Find the sum of the weights of edges of the Minimum-Cost Arborescence with the root r for a given weighted directed graph G = (V, E).

Constraints

* 1 ≤ |V| ≤ 100
* 0 ≤ |E| ≤ 1,000
* 0 ≤ wi ≤ 10,000
* G has arborescence(s) with the root r

Input


|V| |E| r
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. r is the root of the Minimum-Cost Arborescence.

si and ti represent source and target verticess of i-th directed edge. wi represents the weight of the i-th directed edge.

Output

Print the sum of the weights the Minimum-Cost Arborescence.

Examples

Input

4 6 0
0 1 3
0 2 2
2 0 1
2 3 1
3 0 1
3 1 5


Output

6


Input

6 10 0
0 2 7
0 1 1
0 3 5
1 4 9
2 1 6
1 3 2
3 4 3
4 2 2
2 5 8
3 5 3


Output

11
V, E, r = map(int, raw_input().split())
es = [map(int, raw_input().split()) for i in xrange(E)]

def solve(V, es, r):
    mins = [(10**18, -1)]*V
    for s, t, w in es:
        mins[t] = min(mins[t], (w, s))
    mins[r] = (-1, -1)

    group = [0]*V
    comp = [0]*V
    cnt = 0

    used = [0]*V
    for v in xrange(V):
        if not used[v]:
            chain = []
            cur = v
            while not used[cur] and cur!=-1:
                chain.append(cur)
                used[cur] = 1
                cur = mins[cur][1]
            if cur!=-1:
                cycle = 0
                for e in chain:
                    group[e] = cnt
                    if e==cur:
                        cycle = 1
                        comp[cnt] = 1
                    if not cycle:
                        cnt += 1
                if cycle:
                    cnt += 1
            else:
                for e in chain:
                    group[e] = cnt
                    cnt += 1


    if cnt == V:
        return sum(map(lambda x:x[0], mins)) + 1

    res = sum(comp[group[v]]*mins[v][0] for v in xrange(V) if v!=r)

    n_es = []
    for s, t, w in es:
        gs = group[s]; gt = group[t]
        if gs == gt:
            continue
        if comp[gt]:
            n_es.append((gs, gt, w - mins[t][0]))
        else:
            n_es.append((gs, gt, w))

    return res + solve(cnt, n_es, group[r])

print solve(V, es, r)