{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "37be6162",
   "metadata": {},
   "source": [
    "# Tutorial 5 - SOC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cd7a4e14",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:33:51.999366600Z",
     "start_time": "2026-01-30T19:33:51.685898700Z"
    }
   },
   "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": "4d24096e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:33:55.963332400Z",
     "start_time": "2026-01-30T19:33:52.001991Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>20240419100603-CheckUp-1-6-AM23NMC00009.xlsx U...</td>\n",
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       "      <td>2024-04-19 10:06:04</td>\n",
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       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>2.0</th>\n",
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       "      <td>30.1</td>\n",
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       "      <td>2024-04-19 10:06:05</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>None</td>\n",
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       "      <th>4.0</th>\n",
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       "      <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": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data = eet.read(config=\"neware_8_0_0_516\", input_path=r\"..\\..\\res\\raw\\Cal_Ageing_Checkup3.xlsx\")\n",
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "509535c1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:33:56.658880700Z",
     "start_time": "2026-01-30T19:33:55.964335300Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th>Temperature[°C]</th>\n",
       "      <th>Test_Time[s]</th>\n",
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       "      <th>EIS_Z_Imag[Ohm]</th>\n",
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       "      <td>1.4388</td>\n",
       "      <td>1.44</td>\n",
       "      <td>1.439794</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>-9.017133e-08</td>\n",
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       "    <tr>\n",
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       "      <td>1.439794</td>\n",
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       "      <td>Charge</td>\n",
       "      <td>-9.017133e-08</td>\n",
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       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5396</td>\n",
       "      <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",
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       "      <td>1.4388</td>\n",
       "      <td>1.44</td>\n",
       "      <td>1.439794</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>-9.017133e-08</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
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      ],
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       "                                             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]  ... ID  \\\n",
       "0.0 2024-04-19 10:06:03      None            None            None  ...  1   \n",
       "1.0 2024-04-19 10:06:04      None            None            None  ...  1   \n",
       "2.0 2024-04-19 10:06:05      None            None            None  ...  1   \n",
       "3.0 2024-04-19 10:06:06      None            None            None  ...  1   \n",
       "4.0 2024-04-19 10:06:07      None            None            None  ...  1   \n",
       "\n",
       "     Variable  Duration  Length     Min   Max       Avg      Type  Direction  \\\n",
       "0.0         I    8873.0  8872.0  1.4388  1.44  1.439794  Constant     Charge   \n",
       "1.0         I    8873.0  8872.0  1.4388  1.44  1.439794  Constant     Charge   \n",
       "2.0         I    8873.0  8872.0  1.4388  1.44  1.439794  Constant     Charge   \n",
       "3.0         I    8873.0  8872.0  1.4388  1.44  1.439794  Constant     Charge   \n",
       "4.0         I    8873.0  8872.0  1.4388  1.44  1.439794  Constant     Charge   \n",
       "\n",
       "            Slope  \n",
       "0.0 -9.017133e-08  \n",
       "1.0 -9.017133e-08  \n",
       "2.0 -9.017133e-08  \n",
       "3.0 -9.017133e-08  \n",
       "4.0 -9.017133e-08  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data_segmented = eet.add_primitive_segments(Data)\n",
    "Data_segmented.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "50c9ec86",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T19:33:56.980452700Z",
     "start_time": "2026-01-30T19:33:56.658880700Z"
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   },
   "outputs": [
    {
     "data": {
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       "      <th>3.0</th>\n",
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       "      <td>2024-04-19 10:06:06</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.203627</td>\n",
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       "      <th>4.0</th>\n",
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      "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   \n",
       "\n",
       "     Capacity[Ah]       SOC  \n",
       "0.0           NaN  0.203377  \n",
       "1.0           NaN  0.203461  \n",
       "2.0           NaN  0.203544  \n",
       "3.0           NaN  0.203627  \n",
       "4.0           NaN  0.203711  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Battery_Config = eet.lgm50lt_nmc_4800\n",
    "method = eet.SocMethod.WITH_RESET_WHEN_FULL\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",
    "Result = eet.add_soc(df=Data, df_primitives=Data_segmented, standard_method=method, config=Battery_Config)\n",
    "Result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c6c1ee92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(Result[\"Test_Time[s]\"], Result[\"SOC\"])\n",
    "ax.set_xlabel(\"Time (s)\")\n",
    "ax.set_ylabel(\"State of Charge\")\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
}