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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "08417046-1a17-422e-96fd-6e4c546798e5",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import scipy.optimize\n"
]
},
{
"cell_type": "markdown",
"id": "1a0023dd-e56d-4fed-9503-6387bc9f3784",
"metadata": {},
"source": [
"## Hampel filter"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "88dcd31f-e720-4e9d-9944-3d972b7955ff",
"metadata": {},
"outputs": [],
"source": [
", label=\"CS 1\""
]
},
{
"cell_type": "markdown",
"id": "aac96ba7-8c92-45bc-8e30-61b2dfd00292",
"metadata": {},
"source": [
"## Data Loading"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "2ef66349-ca7c-4cc5-a426-15b5cd87f64b",
"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>E</th>\n",
" <th>i</th>\n",
" <th>T</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.326304</td>\n",
" <td>5.000000e-11</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-0.326281</td>\n",
" <td>5.000000e-11</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-0.326251</td>\n",
" <td>5.000000e-11</td>\n",
" <td>0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-0.326228</td>\n",
" <td>5.000000e-11</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-0.326211</td>\n",
" <td>5.000000e-11</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143995</th>\n",
" <td>-0.152261</td>\n",
" <td>5.000000e-11</td>\n",
" <td>14399.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143996</th>\n",
" <td>-0.152255</td>\n",
" <td>5.000000e-11</td>\n",
" <td>14399.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143997</th>\n",
" <td>-0.152253</td>\n",
" <td>5.000000e-11</td>\n",
" <td>14399.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143998</th>\n",
" <td>-0.152250</td>\n",
" <td>5.000000e-11</td>\n",
" <td>14399.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143999</th>\n",
" <td>-0.152254</td>\n",
" <td>5.000000e-11</td>\n",
" <td>14400.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>144000 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" E i T\n",
"0 -0.326304 5.000000e-11 0.1\n",
"1 -0.326281 5.000000e-11 0.2\n",
"2 -0.326251 5.000000e-11 0.3\n",
"3 -0.326228 5.000000e-11 0.4\n",
"4 -0.326211 5.000000e-11 0.5\n",
"... ... ... ...\n",
"143995 -0.152261 5.000000e-11 14399.6\n",
"143996 -0.152255 5.000000e-11 14399.7\n",
"143997 -0.152253 5.000000e-11 14399.8\n",
"143998 -0.152250 5.000000e-11 14399.9\n",
"143999 -0.152254 5.000000e-11 14400.0\n",
"\n",
"[144000 rows x 3 columns]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def ocp_cor_import(filename):\n",
" \"\"\" Import cor file as pandas dataframe.\"\"\"\n",
" return pd.read_csv(\n",
" filename,\n",
" skiprows=26,\n",
" sep='\\s+',\n",
" header=None,\n",
" names=[\"E\", \"i\", \"T\"],\n",
" ) #index_col=\"Freq\")\n",
"\n",
"\n",
"try:\n",
" OCP_CS_1_df = ocp_cor_import(\"Cast_Stellite1_Sample1_Actual/OCP.cor\")\n",
" OCP_CS_2_df = ocp_cor_import(\"Cast_Stellite1_Sample2_Actual/OCP.cor\")\n",
" OCP_CS_3_df = ocp_cor_import(\"Cast_Stellite1_Sample3_Actual/OCP.cor\")\n",
" OCP_HS_1_df = ocp_cor_import(\"HIPed_Stellite1_Sample1_Actual/OCP.cor\") \n",
" \n",
"except FileNotFoundError as e:\n",
" print(f\"Error: File was not found.\")\n",
" print(e.message)\n",
" print(e.args)\n",
" exit()\n",
"except Exception as e:\n",
" print(f\"Error reading the CSV file: {e}\")\n",
" exit()\n",
"\n",
"OCP_CS_1_df"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "ee262e1a-786f-42f5-8864-7b4573e593db",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ nan nan nan ... -0.152253 -0.15225 -0.152254]\n"
]
}
],
"source": [
"import scipy\n",
"from scipy.stats import zscore\n",
"\n",
"arr = OCP_CS_1_df[\"E\"].to_numpy()\n",
"arr[np.abs(zscore(OCP_CS_1_df[\"E\"])) > 3] = None\n",
"\n",
"print(arr)\n"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "f065f9b8-3912-493d-8476-5e0d7368b6bc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CS 1\n",
"CS 2\n",
"CS 3\n"
]
},
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"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",
" print(name)\n",
"\n",
" arr = df[\"E\"].to_numpy()\n",
" arr[np.abs(zscore(df[\"E\"])) > 3] = None\n",
" #ax.plot(df[\"T\"].to_numpy(), arr, label=name, color=\"black\", alpha=0.5)\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
}