class_docstr: Base class for Noisy-Or models.
  
  This is an implementation of generalized Noisy-Or models and
  is not limited to Boolean variables and also any arbitrary
  function can be used instead of the boolean OR function.
  
  Reference: http://xenon.stanford.edu/~srinivas/research/6-UAI93-Srinivas-Generalization-of-Noisy-Or.pdf
docstr: Deletes variables from the NoisyOrModel.
  
  Parameters
  ----------
  variables: list, tuple, dict (array like)
      list of variables to be deleted.
  
  Examples
  --------
  >>> from pgmpy.models import NoisyOrModel
  >>> model = NoisyOrModel(['x1', 'x2', 'x3'], [2, 3, 2], [[0.6, 0.4],
  ...                                                      [0.2, 0.4, 0.7],
  ...                                                      [0.1, 0., 4]])
  >>> model.del_variables(['x1'])
docstr_tok: ["Deletes","variables","from","the","NoisyOrModel",".","Parameters","--","--","--","--","--","variables",":","list",",","tuple",",","dict","(","array","like",")","list","of","variables","to","be","deleted",".","Examples","--","--","--","--",">",">",">","from","pgmpy.models","import","NoisyOrModel",">",">",">","model","=","NoisyOrModel","(","[","'x1","'",",","'x2","'",",","'x3","'","]",",","[","2",",","3",",","2","]",",","[","[","0.6",",","0.4","]",",","...","[","0.2",",","0.4",",","0.7","]",",","...","[","0.1",",","0.",",","4","]","]",")",">",">",">","model.del_variables","(","[","'x1","'","]",")"]
code: def del_variables(self, variables):
      """
      Deletes variables from the NoisyOrModel.
  
      Parameters
      ----------
      variables: list, tuple, dict (array like)
          list of variables to be deleted.
  
      Examples
      --------
      >>> from pgmpy.models import NoisyOrModel
      >>> model = NoisyOrModel(['x1', 'x2', 'x3'], [2, 3, 2], [[0.6, 0.4],
      ...                                                      [0.2, 0.4, 0.7],
      ...                                                      [0.1, 0., 4]])
      >>> model.del_variables(['x1'])
      """
      variables = (
          [variables] if isinstance(variables, str) else set(variables)
      )
      indices = [
          index
          for index, variable in enumerate(self.variables)
          if variable in variables
      ]
      self.variables = np.delete(self.variables, indices, 0)
      self.cardinality = np.delete(self.cardinality, indices, 0)
      self.inhibitor_probability = [
          prob_array
          for index, prob_array in enumerate(self.inhibitor_probability)
          if index not in indices
      ]
  
imports: from itertools import chain
  import numpy
  import networkx
label_desc: Use image node_id 3 for calling the NoisyOrModel obj's underlying member method code with example usage: obj.del_variables(variables) without return types