2012-04-24 55 views
1

美好的一天。基于Python中的策略实现深度优先遍历

我在执行基于Strategy.py类中定义的策略的深度优先搜索时遇到问题。还有一个图形和一个遍历类。遍历类负责很好地遍历图。

策略类如下:

class Strategy: 

init_priority = 0 

def __init__(self, init_pri = 0): 
    self.init_priority = init_pri 

def init(self, graph, node): 
    """Called at beginning of traversal process. Expected that 
    this will carry out any necessary initialisation for the 
    specific traversal process 
    """ 
    pass 

def visit(self, node, pri): 
    """Called whenever NODE is visited by a traversal process. 
    PRI is the priority associated with the node in the priority 
    queue used by the traversal process. 
    """ 
    pass 

def complete(self, node): 
    """Called at the end of all the processing performed in visiting NODE. 
    """ 
    pass 

def discover(self, nbr, node, weight, pri): 
    """Return the priority that should be associated with NBR when it is 
    added to the priority queue. 

    Called whenever NBR is discovered for the first time. NODE 
    is the node from which the neighbour was discovered, and 
    WEIGHT is the value on the edge from NODE to NBR. PRI is the 
    value associated with NODE in the priority queue, at the time 
    of discovering NBR. 
    """ 

def rediscover(self, nbr, node, weight, pri): 
    """Return the priority that should be associated with NBR when it is 
    added to the priority queue. 

    Called whenever NBR is rediscovered. NODE is the node from 
    which the neighbour is rediscovered, and WEIGHT is the value 
    associated with the edge from NODE to NBR. PRI is the 
    priority of NODE in the priority queue. It is provided in 
    case it is relevant to the traversal strategy (e.g. for Dijkstra's) 
    """ 
    pass 

def getResult(self): 
    """Called at the end of the traversal process. It should 
    return whatever is relevant or appropriate for the type of 
    traversal implemented by this strategy. 
    """ 
    pass 

我设法实现广度优先搜索如下:

class BreadthFirst(Strategy): 

sequence = None    # the sequence in which nodes are visted 
treeEdges = None   # the edges used to visit the nodes traversed 
root = -1     # the origin of the traversal 
last_pri = -1    # the most recent priority used 

def __init__(self): 
    """The BreadthFirst strategy uses an initial priority of 0""" 
    Strategy(0) 

def init(self, graph, node): 
    """We reset all our state information so that old traversals do not 
    affect the one that is about to start.""" 

    self.last_pri = self.init_priority 
    self.treeEdges = [] 
    self.sequence = [] 
    self.root = -1 

def visit(self, node, src, pri): 
    """Breadth first traversal pays no attention to weights.""" 
    self.sequence.append(node) 
    if src == -1: 
     self.root = node 
    else: 
     self.treeEdges.append((src, node)) 

def complete(self, node): 
    pass 

def discover(self, nbr, node, pri): 
    """Want FIFO behaviour so increment priority (ignore weights)""" 
    self.last_pri += 1 
    return self.last_pri 

def rediscover(self, nbr, node, pri): 
    """Rules for rediscovery same as for discovery (because weights are 
    ignored)""" 
    self.last_pri += 1 
    return self.last_pri 

def getResult(self): 
    """Return the details of the traversal as a dictionary.""" 
    return {"origin":self.root, 
      "tree":self.treeEdges, 
      "sequence":self.sequence} 

深度第一次是给我的时候麻烦,虽然。这是我到目前为止:

class DepthFirst(Strategy): 

forward = None    # the forward sequence in which nodes are visted 
back = None    # the backward sequence in which nodes are visited 
treeEdges = None   # the edges used to visit the nodes traversed    
cross = None 
root = -1     # the origin of the traversal 
last_pri = -1    # the most recent priority used 

def __init__(self): 
    """The DepthFirst strategy uses an initial priority of 0""" 
    Strategy(0) 

def init(self, graph, node): 
    """Called at beginning of traversal process. Expected that 
    this will carry out any necessary initialisation for the 
    specific traversal process 
    """ 
    self.last_pri = self.init_priority 
    self.treeEdges = [] 
    self.forward = [] 
    self.back = [] 
    self.cross = [] 

def visit(self, node, src, pri): 
    """Called whenever NODE is visited by a traversal process. 
    PRI is the priority associated with the node in the priority 
    queue used by the traversal process. 
    """ 
    self.forward.append(node) 
    if src == -1: 
     self.root = node 
    else: 
     self.treeEdges.append((src, node)) 


def complete(self, node): 
    """Called at the end of all the processing performed in visiting NODE. 
    """ 
    if node not in self.forward: 
     self.cross.append(node) 

def discover(self, nbr, node, pri): 
    """Return the priority that should be associated with NBR when it is 
    added to the priority queue. 

    Called whenever NBR is discovered for the first time. NODE 
    is the node from which the neighbour was discovered, and 
    WEIGHT is the value on the edge from NODE to NBR. PRI is the 
    value associated with NODE in the priority queue, at the time 
    of discovering NBR. 
    """ 
    self.forward.append((node, nbr)) 
    self.last_pri -= 1 
    return self.last_pri 

def rediscover(self, nbr, node, pri): 
    """Return the priority that should be associated with NBR when it is 
    added to the priority queue. 

    Called whenever NBR is rediscovered. NODE is the node from 
    which the neighbour is rediscovered, and WEIGHT is the value 
    associated with the edge from NODE to NBR. PRI is the 
    priority of NODE in the priority queue. It is provided in 
    case it is relevant to the traversal strategy (e.g. for Dijkstra's) 
    """ 
    self.back.append((nbr, node)) 
    self.last_pri -= 1 
    return self.last_pri 

def getResult(self): 
    """Called at the end of the traversal process. It should 
    return whatever is relevant or appropriate for the type of 
    traversal implemented by this strategy. 
    """ 
    return {"tree":self.treeEdges, 
      "forward":self.forward, 
      "back":self.back, 
      "cross":self.cross} 

任何提示,指针?他们将不胜感激。

回答

0

如果你只是写这两个,你会做通常的迭代循环,使用DFS堆栈和BFS队列。在这里你正在统一那些优先队列。所以你需要优先考虑这两个行为。对于DFS来说,这意味着每次添加某个内容时,它的优先级都会比以前更高(因此它会在内存之前出现) - 增加的正数很好。对于BFS而言,它需要比迄今为止添加的任何东西都要低(因为它在已经存在的东西之后出现) - 负数减少效果很好。

这只是我扫描你的代码而已。我可能是错的,我不打算详细看 - 我只是认为这是一个有趣的方式,看看可能有帮助的事情。

ps通过“作业”标记作业是正常的。如果你不这样做,人们会婊子。

+0

好,谢谢。 – Zeno 2012-04-24 22:30:47