calibrate_tracks.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a7569fa-15ba-4863-be82-110eba5987f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "from sqlalchemy import create_engine, MetaData, delete\n",
    "import numpy as np\n",
    "from scipy.stats import linregress as fit\n",
    "\n",
    "import time\n",
    "import pickle\n",
    "import os\n",
    "from tqdm import tqdm\n",
    "\n",
    "from datetime import timedelta, datetime\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "import utils\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "71c50464-0d2f-4e4b-98cb-f94b4b3ba54a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yas Island\n"
     ]
    }
   ],
   "source": [
    "i = 21\n",
    "\n",
    "# this list came from sessions api for 2023, \"location\" attribute\n",
    "locations = ['Sakhir', 'Jeddah', 'Melbourne', 'Baku', 'Miami', 'Monaco',\n",
    "       'Barcelona', 'Montréal', 'Spielberg', 'Silverstone', 'Budapest',\n",
    "       'Spa-Francorchamps', 'Zandvoort', 'Monza', 'Marina Bay', 'Suzuka',\n",
    "       'Lusail', 'Austin', 'Mexico City', 'São Paulo', 'Las Vegas',\n",
    "       'Yas Island', 'Shanghai']\n",
    "location = locations[i]\n",
    "print(location)\n",
    "year = 2023\n",
    "\n",
    "location = 'Shanghai'\n",
    "year = 2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f7e7cc41",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        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>session_key</th>\n",
       "      <th>session_name</th>\n",
       "      <th>date_start</th>\n",
       "      <th>date_end</th>\n",
       "      <th>gmt_offset</th>\n",
       "      <th>session_type</th>\n",
       "      <th>meeting_key</th>\n",
       "      <th>location</th>\n",
       "      <th>country_key</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country_name</th>\n",
       "      <th>circuit_key</th>\n",
       "      <th>circuit_short_name</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9663</td>\n",
       "      <td>Practice 1</td>\n",
       "      <td>2024-04-19T03:30:00</td>\n",
       "      <td>2024-04-19T04:30:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Practice</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9668</td>\n",
       "      <td>Sprint Qualifying</td>\n",
       "      <td>2024-04-19T07:30:00</td>\n",
       "      <td>2024-04-19T08:14:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9672</td>\n",
       "      <td>Sprint</td>\n",
       "      <td>2024-04-20T03:00:00</td>\n",
       "      <td>2024-04-20T03:30:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Race</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9664</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>2024-04-20T07:00:00</td>\n",
       "      <td>2024-04-20T08:00:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9673</td>\n",
       "      <td>Race</td>\n",
       "      <td>2024-04-21T07:00:00</td>\n",
       "      <td>2024-04-21T09:00:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Race</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   session_key       session_name           date_start             date_end  \\\n",
       "0         9663         Practice 1  2024-04-19T03:30:00  2024-04-19T04:30:00   \n",
       "1         9668  Sprint Qualifying  2024-04-19T07:30:00  2024-04-19T08:14:00   \n",
       "2         9672             Sprint  2024-04-20T03:00:00  2024-04-20T03:30:00   \n",
       "3         9664         Qualifying  2024-04-20T07:00:00  2024-04-20T08:00:00   \n",
       "4         9673               Race  2024-04-21T07:00:00  2024-04-21T09:00:00   \n",
       "\n",
       "  gmt_offset session_type  meeting_key  location  country_key country_code  \\\n",
       "0   08:00:00     Practice         1233  Shanghai           53          CHN   \n",
       "1   08:00:00   Qualifying         1233  Shanghai           53          CHN   \n",
       "2   08:00:00         Race         1233  Shanghai           53          CHN   \n",
       "3   08:00:00   Qualifying         1233  Shanghai           53          CHN   \n",
       "4   08:00:00         Race         1233  Shanghai           53          CHN   \n",
       "\n",
       "  country_name  circuit_key circuit_short_name  year  \n",
       "0        China           49           Shanghai  2024  \n",
       "1        China           49           Shanghai  2024  \n",
       "2        China           49           Shanghai  2024  \n",
       "3        China           49           Shanghai  2024  \n",
       "4        China           49           Shanghai  2024  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "session = utils.get_session(location, year)\n",
    "display(session)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2480c3c-f8b8-4ccb-96a5-3a7cd4d931c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        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>session_key</th>\n",
       "      <th>session_name</th>\n",
       "      <th>date_start</th>\n",
       "      <th>date_end</th>\n",
       "      <th>gmt_offset</th>\n",
       "      <th>session_type</th>\n",
       "      <th>meeting_key</th>\n",
       "      <th>location</th>\n",
       "      <th>country_key</th>\n",
       "      <th>country_code</th>\n",
       "      <th>country_name</th>\n",
       "      <th>circuit_key</th>\n",
       "      <th>circuit_short_name</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9663</td>\n",
       "      <td>Practice 1</td>\n",
       "      <td>2024-04-19T03:30:00</td>\n",
       "      <td>2024-04-19T04:30:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Practice</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9668</td>\n",
       "      <td>Sprint Qualifying</td>\n",
       "      <td>2024-04-19T07:30:00</td>\n",
       "      <td>2024-04-19T08:14:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9672</td>\n",
       "      <td>Sprint</td>\n",
       "      <td>2024-04-20T03:00:00</td>\n",
       "      <td>2024-04-20T03:30:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Race</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9664</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>2024-04-20T07:00:00</td>\n",
       "      <td>2024-04-20T08:00:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Qualifying</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9673</td>\n",
       "      <td>Race</td>\n",
       "      <td>2024-04-21T07:00:00</td>\n",
       "      <td>2024-04-21T09:00:00</td>\n",
       "      <td>08:00:00</td>\n",
       "      <td>Race</td>\n",
       "      <td>1233</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>53</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>49</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   session_key       session_name           date_start             date_end  \\\n",
       "0         9663         Practice 1  2024-04-19T03:30:00  2024-04-19T04:30:00   \n",
       "1         9668  Sprint Qualifying  2024-04-19T07:30:00  2024-04-19T08:14:00   \n",
       "2         9672             Sprint  2024-04-20T03:00:00  2024-04-20T03:30:00   \n",
       "3         9664         Qualifying  2024-04-20T07:00:00  2024-04-20T08:00:00   \n",
       "4         9673               Race  2024-04-21T07:00:00  2024-04-21T09:00:00   \n",
       "\n",
       "  gmt_offset session_type  meeting_key  location  country_key country_code  \\\n",
       "0   08:00:00     Practice         1233  Shanghai           53          CHN   \n",
       "1   08:00:00   Qualifying         1233  Shanghai           53          CHN   \n",
       "2   08:00:00         Race         1233  Shanghai           53          CHN   \n",
       "3   08:00:00   Qualifying         1233  Shanghai           53          CHN   \n",
       "4   08:00:00         Race         1233  Shanghai           53          CHN   \n",
       "\n",
       "  country_name  circuit_key circuit_short_name  year  \n",
       "0        China           49           Shanghai  2024  \n",
       "1        China           49           Shanghai  2024  \n",
       "2        China           49           Shanghai  2024  \n",
       "3        China           49           Shanghai  2024  \n",
       "4        China           49           Shanghai  2024  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "session = utils.get_session(location, year)\n",
    "display(session)\n",
    "\n",
    "if \"Practice 1\" in session.session_name.tolist():\n",
    "    session_key_fp1 = session.query(\" session_name == 'Practice 1'\").session_key.iloc[0]\n",
    "else:\n",
    "    session_key_fp1 = session.query(\" session_name == 'Qualifying'\").session_key.iloc[0]\n",
    "if \"Practice 2\" in session.session_name.tolist():\n",
    "    session_key_fp2 = session.query(\" session_name == 'Practice 2'\").session_key.iloc[0]\n",
    "else:\n",
    "    session_key_fp2 = session.query(\" session_name == 'Sprint'\").session_key.iloc[0]\n",
    "\n",
    "session_key_race = session.query(\" session_name == 'Race'\").session_key.iloc[0]\n",
    "race_start_time = pd.to_datetime(session.query(\" session_name == 'Race'\").date_start.iloc[0])\n",
    "race_end_time = pd.to_datetime(session.query(\" session_name == 'Race'\").date_end.iloc[0])\n",
    "\n",
    "driver_config = {row['name_acronym']:row['driver_number'] for ind, row in utils.get_data(f'https://api.openf1.org/v1/drivers?session_key={session_key_race}').iterrows()}\n",
    "driver_config_reverse = {v: k for k, v in driver_config.items()}\n",
    "\n",
    "\n",
    "lap_data = pd.concat([utils.get_data(f'''https://api.openf1.org/v1/laps?session_key={session_key_fp1}'''), utils.get_data(f'''https://api.openf1.org/v1/laps?session_key={session_key_fp2}''')]).dropna(subset =['lap_duration'])\n",
    "lap_data['date_start'] = pd.to_datetime(lap_data['date_start'],format=\"ISO8601\")\n",
    "lap_data['date_end'] = lap_data.apply(lambda x: x.date_start + timedelta(seconds = x.lap_duration), axis = 1)\n",
    "\n",
    "ref_lap_distances = pd.DataFrame()\n",
    "full_laps = pd.DataFrame()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5d9cae8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building model...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "50it [01:41,  2.04s/it]\n"
     ]
    }
   ],
   "source": [
    "LAP_THRESHOLDS = 50\n",
    "\n",
    "print(\"Building model...\")\n",
    "for _, lap in tqdm(lap_data.sort_values(by = 'lap_duration').iloc[:LAP_THRESHOLDS].iterrows()):\n",
    "\n",
    "    driver_number = lap.driver_number\n",
    "    start_time = lap.date_start\n",
    "    end_time = lap.date_end\n",
    "    session_key = lap.session_key\n",
    "    meeting_key = lap.meeting_key\n",
    "    lap_duration = (end_time - start_time).total_seconds()\n",
    "\n",
    "    config = {'start_time' : start_time - timedelta(seconds = 2), 'end_time' : start_time + timedelta(seconds = 2), 'session_key' : session_key, 'driver_number' : driver_number}\n",
    "    car_data, location_data = utils.get_data_channels(config)\n",
    "\n",
    "    # print(car_data.columns)\n",
    "    # print(location_data.columns)\n",
    "    car_data = car_data[['driver_number', 'rpm', 'speed', 'n_gear', 'throttle', 'drs', 'brake', 'date', 'session_key', 'meeting_key']]\n",
    "    location_data = location_data[['x', 'y', 'z', 'driver_number', 'date', 'session_key', 'meeting_key']]\n",
    "\n",
    "    car_data.loc[len(car_data)] = [driver_number, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, start_time, session_key, meeting_key]\n",
    "    location_data.loc[len(location_data)] = [np.nan, np.nan, np.nan, driver_number, start_time, session_key, meeting_key]\n",
    "\n",
    "    merged = utils.merge_data_channels(car_data.sort_values(by = 'date'), location_data.sort_values(by = 'date'))\n",
    "    merged = utils.compute_distance(merged, start_time)\n",
    "    ref_lap_distances = pd.concat([ref_lap_distances, merged[merged.date == start_time][['x','y','distance', 'driver_number']]])\n",
    "\n",
    "    config = {'start_time' : start_time, 'end_time' : end_time, 'session_key' : session_key, 'driver_number' : driver_number}\n",
    "    car_data, location_data = utils.get_data_channels(config)\n",
    "    merged = utils.merge_data_channels(car_data.sort_values(by = 'date'), location_data.sort_values(by = 'date'))\n",
    "    merged = utils.compute_distance(merged, start_time)\n",
    "    full_laps = pd.concat([full_laps, merged[['x','y','distance', 'driver_number']]])\n",
    "\n",
    "ref_lap_distances.dropna(inplace = True)\n",
    "full_laps.dropna(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b51e0aeb-459c-4581-9c08-7194a55e7057",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(55.797, -1496.219)\n"
     ]
    }
   ],
   "source": [
    "ref_lap_distances['mse'] = 0\n",
    "ref_lap_distances.reset_index(inplace = True)\n",
    "# ref_lap_distances\n",
    "\n",
    "for index, row in ref_lap_distances.iterrows():\n",
    "  ref_points = [[row.x, row.y]]\n",
    "  mse = mean_squared_error(ref_lap_distances[['x', 'y']], np.repeat(ref_points, len(ref_lap_distances), 0))\n",
    "  ref_lap_distances.mse.loc[index] = mse\n",
    "\n",
    "start_line = ref_lap_distances.iloc[ref_lap_distances.mse.argmin()].x.round(3), ref_lap_distances.iloc[ref_lap_distances.mse.argmin()].y.round(3)\n",
    "print(start_line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "992263fd-c046-4f9b-8007-79a219ebcf87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
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   "source": [
    "data = ref_lap_distances.iloc[:]\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x = data.x, y = data.y, mode = 'markers'))\n",
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  {
   "cell_type": "code",
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   "id": "39840694-c2ab-4a01-bc58-b4f24da67b98",
   "metadata": {},
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     "output_type": "stream",
     "text": [
      "(55.797, -1496.219)\n"
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    },
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            "gridcolor": "white",
            "linecolor": "white",
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           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "width": 600,
        "xaxis": {
         "range": [
          -7248.3979609769485,
          5958
         ]
        },
        "yaxis": {
         "range": [
          -4140.089354706496,
          7708.636735763254
         ]
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(start_line)\n",
    "\n",
    "data = full_laps.iloc[:5000]\n",
    "\n",
    "yrange = [data.y.min()-500,data.y.max()+500]\n",
    "xrange = [data.x.min()-500,data.x.max()+500]\n",
    "\n",
    "if ((yrange[1] - yrange[0])/(xrange[1] - xrange[0])) > 1:\n",
    "    height = 600\n",
    "    width = int(600*(yrange[1] - yrange[0])/(xrange[1] - xrange[0]))\n",
    "    \n",
    "else:\n",
    "    width = 600\n",
    "    height = int(600*(yrange[1] - yrange[0])/(xrange[1] - xrange[0]))\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x = data.x, y = data.y, mode = 'markers'))\n",
    "fig.add_trace(go.Scatter(x = [start_line[0]], y = [start_line[1]], mode = 'markers', marker = {'size':15}))\n",
    "fig.update_layout(width = width, height = height, yaxis_range = yrange, xaxis_range = xrange)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1f553cbf-cde3-46b3-8e99-700065e98e1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(55.797, -1496.219) (2001, -1068) (-4020, -2493)\n"
     ]
    }
   ],
   "source": [
    "before_start_line = (2001, -1068)\n",
    "after_start_line = (-4020, -2493)\n",
    "\n",
    "print(start_line, before_start_line, after_start_line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc8f91c6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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