def write_gradient_information(dwi_header,
b0_header,
bval_path=None,
bvec_path=None,
flip=None,
swap=None):
"""
Write gradient information in present in the header.
Parameters
----------
header: The header with gradient info.
bval_path: Path to the bval file to be saved.
bvec_path: Path to the bvec path to be saved.
Return
------
None
"""
keys = ['bvalue', 'diff_x', 'diff_y', 'diff_z']
if all(k in dwi_header for k in keys) and \
all(k in b0_header for k in keys):
if bval_path:
bvals = b0_header['bvalue'] + dwi_header['bvalue']
with open(bval_path, 'w') as bval_file:
bval_file.write(' '.join(str(i) for i in bvals))
if bvec_path:
bvecs = np.zeros(
(3, len(b0_header['diff_x'] + dwi_header['diff_x'])))
bvecs[0, :] = b0_header['diff_x'] + dwi_header['diff_x']
bvecs[1, :] = b0_header['diff_y'] + dwi_header['diff_y']
bvecs[2, :] = b0_header['diff_z'] + dwi_header['diff_z']
if flip:
axes = [str_to_index(axis) for axis in list(flip)]
for axis in axes:
bvecs[axis, :] *= -1
if swap:
axes = [str_to_index(axis) for axis in list(swap)]
new_bvecs = np.zeros(bvecs.shape)
new_bvecs[axes[0], :] = bvecs[axes[1], :]
new_bvecs[axes[1], :] = bvecs[axes[0], :]
bvecs = new_bvecs
np.savetxt(bvec_path, bvecs, "%.8f")
else:
raise Exception('Could not save gradient. Some keys are missing.')
def main():
parser = build_args_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.image])
assert_outputs_exists(parser, args, [args.reordered_image_path])
indices = [str_to_index(axis) for axis in list(args.axes)]
if len(indices) != 3 or {0, 1, 2} != set(indices):
parser.error('The axes parameter must contain x, y and z in whatever '
'order.')
img = nib.load(args.image)
data = img.get_data()
swaps = [axis for index, axis in enumerate(indices) if index != axis]
for i in range(len(swaps) - 1):
data = np.swapaxes(data, swaps[i], swaps[i + 1])
new_zooms = np.array(img.get_header().get_zooms())[list(indices)]
if len(data.shape) == 4:
new_zooms = np.append(new_zooms, 1.0)
img.get_header().set_zooms(new_zooms)
nib.Nifti1Image(data, img.get_affine(), img.get_header()). \
to_filename(args.reordered_image_path)
def main():
parser = build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.encoding_file])
assert_outputs_exist(parser, args, [args.flipped_encoding])
indices = [str_to_index(axis) for axis in list(args.axes)]
if args.fsl_bvecs:
flip_fsl_bvecs(args.encoding_file, args.flipped_encoding, indices)
else:
flip_mrtrix_encoding_scheme(args.encoding_file, args.flipped_encoding,
indices)
def main():
parser = _build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, args.gradient_sampling_file)
assert_outputs_exist(parser, args, args.flipped_sampling_file)
indices = [str_to_index(axis) for axis in list(args.axes)]
_, ext = os.path.splitext(args.gradient_sampling_file)
if args.fsl_bvecs:
if ext == '.bvec':
flip_fsl_gradient_sampling(args.gradient_sampling_file,
args.flipped_sampling_file, indices)
else:
parser.error('Extension for FSL format should be .bvec.')
elif ext == '.b':
flip_mrtrix_gradient_sampling(args.gradient_sampling_file,
args.flipped_sampling_file, indices)
else:
parser.error('Extension for MRtrix format should .b.')