{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>elapsed_time (seconds)</th>\n",
       "      <th>function_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.150900</td>\n",
       "      <td>./lib_src/generate.c:75:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000051</td>\n",
       "      <td>./lib_src/build_real.c:50:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000091</td>\n",
       "      <td>./lib_src/cov_value.c:60:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000021</td>\n",
       "      <td>./lib_src/length.c:47:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000017</td>\n",
       "      <td>./lib_src/clean_real.c:48:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000068</td>\n",
       "      <td>./lib_src/gasdev.c:43:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.082331</td>\n",
       "      <td>./lib_src/covariance.c:86:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000713</td>\n",
       "      <td>./lib_src/gasdev.c:35:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000101</td>\n",
       "      <td>./lib_src/ran2.c:68:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000047</td>\n",
       "      <td>./lib_src/prebuild_gwn.c:57:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.236221</td>\n",
       "      <td>./lib_src/Py_kgeneration.c:74:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.084618</td>\n",
       "      <td>./lib_src/fftma2.c:106:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.000007</td>\n",
       "      <td>./lib_src/maxfactor.c:42:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.000835</td>\n",
       "      <td>./lib_src/fourt.c:593:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.000086</td>\n",
       "      <td>./lib_src/cgrid.c:50:</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.000026</td>\n",
       "      <td>./lib_src/Py_getvalues.c:157:</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    elapsed_time (seconds)                   function_name\n",
       "0                 0.150900        ./lib_src/generate.c:75:\n",
       "1                 0.000051      ./lib_src/build_real.c:50:\n",
       "2                 0.000091       ./lib_src/cov_value.c:60:\n",
       "3                 0.000021          ./lib_src/length.c:47:\n",
       "4                 0.000017      ./lib_src/clean_real.c:48:\n",
       "5                 0.000068          ./lib_src/gasdev.c:43:\n",
       "6                 0.082331      ./lib_src/covariance.c:86:\n",
       "7                 0.000713          ./lib_src/gasdev.c:35:\n",
       "8                 0.000101            ./lib_src/ran2.c:68:\n",
       "9                 0.000047    ./lib_src/prebuild_gwn.c:57:\n",
       "10                0.236221  ./lib_src/Py_kgeneration.c:74:\n",
       "11                0.084618         ./lib_src/fftma2.c:106:\n",
       "12                0.000007       ./lib_src/maxfactor.c:42:\n",
       "13                0.000835          ./lib_src/fourt.c:593:\n",
       "14                0.000086           ./lib_src/cgrid.c:50:\n",
       "15                0.000026   ./lib_src/Py_getvalues.c:157:"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {}\n",
    "with open(\"log_16.txt\") as log_file:\n",
    "    lines = log_file.readlines()\n",
    "    for line in lines:\n",
    "        if \"ELAPSED\" in line:\n",
    "            split_line = line.split()\n",
    "            idx_elapsed = split_line.index(\"ELAPSED\") + 2\n",
    "            function_name, elapsed = split_line[2], float(split_line[idx_elapsed])\n",
    "            if function_name not in data or (function_name in data and elapsed > data[function_name]):\n",
    "                data[function_name] = elapsed\n",
    "new_data = {\"function_name\": data.keys(), \"elapsed_time (seconds)\": data.values()}\n",
    "                \n",
    "df = pd.DataFrame(new_data)  \n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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