There are a total of n courses you have to take, labeled from 0 to n - 1.
Some courses may have prerequisites, for example to take course 0 you have to first take course 1, which is expressed as a pair:[0,1]
Given the total number of courses and a list of prerequisite pairs, is it possible for you to finish all courses?
For example:
2, [[1,0]]
There are a total of 2 courses to take. To take course 1 you should have finished course 0. So it is possible.
2, [[1,0],[0,1]]
There are a total of 2 courses to take. To take course 1 you should have finished course 0, and to take course 0 you should also have finished course 1. So it is impossible.
Note:
- The input prerequisites is a graph represented by a list of edges, not adjacency matrices. Read more about how a graph is represented.
- You may assume that there are no duplicate edges in the input prerequisites.
As suggested by the hints, this problem is equivalent to detecting a cycle in the graph represented by prerequisites. Both BFS and DFS can be used to solve it using the idea of topological sort. If you find yourself unfamiliar with these concepts, you may refer to their wikipedia pages. Specifically, you may only need to refer to the link in the third hint to solve this problem.
Since pair<int, int> is inconvenient for the implementation of graph algorithms, we first transform it to a graph. If course u is a prerequisite of course v, we will add a directed edge from node u to node v.
BFS
BFS uses the indegrees of each node. We will first try to find a node with 0 indegree. If we fail to do so, there must be a cycle in the graph and we return false. Otherwise we have found one. We set its indegree to be -1 to prevent from visiting it again and reduce the indegrees of all its neighbors by 1. This process will be repeated for n (number of nodes) times. If we have not returned false, we will return true.
class Solution {
public:
bool canFinish(int numCourses, vector<pair<int, int>>& prerequisites) {
vector<unordered_set<int>> graph = make_graph(numCourses, prerequisites);
vector<int> degrees = compute_indegree(graph);
for (int i = 0; i < numCourses; i++) {
int j = 0;
for (; j < numCourses; j++)
if (!degrees[j]) break;
if (j == numCourses) return false;
degrees[j] = -1;
for (int neigh : graph[j])
degrees[neigh]--;
}
return true;
}
private:
vector<unordered_set<int>> make_graph(int numCourses, vector<pair<int, int>>& prerequisites) {
vector<unordered_set<int>> graph(numCourses);
for (auto pre : prerequisites)
graph[pre.second].insert(pre.first);
return graph;
}
vector<int> compute_indegree(vector<unordered_set<int>>& graph) {
vector<int> degrees(graph.size(), 0);
for (auto neighbors : graph)
for (int neigh : neighbors)
degrees[neigh]++;
return degrees;
}
};
本文介绍了一种算法,用于判断在存在先修课程约束的情况下是否能够完成所有课程。通过使用图论中的拓扑排序方法,结合BFS算法实现,有效地检测了课程依赖图中是否存在环路。
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