fix: align WALOUS with official class codes

backend/tests/test_walous_land_cover_service.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from datetime import datetime, timezone
+import importlib.util
 from pathlib import Path
 from types import SimpleNamespace
 from uuid import uuid4
@@ -22,6 +23,15 @@ from app.services.temporal_analysis_service import TemporalAnalysisService
 from app.services.walous_land_cover_service import WalousLandCoverService
 
 
+def load_provisioner():
+    path = Path(__file__).resolve().parents[2] / "scripts" / "provision_walous_sources.py"
+    spec = importlib.util.spec_from_file_location("walous_source_provisioner_test", path)
+    assert spec and spec.loader
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
 class FakeQuery:
     def filter(self, *_args):
         return self
@@ -70,16 +80,15 @@ def make_source(path: Path) -> tuple[list[float], np.ndarray]:
     to_4326 = Transformer.from_crs("EPSG:3812", "EPSG:4326", always_xy=True)
     x, y = to_3812.transform(4.85, 50.45)
     transform = from_origin(x, y + 100, 1, 1)
-    values = np.ones((100, 100), dtype="uint8")
-    values[:, 20:40] = 4
-    values[:, 40:50] = 8
-    values[:, 50:70] = 9
-    values[:, 70:] = 2
+    class_codes = [1, 2, 3, 4, 5, 6, 7, 8, 9, 80, 90]
+    values = np.empty((100, len(class_codes) * 20), dtype="uint8")
+    for index, class_code in enumerate(class_codes):
+        values[:, index * 20 : (index + 1) * 20] = class_code
     with rasterio.open(
         path,
         "w",
         driver="GTiff",
-        width=100,
+        width=values.shape[1],
         height=100,
         count=1,
         dtype="uint8",
@@ -89,7 +98,7 @@ def make_source(path: Path) -> tuple[list[float], np.ndarray]:
     ) as target:
         target.write(values, 1)
     min_lon, min_lat = to_4326.transform(x, y)
-    max_lon, max_lat = to_4326.transform(x + 100, y + 100)
+    max_lon, max_lat = to_4326.transform(x + values.shape[1], y + values.shape[0])
     return [min_lon, min_lat, max_lon, max_lat], values
 
 
@@ -113,6 +122,17 @@ def test_walous_registry_reports_real_provisioning_state(tmp_path: Path) -> None
     assert after["walous_land_cover_2023"]["native_resolution_m"] == 1.0
     assert after["walous_land_cover_2023"]["analysis_resolution_m"] == 10.0
     assert after["walous_land_cover_2023"]["coverage_zones"] == ["wallonia"]
+    assert after["walous_land_cover_2023"]["included_source_values"] == [1, 2, 3, 4, 5, 6, 7, 8, 9, 80, 90]
+    assert after["walous_land_cover_2023"]["source_value_unit"] == "walous_class_code"
+
+
+def test_walous_provisioner_accepts_official_non_contiguous_class_codes(tmp_path: Path) -> None:
+    source_path = tmp_path / "walous_land_cover_2023_3812.tif"
+    make_source(source_path)
+
+    validation = load_provisioner().validate_raster(source_path)
+
+    assert validation["sample_classes"] == [1, 2, 3, 4, 5, 6, 7, 8, 9, 80, 90]
 
 
 def test_walous_acquisition_reads_real_classes_and_persists_provenance(tmp_path: Path, monkeypatch) -> None:
@@ -141,10 +161,12 @@ def test_walous_acquisition_reads_real_classes_and_persists_provenance(tmp_path:
     assert result["output_dataset_id"] == str(output_id)
     assert result["resolution_m"] == 10
     assert captured["source_name"] == "spw_walous_land_cover"
-    assert captured["source_metadata"]["classes_present"] == [1, 2, 4, 8, 9]
+    assert captured["source_metadata"]["classes_present"] == [1, 2, 3, 4, 5, 6, 7, 8, 9, 80, 90]
     assert captured["provenance_metadata"]["resampling"] == "nearest"
     assert captured["temporal_series_key"].startswith("spw:walous:land-cover:")
-    assert captured["observed_at"].year == 2023
+    assert captured["observed_at"].date().isoformat() == "2023-06-25"
+    assert captured["valid_from"].date().isoformat() == "2023-05-27"
+    assert captured["valid_to"] == captured["observed_at"]
 
 
 def test_walous_analysis_returns_semantic_area_metrics(tmp_path: Path, monkeypatch) -> None:
@@ -193,6 +215,9 @@ def test_walous_analysis_returns_semantic_area_metrics(tmp_path: Path, monkeypat
     assert metrics["forest_cover_area_ha"] > 0
     assert metrics["surface_water_area_ha"] > 0
     assert metrics["artificial_cover_area_ha"] > 0
+    assert metrics["annual_herbaceous_cover_area_ha"] > 0
+    assert metrics["permanent_herbaceous_cover_area_ha"] > 0
+    assert metrics["bare_soil_area_ha"] > 0
     assert "water_volume" in result["unsupported_metrics"]