{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "61aede48",
   "metadata": {},
   "source": [
    "# Tutorial 7 - SOH-R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7341a03d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:34:00.648348100Z",
     "start_time": "2026-01-30T19:34:00.329568700Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pydpeet as eet\n",
    "\n",
    "eet.set_logging_style(\"ERROR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1c768ff5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:34:04.208755300Z",
     "start_time": "2026-01-30T19:34:00.651410100Z"
    }
   },
   "outputs": [],
   "source": [
    "Datas = eet.read(config=\"neware_8_0_0_516\", input_path=r\"..\\..\\res\\raw\")\n",
    "Data = eet.merge_into_series(Datas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3cdc082f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:34:05.611542300Z",
     "start_time": "2026-01-30T19:34:04.209762Z"
    }
   },
   "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>Meta_Data</th>\n",
       "      <th>Step_Count</th>\n",
       "      <th>Voltage[V]</th>\n",
       "      <th>Current[A]</th>\n",
       "      <th>Temperature[°C]</th>\n",
       "      <th>Test_Time[s]</th>\n",
       "      <th>Date_Time</th>\n",
       "      <th>EIS_f[Hz]</th>\n",
       "      <th>EIS_Z_Real[Ohm]</th>\n",
       "      <th>EIS_Z_Imag[Ohm]</th>\n",
       "      <th>EIS_DC[A]</th>\n",
       "      <th>TestIndex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>1.4378</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5287</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>27.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5298</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5307</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Meta_Data  Step_Count  Voltage[V]  \\\n",
       "0  20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...         0.0      3.5269   \n",
       "1                                               None         0.0      3.5287   \n",
       "2                                               None         0.0      3.5298   \n",
       "3                                               None         0.0      3.5307   \n",
       "4                                               None         0.0      3.5315   \n",
       "\n",
       "   Current[A]  Temperature[°C]  Test_Time[s]           Date_Time EIS_f[Hz]  \\\n",
       "0      1.4378             27.8           0.0 2024-02-01 10:09:04      None   \n",
       "1      1.4398             27.8           1.0 2024-02-01 10:09:05      None   \n",
       "2      1.4400             27.8           2.0 2024-02-01 10:09:06      None   \n",
       "3      1.4400             27.8           3.0 2024-02-01 10:09:07      None   \n",
       "4      1.4401             27.8           4.0 2024-02-01 10:09:08      None   \n",
       "\n",
       "  EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm] EIS_DC[A]  TestIndex  \n",
       "0            None            None      None        0.0  \n",
       "1            None            None      None        0.0  \n",
       "2            None            None      None        0.0  \n",
       "3            None            None      None        0.0  \n",
       "4            None            None      None        0.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data_segmented = eet.add_primitive_segments(Data)\n",
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cc2a028c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:34:05.627536900Z",
     "start_time": "2026-01-30T19:34:05.611542300Z"
    }
   },
   "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>Meta_Data</th>\n",
       "      <th>Step_Count</th>\n",
       "      <th>Voltage[V]</th>\n",
       "      <th>Current[A]</th>\n",
       "      <th>Temperature[°C]</th>\n",
       "      <th>Test_Time[s]</th>\n",
       "      <th>Date_Time</th>\n",
       "      <th>EIS_f[Hz]</th>\n",
       "      <th>EIS_Z_Real[Ohm]</th>\n",
       "      <th>EIS_Z_Imag[Ohm]</th>\n",
       "      <th>EIS_DC[A]</th>\n",
       "      <th>TestIndex</th>\n",
       "      <th>InternalResistance[ohm]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>1.4378</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5287</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>27.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5298</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5307</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Meta_Data  Step_Count  Voltage[V]  \\\n",
       "0  20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...         0.0      3.5269   \n",
       "1                                               None         0.0      3.5287   \n",
       "2                                               None         0.0      3.5298   \n",
       "3                                               None         0.0      3.5307   \n",
       "4                                               None         0.0      3.5315   \n",
       "\n",
       "   Current[A]  Temperature[°C]  Test_Time[s]           Date_Time EIS_f[Hz]  \\\n",
       "0      1.4378             27.8           0.0 2024-02-01 10:09:04      None   \n",
       "1      1.4398             27.8           1.0 2024-02-01 10:09:05      None   \n",
       "2      1.4400             27.8           2.0 2024-02-01 10:09:06      None   \n",
       "3      1.4400             27.8           3.0 2024-02-01 10:09:07      None   \n",
       "4      1.4401             27.8           4.0 2024-02-01 10:09:08      None   \n",
       "\n",
       "  EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm] EIS_DC[A]  TestIndex  \\\n",
       "0            None            None      None        0.0   \n",
       "1            None            None      None        0.0   \n",
       "2            None            None      None        0.0   \n",
       "3            None            None      None        0.0   \n",
       "4            None            None      None        0.0   \n",
       "\n",
       "   InternalResistance[ohm]  \n",
       "0                      NaN  \n",
       "1                      NaN  \n",
       "2                      NaN  \n",
       "3                      NaN  \n",
       "4                      NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Battery_Config = eet.lgm50lt_nmc_4800\n",
    "\n",
    "# todo: is it possible to probide acces to the Batemo/About-Energy database and fetch battery configs directly from there?\n",
    "# todo: or we download it and provide the databse directly?\n",
    "\n",
    "Data = eet.add_resistance_internal(Data, config=Battery_Config)\n",
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a91b693a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:34:05.656866100Z",
     "start_time": "2026-01-30T19:34:05.629042600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "ax.scatter(Data[\"Test_Time[s]\"], Data[\"InternalResistance[ohm]\"])\n",
    "ax.set_xlabel(\"Time (s)\")\n",
    "ax.set_ylabel(\"Internal Resistance (ohm)\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pydpeet (3.12.13)",
   "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": "3.12.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}