def test_list_inputs(self):
prob = SellarProblem()
prob.model.add_recorder(self.recorder)
prob.model.recording_options['record_residuals'] = True
prob.setup()
d1 = prob.model.d1 # SellarDis1withDerivatives (an ExplicitComp)
d1.nonlinear_solver = NonlinearBlockGS(maxiter=5)
d1.add_recorder(self.recorder)
prob.run_driver()
prob.cleanup()
cr = CaseReader(self.filename)
inputs = cr.list_inputs(None, True, True, True)
expected_inputs = {
'obj_cmp.x': {'value': [1.]},
'd2.z': {'value': [5., 2.]},
'con_cmp2.y2': {'value': [12.05848815]},
'obj_cmp.y2': {'value': [12.05848815]},
'obj_cmp.z': {'value': [5., 2.]},
'd1.x': {'value': [1.]},
'd1.z': {'value': [5., 2.]},
'd1.y2': {'value': [12.05848815]},
'con_cmp1.y1': {'value': [25.58830237]},
'obj_cmp.y1': {'value': [25.58830237]},
'd2.y1': {'value': [25.58830237]}
}
self.assertEqual(len(inputs), 11)
for o in inputs:
vals = o[1]
name = o[0]
expected = expected_inputs[name]
np.testing.assert_almost_equal(vals['value'], expected['value'])
expected_inputs_case = {
'd1.z': {'value': [5., 2.]},
'd1.x': {'value': [1.]},
'd1.y2': {'value': [12.27257053]}
}
sys_case = cr.system_cases.get_case(1)
inputs_case = cr.list_inputs(sys_case, True, True, True, None)
for o in inputs_case:
vals = o[1]
name = o[0]
expected = expected_inputs_case[name]
np.testing.assert_almost_equal(vals['value'], expected['value'])
def test_list_inputs(self):
self.setup_sellar_model()
nonlinear_solver = self.prob.model.nonlinear_solver
linear_solver = self.prob.model.linear_solver
d1 = self.prob.model.d1 # instance of SellarDis1withDerivatives, a Group
d1.nonlinear_solver = NonlinearBlockGS()
d1.nonlinear_solver.options['maxiter'] = 5
self.prob.model.add_recorder(self.recorder)
self.prob.model.d1.add_recorder(self.recorder)
self.prob.model.recording_options['record_residuals'] = True
self.prob.setup(check=False)
self.prob.run_driver()
self.prob.cleanup()
cr = CaseReader(self.filename)
inputs = cr.list_inputs(None, True, True, True)
expected_inputs = {
'obj_cmp.x': {
'value': [1.]
},
'd2.z': {
'value': [5., 2.]
},
'con_cmp2.y2': {
'value': [12.05848815]
},
'obj_cmp.y2': {
'value': [12.05848815]
},
'obj_cmp.z': {
'value': [5., 2.]
},
'd1.x': {
'value': [1.]
},
'd1.z': {
'value': [5., 2.]
},
'd1.y2': {
'value': [12.05848815]
},
'con_cmp1.y1': {
'value': [25.58830237]
},
'obj_cmp.y1': {
'value': [25.58830237]
},
'd2.y1': {
'value': [25.58830237]
}
}
self.assertEqual(len(inputs), 11)
for o in inputs:
vals = o[1]
name = o[0]
expected = expected_inputs[name]
np.testing.assert_almost_equal(vals['value'], expected['value'])
expected_inputs_case = {
'd1.z': {
'value': [5., 2.]
},
'd1.x': {
'value': [1.]
},
'd1.y2': {
'value': [12.27257053]
}
}
inputs_case = cr.list_inputs(1, True, True, True, None)
for o in inputs_case:
vals = o[1]
name = o[0]
expected = expected_inputs_case[name]
np.testing.assert_almost_equal(vals['value'], expected['value'])
