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

Before Change

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

After Change

    :return: Used for re-drawing the performance plot.
    

    if save is not None:
        plt.ioff()
        _, ax = plt.subplots(figsize=figsize)

        for scheme in performances:
            ax.plot(
                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")
        ax.set_xticks(())
        ax.set_yticks(range(0, 110, 10))
        ax.legend()

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

        for scheme in performances:
            ax.plot(
                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")
        ax.set_xticks(())
        ax.set_yticks(range(0, 110, 10))
        ax.legend()

    return ax


def plot_voltages(

Instances