class_docstr: Base class for factors representing various multivariate
  representations.
docstr: Return a copy of the distribution.
  
  Returns
  -------
  ContinuousFactor object: copy of the distribution
  
  Examples
  --------
  >>> import numpy as np
  >>> from scipy.special import beta
  >>> from pgmpy.factors.continuous import ContinuousFactor
  # Two variable dirichlet distribution with alpha = (1,2)
  >>> def dirichlet_pdf(x, y):
  ...     return (np.power(x, 1) * np.power(y, 2)) / beta(x, y)
  >>> dirichlet_factor = ContinuousFactor(['x', 'y'], dirichlet_pdf)
  >>> dirichlet_factor.variables
  ['x', 'y']
  >>> copy_factor = dirichlet_factor.copy()
  >>> copy_factor.variables
  ['x', 'y']
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code: def copy(self):
      """
      Return a copy of the distribution.
  
      Returns
      -------
      ContinuousFactor object: copy of the distribution
  
      Examples
      --------
      >>> import numpy as np
      >>> from scipy.special import beta
      >>> from pgmpy.factors.continuous import ContinuousFactor
      # Two variable dirichlet distribution with alpha = (1,2)
      >>> def dirichlet_pdf(x, y):
      ...     return (np.power(x, 1) * np.power(y, 2)) / beta(x, y)
      >>> dirichlet_factor = ContinuousFactor(['x', 'y'], dirichlet_pdf)
      >>> dirichlet_factor.variables
      ['x', 'y']
      >>> copy_factor = dirichlet_factor.copy()
      >>> copy_factor.variables
      ['x', 'y']
      """
      return ContinuousFactor(self.scope(), self.distribution.copy())
  
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 7 for calling the ContinuousFactor obj's underlying member method code with example usage: obj.copy() and returns: ContinuousFactor