import heapq
import random
from collections import defaultdict,deque

class Graph:
    def __init__(self,V,edges=False,graph=False,directed=False,weighted=False):
        self.V=V
        self.directed=directed
        self.weighted=weighted
        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 SS_BFS(self,s,bfs_tour=False,bipartite_graph=False,linked_components=False,parents=False,unweighted_dist=False,weighted_dist=False):
        seen=[False]*self.V
        seen[s]=True
        if bfs_tour:
            bt=[s]
        if linked_components:
            lc=[s]
        if parents:
            ps=[None]*self.V
        if unweighted_dist or bipartite_graph:
            uwd=[float('inf')]*self.V
            uwd[s]=0
        if weighted_dist:
            wd=[float('inf')]*self.V
            wd[s]=0
        queue=deque([s])
        while queue:
            x=queue.popleft()
            for y in self.graph[x]:
                if self.weighted:
                    y,d=y
                if not seen[y]:
                    seen[y]=True
                    queue.append(y)
                    if bfs_tour:
                        bt.append(y)
                    if linked_components:
                        lc.append(y)
                    if parents:
                        ps[y]=x
                    if unweighted_dist or bipartite_graph:
                        uwd[y]=uwd[x]+1
                    if weighted_dist:
                        wd[y]=wd[x]+d
        if bipartite_graph:
            bg=[[],[]]
            for tpl in self.edges:
                i,j=tpl[:2] if self.weighted else tpl
                if type(uwd[i])==float or type(uwd[j])==float:
                    continue
                if not uwd[i]%2^uwd[j]%2:
                    bg=False
                    break
            else:
                for x in range(self.V):
                    if type(uwd[x])==float:
                        continue
                    bg[uwd[x]%2].append(x)
        tpl=()
        if bfs_tour:
            tpl+=(bt,)
        if bipartite_graph:
            tpl+=(bg,)
        if linked_components:
            tpl+=(lc,)
        if parents:
            tpl+=(ps,)
        if unweighted_dist:
            tpl+=(uwd,)
        if weighted_dist:
            tpl+=(wd,)
        if len(tpl)==1:
            tpl=tpl[0]
        return tpl

    def AP_BFS(self,bipartite_graph=False,linked_components=False,parents=False):
        seen=[False]*self.V
        if bipartite_graph:
            bg=[None]*self.V
            cnt=-1
        if linked_components:
            lc=[]
        if parents:
            ps=[None]*self.V
        for s in range(self.V):
            if seen[s]:
                continue
            seen[s]=True
            if bipartite_graph:
                cnt+=1
                bg[s]=(cnt,0)
            if linked_components:
                lc.append([s])
            queue=deque([s])
            while queue:
                x=queue.popleft()
                for y in self.graph[x]:
                    if self.weighted:
                        y,d=y
                    if not seen[y]:
                        seen[y]=True
                        queue.append(y)
                        if bipartite_graph:
                            bg[y]=(cnt,bg[x][1]^1)
                        if linked_components:
                            lc[-1].append(y)
                        if parents:
                            ps[y]=x
        if bipartite_graph:
            bg_=bg
            bg=[[[],[]] for i in range(cnt+1)]
            for tpl in self.edges:
                i,j=tpl[:2] if self.weighted else tpl
                if not bg_[i][1]^bg_[j][1]:
                    bg[bg_[i][0]]=False
            for x in range(self.V):
                if bg[bg_[x][0]]:
                    bg[bg_[x][0]][bg_[x][1]].append(x)
        tpl=()
        if bipartite_graph:
            tpl+=(bg,)
        if linked_components:
            tpl+=(lc,)
        if parents:
            tpl+=(ps,)
        if len(tpl)==1:
            tpl=tpl[0]
        return tpl

    def SS_DFS(self,s,bipartite_graph=False,cycle_detection=False,directed_acyclic=False,euler_tour=False,linked_components=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 parents or cycle_detection 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=[float('inf')]*self.V
            uwd[s]=0
        if weighted_dist:
            wd=[float('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 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 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 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:
                i,j=tpl[:2] if self.weighted else tpl
                if type(uwd[i])==float or type(uwd[j])==float:
                    continue
                if not uwd[i]%2^uwd[j]%2:
                    bg=False
                    break
            else:
                for x in range(self.V):
                    if type(uwd[x])==float:
                        continue
                    bg[uwd[x]%2].append(x)
        tpl=()
        if bipartite_graph:
            tpl+=(bg,)
        if cycle_detection:
            if dag:
                cd=[]
            else:
                y,x=cd
                cd=self.Route_Restoration(y,x,ps)
            tpl+=(cd,)
        if directed_acyclic:
            tpl+=(dag,)
        if euler_tour:
            tpl+=(et,)
        if linked_components:
            tpl+=(lc,)
        if parents:
            tpl+=(ps,)
        if postorder:
            tpl+=(post,)
        if preorder:
            tpl+=(pre,)
        if subtree_size:
            tpl+=(ss,)
        if topological_sort:
            if dag:
                tp_sort=post[::-1]
            else:
                tp_sort=[]
            tpl+=(tp_sort,)
        if unweighted_dist:
            tpl+=(uwd,)
        if weighted_dist:
            tpl+=(wd,)
        if len(tpl)==1:
            tpl=tpl[0]
        return tpl

    def AP_DFS(self,bipartite_graph=False,cycle_detection=False,directed_acyclic=False,euler_tour=False,linked_components=False,parents=False,postorder=False,preorder=False,topological_sort=False):
        seen=[False]*self.V
        finished=[False]*self.V
        if bipartite_graph:
            bg=[None]*self.V
            cnt=-1
        if directed_acyclic or cycle_detection or topological_sort:
            dag=True
        if euler_tour:
            et=[]
        if linked_components:
            lc=[]
        if parents or cycle_detection:
            ps=[None]*self.V
        if postorder or topological_sort:
            post=[]
        if preorder:
            pre=[]
        for s in range(self.V):
            if seen[s]:
                continue
            if bipartite_graph:
                cnt+=1
                bg[s]=(cnt,0)
            if linked_components:
                lc.append([])
            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[-1].append(x)
                    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 bipartite_graph:
                                bg[y]=(cnt,bg[x][1]^1)
                            if parents or cycle_detection:
                                ps[y]=x
                        elif not finished[y]:
                            if directed_acyclic and dag:
                                dag=False
                                if cycle_detection:
                                    cd=(y,x)
                elif not finished[x]:
                    finished[x]=True
                    if euler_tour:
                        et.append(~x)
                    if postorder or topological_sort:
                        post.append(x)
        if bipartite_graph:
            bg_=bg
            bg=[[[],[]] for i in range(cnt+1)]
            for tpl in self.edges:
                i,j=tpl[:2] if self.weighted else tpl
                if not bg_[i][1]^bg_[j][1]:
                    bg[bg_[i][0]]=False
            for x in range(self.V):
                if bg[bg_[x][0]]:
                    bg[bg_[x][0]][bg_[x][1]].append(x)
        tpl=()
        if bipartite_graph:
            tpl+=(bg,)
        if cycle_detection:
            if dag:
                cd=[]
            else:
                y,x=cd
                cd=self.Route_Restoration(y,x,ps)
            tpl+=(cd,)
        if directed_acyclic:
            tpl+=(dag,)
        if euler_tour:
            tpl+=(et,)
        if linked_components:
            tpl+=(lc,)
        if parents:
            tpl+=(ps,)
        if postorder:
            tpl+=(post,)
        if preorder:
            tpl+=(pre,)
        if topological_sort:
            if dag:
                tp_sort=post[::-1]
            else:
                tp_sort=[]
            tpl+=(tp_sort,)
        if len(tpl)==1:
            tpl=tpl[0]
        return tpl

    def Tree_Diameter(self,weighted=False):
        def Farthest_Point(u):
            dist=self.SS_BFS(u,weighted_dist=True) if weighted else self.SS_BFS(u,unweighted_dist=True)
            fp=0
            for i in range(self.V):
                if dist[fp]<dist[i]:
                    fp=i
            return fp,dist[fp]
        u,d=Farthest_Point(0)
        v,d=Farthest_Point(u)
        return u,v,d

    def SCC(self):
        reverse_graph=[[] for i in range(self.V)]
        for tpl in self.edges:
            i,j=tpl[:2] if self.weighted else tpl
            reverse_graph[j].append(i)
        postorder=self.AP_DFS(postorder=True)
        scc=[]
        seen=[False]*self.V
        for s in postorder[::-1]:
            if seen[s]:
                continue
            queue=deque([s])
            seen[s]=True
            lst=[]
            while queue:
                x=queue.popleft()
                lst.append(x)
                for y in reverse_graph[x]:
                    if self.weighted:
                        y=y[0]
                    if not seen[y]:
                        seen[y]=True
                        queue.append(y)
            scc.append(lst)
        return scc

    def Build_LCA(self,s):
        self.lca_euler_tour,self.lca_parents,depth=self.SS_DFS(s,euler_tour=True,parents=True,unweighted_dist=True)
        self.lca_dfs_in_index=[None]*self.V
        self.lca_dfs_out_index=[None]*self.V
        for i,x in enumerate(self.lca_euler_tour):
            if x>=0:
                self.lca_dfs_in_index[x]=i
            else:
                self.lca_dfs_out_index[~x]=i
        self.ST=Segment_Tree(2*self.V,lambda x,y:min(x,y),self.V)
        lst=[None]*(2*self.V)
        for i in range(2*self.V-1):
            if self.lca_euler_tour[i]>=0:
                lst[i]=depth[self.lca_euler_tour[i]]
            else:
                lst[i]=depth[self.lca_parents[~self.lca_euler_tour[i]]]
        lst[2*self.V-1]=-1
        self.ST.Build(lst)

    def LCA(self,a,b):
        m=min(self.lca_dfs_in_index[a],self.lca_dfs_in_index[b])
        M=max(self.lca_dfs_in_index[a],self.lca_dfs_in_index[b])
        x=self.lca_euler_tour[self.ST.Fold_Index(m,M+1)]
        if x>=0:
            return x
        else:
            return self.lca_parents[~x]

    def Build_HLD(self,s):
        size=self.SS_DFS(s,subtree_size=True)
        seen=[False]*self.V
        stack=[s]
        self.hld_tour=[]
        self.hld_parents=[None]*self.V
        self.hld_depth=[None]*self.V
        self.hld_path_parents=[None]*self.V
        self.hld_path_parents[s]=s
        self.hld_depth[s]=0
        while stack:
            x=stack.pop()
            seen[x]=True
            self.hld_tour.append(x)
            max_size=0
            max_size_y=None
            for y in self.graph[x]:
                if self.weighted:
                    y,d=y
                if not seen[y] and max_size<size[y]:
                    max_size=size[y]
                    max_size_y=y
            for y in self.graph[x]:
                if self.weighted:
                    y,d=y
                if not seen[y] and y!=max_size_y:
                    stack.append(y)
                    self.hld_parents[y]=x
                    self.hld_depth[y]=self.hld_depth[x]+1
                    self.hld_path_parents[y]=y
            if max_size_y!=None:
                stack.append(max_size_y)
                self.hld_parents[max_size_y]=x
                self.hld_depth[max_size_y]=self.hld_depth[x]+1
                self.hld_path_parents[max_size_y]=self.hld_path_parents[x]
        self.hld_tour_idx=[None]*self.V
        for i in range(self.V):
            self.hld_tour_idx[self.hld_tour[i]]=i

    def HLD(self,a,b,edge=False):
        L,R=[],[]
        while self.hld_path_parents[a]!=self.hld_path_parents[b]:
            if self.hld_depth[self.hld_path_parents[a]]<self.hld_depth[self.hld_path_parents[b]]:
                R.append((self.hld_tour_idx[self.hld_path_parents[b]],self.hld_tour_idx[b]+1))
                b=self.hld_parents[self.hld_path_parents[b]]
            else:
                L.append((self.hld_tour_idx[a]+1,self.hld_tour_idx[self.hld_path_parents[a]]))
                a=self.hld_parents[self.hld_path_parents[a]]
        if edge:
            if self.hld_depth[a]!=self.hld_depth[b]:
                retu=L+[(self.hld_tour_idx[a]+1,self.hld_tour_idx[b]+1)]+R[::-1]
            else:
                retu=L+R[::-1]
        else:
            if self.hld_depth[a]<self.hld_depth[b]:
                retu=L+[(self.hld_tour_idx[a],self.hld_tour_idx[b]+1)]+R[::-1]
            else:
                retu=L+[(self.hld_tour_idx[a]+1,self.hld_tour_idx[b])]+R[::-1]
        return retu

    def Build_Hash(self,s,random_number=False,mod=False,rerooting=False):
        self.bottom_hash=[None]*self.V
        if random_number:
            self.hash_random_number=random_number
        else:
            self.hash_random_number=[random.randint(1,10**10) for i in range(self.V)]
        if mod:
            self.hash_mod=mod
        else:
            self.hash_mod=(1<<61)-1
        parents,postorder,preorder=self.SS_DFS(s,parents=True,postorder=True,preorder=True)
        for x in postorder:
            level=0
            for y in self.graph[x]:
                if y==parents[x]:
                    continue
                h,l=self.bottom_hash[y]
                level=max(level,l+1)
            ha=1
            for y in self.graph[x]:
                if y==parents[x]:
                    continue
                h,l=self.bottom_hash[y]
                ha*=h+self.hash_random_number[l]
                ha%=self.hash_mod
            self.bottom_hash[x]=(ha,level)
        if rerooting:
            self.top_hash=[None]*self.V
            self.top_hash[s]=(1,-1)
            for x in preorder:
                children=[y for y in self.graph[x] if y!=parents[x]]
                if children:
                    l=len(children)
                    l_lst,r_lst=[None]*(l+1),[None]*(l+1)
                    l_lst[0],r_lst[l]=(1,-1),(1,-1)
                    for i in range(1,l+1):
                        h0,l0=l_lst[i-1]
                        h1,l1=self.bottom_hash[children[i-1]]
                        l_lst[i]=(h0*(h1+self.hash_random_number[l1])%self.hash_mod,max(l0,l1))
                    for i in range(l-1,-1,-1):
                        h0,l0=r_lst[i+1]
                        h1,l1=self.bottom_hash[children[i]]
                        r_lst[i]=(h0*(h1+self.hash_random_number[l1])%self.hash_mod,max(l0,l1))
                    for i in range(l):
                        if x==s:
                            ha,level=1,0
                        else:
                            ha,level=self.top_hash[x]
                        h0,l0=l_lst[i]
                        h1,l1=r_lst[i+1]
                        ha*=h0*h1
                        level=max(level,l0+1,l1+1)
                        ha+=self.hash_random_number[level]
                        ha%=self.hash_mod
                        level+=1
                        self.top_hash[children[i]]=(ha,level)
        return 

    def Hash(self,root,subtree=False):
        if subtree:
            ha,level=self.bottom_hash[root]
            ha+=self.hash_random_number[level]
            ha%=self.hash_mod
        else:
            h0,l0=self.bottom_hash[root]
            h1,l1=self.top_hash[root]
            ha=(h0*h1+self.hash_random_number[max(l0,l1)])%self.hash_mod
            level=max(l0,l1)
        return ha,level

    def Dijkstra(self,s,route_restoration=False):
        dist=[float('inf')]*self.V
        dist[s]=0
        hq=[(0,s)]
        if route_restoration:
            parents=[None]*self.V
        while hq:
            dx,x=heapq.heappop(hq)
            if dist[x]<dx:
                continue
            for y,dy in self.graph[x]:
                if dist[y]>dx+dy:
                    dist[y]=dx+dy
                    if route_restoration:
                        parents[y]=x
                    heapq.heappush(hq,(dist[y],y))
        if route_restoration:
            return dist,parents
        else:
            return dist

    def Bellman_Ford(self,s,route_restoration=False):
        dist=[float('inf')]*self.V
        dist[s]=0
        if route_restoration:
            parents=[None]*self.V
        for _ in range(self.V-1):
            for i,j,d in self.edges:
                if dist[j]>dist[i]+d:
                    dist[j]=dist[i]+d
                    if route_restoration:
                        parents[j]=i
                if not self.directed and dist[i]>dist[j]+d:
                    dist[i]=dist[j]+d
                    if route_restoration:
                        parents[i]=j
        negative_cycle=[]
        for i,j,d in self.edges:
            if dist[j]>dist[i]+d:
                negative_cycle.append(j)
            if not self.directed and dist[i]>dist[j]+d:
                negative_cycle.append(i)
        if negative_cycle:
            is_negative_cycle=[False]*self.V
            for i in negative_cycle:
                if is_negative_cycle[i]:
                    continue
                else:
                    queue=deque([i])
                    is_negative_cycle[i]=True
                    while queue:
                        x=queue.popleft()
                        for y,d in self.graph[x]:
                            if not is_negative_cycle[y]:
                                queue.append(y)
                                is_negative_cycle[y]=True
                                if route_restoration:
                                    parents[y]=x
            for i in range(self.V):
                if is_negative_cycle[i]:
                    dist[i]=-float('inf')
        if route_restoration:
            return dist,parents
        else:
            return dist

    def Warshall_Floyd(self,route_restoration=False):
        dist=[[float('inf')]*self.V for i in range(self.V)]
        for i in range(self.V):
            dist[i][i]=0
        if route_restoration:
            parents=[[j for j in range(self.V)] for i in range(self.V)]
        for i,j,d in self.edges:
            if i==j:
                continue
            if dist[i][j]>d:
                dist[i][j]=d
                if route_restoration:
                    parents[i][j]=i
            if not self.directed and dist[j][i]>d:
                dist[j][i]=d
                if route_restoration:
                    parents[j][i]=j
        for k in range(self.V):
            for i in range(self.V):
                for j in range(self.V):
                    if dist[i][j]>dist[i][k]+dist[k][j]:
                        dist[i][j]=dist[i][k]+dist[k][j]
                        if route_restoration:
                            parents[i][j]=parents[k][j]
        for i in range(self.V):
            if dist[i][i]<0:
                for j in range(self.V):
                    if dist[i][j]!=float('inf'):
                        dist[i][j]=-float('inf')
        if route_restoration:
            for i in range(self.V):
                if dist[i][i]==0:
                    parents[i][i]=None
            return dist,parents
        else:
            return dist

    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

    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 Ford_Fulkerson(self,s,t):
        max_flow=0
        residual_graph=[defaultdict(int) for i in range(self.V)]
        if self.weighted:
            for i,j,d in self.edges:
                if not d:
                    continue
                residual_graph[i][j]+=d
                if not self.directed:
                    residual_graph[j][i]+=d
        else:
            for i,j in self.edges:
                residual_graph[i][j]+=1
                if not self.directed:
                    residual_graph[j][i]+=1
        while True:
            parents=[None]*self.V
            parents[s]=s
            seen=[False]*self.V
            seen[s]=True
            queue=deque([s])
            while queue:
                x=queue.popleft()
                for y in residual_graph[x].keys():
                    if not seen[y]:
                        seen[y]=True
                        queue.append(y)
                        parents[y]=x
                        if y==t:
                            tt=t
                            while tt!=s:
                                residual_graph[parents[tt]][tt]-=1
                                residual_graph[tt][parents[tt]]+=1
                                if not residual_graph[parents[tt]][tt]:
                                    residual_graph[parents[tt]].pop(tt)
                                tt=parents[tt]
                            max_flow+=1
                            break
                else:
                    continue
                break
            else:
                break
        return max_flow

    def BFS(self,s):
        seen=[False]*self.V
        seen[s]=True
        queue=deque([s])

        while queue:
            x=queue.popleft()
            for y in self.graph[x]:
                if self.weighted:
                    y,d=y
                if not seen[y]:
                    seen[y]=True
                    queue.append(y)
                    
        return 

    def DFS(self,s):
        seen=[False]*self.V
        finished=[False]*self.V
        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)

                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)
            elif not finished[x]:
                finished[x]=True
                
        return 

class Segment_Tree:
    def __init__(self,N,f,e,lst=None):
        self.f=f
        self.e=e
        self.N=N
        if lst==None:
            self.segment_tree=[self.e]*2*self.N
        else:
            assert len(lst)<=self.N
            self.segment_tree=[self.e]*self.N+[x for x in lst]+[self.e]*(N-len(lst))
            for i in range(self.N-1,0,-1):
                self.segment_tree[i]=self.f(self.segment_tree[i<<1],self.segment_tree[i<<1|1])

    def __getitem__(self,i):
        if type(i)==int:
            if -self.N<=i<0:
                return self.segment_tree[i+self.N*2]
            elif 0<=i<self.N:
                return self.segment_tree[i+self.N]
            else:
                raise IndexError('list index out of range')
        else:
            a,b,c=i.start,i.stop,i.step
            if a==None or a<-self.N:
                a=self.N
            elif self.N<=a:
                a=self.N*2
            elif a<0:
                a+=self.N*2
            else:
                a+=self.N
            if b==None or self.N<=b:
                b=self.N*2
            elif b<-self.N:
                b=self.N
            elif b<0:
                b+=self.N*2
            else:
                b+=self.N
            return self.segment_tree[slice(a,b,c)]

    def __setitem__(self,i,x):
        if -self.N<=i<0:
            i+=self.N*2
        elif 0<=i<self.N:
            i+=self.N
        else:
            raise IndexError('list index out of range')
        self.segment_tree[i]=x
        while i>1:
            i>>= 1
            self.segment_tree[i]=self.f(self.segment_tree[i<<1],self.segment_tree[i<<1|1])

    def Build(self,lst):
        for i,x in enumerate(lst,self.N):
            self.segment_tree[i]=x
        for i in range(self.N-1,0,-1):
            self.segment_tree[i]=self.f(self.segment_tree[i<<1],self.segment_tree[i<<1|1])

    def Fold(self,L=None,R=None):
        if L==None or L<-self.N:
            L=self.N
        elif self.N<=L:
            L=self.N*2
        elif L<0:
            L+=self.N*2
        else:
            L+=self.N
        if R==None or self.N<=R:
            R=self.N*2
        elif R<-self.N:
            R=self.N
        elif R<0:
            R+=self.N*2
        else:
            R+=self.N
        vL=self.e
        vR=self.e
        while L<R:
            if L&1:
                vL=self.f(vL,self.segment_tree[L])
                L+=1
            if R&1:
                R-=1
                vR=self.f(self.segment_tree[R],vR)
            L>>=1
            R>>=1
        return self.f(vL,vR)

    def Fold_Index(self,L=None,R=None):
        if L==None or L<-self.N:
            L=self.N
        elif self.N<=L:
            L=self.N*2
        elif L<0:
            L+=self.N*2
        else:
            L+=self.N
        if R==None or self.N<=R:
            R=self.N*2
        elif R<-self.N:
            R=self.N
        elif R<0:
            R+=self.N*2
        else:
            R+=self.N
        if L==R:
            return None
        x=self.Fold(L-self.N,R-self.N)
        while L<R:
            if L&1:
                if self.segment_tree[L]==x:
                    i=L
                    break
                L+=1
            if R&1:
                R-=1
                if self.segment_tree[R]==x:
                    i=R
                    break
            L>>=1
            R>>=1
        while i<self.N:
            if self.segment_tree[i]==self.segment_tree[i<<1]:
                i<<=1
            else:
                i<<=1
                i|=1
        i-=self.N
        return i

    def __str__(self):
        return '['+', '.join(map(str,self.segment_tree[self.N:]))+']'

import sys
readline=sys.stdin.readline
def Extended_Euclid(n,m):
    stack=[]
    while m:
        stack.append((n,m))
        n,m=m,n%m
    if n>=0:
        x,y=1,0
    else:
        x,y=-1,0
    for i in range(len(stack)-1,-1,-1):
        n,m=stack[i]
        x,y=y,x-(n//m)*y
    return x,y

class MOD:
    def __init__(self,p,e=1):
        self.p=p
        self.e=e
        self.mod=self.p**self.e

    def Pow(self,a,n):
        a%=self.mod
        if n>=0:
            return pow(a,n,self.mod)
        else:
            assert math.gcd(a,self.mod)==1
            x=Extended_Euclid(a,self.mod)[0]
            return pow(x,-n,self.mod)

    def Build_Fact(self,N):
        assert N>=0
        self.factorial=[1]
        self.cnt=[0]*(N+1)
        for i in range(1,N+1):
            ii=i
            self.cnt[i]=self.cnt[i-1]
            while ii%self.p==0:
                ii//=self.p
                self.cnt[i]+=1
            self.factorial.append((self.factorial[-1]*ii)%self.mod)
        self.factorial_inve=[None]*(N+1)
        self.factorial_inve[-1]=self.Pow(self.factorial[-1],-1)
        for i in range(N-1,-1,-1):
            ii=i+1
            while ii%self.p==0:
                ii//=self.p
            self.factorial_inve[i]=(self.factorial_inve[i+1]*ii)%self.mod

    def Fact(self,N):
        return self.factorial[N]*pow(self.p,self.cnt[N],self.mod)%self.mod

    def Fact_Inve(self,N):
        if self.cnt[N]:
            return None
        return self.factorial_inve[N]

    def Comb(self,N,K,divisible_count=False):
        if K<0 or K>N:
            return 0
        retu=self.factorial[N]*self.factorial_inve[K]*self.factorial_inve[N-K]%self.mod
        cnt=self.cnt[N]-self.cnt[N-K]-self.cnt[K]
        if divisible_count:
            return retu,cnt
        else:
            retu*=pow(self.p,cnt,self.mod)
            retu%=self.mod
            return retu

class Matrix:
    def __init__(self,H=0,W=0,matrix=False,eps=0,mod=0,identity=0):
        if identity:
            if H:
                self.H=H
                self.W=H
            else:
                self.H=W
                self.W=W
            self.matrix=[[0]*self.W for i in range(self.H)]
            for i in range(self.H):
                self.matrix[i][i]=identity
        elif matrix:
            self.matrix=matrix
            self.H=len(self.matrix)
            self.W=len(self.matrix[0]) if self.matrix else 0
        else:
            self.H=H
            self.W=W
            self.matrix=[[0]*self.W for i in range(self.H)]
        self.mod=mod
        self.eps=eps

    def __eq__(self,other):
        if type(other)!=Matrix:
            return False
        if self.H!=other.H:
            return False
        if self.mod:
            for i in range(self.H):
                for j in range(self.W):
                    if self.matrix[i][j]%self.mod!=other.matrix[i][j]%self.mod:
                        return False
        else:
            for i in range(self.H):
                for j in range(self.W):
                    if self.eps<abs(self.matrix[i][j]-other.matrix[i][j]):
                        return False
        return True

    def __ne__(self,other):
        if type(other)!=Matrix:
            return True
        if self.H!=other.H:
            return True
        if self.mod:
            for i in range(self.H):
                for j in range(self.W):
                    if self.matrix[i][j]%self.mod!=other.matrix[i][j]%self.mod:
                        return True
        else:
            for i in range(self.H):
                for j in range(self.W):
                    if self.eps<abs(self.matrix[i][j]-other.matrix[i][j]):
                        return True
        return False

    def __add__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            if self.mod:
                summ=Matrix(matrix=[[(self.matrix[i][j]+other.matrix[i][j])%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                summ=Matrix(matrix=[[self.matrix[i][j]+other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            if self.mod:
                summ=Matrix(matrix=[[(self.matrix[i][j]+other)%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                summ=Matrix(matrix=[[self.matrix[i][j]+other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return summ

    def __sub__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            if self.mod:
                diff=Matrix(matrix=[[(self.matrix[i][j]-other.matrix[i][j])%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                diff=Matrix(matrix=[[self.matrix[i][j]-other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            if self.mod:
                diff=Matrix(matrix=[[(self.matrix[i][j]-other)%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                diff=Matrix(matrix=[[self.matrix[i][j]-other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return diff

    def __mul__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            if self.mod:
                prod=Matrix(matrix=[[(self.matrix[i][j]*other.matrix[i][j])%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                prod=Matrix(matrix=[[self.matrix[i][j]*other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            if self.mod:
                prod=Matrix(matrix=[[(self.matrix[i][j]*other)%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                prod=Matrix(matrix=[[self.matrix[i][j]*other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return prod

    def __matmul__(self,other):
        if type(other)==Matrix:
            assert self.W==other.H
            prod=Matrix(H=self.H,W=other.W,eps=self.eps,mod=self.mod)
            for i in range(self.H):
                for j in range(other.W):
                    for k in range(self.W):
                        prod.matrix[i][j]+=self.matrix[i][k]*other.matrix[k][j]
                        if self.mod:
                            prod.matrix[i][j]%=self.mod
        elif type(other)==int:
            assert self.H==self.W
            if other==0:
                prod=Matrix(H=self.H,eps=self.eps,mod=self.mod,identity=1)
            elif other==1:
                prod=Matrix(matrix=[[self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                prod=Matrix(H=self.H,eps=self.eps,mod=self.mod,identity=1)
                doub=Matrix(matrix=[[self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
                while other>=2:
                    if other&1:
                        prod@=doub
                    doub@=doub
                    other>>=1
                prod@=doub
        return prod

    def __truediv__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            if self.mod:
                quot=Matrix(matrix=[[(self.matrix[i][j]*MOD(self.mod).Pow(other.matrix[i][j],-1))%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                quot=Matrix(matrix=[[self.matrix[i][j]/other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            if self.mod:
                inve=MOD(self.mod).Pow(other,-1)
                quot=Matrix(matrix=[[(self.matrix[i][j]*inve)%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                quot=Matrix(matrix=[[self.matrix[i][j]/other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return quot

    def __floordiv__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            quot=Matrix(matrix=[[self.matrix[i][j]//other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            quot=Matrix(matrix=[[self.matrix[i][j]//other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return quot

    def __mod__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            rema=Matrix(matrix=[[self.matrix[i][j]%other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            rema=Matrix(matrix=[[self.matrix[i][j]%other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return rema

    def __pow__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            if self.mod:
                powe=Matrix(matrix=[[pow(self.matrix[i][j],other.matrix[i][j],self.mod) for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                powe=Matrix(matrix=[[pow(self.matrix[i][j],other.matrix[i][j]) for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            if self.mod:
                powe=Matrix(matrix=[[pow(self.matrix[i][j],other,self.mod) for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                powe=Matrix(matrix=[[pow(self.matrix[i][j],other) for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return powe

    def __lshift__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            lshi=Matrix(matrix=[[self.matrix[i][j]<<other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            lshi=Matrix(matrix=[[self.matrix[i][j]<<other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return lshi

    def __rshift__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            rshi=Matrix(matrix=[[self.matrix[i][j]>>other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            rshi=Matrix(matrix=[[self.matrix[i][j]>>other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return rshi

    def __and__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            conj=Matrix(matrix=[[self.matrix[i][j]&other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            conj=Matrix(matrix=[[self.matrix[i][j]&other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return conj

    def __or__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            disj=Matrix(matrix=[[self.matrix[i][j]|other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            disj=Matrix(matrix=[[self.matrix[i][j]|other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return disj

    def __xor__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            excl=Matrix(matrix=[[self.matrix[i][j]^other.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            excl=Matrix(matrix=[[self.matrix[i][j]^other for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return excl

    def __iadd__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]+=other.matrix[i][j]
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]+=other
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        return self

    def __isub__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]-=other.matrix[i][j]
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]-=other
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        return self

    def __imul__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]*=other.matrix[i][j]
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]*=other
                    if self.mod:
                        self.matrix[i][j]%=self.mod
        return self

    def __imatmul__(self,other):
        if type(other)==Matrix:
            assert self.W==other.H
            prod=Matrix(H=self.H,W=other.W,eps=self.eps,mod=self.mod)
            for i in range(self.H):
                for j in range(other.W):
                    for k in range(self.W):
                        prod.matrix[i][j]+=self.matrix[i][k]*other.matrix[k][j]
                        if self.mod:
                            prod.matrix[i][j]%=self.mod
        elif type(other)==int:
            assert self.H==self.W
            if other==0:
                return Matrix(H=self.H,eps=self.eps,mod=self.mod,identity=1)
            elif other==1:
                prod=Matrix(matrix=[[self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
            else:
                prod=Matrix(H=self.H,eps=self.eps,mod=self.mod,identity=1)
                doub=self
                while other>=2:
                    if other&1:
                        prod@=doub
                    doub@=doub
                    other>>=1
                prod@=doub
        return prod

    def __itruediv__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    if self.mod:
                        self.matrix[i][j]=self.matrix[i][j]*MOD(self.mod).Pow(other.matrix[i][j],-1)%self.mod
                    else:
                        self.matrix[i][j]/=other.matrix[i][j]
        else:
            if self.mod:
                inve=MOD(self.mod).Pow(other,-1)
            for i in range(self.H):
                for j in range(self.W):
                    if self.mod:
                        self.matrix[i][j]=self.matrix[i][j]*inve%self.mod
                    else:
                        self.matrix[i][j]/=other
        return self

    def __ifloordiv__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]//=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]//=other
        return self

    def __imod__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]%=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]%=other
        return self

    def __ipow__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    if self.mod:
                        self.matrix[i][j]=pow(self.matrix[i][j],other.matrix[i][j],self.mod)
                    else:
                        self.matrix[i][j]=pow(self.matrix[i][j],other.matrix[i][j])
        else:
            for i in range(self.H):
                for j in range(self.W):
                    if self.mod:
                        self.matrix[i][j]=pow(self.matrix[i][j],other,self.mod)
                    else:
                        self.matrix[i][j]=pow(self.matrix[i][j],other)
        return self

    def __ilshift__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]<<=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]<<=other
        return self

    def __irshift__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]>>=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]>>=other
        return self

    def __iand__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]&=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]&=other
        return self

    def __ior__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]|=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]|=other
        return self

    def __ixor__(self,other):
        if type(other)==Matrix:
            assert self.H==other.H
            assert self.W==other.W
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]^=other.matrix[i][j]
        else:
            for i in range(self.H):
                for j in range(self.W):
                    self.matrix[i][j]^=other
        return self

    def __neg__(self):
        if self.mod:
            nega=Matrix(matrix=[[(-self.matrix[i][j])%self.mod for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        else:
            nega=Matrix(matrix=[[-self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return nega

    def __pos__(self):
        posi=Matrix(matrix=[[self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return posi

    def __invert__(self):
        inve=Matrix(matrix=[[~self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return inve

    def __abs__(self):
        abso=Matrix(matrix=[[abs(self.matrix[i][j]) for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        return abso

    def __getitem__(self,i):
        if type(i)==int:
            return self.matrix[i]
        elif type(i)==tuple:
            i,j=i
            if type(i)==int:
                i=slice(i,i+1)
            if type(j)==int:
                j=slice(j,j+1)
            return Matrix(matrix=[lst[j] for lst in self.matrix[i]],eps=self.eps,mod=self.mod)

    def __contains__(self,x):
        for i in range(self.H):
            if x in self.matrix[i]:
                return True
        return False

    def __str__(self):
        digit=[max(len(str(self.matrix[i][j])) for i in range(self.H)) for j in range(self.W)]
        return "\n".join([(" [" if i else "[[")+", ".join([str(self.matrix[i][j]).rjust(digit[j]," ") for j in range(self.W)])+"]" for i in range(self.H)])+"]"

    def __bool__(self):
        return True

    def Transpose(self):
        return Matrix(matrix=[[self.matrix[i][j] for i in range(self.H)] for j in range(self.W)])

    def Trace(self):
        assert self.H==self.W
        trace=sum(self.matrix[i][i] for i in range(self.H))
        if self.mod:
            trace%=self.mod
        return trace

    def Elem_Raw_Operate_1(self,i1,i2):
        self.matrix[i1],self.matrix[i2]=self.matrix[i2],self.matrix[i1]

    def Elem_Raw_Operate_2(self,i,c):
        if self.mod:
            self.matrix[i]=[self.matrix[i][j]*c%self.mod for j in range(self.W)]
        else:
            self.matrix[i]=[self.matrix[i][j]*c for j in range(self.W)]

    def Elem_Raw_Operate_3(self,i1,i2,c):
        if self.mod:
            self.matrix[i1]=[(self.matrix[i1][j]+c*self.matrix[i2][j])%self.mod for j in range(self.W)]
        else:
            self.matrix[i1]=[self.matrix[i1][j]+c*self.matrix[i2][j] for j in range(self.W)]

    def Elimination(self,determinant=False,inverse_matrix=False,linear_equation=False,rank=False,upper_triangular=False):
        h=0
        ut=Matrix(matrix=[[self.matrix[i][j] for j in range(self.W)] for i in range(self.H)],eps=self.eps,mod=self.mod)
        if determinant or inverse_matrix:
            assert self.H==self.W
            det=1
        if inverse_matrix:
            assert self.H==self.W
            im=Matrix(H=self.H,eps=self.eps,mod=self.mod,identity=1)
        if linear_equation:
            assert self.H==linear_equation.H
            le=Matrix(matrix=[[linear_equation.matrix[i][j] for j in range(linear_equation.W)] for i in range(linear_equation.H)],eps=self.eps,mod=self.mod)
        for j in range(ut.W):
            for i in range(h,ut.H):
                if abs(ut.matrix[i][j])>ut.eps:
                    if ut.mod:
                        inve=MOD(ut.mod).Pow(ut.matrix[i][j],-1)
                    else:
                        inve=1/ut.matrix[i][j]

                    ut.Elem_Raw_Operate_1(i,h)
                    if determinant and h%2!=i%2:
                        det=(-det)%self.mod
                    if inverse_matrix:
                        im.Elem_Raw_Operate_1(i,h)
                    if linear_equation:
                        le.Elem_Raw_Operate_1(i,h)
                    
                    ut.Elem_Raw_Operate_2(h,inve)
                    if determinant or inverse_matrix:
                        det*=inve
                        if ut.mod:
                            det%=ut.mod
                    if inverse_matrix:
                        im.Elem_Raw_Operate_2(h,inve)
                    if linear_equation:
                        le.Elem_Raw_Operate_2(h,inve)
                    
                    for ii in range(ut.H):
                        if ii==h:
                            continue
                        x=-ut.matrix[ii][j]
                        ut.Elem_Raw_Operate_3(ii,h,x)
                        if inverse_matrix:
                            im.Elem_Raw_Operate_3(ii,h,x)
                        if linear_equation:
                            le.Elem_Raw_Operate_3(ii,h,x)
                    h+=1
                    break
            else:
                det=0
        tpl=()
        if determinant:
            tpl+=(det,)
        if inverse_matrix:
            if det<=0:
                im=False
            tpl+=(im,)
        if linear_equation:
            tpl+=(le,)
        if rank:
            tpl+=(h,)
        if upper_triangular:
            tpl+=(ut,)
        if len(tpl)==1:
            tpl=tpl[0]
        return tpl

N=int(readline())
edges=[]
for i in range(N-1):
    a,b=map(int,readline().split())
    edges.append((a,b))
G=Graph(N,edges=edges)
G.Build_HLD(0)
parents=G.SS_DFS(0,parents=True)
mod=10**9+7
ST=Segment_Tree(N,lambda x,y:x@y,Matrix(H=2,identity=1,mod=mod))
Q=int(readline())
for i in range(Q):
    query=readline().rstrip()
    if query[0]=="x":
        i,a,b,c,d=map(int,query[2:].split())
        u,v=edges[i]
        if u==parents[v]:
            u,v=v,u
        ST[G.hld_tour_idx[u]]=Matrix(matrix=[[a,b],[c,d]],mod=mod)
    else:
        i,j=map(int,query[2:].split())
        ans=Matrix(H=2,identity=1,mod=mod)
        for a,b in G.HLD(i,j,edge=True):
            ans@=ST.Fold(a,b)
        print(ans[0][0],ans[0][1],ans[1][0],ans[1][1])