基于Python中的策略实现深度优先遍历

Question

美好的一天。

我在基于策略实现深度优先搜索时遇到问题，策略是在strategy.py类中定义的。还有一个图表和一个遍历类。遍历类负责，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

我设法实现了广度优先搜索，如下所示：

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}

深度优先是给我一个时间的麻烦。这是我到目前为止所做的：

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，指示？他们将非常感激。

Answer 1

如果您只是编写这两个，那么您将执行通常的迭代循环，使用DFS堆栈和BFS队列。在这里，您将统一具有优先级队列的那些。所以你需要优先考虑这两种行为。对于DFS来说，这意味着每次你添加的东西都比以前有更高的优先级（因此它在已经存在的东西之前出现） - 增加正数就可以了。对于BFS来说，它需要低于你到目前为止所添加的任何东西（因此它已经在已经存在的东西之后出现） - 减少负数的效果很好。

这只是我扫描你的代码所得到的。我可能错了，我不打算详细看 - 我只是觉得这是一种有趣的方式来看待可能会有所帮助的事情。

ps用“家庭作业”标记家庭作业是正常的。如果你不这样做，人们就会婊子。