class_docstr: In its most common representation, a multivariate Gaussian distribution
  over X1, X2, ..., Xn is characterized by an n-dimensional mean vector μ,
  and a symmetric n x n covariance matrix Σ.
  
  This is the base class for its representation.
docstr: Returns the probability value of the PDF at the given parameter values.
  
  Parameters
  ----------
  *x: int, float
      The point at which the value of the pdf needs to be computed. The
      number of values passed should be equal to the number of variables
      in the distribution.
  
  Returns
  -------
  float: float
      The probability value at the point.
  
  Examples
  --------
  >>> from pgmpy.factors.distributions import GaussianDistribution
  >>> dist = GaussianDistribution(variables=['x1', 'x2'],
  ...                             mean=[0, 0],
  ...                             cov=[[1, 0],
                                       [0, 1]])
  >>> dist.assignment(0, 0)
  0.15915494309189535
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code: def assignment(self, *x):
      """
      Returns the probability value of the PDF at the given parameter values.
  
      Parameters
      ----------
      *x: int, float
          The point at which the value of the pdf needs to be computed. The
          number of values passed should be equal to the number of variables
          in the distribution.
  
      Returns
      -------
      float: float
          The probability value at the point.
  
      Examples
      --------
      >>> from pgmpy.factors.distributions import GaussianDistribution
      >>> dist = GaussianDistribution(variables=['x1', 'x2'],
      ...                             mean=[0, 0],
      ...                             cov=[[1, 0],
                                           [0, 1]])
      >>> dist.assignment(0, 0)
      0.15915494309189535
      """
      return self.pdf(*x)
  
imports: import numpy
  from scipy.stats import multivariate_normal
  from pgmpy.factors.distributions import BaseDistribution
label_desc: Use image node_id 3 for calling the GaussianDistribution obj's underlying member method code with example usage: obj.assignment() and returns: self