Add debug statements in calculate_weighted_ownership function: include print statements to trace input values and intermediate calculations, aiding in the debugging process for ownership metrics.

global_func/predict_dupes.py

@@ -16,20 +16,28 @@ def calculate_weighted_ownership(row_ownerships):
     Returns:
         float: Calculated weighted ownership value
     """
+    print("Input row:", row_ownerships)  # Debug print
+    print("Type:", type(row_ownerships))  # Debug print
+    
     # Get the mean of all ownership values
     row_mean = row_ownerships.mean()
+    print("Row mean:", row_mean)  # Debug print
     
     # Calculate average of each value with the overall mean
     value_means = [(val + row_mean) / 2 for val in row_ownerships]
+    print("Value means:", value_means)  # Debug print
     
     # Take average of all those means
     avg_of_means = sum(value_means) / len(value_means)
+    print("Average of means:", avg_of_means)  # Debug print
     
     # Multiply by count of values
     weighted = avg_of_means * len(row_ownerships)
+    print("After multiplication:", weighted)  # Debug print
     
     # Subtract (max - min)
     weighted = weighted - (row_ownerships.max() - row_ownerships.min())
+    print("Final weighted:", weighted)  # Debug print
     
     return weighted