"""逐根对拍「全量重算」与「增量追加」，并量提速。

## 为什么必须逐根对拍，不能引用 HANDOFF §5.5

§5.5 验的是 step46 那批用例（走 bsp_list 那条链），且是「追加 150~200 根 vs
全量重建」的整体哈希。影子路径不同：

  - 走 find_fast_bsp3 + build_htf_zones + htf_fx_timeline + attach_htf_context
  - 流式对象**跨根复用**，而 worker 轮流拿多个币，同一条流可能隔几根才被
    再次追加。状态污染只会让信号悄悄换一批，不报错、不崩

而且代码阅读已经暴露一处偏差：`init_stream/append_bar` 从不调 `cal_trend`
（它只在 `get_klc_list` 里），所以增量路径下 `klc.trend` 恒为 UNKNOWN。
HANDOFF 说「笔的计算依赖 klc.trend」——若为真，增量的笔就和全量不同。
那句话所引的 bi.py:221 其实在 `cal_trend` 自己的循环里，不是 `cal_bi_list`
的依赖。**这条只能由对拍来定论**，不能靠读代码。

## 判据

逐字段相同，排除 last_idx/n_bars（随窗口长度必然变，见 verify_window_sens）
与计时字段。数量相同而标志不同一样算失败。

模拟真实调用模式：连续推进，且每根都按「全量」和「增量」各算一次，增量那侧
复用同一条流。

    python research/live/verify_incr_parity.py --syms BTC,ETH,SOL --n 300
"""
from __future__ import annotations

import argparse
import os
import sys
import time
import warnings
from pathlib import Path

import numpy as np
import pandas as pd

warnings.filterwarnings("ignore")
for _v in ("OMP_NUM_THREADS", "OPENBLAS_NUM_THREADS", "MKL_NUM_THREADS"):
    os.environ.setdefault(_v, "1")

HERE = Path(__file__).resolve()
sys.path.insert(0, str(HERE.parents[1]))
sys.path.insert(0, str(HERE.parents[2]))
sys.path.insert(0, str(HERE.parent))

BASE_L, BASE_H = 2001, 801


def run_one(sym: str, cache: Path, n: int, start_at: int | None) -> dict:
    import shadow_signal as ss
    from verify_lean_parity import SKIP, WINDOW_KEYS, canon, load, signal_bars

    skip = SKIP + WINDOW_KEYS + ("stream_bars",)
    l_all, h_all = load(sym, "1m", cache), load(sym, "5m", cache)
    l_ts = l_all["timestamp"].to_numpy("int64")
    h_ts = h_all["timestamp"].to_numpy("int64")

    # 从最后一个信号根往前 n 根开始，保证这段里一定有信号分支被执行
    if start_at is None:
        try:
            sb = signal_bars(sym, cache)
            sb = sb[(sb > BASE_L + n) & (sb < len(l_all) - 1)]
            start_at = int(sb[-1]) - n + 5 if len(sb) else BASE_L + 10
        except Exception:
            start_at = BASE_L + 10
    ends = [e for e in range(start_at, start_at + n) if e < len(l_all) - 1]
    if not ends:
        raise RuntimeError("窗口不足")

    ss._STREAMS.clear()
    same = diff = 0
    t_full = t_incr = 0.0
    n_hits = 0
    first = None
    rebuilds = 0
    prev_grown = 0

    for e in ends:
        hi = int(np.searchsorted(h_ts, l_ts[e], side="right"))
        df_l = l_all.iloc[e - BASE_L + 1:e + 1]
        df_h = h_all.iloc[max(0, hi - BASE_H):hi]
        entry = float(l_all["open"].to_numpy(float)[e + 1])

        t0 = time.perf_counter()
        rf = ss.compute(df_l.copy(), df_h.copy(), entry, incr=False)
        t_full += time.perf_counter() - t0

        t0 = time.perf_counter()
        ri = ss.compute(df_l.copy(), df_h.copy(), entry, sym=sym, incr=True)
        t_incr += time.perf_counter() - t0

        grown = len(ss._STREAMS[(sym, "1m")][0].dataframe)
        if grown <= prev_grown:
            rebuilds += 1
        prev_grown = grown

        n_hits += len(rf.get("hits") or [])
        if canon(rf, skip) == canon(ri, skip):
            same += 1
        else:
            diff += 1
            if first is None:
                first = (e, canon(rf, skip), canon(ri, skip))

    k = len(ends)
    print(f"  {k} 根 · 一致 {same} · 不一致 {diff} · 命中 {n_hits} 个 · "
          f"重建 {rebuilds} 次 · 末窗 {prev_grown} 根")
    print(f"  单根 全量 {t_full / k * 1000:.1f}ms → "
          f"增量 {t_incr / k * 1000:.1f}ms "
          f"（{t_full / max(t_incr, 1e-9):.2f}x）")
    if first:
        e, a, b = first
        print(f"  ⚠ 首个分歧 idx={e}\n    全量: {a[:300]}\n    增量: {b[:300]}")
    ss._STREAMS.clear()
    del l_all, h_all
    return {"sym": sym, "n": k, "same": same, "diff": diff, "hits": n_hits,
            "full_ms": t_full / k * 1000, "incr_ms": t_incr / k * 1000}


def main() -> None:
    ap = argparse.ArgumentParser()
    ap.add_argument("--syms", default="BTC,ETH,SOL")
    ap.add_argument("--cache", default="research/live/cache")
    ap.add_argument("--n", type=int, default=300)
    ap.add_argument("--start", type=int, default=None)
    a = ap.parse_args()

    rows = []
    for sym in a.syms.split(","):
        print(f"\n{'=' * 70}\n{sym}")
        try:
            rows.append(run_one(sym, Path(a.cache), a.n, a.start))
        except Exception as e:
            print(f"  跳过：{e!r}")
    if not rows:
        return
    d = pd.DataFrame(rows)
    print(f"\n\n{'=' * 70}\n汇总\n")
    print(f"  对拍 {int(d['n'].sum()):,} 根 · 不一致 {int(d['diff'].sum())} · "
          f"命中 {int(d['hits'].sum())} 个")
    print(f"  单根 全量 {d['full_ms'].mean():.1f}ms → "
          f"增量 {d['incr_ms'].mean():.1f}ms "
          f"（{d['full_ms'].sum() / max(d['incr_ms'].sum(), 1e-9):.2f}x）")
    if int(d["diff"].sum()) == 0:
        print("\n  逐字段一致，增量可以上线。")
    else:
        print("\n  ⛔ 有分歧，不要上线。增量流的状态与全量重建不等价。")


if __name__ == "__main__":
    main()