Retry finwin pkg

gallery/tutorials/tutorials/apple_picker.py

@@ -4,6 +4,7 @@
 
 We demonstrate ASPIRE's particle picking methods using the ``Apple`` class.
 """
+
 import logging
 import os
 

gallery/tutorials/tutorials/basic_image_array.py

@@ -8,7 +8,6 @@
 whiten that noise using some tools from the ASPIRE pipeline.
 """
 
-
 import matplotlib.pyplot as plt
 import numpy as np
 from scipy.datasets import face

gallery/tutorials/tutorials/cov3d_simulation.py

@@ -5,6 +5,7 @@
 This script illustrates the example of Covariance 3D estimation using simulation images
 generated from Gaussian blob volumes.
 """
+
 import logging
 
 import numpy as np

gallery/tutorials/tutorials/preprocess_imgs_sim.py

@@ -5,6 +5,7 @@
 This script illustrates the preprocess steps implemented prior to starting the pipeline of
 reconstructing a 3D map using simulated 2D images.
 """
+
 import logging
 import os
 

pyproject.toml

@@ -31,9 +31,7 @@ dependencies = [
     "click",
     "confuse >= 2.0.0",
     "cvxpy",
-    # finufft 2.2.0 doesn't seemt to run on GHA Windows CI...    
-    "finufft==2.2.0 ; sys_platform != 'win32'",
-    "finufft==2.1.0 ; sys_platform == 'win32'",
+    "finufft==2.2.0",
     "gemmi >= 0.4.8",
     "grpcio >= 1.54.2",
     "joblib",

src/aspire/basis/fpswf_2d.py

@@ -361,9 +361,9 @@ def _pswf_integration(self, images_nufft):
         )
         m = self.pswf_radial_quad.shape[1]
         for i in range(self.n_max):
-            coef_vec_quad[
-                :, self.indices_for_n[i] + np.arange(self.numel_for_n[i])
-            ] = np.dot(self.blk_r[i], r_n_eval_mat[i * m : (i + 1) * m, :]).T
+            coef_vec_quad[:, self.indices_for_n[i] + np.arange(self.numel_for_n[i])] = (
+                np.dot(self.blk_r[i], r_n_eval_mat[i * m : (i + 1) * m, :]).T
+            )
 
         return coef_vec_quad
 

src/aspire/image/image.py

@@ -360,9 +360,7 @@ def downsample(self, ds_res):
         # crop 2D Fourier transform for each image
         crop_fx = np.array([crop_pad_2d(fx[i], ds_res) for i in range(self.n_images)])
         # take back to real space, discard complex part, and scale
-        out = np.real(fft.centered_ifft2(crop_fx)) * (
-            ds_res**2 / self.resolution**2
-        )
+        out = np.real(fft.centered_ifft2(crop_fx)) * (ds_res**2 / self.resolution**2)
 
         return self.__class__(out).stack_reshape(original_stack_shape)
 

src/aspire/utils/logging.py

@@ -1,6 +1,7 @@
 """
 Miscellaneous Utilities that relate to logging.
 """
+
 import logging
 import os.path
 import subprocess

src/aspire/utils/misc.py

@@ -1,6 +1,7 @@
 """
 Miscellaneous Utilities that have no better place (yet).
 """
+
 import hashlib
 import importlib.resources
 import logging

src/aspire/utils/resolution_estimation.py

@@ -1,6 +1,7 @@
 """
 This module contains code for estimating resolution achieved by reconstructions.
 """
+
 import logging
 import warnings