54 lines
2.3 KiB
Python
54 lines
2.3 KiB
Python
from fusion import run_all_efast_scenarios
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from postprocessing import post_process_all_scenarios, post_process_timeseries
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from acquisition_s2 import download_s2
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from acquisition_s3 import download_s3
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from acquisition_phenocam import download_phenocam
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from preselection import create_timeseries
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from preparation import prepare_s2, prepare_s3
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from metrics_indices import create_prepared_fusion_timeseries
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from metrics_stats import calculate_all_metrics
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def run_pipeline(season, site_position, site_name):
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"""Run pipeline."""
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try:
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#print(f"Downloading S2, S3, and PhenoCam: {site_name}, {season}")
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#download_s2(season, site_position, site_name)
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#download_s3(season, site_position, site_name)
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#download_phenocam(season, site_position, site_name)
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# print(f"Creating preselection timeseries: {site_name}, {season}")
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# create_timeseries(season, site_position, site_name)
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# print(f"Preparing S2 and S3 for fusion: {site_name}, {season}")
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# for strategy in ["aggressive", "nonaggressive"]:
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# prepare_s2(season, site_position, site_name, cleaning_strategy=strategy)
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# prepare_s3(season, site_position, site_name, cleaning_strategy=strategy)
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# print(f"Running EFAST fusion for all scenarios: {site_name}, {season}")
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# run_all_efast_scenarios(season, site_position, site_name)
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print(f"Creating prepared/fusion timeseries: {site_name}, {season}")
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create_prepared_fusion_timeseries(season, site_position, site_name)
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print(f"Post-processing: {site_name}, {season}")
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# post_process_all_scenarios(season, site_position, site_name)
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post_process_timeseries(season, site_position, site_name)
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print(f"Calculating metrics: {site_name}, {season}")
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# calculate_all_metrics(season, site_name, site_position)
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except Exception as e:
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print(f"Error: {e}")
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raise
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if __name__ == "__main__":
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run_pipeline(2024, (47.116171, 11.320308), "innsbruck")
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run_pipeline(2024, (35.3045, 25.0743), "forthgr")
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run_pipeline(2020, (47.116171, 11.320308), "innsbruck")
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run_pipeline(2024, (58.5633, 24.3688), "pitsalu")
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run_pipeline(2023, (64.2437, 19.7673), "vindeln2")
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run_pipeline(2024, (36.7455, -6.0033), "sunflowerjerez1")
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run_pipeline(2024, (42.6558, 26.9837), "institutekarnobat")
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