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:
import sys
from itertools import islice

def kruskal(v_count: int, edges: list) -> int:
    tree = [-1]*v_count

    def get_root(x):
        if tree[x] < 0:
            return x
        tree[x] = get_root(tree[x])
        return tree[x]

    def unite(a):
        x, y = get_root(a[1]), get_root(a[2])
        if x != y:
            big, small = (x, y) if tree[x] < tree[y] else (y, x)
            tree[big] += tree[small]
            tree[small] = big
        return x != y

    cost = 0
    for w, _s, _t in islice(filter(unite, sorted(edges)), v_count-1):
        cost += w
    return cost

V, E = map(int, input().split())
edges = [(w, s, t) for s, t, w in (map(int, l.split()) for l in sys.stdin)]
print(kruskal(V, edges))