fix: remove ragged array in tests

NSLS-II-CSX · Apr 5, 2024 · d935601 · d935601
1 parent 2795117
commit d935601
Showing 1 changed file with 17 additions and 20 deletions.
diff --git a/tests/test_image.py b/tests/test_image.py
@@ -1,16 +1,16 @@
-from csxtools.image import (rotate90, stackmean, stacksum, stackstd,
-                            stackvar, stackstderr, images_mean, images_sum)
 import numpy as np
-from numpy.testing import assert_array_equal, assert_array_almost_equal
+from numpy.testing import assert_array_almost_equal, assert_array_equal
+
+from csxtools.image import images_mean, images_sum, rotate90, stackmean, stackstd, stackstderr, stacksum, stackvar
 
 
 def test_rotate90():
-    x = np.arange(4*20, dtype=np.float32).reshape(4, 20)
-    y = rotate90(np.array([x, x, x, x]), 'ccw')
+    x = np.arange(4 * 20, dtype=np.float32).reshape(4, 20)
+    y = rotate90(np.array([x, x, x, x]), "ccw")
     for i in y:
         assert_array_equal(i, np.rot90(x, 1))
 
-    y = rotate90(np.array([x, x, x, x]), 'cw')
+    y = rotate90(np.array([x, x, x, x]), "cw")
     for i in y:
         assert_array_equal(i, np.rot90(x, -1))
 
@@ -52,45 +52,42 @@ def test_stacksum():
     x[23] = np.nan
     x[40] = np.nan
     m, n = stacksum(x)
-    assert_array_almost_equal(m, np.ones((100, 100), dtype=np.float32) * 2000,
-                              decimal=3)
+    assert_array_almost_equal(m, np.ones((100, 100), dtype=np.float32) * 2000, decimal=3)
     assert_array_equal(n, np.ones((100, 100), dtype=np.float32) * (1000 - 3))
 
 
 def test_stackstd():
-    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape(
-        (1000, 20, 20))
+    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape((1000, 20, 20))
     m, n = stackstd(x)
     assert_array_almost_equal(m, np.std(x, axis=0), 2)
     assert_array_equal(n, np.ones((20, 20), dtype=np.float32) * 1000.0)
 
 
 def test_stackvar():
-    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape(
-        (1000, 20, 20))
+    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape((1000, 20, 20))
     m, n = stackvar(x)
     assert_array_almost_equal(m, np.var(x, axis=0), 0)
     assert_array_equal(n, np.ones((20, 20), dtype=np.float32) * 1000.0)
 
 
 def test_stackstderr():
-    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape(
-        (1000, 20, 20))
+    x = np.repeat(np.arange(1000, dtype=np.float32), 400).reshape((1000, 20, 20))
     m, n = stackstderr(x)
     assert_array_almost_equal(m, np.std(x, axis=0) / np.sqrt(n), 3)
     assert_array_equal(n, np.ones((20, 20), dtype=np.float32) * 1000.0)
 
 
 def test_images_mean():
-    x = np.array([np.repeat(ii*np.ones(ii*100, dtype=np.float32), 400).reshape(
-                 (ii*100, 20, 20)) for ii in range(1, 11)])
+    x = [
+        np.repeat(ii * np.ones(ii * 100, dtype=np.float32), 400).reshape((ii * 100, 20, 20)) for ii in range(1, 11)
+    ]
     m = images_mean(x)
     assert_array_equal(m, np.array([np.mean(x1) for x1 in x]), 3)
 
 
 def test_images_sum():
-    x = np.array([np.repeat(ii*np.ones(ii*100, dtype=np.float32), 400).reshape(
-                 (ii*100, 20, 20)) for ii in range(1, 11)])
+    x = [
+        np.repeat(ii * np.ones(ii * 100, dtype=np.float32), 400).reshape((ii * 100, 20, 20)) for ii in range(1, 11)
+    ]
     m = images_sum(x)
-    assert_array_equal(m, np.array([np.sum(np.mean(x1, axis=0))
-                                    for x1 in x]), 3)
+    assert_array_equal(m, np.array([np.sum(np.mean(x1, axis=0)) for x1 in x]), 3)