def test_sellarCS(self):
# Just tests Newton on Sellar with FD derivs.
prob = Problem()
prob.model = SellarNoDerivativesCS()
prob.setup(check=False)
prob.run_model()
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.model.nonlinear_solver._iter_count, 8)
def test_assert_no_dict_jacobians_exception_expected(self):
prob = Problem()
prob.model = SellarNoDerivativesCS()
prob.setup(check=False)
try:
assert_no_dict_jacobians(prob.model, include_self=True, recurse=True)
except AssertionError as err:
expected_err = "The following groups use dictionary jacobians:\n \n cycle"
self.assertEqual(str(err), expected_err)
else:
self.fail('Exception expected.')
def test_sellarCS(self):
# Just tests Newton on Sellar with FD derivs.
import numpy as np
from openmdao.api import Problem
from openmdao.test_suite.components.sellar_feature import SellarNoDerivativesCS
prob = Problem()
prob.model = SellarNoDerivativesCS()
prob.setup(check=False)
prob.run_model()
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.model.nonlinear_solver._iter_count, 8)
def test_assert_no_approx_partials_exception_expected(self):
prob = om.Problem()
prob.model = SellarNoDerivativesCS()
prob.setup()
try:
assert_no_approx_partials(prob.model, include_self=True, recurse=True)
except AssertionError as err:
expected_err = \
'''The following components use approximated partials:
cycle.d1
of=* wrt=* method=cs
cycle.d2
of=* wrt=* method=cs
'''
self.assertEqual(str(err), expected_err)
else:
self.fail('Exception expected.')