def test_input_input_explicit_conns_w_conn(self):
prob = Problem(root=Group())
root = prob.root
root.add('p1', ParamComp('x', 1.0))
root.add('c1', ExecComp('y = x*2.0'))
root.add('c2', ExecComp('y = x*3.0'))
root.connect('c1.x', 'c2.x')
root.connect('p1.x', 'c2.x')
prob.setup(check=False)
prob.run()
self.assertEqual(root.connections['c1.x'], 'p1.x')
self.assertEqual(root.connections['c2.x'], 'p1.x')
self.assertEqual(len(root.connections), 2)
def test_sellar_derivs_grouped(self):
prob = Problem()
prob.root = SellarDerivativesGrouped()
prob.root.mda.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['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
param_list = ['x', 'z']
unknown_list = ['obj', 'con1', 'con2']
Jbase = {}
Jbase['con1'] = {}
Jbase['con1']['x'] = -0.98061433
Jbase['con1']['z'] = np.array([-9.61002285, -0.78449158])
Jbase['con2'] = {}
Jbase['con2']['x'] = 0.09692762
Jbase['con2']['z'] = np.array([1.94989079, 1.0775421])
Jbase['obj'] = {}
Jbase['obj']['x'] = 2.98061392
Jbase['obj']['z'] = np.array([9.61001155, 1.78448534])
J = prob.calc_gradient(param_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(param_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)
prob.root.fd_options['form'] = 'central'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fd',
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 setup(self, check=False):
"""
Creates the containing `Problem` and performs needed initializations.
Parameters
----------
check : bool
If setup should run checks.
"""
args = self.args
group = MODELS[self._group_type](**args)
local_vec_class = args.get('local_vector_class', 'default')
if local_vec_class == 'default':
vec_class = DefaultVector
elif local_vec_class == 'petsc':
vec_class = PETScVector
if PETScVector is None:
raise SkipTest('PETSc not available.')
else:
raise RuntimeError("Unrecognized local_vector_class '%s'" %
local_vec_class)
self.problem = prob = Problem(group)
if args['assembled_jac']:
jacobian_type = args.get('jacobian_type', 'dense')
if jacobian_type == 'dense':
prob.model.jacobian = DenseJacobian()
elif jacobian_type == 'sparse-coo':
prob.model.jacobian = COOJacobian()
elif jacobian_type == 'sparse-csr':
prob.model.jacobian = CSRJacobian()
elif jacobian_type == 'sparse-csc':
prob.model.jacobian = CSCJacobian()
prob.model.linear_solver = self.linear_solver_class(
**self.linear_solver_options)
prob.model.nonlinear_solver = self.solver_class(**self.solver_options)
prob.set_solver_print(level=0)
prob.setup(check=check, local_vector_class=vec_class)
fail, rele, abse = prob.run_model()
if fail:
raise RuntimeError('Problem run failed: re %f ; ae %f' %
(rele, abse))
def test_group_fd(self):
class SimpleComp(Component):
""" A simple component that provides derivatives. """
def __init__(self):
super(SimpleComp, self).__init__()
# Params
self.add_param('x', 2.0)
# Unknowns
self.add_output('y', 0.0)
def solve_nonlinear(self, params, unknowns, resids):
""" Doesn't do much. Just multiply by 3"""
unknowns['y'] = 3.0 * params['x']
def jacobian(self, params, unknowns, resids):
"""Analytical derivatives."""
J = {}
J[('y', 'x')] = 3.0
return J
class Model(Group):
""" Simple model to experiment with finite difference."""
def __init__(self):
super(Model, self).__init__()
self.add('px', ParamComp('x', 2.0))
self.add('comp1', SimpleComp())
sub = self.add('sub', Group())
sub.add('comp2', SimpleComp())
sub.add('comp3', SimpleComp())
self.add('comp4', SimpleComp())
self.connect('px.x', 'comp1.x')
self.connect('comp1.y', 'sub.comp2.x')
self.connect('sub.comp2.y', 'sub.comp3.x')
self.connect('sub.comp3.y', 'comp4.x')
self.sub.fd_options['force_fd'] = True
prob = Problem()
prob.root = Model()
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(['px.x'], ['comp4.y'])
assert_rel_error(self, J[0][0], 81.0, 1e-6)
def test_basic(self):
size = 3
prob = Problem(Group(), impl=impl)
G1 = prob.root.add('G1', ParallelGroup())
G1.add('P1', IndepVarComp('x', np.ones(size, float) * 1.0))
G1.add('P2', IndepVarComp('x', np.ones(size, float) * 2.0))
prob.root.add('C1', ABCDArrayComp(size))
prob.root.connect('G1.P1.x', 'C1.a')
prob.root.connect('G1.P2.x', 'C1.b')
prob.driver.add_recorder(self.recorder)
self.recorder.options['record_params'] = True
self.recorder.options['record_resids'] = True
prob.setup(check=False)
t0, t1 = run(prob)
prob.cleanup()
coordinate = ['Driver', (1, )]
expected_params = [
("C1.a", [1.0, 1.0, 1.0]),
("C1.b", [2.0, 2.0, 2.0]),
]
expected_unknowns = [
("G1.P1.x", np.array([1.0, 1.0, 1.0])),
("G1.P2.x", np.array([2.0, 2.0, 2.0])),
("C1.c", np.array([3.0, 3.0, 3.0])),
("C1.d", np.array([-1.0, -1.0, -1.0])),
("C1.out_string", "_C1"),
("C1.out_list", [1.5]),
]
expected_resids = [
("G1.P1.x", np.array([0.0, 0.0, 0.0])),
("G1.P2.x", np.array([0.0, 0.0, 0.0])),
("C1.c", np.array([0.0, 0.0, 0.0])),
("C1.d", np.array([0.0, 0.0, 0.0])),
("C1.out_string", ""),
("C1.out_list", []),
]
self.assertIterationDataRecorded(
((coordinate, (t0, t1), expected_params, expected_unknowns,
expected_resids), ), self.eps, prob.root)
def test_sellar(self):
prob = Problem()
prob.root = SellarNoDerivatives()
prob.root.nl_solver = NLGaussSeidel()
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.root.nl_solver.iter_count, 8)
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_simplest_run(self):
prob = Problem(root=Group())
root = prob.root
root.add('x_param', ParamComp('x', 7.0))
root.add('mycomp', ExecComp('y=x*2.0'))
root.connect('x_param.x', 'mycomp.x')
prob.setup(check=False)
prob.run()
result = root.unknowns['mycomp.y']
self.assertAlmostEqual(14.0, result, 3)
def test_root_solver_records_metadata(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.root.nl_solver.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = True
prob.setup(check=False)
self.recorder.close()
expected_params = list(iteritems(prob.root.params))
expected_unknowns = list(iteritems(prob.root.unknowns))
expected_resids = list(iteritems(prob.root.resids))
self.assertMetadataRecorded(
(expected_params, expected_unknowns, expected_resids))
def test_multilevel_record(self):
prob = Problem()
prob.root = ExampleGroup()
prob.root.G2.G1.nl_solver.add_recorder(self.recorder)
prob.driver.add_recorder(self.recorder)
self.recorder.options['record_params'] = True
self.recorder.options['record_resids'] = True
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
solver_coordinate = [0, 'Driver', (1,), "root", (1,), "G2", (1,), "G1", (1,)]
g1_expected_params = [
("C2.x", 5.0)
]
g1_expected_unknowns = [
("C2.y", 10.0)
]
g1_expected_resids = [
("C2.y", 0.0)
]
g1_expected = (g1_expected_params, g1_expected_unknowns, g1_expected_resids)
driver_coordinate = [0, 'Driver', (1,)]
driver_expected_params = [
("G3.C3.x", 10.0)
]
driver_expected_unknowns = [
("G2.C1.x", 5.0),
("G2.G1.C2.y", 10.0),
("G3.C3.y", 20.0),
("G3.C4.y", 40.0),
]
driver_expected_resids = [
("G2.C1.x", 0.0),
("G2.G1.C2.y", 0.0),
("G3.C3.y", 0.0),
("G3.C4.y", 0.0),
]
expected = []
expected.append((solver_coordinate, (t0, t1), g1_expected_params, g1_expected_unknowns, g1_expected_resids))
expected.append((driver_coordinate, (t0, t1), driver_expected_params, driver_expected_unknowns, driver_expected_resids))
self.assertIterationDataRecorded(expected, self.eps)
def test_subsolver_records_metadata(self):
prob = Problem()
prob.root = ExampleGroup()
prob.root.G2.G1.nl_solver.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = True
prob.setup(check=False)
prob.cleanup() # closes recorders
expected_params = list(iteritems(prob.root.params))
expected_unknowns = list(iteritems(prob.root.unknowns))
expected_resids = list(iteritems(prob.root.resids))
self.assertMetadataRecorded(
(expected_params, expected_unknowns, expected_resids))
def test_fd_params(self):
# tests retrieval of a list of any internal params whose source is either
# a ParamComp or is outside of the Group
prob = Problem(root=ExampleGroup())
prob.setup(check=False)
root = prob.root
self.assertEqual(root._get_fd_params(), ['G2.G1.C2.x'])
self.assertEqual(root.G2._get_fd_params(), ['G1.C2.x'])
self.assertEqual(root.G2.G1._get_fd_params(), ['C2.x'])
self.assertEqual(root.G3._get_fd_params(), ['C3.x'])
self.assertEqual(root.G3.C3._get_fd_params(), ['x'])
self.assertEqual(root.G2.G1.C2._get_fd_params(), ['x'])
def test_model_viewer_has_correct_data_from_problem(self):
"""
Verify that the correct model structure data exists when stored as compared
to the expected structure, using the SellarStateConnection model.
"""
p = Problem()
p.model = SellarStateConnection()
p.setup(check=False)
model_viewer_data = _get_viewer_data(p)
tree_json = json.dumps(model_viewer_data['tree'])
conns_json = json.dumps(model_viewer_data['connections_list'])
self.assertEqual(self.expected_tree_json, tree_json)
self.assertEqual(self.expected_conns_json, conns_json)
def test_solver_debug_print(self, name, solver):
p = Problem()
model = p.model
model.add_subsystem('ground', IndepVarComp('V', 0., units='V'))
model.add_subsystem('source', IndepVarComp('I', 0.1, units='A'))
model.add_subsystem('circuit', Circuit())
model.connect('source.I', 'circuit.I_in')
model.connect('ground.V', 'circuit.Vg')
p.setup()
nl = model.circuit.nonlinear_solver = solver()
nl.options['debug_print'] = True
# suppress solver output for test
nl.options['iprint'] = model.circuit.linear_solver.options['iprint'] = -1
# For Broydensolver, don't calc Jacobian
try:
nl.options['compute_jacobian'] = False
except KeyError:
pass
# set some poor initial guesses so that we don't converge
p['circuit.n1.V'] = 10.
p['circuit.n2.V'] = 1e-3
opts = {}
# formatting has changed in numpy 1.14 and beyond.
if LooseVersion(np.__version__) >= LooseVersion("1.14"):
opts["legacy"] = '1.13'
with printoptions(**opts):
# run the model and check for expected output file
output = run_model(p)
expected_output = '\n'.join([
self.expected_data,
"Inputs and outputs at start of iteration "
"have been saved to '%s'.\n" % self.filename
])
self.assertEqual(output, expected_output)
with open(self.filename, 'r') as f:
self.assertEqual(f.read(), self.expected_data)
def setup(self, check=False):
"""
Creates the containing `Problem` and performs needed initializations.
Parameters
----------
check : bool
If setup should run checks.
"""
args = self.args
group = MODELS[self._group_type](**args)
local_vec_class = args.get('local_vector_class', 'default')
if local_vec_class == 'default':
vec_class = DefaultVector
elif local_vec_class == 'petsc':
vec_class = PETScVector
if PETScVector is None:
raise SkipTest('PETSc not available.')
else:
raise RuntimeError("Unrecognized local_vector_class '%s'" %
local_vec_class)
self.problem = prob = Problem(group)
if args['assembled_jac']:
jacobian_type = args.get('jacobian_type', 'dense')
if jacobian_type == 'dense':
self.linear_solver_options['assemble_jac'] = True
prob.model.options['assembled_jac_type'] = 'dense'
elif jacobian_type == 'sparse-csc':
self.linear_solver_options['assemble_jac'] = True
prob.model.options['assembled_jac_type'] = 'csc'
elif jacobian_type != 'matvec':
raise RuntimeError("Invalid assembled_jac: '%s'." %
jacobian_type)
prob.model.linear_solver = self.linear_solver_class(
**self.linear_solver_options)
prob.model.nonlinear_solver = self.solver_class(**self.solver_options)
prob.set_solver_print(level=0)
prob.setup(check=check, local_vector_class=vec_class)
prob.run_model()
def test_solver_record(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.root.nl_solver.add_recorder(self.recorder)
self.recorder.options['record_params'] = True
self.recorder.options['record_resids'] = True
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = [0, 'Driver', (1,), "root", (1,)]
expected_params = [
("comp1.x1", 2.0),
("comp2.x1", 8.0),
("comp3.x1", 6.0),
("comp4.x1", 4.0),
("comp4.x2", 21.0),
("comp5.x1", 46.0),
("comp6.x1", -93.0),
("comp7.x1", 36.8),
("comp7.x2", -46.5)
]
expected_unknowns = [
("comp1.y1", 8.0),
("comp1.y2", 6.0),
("comp2.y1", 4.0),
("comp3.y1", 21.0),
("comp4.y1", 46.0),
("comp4.y2", -93.0),
("comp5.y1", 36.8),
("comp6.y1", -46.5),
("comp7.y1", -102.7),
("p.x", 2.0)
]
expected_resids = [
("comp1.y1", 0.0),
("comp1.y2", 0.0),
("comp2.y1", 0.0),
("comp3.y1", 0.0),
("comp4.y1", 0.0),
("comp4.y2", 0.0),
("comp5.y1", 0.0),
("comp6.y1", 0.0),
("comp7.y1", 0.0),
("p.x", 0.0)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_variable_access(self):
prob = Problem(root=ExampleGroup())
# try accessing variable value before setup()
try:
prob['G2.C1.x']
except Exception as err:
msg = "'unknowns' has not been initialized, setup() must be called before 'G2.C1.x' can be accessed"
self.assertEqual(text_type(err), msg)
else:
self.fail('Exception expected')
prob.setup(check=False)
# check that we can access values from unknowns (default) and params
self.assertEqual(prob['G2.C1.x'], 5.) # default output from ParamComp
self.assertEqual(prob['G2.G1.C2.y'], 5.5) # output from ExecComp
self.assertEqual(prob.root.G3.C3.params['x'],
0.) # initial value for a parameter
self.assertEqual(prob.root.G2.G1.C2.params['x'],
0.) # initial value for a parameter
# now try same thing in a Group with promotes
prob = Problem(root=ExampleGroupWithPromotes())
prob.setup(check=False)
prob.root.G2.unknowns['x'] = 99.
self.assertEqual(prob['G2.x'], 99.)
self.assertEqual(prob.root.G2.G1.C2.params['x'],
0.) # initial value for a parameter
# and make sure we get the correct value after a transfer
prob.root.G2._transfer_data('G1')
self.assertEqual(prob.root.G2.G1.C2.params['x'],
99.) # transferred value of parameter
def test_fd_unknowns(self):
# tests retrieval of a list of any internal unknowns with ParamComp
# variables filtered out.
prob = Problem(root=ExampleGroup())
prob.setup(check=False)
root = prob.root
self.assertEqual(root._get_fd_unknowns(),
['G2.G1.C2.y', 'G3.C3.y', 'G3.C4.y'])
self.assertEqual(root.G2._get_fd_unknowns(), ['G1.C2.y'])
self.assertEqual(root.G2.G1._get_fd_unknowns(), ['C2.y'])
self.assertEqual(root.G3._get_fd_unknowns(), ['C3.y', 'C4.y'])
self.assertEqual(root.G3.C3._get_fd_unknowns(), ['y'])
self.assertEqual(root.G2.G1.C2._get_fd_unknowns(), ['y'])
def test_model_viewer_has_correct_data_from_problem(self):
"""
Verify that the correct model structure data exists when stored as compared
to the expected structure, using the SellarStateConnection model.
"""
p = Problem()
p.model = SellarStateConnection()
p.setup(check=False)
model_viewer_data = _get_viewer_data(p)
self.assertDictEqual(model_viewer_data['tree'], self.expected_tree)
self.assertListEqual(model_viewer_data['connections_list'],
self.expected_conns)
self.assertDictEqual(model_viewer_data['abs2prom'],
self.expected_abs2prom)
def test_auto_order2(self):
# this tests the auto ordering when we have a cycle that is the full graph.
p = Problem(root=Group())
root = p.root
C1 = root.add("C1", ExecComp('y=x*2.0'))
C2 = root.add("C2", ExecComp('y=x*2.0'))
C3 = root.add("C3", ExecComp('y=x*2.0'))
root.connect('C1.y', 'C3.x')
root.connect('C3.y', 'C2.x')
root.connect('C2.y', 'C1.x')
p.setup(check=False)
self.assertEqual(p.root.list_auto_order(), ['C1', 'C3', 'C2'])
def test_incompatible_units(self):
prob = Problem()
prob.root = Group()
prob.root.add(
'uc',
UnitComp(shape=1, param_name='in', out_name='out', units='degC'))
prob.root.add('pc', ParamComp('x', 0., units='ft'))
prob.root.connect('pc.x', 'uc.in')
with self.assertRaises(TypeError) as cm:
prob.setup(check=False)
expected_msg = "Unit 'ft' in source 'pc.x' is incompatible with unit 'degC' in target 'uc.in'."
self.assertEqual(expected_msg, str(cm.exception))
def test_invalid_unit(self):
prob = Problem()
prob.root = Group()
prob.root.add(
'uc',
UnitComp(shape=1, param_name='in', out_name='out', units='junk'))
prob.root.add('pc', ParamComp('x', 0., units='ft'))
prob.root.connect('pc.x', 'uc.in')
with self.assertRaises(ValueError) as cm:
prob.setup(check=False)
expected_msg = "no unit named 'junk' is defined"
self.assertEqual(expected_msg, str(cm.exception))
def test_input_input_explicit_conns_no_conn(self):
prob = Problem(root=Group())
root = prob.root
root.add('p1', ParamComp('x', 1.0))
root.add('c1', ExecComp('y = x*2.0'))
root.add('c2', ExecComp('y = x*3.0'))
root.connect('c1.x', 'c2.x')
# ignore warning about the unconnected params
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("ignore")
prob.setup(check=False)
prob.run()
self.assertEqual(root.connections, {})
def test_check_promotes(self):
# verify we get an error at setup time if we have promoted a var that doesn't exist
# valid case, no error
prob = Problem(Group())
G = prob.root.add('G', Group())
C = G.add('C', SimpleComp(), promotes=['x*', 'y'])
# ignore warning about the unconnected param
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("ignore")
prob.setup(check=False)
# promoting a non-existent variable should throw an error
prob = Problem(Group())
G = prob.root.add('G', Group())
C = G.add('C', SimpleComp(), promotes=['spoon']) # there is no spoon
try:
prob.setup(check=False)
except Exception as error:
msg = "'C' promotes 'spoon' but has no variables matching that specification"
self.assertEqual(text_type(error), msg)
else:
self.fail("Error expected")
# promoting a pattern with no matches should throw an error
prob = Problem(Group())
G = prob.root.add('G', Group())
P = G.add('P', ParamComp('x', 5.),
promotes=['a*']) # there is no match
try:
prob.setup(check=False)
except Exception as error:
msg = "'P' promotes 'a*' but has no variables matching that specification"
self.assertEqual(text_type(error), msg)
else:
self.fail("Error expected")
def test_subsystem_access(self):
prob = Problem(root=ExampleGroup())
root = prob.root
self.assertEqual(root.G2, prob.root.G2)
self.assertEqual(root.G2.C1, prob.root.C1)
self.assertEqual(root.G2.G1, prob.root.G1)
self.assertEqual(root.G2.G1.C2, prob.root.C2)
self.assertEqual(root.G3, prob.root.G3)
self.assertEqual(root.G3.C3, prob.root.C3)
self.assertEqual(root.G3.C4, prob.root.C4)
prob = Problem(root=ExampleGroupWithPromotes())
root = prob.root
self.assertEqual(root.G2, prob.root.G2)
self.assertEqual(root.G2.C1, prob.root.C1)
self.assertEqual(root.G2.G1, prob.root.G1)
self.assertEqual(root.G2.G1.C2, prob.root.C2)
self.assertEqual(root.G3, prob.root.G3)
self.assertEqual(root.G3.C3, prob.root.C3)
self.assertEqual(root.G3.C4, prob.root.C4)
def test_sellar_group(self):
prob = Problem()
prob.root = SellarDerivativesGrouped()
prob.root.nl_solver = NLGaussSeidel()
prob.root.nl_solver.options['atol'] = 1e-9
prob.root.mda.nl_solver.options['atol'] = 1e-3
prob.root.nl_solver.options[
'iprint'] = 1 # so that print_norm is in coverage
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['y1'], 25.58830273, .00001)
assert_rel_error(self, prob['y2'], 12.05848819, .00001)
def test_direct_solver_comp(self):
"""
Test the direct solver on a component.
"""
for jac in ['dict', 'coo', 'csr', 'csc', 'dense']:
prob = Problem(model=ImplComp4Test())
prob.model.nonlinear_solver = NewtonSolver()
prob.model.linear_solver = DirectSolver()
prob.set_solver_print(level=0)
if jac == 'dict':
pass
elif jac == 'csr':
prob.model.jacobian = CSRJacobian()
elif jac == 'csc':
prob.model.jacobian = CSCJacobian()
elif jac == 'coo':
prob.model.jacobian = COOJacobian()
elif jac == 'dense':
prob.model.jacobian = DenseJacobian()
prob.setup(check=False)
if jac == 'coo':
with self.assertRaises(Exception) as context:
prob.run_model()
self.assertEqual(
str(context.exception),
"Direct solver is not compatible with matrix type COOMatrix in system ''."
)
continue
prob.run_model()
assert_rel_error(self, prob['y'], [-1., 1.])
d_inputs, d_outputs, d_residuals = prob.model.get_linear_vectors()
d_residuals.set_const(2.0)
d_outputs.set_const(0.0)
prob.model.run_solve_linear(['linear'], 'fwd')
result = d_outputs.get_data()
assert_rel_error(self, result, [-2., 2.])
d_outputs.set_const(2.0)
d_residuals.set_const(0.0)
prob.model.run_solve_linear(['linear'], 'rev')
result = d_residuals.get_data()
assert_rel_error(self, result, [2., -2.])
def test_implicit_component(self, m):
self.setup_endpoints(m)
from openmdao.core.tests.test_impl_comp import QuadraticLinearize, QuadraticJacVec
group = Group()
group.add_subsystem('comp1', IndepVarComp([('a', 1.0), ('b', 1.0), ('c', 1.0)]))
group.add_subsystem('comp2', QuadraticLinearize())
group.add_subsystem('comp3', QuadraticJacVec())
group.connect('comp1.a', 'comp2.a')
group.connect('comp1.b', 'comp2.b')
group.connect('comp1.c', 'comp2.c')
group.connect('comp1.a', 'comp3.a')
group.connect('comp1.b', 'comp3.b')
group.connect('comp1.c', 'comp3.c')
prob = Problem(model=group)
prob.setup(check=False)
prob['comp1.a'] = 1.
prob['comp1.b'] = -4.
prob['comp1.c'] = 3.
comp2 = prob.model.comp2 # ImplicitComponent
comp2.recording_options['record_metadata'] = False
comp2.add_recorder(self.recorder)
t0, t1 = run_driver(prob)
prob.cleanup()
upload(self.filename, self._accepted_token)
expected_inputs = [
{'name': 'comp2.a', 'values': [1.0]},
{'name': 'comp2.b', 'values': [-4.0]},
{'name': 'comp2.c', 'values': [3.0]}
]
expected_outputs = [{'name': 'comp2.x', 'values': [3.0]}]
expected_residuals = [{'name': 'comp2.x', 'values': [0.0]}]
system_iteration = json.loads(self.system_iterations)
for i in expected_inputs:
self.assert_array_close(i, system_iteration['inputs'])
for r in expected_residuals:
self.assert_array_close(r, system_iteration['residuals'])
for o in expected_outputs:
self.assert_array_close(o, system_iteration['outputs'])
def test_simple_matvec(self):
group = Group()
group.add('x_param', ParamComp('x', 1.0), promotes=['*'])
group.add('mycomp', SimpleCompDerivMatVec(), promotes=['x', 'y'])
prob = Problem()
prob.root = group
prob.root.ln_solver = LinearGaussSeidel()
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(['x'], ['y'], mode='fwd', return_format='dict')
assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6)
J = prob.calc_gradient(['x'], ['y'], mode='rev', return_format='dict')
assert_rel_error(self, J['y']['x'][0][0], 2.0, 1e-6)
def test_view_model_from_sqlite(self):
"""
Test that an n2 html file is generated from a sqlite file.
"""
p = Problem()
p.model = SellarStateConnection()
r = SqliteRecorder(self.sqlite_db_filename2)
p.driver.add_recorder(r)
p.setup(check=False)
p.final_setup()
r.shutdown()
view_model(self.sqlite_db_filename2, outfile=self.sqlite_filename, show_browser=False)
# Check that the html file has been created and has something in it.
self.assertTrue(os.path.isfile(self.sqlite_html_filename), (self.problem_html_filename + " is not a valid file."))
self.assertGreater(os.path.getsize(self.sqlite_html_filename), 100)
