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:
V, E = map(int, input().split())

PAR = list(range(V))
 
def root(x):
    if PAR[x] == x:
        return x
    else:
        PAR[x] = root(PAR[x])
        return PAR[x]
 
def same(x, y):
    return root(x) == root(y)
 
def unite(x, y):
    x = root(x)
    y = root(y)
    
    if x == y:
        return
    
    PAR[max(x, y)] = min(x, y)


class Edge:
    def __init__(self, u, v, cost):
        self.u = u
        self.v = v
        self.cost = cost
        
        

EDGES = []
for _ in range(E):
    s, t, w = map(int, input().split())
    EDGES.append(Edge(s, t, w))
    
def kruskal():
    edges = sorted(EDGES, key=lambda a: a.cost )
    res = 0
    for edge in edges:
        if (not same(edge.u, edge.v)):
            unite(edge.u, edge.v)
            res += edge.cost
    
    return res
    
print(kruskal())