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:
from collections import defaultdict
import heapq

V, E = map(int, input().split())

edges = defaultdict(list)

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

in_tree = [False] * V
ans = 0
start = 0
in_tree[start] = True

q = [(w, start, t) for t, w in edges[start]]
heapq.heapify(q)

while q:
    w, s, t = heapq.heappop(q)
    if in_tree[s] == in_tree[t]:
        continue
    ans += w
    in_tree[t] = True
    for tt, w in edges[t]:
        heapq.heappush(q, (w, t, tt))

print(ans)