Fix lint

src/openeo_gfmap/fetching/generic.py

@@ -1,118 +1,127 @@
 """ Generic extraction of features, supporting VITO backend.
 """
-from openeo_gfmap.fetching import CollectionFetcher,FetchType
+from functools import partial
 from typing import Callable
+
 import openeo
+from geojson import GeoJSON
+
 from openeo_gfmap.backend import Backend, BackendContext
-from openeo_gfmap.spatial import BoundingBoxExtent, SpatialContext
-from openeo_gfmap.temporal import TemporalContext
+from openeo_gfmap.fetching import CollectionFetcher, FetchType
 from openeo_gfmap.fetching.commons import (
     convert_band_names,
     load_collection,
     rename_bands,
 )
-from functools import partial
-from geojson import GeoJSON
-
-BASE_DEM_MAPPING = {'DEM':'COP-DEM'}
-BASE_WEATHER_MAPPING = {'dewpoint-temperature':'A5-dewtemp',
-                        'precipitation-flux':'A5-precip',
-                        'solar-radiation-flux':'A5-solrad',
-                        'temperature-max':'A5-tmax',
-                        'temperature-mean':'A5-tmean',
-                        'temperature-min':'A5-tmin',
-                        'vapour-pressure':'A5-vapour',
-                        'wind-speed':'A5-wind'}
+from openeo_gfmap.spatial import SpatialContext
+from openeo_gfmap.temporal import TemporalContext
+
+BASE_DEM_MAPPING = {"DEM": "COP-DEM"}
+BASE_WEATHER_MAPPING = {
+    "dewpoint-temperature": "A5-dewtemp",
+    "precipitation-flux": "A5-precip",
+    "solar-radiation-flux": "A5-solrad",
+    "temperature-max": "A5-tmax",
+    "temperature-mean": "A5-tmean",
+    "temperature-min": "A5-tmin",
+    "vapour-pressure": "A5-vapour",
+    "wind-speed": "A5-wind",
+}
 
-def get_generic_fetcher(collection_name: str, fetch_type: FetchType) -> Callable:
 
-    if collection_name == 'COPERNICUS_30':
+def get_generic_fetcher(collection_name: str, fetch_type: FetchType) -> Callable:
+    if collection_name == "COPERNICUS_30":
         BASE_MAPPING = BASE_DEM_MAPPING
-    elif collection_name == 'AGERA5':
+    elif collection_name == "AGERA5":
         BASE_MAPPING = BASE_WEATHER_MAPPING
     else:
-        raise Exception('Please choose a valid collection.')
+        raise Exception("Please choose a valid collection.")
 
     def generic_default_fetcher(
         connection: openeo.Connection,
         spatial_extent: SpatialContext,
         temporal_extent: TemporalContext,
         bands: list,
         **params,
-        ) -> openeo.DataCube:
-
+    ) -> openeo.DataCube:
         bands = convert_band_names(bands, BASE_MAPPING)
 
         cube = load_collection(
-                connection,
-                bands,
-                collection_name,
-                spatial_extent,
-                temporal_extent,
-                fetch_type,
-                **params,
-                )
-                
-                # Apply if the collection is a GeoJSON Feature collection
+            connection,
+            bands,
+            collection_name,
+            spatial_extent,
+            temporal_extent,
+            fetch_type,
+            **params,
+        )
+
+        # Apply if the collection is a GeoJSON Feature collection
         if isinstance(spatial_extent, GeoJSON):
             cube = cube.filter_spatial(spatial_extent)
 
         return cube
 
     return generic_default_fetcher
 
+
 def get_generic_processor(collection_name: str, fetch_type: FetchType) -> Callable:
     """Builds the preprocessing function from the collection name as it stored
     in the target backend.
     """
-    if collection_name == 'COPERNICUS_30':
+    if collection_name == "COPERNICUS_30":
         BASE_MAPPING = BASE_DEM_MAPPING
-    elif collection_name == 'AGERA5':
+    elif collection_name == "AGERA5":
         BASE_MAPPING = BASE_WEATHER_MAPPING
     else:
-        raise Exception('Please choose a valid collection.')
-    
+        raise Exception("Please choose a valid collection.")
+
     def generic_default_processor(cube: openeo.DataCube, **params):
         """Default collection preprocessing method for generic datasets.
-        This method renames bands and removes the time dimension in case the 
+        This method renames bands and removes the time dimension in case the
         requested dataset is DEM
         """
 
         cube = rename_bands(cube, BASE_MAPPING)
 
-        if collection_name =='COPERNICUS_30':
+        if collection_name == "COPERNICUS_30":
             cube = cube.min_time()
 
         return cube
 
     return generic_default_processor
 
-OTHER_BACKEND_MAP = {'AGERA5':
-        {
-            Backend.TERRASCOPE: {
+
+OTHER_BACKEND_MAP = {
+    "AGERA5": {
+        Backend.TERRASCOPE: {
             "fetch": partial(get_generic_fetcher, collection_name="AGERA5"),
             "preprocessor": partial(get_generic_processor, collection_name="AGERA5"),
-            },
-            Backend.CDSE: {
+        },
+        Backend.CDSE: {
             "fetch": partial(get_generic_fetcher, collection_name="AGERA5"),
             "preprocessor": partial(get_generic_processor, collection_name="AGERA5"),
-            },
         },
-                    'COPERNICUS_30':
-        {
-            Backend.TERRASCOPE: {
+    },
+    "COPERNICUS_30": {
+        Backend.TERRASCOPE: {
             "fetch": partial(get_generic_fetcher, collection_name="COPERNICUS_30"),
             "preprocessor": partial(get_generic_processor, collection_name="COPERNICUS_30"),
-            },
-            Backend.CDSE: {
+        },
+        Backend.CDSE: {
             "fetch": partial(get_generic_fetcher, collection_name="COPERNICUS_30"),
             "preprocessor": partial(get_generic_processor, collection_name="COPERNICUS_30"),
-            },
-        }
-        }
+        },
+    },
+}
+
 
 def build_generic_extractor(
-    backend_context: BackendContext, bands: list, fetch_type: FetchType, collection_name: str, **params
+    backend_context: BackendContext,
+    bands: list,
+    fetch_type: FetchType,
+    collection_name: str,
+    **params,
 ) -> CollectionFetcher:
     """Creates a generic extractor adapted to the given backend. Currently only tested with VITO backend"""
     backend_functions = OTHER_BACKEND_MAP.get(collection_name).get(backend_context.backend)

src/openeo_gfmap/fetching/s1.py

@@ -5,7 +5,6 @@
 
 import openeo
 from geojson import GeoJSON
-from openeo.processes import array_create, if_, is_nodata, power
 
 from openeo_gfmap.backend import Backend, BackendContext
 from openeo_gfmap.spatial import SpatialContext

src/openeo_gfmap/preprocessing/compositing.py

@@ -39,14 +39,12 @@ def max_ndvi_selection(ndvi: openeo.DataCube):
             size=[
                 {"dimension": "x", "unit": "px", "value": 1},
                 {"dimension": "y", "unit": "px", "value": 1},
-                {"dimension": "t", "value": period}
+                {"dimension": "t", "value": period},
             ],
-            overlap=[]
+            overlap=[],
         )
 
-        cube = cube.mask(mask=rank_mask).aggregate_temporal_period(
-            period, "first"
-        )
+        cube = cube.mask(mask=rank_mask).aggregate_temporal_period(period, "first")
 
     else:
         raise ValueError(

src/openeo_gfmap/preprocessing/sar.py

@@ -1,11 +1,13 @@
 """Routines to pre-process sar signals."""
 import openeo
-from openeo.processes import if_, power, is_nodata, array_create
+from openeo.processes import array_create, if_, is_nodata, power
 
-from openeo_gfmap import BackendContext, Backend
+from openeo_gfmap import Backend, BackendContext
 
 
-def compress_backscatter_uint16(backend_context: BackendContext, cube: openeo.DataCube) -> openeo.DataCube:
+def compress_backscatter_uint16(
+    backend_context: BackendContext, cube: openeo.DataCube
+) -> openeo.DataCube:
     """
     Scaling the bands from float32 power values to uint16 for memory optimization. The scaling
     casts the values from power to decibels and applies a linear scaling from 0 to 65534.

src/openeo_gfmap/spatial.py

@@ -42,7 +42,7 @@ def __iter__(self):
 
     def to_geometry(self) -> Polygon:
         return box(self.west, self.south, self.east, self.north)
-    
+
     def to_geojson(self) -> GeoJSON:
         return self.to_geometry().__geo_interface__
 

tests/test_openeo_gfmap/test_feature_extractors.py

@@ -12,7 +12,6 @@
     BackendContext,
     cdse_connection,
 )
-from openeo_gfmap.preprocessing.sar import compress_backscatter_uint16
 from openeo_gfmap.features import (
     PatchFeatureExtractor,
     apply_feature_extractor,
@@ -22,6 +21,7 @@
     build_sentinel1_grd_extractor,
     build_sentinel2_l2a_extractor,
 )
+from openeo_gfmap.preprocessing.sar import compress_backscatter_uint16
 
 SPATIAL_CONTEXT = BoundingBoxExtent(
     west=4.261,

tests/test_openeo_gfmap/test_s1_fetchers.py

@@ -21,9 +21,7 @@
     FetchType,
     build_sentinel1_grd_extractor,
 )
-from openeo_gfmap.preprocessing.sar import (
-    compress_backscatter_uint16
-)
+from openeo_gfmap.preprocessing.sar import compress_backscatter_uint16
 from openeo_gfmap.utils import (
     array_bounds,
     arrays_cosine_similarity,