Use Black

.git-blame-ignore-revs

@@ -6,3 +6,6 @@ f4978b11499e499cc006c417b3bf0ccf245ca72c
 
 # Adopt ruff and cython-lint (gh-6729)
 b22ecff8d52eeb59e5d1d2e7fcc7962b4a0a84ce
+
+# Adopt black (gh-7197)
+659af605da92732b57b7862f78fe77f3fd161fd0

.pre-commit-config.yaml

@@ -26,14 +26,19 @@ repos:
     rev: v0.0.292 # v0.0.261
     hooks:
       - id: ruff
-        args: [--fix, --exit-non-zero-on-fix]
+        args: [--fix, --show-fixes, --exit-non-zero-on-fix]
 
   - repo: https://github.com/MarcoGorelli/cython-lint
     rev: v0.15.0 # v0.15.0
     hooks:
       - id: cython-lint
         args: [--no-pycodestyle, --max-line-length=88]
 
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 23.9.1
+    hooks:
+      - id: black
+
   - repo: local
     hooks:
       - id: generate_requirements.py

.spin/cmds.py

@@ -30,10 +30,12 @@
 @click.option(
     "--install-deps/--no-install-deps",
     default=False,
-    help="Install dependencies before building"
+    help="Install dependencies before building",
 )
 @click.pass_context
-def docs(ctx, sphinx_target, clean, first_build, jobs, sphinx_gallery_plot, install_deps):
+def docs(
+    ctx, sphinx_target, clean, first_build, jobs, sphinx_gallery_plot, install_deps
+):
     """📖 Build documentation
 
     By default, SPHINXOPTS="-W", raising errors on warnings.
@@ -77,14 +79,11 @@ def asv(asv_args):
 
 @click.command()
 def sdist():
-    """📦 Build a source distribution in `dist/`.
-    """
+    """📦 Build a source distribution in `dist/`."""
     util.run(['python', '-m', 'build', '.', '--sdist'])
 
 
-@click.command(context_settings={
-    'ignore_unknown_options': True
-})
+@click.command(context_settings={'ignore_unknown_options': True})
 @click.argument("ipython_args", metavar='', nargs=-1)
 @click.pass_context
 def ipython(ctx, ipython_args):
@@ -101,6 +100,8 @@ def ipython(ctx, ipython_args):
         r"import skimage as ski; "
         r"print(f'\nPreimported scikit-image {ski.__version__} as ski')"
     )
-    ctx.params['ipython_args'] = (f"--TerminalIPythonApp.exec_lines={preimport}",) + ipython_args
+    ctx.params['ipython_args'] = (
+        f"--TerminalIPythonApp.exec_lines={preimport}",
+    ) + ipython_args
 
     ctx.forward(meson.ipython)

benchmarks/benchmark_exposure.py

@@ -11,6 +11,7 @@
 
 class ExposureSuite:
     """Benchmark for exposure routines in scikit-image."""
+
     def setup(self):
         self.image_u8 = data.moon()
         self.image = img_as_float(self.image_u8)
@@ -29,8 +30,8 @@ def time_equalize_adapthist(self):
         exposure.equalize_adapthist(self.image, clip_limit=0.03)
 
     def time_rescale_intensity(self):
-        exposure.rescale_intensity(self.image,
-                                            in_range=(self.p2, self.p98))
+        exposure.rescale_intensity(self.image, in_range=(self.p2, self.p98))
+
     def time_histogram(self):
         # Running it 10 times to achieve significant performance time.
         for i in range(10):
@@ -42,7 +43,6 @@ def time_gamma_adjust_u8(self):
 
 
 class MatchHistogramsSuite:
-
     param_names = ["shape", "dtype", "multichannel"]
     params = [
         ((64, 64), (256, 256), (1024, 1024)),
@@ -60,13 +60,13 @@ def _tile_to_shape(self, image, shape, multichannel):
         return image[sl]
 
     """Benchmark for exposure routines in scikit-image."""
+
     def setup(self, shape, dtype, multichannel):
         self.image = data.moon().astype(dtype, copy=False)
         self.reference = data.camera().astype(dtype, copy=False)
 
         self.image = self._tile_to_shape(self.image, shape, multichannel)
-        self.reference = self._tile_to_shape(self.reference, shape,
-                                             multichannel)
+        self.reference = self._tile_to_shape(self.reference, shape, multichannel)
         channel_axis = -1 if multichannel else None
         self.kwargs = {'channel_axis': channel_axis}
 

benchmarks/benchmark_feature.py

@@ -6,22 +6,24 @@
 
 class FeatureSuite:
     """Benchmark for feature routines in scikit-image."""
+
     def setup(self):
         # Use a real-world image for more realistic features, but tile it to
         # get a larger size for the benchmark.
         self.image = np.tile(color.rgb2gray(data.astronaut()), (4, 4))
         self.image_ubyte = util.img_as_ubyte(self.image)
         self.keypoints = feature.corner_peaks(
-                self.image, min_distance=5, threshold_rel=0.1
-                )
+            self.image, min_distance=5, threshold_rel=0.1
+        )
 
     def time_canny(self):
         feature.canny(self.image)
 
     def time_glcm(self):
         pi = np.pi
-        feature.greycomatrix(self.image_ubyte, distances=[1, 2],
-                             angles=[0, pi/4, pi/2, 3*pi/4])
+        feature.greycomatrix(
+            self.image_ubyte, distances=[1, 2], angles=[0, pi / 4, pi / 2, 3 * pi / 4]
+        )
 
     def time_brief(self):
         extractor = feature.BRIEF()

benchmarks/benchmark_filters.py

@@ -8,6 +8,7 @@
 
 class FiltersSuite:
     """Benchmark for filter routines in scikit-image."""
+
     def setup(self):
         self.image = np.random.random((4000, 4000))
         self.image[:2000, :2000] += 1
@@ -19,6 +20,7 @@ def time_sobel(self):
 
 class FiltersSobel3D:
     """Benchmark for 3d sobel filters."""
+
     def setup(self):
         try:
             filters.sobel(np.ones((8, 8, 8)))
@@ -32,8 +34,10 @@ def time_sobel_3d(self):
 
 class MultiOtsu:
     """Benchmarks for MultiOtsu threshold."""
+
     param_names = ['classes']
     params = [3, 4, 5]
+
     def setup(self, *args):
         self.image = data.camera()
 
@@ -63,7 +67,6 @@ def peakmem_threshold_multiotsu(self, classes):
 class ThresholdSauvolaSuite:
     """Benchmark for transform routines in scikit-image."""
 
-
     def setup(self):
         self.image = np.zeros((2000, 2000), dtype=np.uint8)
         self.image3D = np.zeros((30, 300, 300), dtype=np.uint8)

benchmarks/benchmark_graph.py

@@ -8,20 +8,21 @@
 
 class GraphSuite:
     """Benchmark for pixel graph routines in scikit-image."""
+
     def setup(self):
         retina = color.rgb2gray(data.retina())
         t0, _ = filters.threshold_multiotsu(retina, classes=3)
-        mask = (retina > t0)
+        mask = retina > t0
         vessels = filters.sato(retina, sigmas=range(1, 10)) * mask
         thresholded = filters.apply_hysteresis_threshold(vessels, 0.01, 0.03)
         labeled = ndi.label(thresholded)[0]
         largest_nonzero_label = np.argmax(np.bincount(labeled[labeled > 0]))
-        binary = (labeled == largest_nonzero_label)
+        binary = labeled == largest_nonzero_label
         self.skeleton = morphology.skeletonize(binary)
 
         labeled2 = ndi.label(thresholded[::2, ::2])[0]
         largest_nonzero_label2 = np.argmax(np.bincount(labeled2[labeled2 > 0]))
-        binary2 = (labeled2 == largest_nonzero_label2)
+        binary2 = labeled2 == largest_nonzero_label2
         small_skeleton = morphology.skeletonize(binary2)
         self.g, self.n = graph.pixel_graph(small_skeleton, connectivity=2)
 

benchmarks/benchmark_import_time.py

@@ -1,8 +1,10 @@
 from subprocess import run, PIPE
 from sys import executable
 
+
 class ImportSuite:
     """Benchmark the time it takes to import various modules"""
+
     params = [
         'numpy',
         'skimage',
@@ -12,9 +14,14 @@ class ImportSuite:
         'skimage.io',
     ]
     param_names = ["package_name"]
+
     def setup(self, package_name):
         pass
 
     def time_import(self, package_name):
-        run(executable + ' -c "import ' + package_name + '"',
-            capture_output=True, stdin=PIPE, shell=True)
+        run(
+            executable + ' -c "import ' + package_name + '"',
+            capture_output=True,
+            stdin=PIPE,
+            shell=True,
+        )

benchmarks/benchmark_interpolation.py

@@ -5,17 +5,17 @@
 
 
 class InterpolationResize:
-
     param_names = ['new_shape', 'order', 'mode', 'dtype', 'anti_aliasing']
     params = [
         ((500, 800), (2000, 4000), (80, 80, 80), (150, 150, 150)),  # new_shape
-        (0, 1, 3, 5),    # order
+        (0, 1, 3, 5),  # order
         ('symmetric',),  # mode
-        (np.float64, ),  # dtype
-        (True,),         # anti_aliasing
+        (np.float64,),  # dtype
+        (True,),  # anti_aliasing
     ]
 
     """Benchmark for filter routines in scikit-image."""
+
     def setup(self, new_shape, order, mode, dtype, anti_aliasing):
         ndim = len(new_shape)
         if ndim == 2:
@@ -25,17 +25,20 @@ def setup(self, new_shape, order, mode, dtype, anti_aliasing):
         self.image = image.astype(dtype, copy=False)
 
     def time_resize(self, new_shape, order, mode, dtype, anti_aliasing):
-        transform.resize(self.image, new_shape, order=order, mode=mode,
-                         anti_aliasing=anti_aliasing)
+        transform.resize(
+            self.image, new_shape, order=order, mode=mode, anti_aliasing=anti_aliasing
+        )
 
     def time_rescale(self, new_shape, order, mode, dtype, anti_aliasing):
         scale = tuple(s2 / s1 for s2, s1 in zip(new_shape, self.image.shape))
-        transform.rescale(self.image, scale, order=order, mode=mode,
-                          anti_aliasing=anti_aliasing)
+        transform.rescale(
+            self.image, scale, order=order, mode=mode, anti_aliasing=anti_aliasing
+        )
 
     def peakmem_resize(self, new_shape, order, mode, dtype, anti_aliasing):
-        transform.resize(self.image, new_shape, order=order, mode=mode,
-                         anti_aliasing=anti_aliasing)
+        transform.resize(
+            self.image, new_shape, order=order, mode=mode, anti_aliasing=anti_aliasing
+        )
 
     def peakmem_reference(self, *args):
         """Provide reference for memory measurement with empty benchmark.

benchmarks/benchmark_measure.py

@@ -1,6 +1,7 @@
 import numpy as np
 
 from skimage import data, filters, measure
+
 try:
     from skimage.measure._regionprops import PROP_VALS
 except ImportError:
@@ -17,7 +18,6 @@ def init_regionprops_data():
 
 
 class RegionpropsTableIndividual:
-
     param_names = ['prop']
     params = sorted(list(PROP_VALS))
 
@@ -30,14 +30,14 @@ def setup(self, prop):
         self.label_image, self.intensity_image = init_regionprops_data()
 
     def time_single_region_property(self, prop):
-        measure.regionprops_table(self.label_image, self.intensity_image,
-                                  properties=[prop], cache=True)
+        measure.regionprops_table(
+            self.label_image, self.intensity_image, properties=[prop], cache=True
+        )
 
     # omit peakmem tests to save time (memory usage was minimal)
 
 
 class RegionpropsTableAll:
-
     param_names = ['cache']
     params = (False, True)
 
@@ -50,19 +50,23 @@ def setup(self, cache):
         self.label_image, self.intensity_image = init_regionprops_data()
 
     def time_regionprops_table_all(self, cache):
-        measure.regionprops_table(self.label_image, self.intensity_image,
-                                  properties=PROP_VALS, cache=cache)
+        measure.regionprops_table(
+            self.label_image, self.intensity_image, properties=PROP_VALS, cache=cache
+        )
 
     # omit peakmem tests to save time (memory usage was minimal)
 
 
 class MomentsSuite:
-    params = ([(64, 64), (4096, 2048), (32, 32, 32), (256, 256, 192)],
-              [np.uint8, np.float32, np.float64],
-              [1, 2, 3])
+    params = (
+        [(64, 64), (4096, 2048), (32, 32, 32), (256, 256, 192)],
+        [np.uint8, np.float32, np.float64],
+        [1, 2, 3],
+    )
     param_names = ['shape', 'dtype', 'order']
 
     """Benchmark for filter routines in scikit-image."""
+
     def setup(self, shape, dtype, *args):
         rng = np.random.default_rng(1234)
         if np.dtype(dtype).kind in 'iu':