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milestone_5_without_improvements-logs
chortas 3 years ago
parent 6567ec3afc
commit fb20a57560
1 changed files with 199 additions and 0 deletions
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199
fftma_module/gen/analysis.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd "
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
"<style scoped>\n",
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"<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",
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" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.150900</td>\n",
" <td>./lib_src/generate.c:75:</td>\n",
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" <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",
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" <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",
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" <th>6</th>\n",
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" <td>./lib_src/covariance.c:86:</td>\n",
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" <th>7</th>\n",
" <td>0.000713</td>\n",
" <td>./lib_src/gasdev.c:35:</td>\n",
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" <th>8</th>\n",
" <td>0.000101</td>\n",
" <td>./lib_src/ran2.c:68:</td>\n",
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" <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",
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"</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:"
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},
"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": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.18"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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