cleanup, cob ladder still broken

web/clean_dashboard.py

@@ -5426,9 +5426,24 @@ class CleanTradingDashboard:
                         confidence_target_tensor = torch.FloatTensor([confidence_target]).to(device)
                         
                         network.train()
-                        action_logits, predicted_confidence = network(features_tensor)
+                        network_output = network(features_tensor)
+                        
+                        # Handle different return formats from network
+                        if isinstance(network_output, tuple) and len(network_output) == 2:
+                            action_logits, predicted_confidence = network_output
+                        elif hasattr(network_output, 'dim'):
+                            # Single tensor output - assume it's action logits
+                            action_logits = network_output
+                            predicted_confidence = torch.tensor(0.5, device=device)  # Default confidence
+                        else:
+                            logger.debug(f"Unexpected network output format: {type(network_output)}")
+                            continue
+                        
+                        # Ensure predicted_confidence is a tensor with proper dimensions
+                        if not hasattr(predicted_confidence, 'dim'):
+                            # If it's not a tensor, convert it
+                            predicted_confidence = torch.tensor(float(predicted_confidence), device=device)
                         
-                        # Ensure predicted_confidence has a batch dimension if it doesn't already
                         if predicted_confidence.dim() == 0:
                             predicted_confidence = predicted_confidence.unsqueeze(0)
                         
@@ -6048,4 +6063,7 @@ def create_clean_dashboard(data_provider: Optional[DataProvider] = None, orchest
         data_provider=data_provider,
         orchestrator=orchestrator,
         trading_executor=trading_executor
-    ) 
+    ) 
+    
+    
+    # test edit

web/component_manager.py

@@ -275,18 +275,28 @@ class DashboardComponentManager:
     def format_cob_data(self, cob_snapshot, symbol, cumulative_imbalance_stats=None):
         """Format COB data into a split view with summary, imbalance stats, and a compact ladder."""
         try:
-            if not cob_snapshot or not hasattr(cob_snapshot, 'stats'):
+            if not cob_snapshot:
                 return html.Div([
                     html.H6(f"{symbol} COB", className="mb-2"),
                     html.P("No COB data available", className="text-muted small")
                 ])
 
-            stats = cob_snapshot.stats if hasattr(cob_snapshot, 'stats') else {}
-            mid_price = stats.get('mid_price', 0)
-            spread_bps = stats.get('spread_bps', 0)
-            imbalance = stats.get('imbalance', 0)
-            bids = getattr(cob_snapshot, 'consolidated_bids', [])
-            asks = getattr(cob_snapshot, 'consolidated_asks', [])
+            # Handle both old format (with stats attribute) and new format (direct attributes)
+            if hasattr(cob_snapshot, 'stats'):
+                # Old format with stats attribute
+                stats = cob_snapshot.stats
+                mid_price = stats.get('mid_price', 0)
+                spread_bps = stats.get('spread_bps', 0)
+                imbalance = stats.get('imbalance', 0)
+                bids = getattr(cob_snapshot, 'consolidated_bids', [])
+                asks = getattr(cob_snapshot, 'consolidated_asks', [])
+            else:
+                # New COBSnapshot format with direct attributes
+                mid_price = getattr(cob_snapshot, 'volume_weighted_mid', 0)
+                spread_bps = getattr(cob_snapshot, 'spread_bps', 0)
+                imbalance = getattr(cob_snapshot, 'liquidity_imbalance', 0)
+                bids = getattr(cob_snapshot, 'consolidated_bids', [])
+                asks = getattr(cob_snapshot, 'consolidated_asks', [])
 
             if mid_price == 0 or not bids or not asks:
                 return html.Div([
@@ -294,6 +304,17 @@ class DashboardComponentManager:
                     html.P("Awaiting valid order book data...", className="text-muted small")
                 ])
 
+            # Create stats dict for compatibility with existing code
+            stats = {
+                'mid_price': mid_price,
+                'spread_bps': spread_bps,
+                'imbalance': imbalance,
+                'total_bid_liquidity': getattr(cob_snapshot, 'total_bid_liquidity', 0),
+                'total_ask_liquidity': getattr(cob_snapshot, 'total_ask_liquidity', 0),
+                'bid_levels': len(bids),
+                'ask_levels': len(asks)
+            }
+
             # --- Left Panel: Overview and Stats ---
             overview_panel = self._create_cob_overview_panel(symbol, stats, cumulative_imbalance_stats)
 
@@ -381,10 +402,19 @@ class DashboardComponentManager:
         def aggregate_buckets(orders):
             buckets = {}
             for order in orders:
-                price = order.get('price', 0)
-                # Handle both old format (size) and new format (total_size)
-                size = order.get('total_size', order.get('size', 0))
-                volume_usd = order.get('total_volume_usd', size * price)
+                # Handle both dictionary format and ConsolidatedOrderBookLevel objects
+                if hasattr(order, 'price'):
+                    # ConsolidatedOrderBookLevel object
+                    price = order.price
+                    size = order.total_size
+                    volume_usd = order.total_volume_usd
+                else:
+                    # Dictionary format (legacy)
+                    price = order.get('price', 0)
+                    # Handle both old format (size) and new format (total_size)
+                    size = order.get('total_size', order.get('size', 0))
+                    volume_usd = order.get('total_volume_usd', size * price)
+                
                 if price > 0:
                     bucket_key = round(price / bucket_size) * bucket_size
                     if bucket_key not in buckets: