feat: add semantic GIS selection metrics

2026-07-15 06:07:34 +02:00
parent 3ff2d07f3c
commit 0baa9b069c
16 changed files with 520 additions and 22 deletions
@@ -0,0 +1,128 @@
+from __future__ import annotations
+
+from pathlib import Path
+from uuid import uuid4
+
+from app.models import Dataset
+from app.schemas.operations import VectorSelectionSummary
+from app.services.vector_feature_service import VectorFeatureService
+
+
+ROOT = Path(__file__).parents[2]
+BBOX = {"min_x": 5.0, "min_y": 51.1, "max_x": 5.2, "max_y": 51.3, "crs": "EPSG:4326"}
+
+
+class ScalarQuery:
+    def __init__(self, value: float):
+        self.value = value
+
+    def filter(self, *args):  # noqa: ANN002, ARG002
+        return self
+
+    def scalar(self):
+        return self.value
+
+
+class SequenceScalarSession:
+    def __init__(self, values: list[float]):
+        self.values = iter(values)
+
+    def query(self, *args):  # noqa: ANN002, ARG002
+        return ScalarQuery(next(self.values))
+
+
+def themed_dataset(theme: str, *, method: str = "feature_count") -> Dataset:
+    return Dataset(
+        id=uuid4(),
+        project_id=uuid4(),
+        name=f"regional-{theme}.geojson",
+        dataset_type="vector",
+        dataset_role="reference",
+        source_name="grb",
+        reference_layer_name=theme,
+        source_metadata={
+            "theme": theme,
+            "selection_aggregation": {
+                "method": method,
+                "label": theme.title(),
+                "unit": "objecten",
+            },
+        },
+    )
+
+
+def test_building_selection_promotes_footprint_area_and_retains_object_count() -> None:
+    result = VectorFeatureService.summarize_features_by_bbox(
+        SequenceScalarSession([125_000.0]),
+        dataset=themed_dataset("buildings"),
+        bbox=BBOX,
+        total_feature_count=40,
+    )
+
+    assert result["primary_metric_key"] == "footprint_area"
+    assert result["metric_label"] == "Bebouwde grondoppervlakte"
+    assert result["metric_value"] == 12.5
+    assert result["metric_unit"] == "ha"
+    assert [(item["metric_key"], item["metric_value"]) for item in result["metrics"]] == [
+        ("footprint_area", 12.5),
+        ("feature_count", 40.0),
+    ]
+    assert "niet de totale vloeroppervlakte" in result["warning"]
+    VectorSelectionSummary(**result)
+
+
+def test_water_selection_reports_surface_length_and_honest_volume_limitation() -> None:
+    result = VectorFeatureService.summarize_features_by_bbox(
+        SequenceScalarSession([52_500.0, 12_750.0]),
+        dataset=themed_dataset("water"),
+        bbox=BBOX,
+        total_feature_count=23,
+    )
+
+    assert result["metric_value"] == 5.25
+    assert result["metric_unit"] == "ha"
+    assert [(item["metric_key"], item["metric_value"], item["metric_unit"]) for item in result["metrics"]] == [
+        ("water_area", 5.25, "ha"),
+        ("watercourse_length", 12.75, "km"),
+        ("feature_count", 23.0, "objecten"),
+    ]
+    assert "Watervolume is niet berekenbaar" in result["warning"]
+
+
+def test_population_keeps_configured_metric_and_adds_sector_count() -> None:
+    dataset = themed_dataset("population", method="sum")
+    dataset.source_metadata["selection_aggregation"].update(
+        {"metric_key": "population", "property": "population_total", "label": "Inwoners", "unit": "inwoners"}
+    )
+    result = VectorFeatureService.summarize_features_by_bbox(
+        SequenceScalarSession([86_458.0]),
+        dataset=dataset,
+        bbox=BBOX,
+        total_feature_count=733,
+    )
+
+    assert result["primary_metric_key"] == "population"
+    assert result["metric_value"] == 86_458.0
+    assert result["metrics"][1] == {
+        "metric_key": "feature_count",
+        "metric_label": "Statistische sectoren",
+        "metric_value": 733.0,
+        "metric_unit": "objecten",
+        "aggregation_method": "feature_count",
+        "is_estimate": False,
+        "warning": None,
+    }
+
+
+def test_future_regional_imports_persist_semantic_aggregation_configuration() -> None:
+    buildings = (ROOT / "scripts/provision_regional_grb_buildings.py").read_text(encoding="utf-8")
+    context = (ROOT / "scripts/provision_regional_grb_context.py").read_text(encoding="utf-8")
+    frontend = (ROOT / "frontend/src/components/map/MapWorkspace.tsx").read_text(encoding="utf-8")
+
+    assert '"method": "intersection_area"' in buildings
+    assert '"label": "Bebouwde grondoppervlakte"' in buildings
+    assert 'metric_method="intersection_length"' in context
+    assert 'metric_label="Wateroppervlakte"' in context
+    assert 'metric_label="Perceeloppervlakte"' in context
+    assert 'aria-label="Aanvullende gebiedsmetingen"' in frontend
+    assert "activeSelectionResult.summary.warning" in frontend