Make combine_arrays understand non-numpy arrays

satpy/dataset.py

@@ -17,10 +17,10 @@
 # satpy.  If not, see <http://www.gnu.org/licenses/>.
 """Dataset objects."""
 
-import sys
 import logging
 import numbers
 from collections import namedtuple
+from collections.abc import Collection
 from datetime import datetime
 
 import numpy as np
@@ -98,10 +98,21 @@ def combine_metadata(*metadata_objects, **kwargs):
     shared_info = {}
     for k in shared_keys:
         values = [nfo[k] for nfo in info_dicts]
-        any_arrays = any([isinstance(val, np.ndarray) for val in values])
+        any_arrays = any([hasattr(val, "__array__") for val in values])
+        # in the real world, the `ancillary_variables` attribute may be
+        # List[xarray.DataArray], this means our values are now
+        # List[List[xarray.DataArray]].
+        any_list_of_arrays = any(
+                [isinstance(val, Collection) and len(val) > 0 and
+                 all([hasattr(subval, "__array__")
+                     for subval in val])
+                 for val in values])
         if any_arrays:
             if all(np.all(val == values[0]) for val in values[1:]):
                 shared_info[k] = values[0]
+        elif any_list_of_arrays:
+            if all(np.array_equal(val, values[0]) for val in values[1]):
+                shared_info[k] = values[0]
         elif 'time' in k and isinstance(values[0], datetime) and average_times:
             shared_info[k] = average_datetimes(values)
         elif all(val == values[0] for val in values[1:]):

satpy/tests/test_dataset.py

@@ -84,3 +84,20 @@ def test_combine_times(self):
         ret = combine_metadata(*dts, average_times=False)
         # times are not equal so don't include it in the final result
         self.assertNotIn('start_time', ret)
+
+    def test_combine_arrays(self):
+        """Test the combine_metadata with arrays."""
+        from satpy.dataset import combine_metadata
+        from numpy import arange, ones
+        from xarray import DataArray
+        dts = [
+                {"quality": (arange(25) % 2).reshape(5, 5).astype("?")},
+                {"quality": (arange(1, 26) % 3).reshape(5, 5).astype("?")},
+                {"quality": ones((5, 5,), "?")},
+        ]
+        combine_metadata(*dts)
+        dts2 = [{"quality": DataArray(d["quality"])} for d in dts]
+        combine_metadata(*dts2)
+        # the ancillary_variables attribute is actually a list of data arrays
+        dts3 = [{"quality": [d["quality"]]} for d in dts]
+        combine_metadata(*dts3)