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 heappush, heappop
class Prim:
    """ find minimum spanning tree by Prim's algorithm
    """

    def __init__(self, V, E, start=0, INF=10**9):
        """ V: the number of vertexes
            E: adjacency list (undirected graph)
            start: start vertex
            INF: Infinity cost
        """
        self.prim(V, E, start, INF)

    def prim(self, V, E, start=0, INF=10**9):
        used = [False] * V
        self.mincost = 0
        que = []
        heappush(que, (0, 0))
        while len(que) > 0:
            cost, v = heappop(que)
            if used[v]: continue
            used[v] = True
            self.mincost += cost
            for to, c in E[v]:
                heappush(que, (c, to))

    def minCost(self):
        return self.mincost
    

    
V, E = map(int, input().split())
edge = [[] for _ in range(V)]
for _ in range(E):
    s, t, w = map(int, input().split())
    edge[s].append((t, w))
    edge[t].append((s, w))

msp = Prim(V, edge)
print(msp.minCost())