class_docstr: Base class for factors representing various multivariate
  representations.
docstr: Normalizes the pdf of the continuous factor so that it integrates to
  1 over all the variables.
  
  Parameters
  ----------
  inplace: boolean
      If inplace=True it will modify the factor itself, else would return
      a new factor.
  
  Returns
  -------
  ContinuousFactor or None:
       if inplace=True (default) returns None
       if inplace=False returns a new ContinuousFactor instance.
  
  Examples
  --------
  >>> from pgmpy.factors.continuous import ContinuousFactor
  >>> from scipy.stats import multivariate_normal
  >>> std_normal_pdf = lambda x: 2 * multivariate_normal.pdf(x, [0, 0], [[1, 0], [0, 1]])
  >>> std_normal = ContinuousFactor(['x1', 'x2'], std_normal_pdf)
  >>> std_normal.assignment(1, 1)
  0.117099663049
  >>> std_normal.normalize()
  >>> std_normal.assignment(1, 1)
  0.0585498315243
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code: def normalize(self, inplace=True):
      """
      Normalizes the pdf of the continuous factor so that it integrates to
      1 over all the variables.
  
      Parameters
      ----------
      inplace: boolean
          If inplace=True it will modify the factor itself, else would return
          a new factor.
  
      Returns
      -------
      ContinuousFactor or None:
           if inplace=True (default) returns None
           if inplace=False returns a new ContinuousFactor instance.
  
      Examples
      --------
      >>> from pgmpy.factors.continuous import ContinuousFactor
      >>> from scipy.stats import multivariate_normal
      >>> std_normal_pdf = lambda x: 2 * multivariate_normal.pdf(x, [0, 0], [[1, 0], [0, 1]])
      >>> std_normal = ContinuousFactor(['x1', 'x2'], std_normal_pdf)
      >>> std_normal.assignment(1, 1)
      0.117099663049
      >>> std_normal.normalize()
      >>> std_normal.assignment(1, 1)
      0.0585498315243
  
      """
      phi = self if inplace else self.copy()
      phi.distribution.normalize(inplace=True)
  
      if not inplace:
          return phi
  
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 11 for calling the ContinuousFactor obj's underlying member method code with example usage: obj.normalize(inplace) and returns: phi