tox cleanup

[skip ci]

Author: garrettwrong

src/aspire/image/image.py

@@ -361,9 +361,7 @@ def downsample(self, ds_res):
         # crop 2D Fourier transform for each image
         crop_fx = crop_pad_2d(fx, ds_res)
         # take back to real space, discard complex part, and scale
-        out = fft.centered_ifft2(crop_fx).real * (
-            ds_res**2 / self.resolution**2
-        )
+        out = fft.centered_ifft2(crop_fx).real * (ds_res**2 / self.resolution**2)
         out = xp.asnumpy(out)
 
         return self.__class__(out).stack_reshape(original_stack_shape)

src/aspire/utils/coor_trans.py

@@ -386,7 +386,7 @@ def crop_pad_2d(im, size, fill_value=0):
     elif size >= max(im_y, im_x):
         # Determine shape
         shape = list(im.shape[:-2])
-        shape.extend([size,size])
+        shape.extend([size, size])
         # ensure that we return in the same dtype as the input
         to_return = xp.full(shape, fill_value, dtype=im.dtype)
         # when padding, start_x and start_y are negative since size is larger

tests/test_numeric_sparse.py

@@ -51,4 +51,3 @@ def test_eigsh(backends):
 
     lamb, _ = sparse.linalg.eigsh(A)
     np.testing.assert_allclose(xp.asnumpy(lamb), 1.0)
-    print(lamb)