def test_double_diamond_model_complex_step(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.root.sub1.comp1.fd_options['form'] = 'complex_step'
prob.root.sub1.sub2.comp2.fd_options['form'] = 'complex_step'
prob.root.sub1.sub2.comp3.fd_options['form'] = 'complex_step'
prob.root.sub1.comp4.fd_options['form'] = 'complex_step'
prob.root.sub3.comp5.fd_options['form'] = 'complex_step'
prob.root.sub3.comp6.fd_options['form'] = 'complex_step'
prob.root.comp7.fd_options['form'] = 'complex_step'
prob.setup(check=False)
prob.run()
data = prob.check_partial_derivatives(out_stream=None)
for key1, val1 in iteritems(data):
for key2, val2 in iteritems(val1):
assert_rel_error(self, val2['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, val2['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, val2['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][2], 0.0, 1e-5)
def test_converge_diverge_groups(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.root.ln_solver = LinearGaussSeidel()
prob.setup(check=False)
prob.run()
# Make sure value is fine.
assert_rel_error(self, prob['comp7.y1'], -102.7, 1e-6)
indep_list = ['p.x']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(indep_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(indep_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(indep_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_converge_diverge_groups(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.root.ln_solver = ScipyGMRES()
prob.root.ln_solver.options['precondition'] = True
prob.root.sub1.ln_solver = DirectSolver()
prob.root.sub3.ln_solver = DirectSolver()
prob.setup(check=False)
prob.run()
# Make sure value is fine.
assert_rel_error(self, prob['comp7.y1'], -102.7, 1e-6)
indep_list = ['p.x']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(indep_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(indep_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(indep_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_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
indep_list = ['sub1.comp1.x1']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(indep_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(indep_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_converge_diverge_groups(self):
prob = Problem()
prob.root = Group()
prob.root.add('sub', ConvergeDivergeGroups())
indep_list = ['sub.p.x']
unknown_list = ['sub.comp7.y1']
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(indep_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(indep_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_converge_diverge_groups(self):
prob = Problem()
root = prob.root = Group()
root.add('sub', ConvergeDivergeGroups())
indep_list = ['sub.p.x']
unknown_list = ['sub.comp7.y1']
prob.setup(check=False)
prob.run()
J = prob.calc_gradient(indep_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(indep_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)
# Piggyback here to test out user calls to group.assemble_jacobian.
J, idx_dict = root.assemble_jacobian()
rs, re, cs, ce = idx_dict[('sub.sub1.comp1', ('y1', 'x1'))]
self.assertEqual(J[rs:re, cs:ce], 8)
def test_converge_diverge_groups(self):
prob = Problem()
root = prob.root = Group()
root.add('sub', ConvergeDivergeGroups())
root.fd_options['force_fd'] = True
root.fd_options['form'] = 'complex_step'
# We can't reach our desired accuracy with this step size in fd, but
# we can with cs (where step size is irrelevant.)
root.fd_options['step_size'] = 1.0e-4
prob.setup(check=False)
prob.run()
indep_list = ['sub.p.x']
unknown_list = ['sub.comp7.y1']
J = prob.calc_gradient(indep_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(indep_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_full_model_fd_double_diamond_grouped_par_sys(self):
prob = Problem()
root = prob.root = Group()
par = root.add('par', ParallelGroup())
par.add('sub', ConvergeDivergeGroups())
prob.setup(check=False)
prob.run()
prob.root.fd_options['force_fd'] = True
# Make sure we don't get a key error.
data = prob.check_total_derivatives(out_stream=None)
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_double_diamond_model(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.setup(check=False)
prob.run()
data = prob.check_partial_derivatives(out_stream=None)
for key1, val1 in iteritems(data):
for key2, val2 in iteritems(val1):
assert_rel_error(self, val2['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, val2['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, val2['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, val2['rel error'][2], 0.0, 1e-5)
self.assertEqual(len(data), 7)
# Piggyback a test for the 'comps' option.
data = prob.check_partial_derivatives(out_stream=None,
comps=['sub1.sub2.comp3', 'comp7'])
self.assertEqual(len(data), 2)
self.assertTrue('sub1.sub2.comp3' in data)
self.assertTrue('comp7' in data)
with self.assertRaises(RuntimeError) as cm:
data = prob.check_partial_derivatives(out_stream=None,
comps=['sub1', 'bogus'])
expected_msg = "The following are not valid comp names: ['bogus', 'sub1']"
self.assertEqual(str(cm.exception), expected_msg)
# This is a good test to piggyback the compact_print test
mystream = StringIO()
prob.check_partial_derivatives(out_stream=mystream,
compact_print=True)
text = mystream.getvalue()
expected = "'y1' wrt 'x1' | 8.0000e+00 | 8.0000e+00 | 8.0000e+00 | 2.0013e-06 | 2.0013e-06 | 2.5016e-07 | 2.5016e-07"
self.assertTrue(expected in text)
def test_full_model_fd_double_diamond_grouped(self):
prob = Problem()
prob.root = ConvergeDivergeGroups()
prob.root.deriv_options['type'] = 'fd'
prob.setup(check=False)
prob.run()
indep_list = ['sub1.comp1.x1']
unknown_list = ['comp7.y1']
J = prob.calc_gradient(indep_list, unknown_list, mode='fwd', return_format='dict')
assert_rel_error(self, J['comp7.y1']['sub1.comp1.x1'][0][0], -40.75, 1e-6)
# Cheat a bit so I can twiddle mode
OptionsDictionary.locked = False
prob.root.deriv_options['form'] = 'central'
J = prob.calc_gradient(indep_list, unknown_list, mode='fwd', return_format='dict')
assert_rel_error(self, J['comp7.y1']['sub1.comp1.x1'][0][0], -40.75, 1e-6)