a802d31210ed262b8159b656b256bdacf10c9d61,bindsnet/analysis/plotting.py,,plot_performance,#,398

Before Change

    else:
        ax.clear()

    for scheme in performances:
        ax.plot(
            [n * x_scale for n in range(len(performances[scheme]))],
            [p for p in performances[scheme]],
            label=scheme,
        )

    ax.set_ylim([0, 100])
    ax.set_title("Estimated classification accuracy")
    ax.set_xlabel("No. of examples")
    ax.set_ylabel("Accuracy")

After Change

        ax.legend()

        plt.savefig(save, bbox_inches="tight")
        plt.close()
        plt.ion()
    else:
        if not ax:
            _, ax = plt.subplots(figsize=figsize)

Instances