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
import sys


class PriorityQueue:
    def __init__(self):
        self._queue = []

    def push(self, value):
        heappush(self._queue, value)

    def pop(self):
        return heappop(self._queue)

    @property
    def empty(self):
        return not self._queue

    def __len__(self):
        return len(self._queue)

    def __contains__(self, item):
        return item in self._queue


v, e = map(int, input().split())
if v == 1:
    print(0)
    sys.exit()
edge = [[] for _ in range(v)]
for _ in range(e):
    s, t, w = map(int, input().split())
    # 無向グラフ
    edge[s].append((w, t))
    edge[t].append((w, s))

V = set()
pq = PriorityQueue()
weight = 0
V.add(0)
for i in edge[0]:
    pq.push(i)

while True:
    nw, nv = pq.pop()
    if nv in V:
        continue
    else:
        weight += nw
        V.add(nv)
        for i in edge[nv]:
            pq.push(i)

    if len(V) == v:
        break

print(weight)