feat: wavelets

backend/services/geo_analyzer.py

@@ -640,6 +640,13 @@ GEOPOLITICAL_RISK_WEIGHTS = {
 }
 
 
+# A single extreme-severity article (e.g. imminent war, market-moving Fed shock) must not get diluted
+# away just because other categories are quiet that day. This floor is driven by the single worst
+# category score and stays inert below ~0.7, then ramps up steeply — solved so a lone 0.90 floors the
+# final score at 50 (see MAX_CATEGORY_FLOOR_EXPONENT below).
+MAX_CATEGORY_FLOOR_EXPONENT = 6.58
+
+
 def compute_geo_risk_score(events: List[Dict[str, Any]]) -> Dict[str, Any]:
     """Compute a global geopolitical risk score 0-100 from recent events."""
     if not events:
@@ -658,7 +665,13 @@ def compute_geo_risk_score(events: List[Dict[str, Any]]) -> Dict[str, Any]:
         category_scores.get(cat, 0) * weight
         for cat, weight in GEOPOLITICAL_RISK_WEIGHTS.items()
     )
-    score = min(100, round(weighted * 100, 1))
+
+    # Non-linear floor: the single most severe category score alone can force the score up,
+    # even if it's the only hot category — breaks the "many quiet categories dilute one severe one" effect.
+    max_category_impact = max(category_scores.values(), default=0.0)
+    floor = max_category_impact ** MAX_CATEGORY_FLOOR_EXPONENT
+
+    score = min(100, round(max(weighted, floor) * 100, 1))
 
     if score < 25:
         level = "low"