issue resolved

Author: konstntokas

CHANGES.md

@@ -1,3 +1,12 @@
+## Changes in 0.2.0
+
+* Switched to [xcube-resampling](https://xcube-dev.github.io/xcube-resampling/) 
+  for dataset resampling and reprojection.  
+* Renamed the keyword argument `spline_orders` to `interp_methods` to align with 
+  the naming convention used in xcube-resampling.  
+* Fixed issue #39: resolved `AttributeError: 'dict' object has no attribute 'coords'`.
+
+
 ## Changes in 0.1.1
 
 * Fixed a bug in Sentinel-2 cube generation where, during mosaicking of adjacent tiles 

docs/guide.md

@@ -174,7 +174,7 @@ These tiles are stored in their native UTM CRS, which varies by geographic locat
 | Condition        | Requested bounding box lies within a single UTM zone, native CRS is requested, and the spatial resolution matches the native resolution.                                                                                                                                            | Data spans multiple UTM zones, a different CRS is requested (e.g., EPSG:4326), or a custom spatial resolution is requested.                                                                |
 | Processing steps | Only upsampling or downsampling is applied to align the differing resolutions of the spectral bands. Data cube is directly cropped using the requested bounding box, preserving original pixel values. Spatial extent may deviate slightly due to alignment with native pixel grid. | A target grid mapping is computed from bounding box, spatial resolution, and CRS. Data from each UTM zone is reprojected/resampled to this grid. Overlaps resolved by first non-NaN pixel. |
 
-Upsampling and downsampling are controlled using the `agg_methods` and `spline_order`
+Upsampling and downsampling are controlled using the `agg_methods` and `interp_methods`
 parameters ([see below](#remarks-to-opening-parameters)).
 
 #### Data Identifiers
@@ -209,20 +209,21 @@ subsequently performs the reprojection.
 
 **Upsampling / Reprojecting:**  
 
-- Controlled via 2D interpolation using the `spline_orders` parameter. 
-- Accepts a single order for all variables, or a dictionary mapping orders to variable 
-  names or data types.
-- Supported spline orders: 
-    - `0`: nearest neighbor (default for `scl`)
-    - `1`: linear
-    - `2`: bi-linear
-    - `3`: cubic (default)
+- Controlled via 2D interpolation using the `interp_methods` parameter. 
+- Accepts a single interpolation method for all variables, or a dictionary mapping from
+  variable names or data types to specific interpolation methods.
+- Supported interpolation methods: 
+    - `0` (nearest neighbor)
+    - `1` (linear / bilinear)
+    - `"nearest"`
+    - `"triangular"`
+    - `"bilinear"`
 
 **Downsampling:**  
 
 - Controlled via the `agg_methods` parameter.
-- Can be specified as a single method for all variables, or as a dictionary mapping
-  methods to variable names or data types.  
+- Can be specified as a single method for all variables, or a dictionary mapping from
+  variable names or data types to specific interpolation methods. 
 - Supported aggregation methods:
     - `"center"` (default for `scl`)
     - `"count"`

environment.yml

@@ -12,6 +12,7 @@ dependencies:
   - xarray
   - xarray-eopf >=0.1.1
   - xcube >=1.11.0
+  - xcube-resampling
   # Development Dependencies - Tools
   - black
   - isort

pyproject.toml

@@ -48,7 +48,8 @@ dependencies = [
   "pystac-client",
   "xarray",
   "xarray-eopf>=0.1.1",
-  "xcube-core>=1.11.0"
+  "xcube-core>=1.11.0",
+  "xcube-resampling",
 ]
 
 [project.optional-dependencies]

tests/test_store.py

@@ -117,7 +117,7 @@ def test_open_data_10m(self, mock_xarray):
             spatial_res=10,
             crs="EPSG:32632",
             variables=["b02", "b03", "b04", "scl"],
-            spline_orders={0: [np.float32], 3: ["scl"]},
+            interp_methods={np.float32: 0, "scl": 3},
         )
         self.assertIsInstance(ds, xr.Dataset)
         self.assertCountEqual(["b02", "b03", "b04", "scl"], list(ds.data_vars))
@@ -135,26 +135,17 @@ def test_open_data_10m(self, mock_xarray):
 
     @pytest.mark.vcr()
     @patch("xarray.open_dataset")
-    def test_open_data_5m_spline_order(self, mock_xarray):
+    def test_open_data_5m_interp_method(self, mock_xarray):
         mock_xarray.return_value = l2a_10m()
-
-        with self.assertLogs("xcube.eopf", level="WARNING") as cm:
-            ds = self.store.open_data(
-                data_id="sentinel-2-l2a",
-                bbox=(610000, 5880000, 630000, 5900000),
-                time_range=["2025-05-01", "2025-05-15"],
-                spatial_res=5,
-                crs="EPSG:32632",
-                variables=["b02", "b03", "b04", "scl"],
-                spline_orders={0: [np.float32], 3: ["scl"]},
-            )
-        self.assertEqual(1, len(cm.output))
-        msg = (
-            f"WARNING:xcube.eopf:Spline order 3 selected for 'scl' "
-            f"(categorical data). This may produce corrupted results."
+        ds = self.store.open_data(
+            data_id="sentinel-2-l2a",
+            bbox=(610000, 5880000, 630000, 5900000),
+            time_range=["2025-05-01", "2025-05-15"],
+            spatial_res=5,
+            crs="EPSG:32632",
+            variables=["b02", "b03", "b04", "scl"],
+            interp_methods={np.dtype("float64"): "bilinear", "scl": "nearest"},
         )
-        self.assertEqual(msg, str(cm.output[-1]))
-
         self.assertIsInstance(ds, xr.Dataset)
         self.assertCountEqual(["b02", "b03", "b04", "scl"], list(ds.data_vars))
         self.assertCountEqual(
@@ -173,24 +164,15 @@ def test_open_data_5m_spline_order(self, mock_xarray):
     @patch("xarray.open_dataset")
     def test_open_data_100m_agg_methods(self, mock_xarray):
         mock_xarray.return_value = l2a_60m()
-
-        with self.assertLogs("xcube.eopf", level="WARNING") as cm:
-            ds = self.store.open_data(
-                data_id="sentinel-2-l2a",
-                bbox=(610000, 5880000, 630000, 5900000),
-                time_range=["2025-05-01", "2025-05-15"],
-                spatial_res=100,
-                crs="EPSG:32632",
-                variables=["b02", "b03", "b04", "scl"],
-                agg_methods={"max": [np.float32], "mean": ["scl"]},
-            )
-        self.assertEqual(1, len(cm.output))
-        msg = (
-            "WARNING:xcube.eopf:Aggregation method 'mean' selected for 'scl' "
-            "(categorical data). This may produce corrupted results."
+        ds = self.store.open_data(
+            data_id="sentinel-2-l2a",
+            bbox=(610000, 5880000, 630000, 5900000),
+            time_range=["2025-05-01", "2025-05-15"],
+            spatial_res=100,
+            crs="EPSG:32632",
+            variables=["b02", "b03", "b04", "scl"],
+            agg_methods={np.dtype("float64"): "max", "scl": "mode"},
         )
-        self.assertEqual(msg, str(cm.output[-1]))
-
         self.assertIsInstance(ds, xr.Dataset)
         self.assertCountEqual(["b02", "b03", "b04", "scl"], list(ds.data_vars))
         self.assertCountEqual(
@@ -239,48 +221,6 @@ def test_open_data_geographic(self, mock_xarray):
         self.assertIn("open_params", ds.attrs)
         self.assertIn("xcube_eopf_version", ds.attrs)
 
-    @pytest.mark.vcr()
-    @patch("xarray.open_dataset")
-    def test_open_data_spline_order_raise_logs(self, mock_xarray):
-        mock_xarray.return_value = l2a_60m()
-
-        bbox = [610000, 5880000, 630000, 5900000]
-        bbox_wgs84 = reproject_bbox(bbox, "EPSG:32632", "EPSG:4326")
-        with self.assertLogs("xcube.eopf", level="WARNING") as cm:
-            ds = self.store.open_data(
-                data_id="sentinel-2-l2a",
-                bbox=bbox_wgs84,
-                time_range=["2025-05-01", "2025-05-15"],
-                spatial_res=50 / CONVERSION_FACTOR_DEG_METER,
-                crs="EPSG:4326",
-                variables=["b02", "b03", "b04", "scl"],
-                spline_orders=2,
-            )
-        self.assertEqual(1, len(cm.output))
-        msg = (
-            "WARNING:xcube.eopf:User-defined spline-orders is not supported yet, "
-            "when reprojecting to a different CRS. Default interpolation will be "
-            "used: bilinear for continuous data, and nearest-neighbor for 'scl'."
-        )
-        self.assertEqual(msg, str(cm.output[-1]))
-        self.assertIsInstance(ds, xr.Dataset)
-        self.assertCountEqual(["b02", "b03", "b04", "scl"], list(ds.data_vars))
-        self.assertCountEqual(
-            [4, 412, 684], [ds.sizes["time"], ds.sizes["lat"], ds.sizes["lon"]]
-        )
-        self.assertEqual(
-            [1, 412, 684],
-            [
-                ds.chunksizes["time"][0],
-                ds.chunksizes["lat"][0],
-                ds.chunksizes["lon"][0],
-            ],
-        )
-        self.assertIn("stac_url", ds.attrs)
-        self.assertIn("stac_items", ds.attrs)
-        self.assertIn("open_params", ds.attrs)
-        self.assertIn("xcube_eopf_version", ds.attrs)
-
     @pytest.mark.vcr()
     def test_open_data_no_items_found(self):
         with self.assertRaises(DataStoreError) as cm:

tests/test_utils.py

@@ -9,7 +9,7 @@
 import pyproj
 import pystac
 import xarray as xr
-from xcube.core.gridmapping import GridMapping
+from xcube_resampling.gridmapping import GridMapping
 from xcube.core.store import DataStoreError
 
 from xcube_eopf.utils import (