Merge pull request #620 from astrofrog/fix-mask-channels

 Fix bug in VaryingResolutionSpectralCube.mask_channels

CHANGES.rst

@@ -1,6 +1,8 @@
 0.5 (unreleased)
 ----------------
 - Bugfix: subcubes from compound regions previously did not work.  #601
+- Bugfix: VaryingResolutionSpectralCube.mask_channels now preserves
+  previous mask. #620
 - Refactor tests to use fixtures for accessing data instead of needing to
   run a script to generate test files. #598
 - Refactor package infrastructure to no longer use astropy-helpers. #599

spectral_cube/spectral_cube.py

@@ -3971,14 +3971,10 @@ def mask_channels(self, goodchannels):
             raise ValueError("goodchannels must have a length equal to the "
                              "cube's spectral dimension.")
 
-        mask = BooleanArrayMask(goodchannels[:,None,None], self._wcs,
-                                shape=self._data.shape)
-
-        return self._new_cube_with(mask=mask,
-                                   goodbeams_mask=np.logical_and(goodchannels,
-                                                                 self.goodbeams_mask))
-
+        cube = self.with_mask(goodchannels[:,None,None])
+        cube.goodbeams_mask = np.logical_and(goodchannels, self.goodbeams_mask)
 
+        return cube
 
     def spectral_interpolate(self, *args, **kwargs):
         raise AttributeError("VaryingResolutionSpectralCubes can't be "

spectral_cube/tests/test_spectral_cube.py

@@ -2224,3 +2224,25 @@ def test_mask_none():
                              [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]] * u.Jy / u.beam)
     assert_quantity_allclose(cube[:, 0, 0],
                              [0, 12] * u.Jy / u.beam)
+
+
+@pytest.mark.parametrize('filename', ['data_vda', 'data_vda_beams'],
+                            indirect=['filename'])
+def test_mask_channels_preserve_mask(filename):
+
+    # Regression test for a bug that caused the mask to not be preserved.
+
+    cube, data = cube_and_raw(filename)
+
+    # Add a mask to the cube
+    mask = np.ones(cube.shape, dtype=bool)
+    mask[:, ::2, ::2] = False
+    cube = cube.with_mask(mask)
+
+    # Mask by channels
+    cube = cube.mask_channels([False, True, False, True])
+
+    # Check final mask is a combination of both
+    expected_mask = mask.copy()
+    expected_mask[::2] = False
+    np.testing.assert_equal(cube.mask.include(), expected_mask)