black versioning

.github/workflows/pr.yml

@@ -26,7 +26,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install black
+          pip install black==25.1.0
       - name: Check code styling with Black
         run: |
           black --diff -S -t py310 waveorder

.pre-commit-config.yaml

@@ -29,6 +29,6 @@ repos:
   #       args: [--ignore, "E203,W503", --min-python-version, '3.10']
   #       additional_dependencies: [flake8-typing-imports==1.12.0]
   - repo: https://github.com/psf/black
-    rev: 23.3.0
+    rev: 25.1.0
     hooks:
       - id: black

pyproject.toml

@@ -55,7 +55,7 @@ dependencies = [
 dynamic = ["version"]
 
 [project.optional-dependencies]
-dev = ["pytest", "pytest-cov", "black", "flake8"]
+dev = ["pytest", "pytest-cov", "black==25.1.0"]
 examples = ["napari[all]", "jupyter"]
 
 [project.urls]

waveorder/models/inplane_oriented_thick_pol3d.py

@@ -8,7 +8,7 @@
 
 
 def generate_test_phantom(
-    yx_shape: Tuple[int, int]
+    yx_shape: Tuple[int, int],
 ) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
     star, theta, _ = util.generate_star_target(yx_shape, blur_px=0.1)
     retardance = 0.25 * star

waveorder/models/isotropic_thin_3d.py

@@ -76,15 +76,15 @@ def calculate_transfer_function(
     )
 
     for z in range(len(z_position_list)):
-        absorption_2d_to_3d_transfer_function_out[
-            z
-        ] = sampling.nd_fourier_central_cuboid(
-            absorption_2d_to_3d_transfer_function[z], yx_shape
+        absorption_2d_to_3d_transfer_function_out[z] = (
+            sampling.nd_fourier_central_cuboid(
+                absorption_2d_to_3d_transfer_function[z], yx_shape
+            )
         )
-        phase_2d_to_3d_transfer_function_out[
-            z
-        ] = sampling.nd_fourier_central_cuboid(
-            phase_2d_to_3d_transfer_function[z], yx_shape
+        phase_2d_to_3d_transfer_function_out[z] = (
+            sampling.nd_fourier_central_cuboid(
+                phase_2d_to_3d_transfer_function[z], yx_shape
+            )
         )
 
     return (

waveorder/optics.py

@@ -261,9 +261,7 @@ def generate_vector_source_defocus_pupil(
 
     y_broadcast = torch.broadcast_to(y_frequencies[None, :, :], freq_shape)
     x_broadcast = torch.broadcast_to(x_frequencies[None, :, :], freq_shape)
-    z_broadcast = np.sqrt(
-        wavelength ** (-2) - x_broadcast**2 - y_broadcast**2
-    )
+    z_broadcast = np.sqrt(wavelength ** (-2) - x_broadcast**2 - y_broadcast**2)
 
     # Calculate rotation matrix
     rotations = rotation_matrix(

waveorder/stokes.py

@@ -46,6 +46,7 @@
 >>> stokes_after_adr(*adr_params) # * expands along the first axis
 
 """
+
 import numpy as np
 import torch
 

waveorder/waveorder_reconstructor.py

@@ -737,9 +737,7 @@ def inclination_recon_setup(self, inc_recon):
                 wave_vec_norm_x = self.lambda_illu * self.fxx
                 wave_vec_norm_y = self.lambda_illu * self.fyy
                 wave_vec_norm_z = (
-                    np.maximum(
-                        0, 1 - wave_vec_norm_x**2 - wave_vec_norm_y**2
-                    )
+                    np.maximum(0, 1 - wave_vec_norm_x**2 - wave_vec_norm_y**2)
                 ) ** (0.5)
 
                 incident_theta = np.arctan2(
@@ -4023,9 +4021,7 @@ def Fluor_anisotropy_recon(self, S1_stack, S2_stack):
             S1_stack = cp.array(S1_stack)
             S2_stack = cp.array(S2_stack)
 
-            anisotropy = cp.asnumpy(
-                0.5 * cp.sqrt(S1_stack**2 + S2_stack**2)
-            )
+            anisotropy = cp.asnumpy(0.5 * cp.sqrt(S1_stack**2 + S2_stack**2))
             orientation = cp.asnumpy(
                 (0.5 * cp.arctan2(S2_stack, S1_stack)) % np.pi
             )