from __future__ import annotations

import numpy as np

from k1link.compute.e39_perception_refinement import (
    _feature_names,
    _fit_robust_scaler,
    _predict_presence,
    _project_dimensions,
    _transform,
)


def test_e39_feature_contract_and_knn_are_deterministic() -> None:
    assert len(_feature_names()) == 262
    matrix = np.asarray(
        [
            [0.0, 1.0],
            [0.1, 1.1],
            [4.9, 5.0],
            [5.0, 5.1],
        ],
        dtype=np.float64,
    )
    median, scale = _fit_robust_scaler(matrix)
    transformed = _transform(matrix, median=median, scale=scale, clip=20.0)
    first = _predict_presence(
        transformed[0],
        transformed[1:],
        ["background", "object", "object"],
        neighbors=3,
    )
    second = _predict_presence(
        transformed[0],
        transformed[1:],
        ["background", "object", "object"],
        neighbors=3,
    )
    assert first == second == ("object", 2 / 3)


def test_e39_projects_presence_through_frozen_stratum_ontology() -> None:
    assert _project_dimensions("camera-only", "object-present") == {
        "presence": "object-present",
        "geometry_association": "insufficient-support",
        "freshness": "unavailable",
    }
    assert _project_dimensions("geometry-only", "occupied-environment") == {
        "presence": "occupied-environment",
        "geometry_association": "independent-occupied",
        "freshness": "current",
    }
    assert _project_dimensions("unknown", "background-or-noise") == {
        "presence": "background-or-noise",
        "geometry_association": "rejected-nonobject",
        "freshness": "current",
    }