def test_explicit_connection_errors(self):
class A(Component):
def __init__(self):
super(A, self).__init__()
self.add_state('x', 0)
class B(Component):
def __init__(self):
super(B, self).__init__()
self.add_param('x', 0)
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'B.x')
prob.setup(check=False)
expected_error_message = (
"Source 'A.y' cannot be connected to target 'B.x': "
"'A.y' does not exist.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.y', 'B.x')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
expected_error_message = (
"Source 'A.x' cannot be connected to target 'B.y': "
"'B.y' does not exist.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'B.y')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
expected_error_message = (
"Source 'A.x' cannot be connected to target 'A.x': "
"Target must be a parameter but 'A.x' is an unknown.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'A.x')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
def test_incompatible_connections(self):
class BadComp(Component):
def __init__(self):
super(BadComp, self).__init__()
self.add_param('x2', 100.0, units='m')
self.add_output('x3', 100.0)
# Explicit Connection
prob = Problem()
prob.root = Group()
prob.root.add('src', SrcComp())
prob.root.add('dest', BadComp())
prob.root.connect('src.x2', 'dest.x2')
with self.assertRaises(TypeError) as cm:
prob.setup(check=False)
expected_msg = "Unit 'degC' in source 'src.x2' is incompatible with unit 'm' in target 'dest.x2'."
self.assertEqual(str(cm.exception), expected_msg)
# Implicit Connection
prob = Problem()
prob.root = Group()
prob.root.add('src', SrcComp(), promotes=['x2'])
prob.root.add('dest', BadComp(),promotes=['x2'])
with self.assertRaises(TypeError) as cm:
prob.setup(check=False)
expected_msg = "Unit 'degC' in source 'x2' is incompatible with unit 'm' in target 'x2'."
self.assertEqual(str(cm.exception), expected_msg)
def test_incompatible_connections(self):
class BadComp(Component):
def __init__(self):
super(BadComp, self).__init__()
self.add_param('x2', 100.0, units='m')
self.add_output('x3', 100.0)
# Explicit Connection
prob = Problem()
prob.root = Group()
prob.root.add('src', SrcComp())
prob.root.add('dest', BadComp())
prob.root.connect('src.x2', 'dest.x2')
with self.assertRaises(TypeError) as cm:
prob.setup(check=False)
expected_msg = "Unit 'degC' in source 'src.x2' is incompatible with unit 'm' in target 'dest.x2'."
self.assertEqual(str(cm.exception), expected_msg)
# Implicit Connection
prob = Problem()
prob.root = Group()
prob.root.add('src', SrcComp(), promotes=['x2'])
prob.root.add('dest', BadComp(),promotes=['x2'])
with self.assertRaises(TypeError) as cm:
prob.setup(check=False)
expected_msg = "Unit 'degC' in source 'x2' is incompatible with unit 'm' in target 'x2'."
self.assertEqual(str(cm.exception), expected_msg)
def test_explicit_connection_errors(self):
class A(Component):
def __init__(self):
super(A, self).__init__()
self.add_state('x', 0)
class B(Component):
def __init__(self):
super(B, self).__init__()
self.add_param('x', 0)
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'B.x')
prob.setup(check=False)
expected_error_message = ("Source 'A.y' cannot be connected to target 'B.x': "
"'A.y' does not exist.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.y', 'B.x')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
expected_error_message = ("Source 'A.x' cannot be connected to target 'B.y': "
"'B.y' does not exist.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'B.y')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
expected_error_message = ("Source 'A.x' cannot be connected to target 'A.x': "
"Target must be a parameter but 'A.x' is an unknown.")
prob = Problem()
prob.root = Group()
prob.root.add('A', A())
prob.root.add('B', B())
prob.root.connect('A.x', 'A.x')
with self.assertRaises(ConnectError) as cm:
prob.setup(check=False)
self.assertEqual(str(cm.exception), expected_error_message)
def test_read4(self):
# Variables on same line as header
namelist1 = "Testing\n" + \
" \n" + \
"&OPTION boolvar = T, arrayvar = 3.5, 7.76, 1.23\n" + \
"/\n"
outfile = open(self.filename, 'w')
outfile.write(namelist1)
outfile.close()
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
sb.set_filename(self.filename)
sb.parse_file()
sb.load_model()
self.assertEqual(top['my_comp.boolvar'], True)
self.assertEqual(top['my_comp.arrayvar'][0], 3.5)
namelist1 = "Testing\n" + \
" \n" + \
"$OPTION boolvar = T, arrayvar = 3.5, 7.76, 1.23, $END\n"
outfile = open(self.filename, 'w')
outfile.write(namelist1)
outfile.close()
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
sb.set_filename(self.filename)
sb.parse_file()
sb.load_model()
self.assertEqual(top['my_comp.boolvar'], True)
self.assertEqual(top['my_comp.arrayvar'][0], 3.5)
def test_simple_matvec(self):
class VerificationComp(SimpleCompDerivMatVec):
def jacobian(self, params, unknowns, resids):
raise RuntimeError("Derivative functions on this comp should not run.")
def apply_linear(self, params, unknowns, dparams, dunknowns,
dresids, mode):
raise RuntimeError("Derivative functions on this comp should not run.")
sub = Group()
sub.add('mycomp', VerificationComp())
prob = Problem()
prob.root = Group()
prob.root.add('sub', sub)
prob.root.add('x_param', IndepVarComp('x', 1.0))
prob.root.connect('x_param.x', "sub.mycomp.x")
sub.fd_options['force_fd'] = True
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(['x_param.x'], ['sub.mycomp.y'], mode='fwd',
return_format='dict')
assert_rel_error(self, J['sub.mycomp.y']['x_param.x'][0][0], 2.0, 1e-6)
J = prob.calc_gradient(['x_param.x'], ['sub.mycomp.y'], mode='rev',
return_format='dict')
assert_rel_error(self, J['sub.mycomp.y']['x_param.x'][0][0], 2.0, 1e-6)
def test_record_derivs_dicts(self):
if OPT is None:
raise unittest.SkipTest("pyoptsparse is not installed")
if OPTIMIZER is None:
raise unittest.SkipTest(
"pyoptsparse is not providing SNOPT or SLSQP")
prob = Problem()
prob.root = SellarDerivativesGrouped()
prob.driver = pyOptSparseDriver()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.opt_settings['ACC'] = 1e-9
prob.driver.options['print_results'] = False
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.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = False
self.recorder.options['record_derivs'] = True
prob.setup(check=False)
prob.run()
prob.cleanup()
hdf = h5py.File(self.filename, 'r')
deriv_group = hdf['rank0:SLSQP|1']['Derivs']
self.assertEqual(deriv_group.attrs['success'], 1)
self.assertEqual(deriv_group.attrs['msg'], '')
J1 = deriv_group['Derivatives']
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])
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J1[key1][key2][:], val2, .00001)
hdf.close()
def test_simple_deriv_xfer(self):
prob = Problem(impl=impl)
prob.root = FanInGrouped()
prob.setup(check=False)
prob.root.comp3.dpmat[None]['x1'] = 7.
prob.root.comp3.dpmat[None]['x2'] = 11.
prob.root._transfer_data(mode='rev', deriv=True)
if not MPI or self.comm.rank == 0:
self.assertEqual(prob.root.sub.comp1.dumat[None]['y'], 7.)
if not MPI or self.comm.rank == 1:
self.assertEqual(prob.root.sub.comp2.dumat[None]['y'], 11.)
prob.root.comp3.dpmat[None]['x1'] = 0.
prob.root.comp3.dpmat[None]['x2'] = 0.
self.assertEqual(prob.root.comp3.dpmat[None]['x1'], 0.)
self.assertEqual(prob.root.comp3.dpmat[None]['x2'], 0.)
prob.root._transfer_data(mode='fwd', deriv=True)
self.assertEqual(prob.root.comp3.dpmat[None]['x1'], 7.)
self.assertEqual(prob.root.comp3.dpmat[None]['x2'], 11.)
def test_bad_size(self):
class BadComp(SimpleArrayComp):
def jacobian(self, params, unknowns, resids):
"""Analytical derivatives"""
J = {}
J[('y', 'x')] = np.zeros((3, 3))
return J
prob = Problem()
prob.root = Group()
prob.root.add('comp', BadComp())
prob.root.add('p1', ParamComp('x', np.ones([2])))
prob.root.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.run()
try:
data = prob.check_partial_derivatives(out_stream=None)
except Exception as err:
msg = "Jacobian in component 'comp' between the" + \
" variables 'x' and 'y' is the wrong size. " + \
"It should be 2 by 2"
self.assertEqual(str(err), msg)
else:
self.fail("Error expected")
def test_full_model_fd_double_diamond_grouped(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.setup(check=False)
prob.run()
prob.root.fd_options['force_fd'] = True
param_list = ['sub1.comp1.x1']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp7.y1']['sub1.comp1.x1'][0][0], -40.75,
1e-6)
prob.root.fd_options['form'] = 'central'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp7.y1']['sub1.comp1.x1'][0][0], -40.75,
1e-6)
def test_bad_size(self):
class BadComp(SimpleArrayComp):
def jacobian(self, params, unknowns, resids):
"""Analytical derivatives"""
J = {}
J[('y', 'x')] = np.zeros((3, 3))
return J
prob = Problem()
prob.root = Group()
prob.root.add('comp', BadComp())
prob.root.add('p1', ParamComp('x', np.ones([2])))
prob.root.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.run()
try:
data = prob.check_partial_derivatives(out_stream=None)
except Exception as err:
msg = "Jacobian in component 'comp' between the" + \
" variables 'x' and 'y' is the wrong size. " + \
"It should be 2 by 2"
self.assertEqual(str(err), msg)
else:
self.fail("Error expected")
def test_fan_in_serial_sets(self):
prob = Problem(impl=impl)
prob.root = FanInGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.sub.ln_solver = LinearGaussSeidel()
# Parallel Groups
prob.driver.add_param('p1.x1')
prob.driver.add_param('p2.x2')
prob.driver.add_objective('comp3.y')
prob.setup(check=False)
prob.run()
param_list = ['p1.x1', 'p2.x2']
unknown_list = ['comp3.y']
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
def test_fan_out_serial_sets(self):
prob = Problem(impl=impl)
prob.root = FanOutGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.sub.ln_solver = LinearGaussSeidel()
# Parallel Groups
prob.driver.add_param('p.x')
prob.driver.add_constraint('c2.y')
prob.driver.add_constraint('c3.y')
prob.setup(check=False)
prob.run()
unknown_list = ['c2.y', 'c3.y']
param_list = ['p.x']
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
def test_fan_out_parallel_sets(self):
prob = Problem(impl=impl)
prob.root = FanOutGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.sub.ln_solver = LinearGaussSeidel()
# need to set mode to rev before setup. Otherwise the sub-vectors
# for the parallel set vars won't get allocated.
prob.root.ln_solver.options['mode'] = 'rev'
prob.root.sub.ln_solver.options['mode'] = 'rev'
# Parallel Groups
prob.driver.add_param('p.x')
prob.driver.add_constraint('c2.y')
prob.driver.add_constraint('c3.y')
prob.driver.parallel_derivs(['c2.y','c3.y'])
self.assertEqual(prob.driver.outputs_of_interest(),
[('c2.y','c3.y')])
prob.setup(check=False)
prob.run()
unknown_list = ['c2.y', 'c3.y']
param_list = ['p.x']
J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
def test_only_params_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['record_params'] = True
self.recorder.options['record_resids'] = False
self.recorder.options['record_unknowns'] = False
prob.setup(check=False)
t0, t1 = run_problem(prob)
self.recorder.close()
coordinate = ['Driver', (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)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, None, None),), self.eps)
def test_single_diamond_grouped(self):
prob = Problem()
prob.root = SingleDiamondGrouped()
prob.root.ln_solver = ScipyGMRES()
prob.setup(check=False)
prob.run()
param_list = ['p.x']
unknown_list = ['comp4.y1', 'comp4.y2']
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp4.y1']['p.x'][0][0], 25, 1e-6)
assert_rel_error(self, J['comp4.y2']['p.x'][0][0], -40.5, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['comp4.y1']['p.x'][0][0], 25, 1e-6)
assert_rel_error(self, J['comp4.y2']['p.x'][0][0], -40.5, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='fd',
return_format='dict')
assert_rel_error(self, J['comp4.y1']['p.x'][0][0], 25, 1e-6)
assert_rel_error(self, J['comp4.y2']['p.x'][0][0], -40.5, 1e-6)
def test_converge_diverge_groups(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.root.ln_solver = ScipyGMRES()
prob.setup(check=False)
prob.run()
# Make sure value is fine.
assert_rel_error(self, prob['comp7.y1'], -102.7, 1e-6)
param_list = ['p.x']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp7.y1']['p.x'][0][0], -40.75, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['comp7.y1']['p.x'][0][0], -40.75, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='fd',
return_format='dict')
assert_rel_error(self, J['comp7.y1']['p.x'][0][0], -40.75, 1e-6)
def test_fan_in_grouped(self):
prob = Problem()
prob.root = FanInGrouped()
prob.root.ln_solver = ScipyGMRES()
param_list = ['p1.x1', 'p2.x2']
unknown_list = ['comp3.y']
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
def test_double_arraycomp(self):
# Mainly testing a bug in the array return for multiple arrays
group = Group()
group.add('x_param1', ParamComp('x1', np.ones((2))), promotes=['*'])
group.add('x_param2', ParamComp('x2', np.ones((2))), promotes=['*'])
group.add('mycomp', DoubleArrayComp(), promotes=['*'])
prob = Problem()
prob.root = group
prob.root.ln_solver = ScipyGMRES()
prob.setup(check=False)
prob.run()
Jbase = group.mycomp.JJ
J = prob.calc_gradient(['x1', 'x2'], ['y1', 'y2'],
mode='fwd',
return_format='array')
diff = np.linalg.norm(J - Jbase)
assert_rel_error(self, diff, 0.0, 1e-8)
J = prob.calc_gradient(['x1', 'x2'], ['y1', 'y2'],
mode='fd',
return_format='array')
diff = np.linalg.norm(J - Jbase)
assert_rel_error(self, diff, 0.0, 1e-8)
J = prob.calc_gradient(['x1', 'x2'], ['y1', 'y2'],
mode='rev',
return_format='array')
diff = np.linalg.norm(J - Jbase)
assert_rel_error(self, diff, 0.0, 1e-8)
def test_index_error_messages_con(self):
prob = Problem()
prob.root = Group()
prob.root.fd_options['force_fd'] = True
prob.root.ln_solver.options['mode'] = 'auto'
prob.root.add('myparams', ParamComp('x', np.zeros(4)))
prob.root.add('rosen', Rosenbrock(4))
prob.root.connect('myparams.x', 'rosen.x')
prob.driver = MySimpleDriver()
prob.driver.add_param('myparams.x')
prob.driver.add_constraint('rosen.xxx', indices=[4])
prob.setup(check=False)
# Make sure we can't do this
with self.assertRaises(IndexError) as cm:
prob.run()
msg = "Index for constraint 'rosen.xxx' is out of bounds. "
msg += "Requested index: [4], "
msg += "Parameter shape: (4,)."
raised_error = str(cm.exception)
raised_error = raised_error.replace('(4L,', '(4,')
self.assertEqual(msg, raised_error)
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_only_resids_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['record_params'] = False
self.recorder.options['record_unknowns'] = False
self.recorder.options['record_resids'] = True
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = [0, 'Driver', (1, )]
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), None, None, expected_resids),), self.eps)
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 = ["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 = ["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_sublevel_record(self):
prob = Problem()
prob.root = ExampleGroup()
prob.root.G2.G1.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,), "G2", (1,), "G1", (1,)]
expected_params = [
("C2.x", 5.0)
]
expected_unknowns = [
("C2.y", 10.0)
]
expected_resids = [
("C2.y", 0.0)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params,
expected_unknowns, expected_resids),), self.eps)
def test_simple_matvec(self):
class VerificationComp(SimpleCompDerivMatVec):
def jacobian(self, params, unknowns, resids):
raise RuntimeError(
"Derivative functions on this comp should not run.")
def apply_linear(self, params, unknowns, dparams, dunknowns,
dresids, mode):
raise RuntimeError(
"Derivative functions on this comp should not run.")
sub = Group()
sub.add('mycomp', VerificationComp())
prob = Problem()
prob.root = Group()
prob.root.add('sub', sub)
prob.root.add('x_param', ParamComp('x', 1.0))
prob.root.connect('x_param.x', "sub.mycomp.x")
sub.fd_options['force_fd'] = True
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(['x_param.x'], ['sub.mycomp.y'],
mode='fwd',
return_format='dict')
assert_rel_error(self, J['sub.mycomp.y']['x_param.x'][0][0], 2.0, 1e-6)
J = prob.calc_gradient(['x_param.x'], ['sub.mycomp.y'],
mode='rev',
return_format='dict')
assert_rel_error(self, J['sub.mycomp.y']['x_param.x'][0][0], 2.0, 1e-6)
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.add_desvar('z', low=np.array([-10.0]),
high=np.array([10.0]),indices=[0])
prob.driver.add_desvar('x', low=0.0, high=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_driver_param_indices_snopt_force_fd_shift(self):
""" Testt driver param indices with pyOptSparse and force_fd=True
"""
prob = Problem()
prob.root = SellarStateConnection()
prob.root.fd_options['force_fd'] = True
prob.driver.add_desvar('z', low=np.array([-10.0, -10.0]),
high=np.array([10.0, 10.0]), indices=[1])
prob.driver.add_desvar('x', low=0.0, high=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_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', low=np.array([-10.0, 0.0]),
high=np.array([10.0, 10.0]))
prob.driver.add_desvar('x', low=0.0, high=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_includes_and_excludes(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['includes'] = ['comp1.*']
self.recorder.options['excludes'] = ["*.y2"]
prob.setup(check=False)
prob.run()
expected_params = [
("comp1.x1", 2.0)
]
expected_unknowns = [
("comp1.y1", 8.0)
]
expected_resids = [
("comp1.y1", 0.0)
]
expected = (expected_params, expected_unknowns, expected_resids)
self.assertDatasetEquals(
[(['Driver', (1,)], expected)],
self.eps
)
def test_driver_param_indices_snopt(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.add_desvar('z', low=np.array([-10.0]),
high=np.array([10.0]),indices=[0])
prob.driver.add_desvar('x', low=0.0, high=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_includes_and_excludes(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['includes'] = ['comp1.*']
self.recorder.options['excludes'] = ["*.y2"]
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,)]
expected_params = [
("comp1.x1", 2.0)
]
expected_unknowns = [
("comp1.y1", 8.0)
]
expected_resids = [
("comp1.y1", 0.0)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_only_params_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options["record_params"] = True
self.recorder.options["record_resids"] = False
self.recorder.options["record_unknowns"] = False
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = ["Driver", (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),
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, None, None),), self.eps)
def test_converge_diverge_groups(self):
prob = Problem()
prob.root = Group()
prob.root.add('sub', ConvergeDivergeGroups())
param_list = ['sub.p.x']
unknown_list = ['sub.comp7.y1']
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['sub.comp7.y1']['sub.p.x'][0][0], -40.75,
1e-6)
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['sub.comp7.y1']['sub.p.x'][0][0], -40.75,
1e-6)
def test_only_unknowns_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = [0, 'Driver', (1, )]
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)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), None, expected_unknowns, None),), self.eps)
def test_metadata_recorded(self):
prob = Problem(impl=impl)
prob.root = FanInGrouped()
rec = DumpRecorder(out=self.filename)
rec.options['record_metadata'] = True
rec.options['includes'] = ['p1.x1', 'p2.x2', 'comp3.y']
prob.driver.add_recorder(rec)
prob.setup(check=False)
rec.close()
with open(self.expected_filename, 'r') as dumpfile:
params = iteritems(prob.root.params)
unknowns = iteritems(prob.root.unknowns)
self.assertEqual("Metadata:\n", dumpfile.readline())
self.assertEqual("Params:\n", dumpfile.readline())
for name, metadata in params:
fmat = " {0}: {1}\n".format(name, metadata)
self.assertEqual(fmat, dumpfile.readline())
self.assertEqual("Unknowns:\n", dumpfile.readline())
for name, metadata in unknowns:
fmat = " {0}: {1}\n".format(name, metadata)
self.assertEqual(fmat, dumpfile.readline())
def test_fan_out_serial_sets(self):
prob = Problem(impl=impl)
prob.root = FanOutGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.sub.ln_solver = LinearGaussSeidel()
# Parallel Groups
prob.driver.add_desvar('p.x')
prob.driver.add_constraint('c2.y', upper=0.0)
prob.driver.add_constraint('c3.y', upper=0.0)
prob.setup(check=False)
prob.run()
unknown_list = ['c2.y', 'c3.y']
indep_list = ['p.x']
J = prob.calc_gradient(indep_list, unknown_list, mode='fwd', return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
J = prob.calc_gradient(indep_list, unknown_list, mode='rev', return_format='dict')
assert_rel_error(self, J['c2.y']['p.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['p.x'][0][0], 15.0, 1e-6)
def test_fan_in_serial_sets(self):
prob = Problem(impl=impl)
prob.root = FanInGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.sub.ln_solver = LinearGaussSeidel()
# Parallel Groups
prob.driver.add_desvar('p1.x1')
prob.driver.add_desvar('p2.x2')
prob.driver.add_objective('comp3.y')
prob.setup(check=False)
prob.run()
indep_list = ['p1.x1', 'p2.x2']
unknown_list = ['comp3.y']
J = prob.calc_gradient(indep_list, unknown_list, mode='rev', return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
J = prob.calc_gradient(indep_list, unknown_list, mode='fwd', return_format='dict')
assert_rel_error(self, J['comp3.y']['p1.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['comp3.y']['p2.x2'][0][0], 35.0, 1e-6)
def test_array2D_index_connection(self):
group = Group()
group.add('x_param', IndepVarComp('x', np.ones((2, 2))), promotes=['*'])
sub = group.add('sub', Group(), promotes=['*'])
sub.add('mycomp', ArrayComp2D(), promotes=['x', 'y'])
group.add('obj', ExecComp('b = a'))
group.connect('y', 'obj.a', src_indices=[3])
prob = Problem()
prob.root = group
prob.root.ln_solver = LinearGaussSeidel()
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(['x'], ['obj.b'], mode='fwd', return_format='dict')
Jbase = prob.root.sub.mycomp._jacobian_cache
assert_rel_error(self, Jbase[('y', 'x')][3][0], J['obj.b']['x'][0][0], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][1], J['obj.b']['x'][0][1], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][2], J['obj.b']['x'][0][2], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][3], J['obj.b']['x'][0][3], 1e-8)
J = prob.calc_gradient(['x'], ['obj.b'], mode='rev', return_format='dict')
Jbase = prob.root.sub.mycomp._jacobian_cache
assert_rel_error(self, Jbase[('y', 'x')][3][0], J['obj.b']['x'][0][0], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][1], J['obj.b']['x'][0][1], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][2], J['obj.b']['x'][0][2], 1e-8)
assert_rel_error(self, Jbase[('y', 'x')][3][3], J['obj.b']['x'][0][3], 1e-8)
def test_includes_and_excludes(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['includes'] = ['comp1.*']
self.recorder.options['excludes'] = ["*.y2"]
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,)]
expected_params = [
("comp1.x1", 2.0)
]
expected_unknowns = [
("comp1.y1", 8.0)
]
expected_resids = [
("comp1.y1", 0.0)
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps)
def test_calc_gradient_multiple_params(self):
prob = Problem()
prob.root = FanIn()
prob.setup(check=False)
prob.run()
param_list = ['p1.x1', 'p2.x2']
unknown_list = ['comp3.y']
# check that calc_gradient returns proper dict value when mode is 'fwd'
J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]]))
# check that calc_gradient returns proper array value when mode is 'fwd'
J = prob.calc_gradient(param_list, unknown_list, mode='fwd', return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
# check that calc_gradient returns proper dict value when mode is 'rev'
J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]]))
# check that calc_gradient returns proper array value when mode is 'rev'
J = prob.calc_gradient(param_list, unknown_list, mode='rev', return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
# check that calc_gradient returns proper dict value when mode is 'fd'
J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'], np.array([[ 35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'], np.array([[ -6.]]))
# check that calc_gradient returns proper array value when mode is 'fd'
J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
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_metadata_recorded(self):
prob = Problem(impl=impl)
prob.root = FanInGrouped()
rec = DumpRecorder(out=self.filename)
rec.options["record_metadata"] = True
rec.options["includes"] = ["p1.x1", "p2.x2", "comp3.y"]
prob.driver.add_recorder(rec)
prob.setup(check=False)
prob.cleanup()
with open(self.expected_filename, "r") as dumpfile:
params = iteritems(prob.root.params)
unknowns = iteritems(prob.root.unknowns)
self.assertEqual("Metadata:\n", dumpfile.readline())
self.assertEqual("Params:\n", dumpfile.readline())
for name, metadata in params:
fmat = " {0}: {1}\n".format(name, metadata)
self.assertEqual(fmat, dumpfile.readline())
self.assertEqual("Unknowns:\n", dumpfile.readline())
for name, metadata in unknowns:
fmat = " {0}: {1}\n".format(name, metadata)
self.assertEqual(fmat, dumpfile.readline())
def test_unsupported_array(self):
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
top['my_comp.arrayvar'] = zeros([2, 2, 2], dtype=numpy_float32)
sb.set_filename(self.filename)
sb.add_group('Test')
sb.add_var("arrayvar")
try:
sb.generate()
except RuntimeError as err:
self.assertEqual(str(err),
"Don't know how to handle array of" + \
" 3 dimensions")
else:
self.fail('RuntimeError expected')
def test_index_error_messages_con(self):
prob = Problem()
prob.root = Group()
prob.root.fd_options['force_fd'] = True
prob.root.ln_solver.options['mode'] = 'auto'
prob.root.add('myparams', IndepVarComp('x', np.zeros(4)))
prob.root.add('rosen', Rosenbrock(4))
prob.root.connect('myparams.x', 'rosen.x')
prob.driver = MySimpleDriver()
prob.driver.add_desvar('myparams.x')
prob.driver.add_constraint('rosen.xxx', upper=0.0, indices=[4])
prob.setup(check=False)
# Make sure we can't do this
with self.assertRaises(IndexError) as cm:
prob.run()
msg = "Index for constraint 'rosen.xxx' is out of bounds. "
msg += "Requested index: [4], "
msg += "shape: (4,)."
raised_error = str(cm.exception)
raised_error = raised_error.replace('(4L,', '(4,')
self.assertEqual(msg, raised_error)
def test_2Darray_read(self):
namelist1 = "Testing\n" + \
"$GROUP\n" + \
" arrayvartwod(1,1) = 12, 24, 36\n" + \
" arrayvartwod(1,2) = 33, 66, 99\n" + \
"$END\n"
outfile = open(self.filename, 'w')
outfile.write(namelist1)
outfile.close()
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
sb.set_filename(self.filename)
sb.parse_file()
sb.load_model()
# Unchanged
self.assertEqual(top['my_comp.arrayvartwod'][0][0], 12)
self.assertEqual(top['my_comp.arrayvartwod'][1][2], 99)
def test_2Darray_write(self):
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
top['my_comp.arrayvar'] = zeros([3, 2], dtype=numpy_float32)
top['my_comp.arrayvar'][0, 1] = 3.7
top['my_comp.arrayvar'][2, 0] = 7.88
sb.set_filename(self.filename)
sb.add_group('Test')
sb.add_var("arrayvar")
sb.generate()
f = open(self.filename, 'r')
contents = f.read()
compare = "\n" + \
"&Test\n" + \
" arrayvar(1,1) = 0.0, 3.700000047683716, \n" + \
"arrayvar(1,2) = 0.0, 0.0, \n" + \
"arrayvar(1,3) = 7.880000114440918, 0.0, \n" + \
"/\n"
self.assertEqual(contents, compare)
def test_read3(self):
# Parse a single group in a deck with non-unique group names
namelist1 = "Testing\n" + \
"$GROUP\n" + \
" intvar = 99\n" + \
"$END\n" + \
"$GROUP\n" + \
" floatvar = 3.5e-23\n" + \
"$END\n"
outfile = open(self.filename, 'w')
outfile.write(namelist1)
outfile.close()
top = Problem()
top.root = Group()
top.root.add('my_comp', VarComponent())
top.setup(check=False)
top.run()
sb = Namelist(top.root.my_comp)
sb.set_filename(self.filename)
sb.parse_file()
sb.load_model(single_group=1)
# Unchanged
self.assertEqual(top['my_comp.intvar'], 333)
# Changed
self.assertEqual(top['my_comp.floatvar'], 3.5e-23)
def test_only_resids_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options["record_params"] = False
self.recorder.options["record_unknowns"] = False
self.recorder.options["record_resids"] = True
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = ["Driver", (1,)]
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), None, None, expected_resids),), self.eps)
def test_too_few_procs(self):
size = 3
group = Group()
group.add('P', IndepVarComp('x', numpy.ones(size)))
group.add('C1', DistribExecComp(['y=2.0*x'], arr_size=size,
x=numpy.zeros(size),
y=numpy.zeros(size)))
group.add('C2', ExecComp(['z=3.0*y'], y=numpy.zeros(size),
z=numpy.zeros(size)))
prob = Problem(impl=impl)
prob.root = group
prob.root.ln_solver = LinearGaussSeidel()
prob.root.connect('P.x', 'C1.x')
prob.root.connect('C1.y', 'C2.y')
try:
prob.setup(check=False)
except Exception as err:
self.assertEqual(str(err),
"This problem was given 1 MPI processes, "
"but it requires between 2 and 2.")
else:
if MPI: # pragma: no cover
self.fail("Exception expected")
def test_src_indices_error(self):
size = 3
group = Group()
group.add('P', IndepVarComp('x', numpy.ones(size)))
group.add('C1', DistribExecComp(['y=2.0*x'], arr_size=size,
x=numpy.zeros(size),
y=numpy.zeros(size)))
group.add('C2', ExecComp(['z=3.0*y'], y=numpy.zeros(size),
z=numpy.zeros(size)))
prob = Problem(impl=impl)
prob.root = group
prob.root.ln_solver = LinearGaussSeidel()
prob.root.connect('P.x', 'C1.x')
prob.root.connect('C1.y', 'C2.y')
prob.driver.add_desvar('P.x')
prob.driver.add_objective('C1.y')
try:
prob.setup(check=False)
except Exception as err:
self.assertEqual(str(err),
"'C1.y' is a distributed variable and may not be used as a "
"design var, objective, or constraint.")
else:
if MPI: # pragma: no cover
self.fail("Exception expected")
def test_array_values(self):
prob = Problem()
prob.root = Group()
prob.root.add('pc',
ParamComp('x', np.zeros((2, 3)), units='degC'),
promotes=['x'])
prob.root.add('uc',
UnitComp(shape=(2, 3),
param_name='x',
out_name='x_out',
units='degF'),
promotes=['x', 'x_out'])
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['x_out'],
np.array([[32., 32., 32.], [32., 32., 32.]]), 1e-6)
param_list = ['x']
unknown_list = ['x_out']
# Forward Mode
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
assert_rel_error(self, J['x_out']['x'], 1.8 * np.eye(6), 1e-6)
# Reverse Mode
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
assert_rel_error(self, J['x_out']['x'], 1.8 * np.eye(6), 1e-6)
def test_only_unknowns_recorded(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
prob.setup(check=False)
t0, t1 = run_problem(prob)
prob.cleanup() # closes recorders
coordinate = ["Driver", (1,)]
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),
]
self.assertIterationDataRecorded(((coordinate, (t0, t1), None, expected_unknowns, None),), self.eps)
def test_calc_gradient_multiple_params(self):
prob = Problem()
prob.root = FanIn()
prob.setup(check=False)
prob.run()
param_list = ['p1.x1', 'p2.x2']
unknown_list = ['comp3.y']
# check that calc_gradient returns proper dict value when mode is 'fwd'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'],
np.array([[35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'],
np.array([[-6.]]))
# check that calc_gradient returns proper array value when mode is 'fwd'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fwd',
return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
# check that calc_gradient returns proper dict value when mode is 'rev'
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'],
np.array([[35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'],
np.array([[-6.]]))
# check that calc_gradient returns proper array value when mode is 'rev'
J = prob.calc_gradient(param_list,
unknown_list,
mode='rev',
return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
# check that calc_gradient returns proper dict value when mode is 'fd'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fd',
return_format='dict')
np.testing.assert_almost_equal(J['comp3.y']['p2.x2'],
np.array([[35.]]))
np.testing.assert_almost_equal(J['comp3.y']['p1.x1'],
np.array([[-6.]]))
# check that calc_gradient returns proper array value when mode is 'fd'
J = prob.calc_gradient(param_list,
unknown_list,
mode='fd',
return_format='array')
np.testing.assert_almost_equal(J, np.array([[-6., 35.]]))
def test_subsolver_doesnt_record_metadata(self):
prob = Problem()
prob.root = ExampleGroup()
prob.root.G2.G1.nl_solver.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = False
prob.setup(check=False)
prob.cleanup() # closes recorders
self.assertMetadataRecorded(None)
def test_driver_doesnt_record_metadata(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.driver.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = False
prob.setup(check=False)
prob.cleanup() # closes recorders
self.assertMetadataRecorded(None)
def test_root_solver_doesnt_record_metadata(self):
prob = Problem()
prob.root = ConvergeDiverge()
prob.root.nl_solver.add_recorder(self.recorder)
self.recorder.options['record_metadata'] = False
prob.setup(check=False)
self.recorder.close()
self.assertMetadataRecorded(None)
def test_unknown_vec(self):
top = Problem()
top.root = Group()
top.root.add('comp', ArrayComp2D(), promotes=['x', 'y'])
top.root.add('p1',
IndepVarComp('x', np.array([[1.0, 2.0], [3.0, 4.0]])),
promotes=['x'])
top.root.add('comp2', SimpleComp())
top.root.add('p2', IndepVarComp('x', 3.0))
top.root.connect('p2.x', 'comp2.x')
top.setup(check=False)
top.run()
unknowns = ComplexStepSrcVecWrapper(top.root.comp.unknowns)
# Unknowns are always complex
y = unknowns['y']
self.assertTrue(y.dtype == np.complex)
self.assertEquals(y[0, 1], 46.0 + 0j)
# Set an unknown
unknowns['y'][0, 1] = 13.0 + 17.0j
self.assertEquals(unknowns['y'][0, 1], 13.0 + 17.0j)
# Extract flat var
cval = unknowns.flat('y')
self.assertEquals(cval[1], 13.0 + 17.0j)
self.assertEquals(cval.shape[0], 4)
unknowns = ComplexStepSrcVecWrapper(top.root.comp2.unknowns)
# Unknowns are always complex
y = unknowns['y']
self.assertTrue(y.dtype == np.complex)
self.assertEquals(y, 6.0 + 0j)
# Set an unknown
unknowns['y'] = 13.0 + 17.0j
self.assertEquals(unknowns['y'], 13.0 + 17.0j)
# Extract flat var
cval = unknowns.flat('y')
self.assertEquals(cval, 13.0 + 17.0j)
self.assertEquals(cval.shape[0], 1)
# Make sure all other functions work for coverage
self.assertEquals(len(unknowns), 1)
self.assertTrue('y' in unknowns)
plist = [z for z in unknowns]
self.assertEquals(plist, ['y'])
self.assertEquals(unknowns.keys(), top.root.comp2.unknowns.keys())
self.assertEquals(unknowns.metadata('y'),
top.root.comp2.unknowns.metadata('y'))
plist1 = [z for z in unknowns.iterkeys()]
plist2 = [z for z in top.root.comp2.unknowns.iterkeys()]
def test_multilevel_record(self):
# FIXME: this test fails with the csv recorder
self.recorder.close()
raise unittest.SkipTest('This is not supported by the csv recorder yet.')
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)
self.recorder.close()
solver_coordinate = ['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 = ['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_sellar_derivs(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.ln_solver.options['maxiter'] = 4
prob.root.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']
param_list = ['x']
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')
print(J)
#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')
print(J)
#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')
print(J)
#for key1, val1 in Jbase.items():
#for key2, val2 in val1.items():
#assert_rel_error(self, J[key1][key2], val2, .00001)
# Obviously this test doesn't do much right now, but I need to verify
# we don't get a keyerror here.
J = prob.calc_gradient(param_list, unknown_list, mode='fd', return_format='array')
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))
