From d0bc9c5a4d2fbec770203a0f3c7030647318d99f Mon Sep 17 00:00:00 2001 From: Yaroslav Halchenko Date: Mon, 21 May 2018 23:00:49 -0400 Subject: [PATCH 1/5] DOC: improve descriptions for N4BiasFieldCorrection InputSpec --- nipype/interfaces/ants/segmentation.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/nipype/interfaces/ants/segmentation.py b/nipype/interfaces/ants/segmentation.py index f6a3f5da97..a15e969f6d 100644 --- a/nipype/interfaces/ants/segmentation.py +++ b/nipype/interfaces/ants/segmentation.py @@ -266,10 +266,15 @@ class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec): input_image = File( argstr='--input-image %s', mandatory=True, - desc=('image to apply transformation to (generally a ' - 'coregistered functional)')) - mask_image = File(argstr='--mask-image %s') - weight_image = File(argstr='--weight-image %s') + desc=('input for bias correction. Negative values or values close to ' + 'zero should be processed prior to correction')) + mask_image = File( + argstr='--mask-image %s', + desc=('image to specify region to perform final bias correction in')) + weight_image = File( + argstr='--weight-image %s', + desc=('image for relative weighting (e.g. probability map of the white ' + 'matter) of voxels during the B-spline fitting. ')) output_image = traits.Str( argstr='--output %s', desc='output file name', @@ -284,8 +289,7 @@ class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec): False, mandatory=True, usedefault=True, - desc=('True if the estimated bias should be saved' - ' to file.'), + desc=('True if the estimated bias should be saved to file.'), xor=['bias_image']) bias_image = File( desc='Filename for the estimated bias.', hash_files=False) From 10d37010b670cd7ab1d72b054faf9d1a6a4fc0a2 Mon Sep 17 00:00:00 2001 From: Yaroslav Halchenko Date: Wed, 23 May 2018 11:53:38 -0400 Subject: [PATCH 2/5] DOC: Unify short description of preprocess.FSLCommands --- nipype/interfaces/fsl/preprocess.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/nipype/interfaces/fsl/preprocess.py b/nipype/interfaces/fsl/preprocess.py index 201106502f..84da753601 100644 --- a/nipype/interfaces/fsl/preprocess.py +++ b/nipype/interfaces/fsl/preprocess.py @@ -113,7 +113,7 @@ class BETOutputSpec(TraitedSpec): class BET(FSLCommand): - """Use FSL BET command for skull stripping. + """FSL BET command for skull stripping For complete details, see the `BET Documentation. `_ @@ -312,7 +312,7 @@ class FASTOutputSpec(TraitedSpec): class FAST(FSLCommand): - """ Use FSL FAST for segmenting and bias correction. + """FSL FAST command for segmentation and bias correction For complete details, see the `FAST Documentation. `_ @@ -635,7 +635,7 @@ class FLIRTOutputSpec(TraitedSpec): class FLIRT(FSLCommand): - """Use FSL FLIRT for coregistration. + """FSL FLIRT command for coregistration For complete details, see the `FLIRT Documentation. `_ @@ -790,7 +790,7 @@ class MCFLIRTOutputSpec(TraitedSpec): class MCFLIRT(FSLCommand): - """Use FSL MCFLIRT to do within-modality motion correction. + """FSL MCFLIRT command for within-modality motion correction For complete details, see the `MCFLIRT Documentation. `_ @@ -1106,7 +1106,7 @@ class FNIRTOutputSpec(TraitedSpec): class FNIRT(FSLCommand): - """Use FSL FNIRT for non-linear registration. + """FSL FNIRT command for non-linear registration For complete details, see the `FNIRT Documentation. `_ @@ -1305,7 +1305,7 @@ class ApplyWarpOutputSpec(TraitedSpec): class ApplyWarp(FSLCommand): - """Use FSL's applywarp to apply the results of a FNIRT registration + """FSL's applywarp command to apply the results of a FNIRT registration Examples -------- @@ -1389,7 +1389,7 @@ class SliceTimerOutputSpec(TraitedSpec): class SliceTimer(FSLCommand): - """ use FSL slicetimer to perform slice timing correction. + """FSL slicetimer command to perform slice timing correction Examples -------- @@ -1476,7 +1476,7 @@ class SUSANOutputSpec(TraitedSpec): class SUSAN(FSLCommand): - """ use FSL SUSAN to perform smoothing + """FSL SUSAN command to perform smoothing For complete details, see the `SUSAN Documentation. `_ @@ -1646,7 +1646,8 @@ class FUGUEOutputSpec(TraitedSpec): class FUGUE(FSLCommand): - """ + """FSL FUGUE set of tools for EPI distortion correction + `FUGUE `_ is, most generally, a set of tools for EPI distortion correction. @@ -1869,7 +1870,7 @@ class PRELUDEOutputSpec(TraitedSpec): class PRELUDE(FSLCommand): - """Use FSL prelude to do phase unwrapping + """FSL prelude command for phase unwrapping Examples -------- @@ -1979,8 +1980,7 @@ class FIRSTOutputSpec(TraitedSpec): class FIRST(FSLCommand): - """ - Use FSL's run_first_all command to segment subcortical volumes + """FSL run_first_all command for segmentation of subcortical volumes http://www.fmrib.ox.ac.uk/fsl/first/index.html From 4a130872f2f09aadf8e351ff04912571c8ef8113 Mon Sep 17 00:00:00 2001 From: Yaroslav Halchenko Date: Thu, 7 Jun 2018 22:52:43 -0400 Subject: [PATCH 3/5] DOC: Minor spelling fixes and further unification of short description --- nipype/interfaces/ants/registration.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/nipype/interfaces/ants/registration.py b/nipype/interfaces/ants/registration.py index 56cdce10c7..58cfe2492d 100644 --- a/nipype/interfaces/ants/registration.py +++ b/nipype/interfaces/ants/registration.py @@ -70,8 +70,7 @@ class ANTSInputSpec(ANTSCommandInputSpec): traits.Int(), requires=['metric'], mandatory=True, - desc='radius of the region (i.e. number of layers' - ' around a voxel point)' + desc='radius of the region (i.e. number of layers around a voxel/pixel)' ' that is used for computing cross correlation') output_transform_prefix = Str( @@ -126,8 +125,7 @@ class ANTSOutputSpec(TraitedSpec): class ANTS(ANTSCommand): - """ - + """ANTS command for registration of images (old, use Registration instead) Examples -------- @@ -557,7 +555,8 @@ class RegistrationOutputSpec(TraitedSpec): class Registration(ANTSCommand): - """ + """ANTs Registration command for registration of images + `antsRegistration `_ registers a ``moving_image`` to a ``fixed_image``, using a predefined (sequence of) cost function(s) and transformation operations. The cost function is defined using one or more 'metrics', specifically @@ -601,12 +600,12 @@ class Registration(ANTSCommand): Examples -------- - Set up a Registation node with some default settings. This Node registers + Set up a Registration node with some default settings. This Node registers 'fixed1.nii' to 'moving1.nii' by first fitting a linear 'Affine' transformation, and then a non-linear 'SyN' transformation, both using the Mutual Information-cost metric. - The registration is initailized by first applying the (linear) transform + The registration is initialized by first applying the (linear) transform trans.mat. >>> import copy, pprint From 2a952f9e6355a1f6ed73f5cadfdd8d00cb17f74d Mon Sep 17 00:00:00 2001 From: Yaroslav Halchenko Date: Thu, 7 Jun 2018 22:53:06 -0400 Subject: [PATCH 4/5] DOC: fix "joining spaces". Will stay with convention of leading space due to easier detection --- nipype/interfaces/ants/resampling.py | 18 +-- nipype/interfaces/ants/segmentation.py | 166 ++++++++++++------------- 2 files changed, 88 insertions(+), 96 deletions(-) diff --git a/nipype/interfaces/ants/resampling.py b/nipype/interfaces/ants/resampling.py index fe730aef78..e26a48ed6a 100644 --- a/nipype/interfaces/ants/resampling.py +++ b/nipype/interfaces/ants/resampling.py @@ -493,15 +493,15 @@ class ApplyTransformsToPointsInputSpec(ANTSCommandInputSpec): argstr='--input %s', mandatory=True, desc= - ("Currently, the only input supported is a csv file with " - "columns including x,y (2D), x,y,z (3D) or x,y,z,t,label (4D) column headers." - "The points should be defined in physical space." - "If in doubt how to convert coordinates from your files to the space" - "required by antsApplyTransformsToPoints try creating/drawing a simple" - "label volume with only one voxel set to 1 and all others set to 0." - "Write down the voxel coordinates. Then use ImageMaths LabelStats to find" - "out what coordinates for this voxel antsApplyTransformsToPoints is" - "expecting."), + ("Currently, the only input supported is a csv file with" + " columns including x,y (2D), x,y,z (3D) or x,y,z,t,label (4D) column headers." + " The points should be defined in physical space." + " If in doubt how to convert coordinates from your files to the space" + " required by antsApplyTransformsToPoints try creating/drawing a simple" + " label volume with only one voxel set to 1 and all others set to 0." + " Write down the voxel coordinates. Then use ImageMaths LabelStats to find" + " out what coordinates for this voxel antsApplyTransformsToPoints is" + " expecting."), exists=True) output_file = traits.Str( argstr='--output %s', diff --git a/nipype/interfaces/ants/segmentation.py b/nipype/interfaces/ants/segmentation.py index a15e969f6d..6ccfb28ba2 100644 --- a/nipype/interfaces/ants/segmentation.py +++ b/nipype/interfaces/ants/segmentation.py @@ -455,19 +455,19 @@ class CorticalThicknessInputSpec(ANTSCommandInputSpec): exists=True, argstr='-a %s', desc=('Structural *intensity* image, typically T1.' - 'If more than one anatomical image is specified,' - 'subsequently specified images are used during the' - 'segmentation process. However, only the first' - 'image is used in the registration of priors.' - 'Our suggestion would be to specify the T1' - 'as the first image.'), + ' If more than one anatomical image is specified,' + ' subsequently specified images are used during the' + ' segmentation process. However, only the first' + ' image is used in the registration of priors.' + ' Our suggestion would be to specify the T1' + ' as the first image.'), mandatory=True) brain_template = File( exists=True, argstr='-e %s', desc=('Anatomical *intensity* template (possibly created using a' - 'population data set with buildtemplateparallel.sh in ANTs).' - 'This template is *not* skull-stripped.'), + ' population data set with buildtemplateparallel.sh in ANTs).' + ' This template is *not* skull-stripped.'), mandatory=True) brain_probability_mask = File( exists=True, @@ -492,10 +492,10 @@ class CorticalThicknessInputSpec(ANTSCommandInputSpec): t1_registration_template = File( exists=True, desc=('Anatomical *intensity* template' - '(assumed to be skull-stripped). A common' - 'case would be where this would be the same' - 'template as specified in the -e option which' - 'is not skull stripped.'), + ' (assumed to be skull-stripped). A common' + ' case would be where this would be the same' + ' template as specified in the -e option which' + ' is not skull stripped.'), argstr='-t %s', mandatory=True) extraction_registration_mask = File( @@ -508,66 +508,64 @@ class CorticalThicknessInputSpec(ANTSCommandInputSpec): desc='Keep brain extraction/segmentation warps, etc (default = 0).') max_iterations = traits.Int( argstr='-i %d', - desc=('ANTS registration max iterations' - '(default = 100x100x70x20)')) + desc=('ANTS registration max iterations (default = 100x100x70x20)')) prior_segmentation_weight = traits.Float( argstr='-w %f', desc=('Atropos spatial prior *probability* weight for' - 'the segmentation')) + ' the segmentation')) segmentation_iterations = traits.Int( argstr='-n %d', desc=('N4 -> Atropos -> N4 iterations during segmentation' - '(default = 3)')) + ' (default = 3)')) posterior_formulation = traits.Str( argstr='-b %s', desc=('Atropos posterior formulation and whether or not' - 'to use mixture model proportions.' - '''e.g 'Socrates[1]' (default) or 'Aristotle[1]'.''' - 'Choose the latter if you' - 'want use the distance priors (see also the -l option' - 'for label propagation control).')) + ' to use mixture model proportions.' + ''' e.g 'Socrates[1]' (default) or 'Aristotle[1]'.''' + ' Choose the latter if you' + ' want use the distance priors (see also the -l option' + ' for label propagation control).')) use_floatingpoint_precision = traits.Enum( 0, 1, argstr='-j %d', - desc=('Use floating point precision ' - 'in registrations (default = 0)')) + desc=('Use floating point precision in registrations (default = 0)')) use_random_seeding = traits.Enum( 0, 1, argstr='-u %d', desc=('Use random number generated from system clock in Atropos' - '(default = 1)')) + ' (default = 1)')) b_spline_smoothing = traits.Bool( argstr='-v', desc=('Use B-spline SyN for registrations and B-spline' - 'exponential mapping in DiReCT.')) + ' exponential mapping in DiReCT.')) cortical_label_image = File( exists=True, desc='Cortical ROI labels to use as a prior for ATITH.') label_propagation = traits.Str( argstr='-l %s', desc= ('Incorporate a distance prior one the posterior formulation. Should be' - '''of the form 'label[lambda,boundaryProbability]' where label''' - 'is a value of 1,2,3,... denoting label ID. The label' - 'probability for anything outside the current label' - ' = boundaryProbability * exp( -lambda * distanceFromBoundary )' - 'Intuitively, smaller lambda values will increase the spatial capture' - 'range of the distance prior. To apply to all label values, simply omit' - 'specifying the label, i.e. -l [lambda,boundaryProbability].')) + ''' of the form 'label[lambda,boundaryProbability]' where label''' + ' is a value of 1,2,3,... denoting label ID. The label' + ' probability for anything outside the current label' + ' = boundaryProbability * exp( -lambda * distanceFromBoundary )' + ' Intuitively, smaller lambda values will increase the spatial capture' + ' range of the distance prior. To apply to all label values, simply omit' + ' specifying the label, i.e. -l [lambda,boundaryProbability].')) quick_registration = traits.Bool( argstr='-q 1', desc= ('If = 1, use antsRegistrationSyNQuick.sh as the basis for registration' - 'during brain extraction, brain segmentation, and' - '(optional) normalization to a template.' - 'Otherwise use antsRegistrationSyN.sh (default = 0).')) + ' during brain extraction, brain segmentation, and' + ' (optional) normalization to a template.' + ' Otherwise use antsRegistrationSyN.sh (default = 0).')) debug = traits.Bool( argstr='-z 1', desc=( 'If > 0, runs a faster version of the script.' - 'Only for testing. Implies -u 0.' - 'Requires single thread computation for complete reproducibility.' + ' Only for testing. Implies -u 0.' + ' Requires single thread computation for complete reproducibility.' )) @@ -704,25 +702,25 @@ class BrainExtractionInputSpec(ANTSCommandInputSpec): exists=True, argstr='-a %s', desc=('Structural image, typically T1. If more than one' - 'anatomical image is specified, subsequently specified' - 'images are used during the segmentation process. However,' - 'only the first image is used in the registration of priors.' - 'Our suggestion would be to specify the T1 as the first image.' - 'Anatomical template created using e.g. LPBA40 data set with' - 'buildtemplateparallel.sh in ANTs.'), + ' anatomical image is specified, subsequently specified' + ' images are used during the segmentation process. However,' + ' only the first image is used in the registration of priors.' + ' Our suggestion would be to specify the T1 as the first image.' + ' Anatomical template created using e.g. LPBA40 data set with' + ' buildtemplateparallel.sh in ANTs.'), mandatory=True) brain_template = File( exists=True, argstr='-e %s', desc=('Anatomical template created using e.g. LPBA40 data set with' - 'buildtemplateparallel.sh in ANTs.'), + ' buildtemplateparallel.sh in ANTs.'), mandatory=True) brain_probability_mask = File( exists=True, argstr='-m %s', desc=('Brain probability mask created using e.g. LPBA40 data set which' - 'have brain masks defined, and warped to anatomical template and' - 'averaged resulting in a probability image.'), + ' have brain masks defined, and warped to anatomical template and' + ' averaged resulting in a probability image.'), copyfile=False, mandatory=True) out_prefix = traits.Str( @@ -737,7 +735,7 @@ class BrainExtractionInputSpec(ANTSCommandInputSpec): argstr='-f %s', desc=('Mask (defined in the template space) used during' ' registration for brain extraction.' - 'To limit the metric computation to a specific region.')) + ' To limit the metric computation to a specific region.')) image_suffix = traits.Str( 'nii.gz', desc=('any of standard ITK formats,' @@ -749,7 +747,7 @@ class BrainExtractionInputSpec(ANTSCommandInputSpec): 1, argstr='-u %d', desc=('Use random number generated from system clock in Atropos' - '(default = 1)')) + ' (default = 1)')) keep_temporary_files = traits.Int( argstr='-k %d', desc='Keep brain extraction/segmentation warps, etc (default = 0).') @@ -757,14 +755,13 @@ class BrainExtractionInputSpec(ANTSCommandInputSpec): 0, 1, argstr='-q %d', - desc=('Use floating point precision ' - 'in registrations (default = 0)')) + desc=('Use floating point precision in registrations (default = 0)')) debug = traits.Bool( argstr='-z 1', desc=( 'If > 0, runs a faster version of the script.' - 'Only for testing. Implies -u 0.' - 'Requires single thread computation for complete reproducibility.' + ' Only for testing. Implies -u 0.' + ' Requires single thread computation for complete reproducibility.' )) @@ -949,21 +946,19 @@ class JointFusionInputSpec(ANTSCommandInputSpec): default='Joint', argstr='-m %s', usedefault=True, - desc=('Select voting method. Options: Joint (Joint ' - 'Label Fusion). May be followed by optional ' - 'parameters in brackets, e.g., -m Joint[0.1,2]')) + desc=('Select voting method. Options: Joint (Joint' + ' Label Fusion). May be followed by optional' + ' parameters in brackets, e.g., -m Joint[0.1,2]')) alpha = traits.Float( default=0.1, usedefault=True, requires=['method'], - desc=('Regularization term added to matrix Mx for ' - 'inverse')) + desc=('Regularization term added to matrix Mx for inverse')) beta = traits.Int( default=2, usedefault=True, requires=['method'], - desc=('Exponent for mapping intensity difference to joint' - ' error')) + desc=('Exponent for mapping intensity difference to joint error')) output_label_image = File( argstr='%s', mandatory=True, @@ -985,14 +980,12 @@ class JointFusionInputSpec(ANTSCommandInputSpec): exclusion_region = File( exists=True, argstr='-x %s', - desc=('Specify an exclusion region for the given ' - 'label.')) + desc=('Specify an exclusion region for the given label.')) atlas_group_id = traits.ListInt( argstr='-gp %d...', desc='Assign a group ID for each atlas') atlas_group_weights = traits.ListInt( argstr='-gpw %d...', - desc=('Assign the voting weights to ' - 'each atlas group')) + desc=('Assign the voting weights to each atlas group')) class JointFusionOutputSpec(TraitedSpec): @@ -1086,25 +1079,24 @@ class DenoiseImageInputSpec(ANTSCommandInputSpec): default_value=1, usedefault=True, argstr='-s %s', - desc=('Running noise correction on large images can ' - 'be time consuming. To lessen computation time, ' - 'the input image can be resampled. The shrink ' - 'factor, specified as a single integer, describes ' - 'this resampling. Shrink factor = 1 is the default.')) + desc=('Running noise correction on large images can' + ' be time consuming. To lessen computation time,' + ' the input image can be resampled. The shrink' + ' factor, specified as a single integer, describes' + ' this resampling. Shrink factor = 1 is the default.')) output_image = File( argstr="-o %s", name_source=['input_image'], hash_files=False, keep_extension=True, name_template='%s_noise_corrected', - desc='The output consists of the noise corrected ' - 'version of the input image.') + desc='The output consists of the noise corrected' + ' version of the input image.') save_noise = traits.Bool( False, mandatory=True, usedefault=True, - desc=('True if the estimated noise should be saved ' - 'to file.'), + desc=('True if the estimated noise should be saved to file.'), xor=['noise_image']) noise_image = File( name_source=['input_image'], @@ -1449,8 +1441,8 @@ class KellyKapowskiInputSpec(ANTSCommandInputSpec): argstr='--segmentation-image "%s"', mandatory=True, desc= - "A segmentation image must be supplied labeling the gray and white matters.\n" - "Default values = 2 and 3, respectively.", + "A segmentation image must be supplied labeling the gray and white matters." + " Default values = 2 and 3, respectively.", ) gray_matter_label = traits.Int( @@ -1470,26 +1462,26 @@ class KellyKapowskiInputSpec(ANTSCommandInputSpec): exists=True, argstr='--gray-matter-probability-image "%s"', desc= - "In addition to the segmentation image, a gray matter probability image can be\n" - "used. If no such image is supplied, one is created using the segmentation image\n" - "and a variance of 1.0 mm.") + "In addition to the segmentation image, a gray matter probability image can be" + " used. If no such image is supplied, one is created using the segmentation image" + " and a variance of 1.0 mm.") white_matter_prob_image = File( exists=True, argstr='--white-matter-probability-image "%s"', desc= - "In addition to the segmentation image, a white matter probability image can be\n" - "used. If no such image is supplied, one is created using the segmentation image\n" - "and a variance of 1.0 mm.") + "In addition to the segmentation image, a white matter probability image can be" + " used. If no such image is supplied, one is created using the segmentation image" + " and a variance of 1.0 mm.") convergence = traits.Str( default="[50,0.001,10]", argstr='--convergence "%s"', usedefault=True, desc= - "Convergence is determined by fitting a line to the normalized energy profile of\n" - "the last N iterations (where N is specified by the window size) and determining\n" - "the slope which is then compared with the convergence threshold.", + "Convergence is determined by fitting a line to the normalized energy profile of" + " the last N iterations (where N is specified by the window size) and determining" + " the slope which is then compared with the convergence threshold.", ) thickness_prior_estimate = traits.Float( @@ -1520,9 +1512,9 @@ class KellyKapowskiInputSpec(ANTSCommandInputSpec): 1.5, usedefault=True, argstr="--smoothing-velocity-field-parameter %f", desc= - "Defines the Gaussian smoothing of the velocity field (default = 1.5).\n" - "If the b-spline smoothing option is chosen, then this defines the \n" - "isotropic mesh spacing for the smoothing spline (default = 15).") + "Defines the Gaussian smoothing of the velocity field (default = 1.5)." + " If the b-spline smoothing option is chosen, then this defines the" + " isotropic mesh spacing for the smoothing spline (default = 15).") use_bspline_smoothing = traits.Bool( argstr="--use-bspline-smoothing 1", @@ -1536,7 +1528,7 @@ class KellyKapowskiInputSpec(ANTSCommandInputSpec): max_invert_displacement_field_iters = traits.Int( 20, usedefault=True, argstr="--maximum-number-of-invert-displacement-field-iterations %d", - desc="Maximum number of iterations for estimating the invert \n" + desc="Maximum number of iterations for estimating the invert" "displacement field.") cortical_thickness = File( From 6a1e2e682b70aa97e5e76d25223b2088cd3d94b8 Mon Sep 17 00:00:00 2001 From: mathiasg Date: Tue, 3 Jul 2018 11:32:57 -0400 Subject: [PATCH 5/5] DOC: use wrapper in docstrings --- nipype/interfaces/ants/registration.py | 3 ++- nipype/interfaces/fsl/preprocess.py | 20 ++++++++++---------- 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/nipype/interfaces/ants/registration.py b/nipype/interfaces/ants/registration.py index 58cfe2492d..7190816cf3 100644 --- a/nipype/interfaces/ants/registration.py +++ b/nipype/interfaces/ants/registration.py @@ -125,7 +125,8 @@ class ANTSOutputSpec(TraitedSpec): class ANTS(ANTSCommand): - """ANTS command for registration of images (old, use Registration instead) + """ANTS wrapper for registration of images + (old, use Registration instead) Examples -------- diff --git a/nipype/interfaces/fsl/preprocess.py b/nipype/interfaces/fsl/preprocess.py index 84da753601..dd2c969945 100644 --- a/nipype/interfaces/fsl/preprocess.py +++ b/nipype/interfaces/fsl/preprocess.py @@ -113,7 +113,7 @@ class BETOutputSpec(TraitedSpec): class BET(FSLCommand): - """FSL BET command for skull stripping + """FSL BET wrapper for skull stripping For complete details, see the `BET Documentation. `_ @@ -312,7 +312,7 @@ class FASTOutputSpec(TraitedSpec): class FAST(FSLCommand): - """FSL FAST command for segmentation and bias correction + """FSL FAST wrapper for segmentation and bias correction For complete details, see the `FAST Documentation. `_ @@ -635,7 +635,7 @@ class FLIRTOutputSpec(TraitedSpec): class FLIRT(FSLCommand): - """FSL FLIRT command for coregistration + """FSL FLIRT wrapper for coregistration For complete details, see the `FLIRT Documentation. `_ @@ -790,7 +790,7 @@ class MCFLIRTOutputSpec(TraitedSpec): class MCFLIRT(FSLCommand): - """FSL MCFLIRT command for within-modality motion correction + """FSL MCFLIRT wrapper for within-modality motion correction For complete details, see the `MCFLIRT Documentation. `_ @@ -1106,7 +1106,7 @@ class FNIRTOutputSpec(TraitedSpec): class FNIRT(FSLCommand): - """FSL FNIRT command for non-linear registration + """FSL FNIRT wrapper for non-linear registration For complete details, see the `FNIRT Documentation. `_ @@ -1305,7 +1305,7 @@ class ApplyWarpOutputSpec(TraitedSpec): class ApplyWarp(FSLCommand): - """FSL's applywarp command to apply the results of a FNIRT registration + """FSL's applywarp wrapper to apply the results of a FNIRT registration Examples -------- @@ -1389,7 +1389,7 @@ class SliceTimerOutputSpec(TraitedSpec): class SliceTimer(FSLCommand): - """FSL slicetimer command to perform slice timing correction + """FSL slicetimer wrapper to perform slice timing correction Examples -------- @@ -1476,7 +1476,7 @@ class SUSANOutputSpec(TraitedSpec): class SUSAN(FSLCommand): - """FSL SUSAN command to perform smoothing + """FSL SUSAN wrapper to perform smoothing For complete details, see the `SUSAN Documentation. `_ @@ -1870,7 +1870,7 @@ class PRELUDEOutputSpec(TraitedSpec): class PRELUDE(FSLCommand): - """FSL prelude command for phase unwrapping + """FSL prelude wrapper for phase unwrapping Examples -------- @@ -1980,7 +1980,7 @@ class FIRSTOutputSpec(TraitedSpec): class FIRST(FSLCommand): - """FSL run_first_all command for segmentation of subcortical volumes + """FSL run_first_all wrapper for segmentation of subcortical volumes http://www.fmrib.ox.ac.uk/fsl/first/index.html