def test_fan_out_grouped(self, solv_tup, nlsolver):
prob = om.Problem(FanOutGrouped())
of = ['c2.y', "c3.y"]
wrt = ['iv.x']
solver, jactype = solv_tup
prob.model.linear_solver = solver()
if jactype is not None:
prob.model.options['assembled_jac_type'] = jactype
prob.model.nonlinear_solver = nlsolver()
prob.setup(check=False, mode='fwd')
prob.set_solver_print(level=0)
prob.run_model()
J = prob.compute_totals(of=['c2.y', "c3.y"], wrt=['iv.x'])
assert_near_equal(J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
assert_near_equal(prob['c2.y'], -6.0, 1e-6)
assert_near_equal(prob['c3.y'], 15.0, 1e-6)
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=['c2.y', "c3.y"], wrt=['iv.x'])
assert_near_equal(J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
assert_near_equal(prob['c2.y'], -6.0, 1e-6)
assert_near_equal(prob['c3.y'], 15.0, 1e-6)
def test_fan_out_parallel_sets_rev(self):
prob = om.Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('iv.x')
prob.model.add_constraint('c2.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.model.add_constraint('c3.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.setup(check=False, mode='rev')
prob.run_driver()
unknown_list = ['c2.y', 'c3.y']
indep_list = ['iv.x']
J = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict')
assert_near_equal(J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
# Piggyback to make sure the distributed norm calculation is correct.
vec = prob.model._vectors['residual']['c2.y']
norm_val = vec.get_norm()
# NOTE: BAN updated the norm value for the PR that added seed splitting, i.e.
# the seed, c2.y in this case, is half what it was before (-.5 vs. -1).
assert_near_equal(norm_val, 6.422616289332565, 1e-6)
def test_fan_out_parallel_sets_rev(self):
prob = Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = LinearBlockGS()
prob.model.sub.linear_solver = LinearBlockGS()
prob.model.add_design_var('iv.x')
prob.model.add_constraint('c2.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.model.add_constraint('c3.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.setup(vector_class=vector_class, check=False, mode='rev')
prob.run_driver()
unknown_list = ['c2.y', 'c3.y']
indep_list = ['iv.x']
J = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict')
assert_rel_error(self, J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
def test_fan_out_grouped(self):
prob = Problem(FanOutGrouped())
of = ['c2.y', "c3.y"]
wrt = ['iv.x']
prob.setup(check=False, mode='fwd')
prob.set_solver_print(level=0)
prob.run_model()
J = prob.compute_totals(of=['c2.y', "c3.y"], wrt=['iv.x'])
assert_rel_error(self, J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
assert_rel_error(self, prob['c2.y'], -6.0, 1e-6)
assert_rel_error(self, prob['c3.y'], 15.0, 1e-6)
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=['c2.y', "c3.y"], wrt=['iv.x'])
assert_rel_error(self, J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
assert_rel_error(self, prob['c2.y'], -6.0, 1e-6)
assert_rel_error(self, prob['c3.y'], 15.0, 1e-6)
def test_fan_out_parallel_sets_rev(self):
prob = om.Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('iv.x')
prob.model.add_constraint('c2.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.model.add_constraint('c3.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.setup(check=False, mode='rev')
prob.run_driver()
unknown_list = ['c2.y', 'c3.y']
indep_list = ['iv.x']
J = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict')
assert_near_equal(J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
# Piggyback to make sure the distributed norm calculation is correct.
vec = prob.model._vectors['residual']['linear']
norm_val = vec.get_norm()
# NOTE: BAN updated the norm value for the PR that removed vec_names vectors.
# the seeds for the constraints are now back to -1 instead of -.5
assert_near_equal(norm_val, 6.557438524302, 1e-6)
def test_fan_out_parallel_sets_rev(self):
prob = om.Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('iv.x')
prob.model.add_constraint('c2.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.model.add_constraint('c3.y',
upper=0.0,
parallel_deriv_color='par_resp')
prob.setup(check=False, mode='rev')
prob.run_driver()
unknown_list = ['c2.y', 'c3.y']
indep_list = ['iv.x']
J = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict')
assert_rel_error(self, J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
# Piggyback to make sure the distributed norm calculation is correct.
vec = prob.model._vectors['residual']['c2.y']
norm_val = vec.get_norm()
assert_rel_error(self, norm_val, 6.480740698, 1e-6)
def test_fan_out_grouped(self):
# Test derivatives for fan-out-grouped topology.
prob = Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = self.linear_solver_class()
prob.set_solver_print(level=0)
prob.setup(check=False, mode='fwd')
prob.run_model()
wrt = ['iv.x']
of = ['sub.c2.y', "sub.c3.y"]
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['sub.c2.y', 'iv.x'], [[-6.0]], 1e-6)
assert_near_equal(J['sub.c3.y', 'iv.x'], [[15.0]], 1e-6)
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['sub.c2.y', 'iv.x'], [[-6.0]], 1e-6)
assert_near_equal(J['sub.c3.y', 'iv.x'], [[15.0]], 1e-6)
def test_fan_out_serial_sets_rev(self):
prob = om.Problem()
prob.model = FanOutGrouped()
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('iv.x')
prob.model.add_constraint('c2.y', upper=0.0)
prob.model.add_constraint('c3.y', upper=0.0)
prob.setup(check=False, mode='rev')
prob.run_driver()
unknown_list = ['c3.y','c2.y'] #['c2.y', 'c3.y']
indep_list = ['iv.x']
J = prob.compute_totals(unknown_list, indep_list, return_format='flat_dict')
assert_near_equal(J['c2.y', 'iv.x'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x'][0][0], 15.0, 1e-6)
def test_parallel_list_vars(self):
print_opts = {'linewidth': 1024, 'precision': 1}
if LooseVersion(np.__version__) >= LooseVersion("1.14"):
print_opts['legacy'] = '1.13'
prob = om.Problem(FanOutGrouped())
# add another subsystem with similar prefix
prob.model.add_subsystem('sub2', om.ExecComp(['y=x']))
prob.model.connect('iv.x', 'sub2.x')
prob.setup()
prob.run_model()
#
# list inputs, not hierarchical
#
stream = StringIO()
with printoptions(**print_opts):
prob.model.list_inputs(values=True, hierarchical=False, out_stream=stream)
with multi_proc_exception_check(prob.comm):
if prob.comm.rank == 0: # Only rank 0 prints
text = stream.getvalue().split('\n')
expected = [
"6 Input(s) in 'model'",
'',
'varname val',
'-------- -----',
'c1.x',
'sub.c2.x',
'sub.c3.x',
'c2.x',
'c3.x',
'sub2.x'
]
for i, line in enumerate(expected):
if line and not line.startswith('-'):
self.assertTrue(text[i].startswith(line),
'\nExpected: %s\nReceived: %s\n' % (line, text[i]))
#
# list inputs, hierarchical
#
stream = StringIO()
with printoptions(**print_opts):
prob.model.list_inputs(values=True, hierarchical=True, out_stream=stream)
with multi_proc_exception_check(prob.comm):
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"6 Input(s) in 'model'",
'',
'varname val',
'------- -----',
'c1',
' x',
'sub',
' c2',
' x',
' c3',
' x',
'c2',
' x',
'c3',
' x',
'sub2',
' x'
]
for i, line in enumerate(expected):
if line and not line.startswith('-'):
self.assertTrue(text[i].startswith(line),
'\nExpected: %s\nReceived: %s\n' % (line, text[i]))
#
# list outputs, not hierarchical
#
stream = StringIO()
with printoptions(**print_opts):
prob.model.list_outputs(values=True, residuals=True, hierarchical=False, out_stream=stream)
with multi_proc_exception_check(prob.comm):
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"7 Explicit Output(s) in 'model'",
'',
'varname val resids',
'-------- ---- ------',
'iv.x',
'c1.y',
'sub.c2.y',
'sub.c3.y',
'c2.y',
'c3.y',
'sub2.y',
'',
'',
"0 Implicit Output(s) in 'model'",
]
for i, line in enumerate(expected):
if line and not line.startswith('-'):
self.assertTrue(text[i].startswith(line),
'\nExpected: %s\nReceived: %s\n' % (line, text[i]))
#
# list outputs, hierarchical
#
stream = StringIO()
with printoptions(**print_opts):
prob.model.list_outputs(values=True, residuals=True, hierarchical=True, out_stream=stream)
with multi_proc_exception_check(prob.comm):
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"7 Explicit Output(s) in 'model'",
'',
'varname val resids',
'------- ----- ------',
'iv',
' x',
'c1',
' y',
'sub',
' c2',
' y',
' c3',
' y',
'c2',
' y',
'c3',
' y',
'sub2',
' y',
'',
'',
"0 Implicit Output(s) in 'model'",
]
for i, line in enumerate(expected):
if line and not line.startswith('-'):
self.assertTrue(text[i].startswith(line),
'\nExpected: %s\nReceived: %s\n' % (line, text[i]))
def test_parallel_list_vars(self):
prob = Problem(FanOutGrouped())
# add another subsystem with similar prefix
prob.model.add_subsystem('sub2', ExecComp(['y=x']))
prob.model.connect('iv.x', 'sub2.x')
prob.setup()
prob.run_model()
#
# list inputs, not hierarchical
#
stream = cStringIO()
prob.model.list_inputs(values=True, hierarchical=False, out_stream=stream)
if prob.comm.rank == 0: # Only rank 0 prints
text = stream.getvalue().split('\n')
expected = [
"6 Input(s) in 'model'",
'---------------------',
'',
'varname value',
'-------- -----',
'c1.x',
'sub.c2.x',
'sub.c3.x',
'c2.x',
'c3.x',
'sub2.x'
]
for i in range(len(expected)):
self.assertTrue(text[i].startswith(expected[i]),
'\nExpected: %s\nReceived: %s\n' % (expected[i], text[i]))
#
# list inputs, hierarchical
#
stream = cStringIO()
prob.model.list_inputs(values=True, hierarchical=True, out_stream=stream)
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"6 Input(s) in 'model'",
'---------------------',
'',
'varname value',
'------- -----',
'top',
' c1',
' x',
' sub',
' c2',
' x',
' c3',
' x',
' c2',
' x',
' c3',
' x',
' sub2',
' x'
]
for i in range(len(expected)):
self.assertTrue(text[i].startswith(expected[i]),
'\nExpected: %s\nReceived: %s\n' % (expected[i], text[i]))
#
# list outputs, not hierarchical
#
stream = cStringIO()
prob.model.list_outputs(values=True, residuals=True, hierarchical=False, out_stream=stream)
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"7 Explicit Output(s) in 'model'",
'-------------------------------',
'',
'varname value resids',
'-------- ----- ------',
'iv.x',
'c1.y',
'sub.c2.y',
'sub.c3.y',
'c2.y',
'c3.y',
'sub2.y',
'',
'',
"0 Implicit Output(s) in 'model'",
'-------------------------------',
]
for i in range(len(expected)):
self.assertTrue(text[i].startswith(expected[i]),
'\nExpected: %s\nReceived: %s\n' % (expected[i], text[i]))
#
# list outputs, hierarchical
#
stream = cStringIO()
prob.model.list_outputs(values=True, residuals=True, hierarchical=True, out_stream=stream)
if prob.comm.rank == 0:
text = stream.getvalue().split('\n')
expected = [
"7 Explicit Output(s) in 'model'",
'-------------------------------',
'',
'varname value resids',
'------- ----- ------',
'top',
' iv',
' x',
' c1',
' y',
' sub',
' c2',
' y',
' c3',
' y',
' c2',
' y',
' c3',
' y',
' sub2',
' y',
'',
'',
"0 Implicit Output(s) in 'model'",
'-------------------------------',
]
for i in range(len(expected)):
self.assertTrue(text[i].startswith(expected[i]),
'\nExpected: %s\nReceived: %s\n' % (expected[i], text[i]))
