fix: trying to update the band names

src/fusets/openeo/mogpr_udf.py

@@ -4,8 +4,8 @@
 from pathlib import Path
 from typing import Dict
 
-from openeo.metadata import CollectionMetadata, Band
-from openeo.udf import XarrayDataCube
+from openeo.metadata import Band, CollectionMetadata
+from openeo.udf import XarrayDataCube, inspect
 
 
 def load_venv():
@@ -41,6 +41,14 @@ def write_gpy_cfg():
     return home
 
 
+def apply_metadata(metadata: CollectionMetadata, context: dict) -> CollectionMetadata:
+    extra_bands = [Band(f"{x}_STD", None, None) for x in metadata.bands]
+    inspect(data=metadata, message="MOGPR metadata")
+    for band in extra_bands:
+        metadata = metadata.append_band(band)
+    return metadata
+
+
 def apply_datacube(cube: XarrayDataCube, context: Dict) -> XarrayDataCube:
     """
     Apply mogpr integration to a datacube.
@@ -65,20 +73,14 @@ def apply_datacube(cube: XarrayDataCube, context: Dict) -> XarrayDataCube:
         variables=variables,
         time_dimension=time_dimension,
         prediction_period=prediction_period,
-        include_uncertainties=include_uncertainties
+        include_uncertainties=include_uncertainties,
     )
     result_dc = XarrayDataCube(result.to_array(dim="bands").transpose(*dims))
+    inspect(data=result_dc, message="MOGPR result")
     set_home(home)
     return result_dc
 
 
-def apply_metadata(metadata: CollectionMetadata, context: dict) -> CollectionMetadata:
-    extra_bands = [Band(f"{x}_STD", None, None) for x in metadata.bands]
-    for band in extra_bands:
-        metadata = metadata.append_band(band)
-    return metadata
-
-
 def load_mogpr_udf() -> str:
     """
     Loads an openEO udf that applies mogpr.

src/fusets/openeo/services/publish_mogpr.py

@@ -4,10 +4,10 @@
 import openeo
 from openeo import DataCube
 from openeo.api.process import Parameter
-from openeo.processes import apply_neighborhood, ProcessBuilder
+from openeo.processes import ProcessBuilder, apply_neighborhood
 
 from fusets.openeo import load_mogpr_udf
-from fusets.openeo.services.helpers import publish_service, read_description, get_context_value
+from fusets.openeo.services.helpers import get_context_value, publish_service, read_description
 
 NEIGHBORHOOD_SIZE = 32
 
@@ -18,46 +18,29 @@ def execute_udf():
         "type": "Polygon",
         "coordinates": [
             [
-                [
-                    5.170012098271149,
-                    51.25062964728295
-                ],
-                [
-                    5.17085904378298,
-                    51.24882567194015
-                ],
-                [
-                    5.17857421368097,
-                    51.2468515482926
-                ],
-                [
-                    5.178972704726344,
-                    51.24982704376254
-                ],
-                [
-                    5.170012098271149,
-                    51.25062964728295
-                ]
+                [5.170012098271149, 51.25062964728295],
+                [5.17085904378298, 51.24882567194015],
+                [5.17857421368097, 51.2468515482926],
+                [5.178972704726344, 51.24982704376254],
+                [5.170012098271149, 51.25062964728295],
             ]
-        ]
+        ],
     }
     temp_ext = ["2023-01-01", "2023-03-31"]
 
     # Setup NDVI cube
-    base_s2 = connection.load_collection('SENTINEL2_L2A',
-                                         spatial_extent=spat_ext,
-                                         temporal_extent=temp_ext,
-                                         bands=["B04", "B08", "SCL"])
+    base_s2 = connection.load_collection(
+        "SENTINEL2_L2A", spatial_extent=spat_ext, temporal_extent=temp_ext, bands=["B04", "B08", "SCL"]
+    )
     base_s2 = base_s2.process("mask_scl_dilation", data=base_s2, scl_band_name="SCL")
-    base_s2 = base_s2.ndvi(red="B04", nir="B08", target_band='NDVI')
-    base_s2 = base_s2.filter_bands(bands=['NDVI'])
+    base_s2 = base_s2.ndvi(red="B04", nir="B08", target_band="NDVI")
+    base_s2 = base_s2.filter_bands(bands=["NDVI"])
     base_s2 = base_s2.mask_polygon(spat_ext)
 
     # Setup RVI cube
-    base_s1 = connection.load_collection('SENTINEL1_GRD',
-                                         spatial_extent=spat_ext,
-                                         temporal_extent=temp_ext,
-                                         bands=["VH", "VV"])
+    base_s1 = connection.load_collection(
+        "SENTINEL1_GRD", spatial_extent=spat_ext, temporal_extent=temp_ext, bands=["VH", "VV"]
+    )
 
     VH = base_s1.band("VH")
     VV = base_s1.band("VV")
@@ -68,8 +51,7 @@ def execute_udf():
     merged_datacube = base_s2.merge(base_s1)
 
     # Execute MOGPR
-    mogpr = connection.datacube_from_flat_graph(
-        generate_mogpr_cube(merged_datacube, True).flat_graph())
+    mogpr = connection.datacube_from_flat_graph(generate_mogpr_cube(merged_datacube, True).flat_graph())
     mogpr.execute_batch(
         "./result_mogpr.nc",
         title=f"FuseTS - MOGPR - Local",
@@ -84,14 +66,15 @@ def execute_udf():
 
 
 def generate_mogpr_cube(
-        input_cube: Union[DataCube, ProcessBuilder, Parameter],
-        include_uncertainties: Union[bool, Parameter]
+    input_cube: Union[DataCube, ProcessBuilder, Parameter], include_uncertainties: Union[bool, Parameter]
 ):
     return apply_neighborhood(
         input_cube,
-        lambda data: data.run_udf(udf=load_mogpr_udf(), runtime="Python-Jep", context={
-            'include_uncertainties': get_context_value(include_uncertainties)
-        }),
+        lambda data: data.run_udf(
+            udf=load_mogpr_udf(),
+            runtime="Python-Jep",
+            context={"include_uncertainties": get_context_value(include_uncertainties)},
+        ),
         size=[
             {"dimension": "x", "value": NEIGHBORHOOD_SIZE, "unit": "px"},
             {"dimension": "y", "value": NEIGHBORHOOD_SIZE, "unit": "px"},
@@ -106,7 +89,8 @@ def generate_mogpr_udp():
     input_cube = Parameter.raster_cube()
 
     include_uncertainties = Parameter.boolean(
-        "include_uncertainties", "Flag to include the uncertainties in the output results", False)
+        "include_uncertainties", "Flag to include the uncertainties in the output results", False
+    )
 
     mogpr = generate_mogpr_cube()