class_docstr: Base class for factors representing various multivariate
  representations.
docstr: Returns a list of pdf assignments for the corresponding values.
  
  Parameters
  ----------
  *args: values
      Values whose assignment is to be computed.
  
  Examples
  --------
  >>> from pgmpy.factors.continuous import ContinuousFactor
  >>> from scipy.stats import multivariate_normal
  >>> normal_pdf = lambda x1, x2: multivariate_normal.pdf((x1, x2), [0, 0], [[1, 0], [0, 1]])
  >>> phi = ContinuousFactor(['x1', 'x2'], normal_pdf)
  >>> phi.assignment(1, 2)
  0.013064233284684921
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code: def assignment(self, *args):
      """
      Returns a list of pdf assignments for the corresponding values.
  
      Parameters
      ----------
      *args: values
          Values whose assignment is to be computed.
  
      Examples
      --------
      >>> from pgmpy.factors.continuous import ContinuousFactor
      >>> from scipy.stats import multivariate_normal
      >>> normal_pdf = lambda x1, x2: multivariate_normal.pdf((x1, x2), [0, 0], [[1, 0], [0, 1]])
      >>> phi = ContinuousFactor(['x1', 'x2'], normal_pdf)
      >>> phi.assignment(1, 2)
      0.013064233284684921
      """
      return self.distribution.assignment(*args)
  
imports: import types
  import numpy
  import scipy.integrate
  from pgmpy.factors.base import BaseFactor
  from pgmpy.factors.distributions import GaussianDistribution, CustomDistribution
label_desc: Use image node_id 6 for calling the ContinuousFactor obj's underlying member method code with example usage: obj.assignment() and returns: self