def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__, epilog=EPILOG,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_file',
help='Path of the volume (nii or nii.gz).')
p.add_argument('out_file',
help='Output filename of the dilated labels.')
p.add_argument('--distance', type=float, default=2.0,
help='Maximal distance to dilated (in mm) [%(default)s].')
p.add_argument('--label_to_dilate', type=int, nargs='+', default=None,
help='Label list to dilate, by default it dilate all that\n'
' are not in label_to_fill nor label_not_to_dilate.')
p.add_argument('--label_to_fill', type=int, nargs='+', default=[0],
help='Background id / labels to be filled [%(default)s],\n'
' the first one is given as output background value.')
p.add_argument('--label_not_to_dilate', type=int, nargs='+', default=[],
help='Label list not to dilate.')
p.add_argument('--mask',
help='Only dilate values inside the mask.')
add_processes_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
epilog=EPILOG)
p.add_argument('in_bingham', help='Input Bingham image.')
p.add_argument('--out_fd', default='',
help='Path to output fiber density. [fd.nii.gz]')
p.add_argument('--out_fs', default='',
help='Path to output fiber spread. [fs.nii.gz]')
p.add_argument('--out_ff', default='',
help='Path to fiber fraction file. [ff.nii.gz]')
p.add_argument('--not_all', action='store_true',
help='Do not compute all metrics.')
p.add_argument('--mask',
help='Optional mask image. Only voxels inside '
'the mask are computed.')
p.add_argument('--nbr_integration_steps', type=int, default=50,
help='Number of integration steps along the theta axis for'
' fiber density estimation. [%(default)s]')
add_overwrite_arg(p)
add_verbose_arg(p)
add_processes_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_image', help='Path of the image file to denoise.')
p.add_argument('out_image', help='Path to save the denoised image file.')
p.add_argument('number_coils',
type=int,
help='Number of receiver coils of the scanner.\nUse '
'number_coils=1 in the case of a SENSE (GE, Philips) '
'reconstruction and \nnumber_coils >= 1 for GRAPPA '
'reconstruction (Siemens). number_coils=4 works well '
'for the 1.5T\n in Sherbrooke. Use number_coils=0 if '
'the noise is considered Gaussian distributed.')
p.add_argument('--mask',
metavar='',
help='Path to a binary mask. Only the data inside the mask'
' will be used for computations')
p.add_argument('--sigma',
metavar='float',
type=float,
help='The standard deviation of the noise to use instead '
'of computing it automatically.')
p.add_argument('--log',
dest="logfile",
help='If supplied, name of the text file to store '
'the logs.')
add_processes_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
)
p.add_argument('in_hdf5',
help='Input filename for the hdf5 container (.h5).\n'
'Obtained from scil_decompose_connectivity.py.')
p.add_argument('in_labels',
help='Labels file name (nifti).\n'
'This generates a NxN connectivity matrix.')
p.add_argument('--volume',
metavar='OUT_FILE',
help='Output file for the volume weighted matrix (.npy).')
p.add_argument('--streamline_count',
metavar='OUT_FILE',
help='Output file for the streamline count weighted matrix '
'(.npy).')
p.add_argument('--length',
metavar='OUT_FILE',
help='Output file for the length weighted matrix (.npy).')
p.add_argument('--similarity',
nargs=2,
metavar=('IN_FOLDER', 'OUT_FILE'),
help='Input folder containing the averaged bundle density\n'
'maps (.nii.gz) and output file for the similarity '
'weighted matrix (.npy).')
p.add_argument('--maps',
nargs=2,
action='append',
metavar=('IN_FOLDER', 'OUT_FILE'),
help='Input folder containing pre-computed maps (.nii.gz)\n'
'and output file for the weighted matrix (.npy).')
p.add_argument('--metrics',
nargs=2,
action='append',
metavar=('IN_FILE', 'OUT_FILE'),
help='Input (.nii.gz). and output file (.npy) for a metric '
'weighted matrix.')
p.add_argument(
'--density_weighting',
action="store_true",
help='Use density-weighting for the metric weighted matrix.')
p.add_argument('--no_self_connection',
action="store_true",
help='Eliminate the diagonal from the matrices.')
p.add_argument('--include_dps',
metavar='OUT_DIR',
help='Save matrices from data_per_streamline in the output '
'directory.\nWill always overwrite files.')
p.add_argument('--force_labels_list',
help='Path to a labels list (.txt) in case of missing '
'labels in the atlas.')
add_processes_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+',
help='Path of the input bundles.')
p.add_argument('out_json',
help='Path of the output json file.')
p.add_argument('--streamline_dice', action='store_true',
help='Streamlines-wise Dice coefficient will be computed \n'
'Tractograms must be identical [%(default)s].')
p.add_argument('--disable_streamline_distance', action='store_true',
help='Will not compute the streamlines distance \n'
'[%(default)s].')
p.add_argument('--single_compare',
help='Compare inputs to this single file.')
p.add_argument('--keep_tmp', action='store_true',
help='Will not delete the tmp folder at the end.')
add_processes_arg(p)
add_reference_arg(p)
add_json_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('in_bundle', help='Path of the input bundle.')
p.add_argument('min_distance',
type=float,
help='Distance threshold for 2 streamlines to be '
'considered similar (mm).')
p.add_argument('out_bundle', help='Path of the output tractography file')
p.add_argument('--clustering_thr',
type=float,
default=6,
help='Clustering threshold for QB/QBx (mm), during '
'the first approximation [%(default)s].')
p.add_argument('--min_cluster_size',
type=int,
default=5,
help='Minimum cluster size for the first iteration '
'[%(default)s].')
p.add_argument('--convergence',
type=int,
default=100,
help='Streamlines count difference threshold to stop '
're-running the algorithm [%(default)s].')
add_reference_arg(p)
add_processes_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_dwi',
help='Path of the input diffusion volume.')
p.add_argument('in_bval',
help='Path of the bvals file, in FSL format.')
p.add_argument('in_bvec',
help='Path of the bvecs file, in FSL format.')
p.add_argument('frf_file',
help='Path of the FRF file')
p.add_argument('out_fODF',
help='Output path for the fiber ODF coefficients.')
p.add_argument(
'--sh_order', metavar='int', default=8, type=int,
help='SH order used for the CSD. (Default: 8)')
p.add_argument(
'--mask', metavar='',
help='Path to a binary mask. Only the data inside the mask will be '
'used for computations and reconstruction.')
add_force_b0_arg(p)
add_sh_basis_args(p)
add_processes_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
epilog=EPILOG)
p.add_argument('in_sh',
help='Input SH image.')
p.add_argument('out_bingham',
help='Output Bingham functions image.')
p.add_argument('--max_lobes', type=int, default=5,
help='Maximum number of lobes per voxel'
' to extract. [%(default)s]')
p.add_argument('--at', type=float, default=0.0,
help='Absolute threshold for peaks'
' extraction. [%(default)s]')
p.add_argument('--rt', type=float, default=0.1,
help='Relative threshold for peaks'
' extraction. [%(default)s]')
p.add_argument('--min_sep_angle', type=float, default=25.,
help='Minimum separation angle between'
' two peaks. [%(default)s]')
p.add_argument('--max_fit_angle', type=float, default=15.,
help='Maximum distance in degrees around a peak direction'
' for fitting the Bingham function. [%(default)s]')
p.add_argument('--mask',
help='Optional mask file. Only SH inside'
' the mask are fitted.')
add_overwrite_arg(p)
add_verbose_arg(p)
add_processes_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+',
help='Path of the input bundles.')
p.add_argument('out_json',
help='Path of the output json file.')
p.add_argument('--streamline_dice', action='store_true',
help='Compute streamline-wise dice coefficient.\n'
'Tractograms must be identical [%(default)s].')
p.add_argument('--bundle_adjency_no_overlap', action='store_true',
help='If set, do not count zeros in the average BA.')
p.add_argument('--disable_streamline_distance', action='store_true',
help='Will not compute the streamlines distance \n'
'[%(default)s].')
p.add_argument('--single_compare',
help='Compare inputs to this single file.')
p.add_argument('--keep_tmp', action='store_true',
help='Will not delete the tmp folder at the end.')
p.add_argument('--ratio', action='store_true',
help='Compute overlap and overreach as a ratio over the\n'
'reference tractogram in a Tractometer-style way.\n'
'Can only be used if also using the `single_compare` '
'option.')
add_processes_arg(p)
add_reference_arg(p)
add_json_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
epilog=EPILOG,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_sh', help='Input SH image.')
p.add_argument('--mask', default='', help='Optional mask.')
# outputs
p.add_argument('--cos_asym_map',
default='',
help='Output asymmetry map using cos similarity.')
p.add_argument('--odd_power_map', default='', help='Output odd power map.')
p.add_argument('--peaks',
default='',
help='Output filename for the extracted peaks.')
p.add_argument('--peak_values',
default='',
help='Output filename for the extracted peaks values.')
p.add_argument('--peak_indices',
default='',
help='Output filename for the generated peaks indices on '
'the sphere.')
p.add_argument('--nupeaks',
default='',
help='Output filename for the nupeaks file.')
p.add_argument('--not_all',
action='store_true',
help='If set, only saves the files specified using the '
'file flags [%(default)s].')
p.add_argument('--at',
dest='a_threshold',
type=float,
default='0.0',
help='Absolute threshold on fODF amplitude. This '
'value should be set to\napproximately 1.5 to 2 times '
'the maximum fODF amplitude in isotropic voxels\n'
'(ie. ventricles).\n'
'Use compute_fodf_max_in_ventricles.py to find the '
'maximal value.\n'
'See [Dell\'Acqua et al HBM 2013] [%(default)s].')
p.add_argument('--rt',
dest='r_threshold',
type=float,
default='0.1',
help='Relative threshold on fODF amplitude in percentage '
'[%(default)s].')
p.add_argument('--sphere',
default='symmetric724',
choices=sorted(SPHERE_FILES.keys()),
help='Sphere to use for peak directions estimation '
'[%(default)s].')
add_processes_arg(p)
add_sh_basis_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
p.add_argument('in_dwi', help='Path of the input diffusion volume.')
p.add_argument('in_bval', help='Path of the bval file, in FSL format.')
p.add_argument('in_bvec', help='Path of the bvec file, in FSL format.')
p.add_argument('in_wm_frf', help='Text file of WM response function.')
p.add_argument('in_gm_frf', help='Text file of GM response function.')
p.add_argument('in_csf_frf', help='Text file of CSF response function.')
p.add_argument('--sh_order',
metavar='int',
default=8,
type=int,
help='SH order used for the CSD. (Default: 8)')
p.add_argument('--mask',
metavar='',
help='Path to a binary mask. Only the data inside the '
'mask will be used for computations and reconstruction.')
add_force_b0_arg(p)
add_sh_basis_args(p)
add_processes_arg(p)
add_overwrite_arg(p)
p.add_argument('--not_all',
action='store_true',
help='If set, only saves the files specified using the '
'file flags. (Default: False)')
g = p.add_argument_group(title='File flags')
g.add_argument('--wm_out_fODF',
metavar='file',
default='',
help='Output filename for the WM fODF coefficients.')
g.add_argument('--gm_out_fODF',
metavar='file',
default='',
help='Output filename for the GM fODF coefficients.')
g.add_argument('--csf_out_fODF',
metavar='file',
default='',
help='Output filename for the CSF fODF coefficients.')
g.add_argument('--vf',
metavar='file',
default='',
help='Output filename for the volume fractions map.')
g.add_argument('--vf_rgb',
metavar='file',
default='',
help='Output filename for the volume fractions map in rgb.')
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
epilog=EPILOG,
formatter_class=argparse.RawDescriptionHelpFormatter)
p.add_argument('in_dwi',
help='DWI file acquired with a NODDI compatible protocol '
'(single-shell data not suited).')
p.add_argument('in_bval', help='b-values filename, in FSL format (.bval).')
p.add_argument('in_bvec',
help='b-vectors filename, in FSL format (.bvec).')
p.add_argument('--mask', help='Brain mask filename.')
p.add_argument('--out_dir',
default="results",
help='Output directory for the NODDI results. '
'[%(default)s]')
p.add_argument('--b_thr',
type=int,
default=40,
help='Limit value to consider that a b-value is on an '
'existing shell. Above this limit, the b-value is '
'placed on a new shell. This includes b0s values.')
g1 = p.add_argument_group(title='Model options')
g1.add_argument('--para_diff',
type=float,
default=1.7e-3,
help='Axial diffusivity (AD) in the CC. [%(default)s]')
g1.add_argument('--iso_diff',
type=float,
default=3e-3,
help='Mean diffusivity (MD) in ventricles. [%(default)s]')
g1.add_argument('--lambda1',
type=float,
default=5e-1,
help='First regularization parameter. [%(default)s]')
g1.add_argument('--lambda2',
type=float,
default=1e-3,
help='Second regularization parameter. [%(default)s]')
g2 = p.add_argument_group(title='Kernels options')
kern = g2.add_mutually_exclusive_group()
kern.add_argument('--save_kernels',
metavar='DIRECTORY',
help='Output directory for the COMMIT kernels.')
kern.add_argument('--load_kernels',
metavar='DIRECTORY',
help='Input directory where the COMMIT kernels are '
'located.')
add_processes_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__,
epilog=EPILOG)
p.add_argument('in_tractogram',
help='Input tractogram filename (.trk or .tck).')
p.add_argument('in_config_file', help='Path of the config file (.json)')
p.add_argument('in_models_directories',
nargs='+',
help='Path for the directories containing model.')
p.add_argument('in_transfo',
help='Path for the transformation to model space '
'(.txt, .npy or .mat).')
p.add_argument('--out_dir',
default='voting_results',
help='Path for the output directory [%(default)s].')
p.add_argument('--log_level',
default='INFO',
choices=['DEBUG', 'INFO', 'WARNING', 'ERROR'],
help='Log level of the logging class.')
p.add_argument('--multi_parameters',
type=int,
default=1,
help='Pick parameters from the potential combinations\n'
'Will multiply the number of times Recobundles is ran.\n'
'See the documentation [%(default)s].')
p.add_argument('--minimal_vote_ratio',
type=float,
default=0.5,
help='Streamlines will only be considered for saving if\n'
'recognized often enough [%(default)s].')
p.add_argument(
'--tractogram_clustering_thr',
type=int,
default=[12],
nargs='+',
help='Input tractogram clustering thresholds %(default)smm.')
p.add_argument('--seeds',
type=int,
default=[0],
nargs='+',
help='Random number generator seed %(default)s\n'
'Will multiply the number of times Recobundles is ran.')
p.add_argument('--inverse',
action='store_true',
help='Use the inverse transformation.')
add_processes_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_dwi', help='Path of the input diffusion volume.')
p.add_argument('in_bval', help='Path of the bvals file, in FSL format.')
p.add_argument('in_bvec', help='Path of the bvecs file, in FSL format.')
add_overwrite_arg(p)
p.add_argument('--sh_order',
default=4,
type=int,
help='Spherical harmonics order. Must be a positive even '
'number [%(default)s].')
p.add_argument('--mask',
help='Path to a binary mask. Only data inside the mask will'
' be used for computations and reconstruction '
'[%(default)s].')
p.add_argument('--use_qball',
action='store_true',
help='If set, qball will be used as the odf reconstruction'
' model instead of CSA.')
p.add_argument('--not_all',
action='store_true',
help='If set, will only save the files specified using the '
'following flags.')
g = p.add_argument_group(title='File flags')
g.add_argument('--gfa',
default='',
help='Output filename for the generalized fractional '
'anisotropy [gfa.nii.gz].')
g.add_argument('--peaks',
default='',
help='Output filename for the extracted peaks '
'[peaks.nii.gz].')
g.add_argument('--peak_indices',
default='',
help='Output filename for the generated peaks '
'indices on the sphere [peaks_indices.nii.gz].')
g.add_argument('--sh',
default='',
help='Output filename for the spherical harmonics '
'coefficients [sh.nii.gz].')
g.add_argument('--nufo',
default='',
help='Output filename for the NUFO map [nufo.nii.gz].')
g.add_argument('--a_power',
default='',
help='Output filename for the anisotropic power map'
'[anisotropic_power.nii.gz].')
add_force_b0_arg(p)
add_sh_basis_args(p)
add_processes_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog=EPILOG)
p.add_argument('in_dwi',
help='DWI file.')
p.add_argument('in_bval',
help='b-values filename, in FSL format (.bval).')
p.add_argument('in_bvec',
help='b-vectors filename, in FSL format (.bvec).')
p.add_argument('--mask',
help='Brain mask filename.')
p.add_argument('--out_dir', default="results",
help='Output directory for the Free Water results. '
'[%(default)s]')
p.add_argument('--b_thr', type=int, default=40,
help='Limit value to consider that a b-value is on an '
'existing shell. Above this limit, the b-value is '
'placed on a new shell. This includes b0s values.')
g1 = p.add_argument_group(title='Model options')
g1.add_argument('--para_diff', type=float, default=1.5e-3,
help='Axial diffusivity (AD) in the CC. [%(default)s]')
g1.add_argument('--iso_diff', type=float, default=3e-3,
help='Mean diffusivity (MD) in ventricles. [%(default)s]')
g1.add_argument('--perp_diff_min', type=float, default=0.1e-3,
help='Radial diffusivity (RD) minimum. [%(default)s]')
g1.add_argument('--perp_diff_max', type=float, default=0.7e-3,
help='Radial diffusivity (RD) maximum. [%(default)s]')
g1.add_argument('--lambda1', type=float, default=0.0,
help='First regularization parameter. [%(default)s]')
g1.add_argument('--lambda2', type=float, default=1e-3,
help='Second regularization parameter. [%(default)s]')
g2 = p.add_argument_group(title='Kernels options')
kern = g2.add_mutually_exclusive_group()
kern.add_argument('--save_kernels', metavar='DIRECTORY',
help='Output directory for the COMMIT kernels.')
kern.add_argument('--load_kernels', metavar='DIRECTORY',
help='Input directory where the COMMIT kernels are '
'located.')
g2.add_argument('--compute_only', action='store_true',
help='Compute kernels only, --save_kernels must be used.')
p.add_argument('--mouse', action='store_true',
help='If set, use mouse fitting profile.')
add_processes_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
epilog=EPILOG)
p.add_argument('in_sh', help='Input SH image.')
p.add_argument('--out_bingham',
default='bingham.nii.gz',
help='Output Bingham functions image. [%(default)s]')
p.add_argument('--out_fd',
default='fd.nii.gz',
help='Path to output fiber density. [%(default)s]')
p.add_argument('--out_fs',
default='fs.nii.gz',
help='Path to output fiber spread. [%(default)s]')
p.add_argument('--out_ff',
default='ff.nii.gz',
help='Path to fiber fraction file. [%(default)s]')
p.add_argument('--max_lobes',
type=int,
default=5,
help='Maximum number of lobes per voxel'
' to extract. [%(default)s]')
p.add_argument('--at',
type=float,
default=0.0,
help='Absolute threshold for peaks'
' extraction. [%(default)s]')
p.add_argument('--rt',
type=float,
default=0.1,
help='Relative threshold for peaks'
' extraction. [%(default)s]')
p.add_argument('--min_sep_angle',
type=float,
default=25.,
help='Minimum separation angle between'
' two peaks. [%(default)s]')
p.add_argument('--max_fit_angle',
type=float,
default=15.,
help='Maximum distance in degrees around a peak direction'
' for fitting the Bingham function. [%(default)s]')
p.add_argument('--nbr_integration_steps',
type=int,
default=50,
help='Number of integration steps along the theta axis for'
' fiber density estimation. [%(default)s]')
add_overwrite_arg(p)
add_verbose_arg(p)
add_processes_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+', help='Path of the input bundles.')
p.add_argument('out_json', help='Path of the output file.')
add_reference_arg(p)
add_processes_arg(p)
add_json_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter,
)
p.add_argument('in_bundles_dir',
help='Folder containing all the bundle files (.trk).')
p.add_argument('labels_list',
help='Text file containing the list of labels from the '
'atlas.')
p.add_argument('--volume',
metavar='OUT_FILE',
help='Output file for the volume weighted matrix (.npy).')
p.add_argument('--streamline_count',
metavar='OUT_FILE',
help='Output file for the streamline count weighted matrix '
'(.npy).')
p.add_argument('--length',
metavar='OUT_FILE',
help='Output file for the length weighted matrix (.npy).')
p.add_argument('--similarity',
nargs=2,
metavar=('IN_FOLDER', 'OUT_FILE'),
help='Input folder containing the averaged bundle density\n'
'maps (.nii.gz) and output file for the similarity '
'weighted matrix (.npy).')
p.add_argument('--maps',
nargs=2,
action='append',
metavar=('IN_FOLDER', 'OUT_FILE'),
help='Input folder containing pre-computed maps (.nii.gz)\n'
'and output file for the weighted matrix (.npy).')
p.add_argument('--metrics',
nargs=2,
action='append',
metavar=('IN_FILE', 'OUT_FILE'),
help='Input (.nii.gz). and output file (.npy) for a metric '
'weighted matrix.')
p.add_argument(
'--density_weighting',
action="store_true",
help='Use density-weighting for the metric weighted matrix.')
p.add_argument('--no_self_connection',
action="store_true",
help='Eliminate the diagonal from the matrices.')
add_processes_arg(p)
add_reference_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('in_sh', help='Input SH filename. (nii or nii.gz)')
p.add_argument('out_sh', help='Output SH filename. (nii or nii.gz)')
add_sh_basis_args(p, mandatory=True)
add_processes_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_fODF',
help='Path of the fODF volume in spherical harmonics (SH).')
p.add_argument('--sphere', metavar='string', default='repulsion724',
choices=['repulsion100', 'repulsion724'],
help='Discrete sphere to use in the processing '
'[%(default)s].')
p.add_argument('--mask', metavar='',
help='Path to a binary mask. Only the data inside the mask\n'
'will beused for computations and reconstruction '
'[%(default)s].')
p.add_argument('--at', dest='a_threshold', type=float, default='0.0',
help='Absolute threshold on fODF amplitude. This '
'value should be set to\napproximately 1.5 to 2 times '
'the maximum fODF amplitude in isotropic voxels\n'
'(ie. ventricles).\nUse compute_fodf_max_in_ventricles.py '
'to find the maximal value.\n'
'See [Dell\'Acqua et al HBM 2013] [%(default)s].')
p.add_argument('--rt', dest='r_threshold', type=float, default='0.1',
help='Relative threshold on fODF amplitude in percentage '
'[%(default)s].')
add_sh_basis_args(p)
add_overwrite_arg(p)
add_processes_arg(p)
p.add_argument('--not_all', action='store_true',
help='If set, only saves the files specified using the '
'file flags [%(default)s].')
g = p.add_argument_group(title='File flags')
g.add_argument('--afd_max', metavar='file', default='',
help='Output filename for the AFD_max map.')
g.add_argument('--afd_total', metavar='file', default='',
help='Output filename for the AFD_total map (SH coeff = 0).')
g.add_argument('--afd_sum', metavar='file', default='',
help='Output filename for the sum of all peak contributions\n'
'(sum of fODF lobes on the sphere).')
g.add_argument('--nufo', metavar='file', default='',
help='Output filename for the NuFO map.')
g.add_argument('--rgb', metavar='file', default='',
help='Output filename for the RGB map.')
g.add_argument('--peaks', metavar='file', default='',
help='Output filename for the extracted peaks.')
g.add_argument('--peak_values', metavar='file', default='',
help='Output filename for the extracted peaks values.')
g.add_argument('--peak_indices', metavar='file', default='',
help='Output filename for the generated peaks indices on '
'the sphere.')
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_sh', help='Path of the SH volume.')
p.add_argument('out_sf',
help='Name of the output SF file to save (bvals/bvecs will '
'be automatically named when necessary).')
# Sphere vs bvecs choice for SF
directions = p.add_mutually_exclusive_group(required=True)
directions.add_argument('--sphere',
choices=sorted(SPHERE_FILES.keys()),
help='Sphere used for the SH to SF projection. ')
directions.add_argument(
'--in_bvec', help="Directions used for the SH to SF projection.")
p.add_argument('--dtype',
default="float32",
choices=["float32", "float64"],
help="Datatype to use for SF computation and output array."
"'[%(default)s]'")
# Optional args for a DWI-like volume
p.add_argument('--in_bval',
help='b-value file, in FSL format, '
'used to assign a b-value to the '
'output SF and generate a `.bval` file.')
p.add_argument('--in_b0',
help='b0 volume to concatenate to the '
'final SF volume.')
p.add_argument('--out_bval', help="Optional output bval file.")
p.add_argument('--out_bvec', help="Optional output bvec file.")
p.add_argument('--b0_scaling',
action="store_true",
help="Scale resulting SF by the b0 image.")
add_sh_basis_args(p)
p.add_argument('--full_basis',
action="store_true",
help="If true, use a full basis for the input SH "
"coefficients.")
add_processes_arg(p)
add_overwrite_arg(p)
add_force_b0_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_hdf5', nargs='+',
help='List of HDF5 filenames (.h5) from '
'scil_decompose_connectivity.py.')
p.add_argument('out_dir',
help='Path of the output directory.')
p.add_argument('--binary', action='store_true',
help='Binarize density maps before the population average.')
add_processes_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
epilog=EPILOG,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+', help='Path of the input bundles.')
p.add_argument('out_json', help='Path of the output file.')
p.add_argument('--group_statistics',
action='store_true',
help='Show average measures \n'
'[%(default)s].')
add_reference_arg(p)
add_processes_arg(p)
add_json_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__, epilog=EPILOG,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_hdf5',
help='HDF5 filename (.h5) containing decomposed '
'connections.')
p.add_argument('in_fodf',
help='Path of the fODF volume in spherical harmonics (SH).')
p.add_argument('out_hdf5',
help='Path of the output HDF5 filenames (.h5).')
p.add_argument('--length_weighting', action='store_true',
help='If set, will weigh the AFD values according to '
'segment lengths. [%(default)s]')
add_processes_arg(p)
add_sh_basis_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_sh',
help='Path to the input file.')
p.add_argument('out_sh',
help='File name for averaged signal.')
add_sh_basis_args(p)
p.add_argument('--out_sym', default=None,
help='Name of optional symmetric output. [%(default)s]')
p.add_argument('--sphere', default='repulsion724',
choices=sorted(SPHERE_FILES.keys()),
help='Sphere used for the SH to SF projection. '
'[%(default)s]')
p.add_argument('--sigma_angular', default=1.0, type=float,
help='Standard deviation for angular distance.'
' [%(default)s]')
p.add_argument('--sigma_spatial', default=1.0, type=float,
help='Standard deviation for spatial distance.'
' [%(default)s]')
p.add_argument('--sigma_range', default=1.0, type=float,
help='Standard deviation for range filter.'
' [%(default)s]')
p.add_argument('--use_gpu', action='store_true',
help='Use GPU for computation.')
add_verbose_arg(p)
add_overwrite_arg(p)
add_processes_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+', help='Path of the input bundles.')
p.add_argument('out_json', help='Path of the output json.')
p.add_argument(
'--streamlines_measures',
nargs=2,
metavar=('GOLD_STANDARD_STREAMLINES', 'TRACTOGRAM'),
help='The gold standard bundle and the original tractogram.')
p.add_argument(
'--voxels_measures',
nargs=2,
metavar=('GOLD_STANDARD_MASK', 'TRACKING MASK'),
help='The gold standard mask and the original tracking mask.')
add_processes_arg(p)
add_reference_arg(p)
add_verbose_arg(p)
add_json_args(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
add_mandatory_options_tracking(p)
track_g = add_tracking_options(p)
track_g.add_argument('--algo',
default='prob',
choices=['det', 'prob'],
help='Algorithm to use [%(default)s]')
add_sphere_arg(track_g, symmetric_only=False)
track_g.add_argument('--sfthres_init',
metavar='sf_th',
type=float,
default=0.5,
dest='sf_threshold_init',
help="Spherical function relative threshold value "
"for the \ninitial direction. [%(default)s]")
track_g.add_argument('--rk_order',
metavar="K",
type=int,
default=2,
choices=[1, 2, 4],
help="The order of the Runge-Kutta integration used "
"for the \nstep function [%(default)s]. As a "
"rule of thumb, doubling the rk_order \nwill "
"double the computation time in the worst case.")
track_g.add_argument('--max_invalid_length',
metavar='MAX',
type=float,
default=1,
help="Maximum length without valid direction, in mm. "
"[%(default)s]")
track_g.add_argument('--forward_only',
action='store_true',
help="If set, tracks in one direction only (forward) "
"given the \ninitial seed. The direction is "
"randomly drawn from the ODF.")
track_g.add_argument('--sh_interp',
default='trilinear',
choices=['nearest', 'trilinear'],
help="Spherical harmonic interpolation: "
"nearest-neighbor \nor trilinear. [%(default)s]")
track_g.add_argument('--mask_interp',
default='trilinear',
choices=['nearest', 'trilinear'],
help="Mask interpolation: nearest-neighbor or "
"trilinear. [%(default)s]")
add_seeding_options(p)
r_g = p.add_argument_group('Random seeding options')
r_g.add_argument('--rng_seed',
type=int,
default=0,
help='Initial value for the random number generator. '
'[%(default)s]')
r_g.add_argument('--skip',
type=int,
default=0,
help="Skip the first N random number. \n"
"Useful if you want to create new streamlines to "
"add to \na previously created tractogram with a "
"fixed --rng_seed.\nEx: If tractogram_1 was created "
"with -nt 1,000,000, \nyou can create tractogram_2 "
"with \n--skip 1,000,000.")
m_g = p.add_argument_group('Memory options')
add_processes_arg(m_g)
add_out_options(p)
add_verbose_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
epilog=EPILOG,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_tractogram',
help='Input tractogram (.trk or .tck or .h5).')
p.add_argument('in_dwi',
help='Diffusion-weighted images used by COMMIT (.nii.gz).')
p.add_argument('in_bval', help='b-values in the FSL format (.bval).')
p.add_argument('in_bvec', help='b-vectors in the FSL format (.bvec).')
p.add_argument('out_dir', help='Output directory for the COMMIT maps.')
p.add_argument('--b_thr',
type=int,
default=40,
help='Limit value to consider that a b-value is on an '
'existing shell.\nAbove this limit, the b-value is '
'placed on a new shell. This includes b0s values.')
p.add_argument('--nbr_dir',
type=int,
default=500,
help='Number of directions, on the half of the sphere,\n'
'representing the possible orientations of the '
'response functions [%(default)s].')
p.add_argument('--nbr_iter',
type=int,
default=1000,
help='Maximum number of iterations [%(default)s].')
p.add_argument('--in_peaks',
help='Peaks file representing principal direction(s) '
'locally,\n typically coming from fODFs. This file is '
'mandatory for the default\n stick-zeppelin-ball '
'model.')
p.add_argument('--in_tracking_mask',
help='Binary mask where tratography was allowed.\n'
'If not set, uses a binary mask computed from '
'the streamlines.')
g0 = p.add_argument_group(title='COMMIT2 options')
g0.add_argument('--commit2',
action='store_true',
help='Run commit2, requires .h5 as input and will force\n'
'ball&stick model.')
g0.add_argument(
'--lambda_commit_2',
type=float,
default=1e-3,
help='Specify the clustering prior strength [%(default)s].')
g1 = p.add_argument_group(title='Model options')
g1.add_argument('--ball_stick',
action='store_true',
help='Use the ball&Stick model, disable the zeppelin '
'compartment.\nOnly model suitable for single-shell '
'data.')
g1.add_argument('--para_diff',
type=float,
help='Parallel diffusivity in mm^2/s.\n'
'Default for ball_stick: 1.7E-3\n'
'Default for stick_zeppelin_ball: 1.7E-3')
g1.add_argument('--perp_diff',
nargs='+',
type=float,
help='Perpendicular diffusivity in mm^2/s.\n'
'Default for ball_stick: None\n'
'Default for stick_zeppelin_ball: [0.51E-3]')
g1.add_argument('--iso_diff',
nargs='+',
type=float,
help='Istropic diffusivity in mm^2/s.\n'
'Default for ball_stick: [2.0E-3]\n'
'Default for stick_zeppelin_ball: [1.7E-3, 3.0E-3]')
g2 = p.add_argument_group(title='Tractogram options')
g2.add_argument('--keep_whole_tractogram',
action='store_true',
help='Save a tractogram copy with streamlines weights in '
'the data_per_streamline\n[%(default)s].')
g3 = p.add_argument_group(title='Kernels options')
kern = g3.add_mutually_exclusive_group()
kern.add_argument('--save_kernels',
metavar='DIRECTORY',
help='Output directory for the COMMIT kernels.')
kern.add_argument('--load_kernels',
metavar='DIRECTORY',
help='Input directory where the COMMIT kernels are '
'located.')
g2.add_argument('--compute_only',
action='store_true',
help='Compute kernels only, --save_kernels must be used.')
add_processes_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
return p
def add_tracking_options(p):
"""
Similar to scilpy.tracking.utils.add_generic_options_tracking but
- no algo (det/prob) anymore. Rather, propagation depends on the model.
- no sf_threshold or sh_basis args.
"""
track_g = p.add_argument_group(' Tracking options')
track_g.add_argument('--algo',
choices=['det', 'prob'],
default='det',
help="Tracking algorithm (det or prob). Must be "
"implemented in the chosen model. [det]")
track_g.add_argument('--step',
dest='step_size',
type=float,
default=0.5,
help='Step size in mm. [%(default)s]')
track_g.add_argument('--min_length',
type=float,
default=10.,
metavar='m',
help='Minimum length of a streamline in mm. '
'[%(default)s]')
track_g.add_argument('--max_length',
type=float,
default=300.,
metavar='M',
help='Maximum length of a streamline in mm. '
'[%(default)s]')
track_g.add_argument('--rk_order',
metavar="K",
type=int,
default=2,
choices=[1, 2, 4],
help="The order of the Runge-Kutta integration used "
"for the \nstep function [%(default)s]. As a "
"rule of thumb, doubling the rk_order \nwill "
"double the computation time in the worst case.")
# Additional tracking options compared to scil_compute_local_tracking:
track_g.add_argument('--theta',
metavar='t',
type=float,
default=90,
help="The tracking direction at each step being "
"defined by the model, \ntheta arg can't define "
"allowed directions in the tracking field.\n"
"Rather, this new equivalent angle, is used as "
"\na stopping criterion during propagation: "
"tracking \nis stopped when a direction is more "
"than an angle t from preceding direction")
track_g.add_argument('--max_invalid_len',
metavar='M',
type=float,
default=1,
help="Maximum length without valid direction, in mm. "
"[%(default)s]")
track_g.add_argument('--track_forward_only',
action='store_true',
help="If set, tracks in one direction only (forward) "
"given the initial \nseed. The direction is "
"randomly drawn from the ODF.")
track_g.add_argument('--mask_interp',
default='trilinear',
choices=['nearest', 'trilinear'],
help="Mask interpolation: nearest-neighbor or "
"trilinear. [%(default)s]")
track_g.add_argument('--data_interp',
default='trilinear',
choices=['nearest', 'trilinear'],
help="Input data interpolation: nearest-neighbor or "
"trilinear. [%(default)s]")
# As in scilpy:
r_g = p.add_argument_group(' Random seeding options')
r_g.add_argument('--rng_seed',
type=int,
help='Initial value for the random number generator. '
'[%(default)s]')
r_g.add_argument('--skip',
type=int,
default=0,
help="Skip the first N random number. \n"
"Useful if you want to create new streamlines to "
"add to \na previously created tractogram with a "
"fixed --rng_seed.\nEx: If tractogram_1 was created "
"with -nt 1,000,000, \nyou can create tractogram_2 "
"with \n--skip 1,000,000.")
# toDo. This should be clarified in scilpy eventually. Verifiy evolution.
r_g.add_argument('--set_mmap_to_none',
action='store_true',
help="If true, use mmap_mode=None. Else mmap_mode='r+'.\n"
"Used in np.load(data_file_info). Available only "
"with --processes.\nTO BE CLEANED")
# Preparing upcoming GPU option:
m_g = p.add_argument_group(' Memory options')
ram_options = m_g.add_mutually_exclusive_group()
# Parallel processing or GPU processing
add_processes_arg(ram_options)
ram_options.add_argument('--use_gpu',
action='store_true',
help="If set, use GPU for processing. Cannot be "
"used \ntogether with --processes.")
return track_g
