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:
class Edge:
    def __init__(self, s, t, w):
        self.s = s
        self.t = t
        self.w = w

def union(x, y):
    x = findSet(x)
    y = findSet(y)
    link(x, y)


def link(x, y):
    if r[x] > r[y]:
        p[y] = x

    else:
        p[x] = y
        if r[x] == r[y]: r[y] = r[y] + 1


def findSet(x):
    if x != p[x]:
        p[x] = findSet(p[x])

    return p[x]


def same(x, y):
    return findSet(x) == findSet(y)



if __name__ == '__main__':
    p, r = [], []

    n_V, n_E = map(int, input().split())

    for i in range(n_V):
        p.append(i)
        r.append(0)

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

    Es.sort(key=lambda e : e.w)

    sum_w = 0
    for e in Es:
        if not same(e.s, e.t):
            union(e.s, e.t)
            sum_w += e.w

    print(sum_w)