""" Read hippocampal subfield volumes computed by Freesurfer and/or ASHS and export collected data as CSV. """ import argparse import os import re import sys import typing import pandas from freesurfer_volume_reader import __version__, ashs, freesurfer, parse_version_string, \ remove_group_names_from_regex def concat_dataframes(dataframes: typing.Iterable[pandas.DataFrame] ) -> pandas.DataFrame: # pragma: no cover # pylint: disable=unexpected-keyword-arg if parse_version_string(pandas.__version__) < (0, 23): return pandas.concat(dataframes, ignore_index=True) return pandas.concat(dataframes, ignore_index=True, sort=False) VOLUME_FILE_FINDERS = { 'ashs': ashs.HippocampalSubfieldsVolumeFile, # https://github.com/freesurfer/freesurfer/tree/release_6_0_0/HippoSF 'freesurfer-hipposf': freesurfer.HippocampalSubfieldsVolumeFile, } def main(): argparser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) argparser.add_argument('--source-types', nargs='+', default=['freesurfer-hipposf'], choices=VOLUME_FILE_FINDERS.keys(), help='default: [freesurfer-hipposf]') for source_type, file_class in VOLUME_FILE_FINDERS.items(): argparser.add_argument('--{}-filename-regex'.format(source_type), dest='filename_regex.{}'.format(source_type), metavar='REGULAR_EXPRESSION', type=re.compile, default=remove_group_names_from_regex(file_class.FILENAME_PATTERN), help='default: %(default)s') argparser.add_argument('--output-format', choices=['csv'], default='csv', help='default: %(default)s') subjects_dir_path = os.environ.get('SUBJECTS_DIR', None) argparser.add_argument('root_dir_paths', metavar='ROOT_DIR', nargs='*' if subjects_dir_path else '+', default=[subjects_dir_path], help='default: $SUBJECTS_DIR ({})'.format(subjects_dir_path)) argparser.add_argument('--version', action='version', version=__version__) args = argparser.parse_args() filename_regexs = {k[len('filename_regex.'):]: v for k, v in vars(args).items() if k.startswith('filename_regex.')} volume_frames = [] for source_type in args.source_types: find_volume_files = lambda dir_path: VOLUME_FILE_FINDERS[source_type].find( root_dir_path=dir_path, filename_regex=filename_regexs[source_type]) for root_dir_path in args.root_dir_paths: for volume_file in find_volume_files(root_dir_path): volume_frame = volume_file.read_volumes_dataframe() volume_frame['source_type'] = source_type volume_frame['source_path'] = volume_file.absolute_path volume_frames.append(volume_frame) if not volume_frames: print('Did not find any volume files matching the specified criteria.', file=sys.stderr) return os.EX_NOINPUT united_volume_frame = concat_dataframes(volume_frames) print(united_volume_frame.to_csv(index=False)) return os.EX_OK if __name__ == '__main__': sys.exit(main())