Add automaton for word reduction in rewriting systems

sympy/combinatorics/rewritingsystem.py

@@ -2,6 +2,7 @@
 
 from sympy import S
 from sympy.combinatorics.free_groups import FreeGroupElement
+from sympy.combinatorics.rewritingsystem_fsm import State, StateMachine
 
 class RewritingSystem(object):
     '''
@@ -31,11 +32,23 @@ def __init__(self, group):
         # at any point
         self._max_exceeded = False
 
+        # Reduction automaton
+        self.reduction_automaton = None
+        self._new_rules = {}
+
         # dictionary of reductions
         self.rules = {}
         self.rules_cache = deque([], 50)
         self._init_rules()
 
+
+        # All the transition symbols in the automaton
+        generators = list(self.alphabet)
+        generators += [gen**-1 for gen in generators]
+        # Create a finite state machine as an instance of the StateMachine object
+        self.reduction_automaton = StateMachine('Reduction automaton for '+ repr(self.group), generators)
+        self.construct_automaton()
+
     def set_max(self, n):
         '''
         Set the maximum number of rules that can be defined
@@ -74,6 +87,9 @@ def _add_rule(self, r1, r2):
             self._max_exceeded = True
             raise RuntimeError("Too many rules were defined.")
         self.rules[r1] = r2
+        # Add the newly added rule to the `new_rules` dictionary.
+        if self.reduction_automaton:
+            self._new_rules[r1] = r2
 
     def add_rule(self, w1, w2, check=False):
         new_keys = set()
@@ -285,3 +301,164 @@ def reduce(self, word, exclude=None):
                 if new != prev:
                     again = True
         return new
+
+    def _compute_inverse_rules(self, rules):
+        '''
+        Compute the inverse rules for a given set of rules.
+        The inverse rules are used in the automaton for word reduction.
+
+        Arguments:
+            rules (dictionary): Rules for which the inverse rules are to computed.
+
+        Returns:
+            Dictionary of inverse_rules.
+
+        '''
+        inverse_rules = {}
+        for r in rules:
+            rule_key_inverse = r**-1
+            rule_value_inverse = (rules[r])**-1
+            if (rule_value_inverse < rule_key_inverse):
+                inverse_rules[rule_key_inverse] = rule_value_inverse
+            else:
+                inverse_rules[rule_value_inverse] = rule_key_inverse
+        return inverse_rules
+
+    def construct_automaton(self):
+        '''
+        Construct the automaton based on the set of reduction rules of the system.
+
+        Automata Design:
+        The accept states of the automaton are the proper prefixes of the left hand side of the rules.
+        The complete left hand side of the rules are the dead states of the automaton.
+
+        '''
+        self._add_to_automaton(self.rules)
+
+    def _add_to_automaton(self, rules):
+        '''
+        Add new states and transitions to the automaton.
+
+        Summary:
+        States corresponding to the new rules added to the system are computed and added to the automaton.
+        Transitions in the previously added states are also modified if necessary.
+
+        Arguments:
+            rules (dictionary) -- Dictionary of the newly added rules.
+
+        '''
+        # Automaton variables
+        automaton_alphabet = []
+        proper_prefixes = {}
+
+        # compute the inverses of all the new rules added
+        all_rules = rules
+        inverse_rules = self._compute_inverse_rules(all_rules)
+        all_rules.update(inverse_rules)
+
+        # Keep track of the accept_states.
+        accept_states = []
+
+
+        for rule in all_rules:
+            # The symbols present in the new rules are the symbols to be verified at each state.
+            # computes the automaton_alphabet, as the transitions solely depend upon the new states.
+            automaton_alphabet += rule.letter_form_elm
+            # Compute the proper prefixes for every rule.
+            proper_prefixes[rule] = []
+            letter_word_array = [s for s in rule.letter_form_elm]
+            len_letter_word_array = len(letter_word_array)
+            for i in range (1, len_letter_word_array):
+                letter_word_array[i] = letter_word_array[i-1]*letter_word_array[i]
+            proper_prefixes[rule] = letter_word_array
+            # Add dead states
+            if not rule in self.reduction_automaton.states:
+                self.reduction_automaton.add_state(rule, state_type='d', rh_rule=all_rules[rule])
+
+            for elem in proper_prefixes[rule]:
+                if not elem in self.reduction_automaton.states:
+                    self.reduction_automaton.add_state(elem, state_type='a')
+                    accept_states.append(elem)
+
+        automaton_alphabet = set(automaton_alphabet)
+
+        # Add new transitions for every state.
+        for state in self.reduction_automaton.states:
+            current_state_name = state
+            current_state_type = self.reduction_automaton.states[state].state_type
+            # Transitions will be modified only when suffixes of the current_state
+            # belongs to the proper_prefixes of the new rules.
+            # The rest are ignored if they cannot lead to a dead state after a finite number of transisitons.
+            if current_state_type == 's':
+                for letter in automaton_alphabet:
+                    if letter in self.reduction_automaton.states:
+                        self.reduction_automaton.states[state].add_transition(letter, letter)
+                    else:
+                        self.reduction_automaton.states[state].add_transition(letter, current_state_name)
+            elif current_state_type == 'a':
+                next_sub = current_state_name
+                # Check if the transition to any new state in posible.
+                while len(next_sub):
+                    if next_sub in accept_states:
+                        # Add accept states.
+                        for letter in automaton_alphabet:
+                            _next = current_state_name*letter
+                            while len(_next):
+                                if _next in self.reduction_automaton.states:
+                                    self.reduction_automaton.states[state].add_transition(letter, _next)
+                                    break
+                                elif len(_next) == 1:
+                                    self.reduction_automaton.states[state].add_transition(letter, 'start')
+                                _next = _next.subword(1, len(_next))
+                    next_sub = next_sub.subword(1, len(next_sub))
+
+        # Add transitions for new states. All symbols used in the automaton are considered here.
+        # Ignore this if `reduction_automaton.automaton_alphabet` = `automaton_alphabet`.
+        if len(self.reduction_automaton.automaton_alphabet) != len(automaton_alphabet):
+            for state in accept_states:
+                current_state_name = state
+                for letter in self.reduction_automaton.automaton_alphabet:
+                    next = current_state_name*letter
+                    len_next_word = len(next)
+                    while len(next):
+                        if next in self.reduction_automaton.states:
+                            self.reduction_automaton.states[state].add_transition(letter, next)
+                            break
+                        elif len(next) == 1:
+                            self.reduction_automaton.states[state].add_transition(letter, 'start')
+                        next = next.subword(1, len(next))
+
+    def reduce_using_automaton(self, word):
+        '''
+        Reduce a word using an automaton.
+
+        Summary:
+        All the symbols of the word are stored in an array and are given as the input to the automaton.
+        If the automaton reaches a dead state that subword is replaced and the automaton is run from the beginning.
+        The complete word has to be replaced when the word is read and the automaton reaches a dead state.
+        So, this process is repeated until the word is read completely and the automaton reaches the accept state.
+
+        Arguments:
+            word (instance of FreeGroupElement) -- Word that needs to be reduced.
+
+        '''
+        # Modify the automaton if new rules are found.
+        if self._new_rules:
+            self._add_to_automaton(self._new_rules)
+            self._new_rules = {}
+
+        flag = 1
+        while flag:
+            flag = 0
+            current_state = self.reduction_automaton.states['start']
+            word_array = [s for s in word.letter_form_elm]
+            for i in range (0, len(word_array)):
+                next_state_name = current_state.transitions[word_array[i]]
+                next_state = self.reduction_automaton.states[next_state_name]
+                if next_state.state_type == 'd':
+                    subst = next_state.rh_rule
+                    word = word.substituted_word(i - len(next_state_name) + 1, i+1, subst)
+                    flag = 1
+                    break
+                current_state = next_state
+        return word

sympy/combinatorics/rewritingsystem_fsm.py

@@ -0,0 +1,60 @@
+class State(object):
+    '''
+    A representation of a state managed by a ``StateMachine``.
+
+    Attributes:
+        name (instance of FreeGroupElement or string) -- State name which is also assigned to the Machine.
+        transisitons (OrderedDict) -- Represents all the transitions of the state object.
+        state_type (string) -- Denotes the type (accept/start/dead) of the state.
+        rh_rule (instance of FreeGroupElement) -- right hand rule for dead state.
+        state_machine (instance of StateMachine object) -- The finite state machine that the state belongs to.
+    '''
+
+    def __init__(self, name, state_machine, state_type=None, rh_rule=None):
+        self.name = name
+        self.transitions = {}
+        self.state_machine = state_machine
+        self.state_type = state_type[0]
+        self.rh_rule = rh_rule
+
+    def add_transition(self, letter, state):
+        '''
+        Add a transition from the current state to a new state.
+
+        Keyword Arguments:
+            letter -- The alphabet element the current state reads to make the state transition.
+            state -- This will be an instance of the State object which represents a new state after in the transition after the alphabet is read.
+
+        '''
+        self.transitions[letter] = state
+
+class StateMachine(object):
+    '''
+    Representation of a finite state machine the manages the states and the transitions of the automaton.
+
+    Attributes:
+        states (dictionary) -- Collection of all registered `State` objects.
+        name (str) -- Name of the state machine.
+    '''
+
+    def __init__(self, name, automaton_alphabet):
+        self.name = name
+        self.automaton_alphabet = automaton_alphabet
+        self.states = {} # Contains all the states in the machine.
+        self.add_state('start', state_type='s')
+
+    def add_state(self, state_name, state_type=None, rh_rule=None):
+        '''
+        Instantiate a state object and stores it in the 'states' dictionary.
+
+        Arguments:
+            state_name (instance of FreeGroupElement or string) -- name of the new states.
+            state_type (string) -- Denotes the type (accept/start/dead) of the state added.
+            rh_rule (instance of FreeGroupElement) -- right hand rule for dead state.
+
+        '''
+        new_state = State(state_name, self, state_type, rh_rule)
+        self.states[state_name] = new_state
+
+    def __repr__(self):
+        return "%s" % (self.name)

sympy/combinatorics/tests/test_rewriting.py

@@ -12,6 +12,10 @@ def test_rewriting():
     assert G.reduce(b**3*a**4*b**-2*a) == a**5*b
     assert G.equals(b**2*a**-1*b, b**4*a**-1*b**-1)
 
+    assert R.reduce_using_automaton(b*a*a**2*b**-1) == a**3
+    assert R.reduce_using_automaton(b**3*a**4*b**-2*a) == a**5*b
+    assert R.reduce_using_automaton(b**-1*a) == a*b**-1
+
     G = FpGroup(F, [a**3, b**3, (a*b)**2])
     R = G._rewriting_system
     R.make_confluent()
@@ -21,3 +25,16 @@ def test_rewriting():
     # but also the system should actually be confluent
     assert R._check_confluence()
     assert G.reduce(b*a**-1*b**-1*a**3*b**4*a**-1*b**-15) == a**-1*b**-1
+    # check for automaton reduction
+    assert R.reduce_using_automaton(b*a**-1*b**-1*a**3*b**4*a**-1*b**-15) == a**-1*b**-1
+
+    G = FpGroup(F, [a**2, b**3, (a*b)**4])
+    R = G._rewriting_system
+    assert G.reduce(a**2*b**-2*a**2*b) == b**-1
+    assert R.reduce_using_automaton(a**2*b**-2*a**2*b) == b**-1
+    assert G.reduce(a**3*b**-2*a**2*b) == a**-1*b**-1
+    assert R.reduce_using_automaton(a**3*b**-2*a**2*b) == a**-1*b**-1
+    # Check after adding a rule
+    R.add_rule(a**2, b)
+    assert R.reduce_using_automaton(a**2*b**-2*a**2*b) == b**-1
+    assert R.reduce_using_automaton(a**4*b**-2*a**2*b**3) == b