{ "cells": [ { "cell_type": "markdown", "id": "34a7a981-1718-4dcb-af8c-981e0fa84023", "metadata": {}, "source": [ "## Imports" ] }, { "cell_type": "code", "execution_count": 118, "id": "390c33fa-ab42-4d69-ac06-604beb2c69db", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy.optimize\n", "from impedance.models.circuits import CustomCircuit\n", "# from impedance.visualization import plot_nyquist # Kept if you want to switch plotting methods" ] }, { "cell_type": "markdown", "id": "0a055f3f-6b2e-4fa8-8395-acebacade488", "metadata": {}, "source": [ "## Data Loading" ] }, { "cell_type": "code", "execution_count": 119, "id": "9154f27a-5a02-4156-8105-b384205d6416", "metadata": { "jupyter": { "source_hidden": true } }, "outputs": [], "source": [ "# --- Data Loading ---\n", "\n", "def lpr_cor_import(filename):\n", " \"\"\" Import cor file as pandas dataframe.\"\"\"\n", "\n", " try: \n", " df = pd.read_csv(\n", " filename,\n", " skiprows=26,\n", " sep='\\s+',\n", " header=None,\n", " names=[\"E\", \"i\", \"T\"],\n", " ) #index_col=\"Freq\")\n", " except FileNotFoundError as e:\n", " print(f\"Error: File was not found.\")\n", " print(e.message)\n", " print(e.args)\n", " return None\n", " except Exception as e:\n", " print(f\"Error reading the CSV file: {e}\")\n", " return None \n", " else:\n", " return df" ] }, { "cell_type": "code", "execution_count": 127, "id": "4d796ec7-48d9-4a23-bd98-c607067d330d", "metadata": {}, "outputs": [], "source": [ "HS1_1 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_1.cor\")\n", "HS1_2 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_2.cor\")\n", "HS1_3 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_3.cor\")\n", "HS1_4 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_4.cor\")\n", "HS1_5 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_5.cor\")\n", "HS1_6 = lpr_cor_import(\"HIPed_Stellite1_LPR/LPR_6.cor\")\n", "\n", "\n", "# Keep it in the same cell to keep df reproducible, even if Vi clicks it multiple times\n", "area = 2 #cm^2\n", "kernel_size = 5\n", "\n", "for df in [HS1_1, HS1_2, HS1_3, HS1_4, HS1_5, HS1_6]:\n", " df[\"i\"] = np.abs(df[\"i\"]/area) # Current density\n", " #df[\"i\"] = medfilt(df[\"i\"], kernel_size=kernel_size)\n", " df.drop(df.head(60).index, inplace=True)\n", " df.drop(df.tail(60).index, inplace=True)" ] }, { "cell_type": "code", "execution_count": 128, "id": "26ab42ec-9576-4335-a38b-49762228f823", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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62 | \n", "-0.206221 | \n", "4.593445e-11 | \n", "6.3 | \n", "
63 | \n", "-0.206212 | \n", "4.600095e-11 | \n", "6.4 | \n", "
64 | \n", "-0.206202 | \n", "4.606290e-11 | \n", "6.5 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "
3939 | \n", "-0.167438 | \n", "7.020500e-11 | \n", "394.0 | \n", "
3940 | \n", "-0.167428 | \n", "7.005000e-11 | \n", "394.1 | \n", "
3941 | \n", "-0.167417 | \n", "6.993800e-11 | \n", "394.2 | \n", "
3942 | \n", "-0.167407 | \n", "6.988100e-11 | \n", "394.3 | \n", "
3943 | \n", "-0.167398 | \n", "6.985750e-11 | \n", "394.4 | \n", "
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