def test_error_change_after_setup(self):
# Tests error messages for the 5 options that we should never change
# after setup is called.
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
# Not permitted to change this
with self.assertRaises(RuntimeError) as err:
top.root.fd_options['form'] = 'complex_step'
expected_msg = "The 'form' option cannot be changed after setup."
self.assertEqual(str(err.exception), expected_msg)
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
# Not permitted to change this
with self.assertRaises(RuntimeError) as err:
top.root.fd_options['extra_check_partials_form'] = 'complex_step'
expected_msg = "The 'extra_check_partials_form' option cannot be changed after setup."
self.assertEqual(str(err.exception), expected_msg)
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
# Not permitted to change this
with self.assertRaises(RuntimeError) as err:
top.root.fd_options['force_fd'] = True
expected_msg = "The 'force_fd' option cannot be changed after setup."
self.assertEqual(str(err.exception), expected_msg)
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
# Not permitted to change this
with self.assertRaises(RuntimeError) as err:
top.root.ln_solver.options['mode'] = 'rev'
expected_msg = "The 'mode' option cannot be changed after setup."
self.assertEqual(str(err.exception), expected_msg)
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
# Not permitted to change this
with self.assertRaises(RuntimeError) as err:
top.root.ln_solver.options['single_voi_relevance_reduction'] = True
expected_msg = "The 'single_voi_relevance_reduction' option cannot be changed after setup."
self.assertEqual(str(err.exception), expected_msg)
def test_index_array_param(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_desvar('z',
lower=np.array([-10.0]),
upper=np.array([10.0]),
indices=[0])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.driver.options['disp'] = False
prob.setup(check=False)
prob['z'][1] = 5.0
prob.run()
assert_rel_error(self, prob['z'][0], 0.1005, 1e-3)
assert_rel_error(self, prob['z'][1], 5.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_newton_with_backtracking_analysis_error(self):
top = Problem()
top.root = SellarStateConnection()
top.root.nl_solver.line_search.options['atol'] = 1e-12
top.root.nl_solver.line_search.options['rtol'] = 1e-12
top.root.nl_solver.line_search.options['maxiter'] = 2
top.root.nl_solver.line_search.options['err_on_maxiter'] = True
# This is a very contrived test, but we step 8 times farther than we
# should, then allow the line search to backtrack 3 steps, which
# takes us back to 1.0.
top.root.nl_solver.options['alpha'] = 8.0
top.setup(check=False)
try:
top.run()
except AnalysisError as err:
self.assertEqual(
str(err),
"Solve in '': BackTracking failed to converge after 2 iterations."
)
else:
self.fail("AnalysisError expected")
def test_sellar_specify_linear_solver(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.root.nl_solver = Newton()
# Use bad settings for this one so that problem doesn't converge.
# That way, we test that we are really using Newton's Lin Solver
# instead.
prob.root.ln_solver = ScipyGMRES()
prob.root.ln_solver.options['maxiter'] = 1
# The good solver
prob.root.nl_solver.ln_solver = ScipyGMRES()
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['state_eq.y2_command'], 12.05848819,
.00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.root.nl_solver.iter_count, 8)
self.assertEqual(prob.root.ln_solver.iter_count, 0)
self.assertGreater(prob.root.nl_solver.ln_solver.iter_count, 0)
def test_driver_param_indices_force_fd_shift(self):
""" Test driver param indices with shifted indices and force_fd=True
"""
prob = Problem()
prob.root = SellarStateConnection()
prob.root.fd_options['force_fd'] = True
prob.driver.add_desvar('z',
lower=np.array([-10.0, -10.0]),
upper=np.array([10.0, 10.0]),
indices=[1])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
#prob.driver.options['disp'] = False
prob.setup(check=False)
prob['z'][1] = 0.0
prob.run()
J = prob.calc_gradient(['x', 'z'], ['obj'],
mode='fd',
return_format='array')
assert_rel_error(self, J[0][1], 1.78402, 1e-3)
def test_driver_param_indices(self):
""" Test driver param indices with pyOptSparse and force_fd=False
"""
prob = Problem()
prob.root = SellarStateConnection()
prob.root.fd_options['force_fd'] = False
prob.driver = pyOptSparseDriver()
prob.driver.options['optimizer'] = OPTIMIZER
prob.driver.options['print_results'] = False
prob.driver.add_desvar('z',
lower=np.array([-10.0]),
upper=np.array([10.0]),
indices=[0])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.setup(check=False)
prob['z'][1] = 0.0
prob.run()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_Sellar_state_SLSQP(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_param('z',
low=np.array([-10.0, 0.0]),
high=np.array([10.0, 10.0]))
prob.driver.add_param('x', low=0.0, high=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1')
prob.driver.add_constraint('con2')
prob.driver.options['disp'] = False
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_Sellar_state_SLSQP(self):
""" Baseline Sellar test case without specifying indices.
"""
prob = Problem()
prob.root = SellarStateConnection()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_desvar('z',
lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]))
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.driver.options['disp'] = False
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_iprint(self):
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
base_stdout = sys.stdout
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed, '')
# Turn on all iprints
top.print_all_convergence()
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed.count('NEWTON'), 3)
self.assertEqual(printed.count('GMRES'), 4)
self.assertTrue('[root] NL: NEWTON 0 | ' in printed)
self.assertTrue(' [root.sub] LN: GMRES 0 | ' in printed)
def test_driver_param_indices_slsqp_force_fd(self):
""" Test driver param indices with ScipyOptimizer SLSQP and force_fd=True
"""
prob = Problem()
prob.root = SellarStateConnection()
prob.root.fd_options['force_fd'] = True
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.options['disp'] = False
prob.driver.add_desvar('z',
lower=np.array([-10.0]),
upper=np.array([10.0]),
indices=[0])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
#prob.driver.options['disp'] = False
prob.setup(check=False)
prob['z'][1] = 0.0
prob.run()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_sellar_state_connection(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.root.nl_solver = Newton()
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['state_eq.y2_command'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.root.nl_solver.iter_count, 8)
def test_change_solver_after_setup(self):
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
top.root.ln_solver = ScipyGMRES()
with self.assertRaises(RuntimeError) as err:
top.run()
expected_msg = "Before running the model, setup() must be called. If " + \
"the configuration has changed since it was called, then " + \
"setup must be called again before running the model."
self.assertEqual(str(err.exception), expected_msg)
def test_newton_with_backtracking(self):
top = Problem()
top.root = SellarStateConnection()
top.root.nl_solver.line_search.options['atol'] = 1e-12
top.root.nl_solver.line_search.options['rtol'] = 1e-12
top.root.nl_solver.line_search.options['maxiter'] = 3
# This is a very contrived test, but we step 8 times farther than we
# should, then allow the line search to backtrack 3 steps, which
# takes us back to 1.0.
top.root.nl_solver.options['alpha'] = 8.0
top.setup(check=False)
top.run()
assert_rel_error(self, top['y1'], 25.58830273, .00001)
assert_rel_error(self, top['state_eq.y2_command'], 12.05848819, .00001)
def test_generate_numpydocstring(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_desvar('z', lower=np.array([-10.0]), upper=np.array([10.0]),
indices=[0])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.driver.options['disp'] = False
test_string = prob.driver.generate_docstring()
original_string = ' """\n\n Options\n -------\n options[\'disp\'] : bool(False)\n Set to False to prevent printing of Scipy convergence messages\n options[\'maxiter\'] : int(200)\n Maximum number of iterations.\n options[\'optimizer\'] : str(\'SLSQP\')\n Name of optimizer to use\n options[\'tol\'] : float(1e-08)\n Tolerance for termination. For detailed control, use solver-specific options.\n\n """\n'
self.assertEqual(original_string, test_string)
def test_newton_with_backtracking_analysis_error(self):
top = Problem()
top.root = SellarStateConnection()
top.root.nl_solver.line_search = BackTracking()
top.root.nl_solver.line_search.options['maxiter'] = 2
top.root.nl_solver.line_search.options['err_on_maxiter'] = True
top.root.nl_solver.line_search.options['c'] = 1.0
top.root.nl_solver.options['alpha'] = 10.0
top.setup(check=False)
try:
top.run()
except AnalysisError as err:
self.assertEqual(
str(err),
"Solve in '': BackTracking failed to converge after 2 iterations."
)
else:
self.fail("AnalysisError expected")
def test_sellar_derivs_under_lin_GS(self):
prob = Problem()
prob.root = Group()
prob.root.ln_solver = LinearGaussSeidel()
nest = prob.root.add('nest', SellarStateConnection())
nest.ln_solver = DirectSolver()
nest.ln_solver.options['jacobian_method'] = 'assemble'
nest.nl_solver.options['atol'] = 1e-12
prob.setup(check=False)
prob.run()
# Just make sure we are at the right answer
assert_rel_error(self, prob['nest.y1'], 25.58830273, .00001)
assert_rel_error(self, prob['nest.d1.y2'], 12.05848819, .00001)
indep_list = ['nest.x', 'nest.z']
unknown_list = ['nest.obj', 'nest.con1', 'nest.con2']
Jbase = {}
Jbase['nest.con1'] = {}
Jbase['nest.con1']['nest.x'] = -0.98061433
Jbase['nest.con1']['nest.z'] = np.array([-9.61002285, -0.78449158])
Jbase['nest.con2'] = {}
Jbase['nest.con2']['nest.x'] = 0.09692762
Jbase['nest.con2']['nest.z'] = np.array([1.94989079, 1.0775421 ])
Jbase['nest.obj'] = {}
Jbase['nest.obj']['nest.x'] = 2.98061392
Jbase['nest.obj']['nest.z'] = np.array([9.61001155, 1.78448534])
J = prob.calc_gradient(indep_list, unknown_list, mode='fwd', return_format='dict')
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J[key1][key2], val2, .00001)
J = prob.calc_gradient(indep_list, unknown_list, mode='rev', return_format='dict')
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J[key1][key2], val2, .00001)
def test_generate_numpydocstring(self):
prob = Problem()
prob.root = SellarStateConnection()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_desvar('z',
lower=np.array([-10.0]),
upper=np.array([10.0]),
indices=[0])
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.driver.options['disp'] = False
test_string = prob.driver.generate_docstring()
original_string = \
""" \"\"\"
Options
-------
options['disp'] : bool(False)
Set to False to prevent printing of Scipy convergence messages
options['maxiter'] : int(200)
Maximum number of iterations.
options['optimizer'] : str('SLSQP')
Name of optimizer to use
options['tol'] : float(1e-08)
Tolerance for termination. For detailed control, use solver-specific options.
\"\"\"
"""
for sorig, stest in zip(original_string.split('\n'),
test_string.split('\n')):
self.assertEqual(sorig, stest)
def test_iprint(self):
top = Problem()
top.root = SellarStateConnection()
# Can't do it before setup anymore.
with self.assertRaises(RuntimeError) as err:
top.print_all_convergence()
expected_msg = "Please run setup before calling print_all_convergence."
self.assertEqual(str(err.exception), expected_msg)
top.setup(check=False)
base_stdout = sys.stdout
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed, '')
# Turn on all iprints
top.print_all_convergence()
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed.count('NEWTON'), 3)
self.assertEqual(printed.count('GMRES'), 4)
self.assertTrue('[root] NL: NEWTON 0 | ' in printed)
self.assertTrue(' [root.sub] LN: GMRES 1 | ' in printed)
# Now, test out level = 1
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
base_stdout = sys.stdout
top.print_all_convergence(level=1)
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed.count('NEWTON'), 2)
self.assertEqual(printed.count('GMRES'), 4)
self.assertTrue('[root] NL: NEWTON 0 | ' not in printed)
self.assertTrue(' [root.sub] LN: GMRES 1 | ' not in printed)
# Level -1 suppresses it all
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
base_stdout = sys.stdout
top.print_all_convergence(level=-1)
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertEqual(printed, '')
# Lets just look at the top
top = Problem()
top.root = SellarStateConnection()
top.setup(check=False)
base_stdout = sys.stdout
top.print_all_convergence(depth=0)
try:
ostream = cStringIO()
sys.stdout = ostream
top.run()
finally:
sys.stdout = base_stdout
printed = ostream.getvalue()
self.assertTrue('root' in printed)
self.assertTrue('root.sub' not in printed)