class_docstr: Base class for factors representing various multivariate
  representations.
docstr: Gives the ContinuousFactor divide with the other factor.
  
  Parameters
  ----------
  other: ContinuousFactor
      The ContinuousFactor to be divided.
  
  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
  >>> sn_pdf1 = lambda x: multivariate_normal.pdf([x], [0], [[1]])
  >>> sn_pdf2 = lambda x1,x2: multivariate_normal.pdf([x1, x2], [0, 0], [[1, 0], [0, 1]])
  >>> sn1 = ContinuousFactor(['x2'], sn_pdf1)
  >>> sn2 = ContinuousFactor(['x1', 'x2'], sn_pdf2)
  
  >>> sn4 = sn2.divide(sn1, inplace=False)
  >>> sn4.assignment(0, 0)
  0.3989422804014327
  
  >>> sn4 = sn2 / sn1
  >>> sn4.assignment(0, 0)
  0.3989422804014327
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code: def divide(self, other, inplace=True):
      """
      Gives the ContinuousFactor divide with the other factor.
  
      Parameters
      ----------
      other: ContinuousFactor
          The ContinuousFactor to be divided.
  
      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
      >>> sn_pdf1 = lambda x: multivariate_normal.pdf([x], [0], [[1]])
      >>> sn_pdf2 = lambda x1,x2: multivariate_normal.pdf([x1, x2], [0, 0], [[1, 0], [0, 1]])
      >>> sn1 = ContinuousFactor(['x2'], sn_pdf1)
      >>> sn2 = ContinuousFactor(['x1', 'x2'], sn_pdf2)
  
      >>> sn4 = sn2.divide(sn1, inplace=False)
      >>> sn4.assignment(0, 0)
      0.3989422804014327
  
      >>> sn4 = sn2 / sn1
      >>> sn4.assignment(0, 0)
      0.3989422804014327
      """
      if set(other.scope()) - set(self.scope()):
          raise ValueError(
              "Scope of divisor should be a subset of dividend"
          )
  
      return self._operate(other, "divide", inplace)
  
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 15 for calling the ContinuousFactor obj's underlying member method code with example usage: obj.divide(other, inplace) and returns: self