def nfa_to_dfa(old_machine, debug=None):
"""
Given a nondeterministic Machine, return a new equivalent
Machine which is deterministic.
"""
# We build a new machine whose states correspond to sets of states
# in the old machine. Initially we add a new state corresponding to
# the epsilon-closure of each initial old state. Then we give transitions
# to each new state which are the union of all transitions out of any
# of the corresponding old states. The new state reached on a given
# character is the one corresponding to the set of states reachable
# on that character from any of the old states. As new combinations of
# old states are created, new states are added as needed until closure
# is reached.
new_machine = machines.FastMachine()
state_map = StateMap(new_machine)
# Seed the process using the initial states of the old machine.
# Make the corresponding new states into initial states of the new
# machine with the same names.
for (key, old_state) in old_machine.initial_states.items():
new_state = state_map.old_to_new(epsilon_closure(old_state))
new_machine.make_initial_state(key, new_state)
# Tricky bit here: we add things to the end of this list while we're
# iterating over it. The iteration stops when closure is achieved.
for new_state in new_machine.states:
transitions = TransitionMap()
for old_state in state_map.new_to_old(new_state).keys():
for event, old_target_states in old_state.transitions.items():
if event and old_target_states:
transitions.add_set(event,
set_epsilon_closure(old_target_states))
for event, old_states in transitions.items():
new_machine.add_transitions(new_state, event,
state_map.old_to_new(old_states))
if debug:
debug.write("\n===== State Mapping =====\n")
state_map.dump(debug)
return new_machine
def nfa_to_dfa(old_machine, debug=None):
"""
Given a nondeterministic Machine, return a new equivalent
Machine which is deterministic.
"""
# We build a new machine whose states correspond to sets of states
# in the old machine. Initially we add a new state corresponding to
# the epsilon-closure of each initial old state. Then we give transitions
# to each new state which are the union of all transitions out of any
# of the corresponding old states. The new state reached on a given
# character is the one corresponding to the set of states reachable
# on that character from any of the old states. As new combinations of
# old states are created, new states are added as needed until closure
# is reached.
new_machine = machines.FastMachine()
state_map = StateMap(new_machine)
# Seed the process using the initial states of the old machine.
# Make the corresponding new states into initial states of the new
# machine with the same names.
for (key, old_state) in old_machine.initial_states.items():
new_state = state_map.old_to_new(epsilon_closure(old_state))
new_machine.make_initial_state(key, new_state)
# Tricky bit here: we add things to the end of this list while we're
# iterating over it. The iteration stops when closure is achieved.
for new_state in new_machine.states:
transitions = TransitionMap()
for old_state in state_map.new_to_old(new_state).keys():
for event, old_target_states in old_state.transitions.items():
if event and old_target_states:
transitions.add_set(
event, set_epsilon_closure(old_target_states))
for event, old_states in transitions.items():
new_machine.add_transitions(
new_state, event, state_map.old_to_new(old_states))
if debug:
debug.write("\n===== State Mapping =====\n")
state_map.dump(debug)
return new_machine
def __init__(self):
# Preinitialise the list of empty transitions, because
# the nfa-to-dfa algorithm needs it
#self.transitions = {'':[]}
self.transitions = TransitionMap()
self.action_priority = LOWEST_PRIORITY
class Node:
"""A state of an NFA or DFA."""
transitions = None # TransitionMap
action = None # Action
action_priority = None # integer
number = 0 # for debug output
epsilon_closure = None # used by nfa_to_dfa()
def __init__(self):
# Preinitialise the list of empty transitions, because
# the nfa-to-dfa algorithm needs it
#self.transitions = {'':[]}
self.transitions = TransitionMap()
self.action_priority = LOWEST_PRIORITY
def destroy(self):
#print "Destroying", self ###
self.transitions = None
self.action = None
self.epsilon_closure = None
def add_transition(self, event, new_state):
self.transitions.add(event, new_state)
def link_to(self, state):
"""Add an epsilon-move from this state to another state."""
self.add_transition('', state)
def set_action(self, action, priority):
"""Make this an accepting state with the given action. If
there is already an action, choose the action with highest
priority."""
if priority > self.action_priority:
self.action = action
self.action_priority = priority
def get_action(self):
return self.action
def get_action_priority(self):
return self.action_priority
# def merge_actions(self, other_state):
# """Merge actions of other state into this state according
# to their priorities."""
# action = other_state.get_action()
# priority = other_state.get_action_priority()
# self.set_action(action, priority)
def is_accepting(self):
return self.action is not None
def __str__(self):
return "State %d" % self.number
def dump(self, file):
import string
# Header
file.write(" State %d:\n" % self.number)
# Transitions
# self.dump_transitions(file)
self.transitions.dump(file)
# Action
action = self.action
priority = self.action_priority
if action is not None:
file.write(" %s [priority %d]\n" % (action, priority))
def __init__(self):
# Preinitialise the list of empty transitions, because
# the nfa-to-dfa algorithm needs it
#self.transitions = {'':[]}
self.transitions = TransitionMap()
self.action_priority = LOWEST_PRIORITY
class Node:
"""A state of an NFA or DFA."""
transitions = None # TransitionMap
action = None # Action
action_priority = None # integer
number = 0 # for debug output
epsilon_closure = None # used by nfa_to_dfa()
def __init__(self):
# Preinitialise the list of empty transitions, because
# the nfa-to-dfa algorithm needs it
#self.transitions = {'':[]}
self.transitions = TransitionMap()
self.action_priority = LOWEST_PRIORITY
def destroy(self):
#print "Destroying", self ###
self.transitions = None
self.action = None
self.epsilon_closure = None
def add_transition(self, event, new_state):
self.transitions.add(event, new_state)
def link_to(self, state):
"""Add an epsilon-move from this state to another state."""
self.add_transition('', state)
def set_action(self, action, priority):
"""Make this an accepting state with the given action. If
there is already an action, choose the action with highest
priority."""
if priority > self.action_priority:
self.action = action
self.action_priority = priority
def get_action(self):
return self.action
def get_action_priority(self):
return self.action_priority
# def merge_actions(self, other_state):
# """Merge actions of other state into this state according
# to their priorities."""
# action = other_state.get_action()
# priority = other_state.get_action_priority()
# self.set_action(action, priority)
def is_accepting(self):
return self.action is not None
def __str__(self):
return "State %d" % self.number
def dump(self, file):
import string
# Header
file.write(" State %d:\n" % self.number)
# Transitions
# self.dump_transitions(file)
self.transitions.dump(file)
# Action
action = self.action
priority = self.action_priority
if action is not None:
file.write(" %s [priority %d]\n" % (action, priority))