import pandas as pd
import numpy as np

def find_similar(p_index, similarity_matrix, filtered_df, top_x):
    selected_row = similarity_matrix[p_index]
    filtered_indices = filtered_df.index.tolist()
    print(filtered_indices)

    index_position_mapping = {index: position for position, index in enumerate(filtered_indices)}
    print(index_position_mapping)


    #filtered_column_matrix = similarity_matrix[:, filtered_indices]

    #top_indexes = np.argsort(selected_row)[-top_x:][::-1]
    #top_values = selected_row[top_indexes]

    #top_projects_df = projects_df.iloc[top_indexes]

    #top_projects_df["similarity"] = top_values

    return "top_projects_df"