add predict_catboost_probabilities process

see Open-EO/openeo-geopyspark-driver#143

openeo/rest/datacube.py

@@ -890,7 +890,7 @@ def apply_dimension(
             process = PGNode.to_process_graph_argument(callback_process_node)
         elif code or process:
             # TODO EP-3555 unify `code` and `process`
-            process = self._get_callback(code or process, parent_parameters=["data"])
+            process = self._get_callback(code or process, parent_parameters=["data", "context"])
         else:
             raise OpenEoClientException("No UDF code or process given")
         arguments = {
@@ -1902,6 +1902,27 @@ def predict_catboost(self, model: Union[str, RESTJob, MlModel], dimension: str =
         reducer = lambda data, context: process('predict_catboost', data=data, model=context)
         return self.reduce_dimension(dimension=dimension, reducer=reducer, context=model)
 
+    @openeo_process(mode="apply_dimension")
+    def predict_catboost_probabilities(self, model: Union[str, RESTJob, MlModel], dimension: str = "bands"):
+        """
+        Apply ``apply_dimension`` with `predict_catboost` as process.
+
+       :param model: a reference to a trained model, one of
+                - a :py:class:`MlModel` instance (e.g. loaded from :py:meth:`Connection.load_ml_model`)
+                - a :py:class:`RESTJob` instance of a batch job that saved a single random forest model
+                - a job id (``str``) of a batch job that saved a single random forest model
+                - a STAC item URL (``str``) to load the random forest from.
+                  (The STAC Item must implement the `ml-model` extension.)
+        :param dimension: dimension along which to apply the ``reduce_dimension`` process.
+
+        .. versionadded:: 0.10.1
+        """
+        if not isinstance(model, MlModel):
+            model = MlModel.load_ml_model(connection=self.connection, id=model)
+        from openeo.processes import process
+        p = lambda data, context: process('predict_catboost_probabilities', data=data, model=context)
+        return self.apply_dimension(dimension=dimension, process=p, context=model)
+
     @openeo_process
     def dimension_labels(self, dimension: str) -> "DataCube":
         """