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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import pandas as pd\n",
"import pywt\n",
"import seaborn as sns\n",
"import scaleogram as scg \n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.gridspec as GridSpec\n",
"from mat4py import loadmat\n",
"from scipy.fftpack import fft\n",
"import wfdb\n",
"import re\n",
"from math import *\n",
"import plotly.express as px"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"sample_size=5000"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Read source for create a dataset of annotations\n",
"Source : https://physionet.org/content/butqdb/1.0.0/"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"../aura-data/100001/100001_ECG\r",
"../aura-data/100002/100002_ECG\r",
"../aura-data/103001/103001_ECG\r",
"../aura-data/103002/103002_ECG\r",
"../aura-data/103003/103003_ECG\r",
"../aura-data/104001/104001_ECG\r",
"../aura-data/105001/105001_ECG\r",
"../aura-data/111001/111001_ECG\r",
"../aura-data/113001/113001_ECG\r",
"../aura-data/114001/114001_ECG\r",
"../aura-data/115001/115001_ECG\r",
"../aura-data/118001/118001_ECG\r",
"../aura-data/121001/121001_ECG\r",
"../aura-data/122001/122001_ECG\r",
"../aura-data/123001/123001_ECG\r",
"../aura-data/124001/124001_ECG\r",
"../aura-data/125001/125001_ECG\r",
"../aura-data/126001/126001_ECG\r"
]
}
],
"source": [
"# source wfdb\n",
"header_list = [\"start1\", \"end1\", \"class1\",\"start2\", \"end2\", \"class2\",\"start3\", \"end3\", \"class3\",\"start\", \"end\", \"class\"]\n",
"record_list = wfdb.get_record_list('butqdb')\n",
"dataannall = pd.DataFrame(columns=header_list)\n",
"for rcd in record_list:\n",
" if re.search(r'ECG$', rcd):\n",
" record_name = f\"../aura-data/{rcd}\"\n",
" print(record_name, end=\"\\r\")\n",
" record_csv = f\"../aura-data/{rcd.replace('ECG','ANN')}.csv\"\n",
" dataann = pd.read_csv(record_csv, names=header_list)\n",
" dataannall = pd.concat([dataannall,dataann.assign(record=rcd.split('/')[0])], ignore_index=True)\n",
"#Add columns to dataset\n",
"dataannall['signal_length']=dataannall['end'] - dataannall['start']\n",
"dataannall[\"sample\"]=round(dataannall[\"signal_length\"]/sample_size)\n",
"dataannall[\"class1\"].fillna(0, inplace=True)\n",
"dataannall[\"class2\"].fillna(0, inplace=True)\n",
"dataannall[\"class3\"].fillna(0, inplace=True)\n",
"dataannall[\"class\"].fillna(0, inplace=True)\n",
"dataannall=dataannall.astype({'class1': 'int32','class2': 'int32','class3': 'int32','class': 'int32'})\n",
"dataset = dataannall[dataannall[\"class\"].notnull() & dataannall[\"start\"].notnull() & dataannall[\"end\"].notnull() ]\n",
"dataann_nan_class = dataset\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"start1 float64\n",
"end1 float64\n",
"class1 int32\n",
"start2 float64\n",
"end2 float64\n",
"class2 int32\n",
"start3 object\n",
"end3 object\n",
"class3 int32\n",
"start float64\n",
"end float64\n",
"class int32\n",
"record object\n",
"signal_length float64\n",
"sample float64\n",
"dtype: object"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataannall.dtypes"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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"<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>start1</th>\n",
" <th>end1</th>\n",
" <th>class1</th>\n",
" <th>start2</th>\n",
" <th>end2</th>\n",
" <th>class2</th>\n",
" <th>start3</th>\n",
" <th>end3</th>\n",
" <th>class3</th>\n",
" <th>start</th>\n",
" <th>end</th>\n",
" <th>class</th>\n",
" <th>record</th>\n",
" <th>signal_length</th>\n",
" <th>sample</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1.0</td>\n",
" <td>198867.0</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>19525.0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>7047</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>7047.0</td>\n",
" <td>2</td>\n",
" <td>100001</td>\n",
" <td>7046.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>198868.0</td>\n",
" <td>320282.0</td>\n",
" <td>1</td>\n",
" <td>19526.0</td>\n",
" <td>28694.0</td>\n",
" <td>2</td>\n",
" <td>7048</td>\n",
" <td>17209</td>\n",
" <td>1</td>\n",
" <td>7048.0</td>\n",
" <td>17209.0</td>\n",
" <td>1</td>\n",
" <td>100001</td>\n",
" <td>10161.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>320283.0</td>\n",
" <td>373109.0</td>\n",
" <td>2</td>\n",
" <td>28695.0</td>\n",
" <td>32739.0</td>\n",
" <td>1</td>\n",
" <td>17210</td>\n",
" <td>28390</td>\n",
" <td>2</td>\n",
" <td>17210.0</td>\n",
" <td>28694.0</td>\n",
" <td>2</td>\n",
" <td>100001</td>\n",
" <td>11484.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>373110.0</td>\n",
" <td>2197974.0</td>\n",
" <td>1</td>\n",
" <td>32740.0</td>\n",
" <td>96699.0</td>\n",
" <td>2</td>\n",
" <td>28391</td>\n",
" <td>32653</td>\n",
" <td>1</td>\n",
" <td>28695.0</td>\n",
" <td>32653.0</td>\n",
" <td>1</td>\n",
" <td>100001</td>\n",
" <td>3958.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2197975.0</td>\n",
" <td>2582746.0</td>\n",
" <td>2</td>\n",
" <td>96700.0</td>\n",
" <td>110564.0</td>\n",
" <td>1</td>\n",
" <td>32654</td>\n",
" <td>71061</td>\n",
" <td>2</td>\n",
" <td>32654.0</td>\n",
" <td>112474.0</td>\n",
" <td>2</td>\n",
" <td>100001</td>\n",
" <td>79820.0</td>\n",
" <td>16.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" start1 end1 class1 start2 end2 class2 start3 end3 \\\n",
"0 1.0 198867.0 2 1.0 19525.0 1 1 7047 \n",
"1 198868.0 320282.0 1 19526.0 28694.0 2 7048 17209 \n",
"2 320283.0 373109.0 2 28695.0 32739.0 1 17210 28390 \n",
"3 373110.0 2197974.0 1 32740.0 96699.0 2 28391 32653 \n",
"4 2197975.0 2582746.0 2 96700.0 110564.0 1 32654 71061 \n",
"\n",
" class3 start end class record signal_length sample \n",
"0 2 1.0 7047.0 2 100001 7046.0 1.0 \n",
"1 1 7048.0 17209.0 1 100001 10161.0 2.0 \n",
"2 2 17210.0 28694.0 2 100001 11484.0 2.0 \n",
"3 1 28695.0 32653.0 1 100001 3958.0 1.0 \n",
"4 2 32654.0 112474.0 2 100001 79820.0 16.0 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataannall.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Try to score the operator notation"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Choix opérateur 1 dans choix final \t\t: 1179\t/ 7104\t16.6%\n",
"Choix opérateur 2 dans choix final \t\t: 2694\t/ 7104\t37.92%\n",
"Choix opérateur 2 dans choix final \t\t: 2421\t/ 7104\t34.08%\n",
"Choix opérateur 1 & 2 dans choix final \t\t: 601\t/ 7104\t8.46%\n",
"Choix opérateur 1 & 3 dans choix final \t\t: 458\t/ 7104\t6.45%\n",
"Choix opérateur 2 & 3 dans choix final \t\t: 1072\t/ 7104\t15.09%\n",
"Choix opérateur 1 & 2 & 3 dans choix final \t: 297\t/ 7104\t4.18%\n"
]
}
],
"source": [
"#dataannall['class_vote'] = \n",
"class1_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class12_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class1'] == dataannall['class2']) & (dataannall['class'] > 0)])\n",
"class13_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class1'] == dataannall['class3']) & (dataannall['class'] > 0)])\n",
"class2_ds_f = len(dataannall[(dataannall['class2'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class23_ds_f = len(dataannall[(dataannall['class2'] == dataannall['class']) & (dataannall['class2'] == dataannall['class3']) & (dataannall['class'] > 0)])\n",
"class3_ds_f = len(dataannall[(dataannall['class3'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class123_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class2']) & (dataannall['class3'] == dataannall['class1']) & (dataannall['class3'] == dataannall['class2']) & (dataannall['class'] > 0)])\n",
"class_f = len(dataannall[(dataannall['class'] > 0)])\n",
"\n",
"print(f\"Choix opérateur 1 dans choix final \\t\\t: {class1_ds_f}\\t/ {class_f}\\t{round(class1_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 2 dans choix final \\t\\t: {class2_ds_f}\\t/ {class_f}\\t{round(class2_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 2 dans choix final \\t\\t: {class3_ds_f}\\t/ {class_f}\\t{round(class3_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 2 dans choix final \\t\\t: {class12_ds_f}\\t/ {class_f}\\t{round(class12_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 3 dans choix final \\t\\t: {class13_ds_f}\\t/ {class_f}\\t{round(class13_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 2 & 3 dans choix final \\t\\t: {class23_ds_f}\\t/ {class_f}\\t{round(class23_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 2 & 3 dans choix final \\t: {class123_ds_f}\\t/ {class_f}\\t{round(class123_ds_f*100/class_f,2)}%\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3495"
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},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dataannall[dataannall['record'] == '105001'].index)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
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},
{
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"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"start1 139120080.0\n",
"end1 139147000.0\n",
"class1 3.0\n",
"start2 139146833.0\n",
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"sample 9465.0\n",
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"metadata": {},
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"source": [
"df = dataannall[(dataannall['record'] == '105001')]\n",
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"cell_type": "code",
"execution_count": 15,
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{
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{\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('580ea623-afc7-4077-ba62-da3d0e6cb3d7');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; }); </script> </div>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.graph_objects as go\n",
"df = dataannall[(dataannall['record'] == '105001') & (dataannall['start'] > 20000000)]\n",
"fig = go.Figure()\n",
"fig.add_trace(go.Scatter(x=df['end1'],\n",
" y=df['class1'], name=\"Ope1\",\n",
" line_shape='hv'))\n",
"fig.add_trace(go.Scatter(x=df['end2'],\n",
" y=df['class2'], name=\"Ope2\",\n",
" line_shape='hv'))\n",
"fig.add_trace(go.Scatter(x=df['end3'],\n",
" y=df['class3'], name=\"Op3\",\n",
" line_shape='hv'))\n",
"fig.add_trace(go.Scatter(x=df['end'],\n",
" y=df['class'], name=\"Quorum\",\n",
" line_shape='hv'))\n",
"\"\"\"fig.add_trace(go.Scatter(x=x, y=y + 15, name=\"hvh\",\n",
" line_shape='hvh'))\n",
"fig.add_trace(go.Scatter(x=x, y=y + 20, name=\"vh\",\n",
" line_shape='vh'))\n",
"fig.add_trace(go.Scatter(x=x, y=y + 25, name=\"hv\",\n",
" line_shape='hv'))\n",
"\n",
"fig.update_traces(hoverinfo='text+name', mode='lines+markers')\n",
"fig.update_layout(legend=dict(y=0.5, traceorder='reversed', font_size=16))\n",
"\"\"\"\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Check if it's continous notations"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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"nan : nan - nan : nan - 138190752 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138221087 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138222512 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138263647 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138265520 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138285439 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138292784 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138373295 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138375392 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138484351 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138492208 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138506607 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138511584 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138532159 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138534608 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138567743 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138569616 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138583855 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138585536 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138596895 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138599600 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138671119 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138672192 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138701135 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138702736 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138712623 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138716976 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138721439 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138722208 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138725871 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138728832 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138732303 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138735584 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138761823 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138763264 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138768511 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138770560 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138780671 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138783504 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138858703 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138862336 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138875135 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138876448 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138882847 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138885920 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138891103 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138892768 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138907087 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138909568 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138936959 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138938080 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138941647 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138942512 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138956319 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138968832 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138971247 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138973168 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138989039 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 138997600 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139035183 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139036496 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139042847 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139043904 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139045551 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139046208 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139047455 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139048240 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139052575 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139056448 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139057567 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139060224 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139064655 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139068304 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139081887 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139085248 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139102207 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139102896 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139106239 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139108128 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139116479 : 0 - nan : nan -\n",
"nan : nan - nan : nan - 139147000 : 139147000 - nan : nan -\n"
]
}
],
"source": [
"for i in dataannall[dataannall['record'] == '105001'].index:\n",
" ope1=f\"{dataannall['end1'][i]} : {dataannall['end1'][i]-dataannall['start1'][i+1]+1}\"\n",
" ope2=f\"{dataannall['end2'][i]} : {dataannall['end2'][i]-dataannall['start2'][i+1]+1}\"\n",
" ope3=f\"{dataannall['end3'][i]} : {dataannall['end3'][i]-dataannall['start3'][i+1]+1}\"\n",
" final=f\"{dataannall['end'][i]} : {dataannall['end'][i]-dataannall['start'][i+1]+1}\"\n",
" print(f\"{ope1} - {ope2} - {ope3} - {final} -\")"
]
},
{
"cell_type": "code",
"execution_count": 167,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" .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>start1</th>\n",
" <th>end1</th>\n",
" <th>class1</th>\n",
" <th>start2</th>\n",
" <th>end2</th>\n",
" <th>class2</th>\n",
" <th>start</th>\n",
" <th>end</th>\n",
" <th>class</th>\n",
" <th>signal_length</th>\n",
" <th>sample</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>2.076000e+03</td>\n",
" <td>2.076000e+03</td>\n",
" <td>2076.000000</td>\n",
" <td>4.305000e+03</td>\n",
" <td>4.305000e+03</td>\n",
" <td>4305.000000</td>\n",
" <td>7.154000e+03</td>\n",
" <td>7.154000e+03</td>\n",
" <td>7154.000000</td>\n",
" <td>7.154000e+03</td>\n",
" <td>7154.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>5.735894e+07</td>\n",
" <td>5.817328e+07</td>\n",
" <td>1.748073</td>\n",
" <td>5.950179e+07</td>\n",
" <td>5.987307e+07</td>\n",
" <td>1.572590</td>\n",
" <td>5.601431e+07</td>\n",
" <td>5.625521e+07</td>\n",
" <td>1.604417</td>\n",
" <td>2.409030e+05</td>\n",
" <td>48.144255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.225315e+07</td>\n",
" <td>3.202552e+07</td>\n",
" <td>0.731805</td>\n",
" <td>3.072217e+07</td>\n",
" <td>3.057915e+07</td>\n",
" <td>0.603114</td>\n",
" <td>2.802337e+07</td>\n",
" <td>2.796447e+07</td>\n",
" <td>0.609641</td>\n",
" <td>2.530322e+06</td>\n",
" <td>506.072488</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000e+00</td>\n",
" <td>1.988670e+05</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.952500e+04</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>7.047000e+03</td>\n",
" <td>0.000000</td>\n",
" <td>3.020000e+02</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2.961164e+07</td>\n",
" <td>2.970962e+07</td>\n",
" <td>1.000000</td>\n",
" <td>3.180192e+07</td>\n",
" <td>3.216237e+07</td>\n",
" <td>1.000000</td>\n",
" <td>3.405290e+07</td>\n",
" <td>3.411941e+07</td>\n",
" <td>1.000000</td>\n",
" <td>2.264250e+03</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>5.676074e+07</td>\n",
" <td>5.760000e+07</td>\n",
" <td>2.000000</td>\n",
" <td>5.791413e+07</td>\n",
" <td>5.792801e+07</td>\n",
" <td>2.000000</td>\n",
" <td>5.507225e+07</td>\n",
" <td>5.570303e+07</td>\n",
" <td>2.000000</td>\n",
" <td>5.853000e+03</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>7.522529e+07</td>\n",
" <td>7.664065e+07</td>\n",
" <td>2.000000</td>\n",
" <td>7.722608e+07</td>\n",
" <td>7.766738e+07</td>\n",
" <td>2.000000</td>\n",
" <td>6.858724e+07</td>\n",
" <td>6.945778e+07</td>\n",
" <td>2.000000</td>\n",
" <td>1.982150e+04</td>\n",
" <td>4.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>1.391201e+08</td>\n",
" <td>1.391470e+08</td>\n",
" <td>3.000000</td>\n",
" <td>1.391468e+08</td>\n",
" <td>1.391470e+08</td>\n",
" <td>3.000000</td>\n",
" <td>1.391201e+08</td>\n",
" <td>1.391470e+08</td>\n",
" <td>3.000000</td>\n",
" <td>7.464800e+07</td>\n",
" <td>14930.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" start1 end1 class1 start2 end2 \\\n",
"count 2.076000e+03 2.076000e+03 2076.000000 4.305000e+03 4.305000e+03 \n",
"mean 5.735894e+07 5.817328e+07 1.748073 5.950179e+07 5.987307e+07 \n",
"std 3.225315e+07 3.202552e+07 0.731805 3.072217e+07 3.057915e+07 \n",
"min 1.000000e+00 1.988670e+05 0.000000 1.000000e+00 1.952500e+04 \n",
"25% 2.961164e+07 2.970962e+07 1.000000 3.180192e+07 3.216237e+07 \n",
"50% 5.676074e+07 5.760000e+07 2.000000 5.791413e+07 5.792801e+07 \n",
"75% 7.522529e+07 7.664065e+07 2.000000 7.722608e+07 7.766738e+07 \n",
"max 1.391201e+08 1.391470e+08 3.000000 1.391468e+08 1.391470e+08 \n",
"\n",
" class2 start end class signal_length \\\n",
"count 4305.000000 7.154000e+03 7.154000e+03 7154.000000 7.154000e+03 \n",
"mean 1.572590 5.601431e+07 5.625521e+07 1.604417 2.409030e+05 \n",
"std 0.603114 2.802337e+07 2.796447e+07 0.609641 2.530322e+06 \n",
"min 0.000000 1.000000e+00 7.047000e+03 0.000000 3.020000e+02 \n",
"25% 1.000000 3.405290e+07 3.411941e+07 1.000000 2.264250e+03 \n",
"50% 2.000000 5.507225e+07 5.570303e+07 2.000000 5.853000e+03 \n",
"75% 2.000000 6.858724e+07 6.945778e+07 2.000000 1.982150e+04 \n",
"max 3.000000 1.391201e+08 1.391470e+08 3.000000 7.464800e+07 \n",
"\n",
" sample \n",
"count 7154.000000 \n",
"mean 48.144255 \n",
"std 506.072488 \n",
"min 0.000000 \n",
"25% 0.000000 \n",
"50% 1.000000 \n",
"75% 4.000000 \n",
"max 14930.000000 "
]
},
"execution_count": 167,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.describe()"
]
},
{
"cell_type": "code",
"execution_count": 168,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"\n",
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" }\n",
"</style>\n",
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" <th></th>\n",
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" <th>end1</th>\n",
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" <th>class3</th>\n",
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" <th>end</th>\n",
" <th>class</th>\n",
" <th>record</th>\n",
" <th>signal_length</th>\n",
" <th>sample</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2164</th>\n",
" <td>29830121.0</td>\n",
" <td>29843829.0</td>\n",
" <td>2.0</td>\n",
" <td>29833497.0</td>\n",
" <td>29842799.0</td>\n",
" <td>2.0</td>\n",
" <td>29041071</td>\n",
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" <td>2</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>6902</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>22772239</td>\n",
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" <td>1</td>\n",
" <td>42187296.0</td>\n",
" <td>42187599.0</td>\n",
" <td>2.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>14215</th>\n",
" <td>57653762.0</td>\n",
" <td>57664665.0</td>\n",
" <td>1.0</td>\n",
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" <td>1.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>1961</th>\n",
" <td>29896114.0</td>\n",
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" <tr>\n",
" <th>14982</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>65811759.0</td>\n",
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" <td>3.0</td>\n",
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" <td>58414129</td>\n",
" <td>1</td>\n",
" <td>65500416.0</td>\n",
" <td>65500737.0</td>\n",
" <td>2.0</td>\n",
" <td>124001</td>\n",
" <td>321.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15543</th>\n",
" <td>57711177.0</td>\n",
" <td>57779132.0</td>\n",
" <td>1.0</td>\n",
" <td>29622202.0</td>\n",
" <td>29624040.0</td>\n",
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" <td>1.0</td>\n",
" <td>126001</td>\n",
" <td>322.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2087</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>103003</td>\n",
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" <td>0.0</td>\n",
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" <tr>\n",
" <th>1347</th>\n",
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" <td>2.0</td>\n",
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" <td>2</td>\n",
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" <td>2.0</td>\n",
" <td>100002</td>\n",
" <td>328.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15582</th>\n",
" <td>NaN</td>\n",
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" <td>2.0</td>\n",
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" <tr>\n",
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" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" start1 end1 class1 start2 end2 class2 \\\n",
"2164 29830121.0 29843829.0 2.0 29833497.0 29842799.0 2.0 \n",
"6902 NaN NaN NaN NaN NaN NaN \n",
"14215 57653762.0 57664665.0 1.0 29052794.0 29058124.0 1.0 \n",
"1961 29896114.0 29909814.0 1.0 29430978.0 29432026.0 2.0 \n",
"14982 NaN NaN NaN 65811759.0 65824014.0 3.0 \n",
"15543 57711177.0 57779132.0 1.0 29622202.0 29624040.0 1.0 \n",
"2087 NaN NaN NaN NaN NaN NaN \n",
"1347 NaN NaN NaN 29422321.0 29423807.0 2.0 \n",
"15582 NaN NaN NaN 57917191.0 57917810.0 2.0 \n",
"14943 NaN NaN NaN 65570247.0 65579982.0 1.0 \n",
"\n",
" start3 end3 class3 start end class record \\\n",
"2164 29041071 29041373 2 29041071.0 29041373.0 2.0 104001 \n",
"6902 22772239 22806837 1 42187296.0 42187599.0 2.0 111001 \n",
"14215 28815944 28816279 1 28871845.0 28872149.0 1.0 121001 \n",
"1961 29201971 29203041 2 29367658.0 29367979.0 2.0 103003 \n",
"14982 58413007 58414129 1 65500416.0 65500737.0 2.0 124001 \n",
"15543 28902711 29014385 1 29637312.0 29637634.0 1.0 126001 \n",
"2087 29712177 29713943 2 29974330.0 29974654.0 2.0 103003 \n",
"1347 2.95904e+07 2.95909e+07 2 29583767.0 29584095.0 2.0 100002 \n",
"15582 57655491 57655835 2 58410626.0 58410956.0 2.0 126001 \n",
"14943 58189527 58190516 2 65289466.0 65289798.0 2.0 124001 \n",
"\n",
" signal_length sample \n",
"2164 302.0 0.0 \n",
"6902 303.0 0.0 \n",
"14215 304.0 0.0 \n",
"1961 321.0 0.0 \n",
"14982 321.0 0.0 \n",
"15543 322.0 0.0 \n",
"2087 324.0 0.0 \n",
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"14943 332.0 0.0 "
]
},
"execution_count": 168,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.sort_values(by=['signal_length']).head(10)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
" start1 end1 class1 start2 end2 class2 \\\n",
"14558 NaN NaN NaN NaN NaN NaN \n",
"14419 NaN NaN NaN NaN NaN NaN \n",
"2299 1.0 47323379.0 3.0 1.0 47323871.0 3.0 \n",
"15596 NaN NaN NaN 58407654.0 58408005.0 2.0 \n",
"13716 57600001.0 58800000.0 1.0 29389929.0 29392545.0 2.0 \n",
"14375 NaN NaN NaN NaN NaN NaN \n",
"13539 NaN NaN NaN NaN NaN NaN \n",
"14073 NaN NaN NaN 58800001.0 89091000.0 0.0 \n",
"13892 NaN NaN NaN NaN NaN NaN \n",
"13949 1.0 28800000.0 0.0 1.0 28800000.0 0.0 \n",
"\n",
" start3 end3 class3 start end class record \\\n",
"14558 29981332 29991362 2 58800001.0 133448000.0 0.0 123001 \n",
"14419 58497423 58499060 1 58800001.0 122798000.0 0.0 122001 \n",
"2299 1 47323500 3 1.0 47323500.0 3.0 105001 \n",
"15596 57821475 57824016 2 58800001.0 92361000.0 0.0 126001 \n",
"13716 28903735 28905450 2 58800001.0 91651000.0 0.0 114001 \n",
"14375 58662590 58670947 1 58800001.0 91233000.0 0.0 121001 \n",
"13539 36544236 36546336 1 58800001.0 91148000.0 0.0 113001 \n",
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"13892 58398360 58401557 1 58800001.0 87934000.0 0.0 115001 \n",
"13949 1 28800000 0 1.0 28800000.0 0.0 118001 \n",
"\n",
" signal_length sample \n",
"14558 74647999.0 7465.0 \n",
"14419 63997999.0 6400.0 \n",
"2299 47323499.0 4732.0 \n",
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"14073 30290999.0 3029.0 \n",
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]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataannall.sort_values(by=['sample'],ascending=False).head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Check class and repartition"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['100001', '100002', '103001', '103002', '103003', '104001',\n",
" '105001', '111001', '113001', '114001', '115001', '118001',\n",
" '121001', '122001', '123001', '124001', '125001', '126001'],\n",
" dtype=object)"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.record.unique()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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sOfSr6m+BPxlR/zXw8YuccwA4sNRrStKkbX3gB5fkuq8/9MlVeV1/IleSOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI1dN+oJJ9gD/EVgH/Jeqemi1rnWl/RZ7SVquib7TT7IO+E/AvwW2A59Jsn2SfZCknk16eWcXcLqq/raq/h/wJLB3wn2QpG6lqiZ3seTPgD1V9e/b87uAf1FV989ptx/Y357+M+DVJV7yOuDvlnju5eZKGcuVMg5wLJerK2Usyx3HP6mqqbnFSa/pZ0TtPX/rVNVB4OCyL5ZMV9XO5b7O5eBKGcuVMg5wLJerK2UsqzWOSS/vzABbhp5vBs5MuA+S1K1Jh/5fA9uS3JjkD4B9wJEJ90GSujXR5Z2qeifJ/cD/ZHDL5mNVdWoVL7nsJaLLyJUylitlHOBYLldXylhWZRwT/SBXknRp+RO5ktQRQ1+SOnJFhH6SPUleTXI6yQMjjifJw+34i0k+ein6uZAxxnFbkr9PcqJt/+FS9HMhSR5Lci7JSxc5vibmA8Yay5qYE4AkW5L8MMkrSU4l+fyINpf93Iw5jjUxL0nen+R4kp+1sXxlRJuVnZOqWtMbgw+E/zfwT4E/AH4GbJ/T5g7gKIOfE9gNPHep+73EcdwGfP9S93WMsfwr4KPASxc5ftnPxyLGsibmpPV1I/DRtv9B4G/W6P8r44xjTcxL+3P+QNtfDzwH7F7NObkS3umP89UOe4EnauCnwIeSbJx0RxdwxXxFRVX9GPjNPE3WwnwAY41lzaiqs1X1Qts/D7wCbJrT7LKfmzHHsSa0P+e32tP1bZt7d82KzsmVEPqbgDeGns/w3v8AxmlzqY3bx3/Z/il4NMlNk+nailsL87EYa25OkmwFbmHwznLYmpqbecYBa2RekqxLcgI4BxyrqlWdk4l/tfIqGOerHcb6+odLbJw+vsDg+zTeSnIH8N+Bbaves5W3FuZjXGtuTpJ8APgO8IWq+t3cwyNOuSznZoFxrJl5qaoLwI4kHwK+l+Tmqhr+DGlF5+RKeKc/zlc7rIWvf1iwj1X1u3f/KVhVTwPrk1w3uS6umLUwH2NZa3OSZD2DoPxWVX13RJM1MTcLjWOtzQtAVf0W+BGwZ86hFZ2TKyH0x/lqhyPA3e1T8N3A31fV2Ul3dAELjiPJHyZJ29/FYP5+PfGeLt9amI+xrKU5af38JvBKVX3tIs0u+7kZZxxrZV6STLV3+CTZAHwC+PmcZis6J2t+eacu8tUOSf68Hf/PwNMMPgE/Dfxf4N9dqv5ezJjj+DPg3iTvAP8A7Kv28f7lJMm3Gdw9cV2SGeBLDD6gWjPz8a4xxrIm5qT5GHAXcLKtIQN8EfjHsKbmZpxxrJV52QgcyuAXTL0POFxV31/N/PJrGCSpI1fC8o4kaUyGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SerI/wcKzs4cP+92AAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(dataset['class'], bins=10);\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/david/opt/anaconda3/lib/python3.8/site-packages/numpy/lib/histograms.py:839: RuntimeWarning:\n",
"\n",
"invalid value encountered in greater_equal\n",
"\n",
"/Users/david/opt/anaconda3/lib/python3.8/site-packages/numpy/lib/histograms.py:840: RuntimeWarning:\n",
"\n",
"invalid value encountered in less_equal\n",
"\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(dataannall['sample'], bins=10);\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"start1 float64\n",
"end1 float64\n",
"class1 int32\n",
"start2 float64\n",
"end2 float64\n",
"class2 int32\n",
"start3 object\n",
"end3 object\n",
"class3 int32\n",
"start float64\n",
"end float64\n",
"class int32\n",
"record object\n",
"signal_length float64\n",
"sample float64\n",
"dtype: object"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataannall.dtypes"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(dataannall[dataannall['sample'] < 10]['sample'], bins=10);\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3,)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pie_chart_data = dataset[dataset['record'] == '100001'].groupby('class')['sample'].sum()\n",
"pie_chart_data.shape"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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nNncw8PHEN6fiOK43gqD7XE6nAg85rveY43rvLvNnScwpFAfIcb2zCTaxvYUdh2FVpdalz7DsBxe6xpglxhi3wLe0vHHbG8ctuWoJL3/pZV752isNAAtWdx1wwvVbOeQnW7hz8Y5x7rNu3saKzd19fdx24K+hx2+nfBtZ9HYccI/jes85rndBfjhEUkahWCLH9d7tuN4zwB0EO3lXNb+7i/UP/JQJZ7u/AGYCF35i+fKdTjw8Y+krk9d4a67qbguCbtgBw1YC/OTp9pPmHlrH4x8ewZcfbKMxu4n9frCZJ5Z3cd2zQUiu2dpNr+B8jKaW7caYu4wxe1GernN/DiU4M3yx43rvs/D5YpFCsUiO653muN7fgHsIzpNOhfaVL1E7ZjINUw9d7/t+O3Dz89tbTw99S8c/OzpOG+YMe+ag7xzEtKumsenJTZOMMTMbh5qRrZ0+bV0+NQaO32cI08bWsPRTI/nKnOCG/E0vdNATnN/9azvAfGPMmcCzvu+vwE4o9jgA+L3jevc7rjfdYh1SQbrR0g/H9fYDfkYw7pQ6nZvXUTt6Qvip5e2+f1Lo8SZgz5qhNUOWfnsp3du7oYZtwJTPHlu/be6d2/nN8x3MPayO6//eweePq2d4nXnzzXU1hnBwrm/1HwK+CZzpuN44QoeLWXQK8A/H9a4FvpHLZrbYLkjKRy3FPjiuV+u43ucJDshKZSDuRnh1QAtQ2762fR/nsw5TPjSFzo2dE4C144fXTPQuGs7THx3JQeNqeGldN9/9axv7XLuZU3+7lceXdXLRrDrue6WL02/YxlUnDt068bubjwJ+4/v+NuAdxOfvaB3weYIu9QW2i5HyUUuxAMf1jiA4pOow27XYVjtqDzo3rQk/tXd9cIxsjxZg+YiDR6z0fX/y679+ndoxtQs7N3QeQOju871LOrnnwmEsa/F5/o0u/m9JJ196sI0/zx2Bd1Gw4nHVlu6Hu3wywDnGmF/W7zX95HEnf5ihU2ZU4E9atCnATY7rfQy4PJfNLLBdUKw1NUa6dRhNLf3OezzvvPOc+fPnN+6xxx6dL7/8csn/f+LyUzgWHNcbke8i/Q0FIgD1kw+ic8MKtr/WPM4YUw9cMKuh4b7Qt2wC7tr+z+17v/aj12g8spHubd0jJo80LwPjAF5e18XaVp/TD6hjW4fPWycNoaPLZ0vbzstRL7ytdRjwLeBC4JlJ5zV1b3j4N5X5g5buJOA5x/W+57he74nrYtGll1669u677355oO9XKOY5rncGsAD4NMFBTQKYmiGMO+XjrLnjWx8FFgG3/HTvfV68eeMGbt64AYKW4uLuju6G7bntbHx8I3Xj6m5accWo9T3X+I8H2/jU0fX4vs+Fs+r48ZPtrNwCXzhhx565L6/r4oXV3dt93/8LMLx2zOTRmJoD/M52YqyWYPXSi47rXWi7GAmcccYZWyZMmNA50PenvvvsuN4k4AfA+bZriath+x/JPp+6Odtzmt+i6TMmXjDmzZMQWoDj21e1jx6691CMMWxfsf3MC2/tWjvHCf563XLecH78ZDsfuWc7tTUwvM7wl0uGc9w+O/76fe6Btu1rt/mfzD+8ye/Y/tiq315J49svrtwfdOD2BH7nuN57gH/LZTMbbRckA5fqUHRcby5wLfE56ySJWnzff3TWvFkLCeYxbmue2/xWmhrPDn/T5UfVc/lRfZ+mcOcFw2+nqeVlAN/3Vzuu9zjJ2Xm8xwXAcY7rfVBLBpMrlaHouF4D8BOCvQ1lcHrvpTjQYwh6H2Ua5SYQlbQv8KDjet8FrsplM0VvWSXxkLoxRcf1pgGPo0CMSu9dtwd6DEF4/8SDCe7yJlUN8AXgr/l5rpIgqWop5hf7/xYYY7uWKtIya96sGqBnu/eBhOJSmlpyocc2V7FE6QjgWcf1LsllM3fZLsaKIqbQRO3MM8/c729/+9uoDRs21E6aNOmtruuu+MxnPlP0wWapCMX8wv5vAC5g+vl2KU3vvRQH0n2uxFZhtowB7nRc73vAF3LZzIDvikpx7rnnnkGdFV713WfH9SYQHIP5RRSI5dB7L8WBtBTDXecagpUs1eazwMP50xslxqo6FB3XOwZ4lupqecRN770USw3F3keZHk71zgY4FnjScb007cqeOFUbio7rXQ48DOxtu5Yq1zsUV9HUaICJRb7/BZpawusIk3rXuVh7An9xXO8U24VIYVUXio7rDXFc75fAj6jc5qRp1ntMcSUwnuL/21fzeGJfRgGe43oftF2I7KqqQjE///A2gjN/pTIKjSkOdDyxnoEdZZpEdcA8x/W+ZLsQ2VnVhKLjemOA+4GzbNeSIj6wmR2h2AWsofg7z53sepTp8MiqS4ZvOa73k/wNJomBqpiS47jeXsC9wCzbtaTM5hmLF3Uzb1ZPKK5untvcTVNjsS3Fp2hq2Rx6nIaucyH/Bkx2XO+iXDbTaruYKM2aNyvSrcOa5zb3O+9xyZIldRdffPF+a9asqaupqWHu3LlrrrrqqtXFfkbifzrlV6g8hgLRhp7VLD1jiqXOUUzjeGJfzgbmO663h+1Cki5/7vPypUuXLnjqqacW/epXv5r4zDPPNBT7/kSHYn452MOAY7mUtOq97rnU6Ti9jzI9KqK6kupY4DHH9RzbhSTZ1KlTO0444YRtAGPHju3ef//9W1977bW+dyPpJbGh6LjeWwjGo5K8RjbpBrPuuZWdjzI9Ec0WgODs8Ecd15tqu5Bq8OKLL9YvXLhw+Jw5c4o+VyeRoZif/PoQMMlyKWnXOxRL6T4/RlNLW+hxmrvOvU0B/pTf61MGqKWlpeacc87ZP5vNLhs3blyfB433lrhQdFzvbQRjUeNt1yK7jCmW0lLUeOLuHQDcn59VISVqa2szmUxm//POO2/93LlzS9r0N1GhmN+G6Y9U7zKwpBnMmGJ4fuJ44nGUady8lWCSd9qmKQ1Kd3c3F1xwwdSDDjpoe1NT0xulvj8xU3Lyd+XuRV3mONm1+9zUOIId24j1ZSMQnlrxDrRZR1+OA253XO89uWwm1gfWFFLMFJqoPfDAAyPvvPPOPQ488MDW6dOnzwT42te+9vr555/f0t97ISGhmF+pcjdwkO1aZCeFbrQU00r8C00t4TGeal/vPFinATc4rndBLpspemwsrU477bQtvu8POIxj333Oz/S/keAnpsRLTyiOyv9abChqPLF05wE/t11EGsQ+FIHvA+fYLkIKapk1b9YIgh5HS/Pc5u0Ud+c5PJ64D3BgmeqrNpc5rvcd20VUu1iHouN6VwL/z3Yd0qfwZhDF3mRZSVPLwtBjtRJL8znH9b5ou4hqFttQdFzvfEA/FeMtvJdisaHY+9Q+hWLprnZc719tF1GtYhmKjuvNAeahO5JxF95LsdiJ273HE3WTZWCuyy9zlYjFLhQd15sJ3AkMtV2L9GtQLUXH9aYDe5WhrjQYBdyWXzMuEYrVlJz8JNVb0RGkSREeUyympfgKTS3/DD1W13lw3kJwR/r9tgvpy6LpMyLdOmzG4kX9TrXZtm2bOfroo6e3t7ebrq4uc+aZZ2649tprVxT7GXFrKf4AmGG7CClaqS1FTcWJ3sWO6/277SLipKGhwX/00UdffPHFFxcuWLBg4fz580fPnz+/6BZ1bELRcb3z0DECSdI6Y/GiDsKh2NRYy+7XpPc+yvSk8pWXKtc6rpf2bdfeVFNTQ2NjYzdAe3u76ezsNMYUf3siFqGY3ybpF7brkJIU2mB2In3/nep9lOnb0Br2qNQDv9cGtTt0dnYyffr0mZMmTTp0zpw5m04++eStxb7Xeig6rlcL3ITGEZOm0GYQu+s6N9PUsjb0WF3naO1LsBTQ+r/pOKitrWXx4sULX3vttX88++yzI5566qlE7bzdRLDjsCRLeN1zW/Pc5vWUNp6oqTjROx34su0i4mT8+PFdJ5xwwuZ77rmnsf/vDlgNRcf1TgI0Oz+ZwqHYsz3T7u489z7K9IQy1ZV2X3Vc7xTbRdi0YsWK2rVr1w4B2LJli3nooYdGz5gxY3ux77c2JSc//nED8WitSunCY4r93XnuJDhLp8expO8o00qpAX7tuN5bctlMUVtllVMxU2iitmzZsrpLLrlkv66uLnzfN2edddb6Cy+8sOj/FjbnKf4ana+SZOExxeX53/cVik/qKNOKmgJ8F/io7UJsOProo1sXLVq0sP/vLMxKK81xvU8AZ9r4bIlMuPvc38RtzU+svI84rqdx2wGoeCg6rjcZ+HalP1ciFw7F/rrP4aV9I9FRppXySx1lUDobLcXvsmNTUkmuQmOKhVqKrcDjoccnErPlpVVsGvDNCn9md3d3d+w3csnXWHAX84qGouN6JwAXV/IzpWw2zZo3qx5oYEf3uVBL8VEdZWrVp/InYFbKC2vWrGmMczB2d3ebNWvWNAIvFHq9Yj+xHdcbAvy4Up8nZbfzuuemxrEU3tlI44l21QA/dVzv2Eqc79LZ2XnZqlWrrlu1atUhxHdmSTfwQmdnZ8FlxZXsxnwMHWNZTcKhuIoibrI4rjeB4NhOqayjgI9QgTNeZs+evRp4T7k/p5wqkuT5c30rPbYh5dWzwaxPMHm7UNd5A/Bs6LGOMrXn6vy/Q+lHpZq330KL/6tNz16Ka5vnNndQOBR7H2WqrrM949DxHkUpeyg6rjcbbQlWjXq6z7ubo6j1zvFySYVvuiRSWUPRcT1DcHMlrgOuMnA9obi7OYrh8cR9gQMqUJf0zQBfs11E3JU7rOYCx5T5M6TyOmYsXrSN3a97XkFTy6LQY3Wd4+HdjusdabuIOCtbKDquNwytXKlW4XXPfXWfdZRpfDXZLiDOytlS/Bj9H3cpCTRj8aKu/G93133WeGJ8vctxvaNtFxFXZQlFx/UagM+X49oSK7sLxfB655kFXhe7NLbYh3K1FC9D/wjSYDSwiqbGBnY+TmIJTS2vhR6rlRg/pzmupx3vC4g8FPO7Kn8h6utKLPW0FHsPk2hpXzKotVhAOVqKlwB7l+G6Ej89N1r6DMX8mveTKliTFO8Ux/WOt11E3EQaivmTxD4X5TUl1oY0z23ezM5DJT7w59Djt6GTGuPs67YLiJuoW4pnowm6abIt/2s4FJ/XUaaJcrLjeifaLiJOog7FKyO+nsRbTyiGu8+an5g8ugcQElkoOq53HDq/OTVmzZtVA2zJPwy3FMPjiUMBjVnF3+mO6+k+QF6ULUW1EtMlmI4T6AnFDnY9ynRYJYuSAakBLrVdRFxEEoqO6znAWVFcSxIjHIo93ecnaWrZEvoedZ2T49L8jdLUi+o/wvsjvJYkQ6HVLJqfmFxTgVNsFxEHUYaipEsQik2NNcDE/HPh8cRRgHZjSZaP2C4gDgYdivltiA6OoBZJlp6J2+MJzvrZBvwt9PocdJRp0rzHcb2J/X9bdYuipahWYjr17KXY03V+lKaW9tDrWu+cPHUEe6Cm2qBC0XG9WuCCiGqRZBkOrEHjidXmw7YLsG2wLcVT2TGeJOnS1jy32WfHnefeR5nOslKVDNbBjuu93XYRNg02FNV1Tq/W/K+TCY4y/XvotZPRUaZJluobLgMOxfzdxbMjrEWSJbzE7yEdZVpV3pf/951Kg2kpnoNWK6RZeDMIjSdWl2GkeM7iYEJRXed0KxiK+dVN02wUJJE6w3YBtgwoFB3X2wtNuUi7nlDsoqllceh5/b2oDgrFEp05iPdKdegJxUW9nlfXuTpMcVzvrbaLsGGgwfaOSKuQJNpGU+Modl7FAmopVpN32S7ABoWiDNQ2gjvP4aNM34LO+q4mqexClxyKjusdgiZsSxCKW2hqWRZ6Tl3n6nKc43qNtouotIEs2Ff3SGie29zFjq3DeigUq0stwdScW20XUkkD6T4rFGUX+aNM59iuQyKXui50SaGY35lXf/GlkNkE24lJdVEo9kNn+Epf1HWuTpMd1zvMdhGVVGooqussfVEoVq9TbRdQSQpFGTTH9RrQUabV7CjbBVRS0aHouF4dcEIZa5HkOg5osF2ElM0RtguopFJaikcBI8pViCSaehDVbarjeuNtF1EppYTi7LJVIUmn8cTql5qTGUsJxRllq0ISy3G90aToH0yKpaYLrVCUwZoDDLFdhJTd22wXUNShxccAAA6dSURBVCmlhOL0slUhSaauczqk5iCyokLRcb2xwKQy1yLJpFBMh/0c1xtuu4hKKLalqK6z7MJxvYnAW2zXIRVRA8y0XUQlKBRlMHSUabocYruASlAoymCo65wuCsUQ3WSRQhSK6ZKKxpFaijIgjuvtB+xnuw6pqMm2C6iEfkMxv9jfKX8pkjBqJaZPKs7fKaaleHCR3yfpovXO6TPBcb2qv7FWTNhNLXsVkkQKxfSpBfawXUS5FROKqdkdQ4qTP9FRk/nTqeq70ApFGQiNJ6ZX1f8wLCYUJ5S9CkkahWJ6KRRRS1FCdJRp6qn7jEJRdnYEMNp2EWKNWorA2LJXIUmirnO6KRSBUWWvQpJEoZhuCkUUipKXX910nO06xCqFIjCy7FVIUhyPjjJNuzrbBZSbQlFKoa6zVL3dhmJ++sWwCtUi8aelfeLbLqDc+msp1lekCkmCRlJ0zKX0KfWh2F6RKiQJdJSpQNpDMZfNdAGdFapF4u1Y2wVILKQ7FPO2l70KSQINpUgqKBRFpBRqKQJtZa9CRJJCoYhaiiKyg0IRhaKI7KBQRKEoIimiUBSRUmy2XUC56UaLiJRipe0Cyk0tRREphUIR2Fr2KkQkKRSKwPKyVyEiSaFQBHLlLkJEEkOhiEJRRHZQKKJQFJEdFIooFEUk0JrLZlpsF1Fu/YZiLpvZBGyoQC0iEm9V30qE4lqKoNaiiCgUd5IrZxEikggKxZBcOYsQkUT4p+0CKkGhKCLFarZdQCUoFEWkWArFkFfLWoWIxF0XsNB2EZVQbCguBlrLWYiIxNrLuWwmFTtmFRWKuWymA3i6zLWISHz9w3YBlVJsSxHg8bJVISJx97ztAipFoSgixXjSdgGVolAUkf74pGj4rOhQzGUzb6C70CJp9HIum9lou4hKKaWlCPC3slQhInGWmq4zlB6K6kKLpI9CcTcUiiLp85jtAiqp1FB8Hk3iFkmTVcDfbRdRSSWFoiZxi6TOH3PZjG+7iEoqtaUI8NfIqxCRuPJsF1BpAwnFeyOvQkTiqB2433YRlTaQUHwUWB91ISISOw/nspkttouotJJDMZfNdAJ/LEMtIhIvqes6w8BaigB3R1qFiMTRH2wXYMNAQ/FegvEGEalOL+WymSW2i7BhQKGYy2Y2Aw9GXIuIxEcqu84w8JYiwO8jq0JE4kahOAB3oC60SDXaBDxsuwhbBhyKuWxmAymcwySSAnflV6+l0mBaigD/G0kVIhInv7BdgE2DDcW7gFSc8CWSEgtz2cyjtouwaVChmL8LrTmLItUj1a1EGHxLEeC/I7iGiNi3HfiN7SJsG3Qo5rKZh4HnIqhFROy6NX8DNdWiaCkC/DCi64iIPanvOkN0ofg7YE1E1xKRyluUy2YesV1EHEQSirlspg39lBFJMv37zYuqpQjwE6AzwuuJSGXoBktIZKGYy2ZWALdGdT0RqZjbctmMNo7Oi7KlCLrhIpJEP7FdQJxEGoq5bOZx4KkorykiZfVALpvRYXQhUbcUQa1FkSS5ynYBcVOOULwFWFmG64pItLxcNvOE7SLiJvJQzGUz7cDXo76uiETKR63EgsrRUgS4DlhcpmuLyODdkctm/m67iDgqSyjmj0H9YjmuLSKD1g181XYRcVWuliK5bOZOINX7sonE1C25bOYF20XEVdlCMe/KMl9fRErThVqJu1XWUMzf2dIqF5H4uCGXzbxku4g4K3dLEYKxxdQegiMSIx1oZki/yh6KuWxmCfCzcn+OiPTrl7lsZqntIuKuEi1FCH46barQZ4nIrlYD/2G7iCSoSCjmspm1QLYSnyUiBV2Ry2Y22i4iCSrVUgT4PpCr4OeJSODBXDZzg+0ikqJioZjLZlqBDxEsLxKRymgD/s12EUlSyZYiuWzmIeDHlfxMkZT7T03BKU1FQzHPBV628LkiafMC8C3bRSRNxUMxl81sAy4hWH8pIuXRBXwov2uVlMBGS5H8Tr/X2PhskZT4r1w287TtIpKo1uJnXwVkgJkWa6gam56+iy3P3wc+jDz0NEYfeRYbH72RLc/fR83wRgDGnvhBhu1/ZFHvBdjw0K9pXfoM9RP3Y/y7rwBgywsP0r19M6OPOKtyfzgp1WK0vnnArLQU4c2zoj+IjkUdtPY1ObY8fx97fvB7TL70R7S+8iQd618HYNQRZ7PXh37EXh/6UcFA7Ou93W1baXt9EXtd+mN8v5v2NTm6O9rY+sKfGHV4ptJ/RCleF3Bp/t+XDIC1UATIZTPPAN+2WUM16Fi3nKF7TaemrgFTM4Sh+xzCtpcfH+R7DX5XJ77v43e2Y2qGsOnJ2xk1+z2YITY7GNKPL+cPkJMBshqKed8AnrNdRJLVj5/K9mUv0NW6ie6O7bQufZquTWsB2PzsH1hx/eWs/eP36dq+pej31gwdzvCDj2Pl/3yS2sZJmKEjaF/5EsMPPKbSfzwp3h25bEYrxwbJ+L79udSO680CngQabNeSVJufv58tf/cwdQ3Ujd8HUzuUxmPeR82w0WAMGx+5ga4t6xn/rk8X9d5x//KRnb5n3f/9kFFvy9C2agnbX/07dRMdxhx3QaX+eNK/l4Ajc9mM9hgYpDi0FMllM83Ax23XkWSjDj2VyZf8gD0v/k9qGkZRN3YvhowYi6kZgjE1jDr0NNpXFp7DW+i9Ye1vvAJA7dgpbH3hQSac7dKx5p9vjluKdVuBcxWI0YhFKALkspl5aLXLgHVtDdb6d25azbaXHmf4zDl0bln/5uvbXnqcuvFTi35v2MZHbqDxhIuhuxP8/PRSU4PfqbH8mLhMxwtEJ24j5p8B3gqcaLuQpFlz59V0t26GmiGMO+XjDGkYydo/XEP7G0vBGGobJzLutMsB6Ny8jnX3/pBJ532tz/f22PbS49TveSC1o/YAYOhe01nxq09QN9GhfuK0yv9Bpbcf5rKZm20XUU1iMaYY5rjeROAZYG/btYjE3GPAO3LZjHa2j1DsQhHAcb0jgIeBYbZrEYmpVcDbctnMStuFVJvYjCmG5ZcnfRBtMyZSSCdwvgKxPGIZigC5bOZWtH26SCGfzWUzD9suolrFsvsc5rje9QSb04oIfD2XzWhdcxnFtqUY8jHgIdtFiMTAtQrE8ot9SxHAcb0xwHzgbbZrEbHkulw285H+v00GKwktRfKnkL0TeNZ2LSIW/C9Bj0kqIBEtxR6O640D/gQcbrsWkQrxgPdqLmLlJCoUQcEoqfIQcEYum9luu5A0SVwogoJRUuEJ4J25bGbX/d6krBIZivBmMM4HDrNdi0jEmoE5uWxmg+1C0igRN1oKyWUz6wluvmiDWqkmzcCpCkR7EhuKALlsZh1BMD5vuxaRCPwJOCGXzayyXUiaJToU4c1g/BfUYpRkmwe8SxvF2pfYMcXeHNcbBdxEcGyqSJJ8I5fNfMV2ERJIfEuxRy6b2Qy8B/gv27WIFKmTYNdsBWKMVE1LMcxxvUuAnwP1lksR6ctm4LxcNnOf7UJkZ1UZigCO6x0P3AFMsF2LSC8rCcYPNQ4eQ1UbigCO600F7iY490UkDhYSrFJ5zXYhUljVjCkWkstm/gkcD9xluxYR4H7geAVivFV1KALkl0m9F8jarkVSq4tgF/nT8zs+SYxVdfe5N8f13k9wA2a47VokNV4HLsxlM4/YLkSKk6pQBHBc7wCCibLH2a5Fqt69wAdy2cxa24VI8aq++9xbLptZArwd+ALQZrkcqU5twJUEd5gViAmTupZimON6hwC/QVuQSXSagYtz2Uyz7UJkYFLXUgzLZTMvAEcD3yBYXSAyUD5wDXCkAjHZUt1SDHNc70iCscYZtmuRxMkBl+aymT/bLkQGL9UtxbBcNvMUwWmB1xL81BfpTyvQBMxUIFYPtRQLcFxvDvAL4CDbtUhs3QZckV8gIFVEodgHx/XqgMuBrwBjLJcj8bEQ+GQum5lvuxApD4ViPxzXGw98HfgoMMRyOWJPC0FX+ce5bEY35aqYQrFI+ek71wCn2q5FKsoHfg18MZfNrLZdjJSfQrFEjuudDHwbOMp2LVJ2TwKX52/CSUooFAfIcb1zgG8B023XIpF7BPjPXDbj2S5EKk+hOAiO6w0B5gKfBw62XI4Mjg/cQxCGf7VdjNijUIyA43oGOB34FMGYo7FbkZSgA/gd8J1cNrPQdjFin0IxYo7rzQA+CXwQbVEWZ1uB64BrctnMMtvFSHwoFMvEcb2xwEeATwD7Wi5HdlgH/Ihgas0628VI/CgUyyw/7ngOQdf6eMvlpFUXMB+4Abgtl81ss1yPxJhCsYIc15sNXEZwPMIky+WkwdPAjcDNuWxmle1iJBkUihY4rldDsNHtuQStyCl2K6oqSwmC8MZcNvOi7WIkeRSKluXvXB8LvI8gJDX+WLq1wC0EQajpNDIoCsWYye/r2BOQ+1suJ84WAQ8QnIPyp1w202G5HqkSCsUYc1zvUOAdBIdsHUe6u9mrCW6WPAA8kMtmlluuR6qUQjFBHNfblx0BeSxwGFBrtajyeZVgud0jwCMaH5RKUSgmmON6w4Ej2Tko97BaVOm2Ai8Bi/NfC4HHc9nM61arktRSKFYZx/UmAgcW+JoKjLVY2kp2BF/4a1kum9FfQokNhWKKOK43Atgn/7V3/tdxQAMwLP/V0M+vNQQbrm4s8Guh59YDL+eymU2V+DOKDJZCUUQkRKf5iYiEKBRFREIUiiIiIQpFEZEQhaKISIhCUUQkRKEoIhKiUKwixpjTjTEvGmOWGGNc2/WIJJEmb1cJY8wQgjXEpwDLgaeAC33f1wl1IiVQS7F6HAUs8X1/qe/77cDNwFmWaxJJHIVi9ZgChI/qXE66918UGRCFYvUwBZ7T2IhIiRSK1WM5wa43PfYGVliqRSSxFIrV4yngQGPMfsaYeuAC4G7LNYkkTrVuZZ86vu93GmMuB+4DhgDX+76/wHJZIomjKTkiIiHqPouIhCgURURCFIoiIiEKRRGREIWiiEiIQlFEJEShKCIS8v8B8bZNI6aDYRcAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\"\"\"dataset['class_name'] = dataset['class'].apply(lambda x:\n",
" \"Class 1: All significant waveforms\" if int(x)==1 \n",
" else \"Class 2: The noise level is increased\" if int(x)==2\n",
" else \"Class 3: The signal is unsuitable for any analysis. \" if int(x)==3 \n",
" else \"Class 0: The quality was not annotated \")\n",
"\"\"\"\n",
"for patient in dataannall.record.unique():\n",
" pie_chart_data = dataset[dataset['record'] == patient].groupby('class')['sample'].sum()\n",
" if pie_chart_data.shape[0] == 3:\n",
" explode = (0.2,0.2,0.5)\n",
" else:\n",
" explode = (0.2,0.2,0.2,0.5)\n",
" \n",
" plt.figure()\n",
" plt.pie(pie_chart_data.values, labels=pie_chart_data.index, \n",
" autopct='%1.1f%%',\n",
" shadow=False, \n",
" startangle=90,\n",
" explode=explode,\n",
" radius=1.5\n",
" )\n",
" plt.title(patient, fontdict=None,loc='left')\n",
" plt.legend(bbox_to_anchor=(1.1, 1.05))\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Read source and create 2 lists > Bad way to slow\n",
"ecg_data : data\n",
"ecg_labels : labels quality class (1, 2 or 3; 0 means the quality was not annotated in this segment) \n",
"Source : https://physionet.org/content/butqdb/1.0.0/"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"#For cut sample into n sample with cut_size\n",
"def ecgreshape(ecg_array,cut_size):\n",
" ecg_size_multi = ceil(ecg_array.shape[0]/cut_size)\n",
" ecg_result = np.zeros(ecg_size_multi*cut_size)\n",
" ecg_result[:ecg_array.shape[0]] = ecg_array\n",
" print(f\"Array size {ecg_array.shape[0]} cut by {cut_size} done {ecg_size_multi}\", end=\"\\r\")\n",
" ecg_result = np.reshape(ecg_result, (ecg_size_multi,cut_size))\n",
" return ecg_result\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"../aura-data/105001/105001_ECG\n",
"Array size 5041 cut by 5000 done 2 2916\r"
]
}
],
"source": [
"# source wfdb\n",
"header_list = [\"start1\", \"end1\", \"class1\",\"start2\", \"end2\", \"class2\",\"start3\", \"end3\", \"class3\",\"start\", \"end\", \"class\"]\n",
"record_list = wfdb.get_record_list('butqdb')\n",
"record_list =['105001/105001_ECG']\n",
"ecg_data=[np.zeros(sample_size)]\n",
"ecg_labels=[]\n",
"for rcd in record_list:\n",
" if re.search(r'ECG$', rcd):\n",
" record_name = f\"../aura-data/{rcd}\"\n",
" print(record_name)\n",
" record_csv = f\"../aura-data/{rcd.replace('ECG','ANN')}.csv\"\n",
" for i in dataann_nan_class.index:\n",
" record = wfdb.rdrecord(record_name, sampfrom=int(dataann_nan_class.start[i]), sampto=int(dataann_nan_class.end[i]))\n",
" ecg_data = np.concatenate((ecg_data,ecgreshape(record.adc()[:,0],sample_size)), axis=0)\n",
" ecg_labels.append(int(dataann_nan_class[\"class\"][i]))\n",
" if i == 50: #for test not for production\n",
" break"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Scaleogram"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Default wavelet function used to compute the transform: morl ( Morlet wavelet )\n"
]
},
{
"data": {
"image/png": 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R4r/6qlqN9c03QPv2eufWJarPjPe6p3kG4qWcOiiTGi7dQbGSzExpIun7Vq9etPhxsmFD7v+ktYFp6iu8lKUwo9sh3nqrsuGPHQvcc4/euU12zroNL2rDd2/yV2q9V64EfvyxtLRuktbMiJlJoXsdbBrgTZuZqquBm24Czj8fWLRIL69KQtfMVMqS5iCitgFdrZIIM5ah26G+9FL294sv6p076s1Pk2YmKrr228mTgWbN1GfqVL28atWKFt9mnxldTJo2vfFtEmZMm5meegr45z+B4cOBK69M9txpImkzk0nNjGltYJo11mUpzMSJ7oNi8uYnrZnR5bTT1GsBfvsN6NFDL6+oyyV1VzPZrJmJE13hvZTryByPIGHbLNn9XqHXXtPLq5Kw2cxkem8j0cxUEGnSzNim8v/uu+zvb77Ry0t3YErzDCTNRG1z3usc9XlZvRo44ACgVSvgyy+Lx48T0wNLHNsHLFhg1zYEcZAmM1NUTAvQIswkjEmBQFfqt9lckSYNQVQq2WfG5POiK8z8/e9qJ9Tvv1cO+zokba4wrfL/17+AHXYA2ra1W3gXM5O586eJshRm4iTqzUvTDF93kIpqqolTmElaq5QmjZouNjmd6w4sEydmfy9dGi2tLrb7L/Tpo76nTwdGjtTLyyZ071vUxQVxottPmW5z48erlcKlvO28GGX5OoM0deY2DYo2O2N60TUz2XTf/ARoUx1u0poZkyp/02amOCdKcawgNIVum7Nps0PTr9DQPV+nTup7/HjgpJO0i5NDWWpm0mRmsmlVjGkVpklsvm9p0ipVkjBj2sxUab4ucWFao6aTV5rKrsusWfHmV5bCTJwk7TMTJ0kPLJVsZtJl2jS1e/Ktt0ZPa3Obs3llSdzXXfd5TRKbzaqmhVCdvEz3U2mmLM1McVJJDsC6wkycJP3yONP3rUsXtfHZmDHA4YcDnTuHT2uzn5bNK0t025zfwBRlfySbnXbjRMxM4UmTZiZuRDNTBJv3mYmKV22d9ExTB92H3LSZyb2D69tv651bzEylkbQArJvepJnJ5kHRZlNNmrSwusQ9PpSlMGOz30maBpaoA3qcD5ppzYpN9y1NHVzSwkyazExxaGaiYJMGLk3YrN0wvZopzcQizBDRUCJaTkTTXGFbE9E4IprtfDd0HbuRiOYQ0SwiOi6OMrhJ08BikyOp7sBi0p5ru2ZGhzRpA5Nemm3zMlldITTO+2zzICdmpvCk6T7HXZa4NDNPAOjiCbsBwDvM3BrAO85/ENGeAHoAaOOkGUREEd+kkxxJz7ZMoivMmNQQmFb5myRNbS5pzYxJ4m5zUYUTk2amOF5DYYpKNjOlSZiJm1iEGWb+AIB3p4LuAIY5v4cBONkV/hwzr2fmbwHMAdAhjnJky2Mur3IyM9m0YaBplb+0udLyKidhJuk2lyZhJsn7pitI2ayZSdPEJW3UpM/Mdsy8BACc722d8GYAFrjiLXTC8iCinkQ0iYgmrVixogaLGkwlmSvS5DMTFdOzZJMCgTe+TWWvZI1YmsxMUTG5eZvus2qzqcbmstc0JhyA/S6n7y1h5sHM3J6Z2zdu3LiGi+WPzbPkqOiuZjLpnBa3z4xN9y1NAkHSs+Q4SXq/Et1BOU3CjE5ZbFtFFqdAUEnmcC82rWZaRkRNAMD5Xu6ELwTQwhWvOYDFcZ44TQOLTUuzxWcmi2g3SqOSzUxJC/8mzUxpMinrCoEmtRtJa79FM1MarwK40Pl9IYBXXOE9iKgeEbUC0BrAf+M8sQwsCtM+MzZpZtJki7ap7KY3KzSJ6bqnaWm2SWHGpn7Ki+6kySbHay9xC1axLGwkomcBHAmgEREtBHAbgLsBvEBElwL4HsAZAMDM04noBQBfA9gIoBczp1Z/YbO5wuZ9ZqJiuoOrVG2g7qBWyZoZm4WZNLW5pLcDEM1MOolFmGHmswMOHR0Qvx+AfnGcu6apZAfgSlrNZPN9MylExi3M2DTTjFsANrk0W/eFh2JmKg3TE0bm8hFwZAfgmPOyWW1uetO8OM1MSZc9TauZkix73CtLbHpeKtnMlCZhpqY1Yhs2qE8Gm81MJs2DNU1FCDM2LRs0OSjqrmay2WcmTWYmm7RKcc+STarNbVtV40b3OugOijpaIl2tUE2amebNA3bYAWjaFJgxQ4XZrJnxxjfpRB43ZSnMmFw2GPfy5iQx7TNjUjOTJiE0Kml6jURcwsz69cAzzwCffVZ62WqauJ3OdfqpKG/bjoM0aWZq0szUqxewbBmwciVw1lkqzOal2d74v/8eLX2aKUthxttYdaTPqI3F2zhsFmZEMxOeNGlmkhRm4haAM3Xv3x8491zgoIOA+fNLL19NYnrTPDdJv6MqTcJM0HWbMAG49lpgypTS0gO5wvTUqerbZjOTaGYsw6T06W0cST3ka9YA55+vl4dpnxmd2aXuwOC2iQPpWvZaDJMDi64mMqjN3XJL9v+dd5ZWtpomTWYmXc2MSQfgmmjvGzYAhx0GDBwIHHNM4fSFzv+HP+SHlZOZSTQzKSdO6TPqg6armSmFtWuB/fYDhg/PDY9S9nXrgE8/zQ1L2lQTtUP+4APg7LOBMWOCO6iNG4GnngI+/LBwXuvX5/63SaNmUqukK7yHEaCrqoBPPvFPn6brblKjlrSZKe37zCxblv3tfRNOFDNT3MKMrq+RzcJMTfuyJqycTAZvY9W5YbrCTBK+F3fcAcydGz1dhkWLgF12AX77LTc86Qdtk4ii9RFHqO/nngOmTcs9ljFN9OsH3H67+v3228DRvpsFmBNmfvhBmVN08jK5V4u3jbz8crT0YQWCQw6Jlm8mr4kTgcaNgZ13jp4+TP5uol53b5vTEQgqycwURhvoJ2RnBL4o/VQYYSbK8mZdYSLu1UxJmplq2hwumpki2OAAfO+90dO4ufzyfEEGSF6Y8ZtdBl0Pb/iRR+b+Hz5czc7GjcuG9ewZfG7dgaVUYeavfwXeeit8XvPnA/fckyu8leK3wqx8ALzmtajodoY1KYg9/TRw8MFA69bAnDnx5ZtBVzPjfebC1t3vPN5nZ/lyYMAA4PPPw+Vhk2kzzLO6dm3uf/e19pZ91SrgX/8C3n8/3Pl1hNgowozfPTGtmfET2sK2HRFmPCxbpswGK1cGx4l6wxYtUgP6v/9dWplGjAAuuAD44gt9M5N3hsWsHszrrwduuMFf6AgibCObMME/XHfWELXuP/2U+//MM9WySLdAksE7iP7wQ36cfv2Ajz7K/p83L9+UlkFXM1NoZrZundIezZqVf8xrGizGmWeqdnDMMSpfoLRO4s9/BvbZBzjggPz406crAeCAA/yvqxs/YSbKwKgrzASZVhcsyPqQMQPXXBMt3zCU2jl//LEq26hR0dM/+STQpAlw3XW54d72d+WVQN++ym9kzRr1bPXuDdx6q7pnNi3xraoCXntNadmAfAHcr+y//pr7P/OsZPJz89e/An36AMceq/oIN3ELFGHHpuefV8vBr7wyvnMD+otj6tTJ/X/IIcCeewIzZxZP6y1rt27Rzl0Mq8xMzKrBffWVmomPHQs89JASAHr1ygoCUYWZSy8F3nxT/W7bNlqZVq4ETj9d/X79deDqq3OPR52xeE0tv/yiZlj33af+N26sOqkMhRpjWNXnzz/7h0cVZsJe9w0blOBYr172vj32WH7H8eKL6vvYY9WxFSvUXg+HHprbOQXxyy/5YYceCkyalH+fdTUzhXwWbrpJ1XeLLdQg26BB9lidOtG0I/913mK2dCnw7rvACScECwQZM8v22wMtW+bGGTBAfX/1Vf459tor+/vVV4FLLgkuj1/727gxv9MD1ETkoYeUf9epp+aW1Vv2sHhn4NXV6nPQQbnhq1dHy9fLhg1A3bq5YaVqNw4/3L99hSnjhc7b7rwTL+91GzlSfa9bp/q2Tz8FHnhAhTVrln9PdTXIxZ4Xv+sXliFD1GQTUNrEMAJwIWHGG//jj7NlvP12JTAWyruUSVum/mH7yB491Pcjj6g+MvNM6moDvc/r2LHA7ruHT1+7dm5/lfFlO//84tso1LR/m1WamVWrsp3v+PHAE0+oGWbv3mpPigxRpM/167OCDKBU01GYPj37+8cfw2lmmNUAd9pp+b4u3vg//ZT1+QCAv/0t93ihQV3XKVDXzOQVEDIMGqRmQ717Z2enf/xj4bx//VU9dEccoa5HGA2VnzBXVaVmp168ZQ0qe4Z33gH+859sp+kVQgcMUIILkB14fvkFePzx3Hh+g37QQ+8VejLayaDO/fHHlZll112B774LrEpBvI7Tixfnamv82kiQcHbddcA//qHa/cyZ6nPSSblxdDu86mpg9mxVTjd+bcFP4+fHc88BW28NdOmSW75Cz/pvvwHffOOfX9DAf8QRhetfaHJRqL0yA/ffn/3/z38m9+oSZnWPGzbMFRKCWLUK+P773LCMIAOoyeIXXxQ/t1fILSTMuPFqIsMIM8UEuQEDgPr11aTZGzfMRGbJkuBzF7tvH36o+tuMoOx9Xr0avmL49VeAmiAWo6Z9+awSZrw34oorsr8zg+GqVfnxvJ2A20R19925x6I60nnjh3EAfvll1aGMHKkcb2+5JVtmb3zvIOQ9n/ehjRNdzUyQwOF+gM46q7AvS4YhQ5SwCKilumE0M0GaqS++UILRscdmBwHvYOCd2bmZNQvo3Fm1v/79VZi3k+nbV5mEvHg7ryjCjFfTFCTMZP5feqn6/v336J1WBvds+v33gRYtgObNsyYzvzbireO6daqdPvtsNmzoUP/77tfhRVk9smKFMhkUY8oU4LjjwuV59tmqPbz5ptJUZQgSZtavB3bbTX0yGrAMxYS1QmY996DmpZgw48bPzHT11VkNRSF+/DGr/XKzYoU6j9f8P2KEMhGtXZvVKgWxcKFqWy1bAqNH+8cZPx64+OLcMHdZNm5U5osTT8yNc+yxQKtWanAvJHyE0bZFNbH17avuz9Ch+b5bfs+P9166+wjvuV97DdhxR+Cyy/LzWbAAOOoopdm5445wZS2GjqO5CDMuij2wTz4JbLutmkm5cXeuvXsDjRopHxcA+Pvfc+PWrh2t8/Q2du8g63cD3VokQM1W//Y34L338oUTr+rO3ZiefBLYY4/gsgU1ng0bVKdQaMAG8u3HfrgfDu+1cAszzP4PUnU18Oijxc/jNYWVqpkBVKc5a5aamQ8apMK8bcvPRAWotuVWy2Y6Cb8O8tNPi2/YFUX1vmZN7v/MwOFnqvFe61IdYN3X8MQTVd7r12dt+cU0MzNnKtt/s2a5caqq/JfLV1fnlzWKtqZv31xNawZvW+jVqzQtkPuZCJq4DB+e1S707Qu88YaasCxeXFzjV6hdFzJDbdgQ3ll+0SL/vqFLl8Jly/Sve+2V30+deKLSTjZqpO71iBFK+3rGGfn5eJ+VH35QwlSLFipf5mj+FO78Hn/cXxCaP19NDHv3LjyohhFmivX5heJ6HbL9hJlVq3L///qrMgsecQTw9de5x8aOVW1tyBC1VYWbBx7IPp8ZoTqJ1UvMqp4LF+aGizDjotCDzqwkf7+b1b696oSYs3bjp55SA6T3Aj/xRH4D9DagDFVVwFVX5YZ5G+LSpUpwuvbabMP1a/z33KOkaO+D6PaPAbKmo3XrVH2953MT1HjOPRfo1Ek5Bxbq0AcNKmyeuOQSYMst1UoAv/OddZbqpFavVuaOzTdXD10peB/6MJqZOXOKC6YZm69XeBk0SKnHH3ssG/bxx2qW7kfQtfb65nivt58wo6uZOeGE/CWlmXaycGE0/5GqKiX4Meee/733gMmT1ceLe8A+5xxlKvU6dwdp/aqr880/UZbseycyGbztwGuGAsIJN+777K1D5r9Xu9K9u5qw9OpVXJgJatfMxU2xQSuX/PAzga1ZU1gbe+GFqj3MmJGrZfOyeLHyI/RbZfmPf/gvd37ooeJlDsJ9T4I0OhkmTy4uzMycqUyhjRv7TwK86QtNCr3306tB8bve3rBHH1VC2gcfAH/5S/C5vE643nwWLPAfHwcPVv3gzJmFr03//oUX3mR48kk15u60kxK0JkxQCxY6dCieVgtmtuLTrl07njKFWTW3/E+tWsHHAOaOHZnXrcsNmzOncJrMpxGKH10AACAASURBVEkT5rVrOY+hQ4unrVs3+3vQIOaZM8OdM+jTqJE698SJxeN26JBf5urq3Djz5zMTBefRrVt+HszM336bG2/jRuZevfzzOOAAvToDzDfckPs/6FzeT6G6AcyXXKLqc9xxwXHmzVNxjjnG/zgzc6dO4crz97/nXsc2bfLjbLEF8xVXqPP+9BNzVZWK++mnufHOOEOFd+5c/Lzbbcf86qvMm2zCXK9e9Ot/+eX5YZtt5h939uxs/aKeZ/Ro5nvuyQ3r2VO//RxxRO5132mn/Dg77ujf1t1x7rknG/7007nHrruO+eefme++O7gcS5YULmffvqoct92WW4brritex7p1mdesyS/zs8/mxx01yj+P5cv9r0Ep91L38+abql8pFu+661T53n03XL4PPBB8rHNn5latgo9//726P+6wIUPUuauqmD//nPmPf2R+6y1VpsWLi5dn6tTc6+ztW8N+Bg3K5vHrr/5xTjmlcB5B/X2Y+z95MvOll+aG9ejB3K5doXSYxByPjBBLJkl82rVrF2oAL/RZvjz3/zXXhE/7zjv5N/fQQ6OXodjgWuyz1Vbq3G++GS7+lCnMs2Yx33IL88iRzB9+mHt82rTCgmDLlv4N+513cuN9840agHXqVujTt2/N5HvNNao+hxwSHGfYMDUIBV2ntm2ZGzcOd77bb8+9jkcfXTh+vXrMe+yhBPFx40qvZ6NGNXdvvJ/p01XdNmyInvaVV/KfkfPO0y/TkUfmXvedd86Ps8MO6tjnnysB6qmn8oX/u+7K5vHEE9HLcc454eO6BYuwaZ59Nl/I8g6+APMdd/inHzLE/3mPUoY4P4MHF4+TeYbD5jlgQPCxYs/jNtsEH3v+eeYtt8z+//VX5gsuKF6e1q1zr/PcuaVdq4ceyuZx552lX/NmzdQEvmtX5hUrwt9/v4nZUUcVSxefMGPV0uwoe6z44VWJDxwYPu2iRflhzNHLUEoav/RhHX/33Vc5kAWpj3/8sbApJsh3xKum/+kn/ftTCN3N3YLIqLy9/ihuPv9cOasGOQ5++WX483nv/zbbFI6/fr1S6w8cqFYllUpNOop7yThqv/RS9LTjx+dfozAmxTD5nnKKWv3YsaO/6Sqjhj/4YNXeBg/O1iWDuw1494kJg9dfrhBr1ihTRxQ+/zy7jUMGvxd13nabf/qg/UJ0l7aXSpjFAVVVwfXxo1DcYn4dhcwsmbdqZ3j33XAruGbPVlsV7Luv8p0sdQNCd9kz7zYrhcxYt2QJcPzxajuIMGVyr+zNkORmihUlzBRzcCtEnz5qv47OnbNOkCaIKswAhe3gP/5Y2CchaHWF107coUP+Mts4qal3iGRWCmTeiOtHFKG3GFVVauXHoEFKiAzbpmfMUI60pZKkMPO3vynhIeNkHwU/ASiuso8apT5TpgTvZNqtW67gfO21uXFuuUX5Tk2fnr+EOG4ybT7KBOi11/TOGXStC+01ZJqXX/b3gQqi0MRFd7LpplCf4uXll9Xn8ceVU28pVFcrnzi/VZSl8tlnKt+hQ0tLn+Q4aUyYIaIuAB4AUAvAY8x8d6H4ixfnrwxJkh9+UMv7uncHXnnFXDnWrFFOaXF18G+/XfwBfust5ei7zz7KiRfwP7972Wrc1NRgXKuW2uwwKf7xD/WJyq+/Fu6E00RmW/hNN41e5qVL88Pi0My4OeywYE1DmIFkzJh4yxNEZmVPFK2kbhvx0zwwq9VJaSWKIFOMOFfclDL5nj8/eJfyYtxxh1owErc2ZMWKcBoyP4I2ZK0JjAgzRFQLwP8BOAbAQgCfEdGrzBywbkipvAp5cieFSUEmw267KZV5HIRZRZDZj2P33dVso3btZGf6gFp9VhNs3KiWkKadF19UG7fZQnV1aQOrnwYu7rZmymQSlf33B7baKrtbchh0hZkFC5R5rV079QHMaaFNUGh1aFRKbbfFtswIIs6yuwn7zio/vKsYaxJTS7M7AJjDzPOYeQOA5wB0N1QW66iuNjNTmjlTmepWrUpemIlT/etm0SJ/W28a+c9/TJcgPGF8BcKSeYVDJfLzz/m7RhdCV5j56CO142779mrvmM8+i18zlmb8NIOlEsXM5Ma73YdpdPodr89ZTWJKmGkGYIHr/0InTEg577yjXuBY6uwhbQwbZroE5Yl3l1bBPl5/XfnC7buv6ZIkx4oV8eXlt3mjjej09Ulq9UwJM37rZ/Lm3kTUk4gmEVGINz8ISXH//coDXxCE8mfBguJxhPIl87bytGNKmFkIoIXrf3MAeW5czDyYmdszc/uwGeusWBLC88Ybpkvgz2GH6aXfYot4yiEI5UqbNqZLYD+lvkFcCMaUMPMZgNZE1IqI6gLoAUBrLcwuu6iloHEuSzNNq1bh4+68c82Voxg6+59k2Htv/TwA5aw2cmTp6W0XZqJs/S+kgyOO8H+Te1o56ijTJbCbkSOTdYwNS+fOanGJrRjp+ph5I4CrALwJYAaAF5i5ZDfMYcOU2WPYMPsHIzfHHBM+rq5GolQaN85/iWApxHXfiNTL7kplyy3jKYcpavplboI+TZrk/t9mG7Ws9uGHzZQnKvXrmznvtdeW9nxeeaV6LkyVG1DvBPzpJ7U30SmnqG0LkmLZsnDx/vWv3Dd024axeRwzv8HMuzLzzszcTycvt2Ygsw9KFOrV0zl7vOy/v9qB9KabogkoZ50VbRfMuDjmGD3hIcOBB+b+v/FG4K67SstLR4VrizDcsWM8+RTbgdgULVoUj1NocPrww/ydcL3Mm1f8RaQ1gbeNZQaQK65QezrVJNtuq5f+iiuAHXeMnq6UNF7OOkutpNxuu2jp9thD3We/Z7tbN2D58sLp7y64A1o4dtxRLbMP066jEEYo8qv3jTfmh+21l9p2IyxpWwRSFkppd4dUijATZTnj6aeHi1dqJ3nggWqH0X79wm+61K+f2gvm5pvVW7/D0qdPfljUzrRjx/yZZin06qVMhDvtpHaPveuu/DeGh0VHmNEVbNu0AXr3Blq31sunGBMmqDd6N2+eGx7FzPTGG8BFF+mX5YMPwse9/vpcn4tNNwW6ds2PF0Yw90sHqPwPPVS1nyAT6BNPKDOu31u/a5rNNsv97x5AanrGvmgR8H//V3r6gQOLr2764Yd8s3HYdnnkkcHHatdWm1x63zydIajvy5zb+7buvn3VRp/FJmNxCGJx3df33lO7WE+erPY8C+Oc7a138+b+by4H8jUzDz4YnK+3HccxqdWhLIQZ94NSijBTp45SsYXh8MPDxYv6TpUMbjVq0HuRvFx/vRKe6tRRr64PYq+9cv9vskn+Ozxq1Qp3zgynn67/GoPatZXP0/PPA3PnKh8CoHShRMdUpOuYd9hhqi3997/6r0GYPRv4+mv1egA3//yn+r70UtWZtWyZPVZMG+Gma1e1aaAuhx0G9OgRLu7mmwNDhmT/v/aa/2QizPb5XkEuQ3vXcgG/QXTzzYELL1S/27Ytfp6oFBPuvX2UW+AqJkzrts/Ms+bmyivD7W1y772qjynWt22zTX4/EnZyV2gSkLk2//gHMGtWvqAadG0ybcDbFm6/PVzZvPfr9deB554rnMaLnzATJJQV4qCD1C70++2n+t1ttgFeeKFwGm+9mYHzz88NO/dc9e0VZq68MnzZevcOPjZkCHDCCcqnsdRJajGsE2YOPDD/nS+6mhkgvOQcVk3rjbfppqoRFnOeywzkAHD22eHO5W6A3sboVmt6t6Qmyq93FJ+Liy9W9ezUSb3qAVC76Qbt3bLDDrn/77hDaZMKbVRVaPfT2rX9HZ/9dsrt0CE4HzdXXx0uXhCZ+9uggcrrxRdLy2f//dWgs8ceSj3tJrMza4bXX1eaiAsvBK65pnjee+wBjB6tfv/pT/5xiqnDM9qVTp3U9wMPFD8voDrWAw9U75qaOhU4+uh8Z8izzlJtc/vtC+f15z+r9ucdxNyTAL+ByqtKD1v2ILzm4PHj1bMehNfHzN25t28PHHKIf7rNNgMefTQ37I9/DF3M/+EVRu68U7WJYmQ2rgwzA/cOoGFXmQatlDr66Fxtz6675p/D2794y+LdeDOsSdkbr23b6OYiv/EliqCQwU/YPeMM9aofb78AqP7VC7PSSo4apbRsl10G9O+vjnmfDb/JQLt2ar8xQDkNA6qPOu+84HJfconqcw4/PNqEKxJxvX67pj9AO548Wb2K/NZbc18jPmlS9jXl331X+JXj11+f/5p35nCvmgeYR43yD2/UiPmuu7L/P/qI+YUXmJs2Zf7Tn7LlO/XU4Lzr1GGurs59Hfy//128TG6qqnKPvfsu8+WXMw8cyPzVV7nH/vIX5kceyQ0bOzbcdQCYn302e97qaualS7NleOMN5gkTmL/+mvmii5iffJL5mGNy08+bx0Xp0SP4/FOnMu+2W/612LgxP+6YMeHqVF0dvv6Zzx/+wNy3L/Ntt6lze3nggeJ5NG+e+/+227Lp778/99i4cYWvWbt2hc+1fn1u/EmTmF9+mXnDBuYlS5ifeUa130J5LFrEPHw4848/ZvOZMKF4Pe+8M7+8LVrkxpk1S4X/5z/F2/3atcyrV+eGX3RRNu82bfLTbbddfhnmz2fecstsnOOPL3zupk3V8/PXvzJ//HF+3iedFJz2+uvz6+Gmqop5+XLm887LjbdyJfOnn+aHefML+hx0kMp/3rzc8I0b1fNZLP1dd6n01dWqvyt0X7xtcNUq5oMPLpz/AQcwr1nDvNlmueHduuX3i8zMrVvnxquqUmVs3Dg3fPBgFb9ly+DrXqhcftfcew2LfaZNyy//zJm5cbbYong+xbj55tz4I0eq8GeeyYaNGBGc/qij8s/n/u8ey5jV8//YY2rcXbs2fLmzxzCJOSYZIa6MavpTp047nj9fXYjbb8+9UBkhh5l5xQr/izl+PPMnnwTfsCFDwjXKV1/N/X/VVWqw+fJL5nXrVAf8yivZ8ngfwrPPzk3ftav63nZbld6P224LLk+bNvnx3ccXLsyGT52ae+yGG5i/+CI37I03cv8/9JD6/uMfVV3dx55/3r+8QXTpkpt+0aLiac4807/ehxyijt9yS+619LsGjz3G/Oab4e4vc3jBNvPZYYfi9dhqq9w07nID+QKLW5jxCrRvv134XPvvnxvf+99P4PIyd27x6+RHx46F0/Xrl5/mhReyxzt3zj3mfV7cdXKTeX5r1coVkvfeOz/tjjv6l335cnW+yy5Tz2Kheuy9dzZddbUaRI45Rj1jzIWF8Fmzsr9POy34Wl5wQW66X35h/vln5s03V/8zwglzuHaauS4bNjA3aKDCdt9dhY0cWTz90KHZ840YwdypkxokvYMwc74wk8HbBwHMtWszjx6tysXMPHFi7vFLL/W/Pjvv7H+O0aPzn39m9ZwGteF69bLhTZrkxps0Kff/unXqnjdtGr6PmDs3v/wLFuTGuekmJRwH5bHffsFtJcODD+amef11FV5VpQTW4cMLP/+dO+dfI/f1cE9gvaxf71/uTF/tJns8PmHGGjPTPvtk1Yhe1VcYM1PHjsreCDiX0IPb8WynnYLL4T138+bKkXbffZVTVc+euT4kXjW3VyXev79S2U2fHuyUdfvt6j0pfjz/fHBZgVwThbcsREpl+re/qfKPHZt/bXr1UmGDB+f6ZgDR/Wu81y6Ms63XxOKlTx/g+OOVucPti/Hss+pan3OO8i2J4hh74YXR9isKcx285j/vviIbN6oVbIAqt1sF7S171L1kvO0qTPpC96aQ6SzIjyWDn9nnlFOUqeeee5QPjZug1RUvvZT7/+KLleP87Nm5+zP51TXoOWvcGHjmGWXKCYqTwf1CTCLlx/HWW1m/NK+fU4YHH1QmktGj1YtzBwwIPof3Wm2yiVrBNWqUavfu9195d2lt0CD3f9u22etSp45y/u7TJ+tv4fUz8/OBcpsRTj0VePddZQqPsthhr72Ab75R73yqqlLO47NmKX+KzDPiNZcEtdegZcRBz0uht0m/+64y7fbqlTWZZ6hVS5nO994bGDRItQ0i1V9ed12+36EffmYm71hVv36+2ffkk9U16tsXePrp4ufx1j0z3myyifKTOffcwv2V37184w1lpi/WL/rle+ih/m4HYcyaUTHy1mxdCgkz3k5om21UQ3B3in7CzE47qc7h7beV34ef7XaPPfLPHWUpG5AvzNSpE24TqkGD1Ovh3S8vq1XLv5z//rda4XTVVbn23qDrdued6gOo5XabbqpeLuddLeLtPKIOqt7GHkaYueEG9TBs2JAbnil7gwbKZ8RLjx65HXKUstatq4TEo45SS1GLcfnlxeN46+5tNxs3qk5xn33UPXUvPy3U3v04//zsKp1u3fIdycMMPoWWPRda0VdMCPC7D7VrB/v6BA1Y3g0lidSWBl78nvWwfm9DhwY7Invbo5c2bZSjtnsJ7DvvZJ/1E05Qn0IE3ffOnbO+Chk6dFAvpTz4YPUMv/QScMAB2ePe63DwwbnXyyvMeP1ERoyItgeJ33XP4Hby9dt+Iuyz2qdP1g/Q/S6wIGGmkD/gIYcAn3+ufnvvea1ayk/T66u5995KGJ0wIdt/BuHnNO0VZurVy+8XatVS1yjsNh3efiaqw7jffWvbNtwrDbzX/bzzgKee8o/77LPKd2b48GjlK0TZCTNE6kEeNEjNbk87Lb/zDnrQzj8/38s7Q8OGalD1vgU06iZD3sYV9sFt0UI5ebnjB63aufZaNTj4aWKKnXvzzdUeHe++m+/Q5a1rVM2MN36xgQ9QQubYsaqjuf76aOdz4zeA16mTO8P2UkjYevpp4OWXleaokBd/hjBC7x/+oJxfvUQVZnr1Um84X7FCaQJKeeljUNtq2LBwOu9yTS9RBWDdTbz8dlodPDhc2kJOvGFeoOedfUbdriHM8+qmfn2l4WUO3+dl8Aov3vtfaIWgX72Kna8QYa/TpZcC06YBc+ZktZp+6TPXrdCz7hc/Q7F+rmNHtd/WBx+ocefSS3OPX3aZ//PvHQuIot9zL974SW6CV2y8cbPvvkrQiVOYscbM5KaY2v2009Qs6PTT43nQTjgBWLJEzXR0NTM6JoMojcXvWNhBsV07JTh4l5jqama81z3stevUSa1c0cFb1oED1Ux20qTcMDeFZjVHHqnMLY89Fk7D5NepZOqUMU8GEVWYqVMHeOQRNZtu2rT0Dm3MGGDPPXPDij07pZiZChH1+fLiFTpmzgR23z1c2kLCdjHNDKBvHiw1fSl9XjHNTKFr4TY/+60k1CWo7JtsosyTr7+eu9w86LqF3U8sqjBDpEyMq1b5a/LCbtFQXZ1/73RN+VHT20xZCDNRO8iowkydOtkBy6Qw40V3phc1va5mJo49TTJELbvffdt0UyW4vf++Mit5TUqFlm7qDkyAWpr+1FNKhVtouatumyl1b5IuXdRM302xpfvepe3enZ2T1sx4ifLumUJtLMxeRt7nI2rddZ9XN8X6PK9Gzfu/UNmHDVPHiZS2Msz5ohA1r6DnxS3YFqpPqQKBn19Mw4bht/1o1UpfGNHtK0zeN12sNDPpPuRRL7J7MNBV4+mqEQvlVQzdhq7bOZuk0IwnaCPEqKr1Qvi1uc02K7w3QwZd4T3O+xRmhv/TT0pjVV2ttJmZvWiAeDQzxZze48Jb1q22Uto8IHgvJTdx3zed+1hMCHU7DG+1VbRnvW1b5c/3++9ZX6Y0CjNnnZVtO5lNE8Okr0ntxjnnKKfzVq3U5MGrPdI15Zt4XUeGpN8TZ6Uwk4RmJuO8R6ScaYPOrSs56zS2pDUzuipQkw9WKRq1Qm/yjjqw6DzYSWsiCxGmHlttld0Izu2wDsSjmTnjjGh5lIq3rMcfr/yj6tRRO7BGTZ9mzUzt2sqR9bnn1Csuxo+Pdu5i5kUdorbfoAnjffcBCxeqyen994dPX5PCzNChaqFC+/bKlOd11k9aMxMnIsyEQPeGhbnI112nnG5btQpnjw1LmjQzJmeKuuiWPUwn0aiR6txffBFYvRoYNy44v5okTdc9agel2979hJko9z7OycImm4TfSRrQnyUnrd3o2DH7AtP33889ZpO5Iqifa95cCWxR09ekMFOvnlpxGHRuXXN22ic+cWKRoSBLEjesXj21Jt+7tbgpp74weRVDd2ApJ81M2LKfdZZaHedtB0l2EmnqoJIWoHUdgHWIe2WJSSE0LoGgps4XZ15x99FJOtHG7QBs08RHFxFmEj53JWtm0qTJSbqTKBczU1RqQjOTFLplT5P/Qlymmpo6X5x5pUmY0b3u4jMTnrIQZpJ80NKkmUnaZ0b3IY/zwUq67CZnPGmabVWSZsa08B8nSWtm4iRp02aSPjNeTPdTJic+upSFMFOpmpmopMnfJ2niHphsanMmzUzlpJmpZGFGNDPJYFqDbDNWVtXmgcXm1Uxp0sxExfQsu1KFGZtNk16i1j1NKn9dc4f4zCRDOZk2kyZFXUV4TD5ocaswdTrrpFXHcdddB9NlNylA26Q6jrvN2USa7ltUU02aZvhJ+/uYFGZMm5lsRquqRHQGEU0nomoiau85diMRzSGiWUR0nCu8HRFNdY4NJIreXdk8S46zsVXSQ66L6ftmss3FiU1mVdOkaZactBY3TpLWzMTpM5O0A3CatLhJo9u1TANwKoAP3IFEtCeAHgDaAOgCYBARZW7LwwB6AmjtfLpEPanNZibRzJjBtON2uZiZomJaM5Mmp3ObBLk0aZVMm5mSvG/iM1M6WlVl5hnMPMvnUHcAzzHzemb+FsAcAB2IqAmA+sz8CTMzgCcBnBy50JodZJzLZE0+KEnbwdPkM2PaX8gmAdrmpdm6bcakv1A5vf5DfGaSoZyWZifd79TU49UMwALX/4VOWDPntzfcFyLqSUSTiGjSihUr/hdu88Bi8xJfm4UZ0yu5TPrMxInp624TNpsHbdbMmPaP08H0ZNlmM1PRXRyI6G0A2/scupmZXwlK5hPGBcJ9YebBAAYDQPv27f8Xz2aVf5wPStKaGdOzbB1MC6GimfH/HzW97vmTJE1CaFTS1OaS1syYRMxMpVNUmGHmziXkuxBAC9f/5gAWO+HNfcIjkSbNjE1mprgHdJuXZtu8mqmSlmbrkiYzk01aJpsdt023OR3KycyUNDV1m18F0IOI6hFRKyhH3/8y8xIAa4joIGcV0wUAgrQ7gdg8sJh0ADa9rNxmnxmTvhtp6pyT9jWyuTO2WeWfprJXkmbG9NJsk/dNF92l2acQ0UIABwN4nYjeBABmng7gBQBfAxgLoBczVznJrgTwGJRT8FwAYyIXWjQzJWFaM2MS0w95uWhmomJaADYpDFWyA3CcmJ60JUnc22fYPBmIitabT5j5ZQAvBxzrB6CfT/gkAHvpnNdm/wUv4jOTDKYf8nIRZirZAThprVSc2OQjpptXmjQzutfBpsmyaaysapo0MzbNWGQ1U/D/uM/npVzMTFExbd6LE9v8hXSo5KXZaSJpPy2bVzNZeZvTJMzYZAePe68Vm2bZptXmopnx/1/O2OyMmab7lrSZKU3YrJmxymfGFLo3LM5N82zWzOjOkm1ezWTzwGLTbKucNDNRSdPAEpU0tTndfs6mfsqL7DMTHoseryxp0szYJMzE7Vxm02om0wNLubQ527R5JttcmlT+SfvHpUmY+cMf4itL0lTSdgC6iDCjee5Kmm3ZrJkxbWYy+QoNm5f4mvRV0qWS+4o40RVm6tWLryxR0W1/tk3aTGJlVW3eZyZN23xX0oNic9nLaYYvZiY7sFkz4y27zZqZpJdmV+w+M6bQ3b+hXDQzpoUZm1cz2eQAXNuzgUKaNFzFMK2ZsdnM9Pvv0eLHic2DYpo0M7pU0oRTFyurWqdO7v9K1cwkTTntM5P0Q65jZqpbN/e/TWYm0+a9OEl6YNmwIVr8OLFZM6PrMxNnG03azGRyom8aK4UZ3ZlquThjJr0rbZo0M1HRHVQ32yy+skTFpPDuxTbNjLevSBJdzcz69fGVxTZNphtdDXRUzUycz8vGjXrpkzYzVVUVj5NWrBRm0qSZsWnGokuaNDNJv7Nk112jxfeic6/SJMxExXSbMSnM2KyZsbmf85rnTJpafvtNL33Sk4c4hRnxmQmBt3M36TMTtbHpSupuKlmYiTpI6d63gw8G9nJewtGjR7S0QLzCjMnOOekZfpqEmaRV/nFqZqJi8w7Auvdct815zcI6RG0zutpA0cwkjK6ZyeSmeTY3Fi8mVc9Ja2Zq1QI+/BB4+23gySejpQXi9ZmxSTMTt5npsceipU+TZibqfbNZMxMnUdtv48bAmWeq3337xl+eYmy6aXx5Jb0XmE4/ZRorhRmTandd7YTNmpmkndkKoeuvU0pZGjQAjj46v/3VNGkyM+lqVnTNdR07RosfpzCjK4iZ9JmJSpoct0tpv889ByxbBtx3X/zlKUacS8GT1oTaPNm2UpjxdlA2mZlstkmmSZjRNTPZtAOwzWYmAPjzn1WZr74aaN5c73xR6x6nMKMrQEdtAzvtFC1+lLIUI02rYkrJiwjYdtv4yhCFNAkz4jOTctLkAGzSZ0aXqNchTcKMrpnJph2AbTYzAUD//sDatcDAgdHT6moITGpmvES9D/fdB2yzjVqN8957eueOindAjnrdmzbN/o76rHox3X6jcuyx2d/77aeXV9KrmWw2Mxm0KJdOmpZmV5LkK8KMGXQHZJNmpgylblyWJs2MrjAT1ZeiSRNgwQK1IqZhQ71zR8V7v6LWfdgwYN991eRt3Di9sphe6BCV/v2BKVOAVauAp59Otiy6wr+YmRLGpKSv29DTJMxE7eh1z3fZZdnfp52ml1fUsusOirrE2eZs7nCiYrswM2oU0KkT8Mwzpa1y2XTT5AUZQF+Y2WMP4PvvgXnzVP112HFHvfRJs9VWwMSJwKxZ6jrokPSKUZv7Fis1MzarLU03lo4dgY8+AurXB7p3j5ZW97q1OPMZMwAADllJREFUbw889RQwbRrQp49eXjZt2Bc3tqnddUiTmamUfqd79+jPWU0Q9bp5hZlSnp/tt4+eJsPYsUC3bqqfuvfe0vMxSRx9TtJbGaRpsh0VrfkpEfUnoplE9BURvUxEDVzHbiSiOUQ0i4iOc4W3I6KpzrGBRNEvv24H1a5d9vcuu+jlFfWGmV7NNGIE8OCDwOTJagZR0+fzct55wN136zvn6Qq0tpHZ2+aII9TS0yikwcwUF1FnqvXrmzu3zehqZnQ57jhg0SJlZova3ssJm4WZpNFtouMA7MXM+wD4BsCNAEBEewLoAaANgC4ABhFRZvh5GEBPAK2dT5eoJ9UdyAYPVg5qjRoBI0fq5RV1oDAt+W63HXDVVcDOOydzvprC5P4hJhg+XKmuS/E/2GGH+MuTFLqamQEDsgPxI4/olaWShRkTQmzjxvHu2RIW0wK7G5veIWcarUvFzG8xc0bX8CmAzMLL7gCeY+b1zPwtgDkAOhBREwD1mfkTZmYATwI4Oep5t9hCp9RAixbAd98BCxcCe++tl1dUTGtmbDpfIWzWzJTSWdaqBXToUNoeNwMGqD1yatdW6nsdku7odX1mWrUCvv4aePddoGdPvbKIMCMkTdQ217Ah0KaN+h11TybA/GRbhzjnt5cAeN753QxKuMmw0An73fntDY9E7drAa68Bjz8OXHllaYWNa+Mzk5qZpCknYSZN7yuqabbfXgnuv/yiNHM6mBZmSjn/brupjy42C9BRiXNLfqF0SnEAHjMGeOON0ny1bB6figozRPQ2AD9XrpuZ+RUnzs0ANgLILETz63K4QHjQuXtCmaSwg0dXfuKJ6mOaqIPiZZcpkwEAnHpqsufWJSPxA2r/C5N06GD2/DqYmOVuvrn66GJamLFtw8C0ELXsJsw7Qj6ltLkWLYDLLy/tfDvtBKxcqX6b7uOjUrRrYObOzLyXzycjyFwI4EQA5zqmI0BpXFq4smkOYLET3twnPOjcg5m5PTO3b1wmXmBHHAE8/DBw3XXAoEF6eSUtzDRooCT+yy8Hxo9P9twAMGECsPvuwDnnlPayx7Rg86BoGpPXrpLMTJtsot5F1rMn8MknpktTuSTd3ocNU4Js3brA669HT+9eeda/f3zlCoOWmYmIugD4K4AjmHmt69CrAJ4hogEAmkI5+v6XmauIaA0RHQRgIoALADyoUwbTlCJQXHFF/OVIiq5d1ccEHTsCM2aYOXeciDATnjRpZirJzAQAhx6qPpVGmp7PpNv7HnuoVWQbN5a2iuyaa5RZu0ULYM894y9fIXQv1UMAtgQwjoi+JKJHAICZpwN4AcDXAMYC6MXMGWvclQAeg3IKngtgjGYZjGLS9yJNPiy2UUk+M7q49wS66aZkz50mYaaSNDOVTJr6VRN9RcOGpS+Hr1cPOP984MgjYy1SKLQ0M8wcuEsLM/cD0M8nfBKAvXTOW8m89BJw+unq94gRZstiMyLMhOe225TTff36wCWXJHvuNL292TZhpkULtU8LYLePWSXTpInpEthDhe3WET9JD4onnwy8+KL6nYadRYXo2CbM1K8P3HOPmXOLZqZ0XnsNOP54YMstgfvvN10aezD9fD76KNC7N3DSSWrXdCEcIsxYRq1aWc2MYCemO0ubSJNmxjafmX33BebPV+WWNmcPl10GXHhhfNuHVAqWzTXSR5rsq0J6cS+VvOoqc+WwHZPaERuXK9euLYKMjYggEx3RzGjSvHnxOEL60HkJXin885/AunWqk7r11mTPbTOmNTM33KDeJdaokXqvmCAI6UQ0MyUwahSwzz5qgGrRonh8IR2MGKHuW//++jvhRqVhQ7WHw2OP6b+Oo5Iw7TPTrx/w3ntqSwAbNTOCUCmIZqYEuncX51sbOfVU/V2XhWQxrZnZZBMzy0wFc4jQaieimREEIbWY1swIlcfll6sVfABwyy1myyKERzQzgiBYgwgzQk2zxRbAzJnqbeuilbMHEWYEQUgtps1MQmXSpIlsWGcbMs8RBCG1iJlJEIQwSNcgCEJqEc2MIAhhEGFGEARrEGFGEAQ/RJgRBCG1yA7bgiCEQYQZQRBSiwgzgiCEQYQZQRAEQRCsRoQZQRBSi2hmBEEIgwgzgiCkFhFmBEEIgwgzgiCkFhFmBEEIgwgzgiCkFhFmBEEIg5YwQ0R3EtFXRPQlEb1FRE1dx24kojlENIuIjnOFtyOiqc6xgUSyc4QgCIIgCKWjq5npz8z7MHNbAKMB3AoARLQngB4A2gDoAmAQEdVy0jwMoCeA1s6ni2YZBEEoU0QzIwhCGLSEGWZe7fq7OYBM19MdwHPMvJ6ZvwUwB0AHImoCoD4zf8LMDOBJACfrlEEQBEEQhMpG+63ZRNQPwAUAfgbQyQluBuBTV7SFTtjvzm9veFDePaG0ONhhhx10iyoIgmWIZkYQhDAU1cwQ0dtENM3n0x0AmPlmZm4B4GkAV2WS+WTFBcJ9YebBzNyemds3bty4eG0EQSgrRJgRBCEMRTUzzNw5ZF7PAHgdwG1QGpcWrmPNASx2wpv7hAuCIOQhwowgCGHQXc3U2vX3JAAznd+vAuhBRPWIqBWUo+9/mXkJgDVEdJCziukCAK/olEEQhPJFhBlBEMKg6zNzNxHtBqAawHwAVwAAM08nohcAfA1gI4BezFzlpLkSwBMANgUwxvkIgiAIgiCUhJYww8ynFTjWD0A/n/BJAPbSOa8gCJWBaGYEQQiD7AAsCEJqEWFGEIQwiDAjCEJqEWFGEIQwiDAjCIIgCILViDAjCEJqEc2MIAhhEGFGEARBEASrEWFGEITUIpoZQRDCIMKMIAippbradAkEQbABEWYEQRAEQbAaEWYEQUgtYmYSBCEMIswIgiAIgmA1IswIgpBaRDMjCEIYRJgRBCG1iDAjCEIYRJgRBCG1HH109vf++5srhyAI6UbrrdmCIAg1yfbbA2PGAO+9B1x5penSCIKQVkSYEQQh1XTpoj6CIAhBiJlJEARBEASrEWFGEARBEASrEWFGEARBEASrEWFGEARBEASrEWFGEARBEASrEWFGEARBEASrIbZki00iWgNglulyGKARgB9MF8IQUvfKROpeeVRqvYHKrvtuzLxlHBnZtM/MLGZub7oQSUNEkyqx3oDUXepeeVRq3Su13oDUPa68xMwkCIIgCILViDAjCIIgCILV2CTMDDZdAENUar0BqXulInWvPCq13oDUPRascQAWBEEQBEHwwybNjCAIgiAIQh6pF2aIqAsRzSKiOUR0g+nyxA0RtSCi94hoBhFNJ6JrnfDbiWgREX3pfI53pbnRuR6ziOg4c6XXh4i+I6KpTh0nOWFbE9E4IprtfDd0xbe+7kS0m+u+fklEq4mod7necyIaSkTLiWiaKyzyPSaidk5bmUNEA4mIkq5LVALq3p+IZhLRV0T0MhE1cMJbEtE61/1/xJWmXOoeuY2XUd2fd9X7OyL60gkvm/teYDyr+eedmVP7AVALwFwAOwGoC2AKgD1NlyvmOjYBsL/ze0sA3wDYE8DtAP7sE39P5zrUA9DKuT61TNdDo/7fAWjkCbsXwA3O7xsA3FOOdXfqVAvAUgA7lus9B3A4gP0BTNO5xwD+C+BgAARgDICuputWYt2PBVDb+X2Pq+4t3fE8+ZRL3SO38XKpu+f4/QBuLbf7juDxrMaf97RrZjoAmMPM85h5A4DnAHQ3XKZYYeYlzDzZ+b0GwAwAzQok6Q7gOWZez8zfApgDdZ3Kie4Ahjm/hwE42RVebnU/GsBcZp5fII7V9WbmDwD86AmOdI+JqAmA+sz8Caue7klXmtTiV3dmfouZNzp/PwXQvFAe5VT3ApT9fc/gaBjOBPBsoTxsrHuB8azGn/e0CzPNACxw/V+IwgO91RBRSwD7AZjoBF3lqKKHutRy5XZNGMBbRPQ5EfV0wrZj5iWAejgAbOuEl1vdAaAHcju1SrjnQPR73Mz57Q23nUugZp0ZWhHRF0T0PhEd5oSVW92jtPFyqzsAHAZgGTPPdoWV3X33jGc1/rynXZjxs5GV5fIrItoCwAgAvZl5NYCHAewMoC2AJVBqSaD8rklHZt4fQFcAvYjo8AJxy6ruRFQXwEkAXnSCKuWeFyKormV3DYjoZgAbATztBC0BsAMz7wegD4BniKg+yqvuUdt4OdU9w9nIncCU3X33Gc8Co/qElXTf0y7MLATQwvW/OYDFhspSYxBRHagb/zQzjwQAZl7GzFXMXA3gUWTNCmV1TZh5sfO9HMDLUPVc5qgZM6rW5U70sqo7lAA3mZmXAZVzzx2i3uOFyDXHWH0NiOhCACcCONdRo8NRta90fn8O5T+wK8qo7iW08bKpOwAQUW0ApwJ4PhNWbvfdbzxDAs972oWZzwC0JqJWziy2B4BXDZcpVhz76RAAM5h5gCu8iSvaKQAyXvGvAuhBRPWIqBWA1lCOUtZBRJsT0ZaZ31COkdOg6nihE+1CAK84v8um7g45M7RKuOcuIt1jRzW9hogOcp6ZC1xprIKIugD4K4CTmHmtK7wxEdVyfu8EVfd5ZVb3SG28nOru0BnATGb+nwmlnO570HiGJJ53097PxT4AjofyiJ4L4GbT5amB+h0KpT77CsCXzud4AE8BmOqEvwqgiSvNzc71mIWUe7cXqftOUJ7sUwBMz9xfANsAeAfAbOd76zKs+2YAVgLYyhVWlvccSmBbAuB3qBnXpaXcYwDtoQa/uQAegrPpZ5o/AXWfA+UnkHneH3HinuY8B1MATAbQrQzrHrmNl0vdnfAnAFzhiVs29x3B41mNP++yA7AgCIIgCFaTdjOTIAiCIAhCQUSYEQRBEATBakSYEQRBEATBakSYEQRBEATBakSYEQRBEATBakSYEQRBEATBakSYEQRBEATBakSYEQRBEATBav4f7slfwC6Omo0AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 648x252 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# choose default wavelet function \n",
"scg.set_default_wavelet('morl')\n",
"\n",
"nn = 2\n",
"signal_length = 2000\n",
"# range of scales to perform the transform\n",
"scales = scg.periods2scales( np.arange(1, signal_length+1) )\n",
"x_values_wvt_arr = range(0,len(ecg_data[nn]),1)\n",
"\n",
"# plot the signal \n",
"fig1, ax1 = plt.subplots(1, 1, figsize=(9, 3.5)); \n",
"ax1.plot(x_values_wvt_arr, ecg_data[nn], linewidth=3, color='blue')\n",
"ax1.set_xlim(0, signal_length)\n",
"ax1.set_title(f\"Signal class ECG: {ecg_labels[nn]}\")\n",
"\n",
"# the scaleogram\n",
"dav = scg.cws(ecg_data[nn][:signal_length], scales=scales, figsize=(10, 4.0), coi = False, ylabel=\"Period\", xlabel=\"Time\",\n",
" title=f\"Class ECG {ecg_labels[nn]}: scaleogram with linear period\"); \n",
"\n",
"print(\"Default wavelet function used to compute the transform:\", scg.get_default_wavelet(), \"(\",\n",
" pywt.ContinuousWavelet(scg.get_default_wavelet()).family_name, \")\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# ICI c'est le bac à sable"
]
},
{
"cell_type": "code",
"execution_count": 135,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Array size 7 cut by 2 done 4\r",
"[[1. 2.]\n",
" [3. 4.]\n",
" [5. 6.]\n",
" [7. 0.]]\n",
"Array size 7 cut by 2 done 4\r",
"(2,) (4, 2)\n",
"Array size 7 cut by 2 done 4\r"
]
},
{
"data": {
"text/plain": [
"array([[0., 0.],\n",
" [1., 2.],\n",
" [3., 4.],\n",
" [5., 6.],\n",
" [7., 0.]])"
]
},
"execution_count": 135,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Test to validate ecgreshape\n",
"result = np.zeros(9)\n",
"result[:a.shape[0]] = a\n",
"np.reshape(result, (3, 3))\n",
"#print(ecgreshape(a,5))\n",
"b=[[1,2,2]]\n",
"b.append([3,8,6])\n",
"b=[np.zeros(2)]\n",
"print(ecgreshape(a,2))\n",
"print(b[0].shape,ecgreshape(a,2).shape)\n",
"np.concatenate((b,ecgreshape(a,2)), axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 5000 5000\n",
"5000 10000 5000\n",
"10000 15000 5000\n"
]
}
],
"source": [
"#Essai pour boucle while\n",
"sample_start=0\n",
"sample_end=sample_size\n",
"ex=15789\n",
"while sample_end < ex:\n",
" print(sample_start,sample_end,sample_size)\n",
" sample_start=sample_end\n",
" sample_end+=sample_size"
]
},
{
"cell_type": "code",
"execution_count": 182,
"metadata": {},
"outputs": [],
"source": [
"a = np.array([1,2,3,4,5,6,7,8,9,10])"
]
},
{
"cell_type": "code",
"execution_count": 223,
"metadata": {},
"outputs": [],
"source": [
"b = a[::4] "
]
},
{
"cell_type": "code",
"execution_count": 224,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1, 5, 9])"
]
},
"execution_count": 224,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b"
]
},
{
"cell_type": "code",
"execution_count": 186,
"metadata": {},
"outputs": [],
"source": [
"c = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]])"
]
},
{
"cell_type": "code",
"execution_count": 221,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 1, 2, 3, 4],\n",
" [ 5, 6, 7, 8],\n",
" [ 9, 10, 11, 12]])"
]
},
"execution_count": 221,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"c"
]
},
{
"cell_type": "code",
"execution_count": 222,
"metadata": {},
"outputs": [],
"source": [
"d = c[::4]"
]
},
{
"cell_type": "code",
"execution_count": 199,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 1, 2, 3, 4],\n",
" [ 9, 10, 11, 12]])"
]
},
"execution_count": 199,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d"
]
},
{
"cell_type": "code",
"execution_count": 213,
"metadata": {},
"outputs": [],
"source": [
"d=[]\n",
"for arr in c:\n",
" d.append(arr[::2])"
]
},
{
"cell_type": "code",
"execution_count": 214,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[array([1, 3]), array([5, 7]), array([ 9, 11])]"
]
},
"execution_count": 214,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d"
]
},
{
"cell_type": "code",
"execution_count": 220,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1])"
]
},
"execution_count": 220,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from scipy.interpolate import interp1d\n",
"xp = np.arange(1, len(c), 2)\n",
"xp"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Work on 105001_ANN for notations analysis"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"record = wfdb.rdrecord('100001_ECG', pn_dir='butqdb/100001/', sampfrom=0, sampto=20000)"
]
},
{
"cell_type": "code",
"execution_count": 320,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('https://physionet.org/files/butqdb/1.0.0/105001/105001_ANN.csv', names=header_list)"
]
},
{
"cell_type": "code",
"execution_count": 321,
"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>start1</th>\n",
" <th>end1</th>\n",
" <th>class1</th>\n",
" <th>start2</th>\n",
" <th>end2</th>\n",
" <th>class2</th>\n",
" <th>start3</th>\n",
" <th>end3</th>\n",
" <th>class3</th>\n",
" <th>start</th>\n",
" <th>end</th>\n",
" <th>class</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1.0</td>\n",
" <td>47323379.0</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>47323871.0</td>\n",
" <td>3.0</td>\n",
" <td>1</td>\n",
" <td>47323500</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>47323500.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>47323380.0</td>\n",
" <td>47388207.0</td>\n",
" <td>2.0</td>\n",
" <td>47323872.0</td>\n",
" <td>47329547.0</td>\n",
" <td>1.0</td>\n",
" <td>47323501</td>\n",
" <td>47323539</td>\n",
" <td>1</td>\n",
" <td>47323501.0</td>\n",
" <td>47326788.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>47388208.0</td>\n",
" <td>47404719.0</td>\n",
" <td>1.0</td>\n",
" <td>47329548.0</td>\n",
" <td>47333899.0</td>\n",
" <td>2.0</td>\n",
" <td>47323540</td>\n",
" <td>47326788</td>\n",
" <td>2</td>\n",
" <td>47326789.0</td>\n",
" <td>47329547.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>47404720.0</td>\n",
" <td>47449035.0</td>\n",
" <td>2.0</td>\n",
" <td>47333900.0</td>\n",
" <td>47370615.0</td>\n",
" <td>1.0</td>\n",
" <td>47326789</td>\n",
" <td>47329715</td>\n",
" <td>1</td>\n",
" <td>47329548.0</td>\n",
" <td>47333904.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>47449036.0</td>\n",
" <td>47492819.0</td>\n",
" <td>1.0</td>\n",
" <td>47370616.0</td>\n",
" <td>47377747.0</td>\n",
" <td>2.0</td>\n",
" <td>47329716</td>\n",
" <td>47333904</td>\n",
" <td>2</td>\n",
" <td>47333905.0</td>\n",
" <td>47370615.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" start1 end1 class1 start2 end2 class2 start3 \\\n",
"0 1.0 47323379.0 3.0 1.0 47323871.0 3.0 1 \n",
"1 47323380.0 47388207.0 2.0 47323872.0 47329547.0 1.0 47323501 \n",
"2 47388208.0 47404719.0 1.0 47329548.0 47333899.0 2.0 47323540 \n",
"3 47404720.0 47449035.0 2.0 47333900.0 47370615.0 1.0 47326789 \n",
"4 47449036.0 47492819.0 1.0 47370616.0 47377747.0 2.0 47329716 \n",
"\n",
" end3 class3 start end class \n",
"0 47323500 3 1.0 47323500.0 3.0 \n",
"1 47323539 1 47323501.0 47326788.0 2.0 \n",
"2 47326788 2 47326789.0 47329547.0 1.0 \n",
"3 47329715 1 47329548.0 47333904.0 2.0 \n",
"4 47333904 2 47333905.0 47370615.0 1.0 "
]
},
"execution_count": 321,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 322,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3495"
]
},
"execution_count": 322,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df)"
]
},
{
"cell_type": "code",
"execution_count": 323,
"metadata": {},
"outputs": [],
"source": [
"finaltime = np.concatenate((df.start1,df.end1,df.start2,df.end2,df.start3,df.end3,df.start,df.end), axis=0)\n",
"finalclass = np.concatenate((df.class1,df.class1,df.class2,df.class2,df.class3,df.class3,df['class'],df['class']), axis=0)\n",
"finalope = np.concatenate((np.full(len(df)*2,1),np.full(len(df)*2,2),np.full(len(df)*2,3),np.full(len(df)*2,4)),axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 324,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(27960,)"
]
},
"execution_count": 324,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"finalope.shape"
]
},
{
"cell_type": "code",
"execution_count": 325,
"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>time</th>\n",
" <th>class</th>\n",
" <th>operator</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>47323380</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>47388208</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>47404720</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>47449036</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" time class operator\n",
"0 1 3 1\n",
"1 47323380 2 1\n",
"2 47388208 1 1\n",
"3 47404720 2 1\n",
"4 47449036 1 1"
]
},
"execution_count": 325,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"columns = ['time','class','operator']\n",
"data = np.stack((finaltime, finalclass,finalope), axis=1)\n",
"dfclass = pd.DataFrame(data=data, columns=columns)\n",
"dfclass[\"class\"].fillna(0, inplace=True)\n",
"dfclass.dropna(inplace=True)\n",
"dfclass=dfclass.astype({'time': 'int32','class': 'int32','operator': 'int32'})\n",
"dfclass.head()"
]
},
{
"cell_type": "code",
"execution_count": 326,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"time 0\n",
"class 0\n",
"operator 0\n",
"dtype: int64"
]
},
"execution_count": 326,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#dataannall[\"class1\"].fillna(0, inplace=True)\n",
"dfclass.isna().sum()"
]
},
{
"cell_type": "code",
"execution_count": 327,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"13128"
]
},
"execution_count": 327,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dfclass)"
]
},
{
"cell_type": "code",
"execution_count": 328,
"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>time</th>\n",
" <th>class</th>\n",
" <th>operator</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6990</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13980</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20970</th>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3495</th>\n",
" <td>47323379</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>47323380</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17475</th>\n",
" <td>47323500</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24465</th>\n",
" <td>47323500</td>\n",
" <td>3</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13981</th>\n",
" <td>47323501</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20971</th>\n",
" <td>47323501</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17476</th>\n",
" <td>47323539</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13982</th>\n",
" <td>47323540</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10485</th>\n",
" <td>47323871</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6991</th>\n",
" <td>47323872</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24466</th>\n",
" <td>47326788</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17477</th>\n",
" <td>47326788</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13983</th>\n",
" <td>47326789</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20972</th>\n",
" <td>47326789</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10486</th>\n",
" <td>47329547</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24467</th>\n",
" <td>47329547</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" time class operator\n",
"0 1 3 1\n",
"6990 1 3 2\n",
"13980 1 3 3\n",
"20970 1 3 4\n",
"3495 47323379 3 1\n",
"1 47323380 2 1\n",
"17475 47323500 3 3\n",
"24465 47323500 3 4\n",
"13981 47323501 1 3\n",
"20971 47323501 2 4\n",
"17476 47323539 1 3\n",
"13982 47323540 2 3\n",
"10485 47323871 3 2\n",
"6991 47323872 1 2\n",
"24466 47326788 2 4\n",
"17477 47326788 2 3\n",
"13983 47326789 1 3\n",
"20972 47326789 1 4\n",
"10486 47329547 1 2\n",
"24467 47329547 1 4"
]
},
"execution_count": 328,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfclass=dfclass.sort_values('time')\n",
"dfclass.head(20)"
]
},
{
"cell_type": "code",
"execution_count": 329,
"metadata": {},
"outputs": [],
"source": [
"arrmissing=[]\n",
"timref = 1\n",
"ope1 = -1\n",
"ope2 = -1\n",
"ope3 = -1\n",
"ope4 = -1\n",
"for i in dfclass.index:\n",
" if timref != dfclass.time[i]:\n",
" if ope1 < 0:\n",
" arrmissing.append([timref,ope1last,1])\n",
" #print(f\"missing1 {timref} alors j'affecte {ope1last}\")\n",
" else:\n",
" ope1last = ope1\n",
" if ope2 < 0:\n",
" arrmissing.append([timref,ope2last,2])\n",
" #print(f\"missing2 {timref} alors j'affecte {ope2last}\")\n",
" else:\n",
" ope2last = ope2\n",
" if ope3 < 0:\n",
" arrmissing.append([timref,ope3last,3])\n",
" #print(f\"missing3 {timref} alors j'affecte {ope3last}\")\n",
" else:\n",
" ope3last = ope3\n",
" if ope4 < 0:\n",
" arrmissing.append([timref,ope4last,4])\n",
" #print(f\"missing4 {timref} alors j'affecte {ope4last}\")\n",
" else:\n",
" ope4last = ope4 \n",
" ope1 = -1\n",
" ope2 = -1\n",
" ope3 = -1\n",
" ope4 = -1\n",
" if dfclass.operator[i] == 1:\n",
" ope1 = dfclass['class'][i]\n",
" if dfclass.operator[i] == 2:\n",
" ope2 = dfclass['class'][i]\n",
" if dfclass.operator[i] == 3:\n",
" ope3 = dfclass['class'][i]\n",
" if dfclass.operator[i] == 4:\n",
" ope4 = dfclass['class'][i] \n",
" timref = dfclass.time[i]\n",
" \n",
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 341,
"metadata": {},
"outputs": [],
"source": [
"dfclassmissing = pd.DataFrame(data=arrmissing, columns=columns)\n",
"dffinal = pd.concat([dfclassmissing,dfclass])\n",
"dffinal = dffinal.sort_values('time').reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 342,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"class 4\n",
"operator 4\n",
"dtype: int64"
]
},
"execution_count": 342,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dffinal.groupby(['time']).count().min()"
]
},
{
"cell_type": "code",
"execution_count": 343,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" <th>3</th>\n",
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" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>47323379</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>47323380</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>47323500</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>47323501</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41577</th>\n",
" <td>139120079</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41578</th>\n",
" <td>139120080</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41582</th>\n",
" <td>139146832</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41589</th>\n",
" <td>139146833</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41591</th>\n",
" <td>139147000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10398 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" time class operator\n",
"3 1 3 1\n",
"4 47323379 3 1\n",
"10 47323380 2 1\n",
"14 47323500 2 1\n",
"19 47323501 2 1\n",
"... ... ... ...\n",
"41577 139120079 1 1\n",
"41578 139120080 3 1\n",
"41582 139146832 3 1\n",
"41589 139146833 3 1\n",
"41591 139147000 3 1\n",
"\n",
"[10398 rows x 3 columns]"
]
},
"execution_count": 343,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dffinal[(dffinal['operator'] == 1)])\n",
"dffinal[(dffinal['operator'] == 1)].sort_values('time')"
]
},
{
"cell_type": "code",
"execution_count": 344,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" <th>class</th>\n",
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" <tr>\n",
" <th>time</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
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" <tr>\n",
" <th>1</th>\n",
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" </tr>\n",
" <tr>\n",
" <th>104919040</th>\n",
" <td>1</td>\n",
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" </tr>\n",
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" <th>104919041</th>\n",
" <td>1</td>\n",
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" <th>104919775</th>\n",
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" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104919776</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77451144</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77451145</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77477720</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>111664608</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>81233304</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10398 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" class operator\n",
"time \n",
"1 1 1\n",
"104919040 1 1\n",
"104919041 1 1\n",
"104919775 1 1\n",
"104919776 1 1\n",
"... ... ...\n",
"77451144 1 1\n",
"77451145 1 1\n",
"77477720 1 1\n",
"111664608 2 2\n",
"81233304 2 2\n",
"\n",
"[10398 rows x 2 columns]"
]
},
"execution_count": 344,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dffinal[(dffinal['operator'] == 2)])\n",
"dffinal[(dffinal['operator'] == 2)].groupby(['time']).count().sort_values('class')"
]
},
{
"cell_type": "code",
"execution_count": 347,
"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>time</th>\n",
" <th>class</th>\n",
" <th>operator</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>17536</th>\n",
" <td>81233304</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28177</th>\n",
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" <td>2</td>\n",
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" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" time class operator\n",
"17536 81233304 2 2\n",
"28177 111664608 2 2"
]
},
"execution_count": 347,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dffinal.drop([17540,28176], inplace=True)\n",
"dffinal[((dffinal['time'] == 111664608) | (dffinal['time'] == 81233304)) & (dffinal['operator'] == 2)]\n",
"#len(dffinal[(dffinal['operator'] == 2)])"
]
},
{
"cell_type": "code",
"execution_count": 348,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10398"
]
},
"execution_count": 348,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dffinal[(dffinal['operator'] == 3)])"
]
},
{
"cell_type": "code",
"execution_count": 349,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10398"
]
},
"execution_count": 349,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dffinal[(dffinal['operator'] == 4)])"
]
},
{
"cell_type": "code",
"execution_count": 350,
"metadata": {},
"outputs": [],
"source": [
"data = np.stack(([dffinal[(dffinal['operator'] == 1)]['time'].values,\n",
" dffinal[(dffinal['operator'] == 1)]['class'].values,\n",
" dffinal[(dffinal['operator'] == 2)]['class'].values,\n",
" dffinal[(dffinal['operator'] == 3)]['class'].values,\n",
" dffinal[(dffinal['operator'] == 4)]['class'].values]), axis=1)\n",
"#data = np.stack((finaltime, finalclass,finalope), axis=1)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 351,
"metadata": {},
"outputs": [],
"source": [
"dataannall = pd.DataFrame(data=data, columns=['time','class1','class2','class3','class'])"
]
},
{
"cell_type": "code",
"execution_count": 353,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Choix opérateur 1 dans choix final \t\t: 8929\t/ 10398\t85.87%\n",
"Choix opérateur 2 dans choix final \t\t: 9298\t/ 10398\t89.42%\n",
"Choix opérateur 3 dans choix final \t\t: 6408\t/ 10398\t61.63%\n",
"Choix opérateur 1 & 2 dans choix final \t\t: 7830\t/ 10398\t75.3%\n",
"Choix opérateur 1 & 3 dans choix final \t\t: 4939\t/ 10398\t47.5%\n",
"Choix opérateur 2 & 3 dans choix final \t\t: 5316\t/ 10398\t51.13%\n",
"Choix opérateur 1 & 2 & 3 dans choix final \t: 3848\t/ 10398\t37.01%\n"
]
}
],
"source": [
"#dataannall['class_vote'] = \n",
"class1_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class12_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class1'] == dataannall['class2']) & (dataannall['class'] > 0)])\n",
"class13_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class']) & (dataannall['class1'] == dataannall['class3']) & (dataannall['class'] > 0)])\n",
"class2_ds_f = len(dataannall[(dataannall['class2'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class23_ds_f = len(dataannall[(dataannall['class2'] == dataannall['class']) & (dataannall['class2'] == dataannall['class3']) & (dataannall['class'] > 0)])\n",
"class3_ds_f = len(dataannall[(dataannall['class3'] == dataannall['class']) & (dataannall['class'] > 0)])\n",
"class123_ds_f = len(dataannall[(dataannall['class1'] == dataannall['class2']) & (dataannall['class3'] == dataannall['class1']) & (dataannall['class3'] == dataannall['class2']) & (dataannall['class'] > 0)])\n",
"class_f = len(dataannall[(dataannall['class'] > 0)])\n",
"\n",
"print(f\"Choix opérateur 1 dans choix final \\t\\t: {class1_ds_f}\\t/ {class_f}\\t{round(class1_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 2 dans choix final \\t\\t: {class2_ds_f}\\t/ {class_f}\\t{round(class2_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 3 dans choix final \\t\\t: {class3_ds_f}\\t/ {class_f}\\t{round(class3_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 2 dans choix final \\t\\t: {class12_ds_f}\\t/ {class_f}\\t{round(class12_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 3 dans choix final \\t\\t: {class13_ds_f}\\t/ {class_f}\\t{round(class13_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 2 & 3 dans choix final \\t\\t: {class23_ds_f}\\t/ {class_f}\\t{round(class23_ds_f*100/class_f,2)}%\")\n",
"print(f\"Choix opérateur 1 & 2 & 3 dans choix final \\t: {class123_ds_f}\\t/ {class_f}\\t{round(class123_ds_f*100/class_f,2)}%\")"
]
},
{
"cell_type": "code",
"execution_count": 245,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" 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>time</th>\n",
" <th>class1</th>\n",
" <th>class2</th>\n",
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" <th>class</th>\n",
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" <td>2</td>\n",
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" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3507</th>\n",
" <td>86757975</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3508</th>\n",
" <td>86757976</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3509</th>\n",
" <td>86827127</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3510</th>\n",
" <td>86827128</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3511</th>\n",
" <td>87087000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>3512 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" time class1 class2 class3 class\n",
"3110 1 2 1 2 2\n",
"0 7047 2 1 2 2\n",
"1 7048 2 1 2 2\n",
"2 17209 2 1 1 2\n",
"3 17210 2 1 1 2\n",
"... ... ... ... ... ...\n",
"3507 86757975 2 1 2 2\n",
"3508 86757976 1 2 1 1\n",
"3509 86827127 1 2 1 1\n",
"3510 86827128 2 1 2 2\n",
"3511 87087000 2 1 2 2\n",
"\n",
"[3512 rows x 5 columns]"
]
},
"execution_count": 245,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = dataannall.sort_values('time')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 247,
"metadata": {},
"outputs": [
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