{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8d214841495e4a0a",
   "metadata": {},
   "source": "# Tutorial 05.1 - add_primitive_segments, PrimitiveConfig, primitive_config_wrapper, DeviceConfig, calculate_minimum_definitive_differences"
  },
  {
   "cell_type": "markdown",
   "id": "b8cb8d2673bd3b04",
   "metadata": {},
   "source": "## Step 0: Setup the project and prepare the data"
  },
  {
   "cell_type": "code",
   "id": "870dd5b36ab98073",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:50.433515600Z",
     "start_time": "2026-06-13T20:49:49.974325600Z"
    }
   },
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import pydpeet as eet"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "2f71f030a4f5410d",
   "metadata": {},
   "source": "We will use \"ERROR\" as the logging style for better readability of the notebook"
  },
  {
   "cell_type": "code",
   "id": "613345ff1adab01e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:50.453646400Z",
     "start_time": "2026-06-13T20:49:50.433515600Z"
    }
   },
   "source": [
    "eet.set_logging_style(\"ERROR\")"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "id": "81c77f517ebad715",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:54.456965400Z",
     "start_time": "2026-06-13T20:49:50.454754900Z"
    }
   },
   "source": [
    "standardized_data = eet.read(\n",
    "    input_path=str(Path.cwd().parent.parent / \"res\" / \"raw_data_from_cyclers\" / \"Cal_Ageing_Checkup1.xlsx\"),\n",
    "    config=eet.ReadConfig.Neware_8_0_0_516,\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:54.913286800Z",
     "start_time": "2026-06-13T20:49:54.481669900Z"
    }
   },
   "cell_type": "code",
   "source": [
    "standardized_data.plot(x=\"Test_Time[s]\", y=\"Current[A]\", figsize=(20, 5))\n",
    "standardized_data.plot(x=\"Test_Time[s]\", y=\"Voltage[V]\", figsize=(20, 5))"
   ],
   "id": "80df8d8f7da15d45",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Test_Time[s]'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "id": "3a0acd7aef27f0b2",
   "metadata": {},
   "source": "## Step 1: Add primitive segments"
  },
  {
   "cell_type": "markdown",
   "id": "12b421d5caded5c0",
   "metadata": {},
   "source": "\"add_primitive_segments\" segments the data into quasi-linear segments (constant current, constant voltage, power ramp, ...)."
  },
  {
   "cell_type": "code",
   "id": "2007765bcb81c6d3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:55.809857300Z",
     "start_time": "2026-06-13T20:49:54.920470500Z"
    }
   },
   "source": [
    "segmented_data = eet.add_primitive_segments(df=standardized_data, config=eet.PrimitiveConfig.OCV_ANALYSIS_DEFAULT)"
   ],
   "outputs": [],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "id": "126af180fb4f4a5c",
   "metadata": {},
   "source": "It adds the following columns to the dataframe:"
  },
  {
   "cell_type": "code",
   "id": "b15580e8ffbd841b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:55.824050500Z",
     "start_time": "2026-06-13T20:49:55.810527100Z"
    }
   },
   "source": [
    "added_cols = [c for c in segmented_data.columns if c not in standardized_data.columns]\n",
    "added_cols"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Power[W]',\n",
       " 'ID',\n",
       " 'Variable',\n",
       " 'Duration',\n",
       " 'Length',\n",
       " 'Min',\n",
       " 'Max',\n",
       " 'Avg',\n",
       " 'Type',\n",
       " 'Direction',\n",
       " 'Slope']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "code",
   "id": "fc1b733e3bda7224",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:55.840975300Z",
     "start_time": "2026-06-13T20:49:55.824564300Z"
    }
   },
   "source": [
    "segmented_data[added_cols].tail(6)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "          Power[W]   ID Variable  Duration  Length  Min  Max  Avg  Type  \\\n",
       "167857.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "167858.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "167859.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "167860.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "167861.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "167862.0       0.0  497        I    3600.0  3599.0  0.0  0.0  0.0  Rest   \n",
       "\n",
       "         Direction  Slope  \n",
       "167857.0   Neutral    0.0  \n",
       "167858.0   Neutral    0.0  \n",
       "167859.0   Neutral    0.0  \n",
       "167860.0   Neutral    0.0  \n",
       "167861.0   Neutral    0.0  \n",
       "167862.0   Neutral    0.0  "
      ],
      "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>Power[W]</th>\n",
       "      <th>ID</th>\n",
       "      <th>Variable</th>\n",
       "      <th>Duration</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>167857.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167858.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167859.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167860.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167861.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167862.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "id": "3e2e6a5eb6b878",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Hint:</b> You can use *segmented_data.groupby(\"ID\").first()* to get the first value of each segment\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "id": "f1873c52b3652341",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-06-13T20:49:55.880095Z",
     "start_time": "2026-06-13T20:49:55.841980800Z"
    }
   },
   "source": [
    "segmented_data.groupby(\"ID\")[added_cols].first()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     Power[W]   ID Variable  Duration   Length     Min     Max       Avg  \\\n",
       "ID                                                                         \n",
       "1    5.070977    1        V    9112.0   9111.0  3.5269  4.2001  3.889836   \n",
       "2    6.036804    2        V    2411.0   2409.9  4.2001  4.2004  4.200252   \n",
       "3    0.000000    3        I      60.0     59.0  0.0000  0.0000  0.000000   \n",
       "4   -4.005888    4        I   17820.0  17819.0 -0.9601 -0.9599 -0.960029   \n",
       "5   -2.330613    5        V     509.0    507.9  2.5000  2.5020  2.500138   \n",
       "..        ...  ...      ...       ...      ...     ...     ...       ...   \n",
       "493  5.995934  493        I      98.0     96.1  1.4396  1.4399  1.439723   \n",
       "494  0.000000  494        I     360.0    359.0  0.0000  0.0000  0.000000   \n",
       "495  6.007768  495        I      62.0     60.5  1.4387  1.4397  1.439615   \n",
       "496  5.996626  496        V    1664.0   1662.8  4.2002  4.2004  4.200271   \n",
       "497  0.000000  497        I    3600.0   3599.0  0.0000  0.0000  0.000000   \n",
       "\n",
       "         Type  Direction         Slope  \n",
       "ID                                      \n",
       "1        Ramp         Up  7.388871e-05  \n",
       "2    Constant     Charge  8.298755e-08  \n",
       "3        Rest    Neutral  0.000000e+00  \n",
       "4    Constant  Discharge  5.611987e-09  \n",
       "5    Constant  Discharge -3.740157e-06  \n",
       "..        ...        ...           ...  \n",
       "493  Constant     Charge  0.000000e+00  \n",
       "494      Rest    Neutral  0.000000e+00  \n",
       "495  Constant     Charge -1.147541e-05  \n",
       "496  Constant     Charge  6.013229e-08  \n",
       "497      Rest    Neutral  0.000000e+00  \n",
       "\n",
       "[497 rows x 11 columns]"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Power[W]</th>\n",
       "      <th>ID</th>\n",
       "      <th>Variable</th>\n",
       "      <th>Duration</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.070977</td>\n",
       "      <td>1</td>\n",
       "      <td>V</td>\n",
       "      <td>9112.0</td>\n",
       "      <td>9111.0</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>4.2001</td>\n",
       "      <td>3.889836</td>\n",
       "      <td>Ramp</td>\n",
       "      <td>Up</td>\n",
       "      <td>7.388871e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6.036804</td>\n",
       "      <td>2</td>\n",
       "      <td>V</td>\n",
       "      <td>2411.0</td>\n",
       "      <td>2409.9</td>\n",
       "      <td>4.2001</td>\n",
       "      <td>4.2004</td>\n",
       "      <td>4.200252</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>8.298755e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>I</td>\n",
       "      <td>60.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-4.005888</td>\n",
       "      <td>4</td>\n",
       "      <td>I</td>\n",
       "      <td>17820.0</td>\n",
       "      <td>17819.0</td>\n",
       "      <td>-0.9601</td>\n",
       "      <td>-0.9599</td>\n",
       "      <td>-0.960029</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Discharge</td>\n",
       "      <td>5.611987e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-2.330613</td>\n",
       "      <td>5</td>\n",
       "      <td>V</td>\n",
       "      <td>509.0</td>\n",
       "      <td>507.9</td>\n",
       "      <td>2.5000</td>\n",
       "      <td>2.5020</td>\n",
       "      <td>2.500138</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Discharge</td>\n",
       "      <td>-3.740157e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>5.995934</td>\n",
       "      <td>493</td>\n",
       "      <td>I</td>\n",
       "      <td>98.0</td>\n",
       "      <td>96.1</td>\n",
       "      <td>1.4396</td>\n",
       "      <td>1.4399</td>\n",
       "      <td>1.439723</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>494</td>\n",
       "      <td>I</td>\n",
       "      <td>360.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>6.007768</td>\n",
       "      <td>495</td>\n",
       "      <td>I</td>\n",
       "      <td>62.0</td>\n",
       "      <td>60.5</td>\n",
       "      <td>1.4387</td>\n",
       "      <td>1.4397</td>\n",
       "      <td>1.439615</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>-1.147541e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>5.996626</td>\n",
       "      <td>496</td>\n",
       "      <td>V</td>\n",
       "      <td>1664.0</td>\n",
       "      <td>1662.8</td>\n",
       "      <td>4.2002</td>\n",
       "      <td>4.2004</td>\n",
       "      <td>4.200271</td>\n",
       "      <td>Constant</td>\n",
       "      <td>Charge</td>\n",
       "      <td>6.013229e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>497</td>\n",
       "      <td>I</td>\n",
       "      <td>3600.0</td>\n",
       "      <td>3599.0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Rest</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>497 rows × 11 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 8
  }
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