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 heapq import heappop,heappush,heapify

class Graph():
    def __init__(self,n,edge,directed=False):
        self.n = n
        self.graph = [[] for _ in range(n)]
        for e in edge:
            self.graph[e[0]].append((e[1],e[2]))
            if not directed:
                self.graph[e[1]].append((e[0],e[2]))
                
    def prim(self):
        used = [False for _ in range(self.n)]
        used[0] = True
        heap = [(cost,adj) for adj,cost in self.graph[0]]
        heapify(heap)
        res = 0
        while heap:
            cost,node = heappop(heap)
            if used[node]:
                continue
            used[node] = True
            res += cost
            for adj,adjcost in self.graph[node]:
                if used[adj]:
                    continue
                heappush(heap,(adjcost,adj))
        return res
        
import sys
input = sys.stdin.readline

V,E = map(int,input().split())
edge = [tuple(map(int,input().split())) for _ in range(E)]

g = Graph(V,edge)

print(g.prim())