def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_lesion',
help='Binary mask of the lesion(s) (.nii.gz).')
p.add_argument('out_json',
help='Output file for lesion information (.json).')
p1 = p.add_mutually_exclusive_group()
p1.add_argument('--bundle',
help='Path of the bundle file (.trk).')
p1.add_argument('--bundle_mask',
help='Path of the bundle binary mask (.nii.gz).')
p1.add_argument('--bundle_labels_map',
help='Path of the bundle labels map (.nii.gz).')
p.add_argument('--min_lesion_vol', type=float, default=7,
help='Minimum lesion volume in mm3 [%(default)s].')
p.add_argument('--out_lesion_atlas', metavar='FILE',
help='Save the labelized lesion(s) map (.nii.gz).')
p.add_argument('--out_lesion_stats', metavar='FILE',
help='Save the lesion-wise volume measure (.json).')
p.add_argument('--out_streamlines_stats', metavar='FILE',
help='Save the lesion-wise streamline count (.json).')
add_json_args(p)
add_overwrite_arg(p)
add_reference_arg(p)
return p
def _build_args_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=DESCRIPTION,
epilog=EPILOG)
p.add_argument('moving_tractogram', help='Path of the moving tractogram.')
p.add_argument('static_tractogram', help='Path of the target tractogram.')
add_reference_arg(p, 'moving_tractogram')
add_reference_arg(p, 'static_tractogram')
p.add_argument('--out_name',
default='transformation.npy',
help='Filename of the transformation matrix, \n'
'the registration type will be appended as a suffix,\n'
'[<out_name>_<affine/rigid>.npy]')
p.add_argument('--only_rigid',
action='store_true',
help='Will only use a rigid transformation, '
'uses affine by default.')
p.add_argument('--amount_to_load',
type=int,
default=250000,
help='Amount of streamlines to load for each tractogram \n'
'using lazy load. [%(default)s]')
add_overwrite_arg(p)
add_verbose_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_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__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_tractogram',
help='Tractogram filename.\n'
'Path of the input tractogram or bundle.')
p.add_argument('dist_thresh',
type=float,
help='Last QuickBundlesX threshold in mm. Typically \n'
'the value are between 10-20mm.')
p.add_argument('output_clusters_dir',
help='Path to the clusters directory.')
p.add_argument('--nb_points',
type=int,
default='20',
help='Streamlines will be resampled to have this '
'number of points [%(default)s].')
p.add_argument('--output_centroids',
help='Output tractogram filename.\n'
'Format must be readable by the Nibabel API.')
add_reference_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_tractogram',
help='Tractogram filename. Format must be one of \n'
'trk, tck, vtk, fib, dpy.')
p.add_argument('out_tractogram',
help='Output filename. Format must be one of \n'
'trk, tck, vtk, fib, dpy.')
p.add_argument('--cut_invalid',
action='store_true',
help='Cut invalid streamlines rather than removing them.\n'
'Keep the longest segment only.')
p.add_argument('--remove_single_point',
action='store_true',
help='Consider single point streamlines invalid.')
p.add_argument(
'--remove_overlapping_points',
action='store_true',
help='Consider streamlines with overlapping points invalid.')
add_reference_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_tractogram',
help='Tractogram input file name.')
p.add_argument('out_tractogram',
help='Output tractogram without loops.')
p.add_argument('--looping_tractogram',
help='If set, saves detected looping streamlines.')
p.add_argument('--qb', action='store_true',
help='If set, uses QuickBundles to detect\n' +
'outliers (loops, sharp angle turns).\n' +
'Should mainly be used with bundles. '
'[%(default)s]')
p.add_argument('--threshold', default=8., type=float,
help='Maximal streamline to bundle distance\n' +
'for a streamline to be considered as\n' +
'a tracking error. [%(default)s]')
p.add_argument('-a', dest='angle', default=360, type=float,
help='Maximum looping (or turning) angle of\n' +
'a streamline in degrees. [%(default)s]')
add_overwrite_arg(p)
add_reference_arg(p)
return p
def _build_args_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description='Filter streamlines by length.')
p.add_argument('in_tractogram', help='Streamlines input file name.')
p.add_argument('out_tractogram', help='Streamlines output file name.')
p.add_argument('--minL',
default=0.,
type=float,
help='Minimum length of streamlines. [%(default)s]')
p.add_argument('--maxL',
default=np.inf,
type=float,
help='Maximum length of streamlines. [%(default)s]')
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamline.')
p.add_argument('--display_counts',
action='store_true',
help='Print streamline count before and after filtering')
add_reference_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles', nargs='+',
help='List of the clusters filename.')
p.add_argument('out_accepted',
help='Filename of the concatenated accepted clusters.')
p.add_argument('out_rejected',
help='Filename of the concatenated rejected clusters.')
p.add_argument('--out_accepted_dir',
help='Directory to save all accepted clusters separately.')
p.add_argument('--out_rejected_dir',
help='Directory to save all rejected clusters separately.')
p.add_argument('--min_cluster_size', type=int, default=1,
help='Minimum cluster size for consideration [%(default)s].'
'Must be at least 1.')
p.add_argument('--background_opacity', type=float, default=0.1,
help='Opacity of the background streamlines.'
'Keep low between 0 and 0.5 [%(default)s].')
p.add_argument('--background_linewidth', type=float, default=1,
help='Linewidth of the background streamlines [%(default)s].')
p.add_argument('--clusters_linewidth', type=float, default=1,
help='Linewidth of the current cluster [%(default)s].')
add_reference_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__)
p.add_argument('in_bundle',
help='Fiber bundle file to compute the bundle profiles on.')
p.add_argument('in_metrics',
nargs='+',
help='Metric(s) on which to compute the bundle profiles.')
g = p.add_mutually_exclusive_group()
g.add_argument('--in_centroid',
help='If provided it will be used to make sure all '
'streamlines go in the same direction. \n'
'Also, number of points per streamline will be '
'set according to centroid.')
g.add_argument('--nb_pts_per_streamline',
type=int,
default=20,
help='If centroid not provided, resample each streamline to'
' this number of points [%(default)s].')
add_json_args(p)
add_reference_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('moving_tractogram',
help='Path of the tractogram to be transformed.')
p.add_argument('target_file',
help='Path of the reference file (trk or nii).')
p.add_argument('deformation',
help='Path of the file containing deformation field.')
p.add_argument('out_tractogram',
help='Output filename of the transformed tractogram.')
invalid = p.add_mutually_exclusive_group()
invalid.add_argument('--remove_invalid', action='store_true',
help='Remove the streamlines landing out of the '
'bounding box.')
invalid.add_argument('--keep_invalid', action='store_true',
help='Keep the streamlines landing out of the '
'bounding box.')
add_overwrite_arg(p)
add_reference_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('in_tractogram', help='Tractogram input file name.')
p.add_argument('out_tractogram', help='Output tractogram file name.')
p.add_argument('--minU',
default=0.5,
type=float,
help='Min ufactor value. [%(default)s]')
p.add_argument('--maxU',
default=1.0,
type=float,
help='Max ufactor value. [%(default)s]')
p.add_argument('--remaining_tractogram',
help='If set, saves remaining streamlines.')
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamline.')
p.add_argument('--display_counts',
action='store_true',
help='Print streamline count before and after filtering.')
add_overwrite_arg(p)
add_reference_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundle',
help='Fiber bundle file to compute statistics on.')
p.add_argument('in_label_map',
help='Label map (.npz) of the corresponding fiber bundle.')
p.add_argument('in_distance_map',
help='Distance map (.npz) of the corresponding bundle/'
'centroid streamline.')
p.add_argument('in_metrics', nargs='+',
help='Nifti file to compute statistics on. Probably some '
'tractometry measure(s) such as FA, MD, RD, ...')
p.add_argument('--density_weighting', action='store_true',
help='If set, weight statistics by the number of '
'streamlines passing through each voxel.')
p.add_argument('--distance_weighting', action='store_true',
help='If set, weight statistics by the inverse of the '
'distance between a streamline and the centroid.')
p.add_argument('--out_json',
help='Path of the output json file. If not given, json '
'formatted stats are simply printed.')
add_overwrite_arg(p)
add_reference_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('in_hdf5',
help='Path of the tractogram to be transformed.')
p.add_argument('in_target_file',
help='Path of the reference target file (.trk or .nii).')
p.add_argument('in_transfo',
help='Path of the file containing the 4x4 \n'
'transformation, matrix (.txt, .npy or .mat).')
p.add_argument('out_hdf5',
help='Output tractogram filename (transformed data).')
p.add_argument('--inverse', action='store_true',
help='Apply the inverse linear transformation.')
p.add_argument('--in_deformation',
help='Path to the file containing a deformation field.')
invalid = p.add_mutually_exclusive_group()
invalid.add_argument('--cut_invalid', action='store_true',
help='Cut invalid streamlines rather than removing '
'them.\nKeep the longest segment only.\n'
'By default, invalid streamline are removed.')
add_reference_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_bundles', nargs='+', help='Input bundles filename.')
p.add_argument('--ratio_streamlines',
type=float,
default=0.5,
help='Minimum vote to be considered for streamlines '
'[%(default)s].')
p.add_argument('--ratio_voxels',
type=float,
default=0.5,
help='Minimum vote to be considered for voxels'
' [%(default)s].')
p.add_argument('--same_tractogram',
action='store_true',
help='All bundles need to come from the same tractogram,\n'
'will generate a voting for streamlines too.')
p.add_argument('--output_prefix',
default='voting_',
help='Output prefix, [%(default)s].')
add_reference_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(
description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundle',
help='Input path of the tractography file.')
p.add_argument('out_bundle',
help='Output path of the uniformized file.')
method = p.add_mutually_exclusive_group(required=True)
method.add_argument('--axis', choices=['x', 'y', 'z'],
help='Match endpoints of the streamlines along this axis.\n'
'SUGGESTION: Commissural = x, Association = y, '
'Projection = z')
method.add_argument('--auto', action='store_true',
help='Match endpoints of the streamlines along an '
'automatically determined axis.')
p.add_argument('--swap', action='store_true',
help='Swap head <-> tail convention. '
'Can be useful when the reference is not in RAS.')
add_reference_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
p.add_argument('in_bundle',
help='Fiber bundle file to compute statistics on.')
p.add_argument('label_map',
help='Label map (.npz) of the corresponding '
'fiber bundle.')
p.add_argument('distance_map',
help='Distance map (.npz) of the corresponding '
'bundle/centroid streamline.')
p.add_argument('metrics',
nargs='+',
help='Nifti metric(s) to compute statistics on.')
p.add_argument('--density_weighting',
action='store_true',
help='If set, weight statistics by the number of '
'streamlines passing through each voxel.')
p.add_argument('--distance_weighting',
action='store_true',
help='If set, weight statistics by the inverse of the '
'distance between a streamline and the centroid.')
add_reference_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_volume',
help='Volume used as background (e.g. T1, FA, b0).')
p.add_argument('in_bundles',
nargs='+',
help='List of tractography files supported by nibabel '
'or binary mask files.')
p.add_argument('out_image',
help='Name of the output image mosaic '
'(e.g. mosaic.jpg, mosaic.png).')
p.add_argument('--uniform_coloring',
nargs=3,
metavar=('R', 'G', 'B'),
type=float,
help='Assign an uniform color to streamlines (or ROIs).')
p.add_argument('--random_coloring',
metavar='SEED',
type=int,
help='Assign a random color to streamlines (or ROIs).')
p.add_argument('--zoom',
type=float,
default=1.0,
help='Rendering zoom. '
'A value greater than 1 is a zoom-in,\n'
'a value less than 1 is a zoom-out [%(default)s].')
p.add_argument('--ttf',
default=None,
help='Path of the true type font to use for legends.')
p.add_argument('--ttf_size',
type=int,
default=35,
help='Font size (int) to use for the legends '
'[%(default)s].')
p.add_argument('--opacity_background',
type=float,
default=0.4,
help='Opacity of background image, between 0 and 1.0 '
'[%(default)s].')
p.add_argument('--resolution_of_thumbnails',
type=int,
default=300,
help='Resolution of thumbnails used in mosaic '
'[%(default)s].')
p.add_argument('--light_screenshot',
action='store_true',
help='Keep only 3 views instead of 6 '
'[%(default)s].')
p.add_argument('--no_information',
action='store_true',
help='Don\'t display axis and bundle information '
'[%(default)s].')
add_reference_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_tractogram', help='Streamlines input file name.')
p.add_argument('out_tractogram', help='Streamlines output file name.')
p.add_argument('--min_x',
default=0.,
type=float,
help='Minimum distance in the first dimension, in mm.'
'[%(default)s]')
p.add_argument('--max_x',
default=np.inf,
type=float,
help='Maximum distance in the first dimension, in mm.'
'[%(default)s]')
p.add_argument('--min_y',
default=0.,
type=float,
help='Minimum distance in the second dimension, in mm.'
'[%(default)s]')
p.add_argument('--max_y',
default=np.inf,
type=float,
help='Maximum distance in the second dimension, in mm.'
'[%(default)s]')
p.add_argument('--min_z',
default=0.,
type=float,
help='Minimum distance in the third dimension, in mm.'
'[%(default)s]')
p.add_argument('--max_z',
default=np.inf,
type=float,
help='Maximum distance in the third dimension, in mm.'
'[%(default)s]')
p.add_argument('--use_abs',
action='store_true',
help="If set, will use the total of distances in absolute "
"value (ex, coming back on yourself will contribute "
"to the total distance instead of cancelling it).")
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamline.')
p.add_argument('--display_counts',
action='store_true',
help='Print streamline count before and after filtering.')
p.add_argument('--save_rejected',
metavar='filename',
help="Save the SFT of rejected streamlines.")
add_reference_arg(p)
add_overwrite_arg(p)
add_verbose_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument("in_tractogram", help="Input tractogram to score")
p.add_argument("gt_config",
help=".json dict configured as specified above.")
p.add_argument("out_dir", help="Output directory.")
g = p.add_argument_group("Additions to gt_config")
p.add_argument("--gt_dir",
metavar='DIR',
help="Root path of the ground truth files listed in the "
"gt_config.\n If not set, filenames in the config "
"file are considered\n as complete paths.")
g.add_argument("--use_gt_masks_as_limits_masks",
action='store_true',
help="If set, the gt_config's 'gt_mask' will also be used "
"as\n'limits_mask' for each bundle. Note that this "
"means the\nOR will necessarily be 0.")
g = p.add_argument_group("Preprocessing")
g.add_argument("--dilate_endpoints",
metavar="NB_PASS",
default=0,
type=int,
help="Dilate inclusion masks n-times. Default: 0.")
g.add_argument("--remove_invalid",
action="store_true",
help="Remove invalid streamlines before scoring.")
g = p.add_argument_group("Tractometry choices")
g.add_argument("--save_wpc_separately",
action='store_true',
help="If set, streamlines rejected from VC based on the "
"config\nfile criteria will be saved separately from "
"IS (and IC)\nin one file *_WPC.tck per bundle.")
g.add_argument("--compute_ic",
action='store_true',
help="If set, IS are split into NC + IC, where IC are "
"computed as one bundle per\npair of ROI not "
"belonging to a true connection, named\n*_*_IC.tck.")
g.add_argument("--remove_wpc_belonging_to_another_bundle",
action='store_true',
help="If set, WPC actually belonging to VC (from another "
"bundle,\nof course; in the case of overlapping ROIs) "
"will be removed\nfrom the WPC classification.")
p.add_argument("--no_empty",
action='store_true',
help='Do not write file if there is no streamline.')
add_json_args(p)
add_overwrite_arg(p)
add_reference_arg(p)
add_verbose_arg(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('operation',
choices=OPERATIONS.keys(),
metavar='OPERATION',
help='The type of operation to be performed on the '
'streamlines. Must\nbe one of the following: '
'%(choices)s.')
p.add_argument('in_tractograms',
metavar='INPUT_FILES',
nargs='+',
help='The list of files that contain the ' +
'streamlines to operate on.')
p.add_argument('out_tractogram',
metavar='OUTPUT_FILE',
help='The file where the remaining streamlines '
'are saved.')
p.add_argument('--precision',
'-p',
metavar='NBR_OF_DECIMALS',
type=int,
default=4,
help='Precision used to compare streamlines [%(default)s].')
p.add_argument('--robust',
'-r',
action='store_true',
help='Use version robust to small translation/rotation.')
p.add_argument('--no_metadata',
'-n',
action='store_true',
help='Strip the streamline metadata from the output.')
p.add_argument('--fake_metadata',
action='store_true',
help='Skip the metadata verification, create fake metadata '
'if missing, can lead to unexpected behavior.')
p.add_argument('--save_indices',
'-s',
metavar='OUT_INDEX_FILE',
help='Save the streamline indices to the supplied '
'json file.')
p.add_argument('--ignore_invalid',
action='store_true',
help='If set, does not crash because of invalid '
'streamlines.')
add_json_args(p)
add_reference_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_bundle', help='Fiber bundle file.')
add_reference_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
epilog=EPILOG,
description=__doc__)
p.add_argument('in_tractogram', help='Path of the input tractogram file.')
p.add_argument('in_wmparc',
help='Path of the white matter parcellation atlas\n' +
'(.nii or .nii.gz)')
p.add_argument('out_path', help='Path to the output files.')
p.add_argument('--minL',
default=0.,
type=float,
help='Minimum length of streamlines, in mm. [%(default)s]')
p.add_argument('--maxL',
default=np.inf,
type=float,
help='Maximum length of streamlines, in mm. [%(default)s]')
p.add_argument('-a',
dest='angle',
default=np.inf,
type=float,
help='Maximum looping (or turning) angle of\n' +
'a streamline, in degrees. [%(default)s]')
p.add_argument('--csf_bin',
help='Allow CSF endings filtering with this binary\n' +
'mask instead of using the atlas (.nii or .nii.gz)')
p.add_argument('--ctx_dilation_radius',
type=float,
default=0.,
help='Cortical labels dilation radius, in mm.\n' +
' [%(default)s]')
p.add_argument('--save_intermediate_tractograms',
action='store_true',
help='Save accepted and discarded streamlines\n' +
' after each step.')
p.add_argument('--save_volumes',
action='store_true',
help='Save volumetric images (e.g. binarised label\n' +
' images, etc) in the filtering process.')
p.add_argument('--save_counts',
action='store_true',
help='Save the streamline counts to a file (.json)')
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamlines.')
add_reference_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('in_tractogram', help='Path of the input tractogram file.')
p.add_argument('out_tractogram',
help='Path of the output tractogram file.')
p.add_argument('--drawn_roi',
nargs=3,
action='append',
metavar=('ROI_NAME', 'MODE', 'CRITERIA'),
help='Filename of a hand drawn ROI (.nii or .nii.gz).')
p.add_argument('--atlas_roi',
nargs=4,
action='append',
metavar=('ROI_NAME', 'ID', 'MODE', 'CRITERIA'),
help='Filename of an atlas (.nii or .nii.gz).')
p.add_argument('--bdo',
nargs=3,
action='append',
metavar=('BDO_NAME', 'MODE', 'CRITERIA'),
help='Filename of a bounding box (bdo) file from MI-Brain.')
p.add_argument('--x_plane',
nargs=3,
action='append',
metavar=('PLANE', 'MODE', 'CRITERIA'),
help='Slice number in X, in voxel space.')
p.add_argument('--y_plane',
nargs=3,
action='append',
metavar=('PLANE', 'MODE', 'CRITERIA'),
help='Slice number in Y, in voxel space.')
p.add_argument('--z_plane',
nargs=3,
action='append',
metavar=('PLANE', 'MODE', 'CRITERIA'),
help='Slice number in Z, in voxel space.')
p.add_argument('--filtering_list',
help='Text file containing one rule per line\n'
'(i.e. drawn_roi mask.nii.gz both_ends include).')
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamline.')
p.add_argument('--display_counts',
action='store_true',
help='Print streamline count before and after filtering')
add_reference_arg(p)
add_verbose_arg(p)
add_overwrite_arg(p)
add_json_args(p)
return p
def _build_arg_parser():
p = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter,
description=__doc__)
p.add_argument('operation',
choices=OPERATIONS.keys(),
metavar='OPERATION',
help='The type of operation to be performed on the '
'streamlines. Must\nbe one of the following: '
'%(choices)s.')
p.add_argument('inputs',
metavar='INPUT_FILES',
nargs='+',
help='The list of files that contain the ' +
'streamlines to operate on.')
p.add_argument('output',
metavar='OUTPUT_FILE',
help='The file where the remaining streamlines '
'are saved.')
p.add_argument('--precision',
'-p',
metavar='NUMBER_OF_DECIMALS',
type=int,
help='The precision used when comparing streamlines.')
p.add_argument('--no_metadata',
'-n',
action='store_true',
help='Strip the streamline metadata from the output.')
p.add_argument('--save_metadata_indices',
'-m',
action='store_true',
help='Save streamline indices to metadata. Has no '
'effect if --no-data\nis present. Will '
'overwrite \'ids\' metadata if already present.')
p.add_argument('--save_indices',
'-s',
metavar='OUTPUT_INDEX_FILE',
help='Save the streamline indices to the supplied '
'json file.')
p.add_argument('--ignore_invalid',
action='store_true',
help='If set, does not crash because of invalid '
'streamlines.')
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__,
epilog=EPILOG)
p.add_argument('in_tractogram', help='Input tractogram filename.')
p.add_argument('in_model', help='Model to use for recognition.')
p.add_argument('in_transfo',
help='Path for the transformation to model space '
'(.txt, .npy or .mat).')
p.add_argument('out_tractogram', help='Output tractogram filename.')
p.add_argument('--tractogram_clustering_thr',
type=float,
default=8,
help='Clustering threshold used for the whole brain '
'[%(default)smm].')
p.add_argument('--model_clustering_thr',
type=float,
default=4,
help='Clustering threshold used for the model '
'[%(default)smm].')
p.add_argument('--pruning_thr',
type=float,
default=6,
help='MDF threshold used for final streamlines selection '
'[%(default)smm].')
p.add_argument('--slr_threads',
type=int,
default=None,
help='Number of threads for SLR [all].')
p.add_argument('--seed',
type=int,
default=None,
help='Random number generator seed [%(default)s].')
p.add_argument('--inverse',
action='store_true',
help='Use the inverse transformation.')
p.add_argument('--no_empty',
action='store_true',
help='Do not write file if there is no streamline.')
group = p.add_mutually_exclusive_group()
group.add_argument(
'--in_pickle',
help='Input pickle clusters map file.\n'
'Will override the tractogram_clustering_thr parameter.')
group.add_argument('--out_pickle', help='Output pickle clusters map file.')
add_reference_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_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(description=__doc__,
formatter_class=argparse.RawTextHelpFormatter)
p.add_argument('in_bundles',
nargs='+',
help='List of tractography files supported by nibabel.')
p.add_argument('in_labels',
nargs='+',
help='List of labels maps that matches the bundles.')
p.add_argument('--fitting_func',
choices=['lin_up', 'lin_down', 'exp', 'inv', 'log'],
default=None,
help='Function to weigh points using their distance.'
'\n[Default: %(default)s]')
p2 = p.add_argument_group(title='Visualization options')
p3 = p2.add_mutually_exclusive_group()
p3.add_argument('--show_rendering',
action='store_true',
help='Display VTK window (optional).')
p3.add_argument('--save_rendering',
metavar='OUT_FOLDER',
help='Save VTK render in the specified folder (optional)')
p2.add_argument('--wireframe',
action='store_true',
help='Use wireframe for the tube rendering.')
p2.add_argument('--error_coloring',
action='store_true',
help='Use the fitting error to color the tube.')
p2.add_argument('--width',
type=float,
default=0.2,
help='Width of tubes or lines representing streamlines'
'\n[Default: %(default)s]')
p2.add_argument('--opacity',
type=float,
default=0.2,
help='Opacity for the streamlines rendered with the tube.'
'\n[Default: %(default)s]')
p2.add_argument('--background',
metavar=('R', 'G', 'B'),
nargs=3,
default=[1, 1, 1],
type=parser_color_type,
help='RBG values [0, 255] of the color of the background.'
'\n[Default: %(default)s]')
add_reference_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', 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
