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- import pandas as pd
- import os
- # Get the directory where the code file is located
- code_dir = os.path.dirname(os.path.abspath(__file__))
- # Get the parent directory of the code directory
- parent_dir = os.path.dirname(code_dir)
- qc_csv = os.path.join(parent_dir, "input", "AIDAqc_ouptut_for_data", "Votings.csv")
- df_qc = pd.read_csv(qc_csv)
- # Define a function to extract the timepoint information
- def extract_timepoint(path):
- parts = path.split(os.sep)
- for part in parts:
- if 'ses' in part:
- return part
- # Define a function to extract the timepoint number
- def extract_timepoint_number(tp):
- if 'Baseline' in tp:
- return 0
- else:
- return int(tp.split('ses-')[-1].replace("P",""))
-
- # Define the session mapping dictionary
- session_mapping = {
- 0: 0,
- 1: 3, 2: 3, 3: 3,
- 4: 3, 5: 3, 6: 7, 7: 7,
- 8: 7, 9: 7, 10: 7, 11: 14, 12: 14,
- 13: 14, 14: 14, 15: 14, 16: 14, 17: 14, 18: 14, 19: 21,
- 20: 21, 21: 21, 22: 21, 23: 21, 24: 21, 25: 21, 26: 28,
- 27: 28, 28: 28, 29: 28, 30: 28 , 42:42, 43:42, 56:56, 57:56
- }
- # Define a function to extract the subject ID
- def extract_subject_id(path):
- parts = path.split(os.sep)
- for part in parts:
- if 'sub-' in part and '.nii.' not in part:
- return part
- # Remove rows containing "brkraw" or "DN" in the "Pathes" column
- df_qc = df_qc[~df_qc['Pathes'].str.contains('brkraw|DN')]
- # Create the "tp" column
- df_qc['tp'] = df_qc['Pathes'].apply(lambda x: extract_timepoint(x))
- # Define a function to map tp_int using session_mapping
- def map_merged_timepoint(tp_int):
- return session_mapping.get(tp_int, tp_int)
- # Create the "tp_int" column
- df_qc['tp_int'] = df_qc['tp'].apply(lambda x: extract_timepoint_number(x))
- # Create the "merged_timepoint" column
- df_qc['merged_timepoint'] = df_qc['tp_int'].apply(map_merged_timepoint)
- # Add the "subjectID" column
- df_qc['subjectID'] = df_qc['Pathes'].apply(lambda x: extract_subject_id(x))
- # Save the DataFrame as a CSV file
- output_csv = os.path.join(parent_dir, "input", "AIDAqc_ouptut_for_data", "voting_remapped.csv")
- df_qc.to_csv(output_csv, index=False)
- print("DataFrame saved as 'voting_remapped.csv'")
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