class_docstr: Class for Local Penalization acquisition. Used for batch design.
  :param model: model of the class GPyOpt
  :param space: design space of the class GPyOpt.
  :param optimizer: optimizer of the class GPyOpt.
  :param acquisition: acquisition function of the class GPyOpt
  :param transform: transformation applied to the acquisition (default, none).
  
  .. Note:: irrespective of the transformation applied the penalized acquisition is always mapped again to the log space.
  This way gradients can be computed additively and are more stable.
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docstr: Returns the value of the acquisition function at x.
docstr_tok: ["Returns","the","value","of","the","acquisition","function","at","x","."]
code: def acquisition_function(self, x):
      """
      Returns the value of the acquisition function at x.
      """
  
      return self._penalized_acquisition(
          x, self.model, self.X_batch, self.r_x0, self.s_x0
      )
  
file_path: GPyOpt/GPyOpt/acquisitions/LP.py
imports: from .base import AcquisitionBase
  from .LCB import AcquisitionLCB
  from .LCB_mcmc import AcquisitionLCB_MCMC
  import numpy
  from scipy.stats import norm
label_desc: Use image node_id 7 for calling the AcquisitionLP obj's underlying member method code with example usage: obj.acquisition_function(x) and returns: self