def _ip_helper(self, with_bounds, with_ineq, linear_solver):
t0 = 0
delta_t = 1
num_finite_elements = 90
constant_control_duration = 10
time_scale = 0.1
num_time_blocks = 3
interface = Problem(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
num_time_blocks=num_time_blocks,
with_bounds=with_bounds,
with_ineq=with_ineq)
options = parapint.algorithms.IPOptions()
options.linalg.solver = linear_solver
status = parapint.algorithms.ip_solve(interface=interface, options=options)
self.assertEqual(status, parapint.algorithms.InteriorPointStatus.optimal)
interface.load_primals_into_pyomo_model()
x = dict()
p = dict()
local_block_indices = _distribute_blocks(num_time_blocks, rank, size)
for ndx in local_block_indices:
m = interface.pyomo_model(ndx)
for t in m.x_time_points:
if t in x:
self.assertAlmostEqual(x[t], m.x[t].value)
else:
x[t] = m.x[t].value
for t in m.p_time_points:
p[t] = m.p[t].value
m = build_time_block(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
with_bounds=with_bounds,
with_ineq=with_ineq)
opt = pe.SolverFactory('ipopt')
res = opt.solve(m, tee=True)
assert_optimal_termination(res)
for _t, _x in x.items():
self.assertAlmostEqual(_x, m.x[_t].value)
for _t, _p in p.items():
self.assertAlmostEqual(_p, m.p[_t].value)
def test_kkt_system(self):
t0 = 0
delta_t = 1
num_finite_elements = 90
constant_control_duration = 10
time_scale = 0.1
num_time_blocks = 3
interface = Problem(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale,
num_time_blocks=num_time_blocks)
interface.set_primals(interface.init_primals())
interface.set_slacks(interface.init_slacks())
interface.set_duals_eq(interface.init_duals_eq())
interface.set_duals_ineq(interface.init_duals_ineq())
interface.set_duals_primals_lb(interface.init_duals_primals_lb())
interface.set_duals_primals_ub(interface.init_duals_primals_ub())
interface.set_duals_slacks_lb(interface.init_duals_slacks_lb())
interface.set_duals_slacks_ub(interface.init_duals_slacks_ub())
interface.set_barrier_parameter(0)
kkt = interface.evaluate_primal_dual_kkt_matrix()
rhs = interface.evaluate_primal_dual_kkt_rhs()
linear_solver = parapint.linalg.ScipyInterface()
local_kkt = coo_matrix(kkt.to_local_array())
linear_solver.do_symbolic_factorization(local_kkt)
linear_solver.do_numeric_factorization(local_kkt)
sol = linear_solver.do_back_solve(rhs.make_local_copy())
interface.set_primal_dual_kkt_solution(sol)
interface.set_primals(interface.get_primals() + interface.get_delta_primals())
interface.set_slacks(interface.get_slacks() + interface.get_delta_slacks())
interface.set_duals_eq(interface.get_duals_eq() + interface.get_delta_duals_eq())
interface.set_duals_ineq(interface.get_duals_ineq() + interface.get_delta_duals_ineq())
interface.set_duals_primals_lb(interface.get_duals_primals_lb() + interface.get_delta_duals_primals_lb())
interface.set_duals_primals_ub(interface.get_duals_primals_ub() + interface.get_delta_duals_primals_ub())
interface.set_duals_slacks_lb(interface.get_duals_slacks_lb() + interface.get_delta_duals_slacks_lb())
interface.set_duals_slacks_ub(interface.get_duals_slacks_ub() + interface.get_delta_duals_slacks_ub())
interface.load_primals_into_pyomo_model()
x = dict()
p = dict()
local_block_indices = _distribute_blocks(num_time_blocks, rank, size)
for ndx in local_block_indices:
m = interface.pyomo_model(ndx)
for t in m.x_time_points:
if t in x:
self.assertAlmostEqual(x[t], m.x[t].value)
else:
x[t] = m.x[t].value
for t in m.p_time_points:
p[t] = m.p[t].value
m = build_time_block(t0=t0,
delta_t=delta_t,
num_finite_elements=num_finite_elements,
constant_control_duration=constant_control_duration,
time_scale=time_scale)
opt = pe.SolverFactory('ipopt')
res = opt.solve(m)
assert_optimal_termination(res)
for _t, _x in x.items():
self.assertAlmostEqual(_x, m.x[_t].value)
for _t, _p in p.items():
self.assertAlmostEqual(_p, m.p[_t].value)
def setUpClass(cls) -> None:
cls.t0 = 0
cls.delta_t = 1
cls.num_finite_elements = 6
cls.constant_control_duration = 2
cls.time_scale = 1
cls.num_time_blocks = 3
cls.with_bounds = True
cls.with_ineq = False
cls.barrier_parameter = 0.1
cls.interface = Problem(t0=cls.t0,
delta_t=cls.delta_t,
num_finite_elements=cls.num_finite_elements,
constant_control_duration=cls.constant_control_duration,
time_scale=cls.time_scale,
num_time_blocks=cls.num_time_blocks,
with_bounds=cls.with_bounds,
with_ineq=cls.with_ineq)
interface = cls.interface
num_time_blocks = cls.num_time_blocks
primals = BlockVector(num_time_blocks + 1)
duals_eq = BlockVector(num_time_blocks)
duals_ineq = BlockVector(num_time_blocks)
duals_primals_lb = BlockVector(num_time_blocks + 1)
duals_primals_ub = BlockVector(num_time_blocks + 1)
duals_slacks_lb = BlockVector(num_time_blocks)
duals_slacks_ub = BlockVector(num_time_blocks)
ownership_map = _get_ownership_map(num_time_blocks, size)
val_map = pe.ComponentMap()
if ownership_map[0] == rank:
m = interface.pyomo_model(0)
val_map[m.x[0]] = 0
val_map[m.x[1]] = 1
val_map[m.x[2]] = 2
val_map[m.p[0]] = 0.5
val_map[m.cons[1]] = 1
val_map[m.cons[2]] = 2
if ownership_map[1] == rank:
m = interface.pyomo_model(1)
val_map[m.x[2]] = 2
val_map[m.x[3]] = 3
val_map[m.x[4]] = 4
val_map[m.p[2]] = 1
val_map[m.cons[3]] = 3
val_map[m.cons[4]] = 4
if ownership_map[2] == rank:
m = interface.pyomo_model(2)
val_map[m.x[4]] = 4
val_map[m.x[5]] = 5
val_map[m.x[6]] = 6
val_map[m.p[4]] = 1.5
val_map[m.cons[5]] = 5
val_map[m.cons[6]] = 6
for ndx in range(num_time_blocks):
primals.set_block(ndx, np.zeros(4, dtype=np.double))
duals_primals_lb.set_block(ndx, np.zeros(4, dtype=np.double))
duals_primals_ub.set_block(ndx, np.zeros(4, dtype=np.double))
duals_ineq.set_block(ndx, np.zeros(0, dtype=np.double))
duals_slacks_lb.set_block(ndx, np.zeros(0, dtype=np.double))
duals_slacks_ub.set_block(ndx, np.zeros(0, dtype=np.double))
sub_duals_eq = BlockVector(3)
sub_duals_eq.set_block(0, np.zeros(2, dtype=np.double))
if ndx == 0:
sub_duals_eq.set_block(1, np.zeros(0, dtype=np.double))
else:
sub_duals_eq.set_block(1, np.zeros(1, dtype=np.double))
if ndx == num_time_blocks - 1:
sub_duals_eq.set_block(2, np.zeros(0, dtype=np.double))
else:
sub_duals_eq.set_block(2, np.zeros(1, dtype=np.double))
duals_eq.set_block(ndx, sub_duals_eq)
primals.set_block(num_time_blocks, np.zeros(2, dtype=np.double))
duals_primals_lb.set_block(num_time_blocks, np.zeros(2, dtype=np.double))
duals_primals_ub.set_block(num_time_blocks, np.zeros(2, dtype=np.double))
local_block_indices = _distribute_blocks(num_time_blocks, rank, size)
for ndx in local_block_indices:
primals.set_block(ndx, np.array([val_map[i] for i in interface.get_pyomo_variables(ndx)], dtype=np.double))
duals_primals_ub.set_block(ndx, np.array([0, 0, 0, ndx], dtype=np.double))
sub_duals_eq = duals_eq.get_block(ndx)
sub_duals_eq.set_block(0, np.array([val_map[i] for i in interface.get_pyomo_constraints(ndx)], dtype=np.double))
if ndx == 0:
sub_duals_eq.set_block(1, np.zeros(0, dtype=np.double))
else:
sub_duals_eq.set_block(1, np.ones(1, dtype=np.double) * ndx)
if ndx == num_time_blocks - 1:
sub_duals_eq.set_block(2, np.zeros(0, dtype=np.double))
else:
sub_duals_eq.set_block(2, np.ones(1, dtype=np.double) * ndx)
primals_flat = primals.flatten()
res = np.zeros(primals_flat.size, dtype=np.double)
comm.Allreduce(primals_flat, res)
primals.copyfrom(res)
duals_primals_lb_flat = duals_primals_lb.flatten()
res = np.zeros(duals_primals_lb_flat.size, dtype=np.double)
comm.Allreduce(duals_primals_lb_flat, res)
duals_primals_lb.copyfrom(res)
duals_primals_ub_flat = duals_primals_ub.flatten()
res = np.zeros(duals_primals_ub_flat.size, dtype=np.double)
comm.Allreduce(duals_primals_ub_flat, res)
duals_primals_ub.copyfrom(res)
duals_eq_flat = duals_eq.flatten()
res = np.zeros(duals_eq_flat.size, dtype=np.double)
comm.Allreduce(duals_eq_flat, res)
duals_eq.copyfrom(res)
primals.set_block(num_time_blocks, np.array([3, 6], dtype=np.double))
duals_primals_lb.set_block(num_time_blocks, np.zeros(2, dtype=np.double))
duals_primals_ub.set_block(num_time_blocks, np.zeros(2, dtype=np.double))
interface.set_primals(primals)
interface.set_duals_eq(duals_eq)
interface.set_duals_ineq(duals_ineq)
interface.set_duals_slacks_lb(duals_slacks_lb)
interface.set_duals_slacks_ub(duals_slacks_ub)
interface.set_duals_primals_lb(duals_primals_lb)
interface.set_duals_primals_ub(duals_primals_ub)
interface.set_barrier_parameter(cls.barrier_parameter)