def test_closed_system():
c1 = aiger_bv.atom(1, 'c1', signed=False)
a = aiger_bv.atom(1, 'a', signed=False)
dyn = circ2mdp(chain(n=4, state_name='s', action='a'))
dyn <<= (c1 & a).with_output('a').aigbv
c1_coin = coin((1, 8), name='c1')
dyn <<= c1_coin
assert dyn.inputs == {'a'}
assert dyn.outputs == {'s'}
start = {'s_prev': (True, False, False, False, False)}
end = {'s_prev': (False, True, False, False, False)}
assert dyn.prob(start, {'a': (0, )}, end) == 0
assert dyn.prob(start, {'a': (1, )}, end) == c1_coin.prob() == 1 / 8
c2 = aiger_bv.atom(1, 'c2', signed=False)
const_false = aiger_bv.atom(1, 0, signed=False)
state = aiger_bv.atom(5, 's', signed=False)
clip = state == 0b00001
policy = circ2mdp(aiger_bv.ite(clip, const_false, c2).with_output('a'))
policy <<= coin((1, 8), name='c2')
sys = (policy >> dyn).feedback(inputs=['s'],
outputs=['s'],
latches=['s_prev2'],
keep_outputs=True)
assert sys.inputs == set()
assert sys.outputs == {'s'}
def chain(n, state_name='x', action='a', start=None, clip=True, can_stay=True):
if start is None:
start = n // 2
else:
start -= 1
start = encode_int(n, 1 << start, signed=False)
x = atom(n, state_name, signed=False)
a = atom(2, action, signed=False)
backward, forward = a[0], a[1]
x2 = ite(forward, x << 1, x >> 1)
stay = atom(1, 1, signed=False)
if clip:
stay = (x2 == 0)
if can_stay:
stay |= ~(forward | backward)
if clip or can_stay:
x2 = ite(stay, x, x2)
circ = x2.aigbv['o', {x2.output: state_name}]
return circ.feedback(inputs=[state_name],
outputs=[state_name],
initials=[start],
keep_outputs=True)
def test_get_model():
expr = atom(4, 'x') & atom(4, 'y') < 2
f = sat_bv.SolverBVWrapper()
f.add_expr(expr)
model = f.get_model()
assert len(model) == 2
assert expr(model)
def gen_equiv_checks(aps: AtomicPreds) -> Iterable[BVExpr]:
for t, ap in enumerate(aps):
for name, val in ap.items():
size = len(val)
timed_name = f"{name}##time_{t + 1}"
sym = BV.atom(size, timed_name, signed=False)
sym_val = BV.atom(size, val, signed=False)
yield sym == sym_val
def chain(n, state_name='x', action='H'):
bits = n + 1
start = encode_int(bits, 1, signed=False)
x = atom(bits, state_name, signed=False)
forward = atom(1, action, signed=False)
x2 = ite(forward, x << 1, x)
circ = x2.aigbv['o', {x2.output: state_name}]
return circ.feedback(inputs=[state_name],
outputs=[state_name],
latches=[f"{state_name}_prev"],
initials=[start],
keep_outputs=True)
def test_mdp_readme():
from aiger_bv import atom
from aiger_coins import circ2mdp
x = atom(3, 'x', signed=False)
y = atom(3, 'y', signed=False)
expr = (x & y).with_output('x&y')
mdp1 = circ2mdp(expr)
dist = aiger_coins.dist((0, 1, 2), name='y')
mdp2 = dist >> mdp1
assert mdp1.inputs == {'x', 'y'}
assert mdp2.inputs == {'x'}
mdp3 = mdp2 | circ2mdp(aiger_bv.identity_gate(3, 'z'))
assert mdp3.inputs == {'x', 'z'}
assert mdp3.outputs == {'x&y', 'z'}
mdp4 = mdp3.feedback(inputs=['z'], outputs=['x&y'], keep_outputs=True)
assert mdp4.inputs == {'x'}
assert mdp4.outputs == {'x&y', 'z'}
action = atom(1, 'action', signed=False)
x_prev = atom(1, 'x_prev', signed=False)
c = atom(1, 'c', signed=False)
x_next = (x_prev & c & action).with_output('x_next')
sys = circ2mdp(x_next).feedback(
keep_outputs=True,
inputs=['x_prev'],
outputs=['x_next'],
initials=[(True, )],
)
sys <<= coin((1, 2), name='c')
assert sys.inputs == {'action'}
assert sys.outputs == {'x_next'}
sys_actions = 3 * [{'action': (True, )}]
states = 3 * [{'x_next': (True, )}]
actions = sys.encode_trc(sys_actions, states)
assert not any(v['c'][0] for v in actions)
sys_actions2, states2 = sys.decode_trc(actions)
assert sys_actions2 == sys_actions
assert states2 == states
def main():
print("START")
X = BV.atom(8, 'x', signed=False)
Y = BV.atom(8, 'y', signed=False)
APS = { # x-axis y-axis
'yellow': mask_test(0b1000_0001, 0b1000_0001, X, Y),
'blue': mask_test(0b0001_1000, 0b0011100, X, Y),
'brown': mask_test(0b0011_1100, 0b1000_0001, X, Y),
'red': mask_test(0b1000_0001, 0b0100_1100, X, Y) \
| mask_test(0b0100_0010, 0b1100_1100, X, Y),
}
SENSOR = create_sensor(APS)
print_map(SENSOR)
print("SUCCESS")
def dfa2aig(dfa: DFA):
"""
Takes a dfa.DFA object and returns a tuple of:
1. An aiger_bv.AIGBV circuit modeling the DFA's labeling and
transitions. This circuit has 1 input, output, and latch
called "action", "output", and "state" respectively.
2. A dictionary with at three entries, "inputs", "outputs", and
"states".
- Each entry of this dictionary is a bidict that maps one-hot
encoded tuples, e.g. (True, False, False), to dfa inputs,
outputs, states.
3. An aiger_bv.AIGBV circuit which monitors is all inputs are
valid, e.g., one_hot encoded.
"""
in2bv, out2bv, state2bv = create_bv_maps(dfa)
dfa_dict, _ = dfa2dict(dfa)
action = aiger_bv.atom(len(dfa.inputs), 'action', signed=False)
state = aiger_bv.atom(len(dfa.states()), 'state', signed=False)
circ = out_circ(dfa_dict, state2bv, out2bv, state)
circ |= transition_circ(dfa_dict, state2bv, in2bv, action, state)
start = state2bv[dfa.start]
circ = circ.loopback({
"input": "state",
"output": "next_state",
"init": start,
"keep_output": False,
})
relabels = {
'inputs': in2bv.inv,
'outputs': out2bv.inv,
'states': state2bv.inv
}
return circ, relabels, valid_circ(action)
def test_seq_composition():
x = BV.atom(4, 'x')
y = BV.atom(4, 'y')
circ1 = (x + 1).with_output('y').aigbv \
| (x < 5).with_output('##valid').aigbv
func1 = from_aigbv(circ1,)
circ2 = (y - 1).with_output('z').aigbv \
| (y > 2).with_output('##valid').aigbv
func2 = from_aigbv(circ2,)
func12 = func1 >> func2
assert func12({'x': 4})[0] == {'z': 4}
with pytest.raises(ValueError):
func12({'x': 1})
func12 = func2 << func1
assert func12({'x': 4})[0] == {'z': 4}
with pytest.raises(ValueError):
func12({'x': 1})
def test_mdp_smoke():
x = aiger_bv.identity_gate(2, 'x')
y = aiger_bv.identity_gate(3, 'y')
circ = x | y
dist = aiger_coins.dist(((0, 3), (1, 3), (2, 3)), name='y')
assert dist.expr.output == 'y'
dyn = circ2mdp(circ, {'y': dist})
assert dyn.inputs == {'x'}
dyn2 = dist >> circ2mdp(circ)
assert dyn2.inputs == {'x'}
assert dyn2.aigbv.inputs == {'x'} | dist.inputs
assert dyn2.aigbv.outputs == dyn2.outputs | {'##valid'}
assert '##valid[0]' in dyn2.aig.outputs
x = aiger_bv.atom(3, 'x', signed=False)
y = aiger_bv.atom(3, 'y', signed=False)
mdp = dist >> circ2mdp(x < y)
assert mdp.inputs == {'x'}
assert len(mdp.outputs) == 1
def dist(probs, name=None, keep_seperate=False):
"""Distribution generated by mutually exclusive coins.
Encoded using the common denominator method.
"""
is_coin = len(probs) == 1
probs = _normalize_probs(probs)
bots = [p.denominator for p in probs]
lcm = reduce(utils.lcm, bots, 1)
word_len = max(math.ceil(math.log2(lcm)), 1)
weights = map(lambda p: p.numerator * (lcm // p.denominator), probs)
bits = atom(word_len, name, signed=False)
if name is not None:
bits = bits.with_output(name)
name = bits.output
const_true = ~(bits @ 0)
total, coins, max_val = 0, [], 2**word_len
for i, weight in enumerate(weights):
lb = const_true if total == 0 else (bits >= total)
total += weight
ub = const_true if total == max_val else (bits < total)
coins.append(lb & ub)
is_valid = const_true if lcm == max_val else bits < lcm
if keep_seperate:
return coins, is_valid
coins = reduce(UnsignedBVExpr.concat, coins) \
.with_output(name)
_dist = Distribution(expr=coins, valid=is_valid)
return _dist[0] if is_coin else _dist
def test_count_le(i):
expr = atom(4, 'x', signed=False) < atom(4, i, signed=False)
assert count(expr) == i
assert count(expr, fraction=True) == i / (2**4)
def test_bdd_transform_smoke():
to_bdd(atom(3, 'x', signed=False) < 4)
import aiger_ptltl as LTL
import funcy as fn
import termplotlib as tpl
from bidict import bidict
from blessings import Terminal
from mce.infer import spec_mle
# ================= World ========================
TERM = Terminal()
X = BV.atom(8, 'x', signed=False)
Y = BV.atom(8, 'y', signed=False)
def mask_test(xmask, ymask):
return ((X & xmask) != 0) & ((Y & ymask) != 0)
APS = {
'yellow': mask_test(0b1100_0000, 0b0000_0001),
'red': mask_test(0b0011_1111, 0b1111_1111)
}
def create_sensor(aps):
sensor = BV.aig2aigbv(A.empty())
def test_solve():
expr = atom(4, 'x') & atom(4, 'y') < 2
model = sat_bv.solve(expr)
assert len(model) == 2
assert expr(model)
