Add governed bathymetry profile workflow

backend/app/services/vector_feature_service.py

@@ -36,6 +36,8 @@ SEMANTIC_METRICS_DISABLED_OPERATOR_TOOLS = {
     # line metrics (road/watercourse length) would therefore be meaningless.
     "provision_regional_historical_landuse.py",
 }
+PROPERTY_AGGREGATION_METHODS = {"sum", "mean", "area_weighted_sum"}
+PROPERTY_EXTREMA_METHODS = {"min", "max"}
 
 PRECLIPPED_MUNICIPALITY_PARTITION_OPERATOR_TOOLS = {
     "provision_regional_bwk_natura2000.py",
@@ -581,7 +583,7 @@ class VectorFeatureService:
             length_m = db.query(func.coalesce(func.sum(length_expression), 0.0)).filter(*metric_filter).scalar()
             divisor = 1_000.0 if unit == "km" else 1.0
             metric_value = float(length_m or 0.0) / divisor
-        elif method in {"sum", "mean", "area_weighted_sum"}:
+        elif method in PROPERTY_AGGREGATION_METHODS | PROPERTY_EXTREMA_METHODS:
             property_name = str(config.get("property") or "").strip()
             if not property_name:
                 raise AppError(
@@ -599,7 +601,11 @@ class VectorFeatureService:
                 )
                 coverage_ratio = intersection_area / func.nullif(source_area, 0.0)
                 value_expression = numeric_value * coverage_ratio
-            aggregate_function = func.avg if method == "mean" else func.sum
+            aggregate_function = {
+                "mean": func.avg,
+                "min": func.min,
+                "max": func.max,
+            }.get(method, func.sum)
             aggregate_value = (
                 db.query(func.coalesce(aggregate_function(value_expression), 0.0))
                 .filter(*metric_filter)