Removed verbose input (only available in current master of ANTs). Will wait for next release to add.

Author: blakedewey

nipype/interfaces/ants/registration.py

@@ -380,9 +380,6 @@ class RegistrationInputSpec(ANTSCommandInputSpec):
     winsorize_lower_quantile = traits.Range(
         low=0.0, high=1.0, value=0.0, argstr='%s', usedefault=True, desc="The Lower quantile to clip image ranges")
 
-    # Verbose Output
-    verbose = traits.Bool(True, argstr='--verbose %d', desc='enable verbose logging', usedefault=True)
-
 
 class RegistrationOutputSpec(TraitedSpec):
     forward_transforms = traits.List(
@@ -444,7 +441,7 @@ class Registration(ANTSCommand):
 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 --transform SyN[ 0.25, 3.0, 0.0 ] \
 --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.025, 1.0 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.025, 1.0 ]  --write-composite-transform 1'
     >>> reg1.run()  # doctest: +SKIP
 
     >>> reg2 = copy.deepcopy(reg)
@@ -457,7 +454,7 @@ class Registration(ANTSCommand):
 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 --transform SyN[ 0.25, 3.0, 0.0 ] \
 --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 0.975 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 0.975 ]  --write-composite-transform 1'
 
     >>> reg3 = copy.deepcopy(reg)
     >>> reg3.inputs.winsorize_lower_quantile = 0.025
@@ -470,7 +467,7 @@ class Registration(ANTSCommand):
 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 --transform SyN[ 0.25, 3.0, 0.0 ] \
 --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.025, 0.975 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.025, 0.975 ]  --write-composite-transform 1'
 
     >>> reg3a = copy.deepcopy(reg)
     >>> reg3a.inputs.float = True
@@ -482,7 +479,7 @@ class Registration(ANTSCommand):
 --smoothing-sigmas 1.0x0.0vox --shrink-factors 2x1 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 \
 --transform SyN[ 0.25, 3.0, 0.0 ] --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] \
 --convergence [ 100x50x30, 1e-09, 20 ] --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 \
---use-estimate-learning-rate-once 1 --use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
+--use-estimate-learning-rate-once 1 --use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
 --write-composite-transform 1'
 
     >>> reg3b = copy.deepcopy(reg)
@@ -495,7 +492,7 @@ class Registration(ANTSCommand):
 --smoothing-sigmas 1.0x0.0vox --shrink-factors 2x1 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 \
 --transform SyN[ 0.25, 3.0, 0.0 ] --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] \
 --convergence [ 100x50x30, 1e-09, 20 ] --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 \
---use-estimate-learning-rate-once 1 --use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
+--use-estimate-learning-rate-once 1 --use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
 --write-composite-transform 1'
 
     >>> # Test collapse transforms flag
@@ -523,7 +520,7 @@ class Registration(ANTSCommand):
 --smoothing-sigmas 1.0x0.0vox --shrink-factors 2x1 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 \
 --transform SyN[ 0.25, 3.0, 0.0 ] --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] \
 --convergence [ 100x50x30, 1e-09, 20 ] --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 \
---use-estimate-learning-rate-once 1 --use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
+--use-estimate-learning-rate-once 1 --use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
 --write-composite-transform 1'
 
     >>> # Test collapse transforms flag
@@ -551,7 +548,7 @@ class Registration(ANTSCommand):
 --smoothing-sigmas 1.0x0.0vox --shrink-factors 2x1 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 \
 --transform SyN[ 0.25, 3.0, 0.0 ] --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] \
 --convergence [ 100x50x30, 1e-09, 20 ] --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 \
---use-estimate-learning-rate-once 1 --use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
+--use-estimate-learning-rate-once 1 --use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
 --write-composite-transform 0'
 
     >>> # Test multiple metrics per stage
@@ -572,7 +569,7 @@ class Registration(ANTSCommand):
 --metric Mattes[ fixed1.nii, moving1.nii, 0.5, 32, None, 0.05 ] \
 --metric CC[ fixed1.nii, moving1.nii, 0.5, 4, None, 0.1 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
 
     >>> # Test multiple inputs
     >>> reg6 = copy.deepcopy(reg5)
@@ -587,7 +584,7 @@ class Registration(ANTSCommand):
 --metric Mattes[ fixed1.nii, moving1.nii, 0.5, 32, None, 0.05 ] \
 --metric CC[ fixed2.nii, moving2.nii, 0.5, 4, None, 0.1 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
 
     >>> # Test Interpolation Parameters (BSpline)
     >>> reg7a = copy.deepcopy(reg)
@@ -601,7 +598,7 @@ class Registration(ANTSCommand):
 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 --transform SyN[ 0.25, 3.0, 0.0 ] \
 --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
 
     >>> # Test Interpolation Parameters (MultiLabel/Gaussian)
     >>> reg7b = copy.deepcopy(reg)
@@ -615,7 +612,7 @@ class Registration(ANTSCommand):
 --smoothing-sigmas 1.0x0.0vox --shrink-factors 2x1 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 \
 --transform SyN[ 0.25, 3.0, 0.0 ] --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] \
 --convergence [ 100x50x30, 1e-09, 20 ] --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 \
---use-estimate-learning-rate-once 1 --use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
+--use-estimate-learning-rate-once 1 --use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  \
 --write-composite-transform 1'
 
     >>> # Test Extended Transform Parameters
@@ -630,7 +627,7 @@ class Registration(ANTSCommand):
 --use-estimate-learning-rate-once 1 --use-histogram-matching 1 --transform BSplineSyN[ 0.25, 26, 0, 3 ] \
 --metric Mattes[ fixed1.nii, moving1.nii, 1, 32 ] --convergence [ 100x50x30, 1e-09, 20 ] \
 --smoothing-sigmas 2.0x1.0x0.0vox --shrink-factors 3x2x1 --use-estimate-learning-rate-once 1 \
---use-histogram-matching 1 --verbose 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
+--use-histogram-matching 1 --winsorize-image-intensities [ 0.0, 1.0 ]  --write-composite-transform 1'
     """
     DEF_SAMPLING_STRATEGY = 'None'
     """The default sampling strategy argument."""

nipype/interfaces/ants/resampling.py

@@ -253,8 +253,6 @@ class ApplyTransformsInputSpec(ANTSCommandInputSpec):
     print_out_composite_warp_file = traits.Bool(False, requires=["output_image"],
                                                 desc='output a composite warp file instead of a transformed image')
     float = traits.Bool(argstr='--float %d', default=False, desc='Use float instead of double for computations.')
-    # Verbose Output
-    verbose = traits.Bool(True, argstr='--verbose %d', desc='enable verbose logging', usedefault=True)
 
 
 class ApplyTransformsOutputSpec(TraitedSpec):
@@ -281,7 +279,7 @@ class ApplyTransforms(ANTSCommand):
     >>> at.cmdline
     'antsApplyTransforms --default-value 0 --dimensionality 3 --input moving1.nii --interpolation Linear \
 --output deformed_moving1.nii --reference-image fixed1.nii --transform [ trans.mat, 0 ] \
---transform [ ants_Warp.nii.gz, 0 ] --verbose 1'
+--transform [ ants_Warp.nii.gz, 0 ]'
 
     >>> at1 = ApplyTransforms()
     >>> at1.inputs.dimension = 3
@@ -296,7 +294,7 @@ class ApplyTransforms(ANTSCommand):
     >>> at1.cmdline
     'antsApplyTransforms --default-value 0 --dimensionality 3 --input moving1.nii --interpolation BSpline[ 5 ] \
 --output deformed_moving1.nii --reference-image fixed1.nii --transform [ trans.mat, 0 ] \
---transform [ ants_Warp.nii.gz, 0 ] --verbose 1'
+--transform [ ants_Warp.nii.gz, 0 ]'
 
 
     """

nipype/interfaces/ants/segmentation.py

@@ -52,8 +52,6 @@ class AtroposInputSpec(ANTSCommandInputSpec):
     save_posteriors = traits.Bool()
     output_posteriors_name_template = traits.Str('POSTERIOR_%02d.nii.gz',
                                                  usedefault=True)
-    # Verbose Output
-    verbose = traits.Bool(True, argstr='--verbose %d', desc='enable verbose logging', usedefault=True)
 
 
 class AtroposOutputSpec(TraitedSpec):
@@ -95,8 +93,7 @@ class Atropos(ANTSCommand):
     'Atropos --image-dimensionality 3 --icm [1,1] \
 --initialization PriorProbabilityImages[2,priors/priorProbImages%02d.nii,0.8,1e-07] --intensity-image structural.nii \
 --likelihood-model Gaussian --mask-image mask.nii --mrf [0.2,1x1x1] --convergence [5,1e-06] \
---output [structural_labeled.nii,POSTERIOR_%02d.nii.gz] --posterior-formulation Socrates[1] --use-random-seed 1 \
---verbose 1'
+--output [structural_labeled.nii,POSTERIOR_%02d.nii.gz] --posterior-formulation Socrates[1] --use-random-seed 1'
     """
     input_spec = AtroposInputSpec
     output_spec = AtroposOutputSpec

nipype/interfaces/ants/tests/test_auto_ApplyTransforms.py

@@ -48,9 +48,6 @@ def test_ApplyTransforms_inputs():
     transforms=dict(argstr='%s',
     mandatory=True,
     ),
-    verbose=dict(argstr='--verbose %d',
-    usedefault=True,
-    ),
     )
     inputs = ApplyTransforms.input_spec()
 

nipype/interfaces/ants/tests/test_auto_Atropos.py

@@ -64,9 +64,6 @@ def test_Atropos_inputs():
     use_random_seed=dict(argstr='--use-random-seed %d',
     usedefault=True,
     ),
-    verbose=dict(argstr='--verbose %d',
-    usedefault=True,
-    ),
     )
     inputs = Atropos.input_spec()
 

nipype/interfaces/ants/tests/test_auto_Registration.py

@@ -104,9 +104,6 @@ def test_Registration_inputs():
     use_estimate_learning_rate_once=dict(),
     use_histogram_matching=dict(usedefault=True,
     ),
-    verbose=dict(argstr='--verbose %d',
-    usedefault=True,
-    ),
     winsorize_lower_quantile=dict(argstr='%s',
     usedefault=True,
     ),