# -*- coding: utf-8 -*-
"""邻域参数稳健性检验（导出 JSON 供绘图）——逻辑同 稳健性检验.py"""
import os, importlib.util, itertools, json, statistics

BASE = os.path.dirname(os.path.abspath(__file__))
spec = importlib.util.spec_from_file_location("v2", os.path.join(BASE, "均值回归_双向.py"))
v2 = importlib.util.module_from_spec(spec); spec.loader.exec_module(v2)

days = v2.load_days()
cache = {N: v2.make_dev_cache(days, N) for N in (10, 15, 20, 30)}


def score(pl, ps):
    tl = v2.run_side(cache[pl["N"]], "long", K=pl["K"], TP=pl["TP"], SL=pl["SL"], ED=pl["ED"],
                     trend_filter=True, skip_open=5, max_per_day=2)
    ts = v2.run_side(cache[ps["N"]], "short", K=ps["K"], TP=ps["TP"], SL=ps["SL"], ED=ps["ED"],
                     trend_filter=True, skip_open=5, max_per_day=2)
    q = {}
    for t in tl + ts:
        k = v2.quarter_key(t["date"])
        q[k] = q.get(k, 0.0) + t["ret"]
    return q, sum(t["ret"] for t in tl), sum(t["ret"] for t in ts), len(tl) + len(ts)


res = []
for ln, lk, lt, ls in itertools.product([10, 15, 20], [-0.2, -0.3, -0.4], [0.3, 0.5], [0.5, 1.0]):
    for sn, sk, st, ss in itertools.product([10, 15, 20], [0.3, 0.4, 0.5], [0.3, 0.5], [0.3, 0.5]):
        q, tl, ts, n = score({"N": ln, "K": lk, "TP": lt, "SL": ls, "ED": -0.1},
                             {"N": sn, "K": sk, "TP": st, "SL": ss, "ED": -0.1})
        if len(q) < 12 or ts < 0 or tl < 5:
            continue
        res.append({"neg": sum(1 for x in q.values() if x < 0), "lo": min(q.values()),
                    "tot": tl + ts, "n": n,
                    "L": [ln, lk, lt, ls], "S": [sn, sk, st, ss]})

tots = [r["tot"] for r in res]
los = [r["lo"] for r in res]
negs = [r["neg"] for r in res]
out = {
    "all": len(res),
    "ok12": sum(1 for r in res if r["neg"] == 0 and r["lo"] >= 0.2),
    "ok11": sum(1 for r in res if r["neg"] <= 1),
    "zero_neg": sum(1 for r in res if r["neg"] == 0),
    "tot_median": statistics.median(tots), "tot_mean": statistics.mean(tots),
    "tot_min": min(tots), "tot_max": max(tots),
    "lo_median": statistics.median(los), "lo_min": min(los), "lo_max": max(los),
    "neg_hist": {str(i): sum(1 for x in negs if x == i) for i in range(0, 13)},
    "tots": tots, "los": los, "negs": negs,
    "top": sorted(res, key=lambda x: (x["neg"], -x["lo"], -x["tot"]))[:15],
}
json.dump(out, open(os.path.join(BASE, "稳健性检验结果.json"), "w", encoding="utf-8"),
          ensure_ascii=False, indent=1)
print("有效组合 %d ｜ 12季度全正 %d (%.0f%%) ｜ 最多1个季度为负 %d (%.0f%%)"
      % (out["all"], out["ok12"], out["ok12"] / out["all"] * 100,
         out["ok11"], out["ok11"] / out["all"] * 100))
print("总增厚 中位%.2f%% 最小%.2f%% 最大%.2f%% ｜ 最差季度 中位%+.2f%%"
      % (out["tot_median"], out["tot_min"], out["tot_max"], out["lo_median"]))
print("负季度数分布:", out["neg_hist"])