def test_determinize_machine_init():
mach = transys.MealyMachine()
mach.add_inputs({'a': {0, 1}})
mach.add_outputs({'b': {0, 1}, 'c': {0, 1}})
u = 'Sinit'
mach.add_nodes_from([u, 1, 2])
# initial reactions:
# to input: a=0
mach.add_edge(u, 1, a=0, b=0, c=1)
mach.add_edge(u, 2, a=0, b=0, c=1)
mach.add_edge(u, 1, a=0, b=1, c=0)
mach.add_edge(u, 2, a=0, b=1, c=1)
# to input: a=1
mach.add_edge(u, 1, a=1, b=0, c=1)
mach.add_edge(u, 2, a=1, b=0, c=1)
mach.add_edge(u, 1, a=1, b=1, c=0)
mach.add_edge(u, 2, a=1, b=1, c=1)
# determinize all outputs arbitrarily
detmach = synth.determinize_machine_init(mach)
assert detmach is not mach
for a in {0, 1}:
edges = [(i, j) for (i, j, d) in detmach.edges_iter(u, data=True)
if d['a'] == a]
assert len(edges) == 1
# determinize output b arbitrarily,
# but output c is constrained to the initial value 0
detmach = synth.determinize_machine_init(mach, {'c': 0})
for a in {0, 1}:
edges = [(i, j, d) for (i, j, d) in detmach.edges_iter(u, data=True)
if d['a'] == a]
assert len(edges) == 1
((i, j, d), ) = edges
assert j == 1
assert d['b'] == 1
def simulate(randParkSignal, sys_dyn, ctrl, disc_dynamics, T):
# initialization:
# pick initial continuous state consistent with
# initial controller state (discrete)
u, v, edge_data = list(ctrl.edges('Sinit', data=True))[1]
s0_part = edge_data['loc']
init_poly_v = pc.extreme(disc_dynamics.ppp[s0_part][0])
x_init = sum(init_poly_v) / init_poly_v.shape[0]
x = [x_init[0]]
y = [x_init[1]]
N = disc_dynamics.disc_params['N']
s0_part = find_controller.find_discrete_state([x[0], y[0]],
disc_dynamics.ppp)
ctrl = synth.determinize_machine_init(ctrl, {'loc': s0_part})
(s, dum) = ctrl.reaction('Sinit', {'park': randParkSignal[0]})
print(dum)
for i in range(0, T):
(s, dum) = ctrl.reaction(s, {'park': randParkSignal[i]})
u = find_controller.get_input(x0=np.array([x[i * N], y[i * N]]),
ssys=sys_dyn,
abstraction=disc_dynamics,
start=s0_part,
end=disc_dynamics.ppp2ts.index(
dum['loc']),
ord=1,
mid_weight=5)
for ind in range(N):
s_now = np.dot(sys_dyn.A, [x[-1], y[-1]]) + np.dot(
sys_dyn.B, u[ind])
x.append(s_now[0])
y.append(s_now[1])
s0_part = find_controller.find_discrete_state([x[-1], y[-1]],
disc_dynamics.ppp)
s0_loc = disc_dynamics.ppp2ts[s0_part]
print(s0_loc)
print(dum['loc'])
print(dum)
show_traj = True
if show_traj:
assert plt, 'failed to import matplotlib'
plt.plot(x)
plt.plot(y)
plt.show()
disc_dynamics.disc_params['conservative'] = True
disc_dynamics.disc_params['closed_loop'] = False
# initialization:
# pick initial continuous state consistent with
# initial controller state (discrete)
u, v, edge_data = list(ctrl.edges('Sinit', data=True))[1]
s0_part = edge_data['loc']
init_poly_v = pc.extreme(disc_dynamics.ppp[s0_part][0])
x_init = sum(init_poly_v) / init_poly_v.shape[0]
x = [x_init[0]]
y = [x_init[1]]
N = disc_dynamics.disc_params['N']
s0_part = find_controller.find_discrete_state(
[x[0], y[0]], disc_dynamics.ppp)
ctrl = synth.determinize_machine_init(ctrl, {'loc': s0_part})
(s, dum) = ctrl.reaction('Sinit', {'park': randParkSignal[0]})
print(dum)
for i in range(0, T):
(s, dum) = ctrl.reaction(s, {'park': randParkSignal[i]})
u = find_controller.get_input(
x0=np.array([x[i * N], y[i * N]]),
ssys=sys_dyn,
abstraction=disc_dynamics,
start=s0_part,
end=disc_dynamics.ppp2ts.index(dum['loc']),
ord=1,
mid_weight=5)
for ind in range(N):
s_now = np.dot(
sys_dyn.A, [x[-1], y[-1]]
T = 100
# let us pick an environment signal
randParkSignal = [random.randint(0, 1) for b in range(1, T + 1)]
# initialization:
# pick initial continuous state consistent with
# initial controller state (discrete)
u, v, edge_data = ctrl.edges('Sinit', data=True)[1]
s0_part = edge_data['loc']
init_poly_v = pc.extreme(disc_dynamics.ppp[s0_part][0])
x_init = sum(init_poly_v) / init_poly_v.shape[0]
x = [x_init[0]]
y = [x_init[1]]
N = disc_dynamics.disc_params['N']
s0_part = find_controller.find_discrete_state(
[x[0], y[0]], disc_dynamics.ppp)
ctrl = synth.determinize_machine_init(ctrl, {'loc': s0_part})
(s, dum) = ctrl.reaction('Sinit', {'park': randParkSignal[0]})
print(dum)
for i in range(0, T):
(s, dum) = ctrl.reaction(s, {'park': randParkSignal[i]})
u = find_controller.get_input(
x0=np.array([x[i * N], y[i * N]]),
ssys=sys_dyn,
abstraction=disc_dynamics,
start=s0_part,
end=disc_dynamics.ppp2ts.index(dum['loc']),
ord=1,
mid_weight=5)
for ind in range(N):
s_now = np.dot(
sys_dyn.A, [x[-1], y[-1]]