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 heapq


def main():
    nvertices, nedges = map(int, input().split())
    Adj = [[] for i in range(nvertices)]
    for i in range(nedges):
        u, v, w = map(int, input().split())
        Adj[u].append((v, w))
        Adj[v].append((u, w))

    INF = float('inf')
    Q = [(0, 0)]
    for i in range(1, nvertices):
        Q.append((INF, i))
    heapq.heapify(Q)
    key = [INF] * nvertices
    key[0] = 0
    done = [False] * nvertices
    ans = 0
    while Q:
        val, u = heapq.heappop(Q)
        if val > key[u]:
            continue
        done[u] = True
        ans += val
        for v, w in Adj[u]:
            if not done[v] and w < key[v]:
                key[v] = w
                heapq.heappush(Q, (w, v))

    print(ans)


main()