import glob
import csv 

df_list = []
ROOT_DIR = '../../../datasets/anonymized_mri/only_nii_directory/*/*'
x = glob.glob(ROOT_DIR)

for patient_dir in sorted(x): 
    T2 = []
    adc = []
    highb = []
    patient_id = []
    age_year = []

    patient_id = patient_dir.split('/')[-2]
    age_year = patient_dir.split('/')[-1]
    for path in sorted(glob.glob(f'../../../datasets/anonymized_mri/only_nii_directory/{patient_dir.split("/")[-2]}/{patient_dir.split("/")[-1]}/*/*')):
        if ('T2' in path or 't2' in path) and ('tra' in path or 'TRA' in path) and not ('seg' in path):
            T2 = path        
    for path in sorted(glob.glob(f'../../../datasets/anonymized_mri/only_nii_directory/{patient_dir.split("/")[-2]}/{patient_dir.split("/")[-1]}/*')):
        if 'manual_adc' in path:
            manual_adc = path
        else:
            if 'ADC' in path and 'nii.gz' in path: 
                adc = path
                print(path)

        if 'manual_b-1400' in path:
            highb1400 = path
        else:
            if 'b-2000' in path and 'nii.gz' in path: 
                highb = path
                print(path)

    if manual_adc:
        adc = manual_adc
    if highb1400:
        highb = highb1400
        
    df_list.append({'patient_id':patient_id,'age_year':age_year,'t2':T2,'adc':adc,'high_b':highb})
    if not T2 or not adc or not highb:
        input(f'{patient_id} {age_year} {T2} {adc} {highb}')

with open('csv_file.csv', 'w') as csvfile:
    writer = csv.DictWriter(csvfile, fieldnames=['patient_id','age_year','t2','adc','high_b'],delimiter=';')
    writer.writeheader()
    for data in df_list:
        writer.writerow(data)