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 collections import defaultdict

class Graph:

    def __init__(self,vertices):
        self.V = vertices
        self.graph = []

    def addEdge(self,s,t,w):
        self.graph.append([s,t,w])

    def find(self, parent, i):
        if(parent[i] == i):
            return i
        return self.find(parent, parent[i])

    def union(self, parent, rank, x, y):
        xroot = self.find(parent, x)
        yroot = self.find(parent, y)

        if rank[xroot] < rank[yroot]:
            parent[xroot] = yroot
        elif rank[xroot] > rank[yroot]:
            parent[yroot] = xroot

        else :
            parent[yroot] = xroot
            rank[xroot] += 1

    def KruskalMST(self):
        sum = 0
        result = []
        i = 0
        e = 0

        self.graph = sorted(self.graph, key=lambda item:item[2])
        parent = []
        rank = []
        for node in range(self.V):
            parent.append(node)
            rank.append(0)

        while e < self.V - 1:
            s, t, w = self.graph[i]
            i+=1
            x = self.find(parent, s)
            y = self.find(parent, t)

            if x != y:
                e = e + 1
                result.append([s, t, w])
                self.union(parent, rank, x, y)

        for s,t,weight in result:
            sum +=  weight

        print(sum)

if __name__ == "__main__":
    V, E = (int(z) for z in input().split())
    g = Graph(V)

    for i in range(E):
        s, t, w = (int(z) for z in input().split())
        g.addEdge(s, t, w)

    g.KruskalMST()