Removed redundant _format_xarray from ANTSCommand and replaced other join functions with _format_xarray

Author: blakedewey

nipype/interfaces/ants/base.py

@@ -83,9 +83,4 @@ def set_default_num_threads(cls, num_threads):
         type for any existing instances.  For these, assign the
         <instance>.inputs.num_threads
         """
-        cls._num_threads = num_threads
-
-    def _format_xarray(self, val):
-        """ Convienence method for converting [1,2,3] -> 1x2x3 """
-        val = 'x'.join([str(x) for x in val])
-        return val
+        cls._num_threads = num_threads

nipype/interfaces/ants/registration.py

@@ -173,17 +173,15 @@ def _regularization_constructor(self):
                                                       self.inputs.regularization_deformation_field_sigma)
 
     def _affine_gradient_descent_option_constructor(self):
-        retval = ['--affine-gradient-descent-option']
         values = self.inputs.affine_gradient_descent_option
         defaults = [0.1, 0.5, 1.e-4, 1.e-4]
         for ii in range(len(defaults)):
             try:
                 defaults[ii] = values[ii]
             except IndexError:
                 break
-        stringList = [('%g' % defaults[index]) for index in range(4)]
-        parameters = 'x'.join(stringList)
-        retval.append(parameters)
+        parameters = self._format_xarray([('%g' % defaults[index]) for index in range(4)])
+        retval = ['--affine-gradient-descent-option', parameters]
         return ' '.join(retval)
 
     def _format_arg(self, opt, spec, val):
@@ -653,14 +651,13 @@ def _formatRegistration(self):
             retval.append('--convergence %s' % self._formatConvergence(ii))
             if isdefined(self.inputs.sigma_units):
                 retval.append('--smoothing-sigmas %s%s' %
-                              (self._antsJoinList(self.inputs.smoothing_sigmas[
-                                  ii]),
+                              (self._format_xarray(self.inputs.smoothing_sigmas[ii]),
                                self.inputs.sigma_units[ii]))
             else:
                 retval.append('--smoothing-sigmas %s' %
-                              self._antsJoinList(self.inputs.smoothing_sigmas[ii]))
+                              self._format_xarray(self.inputs.smoothing_sigmas[ii]))
             retval.append('--shrink-factors %s' %
-                          self._antsJoinList(self.inputs.shrink_factors[ii]))
+                          self._format_xarray(self.inputs.shrink_factors[ii]))
             if isdefined(self.inputs.use_estimate_learning_rate_once):
                 retval.append('--use-estimate-learning-rate-once %d' %
                               self.inputs.use_estimate_learning_rate_once[ii])
@@ -674,9 +671,6 @@ def _formatRegistration(self):
                 retval.append('--use-histogram-matching %d' % histval)
         return " ".join(retval)
 
-    def _antsJoinList(self, antsList):
-        return "x".join([str(i) for i in antsList])
-
     def _get_outputfilenames(self, inverse=False):
         output_filename = None
         if not inverse:
@@ -699,8 +693,7 @@ def _get_outputfilenames(self, inverse=False):
         return inv_output_filename
 
     def _formatConvergence(self, ii):
-        convergence_iter = self._antsJoinList(
-            self.inputs.number_of_iterations[ii])
+        convergence_iter = self._format_xarray(self.inputs.number_of_iterations[ii])
         if len(self.inputs.convergence_threshold) > ii:
             convergence_value = self.inputs.convergence_threshold[ii]
         else:

nipype/interfaces/ants/segmentation.py

@@ -110,8 +110,7 @@ def _format_arg(self, opt, spec, val):
         if opt == 'mrf_smoothing_factor':
             retval = "--mrf [%g" % val
             if isdefined(self.inputs.mrf_radius):
-                retval += ",%s" % 'x'.join([str(s)
-                                            for s in self.inputs.mrf_radius])
+                retval += ",%s" % self._format_xarray([str(s) for s in self.inputs.mrf_radius])
             return retval + "]"
         if opt == "icm_use_synchronous_update":
             retval = "--icm [%d" % val
@@ -354,10 +353,10 @@ def _format_arg(self, name, trait_spec, value):
 
         if name == 'n_iterations':
             if isdefined(self.inputs.convergence_threshold):
-                newval = '[ %s, %g ]' % ('x'.join([str(elt) for elt in value]),
+                newval = '[ %s, %g ]' % (self._format_xarray([str(elt) for elt in value]),
                                          self.inputs.convergence_threshold)
             else:
-                newval = '[ %s ]' % 'x'.join([str(elt) for elt in value])
+                newval = '[ %s ]' % self._format_xarray([str(elt) for elt in value])
             return trait_spec.argstr % newval
 
         return super(N4BiasFieldCorrection,