# Path Configuration
from tools.preprocess import *

# Processing context
trait = "Telomere_Length"

# Input paths
tcga_root_dir = "../DATA/TCGA"

# Output paths
out_data_file = "./output/preprocess/3/Telomere_Length/TCGA.csv"
out_gene_data_file = "./output/preprocess/3/Telomere_Length/gene_data/TCGA.csv"
out_clinical_data_file = "./output/preprocess/3/Telomere_Length/clinical_data/TCGA.csv"
json_path = "./output/preprocess/3/Telomere_Length/cohort_info.json"

# Get list of available cohorts
available_cohorts = [d for d in os.listdir(tcga_root_dir) 
                    if os.path.isdir(os.path.join(tcga_root_dir, d)) and not d.startswith('.')]

# Initialize flags to track telomere data availability
found_telomere_data = False
telomere_clinical_data = None
telomere_genetic_data = None

# Check each cohort for telomere length data
for cohort in available_cohorts:
    if cohort.startswith('.'): # Skip hidden directories
        continue
        
    cohort_dir = os.path.join(tcga_root_dir, cohort)
    try:
        # Get file paths
        clinical_path, genetic_path = tcga_get_relevant_filepaths(cohort_dir)
        
        # Load data
        clinical_df = pd.read_csv(clinical_path, sep='\t', index_col=0)
        genetic_df = pd.read_csv(genetic_path, sep='\t', index_col=0)
        
        # Check for telomere-related measurements
        clinical_telomere = any('telomere' in col.lower() for col in clinical_df.columns)
        genetic_telomere = any('telomere' in gene.lower() for gene in genetic_df.index)
        
        if clinical_telomere or genetic_telomere:
            found_telomere_data = True
            telomere_clinical_data = clinical_df
            telomere_genetic_data = genetic_df
            print(f"Found telomere data in cohort: {cohort}")
            print("\nClinical data columns:")
            print(clinical_df.columns.tolist())
            break
            
    except Exception as e:
        print(f"Error processing cohort {cohort}: {str(e)}")
        continue

# Record findings
validate_and_save_cohort_info(
    is_final=False,
    cohort='TCGA',
    info_path=json_path,
    is_gene_available=found_telomere_data,
    is_trait_available=found_telomere_data
)

if not found_telomere_data:
    print("\nNo telomere length measurements found in any TCGA cohort.")