def fsl2mrtrix(fsl_bval_filename, fsl_bvec_filename, mrtrix_filename):
"""
Convert a fsl dir_grad.bvec/.bval files to mrtrix encoding.b file.
Parameters
----------
fsl_bval_filename: str
path to input fsl bval file.
fsl_bvec_filename: str
path to input fsl bvec file.
mrtrix_filename : str
path to output mrtrix encoding.b file.
Returns
-------
"""
shells = np.loadtxt(fsl_bval_filename)
points = np.loadtxt(fsl_bvec_filename)
bvals = np.unique(shells).tolist()
if not points.shape[0] == 3:
points = points.transpose()
logging.warning('WARNING: Your bvecs seem transposed. ' +
'Transposing them.')
shell_idx = [int(np.where(bval == bvals)[0]) for bval in shells]
save_gradient_sampling_mrtrix(points, shell_idx, bvals, mrtrix_filename)
def main():
parser = _build_arg_parser()
args = parser.parse_args()
fsl = args.fsl
mrtrix = args.mrtrix
if not (fsl or mrtrix):
parser.error('Select at least one save format.')
return
out_basename, _ = os.path.splitext(args.out_basename)
if fsl:
out_filename = [out_basename + '.bval', out_basename + '.bvec']
else:
out_filename = out_basename + '.b'
assert_outputs_exist(parser, args, out_filename)
logging.basicConfig(level=logging.INFO)
if args.verbose:
logging.basicConfig(level=logging.DEBUG)
Ks = args.nb_samples
eddy = args.eddy
duty = args.duty
# Total number of samples
K = np.sum(Ks)
# Number of non-b0 shells
S = len(Ks)
b0_every = args.b0_every
b0_end = args.b0_end
b0_value = args.b0_value
# Only a b0 at the beginning
if (b0_every > K) or (b0_every < 0):
b0_every = K + 1
# Compute bval list
if args.bvals is not None:
bvals = args.bvals
unique_bvals = np.unique(bvals)
if len(unique_bvals) != S:
parser.error('You have provided {} shells '.format(S) +
'but {} unique bvals.'.format(len(unique_bvals)))
elif args.b_lin_max is not None:
bvals = compute_bvalue_lin_b(bmin=0.0,
bmax=args.b_lin_max,
nb_of_b_inside=S - 1,
exclude_bmin=True)
elif args.q_lin_max is not None:
bvals = compute_bvalue_lin_q(bmin=0.0,
bmax=args.q_lin_max,
nb_of_b_inside=S - 1,
exclude_bmin=True)
# Add b0 b-value
if b0_every != 0:
bvals = add_bvalue_b0(bvals, b0_value=b0_value)
# Gradient sampling generation
points, shell_idx = generate_gradient_sampling(
Ks, verbose=int(3 - logging.getLogger().getEffectiveLevel() // 10))
# eddy current optimization
if eddy:
points, shell_idx = swap_sampling_eddy(points, shell_idx)
# Adding interleaved b0s
if b0_every != 0:
points, shell_idx = add_b0s(points,
shell_idx,
b0_every=b0_every,
finish_b0=b0_end)
# duty cycle optimization
if duty:
points, shell_idx = compute_min_duty_cycle_bruteforce(
points, shell_idx, bvals)
if fsl:
save_gradient_sampling_fsl(points, shell_idx, bvals, out_filename[0],
out_filename[1])
if mrtrix:
if not points.shape[0] == 3:
points = points.transpose()
save_gradient_sampling_mrtrix(points,
shell_idx,
bvals,
filename=out_filename)