Merge pull request #21 from chrisfilo/fix/ants

Fix/ants

Author: satra

examples/smri_ants_registration.py

@@ -69,6 +69,7 @@
 reg.inputs.convergence_threshold = [1.e-8, 1.e-9]
 reg.inputs.convergence_window_size = [20]*2
 reg.inputs.smoothing_sigmas = [[1,0], [2,1,0]]
+reg.inputs.sigma_units = ['vox'] * 2
 reg.inputs.shrink_factors = [[2,1], [3,2,1]]
 reg.inputs.use_estimate_learning_rate_once = [True, True]
 reg.inputs.use_histogram_matching = [True, True] # This is the default

nipype/interfaces/ants/registration.py

@@ -261,11 +261,11 @@ class RegistrationInputSpec(ANTSCommandInputSpec):
                                                                   traits.Float())))
     # Convergence flags
     number_of_iterations = traits.List(traits.List(traits.Int()))
-    smoothing_sigmas = traits.List(traits.List(traits.Int()))
+    smoothing_sigmas = traits.List(traits.List(traits.Int()), mandatory=True)
     sigma_units = traits.List(traits.Enum('mm', 'vox'),
                               requires=['smoothing_sigmas'],
-                              desc="units for smoothing sigmas")
-    shrink_factors = traits.List(traits.List(traits.Int()))
+                              desc="units for smoothing sigmas", mandatory=True)
+    shrink_factors = traits.List(traits.List(traits.Int()), mandatory=True)
     convergence_threshold = traits.List(trait=traits.Float(), value=[1e-6], minlen=1, requires=['number_of_iterations'], usedefault=True)
     convergence_window_size = traits.List(trait=traits.Int(), value=[10], minlen=1, requires=['convergence_threshold'], usedefault=True)
     # Output flags

nipype/workflows/smri/ants/antsRegistrationBuildTemplate.py

@@ -197,6 +197,7 @@ def antsRegistrationTemplateBuildSingleIterationWF(iterationPhasePrefix=''):
     BeginANTS.inputs.use_estimate_learning_rate_once = [False,       False]
     BeginANTS.inputs.shrink_factors =           [[3,2,1],            [3,2,1]]
     BeginANTS.inputs.smoothing_sigmas =         [[3,2,0],            [3,2,0]]
+    BeginANTS.inputs.sigma_units =         ["vox"]*2
 
     GetMovingImagesNode = pe.Node(interface=util.Function(function=GetMovingImages,
                                       input_names=['ListOfImagesDictionaries','registrationImageTypes','interpolationMapping'],