Merge pull request #87 from eslavich/eslavich-fits-array-casting

Support casting of FITS_rec with unsigned integer column

CHANGES.rst

@@ -4,6 +4,8 @@
 - Add schema feature to forward deprecated model attributes to
   a new location. [#86]
 
+- Support casting of FITS_rec tables with unsigned integer columns. [#87]
+
 0.3.0 (2021-09-03)
 ==================
 

src/stdatamodels/util.py

@@ -91,10 +91,13 @@ def gentle_asarray(a, dtype):
 def _safe_asanyarray(a, dtype):
     if isinstance(a, fits.fitsrec.FITS_rec):
         if any(c.bzero is not None for c in a.columns):
-            # Due to an issue in astropy, it's not safe to convert
+            # Due to an issue in astropy, it's not safe to directly cast
             # a FITS_rec with a pseudo-unsigned column.
             # See https://github.com/astropy/astropy/issues/12112
-            raise ValueError("Cannot convert FITS_rec dtype")
+            result = np.zeros(a.shape, dtype=dtype)
+            for old_col, new_col in zip(a.dtype.names, result.dtype.names):
+                result[new_col] = a[old_col]
+            return result
 
     return np.asanyarray(a, dtype=dtype)
 

tests/test_util.py

@@ -87,8 +87,8 @@ def test_gentle_asarray_fits_rec_pseudo_unsigned(tmp_path):
     assert result["col1"][3] == 4
 
     # This tests the case where a table with a pseudo unsigned integer column
-    # is opened from a FITS file and needs to be cast.  Due to a bug in astropy
-    # this isn't safe so we expect an exception.
+    # is opened from a FITS file and needs to be cast.  This requires special
+    # handling on our end to dodge the bug.
     file_path = tmp_path / "test.fits"
 
     data = np.array([(0,)], dtype=[("col1", np.uint16)])
@@ -98,8 +98,10 @@ def test_gentle_asarray_fits_rec_pseudo_unsigned(tmp_path):
     hdul.writeto(file_path)
 
     with fits.open(file_path) as hdul:
-        with pytest.raises(ValueError, match="Cannot convert FITS_rec dtype"):
-            util.gentle_asarray(hdul[-1].data, dtype=[("col1", np.uint32)])
+        result = util.gentle_asarray(hdul[-1].data, dtype=[("col1", np.uint32)])
+        # Without the fix, the value in the array would be 128 due to bzero
+        # shift being applied twice.
+        assert result[0][0] == 0
 
 
 def test_gentle_asarray_nested_array():