import macros macro Please(x): untyped = nnkStmtList.newTree() Please use Nim-ACL Please use Nim-ACL Please use Nim-ACL import macros;macro ImportExpand(s:untyped):untyped = parseStmt($s[2]) import macros # {.checks: off.} ImportExpand "cplib/tmpl/citrus.nim" <=== "when not declared CPLIB_TMPL_CITRUS:\n const CPLIB_TMPL_CITRUS* = 1\n {.warning[UnusedImport]: off.}\n {.hint[XDeclaredButNotUsed]: off.}\n import os\n import algorithm\n import sequtils\n import tables\n import macros\n import std/math\n import sets\n import strutils\n import strformat\n import sugar\n import streams\n import deques\n import bitops\n import heapqueue\n const MODINT998244353* = 998244353\n const MODINT1000000007* = 1000000007\n const INF* = 100100111\n const INFL* = int(3300300300300300491)\n type double* = float64\n let readNext = iterator(getsChar: bool = false): string {.closure.} =\n while true:\n var si: string\n try: si = stdin.readLine\n except EOFError: yield \"\"\n for s in si.split:\n if getsChar:\n for i in 0..>`*(x: int, y: int): int = x shr y\n proc `<<`*(x: int, y: int): int = x shl y\n proc `%=`*(x: var SomeInteger or int64, y: SomeInteger or\n int64): void = x = x % y\n proc `//=`*(x: var int, y: int): void = x = x // y\n proc `^=`*(x: var int, y: int): void = x = x ^ y\n proc `&=`*(x: var int, y: int): void = x = x & y\n proc `|=`*(x: var int, y: int): void = x = x | y\n proc `>>=`*(x: var int, y: int): void = x = x >> y\n proc `<<=`*(x: var int, y: int): void = x = x << y\n proc `[]`*(x: int, n: int): bool = (x and (1 shl n)) != 0\n\n proc pow*(a, n: int, m = INFL): int =\n var\n rev = 1\n a = a\n n = n\n while n > 0:\n if n % 2 != 0: rev = (rev * a) mod m\n if n > 1: a = (a * a) mod m\n n >>= 1\n return rev\n proc sqrt*(x: int): int =\n assert(x >= 0)\n result = int(sqrt(float64(x)))\n while result * result > x: result -= 1\n while (result+1) * (result+1) <= x: result += 1\n proc chmax*[T](x: var T, y: T): bool = (if x < y: (x = y; return true;\n ) return false)\n proc chmin*[T](x: var T, y: T): bool = (if x > y: (x = y; return true;\n ) return false)\n proc `max=`*[T](x: var T, y: T) = x = max(x, y)\n proc `min=`*[T](x: var T, y: T) = x = min(x, y)\n proc at*(x: char, a = '0'): int = int(x) - int(a)\n converter tofloat*(n: int): float = float(n)\n iterator rangeiter*(start: int, ends: int, step: int): int =\n var i = start\n if step < 0:\n while i > ends:\n yield i\n i += step\n elif step > 0:\n while i < ends:\n yield i\n i += step\n iterator rangeiter*(ends: int): int = (for i in 0.. costs[i]:\n continue\n for (j, c) in G.edges[i]:\n var temp = costs[i] + c\n if temp < costs[j]:\n prev[j] = i\n costs[j] = temp\n queue.push((temp, j))\n return (costs, prev)\n proc dijkstra*[T](G: Graph[T], start: int, ZERO: T = 0, INF: T = int(3300300300300300491)): seq[T] =\n var costs, _ = restore_dijkstra(G, start, ZERO, INF)\n return costs\n proc restore_shortestpath_from_prev*(prev: seq[int], goal: int): seq[int] =\n var i = goal\n while i != -1:\n result.add(i)\n i = prev[i]\n result = result.reversed()\n proc shortest_path*[T](G: Graph[T], start: int, goal: int, ZERO: T = 0, INF: T = int(3300300300300300491)): tuple[path: seq[int], cost: int] =\n var (costs, prev) = restore_dijkstra(G, start, ZERO, INF)\n result.path = prev.restore_shortestpath_from_prev(goal)\n result.cost = costs[goal]\n discard\n" # see https://github.com/zer0-star/Nim-ACL/tree/master/src/atcoder/mincostflow.nim ImportExpand "atcoder/mincostflow.nim" <=== "when not declared ATCODER_MINCOSTFLOW_HPP:\n const ATCODER_MINCOSTFLOW_HPP* = 1\n\n import std/heapqueue\n import std/algorithm\n #[ import atcoder/internal_csr ]#\n when not declared ATCODER_INTERNAL_CSR_HPP:\n const ATCODER_INTERNAL_CSR_HPP* = 1\n \n type csr*[E] = object\n start*: seq[int]\n elist*: seq[E]\n proc initCsr*[E](n:int, edges:seq[(int, E)]):csr[E] =\n var start = newSeq[int](n + 1)\n var elist = newSeq[E](edges.len)\n for e in edges: start[e[0] + 1].inc\n for i in 1..n: start[i] += start[i - 1]\n var counter = start\n for e in edges:\n elist[counter[e[0]]] = e[1]\n counter[e[0]].inc\n return csr[E](start:start, elist:elist)\n discard\n #[ import atcoder/internal_queue ]#\n when not declared ATCODER_INTERNAL_QUEUE_HPP:\n const ATCODER_INTERNAL_QUEUE_HPP* = 1\n \n type simple_queue[T] = object\n payload:seq[T]\n pos:int\n proc init_simple_queue*[T]():auto = simple_queue[T](payload:newSeq[T](), pos:0)\n # TODO\n # void reserve(int n) { payload.reserve(n); }\n proc len*[T](self:simple_queue[T]):int = self.payload.len - self.pos\n proc empty*[T](self:simple_queue[T]):bool = self.pos == self.payload.len\n proc push*[T](self:var simple_queue[T], t:T) = self.payload.add(t)\n proc front*[T](self:simple_queue[T]):T = self.payload[self.pos]\n proc clear*[T](self:var simple_queue[T]) =\n self.payload.setLen(0)\n self.pos = 0;\n proc pop*[T](self:var simple_queue[T]) = self.pos.inc\n discard\n #[ import atcoder/internal_heap ]#\n when not declared ATCODER_INTERNAL_HEAP:\n const ATCODER_INTERNAL_HEAP* = 1\n proc push_heap*[T](v: var openArray[T], p:Slice[int]) {.inline.} =\n var i = p.b\n while i > 0:\n var p = (i - 1) shr 1\n if v[p] < v[i]: swap v[p], v[i]\n else: break\n i = p\n proc pop_heap*[T](v: var openArray[T], p:Slice[int]) {.inline.} =\n swap v[0], v[p.b]\n var p = p\n p.b.dec\n var i = 0\n while true:\n var (c0, c1) = (i * 2 + 1, i * 2 + 2)\n if c1 in p:\n if v[c1] > v[i]:\n if v[c0] > v[c1]:\n swap(v[i], v[c0])\n i = c0\n else:\n swap(v[i], v[c1])\n i = c1\n elif v[c0] > v[i]:\n swap(v[i], v[c0])\n i = c0\n else: break\n elif c0 in p:\n if v[c0] > v[i]:\n swap(v[i], v[c0])\n i = c0\n else: break\n else: break\n discard\n\n type MCFEdge*[Cap, Cost] = object\n src*, dst*: int\n cap*, flow*: Cap\n cost*: Cost\n\n type MCFInternalEdge[Cap, Cost] = object\n dst, rev: int\n cap: Cap\n cost: Cost\n\n type MCFGraph*[Cap, Cost] = object\n n:int\n edges:seq[MCFEdge[Cap, Cost]]\n \n proc initMCFGraph*[Cap, Cost](n:int):MCFGraph[Cap, Cost] = result.n = n\n proc initMinCostFLow*[Cap, Cost](n:int):MCFGraph[Cap, Cost] = result.n = n\n\n proc add_edge*[Cap, Cost](self: var MCFGraph[Cap, Cost], src, dst:int, cap:Cap, cost:Cost):int {.discardable.} =\n assert src in 0.. r.key\n\n proc slope*[Cap, Cost](self: MCFGraph[Cap, Cost], g:var csr[MCFInternalEdge[Cap, Cost]], s, t:int, flow_limit:Cap):seq[tuple[cap:Cap, cost:Cost]] =\n ## variants (C = maxcost):\n ## -(n-1)C <= dual[s] <= dual[i] <= dual[t] = 0\n ## reduced cost (= e.cost + dual[e.src] - dual[e.to]) >= 0 for all edge\n\n ## dual_dist[i] = (dual[i], dist[i])\n var\n dual_dist = newSeq[tuple[dual, dist:Cost]](self.n)\n prev_e = newSeq[int](self.n)\n vis = newSeq[bool](self.n)\n que_min = newSeq[int]()\n que = newSeq[MCFQ[Cost]]()\n proc dual_ref(g:csr[MCFInternalEdge[Cap, Cost]]):bool =\n for i in 0.. 0 or que.len > 0:\n var v:int\n if que_min.len > 0:\n v = que_min.pop()\n else:\n while heap_r < que.len:\n heap_r.inc\n que.push_heap(0 ..< heap_r)\n v = que[0].dst\n que.pop_heap(0 ..< que.len)\n discard que.pop()\n heap_r.dec\n if vis[v]: continue\n vis[v] = true\n if v == t: break\n ## dist[v] = shortest(s, v) + dual[s] - dual[v]\n ## dist[v] >= 0 (all reduced cost are positive)\n ## dist[v] <= (n-1)C\n let (dual_v, dist_v) = dual_dist[v]\n for i in g.start[v] ..< g.start[v + 1]:\n let e = g.elist[i]\n if e.cap == Cap(0): continue\n ## |-dual[e.to] + dual[v]| <= (n-1)C\n ## cost <= C - -(n-1)C + 0 = nC\n let cost = e.cost - dual_dist[e.dst].dual + dual_v\n if dual_dist[e.dst].dist - dist_v > cost:\n let dist_to = dist_v + cost\n dual_dist[e.dst].dist = dist_to\n prev_e[e.dst] = e.rev\n if dist_to == dist_v:\n que_min.add(e.dst)\n else:\n que.add(MCFQ[Cost](key:dist_to, dst:e.dst))\n if not vis[t]:\n return false\n\n for v in 0..= 0 - (n-1)C\n dual_dist[v].dual -= dual_dist[t].dist - dual_dist[v].dist\n return true\n var\n flow:Cap = 0\n cost:Cost = 0\n prev_cost_per_flow:Cost = -1\n result = @[(Cap(0), Cost(0))]\n while flow < flow_limit:\n if not g.dual_ref(): break\n var c = flow_limit - flow\n block:\n var v = t\n while v != s:\n c = min(c, g.elist[g.elist[prev_e[v]].rev].cap)\n v = g.elist[prev_e[v]].dst\n block:\n var v = t\n while v != s:\n var e = g.elist[prev_e[v]].addr\n e[].cap += c\n g.elist[e[].rev].cap -= c\n v = g.elist[prev_e[v]].dst\n let d = -dual_dist[s].dual\n flow += c\n cost += c * d\n if prev_cost_per_flow == d:\n discard result.pop()\n result.add((flow, cost))\n prev_cost_per_flow = d\n\n proc slope*[Cap, Cost](self:var MCFGraph[Cap, Cost], s, t:int, flow_limit:Cap):seq[tuple[cap:Cap, cost:Cost]] =\n assert s in 0..