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


n, m = map(int, input().split())

edges = []
for i in range(m):
    s, t, w = map(int, input().split())
    heapq.heappush(edges, (w, s, t))

cost = 0
roots = [i for i in range(n)]
clusters = {i: {i} for i in range(n)}

while len(edges) > 0:
    w, s, t = heapq.heappop(edges)

    if roots[s] != roots[t]:
        cluster = clusters.pop(roots[t])
        for elem in cluster:
            roots[elem] = roots[s]
        clusters[roots[s]] |= cluster
        cost += w

print(cost)