# Path Configuration
from tools.preprocess import *

# Processing context
trait = "Sickle_Cell_Anemia"

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

# Output paths
out_data_file = "./output/preprocess/1/Sickle_Cell_Anemia/TCGA.csv"
out_gene_data_file = "./output/preprocess/1/Sickle_Cell_Anemia/gene_data/TCGA.csv"
out_clinical_data_file = "./output/preprocess/1/Sickle_Cell_Anemia/clinical_data/TCGA.csv"
json_path = "./output/preprocess/1/Sickle_Cell_Anemia/cohort_info.json"

import os

# List of subdirectories from the TCGA root directory
subdirectories = [
    'TCGA-LGG', 'CrawlData.ipynb', '.DS_Store',
    'TCGA_lower_grade_glioma_and_glioblastoma_(GBMLGG)',
    'TCGA_Uterine_Carcinosarcoma_(UCS)', 'TCGA_Thyroid_Cancer_(THCA)',
    'TCGA_Thymoma_(THYM)', 'TCGA_Testicular_Cancer_(TGCT)',
    'TCGA_Stomach_Cancer_(STAD)', 'TCGA_Sarcoma_(SARC)',
    'TCGA_Rectal_Cancer_(READ)', 'TCGA_Prostate_Cancer_(PRAD)',
    'TCGA_Pheochromocytoma_Paraganglioma_(PCPG)', 'TCGA_Pancreatic_Cancer_(PAAD)',
    'TCGA_Ovarian_Cancer_(OV)', 'TCGA_Ocular_melanomas_(UVM)',
    'TCGA_Mesothelioma_(MESO)', 'TCGA_Melanoma_(SKCM)',
    'TCGA_Lung_Squamous_Cell_Carcinoma_(LUSC)', 'TCGA_Lung_Cancer_(LUNG)',
    'TCGA_Lung_Adenocarcinoma_(LUAD)', 'TCGA_Lower_Grade_Glioma_(LGG)',
    'TCGA_Liver_Cancer_(LIHC)', 'TCGA_Large_Bcell_Lymphoma_(DLBC)',
    'TCGA_Kidney_Papillary_Cell_Carcinoma_(KIRP)', 'TCGA_Kidney_Clear_Cell_Carcinoma_(KIRC)',
    'TCGA_Kidney_Chromophobe_(KICH)', 'TCGA_Head_and_Neck_Cancer_(HNSC)',
    'TCGA_Glioblastoma_(GBM)', 'TCGA_Esophageal_Cancer_(ESCA)',
    'TCGA_Endometrioid_Cancer_(UCEC)', 'TCGA_Colon_and_Rectal_Cancer_(COADREAD)',
    'TCGA_Colon_Cancer_(COAD)', 'TCGA_Cervical_Cancer_(CESC)',
    'TCGA_Breast_Cancer_(BRCA)', 'TCGA_Bladder_Cancer_(BLCA)',
    'TCGA_Bile_Duct_Cancer_(CHOL)', 'TCGA_Adrenocortical_Cancer_(ACC)',
    'TCGA_Acute_Myeloid_Leukemia_(LAML)'
]

# We look for subdirectories containing "sickle" or "anemia" in their name (case-insensitive)
relevant_folder = None
for folder in subdirectories:
    folder_lower = folder.lower()
    if "sickle" in folder_lower or "anemia" in folder_lower:
        relevant_folder = folder
        break

if not relevant_folder:
    # No suitable directory found, we skip this trait
    _ = validate_and_save_cohort_info(
        is_final=False,
        cohort="TCGA",
        info_path=json_path,
        is_gene_available=False,
        is_trait_available=False
    )
    print("No suitable directory found for trait Sickle_Cell_Anemia. Skipping this trait.")
else:
    # If there was a match, proceed to load files
    clinical_file, genetic_file = tcga_get_relevant_filepaths(os.path.join(tcga_root_dir, relevant_folder))

    clinical_data = pd.read_csv(clinical_file, index_col=0, sep='\t')
    genetic_data = pd.read_csv(genetic_file, index_col=0, sep='\t')

    print("Clinical data columns:", clinical_data.columns.tolist())