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| #======================================================================= | |
| # | |
| # Python Lexical Analyser | |
| # | |
| # Converting NFA to DFA | |
| # | |
| #======================================================================= | |
| from __future__ import absolute_import | |
| from . import Machines | |
| from .Machines import LOWEST_PRIORITY | |
| from .Transitions import TransitionMap | |
| 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): | |
| 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 set_epsilon_closure(state_set): | |
| """ | |
| Given a set of states, return the union of the epsilon | |
| closures of its member states. | |
| """ | |
| result = {} | |
| for state1 in state_set: | |
| for state2 in epsilon_closure(state1): | |
| result[state2] = 1 | |
| return result | |
| def epsilon_closure(state): | |
| """ | |
| Return the set of states reachable from the given state | |
| by epsilon moves. | |
| """ | |
| # Cache the result | |
| result = state.epsilon_closure | |
| if result is None: | |
| result = {} | |
| state.epsilon_closure = result | |
| add_to_epsilon_closure(result, state) | |
| return result | |
| def add_to_epsilon_closure(state_set, state): | |
| """ | |
| Recursively add to |state_set| states reachable from the given state | |
| by epsilon moves. | |
| """ | |
| if not state_set.get(state, 0): | |
| state_set[state] = 1 | |
| state_set_2 = state.transitions.get_epsilon() | |
| if state_set_2: | |
| for state2 in state_set_2: | |
| add_to_epsilon_closure(state_set, state2) | |
| class StateMap(object): | |
| """ | |
| Helper class used by nfa_to_dfa() to map back and forth between | |
| sets of states from the old machine and states of the new machine. | |
| """ | |
| new_machine = None # Machine | |
| old_to_new_dict = None # {(old_state,...) : new_state} | |
| new_to_old_dict = None # {id(new_state) : old_state_set} | |
| def __init__(self, new_machine): | |
| self.new_machine = new_machine | |
| self.old_to_new_dict = {} | |
| self.new_to_old_dict = {} | |
| def old_to_new(self, old_state_set): | |
| """ | |
| Return the state of the new machine corresponding to the | |
| set of old machine states represented by |state_set|. A new | |
| state will be created if necessary. If any of the old states | |
| are accepting states, the new state will be an accepting state | |
| with the highest priority action from the old states. | |
| """ | |
| key = self.make_key(old_state_set) | |
| new_state = self.old_to_new_dict.get(key, None) | |
| if not new_state: | |
| action = self.highest_priority_action(old_state_set) | |
| new_state = self.new_machine.new_state(action) | |
| self.old_to_new_dict[key] = new_state | |
| self.new_to_old_dict[id(new_state)] = old_state_set | |
| #for old_state in old_state_set.keys(): | |
| #new_state.merge_actions(old_state) | |
| return new_state | |
| def highest_priority_action(self, state_set): | |
| best_action = None | |
| best_priority = LOWEST_PRIORITY | |
| for state in state_set: | |
| priority = state.action_priority | |
| if priority > best_priority: | |
| best_action = state.action | |
| best_priority = priority | |
| return best_action | |
| # def old_to_new_set(self, old_state_set): | |
| # """ | |
| # Return the new state corresponding to a set of old states as | |
| # a singleton set. | |
| # """ | |
| # return {self.old_to_new(old_state_set):1} | |
| def new_to_old(self, new_state): | |
| """Given a new state, return a set of corresponding old states.""" | |
| return self.new_to_old_dict[id(new_state)] | |
| def make_key(self, state_set): | |
| """ | |
| Convert a set of states into a uniquified | |
| sorted tuple suitable for use as a dictionary key. | |
| """ | |
| lst = list(state_set) | |
| lst.sort() | |
| return tuple(lst) | |
| def dump(self, file): | |
| from .Transitions import state_set_str | |
| for new_state in self.new_machine.states: | |
| old_state_set = self.new_to_old_dict[id(new_state)] | |
| file.write(" State %s <-- %s\n" % ( | |
| new_state['number'], state_set_str(old_state_set))) | |