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_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_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_unconnected_param_access_with_promotes(self):
prob = Problem(root=Group())
G1 = prob.root.add('G1', Group())
G2 = G1.add('G2', Group(), promotes=['x'])
C1 = G2.add('C1', ExecComp(['y=2.0*x',
'z=x*x-2.0']), promotes=['x'])
C2 = G2.add('C2', ExecComp(['y=2.0*x',
'z=x*x-2.0']))
G2.connect('C1.y', 'C2.x')
# ignore warning about the unconnected param
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("ignore")
prob.setup(check=False)
prob.run()
# still must use absolute naming to find params even if they're
# promoted. Promoted names for params can refer to more than one param.
C1.params['x'] = 2.
self.assertEqual(prob['G1.x'], 2.0)
self.assertEqual(prob.root.G1.G2.C1.params['x'], 2.0)
prob['G1.x'] = 99.
self.assertEqual(C1.params['x'], 99.)
prob['G1.x'] = 12.
self.assertEqual(C1.params['x'], 12.)
prob['G1.x'] = 17.
self.assertEqual(prob.root.G1.G2.C1.params['x'], 17.0)
prob.run()
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_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_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_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_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_conflicting_connections(self):
# verify we get an error if we have conflicting implicit and explicit connections
root = Group()
# promoting G1.x will create an implicit connection to G3.x
# this is a conflict because G3.x (aka G3.C4.x) is already connected
# to G3.C3.x
G2 = root.add('G2', Group(), promotes=['x']) # BAD PROMOTE
G2.add('C1', ParamComp('x', 5.), promotes=['x'])
G1 = G2.add('G1', Group(), promotes=['x'])
G1.add('C2', ExecComp('y=x*2.0'), promotes=['x'])
G3 = root.add('G3', Group(), promotes=['x'])
G3.add('C3', ExecComp('y=x*2.0'))
G3.add('C4', ExecComp('y=x*2.0'), promotes=['x'])
root.connect('G2.G1.C2.y', 'G3.C3.x')
G3.connect('C3.y', 'x')
prob = Problem(root)
try:
prob.setup(check=False)
except Exception as error:
msg = "Target 'G3.C4.x' is connected to multiple unknowns: ['G2.C1.x', 'G3.C3.y']"
self.assertEqual(text_type(error), msg)
else:
self.fail("Error expected")
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_variable_access(self):
prob = Problem(root=ExampleGroup())
# set with a different shaped array
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)
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
prob = Problem(root=ExampleGroupWithPromotes())
prob.setup(check=False)
self.assertEqual(prob.root.G2.G1.C2.params['x'], 0.) # initial value for a parameter
# __setitem__
prob['G2.G1.C2.y'] = 99.
self.assertEqual(prob['G2.G1.C2.y'], 99.)
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_byobj_run(self):
prob = Problem(root=ExampleByObjGroup())
prob.setup(check=False)
prob.run()
self.assertEqual(prob['G3.C4.y'], 'fooC2C3C4')
def test_basic_run(self):
prob = Problem(root=ExampleGroup())
prob.setup(check=False)
prob.run()
self.assertAlmostEqual(prob['G3.C4.y'], 40.)
def test_mode_auto(self):
# Make sure mode=auto chooses correctly for all prob sizes as well
# as for abs/rel/etc paths
prob = Problem()
root = prob.root = Group()
root.add('p1', ParamComp('a', 1.0), promotes=['*'])
root.add('p2', ParamComp('b', 1.0), promotes=['*'])
root.add('comp', ExecComp(['x = 2.0*a + 3.0*b', 'y=4.0*a - 1.0*b']), promotes=['*'])
root.ln_solver.options['mode'] = 'auto'
prob.setup(check=False)
prob.run()
mode = prob._mode('auto', ['a'], ['x'])
self.assertEqual(mode, 'fwd')
mode = prob._mode('auto', ['a', 'b'], ['x'])
self.assertEqual(mode, 'rev')
# make sure _check function does it too
#try:
#mode = prob._check_for_matrix_matrix(['a'], ['x'])
#except Exception as err:
#msg = "Group '' must have the same mode as root to use Matrix Matrix."
#self.assertEqual(text_type(err), msg)
#else:
#self.fail('Exception expected')
root.ln_solver.options['mode'] = 'fwd'
mode = prob._check_for_matrix_matrix(['a', 'b'], ['x'])
self.assertEqual(mode, 'fwd')
def test_fd_skip_keys(self):
prob = Problem()
root = prob.root = Group()
comp = Component()
comp.add_param('x', 0.)
comp.add_param('y', 0.)
comp.add_output('z', 0.)
comp.solve_nonlinear = lambda p, u, r: u.__setitem__('z', 1.)
comp._get_fd_params = lambda: ['x']
comp.jacobian = lambda a,b,c: {('z', 'x'): 0.}
root.add('comp', comp, promotes=['x', 'y'])
root.add('px', ParamComp('x', 0.), promotes=['*'])
root.add('py', ParamComp('y', 0.), promotes=['*'])
prob.setup(check=False)
prob.run()
try:
prob.check_partial_derivatives()
except KeyError as err:
self.fail('KeyError raised: {0}'.format(str(err)))
def test_conflicting_promotions(self):
# verify we get an error if we have conflicting promotions
root = Group()
# promoting G1.x will create an implicit connection to G3.x
# this is a conflict because G3.x (aka G3.C4.x) is already connected
# to G3.C3.x
G2 = root.add('G2', Group())
G2.add('C1', ParamComp('x', 5.), promotes=['x'])
G1 = G2.add('G1', Group(), promotes=['x'])
G1.add('C2', ExecComp('y=x*2.0'), promotes=['x'])
G3 = root.add('G3', Group(), promotes=['x'])
G3.add('C3', ExecComp('y=x*2.0'), promotes=['y']) # promoting y
G3.add('C4', ExecComp('y=x*2.0'), promotes=['x', 'y']) # promoting y again.. BAD
prob = Problem(root)
try:
prob.setup(check=False)
except Exception as error:
msg = "Promoted name 'G3.y' matches multiple unknowns: ['G3.C3.y', 'G3.C4.y']"
self.assertEqual(text_type(error), msg)
else:
self.fail("Error expected")
def test_driver_records_metadata(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_metadata'] = True
prob.setup(check=False)
prob.cleanup()
expected = (
list(prob.root.params.iteritems()),
list(prob.root.unknowns.iteritems()),
list(prob.root.resids.iteritems()),
)
self.assertMetadataRecorded(expected)
def test_splitterW(self):
g = Group()
p = Problem(root=g)
comp = g.add('comp', SplitterW())
p.setup(check=False)
comp.params['W1_des'] = 1.08
comp.params['MNexit1_des'] = 1.0
comp.params['MNexit2_des'] = 1.0
comp.params['design'] = True
comp.params['flow_in:in:W'] = 3.48771299
comp.params['flow_in:in:Tt'] = 630.74523
comp.params['flow_in:in:Pt'] = 0.0271945
comp.params['flow_in:in:Mach'] = 1.0
p.run()
self.check(comp)
comp.params['design'] = False
comp.params['flow_out_1:in:is_super'] = True
comp.params['flow_out_2:in:is_super'] = True
p.run()
self.check(comp)
comp.params['flow_in:in:W'] *= 0.95
comp.params['flow_out_1:in:is_super'] = False
comp.params['flow_out_2:in:is_super'] = False
p.run()
TOL = 0.001
assert_rel_error(self, comp.unknowns['flow_out_1:out:Mach'], 0.76922, TOL)
assert_rel_error(self, comp.unknowns['flow_out_2:out:Mach'], 0.76922, TOL)
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_noncontiguous_idxs(self):
# take even input indices in 0 rank and odd ones in 1 rank
size = 11
p = Problem(root=Group(), impl=impl)
top = p.root
top.add("C1", InOutArrayComp(size))
top.add("C2", DistribNoncontiguousComp(size))
top.add("C3", DistribGatherComp(size))
top.connect('C1.outvec', 'C2.invec')
top.connect('C2.outvec', 'C3.invec')
p.setup(check=False)
top.C1.params['invec'] = np.array(range(size), float)
p.run()
if MPI:
if self.comm.rank == 0:
self.assertTrue(all(top.C2.unknowns['outvec'] == np.array(list(take_nth(0, 2, range(size))), 'f')*4))
else:
self.assertTrue(all(top.C2.unknowns['outvec'] == np.array(list(take_nth(1, 2, range(size))), 'f')*4))
full_list = list(take_nth(0, 2, range(size))) + list(take_nth(1, 2, range(size)))
self.assertTrue(all(top.C3.unknowns['outvec'] == np.array(full_list, 'f')*4))
else:
self.assertTrue(all(top.C2.unknowns['outvec']==top.C1.unknowns['outvec']*2.))
self.assertTrue(all(top.C3.unknowns['outvec']==top.C2.unknowns['outvec']))
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(model=SellarStateConnection())
p.setup(check=False)
model_viewer_data = _get_viewer_data(p)
# check expected model tree
self.assertDictEqual(model_viewer_data['tree'], self.expected_tree)
# check expected system pathnames
pathnames = model_viewer_data['sys_pathnames_list']
self.assertListEqual(sorted(pathnames), self.expected_pathnames)
# check expected connections, after mapping cycle_arrows indices back to pathnames
connections = model_viewer_data['connections_list']
for conn in connections:
if 'cycle_arrows' in conn:
cycle_arrows = []
for src, tgt in conn['cycle_arrows']:
cycle_arrows.append(' '.join([pathnames[src], pathnames[tgt]]))
conn['cycle_arrows'] = sorted(cycle_arrows)
self.assertListEqual(connections, self.expected_conns)
# check expected abs2prom map
self.assertDictEqual(model_viewer_data['abs2prom'], self.expected_abs2prom)
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_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_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_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_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_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_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_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_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_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_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_sellar_derivs(self):
prob = Problem()
prob.root = SellarDerivatives()
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['y2'], 12.05848819, .00001)
# Make sure we aren't iterating like crazy
self.assertLess(prob.root.nl_solver.iter_count, 8)
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_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_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 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_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_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_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_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_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_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_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_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)
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)
]
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_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_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)
def test_inp_inp_promoted_no_src(self):
p = Problem(root=Group())
root = p.root
G1 = root.add("G1", Group())
G2 = G1.add("G2", Group())
C1 = G2.add("C1", ExecComp('y=x*2.0'))
C2 = G2.add("C2", ExecComp('y=x*2.0'))
G3 = root.add("G3", Group())
G4 = G3.add("G4", Group())
C3 = G4.add("C3", ExecComp('y=x*2.0'), promotes=['x'])
C4 = G4.add("C4", ExecComp('y=x*2.0'), promotes=['x'])
stream = cStringIO()
checks = p.setup(out_stream=stream)
self.assertEqual(checks['dangling_params'],
['G1.G2.C1.x', 'G1.G2.C2.x', 'G3.G4.x'])
self.assertEqual(checks['no_connect_comps'],
['G1.G2.C1', 'G1.G2.C2', 'G3.G4.C3', 'G3.G4.C4'])
self.assertEqual(p._dangling['G3.G4.x'],
set(['G3.G4.C3.x', 'G3.G4.C4.x']))
# setting promoted name should set both params mapped to that name since the
# params are dangling.
p['G3.G4.x'] = 999.
self.assertEqual(p.root.G3.G4.C3.params['x'], 999.)
self.assertEqual(p.root.G3.G4.C4.params['x'], 999.)
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_simple_jac(self):
group = Group()
group.add('x_param', ParamComp('x', 1.0), promotes=['*'])
group.add('mycomp', ExecComp(['y=2.0*x']), promotes=['x', 'y'])
prob = Problem()
prob.root = group
prob.root.ln_solver = ScipyGMRES()
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_too_many_procs(self):
prob = Problem(Group(), impl=impl)
size = 5
A1 = prob.root.add('A1', ParamComp('a', np.zeros(size, float)))
C1 = prob.root.add('C1', ABCDArrayComp(size))
try:
prob.setup(check=False)
except Exception as err:
self.assertEqual(
str(err), "This problem was given 2 MPI processes, "
"but it requires between 1 and 1.")
else:
if MPI:
self.fail("Exception expected")
def test_solver_record(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.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(prob)
prob.cleanup()
if MPI:
coord = [MPI.COMM_WORLD.rank, 'Driver', (1, ), "root", (1,)]
else:
coord = [0, 'Driver', (1, ), "root", (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(((coord, (t0, t1), expected_params, expected_unknowns, expected_resids),), self.eps, prob.root)
def test_sellar_derivs_grouped(self):
prob = Problem()
prob.root = SellarDerivativesGrouped()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.ln_solver.options['maxiter'] = 15
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')
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)
def test_record_derivs_lists(self):
prob = Problem()
prob.root = SellarDerivativesGrouped()
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, 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']
assert_rel_error(self, J1[0][0], 9.61001155, .00001)
assert_rel_error(self, J1[0][1], 1.78448534, .00001)
assert_rel_error(self, J1[0][2], 2.98061392, .00001)
assert_rel_error(self, J1[1][0], -9.61002285, .00001)
assert_rel_error(self, J1[1][1], -0.78449158, .00001)
assert_rel_error(self, J1[1][2], -0.98061433, .00001)
assert_rel_error(self, J1[2][0], 1.94989079, .00001)
assert_rel_error(self, J1[2][1], 1.0775421, .00001)
assert_rel_error(self, J1[2][2], 0.09692762, .00001)
hdf.close()
def test_view_model_set_title(self):
"""
Test that an n2 html file is generated from a Problem.
"""
p = Problem()
p.model = SellarStateConnection()
p.setup()
view_model(p,
outfile=self.problem_html_filename,
show_browser=DEBUG,
title="Sellar State Connection")
# Check that the html file has been created and has something in it.
self.assertTrue(os.path.isfile(self.problem_html_filename),
(self.problem_html_filename + " is not a valid file."))
self.assertTrue( 'OpenMDAO Model Hierarchy and N2 diagram: Sellar State Connection' \
in open(self.problem_html_filename).read() )
def test_distrib_idx_in_full_out(self):
size = 11
p = Problem(root=Group(), impl=impl)
top = p.root
top.add("C1", InOutArrayComp(size))
top.add("C2", DistribInputComp(size))
top.connect('C1.outvec', 'C2.invec')
p.setup(check=False)
top.C1.params['invec'] = np.array(range(size, 0, -1), float)
p.run()
self.assertTrue(
all(top.C2.unknowns['outvec'] ==
np.array(range(size, 0, -1), float) * 4))
def test_double_diamond_model(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.setup(check=False)
prob.run()
data = prob.check_total_derivatives(out_stream=None)
for key, val in iteritems(data):
assert_rel_error(self, val['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, val['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, val['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, val['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, val['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, val['rel error'][2], 0.0, 1e-5)
def test_distrib_full_in_out(self):
size = 11
p = Problem(root=Group(), impl=impl)
top = p.root
top.add("C1", InOutArrayComp(size))
top.add("C2", DistribCompSimple(size))
top.connect('C1.outvec', 'C2.invec')
p.setup(check=False)
top.C1.params['invec'] = np.ones(size, float) * 5.0
p.run()
self.assertTrue(
all(top.C2.unknowns['outvec'] == np.ones(size, float) * 7.5))
