102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
from __future__ import annotations
|
|
|
|
import json
|
|
from pathlib import Path
|
|
from types import SimpleNamespace
|
|
from uuid import uuid4
|
|
|
|
from app.models import Area, Dataset
|
|
from app.services.qa_service import QaService
|
|
|
|
|
|
class FakeSession:
|
|
def __init__(self, datasets=None, areas=None):
|
|
self.datasets = {item.id: item for item in (datasets or [])}
|
|
self.areas = {item.id: item for item in (areas or [])}
|
|
|
|
def get(self, model, item_id):
|
|
if model.__name__ == "Dataset":
|
|
return self.datasets.get(item_id)
|
|
if model.__name__ == "Area":
|
|
return self.areas.get(item_id)
|
|
return None
|
|
|
|
|
|
def _write_dataset(path: Path, coordinates: list[list[list[float]]]) -> None:
|
|
payload = {
|
|
"type": "FeatureCollection",
|
|
"features": [
|
|
{
|
|
"type": "Feature",
|
|
"properties": {},
|
|
"geometry": {
|
|
"type": "Polygon",
|
|
"coordinates": coordinates,
|
|
},
|
|
},
|
|
],
|
|
}
|
|
path.write_text(json.dumps(payload), encoding="utf-8")
|
|
|
|
|
|
def test_qa_compare_candidate_with_reference_returns_metrics(tmp_path) -> None:
|
|
project_id = uuid4()
|
|
candidate_id = uuid4()
|
|
reference_id = uuid4()
|
|
candidate_path = tmp_path / "candidate.geojson"
|
|
reference_path = tmp_path / "reference.geojson"
|
|
polygon = [[[4.0, 51.0], [4.1, 51.0], [4.1, 51.1], [4.0, 51.1], [4.0, 51.0]]]
|
|
_write_dataset(candidate_path, polygon)
|
|
_write_dataset(reference_path, polygon)
|
|
|
|
candidate = Dataset(
|
|
id=candidate_id,
|
|
project_id=project_id,
|
|
name="candidate.geojson",
|
|
dataset_type="vector",
|
|
source="test",
|
|
storage_path=str(candidate_path),
|
|
crs="EPSG:4326",
|
|
metadata_json={"crs_assumed": False},
|
|
)
|
|
reference = Dataset(
|
|
id=reference_id,
|
|
project_id=project_id,
|
|
name="reference.geojson",
|
|
dataset_type="vector",
|
|
source="test",
|
|
storage_path=str(reference_path),
|
|
crs="EPSG:4326",
|
|
metadata_json={"crs_assumed": False},
|
|
)
|
|
|
|
result = QaService.compare_candidate_with_reference(
|
|
db=FakeSession([candidate, reference]),
|
|
project_id=project_id,
|
|
candidate_dataset_id=candidate_id,
|
|
reference_dataset_id=reference_id,
|
|
iou_threshold=0.5,
|
|
)
|
|
|
|
assert result.status == "ok"
|
|
assert result.matches == 1
|
|
assert result.false_positives == 0
|
|
assert result.false_negatives == 0
|
|
assert result.precision == 1.0
|
|
assert result.recall == 1.0
|
|
assert result.f1_score == 1.0
|
|
|
|
|
|
def test_dataset_reference_metadata_migration_declares_required_columns() -> None:
|
|
migration_path = Path(__file__).parents[1] / "alembic" / "versions" / "202606120001_add_dataset_reference_metadata.py"
|
|
migration_text = migration_path.read_text(encoding="utf-8")
|
|
for column_name in (
|
|
"dataset_role",
|
|
"source_name",
|
|
"reference_layer_name",
|
|
"source_metadata",
|
|
"provenance_metadata",
|
|
"imported_at",
|
|
):
|
|
assert column_name in migration_text
|