experiment

functions/calc_matches.py

@@ -54,20 +54,16 @@ def calc_matches(filtered_df, project_df, similarity_matrix, top_x):
     # Get the values corresponding to the top k indices
     top_values = flat_data[top_indices]
 
-
-    # Get the values corresponding to the top k indices
-    top_values = match_matrix[row_indices, col_indices]
-
-    top_filtered_df_indices = [filtered_df_index_map[i] for i in col_indices]
-    top_project_df_indices = [project_df_index_map[i] for i in row_indices]
+    #top_filtered_df_indices = [filtered_df_index_map[i] for i in col_indices]
+    #top_project_df_indices = [project_df_index_map[i] for i in row_indices]
 
     st.write(top_filtered_df_indices)
 
     # Create resulting dataframes with top matches and their similarity scores
-    p1_df = filtered_df.loc[top_filtered_df_indices].copy()
+    p1_df = filtered_df.loc[col_indices].copy()
     p1_df['similarity'] = top_values
 
-    p2_df = project_df.loc[top_project_df_indices].copy()
+    p2_df = project_df.loc[row_indices].copy()
     p2_df['similarity'] = top_values
     print("finished calc matches")