done

Author: konstntokas

CHANGES.md

@@ -2,7 +2,9 @@
 
 - Fixed an issue in `rectify_dataset` when processing datasets with decreasing 
   x-coordinates.
-
+- Boolean (`bool`) data arrays now default to nearest-neighbor interpolation and 
+  center for spatial aggregation, matching the behavior of integer arrays to 
+  ensure valid results.
 
 ## Changes in 0.3.0
 

tests/test_utils.py

@@ -117,6 +117,9 @@ def test_n_get_grid_mapping_name(self):
 
     def test_get_interp_method(self):
         int_var = xr.DataArray(np.array([1, 2, 3], dtype=np.int32), dims=["x"])
+        bool_var = xr.DataArray(
+            np.array([True, False, True], dtype=np.bool_), dims=["x"]
+        )
         float_var = xr.DataArray(
             np.array([1.0, 2.0, 3.0], dtype=np.float32), dims=["x"]
         )
@@ -125,6 +128,10 @@ def test_get_interp_method(self):
         result = _get_spatial_interp_method(None, "var", int_var)
         self.assertEqual(result, 0)
 
+        # bool type data array
+        result = _get_spatial_interp_method(None, "var", bool_var)
+        self.assertEqual(result, 0)
+
         # float type data array
         result = _get_spatial_interp_method(None, "var", float_var)
         self.assertEqual(result, 1)
@@ -182,6 +189,9 @@ def test_prep_interp_methods_downscale(self):
 
     def test_get_agg_method(self):
         int_var = xr.DataArray(np.array([1, 2, 3], dtype=np.int32), dims=["x"])
+        bool_var = xr.DataArray(
+            np.array([True, False, True], dtype=np.bool_), dims=["x"]
+        )
         float_var = xr.DataArray(
             np.array([1.0, 2.0, 3.0], dtype=np.float32), dims=["x"]
         )
@@ -190,6 +200,10 @@ def test_get_agg_method(self):
         result = _get_spatial_agg_method(None, "var", int_var)
         self.assertEqual(result, AGG_METHODS["center"])
 
+        # bool type data array, default
+        result = _get_spatial_agg_method(None, "var", bool_var)
+        self.assertEqual(result, AGG_METHODS["center"])
+
         # float type data array, default
         result = _get_spatial_agg_method(None, "var", float_var)
         self.assertEqual(result, AGG_METHODS["mean"])

xcube_resampling/utils.py

@@ -379,7 +379,11 @@ def _get_spatial_interp_method(
     var: xr.DataArray,
 ) -> SpatialInterpMethod:
     def assign_defaults(data_type: np.dtype) -> SpatialInterpMethod:
-        return 0 if np.issubdtype(data_type, np.integer) else 1
+        if np.issubdtype(data_type, np.bool_):
+            return 0
+        if np.issubdtype(data_type, np.integer):
+            return 0
+        return 1
 
     if isinstance(interp_methods, Mapping):
         interp_method = interp_methods.get(str(key), interp_methods.get(var.dtype))
@@ -450,7 +454,11 @@ def _get_spatial_agg_method(
     var: xr.DataArray,
 ) -> Callable:
     def assign_defaults(data_type: np.dtype) -> SpatialAggMethod:
-        return "center" if np.issubdtype(data_type, np.integer) else "mean"
+        if np.issubdtype(data_type, np.bool_):
+            return "center"
+        if np.issubdtype(data_type, np.integer):
+            return "center"
+        return "mean"
 
     if isinstance(agg_methods, Mapping):
         agg_method = agg_methods.get(str(key), agg_methods.get(var.dtype))