from __future__ import annotations

import math

import pytest

from k1link.compute.e45_binding_sensitivity import (
    E45_ROW_SCHEMA,
    E45BindingSensitivityError,
    E45BindingSensitivityProfile,
    analyze_binding_sensitivity,
)


def _row(
    item_id: str,
    *,
    radius: float,
    speed: float,
    angular: float,
    lidar_age: float,
    pose_age: float,
    residual: float,
    points: int,
) -> dict[str, object]:
    age_seconds = (lidar_age + pose_age) / 1000.0
    return {
        "schema_version": E45_ROW_SCHEMA,
        "item_id": item_id,
        "image_radius_normalized": radius,
        "translation_speed_mps": speed,
        "angular_speed_deg_s": angular,
        "lidar_camera_age_ms": lidar_age,
        "pose_point_age_ms": pose_age,
        "motion_exposure_translation_m": speed * age_seconds,
        "motion_exposure_rotation_deg": angular * age_seconds,
        "centroid_residual_bbox_diagonal": residual,
        "occupied_points_in_bbox": points,
        "supported": points >= 2,
    }


def test_e45_stratifies_existing_diagnostic_residual_without_target_claim() -> None:
    rows = [
        _row(
            "one",
            radius=0.2,
            speed=0.0,
            angular=0.0,
            lidar_age=5.0,
            pose_age=2.0,
            residual=0.1,
            points=5,
        ),
        _row(
            "two",
            radius=0.7,
            speed=0.5,
            angular=6.0,
            lidar_age=40.0,
            pose_age=15.0,
            residual=0.2,
            points=8,
        ),
        _row(
            "three",
            radius=1.0,
            speed=2.0,
            angular=20.0,
            lidar_age=80.0,
            pose_age=35.0,
            residual=0.4,
            points=12,
        ),
    ]

    analysis = analyze_binding_sensitivity(rows)

    assert analysis["correspondence_count"] == 3
    assert analysis["supported_fraction"] == 1.0
    assert [
        item["count"] for item in analysis["strata"]["image_radius"]
    ] == [1, 1, 1]
    assert math.isclose(
        analysis["spearman_residual_correlation"][
            "image_radius_normalized"
        ],
        1.0,
    )
    assert (
        analysis["measured_calibration_target_residual_available"] is False
    )
    assert analysis["physical_mount_inferred"] is False


def test_e45_rejects_missing_support_in_accepted_correspondence() -> None:
    rows = [
        _row(
            "one",
            radius=0.2,
            speed=0.0,
            angular=0.0,
            lidar_age=5.0,
            pose_age=2.0,
            residual=0.1,
            points=1,
        )
    ]

    with pytest.raises(E45BindingSensitivityError, match="supported"):
        analyze_binding_sensitivity(rows)


def test_e45_profile_rejects_overlapping_or_reversed_edges() -> None:
    with pytest.raises(E45BindingSensitivityError):
        E45BindingSensitivityProfile(image_radius_edges=(0.8, 0.4))