def divisors(M): d=[] i=1 while M>=i**2: if M%i==0: d.append(i) if i**2!=M: d.append(M//i) i=i+1 return d def popcount(x): x = x - ((x >> 1) & 0x55555555) x = (x & 0x33333333) + ((x >> 2) & 0x33333333) x = (x + (x >> 4)) & 0x0f0f0f0f x = x + (x >> 8) x = x + (x >> 16) return x & 0x0000007f def eratosthenes(n): res=[0 for i in range(n+1)] prime=set([]) for i in range(2,n+1): if not res[i]: prime.add(i) for j in range(1,n//i+1): res[i*j]=1 return prime def factorization(n): res=[] for p in prime: if n%p==0: while n%p==0: n//=p res.append(p) if n!=1: res.append(n) return res def euler_phi(n): res = n for x in range(2,n+1): if x ** 2 > n: break if n%x==0: res = res//x * (x-1) while n%x==0: n //= x if n!=1: res = res//n * (n-1) return res def ind(b,n): res=0 while n%b==0: res+=1 n//=b return res def isPrimeMR(n): if n==1: return 0 d = n - 1 d = d // (d & -d) L = [2, 3, 5, 7, 11, 13, 17] for a in L: t = d y = pow(a, t, n) if y == 1: continue while y != n - 1: y = (y * y) % n if y == 1 or t == n - 1: return 0 t <<= 1 return 1 def findFactorRho(n): from math import gcd m = 1 << n.bit_length() // 8 for c in range(1, 99): f = lambda x: (x * x + c) % n y, r, q, g = 2, 1, 1, 1 while g == 1: x = y for i in range(r): y = f(y) k = 0 while k < r and g == 1: ys = y for i in range(min(m, r - k)): y = f(y) q = q * abs(x - y) % n g = gcd(q, n) k += m r <<= 1 if g == n: g = 1 while g == 1: ys = f(ys) g = gcd(abs(x - ys), n) if g < n: if isPrimeMR(g): return g elif isPrimeMR(n // g): return n // g return findFactorRho(g) def primeFactor(n): i = 2 ret = {} rhoFlg = 0 while i*i <= n: k = 0 while n % i == 0: n //= i k += 1 if k: ret[i] = k i += 1 + i % 2 if i == 101 and n >= 2 ** 20: while n > 1: if isPrimeMR(n): ret[n], n = 1, 1 else: rhoFlg = 1 j = findFactorRho(n) k = 0 while n % j == 0: n //= j k += 1 ret[j] = k if n > 1: ret[n] = 1 if rhoFlg: ret = {x: ret[x] for x in sorted(ret)} return ret def divisors(n): res = [1] prime = primeFactor(n) for p in prime: newres = [] for d in res: for j in range(prime[p]+1): newres.append(d*p**j) res = newres res.sort() return res def xorfactorial(num):#排他的論理和の階乗 if num==0: return 0 elif num==1: return 1 elif num==2: return 3 elif num==3: return 0 else: x=baseorder(num) return (2**x)*((num-2**x+1)%2)+function(num-2**x) def xorconv(n,X,Y): if n==0: res=[(X[0]*Y[0])%mod] return res x=[digit[i]+X[i+2**(n-1)] for i in range(2**(n-1))] y=[Y[i]+Y[i+2**(n-1)] for i in range(2**(n-1))] z=[digit[i]-X[i+2**(n-1)] for i in range(2**(n-1))] w=[Y[i]-Y[i+2**(n-1)] for i in range(2**(n-1))] res1=xorconv(n-1,x,y) res2=xorconv(n-1,z,w) former=[(res1[i]+res2[i])*inv for i in range(2**(n-1))] latter=[(res1[i]-res2[i])*inv for i in range(2**(n-1))] former=list(map(lambda x:x%mod,former)) latter=list(map(lambda x:x%mod,latter)) return former+latter def merge_sort(A,B): pos_A,pos_B = 0,0 n,m = len(A),len(B) res = [] while pos_A < n and pos_B < m: a,b = A[pos_A],B[pos_B] if a < b: res.append(a) pos_A += 1 else: res.append(b) pos_B += 1 res += A[pos_A:] res += B[pos_B:] return res class UnionFindVerSize(): def __init__(self, N): self._parent = [n for n in range(0, N)] self._size = [1] * N self.group = N def find_root(self, x): if self._parent[x] == x: return x self._parent[x] = self.find_root(self._parent[x]) stack = [x] while self._parent[stack[-1]]!=stack[-1]: stack.append(self._parent[stack[-1]]) for v in stack: self._parent[v] = stack[-1] return self._parent[x] def unite(self, x, y): gx = self.find_root(x) gy = self.find_root(y) if gx == gy: return self.group -= 1 if self._size[gx] < self._size[gy]: self._parent[gx] = gy self._size[gy] += self._size[gx] else: self._parent[gy] = gx self._size[gx] += self._size[gy] def get_size(self, x): return self._size[self.find_root(x)] def is_same_group(self, x, y): return self.find_root(x) == self.find_root(y) class WeightedUnionFind(): def __init__(self,N): self.parent = [i for i in range(N)] self.size = [1 for i in range(N)] self.val = [0 for i in range(N)] self.flag = True self.edge = [[] for i in range(N)] def dfs(self,v,pv): stack = [(v,pv)] new_parent = self.parent[pv] while stack: v,pv = stack.pop() self.parent[v] = new_parent for nv,w in self.edge[v]: if nv!=pv: self.val[nv] = self.val[v] + w stack.append((nv,v)) def unite(self,x,y,w): if not self.flag: return if self.parent[x]==self.parent[y]: self.flag = (self.val[x] - self.val[y] == w) return if self.size[self.parent[x]]>self.size[self.parent[y]]: self.edge[x].append((y,-w)) self.edge[y].append((x,w)) self.size[x] += self.size[y] self.val[y] = self.val[x] - w self.dfs(y,x) else: self.edge[x].append((y,-w)) self.edge[y].append((x,w)) self.size[y] += self.size[x] self.val[x] = self.val[y] + w self.dfs(x,y) class Dijkstra(): class Edge(): def __init__(self, _to, _cost): self.to = _to self.cost = _cost def __init__(self, V): self.G = [[] for i in range(V)] self._E = 0 self._V = V @property def E(self): return self._E @property def V(self): return self._V def add_edge(self, _from, _to, _cost): self.G[_from].append(self.Edge(_to, _cost)) self._E += 1 def shortest_path(self, s): import heapq que = [] d = [10**15] * self.V d[s] = 0 heapq.heappush(que, (0, s)) while len(que) != 0: cost, v = heapq.heappop(que) if d[v] < cost: continue for i in range(len(self.G[v])): e = self.G[v][i] if d[e.to] > d[v] + e.cost: d[e.to] = d[v] + e.cost heapq.heappush(que, (d[e.to], e.to)) return d #Z[i]:length of the longest list starting from S[i] which is also a prefix of S #O(|S|) def Z_algorithm(s): N = len(s) Z_alg = [0]*N Z_alg[0] = N i = 1 j = 0 while i < N: while i+j < N and s[j] == s[i+j]: j += 1 Z_alg[i] = j if j == 0: i += 1 continue k = 1 while i+k < N and k + Z_alg[k] 0: res_sum += self.BIT[idx] if mod: res_sum %= mod idx -= idx&(-idx) return res_sum #Ai += x O(logN) def update(self,idx,x): mod = self.mod while idx <= self.num: self.BIT[idx] += x if mod: self.BIT[idx] %= mod idx += idx&(-idx) return class dancinglink(): def __init__(self,n,debug=False): self.n = n self.debug = debug self._left = [i-1 for i in range(n)] self._right = [i+1 for i in range(n)] self.exist = [True for i in range(n)] def pop(self,k): if self.debug: assert self.exist[k] L = self._left[k] R = self._right[k] if L!=-1: if R!=self.n: self._right[L],self._left[R] = R,L else: self._right[L] = self.n elif R!=self.n: self._left[R] = -1 self.exist[k] = False def left(self,idx,k=1): if self.debug: assert self.exist[idx] res = idx while k: res = self._left[res] if res==-1: break k -= 1 return res def right(self,idx,k=1): if self.debug: assert self.exist[idx] res = idx while k: res = self._right[res] if res==self.n: break k -= 1 return res class SparseTable(): def __init__(self,A,merge_func,ide_ele): N=len(A) n=N.bit_length() self.table=[[ide_ele for i in range(n)] for i in range(N)] self.merge_func=merge_func for i in range(N): self.table[i][0]=A[i] for j in range(1,n): for i in range(0,N-2**j+1): f=self.table[i][j-1] s=self.table[i+2**(j-1)][j-1] self.table[i][j]=self.merge_func(f,s) def query(self,s,t): b=t-s+1 m=b.bit_length()-1 return self.merge_func(self.table[s][m],self.table[t-2**m+1][m]) class Binary_idx_Trie: class node: def __init__(self,val): self.left = None self.right = None self.max = val def __init__(self): self.root = self.node(-10**15) def append(self,key,val): pos = self.root for i in range(29,-1,-1): pos.max = max(pos.max,val) if key>>i & 1: if pos.right is None: pos.right = self.node(val) pos = pos.right else: pos = pos.right else: if pos.left is None: pos.left = self.node(val) pos = pos.left else: pos = pos.left pos.max = max(pos.max,val) def search(self,M,xor): res = -10**15 pos = self.root for i in range(29,-1,-1): if pos is None: break if M>>i & 1: if xor>>i & 1: if pos.right: res = max(res,pos.right.max) pos = pos.left else: if pos.left: res = max(res,pos.left.max) pos = pos.right else: if xor>>i & 1: pos = pos.right else: pos = pos.left if pos: res = max(res,pos.max) return res class BinaryTrie(): class node: def __init__(self): self.left = None self.right = None self.cnt = 0 def __init__(self,n): self.root = self.node() self.n = n def append(self,key): n = self.n pos = self.root pos.cnt += 1 for i in range(n-1,-1,-1): if key>>i & 1: if pos.right is None: pos.right = self.node() pos = pos.right pos.cnt += 1 else: if pos.left is None: pos.left = self.node() pos = pos.left pos.cnt += 1 def delete(self,key): n = self.n pos = self.root pos.cnt -= 1 for i in range(n-1,-1,-1): if key>>i & 1: pos = pos.right pos.cnt -= 1 else: pos = pos.left pos.cnt -= 1 def search_min(self,xor=0): n = self.n res = 0 pos = self.root for i in range(n-1,-1,-1): if xor>>i & 1: if pos.right and pos.right.cnt: pos = pos.right else: res += 1<>i & 1 == 0: if pos.right and pos.right.cnt: res += 1< 0 and r0 + cost - H[w] < dist[w]: dist[w] = r = r0 + cost - H[w] prv_v[w] = v; prv_e[w] = e heappush(que, (r, w)) if dist[t] == INF: return None for i in range(N): H[i] += dist[i] d = f; v = t while v != s: d = min(d, prv_e[v][1]) v = prv_v[v] f -= d res += d * H[t] v = t while v != s: e = prv_e[v] e[1] -= d e[3][1] += d v = prv_v[v] return res import sys,random,bisect from collections import deque,defaultdict from heapq import heapify,heappop,heappush from itertools import permutations from math import gcd,log input = lambda :sys.stdin.readline().rstrip() mi = lambda :map(int,input().split()) li = lambda :list(mi()) N,M,K = mi() Edge = [] for _ in range(M): u,v,c = mi() Edge.append((u-1,v-1,c)) def cond(x): edge = [[] for v in range(N)] #city = Dijkstra(N) for u,v,c in Edge: if c<=x: #city.add_edge(u,v,0) #city.add_edge(v,u,0) edge[u].append((v,0)) edge[v].append((u,0)) else: #city.add_edge(u,v,1) #city.add_edge(v,u,1) edge[u].append((v,1)) edge[v].append((u,1)) #dist = city.shortest_path(0) INF = 10**9 dist = [INF for v in range(N)] dist[0] = 0 deq = deque([0]) check = [False for v in range(N)] while deq: v = deq.popleft() if check[v]: continue check[v] = True for nv,c in edge[v]: if dist[nv] > dist[v] + c: dist[nv] = dist[v] + c if c==0: deq.appendleft(nv) else: deq.append(nv) return dist[N-1] < K ok = 2*10**5 ng = -1 while ok-ng>1: mid = (ok+ng)//2 if cond(mid): ok = mid else: ng = mid print(ok)