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:

# input V, E
v, e = map(int, input().split())


# input weighted edges into priority queue
import heapq
h = []
for i in range(e):
	s, t, w = map(int, input().split())
	heapq.heappush(h, (w, s, t))


# initialize union find tree for vertices
p = [i for i in range(v)]
rank = [0 for i in range(v)]

def union(x, y):
 link(findSet(x), findSet(y))

def link(x, y):
 if rank[x] > rank[y]:
  p[y] = x
 else:
  p[x] = y
  if rank[x] == rank[y]:
   rank[y] = rank[y] + 1

def findSet(x):
 if x != p[x]:
  p[x] = findSet(p[x])
 return p[x]


def unite(x, y):
 union(x, y)

def same(x, y):
 x = findSet(x)
 y = findSet(y)
 if x == y:
  return True
 else :
  return False


# search MST
s = 0
for i in range(e):
	edge = heapq.heappop(h)
	if same(edge[1], edge[2]) == False:
		s = s + edge[0]
		unite(edge[1], edge[2])

# print sum of weights
print(s)