Method predict_log_density

gpflow/models/model.py:332–343

Compute the log of the probability density of the data at the new data points.

(
        self, data: RegressionData, full_cov: bool = False, full_output_cov: bool = False
    )

        "return: [batch..., N]",
    )
    def predict_log_density(
        self, data: RegressionData, full_cov: bool = False, full_output_cov: bool = False
    ) -> tf.Tensor:
        """
        Compute the log of the probability density of the data at the new data points.
        """
        # See https://github.com/GPflow/GPflow/issues/1461
        assert_params_false(self.predict_y, full_cov=full_cov, full_output_cov=full_output_cov)

        X, Y = data
        f_mean, f_var = self.predict_f(X, full_cov=full_cov, full_output_cov=full_output_cov)
        return self.likelihood.predict_log_density(X, f_mean, f_var, Y)