Returns the probability density function(pdf).

        Returns
        -------
        function: The probability density function of the distribution.

        Examples
        --------
        >>> from pgmpy.factors.distributions import GaussianDistribution
        >>> dist = GD(variables=['x1', 'x2', 'x3'],
        ...           mean=[1, -3, 4],
        ...           cov=[[4, 2, -2],
        ...                [2, 5, -5],
        ...                [-2, -5, 8]])
        >>> dist.pdf
        <function pgmpy.factors.distributions.GaussianDistribution.GaussianDistribution.pdf.<locals>.<lambda>>
        >>> dist.pdf([0, 0, 0])
        0.0014805631279234139

def pdf(self):
        """
        Returns the probability density function(pdf).

        Returns
        -------
        function: The probability density function of the distribution.

        Examples
        --------
        >>> from pgmpy.factors.distributions import GaussianDistribution
        >>> dist = GD(variables=['x1', 'x2', 'x3'],
        ...           mean=[1, -3, 4],
        ...           cov=[[4, 2, -2],
        ...                [2, 5, -5],
        ...                [-2, -5, 8]])
        >>> dist.pdf
        <function pgmpy.factors.distributions.GaussianDistribution.GaussianDistribution.pdf.<locals>.<lambda>>
        >>> dist.pdf([0, 0, 0])
        0.0014805631279234139
        """
        return lambda *args: multivariate_normal.pdf(
            args, self.mean.reshape(1, len(self.variables))[0], self.covariance)