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:
par  =[]
V, E = [int(s) for s in input().split()]
for i in range(V+1):
    par.append(i)

graph = []

for _ in range(E):
    x, y, w = [int(s) for s in input().split()]
    graph.append((x,y,w))

def find(x):
    if par[x] == x:
        return x
    else:
        par[x] = find(par[x])
        return par[x]

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

def union(x,y):
    x = find(x)
    y = find(y)
    if x != y:
        par[x] = y

graph = sorted(graph, key=lambda x: x[2])
ans = 0
for g in graph:
    if not same(g[0], g[1]):
        union(g[0], g[1])
        ans += g[2]
print(ans)