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 prim_heap():
    used = [True] * n #True:不使用
    edgelist = []
    for e in edge[0]:
        heapq.heappush(edgelist,e)
    used[0] = False
    res = 0
    while len(edgelist) != 0:
        minedge = heapq.heappop(edgelist)
        if not used[minedge[1]]:
            continue
        v = minedge[1]
        used[v] = False
        for e in edge[v]:
            if used[e[1]]:
                heapq.heappush(edgelist,e)
        res += minedge[0]
    return res

#########################
n,w = map(int,input().split())

edge = [[] for i in range(n)]
#隣接リスト edge[i]:[コスト,行先]
for i in range(w):
    x,y,z = map(int,input().split())
    edge[x].append([z,y])
    edge[y].append([z,x])
print(prim_heap())