#!/usr/bin/env python3
# step48_predict_dd.py - 阴跌中段判定测试
import numpy as np
import pandas as pd

print("=== 加载 ===", flush=True)
tr = pd.read_csv("/tmp/step43_trades.csv")
print("交易:", len(tr), flush=True)
print("全量: avg={:.2f}% wr={:.1f}% 大亏率={:.1f}%".format(
    tr["ret"].mean(), (tr["ret"]>0).mean()*100, (tr["ret"]<-10).mean()*100), flush=True)

def evaluate(cond, label):
    sub = tr[cond]
    if len(sub) < 50:
        print("{}: n={} 不足".format(label, len(sub)), flush=True)
        return
    avg = sub["ret"].mean()
    wr = (sub["ret"]>0).mean()*100
    big_loss = (sub["ret"]<-10).mean()*100
    print("{}: n={} avg={:.2f}% wr={:.1f}% 大亏率={:.1f}%".format(
        label, len(sub), avg, wr, big_loss), flush=True)

print("\n=== 单特征阈值扫描 ===", flush=True)
print("\n-- mkt_down_days >= N --", flush=True)
for t in [2, 3, 4]:
    evaluate(tr["mkt_down_days"] >= t, "连跌>={}（阴跌）".format(t))

print("\n-- sig_mkt_adx <= N --", flush=True)
for t in [40, 45, 50, 55]:
    evaluate(tr["sig_mkt_adx"] <= t, "adx<={}（弱趋势）".format(t))

print("\n-- mkt_news5 <= N --", flush=True)
for t in [1000, 1500, 2000]:
    evaluate(tr["mkt_news5"] <= t, "news<={}（冷清）".format(t))

print("\n=== 组合：阴跌中段判定 ===", flush=True)
yin_die = (tr["mkt_down_days"] >= 2) & (tr["sig_mkt_adx"] <= 50)
print("阴跌判定(连跌>=2+adx<=50) 命中:", yin_die.sum(), flush=True)
evaluate(~yin_die, "保留（非阴跌）")
evaluate(yin_die, "跳过（阴跌）")

yin_die2 = (tr["mkt_down_days"] >= 2) & (tr["sig_mkt_adx"] <= 50) & (tr["mkt_news5"] <= 2000)
print("阴跌判定2(+news<=2000) 命中:", yin_die2.sum(), flush=True)
evaluate(~yin_die2, "保留（非阴跌2）")
evaluate(yin_die2, "跳过（阴跌2）")

yin_die3 = (tr["mkt_down_days"] >= 2) & (tr["sig_mkt_adx"] <= 55) & (tr["sig_mkt_rsi"] >= 33)
print("阴跌判定3(连跌>=2+adx<=55+rsi>=33) 命中:", yin_die3.sum(), flush=True)
evaluate(~yin_die3, "保留（非阴跌3）")
evaluate(yin_die3, "跳过（阴跌3）")

print("\n=== 完成 ===", flush=True)