There is an undirected graph with n nodes, where each node is numbered between 0 and n - 1. You are given a 2D array graph, where graph[u] is an array of nodes that node u is adjacent to. More formally, for each v in graph[u], there is an undirected edge between node u and node v. The graph has the following properties:
- There are no self-edges (
graph[u]does not containu). - There are no parallel edges (
graph[u]does not contain duplicate values). - If
vis ingraph[u], thenuis ingraph[v](the graph is undirected). - The graph may not be connected, meaning there may be two nodes
uandvsuch that there is no path between them.
A graph is bipartite if the nodes can be partitioned into two independent sets A and B such that every edge in the graph connects a node in set A and a node in set B.
Return true if and only if it is bipartite.
Example 1:
Input: graph = [[1,2,3],[0,2],[0,1,3],[0,2]]
Output: false
Explanation: There is no way to partition the nodes into two independent sets such that every edge connects a node in one and a node in the other.
Example 2:
Input: graph = [[1,3],[0,2],[1,3],[0,2]]
Output: true
Explanation: We can partition the nodes into two sets: {0, 2} and {1, 3}.
Constraints:
-
graph.length == n -
1 <= n <= 100 -
0 <= graph[u].length < n -
0 <= graph[u][i] <= n - 1 -
graph[u]does not containu. - All the values of
graph[u]are unique. - If
graph[u]containsv, thengraph[v]containsu.
SOLUTION:
class Solution:
def DFS(self, graph, curr, visited, colors):
for j in graph[curr]:
if j not in visited:
visited.add(j)
colors[j] = not colors[curr]
if not self.DFS(graph, j, visited, colors):
return False
else:
if colors[j] == colors[curr]:
return False
return True
def isBipartite(self, graph: List[List[int]]) -> bool:
n = len(graph)
for i in range(n):
colors = [False for node in graph]
visited = {i}
if not self.DFS(graph, i, visited, colors):
return False
return True


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