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:
#!/usr/bin/env python3

from collections import defaultdict
# クラスカル法を使う

V, E = map(int, input().split())
D = 0
tree = []
vertices = defaultdict(set)
for i in range(V):
    tree.append(i)          # 全ての頂点は自分の頂点 index と同じ index の木に属す
    vertices[i].add(i)

edges = []
for i in range(E):
    s, t, d = map(int, input().split())
    edges.append((s, t, d))

edges.sort(key=lambda x: x[2])
while edges:
    if V == 1:
        break
    s, t, d = edges.pop(0)
    if tree[s] != tree[t]:
        new = min(tree[s], tree[t])
        old = max(tree[s], tree[t])
        vertices[new] = vertices[new] | vertices[old]
        for vertex in vertices[old]:
            tree[vertex] = new

        D += d
        V -= 1
print(D)