841ca66170ecb851d2f1db9df22277318135f12f,GPy/likelihoods/binomial.py,Binomial,d3logpdf_dlink3,#Binomial#,116

Before Change

        N = Y_metadata["trials"]
        np.testing.assert_array_equal(N.shape, y.shape)

        inv_link_f2 = np.square(inv_link_f)
        return 2*y/inv_link_f**3 - 2*(N-y)/(1.-inv_link_f)**3

    def samples(self, gp, Y_metadata=None, **kw):
        

After Change

        //inv_link_f2 = np.square(inv_link_f)  //TODO Remove. Why is this here?
        
        Ny = N-y
        t1 = np.zeros(y.shape)
        t2 = np.zeros(y.shape)
        t1[y>0] = 2*y[y>0]/inv_link_f[y>0]**3
        t2[Ny>0] = - 2*(Ny[Ny>0])/(1.-inv_link_f[Ny>0])**3
        return t1 + t2

    def samples(self, gp, Y_metadata=None, **kw):
        
        Returns a set of samples of observations based on a given value of the latent variable.

Instances