COB heatmap WIP

core/data_models.py

@@ -173,6 +173,38 @@ class BaseDataInput:
                     break
             cob_features.extend(ma_features)
         
+        # Add REAL aggregated COB heatmap features to fill remaining COB slots (no synthetic data)
+        # We compute per-bucket means over the most recent window (up to 300s) and a few global stats
+        try:
+            if self.cob_heatmap_values and self.cob_heatmap_prices:
+                z = np.array(self.cob_heatmap_values, dtype=float)
+                if z.ndim == 2 and z.size > 0:
+                    # Use up to the last 300 seconds (or whatever is available)
+                    window_rows = z[-300:] if z.shape[0] >= 300 else z
+                    # Replace NaNs with 0.0 to respect the no-synthetic rule but avoid NaN propagation
+                    window_rows = np.nan_to_num(window_rows, nan=0.0, posinf=0.0, neginf=0.0)
+
+                    # Per-bucket mean imbalance/liquidity across time
+                    per_bucket_mean = window_rows.mean(axis=0).tolist()
+                    space_left = 200 - len(cob_features)
+                    if space_left > 0 and len(per_bucket_mean) > 0:
+                        cob_features.extend(per_bucket_mean[:space_left])
+
+                    # If there is still space, add compact global stats over the window
+                    space_left = 200 - len(cob_features)
+                    if space_left > 0:
+                        flat = window_rows.reshape(-1)
+                        if flat.size > 0:
+                            global_mean = float(np.mean(flat))
+                            global_std = float(np.std(flat))
+                            global_max = float(np.max(flat))
+                            global_min = float(np.min(flat))
+                            global_stats = [global_mean, global_std, global_max, global_min]
+                            cob_features.extend(global_stats[:space_left])
+        except Exception:
+            # On any error, skip heatmap-derived features (remaining space will be zero-padded below)
+            pass
+
         # Pad COB features to exactly 200
         cob_features.extend([0.0] * (200 - len(cob_features)))
         features.extend(cob_features[:200])  # Ensure exactly 200 COB features