Esempio n. 1
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def plot_decay_majorant_v_of_deg(h, maj, deg, result_path):
    plt.figure()
    plt.hold(True)
    plt.loglog(h, maj, 'b-*')
    plotslopes.slope_marker((h[1], maj[1]), (1 + deg, 1))
    plt.legend(["M^2"], "lower right")
    plt.xlabel("h")
    plt.ylabel("M^2 P%d" % (deg))
    plt.grid(True)

    fig = plt.gcf()
    fig.savefig(result_path + ".eps")
Esempio n. 2
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def plot_convergence_rates():
    r2, E2, dt2 = convergence_rates(m=5, solver_function=solver, num_periods=8)
    plt.loglog(dt2, E2)
    r4, E4, dt4 = convergence_rates(m=5,
                                    solver_function=solver_adjust_w,
                                    num_periods=8)
    plt.loglog(dt4, E4)
    plt.legend(['original scheme', r'adjusted $\omega$'], loc='upper left')
    plt.title('Convergence of finite difference methods')
    from plotslopes import slope_marker
    slope_marker((dt2[1], E2[1]), (2, 1))
    slope_marker((dt4[1], E4[1]), (4, 1))
    plt.savefig('tmp_convrate.png')
    plt.savefig('tmp_convrate.pdf')
    plt.show()
Esempio n. 3
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def plot_decay_error_majorant(deg, h, error, majorant, result_path):
    # Plot error and majorant results for deg = 2
    plt.figure()
    plt.hold(True)
    plt.loglog(h, majorant, 'k-^')
    plt.loglog(h, error, 'k-s')
    if deg == 1:
        plotslopes.slope_marker((h[1], error[1]), (2, 1))
    elif deg == 2:
        plotslopes.slope_marker((h[1], error[1]), (3, 1))

    plt.legend(["M^2", "|| e ||^2"], "lower right")
    plt.xlabel("h")
    plt.ylabel("|| e ||^2, M^2")
    plt.grid(True)

    fig = plt.gcf()
    fig.savefig(result_path + ".eps")