#!/usr/bin/env python3 """Rekonstruiert die heutigen Empfehlungen (echte _build-Logik) über die M5-Bars und korreliert sie mit dem Kurs + den heutigen Trades. Zeigt Signal-Wechsel, Trefferquote und Auffälligkeiten.""" import datetime as dt import sqlite3 import MetaTrader5 as mt5 from core.wave_rec import (WaveRecommender, _atr, _ema_last, _EMA_FAST, _EMA_SLOW, _N_BARS, _HTF_DEADBAND, _ANGLE_LR) from core.analysis import calc_trend_angle OFF = 3600 # Broker(UTC+3)→Berlin(UTC+2, Juni): epoch-1h class _TU: def snapshot(self): return {"intervals": {}} 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 bt(ts): return dt.datetime.utcfromtimestamp(ts-OFF) # Berlin 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, 700) m30=mt5.copy_rates_from_pos(sym, mt5.TIMEFRAME_M30, 0, 200) 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) def m30s(ts): lo,hi,idx=0,len(mT)-1,-1 while lo<=hi: md=(lo+hi)//2 if mT[md]<=ts: idx=md; lo=md+1 else: hi=md-1 if idx<_EMA_SLOW or mA[idx] is None or mA[idx]<=0: return 0 d=mEf[idx]-mEs[idx] return 0 if abs(d)<_HTF_DEADBAND*mA[idx] else (1 if d>0 else -1) today = bt(T[-1]).date() w=WaveRecommender(_TU(), mt5.TIMEFRAME_M5) rows=[] # (i, berlin, close, signal, conf, reason) K=6 for i in range(_N_BARS, len(C)): b=bt(T[i]) if b.date()!=today: continue 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) ang=calc_trend_angle(C[i-_ANGLE_LR-2:i],_ANGLE_LR) rec,_=w._build(ef,es,C[i-1],atr,"M5",5,htf_trend=m30s(T[i]), angle=ang,hour=b.hour) fwd=(C[i+K]-C[i]) if i+K3} {rs[:54]}") prev=sig # Trefferquote der Nicht-WARTEN-Signale (Vorlauf 6 Bars) ev=[(sig,fwd) for (_,_,_,sig,_,_,fwd) in rows if sig in ("LONG","SHORT") and fwd is not None] if ev: win=sum(1 for s,f in ev if (f>0)==(s=="LONG")) edge=sum((f if s=="LONG" else -f) for s,f in ev)/len(ev) nL=sum(1 for s,_ in ev if s=="LONG"); nS=len(ev)-nL print(f"\nSignale heute: {len(ev)} (LONG {nL} / SHORT {nS}) · Treffer {100*win/len(ev):.0f}% · Oe-Edge {edge:+.4f}") warten=sum(1 for (_,_,_,s,_,_,_) in rows if s=="WARTEN") print(f"WARTEN-Bars: {warten}/{len(rows)} ({100*warten/max(1,len(rows)):.0f}%)") # Trades heute print("\nTrades heute (DB):") c=sqlite3.connect('oil_widget_history.db'); c.row_factory=sqlite3.Row t0=dt.datetime.now().replace(hour=0,minute=0,second=0,microsecond=0).timestamp() for r in c.execute('SELECT entry_time,exit_time,direction,entry_price,exit_price,pnl,closed_by FROM trades WHERE exit_time>=? ORDER BY exit_time',(t0,)): print(f" {dt.datetime.fromtimestamp(r['entry_time']).strftime('%H:%M')}→{dt.datetime.fromtimestamp(r['exit_time']).strftime('%H:%M')} " f"{r['direction']:4} {r['entry_price']:.3f}→{r['exit_price']:.3f} pnl {r['pnl']:+.2f} {r['closed_by']}")