fix: make specs after black

Author: oesteban

nipype/interfaces/afni/tests/test_auto_Qwarp.py

@@ -68,9 +68,9 @@ def test_Qwarp_inputs():
         quiet=dict(argstr="-quiet", xor=["verb"],),
         resample=dict(argstr="-resample",),
         verb=dict(argstr="-verb", xor=["quiet"],),
-        wball=dict(argstr="-wball %s",),
+        wball=dict(argstr="-wball %s", xor=["wmask"],),
         weight=dict(argstr="-weight %s", extensions=None,),
-        wmask=dict(argstr="-wpass %s %f",),
+        wmask=dict(argstr="-wpass %s %f", xor=["wball"],),
         workhard=dict(argstr="-workhard", xor=["boxopt", "ballopt"],),
     )
     inputs = Qwarp.input_spec()

nipype/interfaces/afni/tests/test_auto_QwarpPlusMinus.py

@@ -77,9 +77,9 @@ def test_QwarpPlusMinus_inputs():
             new_name="in_file",
         ),
         verb=dict(argstr="-verb", xor=["quiet"],),
-        wball=dict(argstr="-wball %s",),
+        wball=dict(argstr="-wball %s", xor=["wmask"],),
         weight=dict(argstr="-weight %s", extensions=None,),
-        wmask=dict(argstr="-wpass %s %f",),
+        wmask=dict(argstr="-wpass %s %f", xor=["wball"],),
         workhard=dict(argstr="-workhard", xor=["boxopt", "ballopt"],),
     )
     inputs = QwarpPlusMinus.input_spec()

nipype/interfaces/ants/tests/test_auto_ConvertScalarImageToRGB.py

@@ -4,19 +4,19 @@
 
 def test_ConvertScalarImageToRGB_inputs():
     input_map = dict(
-        args=dict(argstr="%s"),
-        colormap=dict(argstr="%s", mandatory=True, position=4),
-        custom_color_map_file=dict(argstr="%s", position=5, usedefault=True),
-        dimension=dict(argstr="%d", mandatory=True, position=0, usedefault=True),
-        environ=dict(nohash=True, usedefault=True),
-        input_image=dict(argstr="%s", extensions=None, mandatory=True, position=1),
-        mask_image=dict(argstr="%s", extensions=None, position=3, usedefault=True),
-        maximum_RGB_output=dict(argstr="%d", position=9, usedefault=True),
-        maximum_input=dict(argstr="%d", mandatory=True, position=7),
-        minimum_RGB_output=dict(argstr="%d", position=8, usedefault=True),
-        minimum_input=dict(argstr="%d", mandatory=True, position=6),
-        num_threads=dict(nohash=True, usedefault=True),
-        output_image=dict(argstr="%s", position=2, usedefault=True),
+        args=dict(argstr="%s",),
+        colormap=dict(argstr="%s", mandatory=True, position=4,),
+        custom_color_map_file=dict(argstr="%s", position=5, usedefault=True,),
+        dimension=dict(argstr="%d", mandatory=True, position=0, usedefault=True,),
+        environ=dict(nohash=True, usedefault=True,),
+        input_image=dict(argstr="%s", extensions=None, mandatory=True, position=1,),
+        mask_image=dict(argstr="%s", extensions=None, position=3, usedefault=True,),
+        maximum_RGB_output=dict(argstr="%d", position=9, usedefault=True,),
+        maximum_input=dict(argstr="%d", mandatory=True, position=7,),
+        minimum_RGB_output=dict(argstr="%d", position=8, usedefault=True,),
+        minimum_input=dict(argstr="%d", mandatory=True, position=6,),
+        num_threads=dict(nohash=True, usedefault=True,),
+        output_image=dict(argstr="%s", position=2, usedefault=True,),
     )
     inputs = ConvertScalarImageToRGB.input_spec()
 
@@ -26,7 +26,7 @@ def test_ConvertScalarImageToRGB_inputs():
 
 
 def test_ConvertScalarImageToRGB_outputs():
-    output_map = dict(output_image=dict(extensions=None))
+    output_map = dict(output_image=dict(extensions=None,),)
     outputs = ConvertScalarImageToRGB.output_spec()
 
     for key, metadata in list(output_map.items()):

nipype/interfaces/freesurfer/tests/test_auto_SmoothTessellation.py

@@ -4,25 +4,25 @@
 
 def test_SmoothTessellation_inputs():
     input_map = dict(
-        args=dict(argstr="%s"),
-        curvature_averaging_iterations=dict(argstr="-a %d"),
-        disable_estimates=dict(argstr="-nw"),
-        environ=dict(nohash=True, usedefault=True),
-        gaussian_curvature_norm_steps=dict(argstr="%d"),
-        gaussian_curvature_smoothing_steps=dict(argstr=" %d"),
+        args=dict(argstr="%s",),
+        curvature_averaging_iterations=dict(argstr="-a %d",),
+        disable_estimates=dict(argstr="-nw",),
+        environ=dict(nohash=True, usedefault=True,),
+        gaussian_curvature_norm_steps=dict(argstr="%d",),
+        gaussian_curvature_smoothing_steps=dict(argstr=" %d",),
         in_file=dict(
-            argstr="%s", copyfile=True, extensions=None, mandatory=True, position=-2
+            argstr="%s", copyfile=True, extensions=None, mandatory=True, position=-2,
         ),
-        normalize_area=dict(argstr="-area"),
-        out_area_file=dict(argstr="-b %s", extensions=None),
-        out_curvature_file=dict(argstr="-c %s", extensions=None),
-        out_file=dict(argstr="%s", extensions=None, genfile=True, position=-1),
-        seed=dict(argstr="-seed %d"),
-        smoothing_iterations=dict(argstr="-n %d"),
-        snapshot_writing_iterations=dict(argstr="-w %d"),
+        normalize_area=dict(argstr="-area",),
+        out_area_file=dict(argstr="-b %s", extensions=None,),
+        out_curvature_file=dict(argstr="-c %s", extensions=None,),
+        out_file=dict(argstr="%s", extensions=None, genfile=True, position=-1,),
+        seed=dict(argstr="-seed %d",),
+        smoothing_iterations=dict(argstr="-n %d",),
+        snapshot_writing_iterations=dict(argstr="-w %d",),
         subjects_dir=dict(),
-        use_gaussian_curvature_smoothing=dict(argstr="-g"),
-        use_momentum=dict(argstr="-m"),
+        use_gaussian_curvature_smoothing=dict(argstr="-g",),
+        use_momentum=dict(argstr="-m",),
     )
     inputs = SmoothTessellation.input_spec()
 
@@ -32,7 +32,7 @@ def test_SmoothTessellation_inputs():
 
 
 def test_SmoothTessellation_outputs():
-    output_map = dict(surface=dict(extensions=None))
+    output_map = dict(surface=dict(extensions=None,),)
     outputs = SmoothTessellation.output_spec()
 
     for key, metadata in list(output_map.items()):