#!/usr/bin/env python3
"""Exit-Refactoring: dreht eine andere Exit-Logik die VERLUST-ASYMMETRIE um?
Live-Problem (real gemessen): WR 59%, aber Ø-Gewinn nur ~0,47× Ø-Verlust → PF 0,68.
Ursache: enges Trailing-TP (HW−0,5×ATR) kappt Gewinner, fixer 2×ATR-SL lässt
Verlierer voll laufen → kleine Gewinne, große Verluste.

Hier: gleiche Signale, verschiedene Exit-Modelle. Kennzahl = avg_win / avg_loss
(>=1 = Schiefe gedreht) + ΣR/PF. Trailing-STOP-Distanz und Initial-SL variiert.
Pessimistisch (Gegenlauf vor Mitlauf).
"""
import sys
import MetaTrader5 as mt5
from core.analysis import calc_trend_angle
from core.wave_rec import (WaveRecommender, _atr, _ema_last, _EMA_FAST, _EMA_SLOW,
                           _N_BARS, _HTF_DEADBAND, _ANGLE_LR)

_MAXH = 288; _ATRMIN = 0.12

def _ema_series(v,p):
    k=2.0/(p+1); o=[]; e=v[0]
    for i,x in enumerate(v): e=x if i==0 else x*k+e*(1-k); o.append(e)
    return o
def _atr_series(H,L,C,p=14):
    t=[0.0]
    for i in range(1,len(C)): t.append(max(H[i]-L[i],abs(H[i]-C[i-1]),abs(L[i]-C[i-1])))
    return [(sum(t[max(1,i-p+1):i+1])/max(1,len(t[max(1,i-p+1):i+1]))) if i else None for i in range(len(C))]

def sim(entry,d,atr,H,L,C,j0, sl_atr, trail, trail_on=0.3, be_on=1.0, tp_atr=None):
    """Trailing-STOP-Modell: Initial-SL sl_atr; ab trail_on Profit Stop = HW∓trail×ATR
    (Breakeven-Floor ab be_on). Optionaler harter TP. Rückgabe R."""
    eff = entry - d*sl_atr*atr
    hw = entry
    tp = (entry + d*tp_atr*atr) if tp_atr else None
    end=min(j0+_MAXH, len(C)-1); exit_px=C[end]
    for j in range(j0,end+1):
        hi,lo=H[j],L[j]
        # Gegenlauf zuerst (Stop)
        if (lo<=eff) if d>0 else (hi>=eff): exit_px=eff; break
        # harter TP
        if tp is not None and ((hi>=tp) if d>0 else (lo<=tp)): exit_px=tp; break
        hw=max(hw,hi) if d>0 else min(hw,lo)
        prof=(C[j]-entry)*d
        if trail and prof>=trail_on*atr:
            cand=hw-d*trail*atr
            if prof>=be_on*atr:
                cand=max(cand,entry) if d>0 else min(cand,entry)
            eff=max(eff,cand) if d>0 else min(eff,cand)
    return (exit_px-entry)*d/atr

def stats(name, Rs):
    if not Rs: print(f"  {name:<26} -"); return
    n=len(Rs); wins=[r for r in Rs if r>0]; loss=[r for r in Rs if r<=0]
    aw=sum(wins)/len(wins) if wins else 0; al=sum(loss)/len(loss) if loss else 0
    ratio=(aw/abs(al)) if al<0 else 99
    g=sum(wins); ls=-sum(loss); pf=g/ls if ls>0 else 99
    print(f"  {name:<26} n={n:>4} WR={100*len(wins)/n:>3.0f}% Øgew={aw:+.2f} Øverl={al:+.2f} "
          f"Verh={ratio:>4.2f} ØR={sum(Rs)/n:+.3f} PF={pf:>4.2f} ΣR={sum(Rs):+.0f} Worst={min(Rs):+.1f}")

def main():
    n=int(sys.argv[1]) if len(sys.argv)>1 else 40000
    mt5.initialize()
    sym=None
    for c in ("SpotCrude","USOIL","WTI","XTIUSD"):
        if mt5.symbol_info(c): sym=c; break
    bars=mt5.copy_rates_from_pos(sym,mt5.TIMEFRAME_M5,0,n+_N_BARS+_MAXH+5)
    m30=mt5.copy_rates_from_pos(sym,mt5.TIMEFRAME_M30,0,n//6+500)
    mt5.shutdown()
    T=[int(b["time"]) for b in bars]; H=[float(b["high"]) for b in bars]
    L=[float(b["low"]) for b in bars]; C=[float(b["close"]) for b in bars]
    mT=[int(b["time"]) for b in m30]; mc=[float(b["close"]) for b in m30]
    mh=[float(b["high"]) for b in m30]; ml=[float(b["low"]) for b in m30]
    mEf=_ema_series(mc,_EMA_FAST); mEs=_ema_series(mc,_EMA_SLOW); mA=_atr_series(mh,ml,mc)
    import bisect
    def m30s(ts):
        idx=bisect.bisect_right(mT,ts)-1
        if idx<_EMA_SLOW or mA[idx] is None or mA[idx]<=0: return 0
        dd=mEf[idx]-mEs[idx]
        return 0 if abs(dd)<_HTF_DEADBAND*mA[idx] else (1 if dd>0 else -1)
    class _TU:
        def snapshot(self): return {"intervals": {}}
    w=WaveRecommender(_TU(), mt5.TIMEFRAME_M5)
    sigs=[]
    for i in range(_N_BARS, len(C)-_MAXH-1):
        wc=C[i-_N_BARS:i]; wh=H[i-_N_BARS:i]; wl=L[i-_N_BARS:i]
        atr=_atr(wh,wl,wc)
        if not atr or atr<=0: continue
        ef=_ema_last(wc,_EMA_FAST); es=_ema_last(wc,_EMA_SLOW)
        a5=calc_trend_angle(C[i-_ANGLE_LR-2:i],_ANGLE_LR)
        rec,_=w._build(ef,es,C[i-1],atr,"M5",0,htf_trend=m30s(T[i]),angle=a5)
        if rec["signal"]=="WARTEN": continue
        d=1 if rec["signal"]=="LONG" else -1
        sigs.append((i,d,max(atr,_ATRMIN)))

    print("="*112)
    print(f"  Exit-Refactoring — {sym} M5  Signale={len(sigs)}  (Ziel: Verh = Øgew/Øverl ≥ 1)")
    print("="*112)
    def run(name,**kw):
        Rs=[sim(C[i],d,atr,H,L,C,i+1,**kw) for (i,d,atr) in sigs]
        stats(name,Rs)
    print("AKTUELL (Problem):")
    run("SL2.0 + Trail 0.5 (live)", sl_atr=2.0, trail=0.5, be_on=1.0)
    print("\nGewinner laufen lassen (weiteres Trailing):")
    run("SL2.0 + Trail 1.0", sl_atr=2.0, trail=1.0, be_on=1.0)
    run("SL2.0 + Trail 1.5", sl_atr=2.0, trail=1.5, be_on=1.0)
    run("SL2.0 + Trail 2.0", sl_atr=2.0, trail=2.0, be_on=1.0)
    print("\nVerlierer enger cutten (kleinerer Initial-SL) + Trailing 1.5:")
    run("SL1.0 + Trail 1.5", sl_atr=1.0, trail=1.5, be_on=0.8)
    run("SL1.2 + Trail 1.5", sl_atr=1.2, trail=1.5, be_on=0.8)
    run("SL1.5 + Trail 1.5", sl_atr=1.5, trail=1.5, be_on=1.0)
    print("\nFeste R:R-Ziele (TP erzwingt Symmetrie):")
    run("SL1.5 + TP2.25 (RR1.5)", sl_atr=1.5, trail=None, tp_atr=2.25)
    run("SL1.5 + TP3.0 (RR2.0)", sl_atr=1.5, trail=None, tp_atr=3.0)
    run("SL2.0 + TP4.0 (RR2.0)", sl_atr=2.0, trail=None, tp_atr=4.0)

if __name__=="__main__":
    main()