def profile():
import time
int_alphabet = ['0', '1']
call_alphabet = ['<0', '<1']
ret_alphabet = ['0>', '1>']
Q = ['q0', 'q1']
P = ['p0', 'p1']
q0 = 'q0'
Qf = Q
calls = [('q0', '<1', 'q0', 'p0'), ('q0', '<0', 'q1', 'p0'),
('q1', '<1', 'q0', 'p1'), ('q1', '<0', 'q1', 'p1')]
interns = [('q0', '0', 'q1'), ('q0', '1', 'q0'), ('q1', '0', 'q0'),
('q1', '1', 'q1')]
returns = [('q0', 'p0', '1>', 'q0'), ('q0', 'p1', '1>', 'q1'),
('q1', 'p0', '0>', 'q0'), ('q1', 'p1', '0>', 'q1')]
vpa = DVPA.build(call_alphabet=call_alphabet,
int_alphabet=int_alphabet,
ret_alphabet=ret_alphabet,
states=Q,
start_state=q0,
accept_states=Qf,
stack_alphabet=P,
call_transitions=calls,
int_transitions=interns,
ret_transitions=returns)
s1 = "1.<0.1.<1.0.0.1>.0>.0.1.1.1".split('.') * 1000000
stackmap = mapping()
vpa.rename(stack_func=stackmap)
t = time.time()
vpa.membership(s1)
t = time.time() - t
print "finished ", (len(s1) / 1000000.0) / t, "MB/s"
def rename(self, state_func=None, alp_func=None, stack_func=None):
# states first
if state_func is None:
state_func = mapping()
start = state_func(self.start)
states = {state_func(s) for s in self.states}
accept = {state_func(s) for s in self.accept}
# alphabet x3
alp = None
if alp_func is None:
# identity
alp = self.alphabet
alp_func = (lambda x: x, lambda x: x, lambda x: x)
else:
alp = ({alp_func[0](a)
for a in self.alphabet[0]
}, {alp_func[1](a)
for a in self.alphabet[1]},
{alp_func[2](a)
for a in self.alphabet[2]})
# stack alphabet
stack = None
if stack_func is None:
stack = self.stack
stack_func = lambda x: x
else:
stack = {stack_func(gamma) for gamma in self.stack}
newsink = None
if self.sink is not None:
newsink = state_func(self.sink)
rand_stack_item = iter(self.stack).next()
tr = (collections.defaultdict(lambda: (newsink, rand_stack_item)),
collections.defaultdict(lambda: newsink),
collections.defaultdict(lambda: newsink))
for q, a, qn, gamma in self.itercalls():
if qn != self.sink:
tr[0][state_func(q),
alp_func[0](a)] = (state_func(qn), stack_func(gamma))
for q, a, qn in self.iterinterns():
if qn != self.sink:
tr[1][state_func(q), alp_func[1](a)] = state_func(qn)
for q, gamma, a, qn in self.iterreturns():
if qn != self.sink:
tr[2][state_func(q), stack_func(gamma), alp_func[2](a)] = \
state_func(qn)
delta_c = lambda q, a: tr[0][q, a]
delta_i = lambda q, a: tr[1][q, a]
delta_r = lambda q, gamma, a: tr[2][q, gamma, a]
delta = (delta_c, delta_i, delta_r)
return DVPA(alp, states, start, accept, stack, delta, tr, newsink)
def rename(self, state_func=None, alp_func=None):
if state_func is None:
state_func = mapping()
if alp_func is None:
# identity
alp_func = lambda x: x
start = {state_func(s) for s in self.start}
states = {state_func(s) for s in self.states}
accept = {state_func(s) for s in self.accept}
reject = {state_func(s) for s in self.reject}
tr = collections.defaultdict(set)
for s, a, ns in self.itertransitions():
tr[state_func(s), alp_func(a)].add(state_func(ns))
delta = lambda s, a: tr.get((s, a), empty_set)
return NFA(self.alphabet, states, start, accept, reject, delta, tr)
def rename(self, state_func=None, alp_func=None, stack_func=None):
# states first
if state_func is None:
state_func = mapping()
start = {state_func(s) for s in self.start}
states = {state_func(s) for s in self.states}
accept = {state_func(s) for s in self.accept}
# alphabet x3
alp = None
if alp_func is None:
# identity
alp = self.alphabet
alp_func = (lambda x: x, lambda x: x, lambda x: x)
else:
alp = ({alp_func[0](a)
for a in self.alphabet[0]
}, {alp_func[1](a)
for a in self.alphabet[1]},
{alp_func[2](a)
for a in self.alphabet[2]})
# stack alphabet
stack = None
if stack_func is None:
stack = self.stack
stack_func = lambda x: x
else:
stack = {stack_func(gamma) for gamma in self.stack}
tr = (collections.defaultdict(set), collections.defaultdict(set),
collections.defaultdict(set))
for q, a, qn, gamma in self.itercalls():
tr[0][state_func(q), alp_func[0](a)].add(
(state_func(qn), stack_func(gamma)))
for q, a, qn in self.iterinterns():
tr[1][state_func(q), alp_func[1](a)].add(state_func(qn))
for q, gamma, a, qn in self.iterreturns():
tr[2][state_func(q), stack_func(gamma), alp_func[2](a)].add(\
state_func(qn))
delta_c = lambda q, a: tr[0][q, a]
delta_i = lambda q, a: tr[1][q, a]
delta_r = lambda q, gamma, a: tr[2][q, gamma, a]
delta = (delta_c, delta_i, delta_r)
return VPA(alp, states, start, accept, stack, delta, tr)
def rename(self, state_func=None, alp_func=None):
if state_func is None:
state_func = mapping()
alp = None
if alp_func is None:
# identity
alp_func = lambda x: x
alp = self.alphabet
else:
alp = {alp_func(a) for a in self.alphabet}
start = state_func(self.start)
states = {state_func(s) for s in self.states}
accept = {state_func(s) for s in self.accept}
reject = {state_func(s) for s in self.reject}
newsink = None
if self.sink is not None:
newsink = state_func(self.sink)
tr = collections.defaultdict(lambda: newsink)
for q, a, qn in self.itertransitions():
tr[state_func(q), alp_func(a)] = state_func(qn)
delta = lambda q, a: tr[q, a]
return DFA(alp, states, start, accept, reject, delta, tr, newsink)