BUG: Zonal stats with method='exactextract' not working on flat xarray.Dataarray (#132)

* fix #131

* fix typos

* add new tests covering "flat" Dataset and Dataarray

* lint

---------

Co-authored-by: Martin Fleischmann <martin@martinfleischmann.net>

Author: maawoo

xvec/tests/test_zonal_stats.py

@@ -147,6 +147,36 @@ def test_dataset(method):
         )
 
 
+@pytest.mark.parametrize("method", [None, "rasterize", "iterate", "exactextract"])
+def test_dataset_flat(method):
+    ds = xr.tutorial.open_dataset("eraint_uvz").isel(month=0).isel(level=0)
+    world = gpd.read_file(geodatasets.get_path("naturalearth land"))
+    result = ds.xvec.zonal_stats(world.geometry, "longitude", "latitude", method=method)
+
+    if method in ["exactextract", None]:
+        xr.testing.assert_allclose(
+            xr.Dataset(
+                {
+                    "z": np.array(114857.63685302),
+                    "u": np.array(9.84182437),
+                    "v": np.array(-0.00330402),
+                }
+            ),
+            result.mean(),
+        )
+    else:
+        xr.testing.assert_allclose(
+            xr.Dataset(
+                {
+                    "z": np.array(114302.08524294),
+                    "u": np.array(9.5196515),
+                    "v": np.array(0.29297792),
+                }
+            ),
+            result.drop_vars(["month", "level"]).mean(),
+        )
+
+
 @pytest.mark.parametrize("method", [None, "rasterize", "iterate", "exactextract"])
 def test_dataarray(method):
     ds = xr.tutorial.open_dataset("eraint_uvz")
@@ -163,6 +193,24 @@ def test_dataarray(method):
         assert result.mean() == pytest.approx(61367.76185577)
 
 
+@pytest.mark.parametrize("method", [None, "rasterize", "iterate", "exactextract"])
+def test_dataarray_flat(method):
+    ds = xr.tutorial.open_dataset("eraint_uvz")
+    world = gpd.read_file(geodatasets.get_path("naturalearth land"))
+    result = (
+        ds.z.isel(month=0)
+        .isel(level=0)
+        .xvec.zonal_stats(world.geometry, "longitude", "latitude", method=method)
+    )
+
+    assert result.shape == (127,)
+    assert result.dims == ("geometry",)
+    if method in ["exactextract", None]:
+        assert result.mean() == pytest.approx(114857.63685302)
+    else:
+        assert result.mean() == pytest.approx(114302.08524294)
+
+
 @pytest.mark.parametrize("method", [None, "rasterize", "iterate", "exactextract"])
 def test_stat(method):
     ds = xr.tutorial.open_dataset("eraint_uvz")

xvec/zonal.py

@@ -698,8 +698,14 @@ def _agg_exactextract(
 
     # Stack the other dimensions into one dimension called "location"
     arr_dims = tuple(dim for dim in acc._obj.dims if dim not in [x_coords, y_coords])
-    data = acc._obj.stack(location=arr_dims)
-    locs = data.location.size
+    if arr_dims:
+        # Stack non-spatial dimensions if they exist
+        data = acc._obj.stack(location=arr_dims)
+        locs = data.location.size
+    else:
+        # No additional dimensions to stack, create a dummy "location" dimension
+        data = acc._obj.expand_dims("location")
+        locs = 1
 
     # Check the order of dimensions
     data = data.transpose("location", y_coords, x_coords)
@@ -713,23 +719,25 @@ def _agg_exactextract(
     results = exactextract.exact_extract(
         rast=data, vec=gdf, ops=stats, output="pandas", strategy=strategy
     )
-    # Get all the dimensions execpt x_coords, y_coords, they will be used to stack the
+    # Get all the dimensions except x_coords, y_coords, they will be used to stack the
     # dataarray later
     if original_is_ds is True:
-        # Get the original dataset information to use for unstacking the resulte later
+        # Get the original dataset information to use for unstacking the result later
         coords_info = {name: geometry}
         original_shape = [len(geometry)]
-        for dim in arr_dims:
-            original_shape.append(acc._obj[dim].size)
-            if dim != "variable":
-                coords_info[dim] = acc._obj[dim].values
+        if arr_dims:
+            for dim in arr_dims:
+                original_shape.append(acc._obj[dim].size)
+                if dim != "variable":
+                    coords_info[dim] = acc._obj[dim].values
     else:
-        # Get the original dataarray information to use for unstacking the resulte later
+        # Get the original dataarray information to use for unstacking the result later
         coords_info = {name: geometry}
         original_shape = [len(geometry)]
-        for dim in arr_dims:
-            original_shape.append(acc._obj[dim].size)
-            coords_info[dim] = acc._obj[dim].values
+        if arr_dims:
+            for dim in arr_dims:
+                original_shape.append(acc._obj[dim].size)
+                coords_info[dim] = acc._obj[dim].values
     return results, original_shape, coords_info, locs