TST: Fix missing tests

pmgbergen · Oct 9, 2023 · 9e50304 · 9e50304
1 parent ac31f7a
commit 9e50304
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Showing 2 changed files with 22 additions and 22 deletions.
diff --git a/tests/unit/test_arithmetics.py b/tests/unit/test_arithmetics.py
@@ -9,42 +9,42 @@
 
 def test_scalar_weight_3d():
 
-    image = darsia.Image(np.ones((3, 4, 5), dtype=float), dim=3)
+    image = darsia.Image(np.ones((3, 4, 5), dtype=float), space_dim=3)
     weight = 2.0
     weighted_image = darsia.weight(image, weight)
     assert np.allclose(weighted_image.img, 2 * np.ones((3, 4, 5)))
 
 
 def test_array_weight_2d():
 
-    image = darsia.Image(np.ones((3, 4), dtype=float), dim=2)
-    weight = darsia.Image(np.random.rand(3, 4), dim=2)
+    image = darsia.Image(np.ones((3, 4), dtype=float), space_dim=2)
+    weight = darsia.Image(np.random.rand(3, 4), space_dim=2)
     weighted_image = darsia.weight(image, weight)
     assert np.allclose(weighted_image.img, weight.img)
 
 
 def test_incompatible_weight_2d():
 
-    image = darsia.Image(np.ones((6, 8), dtype=float), dim=2, dimensions=[6, 8])
-    weight = darsia.Image(2 * np.ones((3, 4)), dim=2, dimensions=[6, 8])
+    image = darsia.Image(np.ones((6, 8), dtype=float), space_dim=2, dimensions=[6, 8])
+    weight = darsia.Image(2 * np.ones((3, 4)), space_dim=2, dimensions=[6, 8])
 
     weighted_image = darsia.weight(image, weight)
     assert np.allclose(weighted_image.img, 2 * np.ones((6, 8)))
 
 
 def test_array_weight_3d():
 
-    image = darsia.Image(np.ones((3, 4, 5), dtype=float), dim=3)
-    weight = darsia.Image(np.random.rand(3, 4, 5), dim=3)
+    image = darsia.Image(np.ones((3, 4, 5), dtype=float), space_dim=3)
+    weight = darsia.Image(np.random.rand(3, 4, 5), space_dim=3)
     weighted_image = darsia.weight(image, weight)
     assert np.allclose(weighted_image.img, weight.img)
 
 
 def test_superposition_2d():
 
-    image1 = darsia.ScalarImage(np.ones((3, 4), dtype=float), dim=2)
-    image2 = darsia.ScalarImage(2 * np.ones((3, 4), dtype=float), dim=2)
-    image3 = darsia.ScalarImage(3 * np.ones((3, 4), dtype=float), dim=2)
+    image1 = darsia.ScalarImage(np.ones((3, 4), dtype=float), space_dim=2)
+    image2 = darsia.ScalarImage(2 * np.ones((3, 4), dtype=float), space_dim=2)
+    image3 = darsia.ScalarImage(3 * np.ones((3, 4), dtype=float), space_dim=2)
     superposed_image = darsia.superpose([image1, image2, image3])
     assert np.allclose(superposed_image.img, 6 * np.ones((3, 4)))
 

diff --git a/tests/unit/test_dimension_reduction.py b/tests/unit/test_dimension_reduction.py
@@ -12,14 +12,14 @@ def test_axis_averaging_x():
 
     image_3d = darsia.Image(
         np.ones((3, 4, 5), dtype=float),
-        dim=3,
+        space_dim=3,
         dimensions=[2, 3, 4],
         series=False,
         scalar=True,
     )
 
-    averaging_axis = darsia.AxisReduction(axis="x", dim=3, mode = "sum")
-    averaging_index = darsia.AxisReduction(axis=2, dim=3, mode = "sum")
+    averaging_axis = darsia.AxisReduction(axis="x", dim=3, mode="sum")
+    averaging_index = darsia.AxisReduction(axis=2, dim=3, mode="sum")
 
     image_2d_via_axis = averaging_axis(image_3d)
     image_2d_via_index = averaging_index(image_3d)
@@ -39,14 +39,14 @@ def test_axis_averaging_y():
 
     image_3d = darsia.Image(
         np.ones((3, 4, 5), dtype=float),
-        dim=3,
+        space_dim=3,
         dimensions=[2, 3, 4],
         series=False,
         scalar=True,
     )
 
-    averaging_axis = darsia.AxisReduction(axis="y", dim=3, mode = "sum")
-    averaging_index = darsia.AxisReduction(axis=1, dim=3, mode = "sum")
+    averaging_axis = darsia.AxisReduction(axis="y", dim=3, mode="sum")
+    averaging_index = darsia.AxisReduction(axis=1, dim=3, mode="sum")
 
     image_2d_via_axis = averaging_axis(image_3d)
     image_2d_via_index = averaging_index(image_3d)
@@ -66,14 +66,14 @@ def test_axis_averaging_z():
 
     image_3d = darsia.Image(
         np.ones((3, 4, 5), dtype=float),
-        dim=3,
+        space_dim=3,
         dimensions=[2, 3, 4],
         series=False,
         scalar=True,
     )
 
-    averaging_axis = darsia.AxisReduction(axis="z", dim=3, mode = "sum")
-    averaging_index = darsia.AxisReduction(axis=0, dim=3, mode = "sum")
+    averaging_axis = darsia.AxisReduction(axis="z", dim=3, mode="sum")
+    averaging_index = darsia.AxisReduction(axis=0, dim=3, mode="sum")
 
     image_2d_via_axis = averaging_axis(image_3d)
     image_2d_via_index = averaging_index(image_3d)
@@ -96,15 +96,15 @@ def test_axis_averaging_series_x():
 
     image_3d = darsia.Image(
         np.ones((3, 4, 5, 6), dtype=float),
-        dim=3,
+        space_dim=3,
         dimensions=[2, 3, 4],
         series=True,
         scalar=True,
         time=[0, 1, 2, 3, 4, 5],
     )
 
-    averaging_axis = darsia.AxisReduction(axis="x", dim=3, mode = "sum")
-    averaging_index = darsia.AxisReduction(axis=2, dim=3, mode = "sum")
+    averaging_axis = darsia.AxisReduction(axis="x", dim=3, mode="sum")
+    averaging_index = darsia.AxisReduction(axis=2, dim=3, mode="sum")
 
     image_2d_via_axis = averaging_axis(image_3d)
     image_2d_via_index = averaging_index(image_3d)