add tabular-fits support for Spectrum1D mask (astropy#1104)

* add tabular-fits support for Spectrum1D mask

* Fix codestyle

---------

Co-authored-by: Ricky O'Steen <rosteen@stsci.edu>

specutils/io/default_loaders/tabular_fits.py

@@ -163,6 +163,19 @@ def tabular_fits_writer(spectrum, file_name, hdu=1, update_header=False, **kwarg
             raise ValueError("Could not convert uncertainty to StdDevUncertainty due"
                              " to divide-by-zero error.")
 
+    # Add mask column if present
+    if spectrum.mask is not None:
+        # work around https://github.com/astropy/astropy/issues/11963
+        # where int8 columns are written as bool, loosing information.
+        # upcast to int16 instead.
+        if spectrum.mask.dtype == np.int8:
+            mask = spectrum.mask.astype(np.int16)
+        else:
+            mask = spectrum.mask
+
+        columns.append(mask)
+        colnames.append('mask')
+
     # For > 1D data transpose from row-major format
     for c in range(1, len(columns)):
         if columns[c].ndim > 1:

specutils/io/parsing_utils.py

@@ -282,11 +282,20 @@ def _find_spectral_column(table, columns_to_search, spectral_axis):
     else:
         err = None
 
+    # Check for mask
+    if 'mask' in table.colnames:
+        mask = table['mask']
+        if mask.ndim > 1:
+            mask = mask.T
+    else:
+        mask = None
+
     # Create the Spectrum1D object and return it
     if wcs is not None or spectral_axis_column is not None and flux_column is not None:
         # For > 1D spectral axis transpose to row-major format and return SpectrumCollection
         spectrum = Spectrum1D(flux=flux, spectral_axis=spectral_axis,
-                              uncertainty=err, meta={'header': table.meta}, wcs=wcs)
+                              uncertainty=err, meta={'header': table.meta}, wcs=wcs,
+                              mask=mask)
 
     return spectrum
 

specutils/tests/test_loaders.py

@@ -594,7 +594,70 @@ def test_tabular_fits_multid(tmp_path, ndim, spectral_axis):
                              spectrum.uncertainty.quantity)
 
 
-def test_tabular_fits_header(tmp_path):
+@pytest.mark.parametrize("mask_type", [bool, np.uint8, np.int8, np.uint16, np.int16, '>i2'])
+def test_tabular_fits_mask(tmp_path, mask_type):
+    # test mask I/O with tabular fits format
+    wave = np.arange(3600, 3700) * u.AA
+    nwave = len(wave)
+
+    # 1D Case
+    flux = np.random.uniform(0,1,size=nwave) * u.Jy
+    mask = np.zeros(flux.shape, dtype=mask_type)
+    mask[0] = 1
+
+    sp1 = Spectrum1D(spectral_axis=wave, flux=flux, mask=mask)
+    assert sp1.mask.dtype == mask.dtype
+
+    tmpfile = str(tmp_path / '_mask_tst.fits')
+    sp1.write(tmpfile, format='tabular-fits', overwrite=True)
+
+    sp2 = Spectrum1D.read(tmpfile)
+    assert np.all(sp1.spectral_axis == sp2.spectral_axis)
+    assert np.all(sp1.flux == sp2.flux)
+    assert sp2.mask is not None
+    assert np.all(sp1.mask == sp2.mask)
+
+    # int16 is returned as FITS-native '>i2'
+    if mask_type == np.int16:
+        assert sp1.mask.dtype.kind == sp2.mask.dtype.kind
+        assert sp1.mask.dtype.itemsize == sp2.mask.dtype.itemsize
+    elif mask_type == np.int8:
+        # due to https://github.com/astropy/astropy/issues/11963,
+        # int8 is upcast to int16 which is returned as >i2...
+        assert sp2.mask.dtype == np.dtype('>i2')
+    else:
+        assert sp1.mask.dtype == sp2.mask.dtype
+
+    # 2D Case
+    nspec = 3
+    flux = np.random.uniform(0,1,size=(nspec,nwave)) * u.Jy
+    mask = np.zeros(flux.shape, dtype=mask_type)
+    mask[0,0] = 1
+
+    sp1 = Spectrum1D(spectral_axis=wave, flux=flux, mask=mask)
+
+    tmpfile = str(tmp_path / '_mask_tst.fits')
+    sp1.write(tmpfile, format='tabular-fits', overwrite=True)
+
+    sp2 = Spectrum1D.read(tmpfile)
+    assert np.all(sp1.spectral_axis == sp2.spectral_axis)
+    assert np.all(sp1.flux == sp2.flux)
+    assert sp2.mask is not None
+    assert np.all(sp1.mask == sp2.mask)
+
+    # int16 is returned as FITS-native '>i2'
+    if mask_type == np.int16:
+        assert sp1.mask.dtype.kind == sp2.mask.dtype.kind
+        assert sp1.mask.dtype.itemsize == sp2.mask.dtype.itemsize
+    elif mask_type == np.int8:
+        # due to https://github.com/astropy/astropy/issues/11963,
+        # int8 is upcast to int16 which is returned as >i2...
+        assert sp2.mask.dtype == np.dtype('>i2')
+    else:
+        assert sp1.mask.dtype == sp2.mask.dtype
+
+
+def test_tabular_fits_maskheader(tmp_path):
     # Create a small data set + header with reserved FITS keywords
     disp = np.linspace(1, 1.2, 21) * u.AA
     flux = np.random.normal(0., 1.0e-14, disp.shape[0]) * u.Jy