experiment

functions/calc_matches.py

@@ -54,9 +54,6 @@ def calc_matches(filtered_df, project_df, similarity_matrix, top_x):
     filtered_df_index_map = {index: i for i, index in enumerate(filtered_df_indices)}
     project_df_index_map = {index: i for i, index in enumerate(project_df_indices)}
 
-    st.write(filtered_df_indices)
-    st.write(project_df_indices)
-
     # Select submatrix based on indices from both dataframes
     match_matrix = similarity_matrix[filtered_df_indices, :][:, project_df_indices]
 
@@ -74,8 +71,8 @@ def calc_matches(filtered_df, project_df, similarity_matrix, top_x):
     # Get the corresponding similarity values
     top_values = match_matrix.data[linear_indices]
 
-    top_filtered_df_indices = [filtered_df_indices[i] for i in top_indices[0]]
-    top_project_df_indices = [project_df_indices[i] for i in top_indices[1]]
+    top_filtered_df_indices = [filtered_df_index_map[i] for i in top_indices[0]]
+    top_project_df_indices = [project_df_index_map[i] for i in top_indices[1]]
 
     # Create resulting dataframes with top matches and their similarity scores
     st.write(top_indices)