"""motionSample 的自洽性检查: python3 validate.py

检查键、形状、四元数模长、pose_aa 能否零误差还原 dof、接触相位, 以及用随文件发布的
com_pos 拟合腾空相重力。只依赖 numpy。
"""
import pickle
import sys
from pathlib import Path

import numpy as np

HERE = Path(__file__).resolve().parent
REQUIRED = {"root_trans_offset": 3, "root_rot": 4, "dof": None, "dof_pos": None,
            "dof_vel": None, "root_lin_vel": 3, "root_ang_vel": 3, "contacts": 2,
            "com_pos": 3}
G = 9.80665
fail = []


def chk(name, ok, detail=""):
    print(("  OK   " if ok else "  FAIL ") + name + (f" — {detail}" if detail else ""))
    if not ok:
        fail.append(name)


def air_runs(mask):
    m = np.concatenate([[0], mask.astype(int), [0]])
    d = np.diff(m)
    return list(zip(np.where(d == 1)[0], np.where(d == -1)[0]))


def main():
    files = sorted(HERE.glob("*.pkl"))
    if not files:
        print("目录下没有 .pkl")
        return 1
    d = {}
    for f in files:
        one = pickle.load(open(f, "rb"))
        print(f"── {f.name}  {len(one)} 条: {list(one)}")
        for k in one:
            chk(f"{f.name}: 文件名与内部键一致", k == f.stem, f"键 {k}")
        d.update(one)
    for k, m in d.items():
        print(f"── 结构 ── {k}")
        T, D = m["dof"].shape
        chk(f"{k}: 必需键齐全", not (set(REQUIRED) - set(m)),
            str(set(REQUIRED) - set(m)) or f"T={T} D={D}")
        bad = [c for c, w in REQUIRED.items() if w and m[c].shape != (T, w)]
        chk(f"{k}: 各键形状一致", not bad, ", ".join(bad))
        chk(f"{k}: dof_names / dof_axes 长度 == D",
            len(m["dof_names"]) == D and m["dof_axes"].shape == (D, 3))
        chk(f"{k}: quat_order 标注为 xyzw", m.get("quat_order") == "xyzw")
        chk(f"{k}: fps 是正整数", isinstance(m["fps"], int) and m["fps"] > 0, str(m["fps"]))

        print(f"── 数值 ── {k}")
        chk(f"{k}: 无 NaN/Inf",
            all(np.isfinite(m[c]).all() for c in REQUIRED if c in m))
        n = np.linalg.norm(m["root_rot"], axis=1)
        chk(f"{k}: |root_rot| == 1", np.allclose(n, 1, atol=1e-5), f"{n.min():.6f}~{n.max():.6f}")
        chk(f"{k}: dof 与 dof_pos 是同一份", np.array_equal(m["dof"], m["dof_pos"]))
        rec = np.einsum("tjc,jc->tj", m["pose_aa"][:, 1:], m["dof_axes"])
        e = np.abs(rec - m["dof"]).max()
        chk(f"{k}: pose_aa 沿关节轴投影可还原 dof", e < 1e-5, f"最大误差 {e:.2e} rad")

        c, fps = m["contacts"], m["fps"]
        air = c.max(1) == 0
        runs = [(a, b) for a, b in air_runs(air) if (b - a) / fps > 0.15]
        n2 = (c.sum(1) == 2).mean() * 100
        dur = np.array([(b - a) / fps for a, b in runs])
        print(f"       双支撑 {n2:.1f}% | 腾空 {air.mean()*100:.1f}%"
              + (f" | 腾空段 >150ms 共 {len(runs)} 次, 中位 {np.median(dur)*1000:.0f} ms"
                 if len(runs) else " | 无 >150ms 的腾空段"))
        if not runs:
            print("       注: 没有 >150ms 的腾空段, 接触模式偏走路而非跑步(见 README)")

        # 腾空相重力: 取每段中间 2/3 拟合抛物线, 避开起落瞬间的接触判定误差
        if runs:
            acc = []
            for a, b in runs:
                w = (b - a) // 6
                a2, b2 = a + w, b - w
                if b2 - a2 < 8:
                    continue
                t = np.arange(b2 - a2) / fps
                acc.append(2 * np.polyfit(t, m["com_pos"][a2:b2, 2], 2)[0])
            if acc:
                acc = np.array(acc)
                r = abs(acc.mean()) / G
                print(f"       腾空相重力 {acc.mean():+.3f} ± {acc.std():.3f} m/s²"
                      f" = {r:.3f} g  ({len(acc)} 段)")
                if abs(r - 1) > 0.05:
                    print(f"       注: 偏离 -9.807 达 {abs(r-1)*100:.0f}%,"
                          f" 动力学不自洽(见 README 的 Froude 说明)")
    print()
    print(f"失败 {len(fail)} 项: " + ", ".join(fail) if fail else "全部通过")
    return 1 if fail else 0


if __name__ == "__main__":
    sys.exit(main())