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 PYTHON):

Solution:
class UnionFindTree:
    def __init__(self, V):
        self.parent = [i for i in range(V)]

    def root(self, x):
        if self.parent[x] == x:
            return x
        self.parent[x] = self.root(self.parent[x])
        return self.parent[x]

    def unite(self, x, y):
        rx = self.root(x)
        ry = self.root(y)
        self.parent[rx] = ry
        return

    def find(self, x, y):
        return self.root(x) == self.root(y)

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

    def __lt__(self, right):
        return self.w < right.w

def Kruscal(edges, V):
    utf = UnionFindTree(V)
    res = 0
    edges.sort()
    for e in edges:
        s = e.s
        t = e.t
        if not utf.find(e.s, e.t):
            res += e.w
            utf.unite(e.s, e.t)
    return res

def main():
    [V, E] = map(int, (raw_input()).split(" "))
    edges = [None]*E
    for i in range(E):
        [s,t,w] = map(int, (raw_input()).split(" "))
        edges[i] = Edge(s,t,w)

    print Kruscal(edges, V)

if __name__ == "__main__":
    main()