"""Unit tests for ``runner.helpers.smoothing_evaluator`` (FT-P-10 / AZ-418).

Covers AC-2 (improvement rate ≥0.80), AC-3 (mean improvement ≥5 m), and
the FDR pairing discipline (raw + smoothed per keyframe, no dupes).
"""

from __future__ import annotations

import csv
from pathlib import Path

import pytest

from runner.helpers.geo import offset
from runner.helpers.smoothing_evaluator import (
    IMPROVEMENT_RATE_REQUIRED,
    MEAN_IMPROVEMENT_M_REQUIRED,
    GtPose,
    KeyframePair,
    KeyframePoseRecord,
    SmoothingReport,
    evaluate,
    pair_records,
    resolve_gt_at,
    write_csv_evidence,
)


def _gt_track(n: int = 60, dt_ms: int = 100) -> list[GtPose]:
    """A straight-line GT track 10 Hz for 6 s, base lat/lon = Derkachi-ish."""
    return [
        GtPose(monotonic_ms=i * dt_ms, lat_deg=48.275 + i * 1e-4, lon_deg=37.385)
        for i in range(n)
    ]


def _raw_smoothed_pair(
    keyframe_id: int,
    gt: GtPose,
    raw_offset_m: float,
    smoothed_offset_m: float,
) -> tuple[KeyframePoseRecord, KeyframePoseRecord]:
    """Build a (raw, smoothed) pair offset north of the GT pose by given amounts."""
    raw_lat, raw_lon = offset(gt.lat_deg, gt.lon_deg, bearing_deg=0.0, distance_m=raw_offset_m)
    sm_lat, sm_lon = offset(gt.lat_deg, gt.lon_deg, bearing_deg=0.0, distance_m=smoothed_offset_m)
    raw = KeyframePoseRecord(
        keyframe_id=keyframe_id,
        pose_kind="raw",
        monotonic_ms=gt.monotonic_ms,
        lat_deg=raw_lat,
        lon_deg=raw_lon,
    )
    smoothed = KeyframePoseRecord(
        keyframe_id=keyframe_id,
        pose_kind="smoothed",
        monotonic_ms=gt.monotonic_ms + 500,  # window-exit later
        lat_deg=sm_lat,
        lon_deg=sm_lon,
    )
    return raw, smoothed


def test_constants_match_spec() -> None:
    """The AC-2 + AC-3 thresholds must match the spec text."""
    # Assert
    assert IMPROVEMENT_RATE_REQUIRED == 0.80
    assert MEAN_IMPROVEMENT_M_REQUIRED == 5.0


def test_resolve_gt_at_picks_nearest() -> None:
    """Linear scan picks the nearest GT pose."""
    # Arrange
    track = _gt_track()

    # Act
    nearest = resolve_gt_at(monotonic_ms=523, gt_track=track)

    # Assert — nearest 10 Hz sample to 523 ms is at 500 ms.
    assert nearest.monotonic_ms == 500


def test_resolve_gt_at_rejects_empty_track() -> None:
    # Act / Assert
    with pytest.raises(ValueError, match="gt_track is empty"):
        resolve_gt_at(monotonic_ms=0, gt_track=[])


def test_pair_records_groups_by_keyframe() -> None:
    """raw + smoothed get grouped per keyframe; partial entries remain partial."""
    # Arrange
    gt = _gt_track()[0]
    raw, sm = _raw_smoothed_pair(7, gt, raw_offset_m=10.0, smoothed_offset_m=3.0)
    records = [raw, sm]

    # Act
    paired = pair_records(records)

    # Assert
    assert paired == {7: (raw, sm)}


def test_pair_records_keeps_orphans_partial() -> None:
    """Smoothed without raw → (None, smoothed)."""
    # Arrange
    gt = _gt_track()[0]
    _, sm = _raw_smoothed_pair(7, gt, raw_offset_m=10.0, smoothed_offset_m=3.0)

    # Act
    paired = pair_records([sm])

    # Assert
    assert paired == {7: (None, sm)}


def test_pair_records_rejects_duplicate_pose_kind() -> None:
    """Two raws for the same keyframe → ValueError."""
    # Arrange
    gt = _gt_track()[0]
    raw1, _ = _raw_smoothed_pair(7, gt, raw_offset_m=10.0, smoothed_offset_m=3.0)
    raw2, _ = _raw_smoothed_pair(7, gt, raw_offset_m=8.0, smoothed_offset_m=3.0)

    # Act / Assert
    with pytest.raises(ValueError, match="duplicate raw pose"):
        pair_records([raw1, raw2])


def test_pair_records_rejects_unknown_pose_kind() -> None:
    """Programming-error guard for unknown pose_kind values."""
    # Arrange
    bogus = KeyframePoseRecord(
        keyframe_id=1, pose_kind="filtered", monotonic_ms=0, lat_deg=0.0, lon_deg=0.0
    )

    # Act / Assert
    with pytest.raises(ValueError, match="unknown pose_kind 'filtered'"):
        pair_records([bogus])


def test_evaluate_all_smoothed_wins_passes() -> None:
    """Every keyframe's smoothed is closer to GT → improvement rate 1.0."""
    # Arrange — 20 keyframes; raw 15m off, smoothed 2m off → 13m improvement each.
    track = _gt_track()
    records: list[KeyframePoseRecord] = []
    for i, gt in enumerate(track[:20]):
        raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=15.0, smoothed_offset_m=2.0)
        records += [raw, sm]

    # Act
    report = evaluate(records, track)

    # Assert
    assert report.pair_count == 20
    assert report.improvement_rate == 1.0
    assert report.mean_improvement_m == pytest.approx(13.0, abs=1.0)
    assert report.passes is True


def test_evaluate_at_80_pct_improvement_rate_passes() -> None:
    """80% smoothed wins AND mean improvement ≥5m → AC-2+AC-3 pass."""
    # Arrange — 10 keyframes: 8 smoothed_wins by 10m, 2 smoothed_loses by 1m.
    track = _gt_track()
    records: list[KeyframePoseRecord] = []
    for i, gt in enumerate(track[:10]):
        if i < 8:
            raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=12.0, smoothed_offset_m=2.0)
        else:
            raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=2.0, smoothed_offset_m=3.0)
        records += [raw, sm]

    # Act
    report = evaluate(records, track)

    # Assert
    assert report.improvement_rate == pytest.approx(0.80, abs=1e-6)
    assert report.passes_rate is True
    # mean = ((10 * 8) + (-1 * 2)) / 10 = 7.8 m
    assert report.mean_improvement_m == pytest.approx(7.8, abs=1.0)
    assert report.passes_mean is True
    assert report.passes is True


def test_evaluate_below_80_pct_fails_overall() -> None:
    """79% smoothed wins → AC-2 fails."""
    # Arrange — 100 keyframes: 79 wins, 21 losses.
    track = _gt_track(n=100)
    records: list[KeyframePoseRecord] = []
    for i, gt in enumerate(track):
        if i < 79:
            raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=15.0, smoothed_offset_m=2.0)
        else:
            raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=2.0, smoothed_offset_m=3.0)
        records += [raw, sm]

    # Act
    report = evaluate(records, track)

    # Assert
    assert report.improvement_rate == pytest.approx(0.79)
    assert report.passes_rate is False
    assert report.passes is False


def test_evaluate_mean_improvement_below_5m_fails() -> None:
    """100% rate but mean improvement = 3m → AC-3 fails."""
    # Arrange — every keyframe smoothed wins by 3 m.
    track = _gt_track()
    records: list[KeyframePoseRecord] = []
    for i, gt in enumerate(track[:20]):
        raw, sm = _raw_smoothed_pair(i, gt, raw_offset_m=8.0, smoothed_offset_m=5.0)
        records += [raw, sm]

    # Act
    report = evaluate(records, track)

    # Assert
    assert report.improvement_rate == 1.0
    assert report.mean_improvement_m == pytest.approx(3.0, abs=0.5)
    assert report.passes_mean is False
    assert report.passes is False


def test_evaluate_excludes_unpaired_keyframes() -> None:
    """Keyframe with only raw OR only smoothed is silently excluded."""
    # Arrange — keyframe 0 fully paired, keyframe 1 has only raw.
    track = _gt_track()
    raw0, sm0 = _raw_smoothed_pair(0, track[0], raw_offset_m=10.0, smoothed_offset_m=2.0)
    raw1, _ = _raw_smoothed_pair(1, track[1], raw_offset_m=10.0, smoothed_offset_m=2.0)

    # Act
    report = evaluate([raw0, sm0, raw1], track)

    # Assert
    assert report.pair_count == 1
    assert report.pairs[0].keyframe_id == 0


def test_evaluate_empty_records_does_not_pass() -> None:
    """Zero pairs → does NOT pass; rate + mean are 0."""
    # Arrange
    track = _gt_track()

    # Act
    report = evaluate([], track)

    # Assert
    assert report.pair_count == 0
    assert report.passes_rate is False
    assert report.passes_mean is False
    assert report.passes is False


def test_evaluate_rejects_empty_gt_track() -> None:
    # Act / Assert
    with pytest.raises(ValueError, match="gt_track must not be empty"):
        evaluate([], [])


def test_write_csv_evidence_round_trip(tmp_path: Path) -> None:
    """CSV header + one row per pair."""
    # Arrange
    track = _gt_track()
    raw, sm = _raw_smoothed_pair(0, track[0], raw_offset_m=15.0, smoothed_offset_m=2.0)
    report = evaluate([raw, sm], track)
    out = tmp_path / "ft-p-10.csv"

    # Act
    write_csv_evidence(out, report)

    # Assert
    rows = list(csv.reader(out.open()))
    assert rows[0] == [
        "keyframe_id",
        "raw_lat",
        "raw_lon",
        "smoothed_lat",
        "smoothed_lon",
        "gt_lat",
        "gt_lon",
        "raw_error_m",
        "smoothed_error_m",
        "improvement_m",
        "smoothed_wins",
    ]
    assert rows[1][-1] == "true"