better testcase managment, script fix
This commit is contained in:
Dobromir Popov
@ -138,6 +138,7 @@ class CleanTradingDashboard:
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self.current_leverage = 50 # Default x50 leverage
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self.min_leverage = 1
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self.max_leverage = 100
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self.pending_trade_case_id = None # For tracking opening trades until closure
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# WebSocket streaming
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self.ws_price_cache = {}
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@ -2026,73 +2027,109 @@ class CleanTradingDashboard:
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'training_ready': True
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}
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# APPLY LEVERAGE TO P&L for display and storage
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raw_pnl = latest_trade.pnl
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leveraged_pnl = raw_pnl * self.current_leverage
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# Update trade record with leveraged P&L
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trade_record['pnl_raw'] = raw_pnl
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trade_record['pnl_leveraged'] = leveraged_pnl
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trade_record['leverage_used'] = self.current_leverage
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# Update latest_trade P&L for display
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latest_trade.pnl = leveraged_pnl
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# Add leveraged P&L to session total
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self.session_pnl += leveraged_pnl
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# Only add if not already in closed_trades
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if not any(t.get('entry_time') == trade_record['entry_time'] for t in self.closed_trades):
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self.closed_trades.append(trade_record)
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logger.info(f"Added completed trade to closed_trades: {action} P&L ${latest_trade.pnl:.2f}")
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logger.info(f"Added completed trade to closed_trades: {action} P&L ${leveraged_pnl:.2f} (raw: ${raw_pnl:.2f}, leverage: x{self.current_leverage})")
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# MOVE BASE CASE TO POSITIVE/NEGATIVE based on leveraged outcome
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if hasattr(self, 'pending_trade_case_id') and self.pending_trade_case_id:
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try:
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# Capture closing snapshot
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closing_model_inputs = self._get_comprehensive_market_state(symbol, current_price)
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closing_cob_snapshot = self._capture_cob_snapshot_for_training(symbol, current_price)
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closing_trade_record = {
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'symbol': symbol,
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'side': action,
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'quantity': latest_trade.quantity,
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'exit_price': current_price,
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'leverage': self.current_leverage,
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'pnl_raw': raw_pnl,
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'pnl_leveraged': leveraged_pnl,
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'confidence': 1.0,
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'trade_type': 'manual',
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'model_inputs_at_exit': closing_model_inputs,
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'cob_snapshot_at_exit': closing_cob_snapshot,
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'timestamp_exit': datetime.now(),
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'training_ready': True,
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'trade_status': 'CLOSED'
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}
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# Move from base to positive/negative based on leveraged outcome
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outcome_case_id = trade_data_manager.move_base_trade_to_outcome(
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self.pending_trade_case_id,
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closing_trade_record,
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leveraged_pnl >= 0
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)
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if outcome_case_id:
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logger.info(f"Trade moved from base to {'positive' if leveraged_pnl >= 0 else 'negative'}: {outcome_case_id}")
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# TRIGGER TRAINING on completed trade pair (opening + closing)
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try:
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from core.training_integration import TrainingIntegration
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training_integration = TrainingIntegration(self.orchestrator)
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training_success = training_integration.trigger_cold_start_training(
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closing_trade_record, outcome_case_id
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)
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if training_success:
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logger.info(f"Retrospective RL training completed for trade pair (P&L: ${leveraged_pnl:.3f})")
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else:
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logger.warning(f"Retrospective RL training failed for trade pair")
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except Exception as e:
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logger.warning(f"Failed to trigger retrospective RL training: {e}")
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# Clear pending case ID
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self.pending_trade_case_id = None
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except Exception as e:
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logger.warning(f"Failed to move base case to outcome: {e}")
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else:
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logger.debug("No pending trade case ID found - this may be a position opening")
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# Store for cold start training when trade closes using core TradeDataManager
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# Store OPENING trade as BASE case (temporary) - will be moved to positive/negative when closed
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try:
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case_id = trade_data_manager.store_trade_for_training({
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opening_trade_record = {
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'symbol': symbol,
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'side': action,
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'quantity': 0.01,
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'quantity': size,
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'entry_price': current_price,
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'leverage': self.current_leverage, # Store leverage at entry
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'pnl': 0.0, # Will be updated when position closes
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'confidence': 1.0,
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'trade_type': 'manual',
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'model_inputs_at_entry': model_inputs,
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'training_ready': True
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})
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if case_id:
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logger.info(f"Trade stored for training with case ID: {case_id}")
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except Exception as e:
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logger.warning(f"Failed to store trade for training: {e}")
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# Store for cold start training when trade closes using core TradeDataManager
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try:
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case_id = trade_data_manager.store_trade_for_training(trade_record)
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if case_id:
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logger.info(f"Trade stored for training with case ID: {case_id}")
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except Exception as e:
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logger.warning(f"Failed to store trade for training: {e}")
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# Update session metrics
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if action == 'BUY':
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self.session_pnl += 0.0 # No immediate P&L for entry
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else: # SELL
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# For demo purposes, simulate small positive P&L
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demo_pnl = 0.05 # $0.05 demo profit
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self.session_pnl += demo_pnl
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trade_record['pnl'] = demo_pnl
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'cob_snapshot_at_entry': cob_snapshot,
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'timestamp_entry': datetime.now(),
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'training_ready': False, # Not ready until closed
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'trade_status': 'OPENING'
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}
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# TRIGGER RETROSPECTIVE RL TRAINING (NO HOLD SIGNALS)
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# Only train on BUY/SELL actions with meaningful outcomes
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if action in ['BUY', 'SELL'] and case_id:
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try:
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from core.training_integration import TrainingIntegration
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training_integration = TrainingIntegration(self.orchestrator)
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# Enhanced trade record with COB data for RL loop
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enhanced_trade_record = trade_record.copy()
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enhanced_trade_record.update({
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'cob_data_available': bool(cob_snapshot),
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'training_priority': 'HIGH' if abs(demo_pnl) > 0.1 else 'NORMAL',
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'signal_type': 'BUY_SELL_ONLY', # No HOLD signals
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'model_inputs_complete': bool(model_inputs)
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})
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training_success = training_integration.trigger_cold_start_training(
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enhanced_trade_record, case_id
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)
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if training_success:
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logger.info(f"Retrospective RL training completed for {action} trade (P&L: ${demo_pnl:.3f})")
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else:
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logger.warning(f"Retrospective RL training failed for {action} trade")
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except Exception as e:
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logger.warning(f"Failed to trigger retrospective RL training: {e}")
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else:
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logger.debug(f"Skipped training for {action} - only BUY/SELL signals are trained")
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# Store as BASE case (temporary) using special base directory
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base_case_id = trade_data_manager.store_base_trade_for_later_classification(opening_trade_record)
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if base_case_id:
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logger.info(f"Opening trade stored as base case: {base_case_id}")
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# Store the base case ID for when we close the position
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self.pending_trade_case_id = base_case_id
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except Exception as e:
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logger.warning(f"Failed to store opening trade as base case: {e}")
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self.pending_trade_case_id = None
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else:
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decision['executed'] = False
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@ -2418,8 +2455,9 @@ class CleanTradingDashboard:
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self.ws_price_cache = {}
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self.current_prices = {}
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# Clear current position
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# Clear current position and pending trade tracking
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self.current_position = None
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self.pending_trade_case_id = None # Clear pending trade tracking
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logger.info("Session data cleared")
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