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 UnionFind():
    def __init__(self,n):
        self.n=n
        self.parents = [i for i in range(n+1)]
        self.size = [1]*(n+1)
    def find(self,x):
        if self.parents[x]==x:
            return x
        else:
            self.parents[x]=self.find(self.parents[x])
            return self.parents[x]
    def unite(self,x,y):
        xRoot = self.find(x)
        yRoot = self.find(y)
        if xRoot == yRoot:
            return
        if self.size[xRoot]>self.size[yRoot]:
            self.parents[yRoot] = xRoot
            self.size[xRoot] += self.size[yRoot]
            self.size[yRoot] = 0
        else:
            self.parents[xRoot] = yRoot
            self.size[yRoot] += self.size[xRoot]
            self.size[xRoot] = 0

V,E = map(int,input().split())
tree = UnionFind(V)
edges = [list(map(int,input().split())) for _ in range(E)]
edges.sort(key=lambda x: x[2])
cost = 0
for s,t,w in edges:
    if tree.find(s) != tree.find(t):
        cost += w
        tree.unite(s,t)

print(cost)