def test_solve_subsystems_assembled_jac_top_implicit_scaling_units(self):
prob = Problem(model=DoubleSellarImplicit(units=True, scaling=True))
model = prob.model
model.jacobian = DenseJacobian()
g1 = model.g1
g1.nonlinear_solver = NewtonSolver()
g1.nonlinear_solver.options['rtol'] = 1.0e-5
g1.linear_solver = DirectSolver()
g2 = model.g2
g2.nonlinear_solver = NewtonSolver()
g2.nonlinear_solver.options['rtol'] = 1.0e-5
g2.linear_solver = DirectSolver()
model.nonlinear_solver = NewtonSolver()
model.linear_solver = ScipyKrylov()
model.nonlinear_solver.options['solve_subsystems'] = True
prob.setup()
prob.run_model()
assert_rel_error(self, prob['g1.y1'], 0.053333333, .00001)
assert_rel_error(self, prob['g1.y2'], 0.80, .00001)
assert_rel_error(self, prob['g2.y1'], 0.053333333, .00001)
assert_rel_error(self, prob['g2.y2'], 0.80, .00001)
def test_solve_subsystems_assembled_jac_top_implicit_scaling(self):
prob = Problem()
model = prob.model = DoubleSellarImplicit(scaling=True)
model.jacobian = DenseJacobian()
g1 = model.get_subsystem('g1')
g1.nonlinear_solver = NewtonSolver()
g1.nonlinear_solver.options['rtol'] = 1.0e-5
g1.linear_solver = DirectSolver()
g2 = model.get_subsystem('g2')
g2.nonlinear_solver = NewtonSolver()
g2.nonlinear_solver.options['rtol'] = 1.0e-5
g2.linear_solver = DirectSolver()
model.nonlinear_solver = NewtonSolver()
model.linear_solver = ScipyIterativeSolver()
model.nonlinear_solver.options['solve_subsystems'] = True
prob.setup()
prob.run_model()
assert_rel_error(self, prob['g1.y1'], 0.64, .00001)
assert_rel_error(self, prob['g1.y2'], 0.80, .00001)
assert_rel_error(self, prob['g2.y1'], 0.64, .00001)
assert_rel_error(self, prob['g2.y2'], 0.80, .00001)
def test_solve_subsystems_assembled_jac_top_implicit_scaling_units(self):
prob = om.Problem(model=DoubleSellarImplicit(units=True, scaling=True))
model = prob.model
g1 = model.g1
g1.nonlinear_solver = om.NewtonSolver(solve_subsystems=False,
rtol=1.0e-5)
g1.nonlinear_solver.linesearch = None
g1.linear_solver = om.DirectSolver()
g2 = model.g2
g2.nonlinear_solver = om.NewtonSolver(solve_subsystems=False,
rtol=1.0e-5)
g2.nonlinear_solver.linesearch = None
g2.linear_solver = om.DirectSolver()
model.nonlinear_solver = om.NewtonSolver(solve_subsystems=True)
model.nonlinear_solver.linesearch = None
model.linear_solver = om.ScipyKrylov(assemble_jac=True)
model.options['assembled_jac_type'] = 'dense'
prob.setup()
prob.run_model()
assert_rel_error(self, prob['g1.y1'], 0.053333333, .00001)
assert_rel_error(self, prob['g1.y2'], 0.80, .00001)
assert_rel_error(self, prob['g2.y1'], 0.053333333, .00001)
assert_rel_error(self, prob['g2.y2'], 0.80, .00001)
def test_solve_subsystems_assembled_jac_top_implicit(self):
prob = om.Problem(model=DoubleSellarImplicit())
model = prob.model
g1 = model.g1
g1.nonlinear_solver = om.NewtonSolver(solve_subsystems=False,
rtol=1.0e-5)
g1.linear_solver = om.DirectSolver()
g2 = model.g2
g2.nonlinear_solver = om.NewtonSolver(solve_subsystems=False,
rtol=1.0e-5)
g2.linear_solver = om.DirectSolver()
model.nonlinear_solver = om.NewtonSolver(solve_subsystems=True)
model.linear_solver = om.ScipyKrylov(assemble_jac=True)
model.options['assembled_jac_type'] = 'dense'
prob.setup()
prob.run_model()
assert_near_equal(prob['g1.y1'], 0.64, .00001)
assert_near_equal(prob['g1.y2'], 0.80, .00001)
assert_near_equal(prob['g2.y1'], 0.64, .00001)
assert_near_equal(prob['g2.y2'], 0.80, .00001)
def _build_model(mode, implicit=False):
p = Problem()
dv = p.model.add_subsystem('dv', IndepVarComp(), promotes=['*'])
dv.add_output('z', [1.,1.])
if implicit:
p.model.add_subsystem('double_sellar', DoubleSellarImplicit())
else:
p.model.add_subsystem('double_sellar', DoubleSellar())
p.model.connect('z', ['double_sellar.g1.z', 'double_sellar.g2.z'])
p.model.add_design_var('z', lower=-10, upper=10)
p.model.add_objective('double_sellar.g1.y1')
p.setup(mode=mode)
p.model.nonlinear_solver = NewtonSolver()
return p
def test_solve_subsystems_assembled_jac_top_implicit_scaling(self):
prob = Problem(model=DoubleSellarImplicit(scaling=True))
model = prob.model
g1 = model.g1
g1.nonlinear_solver = NewtonSolver(rtol=1.0e-5)
g1.linear_solver = DirectSolver()
g2 = model.g2
g2.nonlinear_solver = NewtonSolver(rtol=1.0e-5)
g2.linear_solver = DirectSolver()
model.nonlinear_solver = NewtonSolver(solve_subsystems=True)
model.linear_solver = ScipyKrylov(assemble_jac=True)
model.options['assembled_jac_type'] = 'dense'
prob.setup()
prob.run_model()
assert_rel_error(self, prob['g1.y1'], 0.64, .00001)
assert_rel_error(self, prob['g1.y2'], 0.80, .00001)
assert_rel_error(self, prob['g2.y1'], 0.64, .00001)
assert_rel_error(self, prob['g2.y2'], 0.80, .00001)
