watson-backup-to-data

import logging
import os
import argparse
from fitting.watsonfit import WatsonResultModel

def main():
    parser = argparse.ArgumentParser(
        description='Helper script to compute outputs from backup data', formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    parser.add_argument('--infile',
                        help='Backup file', default=argparse.SUPPRESS)
    parser.add_argument('-o', '--outfile',
                        help='5D output file with the approximation result (5,r,x,y,z), the first axis contains in place 0 '
                        'the kappa value, in place 1 the volume fraction and in the remaining places the unit direction.', default=argparse.SUPPRESS)
    parser.add_argument('-op', '--outfilepeaks',
                        help='5D output file with the approximation result without kappa (4,r,x,y,z), the first axis contains in place 0 '
                        'the volume fraction and in the remaining places the unit direction.', default=argparse.SUPPRESS)
    parser.add_argument('-of', '--outfilefodf',
                        help='If filename is set, Watson parameters are used to generate fodf data', default=argparse.SUPPRESS)
    parser.add_argument('-ofn', '--outfilefodfpeaknumber',
                        help='Only export one distribution per voxel, 0 for principal direction, 1 and 2 for 2nd and 3rd.', default=None)
    parser.add_argument('-vvi', '--vvicones',
                        help='If filename is set, r files are generated beginning with the given filename that contain data to visualize as cones with vvi.', default=argparse.SUPPRESS)
    parser.add_argument('-v', '--verbose', default=True)
    args = parser.parse_args()
    print(args)


    logging.basicConfig(filename=os.path.join("./", 'watson_backup_to_data.log'),
                        format='%(asctime)s %(levelname)-8s %(message)s',
                        datefmt='%y-%m-%d %H:%M',
                        level=logging.INFO,
                        filemode='w')

    if args.verbose:
        console = logging.StreamHandler()
        console.setLevel(logging.DEBUG)
        # set a format which is simpler for console use
        formatter = logging.Formatter(
        	'%(asctime)s: %(levelname)-8s %(message)s', datefmt='%y-%m-%d %H:%M')
        # tell the handler to use this format
        console.setFormatter(formatter)
        # add the handler to the root logger
        logging.getLogger('').addHandler(console)

    result_model = WatsonResultModel.load_from_file(args.infile)

    if 'outfilebackup' in args:
        logging.info(f"Saving backup to {args.outfilebackup}")
        result_model.backup_to_file(args.outfilebackup)
    
    if 'outfile' in args:
        logging.info(f"Saving Watson output to {args.outfile}")
        result_model.export_for_watson_tracking(args.outfile)

    if 'outfilepeaks' in args:
        logging.info(f"Saving Peak output to {args.outfilepeaks}")
        result_model.export_for_peak_tracking(args.outfilepeaks)

    if 'vvicones' in args:
        logging.info(f"Saving vvi cones")
        result_model.export_for_vvi_with_cones(args.vvicones)

    if 'outfilefodf' in args:
        logging.info(f"Saving fodf output to {args.outfilefodf}")
        if args.outfilefodfpeaknumber is not None:
            result_model.export_as_fodf_signal(args.outfilefodf, peak_number=int(args.outfilefodfpeaknumber))
        else:
            result_model.export_as_fodf_signal(args.outfilefodf)

if __name__=="__main__":
    main()