tobias/entropice
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions
entropice/steps/s1_0_alphaearth/alphaearth.ipynb

645 lines
443 KiB
Text
Raw Normal View History

Restructure to steps
2025-10-21 18:42:01 +02:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "fc84c2a2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"PosixPath('/isipd/projects/p_aicore_pf/tohoel001/data/entropyc-rts')"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"from pathlib import Path\n",
"\n",
"import geopandas as gpd\n",
"import seaborn as sns\n",
"\n",
"DATA_DIR = Path(os.getenv(\"DATA_DIR\", \"../../data\")) / \"entropyc-rts\"\n",
"DATA_DIR"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "ba12e39e",
"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>cell_id</th>\n",
" <th>cell_area</th>\n",
" <th>geometry</th>\n",
" <th>water_area</th>\n",
" <th>land_area</th>\n",
" <th>land_ratio</th>\n",
" <th>A00_median</th>\n",
" <th>A00_stdDev</th>\n",
" <th>A00_min</th>\n",
" <th>A00_max</th>\n",
" <th>...</th>\n",
" <th>A63_stdDev</th>\n",
" <th>A63_min</th>\n",
" <th>A63_max</th>\n",
" <th>A63_mean</th>\n",
" <th>A63_p1</th>\n",
" <th>A63_p5</th>\n",
" <th>A63_p25</th>\n",
" <th>A63_p75</th>\n",
" <th>A63_p95</th>\n",
" <th>A63_p99</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>830018fffffffff</td>\n",
" <td>12833.417730</td>\n",
" <td>POLYGON ((1038231.032 93001.954, 1007144.142 1...</td>\n",
" <td>10600.837914</td>\n",
" <td>2232.579815</td>\n",
" <td>0.173966</td>\n",
" <td>-0.166336</td>\n",
" <td>0.006257</td>\n",
" <td>-0.172795</td>\n",
" <td>-0.153787</td>\n",
" <td>...</td>\n",
" <td>0.018647</td>\n",
" <td>0.228897</td>\n",
" <td>0.276140</td>\n",
" <td>0.256590</td>\n",
" <td>0.228897</td>\n",
" <td>0.228897</td>\n",
" <td>0.228897</td>\n",
" <td>0.276140</td>\n",
" <td>0.276140</td>\n",
" <td>0.276140</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>83001afffffffff</td>\n",
" <td>13005.383987</td>\n",
" <td>POLYGON ((1045152.586 212150.003, 1013846.955 ...</td>\n",
" <td>7494.831943</td>\n",
" <td>5510.552043</td>\n",
" <td>0.423713</td>\n",
" <td>-0.172795</td>\n",
" <td>0.008128</td>\n",
" <td>-0.186082</td>\n",
" <td>-0.166336</td>\n",
" <td>...</td>\n",
" <td>0.021743</td>\n",
" <td>0.192910</td>\n",
" <td>0.259900</td>\n",
" <td>0.232716</td>\n",
" <td>0.192910</td>\n",
" <td>0.192910</td>\n",
" <td>0.228897</td>\n",
" <td>0.244152</td>\n",
" <td>0.259900</td>\n",
" <td>0.259900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>83001cfffffffff</td>\n",
" <td>12607.559405</td>\n",
" <td>POLYGON ((1137527.559 33377.972, 1106995.284 9...</td>\n",
" <td>10141.598070</td>\n",
" <td>2465.961335</td>\n",
" <td>0.195594</td>\n",
" <td>-0.166336</td>\n",
" <td>0.005647</td>\n",
" <td>-0.179377</td>\n",
" <td>-0.166336</td>\n",
" <td>...</td>\n",
" <td>0.023313</td>\n",
" <td>0.228897</td>\n",
" <td>0.284444</td>\n",
" <td>0.250580</td>\n",
" <td>0.228897</td>\n",
" <td>0.228897</td>\n",
" <td>0.228897</td>\n",
" <td>0.259900</td>\n",
" <td>0.284444</td>\n",
" <td>0.284444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>83001efffffffff</td>\n",
" <td>12781.831078</td>\n",
" <td>POLYGON ((1144981.442 151688.88, 1114226.065 2...</td>\n",
" <td>11075.372042</td>\n",
" <td>1706.459036</td>\n",
" <td>0.133507</td>\n",
" <td>-0.166336</td>\n",
" <td>0.002797</td>\n",
" <td>-0.172795</td>\n",
" <td>-0.166336</td>\n",
" <td>...</td>\n",
" <td>0.017219</td>\n",
" <td>0.228897</td>\n",
" <td>0.276140</td>\n",
" <td>0.253232</td>\n",
" <td>0.228897</td>\n",
" <td>0.228897</td>\n",
" <td>0.244152</td>\n",
" <td>0.276140</td>\n",
" <td>0.276140</td>\n",
" <td>0.276140</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>830028fffffffff</td>\n",
" <td>11818.417986</td>\n",
" <td>POLYGON ((1106470.805 -427995.192, 1076828.817...</td>\n",
" <td>2728.182359</td>\n",
" <td>9090.235627</td>\n",
" <td>0.769158</td>\n",
" <td>-0.166336</td>\n",
" <td>0.026091</td>\n",
" <td>-0.172795</td>\n",
" <td>-0.113741</td>\n",
" <td>...</td>\n",
" <td>0.049976</td>\n",
" <td>0.172795</td>\n",
" <td>0.284444</td>\n",
" <td>0.195568</td>\n",
" <td>0.172795</td>\n",
" <td>0.172795</td>\n",
" <td>0.179377</td>\n",
" <td>0.199862</td>\n",
" <td>0.284444</td>\n",
" <td>0.284444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2755</th>\n",
" <td>8327b5fffffffff</td>\n",
" <td>12479.437618</td>\n",
" <td>POLYGON ((-3904533.281 -1950151.978, -3978391....</td>\n",
" <td>0.000000</td>\n",
" <td>12479.437618</td>\n",
" <td>1.000000</td>\n",
" <td>0.088827</td>\n",
" <td>0.016166</td>\n",
" <td>0.079723</td>\n",
" <td>0.119093</td>\n",
" <td>...</td>\n",
" <td>0.016595</td>\n",
" <td>0.103406</td>\n",
" <td>0.141730</td>\n",
" <td>0.117905</td>\n",
" <td>0.103406</td>\n",
" <td>0.103406</td>\n",
" <td>0.103406</td>\n",
" <td>0.141730</td>\n",
" <td>0.141730</td>\n",
" <td>0.141730</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2756</th>\n",
" <td>8327b6fffffffff</td>\n",
" <td>12148.179896</td>\n",
" <td>POLYGON ((-3999658.053 -1746829.203, -4072462....</td>\n",
" <td>0.000000</td>\n",
" <td>12148.179896</td>\n",
" <td>1.000000</td>\n",
" <td>0.088827</td>\n",
" <td>0.025067</td>\n",
" <td>0.044844</td>\n",
" <td>0.108512</td>\n",
" <td>...</td>\n",
" <td>0.026149</td>\n",
" <td>0.059116</td>\n",
" <td>0.135886</td>\n",
" <td>0.100635</td>\n",
" <td>0.059116</td>\n",
" <td>0.059116</td>\n",
" <td>0.103406</td>\n",
" <td>0.108512</td>\n",
" <td>0.108512</td>\n",
" <td>0.108512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2757</th>\n",
" <td>8328dbfffffffff</td>\n",
" <td>10331.135948</td>\n",
" <td>POLYGON ((-4304632.552 -720269.778, -4372252.4...</td>\n",
" <td>913.035656</td>\n",
" <td>9418.100291</td>\n",
" <td>0.911623</td>\n",
" <td>0.051734</td>\n",
" <td>0.039091</td>\n",
" <td>-0.007443</td>\n",
" <td>0.098424</td>\n",
" <td>...</td>\n",
" <td>0.029913</td>\n",
" <td>0.079723</td>\n",
" <td>0.153787</td>\n",
" <td>0.120128</td>\n",
" <td>0.079723</td>\n",
" <td>0.079723</td>\n",
" <td>0.119093</td>\n",
" <td>0.153787</td>\n",
" <td>0.153787</td>\n",
" <td>0.153787</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2758</th>\n",
" <td>832d69fffffffff</td>\n",
" <td>12395.223580</td>\n",
" <td>POLYGON ((4432070.553 -304743.386, 4485745.557...</td>\n",
" <td>0.000000</td>\n",
" <td>12395.223580</td>\n",
" <td>1.000000</td>\n",
" <td>-0.098424</td>\n",
" <td>0.007859</td>\n",
" <td>-0.103406</td>\n",
" <td>-0.084214</td>\n",
" <td>...</td>\n",
" <td>0.007772</td>\n",
" <td>0.079723</td>\n",
" <td>0.098424</td>\n",
" <td>0.087812</td>\n",
" <td>0.079723</td>\n",
" <td>0.079723</td>\n",
" <td>0.079723</td>\n",
" <td>0.098424</td>\n",
" <td>0.098424</td>\n",
" <td>0.098424</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2759</th>\n",
" <td>832d6dfffffffff</td>\n",
" <td>12148.179896</td>\n",
" <td>POLYGON ((4400410.65 -426345.057, 4453901.584 ...</td>\n",
" <td>0.000000</td>\n",
" <td>12148.179896</td>\n",
" <td>1.000000</td>\n",
" <td>-0.103406</td>\n",
" <td>0.002158</td>\n",
" <td>-0.103406</td>\n",
" <td>-0.098424</td>\n",
" <td>...</td>\n",
" <td>0.013049</td>\n",
" <td>0.093564</td>\n",
" <td>0.130165</td>\n",
" <td>0.113803</td>\n",
" <td>0.093564</td>\n",
" <td>0.093564</td>\n",
" <td>0.108512</td>\n",
" <td>0.130165</td>\n",
" <td>0.130165</td>\n",
" <td>0.130165</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2760 rows × 710 columns</p>\n",
"</div>"
],
"text/plain": [
" cell_id cell_area \\\n",
"0 830018fffffffff 12833.417730 \n",
"1 83001afffffffff 13005.383987 \n",
"2 83001cfffffffff 12607.559405 \n",
"3 83001efffffffff 12781.831078 \n",
"4 830028fffffffff 11818.417986 \n",
"... ... ... \n",
"2755 8327b5fffffffff 12479.437618 \n",
"2756 8327b6fffffffff 12148.179896 \n",
"2757 8328dbfffffffff 10331.135948 \n",
"2758 832d69fffffffff 12395.223580 \n",
"2759 832d6dfffffffff 12148.179896 \n",
"\n",
" geometry water_area \\\n",
"0 POLYGON ((1038231.032 93001.954, 1007144.142 1... 10600.837914 \n",
"1 POLYGON ((1045152.586 212150.003, 1013846.955 ... 7494.831943 \n",
"2 POLYGON ((1137527.559 33377.972, 1106995.284 9... 10141.598070 \n",
"3 POLYGON ((1144981.442 151688.88, 1114226.065 2... 11075.372042 \n",
"4 POLYGON ((1106470.805 -427995.192, 1076828.817... 2728.182359 \n",
"... ... ... \n",
"2755 POLYGON ((-3904533.281 -1950151.978, -3978391.... 0.000000 \n",
"2756 POLYGON ((-3999658.053 -1746829.203, -4072462.... 0.000000 \n",
"2757 POLYGON ((-4304632.552 -720269.778, -4372252.4... 913.035656 \n",
"2758 POLYGON ((4432070.553 -304743.386, 4485745.557... 0.000000 \n",
"2759 POLYGON ((4400410.65 -426345.057, 4453901.584 ... 0.000000 \n",
"\n",
" land_area land_ratio A00_median A00_stdDev A00_min A00_max \\\n",
"0 2232.579815 0.173966 -0.166336 0.006257 -0.172795 -0.153787 \n",
"1 5510.552043 0.423713 -0.172795 0.008128 -0.186082 -0.166336 \n",
"2 2465.961335 0.195594 -0.166336 0.005647 -0.179377 -0.166336 \n",
"3 1706.459036 0.133507 -0.166336 0.002797 -0.172795 -0.166336 \n",
"4 9090.235627 0.769158 -0.166336 0.026091 -0.172795 -0.113741 \n",
"... ... ... ... ... ... ... \n",
"2755 12479.437618 1.000000 0.088827 0.016166 0.079723 0.119093 \n",
"2756 12148.179896 1.000000 0.088827 0.025067 0.044844 0.108512 \n",
"2757 9418.100291 0.911623 0.051734 0.039091 -0.007443 0.098424 \n",
"2758 12395.223580 1.000000 -0.098424 0.007859 -0.103406 -0.084214 \n",
"2759 12148.179896 1.000000 -0.103406 0.002158 -0.103406 -0.098424 \n",
"\n",
" ... A63_stdDev A63_min A63_max A63_mean A63_p1 A63_p5 \\\n",
"0 ... 0.018647 0.228897 0.276140 0.256590 0.228897 0.228897 \n",
"1 ... 0.021743 0.192910 0.259900 0.232716 0.192910 0.192910 \n",
"2 ... 0.023313 0.228897 0.284444 0.250580 0.228897 0.228897 \n",
"3 ... 0.017219 0.228897 0.276140 0.253232 0.228897 0.228897 \n",
"4 ... 0.049976 0.172795 0.284444 0.195568 0.172795 0.172795 \n",
"... ... ... ... ... ... ... ... \n",
"2755 ... 0.016595 0.103406 0.141730 0.117905 0.103406 0.103406 \n",
"2756 ... 0.026149 0.059116 0.135886 0.100635 0.059116 0.059116 \n",
"2757 ... 0.029913 0.079723 0.153787 0.120128 0.079723 0.079723 \n",
"2758 ... 0.007772 0.079723 0.098424 0.087812 0.079723 0.079723 \n",
"2759 ... 0.013049 0.093564 0.130165 0.113803 0.093564 0.093564 \n",
"\n",
" A63_p25 A63_p75 A63_p95 A63_p99 \n",
"0 0.228897 0.276140 0.276140 0.276140 \n",
"1 0.228897 0.244152 0.259900 0.259900 \n",
"2 0.228897 0.259900 0.284444 0.284444 \n",
"3 0.244152 0.276140 0.276140 0.276140 \n",
"4 0.179377 0.199862 0.284444 0.284444 \n",
"... ... ... ... ... \n",
"2755 0.103406 0.141730 0.141730 0.141730 \n",
"2756 0.103406 0.108512 0.108512 0.108512 \n",
"2757 0.119093 0.153787 0.153787 0.153787 \n",
"2758 0.079723 0.098424 0.098424 0.098424 \n",
"2759 0.108512 0.130165 0.130165 0.130165 \n",
"\n",
"[2760 rows x 710 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grid = \"hex\"\n",
"level = 3\n",
"year = 2017\n",
"embs = gpd.read_parquet(DATA_DIR / \"embeddings\" / f\"permafrost_{grid}{level}_embeddings-{year}.parquet\")\n",
"embs"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "20d46465",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0x771f3c2ca9c0>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 600x600 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(data=embs, x=\"A00_median\", y=\"A03_median\", kind=\"hex\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "1964ffa9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A00: mean=-0.0697, spread=0.0385\n",
"A01: mean=-0.1440, spread=0.0377\n",
"A02: mean=-0.0625, spread=0.0529\n",
"A03: mean=-0.1933, spread=0.0452\n",
"A04: mean=-0.0144, spread=0.0408\n",
"A05: mean=-0.0815, spread=0.0519\n",
"A06: mean=-0.0489, spread=0.0426\n",
"A07: mean=0.2447, spread=0.0506\n",
"A08: mean=0.1384, spread=0.0394\n",
"A09: mean=0.0110, spread=0.0413\n",
"A10: mean=0.0941, spread=0.0655\n",
"A11: mean=0.0247, spread=0.0558\n",
"A12: mean=-0.0717, spread=0.0535\n",
"A13: mean=-0.0531, spread=0.0444\n",
"A14: mean=-0.2022, spread=0.0645\n",
"A15: mean=0.0798, spread=0.0664\n",
"A16: mean=0.0862, spread=0.0489\n",
"A17: mean=-0.0413, spread=0.0380\n",
"A18: mean=0.0210, spread=0.0562\n",
"A19: mean=-0.0051, spread=0.0406\n",
"A20: mean=0.1406, spread=0.0330\n",
"A21: mean=0.0182, spread=0.0697\n",
"A22: mean=0.0057, spread=0.0328\n",
"A23: mean=-0.1239, spread=0.0625\n",
"A24: mean=-0.0139, spread=0.0605\n",
"A25: mean=0.2142, spread=0.0671\n",
"A26: mean=-0.0223, spread=0.0574\n",
"A27: mean=0.0153, spread=0.0684\n",
"A28: mean=0.2022, spread=0.0477\n",
"A29: mean=-0.1456, spread=0.0720\n",
"A30: mean=0.0402, spread=0.0431\n",
"A31: mean=0.0337, spread=0.0799\n",
"A32: mean=0.0384, spread=0.0485\n",
"A33: mean=-0.0394, spread=0.0491\n",
"A34: mean=-0.0797, spread=0.0490\n",
"A35: mean=0.1106, spread=0.0530\n",
"A36: mean=0.1061, spread=0.0510\n",
"A37: mean=-0.0381, spread=0.0415\n",
"A38: mean=-0.0392, spread=0.0363\n",
"A39: mean=0.0324, spread=0.0407\n",
"A40: mean=-0.0252, spread=0.0574\n",
"A41: mean=-0.0208, spread=0.0676\n",
"A42: mean=-0.1557, spread=0.0613\n",
"A43: mean=0.0368, spread=0.0511\n",
"A44: mean=-0.0193, spread=0.0358\n",
"A45: mean=0.1510, spread=0.0448\n",
"A46: mean=0.0198, spread=0.0524\n",
"A47: mean=-0.1534, spread=0.0551\n",
"A48: mean=-0.0040, spread=0.0597\n",
"A49: mean=-0.0756, spread=0.0418\n",
"A50: mean=0.0878, spread=0.0506\n",
"A51: mean=-0.0490, spread=0.0379\n",
"A52: mean=-0.0406, spread=0.0465\n",
"A53: mean=-0.0721, spread=0.0380\n",
"A54: mean=0.0799, spread=0.0581\n",
"A55: mean=0.1076, spread=0.0549\n",
"A56: mean=0.0067, spread=0.0598\n",
"A57: mean=-0.0163, spread=0.0517\n",
"A58: mean=-0.0496, spread=0.0406\n",
"A59: mean=-0.0344, spread=0.0353\n",
"A60: mean=-0.1666, spread=0.0429\n",
"A61: mean=0.0667, spread=0.0655\n",
"A62: mean=0.0405, spread=0.0439\n",
"A63: mean=0.1079, spread=0.0614\n"
]
}
],
"source": [
"aggs = [\"median\", \"stdDev\", \"min\", \"max\", \"mean\", \"p1\", \"p5\", \"p25\", \"p75\", \"p95\", \"p99\"]\n",
"bands = [f\"A{str(i).zfill(2)}_{agg}\" for i in range(64) for agg in aggs]\n",
"\n",
"avg_embs = embs[bands].mean(axis=\"index\")\n",
"for i in range(64):\n",
" istr = str(i).zfill(2)\n",
" spread = avg_embs[f\"A{istr}_max\"] - avg_embs[f\"A{istr}_min\"]\n",
" print(f\"A{istr}: mean={avg_embs[f'A{istr}_mean']:.4f}, spread={spread:.4f}\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "1e132a67",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"embs.plot(\"A00_min\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "950ce47c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAaYAAAG+CAYAAADY9KD1AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs/Xe4LOlV34t/KnbOvbt3d++8T85xzoxGo0DmygYZG2Mw/hkMOAmMfX/29XW6fsAY7GvitS8YAwaLaAQmCxBCjGbmzMzJOYede8fenXOF+0f16eraPQoIac4Zqb7Pc57nVOiqt6p7v993rfVdawmmaZq4cOHChQsXzwjEpz0AFy5cuHDhYhAuMblw4cKFi2cKLjG5cOHChYtnCi4xuXDhwoWLZwouMblw4cKFi2cKLjG5cOHChYtnCi4xuXDhwoWLZwouMblw4cKFi2cKLjG5cOHChYtnCi4xuXDhwoWLZwrvGGJ65ZVX+Mt/+S+TzWYRBIHf/u3f/nNfwzRNfviHf5g9e/bg8XjI5XL8+3//7z//g3XhwoULF58z5Kc9gM8W9Xqdo0eP8nf+zt/hG77hGz6na3zv934vH/vYx/jhH/5hDh8+zPb2Ntvb25/nkbpw4cKFi78IhHdiEVdBEPit3/otPvjBD/b3tdtt/tW/+lf86q/+KqVSiUOHDvEf/+N/5H3vex8Ad+7c4ciRI9y8eZO9e/c+nYG7cOHChYvPiHeMK+8z4bu/+7t54403+LVf+zWuX7/ON37jN/I1X/M1PHjwAIDf+73fY2Zmht///d9nenqaqakpvvM7v9O1mFy4cOHiGcMXBTEtLi7y8z//83zkIx/hpZdeYnZ2ln/6T/8p7373u/n5n/95AB4/fszCwgIf+chH+PCHP8wv/MIvcOnSJf7aX/trT3n0Lly4cOFiEO+YGNOnw40bN9B1nT179jj2t9ttEokEAIZh0G63+fCHP9w/7+d+7uc4efIk9+7dc917Lly4cPGM4IuCmGq1GpIkcenSJSRJchwLBoMAZDIZZFl2kNf+/fsBy+JyicmFCxcung18URDT8ePH0XWdjY0NXnrppbc858UXX0TTNB49esTs7CwA9+/fB2BycvJtG6sLFy5cuPj0eMeo8mq1Gg8fPgQsIvrRH/1R3v/+9xOPx5mYmOBbv/VbOXv2LD/yIz/C8ePH2dzc5E//9E85cuQIH/jABzAMg9OnTxMMBvnxH/9xDMPgQx/6EOFwmI997GNP+elcuHDhwsUTvGOI6eWXX+b973//0P6//bf/Nr/wC79At9vlB37gB/jwhz/MysoKyWSS559/nu/7vu/j8OHDAOTzeb7ne76Hj33sYwQCAb72a7+WH/mRHyEej7/dj+PChQsXLj4F3jHE5MKFCxcuvjTwRSEXd+HChQsXXzxwicmFCxcuXDxTeKZVeYZhkM/nCYVCCILwtIfjwoULFy7+AjBNk2q1SjabRRQ/tV30TBNTPp9nfHz8aQ/DhQsXLlx8HrG0tMTY2NinPP5ME1MoFAKshwiHw095NC5cuHDh4i+CSqXC+Ph4f27/VHimiemJ+y4cDrvE5MKFCxdfJPhMoRlX/ODChQsXLp4puMTkwoULFy6eKbjE5MKFCxcunim4xOTChQsXLp4puMTkwoULFy6eKbjE5MKFCxcunim4xOTChQsXLp4puMTkwoULFy6eKbjE5MKFCxcunim4xOTChQsXLp4puMTkwoULFy6eKbjE5MKFCxcunim4xOTChQsXLp4pPNPVxV24eCei0mnxby7/AWAiCxL/cP9LzIaTjnMeV9c5u3kfjyST8kZ4X/rA0HU2m3V0w8AnKwQVFenTNFZz4eKLCS4xuXDxecYPXf8Yf7h8u7+92arxP97zrf1S/11D419f+588qK71z/nZ5/8eR2OT9meadb7qt3+OYrsJwDftPsJ/fPFrHfd5WF3jv9z7I4Kyl4jq53v2fi1eSXGcs9Ys09S6hFUvEcWHLEqf9+d14eLzDZeYXLj4NGh2u/zohbNohoEgCHzn0ZNkg87eYHeK63x8+QGSKGJi8pvz1xzH39yc5xcenGM8EEOVZK6XHjlICeA/3vpd/utz30VAVhEFgX/z5sf6pATwPx9c55t2H+FEKgeAZuh8/43f4G4l3z8novj5u7u/or9d7bb4lld+jrVmBYCvyu7nx5/7ps/Pi3Hh4gsIl5hcuPg0+OHzr/Fz1y/1t1drFX7qq7++v93WNb737G/zsFLo7zuUGOXuAPFkfGF+9ObLtHQNgL3R+NB9RFPiyK/8OCCgCCKz0cTQOf/19usE5k0CsgefLDlICeDDc69wPDZF0hsmJHv58duf6JMSwMfyd3h94xHvSs3+ud+DCxdvJ1xicuHiU+BeYZP/PkBKAH/4+AG/ce8G2WAYQRD45OpDBykBlFodsr4wOiaarhOSveQbVfu6pW1eyk1xozwPgF/ycH9NA3quPtOgqXWRBAHdNAHIBsKcL9+jU7LITQD2xlIsNzf61x33J/jQxf/e3z4Unhl6pv9+9zy/+eAuMY+Pw4lRvn56OLZlmCbiZ+gw6sLFFxIuMblw8SkwFY0xFYkxVy7292UCQf7N2Y/T1CyC2J8YwTRhcB5P+YNcLy/2t3OB2NC1220vQjeOKkrElSBX6wWeEBPAQrXEuzOTtHUdQRBQVI0r1fX+cRMwdZVxf5KW3kUzNOpay3GPx/UVYqqXYsfaH5X9nM+vU+lYY5MFkQOxFLujtjDjVmGdD/7OLxNUVRJePz/15V/P7pjTeltr5ekabcJKlJAcQRRcUYaLzy/cX5QLF58CHknm+1768oE9JjG/r09KAHcKmxyPjvW3Yx4f840NBrHaKOOV7DXgnvAIF7YWKbZbrDfr3CyucyaXc3zmVCrHa6sLXNhY5vz6EvlyC8F0WjExr4e52jarzSrbnTbCjj/nht7mcGyUo7ExTsYn2O0fp9Jp949rpsH3nf84pVYTwzTpGjr/9JU/omPobLeaPCgV+P43P4HZs9oAqt0KP3H/+/m/7/5r/vWN7+Y3lj/82b9QFy4+S7gWkwsXnwYdQ8OUrYlZALqmPnSOZMgE9CCSIDAiBpnrrAwaPxTadQ5HxmgaXSRBJKSqmDuusdos8Xy4p8oT4HbRKY6YqxR59/gsS501WnqXtC/IjfJC/7huGgRkP6ZZ7Ftv+8JjvLI+x5PBJNUQXknux7oAOl2DYx/+L4iCwGggREVrD96WV1bm+bW5V5kIR4gqIc4VPkpNs92Sr21+nHcnv4ysb+KzeJsuXHx2cInJhYtPgXK7xb88+yd9kjGxrAyh93+wXHnn12wiKrZaPD8+xZXqXP86J+KTnNtY6m/HVC8BWaWudfr7RloJLizbYoZT01nODRCPKAhsdaqsNxvW+V4Bw3TS20J9i+PxMQQBREFktdphkCG3OlVOju7ibqFIpdMi6Qlyfc1yDxqmSb5W4fRojvMbK/Y4xsJ8ePk3+9unByTt1jsx+eO1/0VcjRJWYuwJHiHnn/70L9aFi88Al5hcuPgUuLi+wnqj5tg3VylxJj1OW9cQBJAk0WEdAayVmxyPTCMAgiBwvbDiOF7stHhpdIq63sYwTfyal9dvOy2kuytbpBNBNto1TOC5TJartcf94w8r27wwOsm10nx/36Fomju1R/3t/aEp7tuiPEwTGmaLilDGVCHsD7NWtK0ngOuba7wwOoaGSUfXCUQf07D5k6ulFfaHkzT0LQBiSoJ7lYtodAF4U/1T/tneH0EWnflULlz8eeASkwsXnwJfNj7D86PjvLlmWztnUmOcW1nub2eDIRRBpGsavT0mQa/CuVWbjM5kxrhYtK0fnyRzv1hgrWm5xCKyl5BHpdq2GSCgqpSFMig6XklCkIZdiLWOxtHoBKIgoIoyNyq3GSwOcac6z6nkLI8qFardFgejY1zctKwyQYDHjU1OZae5kLcttaPpDG8MWHdfl0myyXZ/u2tqNDv70fQmIVXAL3ZpGLYoo9BZ55Wtj/JlKVtS78LFnxeCaZo73d3PDCqVCpFIhHK5TDgc/swfcOHi84zz64v8yLVPYmIiInJ
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"embs.plot(\"A00_max\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2c31bcb5",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "entropic-perma-risk",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Reference in a new issue Copy permalink