Source code for openmdao.lib.architectures.mdf

from openmdao.main.api import Driver, Architecture
from openmdao.lib.drivers.api import SLSQPdriver, BroydenSolver#, COBYLAdriver as SLSQPdriver

from openmdao.lib.differentiators.finite_difference import FiniteDifference

class MDF(Architecture):
    
    def __init__(self, *args, **kwargs):
        super(MDF, self).__init__(*args, **kwargs)
        
        # the following variables determine the behavior of check_config
        self.param_types = ['continuous']
        self.constraint_types = ['ineq']
        self.num_allowed_objectives = 1
        self.has_coupling_vars = True
        self.has_global_des_vars = False
    
    def configure(self): 
        """Setup an MDF architecture inside this assembly.
        """
        #create the top level optimizer
        self.parent.add("driver",SLSQPdriver())
        self.parent.driver.differentiator = FiniteDifference()
        self.parent.driver.iprint = 0
        self.parent.driver.recorders = self.data_recorders
        
        params = self.parent.get_parameters()
        global_dvs = []
        local_dvs = []
        

        for k,v in self.parent.get_global_des_vars(): 
            global_dvs.append(v)
            # and add the broadcast parameters to the driver            
            self.parent.driver.add_parameter(v,name=k)   
        
        for k,v in self.parent.get_local_des_vars(): 
            local_dvs.append(v)
            self.parent.driver.add_parameter(v,name=k)
         
        #TODO: possibly add method for passing constraint directly?
        #add the constraints to the driver
        for const in self.parent.list_constraints(): 
            self.parent.driver.add_constraint(const)
            
        #set the global objective
        objective = self.parent.get_objectives().items()[0]
        self.parent.driver.add_objective(objective[1].text, name=objective[0])
            
        #setup the inner loop solver
        self.parent.add('solver', BroydenSolver())    
        self.parent.solver.itmax = 10
        self.parent.solver.alpha = .4
        self.parent.solver.tol = .0000001
        self.parent.solver.algorithm = "broyden2"
        
        #add the coupling vars parameters/constraints to the solver
        for key,couple in self.parent.list_coupling_vars().iteritems(): 
            self.parent.solver.add_parameter(couple.indep.target, low=-1.e99, high=1.e99,name=key)
            self.parent.solver.add_constraint("%s=%s"%(couple.indep.target,couple.dep.target))

        #setup the workflows
        self.parent.driver.workflow.add(['solver'])
        #self.parent.solver.workflow.add(disciplines)