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:
    MAX_N = 0
    PAR  = [] 
    RANK = []

    def __init__(self,n):
        self.MAX_N = n
        self.PAR = [ i for i in range(n)]
        self.RANK= [ 0 ] * n

    def find(self,x):
        if self.PAR[x] == x:
            return x
        else:
            self.PAR[x] = self.find(self.PAR[x])
            return self.PAR[x] 

    def unite(self,x,y):
        x = self.find(x)
        y = self.find(y)
        if x == y:
            return
        if self.RANK[x] < self.RANK[y]:
            self.PAR[x] = y
        else:
            self.PAR[y] = x
            if self.RANK[x] == self.RANK[y]:
                self.RANK[x] += 1

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

def kruskal(Edge):
    Edge.sort(key=lambda x:x[2])
    data = UnionFind(V)
    res = 0
    for i in range(E):
        u = Edge[i][0]
        v = Edge[i][1]
        d = Edge[i][2]
        if data.same(u,v) == False:
            data.unite(u,v)
            res += d
    return res

V,E = map(int,input().split())
Edge = []
for _ in range(E):
    Edge.append(list(map(int,input().split())))

ans = kruskal(Edge)
print(ans)