"""The object count and the area metric must describe the same selection.

``intersection_area`` clips a feature to the drawn rectangle, but the object
count treated any feature that merely touches the rectangle as wholly inside.
For a rectangle across a built-up area that overstates the count at every
edge, and the two headline numbers on the same panel then describe different
populations: "1.000 gebouwen" next to the clipped area of rather fewer.

The count now reports how many features lie entirely inside and how many are
cut by the selection edge, and is marked as an estimate when any are.
"""

from __future__ import annotations

from app.services.vector_feature_service import VectorFeatureService


def test_a_count_without_partial_features_is_exact() -> None:
    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=120,
        fully_covered_feature_count=120,
    )

    assert disclosure["partially_covered_feature_count"] == 0
    assert disclosure["is_estimate"] is False
    assert disclosure["warning"] is None


def test_features_cut_by_the_selection_edge_are_reported() -> None:
    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=120,
        fully_covered_feature_count=98,
    )

    assert disclosure["partially_covered_feature_count"] == 22
    assert disclosure["is_estimate"] is True
    assert "22" in disclosure["warning"]
    assert "rand" in disclosure["warning"]


def test_a_selection_of_only_partial_features_is_still_coherent() -> None:
    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=3,
        fully_covered_feature_count=0,
    )

    assert disclosure["partially_covered_feature_count"] == 3
    assert disclosure["is_estimate"] is True


def test_an_empty_selection_makes_no_claim() -> None:
    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=0,
        fully_covered_feature_count=0,
    )

    assert disclosure["partially_covered_feature_count"] == 0
    assert disclosure["is_estimate"] is False
    assert disclosure["warning"] is None


def test_a_preclipped_full_area_selection_has_no_edge_effect() -> None:
    """Selecting the whole work area cuts nothing; the count is exact."""

    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=500,
        fully_covered_feature_count=None,
    )

    assert disclosure["partially_covered_feature_count"] is None
    assert disclosure["is_estimate"] is False
    assert disclosure["warning"] is None


def test_an_inconsistent_covered_count_never_produces_a_negative() -> None:
    disclosure = VectorFeatureService.count_disclosure(
        total_feature_count=10,
        fully_covered_feature_count=14,
    )

    assert disclosure["partially_covered_feature_count"] == 0
    assert disclosure["is_estimate"] is False


class _ScalarQuery:
    def __init__(self, value):
        self.value = value

    def filter(self, *args):  # noqa: ANN002, ARG002
        return self

    def scalar(self):
        return self.value


class _SequenceSession:
    """Answers the summary's scalar queries in order: covered count, then metrics."""

    def __init__(self, values):
        self.values = iter(values)

    def query(self, *args):  # noqa: ANN002, ARG002
        return _ScalarQuery(next(self.values))


def _buildings_dataset():
    from uuid import uuid4

    from app.models import Dataset

    return Dataset(
        id=uuid4(),
        project_id=uuid4(),
        name="grb-buildings.geojson",
        dataset_type="vector",
        dataset_role="reference",
        source_name="grb",
        reference_layer_name="buildings",
        source_metadata={"theme": "buildings"},
    )


BBOX = {"min_x": 5.0, "min_y": 51.1, "max_x": 5.2, "max_y": 51.3, "crs": "EPSG:4326"}


def test_summary_reports_the_edge_cut_next_to_the_object_count() -> None:
    summary = VectorFeatureService.summarize_features_by_bbox(
        _SequenceSession([88, 125_000.0]),
        dataset=_buildings_dataset(),
        bbox=BBOX,
        total_feature_count=100,
    )

    assert summary["feature_count"] == 100
    assert summary["fully_covered_feature_count"] == 88
    assert summary["partially_covered_feature_count"] == 12
    assert "12 van de 100" in summary["selection_edge_warning"]

    count_metric = next(
        item for item in summary["metrics"] if item["aggregation_method"] == "feature_count"
    )
    assert count_metric["is_estimate"] is True
    assert "doorgesneden" in count_metric["warning"]

    # The clipped area metric is exact and must not inherit the count's caveat.
    area_metric = next(
        item for item in summary["metrics"] if item["aggregation_method"] == "intersection_area"
    )
    assert area_metric["is_estimate"] is False


def test_summary_stays_exact_when_the_selection_cuts_nothing() -> None:
    summary = VectorFeatureService.summarize_features_by_bbox(
        _SequenceSession([100, 125_000.0]),
        dataset=_buildings_dataset(),
        bbox=BBOX,
        total_feature_count=100,
    )

    assert summary["partially_covered_feature_count"] == 0
    assert summary["selection_edge_warning"] is None