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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 scale_geom_opt_threshold(self, gradient=0.1, displacement=0.1, energy=0.1):
 """ Adjust the convergence criteria of geometry optimization. Args: gradient: the scale factor for gradient criteria. If less than 1.0, you are tightening the threshold. The base value is 300 × 10E−6 displacement: the scale factor for atomic displacement. If less then 1.0, you are tightening the threshold. The base value is 1200 × 10E−6 energy: the scale factor for energy change between successive iterations. If less than 1.0, you are tightening the threshold. The base value is 100 × 10E−8. """

        if gradient < 1.0/(300-1) or displacement < 1.0/(1200-1) or \
                energy < 1.0/(100-1):
            raise ValueError("The geometry optimization convergence criteria "
                             "is too tight")
        self.params["rem"]["geom_opt_tol_gradient"] = int(gradient * 300)
        self.params["rem"]["geom_opt_tol_displacement"] = int(displacement *
                                                              1200)
        self.params["rem"]["geom_opt_tol_energy"] = int(energy * 100)