Refactor dupe adjustment logic in reassess_dupes function of reassess_edge.py to conditionally apply adjustments based on salary_diff, ensuring accurate calculations for positive salary differences while maintaining original dupes for non-positive differences.

global_func/reassess_edge.py

@@ -75,10 +75,13 @@ def reassess_dupes(row: pd.Series, salary_max: int) -> float:
         adjusted_dupes = dupes / reduction_factor
     else:
         # Above threshold: use original formula
-        adjusted_dupes = dupes + (
-            (distance_from_threshold / 100) * (2 + (salary_diff / 200)) * 
-            (1 if salary_diff >= 0 else -1)
-        )
+        if salary_diff > 0:
+            adjusted_dupes = dupes + (
+                (distance_from_threshold / 100) * (2 + (salary_diff / 200)) * 
+                (1 if salary_diff >= 0 else -1)
+            )
+        else:
+            adjusted_dupes = dupes
     
     # Add ownership component
     final_dupes = max(0, adjusted_dupes + (own_diff / 10))