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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs):
 """ Returns an Arrhenius plot. Args: temps ([float]):
 A sequence of temperatures. diffusivities ([float]):
 A sequence of diffusivities (e.g., from DiffusionAnalyzer.diffusivity). diffusivity_errors ([float]):
 A sequence of errors for the diffusivities. If None, no error bar is plotted. \\*\\*kwargs: Any keyword args supported by matplotlib.pyplot.plot. Returns: A matplotlib.pyplot object. Do plt.show() to show the plot. """

    Ea, c, _ = fit_arrhenius(temps, diffusivities)

    from pymatgen.util.plotting import pretty_plot
    plt = pretty_plot(12, 8)

    # log10 of the arrhenius fit
    arr = c * np.exp(-Ea / (const.k / const.e * np.array(temps)))

    t_1 = 1000 / np.array(temps)

    plt.plot(t_1, diffusivities, 'ko', t_1, arr, 'k--', markersize=10,
             **kwargs)
    if diffusivity_errors is not None:
        n = len(diffusivity_errors)
        plt.errorbar(t_1[0:n], diffusivities[0:n], yerr=diffusivity_errors,
                     fmt='ko', ecolor='k', capthick=2, linewidth=2)
    ax = plt.axes()
    ax.set_yscale('log')
    plt.text(0.6, 0.85, "E$_a$ = {:.0f} meV".format(Ea * 1000),
             fontsize=30, transform=plt.axes().transAxes)
    plt.ylabel("D (cm$^2$/s)")
    plt.xlabel("1000/T (K$^{-1}$)")
    plt.tight_layout()
    return plt