physio_convert.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import os

import numpy as np
import pydicom as dicom

PHYSIO_DATA_TAG = '7fe11010'


def main(path, outdir=None):
    '''Main function.'''
    if outdir is None:
        outdir, _ = os.path.split(path)
    d = dicom.read_file(path)
    data = d[int(PHYSIO_DATA_TAG, 16)]
    raw = data.value
    length_bytes = len(raw)
    rows = d.AcquisitionNumber
    columns = length_bytes / rows
    num_files = columns / 1024
    length_file = int(len(raw) / num_files)
    arrs = [raw[i:i + length_file] for i in range(0, len(raw), length_file)]

    for arr in arrs:
        data_length = int(np.array(arr[:4]).view(np.uint32))
        fn_length = int(np.array(arr[4:8]).view(np.uint32))
        fn = arr[8:(8+fn_length)].decode('ascii')
        out_path = os.path.join(outdir, fn)
        print(fn)
        data = arr[1024:(1024 + data_length)]
        with open(out_path, 'wb') as f:
            f.write(data)


def parse_args():
    '''Parse arguments.'''
    parser = argparse.ArgumentParser(add_help=False)
    reqarg = parser.add_argument_group(title='required arguments')
    optarg = parser.add_argument_group(title='optional arguments')
    reqarg.add_argument('--physio', help='path of physio DICOM file',
                        required=True)
    optarg.add_argument('-h', '--help', action='help',
                        default=argparse.SUPPRESS,
                        help='Show this help message and exit')
    optarg.add_argument('--outdir', help='directory for output',
                        required=False)
    return parser.parse_args()


if __name__ == '__main__':
    args = parse_args()
    main(args.physio, args.outdir)

Ooops, I didn't know you started this but I wanted a python version too and ported the matlab code. I figured you might find this interesting:
https://github.com/CMRR-C2P/MB/blob/master/readCMRRPhysio.py

I integrated it in and may develop it further in the context of my bidscoin tool:
https://github.com/Donders-Institute/bidscoin/tree/master/bidscoin

Very cool, glad that someone else did the hard part!

PS I wrote this up at my blog, too: https://david-e-warren.me/blog/physiological-data-from-mri/