visualization_utils/plotting.py [314:354]:
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        experiment_name = get_experiments_name(file_full_addr, res_column_name_number)
        experiment_name_list.append(experiment_name)
        column_co_design_dist_avg[experiment_name] = {}
        column_co_design_efficacy_avg[experiment_name] = {}

        column_co_design_cnt = {}
        for y_column_name in y_column_name_list:
            y_column_number = res_column_name_number[y_column_name]
            x_column_number = res_column_name_number[x_column_name]


            dis_to_goal_column_number = res_column_name_number["dist_to_goal_non_cost"]
            ref_des_dis_to_goal_column_number = res_column_name_number["ref_des_dist_to_goal_non_cost"]
            column_co_design_cnt[y_column_name] = []
            column_non_co_design_cnt[y_column_name] = []

            column_non_co_design_efficacy[y_column_name] = []
            column_co_design_dist[y_column_name] = []
            column_co_design_improvement[y_column_name] = []
            column_co_design_rate[y_column_name] = []

            all_values = get_all_col_values_of_a_folders(input_dir_names, all_res_column_name_number, y_column_name)

            last_row_change = ""
            with open(file_full_addr, newline='') as csvfile:
                resultReader = csv.reader(csvfile, delimiter=',', quotechar='|')
                rows = list(resultReader)
                for i, row in enumerate(rows):
                    if i > 1:
                        last_row = rows[i - 1]
                        if row[y_column_number] not in all_values or row[move_name_number]=="identity":
                            continue

                        col_value = row[y_column_number]
                        col_values = col_value.split(";")
                        for idx, col_val in enumerate(col_values):


                            # only for improvement
                            if float(row[ref_des_dis_to_goal_column_number]) - float(row[dis_to_goal_column_number]) < 0:
                                continue
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visualization_utils/plotting.py [478:518]:
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        experiment_name = get_experiments_name(file_full_addr, res_column_name_number)
        experiment_name_list.append(experiment_name)
        column_co_design_dist_avg[experiment_name] = {}
        column_co_design_efficacy_avg[experiment_name] = {}

        column_co_design_cnt = {}
        for y_column_name in y_column_name_list:
            y_column_number = res_column_name_number[y_column_name]
            x_column_number = res_column_name_number[x_column_name]


            dis_to_goal_column_number = res_column_name_number["dist_to_goal_non_cost"]
            ref_des_dis_to_goal_column_number = res_column_name_number["ref_des_dist_to_goal_non_cost"]
            column_co_design_cnt[y_column_name] = []
            column_non_co_design_cnt[y_column_name] = []

            column_non_co_design_efficacy[y_column_name] = []
            column_co_design_dist[y_column_name] = []
            column_co_design_improvement[y_column_name] = []
            column_co_design_rate[y_column_name] = []

            all_values = get_all_col_values_of_a_folders(input_dir_names, all_res_column_name_number, y_column_name)

            last_row_change = ""
            with open(file_full_addr, newline='') as csvfile:
                resultReader = csv.reader(csvfile, delimiter=',', quotechar='|')
                rows = list(resultReader)
                for i, row in enumerate(rows):
                    if i > 1:
                        last_row = rows[i - 1]
                        if row[y_column_number] not in all_values or row[move_name_number]=="identity":
                            continue

                        col_value = row[y_column_number]
                        col_values = col_value.split(";")
                        for idx, col_val in enumerate(col_values):


                            # only for improvement
                            if float(row[ref_des_dis_to_goal_column_number]) - float(row[dis_to_goal_column_number]) < 0:
                                continue
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