Remove superfluous NDCube.__add__ tests.

Author: DanRyanIrish

ndcube/tests/test_ndcube_arithmetic.py

@@ -49,6 +49,48 @@ def test_arithmetic_add_one_unit(ndc, value):
         ndc + value
 
 
+@pytest.mark.parametrize(("ndc", "value", "expected_kwargs"),
+                        [(
+                          "ndcube_2d_ln_lt_no_unit_no_unc_no_mask_2",
+                          NDData(np.ones((2, 3)), wcs=None),
+                          {"data": np.array([[1, 2, 3], [4, 5, 6]])}
+                         ),
+                         (
+                          "ndcube_2d_ln_lt_no_unit_no_unc_no_mask_2",
+                          NDData(np.ones((2, 3)),
+                                 wcs=None,
+                                 uncertainty=StdDevUncertainty(np.ones((2, 3))*0.1),
+                                 mask=np.array([[True, False, False], [False, True, False]])),
+                          {"data": np.array([[1, 2, 3], [4, 5, 6]]),
+                           "uncertainty": astropy.nddata.StdDevUncertainty(np.ones((2, 3))*0.1),
+                           "mask": np.array([[True, False, False], [False, True, False]])}
+                         ), # ndc has no mask no uncertainty no unit, but nddata has all.
+                         (
+                          "ndcube_2d_ln_lt_unit_unc_mask",
+                          NDData(np.ones((2, 3)),
+                                 wcs=None,
+                                 uncertainty=StdDevUncertainty(np.ones((2, 3))*0.1),
+                                 mask=np.array([[True, False, False], [False, True, False]]),
+                                 unit=u.ct),
+                          {"unit": u.ct,
+                           "data": np.array([[1, 2, 3], [4, 5, 6]]),
+                           "uncertainty": astropy.nddata.StdDevUncertainty(np.array([[0.1       , 0.1118034 , 0.14142136],
+                                                                                     [0.18027756, 0.2236068 , 0.26925824]])),
+                           "mask": np.array([[True, True, True], [False, True, True]])}
+                         ) # both of them have uncertainty and mask and unit.
+                        ],
+                        indirect=("ndc",))
+def test_cube_arithmetic_add_nddata(ndc, value, expected_kwargs, wcs_2d_lt_ln):
+    output_cube = ndc + value  # perform the multiplication
+
+    expected_kwargs["wcs"] = wcs_2d_lt_ln
+    expected_cube = NDCube(**expected_kwargs)
+
+    # Assert output cube is same as expected cube
+    assert_cubes_equal(output_cube, expected_cube, check_uncertainty_values=True)
+
+
+"""
 # Both NDData and NDCube have unit and uncertainty. No mask is involved.
 # Test different scenarios when units are equivalent and when they are not. TODO (bc somewhere is checking the units are the same)
 # what is an equivalent unit in astropy for count (ct)?
@@ -288,7 +330,7 @@ def test_arithmetic_add_nddata_mask(ndcube_2d_ln_lt_nomask, value):
 
     # Assert output cube is same as expected cube
     assert_cubes_equal(output_cube, expected_cube)
-
+"""
 
 @pytest.mark.parametrize('value', [
     10 * u.ct,
@@ -385,47 +427,6 @@ def test_cube_arithmetic_multiply_nddata(ndc, value, expected_kwargs, wcs_2d_lt_
     assert_cubes_equal(output_cube, expected_cube, check_uncertainty_values=True)
 
 
-@pytest.mark.parametrize(("ndc", "value", "expected_kwargs"),
-                        [(
-                          "ndcube_2d_ln_lt_no_unit_no_unc_no_mask_2",
-                          NDData(np.ones((2, 3)), wcs=None),
-                          {"data": np.array([[1, 2, 3], [4, 5, 6]])}
-                         ),
-                         (
-                          "ndcube_2d_ln_lt_no_unit_no_unc_no_mask_2",
-                          NDData(np.ones((2, 3)),
-                                 wcs=None,
-                                 uncertainty=StdDevUncertainty(np.ones((2, 3))*0.1),
-                                 mask=np.array([[True, False, False], [False, True, False]])),
-                          {"data": np.array([[1, 2, 3], [4, 5, 6]]),
-                           "uncertainty": astropy.nddata.StdDevUncertainty(np.ones((2, 3))*0.1),
-                           "mask": np.array([[True, False, False], [False, True, False]])}
-                         ), # ndc has no mask no uncertainty no unit, but nddata has all.
-                         (
-                          "ndcube_2d_ln_lt_unit_unc_mask",
-                          NDData(np.ones((2, 3)),
-                                 wcs=None,
-                                 uncertainty=StdDevUncertainty(np.ones((2, 3))*0.1),
-                                 mask=np.array([[True, False, False], [False, True, False]]),
-                                 unit=u.ct),
-                          {"unit": u.ct,
-                           "data": np.array([[1, 2, 3], [4, 5, 6]]),
-                           "uncertainty": astropy.nddata.StdDevUncertainty(np.array([[0.1       , 0.1118034 , 0.14142136],
-                                                                                     [0.18027756, 0.2236068 , 0.26925824]])),
-                           "mask": np.array([[True, True, True], [False, True, True]])}
-                         ) # both of them have uncertainty and mask and unit.
-                        ],
-                        indirect=("ndc",))
-def test_cube_arithmetic_add_nddata(ndc, value, expected_kwargs, wcs_2d_lt_ln):
-    output_cube = ndc + value  # perform the multiplication
-
-    expected_kwargs["wcs"] = wcs_2d_lt_ln
-    expected_cube = NDCube(**expected_kwargs)
-
-    # Assert output cube is same as expected cube
-    assert_cubes_equal(output_cube, expected_cube, check_uncertainty_values=True)
-
-
 @pytest.mark.parametrize('value', [
     10 * u.ct,
     u.Quantity([10], u.ct),