{
 "cells": [
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   "cell_type": "markdown",
   "id": "a3a2e70b-c76f-4092-81e1-7a1cc873e02b",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "9e37c18c-4cd1-493c-b518-017e548ea236",
   "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": "a7f0aa03-7702-49c3-9e7e-985a2e46acfe",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Data Loading"
   ]
  },
  {
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   "execution_count": 223,
   "id": "4a0dbc36-458e-42c7-abf3-e1ae9ab6882b",
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    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ampl</th>\n",
       "      <th>Bias</th>\n",
       "      <th>Time</th>\n",
       "      <th>Z'</th>\n",
       "      <th>Z''</th>\n",
       "      <th>GD</th>\n",
       "      <th>Err</th>\n",
       "      <th>Range</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Freq</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100000.000000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>5.30156</td>\n",
       "      <td>1.079740e+01</td>\n",
       "      <td>2.284260e+00</td>\n",
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       "    <tr>\n",
       "      <th>89038.900000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>7.57639</td>\n",
       "      <td>1.077640e+01</td>\n",
       "      <td>1.850430e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>79279.300000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>9.88210</td>\n",
       "      <td>1.078170e+01</td>\n",
       "      <td>1.183330e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>70589.400000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>12.15070</td>\n",
       "      <td>1.080220e+01</td>\n",
       "      <td>7.015430e-01</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>62852.000000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>14.44200</td>\n",
       "      <td>1.084920e+01</td>\n",
       "      <td>2.390310e-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.147548</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>421.26800</td>\n",
       "      <td>1.202140e+06</td>\n",
       "      <td>-5.601180e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.131375</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>438.67600</td>\n",
       "      <td>1.610990e+06</td>\n",
       "      <td>-8.475710e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.116975</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>458.01900</td>\n",
       "      <td>-1.276680e+05</td>\n",
       "      <td>-1.894920e+06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.104153</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>479.57100</td>\n",
       "      <td>1.322450e+06</td>\n",
       "      <td>8.458330e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.100000</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-0.152227</td>\n",
       "      <td>501.93200</td>\n",
       "      <td>1.004850e+06</td>\n",
       "      <td>-6.285010e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
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       "<p>120 rows × 8 columns</p>\n",
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      ],
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       "               Ampl      Bias       Time            Z'           Z''   GD  \\\n",
       "Freq                                                                        \n",
       "100000.000000  10.0 -0.152227    5.30156  1.079740e+01  2.284260e+00  0.0   \n",
       "89038.900000   10.0 -0.152227    7.57639  1.077640e+01  1.850430e+00  0.0   \n",
       "79279.300000   10.0 -0.152227    9.88210  1.078170e+01  1.183330e+00  0.0   \n",
       "70589.400000   10.0 -0.152227   12.15070  1.080220e+01  7.015430e-01  0.0   \n",
       "62852.000000   10.0 -0.152227   14.44200  1.084920e+01  2.390310e-01  0.0   \n",
       "...             ...       ...        ...           ...           ...  ...   \n",
       "0.147548       10.0 -0.152227  421.26800  1.202140e+06 -5.601180e+05  0.0   \n",
       "0.131375       10.0 -0.152227  438.67600  1.610990e+06 -8.475710e+05  0.0   \n",
       "0.116975       10.0 -0.152227  458.01900 -1.276680e+05 -1.894920e+06  0.0   \n",
       "0.104153       10.0 -0.152227  479.57100  1.322450e+06  8.458330e+04  0.0   \n",
       "0.100000       10.0 -0.152227  501.93200  1.004850e+06 -6.285010e+05  0.0   \n",
       "\n",
       "               Err  Range  \n",
       "Freq                       \n",
       "100000.000000    0      0  \n",
       "89038.900000     0      0  \n",
       "79279.300000     0      0  \n",
       "70589.400000     0      0  \n",
       "62852.000000     0      0  \n",
       "...            ...    ...  \n",
       "0.147548         0      0  \n",
       "0.131375         0      0  \n",
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       "0.104153         0      0  \n",
       "0.100000         0      0  \n",
       "\n",
       "[120 rows x 8 columns]"
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     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# --- Data Loading ---\n",
    "\n",
    "def eis_z60_import(filename):\n",
    "    \"\"\" Import z60 file as pandas dataframe.\"\"\"\n",
    "    return pd.read_csv(\n",
    "        filename,\n",
    "        skiprows=11,\n",
    "        sep='\\s+',\n",
    "        header=None,\n",
    "        names=[\"Freq\", \"Ampl\", \"Bias\", \"Time\", \"Z'\", \"Z''\", \"GD\", \"Err\", \"Range\"],\n",
    "        index_col=\"Freq\")\n",
    "    \n",
    "try:\n",
    "    EIS_10mV_1_df = eis_z60_import(\"Cast_Stellite1_Sample1_Actual/EIS_10mV.z60\")\n",
    "    EIS_10mV_2_df = eis_z60_import(\"Cast_Stellite1_Sample2_Actual/EIS_10mV.z60\")\n",
    "    EIS_10mV_3_df = eis_z60_import(\"Cast_Stellite1_Sample3_Actual/EIS_10mV.z60\")\n",
    "\n",
    "    EIS_20mV_1_df = eis_z60_import(\"Cast_Stellite1_Sample1_Actual/EIS_20mV.z60\")\n",
    "    EIS_20mV_2_df = eis_z60_import(\"Cast_Stellite1_Sample2_Actual/EIS_20mV.z60\")\n",
    "    EIS_20mV_3_df = eis_z60_import(\"Cast_Stellite1_Sample3_Actual/EIS_20mV.z60\")\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",
    "EIS_10mV_1_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b481dbed-deac-4250-887b-673df223ea33",
   "metadata": {},
   "source": [
    "## Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "21b2f1d3-ace5-4134-8901-2f8a913f44e8",
   "metadata": {
    "collapsed": true,
    "jupyter": {
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   },
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>0.147548</th>\n",
       "      <td>1202140.0</td>\n",
       "      <td>-560118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.131375</th>\n",
       "      <td>1610990.0</td>\n",
       "      <td>-847571.0</td>\n",
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       "    <tr>\n",
       "      <th>0.116975</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>0.104153</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.100000</th>\n",
       "      <td>1004850.0</td>\n",
       "      <td>-628501.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Z'       Z''\n",
       "Freq                              \n",
       "100000.000000        NaN       NaN\n",
       "89038.900000         NaN       NaN\n",
       "79279.300000         NaN       NaN\n",
       "70589.400000         NaN       NaN\n",
       "62852.000000         NaN       NaN\n",
       "...                  ...       ...\n",
       "0.147548       1202140.0 -560118.0\n",
       "0.131375       1610990.0 -847571.0\n",
       "0.116975             NaN       NaN\n",
       "0.104153             NaN       NaN\n",
       "0.100000       1004850.0 -628501.0\n",
       "\n",
       "[120 rows x 2 columns]"
      ]
     },
     "execution_count": 224,
     "metadata": {},
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    }
   ],
   "source": [
    "# --- Preprocessing ---\n",
    "def eis_z60_preprocess(df):\n",
    "\n",
    "    df = df.drop(columns=['Ampl', 'Bias', 'Time', 'GD', 'Err', 'Range']) # Drop columns\n",
    "    mask = (df[\"Z'\"] > 0) & (df[\"Z''\"] < 0) # Only keep first quadrant in Nyquist plot\n",
    "    df[~mask] = None\n",
    "    return df\n",
    "\n",
    "EIS_10mV_1_df = eis_z60_preprocess(EIS_10mV_1_df)\n",
    "EIS_10mV_2_df = eis_z60_preprocess(EIS_10mV_2_df)\n",
    "EIS_10mV_3_df = eis_z60_preprocess(EIS_10mV_3_df)\n",
    "\n",
    "EIS_20mV_1_df = eis_z60_preprocess(EIS_20mV_1_df)\n",
    "EIS_20mV_2_df = eis_z60_preprocess(EIS_20mV_2_df)\n",
    "EIS_20mV_3_df = eis_z60_preprocess(EIS_20mV_3_df)\n",
    "\n",
    "EIS_10mV_1_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1e99c75-c3e1-4fe9-8c10-6beeee5f5dc6",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Find Impedence Amplitude and Phase\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "cc01bd81-46e9-44c5-af98-b5f45bd4e0a1",
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   "outputs": [
    {
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       "      <th>79279.300000</th>\n",
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       "    <tr>\n",
       "      <th>62852.000000</th>\n",
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       "    <tr>\n",
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       "      <th>0.131375</th>\n",
       "      <td>1610990.0</td>\n",
       "      <td>-847571.0</td>\n",
       "      <td>2.278284e+06</td>\n",
       "      <td>-117.749670</td>\n",
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       "    <tr>\n",
       "      <th>0.116975</th>\n",
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       "      <th>0.104153</th>\n",
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       "    <tr>\n",
       "      <th>0.100000</th>\n",
       "      <td>1004850.0</td>\n",
       "      <td>-628501.0</td>\n",
       "      <td>1.421072e+06</td>\n",
       "      <td>-122.024640</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Z'       Z''             Z       theta\n",
       "Freq                                                        \n",
       "100000.000000        NaN       NaN           NaN         NaN\n",
       "89038.900000         NaN       NaN           NaN         NaN\n",
       "79279.300000         NaN       NaN           NaN         NaN\n",
       "70589.400000         NaN       NaN           NaN         NaN\n",
       "62852.000000         NaN       NaN           NaN         NaN\n",
       "...                  ...       ...           ...         ...\n",
       "0.147548       1202140.0 -560118.0  1.700083e+06 -114.982416\n",
       "0.131375       1610990.0 -847571.0  2.278284e+06 -117.749670\n",
       "0.116975             NaN       NaN           NaN         NaN\n",
       "0.104153             NaN       NaN           NaN         NaN\n",
       "0.100000       1004850.0 -628501.0  1.421072e+06 -122.024640\n",
       "\n",
       "[120 rows x 4 columns]"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def eis_z60_imp_amp_phase(df):\n",
    "    df['Z'] = np.sqrt( (df[\"Z'\"].to_numpy())**2 + \\\n",
    "                       (df[\"Z'\"].to_numpy())**2 )\n",
    "\n",
    "    df['theta'] = np.arctan2(-df[\"Z'\"].to_numpy(), df[\"Z''\"].to_numpy()) * 180 / np.pi\n",
    "    return df\n",
    "    \n",
    "EIS_10mV_1_df = eis_z60_imp_amp_phase(EIS_10mV_1_df)\n",
    "EIS_10mV_2_df = eis_z60_imp_amp_phase(EIS_10mV_2_df)\n",
    "EIS_10mV_3_df = eis_z60_imp_amp_phase(EIS_10mV_3_df)\n",
    "\n",
    "EIS_20mV_1_df = eis_z60_imp_amp_phase(EIS_20mV_1_df)\n",
    "EIS_20mV_2_df = eis_z60_imp_amp_phase(EIS_20mV_2_df)\n",
    "EIS_20mV_3_df = eis_z60_imp_amp_phase(EIS_20mV_3_df)\n",
    "\n",
    "EIS_10mV_1_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fdbae85-aaea-4925-9efd-94ec786b7f4f",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Find average and standard deviation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "aa0166b4-f254-4874-a5d5-b4b626680844",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_10mV_concat = pd.concat((EIS_10mV_1_df, EIS_10mV_2_df, EIS_10mV_3_df))\n",
    "df_10mV_means = df_10mV_concat.groupby(df_10mV_concat.index).mean()\n",
    "df_10mV_err = df_10mV_concat.groupby(df_10mV_concat.index).std()\n",
    "\n",
    "df_20mV_concat = pd.concat((EIS_20mV_1_df, EIS_20mV_2_df, EIS_20mV_3_df))\n",
    "df_20mV_means = df_20mV_concat.groupby(df_20mV_concat.index).mean()\n",
    "df_20mV_err = df_20mV_concat.groupby(df_20mV_concat.index).std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "77bdee00-bd44-4942-a9f8-ba500710a48f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Z'</th>\n",
       "      <th>Z''</th>\n",
       "      <th>Z</th>\n",
       "      <th>theta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Freq</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.100000</th>\n",
       "      <td>561617.000000</td>\n",
       "      <td>-339202.750000</td>\n",
       "      <td>7.942464e+05</td>\n",
       "      <td>-117.441191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.104153</th>\n",
       "      <td>374151.800000</td>\n",
       "      <td>-335554.700000</td>\n",
       "      <td>5.291305e+05</td>\n",
       "      <td>-128.224700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.116975</th>\n",
       "      <td>586732.900000</td>\n",
       "      <td>-136540.350000</td>\n",
       "      <td>8.297656e+05</td>\n",
       "      <td>-113.064264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.131375</th>\n",
       "      <td>825848.200000</td>\n",
       "      <td>-607456.700000</td>\n",
       "      <td>1.167926e+06</td>\n",
       "      <td>-127.817170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.147548</th>\n",
       "      <td>673378.133333</td>\n",
       "      <td>-327485.633333</td>\n",
       "      <td>9.523005e+05</td>\n",
       "      <td>-119.913783</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Z'            Z''             Z       theta\n",
       "Freq                                                            \n",
       "0.100000  561617.000000 -339202.750000  7.942464e+05 -117.441191\n",
       "0.104153  374151.800000 -335554.700000  5.291305e+05 -128.224700\n",
       "0.116975  586732.900000 -136540.350000  8.297656e+05 -113.064264\n",
       "0.131375  825848.200000 -607456.700000  1.167926e+06 -127.817170\n",
       "0.147548  673378.133333 -327485.633333  9.523005e+05 -119.913783"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_10mV_means.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "947a113e-334f-4e99-b6ab-80eb236ab7f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Z'</th>\n",
       "      <th>Z''</th>\n",
       "      <th>Z</th>\n",
       "      <th>theta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Freq</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.100000</th>\n",
       "      <td>1.247627e+06</td>\n",
       "      <td>914047.000305</td>\n",
       "      <td>1.764411e+06</td>\n",
       "      <td>9.857596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.104153</th>\n",
       "      <td>4.541379e+05</td>\n",
       "      <td>410368.713355</td>\n",
       "      <td>6.422480e+05</td>\n",
       "      <td>3.564236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.116975</th>\n",
       "      <td>3.836831e+05</td>\n",
       "      <td>358439.498451</td>\n",
       "      <td>5.426099e+05</td>\n",
       "      <td>7.954958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.131375</th>\n",
       "      <td>2.397636e+05</td>\n",
       "      <td>278657.363188</td>\n",
       "      <td>3.390769e+05</td>\n",
       "      <td>9.753189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.147548</th>\n",
       "      <td>8.643296e+05</td>\n",
       "      <td>888082.330925</td>\n",
       "      <td>1.222347e+06</td>\n",
       "      <td>3.779877</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Z'            Z''             Z     theta\n",
       "Freq                                                         \n",
       "0.100000  1.247627e+06  914047.000305  1.764411e+06  9.857596\n",
       "0.104153  4.541379e+05  410368.713355  6.422480e+05  3.564236\n",
       "0.116975  3.836831e+05  358439.498451  5.426099e+05  7.954958\n",
       "0.131375  2.397636e+05  278657.363188  3.390769e+05  9.753189\n",
       "0.147548  8.643296e+05  888082.330925  1.222347e+06  3.779877"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_20mV_err.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7bf7352-ebd7-45e5-84e4-8e8dfe6eaeb7",
   "metadata": {},
   "source": [
    "## Plotting average data in Bode Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "997aab6a-136d-4b16-ad8a-0a7d6ae8fd74",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Theta mean error 8.226960033482918%\n",
      "|Z| mean error 160305.02735254532%\n"
     ]
    }
   ],
   "source": [
    "print(f\"Theta mean error {df_err['theta'].mean()}%\")\n",
    "print(f\"|Z| mean error {df_err['Z'].mean()}%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe068107-674b-48b7-a9d3-44074c27d878",
   "metadata": {},
   "source": [
    "Clearly, the phase shift error is far higher than the gain, but it would be a mistake to say that gain is less reliable than the phase shift.\n",
    "The error with the gain, likely due to noise at low frequencies, appears more reasonable when the data is plotted on a log axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "id": "358cca84-336e-4c49-846f-868706a26b1b",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 376,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2,1,figsize=(8,4), sharex=True, dpi=150)\n",
    "\n",
    "ax1.errorbar(df_10mV_means.index.to_numpy(), df_10mV_means[\"Z\"].to_numpy(), df_10mV_err[\"Z\"].to_numpy(),\n",
    "             fmt = '.', color='mediumblue', markersize=5, \n",
    "             ecolor=\"mediumblue\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "             label=\"10 mV\")\n",
    "ax1.errorbar(df_20mV_means.index.to_numpy(), df_20mV_means[\"Z\"].to_numpy(), df_20mV_err[\"Z\"].to_numpy(),\n",
    "             fmt = '.', color='firebrick', markersize=5, \n",
    "             ecolor=\"firebrick\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "             label=\"20 mV\")\n",
    "\n",
    "ax2.errorbar(df_10mV_means.index.to_numpy(), df_10mV_means[\"theta\"].to_numpy(), df_10mV_err[\"theta\"].to_numpy(),\n",
    "             fmt = '.', color='mediumblue', markersize=5, \n",
    "             ecolor=\"mediumblue\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "             label=\"10 mV\")\n",
    "ax2.errorbar(df_20mV_means.index.to_numpy(), df_20mV_means[\"theta\"].to_numpy(), df_20mV_err[\"theta\"].to_numpy(),\n",
    "             fmt = '.', color='firebrick', markersize=5, \n",
    "             ecolor=\"firebrick\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "             label=\"20 mV\")\n",
    "\n",
    "ax1.grid(True, which=\"both\", ls=\"-\", alpha=0.5)\n",
    "ax2.grid(True, which=\"both\", ls=\"-\", alpha=0.5)\n",
    "ax1.legend()\n",
    "\n",
    "#ax2.xaxis.set_major_locator(plt.MaxNLocator(11))\n",
    "ax1.set_ylabel('|Z| (Ohm)')\n",
    "ax2.set_ylabel('Phase (deg)')\n",
    "ax2.set_xlabel(\"Frequency\")\n",
    "ax1.set_yscale(\"log\")\n",
    "ax1.set_xscale(\"log\")\n",
    "ax2.set_xscale(\"log\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d1c3dcb-b519-4564-b1a1-8598ede08b86",
   "metadata": {},
   "source": [
    "Okay, the errors with the impedence shift clearly show that:\n",
    "- 20mV is less reliable than 10mV at high frequencies, likely due to non-linearity,\n",
    "- 20mV is more reliable than 10 mV at low frequencies, or atleast, lower frequencies than 10mV\n",
    "\n",
    "Makes me think that I need to use higher excitation voltages at low frequencies, ~although I've only seen 10mV and 20mV in research.~ this paper does 30mV! https://www.mdpi.com/2076-3417/14/13/5754\n",
    "\n",
    "Then again, I've never seen errorbars on a Bode plot in a research paper\n",
    "\n",
    "\n",
    "Source of discontinuities: https://www.gamry.com/Framework%20Help/HTML5%20-%20Tripane%20-%20Audience%20A/Content/UT/Discontinuities%20in%20EIS%20Spectra.htm\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fef8582e-567c-492c-9ae6-e775838b8ca6",
   "metadata": {},
   "source": [
    "## Plotting average data on Nyquist plot\n",
    "\n",
    "So let's have a look at how the Nyquist plot looks, with and without the sketchy data\n",
    "So we'll remove everything below 10 Hz, plus remove the weird region at 50Hz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "id": "b2667cfa-b5e2-44a4-bbbf-5409636b4aae",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ignoring fixed y limits to fulfill fixed data aspect with adjustable data limits.\n",
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n",
      "Ignoring fixed y limits to fulfill fixed data aspect with adjustable data limits.\n",
      "Ignoring fixed x limits to fulfill fixed data aspect with adjustable data limits.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Nyquist Plot\n",
    "\n",
    "import warnings\n",
    "with warnings.catch_warnings():\n",
    "    warnings.simplefilter('ignore')\n",
    "    fig, (ax,bx) = plt.subplots(1,2,figsize=(8, 4), dpi=150)\n",
    "\n",
    "    #ax.errorbar(   x = df_10mV_means[\"Z'\"].to_numpy(), y = -df_10mV_means[\"Z''\"].to_numpy(), \n",
    "    #            xerr = df_10mV_err[\"Z\"].to_numpy(), yerr = df_10mV_err[\"Z\"].to_numpy(),             \n",
    "    #            color='mediumblue', markersize=2, fmt = 's', ecolor=\"mediumblue\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "    #            label=\"10 mV\")\n",
    "    #ax.errorbar(   x = df_20mV_means[\"Z'\"].to_numpy(), y = -df_20mV_means[\"Z''\"].to_numpy(), \n",
    "    #            xerr = df_20mV_err[\"Z\"].to_numpy(), yerr =  df_20mV_err[\"Z\"].to_numpy(),             \n",
    "    #            color='firebrick', markersize=2, fmt = 's', ecolor=\"firebrick\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "    #            label=\"20 mV\")\n",
    "    ax.plot(df_20mV_means[\"Z'\"].to_numpy(), -df_20mV_means[\"Z''\"].to_numpy(), 's-',\n",
    "            linewidth=1, alpha=0.5, color='firebrick', markersize=2)\n",
    "    ax.plot(df_10mV_means[\"Z'\"].to_numpy(), -df_10mV_means[\"Z''\"].to_numpy(), 's-',\n",
    "            linewidth=1, alpha=0.5, color='mediumblue', markersize=2)\n",
    "\n",
    "# Filtered plot\n",
    "    mask = (df_10mV_means.index > 10) & ((df_10mV_means.index < 30) | (df_10mV_means.index > 100))  # Only keep those frequencies above 10 Hz\n",
    "    bx.errorbar(x=(df_10mV_means[mask])[\"Z'\"].to_numpy(), y=(-df_10mV_means[mask])[\"Z''\"].to_numpy(), \n",
    "            xerr=(df_10mV_err[mask])[\"Z\"].to_numpy(), yerr=(df_10mV_err[mask])[\"Z\"].to_numpy(),             \n",
    "            color='mediumblue', markersize=2, \n",
    "            fmt = 's', ecolor=\"mediumblue\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "            label=\"10 mV\")\n",
    "    bx.errorbar(x=(df_20mV_means[mask])[\"Z'\"].to_numpy(), y=(-df_20mV_means[mask])[\"Z''\"].to_numpy(), \n",
    "            xerr=(df_20mV_err[mask])[\"Z\"].to_numpy(), yerr=(df_20mV_err[mask])[\"Z\"].to_numpy(),             \n",
    "            color='firebrick', markersize=2, \n",
    "            fmt = 's', ecolor=\"firebrick\", elinewidth=0.50, capsize=2, capthick=0.50,\n",
    "            label=\"20 mV\")\n",
    "    bx.plot((df_10mV_means[mask])[\"Z'\"].to_numpy(), (-df_10mV_means[mask])[\"Z''\"].to_numpy(), 's-',\n",
    "            linewidth=1, alpha=0.5, color='mediumblue', markersize=2)\n",
    "    bx.plot((df_20mV_means[mask])[\"Z'\"].to_numpy(), (-df_20mV_means[mask])[\"Z''\"].to_numpy(), 's-', \n",
    "            linewidth=1, alpha=0.5, color='firebrick', markersize=2)\n",
    "\n",
    "    ax.set_xlabel(r\"Z' $[\\Omega]$\")\n",
    "    ax.set_ylabel(r\"Z'' $[\\Omega]$\")\n",
    "    ax.set_title('Nyquist Plot w/ unfiltered data, not showing errorbars')\n",
    "    ax.legend()\n",
    "\n",
    "    bx.set_xlabel(r\"Z' $[\\Omega]$\")\n",
    "    bx.set_ylabel(r\"Z'' $[\\Omega]$\")\n",
    "    bx.set_title('Nyquist Plot w/ filtered data')\n",
    "    bx.legend()\n",
    "\n",
    "    ax.axis('equal') # Important for Nyquist plots\n",
    "    ax.set_xlim(left=0)\n",
    "    ax.set_ylim(bottom=0)\n",
    "    ax.grid(True)\n",
    "\n",
    "    bx.axis('equal') # Important for Nyquist plots\n",
    "    bx.set_xlim(left=0)\n",
    "    bx.set_ylim(bottom=0)\n",
    "    bx.grid(True)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "beb7b1a7-8ef7-4ff1-91ec-3d4414e1d1a8",
   "metadata": {},
   "source": [
    "I didn't even bother plotting the errorbars on the unfiltered plot because it's just all errorbars, yeesh.\n",
    "But the filtered data is actually pretty alright? Like, I can use it confidently.\n",
    "\n",
    "So I guess I need to use higher amplitude to reach the crescent circle :)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "771a8570-2eb8-471d-a3ea-2202c46e7043",
   "metadata": {},
   "source": [
    "\n",
    "| Circuit Element | Impedence                                    |\n",
    "| --------------- | -------------------------------------------- | \n",
    "| Resistor        | $$ Z = R $$                                  |\n",
    "| Capacitor       | $$ Z = \\frac{1}{C \\cdot j 2 \\pi f} $$        |\n",
    "| Inductor        | $$Z = L \\cdot j 2 \\pi f $$                   |\n",
    "| CPE             | $$Z = \\frac{1}{Q \\cdot (j 2 \\pi f)^\\alpha}$$ |\n",
    "\n",
    "| Impedences in parallel | Impedences in series |\n",
    "| --------------- | -------------------------------------------- | \n",
    "| $$ Z_{parallel} = \\frac{1}{\\frac{1}{Z_1} + \\frac{1}{Z_2} + ... + \\frac{1}{Z_n}}$$ | $$ Z_{series} = Z_1 + Z_2 + ... + Z_n $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "736a0854-c83b-4717-b0a2-060f9c706f2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import functools\n",
    "import numpy as np\n",
    "\n",
    "def R(f, R): return np.zeros(len(f)) + (R + 0 * 1j)\n",
    "def C(f, C): return 1.0 / (C * 1j * (2 * np.pi * np.array(f)) )\n",
    "def L(f, L): return L * 1j * (2 * np.pi * np.array(f))\n",
    "def CPE(f, Q, alpha): return 1.0 / (Q * (1j * (2 * np.pi * np.array(f))) ** alpha)\n",
    "\n",
    "def s(*args): return functools.reduce(np.add, [*args])\n",
    "def p(*args): return np.reciprocal(functools.reduce(np.add, np.reciprocal([*args])))\n",
    "\n",
    "f = np.linspace(1e5,1e-2,70)\n",
    "\n",
    "# Some common-sense tests to make sure the code is correct\n",
    "assert (s(R(f, 10),R(f, 10)) == R(f, 20)).all()\n",
    "assert (p(R(f, 10),R(f, 10)) == R(f, 5)).all()\n",
    "assert (s(C(f, 10),C(f, 10)) == C(f, 5)).all()\n",
    "assert (p(C(f, 10),C(f, 10)) == C(f, 20)).all()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "cb098c7e-b8cf-4c8c-9978-f53442ef77a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def randles_circuit(f, Rs, Rp, Q, alpha): \n",
    "    return s(R(f, Rs), p(R(f, Rp), CPE(f, Q, alpha)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "22b91a0d-960e-4843-b9c0-d33db2030698",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fake data\n",
    "\n",
    "# Parameters for the simplified Randles circuit (R_s + (R_ct || C_dl))\n",
    "#freq_data = np.logspace(5, -1, 60) # 10 kHz down to 0.01 Hz\n",
    "R_s_true = 20.0      # Ohms\n",
    "R_ct_true = 100.0    # Ohms\n",
    "Q_dl_true = 1e-5     # Farads\n",
    "alpha_dl_true = 0.98 # -\n",
    "Z_fake = randles_circuit(freq_data, R_s_true, R_ct_true, Q_dl_true, alpha_dl_true) + \\\n",
    "        (0.5 + 0.5 * 1j) * np.random.normal(size=freq_data.size)\n",
    "Z_fake_concat = np.concatenate([Z_exp.real,Z_exp.imag])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "672eb5f0-bd38-4d42-a77f-583db50ae9c2",
   "metadata": {},
   "source": [
    "## Curve Fitting\n",
    "\n",
    "Fitting is performed by non-linear least squares regression of circuit model to impedence data via the scipy.optimize.curve_fit function.\n",
    "\n",
    "The objective function is:\n",
    "$$ \\chi^2 = \\sum_{n=0}^{N} [Z^\\prime_{exp}(\\omega_n) - Z^\\prime_{fit}(\\omega_n)]^2 +\n",
    "               [Z^{\\prime\\prime}_{exp}(\\omega_n) - Z^{\\prime\\prime}_{fit}(\\omega_n)]^2 $$\n",
    "               "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "a62ea723-f23f-43de-9622-fd4c0157b871",
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_func(f, Rs, Rp, Q, alpha):\n",
    "    Z_fit = randles_circuit(f, Rs, Rp, Q, alpha)\n",
    "    return np.concatenate([Z_fit.real,Z_fit.imag])\n",
    "\n",
    "# Initial guesses for the parameters (R_s, R_ct, C_dl)\n",
    "# Good initial guesses are VERY important for convergence and finding the global minimum.\n",
    "initial_params_simple = [10.0, 50.0, 1e-6]\n",
    "\n",
    "# Parameter bounds (optional, but highly recommended)\n",
    "# Helps to keep parameters within physically realistic ranges.\n",
    "# Format: ([lower_bounds], [upper_bounds])\n",
    "bounds_simple = ([0, 0, 1e-9], [1000, 1e4, 1e-2]) # (R_s, R_ct, C_dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "a7567100-ca22-440b-ab44-f3cf0142571a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting curve_fit for real data...\n",
      "curve_fit finished successfully!\n"
     ]
    }
   ],
   "source": [
    "print(\"Starting curve_fit for real data...\")\n",
    "try:\n",
    "    popt, pcov = scipy.optimize.curve_fit( \n",
    "        model_func,\n",
    "        freq_data,\n",
    "        np.concatenate([Z_exp.real,Z_exp.imag]),\n",
    "        # Initial guesses for the parameters (R_s, R_ct, C_dl)        \n",
    "        p0=[10.0, 50.0, 1e-6, 0.87], \n",
    "        # Helps to keep parameters within physically realistic ranges.        \n",
    "        bounds=([0, 0, 1e-9, 0], [1000, 1e4, 1e-2, 1]), \n",
    "        maxfev=50000) # Max number of function evaluations\n",
    "\n",
    "except RuntimeError:\n",
    "    print(\"Curve fitting failed. Could not find optimal parameters.\")\n",
    "    print(\"Try adjusting initial guesses, bounds, or the model itself.\")\n",
    "except ValueError as e:\n",
    "    print(f\"An error occurred: {e}\") \n",
    "else:\n",
    "    print(\"curve_fit finished successfully!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "1937913c-acbe-44e2-83bd-8c5817724160",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimized Parameters:\n",
      "Rs      : 4.3912e+00 +- 220.09%\n",
      "Rp      : 4.2998e+03 +- 40.83%\n",
      "Q       : 1.9134e-05 +- 26.63%\n",
      "alpha   : 7.4275e-01 +- 5.55%\n"
     ]
    }
   ],
   "source": [
    "# Results\n",
    "\n",
    "perr = np.sqrt(np.diag(pcov))\n",
    "\n",
    "print(\"\\nOptimized Parameters:\")\n",
    "for name, val, err in zip([\"Rs\", \"Rp\", \"Q\", \"alpha\"], popt, perr):\n",
    "    print(f\"{name:<8}: {val:.4e} +- {100*(err/val):.2f}%\")\n",
    "\n",
    "Z_fit = randles_circuit(freq_data, *popt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "c5985667-18a5-4bf9-8c7c-e310d18af276",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Nyquist Plot\n",
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "ax.plot(Z_exp.real, -Z_exp.imag, 's', markersize=2, label='Experimental Data')\n",
    "ax.plot(Z_fit.real, -Z_fit.imag, '-', linewidth=2, label='Fitted Model')\n",
    "ax.set_xlabel(r\"Z' $[\\Omega]$\")\n",
    "ax.set_ylabel(r\"Z'' $[\\Omega]$\")\n",
    "ax.set_title('Nyquist Plot')\n",
    "ax.legend()\n",
    "\n",
    "ax.set_xlim(left=0)\n",
    "#ax.set_xlim(left=0,   right=popt[0]+popt[1])\n",
    "#ax.set_ylim(bottom=0, top=popt[0]+popt[1])\n",
    "ax.axis('equal') # Important for Nyquist plots\n",
    "ax.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "d03517e4-53a4-4196-9382-31e0f9b9898f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bode Plots\n",
    "plt.figure(figsize=(10, 6))\n",
    "    \n",
    "# Magnitude\n",
    "ax1 = plt.subplot(2, 1, 1)\n",
    "plt.loglog(freq_data, np.sqrt(Z_exp.real**2 + Z_exp.imag**2), \n",
    "           'o', markersize=5, label='Experimental |Z|')\n",
    "plt.loglog(freq_data, np.sqrt(Z_fit.real**2 + Z_fit.imag**2), \n",
    "           '-', linewidth=2, label='Fitted |Z|')\n",
    "plt.ylabel('|Z| (Ohm)')\n",
    "plt.legend()\n",
    "plt.grid(True, which=\"both\", ls=\"-\")\n",
    "plt.title('Bode Plot')\n",
    "\n",
    "# Phase\n",
    "ax2 = plt.subplot(2, 1, 2, sharex=ax1)\n",
    "phase_exp = np.arctan2(-Z_exp.imag, Z_exp.real) * 180 / np.pi\n",
    "phase_fit = np.arctan2(-Z_fit.imag, Z_fit.real) * 180 / np.pi\n",
    "plt.semilogx(freq_data, phase_exp, \n",
    "             'o', markersize=5, label='Experimental Phase')\n",
    "plt.semilogx(freq_data, phase_fit, \n",
    "             '-', linewidth=2, label='Fitted Phase')\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Phase (deg)')\n",
    "plt.legend()\n",
    "plt.grid(True, which=\"both\", ls=\"-\")\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "730035d7-92f3-4142-aa5e-d1c16692bbf6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88eea2d2-77d2-42ff-98d1-2258040975d2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6a9c459-0246-4341-bd1f-403fb245dba0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b83f347-1a57-46f6-a38a-33d2c0dd89f3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ce75eff-f3aa-4b48-8d91-46d40555cc9c",
   "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
}