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 UnionFind:
    def __init__(self, n):
        self.n = n
        self.parents = [-1] * n

    def root(self, x):
        if self.parents[x] < 0:
            return x
        else:
            self.parents[x] = self.root(self.parents[x])
            return self.parents[x]

    def unite(self, x, y):
        x = self.root(x)
        y = self.root(y)

        if x == y:
            return

        if self.parents[x] > self.parents[y]:
            x, y = y, x

        self.parents[x] += self.parents[y]
        self.parents[y] = x

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


def main():

    V, E = map(int, input().split())

    # need sorted
    edge_q = sorted([tuple(map(int, input().split())) for _ in range(E)], key=lambda x: x[2])

    # kruskal
    ans = 0
    forest = UnionFind(V)
    for s, t, w in edge_q:
        if forest.same(s, t):
            continue
        forest.unite(s, t)
        ans += w
    print(ans)


if __name__ == '__main__':
    main()