Fix various bugs introduced by style updates (#55)

* test log-file

* use Path in downloader

* type not iterable

* fix spatiotemporal topology handling

src/imagery/i.pytorch/pytorchlib/utils.py

@@ -197,8 +197,9 @@ def predict_torch(data_cube, config_dict=None, device=None, dl_model=None):
 
 def not_in_types(data_type, allowed_types):
     """Check if data_type is not an element of allowed_types"""
+
     allowed_types = (
-        tuple(allowed_types) if isinstance(allowed_types, type) else allowed_types
+        (allowed_types,) if isinstance(allowed_types, type) else allowed_types
     )
     if data_type is None:
         data_type_str = "'None'"

src/temporal/t.import.hrsi/t.import.hrsi.py

@@ -257,7 +257,7 @@ def __init__(
         #: Attribute for storing a dictionary with the access token for downloading Copernicus Cryosphere data
         self.token = {}
         #: Attribute containg directory to which data is downloaded or written to
-        self.output_directory = output_directory
+        self.output_directory = Path(output_directory)
         # Check if download directory is writable
         check_permissions(self.output_directory, "Download")
         #: Attribute containg a maximum number for retries for incomplete downloads (may happen if connection is closed prematurely or empty chunk of data is send
@@ -407,7 +407,6 @@ def print_search_info(self, shell_script_style):
 
     def fetch_data(self, query_params, product_metadata):
         """Wrapper method to execute download in batches"""
-        check_permissions(self.output_directory, "Download")
         # Minimize pageing
         query_params["maxRecords"] = self.batch_size
         batches_n = int(
@@ -569,7 +568,7 @@ def _download_and_import_data(self, download_urls):
                     if hrsi_file.endswith("xml")
                 ][0]
                 zip_data = zip_file.read(hrsi_file_xml)
-                hrsi_file_path = Path(self.output_directory) / Path(hrsi_file_xml).name
+                hrsi_file_path = self.output_directory / Path(hrsi_file_xml).name
                 hrsi_file_path.write_bytes(zip_data)
 
                 # temporal extend is not consistently represented in the
@@ -593,7 +592,7 @@ def _download_and_import_data(self, download_urls):
                         continue
 
                     zip_data = zip_file.read(hrsi_file)
-                    hrsi_file_path = Path(self.output_directory) / Path(hrsi_file).name
+                    hrsi_file_path = self.output_directory / Path(hrsi_file).name
                     hrsi_file_path.write_bytes(zip_data)
                     map_name = legalize_name_string(hrsi_file_path.stem)
                     full_map_name = f"{map_name}@{self.gisenv['MAPSET']}"

src/temporal/t.import.hrsi/testsuite/test_t_import_hrsi_snow.py

@@ -68,7 +68,7 @@ def test_import_SWS(self):
         test_product = "SARWetSnow"
         self.assertModule(
             "t.import.hrsi",
-            flags="f",
+            flags="fw",
             product_type=test_product,
             aoi="./data/aoi.geojson",
             start_time="2023-04-05T00:00:00",

src/temporal/t.rast.aggregate.patch/t.rast.aggregate.patch.py

@@ -245,6 +245,7 @@ def patch_by_topology(
     count = 0
     current_mapset = get_current_mapset()
 
+    # Handle semantic labels (one granule_list per semantic label)
     for semantic_label, raster_map_list in map_dict.items():
         topo_builder = SpatioTemporalTopologyBuilder()
         topo_builder.build(mapsA=granularity_list, mapsB=raster_map_list)
@@ -253,48 +254,20 @@ def patch_by_topology(
             msgr.percent(count, len(granularity_list), 1)
             count += 1
 
-            start_time = granule.temporal_extent.get_start_time()
-            end_time = granule.temporal_extent.get_end_time()
+            start_time, end_time = granule.get_temporal_extent_as_tuple()
 
             aggregation_list = []
 
-            # Handle semantic labels (one granule per semantic label)
-            if "equal" in topo_list and granule.equal:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "contains" in topo_list and granule.contains:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "during" in topo_list and granule.during:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "starts" in topo_list and granule.starts:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "started" in topo_list and granule.started:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "finishes" in topo_list and granule.finishes:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "finished" in topo_list and granule.finished:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "overlaps" in topo_list and granule.overlaps:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
-            if "overlapped" in topo_list and granule.overlapped:
-                aggregation_list.extend(
-                    [map_layer.get_name() for map_layer in granule.equal]
-                )
+            for topology in topo_list:
+                matching_objects = getattr(granule, topology)
+                # Check if any maps are temporally related to the granule with the given topology
+                if matching_objects:
+                    aggregation_list.extend(
+                        [map_layer.get_name() for map_layer in matching_objects]
+                    )
+            # Reset Spatio-Temporal-Topology
+            granule.set_spatial_topology_build_false()
+            granule.set_temporal_topology_build_false()
 
             if aggregation_list:
                 msgr.verbose(