Avoid dimensionality mismatch between data array and CF variables. (#4610)

Author: trexfeathers

docs/src/whatsnew/3.2.rst

@@ -44,6 +44,10 @@ v3.2.1 |build_date| [unreleased]
       attribute from a given CRS instead of creating a new `ccrs.Globe()` object.
       Iris can now handle non-Earth semi-major axes, as discussed in :issue:`4582` (:pull:`4605`).
 
+   #. `@trexfeathers`_ avoided a dimensionality mismatch when streaming the
+      :attr:`~iris.coords.Coord.bounds` array for a scalar
+      :class:`~iris.coords.Coord`. (:pull:`4610`).
+
    💼 **Internal**
 
    #. N/A
@@ -198,7 +202,7 @@ v3.2.1 |build_date| [unreleased]
    from assuming the globe to be the Earth (:issue:`4408`, :pull:`4497`)
 
 #. `@rcomer`_ corrected the ``long_name`` mapping from UM stash code ``m01s09i215``
-   to indicate cloud fraction greater than 7.9 oktas, rather than 7.5 
+   to indicate cloud fraction greater than 7.9 oktas, rather than 7.5
    (:issue:`3305`, :pull:`4535`)
 
 #. `@lbdreyer`_ fixed a bug in :class:`iris.io.load_http` which was missing an import

lib/iris/fileformats/netcdf.py

@@ -2865,6 +2865,14 @@ def _increment_name(self, varname):
 
     @staticmethod
     def _lazy_stream_data(data, fill_value, fill_warn, cf_var):
+        if hasattr(data, "shape") and data.shape == (1,) + cf_var.shape:
+            # (Don't do this check for string data).
+            # Reduce dimensionality where the data array has an extra dimension
+            #  versus the cf_var - to avoid a broadcasting ambiguity.
+            # Happens when bounds data is for a scalar point - array is 2D but
+            #  contains just 1 row, so the cf_var is 1D.
+            data = data.squeeze(axis=0)
+
         if is_lazy_data(data):
 
             def store(data, cf_var, fill_value):

lib/iris/tests/unit/fileformats/netcdf/test_Saver.py

@@ -30,7 +30,7 @@
     TransverseMercator,
     VerticalPerspective,
 )
-from iris.coords import DimCoord
+from iris.coords import AuxCoord, DimCoord
 from iris.cube import Cube
 from iris.fileformats.netcdf import Saver
 import iris.tests.stock as stock
@@ -299,6 +299,22 @@ def test_with_climatology(self):
                 saver.write(cube)
             self.assertCDL(nc_path)
 
+    def test_dimensional_to_scalar(self):
+        # Bounds for 1 point are still in a 2D array.
+        scalar_bounds = self.array_lib.arange(2).reshape(1, 2)
+        scalar_point = scalar_bounds.mean()
+        scalar_data = self.array_lib.zeros(1)
+        scalar_coord = AuxCoord(points=scalar_point, bounds=scalar_bounds)
+        cube = Cube(scalar_data, aux_coords_and_dims=[(scalar_coord, 0)])[0]
+        with self.temp_filename(".nc") as nc_path:
+            with Saver(nc_path, "NETCDF4") as saver:
+                saver.write(cube)
+            ds = nc.Dataset(nc_path)
+            # Confirm that the only dimension is the one denoting the number
+            #  of bounds - have successfully saved the 2D bounds array into 1D.
+            self.assertEqual(["bnds"], list(ds.dimensions.keys()))
+            ds.close()
+
 
 class Test__create_cf_bounds(tests.IrisTest):
     # Method is substituted in test_Saver__lazy.