCggEuXLpW6QeHatWvZsmULP//8Mzt27ODs2bOcO3eOc+fOERsbi1KpxH/clySZupe4FnhihbS/s1IXn/t9+PBh5s6dy2+//Yavry9yuRwbGxtdqcvSnrs89xNqhlrRvQBiFoOxCgsL49q1a5w5c4YzZ87wxhtv0LdvX10fvUaj4ejRo/z73/8mJCSEUaNGkZWVRUhICMuXLyc7O5sBAwbw888/k56ejo+PDy7ZMagkLVJhAXnJMeQmltwS5mnUSjlNnS2LPZaRkYFSqcTBwYH8/HxmzpxJenq67ni9evWIiYmhsLCw2GNia6napdYkXdGva5zMzMxwcnLC0dGRzMxM4uLiiIqKYty4cXh7e+Po6Mhbb73FiRMniImJQZIkZDIZaWlpHDx4kEWLFjF27Fh+/vlnTExM2LZtG7LUGG4sHkP816+RsnMRhblPL5T9dxLoCqQ80Lt3b4KCgmjcuDHu7u6o1Wrc3Nx0xwcNGgQUFVRp3bo1UNQVsnnzZmxsbHj77bcr/oMSjEaNXgb8KK1Wi4ODA1FRUaI+qoFLT0/n/Pnzum6Bs2fPcv78eWxsbPDz88Pf3x8/Pz/8/Pxo1KhRhfrpjalAilCz1Io+XSiqTN+9e3f27Nnz2BVNQvUqLCzk+vXrxfpdz549S1JSEr6+vroEO2TIEFq0aFHuQjZPMiHQm8NX71aoQIpaqWB8oHelxSLULrWmpQuwfPlyDh48WO7dO4Vnd//+fc6fP18swV64cAFbW1tdy/XBf729vVEoFFUek7EUSBFqllqVdG/evEmbNm24fft2tfxSG4vc3FzOnj3LsWPHsLOz48UXX8TKyqpCz1VQUMC1a9d0rdYHCTY5OZnmzZvrugX8/f1p0aIF1tbWlftiyklUGROqW61KulA0t/M///kP7dq103coBmP+/Pls3ryZgIAAUlJScHZ2LjHHtTRpaWnFugXOnTvHxYsXcXBwKNbv6u/vT8OGDQ32D925+DSWHohm/5VkZEDOI/V01Uo5EvB8EwfGB3rrb72+UGPUuqT73nvvYWVlxSeffKLvUAyCJElcu3YNJycnLCwsOHPmDNOnT2fJkiW6FWCSJBEdHc3p06eLJdjU1FSaN29eLMG2aNHiqTVsDVWKJpfNf8VzOTGD9BwtVmoVTZ0tGdjaVewcIVSaWpd09+3bx8cff8zRo0f1HYpBSkpKokuXLkRGRupmBdy/f59x48aRm5tbLME2bNiw3JvyCUJtV+uSbm5uLo6Ojly/fh07Ozt9h2MwHsxvnTFjBtnZ2cyePVuXUB8cEwTh2dW6ZoqJiQndunVj7969+g6l2qSkpLB//36+/vprxo4di1arLXGOTCYjMjKSAwcOMHTo0GItWJFwBaHy1Jp5uo8KCgpi165dDBkyRN+hVKr8/HyuXLlSYnArIyODFi1a4O/vT0BAAAUFBcX2jHvQkl22bBlhYWFi23FBqEK1rnsB4Pr163Tq1Ilbt24ZbZ/k3bt3dUn1wX8vX76Mq6trsTmv/v7+uLu7P7W1umnTJiZPnszAgQNJTk5GrVYzZ86cStnaXBCEh2plS7dhw4ZYOdZn+sY/yFBYkp6Tj5VaSVMnKwa1MayRaq1Wy5UrV0qs2srKytINaHXu3Jk333yT5s2bY25uXqH7pKSk4O7ujqurK506daJ9+/Yi4QpCFah1Ld2zcWksORDNvotF9U4LHunWfjAnM7CJA+O7eePvZl2tsd25c6dYy/Xs2bNcuXIFd3f3YnNe/fz8aNCggehrFQQjVKuSrqGsPsrLy+Py5cslEuzfp2T5+/vj6+uLmZlZpccgCIJ+1Jqkq6919rdv3y4xsBUVFYWHh0eJmgOurq6i9SoINZxBJN2NGzfy6aefcvPmTZycnFi9erVu65VHeXh4cOvWLW7duoW9/cNtVVq1asWZM2e4ceMGHh4eJa47G5fGkBXHylRR6vb6qZg3fx5L/94AmKoURIR1eOryz9zcXCIjI0skWK1Wi7+/f7EWrK+vL6ampk+NRRCEmkfvA2l79+7lww8/JCIignbt2pGYmPjE8z09Pfn+++956623ADh//jxZWU8uQr3kQDQ5+eUv4QeQk1/A0gPRutqpWq222MyBBwk2Ojqahg0b6lqukyZNwt/fHxcXF9F6FQThoWrY5v2JOnbsKK1cubJM57q7u0ufffaZFBAQoHtsypQp0ueffy4B0o0bNyRJkqS0tDQpNDRUsre3l1zd3CS7bqFSgw9/ldynbpPsgt+VTFx9JKt2r0pyE3NJUbee5DhohuQ+dZtk1XGwhEwuoVBJMpVasmzdV3Kfuk0CpOeef0EyNTWV5HK5ZGdnJ/n5+Un29vaSqamp5OfnJ504cUIXEyBdvXpV9++RI0dK4eHhkiRJ0pw5c6R27dpJWq1WkiRJWrp0qeTj4yNlZ2c/649SEAQjoNdJqgUFBZw8eZLk5GS8vb1xdXVl4sSJZGdnP/aaDh06kJ6eTmRkJAUFBWzcuLFEUfK33nqL+/fvc/36dd6Yu5b087+hObdPdzz31hWUtvVxfWcDddsPIGXnN0iShE23EZi4+mDb6w0aTNmMba83dddExSbw3XffERUVxZ49e0hMTGTbtm1kZGQwefJkBg0aRG5u7lNf8/vvv4+JiQmff/45V69eZdq0aaxbtw61Wl2Bn6AgCMZGr0k3KSkJrVbL5s2bOXz4MGfOnOH06dN8/vnnT7wuNDSUNWvWsHfvXpo1a0b9+vV1xx4k4tmzZ2NpaUmyzArLtq+SeeF33TlKK0csWwYhkyswb9GdAk0qhZlpT7xnl9feZdCgQXh5ebFixQrGjRtH+/btUSgUjBw5EhMTE44dO/bU1yyXy1mzZg3ffPMNL730Eh988AGtWrV66nWCINQMek26DwaT3nrrLZydnbG3t2fy5Mns2LGDPn36YGFhgYWFRYmdHkJDQ9mwYQOrV69mxIgRxY7dvXsXrVaLu3vRFtvpOfko6zpSoEnRnaOwsNF9L1cVtTALtY9vXQNg8bA4TmxsLPPnz8fa2lr3FRcXx61bt8r0uj08PHj++eeJiYlhwoQJZbpGEISaQa9J18bGpsQ0qQff79y5E41Gg0ajYdiwYcWuc3d3x9PTkx07dtC/f/9ix+zt7VGpVMTGxgJgpVaSn56MwqKMFcUeM+hlqX5Yq8DNzY3w8HDS0tJ0X1lZWQwdOhQo2sH20cG927dvF3uu7du3c/ToUXr06MH7779ftrgEQagR9F54YPTo0SxatIg7d+5w7949FixYQL9+/Z563apVq/j9999LLHtVKBQMHjyY8PBwMjIycCCDjD9/xrz582WKR2FuTX7a7RKPN3R4eJ+xY8eybNkyjh8/jiRJZGZmsn37djIyMgBo2bIlGzZsoKCggF27dnHw4EHdtXfv3uUf//gHK1eu5LvvvmPr1q3s2LGjTLEJgmD89J50P/74Y9q2bUvjxo1p1qwZrVq1Ijw8/KnXeXl5ERBQ+hbYixYtwtzcnIYNG7J0ymtY+QZi4dezTPFYBbxE1uX/ErcghNS9/9Y9HuTrrPs+ICCAFStWMHHiRGxsbPD29mb16tW6419//TVbt27F2tqa9evX88orr+iOhYWF8fLLLxMcHIydnR2rVq3iH//4BykpD7s/BEGouQxicURVC1t7kr2RSU9c+vs4Mhn09qmnm6crCILwLPTe0q0OEwK9USsrtimiWqlgfKB3JUckCEJtVSuSrr+bNeHBTTFVle/lFtVeaCp2gBUEodLofRlwdXlQtMYQqowJglB71Yo+3Uedi09j6YFo9l9JRgbk5D+sOvagnu7zTRwYH+gtWriCIFS6Wpd0H0jR5LL5r3guJ2aQnqPFSq2iqbMlA1sb1s4RgiDULLU26QqCIOhDrRhIEwRBMBQi6QqCIFQjkXQFQRCqkUi6giAI1UgkXUEQhGokkq4gCEI1EklXEAShGomkKwiCUI1E0hUEQahGIukKgiBUI5F0BUEQqpFIuoIgCNVIJF1BEIRqJJKuIAhCNfp/tuKSRJ9pGooAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def solve_mst(G, weight_key='cost'):\n",
    "    return nx.minimum_spanning_tree(G, weight=weight_key)\n",
    "\n",
    "\n",
    "def calculate_network_cost(G):\n",
    "    return sum([d['cost'] for u, v, d in G.edges(data=True) if 'cost' in d])\n",
    "\n",
    "\n",
    "def calculate_edge_set_cost(edge_set, G):\n",
    "    return sum([G[u][v]['cost'] for u, v in edge_set])\n",
    "\n",
    "\n",
    "mst_network = solve_mst(network)\n",
    "mst_network.graph['cost'] = calculate_network_cost(mst_network)\n",
    "\n",
    "print('MST found, {} nodes, {} edges, cost = {}'.format(\n",
    "    mst_network.number_of_nodes(), mst_network.number_of_edges(),\n",
    "    mst_network.graph['cost']))\n",
    "\n",
    "draw_network(mst_network)\n",
    "optimal_cost = mst_network.graph['cost']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Construct the second one manually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alternative MST constructed, 10 nodes, 9 edges, cost = 22\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 432x288 with 1 Axes>, <AxesSubplot:>)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mst_network_2 = mst_network.copy()\n",
    "mst_network_2.add_edge(2, 8, cost=3)\n",
    "mst_network_2.remove_edge(1, 9)\n",
    "\n",
    "mst_network_2.graph['cost'] = calculate_network_cost(mst_network_2)\n",
    "print('Alternative MST constructed, {} nodes, {} edges, cost = {}'.format(\n",
    "    mst_network_2.number_of_nodes(), mst_network_2.number_of_edges(),\n",
    "    mst_network_2.graph['cost']))\n",
    "\n",
    "draw_network(mst_network_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extract features from logs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make a tables object to hold the data and computed feature tables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "tables = {'data': data_df}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute time difference between the time of consecutive event pairs.\n",
    "To be used for computing duration later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "durations = lambda x: x['time'].diff().fillna(0)\n",
    "data_df['duration'] = data_df.groupby('team_no').apply(durations).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create groups that represent the different granularities (levels of analysis)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "levels = {\n",
    "    'corpus': data_df.groupby('corpus_no'),\n",
    "    'task': data_df.groupby(['corpus_no', 'team_no']), \n",
    "    'attempt': data_df.groupby(['corpus_no', 'team_no', 'attempt_no']), \n",
    "    'turn': data_df.groupby(['team_no', 'attempt_no', 'turn_no']),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the features as functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Performance Features\n",
    "\n",
    "def success(x, opt_cost=optimal_cost):\n",
    "    '''whether a team has succeeded i.e. found the optimal solution, at task level only'''\n",
    "   # return x.name[-1] in metadata['success']\n",
    "    c = cost(x)\n",
    "    return not np.isnan(c) and c == opt_cost\n",
    "\n",
    "\n",
    "def cost(x):\n",
    "    '''the sum of the edge costs of the submitted solution'''\n",
    "    submits = x[x['verb'].isin(['submits'])]\n",
    "    if len(submits) > 0:\n",
    "        return int(submits['object'].iloc[-1].split()[0].split('=')[-1])\n",
    "    else:\n",
    "        return np.nan\n",
    "\n",
    "\n",
    "def abs_error(x, opt_cost=optimal_cost):\n",
    "    '''absolute error, i.e. the difference between the cost of the submitted solution and the cost of an optimal/correct solution (optimal cost)'''\n",
    "    return (cost(x) - opt_cost)\n",
    "\n",
    "\n",
    "def error(x, opt_cost=optimal_cost):\n",
    "    '''relative error, i.e. absolute error divided by the optimal cost'''\n",
    "    return 1.0 * (cost(x) - opt_cost) / opt_cost\n",
    "\n",
    "# Task/Attempt/Turn/Event Counts\n",
    "\n",
    "\n",
    "def num_task(x):\n",
    "    '''number of tasks, where a task is \n",
    "    the complete period that a team plays to find an optimal solution'''\n",
    "    return len(x['team_no'].unique())\n",
    "\n",
    "\n",
    "def num_attempt(x):\n",
    "    '''number of attempts, where an attempt is the duration of the team constructing a solution and submitting it together as a proposal'''\n",
    "    return len(x['attempt_no'].unique())\n",
    "\n",
    "\n",
    "def num_turn(x):\n",
    "    '''number of turns, where a turn is the duration where one player is in figurative view and the other player is in abstract view'''\n",
    "    return len(x['turn_no'].unique())\n",
    "\n",
    "\n",
    "def num_action(x):\n",
    "    '''number of actions, where an action is something done by the players or the tutor.'''\n",
    "    return len(x['subject'].isin(['A', 'B', 'R']))\n",
    "\n",
    "\n",
    "def avg_turn(x):\n",
    "    '''number of turns normalized by the number of attempts'''\n",
    "    return 1.0 * num_turn(x) / num_attempt(x)\n",
    "\n",
    "\n",
    "def avg_action_per_turn(x):\n",
    "    '''number of actions normalized by the number of turns'''\n",
    "    return 1.0 * num_action(x) / num_turn(x)\n",
    "\n",
    "\n",
    "# Duration Related\n",
    "\n",
    "\n",
    "def start(x):\n",
    "    '''start time in seconds'''\n",
    "    return x['time'].iloc[0]\n",
    "\n",
    "\n",
    "def end(x):\n",
    "    '''end time in seconds'''\n",
    "    return x['time'].iloc[-1]\n",
    "\n",
    "\n",
    "def duration(x):\n",
    "    '''total time (in seconds) spent in the task until finding the optimal solution or time-up intervention'''\n",
    "    return x['duration'].sum()\n",
    "\n",
    "\n",
    "# Features on Edit Actions\n",
    "\n",
    "\n",
    "def num_add(x):\n",
    "    '''number of additions'''\n",
    "    return x['verb'].isin(['adds']).sum()\n",
    "\n",
    "\n",
    "def num_del(x):\n",
    "    '''number of deletions'''\n",
    "    return x['verb'].isin(['removes']).sum()\n",
    "\n",
    "\n",
    "def num_edit(x):\n",
    "    '''number of edits (additions and deletions) on the graph'''\n",
    "    return num_add(x) + num_del(x)\n",
    "\n",
    "\n",
    "def freq_add(x):\n",
    "    '''relative frequency of additions, as divided by the total number of additions and deletions'''\n",
    "    n = num_edit(x)\n",
    "    if n == 0:\n",
    "        return -1\n",
    "    else:\n",
    "        return 1.0 * num_add(x) / n\n",
    "\n",
    "\n",
    "def freq_del(x):\n",
    "    '''relative frequency of deletions, as normalized by the total number of additions and deletions'''\n",
    "    return 1 - freq_add(x)\n",
    "\n",
    "def num_histload(x):\n",
    "    ''' how many times a previous solution was loaded i.e. brought back'''\n",
    "    return x['object'].isin(['apply (enabled)']).sum()\n",
    "\n",
    "\n",
    "def freq_histload(x):\n",
    "    '''relative frequency of the previous solution was bring-backs \n",
    "    as normalized by the number of times the previous solutions were shown'''\n",
    "    n = num_histview(x)\n",
    "    if n == 0:\n",
    "        return -1\n",
    "    else:\n",
    "        return 1.0 * num_histload(x) / n\n",
    "\n",
    "# Evaluation Actions\n",
    "\n",
    "\n",
    "def num_submitselect(x):\n",
    "    '''number of times the current solution is selected for submission'''\n",
    "    return x['object'].isin(['submit (disabled)']).sum()\n",
    "\n",
    "\n",
    "def num_histview(x):\n",
    "    '''number of times the player opens to view the solutions history'''\n",
    "    return x['object'].isin(['compare (enabled)']).sum()\n",
    "\n",
    "\n",
    "def num_histnext(x):\n",
    "    '''number of times the player chooses to view the next solution in the solutions history'''\n",
    "    return x['object'].isin(['next (enabled)']).sum()\n",
    "\n",
    "\n",
    "def num_histprev(x):\n",
    "    '''number of times the player chooses to view the previous solution in the solutions history'''\n",
    "    return x['object'].isin(['previous (enabled)']).sum()\n",
    "\n",
    "\n",
    "def num_histnavi(x):\n",
    "    '''number of times the player chooses to navigate (view next or view previous)  \n",
    "    among the solutions in the solutions history'''\n",
    "    return num_histnext(x) + num_histprev(x)\n",
    "\n",
    "# Other\n",
    "\n",
    "\n",
    "def num_help(x):\n",
    "    '''number of times a player opened help/info window'''\n",
    "    return x['object'].isin(['help (enabled)']).sum()\n",
    "\n",
    "\n",
    "def last_valid_value(x):\n",
    "    '''the error of the last completed attempt'''\n",
    "    return x.iloc[-1] if not np.isnan(x.iloc[-1]) else x.iloc[-2]\n",
    "\n",
    "\n",
    "def series_range(x):\n",
    "    #     x = x[1:]\n",
    "    '''maximum - minimum of the sequence'''\n",
    "    return np.max(x) - np.min(x)\n",
    "\n",
    "\n",
    "def series_slope(x):\n",
    "    #     x = x[1:]\n",
    "    '''(simple linear) regression coefficient (i.e. slope) of the sequence'''\n",
    "    x = x[~np.isnan(x)]\n",
    "    if len(np.unique(x)) == 1:\n",
    "        return 0.0\n",
    "    y = np.arange(len(x))\n",
    "    slope, intercept, r_value, p_value, std_err = stats.linregress(x, y)\n",
    "    return slope\n",
    "\n",
    "\n",
    "def series_noninc(x):\n",
    "    '''True if the sequence is non-increasing, False otherwise.'''\n",
    "    for i in range(len(x) - 1):\n",
    "        if x.iloc[i+1] > x.iloc[i]:\n",
    "            return False\n",
    "    return True\n",
    "\n",
    "\n",
    "def compute_features(grouped, functions=[], df=None, inplace=False, insert_index=None):\n",
    "    '''Computes features on a grouped object from a list of functions'''\n",
    "    if df is not None and not inplace:\n",
    "        df = df.copy()\n",
    "\n",
    "    if insert_index is not None:\n",
    "        functions.reverse()\n",
    "\n",
    "    for i, entry in enumerate(functions):\n",
    "        if callable(entry):  # if it is a function\n",
    "            # Print the name of the function.\n",
    "            s = entry.__name__ if hasattr(entry, '__name__') else entry\n",
    "            print('Computing feature {}'.format(s))\n",
    "            \n",
    "            func = entry\n",
    "            result_column = func.__name__\n",
    "\n",
    "            if df is None and i == 0:\n",
    "                df = grouped.apply(func).to_frame(func.__name__)\n",
    "            else:\n",
    "                i = len(df.columns) if insert_index is None else insert_index\n",
    "                df.insert(i, result_column, grouped.apply(func))\n",
    "\n",
    "        elif type(entry) is list:\n",
    "            applied_column, prefix_func_pairs = entry\n",
    "\n",
    "            if insert_index is not None:\n",
    "                prefix_func_pairs.reverse()\n",
    "\n",
    "            for prefix, func in prefix_func_pairs:\n",
    "                result_column = '{}_{}'.format(prefix, applied_column)\n",
    "                \n",
    "                # Print the name of the function.\n",
    "                print('Computing feature {}'.format(result_column))\n",
    "\n",
    "                i = len(df.columns) if insert_index is None else insert_index\n",
    "\n",
    "                if df is None and i == 0:\n",
    "                    df = grouped[applied_column].apply(\n",
    "                        func).to_frame(result_column)\n",
    "                else:\n",
    "                    df.insert(i, result_column,\n",
    "                              grouped[applied_column].apply(func))\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute attempt level features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing feature cost\n",
      "Computing feature abs_error\n",
      "Computing feature error\n",
      "Computing feature num_turn\n",
      "Computing feature num_action\n",
      "Computing feature duration\n",
      "Computing feature start\n",
      "Computing feature end\n",
      "Computing feature num_add\n",
      "Computing feature num_del\n",
      "Computing feature num_edit\n",
      "Computing feature freq_add\n",
      "Computing feature freq_del\n",
      "Computing feature num_histload\n",
      "Computing feature freq_histload\n",
      "Computing feature success\n"
     ]
    },
    {
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      "text/plain": [
       "                              cost  abs_error     error  num_turn  num_action  \\\n",
       "corpus_no team_no attempt_no                                                    \n",
       "1         6       1           24.0        2.0  0.090909        21          72   \n",
       "                  2           22.0        0.0  0.000000         8          28   \n",
       "          7       1           64.0       42.0  1.909091        14          50   \n",
       "                  2           64.0       42.0  1.909091         4          23   \n",
       "                  3           29.0        7.0  0.318182         6          16   \n",
       "                  4           30.0        8.0  0.363636         8          21   \n",
       "                  5           31.0        9.0  0.409091         7          23   \n",
       "                  6           31.0        9.0  0.409091        10          24   \n",
       "                  7           31.0        9.0  0.409091         6          18   \n",
       "                  8           30.0        8.0  0.363636         8          30   \n",
       "\n",
       "                              duration     start       end  num_add  num_del  \\\n",
       "corpus_no team_no attempt_no                                                   \n",
       "1         6       1           1013.047     0.122  1013.169       25       16   \n",
       "                  2            337.414  1025.061  1350.583       12        3   \n",
       "          7       1            264.240     0.315   264.555       23        3   \n",
       "                  2             75.149   277.949   339.704        5        2   \n",
       "                  3             45.036   355.730   384.740       10        0   \n",
       "                  4            103.876   397.215   488.616       12        2   \n",
       "                  5             90.407   501.269   579.023       11        1   \n",
       "                  6             94.255   586.504   673.278       14        4   \n",
       "                  7             58.610   697.498   731.888       10        0   \n",
       "                  8             66.548   742.335   798.436       12        3   \n",
       "\n",
       "                              num_edit  freq_add  freq_del  num_histload  \\\n",
       "corpus_no team_no attempt_no                                               \n",
       "1         6       1                 41  0.609756  0.390244             0   \n",
       "                  2                 15  0.800000  0.200000             0   \n",
       "          7       1                 26  0.884615  0.115385             0   \n",
       "                  2                  7  0.714286  0.285714             5   \n",
       "                  3                 10  1.000000  0.000000             0   \n",
       "                  4                 14  0.857143  0.142857             0   \n",
       "                  5                 12  0.916667  0.083333             0   \n",
       "                  6                 18  0.777778  0.222222             0   \n",
       "                  7                 10  1.000000  0.000000             0   \n",
       "                  8                 15  0.800000  0.200000             0   \n",
       "\n",
       "                              freq_histload  success  \n",
       "corpus_no team_no attempt_no                          \n",
       "1         6       1               -1.000000    False  \n",
       "                  2                0.000000     True  \n",
       "          7       1               -1.000000    False  \n",
       "                  2                1.666667    False  \n",
       "                  3               -1.000000    False  \n",
       "                  4               -1.000000    False  \n",
       "                  5               -1.000000    False  \n",
       "                  6               -1.000000    False  \n",
       "                  7               -1.000000    False  \n",
       "                  8               -1.000000    False  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute task features.\n",
    "attempt_features = [\n",
    "    cost, abs_error, error,\n",
    "    # Attempt/Turn/Event Counts\n",
    "    num_turn, num_action,\n",
    "    # Time Related\n",
    "    duration, start, end,\n",
    "#     # Edit Action Related\n",
    "    num_add, num_del, num_edit, freq_add, freq_del, num_histload, freq_histload,\n",
    "#     # Evaluation Action Related\n",
    "#     num_submitselect, num_histview, num_histnext, num_histprev, num_histnavi,\n",
    "#     # Other\n",
    "#     num_help,\n",
    "    success,\n",
    "    ]\n",
    "tables['attempt'] = compute_features(levels['attempt'], attempt_features)\n",
    "\n",
    "# Display the task features table.\n",
    "tables['attempt'].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute task level features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing feature success\n",
      "Computing feature num_attempt\n",
      "Computing feature avg_turn\n",
      "Computing feature avg_action_per_turn\n",
      "Computing feature num_turn\n",
      "Computing feature num_action\n",
      "Computing feature duration\n",
      "Computing feature num_edit\n",
      "Computing feature freq_add\n",
      "Computing feature freq_histload\n",
      "Computing feature num_submitselect\n",
      "Computing feature num_histview\n",
      "Computing feature num_help\n",
      "Computing feature slope_error\n",
      "Computing feature noninc_error\n",
      "Computing feature std_error\n",
      "Computing feature avg_error\n",
      "Computing feature range_error\n",
      "Computing feature min_error\n",
      "Computing feature max_error\n",
      "Computing feature last_error\n"
     ]
    },
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       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.136364</td>\n",
       "      <td>1.909091</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>1.772727</td>\n",
       "      <td>0.505051</td>\n",
       "      <td>0.505908</td>\n",
       "      <td>False</td>\n",
       "      <td>-6.363863</td>\n",
       "      <td>False</td>\n",
       "      <td>19</td>\n",
       "      <td>5.157895</td>\n",
       "      <td>4.285714</td>\n",
       "      <td>98</td>\n",
       "      <td>420</td>\n",
       "      <td>1581.128</td>\n",
       "      <td>206</td>\n",
       "      <td>0.922330</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>9</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.409091</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.308081</td>\n",
       "      <td>0.114948</td>\n",
       "      <td>False</td>\n",
       "      <td>9.555985</td>\n",
       "      <td>False</td>\n",
       "      <td>9</td>\n",
       "      <td>5.777778</td>\n",
       "      <td>5.057692</td>\n",
       "      <td>52</td>\n",
       "      <td>263</td>\n",
       "      <td>1559.334</td>\n",
       "      <td>107</td>\n",
       "      <td>0.897196</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.234848</td>\n",
       "      <td>0.103041</td>\n",
       "      <td>False</td>\n",
       "      <td>-20.335135</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>7.823529</td>\n",
       "      <td>34</td>\n",
       "      <td>266</td>\n",
       "      <td>2152.799</td>\n",
       "      <td>68</td>\n",
       "      <td>0.720588</td>\n",
       "      <td>0.645161</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.454545</td>\n",
       "      <td>0.681818</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.545455</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.202430</td>\n",
       "      <td>False</td>\n",
       "      <td>-8.873950</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>5.882353</td>\n",
       "      <td>51</td>\n",
       "      <td>300</td>\n",
       "      <td>1375.537</td>\n",
       "      <td>108</td>\n",
       "      <td>0.981481</td>\n",
       "      <td>0.275862</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.136364</td>\n",
       "      <td>1.909091</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>1.863636</td>\n",
       "      <td>0.586777</td>\n",
       "      <td>0.529539</td>\n",
       "      <td>False</td>\n",
       "      <td>-5.054561</td>\n",
       "      <td>False</td>\n",
       "      <td>12</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>5.196970</td>\n",
       "      <td>66</td>\n",
       "      <td>343</td>\n",
       "      <td>1585.635</td>\n",
       "      <td>134</td>\n",
       "      <td>0.902985</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>3</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.181818</td>\n",
       "      <td>0.681818</td>\n",
       "      <td>0.045455</td>\n",
       "      <td>0.636364</td>\n",
       "      <td>0.306818</td>\n",
       "      <td>0.206743</td>\n",
       "      <td>False</td>\n",
       "      <td>-7.444109</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>6.875000</td>\n",
       "      <td>7.018182</td>\n",
       "      <td>55</td>\n",
       "      <td>386</td>\n",
       "      <td>1876.304</td>\n",
       "      <td>114</td>\n",
       "      <td>0.850877</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.772727</td>\n",
       "      <td>0.397727</td>\n",
       "      <td>0.302153</td>\n",
       "      <td>True</td>\n",
       "      <td>-3.298444</td>\n",
       "      <td>False</td>\n",
       "      <td>5</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>4.486486</td>\n",
       "      <td>37</td>\n",
       "      <td>166</td>\n",
       "      <td>1773.024</td>\n",
       "      <td>73</td>\n",
       "      <td>0.712329</td>\n",
       "      <td>0.380952</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.409091</td>\n",
       "      <td>0.727273</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.422078</td>\n",
       "      <td>0.151175</td>\n",
       "      <td>False</td>\n",
       "      <td>0.284133</td>\n",
       "      <td>False</td>\n",
       "      <td>8</td>\n",
       "      <td>8.625000</td>\n",
       "      <td>4.666667</td>\n",
       "      <td>69</td>\n",
       "      <td>322</td>\n",
       "      <td>1720.674</td>\n",
       "      <td>141</td>\n",
       "      <td>0.737589</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>59</td>\n",
       "      <td>22</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.117546</td>\n",
       "      <td>True</td>\n",
       "      <td>-8.635514</td>\n",
       "      <td>True</td>\n",
       "      <td>4</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.288462</td>\n",
       "      <td>52</td>\n",
       "      <td>171</td>\n",
       "      <td>1270.777</td>\n",
       "      <td>106</td>\n",
       "      <td>0.669811</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   last_error  max_error  min_error  range_error  avg_error  \\\n",
       "corpus_no team_no                                                             \n",
       "1         6          0.000000   0.090909   0.000000     0.090909   0.045455   \n",
       "          7          0.136364   1.909091   0.136364     1.772727   0.505051   \n",
       "          8          0.409091   0.500000   0.136364     0.363636   0.308081   \n",
       "          9          0.318182   0.363636   0.045455     0.318182   0.234848   \n",
       "          10         0.454545   0.681818   0.136364     0.545455   0.318182   \n",
       "          11         0.136364   1.909091   0.045455     1.863636   0.586777   \n",
       "          12         0.181818   0.681818   0.045455     0.636364   0.306818   \n",
       "          14         0.136364   0.909091   0.136364     0.772727   0.397727   \n",
       "          15         0.409091   0.727273   0.227273     0.500000   0.422078   \n",
       "          16         0.000000   0.318182   0.000000     0.318182   0.125000   \n",
       "\n",
       "                   std_error  noninc_error  slope_error  success  num_attempt  \\\n",
       "corpus_no team_no                                                               \n",
       "1         6         0.045455          True   -11.000000     True            2   \n",
       "          7         0.505908         False    -6.363863    False           19   \n",
       "          8         0.114948         False     9.555985    False            9   \n",
       "          9         0.103041         False   -20.335135    False           12   \n",
       "          10        0.202430         False    -8.873950    False           12   \n",
       "          11        0.529539         False    -5.054561    False           12   \n",
       "          12        0.206743         False    -7.444109    False            8   \n",
       "          14        0.302153          True    -3.298444    False            5   \n",
       "          15        0.151175         False     0.284133    False            8   \n",
       "          16        0.117546          True    -8.635514     True            4   \n",
       "\n",
       "                    avg_turn  avg_action_per_turn  num_turn  num_action  \\\n",
       "corpus_no team_no                                                         \n",
       "1         6        14.000000             3.571429        28         100   \n",
       "          7         5.157895             4.285714        98         420   \n",
       "          8         5.777778             5.057692        52         263   \n",
       "          9         2.833333             7.823529        34         266   \n",
       "          10        4.250000             5.882353        51         300   \n",
       "          11        5.500000             5.196970        66         343   \n",
       "          12        6.875000             7.018182        55         386   \n",
       "          14        7.400000             4.486486        37         166   \n",
       "          15        8.625000             4.666667        69         322   \n",
       "          16       13.000000             3.288462        52         171   \n",
       "\n",
       "                   duration  num_edit  freq_add  freq_histload  \\\n",
       "corpus_no team_no                                                \n",
       "1         6        1350.461        56  0.660714       0.000000   \n",
       "          7        1581.128       206  0.922330       0.208333   \n",
       "          8        1559.334       107  0.897196       0.000000   \n",
       "          9        2152.799        68  0.720588       0.645161   \n",
       "          10       1375.537       108  0.981481       0.275862   \n",
       "          11       1585.635       134  0.902985       0.142857   \n",
       "          12       1876.304       114  0.850877       0.000000   \n",
       "          14       1773.024        73  0.712329       0.380952   \n",
       "          15       1720.674       141  0.737589       0.090909   \n",
       "          16       1270.777       106  0.669811       0.000000   \n",
       "\n",
       "                   num_submitselect  num_histview  num_help  \n",
       "corpus_no team_no                                            \n",
       "1         6                       9             5         3  \n",
       "          7                       9            24         8  \n",
       "          8                       0            28        14  \n",
       "          9                       0            31         6  \n",
       "          10                      1            29        21  \n",
       "          11                      3            42         1  \n",
       "          12                      3            77         4  \n",
       "          14                      0            21         2  \n",
       "          15                     59            22        17  \n",
       "          16                      1            13         4  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute task features.\n",
    "task_features = [\n",
    "    success,\n",
    "    # Attempt/Turn/Event Counts\n",
    "    num_attempt, avg_turn, avg_action_per_turn, num_turn, num_action,\n",
    "    # Time Related\n",
    "    duration,\n",
    "    # Edit Action Related\n",
    "    # num_add, num_del, \n",
    "    num_edit, freq_add, \n",
    "    #freq_del, num_histload, \n",
    "    freq_histload,\n",
    "    # Evaluation Action Related\n",
    "    num_submitselect, \n",
    "    num_histview,\n",
    "    # num_histnext, num_histprev, num_histnavi,\n",
    "    # Other\n",
    "    num_help,\n",
    "    ]\n",
    "tables['task'] = compute_features(levels['task'], task_features)\n",
    "\n",
    "attempt_to_task_features = [\n",
    "    ['error', [\n",
    "        ('last', last_valid_value),\n",
    "        ('max', np.max),\n",
    "        ('min', np.min),\n",
    "        ('range', series_range),\n",
    "        ('avg', np.mean),\n",
    "        ('std', np.std), \n",
    "        ('noninc', series_noninc),\n",
    "        ('slope', series_slope),\n",
    "        ]\n",
    "    ], \n",
    "]\n",
    "grouped = tables['attempt'].reset_index().groupby(['corpus_no', 'team_no'])\n",
    "insert_index = 0\n",
    "compute_features(grouped, attempt_to_task_features, df=tables['task'], \n",
    "                 insert_index=insert_index, inplace=True)\n",
    "\n",
    "# Display the task features table.\n",
    "tables['task'].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute turn level features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing feature num_action\n",
      "Computing feature duration\n",
      "Computing feature num_add\n",
      "Computing feature num_del\n",
      "Computing feature num_edit\n",
      "Computing feature freq_add\n",
      "Computing feature freq_del\n"
     ]
    },
    {
     "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>num_action</th>\n",
       "      <th>duration</th>\n",
       "      <th>num_add</th>\n",
       "      <th>num_del</th>\n",
       "      <th>num_edit</th>\n",
       "      <th>freq_add</th>\n",
       "      <th>freq_del</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "      <td>2151.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.071130</td>\n",
       "      <td>26.656066</td>\n",
       "      <td>1.430033</td>\n",
       "      <td>0.344026</td>\n",
       "      <td>1.774059</td>\n",
       "      <td>0.703626</td>\n",
       "      <td>0.296374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.662972</td>\n",
       "      <td>27.072497</td>\n",
       "      <td>0.708493</td>\n",
       "      <td>0.565447</td>\n",
       "      <td>0.535351</td>\n",
       "      <td>0.513905</td>\n",
       "      <td>0.513905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.244000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>17.785000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>32.430000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>240.198000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        num_action     duration      num_add      num_del     num_edit  \\\n",
       "count  2151.000000  2151.000000  2151.000000  2151.000000  2151.000000   \n",
       "mean      4.071130    26.656066     1.430033     0.344026     1.774059   \n",
       "std       4.662972    27.072497     0.708493     0.565447     0.535351   \n",
       "min       1.000000     0.010000     0.000000     0.000000     0.000000   \n",
       "25%       2.000000    10.244000     1.000000     0.000000     2.000000   \n",
       "50%       2.000000    17.785000     2.000000     0.000000     2.000000   \n",
       "75%       4.000000    32.430000     2.000000     1.000000     2.000000   \n",
       "max      59.000000   240.198000     2.000000     2.000000     2.000000   \n",
       "\n",
       "          freq_add     freq_del  \n",
       "count  2151.000000  2151.000000  \n",
       "mean      0.703626     0.296374  \n",
       "std       0.513905     0.513905  \n",
       "min      -1.000000     0.000000  \n",
       "25%       0.500000     0.000000  \n",
       "50%       1.000000     0.000000  \n",
       "75%       1.000000     0.500000  \n",
       "max       1.000000     2.000000  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute task features.\n",
    "turn_features = [\n",
    "    # Attempt/Turn/Event Counts\n",
    "    num_action,\n",
    "    # Time Related\n",
    "    duration,\n",
    "#     # Edit Action Related\n",
    "    num_add, num_del, num_edit, freq_add, freq_del, # num_histload, freq_histload,\n",
    "#     # Evaluation Action Related\n",
    "#     num_submitselect, num_histview, num_histnext, num_histprev, num_histnavi,\n",
    "#     # Other\n",
    "#     num_help,\n",
    "    ]\n",
    "tables['turn'] = compute_features(levels['turn'], turn_features)\n",
    "\n",
    "# Display the task features table.\n",
    "tables['turn'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute corpus level features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing feature num_task\n"
     ]
    },
    {
     "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>corpus_no</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>num_task</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sum_last_error</th>\n",
       "      <td>7.77273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_last_error</th>\n",
       "      <td>0.199301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std_last_error</th>\n",
       "      <td>0.159045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amax_last_error</th>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amin_last_error</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sum_max_error</th>\n",
       "      <td>27.0909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_max_error</th>\n",
       "      <td>0.694639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std_max_error</th>\n",
       "      <td>0.56638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amax_max_error</th>\n",
       "      <td>1.90909</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "corpus_no               1\n",
       "num_task               39\n",
       "sum_last_error    7.77273\n",
       "mean_last_error  0.199301\n",
       "std_last_error   0.159045\n",
       "amax_last_error       0.5\n",
       "amin_last_error         0\n",
       "sum_max_error     27.0909\n",
       "mean_max_error   0.694639\n",
       "std_max_error     0.56638\n",
       "amax_max_error    1.90909"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corpus_features = [num_task] #num_success] #, freq_success]\n",
    "\n",
    "grouped = tables['task'].reset_index().groupby('corpus_no')\n",
    "tables['corpus'] = compute_features(grouped, corpus_features)\n",
    "\n",
    "features = tables['task'].columns\n",
    "# features = ['num_attempt', 'num_turn', 'num_action', 'num_add', 'num_del', 'success']\n",
    "\n",
    "df = tables['task'][features].groupby('corpus_no').agg([np.sum, np.mean, np.std, np.max, np.min])\n",
    "df.columns = ['_'.join(reversed(col)).strip() for col in df.columns.values]\n",
    "\n",
    "tables['corpus'] = pd.concat([tables['corpus'], df], axis=1)\n",
    "\n",
    "column_map = {\n",
    "    'sum_success':'num_success', \n",
    "    'mean_success':'freq_success',\n",
    "}\n",
    "tables['corpus'].columns = [column_map[c] if c in column_map else c for c in tables['corpus'].columns]\n",
    "tables['corpus'] = tables['corpus'].T\n",
    "\n",
    "tables['corpus'].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Draw log feature correlation heatmaps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_pvalues(df):\n",
    "    df = df.dropna()._get_numeric_data()\n",
    "    dfcols = pd.DataFrame(columns=df.columns)\n",
    "    pvalues = dfcols.transpose().join(dfcols, how='outer')\n",
    "    for r in df.columns:\n",
    "        for c in df.columns:\n",
    "            pvalues[r][c] = pearsonr(df[r], df[c])[1]\n",
    "    return pvalues\n",
    "\n",
    "\n",
    "p_thres = 0.05\n",
    "\n",
    "df = tables['task']\n",
    "pvalues_df = calculate_pvalues(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Significant (p < 0.05) values (without correction for multiple testing) are in bold and highlighted with a border\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = tables['task']\n",
    "corr = df.corr(method='pearson')\n",
    "\n",
    "corr = corr.round(2)\n",
    "fig, ax = plt.subplots(figsize=(16, 8)) \n",
    "annot_kws = {} \n",
    "\n",
    "sns.set(font_scale=1.1)            \n",
    "sns_plot_1 = sns.heatmap(corr, \n",
    "            xticklabels=corr.columns,\n",
    "            yticklabels=corr.columns,\n",
    "            cmap='coolwarm', \n",
    "            robust=True,\n",
    "            annot=True,\n",
    "            fmt='.2f',\n",
    "            annot_kws=annot_kws,\n",
    "            linewidth=1, #1.5,\n",
    "\n",
    "            ax=ax)\n",
    "\n",
    "from matplotlib.patches import Rectangle\n",
    "\n",
    "for i, annot in enumerate(ax.texts):\n",
    "    row = i % len(pvalues_df)\n",
    "    col = int(i / len(pvalues_df))\n",
    "    p_val = pvalues_df.iloc[row, col]\n",
    "    annot.set_text('{:.2f}'.format(np.abs(float(annot.get_text()))))\n",
    "    if 1 - float(annot.get_text()) < 0.001:\n",
    "        annot.set_visible(False)\n",
    "    elif p_val < p_thres:\n",
    "        annot.set_weight('bold')\n",
    "        annot.set_text('{}'.format(annot.get_text()))\n",
    "\n",
    "        ax.add_patch(Rectangle((row, col), 1, 1, fill=False, edgecolor='black', lw=2)) #blue\n",
    "\n",
    "print('Significant (p < 0.05) values (without correction for multiple testing) are in bold and highlighted with a border\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Export a separate table for each level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempt-level table is exported to ../processed_data/log_features/justhink19_log_features_attempt_level.csv\n",
      "task-level table is exported to ../processed_data/log_features/justhink19_log_features_task_level.csv\n",
      "turn-level table is exported to ../processed_data/log_features/justhink19_log_features_turn_level.csv\n",
      "corpus-level table is exported to ../processed_data/log_features/justhink19_log_features_corpus_level.csv\n"
     ]
    }
   ],
   "source": [
    "for key, data in tables.items():\n",
    "    if key in ['data']:\n",
    "        continue\n",
    "        \n",
    "    file = 'justhink19_log_features_{}_level.csv'.format(key)\n",
    "    file = output_dir.joinpath(file)\n",
    "    \n",
    "    data.to_csv(str(file))\n",
    "    \n",
    "    print('{}-level table is exported to {}'.format(key, file))"
   ]
  }
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