def __init__(self, state_machine): self.__depth = 0 self.sm = state_machine self.empty_list = [] self.result = dict((i, []) for i in self.sm.states.iterkeys()) self.dangerous_positioning_state_set = set() TreeWalker.__init__(self)
def __init__(self, TheAnalyzer, CompressionType, AvailableStateIndexSet): self.__depth = 0 self.analyzer = TheAnalyzer self.available_set = AvailableStateIndexSet self.uniform_f = (CompressionType == E_Compression.PATH_UNIFORM) self.result = [] TreeWalker.__init__(self)
def __init__(self): self.path = [] self.depth = 0 self.current = Count() self.result = Count() self.known_db = {} # state_index --> count TreeWalker.__init__(self)
def __init__(self, TheAnalyzer, CompressionType, AvailableStateIndexSet): self.__depth = 0 self.analyzer = TheAnalyzer self.available_set = AvailableStateIndexSet self.uniform_f = CompressionType == E_Compression.PATH_UNIFORM self.result = [] self.info_db = defaultdict(list) TreeWalker.__init__(self)
def __init__(self, state_machine, ToDB): self.sm = state_machine self.empty_list = [] self.to_db = ToDB self.result = dict((i, []) for i in self.sm.states.iterkeys()) self.path = [] # Each state is a 'on the path to itself', i.e. it holds # 'i in path_element_db[i]'. self.path_element_db = dict((i,set([i])) for i in self.sm.states.iterkeys()) TreeWalker.__init__(self)
def __init__(self, SM_A, SM_B, result=None): self.original = SM_A self.admissible = SM_B if result is None: init_state_index = index.map_state_combination_to_index((SM_A.init_state_index, SM_B.init_state_index)) state = self.get_state_core(SM_A.init_state_index) self.result = StateMachine(InitStateIndex = init_state_index, InitState = state) else: self.result = result self.path = [] # Use 'operation_index' to get a unique index that allows to indicate # that 'SM_B' is no longer involved. Also, it ensures that the # generated state indices from (a_state_index, operation_index) are # unique. self.operation_index = index.get() TreeWalker.__init__(self)
def __init__(self, SM_A, SM_B, result=None): self.original = SM_A self.admissible = SM_B if result is None: init_state_index = index.map_state_combination_to_index( (SM_A.init_state_index, SM_B.init_state_index)) state = self.get_state_core(SM_A.init_state_index) self.result = StateMachine(InitStateIndex=init_state_index, InitState=state) else: self.result = result self.path = [] # Use 'operation_index' to get a unique index that allows to indicate # that 'SM_B' is no longer involved. Also, it ensures that the # generated state indices from (a_state_index, operation_index) are # unique. self.operation_index = index.get() TreeWalker.__init__(self)
def __init__(self, SM_A, SM_B, StartingSM=None): self.original = SM_A self.admissible = SM_B if StartingSM is None: self.result = StateMachine(InitStateIndex = index.map_state_combination_to_index((SM_A.init_state_index, SM_B.init_state_index)), InitState = self.get_state_core(SM_A.init_state_index, SM_B.init_state_index)) else: self.result = StartingSM # TODO: Think if 'state_db' cannot be replaced by 'result' self.state_db = {} self.path = [] # Use 'operation_index' to get a unique index that allows to indicate # that 'SM_B' is no longer involved. Also, it ensures that the # generated state indices from (a_state_index, operation_index) are # unique. self.operation_index = index.get() TreeWalker.__init__(self)
def __init__(self, High, Low): self.high = High # State Machine of the higher priority pattern self.low = Low # State Machine of the lower priority pattern self.result = [] self.done_set = set() TreeWalker.__init__(self)
def __init__(self, TheExaminer): self.examiner = TheExaminer self.mouths_touched_set = set() TreeWalker.__init__(self)
def __init__(self, SM): self.sm = SM self.depth = 0 self.result = Count(E_Count.VIRGIN, E_Count.VIRGIN, E_Count.VIRGIN, E_Count.VIRGIN) self.known_db = {} # state_index --> count TreeWalker.__init__(self)
def __init__(self, High, Low): self.high = High # DFA of the higher priority pattern self.low = Low # DFA of the lower priority pattern self.result = False # Low cannot outrun High self.done_set = set() TreeWalker.__init__(self)
def __init__(self, A, B): self.sm_a = A # State Machine of the higher priority pattern self.sm_b = B # State Machine of the lower priority pattern self.result = [] self.done_set = set() TreeWalker.__init__(self)
def __init__(self, A, B): self.sm_a = A # DFA of the higher priority pattern self.sm_b = B # DFA of the lower priority pattern self.result = False self.done_set = set() TreeWalker.__init__(self)
def __init__(self, SM): self.sm = SM self.depth = 0 self.result = Count(E_Count.VIRGIN, E_Count.VIRGIN) self.known_db = {} # state_index --> count TreeWalker.__init__(self)