def test_polynomial_control_group_scalar_gl(self):
transcription = 'gauss-lobatto'
compressed = True
segends = np.array([0.0, 3.0, 10.0])
gd = GridData(num_segments=2,
transcription_order=5,
segment_ends=segends,
transcription=transcription,
compressed=compressed)
p = om.Problem(model=om.Group())
controls = {
'a': PolynomialControlOptionsDictionary(),
'b': PolynomialControlOptionsDictionary()
}
controls['a']['units'] = 'm'
controls['a']['order'] = 3
controls['a']['shape'] = (1, )
controls['a']['opt'] = True
controls['b']['units'] = 'm'
controls['b']['order'] = 3
controls['b']['shape'] = (1, )
controls['b']['opt'] = True
ivc = om.IndepVarComp()
p.model.add_subsystem('ivc', ivc, promotes_outputs=['*'])
ivc.add_output('t_initial', val=0.0, units='s')
ivc.add_output('t_duration', val=10.0, units='s')
p.model.add_subsystem('time_comp',
subsys=TimeComp(
num_nodes=gd.num_nodes,
node_ptau=gd.node_ptau,
node_dptau_dstau=gd.node_dptau_dstau,
units='s'),
promotes_inputs=['t_initial', 't_duration'],
promotes_outputs=['time', 'dt_dstau'])
polynomial_control_group = PolynomialControlGroup(
grid_data=gd, polynomial_control_options=controls, time_units='s')
p.model.add_subsystem('polynomial_control_group',
subsys=polynomial_control_group,
promotes_inputs=['*'],
promotes_outputs=['*'])
p.setup(force_alloc_complex=True)
p['t_initial'] = 0.0
p['t_duration'] = 3.0
p.run_model()
control_nodes_ptau, _ = lgl(controls['a']['order'] + 1)
t_control_input = p['t_initial'] + 0.5 * (control_nodes_ptau +
1) * p['t_duration']
t_all = p['time']
p['polynomial_controls:a'][:, 0] = f_a(t_control_input)
p['polynomial_controls:b'][:, 0] = f_b(t_control_input)
p.run_model()
a_value_expected = f_a(t_all)
b_value_expected = f_b(t_all)
a_rate_expected = f1_a(t_all)
b_rate_expected = f1_b(t_all)
a_rate2_expected = f2_a(t_all)
b_rate2_expected = f2_b(t_all)
assert_almost_equal(p['polynomial_control_values:a'],
np.atleast_2d(a_value_expected).T)
assert_almost_equal(p['polynomial_control_values:b'],
np.atleast_2d(b_value_expected).T)
assert_almost_equal(p['polynomial_control_rates:a_rate'],
np.atleast_2d(a_rate_expected).T)
assert_almost_equal(p['polynomial_control_rates:b_rate'],
np.atleast_2d(b_rate_expected).T)
assert_almost_equal(p['polynomial_control_rates:a_rate2'],
np.atleast_2d(a_rate2_expected).T)
assert_almost_equal(p['polynomial_control_rates:b_rate2'],
np.atleast_2d(b_rate2_expected).T)
np.set_printoptions(linewidth=1024)
cpd = p.check_partials(compact_print=False,
out_stream=None,
method='cs')
assert_check_partials(cpd)
def test_polynomial_control_group_matrix_rungekutta(self):
transcription = 'runge-kutta'
compressed = True
segends = np.array([0.0, 3.0, 10.0])
gd = GridData(num_segments=2,
transcription_order='RK4',
segment_ends=segends,
transcription=transcription,
compressed=compressed)
p = om.Problem(model=om.Group())
controls = {'a': PolynomialControlOptionsDictionary()}
controls['a']['units'] = 'm'
controls['a']['order'] = 3
controls['a']['opt'] = True
controls['a']['shape'] = (3, 1)
ivc = om.IndepVarComp()
p.model.add_subsystem('ivc', ivc, promotes_outputs=['*'])
ivc.add_output('t_initial', val=0.0, units='s')
ivc.add_output('t_duration', val=10.0, units='s')
p.model.add_subsystem('time_comp',
subsys=TimeComp(num_nodes=gd.num_nodes, node_ptau=gd.node_ptau,
node_dptau_dstau=gd.node_dptau_dstau, units='s'),
promotes_inputs=['t_initial', 't_duration'],
promotes_outputs=['time', 'dt_dstau'])
polynomial_control_group = PolynomialControlGroup(grid_data=gd,
polynomial_control_options=controls,
time_units='s')
p.model.add_subsystem('polynomial_control_group',
subsys=polynomial_control_group,
promotes_inputs=['*'],
promotes_outputs=['*'])
# p.model.connect('dt_dstau', 'control_interp_comp.dt_dstau')
p.setup(force_alloc_complex=True)
p['t_initial'] = 0.0
p['t_duration'] = 3.0
p.run_model()
control_nodes_ptau, _ = lgl(controls['a']['order'] + 1)
t_control_input = p['t_initial'] + 0.5 * (control_nodes_ptau + 1) * p['t_duration']
t_all = p['time']
p['polynomial_controls:a'][:, 0, 0] = f_a(t_control_input)
p['polynomial_controls:a'][:, 1, 0] = f_b(t_control_input)
p['polynomial_controls:a'][:, 2, 0] = f_c(t_control_input)
p.run_model()
a0_value_expected = f_a(t_all)
a1_value_expected = f_b(t_all)
a2_value_expected = f_c(t_all)
a0_rate_expected = f1_a(t_all)
a1_rate_expected = f1_b(t_all)
a2_rate_expected = f1_c(t_all)
a0_rate2_expected = f2_a(t_all)
a1_rate2_expected = f2_b(t_all)
a2_rate2_expected = f2_c(t_all)
assert_almost_equal(p['polynomial_control_values:a'][:, 0, 0],
a0_value_expected)
assert_almost_equal(p['polynomial_control_values:a'][:, 1, 0],
a1_value_expected)
assert_almost_equal(p['polynomial_control_values:a'][:, 2, 0],
a2_value_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate'][:, 0, 0],
a0_rate_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate'][:, 1, 0],
a1_rate_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate'][:, 2, 0],
a2_rate_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate2'][:, 0, 0],
a0_rate2_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate2'][:, 1, 0],
a1_rate2_expected)
assert_almost_equal(p['polynomial_control_rates:a_rate2'][:, 2, 0],
a2_rate2_expected)
np.set_printoptions(linewidth=1024)
cpd = p.check_partials(method='cs', out_stream=None)
assert_check_partials(cpd)
