def loglkl(self, cosmo, data):
        # Modes

        difference = []
        for z, Dv in zip(self.z_eff, self.Dv):
            # Recover the Dv and rs from CLASS
            da = cosmo.angular_distance(z)
            dr = z/cosmo.Hubble(z)
            dv = pow(da**2*(1.+z)**2*dr, 1./3)
            rs = cosmo.rs_drag()
            # To have the same units, we must multiply dv/rs from CLASS by
            # rs_fiducial
            difference.append(Dv - dv/rs*self.rs_fiducial)

        difference = np.array(difference)
        likelihood = np.exp(-0.5 * (
            np.dot(difference, np.dot(self.inverse_covmat, difference.T))))
        return log(likelihood)
dataset/ETHPy150Open baudren/montepython_public/montepython/likelihoods/WiggleZ_bao/__init__.py/WiggleZ_bao.loglkl/original