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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_plot(self, normalize_rxn_coordinate=True, label_barrier=True):
 """ Returns the NEB plot. Uses Henkelman's approach of spline fitting each section of the reaction path based on tangent force and energies. Args: normalize_rxn_coordinate (bool):
 Whether to normalize the reaction coordinate to between 0 and 1. Defaults to True. label_barrier (bool):
 Whether to label the maximum barrier. Returns: matplotlib.pyplot object. """

        plt = pretty_plot(12, 8)
        scale = 1 if not normalize_rxn_coordinate else 1 / self.r[-1]
        x = np.arange(0, np.max(self.r), 0.01)
        y = self.spline(x) * 1000
        relative_energies = self.energies - self.energies[0]
        plt.plot(self.r * scale, relative_energies * 1000, 'ro',
                 x * scale, y, 'k-', linewidth=2, markersize=10)
        plt.xlabel("Reaction coordinate")
        plt.ylabel("Energy (meV)")
        plt.ylim((np.min(y) - 10, np.max(y) * 1.02 + 20))
        if label_barrier:
            data = zip(x * scale, y)
            barrier = max(data, key=lambda d: d[1])
            plt.plot([0, barrier[0]], [barrier[1], barrier[1]], 'k--')
            plt.annotate('%.0f meV' % (np.max(y) - np.min(y)),
                         xy=(barrier[0] / 2, barrier[1] * 1.02),
                         xytext=(barrier[0] / 2, barrier[1] * 1.02),
                         horizontalalignment='center')
        plt.tight_layout()
        return plt