ed3f6c56c22a7fafa4aa7e4aefd2639e00c0a668,GPy/likelihoods/likelihood.py,Likelihood,ep_gradients,#Likelihood#Any#Any#Any#Any#Any#Any#Any#,230

Before Change

                    Y_metadata_list.append(Y_metadata_i)

                val = self.site_derivatives_ep(Y[index], tau[index], v[index], Y_metadata_i)
                dlik_dtheta[:, index] = val.ravel()

            f = partial(self.integrate)
            quads = zip(*map(f, Y.flatten(), mu.flatten(), np.sqrt(sigma2.flatten())))
            quads = np.vstack(quads)

After Change

                        Y_metadata_i[key] = Y_metadata[key][index,:]
                    Y_metadata_list.append(Y_metadata_i)

            if quad_mode == "gk":
                f = partial(self.integrate_gk)
                quads = zip(*map(f, Y.flatten(), mu.flatten(), np.sqrt(sigma2.flatten()), Y_metadata_list))
                quads = np.vstack(quads)
                quads.reshape(self.size, shape[0], shape[1])
            elif quad_mode == "gh":
                f = partial(self.integrate_gh)
                quads = zip(*map(f, Y.flatten(), mu.flatten(), np.sqrt(sigma2.flatten())))
                quads = np.hstack(quads)
                quads = quads.T
            else:
                raise Exception("no other quadrature mode available")
            //     do a gaussian-hermite integration
            dL_dtheta_avg = boost_grad * np.nanmean(quads, axis=1)
            dL_dtheta = boost_grad * np.nansum(quads, axis=1)
            // dL_dtheta = boost_grad * np.nansum(dlik_dtheta, axis=1)
        else:

Instances