import sys from scipy.sparse.csgraph import minimum_spanning_tree from scipy.sparse import csr_matrix input = sys.stdin.buffer.readline class UnionFind: def __init__(self, n): self.n = n self.parent = [i for i in range(n)] self.height = [1] * n self.size = [1] * n def find(self, x): if self.parent[x] == x: return x else: self.parent[x] = self.find(self.parent[x]) return self.parent[x] def unite(self, x, y): x = self.find(x) y = self.find(y) if x != y: if self.height[x] < self.height[y]: self.parent[x] = y self.size[y] += self.size[x] else: self.parent[y] = x self.size[x] += self.size[y] if self.height[x] == self.height[y]: self.height[x] += 1 def issame(self, x, y): return self.find(x) == self.find(y) def group_size(self, x): return self.size[self.find(x)] def group_members(self, x): root = self.find(x) return [i for i in range(self.n) if self.find(i) == root] def roots(self): return [i for i, x in enumerate(self.parent) if i == x] def group_count(self): return len(self.roots()) N, M, K = map(int, input().split()) ABC = [] for _ in range(M): a, b, c = map(int, input().split()) a -= 1 b -= 1 ABC.append([a, b, c]) cost = 0 uf = UnionFind(N) for _ in range(K): e = int(input()) - 1 a, b, c = ABC[e] uf.unite(a, b) cost += c compress_dict = {x: i for i, x in enumerate(uf.roots())} compress_N = uf.group_count() length, frm, to = [], [], [] for a, b, c in ABC: a, b = uf.find(a), uf.find(b) if a == b: continue a, b = compress_dict[a], compress_dict[b] length.append(c) frm.append(a) to.append(b) matr = csr_matrix((length, (frm, to)), shape=(N, N)) T = minimum_spanning_tree(matr) cost += int(T.sum()) ans = sum(c for _, _, c in ABC) - cost print(ans)