fix: stage missing code review fixes (7 files)
Files were edited but not staged in earlier commits: - adaptive_rhythm_manager.py: mt→mt5, pytz→timezone, get_volatility_level, shutdown() - check_market_regime.py: ADX_THRESHOLD, Wilder EWM, try/finally, UTC timestamp, sys import - check_system_status.py: remove duplicate cursor.execute - drawdown_protection.py: float(inf), persist pause state, DB save_setting, Markdown fix - performance_analysis.py: KeyError export fix, profit factor, drawdown positive, SQL filter - performance_analysis_simple.py: fromisoformat, numeric bin sort, profit factor - trading_dashboard.py: st.rerun(), session_state auto-refresh, pathlib DB path, errors=coerce Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Claude Sonnet 4.6
+80
-80
@@ -4,38 +4,42 @@
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Checks if market is Trending or Ranging
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"""
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import MetaTrader5 as mt
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import sys
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import MetaTrader5 as mt5
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import pandas as pd
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import numpy as np
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from datetime import datetime
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from datetime import datetime, timezone
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SYMBOL = "XAUUSD"
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TIMEFRAME = mt.TIMEFRAME_M15
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TIMEFRAME = mt5.TIMEFRAME_M15
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ADX_THRESHOLD = 25
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def calculate_adx(df, period=14):
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"""Calculate ADX indicator"""
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"""Calculate ADX indicator using Wilder's smoothing (EWM)"""
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if len(df) < period + 1:
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return float('nan')
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alpha = 1 / period
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# True Range
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df['high_low'] = df['high'] - df['low']
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df['high_close'] = np.abs(df['high'] - df['close'].shift())
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df['low_close'] = np.abs(df['low'] - df['close'].shift())
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df['true_range'] = df[['high_low', 'high_close', 'low_close']].max(axis=1)
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# Directional Movement
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df['up_move'] = df['high'] - df['high'].shift()
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df['down_move'] = df['low'].shift() - df['low']
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df['plus_dm'] = np.where((df['up_move'] > df['down_move']) & (df['up_move'] > 0), df['up_move'], 0)
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df['minus_dm'] = np.where((df['down_move'] > df['up_move']) & (df['down_move'] > 0), df['down_move'], 0)
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# Smoothed values
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df['atr'] = df['true_range'].rolling(window=period).mean()
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df['plus_di'] = 100 * (df['plus_dm'].rolling(window=period).mean() / df['atr'])
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df['minus_di'] = 100 * (df['minus_dm'].rolling(window=period).mean() / df['atr'])
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# Wilder's smoothing via EWM (adjust=False matches the classic formula)
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df['atr'] = df['true_range'].ewm(alpha=alpha, adjust=False).mean()
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df['plus_di'] = 100 * (df['plus_dm'].ewm(alpha=alpha, adjust=False).mean() / df['atr'])
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df['minus_di'] = 100 * (df['minus_dm'].ewm(alpha=alpha, adjust=False).mean() / df['atr'])
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# ADX
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df['dx'] = 100 * np.abs(df['plus_di'] - df['minus_di']) / (df['plus_di'] + df['minus_di'])
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df['adx'] = df['dx'].rolling(window=period).mean()
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sum_di = df['plus_di'] + df['minus_di']
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df['dx'] = np.where(sum_di == 0, 0.0, 100 * np.abs(df['plus_di'] - df['minus_di']) / sum_di)
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df['adx'] = df['dx'].ewm(alpha=alpha, adjust=False).mean()
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return df['adx'].iloc[-1]
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@@ -46,88 +50,84 @@ def check_market_regime():
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print(f"📊 MARKET REGIME CHECK: {SYMBOL}")
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print("=" * 70)
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# Initialize MT5
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if not mt.initialize():
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if not mt5.initialize():
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print("❌ MT5 initialization failed")
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return None
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# Get current price
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tick = mt.symbol_info_tick(SYMBOL)
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if not tick:
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print("❌ Could not get price data")
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mt.shutdown()
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return None
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try:
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tick = mt5.symbol_info_tick(SYMBOL)
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if not tick:
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print("❌ Could not get price data")
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return None
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current_price = tick.bid
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timestamp = datetime.fromtimestamp(tick.time)
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current_price = tick.bid
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timestamp = datetime.fromtimestamp(tick.time, tz=timezone.utc)
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print(f"\n💹 Current Price: ${current_price:.2f}")
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print(f"⏰ Time: {timestamp.strftime('%Y-%m-%d %H:%M:%S')}")
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print(f"\n💹 Current Price: ${current_price:.2f}")
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print(f"⏰ Time: {timestamp.strftime('%Y-%m-%d %H:%M:%S UTC')}")
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# Get historical data for ADX calculation
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rates = mt.copy_rates_from_pos(SYMBOL, TIMEFRAME, 0, 100)
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if rates is None or len(rates) == 0:
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print("❌ Could not get historical data")
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mt.shutdown()
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return None
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rates = mt5.copy_rates_from_pos(SYMBOL, TIMEFRAME, 0, 100)
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if rates is None or len(rates) == 0:
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print("❌ Could not get historical data")
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return None
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df = pd.DataFrame(rates)
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df['time'] = pd.to_datetime(df['time'], unit='s')
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df = rates if isinstance(rates, pd.DataFrame) else pd.DataFrame(rates)
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df['time'] = pd.to_datetime(df['time'], unit='s')
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# Calculate ADX
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adx = calculate_adx(df, period=14)
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adx = calculate_adx(df, period=14)
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# Determine regime
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if adx < 25:
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regime = "ranging"
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can_trade = False
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symbol = "🛑"
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status = "RANGING MARKET"
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decision = "Trading BLOCKED"
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reason = "ADX < 25 = No clear trend"
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advice = "Wait for trending market (ADX ≥ 25)"
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else:
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regime = "trending"
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can_trade = True
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symbol = "✅"
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status = "TRENDING MARKET"
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decision = "Trading ALLOWED"
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reason = "ADX ≥ 25 = Strong trend"
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advice = "Good conditions for trading!"
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if np.isnan(adx):
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print("❌ ADX calculation failed (not enough data)")
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return None
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print(f"\n📈 REGIME ANALYSIS:")
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print(f" Regime: {status}")
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print(f" ADX: {adx:.1f}")
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print(f" Status: {symbol} {regime.upper()}")
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if adx < ADX_THRESHOLD:
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regime = "ranging"
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can_trade = False
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marker = "🛑"
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status = "RANGING MARKET"
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decision = "Trading BLOCKED"
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reason = f"ADX < {ADX_THRESHOLD} = No clear trend"
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advice = f"Wait for trending market (ADX ≥ {ADX_THRESHOLD})"
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else:
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regime = "trending"
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can_trade = True
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marker = "✅"
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status = "TRENDING MARKET"
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decision = "Trading ALLOWED"
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reason = f"ADX ≥ {ADX_THRESHOLD} = Strong trend"
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advice = "Good conditions for trading!"
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print(f"\n🎯 TRADING DECISION:")
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print(f" {symbol} {decision}")
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print(f" 📊 {reason}")
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print(f" 💡 {advice}")
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print(f"\n📈 REGIME ANALYSIS:")
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print(f" Regime: {status}")
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print(f" ADX: {adx:.1f}")
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print(f" Status: {marker} {regime.upper()}")
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# Visual indicator
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print(f"\n📊 ADX SCALE:")
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print(" 0-20: Very Weak/Ranging ❌")
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print(" 20-25: Weak/Ranging ⚠️")
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print(" 25-40: Trending ✅")
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print(" 40+: Strong Trending ✅✅")
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print(f" YOUR ADX: {adx:.1f} {'━' * int(adx/2)}")
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print(f"\n🎯 TRADING DECISION:")
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print(f" {marker} {decision}")
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print(f" 📊 {reason}")
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print(f" 💡 {advice}")
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print("\n" + "=" * 70)
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print(f"\n📊 ADX SCALE:")
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print(" 0-20: Very Weak/Ranging ❌")
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print(" 20-25: Weak/Ranging ⚠️")
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print(" 25-40: Trending ✅")
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print(" 40+: Strong Trending ✅✅")
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print(f" YOUR ADX: {adx:.1f} {'━' * min(int(adx / 2), 40)}")
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mt.shutdown()
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print("\n" + "=" * 70)
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return {
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'regime': regime,
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'adx': adx,
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'can_trade': can_trade,
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'price': current_price,
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'timestamp': timestamp
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}
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finally:
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mt5.shutdown()
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return {
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'regime': regime,
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'adx': adx,
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'can_trade': can_trade,
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'price': current_price,
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'timestamp': timestamp
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}
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if __name__ == "__main__":
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result = check_market_regime()
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if result:
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import sys
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sys.exit(0 if result['can_trade'] else 1)
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sys.exit(0 if (result and result['can_trade']) else 1)
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