Source code for models.fleet_simulator.main

import pandas as pd
import warnings
import datetime
from pathlib import Path
from . import commercial_simulation
from .import_vehicles import get_vehicle_data
from .. import utils

print_level_base = 1

warnings.filterwarnings("ignore")
    
utils.print_update(level=print_level_base,message="Initializing Fleet Simulator...")



def run_fleet_simulation(start_date:str, 
                         end_date:str,
                         samples:int,
                         force_update=True,
                         show_log:bool=False):
    """_summary_

    Args:
        start_date (str): "yyyy-mm-dd"
        days (int): Number of days to simulate
        samples (int): Number of samples to get from the vehicle population
    """

    travel_patterns_save_to = Path('results/fleet_simulator/commercial_travel_patterns.csv')
    if travel_patterns_save_to.exists():
            utils.print_update(level=print_level_base+1, message="Travel patterns file already exists")
            if not force_update:
                utils.print_update(level=print_level_base+1, message="force-update is disabled. Skipping travel pattern simulation.")
                return  # Gracefully exit the function
            else:
                utils.print_update(level=print_level_base+1, message="The simulation will overwrite the existing travel patterns file.")
                vehicle_resolution:int=1
                # Import data
                icbc_commercial_data = pd.read_csv('data/fleet_simulator/inputs/icbc_commercial_population.csv')
                icbc_passenger_data = pd.read_csv('data/fleet_simulator/inputs/icbc_passenger_population.csv')
                vehicle_types = pd.read_csv('data/fleet_simulator/inputs/vehicle_types.csv')
                
                utils.print_update(level=print_level_base+1,message="Preparing vehicle data...")
                get_vehicle_data(vehicle_resolution, 
                                    False,
                                    icbc_commercial_data,
                                    icbc_passenger_data,
                                    vehicle_types)

                business_fleet = pd.read_csv('data/fleet_simulator/processed/vehicle_populations/disaggregated_business_fleet.csv')
                nrel_data = pd.read_csv('data/fleet_simulator/inputs/nrel_commercial_fleet_data.csv')
                
                timespan = (datetime.datetime.strptime(end_date, '%Y-%m-%d') - datetime.datetime.strptime(start_date, '%Y-%m-%d')).days+1
                utils.print_update(level=print_level_base+1,message=f"Preparing travel pattern for {timespan} days...")
                commercial_simulation.generate_travel_patterns(start_date, 
                                                            end_date, 
                                                            samples,
                                                            nrel_data,
                                                            business_fleet,
                                                            show_log=show_log)