# from fusion import run_all_efast_scenarios
# from postprocessing import process_all_scenarios
# from metrics_indices import (
#     create_ndvi_timeseries_post_process,
#     create_gcc_timeseries_post_process,
#     create_s2_bands_timeseries_post_process,
# )
from acquisition_s2 import download_s2
from acquisition_s3 import download_s3
from acquisition_phenocam import download_phenocam
from preselection import create_timeseries
from preparation import prepare_s2, prepare_s3
# from metrics_stats import calculate_all_metrics


def run_pipeline(season, site_position, site_name):
    """Run pipeline."""
    try:
        #print(f"Downloading S2, S3, and PhenoCam: {site_name}, {season}")
        #download_s2(season, site_position, site_name)
        #download_s3(season, site_position, site_name)
        #download_phenocam(season, site_position, site_name)

        #print(f"Creating preselection timeseries: {site_name}, {season}")
        #create_timeseries(season, site_position, site_name)

        #print(f"Preparing S2 and S3 for fusion: {site_name}, {season}")
        #for strategy in ["aggressive", "nonaggressive"]:
        #    prepare_s2(season, site_position, site_name, cleaning_strategy=strategy)
        #    prepare_s3(season, site_position, site_name, cleaning_strategy=strategy)

        print(f"Running EFAST fusion for all scenarios: {site_name}, {season}")
        run_all_efast_scenarios(season, site_position, site_name)
        # print(f"Post-processing data: {site_name}, {season}")
        # process_all_scenarios(season, site_position, site_name)
        # print(f"Generating NDVI for final outputs: {site_name}, {season}")
        # create_ndvi_timeseries_post_process(season, site_position, site_name)
        # print(f"Generating GCC for final outputs: {site_name}, {season}")
        # create_gcc_timeseries_post_process(season, site_position, site_name)
        # print(f"Generating S2 band timeseries: {site_name}, {season}")
        # create_s2_bands_timeseries_post_process(season, site_position, site_name)
        # print(f"Calculating metrics: {site_name}, {season}")
        # calculate_all_metrics(season, site_name, site_position)

    except Exception as e:
        print(f"Error: {e}")
        raise


if __name__ == "__main__":
    run_pipeline(2024, (47.116171, 11.320308), "innsbruck")
    # run_pipeline(2024, (35.3045, 25.0743), "forthgr")
    # run_pipeline(2020, (47.116171, 11.320308), "innsbruck")
    # run_pipeline(2024, (58.5633, 24.3688), "pitsalu")
    # run_pipeline(2023, (64.2437, 19.7673), "vindeln2")
    # run_pipeline(2024, (36.7455, -6.0033), "sunflowerjerez1")
    # run_pipeline(2024, (42.6558, 26.9837), "institutekarnobat")