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
from itertools import accumulate

v, e = map(int, input().split())
g = [[] for _ in range(v)]
for i in range(e):
    s, t, d = map(int, input().split())
    g[s].append((d, t))#(重み, 次の頂点)
    g[t].append((d, s))#(重み, 次の頂点)

visitedv = [False] * v
visitedv[0] = True
#visitede = []
visitede = 0
candidate = []
for i in g[0]:
    heapq.heappush(candidate, i)
while len(candidate):
    #まだ使われていない頂点から最小のものを探す
    minedge = heapq.heappop(candidate)#(重み, 頂点)
    if visitedv[minedge[1]]:
        continue
    c = minedge[1]
    visitedv[c] = True
    #visitede.append(minedge[0])
    visitede += minedge[0]
    for i in g[c]:
        if not visitedv[i[1]]:
            heapq.heappush(candidate, i)

#print(list(accumulate(visitede))[-1])
print(visitede)