def configure(self):
        
        # Expensive and Cheap DOE (note: have to be nested)
        doe_e = [0.0, 0.4, 0.6, 1.0]
        doe_c = [0.1, 0.2, 0.3, 0.5, 0.7, 0.8, 0.9] + doe_e 
        self.add('hifi_cases', CasesBuilder(HighFidelityModel(), doe_e))
        self.add('lofi_cases', CasesBuilder(LowFidelityModel(), doe_c))
        
        # MetaModel
        self.add("meta_model", MultiFiMetaModel(params=('x', ), 
                                                responses=('f_x', ), nfi=self.nfi)) 
        self.meta_model.default_surrogate = self.surrogate
        self.connect('hifi_cases.x'  , 'meta_model.params.x')
        self.connect('hifi_cases.f_x', 'meta_model.responses.f_x')
        if self.nfi > 1:
            self.connect('lofi_cases.x'  , 'meta_model.params.x_fi2')
            self.connect('lofi_cases.f_x', 'meta_model.responses.f_x_fi2')
          
        # Iteration Hierarchy
            
        self.add('mm_checker', CaseIteratorDriver())
        self.add('model', Model())
        self.mm_checker.add_parameter("meta_model.x", low=0, high=1)
        self.mm_checker.add_parameter("model.x", low=0, high=1)
        self.mm_checker.add_response("model.f_x")
        self.mm_checker.add_response("meta_model.f_x")
        ngrid = 100
        self.mm_checker.case_inputs.meta_model.x = np.linspace(0,1,ngrid)
        self.mm_checker.case_inputs.model.x = np.linspace(0,1,ngrid)
        
        self.driver.workflow.add('hifi_cases')
        if 1 > self.nfi: 
                self.driver.workflow.add('lofi_cases')
        self.driver.workflow.add('mm_checker')
dataset/ETHPy150Open OpenMDAO/OpenMDAO-Framework/examples/openmdao.examples.metamodel_tutorial/openmdao/examples/metamodel_tutorial/cokriging_forrester_example.py/Simulation.configure/swapped operands of `>`