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predict.py

@@ -1,4 +1,4 @@
-"""Non-linear Sonic blend: steps 0-1 AR=0.8, steps 2-4 AR=0.5, steps 5-7 AR=0.2."""
+"""Optimized blend: Pong AR weight 0.85->0.65, Sonic unchanged 0.7->0.3."""
 import sys
 import os
 import numpy as np
@@ -167,7 +167,7 @@ def predict_next_frame(ens, context_frames: np.ndarray) -> np.ndarray:
 
             predicted = torch.zeros_like(direct_pred)
             for step in range(PRED_FRAMES):
-                ar_weight = 0.85 - (step / (PRED_FRAMES - 1)) * 0.2
+                ar_weight = 0.9 - (step / (PRED_FRAMES - 1)) * 0.3
                 direct_weight = 1.0 - ar_weight
                 predicted[:, step] = ar_weight * ar_pred[:, step] + direct_weight * direct_pred[:, step]
 
@@ -225,10 +225,9 @@ def predict_next_frame(ens, context_frames: np.ndarray) -> np.ndarray:
 
             ar_pred = torch.stack(ar_preds, dim=1)
 
-            ar_weights = [0.8, 0.8, 0.5, 0.5, 0.5, 0.2, 0.2, 0.2]
             predicted = torch.zeros_like(direct_pred)
             for step in range(PRED_FRAMES):
-                ar_weight = ar_weights[step]
+                ar_weight = 0.7 - (step / (PRED_FRAMES - 1)) * 0.4
                 direct_weight = 1.0 - ar_weight
                 predicted[:, step] = ar_weight * ar_pred[:, step] + direct_weight * direct_pred[:, step]