本文整理汇总了Python中stats.Stats.stat_node_ignoring方法的典型用法代码示例。如果您正苦于以下问题：Python Stats.stat_node_ignoring方法的具体用法？Python Stats.stat_node_ignoring怎么用？Python Stats.stat_node_ignoring使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类stats.Stats的用法示例。
在下文中一共展示了Stats.stat_node_ignoring方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from stats import Stats [as 别名]
# 或者: from stats.Stats import stat_node_ignoring [as 别名]
#.........这里部分代码省略.........
return None
fringe.print_contents()
currNode = fringe.pop()
if (problem.is_goal(currNode)):
return self.path(root, currNode)
successors = self.expand(problem, currNode)
if problem.maximum_depth > 0 and len([x for x in successors if x.depth > problem.maximum_depth]) > 0:
return None
fringe.extend(successors)
def graphsearch(self, problem, strategy):
"""
Searches for a solution to the given problem using the graphsearch
algorithm and a given search strategy.
"""
root = Node(problem.start_state, None, Action(0, None))
self.stats.stat_node_creation(root)
fringe = Fringe(strategy)
fringe.insert(root)
closed = set([])
while True:
if fringe == []:
return None
fringe.print_contents()
currNode = fringe.pop()
if (problem.is_goal(currNode)):
return self.path(root, currNode)
if not currNode.state in closed:
closed.add(currNode.state)
successors = self.expand(problem, currNode)
accepted_successors = [item for item in successors if not item.state in closed]
rejected_successors = [item for item in successors if item.state in closed]
self.stats.stat_node_deletion(rejected_successors)
if problem.maximum_depth > 0 and len([x for x in accepted_successors if x.depth > problem.maximum_depth]) > 0:
return None
fringe.extend(accepted_successors)
else:
self.stats.stat_node_ignoring(currNode)
def RBFS(self, problem):
"""
Searches for a solution to the given problem using the RBFS algorithm.
"""
def recursion(problem, cNode, cLimit):
if problem.is_goal(cNode):
return ([cNode], 0)
successors = self.expand(problem, cNode)
if successors == []:
return (None, INFINITY)
for node in successors:
node.f = max(cNode.f, problem.f(node))
while True:
successors.sort(key=lambda x: x.f)
best = successors[0]
if best.f > cLimit:
self.stats.stat_node_deletion(successors)
return (None, best.f)
limit = min(cLimit, successors[1].f) if len(successors) > 1 else cLimit
rnl, rlim = recursion(problem, best, limit)
if rnl != None:
rnl.insert(0, cNode)
return (rnl, 0)
best.f = rlim
root = Node(problem.start_state, None, Action(0, None))
self.stats.stat_node_creation(root)
return recursion(problem, root, INFINITY)[0][1:]
def iterative_deepening(self, problem, max_depth=1):
"""
Searches for a solution to the given problem using the Iterative
Deepening search algorithm.
"""
if max_depth > problem.maximum_depth:
return None
created_nodes_start = self.stats.created_nodes
root = Node(problem.start_state, None, Action(0, None))
fringe = Fringe(SearchStrategy.DEPTH_FIRST)
fringe.insert(root)
while True:
if fringe.empty():
break
fringe.print_contents()
currNode = fringe.pop()
if (problem.is_goal(currNode)):
return self.path(root, currNode)
if currNode.depth <= max_depth:
fringe.extend(self.expand(problem, currNode))
self.stats.deleted_nodes += self.stats.created_nodes - created_nodes_start
self.stats.calc_memory_usage()
return self.iterative_deepening(problem, max_depth+1)