corrected bool to bools

examples/convex_hull_full.py

@@ -90,6 +90,6 @@ logging.info(f'AFTER DBSCAN, {df_names[1]} is fixed')
 df_1_in_2 = pd.DataFrame()
 for combo, bool_1, bool_2 in zip(combos, result_bools_1, result_bools_2):
     df_curr = compute_intersections(combo = combo, df_1 = df_1, df_2 = df_2, df_names = df_names,
-                                    bools_1 = bool_1, bool_2 = bool_2, first_fixed = None)
+                                    bools_1 = bool_1, bools_2 = bool_2, first_fixed = None)
     df_1_in_2 = pd.concat([df_1_in_2, df_curr])
 df_1_in_2.to_csv(f"./full_{df_names[0]}_and_full_{df_names[1]}_wo_outliers.csv", index=False)

examples/convex_hull_sampled.py

@@ -113,6 +113,6 @@ logging.info(f'AFTER DBSCAN, {df_names[0]} is fixed')
 df_1_in_2 = pd.DataFrame()
 for combo, bool_1, bool_2 in zip(combos, result_bools_1, result_bools_2):
     df_curr = compute_intersections(combo = combo, df_1 = df_1, df_2 = df_2, df_names = df_names,
-                                    bool_1 = bool_1, bool_2 = bool_2, first_fixed = True, size = size)
+                                    bools_1 = bool_1, bools_2 = bool_2, first_fixed = True, size = size)
     df_1_in_2 = pd.concat([df_1_in_2, df_curr])
 df_1_in_2.to_csv(f"./sampled_{df_names[1]}_and_full_{df_names[0]}_wo_outliers_diamonds.csv", index=False)