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"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>Total</th>\n",
" <th>Cal.</th>\n",
" <th>Test</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Images</th>\n",
" <td>7481</td>\n",
" <td>807.0</td>\n",
" <td>748.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B. boxes</th>\n",
" <td>28742</td>\n",
" <td>3100.1</td>\n",
" <td>2874.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Total Cal. Test\n",
"Images 7481 807.0 748.1\n",
"B. boxes 28742 3100.1 2874.2"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kitti = FullKitti('datasets', download=True)\n",
"set_random_seed(123456)\n",
"params = {\n",
" 'k_folds': 10, 'cal_ratio': 0.12,\n",
" 'iou_threshold': 0.3, 'objectness_threshold': 0.3\n",
"}\n",
"DatasetDescriber().describe(kitti, **params)\n",
"#TBD -> summary table and an example of prediction with 2+1 boxes\n",
"# https://datasetninja.com/kitti-object-detection"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summary"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"filters = (filter, filter2) #, filter3)\n",
"results = (res, res2) #, res3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Summarizing validity"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1500x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mrkz=['v', 'D', '$0$', '+', 'x', 'o', 'P', 'X']\n",
"validity_tbls = SummaryReporter(approaches, filters, markers=mrkz).report(results, folds)"
]
},
{
"cell_type": "code",
"execution_count": null,
"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>$1 - \\epsilon^g$</th>\n",
" <th>Bonferroni</th>\n",
" <th>Max additive</th>\n",
" <th>Independent DE-CCP</th>\n",
" <th>Gumbel DE-CCP</th>\n",
" <th>Empirical DE-CCP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.99</td>\n",
" <td>0.992±0.002</td>\n",
" <td>0.991±0.002</td>\n",
" <td>0.990±0.002</td>\n",
" <td>0.990±0.002</td>\n",
" <td>0.990±0.002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.95</td>\n",
" <td>0.960±0.006</td>\n",
" <td>0.947±0.007</td>\n",
" <td>0.955±0.006</td>\n",
" <td>0.953±0.007</td>\n",
" <td>0.952±0.007</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.90</td>\n",
" <td>0.920±0.009</td>\n",
" <td>0.898±0.008</td>\n",
" <td>0.913±0.009</td>\n",
" <td>0.908±0.009</td>\n",
" <td>0.906±0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.80</td>\n",
" <td>0.849±0.011</td>\n",
" <td>0.796±0.013</td>\n",
" <td>0.834±0.012</td>\n",
" <td>0.822±0.012</td>\n",
" <td>0.815±0.012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.70</td>\n",
" <td>0.779±0.012</td>\n",
" <td>0.694±0.016</td>\n",
" <td>0.748±0.015</td>\n",
" <td>0.735±0.014</td>\n",
" <td>0.722±0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.60</td>\n",
" <td>0.715±0.012</td>\n",
" <td>0.594±0.017</td>\n",
" <td>0.665±0.014</td>\n",
" <td>0.649±0.016</td>\n",
" <td>0.628±0.012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.50</td>\n",
" <td>0.654±0.013</td>\n",
" <td>0.498±0.019</td>\n",
" <td>0.573±0.019</td>\n",
" <td>0.553±0.012</td>\n",
" <td>0.531±0.011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.40</td>\n",
" <td>0.594±0.011</td>\n",
" <td>0.403±0.015</td>\n",
" <td>0.478±0.019</td>\n",
" <td>0.455±0.015</td>\n",
" <td>0.435±0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.30</td>\n",
" <td>0.541±0.013</td>\n",
" <td>0.308±0.009</td>\n",
" <td>0.382±0.012</td>\n",
" <td>0.351±0.012</td>\n",
" <td>0.338±0.014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.20</td>\n",
" <td>0.490±0.013</td>\n",
" <td>0.208±0.008</td>\n",
" <td>0.267±0.013</td>\n",
" <td>0.251±0.011</td>\n",
" <td>0.226±0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.10</td>\n",
" <td>0.442±0.014</td>\n",
" <td>0.109±0.005</td>\n",
" <td>0.149±0.012</td>\n",
" <td>0.131±0.012</td>\n",
" <td>0.114±0.011</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" $1 - \\epsilon^g$ Bonferroni Max additive Independent DE-CCP \\\n",
"0 0.99 0.992±0.002 0.991±0.002 0.990±0.002 \n",
"1 0.95 0.960±0.006 0.947±0.007 0.955±0.006 \n",
"2 0.90 0.920±0.009 0.898±0.008 0.913±0.009 \n",
"3 0.80 0.849±0.011 0.796±0.013 0.834±0.012 \n",
"4 0.70 0.779±0.012 0.694±0.016 0.748±0.015 \n",
"5 0.60 0.715±0.012 0.594±0.017 0.665±0.014 \n",
"6 0.50 0.654±0.013 0.498±0.019 0.573±0.019 \n",
"7 0.40 0.594±0.011 0.403±0.015 0.478±0.019 \n",
"8 0.30 0.541±0.013 0.308±0.009 0.382±0.012 \n",
"9 0.20 0.490±0.013 0.208±0.008 0.267±0.013 \n",
"10 0.10 0.442±0.014 0.109±0.005 0.149±0.012 \n",
"\n",
" Gumbel DE-CCP Empirical DE-CCP \n",
"0 0.990±0.002 0.990±0.002 \n",
"1 0.953±0.007 0.952±0.007 \n",
"2 0.908±0.009 0.906±0.009 \n",
"3 0.822±0.012 0.815±0.012 \n",
"4 0.735±0.014 0.722±0.009 \n",
"5 0.649±0.016 0.628±0.012 \n",
"6 0.553±0.012 0.531±0.011 \n",
"7 0.455±0.015 0.435±0.010 \n",
"8 0.351±0.012 0.338±0.014 \n",
"9 0.251±0.011 0.226±0.010 \n",
"10 0.131±0.012 0.114±0.011 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"validity_tbls[0] # Correlated(s)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\begin{tabular}{rlllll}\n",
"\\toprule\n",
"$1 - \\epsilon^g$ & Bonferroni & Max additive & Independent DE-CCP & Gumbel DE-CCP & Empirical DE-CCP \\\\\n",
"\\midrule\n",
"0.99 & 0.992±0.002 & 0.991±0.002 & 0.990±0.002 & 0.990±0.002 & 0.990±0.002 \\\\\n",
"0.95 & 0.960±0.006 & 0.947±0.007 & 0.955±0.006 & 0.953±0.007 & 0.952±0.007 \\\\\n",
"0.90 & 0.920±0.009 & 0.898±0.008 & 0.913±0.009 & 0.908±0.009 & 0.906±0.009 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n",
"\n"
]
}
],
"source": [
"print(validity_tbls[0][0:3].to_latex(index=False, float_format=\"{:.2f}\".format))"
]
},
{
"cell_type": "code",
"execution_count": null,
"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>$1 - \\epsilon^g$</th>\n",
" <th>Bonferroni</th>\n",
" <th>Max additive</th>\n",
" <th>Independent DE-CCP</th>\n",
" <th>Gumbel DE-CCP</th>\n",
" <th>Empirical DE-CCP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.99</td>\n",
" <td>0.990±0.002</td>\n",
" <td>0.991±0.002</td>\n",
" <td>0.987±0.002</td>\n",
" <td>0.988±0.003</td>\n",
" <td>0.987±0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.95</td>\n",
" <td>0.952±0.007</td>\n",
" <td>0.951±0.004</td>\n",
" <td>0.945±0.006</td>\n",
" <td>0.944±0.004</td>\n",
" <td>0.945±0.006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.90</td>\n",
" <td>0.902±0.008</td>\n",
" <td>0.902±0.006</td>\n",
" <td>0.892±0.007</td>\n",
" <td>0.892±0.008</td>\n",
" <td>0.894±0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.80</td>\n",
" <td>0.812±0.011</td>\n",
" <td>0.802±0.009</td>\n",
" <td>0.792±0.010</td>\n",
" <td>0.792±0.012</td>\n",
" <td>0.791±0.011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.70</td>\n",
" <td>0.729±0.013</td>\n",
" <td>0.703±0.012</td>\n",
" <td>0.691±0.011</td>\n",
" <td>0.690±0.010</td>\n",
" <td>0.688±0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.60</td>\n",
" <td>0.654±0.013</td>\n",
" <td>0.605±0.012</td>\n",
" <td>0.590±0.012</td>\n",
" <td>0.591±0.012</td>\n",
" <td>0.586±0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.50</td>\n",
" <td>0.585±0.013</td>\n",
" <td>0.504±0.013</td>\n",
" <td>0.490±0.011</td>\n",
" <td>0.491±0.011</td>\n",
" <td>0.488±0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.40</td>\n",
" <td>0.520±0.014</td>\n",
" <td>0.404±0.014</td>\n",
" <td>0.390±0.011</td>\n",
" <td>0.391±0.012</td>\n",
" <td>0.385±0.013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.30</td>\n",
" <td>0.463±0.009</td>\n",
" <td>0.301±0.015</td>\n",
" <td>0.294±0.010</td>\n",
" <td>0.291±0.010</td>\n",
" <td>0.265±0.047</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.20</td>\n",
" <td>0.408±0.010</td>\n",
" <td>0.202±0.012</td>\n",
" <td>0.193±0.008</td>\n",
" <td>0.190±0.008</td>\n",
" <td>0.176±0.024</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.10</td>\n",
" <td>0.358±0.011</td>\n",
" <td>0.100±0.008</td>\n",
" <td>0.093±0.005</td>\n",
" <td>0.092±0.006</td>\n",
" <td>0.090±0.008</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" $1 - \\epsilon^g$ Bonferroni Max additive Independent DE-CCP \\\n",
"0 0.99 0.990±0.002 0.991±0.002 0.987±0.002 \n",
"1 0.95 0.952±0.007 0.951±0.004 0.945±0.006 \n",
"2 0.90 0.902±0.008 0.902±0.006 0.892±0.007 \n",
"3 0.80 0.812±0.011 0.802±0.009 0.792±0.010 \n",
"4 0.70 0.729±0.013 0.703±0.012 0.691±0.011 \n",
"5 0.60 0.654±0.013 0.605±0.012 0.590±0.012 \n",
"6 0.50 0.585±0.013 0.504±0.013 0.490±0.011 \n",
"7 0.40 0.520±0.014 0.404±0.014 0.390±0.011 \n",
"8 0.30 0.463±0.009 0.301±0.015 0.294±0.010 \n",
"9 0.20 0.408±0.010 0.202±0.012 0.193±0.008 \n",
"10 0.10 0.358±0.011 0.100±0.008 0.093±0.005 \n",
"\n",
" Gumbel DE-CCP Empirical DE-CCP \n",
"0 0.988±0.003 0.987±0.003 \n",
"1 0.944±0.004 0.945±0.006 \n",
"2 0.892±0.008 0.894±0.009 \n",
"3 0.792±0.012 0.791±0.011 \n",
"4 0.690±0.010 0.688±0.010 \n",
"5 0.591±0.012 0.586±0.010 \n",
"6 0.491±0.011 0.488±0.010 \n",
"7 0.391±0.012 0.385±0.013 \n",
"8 0.291±0.010 0.265±0.047 \n",
"9 0.190±0.008 0.176±0.024 \n",
"10 0.092±0.006 0.090±0.008 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"validity_tbls[1] # uncorrelated(s)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\begin{tabular}{rlllll}\n",
"\\toprule\n",
"$1 - \\epsilon^g$ & Bonferroni & Max additive & Independent DE-CCP & Gumbel DE-CCP & Empirical DE-CCP \\\\\n",
"\\midrule\n",
"0.99 & 0.990±0.002 & 0.991±0.002 & 0.987±0.002 & 0.988±0.003 & 0.987±0.003 \\\\\n",
"0.95 & 0.952±0.007 & 0.951±0.004 & 0.945±0.006 & 0.944±0.004 & 0.945±0.006 \\\\\n",
"0.90 & 0.902±0.008 & 0.902±0.006 & 0.892±0.007 & 0.892±0.008 & 0.894±0.009 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n",
"\n"
]
}
],
"source": [
"print(validity_tbls[1][0:3].to_latex(index=False, float_format=\"{:.2f}\".format))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list index out of range",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mvalidity_tbls\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;66;03m# KITTI\u001b[39;00m\n",
"\u001b[0;31mIndexError\u001b[0m: list index out of range"
]
}
],
"source": [
"validity_tbls[2] # KITTI"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\begin{tabular}{rll}\n",
"\\toprule\n",
"$1 - \\epsilon^g$ & Max multiplicative & s.n. Empirical DE-CCP \\\\\n",
"\\midrule\n",
"0.95 & 0.948±0.003 & 0.945±0.008 \\\\\n",
"0.86 & 0.851±0.008 & 0.847±0.007 \\\\\n",
"0.76 & 0.759±0.011 & 0.752±0.010 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n",
"\n"
]
}
],
"source": [
"print(validity_tbls[2][0:3].to_latex(index=False, float_format=\"{:.2f}\".format))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Summarizing efficiency"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 1500x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"efficiency_tbls = SummaryReporter(approaches, filters, efficiency_score=hypercube_volumes).report(results, folds)"
]
},
{
"cell_type": "code",
"execution_count": null,
"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>$1 - \\epsilon^g$</th>\n",
" <th>Bonferroni</th>\n",
" <th>Max additive</th>\n",
" <th>Independent DE-CCP</th>\n",
" <th>Gumbel DE-CCP</th>\n",
" <th>Empirical DE-CCP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.99</td>\n",
" <td>1.15e+04±8.89e+02</td>\n",
" <td>1.62e+05±8.09e+03</td>\n",
" <td>1.09e+04±7.70e+02</td>\n",
" <td>1.06e+04±6.77e+02</td>\n",
" <td>1.05e+04±6.73e+02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.95</td>\n",
" <td>5.16e+03±1.88e+02</td>\n",
" <td>5.16e+04±2.93e+03</td>\n",
" <td>4.95e+03±1.91e+02</td>\n",
" <td>4.79e+03±1.68e+02</td>\n",
" <td>4.72e+03±1.69e+02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.90</td>\n",
" <td>3.29e+03±1.70e+02</td>\n",
" <td>2.59e+04±1.66e+03</td>\n",
" <td>3.14e+03±1.43e+02</td>\n",
" <td>3.01e+03±1.35e+02</td>\n",
" <td>2.96e+03±1.38e+02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.80</td>\n",
" <td>1.92e+03±8.06e+01</td>\n",
" <td>9.48e+03±6.74e+02</td>\n",
" <td>1.76e+03±6.94e+01</td>\n",
" <td>1.67e+03±6.08e+01</td>\n",
" <td>1.59e+03±5.80e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.70</td>\n",
" <td>1.31e+03±5.06e+01</td>\n",
" <td>4.10e+03±2.21e+02</td>\n",
" <td>1.13e+03±4.11e+01</td>\n",
" <td>1.06e+03±3.37e+01</td>\n",
" <td>9.88e+02±2.93e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.60</td>\n",
" <td>9.55e+02±3.53e+01</td>\n",
" <td>1.97e+03±1.06e+02</td>\n",
" <td>7.52e+02±2.46e+01</td>\n",
" <td>6.95e+02±2.22e+01</td>\n",
" <td>6.35e+02±1.88e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.50</td>\n",
" <td>7.20e+02±2.45e+01</td>\n",
" <td>1.02e+03±5.21e+01</td>\n",
" <td>5.05e+02±1.82e+01</td>\n",
" <td>4.61e+02±1.68e+01</td>\n",
" <td>4.14e+02±1.17e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.40</td>\n",
" <td>5.57e+02±1.93e+01</td>\n",
" <td>5.29e+02±2.28e+01</td>\n",
" <td>3.32e+02±1.33e+01</td>\n",
" <td>2.99e+02±1.09e+01</td>\n",
" <td>2.67e+02±1.03e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.30</td>\n",
" <td>4.40e+02±1.80e+01</td>\n",
" <td>2.76e+02±1.15e+01</td>\n",
" <td>2.07e+02±7.61e+00</td>\n",
" <td>1.83e+02±5.94e+00</td>\n",
" <td>1.60e+02±7.22e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.20</td>\n",
" <td>3.50e+02±1.38e+01</td>\n",
" <td>1.28e+02±5.52e+00</td>\n",
" <td>1.13e+02±3.59e+00</td>\n",
" <td>9.77e+01±3.26e+00</td>\n",
" <td>8.35e+01±4.03e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.10</td>\n",
" <td>2.81e+02±1.19e+01</td>\n",
" <td>4.30e+01±2.04e+00</td>\n",
" <td>4.61e+01±1.73e+00</td>\n",
" <td>3.83e+01±1.74e+00</td>\n",
" <td>3.22e+01±2.01e+00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" $1 - \\epsilon^g$ Bonferroni Max additive Independent DE-CCP \\\n",
"0 0.99 1.15e+04±8.89e+02 1.62e+05±8.09e+03 1.09e+04±7.70e+02 \n",
"1 0.95 5.16e+03±1.88e+02 5.16e+04±2.93e+03 4.95e+03±1.91e+02 \n",
"2 0.90 3.29e+03±1.70e+02 2.59e+04±1.66e+03 3.14e+03±1.43e+02 \n",
"3 0.80 1.92e+03±8.06e+01 9.48e+03±6.74e+02 1.76e+03±6.94e+01 \n",
"4 0.70 1.31e+03±5.06e+01 4.10e+03±2.21e+02 1.13e+03±4.11e+01 \n",
"5 0.60 9.55e+02±3.53e+01 1.97e+03±1.06e+02 7.52e+02±2.46e+01 \n",
"6 0.50 7.20e+02±2.45e+01 1.02e+03±5.21e+01 5.05e+02±1.82e+01 \n",
"7 0.40 5.57e+02±1.93e+01 5.29e+02±2.28e+01 3.32e+02±1.33e+01 \n",
"8 0.30 4.40e+02±1.80e+01 2.76e+02±1.15e+01 2.07e+02±7.61e+00 \n",
"9 0.20 3.50e+02±1.38e+01 1.28e+02±5.52e+00 1.13e+02±3.59e+00 \n",
"10 0.10 2.81e+02±1.19e+01 4.30e+01±2.04e+00 4.61e+01±1.73e+00 \n",
"\n",
" Gumbel DE-CCP Empirical DE-CCP \n",
"0 1.06e+04±6.77e+02 1.05e+04±6.73e+02 \n",
"1 4.79e+03±1.68e+02 4.72e+03±1.69e+02 \n",
"2 3.01e+03±1.35e+02 2.96e+03±1.38e+02 \n",
"3 1.67e+03±6.08e+01 1.59e+03±5.80e+01 \n",
"4 1.06e+03±3.37e+01 9.88e+02±2.93e+01 \n",
"5 6.95e+02±2.22e+01 6.35e+02±1.88e+01 \n",
"6 4.61e+02±1.68e+01 4.14e+02±1.17e+01 \n",
"7 2.99e+02±1.09e+01 2.67e+02±1.03e+01 \n",
"8 1.83e+02±5.94e+00 1.60e+02±7.22e+00 \n",
"9 9.77e+01±3.26e+00 8.35e+01±4.03e+00 \n",
"10 3.83e+01±1.74e+00 3.22e+01±2.01e+00 "
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"efficiency_tbls[0] # Correlated(s)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\begin{tabular}{rlllll}\n",
"\\toprule\n",
"$1 - \\epsilon^g$ & Bonferroni & Max additive & Independent DE-CCP & Gumbel DE-CCP & Empirical DE-CCP \\\\\n",
"\\midrule\n",
"0.99 & 1.15e+04±8.89e+02 & 1.62e+05±8.09e+03 & 1.09e+04±7.70e+02 & 1.06e+04±6.77e+02 & 1.05e+04±6.73e+02 \\\\\n",
"0.95 & 5.16e+03±1.88e+02 & 5.16e+04±2.93e+03 & 4.95e+03±1.91e+02 & 4.79e+03±1.68e+02 & 4.72e+03±1.69e+02 \\\\\n",
"0.90 & 3.29e+03±1.70e+02 & 2.59e+04±1.66e+03 & 3.14e+03±1.43e+02 & 3.01e+03±1.35e+02 & 2.96e+03±1.38e+02 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n",
"\n"
]
}
],
"source": [
"print(efficiency_tbls[0][0:3].to_latex(index=False, float_format=\"{:.2f}\".format))"
]
},
{
"cell_type": "code",
"execution_count": null,
"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>$1 - \\epsilon^g$</th>\n",
" <th>Bonferroni</th>\n",
" <th>Max additive</th>\n",
" <th>Independent DE-CCP</th>\n",
" <th>Gumbel DE-CCP</th>\n",
" <th>Empirical DE-CCP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.99</td>\n",
" <td>2.22e+03±3.86e+00</td>\n",
" <td>6.31e+04±3.43e+02</td>\n",
" <td>2.21e+03±4.39e+00</td>\n",
" <td>2.21e+03±4.07e+00</td>\n",
" <td>2.21e+03±3.45e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.95</td>\n",
" <td>2.13e+03±1.12e+01</td>\n",
" <td>5.34e+04±5.71e+02</td>\n",
" <td>2.12e+03±7.99e+00</td>\n",
" <td>2.12e+03±7.66e+00</td>\n",
" <td>2.12e+03±9.99e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.90</td>\n",
" <td>2.02e+03±7.93e+00</td>\n",
" <td>4.32e+04±4.71e+02</td>\n",
" <td>2.00e+03±1.07e+01</td>\n",
" <td>2.00e+03±1.03e+01</td>\n",
" <td>2.00e+03±1.04e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.80</td>\n",
" <td>1.82e+03±8.97e+00</td>\n",
" <td>2.69e+04±4.58e+02</td>\n",
" <td>1.78e+03±1.31e+01</td>\n",
" <td>1.77e+03±1.37e+01</td>\n",
" <td>1.77e+03±1.16e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.70</td>\n",
" <td>1.64e+03±1.63e+01</td>\n",
" <td>1.58e+04±5.22e+02</td>\n",
" <td>1.55e+03±1.22e+01</td>\n",
" <td>1.55e+03±1.24e+01</td>\n",
" <td>1.54e+03±1.73e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.60</td>\n",
" <td>1.47e+03±1.25e+01</td>\n",
" <td>8.51e+03±4.03e+02</td>\n",
" <td>1.32e+03±1.28e+01</td>\n",
" <td>1.32e+03±1.22e+01</td>\n",
" <td>1.31e+03±1.47e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.50</td>\n",
" <td>1.32e+03±1.51e+01</td>\n",
" <td>4.16e+03±2.30e+02</td>\n",
" <td>1.10e+03±1.32e+01</td>\n",
" <td>1.10e+03±1.45e+01</td>\n",
" <td>1.09e+03±1.33e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.40</td>\n",
" <td>1.17e+03±1.27e+01</td>\n",
" <td>1.72e+03±1.10e+02</td>\n",
" <td>8.72e+02±1.47e+01</td>\n",
" <td>8.71e+02±1.52e+01</td>\n",
" <td>8.60e+02±1.67e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.30</td>\n",
" <td>1.04e+03±1.41e+01</td>\n",
" <td>7.29e+02±3.50e+01</td>\n",
" <td>6.50e+02±1.29e+01</td>\n",
" <td>6.45e+02±1.45e+01</td>\n",
" <td>5.91e+02±9.97e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.20</td>\n",
" <td>9.17e+02±1.28e+01</td>\n",
" <td>4.50e+02±1.64e+01</td>\n",
" <td>4.27e+02±1.48e+01</td>\n",
" <td>4.24e+02±1.24e+01</td>\n",
" <td>3.90e+02±4.57e+01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.10</td>\n",
" <td>8.05e+02±1.48e+01</td>\n",
" <td>2.26e+02±1.38e+01</td>\n",
" <td>2.10e+02±8.30e+00</td>\n",
" <td>2.09e+02±7.72e+00</td>\n",
" <td>1.95e+02±8.93e+00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" $1 - \\epsilon^g$ Bonferroni Max additive Independent DE-CCP \\\n",
"0 0.99 2.22e+03±3.86e+00 6.31e+04±3.43e+02 2.21e+03±4.39e+00 \n",
"1 0.95 2.13e+03±1.12e+01 5.34e+04±5.71e+02 2.12e+03±7.99e+00 \n",
"2 0.90 2.02e+03±7.93e+00 4.32e+04±4.71e+02 2.00e+03±1.07e+01 \n",
"3 0.80 1.82e+03±8.97e+00 2.69e+04±4.58e+02 1.78e+03±1.31e+01 \n",
"4 0.70 1.64e+03±1.63e+01 1.58e+04±5.22e+02 1.55e+03±1.22e+01 \n",
"5 0.60 1.47e+03±1.25e+01 8.51e+03±4.03e+02 1.32e+03±1.28e+01 \n",
"6 0.50 1.32e+03±1.51e+01 4.16e+03±2.30e+02 1.10e+03±1.32e+01 \n",
"7 0.40 1.17e+03±1.27e+01 1.72e+03±1.10e+02 8.72e+02±1.47e+01 \n",
"8 0.30 1.04e+03±1.41e+01 7.29e+02±3.50e+01 6.50e+02±1.29e+01 \n",
"9 0.20 9.17e+02±1.28e+01 4.50e+02±1.64e+01 4.27e+02±1.48e+01 \n",
"10 0.10 8.05e+02±1.48e+01 2.26e+02±1.38e+01 2.10e+02±8.30e+00 \n",
"\n",
" Gumbel DE-CCP Empirical DE-CCP \n",
"0 2.21e+03±4.07e+00 2.21e+03±3.45e+00 \n",
"1 2.12e+03±7.66e+00 2.12e+03±9.99e+00 \n",
"2 2.00e+03±1.03e+01 2.00e+03±1.04e+01 \n",
"3 1.77e+03±1.37e+01 1.77e+03±1.16e+01 \n",
"4 1.55e+03±1.24e+01 1.54e+03±1.73e+01 \n",
"5 1.32e+03±1.22e+01 1.31e+03±1.47e+01 \n",
"6 1.10e+03±1.45e+01 1.09e+03±1.33e+01 \n",
"7 8.71e+02±1.52e+01 8.60e+02±1.67e+01 \n",
"8 6.45e+02±1.45e+01 5.91e+02±9.97e+01 \n",
"9 4.24e+02±1.24e+01 3.90e+02±4.57e+01 \n",
"10 2.09e+02±7.72e+00 1.95e+02±8.93e+00 "
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"efficiency_tbls[1] # Uncorrelated(s)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\\begin{tabular}{rlllll}\n",
"\\toprule\n",
"$1 - \\epsilon^g$ & Bonferroni & Max additive & Independent DE-CCP & Gumbel DE-CCP & Empirical DE-CCP \\\\\n",
"\\midrule\n",
"0.99 & 2.22e+03±3.86e+00 & 6.31e+04±3.43e+02 & 2.21e+03±4.39e+00 & 2.21e+03±4.07e+00 & 2.21e+03±3.45e+00 \\\\\n",
"0.95 & 2.13e+03±1.12e+01 & 5.34e+04±5.71e+02 & 2.12e+03±7.99e+00 & 2.12e+03±7.66e+00 & 2.12e+03±9.99e+00 \\\\\n",
"0.90 & 2.02e+03±7.93e+00 & 4.32e+04±4.71e+02 & 2.00e+03±1.07e+01 & 2.00e+03±1.03e+01 & 2.00e+03±1.04e+01 \\\\\n",
"\\bottomrule\n",
"\\end{tabular}\n",
"\n"
]
}
],
"source": [
"print(efficiency_tbls[1][0:3].to_latex(index=False, float_format=\"{:.2f}\".format))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{