We can use both BFS and DFS.
Solution 1:
# T:O(n) S:O(n)
class Solution:
# @param node, a undirected graph node
# @return a undirected graph node
# @DFS
def cloneGraph(self, node):
def dfs(input, map):
if input in map:
return map[input]
output = UndirectedGraphNode(input.label)
map[input] = output
for neighbor in input.neighbors:
output.neighbors.append(dfs(neighbor, map))
return output
if node == None: return None
return dfs(node, {})
Run Time: 192 msSolution 2:
# T:O(n) S:O(n)
class Solution:
# @param node, a undirected graph node
# @return a undirected graph node
# @BFS
def cloneGraph(self, node):
if node == None: return None
queue, map = [], {}
newhead = UndirectedGraphNode(node.label)
queue.append(node)
map[node] = newhead
while queue:
curr = queue.pop()
for neighbor in curr.neighbors:
if neighbor not in map:
copy = UndirectedGraphNode(neighbor.label)
map[curr].neighbors.append(copy)
map[neighbor] = copy
queue.append(neighbor)
else:
# turn directed graph to undirected graph
map[curr].neighbors.append(map[neighbor])
return newhead
Run Time: 84 ms
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