069378b414de5ff95cd0f5bd4024e82f03862832,snntoolbox/simulation/plotting.py,,plot_param_sweep,#Any#Any#Any#Any#Any#,803

Before Change

    // Compute confidence intervals of the experiments
    ci = [wilson_score(q, n) for q in results]
    ax = plt.subplot()
    if param_logscale:
        ax.set_xscale("log", nonposx="clip")
    ax.errorbar(params, results, yerr=ci, fmt="x-")
    ax.set_title("Accuracy vs Hyperparameter")
    ax.set_xlabel(param_name)
    ax.set_ylabel("accuracy")
    fac = 0.9
    if params[0] < 0:
        fac += 0.2
    ax.set_xlim(fac * params[0], 1.1 * params[-1])

After Change

    if param_logscale:
        plt.xscale("log", nonposx="clip")
    plt.errorbar(params, results, yerr=ci, fmt="x-")
    plt.title("Accuracy vs Hyperparameter")
    plt.xlabel(param_name)
    plt.ylabel("accuracy")
    fac = 0.9
    if params[0] < 0:

Instances