def test_option_parallel(self):
import openmdao.api as om
from openmdao.test_suite.components.branin import Branin
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver.options['max_gen'] = 10
prob.driver.options['run_parallel'] = True
prob.setup()
prob.run_driver()
# Optimal solution
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_option_parallel(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.DifferentialEvolutionDriver()
prob.driver.options['max_gen'] = 10
prob.driver.options['run_parallel'] = True
prob.setup()
prob.run_driver()
# Optimal solution
if extra_prints:
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_basic_with_assert(self):
from openmdao.api import Problem, Group, IndepVarComp, SimpleGADriver
from openmdao.test_suite.components.branin import Branin
prob = Problem()
model = prob.model = Group()
model.add_subsystem('p1', IndepVarComp('xC', 7.5))
model.add_subsystem('p2', IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver._randomstate = 1
prob.setup()
prob.run_driver()
# Optimal solution
assert_rel_error(self, prob['comp.f'], 0.49399549, 1e-4)
def test_mixed_integer_branin(self):
np.random.seed(1)
prob = Problem()
model = prob.model = Group()
model.add_subsystem('p1', IndepVarComp('xC', 7.5))
model.add_subsystem('p2', IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = SimpleGADriver(max_gen=75, pop_size=25)
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver._randomstate = 1
prob.setup(check=False)
prob.run_driver()
# Optimal solution
assert_rel_error(self, prob['comp.f'], 0.49398, 1e-4)
self.assertTrue(int(prob['p2.xI']) in [3, -3])
def test_option_parallel(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
cma_es = CMAES()
cma_es.options['verbose'] = -9 # silence output
prob.driver = GenericDriver(algorithm=cma_es)
prob.driver.options['run_parallel'] = True
prob.setup()
prob.run_driver()
# Optimal solution
if extra_prints:
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_option_pop_size(self):
from openmdao.api import Problem, Group, IndepVarComp, SimpleGADriver
from openmdao.test_suite.components.branin import Branin
prob = Problem()
model = prob.model = Group()
model.add_subsystem('p1', IndepVarComp('xC', 7.5))
model.add_subsystem('p2', IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver.options['pop_size'] = 10
prob.setup()
prob.run_driver()
# Optimal solution
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_mixed_integer_branin(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
model.add_subsystem('comp', Branin())
model.connect('p2.xI', 'comp.x0')
model.connect('p1.xC', 'comp.x1')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver.options['max_gen'] = 50
prob.driver.options['pop_size'] = 25
prob.driver.options['run_parallel'] = True
prob.driver._randomstate = 1
prob.setup()
prob.run_driver()
# Optimal solution
assert_rel_error(self, prob['comp.f'], 0.49398, 1e-4)
self.assertTrue(int(prob['p2.xI']) in [3, -3])
def test_option_procs_per_model(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 2.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 3.0))
par = model.add_subsystem('par', om.ParallelGroup())
par.add_subsystem('comp1', Branin())
par.add_subsystem('comp2', Branin())
model.connect('p2.xI', 'par.comp1.x0')
model.connect('p1.xC', 'par.comp1.x1')
model.connect('p2.xI', 'par.comp2.x0')
model.connect('p1.xC', 'par.comp2.x1')
model.add_subsystem('comp', om.ExecComp('f = f1 + f2'))
model.connect('par.comp1.f', 'comp.f1')
model.connect('par.comp2.f', 'comp.f2')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
cma_es = CMAES()
cma_es.options['popsize'] = 25
cma_es.options['verbose'] = -9 # silence output
prob.driver = GenericDriver(algorithm=cma_es)
prob.driver.options['run_parallel'] = True
prob.driver.options['procs_per_model'] = 2
prob.setup()
prob.run_driver()
# Optimal solution from DifferentialEvolutionDriver:
# comp.f [0.80220303]
# p2.xI [3.11628575]
# p1.xC [2.28300608]
if extra_prints:
print('comp.f', prob.get_val('comp.f'))
print('p2.xI', prob.get_val('p2.xI'))
print('p1.xC', prob.get_val('p1.xC'))
def test_option_procs_per_model(self):
import openmdao.api as om
from openmdao.test_suite.components.branin import Branin
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
par = model.add_subsystem('par', om.ParallelGroup())
par.add_subsystem('comp1', Branin())
par.add_subsystem('comp2', Branin())
model.connect('p2.xI', 'par.comp1.x0')
model.connect('p1.xC', 'par.comp1.x1')
model.connect('p2.xI', 'par.comp2.x0')
model.connect('p1.xC', 'par.comp2.x1')
model.add_subsystem('comp', om.ExecComp('f = f1 + f2'))
model.connect('par.comp1.f', 'comp.f1')
model.connect('par.comp2.f', 'comp.f2')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver.options['max_gen'] = 10
prob.driver.options['pop_size'] = 25
prob.driver.options['run_parallel'] = True
prob.driver.options['procs_per_model'] = 2
prob.driver._randomstate = 1
prob.setup()
prob.run_driver()
# Optimal solution
if extra_prints:
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_two_branin_parallel_model(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
par = model.add_subsystem('par', om.ParallelGroup())
par.add_subsystem('comp1', Branin())
par.add_subsystem('comp2', Branin())
model.connect('p2.xI', 'par.comp1.x0')
model.connect('p1.xC', 'par.comp1.x1')
model.connect('p2.xI', 'par.comp2.x0')
model.connect('p1.xC', 'par.comp2.x1')
model.add_subsystem('comp', om.ExecComp('f = f1 + f2'))
model.connect('par.comp1.f', 'comp.f1')
model.connect('par.comp2.f', 'comp.f2')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.SimpleGADriver()
prob.driver.options['bits'] = {'p1.xC': 8}
prob.driver.options['max_gen'] = 40
prob.driver.options['pop_size'] = 25
prob.driver.options['run_parallel'] = False
prob.driver.options['procs_per_model'] = 2
prob.driver._randomstate = 1
prob.setup()
prob.run_driver()
if extra_prints:
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
# Optimal solution
assert_rel_error(self, prob['comp.f'], 0.98799098, 1e-4)
self.assertTrue(int(prob['p2.xI']) in [3, -3])
def test_option_procs_per_model(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('p1', om.IndepVarComp('xC', 7.5))
model.add_subsystem('p2', om.IndepVarComp('xI', 0.0))
par = model.add_subsystem('par', om.ParallelGroup())
par.add_subsystem('comp1', Branin())
par.add_subsystem('comp2', Branin())
model.connect('p2.xI', 'par.comp1.x0')
model.connect('p1.xC', 'par.comp1.x1')
model.connect('p2.xI', 'par.comp2.x0')
model.connect('p1.xC', 'par.comp2.x1')
model.add_subsystem('comp', om.ExecComp('f = f1 + f2'))
model.connect('par.comp1.f', 'comp.f1')
model.connect('par.comp2.f', 'comp.f2')
model.add_design_var('p2.xI', lower=-5.0, upper=10.0)
model.add_design_var('p1.xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = GenericDriver(
algorithm=DifferentialEvolution(max_gen=10, pop_size=25))
# prob.driver.options['max_gen'] = 10
# prob.driver.options['pop_size'] = 25
prob.driver.options['run_parallel'] = True
prob.driver.options['procs_per_model'] = 2
prob.setup()
prob.run_driver()
# Optimal solution
if extra_prints:
print('comp.f', prob['comp.f'])
print('p2.xI', prob['p2.xI'])
print('p1.xC', prob['p1.xC'])
def test_basic(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('comp', Branin(), promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.DifferentialEvolutionDriver()
prob.setup()
prob.run_driver()
def test_basic(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('comp',
Branin(),
promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = CMAESDriver()
prob.driver.CMAOptions['verbose'] = -9 # silence output
prob.setup()
prob.run_driver()
def test_basic_with_assert(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('comp', Branin(), promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.DifferentialEvolutionDriver()
prob.setup()
prob.run_driver()
# Optimal solution (actual optimum, not the optimal with integer inputs as found by SimpleGA)
assert_near_equal(prob['comp.f'], 0.397887, 1e-4)
def test_random_state_bug(self):
# this test passes if it raises no exceptions
prob = om.Problem()
model = prob.model
model.add_subsystem('comp', Branin(), promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.DifferentialEvolutionDriver()
prob.driver.options['max_gen'] = 5
prob.driver.options['run_parallel'] = True
prob.setup()
prob.run_driver()
def test_option_pop_size(self):
import openmdao.api as om
from openmdao.test_suite.components.branin import Branin
prob = om.Problem()
model = prob.model
model.add_subsystem('comp', Branin(), promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = om.DifferentialEvolutionDriver()
prob.driver.options['pop_size'] = 10
prob.setup()
prob.run_driver()
def test_option_max_gen(self):
import openmdao.api as om
from openmdao.test_suite.components.branin import Branin
prob = om.Problem()
model = prob.model
model.add_subsystem('comp',
Branin(),
promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
prob.driver = GenericDriver(algorithm=DifferentialEvolution(max_gen=5))
# prob.driver.options['max_gen'] = 5
prob.setup()
prob.run_driver()
def test_basic_with_assert(self):
prob = om.Problem()
model = prob.model
model.add_subsystem('comp',
Branin(),
promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
cma_es = CMAES()
cma_es.options['verbose'] = -9 # silence output
prob.driver = GenericDriver(algorithm=cma_es)
prob.setup()
prob.run_driver()
# Optimal solution (actual optimum, not the optimal with integer inputs as found by SimpleGA)
assert_near_equal(prob['comp.f'], 0.397887, 1e-4)
def test_option_pop_size(self):
import openmdao.api as om
from openmdao.test_suite.components.branin import Branin
prob = om.Problem()
model = prob.model
model.add_subsystem('comp',
Branin(),
promotes_inputs=[('x0', 'xI'), ('x1', 'xC')])
model.add_design_var('xI', lower=-5.0, upper=10.0)
model.add_design_var('xC', lower=0.0, upper=15.0)
model.add_objective('comp.f')
cma_es = CMAES()
cma_es.options['popsize'] = 10
cma_es.options['verbose'] = -9 # silence output
prob.driver = GenericDriver(algorithm=cma_es)
prob.setup()
prob.run_driver()
