Create scorer.py

scorer.py

@@ -0,0 +1,69 @@
+import numpy as np
+from typing import Dict, Any
+
+
+def compute_structure_score(regime_data: Dict[str, Any]) -> float:
+    trend = regime_data.get("trend", "ranging")
+    structure = regime_data.get("structure", 0)
+    vol_expanding = regime_data.get("volatility_expanding", False)
+
+    if trend == "bullish":
+        base = 1.0
+    elif trend == "ranging":
+        base = 0.4
+    else:
+        base = 0.1
+
+    if structure == 1:
+        base = min(1.0, base + 0.2)
+    elif structure == -1:
+        base = max(0.0, base - 0.2)
+
+    if vol_expanding:
+        base = max(0.0, base - 0.15)
+
+    return float(np.clip(base, 0.0, 1.0))
+
+
+def score_token(
+    regime_data: Dict[str, Any],
+    volume_data: Dict[str, Any],
+    vetoed: bool,
+) -> Dict[str, float]:
+    if vetoed:
+        return {
+            "regime_score": 0.0,
+            "volume_score": 0.0,
+            "structure_score": 0.0,
+            "total_score": 0.0,
+        }
+
+    regime_score = float(np.clip(regime_data.get("regime_score", 0.0), 0.0, 1.0))
+    volume_score = float(np.clip(volume_data.get("volume_score", 0.0), 0.0, 1.0))
+    structure_score = compute_structure_score(regime_data)
+
+    regime_weight = 0.40
+    volume_weight = 0.35
+    structure_weight = 0.25
+
+    total_score = (
+        regime_score * regime_weight
+        + volume_score * volume_weight
+        + structure_score * structure_weight
+    )
+
+    return {
+        "regime_score": round(regime_score, 4),
+        "volume_score": round(volume_score, 4),
+        "structure_score": round(structure_score, 4),
+        "total_score": round(float(total_score), 4),
+    }
+
+
+def rank_tokens(scored_tokens: Dict[str, Dict[str, Any]]) -> list:
+    ranked = sorted(
+        scored_tokens.items(),
+        key=lambda x: x[1].get("total_score", 0.0),
+        reverse=True,
+    )
+    return ranked