Fix Cube.rolling_window with lazy auxiliary coordinates

rolling_window built each window's coordinate bounds with new_bounds[:,
(0, -1)]. A tuple index is treated by Dask as a multidimensional index,
so a lazy coordinate along the windowed dimension raised a TypeError.
Index with the list [0, -1] instead, which numpy and Dask both treat as
selecting the first and last column, giving an identical (and still lazy)
result.

Fixes #6480.

Author: gaoflow

changelog/7123.bugfix.rst

@@ -0,0 +1,3 @@
+:user:`gaoflow` fixed :meth:`iris.cube.Cube.rolling_window` so that it no
+longer raises a ``TypeError`` when the cube has a lazy auxiliary coordinate
+along the windowed dimension. (:issue:`6480`)

lib/iris/cube.py

@@ -5243,12 +5243,15 @@ def rolling_window(
                 # window and the bounds are the first and last points in the
                 # window as with numeric coordinates.
                 new_points = np.apply_along_axis(lambda x: "|".join(x), -1, new_bounds)
-                new_bounds = new_bounds[:, (0, -1)]
+                # Index with a list rather than a tuple: a tuple is interpreted
+                # as a multidimensional index by Dask, so lazy coordinates would
+                # otherwise fail here (see #6480).
+                new_bounds = new_bounds[:, [0, -1]]
             else:
                 # Take the first and last element of the rolled window (i.e.
                 # the bounds) and the new points are the midpoints of these
                 # bounds.
-                new_bounds = new_bounds[:, (0, -1)]
+                new_bounds = new_bounds[:, [0, -1]]
                 new_points = np.mean(new_bounds, axis=-1)
 
             # wipe the coords points and set the bounds

lib/iris/tests/unit/cube/test_Cube.py

@@ -1086,6 +1086,22 @@ def test_lazy(self):
         )
         _shared_utils.assert_masked_array_equal(expected_result, res_cube.data)
 
+    def test_lazy_aux_coord(self):
+        # A lazy aux-coord paralleling the rolled dimension must not cause a
+        # failure, and should give the same result as a real one, staying lazy
+        # (see #6480).
+        self.cube.add_aux_coord(AuxCoord(da.arange(6), long_name="lazy_extra"), 0)
+        res_cube = self.cube.rolling_window("val", iris.analysis.MEAN, 3)
+        result_coord = res_cube.coord("lazy_extra")
+        assert result_coord.has_lazy_points()
+        assert result_coord.has_lazy_bounds()
+        expected = AuxCoord(
+            np.array([1.0, 2.0, 3.0, 4.0]),
+            bounds=np.array([[0, 2], [1, 3], [2, 4], [3, 5]]),
+            long_name="lazy_extra",
+        )
+        assert result_coord == expected
+
     def test_ancillary_variables_and_cell_measures_kept(self, dataless):
         if dataless:
             self.cube.data = None