Compute mean b-value from voxelwise btable (output of compute_spatial_btable.py).

compute_mean_b.py

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

import numpy as np
import nibabel as nib
import argparse


DESCRIPTION = """
Compute mean b-value from voxelwise btable (output of compute_spatial_btable.py).
"""

def buildArgsParser():
    p = argparse.ArgumentParser(description=DESCRIPTION)

    p.add_argument('btable', action='store', type=str,
                            help='Path of voxelwise btable file')

    p.add_argument('outfile', action='store', type=str,
                            help='Path of the output mean b-value file')


    p.add_argument('--mask', dest='mask', action='store', type=str,
                            help='Path of the mask file. If none given, computes on the full volume.')

    return p


def main():

    # parse inpout
    parser = buildArgsParser()
    args = parser.parse_args()

    btablefile = args.btable
    outfile = args.outfile
    maskfile = args.mask


    btable_img = nib.load(btablefile)
    btable = btable_img.get_data()

    if maskfile is None:
        mask = np.ones(btable.shape[:3])
        print('No mask used, beware of inaccurate volume boundary.')
    else:
        mask = nib.load(maskfile).get_data()

    # such GRANDIOS 
    mean_b = (btable[...,3]*mask[...,None]).mean(axis=-1)

    # save
    output_img = nib.Nifti1Image(mean_b, btable_img.affine, btable_img.header)
    nib.save(output_img, outfile)


if __name__ == '__main__':
    main()