docstr: Test that acquisition function optimize method returns expected optimum without analytical gradient prediction
          
docstr_tok: ["Test","that","acquisition","function","optimize","method","returns","expected","optimum","without","analytical","gradient","prediction"]
code: def test_optimize_without_analytical_gradient_prediction(self):
      """Test that acquisition function optimize method returns expected optimum without analytical gradient prediction"""
      expected_optimum_position = [[0, 0]]
      self.mock_optimizer.optimize.return_value = (
          expected_optimum_position
      )
      self.mock_model.analytical_gradient_prediction = False
      self.ei_acquisition = AcquisitionEI(
          self.mock_model, self.space, self.mock_optimizer
      )
  
      optimum_position = self.ei_acquisition.optimize()
  
      assert optimum_position == expected_optimum_position
  
file_path: GPyOpt/GPyOpt/testing/acquisitions_tests/test_ei_acquisition.py
imports: import unittest
  from mock import Mock
  import numpy
  from GPyOpt.acquisitions import AcquisitionEI
  from GPyOpt.core.task.space import Design_space
label_desc: Use image node_id 5 for calling the TestEIAcquisition obj's underlying member method code with example usage: obj.test_optimize_without_analytical_gradient_prediction() without return types