Addresses MAC OS numpy singularity handling

numpy 1.x on MAC OS may not raise a singularity flag where Linux and Windows due. This issue appears to be addressed in numpy 2. Either way, this test should now be more in line with the goals of this test case (i.e., either (a) confirming that the matrix is singular and caught appropriately with nans in the DOP entries or (b) near singular even if the flag is not raised and the relevant DOP entries are non-physical).

tests/utils/test_dop.py

@@ -412,18 +412,23 @@ def test_singularity_dop(navdata):
         # is an issue in comparing nan > number).
         # Note: we use np.any() since we can get small values in the DOP matrix
         # even if singular (i.e., in the off-diagonal entries).
-        for _, val in dop_dict.items():
-            print("1:",val)
-            assert np.any(np.isnan(val)) or np.any(np.abs(val) > 1e6)
+        dop_mat = dop_dict['dop_matrix']
+        print("1 (singularity flag not raised): DOP matrix is:")
+        print(dop_mat)
+        assert np.any(np.isnan(dop_mat)) or np.any(np.abs(dop_mat) > 1e6)
+
+        dop_scalars = [val for key, val in dop_dict.items() if key != 'dop_matrix']
+        print("1: DOP Values are:", dop_scalars)
+        assert np.any(np.isnan(dop_scalars)) or np.any(np.abs(dop_scalars) > 1e6)
 
     except np.linalg.LinAlgError:
         # We expect a singularity error. If we get the singularity error, then
         # the values should all be NaNs
 
         # Now check that we get all NaNs for the DOP values when we have a
         # singularity
-        for _, val in dop_dict.items():
-            print("2:",val)
+        for key, val in dop_dict.items():
+            print("2:", key, " : ", val)
             assert np.all(np.isnan(val))