Clone an undirected graph. Each node in the graph contains a label and a list of its neighbors.
Nodes are labeled uniquely.
We use# as a separator for each node, and , as
a separator for node label and each neighbor of the node.
As an example, consider the serialized graph {0,1,2#1,2#2,2}.
The graph has a total of three nodes, and therefore contains three parts as separated by #.
0. Connect node 0 to
both nodes 1 and 2.1. Connect node 1 to
node 2.2. Connect node 2 to
node 2 (itself), thus forming a self-cycle.There are two solutions for this problem both based on BFS
one iterative another recursive.
The time complexity if O(V+E) and space is the same.
we need to maintain the que.
1. Recursive:
# Definition for a undirected graph node
# class UndirectedGraphNode:
# def __init__(self, x):
# self.label = x
# self.neighbors = []
class Solution:
# @param node, a undirected graph node
# @return a undirected graph node
def __init__(self):
self.dict={None:None}
def cloneGraph(self, node):
if node==None:
return None
head=UndirectedGraphNode(node.label)
self.dict[node]=head
for n in node.neighbors:
if n in self.dict:
head.neighbors.append(self.dict[n])
else:
neigh=self.cloneGraph(n)
head.neighbors.append(neigh)
return head
For iterative solution.
It looks more intuitive.
# Definition for a undirected graph node
# class UndirectedGraphNode:
# def __init__(self, x):
# self.label = x
# self.neighbors = []
class Solution:
# @param node, a undirected graph node
# @return a undirected graph node
def cloneGraph(self, node):
if node==None:
return node
que=[node]
head=UndirectedGraphNode(node.label)
dict={node:head}
while que:
curr=que.pop(0)
for n in curr.neighbors:
if n in dict:
dict[curr].neighbors.append(dict[n])
else:
que.append(n)
copy=UndirectedGraphNode(n.label)
dict[n]=copy
dict[curr].neighbors.append(copy)
return head
133. Clone Graph Leetcode Python
原文:http://blog.csdn.net/hyperbolechi/article/details/43951283