def test_add_duplicate(self):
prob = Problem()
root = prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
prob.driver.add_desvar('z', lower=-100.0, upper=100.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
# Add duplicate desvar
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_desvar('z', lower=-50.0, upper=49.0)
msg = "Desvar 'z' already exists."
raised_error = str(cm.exception)
self.assertEqual(msg, raised_error)
# Add duplicate constraint
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', upper=0.0)
msg = "Constraint 'con1' already exists."
raised_error = str(cm.exception)
self.assertEqual(msg, raised_error)
# Add duplicate objective
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_objective('obj')
msg = "Objective 'obj' already exists."
raised_error = str(cm.exception)
self.assertEqual(msg, raised_error)
def test_Sellar_SLSQP(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.driver = ScipyOptimizer()
prob.driver.options['optimizer'] = 'SLSQP'
prob.driver.options['tol'] = 1.0e-8
prob.driver.add_desvar('z',
lower=np.array([-10.0, 0.0]),
upper=np.array([10.0, 10.0]))
prob.driver.add_desvar('x', lower=0.0, upper=10.0)
prob.driver.add_objective('obj')
prob.driver.add_constraint('con1', upper=0.0)
prob.driver.add_constraint('con2', upper=0.0)
prob.driver.options['disp'] = False
prob.setup(check=False)
prob.run()
assert_rel_error(self, prob['z'][0], 1.9776, 1e-3)
assert_rel_error(self, prob['z'][1], 0.0, 1e-3)
assert_rel_error(self, prob['x'], 0.0, 1e-3)
def test_eq_ineq_error_messages(self):
prob = Problem()
root = prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
# Don't try this at home, kids
prob.driver.supports['equality_constraints'] = False
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', ctype='eq')
self.assertEqual(
str(cm.exception),
"Driver does not support equality constraint 'con1'.")
# Don't try this at home, kids
prob.driver.supports['inequality_constraints'] = False
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', ctype='ineq')
self.assertEqual(
str(cm.exception),
"Driver does not support inequality constraint 'con1'.")
def test_sellar_derivs(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.ln_solver.options['maxiter'] = 10
prob.root.ln_solver.options['atol'] = 1e-12
prob.root.ln_solver.options['rtol'] = 1e-12
#prob.root.ln_solver.options['iprint'] = 1
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)
indep_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(indep_list, unknown_list, mode='fwd', return_format='dict')
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J[key1][key2], val2, .00001)
J = prob.calc_gradient(indep_list, unknown_list, mode='rev', return_format='dict')
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J[key1][key2], val2, .00001)
# Cheat a bit so I can twiddle mode
OptionsDictionary.locked = False
prob.root.fd_options['form'] = 'central'
J = prob.calc_gradient(indep_list, unknown_list, mode='fd', return_format='dict')
for key1, val1 in Jbase.items():
for key2, val2 in val1.items():
assert_rel_error(self, J[key1][key2], val2, .00001)
# 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(indep_list, unknown_list, mode='fd', return_format='array')
def test_eq_ineq_error_messages(self):
prob = Problem()
root = prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1')
self.assertEqual(
str(cm.exception),
"Constraint 'con1' needs to define lower, upper, or equals.")
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1',
lower=0.0,
upper=1.1,
equals=2.2)
self.assertEqual(
str(cm.exception),
"Constraint 'con1' cannot be both equality and inequality.")
# Don't try this at home, kids
prob.driver.supports['two_sided_constraints'] = False
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', lower=0.0, upper=1.1)
self.assertEqual(str(cm.exception),
"Driver does not support 2-sided constraint 'con1'.")
# Don't try this at home, kids
prob.driver.supports['equality_constraints'] = False
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', equals=0.0)
self.assertEqual(
str(cm.exception),
"Driver does not support equality constraint 'con1'.")
# Don't try this at home, kids
prob.driver.supports['inequality_constraints'] = False
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_constraint('con1', upper=0.0)
self.assertEqual(
str(cm.exception),
"Driver does not support inequality constraint 'con1'.")
def test_no_desvar_bound(self):
prob = Problem()
root = prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
prob.driver.add_desvar('z')
prob.setup(check=False)
meta = prob.driver._desvars['z']
self.assertLess(meta['lower'], -1e12)
self.assertGreater(meta['upper'], 1e12)
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_sellar_derivs_with_Lin_GS(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.root.nl_solver = Newton()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.ln_solver.options['maxiter'] = 2
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_unsupported_multiple_obj(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
prob.driver.add_desvar('z', lower=-100.0, upper=100.0)
prob.driver.add_objective('obj')
# Add duplicate objective
with self.assertRaises(RuntimeError) as cm:
prob.driver.add_objective('x')
msg = "Attempted to add multiple objectives to a driver that does not " \
"support multiple objectives."
raised_error = str(cm.exception)
self.assertEqual(msg, raised_error)
def test_mydriver(self):
prob = Problem()
root = prob.root = SellarDerivatives()
prob.driver = MySimpleDriver()
prob.driver.add_desvar('z', lower=-100.0, upper=100.0)
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.run()
obj = prob['obj']
self.assertLess(obj, 28.0)
def test_sellar_analysis_error(self):
prob = Problem()
prob.root = SellarDerivatives()
prob.root.ln_solver = LinearGaussSeidel()
prob.root.ln_solver.options['maxiter'] = 2
prob.root.ln_solver.options['err_on_maxiter'] = True
prob.root.ln_solver.options['atol'] = 1e-12
prob.root.ln_solver.options['rtol'] = 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)
indep_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])
try:
J = prob.calc_gradient(indep_list,
unknown_list,
mode='fwd',
return_format='dict')
except AnalysisError as err:
self.assertEqual(
str(err),
"Solve in '': LinearGaussSeidel FAILED to converge after 2 iterations"
)
else:
self.fail("expected AnalysisError")
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)
# Make sure we only call apply_linear on 'heads'
nd1 = prob.root.d1.execution_count
nd2 = prob.root.d2.execution_count
if prob.root.d1._run_apply == True:
self.assertEqual(nd1, 2 * nd2)
else:
self.assertEqual(2 * nd1, nd2)