"""762-1 지면점 다듬기(SMRF 꼴) · 766-1 다듬기 기본 흐름 · 762-2 품질 지표 지킴 시험.

합성 비탈(17°) + 능선(높이 6 m · 폭 약 16 m) + 덤불 혹(3 × 3 m · 1.5 m 뜸) — 필터가
덤불까지 지면으로 고른 판 → 다듬기가 혹은 지우고 능선 · 비탈은 남김.
"""

import numpy as np

import B04_PreProcess.B04_PreProcess_Engine_Ground as ground
from B04_PreProcess.B04_PreProcess_Engine_Filter_Refine import refine_ground_mask
from B04_PreProcess.B04_PreProcess_Engine_Quality import spike_stats

RNG = np.random.default_rng(7621)


def _terrain(x: np.ndarray, y: np.ndarray) -> np.ndarray:
    return 0.3 * x + 6.0 * np.exp(-(((x - 60.0) / 8.0) ** 2)) + 0.02 * y


def _scene() -> tuple[np.ndarray, np.ndarray, np.ndarray]:
    count = 120 * 120 * 4
    x = RNG.uniform(0, 120, count)
    y = RNG.uniform(0, 120, count)
    z = _terrain(x, y) + RNG.normal(0, 0.03, count)
    bush = np.zeros(count, dtype=bool)
    for cx, cy in RNG.uniform(10, 110, (15, 2)):
        if abs(cx - 60) < 12:  # 능선 위 덤불은 따로 가름 — 여기선 비탈 · 골 덤불
            cx += 25
        inside = (np.abs(x - cx) < 1.5) & (np.abs(y - cy) < 1.5)
        z[inside] += 1.5
        bush |= inside
    ridge = (np.abs(x - 60) < 4) & ~bush
    return np.column_stack((x, y, z)), bush, ridge


def test_refine_drops_bushes_keeps_ridge() -> None:
    xyz, bush, ridge = _scene()
    kept = refine_ground_mask(xyz, np.ones(len(xyz), dtype=bool))
    print(kept[bush].mean(), kept[ridge].mean(), kept[~bush].mean())
    assert kept[bush].mean() < 0.1  # 덤불 혹 90 % 넘게 지움
    assert kept[ridge].mean() > 0.95  # 능선 안 깎음
    assert kept[~bush].mean() > 0.97  # 땅 점 거의 그대로


def test_refine_never_adds_points() -> None:
    xyz, _, _ = _scene()
    mask = RNG.random(len(xyz)) < 0.5
    kept = refine_ground_mask(xyz, mask)
    assert not (kept & ~mask).any()
    assert refine_ground_mask(xyz, np.zeros(len(xyz), dtype=bool)).sum() == 0


def test_refine_flow_is_default() -> None:
    xyz, _, _ = _scene()
    bounds = np.array([[0, 120], [0, 120], [0, 50]], dtype=np.float64)
    data = {"xyz": xyz, "bounds": bounds, "classification": np.full(len(xyz), 2, np.uint8)}
    assert ground.resolve_auto_source_filters(data) == ["classification_refine", "ptd_refine"]
    data["classification"][:] = 0
    assert ground.resolve_auto_source_filters(data) == ["ptd_refine"]
    assert ground.base_filter("ptd_refine") == "ptd"
    assert ground.base_filter("ptd") is None
    assert {"classification_refine", "ptd_refine"} <= set(ground.available_filters())
    # 바탕 마스크를 넘기면 바탕 필터를 다시 돌리지 않고 다듬기만
    base = np.ones(len(xyz), dtype=bool)
    refined = ground.run_ground_filter("ptd_refine", data, base)
    assert refined.sum() < base.sum()


def test_spike_stat_sees_bumps() -> None:
    yy, xx = np.mgrid[0:100, 0:100].astype(float)
    z = 0.3 * xx
    valid = np.ones(z.shape, dtype=bool)
    assert spike_stats(z, valid)["spike_pct"] == 0.0
    z[40:42, 40:42] += 1.5
    stats = spike_stats(z, valid)
    assert stats["spike_count"] == 1 and stats["spike_pct"] > 0