add apply_vectorcube udf

CHANGELOG.md

@@ -14,6 +14,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added `openeo.api.process.Parameter` helper to easily create a "spatial_extent" UDP parameter
 - Wrap OIDC token request failure in more descriptive `OidcException` (related to [#624](https://github.com/Open-EO/openeo-python-client/issues/624))
 - Added `auto_add_save_result` option (on by default) to disable automatic addition of `save_result` node on `download`/`create_job`/`execute_batch` ([#513](https://github.com/Open-EO/openeo-python-client/issues/513))
+- Add support for `apply_vectorcube` UDF signature in `run_udf_code` ([Open-EO/openeo-geopyspark-driver#881]https://github.com/Open-EO/openeo-geopyspark-driver/issues/811)
 
 ### Changed
 

openeo/_version.py

@@ -1 +1 @@
-__version__ = "0.32.0a1"
+__version__ = "0.32.0a2"

openeo/udf/run_code.py

@@ -88,7 +88,6 @@ def _annotation_is_data_array(annotation) -> bool:
         _get_annotation_str(xarray.DataArray)
     }
 
-
 def _annotation_is_udf_data(annotation) -> bool:
     return annotation is UdfData or _get_annotation_str(annotation) in {
         _get_annotation_str(UdfData),
@@ -196,6 +195,38 @@ def run_udf_code(code: str, data: UdfData) -> UdfData:
             result_cube: xarray.DataArray = func(cube=data.get_datacube_list()[0].get_array(), context=data.user_context)
             data.set_datacube_list([XarrayDataCube(result_cube)])
             return data
+        elif (
+            fn_name in ["apply_vectorcube"]
+            and "geometries" in params
+            and _get_annotation_str(params["geometries"].annotation) == "geopandas.geodataframe.GeoDataFrame"
+            and "cube" in params
+            and _annotation_is_data_array(params["cube"].annotation)
+        ):
+            if data.get_feature_collection_list is None or data.get_datacube_list() is None:
+                raise ValueError(
+                    "The provided UDF expects a FeatureCollection and a datacube, but received {f} and {c}".format(
+                        f=data.get_feature_collection_list(), c=data.get_datacube_list()
+                    )
+                )
+            if len(data.get_feature_collection_list()) != 1:
+                raise ValueError(
+                    "The provided UDF expects exactly one FeatureCollection, but {c} were provided.".format(
+                        c=len(data.get_feature_collection_list())
+                    )
+                )
+            if len(data.get_datacube_list()) != 1:
+                raise ValueError(
+                    "The provided UDF expects exactly one datacube, but {c} were provided.".format(
+                        c=len(data.get_datacube_list())
+                    )
+                )
+            # TODO: geopandas is optional dependency.
+            input_geoms = data.get_feature_collection_list()[0].data
+            input_cube = data.get_datacube_list()[0].get_array()
+            result_geoms, result_cube = func(geometries=input_geoms, cube=input_cube, context=data.user_context)
+            data.set_datacube_list([XarrayDataCube(result_cube)])
+            data.set_feature_collection_list([FeatureCollection(id="udf_result", data=result_geoms)])
+            return data
         elif len(params) == 1 and _annotation_is_udf_data(first_param.annotation):
             _log.info("Found generic UDF `{n}` {f!r}".format(n=fn_name, f=func))
             func(data)

openeo/udf/udf_signatures.py

@@ -6,6 +6,7 @@
 """
 # Note: this module was initially developed under the ``openeo-udf`` project (https://github.com/Open-EO/openeo-udf)
 
+import xarray
 from pandas import Series
 
 from openeo.metadata import CollectionMetadata
@@ -85,3 +86,18 @@ def apply_metadata(metadata: CollectionMetadata, context: dict) -> CollectionMet
 
     """
     pass
+
+
+def apply_vectorcube(
+    geometries: "geopandas.geodataframe.GeoDataFrame", cube: xarray.DataArray, context: dict
+) -> ("geopandas.geodataframe.GeoDataFrame", xarray.DataArray):
+    """
+    Map a vector cube to another vector cube.
+
+    :param geometries: input geometries as a geopandas.GeoDataFrame. This contains the actual shapely geometries and optional properties.
+    :param cube: a data cube with dimensions (geometries, time, bands) where time and bands are optional.
+        The coordinates for the geometry dimension are integers and match the index of the geometries in the geometries parameter.
+    :param context: A dictionary containing user context.
+    :return: output geometries, output data cube
+    """
+    pass