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 pprint import pprint

INF = float('inf')

n_nodes, m_edges = map(int, input().split())
edges = []
for _ in range(m_edges):
    u, v, w = map(int, input().split())
    edges.append([u, v, w])
# pprint(edges)

edges_sorted = sorted(edges, key=lambda e: e[2])
# pprint(edges_sorted)


# Kruskal's algorithm
def find_root(v, parents):
    if v == parents[v]:
        return v
    parents[v] = find_root(parents[v], parents)
    return parents[v]


def has_same_root(u, v, parents):
    return find_root(u, parents) == find_root(v, parents)


def unite(u, v, parents):
    root_u = find_root(u, parents)
    root_v = find_root(v, parents)
    parents[root_u] = root_v
    return parents


parents = [i for i in range(n_nodes)]
res = 0
for u, v, w in edges_sorted:
    if not has_same_root(u, v, parents):
        res += w
        parents = unite(u, v, parents)
print(res)