def make_fig_S8()

in figs/fig_S8.py [0:0]

• 30 lines of code
• 3 McCabe index (conditional complexity)

def make_fig_S8():
    ys1, ys2 = extract_sensitivity_results()

    fig = plt.figure(figsize=(5.5, 2.2))
    ax = fig.add_subplot(121)

    x = np.arange(1, 51)
    for d_e in [2, 3, 4, 6, 8]:
        ax.plot(x, ys1[d_e].mean(axis=0), label=f'$d_e={d_e}$')

    ax.set_ylim([0, 7])
    ax.set_yticks([0, 2, 4, 6])
    ax.legend(fontsize=7)
    ax.set_title(r'Branin, $D=100$')
    ax.set_ylabel('Best value found', fontsize=9)
    ax.set_xlabel('Function evaluations', fontsize=9)
    ax.axhline(y=0.397887, c='gray', ls='--')
    ax.grid(alpha=0.2, zorder=-10)
    ax.set_xlim([0, 51])

    ax = fig.add_subplot(122)

    for D in [50, 100, 200, 500, 1000]:
        ax.plot(x, ys2[D].mean(axis=0), label=f'$D={D}$')

    ax.set_title(r'Branin, $d_e=4$')

    ax.set_ylim([0, 7])
    ax.legend(fontsize=7)
    ax.set_xlabel('Function evaluations', fontsize=9)
    ax.axhline(y=0.397887, c='gray', ls='--')
    ax.grid(alpha=0.2, zorder=-10)
    ax.set_yticks([0, 2, 4, 6])
    ax.set_xlim([0, 51])
    ax.set_yticklabels([])

    plt.subplots_adjust(right=0.995, bottom=0.16, left=0.06, top=0.91, wspace=0.05)
    plt.savefig('pdfs/branin_by_d_D_traces.pdf', pad_inches=0)