bugfixes aggregation composite areas

examples/data/setup_new_composite_area/test_setup_new_composite_area_elevation_aggregation/settings.toml

@@ -21,3 +21,4 @@ file = "./exposure/exposure.csv"
 crs = "EPSG:4326"
 file1 = "./exposure/building_points.gpkg"
 file2 = "./exposure/new_development_area.gpkg"
+file3 = "./exposure/new_development_area_aggregated.gpkg"

hydromt_fiat/workflows/aggregation_areas.py

@@ -68,8 +68,16 @@ def join_exposure_aggregation_multiple_areas(
         )
         exposure_gdf.drop_duplicates(subset="Object ID", keep="first", inplace=True)
 
+        # Check if new gdf was already created in previous loop
+        try:
+            new_exposure_aggregation
+        except NameError:
+            new_exposure_aggregation = None
+        else:
+            new_exposure_aggregation = new_exposure_aggregation
+
         if new_composite_area[0] is True:
-            new_exposure_aggregation, exposure_gdf = split_composite_area(exposure_gdf, aggregated, aggregation_gdf, attribute_name)     
+            new_exposure_aggregation, exposure_gdf = split_composite_area(exposure_gdf, aggregated, aggregation_gdf, attribute_name, new_exposure_aggregation)     
 
         else:
             exposure_gdf.drop(columns=attribute_name, inplace=True)
@@ -90,7 +98,7 @@ def join_exposure_aggregation_multiple_areas(
 
     return exposure_gdf
 
-def split_composite_area(exposure_gdf, aggregated, aggregation_gdf, attribute_name):
+def split_composite_area(exposure_gdf, aggregated, aggregation_gdf, attribute_name, new_exposure_aggregation):
     if aggregated[attribute_name].apply(lambda x: len(x) >= 2).any():
         # Split exposure_gdf by aggregation zone 
         new_exposure_gdf = exposure_gdf.rename(columns = {attribute_name: "pot"})
@@ -104,14 +112,13 @@ def split_composite_area(exposure_gdf, aggregated, aggregation_gdf, attribute_na
 
         # Combine divided objects of new composite area with areas that fall in no zone
         exposure_gdf = pd.concat([res_intersection, exposure_outside_aggregation], ignore_index=True)
-        idx_duplicates = exposure_gdf.index[exposure_gdf.duplicated("Object ID") == True]
+        idx_duplicates = exposure_gdf.index[exposure_gdf.duplicated(subset = "Object ID")]
         exposure_gdf["Object ID"] = exposure_gdf["Object ID"].astype(int)
         exposure_gdf.loc[idx_duplicates, "Object ID"] = np.random.choice(range(exposure_gdf["Object ID"].values.max() + 1 ,exposure_gdf["Object ID"].values.max() +1 + len(idx_duplicates)), size=len(idx_duplicates), replace=False)
 
     # Create an empty GeoDataFrame and append the exposure data
-    try:
-        new_exposure_aggregation
-    except NameError:
+
+    if new_exposure_aggregation is None:
         data = pd.DataFrame(columns=['geometry'])
         final_exposure = gpd.GeoDataFrame(data, geometry='geometry')
         new_exposure_aggregation = pd.concat([final_exposure, exposure_gdf], ignore_index=True) 
@@ -158,6 +165,9 @@ def join_exposure_aggregation_areas(
 
     exposure_gdf = join_exposure_aggregation_multiple_areas(exposure_gdf, aggregation_area_fn, attribute_names, label_names, new_composite_area)
 
+
     # Remove the geometry column from the exposure_gdf to return a dataframe
+    exposure_geoms = exposure_gdf[["Object ID", "geometry"]]
+
     del exposure_gdf["geometry"]
-    return exposure_gdf
+    return exposure_gdf, exposure_geoms 

hydromt_fiat/workflows/exposure_vector.py

@@ -1198,13 +1198,16 @@ def setup_new_composite_areas(
         # If the user supplied aggregation area data, assign that to the
         # new composite areas
         if aggregation_area_fn is not None:
-            new_objects = join_exposure_aggregation_areas(
+            new_objects, aggregated_objects_geoms = join_exposure_aggregation_areas(
                 _new_exposure_geoms.merge(new_objects, on="Object ID"),
                 aggregation_area_fn=aggregation_area_fn,
                 attribute_names=attribute_names,
                 label_names=label_names,
                 new_composite_area = True
             )
+            # Update the exposure_geoms incl aggregation
+            self.set_geom_names("new_development_area_aggregated")
+            self.set_exposure_geoms(aggregated_objects_geoms)
 
         # Update the exposure_db
         self.exposure_db = pd.concat([self.exposure_db, new_objects]).reset_index(