PrivacyScanData/target/visualize/data_analysis_3.py

def develop_stats_plot(delta:str):
    with open(os.path.join(folder_use, get_file_name_json(False)), 'r') as file:
        value_delta = [f.get(delta, -1) for f in json.load(file)]
    value_plot_mean = plt.scatter(
        value_x, 
        [
            statistics.mean(value_delta[:i])
            for i in value_x
        ]
    )
    
    if delta == 'delta_full':
        k = "Between send and inserting values"
    elif delta == 'delta_send':
        k = "Between sent and receive of the consumer"
    elif delta == 'delta_proccessed':
        k = "Between receive of the consumer and insert"
    
    plt.title(f'{k}: mean')
    plt.ylabel("Seconds")
    plt.xlabel("Number of elements")
    plt.close()
    
    value_plot_var = plt.scatter(
        value_x, 
        [
            statistics.variance(value_delta[:i])
            for i in value_x
        ]
    )

    plt.title(f'{k}: variance')
    plt.ylabel("Seconds")
    plt.xlabel("Number of elements")
    plt.close()

    value_plot_dev = plt.scatter(
        value_x, 
        [
            statistics.stdev(value_delta[:i])
            for i in value_x
        ]
    )

    plt.title(f'{k}: deviation')
    plt.ylabel("Seconds")
    plt.xlabel("Number of elements")
    plt.close()

    value_plot_mean.figure.savefig(value_selected_file_plot(delta, 'mean'))
    value_plot_var.figure.savefig(value_selected_file_plot(delta, 'variance'))
    value_plot_dev.figure.savefig(value_selected_file_plot(delta, 'deviation'))