Refactored

Author: andreped

tests/test_torch.py

@@ -11,13 +11,15 @@
 def setup_function(fn):
     print("torch version:", torch.__version__, "torchvision version:", torchvision.__version__)
 
+
 def test_cov():
     x = np.random.randn(10, 10)
     cov_np = np.cov(x)
     cov_t = torchstain.torch.utils.cov(torch.tensor(x))
 
     np.testing.assert_almost_equal(cov_np, cov_t.numpy())
 
+
 def test_percentile():
     x = np.random.randn(10, 10)
     p = 20
@@ -26,6 +28,7 @@ def test_percentile():
 
     np.testing.assert_almost_equal(p_np, p_t)
 
+
 def test_macenko_torch():
     size = 1024
     curr_file_path = os.path.dirname(os.path.realpath(__file__))
@@ -57,6 +60,7 @@ def test_macenko_torch():
     # assess whether the normalized images are identical across backends
     np.testing.assert_almost_equal(result_numpy.flatten(), result_torch.flatten(), decimal=2, verbose=True)
 
+
 def test_multitarget_macenko_torch():
     size = 1024
     curr_file_path = os.path.dirname(os.path.realpath(__file__))