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 # 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)
