# -*- coding: utf-8 -*-
"""择优激活规则 v2：修正上限逻辑——按质量排序选最优N个,家族去重,软上限
输出：每个温区应激活的策略（写入 strategy_weights.json 的 active）"""
import sys, json, sqlite3
sys.path.insert(0, "/home/hmo/MoFin")
sys.path.insert(0, "/home/hmo/MoFin/deploy/profile-scripts")
import strategy_qualify as sq

MIN_YEARLY = 15   # 年化成交下限（低于此=机会不足）
MAX_YEARLY = 300   # 年化成交上限（软上限，质量优先）

FAMILIES = {
    "s2_panic": "s2", "s2_panic_v2": "s2", "s2_panic_v3": "s2",
    "v_lurk_v1": "vlurk", "v_lurk_v2": "vlurk", "v_lurk_v3": "vlurk",
    "v_mr": "vmr", "v_mr2": "vmr", "v_mr3": "vmr", "v_mr4": "vmr",
    "v_oversold": "vover", "v_weak": "vweak",
    "b_td1": "b_td", "b_td1_v2": "b_td", "b_td1_v3": "b_td",
    "v1.0": "v1", "v2.0": "v2", "v3.0": "v3", "v_next": "vnext",
    "hk_pe_mom": "hkpe", "hk_pe_oversold": "hkpe", "hk_mr1": "hkmr", "hk_mr2": "hkmr",
}


def efficiency_factor(sig, pos):
    ratio = sig / pos if pos else 99
    if ratio <= 2: return 1.0
    if ratio <= 5: return 0.9
    if ratio <= 10: return 0.75
    return 0.5


def get_strategy_info(version, market, regime):
    conn = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=10)
    r = conn.execute(
        "SELECT trades, positions_taken, win_rate, sharpe_ratio, profit_factor, total_return_pct, "
        "portfolio_max_dd_pct, universality_score, universality_years, universality_valid_years "
        "FROM strategy_regime_perf_by_period WHERE strategy=? AND market=? AND regime=? AND period_tag='2y'",
        (version, market, regime)).fetchone()
    dep = conn.execute("SELECT MAX(deprecated) FROM strategy_research WHERE version=? AND deprecated IS NOT NULL AND deprecated!=''", (version,)).fetchone()[0]
    conn.close()
    if not r:
        return None
    sig, pos, wr, sh, pf, ret, dd, univ, uyears, uvalid = r
    pos = pos or 0
    ret_c = min(ret or 0, 100) / 100 * 30
    wr_c = (wr or 0) / 100 * 20
    sh_c = min(max(sh or 0, 0), 20) / 20 * 20
    pf_c = min(pf or 0, 5) / 5 * 15
    dd_c = (1 - min(dd or 0, 50) / 50) * 15
    n = sig or 0
    conf = min(1, n / 40)
    eff = efficiency_factor(sig, pos)
    comp = round((ret_c + wr_c + sh_c + pf_c + dd_c) * conf * eff)
    return {"sig": sig, "pos": pos, "comp": comp, "univ": univ or 0,
            "uyears": uyears or 0, "uvalid": uvalid or 0, "dep": dep}


def select_best(regime, market='a'):
    conn = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=10)
    rows = conn.execute("SELECT DISTINCT strategy FROM strategy_regime_perf_by_period WHERE market=? AND regime=?", (market, regime)).fetchall()
    conn.close()
    avail = sq.load_availability()
    candidates = []
    for (version,) in rows:
        info = get_strategy_info(version, market, regime)
        if not info or info["dep"]:
            continue
        if not avail.get(version, {}).get("available", False):
            continue
        try:
            q = sq.evaluate_all_regimes(version, market=market)
            qr = q.get(regime, {})
            if not (qr.get("long_ok") and qr.get("mid_ok") and qr.get("short_ok")):
                continue
        except Exception:
            continue
        # 质量分 = 综合分 × 普适（有效年占比越高越好）
        univ_ratio = (info["uvalid"] / info["uyears"]) if info["uyears"] else 0
        quality = info["comp"] * (0.5 + 0.5 * univ_ratio)
        candidates.append({"version": version, "info": info, "quality": round(quality, 1),
                           "family": FAMILIES.get(version, version)})
    candidates.sort(key=lambda x: -x["quality"])

    # 择优：家族去重 + 软上限
    selected = []
    used_fam = set()
    total_yearly = 0
    for c in candidates:
        if c["family"] in used_fam:
            continue
        # 出手次数太少的不选（年化 < MIN_YEARLY/2）
        yearly = c["info"]["pos"] / 2  # 2y→年化
        if yearly < 5:
            continue
        if total_yearly + yearly > MAX_YEARLY and selected:
            break  # 超上限停止
        used_fam.add(c["family"])
        selected.append(c)
        total_yearly += yearly
    return selected, total_yearly


if __name__ == "__main__":
    print("# 择优激活建议（质量分=综合分×普适有效年占比）")
    all_sel = {}
    for market in ["a", "hk"]:
        for regime in ["trend_down", "choppy", "trend_up"]:
            sel, total = select_best(regime, market)
            if sel:
                print(f"\n## {market} {regime}: 年化总出手≈{total:.0f}")
                for c in sel:
                    i = c["info"]
                    print(f"   {c['version']:18} 质量{c['quality']:5.1f} 综合{i['comp']:4} 信号{i['sig']:5} 成交{i['pos']:4} 普适{i['univ']:4.0f}({i['uvalid']}/{i['uyears']}年)")
                all_sel[(market, regime)] = [c["version"] for c in sel]
    # 保存建议
    with open("/tmp/activation_suggestion.json", "w") as f:
        json.dump({f"{m}:{r}": v for (m, r), v in all_sel.items()}, f, ensure_ascii=False, indent=1)
    print("\n# 建议已存 /tmp/activation_suggestion.json")