288 lines
69 KiB
Plaintext
288 lines
69 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 26,
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"id": "08417046-1a17-422e-96fd-6e4c546798e5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import scipy.optimize\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1a0023dd-e56d-4fed-9503-6387bc9f3784",
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"metadata": {},
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"source": [
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"## Hampel filter"
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]
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},
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{
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"cell_type": "markdown",
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"id": "aac96ba7-8c92-45bc-8e30-61b2dfd00292",
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"metadata": {},
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"source": [
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"## Data Loading"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"id": "2ef66349-ca7c-4cc5-a426-15b5cd87f64b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>E</th>\n",
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" <th>i</th>\n",
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" <th>T</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>-0.326304</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>0.1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>-0.326281</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>0.2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>-0.326251</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>0.3</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>-0.326228</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>0.4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>-0.326211</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>0.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>143995</th>\n",
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" <td>-0.152261</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>14399.6</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>143996</th>\n",
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" <td>-0.152255</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>14399.7</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>143997</th>\n",
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" <td>-0.152253</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>14399.8</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>143998</th>\n",
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" <td>-0.152250</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>14399.9</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>143999</th>\n",
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" <td>-0.152254</td>\n",
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" <td>5.000000e-11</td>\n",
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" <td>14400.0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>144000 rows × 3 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" E i T\n",
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"0 -0.326304 5.000000e-11 0.1\n",
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"1 -0.326281 5.000000e-11 0.2\n",
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"2 -0.326251 5.000000e-11 0.3\n",
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"3 -0.326228 5.000000e-11 0.4\n",
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"4 -0.326211 5.000000e-11 0.5\n",
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"... ... ... ...\n",
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"143995 -0.152261 5.000000e-11 14399.6\n",
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"143996 -0.152255 5.000000e-11 14399.7\n",
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"143997 -0.152253 5.000000e-11 14399.8\n",
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"143998 -0.152250 5.000000e-11 14399.9\n",
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"143999 -0.152254 5.000000e-11 14400.0\n",
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"\n",
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"[144000 rows x 3 columns]"
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]
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},
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"execution_count": 27,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def ocp_cor_import(filename):\n",
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" \"\"\" Import cor file as pandas dataframe.\"\"\"\n",
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" return pd.read_csv(\n",
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" filename,\n",
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" skiprows=26,\n",
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" sep='\\s+',\n",
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" header=None,\n",
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" names=[\"E\", \"i\", \"T\"],\n",
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" ) #index_col=\"Freq\")\n",
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"\n",
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"\n",
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"try:\n",
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" OCP_CS_1_df = ocp_cor_import(\"Cast_Stellite1_OCP/OCP_1.cor\")\n",
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" OCP_CS_2_df = ocp_cor_import(\"Cast_Stellite1_OCP/OCP_2.cor\")\n",
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" OCP_CS_3_df = ocp_cor_import(\"Cast_Stellite1_OCP/OCP_3.cor\")\n",
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" #OCP_CS_4_df = ocp_cor_import(\"Cast_Stellite1_OCP/OCP_4.cor\") \n",
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" \n",
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"except FileNotFoundError as e:\n",
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" print(f\"Error: File was not found.\")\n",
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" print(e.message)\n",
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" print(e.args)\n",
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" exit()\n",
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"except Exception as e:\n",
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" print(f\"Error reading the CSV file: {e}\")\n",
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" exit()\n",
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"\n",
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"OCP_CS_1_df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"id": "ee262e1a-786f-42f5-8864-7b4573e593db",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[ nan nan nan ... -0.152253 -0.15225 -0.152254]\n"
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]
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}
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],
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"source": [
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"import scipy\n",
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"from scipy.stats import zscore\n",
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"\n",
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"arr = OCP_CS_1_df[\"E\"].to_numpy()\n",
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"arr[np.abs(zscore(OCP_CS_1_df[\"E\"])) > 3] = None\n",
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"\n",
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"print(arr)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"id": "f065f9b8-3912-493d-8476-5e0d7368b6bc",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[]"
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]
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},
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"execution_count": 31,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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",
|
||
"text/plain": [
|
||
"<Figure size 1200x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from scipy.stats import zscore\n",
|
||
"\n",
|
||
"fig, ax = plt.subplots(figsize=(8,4), sharex=True, dpi=150)\n",
|
||
"\n",
|
||
"for df, name in zip([OCP_CS_1_df, OCP_CS_2_df, OCP_CS_3_df], [\"CS 1\", \"CS 2\", \"CS 3\"]):\n",
|
||
" \n",
|
||
" \n",
|
||
" arr = df[\"E\"].to_numpy()\n",
|
||
" arr[np.abs(zscore(df[\"E\"])) > 1] = None\n",
|
||
"\n",
|
||
" ax.plot(df[\"T\"].to_numpy(), arr, label=name)\n",
|
||
"\n",
|
||
"\n",
|
||
"ax.legend()\n",
|
||
"ax.plot()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "0c066c0e-227b-4908-99c1-c26f1a7d0a21",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.10.16"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|