fix: some lgtm errors (#2475)

Author: mgxd

nipype/algorithms/misc.py

@@ -1191,7 +1191,7 @@ def _list_outputs(self):
         return outputs
 
 
-def normalize_tpms(in_files, in_mask=None, out_files=[]):
+def normalize_tpms(in_files, in_mask=None, out_files=None):
     """
     Returns the input tissue probability maps (tpms, aka volume fractions)
     normalized to sum up 1.0 at each voxel within the mask.
@@ -1202,6 +1202,9 @@ def normalize_tpms(in_files, in_mask=None, out_files=[]):
 
     in_files = np.atleast_1d(in_files).tolist()
 
+    if not out_files:
+        out_files = []
+
     if len(out_files) != len(in_files):
         for i, finname in enumerate(in_files):
             fname, fext = op.splitext(op.basename(finname))

nipype/interfaces/ants/segmentation.py

@@ -150,7 +150,7 @@ def _format_arg(self, opt, spec, val):
             if isdefined(self.inputs.save_posteriors):
                 retval += ",%s" % self.inputs.output_posteriors_name_template
             return retval + "]"
-        return super(ANTSCommand, self)._format_arg(opt, spec, val)
+        return super(Atropos, self)._format_arg(opt, spec, val)
 
     def _run_interface(self, runtime, correct_return_codes=[0]):
         if self.inputs.initialization == "PriorProbabilityImages":
@@ -640,7 +640,7 @@ def _format_arg(self, opt, spec, val):
             _, _, ext = split_filename(self.inputs.segmentation_priors[0])
             retval = "-p nipype_priors/BrainSegmentationPrior%02d" + ext
             return retval
-        return super(ANTSCommand, self)._format_arg(opt, spec, val)
+        return super(CorticalThickness, self)._format_arg(opt, spec, val)
 
     def _run_interface(self, runtime, correct_return_codes=[0]):
         priors_directory = os.path.join(os.getcwd(), "nipype_priors")
@@ -1066,7 +1066,7 @@ def _format_arg(self, opt, spec, val):
                 assert len(val) == self.inputs.modalities * len(self.inputs.warped_label_images), \
                     "Number of intensity images and label maps must be the same {0}!={1}".format(
                     len(val), len(self.inputs.warped_label_images))
-            return super(ANTSCommand, self)._format_arg(opt, spec, val)
+            return super(JointFusion, self)._format_arg(opt, spec, val)
         return retval
 
     def _list_outputs(self):

nipype/interfaces/cmtk/nx.py

@@ -139,7 +139,7 @@ def average_networks(in_files, ntwk_res_file, group_id):
                     current = ntwk.edge[edge[0]][edge[1]]
                     data = add_dicts_by_key(current, data)
                 ntwk.add_edge(edge[0], edge[1], **data)
-            nodes = list(nodes())
+            nodes = list(tmp.nodes())
             for node in nodes:
                 data = {}
                 data = ntwk.nodes[node]

nipype/interfaces/fsl/preprocess.py

@@ -2025,7 +2025,7 @@ def _list_outputs(self):
         outputs['bvars'] = self._gen_mesh_names('bvars', structures)
         return outputs
 
-    def _gen_fname(self, name):
+    def _gen_fname(self, basename):
         path, outname, ext = split_filename(self.inputs.out_file)
 
         method = 'none'
@@ -2039,9 +2039,9 @@ def _gen_fname(self, name):
             thres = '%.4f' % self.inputs.method_as_numerical_threshold
             method = thres.replace('.', '')
 
-        if name == 'original_segmentations':
+        if basename == 'original_segmentations':
             return op.abspath('%s_all_%s_origsegs.nii.gz' % (outname, method))
-        if name == 'segmentation_file':
+        if basename == 'segmentation_file':
             return op.abspath('%s_all_%s_firstseg.nii.gz' % (outname, method))
 
         return None