STY: black [ignore-rev]

Author: effigies

nipype/algorithms/confounds.py

@@ -1435,7 +1435,7 @@ def compute_noise_components(
             else:
                 u = np.full((M.shape[0], 1), np.nan, dtype=np.float32)
 
-        variance_explained = (s ** 2) / np.sum(s ** 2)
+        variance_explained = (s**2) / np.sum(s**2)
         cumulative_variance_explained = np.cumsum(variance_explained)
 
         num_components = int(components_criterion)

nipype/algorithms/icc.py

@@ -116,7 +116,7 @@ def ICC_rep_anova(Y):
     # Sum Square Error
     predicted_Y = dot(dot(dot(X, pinv(dot(X.T, X))), X.T), Y.flatten("F"))
     residuals = Y.flatten("F") - predicted_Y
-    SSE = (residuals ** 2).sum()
+    SSE = (residuals**2).sum()
 
     residuals.shape = Y.shape
 

nipype/algorithms/metrics.py

@@ -337,7 +337,7 @@ def _run_interface(self, runtime):
         if self.inputs.weighting != "none":
             weights = weights / np.array(volumes1)
             if self.inputs.weighting == "squared_vol":
-                weights = weights ** 2
+                weights = weights**2
         weights = weights / np.sum(weights)
 
         both_data = np.zeros(data1.shape)
@@ -500,7 +500,7 @@ def _run_interface(self, runtime):
             volumes = np.sum((refdata + tstdata) > 0, axis=1).reshape((-1, ncomp))
             weights = 1.0 / volumes
             if self.inputs.weighting == "squared_vol":
-                weights = weights ** 2
+                weights = weights**2
 
         weights = weights / np.sum(weights)
         dices = 2.0 * jaccards / (jaccards + 1.0)
@@ -591,7 +591,7 @@ def _run_interface(self, runtime):
 
         # Scale the difference
         if self.inputs.metric == "sqeuclidean":
-            errvector = diffvector ** 2
+            errvector = diffvector**2
             if comps > 1:
                 errvector = np.sum(errvector, axis=1)
             else:

nipype/algorithms/tests/test_ErrorMap.py

@@ -75,4 +75,4 @@ def test_errormap(tmpdir):
 
     errmap.inputs.metric = "euclidean"
     result = errmap.run()
-    assert result.outputs.distance == np.float32(1.25 * (2 ** 0.5))
+    assert result.outputs.distance == np.float32(1.25 * (2**0.5))

nipype/interfaces/ants/registration.py

@@ -1293,16 +1293,12 @@ def _format_arg(self, opt, spec, val):
                 do_center_of_mass_init,
             )
         elif opt == "interpolation":
-            if (
-                self.inputs.interpolation
-                in [
-                    "BSpline",
-                    "MultiLabel",
-                    "Gaussian",
-                    "GenericLabel",
-                ]
-                and isdefined(self.inputs.interpolation_parameters)
-            ):
+            if self.inputs.interpolation in [
+                "BSpline",
+                "MultiLabel",
+                "Gaussian",
+                "GenericLabel",
+            ] and isdefined(self.inputs.interpolation_parameters):
                 return "--interpolation %s[ %s ]" % (
                     self.inputs.interpolation,
                     ", ".join(
@@ -1595,14 +1591,17 @@ class MeasureImageSimilarity(ANTSCommand):
     output_spec = MeasureImageSimilarityOutputSpec
 
     def _metric_constructor(self):
-        retval = '--metric {metric}["{fixed_image}","{moving_image}",{metric_weight},' "{radius_or_number_of_bins},{sampling_strategy},{sampling_percentage}]".format(
-            metric=self.inputs.metric,
-            fixed_image=self.inputs.fixed_image,
-            moving_image=self.inputs.moving_image,
-            metric_weight=self.inputs.metric_weight,
-            radius_or_number_of_bins=self.inputs.radius_or_number_of_bins,
-            sampling_strategy=self.inputs.sampling_strategy,
-            sampling_percentage=self.inputs.sampling_percentage,
+        retval = (
+            '--metric {metric}["{fixed_image}","{moving_image}",{metric_weight},'
+            "{radius_or_number_of_bins},{sampling_strategy},{sampling_percentage}]".format(
+                metric=self.inputs.metric,
+                fixed_image=self.inputs.fixed_image,
+                moving_image=self.inputs.moving_image,
+                metric_weight=self.inputs.metric_weight,
+                radius_or_number_of_bins=self.inputs.radius_or_number_of_bins,
+                sampling_strategy=self.inputs.sampling_strategy,
+                sampling_percentage=self.inputs.sampling_percentage,
+            )
         )
         return retval
 

nipype/interfaces/ants/resampling.py

@@ -504,15 +504,11 @@ def _format_arg(self, opt, spec, val):
         elif opt == "transforms":
             return self._get_transform_filenames()
         elif opt == "interpolation":
-            if (
-                self.inputs.interpolation
-                in [
-                    "BSpline",
-                    "MultiLabel",
-                    "Gaussian",
-                ]
-                and isdefined(self.inputs.interpolation_parameters)
-            ):
+            if self.inputs.interpolation in [
+                "BSpline",
+                "MultiLabel",
+                "Gaussian",
+            ] and isdefined(self.inputs.interpolation_parameters):
                 return "--interpolation %s[ %s ]" % (
                     self.inputs.interpolation,
                     ", ".join(

nipype/interfaces/brainsuite/brainsuite.py

@@ -260,12 +260,15 @@ def _format_arg(self, name, spec, value):
                 % {"low": "--low", "medium": "--medium", "high": "--high"}[value]
             )
         if name == "intermediate_file_type":
-            return spec.argstr % {
-                "analyze": "--analyze",
-                "nifti": "--nifti",
-                "gzippedAnalyze": "--analyzegz",
-                "gzippedNifti": "--niftigz",
-            }[value]
+            return (
+                spec.argstr
+                % {
+                    "analyze": "--analyze",
+                    "nifti": "--nifti",
+                    "gzippedAnalyze": "--analyzegz",
+                    "gzippedNifti": "--niftigz",
+                }[value]
+            )
 
         return super(Bfc, self)._format_arg(name, spec, value)
 
@@ -772,11 +775,14 @@ def _format_arg(self, name, spec, value):
             return ""  # blank argstr
         if name == "specialTessellation":
             threshold = self.inputs.tessellationThreshold
-            return spec.argstr % {
-                "greater_than": "".join(("-gt %f" % threshold)),
-                "less_than": "".join(("-lt %f" % threshold)),
-                "equal_to": "".join(("-eq %f" % threshold)),
-            }[value]
+            return (
+                spec.argstr
+                % {
+                    "greater_than": "".join(("-gt %f" % threshold)),
+                    "less_than": "".join(("-lt %f" % threshold)),
+                    "equal_to": "".join(("-eq %f" % threshold)),
+                }[value]
+            )
         return super(Dfs, self)._format_arg(name, spec, value)
 
     def _gen_filename(self, name):

nipype/interfaces/cmtk/parcellation.py

@@ -303,13 +303,16 @@ def create_annot_label(subject_id, subjects_dir, fs_dir, parcellation_name):
         op.join(output_dir, "regenerated_lh_60", "lh.corpuscallosum.label"), lhco
     )
 
-    mri_cmd = """mri_label2vol --label "%s" --label "%s" --label "%s" --label "%s" --temp "%s" --o  "%s" --identity """ % (
-        rhun,
-        lhun,
-        rhco,
-        lhco,
-        op.join(op.join(subjects_dir, subject_id), "mri", "orig.mgz"),
-        op.join(fs_label_dir, "cc_unknown.nii.gz"),
+    mri_cmd = (
+        """mri_label2vol --label "%s" --label "%s" --label "%s" --label "%s" --temp "%s" --o  "%s" --identity """
+        % (
+            rhun,
+            lhun,
+            rhco,
+            lhco,
+            op.join(op.join(subjects_dir, subject_id), "mri", "orig.mgz"),
+            op.join(fs_label_dir, "cc_unknown.nii.gz"),
+        )
     )
     runCmd(mri_cmd, log)
     runCmd("mris_volmask %s" % subject_id, log)

nipype/interfaces/freesurfer/preprocess.py

@@ -1883,16 +1883,12 @@ def _list_outputs(self):
         return outputs
 
     def _format_arg(self, name, spec, value):
-        if (
-            name
-            in (
-                "registered_file",
-                "out_fsl_file",
-                "out_lta_file",
-                "init_cost_file",
-            )
-            and isinstance(value, bool)
-        ):
+        if name in (
+            "registered_file",
+            "out_fsl_file",
+            "out_lta_file",
+            "init_cost_file",
+        ) and isinstance(value, bool):
             value = self._list_outputs()[name]
         return super(BBRegister, self)._format_arg(name, spec, value)
 

nipype/interfaces/fsl/base.py

@@ -51,7 +51,6 @@ class Info(PackageInfo):
     >>> Info.version()  # doctest: +SKIP
     >>> Info.output_type()  # doctest: +SKIP
 
-
     """
 
     ftypes = {

nipype/interfaces/niftyseg/label_fusion.py

@@ -168,19 +168,15 @@ class LabelFusion(NiftySegCommand):
     def _format_arg(self, opt, spec, val):
         """Convert input to appropriate format for seg_maths."""
         # Remove options if not STAPLE or STEPS as fusion type:
-        if (
-            opt
-            in [
-                "proportion",
-                "prob_update_flag",
-                "set_pq",
-                "mrf_value",
-                "max_iter",
-                "unc_thresh",
-                "conv",
-            ]
-            and self.inputs.classifier_type not in ["STAPLE", "STEPS"]
-        ):
+        if opt in [
+            "proportion",
+            "prob_update_flag",
+            "set_pq",
+            "mrf_value",
+            "max_iter",
+            "unc_thresh",
+            "conv",
+        ] and self.inputs.classifier_type not in ["STAPLE", "STEPS"]:
             return ""
 
         if opt == "sm_ranking":

nipype/interfaces/slicer/generate_classes.py

@@ -367,18 +367,14 @@ def generate_class(
                     param.getElementsByTagName("channel")[0].firstChild.nodeValue
                     == "input"
                 ):
-                    if (
-                        param.nodeName
-                        in [
-                            "file",
-                            "directory",
-                            "image",
-                            "geometry",
-                            "transform",
-                            "table",
-                        ]
-                        and type not in ["InputMultiPath", "traits.List"]
-                    ):
+                    if param.nodeName in [
+                        "file",
+                        "directory",
+                        "image",
+                        "geometry",
+                        "transform",
+                        "table",
+                    ] and type not in ["InputMultiPath", "traits.List"]:
                         traitsParams["exists"] = True
                     inputTraits.append(
                         "%s = %s(%s%s)"

nipype/pipeline/engine/tests/test_join.py

@@ -623,7 +623,7 @@ def test_name_prefix_join(tmpdir):
     tmpdir.chdir()
 
     def sq(x):
-        return x ** 2
+        return x**2
 
     wf = pe.Workflow("wf", base_dir=tmpdir.strpath)
     square = pe.Node(Function(function=sq), name="square")
@@ -642,7 +642,7 @@ def test_join_nestediters(tmpdir):
     tmpdir.chdir()
 
     def exponent(x, p):
-        return x ** p
+        return x**p
 
     wf = pe.Workflow("wf", base_dir=tmpdir.strpath)
 

nipype/utils/profiler.py

@@ -21,7 +21,7 @@
 resource_monitor = config.resource_monitor
 
 # Init variables
-_MB = 1024.0 ** 2
+_MB = 1024.0**2
 
 
 class ResourceMonitorMock:
@@ -207,10 +207,10 @@ def get_system_total_memory_gb():
             meminfo_lines = f_in.readlines()
             mem_total_line = [line for line in meminfo_lines if "MemTotal" in line][0]
             mem_total = float(mem_total_line.split()[1])
-            memory_gb = mem_total / (1024.0 ** 2)
+            memory_gb = mem_total / (1024.0**2)
     elif "darwin" in sys.platform:
         mem_str = os.popen("sysctl hw.memsize").read().strip().split(" ")[-1]
-        memory_gb = float(mem_str) / (1024.0 ** 3)
+        memory_gb = float(mem_str) / (1024.0**3)
     else:
         err_msg = "System platform: %s is not supported"
         raise Exception(err_msg)
@@ -387,7 +387,7 @@ def _use_resources(n_procs, mem_gb):
     # Getsize of one character string
     BSIZE = sys.getsizeof("  ") - sys.getsizeof(" ")
     BOFFSET = sys.getsizeof("")
-    _GB = 1024.0 ** 3
+    _GB = 1024.0**3
 
     def _use_gb_ram(mem_gb):
         """A test function to consume mem_gb GB of RAM"""

nipype/utils/tests/test_functions.py

@@ -4,12 +4,12 @@
 
 
 def _func1(x):
-    return x ** 3
+    return x**3
 
 
 def test_func_to_str():
     def func1(x):
-        return x ** 2
+        return x**2
 
     # Should be ok with both functions!
     for f in _func1, func1: