Problem: Find the sum of weights of edges of the Minimum Spanning Tree for a given weighted undirected graph G = (V, E).

Constraints

* 1 ≤ |V| ≤ 10,000
* 0 ≤ |E| ≤ 100,000
* 0 ≤ wi ≤ 10,000
* The graph is connected
* There are no parallel edges
* There are no self-loops

Input


|V| |E|
s0 t0 w0
s1 t1 w1
:
s|E|-1 t|E|-1 w|E|-1


, where |V| is the number of vertices and |E| is the number of edges in the graph. The graph vertices are named with the numbers 0, 1,..., |V|-1 respectively.

si and ti represent source and target verticess of i-th edge (undirected) and wi represents the weight of the i-th edge.

Output

Print the sum of the weights of the Minimum Spanning Tree.

Examples

Input

4 6
0 1 2
1 2 1
2 3 1
3 0 1
0 2 3
1 3 5


Output

3


Input

6 9
0 1 1
0 2 3
1 2 1
1 3 7
2 4 1
1 4 3
3 4 1
3 5 1
4 5 6


Output

5

Solution (in PYTHON3):

Solution:
class Kruskal_UnionFind():
    # 無向グラフであるという前提に注意
    def __init__(self, N):
        self.edges = []
        self.rank = [0] * N
        self.par = [i for i in range(N)]
        self.counter = [1] * N

    def add(self, u, v, d):
        """
        :param u: 始点
        :param v: 終点
        :param d: コスト
        """
        self.edges.append([u, v, d])

    def find(self, x):
        if self.par[x] == x:
            return x
        else:
            self.par[x] = self.find(self.par[x])
            return self.par[x]

    def unite(self, x, y):
        x = self.find(x)
        y = self.find(y)
        if x != y:
            z = self.counter[x] + self.counter[y]
            self.counter[x], self.counter[y] = z, z
        if self.rank[x] < self.rank[y]:
            self.par[x] = y
        else:
            self.par[y] = x
            if self.rank[x] == self.rank[y]:
                self.rank[x] += 1

    def size(self, x):
        x = self.find(x)
        return self.counter[x]

    def same(self, x, y):
        return self.find(x) == self.find(y)

    def Kruskal(self):
        """
        :return: 最小全域木のコストの和
        """
        edges = sorted(self.edges, key=lambda x: x[2])  # costでself.edgesをソートする
        res = 0
        for e in edges:
            if not self.same(e[0], e[1]):
                self.unite(e[0], e[1])
                res += e[2]
        return res

V, E = map(int, input().split())
graph = Kruskal_UnionFind(V)
for i in range(E):
    s, t, w = map(int, input().split())
    graph.add(s, t, w)

print(graph.Kruskal())