def test_optimize_derivs(self):
from openmdao.api import Problem, IndepVarComp
from openmdao.api import ScipyOptimizeDriver
from openmdao.components.tests.test_external_code_comp import ParaboloidExternalCodeCompDerivs
prob = Problem()
model = prob.model
# create and connect inputs
model.add_subsystem('p1', IndepVarComp('x', 3.0))
model.add_subsystem('p2', IndepVarComp('y', -4.0))
model.add_subsystem('p', ParaboloidExternalCodeCompDerivs())
model.connect('p1.x', 'p.x')
model.connect('p2.y', 'p.y')
# find optimal solution with SciPy optimize
# solution (minimum): x = 6.6667; y = -7.3333
prob.driver = ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
prob.model.add_design_var('p1.x', lower=-50, upper=50)
prob.model.add_design_var('p2.y', lower=-50, upper=50)
prob.model.add_objective('p.f_xy')
prob.driver.options['tol'] = 1e-9
prob.driver.options['disp'] = True
prob.setup()
prob.run_driver()
assert_rel_error(self, prob['p1.x'], 6.66666667, 1e-6)
assert_rel_error(self, prob['p2.y'], -7.3333333, 1e-6)
def test_optimize_derivs(self):
import openmdao.api as om
from openmdao.components.tests.test_external_code_comp import ParaboloidExternalCodeCompDerivs
prob = om.Problem()
model = prob.model
model.add_subsystem('p', ParaboloidExternalCodeCompDerivs())
# find optimal solution with SciPy optimize
# solution (minimum): x = 6.6667; y = -7.3333
prob.driver = om.ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
prob.model.add_design_var('p.x', lower=-50, upper=50)
prob.model.add_design_var('p.y', lower=-50, upper=50)
prob.model.add_objective('p.f_xy')
prob.driver.options['tol'] = 1e-9
prob.driver.options['disp'] = True
prob.setup()
# Set input values
prob.set_val('p.x', 3.0)
prob.set_val('p.y', -4.0)
prob.run_driver()
assert_near_equal(prob.get_val('p.x'), 6.66666667, 1e-6)
assert_near_equal(prob.get_val('p.y'), -7.3333333, 1e-6)