{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a18039fb",
   "metadata": {},
   "source": [
    "# Tutorial 4 - iOCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a8f68619",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pydpeet as eet\n",
    "\n",
    "eet.set_logging_style(\"ERROR\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd1aac60",
   "metadata": {},
   "source": [
    "OCVs are Importend for Analyzing Materials, Ageeing and for Parametrisiation of Models. Here the Funtion from [Squences](Tutorial_02_Sequence.ipynb) is used to automatically extract incremntall OCVs from Lab-Data and analyze it through DVA and ICA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7aa97f4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "Data = eet.read(config=\"neware_8_0_0_516\", input_path=r\"..\\..\\res\\raw\\Cal_Ageing_Checkup3.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "892963a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "LGM50LT = eet.BatteryConfig(\n",
    "    c_ref=4.75,\n",
    "    max_voltage=4.2,\n",
    "    min_voltage=2.5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f1f85e52",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>20240419100603-CheckUp-1-6-AM23NMC00009.xlsx U...</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5353</td>\n",
       "      <td>1.4396</td>\n",
       "      <td>30.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-04-19 10:06:03</td>\n",
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       "      <td>None</td>\n",
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       "      <td>3.5388</td>\n",
       "      <td>1.4398</td>\n",
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       "      <td>None</td>\n",
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       "      <td>1.4399</td>\n",
       "      <td>29.9</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2024-04-19 10:06:07</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Meta_Data  Step_Count  \\\n",
       "0.0  20240419100603-CheckUp-1-6-AM23NMC00009.xlsx U...           0   \n",
       "1.0                                               None           0   \n",
       "2.0                                               None           0   \n",
       "3.0                                               None           0   \n",
       "4.0                                               None           0   \n",
       "\n",
       "     Voltage[V]  Current[A]  Temperature[°C]  Test_Time[s]  \\\n",
       "0.0      3.5353      1.4396             30.1           0.0   \n",
       "1.0      3.5368      1.4397             30.1           1.0   \n",
       "2.0      3.5379      1.4398             30.1           2.0   \n",
       "3.0      3.5388      1.4398             29.9           3.0   \n",
       "4.0      3.5396      1.4399             29.9           4.0   \n",
       "\n",
       "              Date_Time EIS_f[Hz] EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm] EIS_DC[A]  \n",
       "0.0 2024-04-19 10:06:03      None            None            None      None  \n",
       "1.0 2024-04-19 10:06:04      None            None            None      None  \n",
       "2.0 2024-04-19 10:06:05      None            None            None      None  \n",
       "3.0 2024-04-19 10:06:06      None            None            None      None  \n",
       "4.0 2024-04-19 10:06:07      None            None            None      None  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7482210b",
   "metadata": {},
   "outputs": [],
   "source": [
    "OCVs = eet.extract_ocv_iocv(df=Data, config=LGM50LT, visualize=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "137aa078",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Test_Time[s]</th>\n",
       "      <th>Voltage[V]</th>\n",
       "      <th>Current[A]</th>\n",
       "      <th>Power[W]</th>\n",
       "      <th>ID</th>\n",
       "      <th>Meta_Data</th>\n",
       "      <th>Step_Count</th>\n",
       "      <th>Temperature[°C]</th>\n",
       "      <th>Date_Time</th>\n",
       "      <th>EIS_f[Hz]</th>\n",
       "      <th>...</th>\n",
       "      <th>Length</th>\n",
       "      <th>Min</th>\n",
       "      <th>Max</th>\n",
       "      <th>Avg</th>\n",
       "      <th>Type</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Slope</th>\n",
       "      <th>Capacity[Ah]</th>\n",
       "      <th>SOC</th>\n",
       "      <th>iOCV_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>44008.0</th>\n",
       "      <td>44002.6</td>\n",
       "      <td>4.1934</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>None</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25.7</td>\n",
       "      <td>2024-04-19 22:19:24</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>899.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Discharge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44516.0</th>\n",
       "      <td>44508.1</td>\n",
       "      <td>4.1683</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
       "      <td>None</td>\n",
       "      <td>7.0</td>\n",
       "      <td>25.9</td>\n",
       "      <td>2024-04-19 22:27:50</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Discharge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45024.0</th>\n",
       "      <td>45013.6</td>\n",
       "      <td>4.1500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "      <td>9.0</td>\n",
       "      <td>25.7</td>\n",
       "      <td>2024-04-19 22:36:16</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.991777</td>\n",
       "      <td>Discharge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45532.0</th>\n",
       "      <td>45519.1</td>\n",
       "      <td>4.1361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15</td>\n",
       "      <td>None</td>\n",
       "      <td>11.0</td>\n",
       "      <td>25.7</td>\n",
       "      <td>2024-04-19 22:44:41</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.983555</td>\n",
       "      <td>Discharge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46040.0</th>\n",
       "      <td>46024.6</td>\n",
       "      <td>4.1252</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>None</td>\n",
       "      <td>13.0</td>\n",
       "      <td>25.7</td>\n",
       "      <td>2024-04-19 22:53:07</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.975332</td>\n",
       "      <td>Discharge</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Test_Time[s]  Voltage[V]  Current[A]  Power[W]  ID Meta_Data  \\\n",
       "44008.0       44002.6      4.1934         0.0       0.0   9      None   \n",
       "44516.0       44508.1      4.1683         0.0       0.0  11      None   \n",
       "45024.0       45013.6      4.1500         0.0       0.0  13      None   \n",
       "45532.0       45519.1      4.1361         0.0       0.0  15      None   \n",
       "46040.0       46024.6      4.1252         0.0       0.0  17      None   \n",
       "\n",
       "         Step_Count  Temperature[°C]           Date_Time EIS_f[Hz]  ...  \\\n",
       "44008.0         5.0             25.7 2024-04-19 22:19:24      None  ...   \n",
       "44516.0         7.0             25.9 2024-04-19 22:27:50      None  ...   \n",
       "45024.0         9.0             25.7 2024-04-19 22:36:16      None  ...   \n",
       "45532.0        11.0             25.7 2024-04-19 22:44:41      None  ...   \n",
       "46040.0        13.0             25.7 2024-04-19 22:53:07      None  ...   \n",
       "\n",
       "        Length  Min  Max  Avg  Type  Direction  Slope  Capacity[Ah]       SOC  \\\n",
       "44008.0  899.0  0.0  0.0  0.0  Rest    Neutral    0.0           NaN  1.000000   \n",
       "44516.0  359.0  0.0  0.0  0.0  Rest    Neutral    0.0           NaN  1.000000   \n",
       "45024.0  359.0  0.0  0.0  0.0  Rest    Neutral    0.0           NaN  0.991777   \n",
       "45532.0  359.0  0.0  0.0  0.0  Rest    Neutral    0.0           NaN  0.983555   \n",
       "46040.0  359.0  0.0  0.0  0.0  Rest    Neutral    0.0           NaN  0.975332   \n",
       "\n",
       "         iOCV_type  \n",
       "44008.0  Discharge  \n",
       "44516.0  Discharge  \n",
       "45024.0  Discharge  \n",
       "45532.0  Discharge  \n",
       "46040.0  Discharge  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OCVs[0].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "56f3f825",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "for ocv in OCVs:\n",
    "    ax.plot(ocv[\"SOC\"], ocv[\"Voltage[V]\"], linestyle=\"-\")\n",
    "    ax.set_xlabel(\"SOC\")\n",
    "    ax.set_ylabel(\"Voltage [V]\")"
   ]
  }
 ],
 "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
}