SMLMdataAnalyser/main.py at main · HeilemannLab/SMLMdataAnalyser · GitHub

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import os
import yaml
import pickle
import time

from utils import load_config, get_directory_structure
from collectors import AnalysisCollector
from colocalization import run_analysis

###############################################################################################


def main():
    """Main processing function that handles multiple conditions and proteins"""

    start_time = time.time()

    config = load_config('config.yaml')

    input_dir = config['input_dir']
    output_dir = config['output_dir']

    dark_time_analysis = config.get('dark_time_analysis', False)
    cross_coloc = config.get('cross_coloc', False)
    patching = config.get('patching', False)
    simulation = config.get('simulation', False)

    data_mask = config['data_mask']
    calibration_mask = config['calibration_mask']

    # Extract filter parameters from config
    filter_params = config.get('filter_params', {})
    filter_enabled = filter_params.pop('enabled', False)

    # Extract analysis parameters from config
    pxl_size = config['analysis']['pixel_size']
    coloc_threshold = config['analysis']['coloc_threshold']
    patch_size = config['analysis']['patch_size']


    # Get directory structure: conditions -> proteins -> files
    structure, protein_names, condition_names = get_directory_structure(input_dir)
    collector = AnalysisCollector(protein_names, cross_coloc)


    print(f"Analysis parameters: \n Pixel size: {pxl_size} \n Colocalization threshold: {coloc_threshold}")
    print(f"\nFiltering of raw data: {filter_enabled}")
    print(f"Dark time analysis enabled: {dark_time_analysis}")
    print(f"Cross colocalization enabled: {cross_coloc}")

    print(f"\nConditions to process: {condition_names} \nProteins to process: {protein_names}")


    run_analysis(output_dir,
                     structure,
                    filter_params,
                    filter_enabled,
                    condition_names,
                    collector,
                    protein_names,
                    coloc_threshold,
                    pxl_size,
                    data_mask,
                    calibration_mask,
                    dark_time_analysis,
                    cross_coloc,
                    patching, patch_size,
                    simulation)


    # with open(os.path.join(output_dir, 'collector.pkl'), 'wb') as f:
    #     pickle.dump(collector, f)
    print("\n=== Saving results ===")
    protein_df = collector.get_protein_df()
    protein_df.to_pickle(os.path.join(output_dir, 'protein_df.pkl'))
    collector.save_results(output_dir)

    print(f"Analysis completed in {time.time() - start_time:.2f} seconds")


if __name__ == "__main__":
    config = load_config('config.yaml')
    input_dir = config['input_dir']
    out_base_path = config['output_dir']
    main()