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 heapq import heappush, heappop

line = input()
v, e = list(map(int, line.split()))
edge = {}
edge[0] = [[0, 0]]
for _ in range(0, e):
    line = input()
    s, t, w = list(map(int, line.split()))
    if s not in edge:
        edge[s]  = [[t, w]]
    else:
        edge[s] += [[t, w]]
    if t not in edge:
        edge[t]  = [[s, w]]
    else:
        edge[t] += [[s, w]]

def solve(v, edge):
    q = []
    vtx = set([i for i in range(0, v)])
    for t, w in edge[0]:
        heappush(q, (w, 0, t))
    vn = set([0])
    en = []
    cost = 0
    while len(vn) < v:
        w = s = t = 0
        qq = []
        while q:
            w, s, t = heappop(q)
            if s in vn and t not in vn:
                s, t = t, s
                break
            if s not in vn and t in vn:
                break
        vn.add(s)
        en += [(s, t)]
        cost += w
        for t, w in edge[s]:
            heappush(q, (w, s, t))
    return cost
        
print(solve(v, edge))