import sys readline=sys.stdin.readline from collections import defaultdict class UnionFind: def __init__(self,n): self.n=n self.parents=[-1]*n def Find(self,x): stack=[] while self.parents[x]>=0: stack.append(x) x=self.parents[x] for y in stack: self.parents[y]=x return x def Union(self,x,y): x=self.Find(x) y=self.Find(y) if x==y: return if self.parents[x]>self.parents[y]: x,y=y,x self.parents[x]+=self.parents[y] self.parents[y]=x def Size(self,x): return -self.parents[self.Find(x)] def Same(self,x,y): return self.Find(x)==self.Find(y) def 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.parents) if x<0] def Group_Count(self): return len(self.Roots()) def All_Group_Members(self): group_members = defaultdict(list) for member in range(self.n): group_members[self.Find(member)].append(member) return group_members def __str__(self): return '\n'.join(f'{r}: {m}' for r, m in self.All_Group_Members().items()) class Graph: def __init__(self,V,edges=False,graph=False,directed=False,weighted=False,inf=float("inf")): self.V=V self.directed=directed self.weighted=weighted self.inf=inf if not graph: self.edges=edges self.graph=[[] for i in range(self.V)] if weighted: for i,j,d in self.edges: self.graph[i].append((j,d)) if not self.directed: self.graph[j].append((i,d)) else: for i,j in self.edges: self.graph[i].append(j) if not self.directed: self.graph[j].append(i) else: self.graph=graph self.edges=[] for i in range(self.V): if self.weighted: for j,d in self.graph[i]: if self.directed or not self.directed and i<=j: self.edges.append((i,j,d)) else: for j in self.graph[i]: if self.directed or not self.directed and i<=j: self.edges.append((i,j)) def Kruskal(self): UF=UnionFind(self.V) sorted_edges=sorted(self.edges,key=lambda x:x[2]) minimum_spnning_tree=[] for i,j,d in sorted_edges: if not UF.Same(i,j): UF.Union(i,j) minimum_spnning_tree.append((i,j,d)) return minimum_spnning_tree def SIV_DFS(self,s,bipartite_graph=False,cycle_detection=False,directed_acyclic=False,euler_tour=False,linked_components=False,lowlink=False,parents=False,postorder=False,preorder=False,subtree_size=False,topological_sort=False,unweighted_dist=False,weighted_dist=False): seen=[False]*self.V finished=[False]*self.V if directed_acyclic or cycle_detection or topological_sort: dag=True if euler_tour: et=[] if linked_components: lc=[] if lowlink: order=[None]*self.V ll=[None]*self.V idx=0 if parents or cycle_detection or lowlink or subtree_size: ps=[None]*self.V if postorder or topological_sort: post=[] if preorder: pre=[] if subtree_size: ss=[1]*self.V if unweighted_dist or bipartite_graph: uwd=[self.inf]*self.V uwd[s]=0 if weighted_dist: wd=[self.inf]*self.V wd[s]=0 stack=[(s,0)] if self.weighted else [s] while stack: if self.weighted: x,d=stack.pop() else: x=stack.pop() if not seen[x]: seen[x]=True stack.append((x,d) if self.weighted else x) if euler_tour: et.append(x) if linked_components: lc.append(x) if lowlink: order[x]=idx ll[x]=idx idx+=1 if preorder: pre.append(x) for y in self.graph[x]: if self.weighted: y,d=y if not seen[y]: stack.append((y,d) if self.weighted else y) if parents or cycle_detection or lowlink or subtree_size: ps[y]=x if unweighted_dist or bipartite_graph: uwd[y]=uwd[x]+1 if weighted_dist: wd[y]=wd[x]+d elif not finished[y]: if (directed_acyclic or cycle_detection or topological_sort) and dag: dag=False if cycle_detection: cd=(y,x) elif not finished[x]: finished[x]=True if euler_tour: et.append(~x) if lowlink: bl=True for y in self.graph[x]: if self.weighted: y,d=y if ps[x]==y and bl: bl=False continue ll[x]=min(ll[x],order[y]) if x!=s: ll[ps[x]]=min(ll[ps[x]],ll[x]) if postorder or topological_sort: post.append(x) if subtree_size: for y in self.graph[x]: if self.weighted: y,d=y if y==ps[x]: continue ss[x]+=ss[y] if bipartite_graph: bg=[[],[]] for tpl in self.edges: x,y=tpl[:2] if self.weighted else tpl if uwd[x]==self.inf or uwd[y]==self.inf: continue if not uwd[x]%2^uwd[y]%2: bg=False break else: for x in range(self.V): if uwd[x]==self.inf: continue bg[uwd[x]%2].append(x) retu=() if bipartite_graph: retu+=(bg,) if cycle_detection: if dag: cd=[] else: y,x=cd cd=self.Route_Restoration(y,x,ps) retu+=(cd,) if directed_acyclic: retu+=(dag,) if euler_tour: retu+=(et,) if linked_components: retu+=(lc,) if lowlink: retu=(ll,) if parents: retu+=(ps,) if postorder: retu+=(post,) if preorder: retu+=(pre,) if subtree_size: retu+=(ss,) if topological_sort: if dag: tp_sort=post[::-1] else: tp_sort=[] retu+=(tp_sort,) if unweighted_dist: retu+=(uwd,) if weighted_dist: retu+=(wd,) if len(retu)==1: retu=retu[0] return retu def Route_Restoration(self,s,g,parents): route=[g] while s!=g: if parents[g]==None: route=[] break g=parents[g] route.append(g) route=route[::-1] return route N,M,K=map(int,readline().split()) edges=[] for _ in range(M): a,b,c=map(int,readline().split()) a-=1;b-=1 edges.append((a,b,c)) C={int(readline())-1 for i in range(K)} UF=UnionFind(N) for i in C: a,b,c=edges[i] UF.Union(a,b) edges=[edges[i] for i in range(M) if not i in C] edges.sort(key=lambda tpl:tpl[2]) ans=0 for a,b,c in edges: if UF.Same(a,b): ans+=c else: UF.Union(a,b) print(ans)