Merge pull request #693 from nabobalis/wcs

Check more things in test helpers

ndcube/tests/helpers.py

@@ -13,6 +13,7 @@
 from numpy.testing import assert_equal
 
 import astropy
+from astropy.wcs.wcsapi import BaseHighLevelWCS
 from astropy.wcs.wcsapi.fitswcs import SlicedFITSWCS
 from astropy.wcs.wcsapi.low_level_api import BaseLowLevelWCS
 from astropy.wcs.wcsapi.wrappers.sliced_wcs import sanitize_slices
@@ -95,9 +96,11 @@ def assert_metas_equal(test_input, expected_output):
             assert test_input[key] == expected_output[key]
 
 
-def assert_cubes_equal(test_input, expected_cube):
+def assert_cubes_equal(test_input, expected_cube, check_data=True):
     assert isinstance(test_input, type(expected_cube))
     assert np.all(test_input.mask == expected_cube.mask)
+    if check_data:
+        np.testing.assert_array_equal(test_input.data, expected_cube.data)
     assert_wcs_are_equal(test_input.wcs, expected_cube.wcs)
     if test_input.uncertainty:
         assert test_input.uncertainty.array.shape == expected_cube.uncertainty.array.shape
@@ -110,12 +113,12 @@ def assert_cubes_equal(test_input, expected_cube):
         assert_extra_coords_equal(test_input.extra_coords, expected_cube.extra_coords)
 
 
-def assert_cubesequences_equal(test_input, expected_sequence):
+def assert_cubesequences_equal(test_input, expected_sequence, check_data=True):
     assert isinstance(test_input, type(expected_sequence))
     assert_metas_equal(test_input.meta, expected_sequence.meta)
     assert test_input._common_axis == expected_sequence._common_axis
     for i, cube in enumerate(test_input.data):
-        assert_cubes_equal(cube, expected_sequence.data[i])
+        assert_cubes_equal(cube, expected_sequence.data[i], check_data=check_data)
 
 
 def assert_wcs_are_equal(wcs1, wcs2):
@@ -140,7 +143,12 @@ def assert_wcs_are_equal(wcs1, wcs2):
     assert wcs1.world_axis_units == wcs2.world_axis_units
     assert_equal(wcs1.axis_correlation_matrix, wcs2.axis_correlation_matrix)
     assert wcs1.pixel_bounds == wcs2.pixel_bounds
-
+    if wcs1.pixel_shape is not None:
+        random_idx = np.random.randint(wcs1.pixel_shape,size=[10,wcs1.pixel_n_dim])
+        # SlicedLowLevelWCS vs BaseHighLevelWCS don't have the same pixel_to_world method
+        low_level_wcs1 = wcs1.low_level_wcs if isinstance(wcs1, BaseHighLevelWCS) else wcs1
+        low_level_wcs2 = wcs2.low_level_wcs if isinstance(wcs2, BaseHighLevelWCS) else wcs2
+        np.testing.assert_array_equal(low_level_wcs1.pixel_to_world_values(*random_idx.T), low_level_wcs2.pixel_to_world_values(*random_idx.T))
 
 def create_sliced_wcs(wcs, item, dim):
     """
@@ -152,15 +160,15 @@ def create_sliced_wcs(wcs, item, dim):
     return SlicedFITSWCS(wcs, item)
 
 
-def assert_collections_equal(collection1, collection2):
+def assert_collections_equal(collection1, collection2, check_data=True):
     assert collection1.keys() == collection2.keys()
     assert collection1.aligned_axes == collection2.aligned_axes
     for cube1, cube2 in zip(collection1.values(), collection2.values()):
         # Check cubes are same type.
         assert type(cube1) is type(cube2)
         if isinstance(cube1, NDCube):
-            assert_cubes_equal(cube1, cube2)
+            assert_cubes_equal(cube1, cube2, check_data=check_data)
         elif isinstance(cube1, NDCubeSequence):
-            assert_cubesequences_equal(cube1, cube2)
+            assert_cubesequences_equal(cube1, cube2, check_data=check_data)
         else:
             raise TypeError(f"Unsupported Type in NDCollection: {type(cube1)}")