def get_f_clvd(self):
        """
        Returns the statistic f_clvd: the signed ratio of the sizes of the
        intermediate and largest principal moments::

         f_clvd = -b_axis_eigenvalue / max(|t_axis_eigenvalue|,|p_axis_eigenvalue|)
        """
        if not self.principal_axes:
            # Principal axes not yet defined for moment tensor - raises error
            raise ValueError('Principal Axes not defined!')

        denominator = np.max(np.array([
            fabs(self.principal_axes.t_axis['eigenvalue']),
            fabs(self.principal_axes.p_axis['eigenvalue'])
        ]))
        self.f_clvd = -self.principal_axes.b_axis['eigenvalue'] / denominator
        return self.f_clvd
def get_f_clvd ( self ) : if not self . principal_axes : raise ValueError ( 'Principal Axes not defined!' ) denominator = np . max ( np . array ( [ fabs ( self . principal_axes . t_axis [ 'eigenvalue' ] ) , fabs ( self . principal_axes . p_axis [ 'eigenvalue' ] ) ] ) ) self . f_clvd = - self . principal_axes . b_axis [ 'eigenvalue' ] / denominator return self . f_clvd
Returns the statistic f_clvd: the signed ratio of the sizes of the
        intermediate and largest principal moments::

         f_clvd = -b_axis_eigenvalue / max(|t_axis_eigenvalue|,|p_axis_eigenvalue|)