Enhance reassess_dupes function in reassess_edge.py by implementing a threshold-based adjustment mechanism for dupes, improving accuracy in ownership calculations while removing redundant debug statements for cleaner code.

global_func/reassess_edge.py

@@ -45,29 +45,32 @@ def calculate_weighted_ownership_single_row(row_ownerships):
     return weighted * 10000
 
 def reassess_dupes(row: pd.Series, salary_max: int) -> float:
-
+    # Convert to signed integers to avoid uint16 wrap-around
     salary = int(row['salary'])
     salary_diff = int(row['salary_diff'])
     own_diff = float(row['own_diff'])
     dupes = int(row['Dupes'])
-
-    st.write(f"DEBUG: row['salary'] = {row['salary']}")
-    st.write(f"DEBUG: (salary_max - 500) = {salary_max - 500}")
-    st.write(f"DEBUG: row['salary'] - (salary_max - 500) = {row['salary'] - (salary_max - 500)}")
-    st.write(f"DEBUG: type check: {type(row['salary'] - (salary_max - 500))}")
-    st.write(f"DEBUG: threshold calc: {row['salary']} - ({salary_max} - 500) = {row['salary'] - (salary_max - 500)}")
-    st.write(f"DEBUG: max(0, threshold) = {max(0, row['salary'] - (salary_max - 500))}")
-    st.write(f"DEBUG: max/100 = {max(0, row['salary'] - (salary_max - 500)) / 100}")
-    st.write(f"DEBUG: salary component = {(max(0, row['salary'] - (salary_max - 500)) / 100) * (2 + row['salary_diff'] / 200) * (1 if row['salary_diff'] >= 0 else -1)}")
-    return math.ceil(
-        dupes + 
-        (
-            (max(0, (salary - (salary_max - 500)) / 100) * (2 + (salary_diff / 200)) * 
-             (1 if salary_diff >= 0 else -1)) +
-            
-            (own_diff / 10)
+    
+    # Calculate distance from threshold
+    threshold = salary_max - 500
+    distance_from_threshold = salary - threshold
+    
+    # Apply dramatic reduction when below threshold
+    if distance_from_threshold < 0:
+        # For every 100 under threshold, divide dupes by 2
+        reduction_factor = 2 ** (abs(distance_from_threshold) / 100)
+        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)
         )
-    )
+    
+    # Add ownership component
+    final_dupes = adjusted_dupes + (own_diff / 10)
+    
+    return math.ceil(final_dupes)
 
 def reassess_lineup_edge(row: pd.Series, Contest_Size: int) -> float:
     row['Lineup Edge'] = row['Win%'] * ((.5 - row['Finish_percentile']) * (Contest_Size / 2.5))