ac-library-hs-1.5.2.0: src/AtCoder/Extra/Graph.hs
{-# LANGUAGE LambdaCase #-}
{-# LANGUAGE MultiWayIf #-}
{-# LANGUAGE RecordWildCards #-}
-- | Re-export of the @Csr@ module and additional graph search functions.
--
-- @since 1.1.0.0
module AtCoder.Extra.Graph
( -- * Re-export of CSR
-- | The @Csr@ data type and all the functions such as `build` or `adj` are re-exported.
-- See the @Csr@ module for details.
module Csr,
-- * CSR helpers
swapDupe,
swapDupe',
scc,
rev,
findCycleDirected,
findCycleUndirected,
-- * Generic graph functions
-- TODO: generalize vertex dimensions?
topSort,
connectedComponents,
bipartiteVertexColors,
blockCut,
blockCutComponents,
-- * Shortest path search
-- | Most of the functions are opinionated as the followings:
--
-- - Indices are abstracted with `Ix0` (n-dimensional `Int`).
-- - Functions that return a predecessor array are named as @tracking*@.
-- ** BFS (breadth-first search)
-- | Constraints:
--
-- - Edge weight \(w > 0\)
bfs,
trackingBfs,
-- ** 01-BFS
-- | Constraints:
--
-- - Edge weight \(w\) is either \(0\) or \(1\) of type `Int`.
bfs01,
trackingBfs01,
-- ** Dijkstra's algorithm
-- | Constraints:
--
-- - Edge weight \(w > 0\)
dijkstra,
trackingDijkstra,
-- ** Bellman–Ford algorithm
-- | - Vertex type is restricted to one-dimensional `Int`.
bellmanFord,
trackingBellmanFord,
-- ** Floyd–Warshall algorithm
--
-- | All-pair shortest path.
floydWarshall,
trackingFloydWarshall,
-- *** Incremental Floyd–Warshall algorithm
newFloydWarshall,
newTrackingFloydWarshall,
updateEdgeFloydWarshall,
updateEdgeTrackingFloydWarshall,
-- ** Path reconstruction
-- TODO: panic instead of infinite loop?
-- *** Single source point (root)
-- | Functions for retrieving a path from a predecessor array, where @-1@ represents none.
constructPathFromRoot,
constructPathToRoot,
-- *** All-pair
-- | Functions for retrieving a path from a predecessor matrix \(m\).
constructPathFromRootMat,
constructPathToRootMat,
constructPathFromRootMatM,
constructPathToRootMatM,
)
where
import AtCoder.Dsu qualified as Dsu
import AtCoder.Extra.HashMap qualified as HM
import AtCoder.Extra.IntSet qualified as IS
import AtCoder.Extra.Ix0 (Bounds0, Ix0 (..))
import AtCoder.Internal.Assert qualified as ACIA
import AtCoder.Internal.Buffer qualified as B
import AtCoder.Internal.Csr as Csr
import AtCoder.Internal.GrowVec qualified as GV
import AtCoder.Internal.MinHeap qualified as MH
import AtCoder.Internal.Queue qualified as Q
import AtCoder.Internal.Scc qualified as ACISCC
import Control.Applicative ((<|>))
import Control.Monad (replicateM_, unless, when)
import Control.Monad.Fix (fix)
import Control.Monad.Primitive (PrimMonad, PrimState, stToPrim)
import Control.Monad.ST (ST, runST)
import Data.Bit (Bit (..))
import Data.Bits ((.<<.), (.|.))
import Data.Foldable (for_)
import Data.Maybe (fromJust, fromMaybe)
import Data.Vector qualified as V
import Data.Vector.Generic qualified as VG
import Data.Vector.Generic.Mutable qualified as VGM
import Data.Vector.Unboxed qualified as VU
import Data.Vector.Unboxed.Mutable qualified as VUM
import Data.Word (Word8)
import GHC.Stack (HasCallStack)
-- | \(O(n)\) Converts directed edges into non-directed edges; each edge \((u, v, w)\) is duplicated
-- to be \((u, v, w)\) and \((v, u, w)\). This is a convenient function for making an input to
-- `build`.
--
-- ==== __Example__
-- `swapDupe` duplicates each edge reversing the direction:
--
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> Gr.swapDupe $ VU.fromList [(0, 1, ()), (1, 2, ())]
-- [(0,1,()),(1,0,()),(1,2,()),(2,1,())]
--
-- Create a non-directed graph:
--
-- >>> let gr = Gr.build 3 . Gr.swapDupe $ VU.fromList [(0, 1, ()), (1, 2, ())]
-- >>> gr `Gr.adj` 0
-- [1]
--
-- >>> gr `Gr.adj` 1
-- [0,2]
--
-- >>> gr `Gr.adj` 2
-- [1]
--
-- @since 1.1.0.0
{-# INLINEABLE swapDupe #-}
swapDupe :: (VU.Unbox w) => VU.Vector (Int, Int, w) -> VU.Vector (Int, Int, w)
swapDupe uvws = VU.create $ do
vec <- VUM.unsafeNew (2 * VU.length uvws)
VU.iforM_ uvws $ \i (!u, !v, !w) -> do
VGM.unsafeWrite vec (2 * i + 0) (u, v, w)
VGM.unsafeWrite vec (2 * i + 1) (v, u, w)
pure vec
-- | \(O(n)\) Converts directed edges into non-directed edges; each edge \((u, v)\) is duplicated
-- to be \((u, v)\) and \((v, u)\). This is a convenient function for making an input to `build'`.
--
-- ==== __Example__
-- `swapDupe'` duplicates each edge reversing the direction:
--
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> Gr.swapDupe' $ VU.fromList [(0, 1), (1, 2)]
-- [(0,1),(1,0),(1,2),(2,1)]
--
-- Create a non-directed graph:
--
-- >>> let gr = Gr.build' 3 . Gr.swapDupe' $ VU.fromList [(0, 1), (1, 2)]
-- >>> gr `Gr.adj` 0
-- [1]
--
-- >>> gr `Gr.adj` 1
-- [0,2]
--
-- >>> gr `Gr.adj` 2
-- [1]
--
-- @since 1.1.0.0
{-# INLINEABLE swapDupe' #-}
swapDupe' :: VU.Vector (Int, Int) -> VU.Vector (Int, Int)
swapDupe' uvs = VU.create $ do
vec <- VUM.unsafeNew (2 * VU.length uvs)
VU.iforM_ uvs $ \i (!u, !v) -> do
VGM.unsafeWrite vec (2 * i + 0) (u, v)
VGM.unsafeWrite vec (2 * i + 1) (v, u)
pure vec
-- | \(O(n + m)\) Returns the strongly connected components of a `Csr`.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> -- 0 == 1 -> 2 3
-- >>> let gr = Gr.build' 4 $ VU.fromList [(0, 1), (1, 0), (1, 2)]
-- >>> Gr.scc gr
-- [[3],[0,1],[2]]
--
-- @since 1.1.0.0
{-# INLINE scc #-}
scc :: Csr w -> V.Vector (VU.Vector Int)
scc = ACISCC.sccCsr
-- | \(O(n + m)\) Returns a reverse graph, where original edges \((u, v, w)\) are transposed to be
-- \((v, u, w)\). Reverse graphs are useful for, for example, getting distance to a specific vertex
-- from every other vertex with `dijkstra`.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> -- 0 == 1 -> 2 -> 3
-- >>> let gr = Gr.build' 4 $ VU.fromList [(0, 1), (1, 0), (1, 2), (2, 3)]
-- >>> map (Gr.adj gr) [0 .. 3]
-- [[1],[0,2],[3],[]]
--
-- >>> -- 0 == 1 <- 2 <- 3
-- >>> let revGr = Gr.rev gr
-- >>> map (Gr.adj revGr) [0 .. 3]
-- [[1],[0],[1],[2]]
--
-- @since 1.2.3.0
{-# INLINEABLE rev #-}
rev :: (VU.Unbox w) => Csr w -> Csr w
rev Csr {..} = Csr.build nCsr revEdges
where
vws = VU.zip adjCsr wCsr
revEdges = flip VU.concatMap (VU.generate nCsr id) $ \v1 ->
let !o1 = startCsr VG.! v1
!o2 = startCsr VG.! (v1 + 1)
!vw2s = VU.slice o1 (o2 - o1) vws
in VU.map (\(!v2, !w2) -> (v2, v1, w2)) vw2s
-- TODO: is this minimum cycle?
-- | \(O(n + m)\) Given a directed graph, finds a minimal cycle and returns @(vertices, csrEdgeIndices)@.
--
-- ==== __Example__
--
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let gr = Gr.build' 4 $ VU.fromList [(0, 1), (1, 2), (2, 3), (3, 1)]
-- >>> findCycleDirected gr -- returns (vs, es)
-- Just ([1,2,3],[1,2,3])
--
-- @since 1.4.0.0
{-# INLINEABLE findCycleDirected #-}
findCycleDirected :: (HasCallStack, VU.Unbox w) => Csr w -> Maybe (VU.Vector Int, VU.Vector Int)
findCycleDirected gr@Csr {..} = runST $ do
used <- VUM.replicate @_ @Word8 nCsr 0
-- par <- VUM.unsafeNew @_ @(Int, Int) nCsr
par <- VUM.replicate nCsr (-1 :: Int, -1 :: Int)
vs <- GV.new @_ @Int 16
es <- GV.new @_ @Int 16
esFrom <- GV.new @_ @Int 16 -- If we had `from` in Csr, we could skip this
let dfs u = do
VGM.write used u 1
let next evs = case VU.uncons evs of
Nothing -> pure ()
Just ((!iEdge, !v), !evs') -> do
b <- GV.null es
when b $ do
use <- VGM.read used v
case use of
0 -> do
VGM.write par v (u, iEdge)
dfs v
next evs'
1 -> do
GV.pushBack es iEdge
GV.pushBack esFrom u
let backtrack cur
| cur == v = pure ()
| otherwise = do
(!prevVert, !edge) <- VGM.read par cur
GV.pushBack es edge
GV.pushBack esFrom prevVert
backtrack prevVert
backtrack u
GV.reverse es
GV.reverse esFrom
_ -> do
next evs'
next $ eAdj gr u
VGM.write used u 2
VGM.iforM_ used $ \v use -> do
when (use == 0) $ do
dfs v
b <- GV.null es
unless b $ do
-- find minimum cycle
nxt <- VUM.replicate nCsr (-1 :: Int) -- edge indices
do
es' <- GV.unsafeFreeze es
esFrom' <- GV.unsafeFreeze esFrom
VU.forM_ (VU.zip es' esFrom') $ \(!iEdge, !vFrom) -> do
VGM.write nxt vFrom iEdge
for_ [0 .. nCsr - 1] $ \vA -> do
nxtA <- VGM.read nxt vA
unless (nxtA == -1) $ do
VU.forM_ (eAdj gr vA) $ \(!iEdge, !vB) -> do
nxtB <- VGM.read nxt vB
unless (nxtB == -1 || adjCsr VG.! nxtA == vB) $ do
let inner x
| x == vB = pure ()
| otherwise = do
nxtX <- VGM.exchange nxt x (-1)
inner $ adjCsr VG.! nxtX
inner vA
VGM.write nxt vA iEdge
GV.clear es
let loop v
| v >= nCsr = pure ()
| otherwise = do
nxtV <- VGM.read nxt v
if nxtV == -1
then loop (v + 1)
else do
let inner x = do
GV.pushBack vs x
nxtX <- VGM.read nxt x
GV.pushBack es nxtX
let !x' = adjCsr VG.! nxtX
unless (x' == v) $ inner x'
inner v
loop 0
vs' <- GV.unsafeFreeze vs
es' <- GV.unsafeFreeze es
if VU.null es'
then pure Nothing
else pure $ Just (vs', es')
-- | \(O(n + m)\) Given an undirected graph, finds a minimal cycle and returns @(vertices, csrEdgeIndices)@.
-- A single edge index does not make much sense for an undirected graph, so map back to the original
-- edge index manually if needed.
--
-- ==== Constraints
-- - The graph must be created with `swapDupe` or `swapDupe'`. Otherwise the returned edge indices
-- could make no sense.
--
-- ==== __Example__
--
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let gr = Gr.build' 4 . Gr.swapDupe' $ VU.fromList [(0, 1), (1, 2), (1, 3), (2, 3)]
-- >>> findCycleUndirected gr -- returns (vs, es)
-- Just ([1,3,2],[3,5,2])
--
-- Retrieve original edge indices that makes up the cycle, by recording them in edge weights:
--
-- >>> let gr = Gr.build 4 . Gr.swapDupe $ VU.fromList [(0, 1, 0 :: Int), (1, 2, 1), (1, 3, 2), (2, 3, 3)]
-- >>> let Just (vs, es) = findCycleUndirected gr -- returns (vs, es)
-- >>> VU.backpermute (Gr.wCsr gr) es
-- [2,3,1]
--
-- It's a bit hacky.
--
-- @since 1.4.0.0
{-# INLINEABLE findCycleUndirected #-}
findCycleUndirected :: (HasCallStack, VU.Unbox w) => Csr w -> Maybe (VU.Vector Int, VU.Vector Int)
findCycleUndirected gr@Csr {..} =
let !_ = ACIA.runtimeAssert (even mCsr) $ "AtCoder.Extra.Graph.findCycleUndirected: the number of edge in an undirected graph must be even: `" ++ show mCsr ++ "`"
in -- If we have the same edge id for duplicated edges, `findCycleSimpleUndirected` could be modified
-- to handle both complex and simple graph. We don't, and we need the complex graph handling.
-- This is not optimal, but we need a dedicated `buildUndirected` function and different edge ID
-- (not index) handling in CSR if we go with the optimal approach.
--
-- Note that the implementations are suspecious..
findCycleComplexUndirected gr <|> findCycleSimpleUndirected gr
{-# INLINEABLE findCycleComplexUndirected #-}
findCycleComplexUndirected :: (HasCallStack, VU.Unbox w) => Csr w -> Maybe (VU.Vector Int, VU.Vector Int)
findCycleComplexUndirected gr@Csr {..} = runST $ do
usedE <- HM.new @_ @Int (mCsr `div` 2 + {- not needed, but in case of panic? -} 4)
cntE <- HM.new @_ @Word8 (mCsr `div` 2 + {- not needed, but in case of panic? -} 4)
-- we'll give unique indices to (u, v) pairs
let ix u v = min u v .<<. 32 .|. max u v
let nextU u
| u >= nCsr = pure Nothing
| otherwise = do
let nextV evs = case VU.uncons evs of
Nothing -> pure Nothing
Just ((!e, !v), !evs') -> case compare u v of
-- self loop edge
EQ -> pure $ Just (VU.singleton v, VU.singleton e)
LT -> do
let !i = ix u v
c <- fromMaybe 0 <$> HM.lookup cntE i
case c of
0 -> do
HM.insert usedE i e
HM.insert cntE i 1
nextV evs'
1 -> do
-- found the first duplicated edge
HM.insert cntE i 2
nextV evs'
_ -> do
nextV evs'
GT -> do
let !i = ix u v
cnt <- fromMaybe 0 <$> HM.lookup cntE i
case cnt of
2 -> do
-- there are duplicate edges between (u, v) and this is the
-- first (u, v) (u > v)
HM.insert cntE i 3
nextV evs'
3 -> do
-- this is the second duplicate edge (u, v) (u > v)
e1 <- fromJust <$> HM.lookup usedE i
let vs = VU.fromListN 2 [v, u]
let es = VU.fromListN 2 [e1, e]
pure $ Just (vs, es)
_ -> nextV evs'
res <- nextV $ eAdj gr u
case res of
Just ret -> pure $ Just ret
Nothing -> nextU (u + 1)
nextU 0
{-# INLINEABLE findCycleSimpleUndirected #-}
findCycleSimpleUndirected :: (HasCallStack, VU.Unbox w) => Csr w -> Maybe (VU.Vector Int, VU.Vector Int)
findCycleSimpleUndirected gr@Csr {..} = runST $ do
-- marks both (u, v) and (v, u)
usedUV <- HM.new @_ @Bit (mCsr + 4)
-- we'll give unique indices to (u, v) pairs
let ix u v = min u v .<<. 32 .|. max u v
-- depth
dep <- VUM.replicate nCsr (-1 :: Int)
-- vertex -> edge index
par <- VUM.replicate nCsr (-1 :: Int)
parFrom <- VUM.replicate nCsr (-1 :: Int)
-- Get DFS forest
let dfs u d = do
VGM.write dep u d
VU.forM_ (eAdj gr u) $ \(!iEdge, !v) -> do
dv <- VGM.read dep v
when (dv == -1) $ do
-- we're marking both direction of an undirected edge
HM.insert usedUV (ix u v) $ Bit True
VGM.write par v iEdge
VGM.write parFrom v u
dfs v (d + 1)
VGM.iforM_ dep $ \v d -> do
when (d == -1) $ do
dfs v 0
vs <- GV.new @_ @Int 16
es <- GV.new @_ @Int 16
dep' <- VU.unsafeFreeze dep
-- Find edge with minimum depth difference, which makes up a loop (not used in the DFS forets):
minLen <- VUM.replicate 1 (maxBound `div` 2 :: Int)
backE <- VUM.replicate 1 (-1 :: Int, -1 :: Int)
for_ [0 .. nCsr - 1] $ \vA -> do
let !dA = dep' VG.! vA
VU.forM_ (eAdj gr vA) $ \(!iEdge, !vB) -> do
b <- maybe False unBit <$> HM.lookup usedUV (ix vA vB)
unless b $ do
let !dB = dep' VG.! vB
let !d = abs $ dA - dB
minLen' <- VGM.read minLen 0
when (d < minLen') $ do
VGM.write minLen 0 d
VGM.write backE 0 (iEdge, vA)
(!backE', !backFrom) <- VGM.read backE 0
when (backE' /= -1) $ do
let try a b = do
if dep' VG.! a > dep' VG.! b
then try b a
else do
-- v_1 -> v_N -> v_{N - 1} -> .. -> v_2 -> v_1
GV.pushBack es backE'
GV.pushBack vs a
let backtrack v = do
unless (v == a) $ do
parE <- VGM.read par v
v' <- VGM.read parFrom v
GV.pushBack vs v
GV.pushBack es parE
backtrack v'
backtrack b
try backFrom (adjCsr VG.! backE')
vs' <- GV.unsafeFreeze vs
es' <- GV.unsafeFreeze es
if VU.null es'
then pure Nothing
else pure $ Just (vs', es')
-- -------------------------------------------------------------------------------------------------
-- Generic graph search functions
-- -------------------------------------------------------------------------------------------------
-- | \(O(n \log n + m)\) Returns the lexicographically smallest topological ordering of the given
-- graph.
--
-- ==== Constraints
-- - The graph must be a DAG; there must be no cycle.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let n = 5
-- >>> let gr = Gr.build' n $ VU.fromList [(1, 2), (4, 0), (0, 3)]
-- >>> Gr.topSort n (gr `Gr.adj`)
-- [1,2,4,0,3]
--
-- @since 1.1.0.0
{-# INLINEABLE topSort #-}
topSort ::
-- | \(n\): The number of vertices.
Int ->
-- | \(g\): Graph function, typically @'adj' gr@.
(Int -> VU.Vector Int) ->
-- | Vertices in topological ordering: upstream vertices come first.
VU.Vector Int
topSort n gr = runST $ do
inDeg <- VUM.replicate n (0 :: Int)
for_ [0 .. n - 1] $ \u -> do
VU.forM_ (gr u) $ \v -> do
VGM.modify inDeg (+ 1) v
-- start from the vertices with zero in-degrees:
que <- IS.new n
inDeg' <- VU.unsafeFreeze inDeg
VU.iforM_ inDeg' $ \v d -> do
when (d == 0) $ do
IS.insert que v
buf <- B.new n
fix $ \loop -> do
IS.deleteMin que >>= \case
Nothing -> pure ()
Just u -> do
B.pushBack buf u
VU.forM_ (gr u) $ \v -> do
nv <- subtract 1 <$> VGM.read inDeg v
VGM.write inDeg v nv
when (nv == 0) $ do
IS.insert que v
loop
B.unsafeFreeze buf
-- | \(O(n)\) Returns connected components for a non-directed graph.
--
-- ==== Constraints
-- - The graph must be non-directed: both \((u, v)\) and \((v, u)\) edges must exist.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1), (1, 2)]
-- >>> let gr = Gr.build' 4 $ Gr.swapDupe' es
-- >>> Gr.connectedComponents 4 (Gr.adj gr)
-- [[0,1,2],[3]]
--
-- >>> Gr.connectedComponents 0 (const VU.empty)
-- []
--
-- @since 1.2.4.0
{-# INLINEABLE connectedComponents #-}
connectedComponents ::
-- | \(n\): The number of vertices.
Int ->
-- | \(g\): Graph function, typically @'adj' gr@.
(Int -> VU.Vector Int) ->
-- | Connected components.
V.Vector (VU.Vector Int)
connectedComponents n gr = runST $ do
buf <- B.new @_ @Int n
len <- B.new @_ @Int n
vis <- VUM.replicate @_ @Bit n (Bit False)
let dfs !acc u = do
Bit b <- VGM.exchange vis u $ Bit True
if b
then pure acc
else do
B.pushBack buf u
VU.foldM' dfs (acc + 1) (gr u)
for_ [0 .. n - 1] $ \u -> do
l :: Int <- dfs 0 u
when (l > 0) $ do
B.pushBack len l
vs0 <- B.unsafeFreeze buf
lens0 <- B.unsafeFreeze len
pure
. V.unfoldrExactN
(VU.length lens0)
( \(!vs, !ls) ->
let (!l, !lsR) = fromJust $ VU.uncons ls
(!vsL, !vsR) = VU.splitAt l vs
in (vsL, (vsR, lsR))
)
$ (vs0, lens0)
-- | \(O((n + m) \alpha)\) Returns a bipartite vertex coloring for a bipartite graph.
-- Returns `Nothing` for a non-bipartite graph.
--
-- ==== Constraints
-- - The graph must not be directed.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1), (1, 2)]
-- >>> let gr = Gr.build' 4 es
-- >>> Gr.bipartiteVertexColors 4 (Gr.adj gr)
-- Just [0,1,0,0]
--
-- @since 1.2.4.0
{-# INLINEABLE bipartiteVertexColors #-}
bipartiteVertexColors ::
-- | \(n\): The number of vertices.
Int ->
-- | \(g\): Graph function, typically @'adj' gr@.
(Int -> VU.Vector Int) ->
-- | Bipartite vertex coloring.
Maybe (VU.Vector Bit)
bipartiteVertexColors n gr = runST $ do
(!isBipartite, !color, !_) <- bipartiteVertexColorsImpl n gr
if isBipartite
then pure $ Just color
else pure Nothing
{-# INLINEABLE bipartiteVertexColorsImpl #-}
bipartiteVertexColorsImpl :: Int -> (Int -> VU.Vector Int) -> ST s (Bool, VU.Vector Bit, Dsu.Dsu s)
bipartiteVertexColorsImpl n gr
| n == 0 = do
dsu <- Dsu.new 0
pure (True, VU.empty, dsu)
| otherwise = do
-- 0 <= v < n: red, n <= v: green
dsu <- Dsu.new (2 * n)
for_ [0 .. n - 1] $ \u -> do
VU.forM_ (gr u) $ \v -> do
-- try both (red, green) and (green, red) colorings:
Dsu.merge_ dsu (u + n) v
Dsu.merge_ dsu u (v + n)
color <- VUM.replicate (2 * n) $ Bit False
-- for each leader vertices, paint their colors:
for_ [0 .. n - 1] $ \v -> do
l <- Dsu.leader dsu v
when (l == v) $ do
VGM.write color (v + n) $ Bit True
-- paint other vertices:
for_ [0 .. n - 1] $ \v -> do
VGM.write color v =<< VGM.read color =<< Dsu.leader dsu v
VGM.write color (v + n) =<< VGM.read color =<< Dsu.leader dsu (v + n)
color' <- VU.unsafeFreeze $ VGM.take n color
let isCompatible v
| v >= n = pure True
| otherwise = do
c1 <- VGM.read color =<< Dsu.leader dsu v
c2 <- VGM.read color =<< Dsu.leader dsu (v + n)
if c1 == c2
then pure False
else isCompatible $ v + 1
b <- isCompatible 0
pure (b, color', dsu)
-- | \(O(n + m)\) Returns a [block-cut tree](https://en.wikipedia.org/wiki/Biconnected_component)
-- where super vertices \((v \ge n)\) represent each biconnected component.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> -- 0---3---2
-- >>> -- +-1-+
-- >>> let n = 4
-- >>> let gr = Gr.build' n . Gr.swapDupe' $ VU.fromList [(0, 3), (0, 1), (1, 3), (3, 2)]
-- >>> let bct = blockCut n (gr `Gr.adj`)
-- >>> bct
-- Csr {nCsr = 6, mCsr = 5, startCsr = [0,0,0,0,0,2,5], adjCsr = [3,2,0,3,1], wCsr = [(),(),(),(),()]}
--
-- >>> V.generate (Gr.nCsr bct - n) ((bct `Gr.adj`) . (+ n))
-- [[3,2],[0,3,1]]
--
-- @since 1.1.1.0
{-# INLINEABLE blockCut #-}
blockCut ::
-- | \(n\): The number of vertices.
Int ->
-- | \(g\): Graph function, typically @'adj' gr@.
(Int -> VU.Vector Int) ->
-- | Graph that represents a block-cut tree, where super vertices \((v \ge n)\) represent each
-- biconnected component.
Csr ()
blockCut n gr = runST $ do
low <- VUM.replicate n (0 :: Int)
ord <- VUM.replicate n (0 :: Int)
st <- B.new @_ @Int n
used <- VUM.replicate n $ Bit False
edges <- B.new @_ @(Int, Int {- TODO: correct capacity? -}) (2 * n)
-- represents the bidirected component's index. also works as super vertex indices.
next <- VUM.replicate 1 n
let dfs k0 v p = do
B.pushBack st v
VGM.write used v $ Bit True
VGM.write low v k0
VGM.write ord v k0
snd
<$> VU.foldM'
( \(!child, !k) to -> do
if to == p
then pure (child, k)
else do
Bit b <- VGM.read used to
if not b
then do
let !child' = child + 1
s <- B.length st
k' <- dfs k to v
lowTo <- VGM.read low to
VGM.modify low (min lowTo) v
ordV <- VGM.read ord v
when ((p == -1 && child' > 1) || (p /= -1 && lowTo >= ordV)) $ do
nxt <- VGM.unsafeRead next 0
VGM.unsafeWrite next 0 (nxt + 1)
B.pushBack edges (nxt, v)
len <- B.length st
replicateM_ (len - s) $ do
back <- fromJust <$> B.popBack st
B.pushBack edges (nxt, back)
pure (child', k')
else do
ordTo <- VGM.read ord to
VGM.modify low (min ordTo) v
pure (child, k)
)
(0 :: Int, k0 + 1)
(gr v)
_ <-
VGM.ifoldM'
( \k v (Bit b) -> do
if b
then do
pure k
else do
k' <- dfs k v (-1)
st' <- B.unsafeFreeze st
nxt <- VGM.unsafeRead next 0
VGM.unsafeWrite next 0 (nxt + 1)
VU.forM_ st' $ \x -> do
B.pushBack edges (nxt, x)
B.clear st
pure k'
)
(0 :: Int)
used
n' <- VGM.unsafeRead next 0
Csr.build' n' <$> B.unsafeFreeze edges
-- | \(O(n + m)\) Returns [blocks (biconnected components)](https://en.wikipedia.org/wiki/Biconnected_component)
-- of the graph.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> -- 0---3---2
-- >>> -- +-1-+
-- >>> let n = 4
-- >>> let gr = Gr.build' n . Gr.swapDupe' $ VU.fromList [(0, 3), (0, 1), (1, 3), (3, 2)]
-- >>> Gr.blockCutComponents n (gr `Gr.adj`)
-- [[3,2],[0,3,1]]
--
-- @since 1.1.1.0
{-# INLINEABLE blockCutComponents #-}
blockCutComponents ::
-- | \(n\): The number of vertices.
Int ->
-- | \(g\): Graph function, typically @'adj' gr@.
(Int -> VU.Vector Int) ->
-- | Block-cut components
V.Vector (VU.Vector Int)
blockCutComponents n gr =
let bct = blockCut n gr
d = nCsr bct - n
in V.generate d ((bct `adj`) . (+ n))
-- -------------------------------------------------------------------------------------------------
-- Opinionated graph search functions
-- -------------------------------------------------------------------------------------------------
-- The implementations can be a bit simpler with `whenJustM`
-- | \(O(n + m)\) Opinionated breadth-first search function that returns a distance array.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 1 :: Int), (1, 2, 10)]
-- >>> let gr = Gr.build 4 es
-- >>> Gr.bfs 4 (Gr.adjW gr) (-1) (VU.singleton (0, 0))
-- [0,1,11,-1]
--
-- @since 1.2.4.0
{-# INLINE bfs #-}
bfs ::
forall i w.
(HasCallStack, Ix0 i, VU.Unbox i, VU.Unbox w, Num w, Eq w) =>
-- | Zero-based vertex boundary.
Bounds0 i ->
-- | Graph function that takes a vertex and returns adjacent vertices with edge weights, where
-- \(w > 0\).
(i -> VU.Vector (i, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Weighted source vertices.
VU.Vector (i, w) ->
-- | Distance array in one-dimensional index.
VU.Vector w
bfs !bnd0 !gr !undefW !sources =
let (!dist, !_) = bfsImpl False bnd0 gr undefW sources
in dist
-- | \(O(n + m)\) Opinionated breadth-first search function that returns a distance array and a
-- predecessor array.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 1 :: Int), (1, 2, 10)]
-- >>> let gr = Gr.build 4 es
-- >>> let (!dist, !prev) = Gr.trackingBfs 4 (Gr.adjW gr) (-1) (VU.singleton (0, 0))
-- >>> dist
-- [0,1,11,-1]
--
-- >>> Gr.constructPathFromRoot prev 2
-- [0,1,2]
--
-- @since 1.2.4.0
{-# INLINE trackingBfs #-}
trackingBfs ::
forall i w.
(HasCallStack, Ix0 i, VU.Unbox i, VU.Unbox w, Num w, Eq w) =>
-- | Zero-based vertex boundary.
Bounds0 i ->
-- | Graph function that takes a vertex and returns adjacent vertices with edge weights, where
-- \(w > 0\).
(i -> VU.Vector (i, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Weighted source vertices.
VU.Vector (i, w) ->
-- | A tuple of (Distance vector in one-dimensional index, Predecessor array (@-1@ represents none)).
(VU.Vector w, VU.Vector Int)
trackingBfs = bfsImpl True
{-# INLINEABLE bfsImpl #-}
bfsImpl ::
forall i w.
(HasCallStack, Ix0 i, VU.Unbox i, VU.Unbox w, Num w, Eq w) =>
Bool ->
Bounds0 i ->
(i -> VU.Vector (i, w)) ->
w ->
VU.Vector (i, w) ->
(VU.Vector w, VU.Vector Int)
bfsImpl !trackPrev !bnd0 !gr !undefW !sources
| VU.null sources && trackPrev = (VU.replicate nVerts undefW, VU.replicate nVerts (-1))
| VU.null sources = (VU.replicate nVerts undefW, VU.replicate 0 (-1))
| otherwise = runST $ do
dist <- VUM.replicate @_ @w nVerts undefW
prev <-
if trackPrev
then VUM.replicate @_ @Int nVerts (-1)
else VUM.replicate @_ @Int 0 (-1)
-- NOTE: We only need capacity of `n`, as first appearance of vertex is always with the
-- minimum distance.
queue <- Q.new nVerts
-- set source values
VU.forM_ sources $ \(!src, !w0) -> do
-- TODO: assert w1 <= w2
let !i = index0 bnd0 src
!lastD <- VGM.read dist i
-- Note that duplicate inputs are pruned here:
when (lastD == undefW) $ do
VGM.write dist i w0
Q.pushBack queue src
-- run BFS
fix $ \loop -> do
Q.popFront queue >>= \case
Nothing -> pure ()
Just v1 -> do
let !i1 = index0 bnd0 v1
!d1 <- VGM.read dist i1
VU.forM_ (gr v1) $ \(!v2, !dw) -> do
let !i2 = index0 bnd0 v2
!lastD <- VGM.read dist i2
when (lastD == undefW) $ do
VGM.write dist i2 $! d1 + dw
when trackPrev $ do
VGM.write prev i2 i1
Q.pushBack queue v2
loop
(,) <$> VU.unsafeFreeze dist <*> VU.unsafeFreeze prev
where
!nVerts = rangeSize0 bnd0
-- | \(O(n + m)\) Opinionated 01-BFS that returns a distance array.
--
-- Unreachable vertices are given distance of `-1`. Note that the third argument is the capacity of
-- deque, not distance of unreachable vertices.
--
-- ==== Constraints
-- - \(\mathrm{capacity} \ge 0\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (0, 2, 0), (2, 1, 1)]
-- >>> let gr = Gr.build 4 es
-- >>> let capacity = VU.length es
-- >>> Gr.bfs01 4 capacity (Gr.adjW gr) (VU.singleton (0, 0))
-- [0,1,0,-1]
--
-- @since 1.5.0.0
{-# INLINE bfs01 #-}
bfs01 ::
forall i.
(HasCallStack, Ix0 i, VU.Unbox i) =>
-- | Zero-based vertex boundary. It's \(n\) if the graph is one-dimensional.
Bounds0 i ->
-- | Capacity of deque, often the number of edges \(m\).
Int ->
-- | Graph function that takes the vertexand returns adjacent vertices with edge weights, where
-- \(w > 0\).
(i -> VU.Vector (i, Int)) ->
-- | Weighted source vertices.
VU.Vector (i, Int) ->
-- | Distance array in one-dimensional index. Unreachable vertices are assigned distance of @-1@.
VU.Vector Int
bfs01 !bnd0 !capacity !gr !sources =
let (!dist, !_) = bfs01Impl False bnd0 capacity gr sources
in dist
-- | \(O(n + m)\) Opinionated 01-BFS that returns a distance array and a predecessor array.
--
-- Unreachable vertices are given distance of `-1`. Note that the third argument is the capacity of
-- deque, not distance of unreachable vertices.
--
-- ==== Constraints
-- - \(\mathrm{capacity} \ge 0\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (0, 2, 0), (2, 1, 1)]
-- >>> let gr = Gr.build 4 es
-- >>> let capacity = VU.length es
-- >>> let (!dist, !prev) = Gr.trackingBfs01 4 capacity (Gr.adjW gr) (VU.singleton (0, 0))
-- >>> dist
-- [0,1,0,-1]
--
-- >>> Gr.constructPathFromRoot prev 1
-- [0,2,1]
--
-- @since 1.5.0.0
{-# INLINE trackingBfs01 #-}
trackingBfs01 ::
forall i.
(HasCallStack, Ix0 i, VU.Unbox i) =>
-- | Zero-based vertex boundary. It's \(n\) if the graph is one-dimensional.
Bounds0 i ->
-- | Capacity of deque, often the number of edges \(m\).
Int ->
-- | Graph function that takes the vertex and returns adjacent vertices with edge weights, where
-- \(w > 0\).
(i -> VU.Vector (i, Int)) ->
-- | Weighted source vertices.
VU.Vector (i, Int) ->
-- | A tuple of (distance array in one-dimensional index, predecessor array). Unreachable vertices
-- are assigned distance of @-1@.
(VU.Vector Int, VU.Vector Int)
trackingBfs01 = bfs01Impl True
{-# INLINEABLE bfs01Impl #-}
bfs01Impl ::
forall i.
(HasCallStack, Ix0 i, VU.Unbox i) =>
Bool ->
Bounds0 i ->
Int ->
(i -> VU.Vector (i, Int)) ->
VU.Vector (i, Int) ->
(VU.Vector Int, VU.Vector Int)
bfs01Impl !trackPrev !bnd0 !capacity !gr !sources
| VU.null sources && trackPrev = (VU.replicate nVerts (-1), VU.replicate nVerts (-1))
| VU.null sources = (VU.replicate nVerts (-1), VU.replicate 0 (-1))
| otherwise = runST $ do
dist <- VUM.replicate @_ @Int nVerts undef
prev <-
if trackPrev
then VUM.replicate @_ @Int nVerts (-1)
else VUM.replicate @_ @Int 0 (-1)
-- NOTE: Just like Dijkstra, we need capacity of `m`, as the first appearance of a vertex is not
-- always with minimum distance.
-- NOTE: Ensure minimum capacity of |sources| (too conservative?)
deque <- Q.newDeque @_ @(i, Int) $ capacity + VU.length sources
-- set source values
VU.forM_ sources $ \(!src, !w0) -> do
-- TODO: assert x1 <= w2
let !i = index0 bnd0 src
!lastD <- VGM.read dist i
-- Note that duplicate inputs are pruned here:
when (lastD == undef) $ do
VGM.write dist i w0
Q.pushBack deque (src, w0)
let step !vExt0 !w0 = do
let !i0 = index0 bnd0 vExt0
!wReserved0 <- VGM.read dist i0
when (w0 == wReserved0) $ do
VU.forM_ (gr vExt0) $ \(!vExt, !dw) -> do
let !w = w0 + dw
let !i = index0 bnd0 vExt
!wReserved <- VGM.read dist i
-- NOTE: Do pruning just like Dijkstra:
when (wReserved == undef || w < wReserved) $ do
VGM.write dist i w
when trackPrev $ do
VGM.write prev i i0
if dw == 0
then Q.pushFront deque (vExt, w)
else Q.pushBack deque (vExt, w)
fix $ \popLoop -> do
Q.popFront deque >>= \case
Nothing -> pure ()
Just (!vExt0, !w0) -> do
step vExt0 w0
popLoop
(,) <$> VU.unsafeFreeze dist <*> VU.unsafeFreeze prev
where
!undef = -1 :: Int
!nVerts = rangeSize0 bnd0
-- | \(O((n + m) \log n)\) Dijkstra's algorithm that returns a distance array.
--
-- ==== Constraints
-- - \(\mathrm{capacity} \ge 0\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (1, 2, 20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let gr = Gr.build 5 es
-- >>> let capacity = VU.length es
-- >>> Gr.dijkstra 5 capacity (Gr.adjW gr) (-1) (VU.singleton (0, 0))
-- [0,10,30,31,-1]
--
-- @since 1.5.0.0
{-# INLINE dijkstra #-}
dijkstra ::
forall i w.
(HasCallStack, Ix0 i, Ord i, VU.Unbox i, Num w, Ord w, VU.Unbox w) =>
-- | Zero-based vertex boundary. It's \(n\) if the graph is one-dimensional.
Bounds0 i ->
-- | Capacity of the heap, often the number of edges \(m\).
Int ->
-- | Graph function that takes a vertex and returns adjacent vertices with edge weights, where
-- \(w \ge 0\).
(i -> VU.Vector (i, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Source vertices with initial weights.
VU.Vector (i, w) ->
-- | Distance array in one-dimensional index.
VU.Vector w
dijkstra !bnd0 !capacity !gr !undefW !sources =
let (!dist, !_) = dijkstraImpl False bnd0 capacity gr undefW sources
in dist
-- | \(O((n + m) \log n)\) Dijkstra's algorithm that returns a distance array and a predecessor
-- array.
--
-- ==== Constraints
-- - \(\mathrm{capacity} \ge 0\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (1, 2, 20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let gr = Gr.build 5 es
-- >>> let capacity = VU.length es
-- >>> let (!dist, !prev) = Gr.trackingDijkstra 5 capacity (Gr.adjW gr) (-1) (VU.singleton (0, 0))
-- >>> dist
-- [0,10,30,31,-1]
--
-- >>> Gr.constructPathFromRoot prev 3
-- [0,1,2,3]
--
-- @since 1.5.0.0
{-# INLINE trackingDijkstra #-}
trackingDijkstra ::
forall i w.
(HasCallStack, Ix0 i, Ord i, VU.Unbox i, Num w, Ord w, VU.Unbox w) =>
-- | Zero-based vertex boundary. It's \(n\) if the graph is one-dimensional.
Bounds0 i ->
-- | Capacity of the heap, often the number of edges \(m\).
Int ->
-- | Graph function that takes a vertex and returns adjacent vertices with edge weights, where
-- \(w \ge 0\).
(i -> VU.Vector (i, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Source vertices with initial weights.
VU.Vector (i, w) ->
-- | A tuple of (distance array in one-dimensional index, predecessor array).
(VU.Vector w, VU.Vector Int)
trackingDijkstra = dijkstraImpl True
{-# INLINEABLE dijkstraImpl #-}
dijkstraImpl ::
forall i w.
(HasCallStack, Ix0 i, Ord i, VU.Unbox i, Num w, Ord w, VU.Unbox w) =>
Bool ->
Bounds0 i ->
Int ->
(i -> VU.Vector (i, w)) ->
w ->
VU.Vector (i, w) ->
(VU.Vector w, VU.Vector Int)
dijkstraImpl !trackPrev !bnd0 !capacity !gr !undefW !sources
| VU.null sources && trackPrev = (VU.replicate nVerts undefW, VU.replicate nVerts (-1))
| VU.null sources = (VU.replicate nVerts undefW, VU.replicate 0 (-1))
| otherwise = runST $ do
!dist <- VUM.replicate @_ @w nVerts undefW
-- REMARK: (w, i) for sort by width
-- REMARK: We need least capacity of |source|
!heap <- MH.new @_ @(w, i) $ capacity + VU.length sources
!prev <-
if trackPrev
then VUM.replicate @_ @Int nVerts (-1)
else VUM.replicate @_ @Int 0 (-1)
VU.forM_ sources $ \(!v, !w) -> do
let !i = index0 bnd0 v
VGM.write dist i w
MH.push heap (w, v)
fix $ \loop -> do
MH.pop heap >>= \case
Nothing -> pure ()
Just (!w1, !v1) -> do
let !i1 = index0 bnd0 v1
!wReserved <- VGM.read dist i1
when (wReserved == w1) $ do
VU.forM_ (gr v1) $ \(!v2, !dw2) -> do
let !i2 = index0 bnd0 v2
!w2 <- VGM.read dist i2
let !w2' = w1 + dw2
when (w2 == undefW || w2' < w2) $ do
VGM.write dist i2 w2'
when trackPrev $ do
VGM.write prev i2 i1
MH.push heap (w2', v2)
loop
(,) <$> VU.unsafeFreeze dist <*> VU.unsafeFreeze prev
where
!nVerts = rangeSize0 bnd0
-- -- | Option for `bellmanFord`.
-- data BellmanFordPolicy = QuitOnNegaitveLoop | ContinueOnNegaitveLoop
-- | \(O(nm)\) Bellman–Ford algorithm that returns a distance array, or `Nothing` on negative loop
-- detection. Vertices are one-dimensional.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let gr = Gr.build @Int 5 $ VU.fromList [(0, 1, 10), (1, 2, -20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let undefW = maxBound `div` 2
-- >>> Gr.bellmanFord 5 (Gr.adjW gr) undefW (VU.singleton (0, 0))
-- Just [0,10,-10,-9,4611686018427387903]
--
-- It returns `Nothing` on negative loop detection:
--
-- >>> let gr = Gr.build @Int 2 $ VU.fromList [(0, 1, -1), (1, 0, -1)]
-- >>> Gr.bellmanFord 5 (Gr.adjW gr) undefW (VU.singleton (0, 0))
-- Nothing
--
-- @since 1.2.4.0
{-# INLINE bellmanFord #-}
bellmanFord ::
forall w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Graph function. Edges weights can be negative.
(Int -> VU.Vector (Int, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Source vertex with initial distances.
VU.Vector (Int, w) ->
-- | Distance array in one-dimensional index.
Maybe (VU.Vector w)
bellmanFord {- !policy -} !nVerts !gr !undefW source = do
(!dist, !_) <- bellmanFordImpl False nVerts gr undefW source
pure dist
-- | \(O(nm)\) Bellman–Ford algorithm that returns a distance array and a predecessor array, or
-- `Nothing` on negative loop detection. Vertices are one-dimensional.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let gr = Gr.build @Int 5 $ VU.fromList [(0, 1, 10), (1, 2, -20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let undefW = maxBound `div` 2
-- >>> let Just (!dist, !prev) = Gr.trackingBellmanFord 5 (Gr.adjW gr) undefW (VU.singleton (0, 0))
-- >>> dist
-- [0,10,-10,-9,4611686018427387903]
--
-- >>> Gr.constructPathFromRoot prev 3
-- [0,1,2,3]
--
-- It returns `Nothing` on negative loop detection:
--
-- >>> let gr = Gr.build @Int 2 $ VU.fromList [(0, 1, -1), (1, 0, -1)]
-- >>> Gr.trackingBellmanFord 5 (Gr.adjW gr) undefW (VU.singleton (0, 0))
-- Nothing
--
-- @since 1.2.4.0
{-# INLINE trackingBellmanFord #-}
trackingBellmanFord ::
forall w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Graph function. The weight can be negative.
(Int -> VU.Vector (Int, w)) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Source vertex with initial distances.
VU.Vector (Int, w) ->
-- | A tuple of (distance array, predecessor array).
Maybe (VU.Vector w, VU.Vector Int)
trackingBellmanFord {- !policy -} = bellmanFordImpl True
{-# INLINEABLE bellmanFordImpl #-}
bellmanFordImpl ::
forall w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
Bool ->
Int ->
(Int -> VU.Vector (Int, w)) ->
w ->
VU.Vector (Int, w) ->
Maybe (VU.Vector w, VU.Vector Int)
bellmanFordImpl {- !policy -} !trackPrev !nVerts !gr !undefW !sources = runST $ do
!dist <- VUM.replicate @_ @w nVerts undefW
!prev <-
if trackPrev
then VUM.replicate @_ @Int nVerts (-1)
else VUM.replicate @_ @Int 0 (-1)
VU.forM_ sources $ \(!v, !w) -> do
!lastD <- VGM.read dist v
-- Note that duplicate inputs are pruned here:
when (lastD == undefW) $ do
VGM.write dist v w
updated <- VUM.replicate 1 False
-- look around adjaenct vertices
let update v1 = do
d1 <- VGM.read dist v1
when (d1 /= undefW) $ do
VU.forM_ (gr v1) $ \(!v2, !dw) -> do
d2 <- VGM.read dist v2
let !d2' = d1 + dw
when (d2 == undefW || d2' < d2) $ do
VGM.write dist v2 d2'
when trackPrev $ do
VGM.write prev v2 v1
-- NOTE: we should actually instantly stop if nLoop == nVerts + 1, but
-- here we're preferring simple code. Be warned that we're not correctly handling
-- the distance array on negative loop.
VGM.write updated 0 True
let runLoop nLoop
| nLoop >= nVerts + 1 = do
-- We detected update in the (n + 1)-th loop, so we found negative loop
pure Nothing
| otherwise = do
for_ [0 .. nVerts - 1] update
b <- VGM.exchange updated 0 False
if b
then runLoop (nLoop + 1)
else Just <$> ((,) <$> VU.unsafeFreeze dist <*> VU.unsafeFreeze prev)
runLoop 0
-- | \(O(n^3)\) Floyd–Warshall algorithm that returns a distance matrix \(m\).
--
-- - The distance matrix should be accessed as @m VG.! (`index0` (n, n) (from, to))@,
-- - There's a negative loop if there's any vertex \(v\) where @m VU.! (`index0` (n, n) (v, v))@
-- is negative.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (1, 2, -20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let undefW = maxBound `div` 2
-- >>> let dist = Gr.floydWarshall 5 es undefW
-- >>> dist VG.! (5 * 0 + 3) -- from `0` to `3`
-- -9
--
-- >>> dist VG.! (5 * 1 + 3) -- from `0` to `3`
-- -19
--
-- Negative loop can be detected by testing if there's any vertex \(v\) where
-- @m VU.! (`index0` (n, n) (v, v))@:
--
-- >>> any (\v -> dist VG.! (5 * v + v) < 0) [0 .. 5 - 1]
-- False
--
-- >>> let es = VU.fromList [(0, 1, -1 :: Int), (1, 0, -1)]
-- >>> let dist = Gr.floydWarshall 3 es undefW
-- >>> any (\v -> dist VG.! (3 * v + v) < 0) [0 .. 3 - 1]
-- True
--
-- @since 1.2.4.0
{-# INLINE floydWarshall #-}
floydWarshall ::
forall w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Weighted edges.
VU.Vector (Int, Int, w) ->
-- | Distance assignment \(d_0 \gt 0\) for unreachable vertices. It should be @maxBound \`div` 2@
-- for `Int`.
w ->
-- | Distance array in one-dimensional index.
VU.Vector w
floydWarshall !nVerts !edges !undefW = VU.create $ do
(!dist, !_) <- newFloydWarshallST False nVerts edges undefW
pure dist
-- | \(O(n^3)\) Floyd–Warshall algorithm that returns a distance matrix \(m\) and predecessor
-- matrix \(p\).
--
-- - The distance matrix should be accessed as @m VG.! (`index0` (n, n) (from, to))@,
-- - The predecessor matrix should be accessed as @m VG.! (`index0` (n, n) (root, v))@
-- - There's a negative loop if there's any vertex \(v\) where @m VU.! (`index0` (n, n) (v, v))@
-- is negative.
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 10 :: Int), (1, 2, -20), (2, 3, 1), (1, 3, 40), (4, 3, 0)]
-- >>> let undefW = maxBound `div` 2
-- >>> let (!dist, !prev) = Gr.trackingFloydWarshall 5 es undefW
-- >>> dist VG.! (5 * 0 + 3) -- from `0` to `3`
-- -9
--
-- >>> Gr.constructPathFromRootMat prev 0 3 -- from `0` to `3`
-- [0,1,2,3]
--
-- >>> dist VG.! (5 * 1 + 3) -- from `0` to `3`
-- -19
--
-- >>> Gr.constructPathFromRootMat prev 1 3 -- from `1` to `3`
-- [1,2,3]
--
-- Negative loop can be detected by testing if there's any vertex \(v\) where
-- @m VU.! (`index0` (n, n) (v, v))@:
--
-- >>> any (\v -> dist VG.! (5 * v + v) < 0) [0 .. 5 - 1]
-- False
--
-- >>> let es = VU.fromList [(0, 1, -1 :: Int), (1, 0, -1)]
-- >>> let (!dist, !_) = Gr.trackingFloydWarshall 3 es undefW
-- >>> any (\v -> dist VG.! (3 * v + v) < 0) [0 .. 3 - 1]
-- True
--
-- @since 1.2.4.0
{-# INLINE trackingFloydWarshall #-}
trackingFloydWarshall ::
forall w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Weighted edges.
VU.Vector (Int, Int, w) ->
-- | Distance assignment \(d_0 \gt 0\) for unreachable vertices. It should be @maxBound \`div` 2@
-- for `Int`.
w ->
-- | Distance array in one-dimensional index.
(VU.Vector w, VU.Vector Int)
trackingFloydWarshall !nVerts !edges !undefW = runST $ do
(!dist, !prev) <- newFloydWarshallST True nVerts edges undefW
(,) <$> VU.unsafeFreeze dist <*> VU.unsafeFreeze prev
-- | \(O(n^3)\) Floyd–Warshall algorithm that returns a distance matrix \(m\).
--
-- - The distance matrix should be accessed as @m VG.! (`index0` (n, n) (from, to))@,
-- - There's a negative loop if there's any vertex \(v\) where @m VU.! (`index0` (n, n) (v, v))@
-- is negative.
--
-- ==== Constraints
-- - \(n \ge 1\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 1 :: Int), (1, 2, 1), (2, 3, 1), (1, 3, 4)]
-- >>> let undefW = -1
-- >>> dist <- Gr.newFloydWarshall 4 es undefW
-- >>> VGM.read dist (4 * 0 + 3)
-- 3
--
-- >>> updateEdgeFloydWarshall dist 4 undefW 1 3 (-2)
-- >>> VGM.read dist (4 * 0 + 3)
-- -1
--
-- @since 1.2.4.0
{-# INLINE newFloydWarshall #-}
newFloydWarshall ::
forall m w.
(HasCallStack, PrimMonad m, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Weighted edges.
VU.Vector (Int, Int, w) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Distance array in one-dimensional index.
m (VUM.MVector (PrimState m) w)
newFloydWarshall !nVerts !edges !undefW = stToPrim $ do
(!dist, !_) <- newFloydWarshallST False nVerts edges undefW
pure dist
-- | \(O(n^3)\) Floyd–Warshall algorithm that returns a distance matrix \(m\) and predecessor
-- matrix.
--
-- - The distance matrix should be accessed as @m VG.! (`index0` (n, n) (from, to))@,
-- - The predecessor matrix should be accessed as @m VG.! (`index0` (n, n) (root, v))@
-- - There's a negative loop if there's any vertex \(v\) where @m VU.! (`index0` (n, n) (v, v))@
-- is negative.
--
-- ==== Constraints
-- - \(n \ge 1\)
--
-- ==== __Example__
-- >>> import AtCoder.Extra.Graph qualified as Gr
-- >>> import Data.Vector.Unboxed qualified as VU
-- >>> let es = VU.fromList [(0, 1, 1 :: Int), (1, 2, 1), (2, 3, 1), (1, 3, 4)]
-- >>> let undefW = -1
-- >>> (!dist, !prev) <- Gr.newTrackingFloydWarshall 4 es undefW
-- >>> VGM.read dist (4 * 0 + 3)
-- 3
--
-- >>> constructPathFromRootMatM prev 0 3
-- [0,1,2,3]
--
-- >>> updateEdgeTrackingFloydWarshall dist prev 4 undefW 1 3 (-2)
-- >>> VGM.read dist (4 * 0 + 3)
-- -1
--
-- >>> constructPathFromRootMatM prev 0 3
-- [0,1,3]
--
-- @since 1.2.4.0
{-# INLINE newTrackingFloydWarshall #-}
newTrackingFloydWarshall ::
forall m w.
(HasCallStack, PrimMonad m, Num w, Ord w, VU.Unbox w) =>
-- | The number of vertices.
Int ->
-- | Weighted edges.
VU.Vector (Int, Int, w) ->
-- | Distance assignment for unreachable vertices.
w ->
-- | Distance array in one-dimensional index.
m (VUM.MVector (PrimState m) w, VUM.MVector (PrimState m) Int)
newTrackingFloydWarshall !nVerts !edges !undefW = stToPrim $ do
newFloydWarshallST True nVerts edges undefW
{-# INLINEABLE newFloydWarshallST #-}
newFloydWarshallST ::
forall s w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
Bool ->
Int ->
VU.Vector (Int, Int, w) ->
w ->
ST s (VUM.MVector s w, VUM.MVector s Int)
newFloydWarshallST !trackPrev !nVerts !edges !undefW = do
!dist <- VUM.replicate @_ @w (nVerts * nVerts) undefW
!prev <-
if trackPrev
then VUM.replicate @_ @Int (nVerts * nVerts) (-1)
else VUM.replicate @_ @Int 0 (-1)
-- diagonals (self to self)
for_ [0 .. nVerts - 1] $ \v -> do
VGM.write dist (idx v v) 0
-- initial walks
VU.forM_ edges $ \(!v1, !v2, !dw) -> do
let !i = idx v1 v2
wOld <- VGM.read dist i
-- REMARK: We're handling multiple edges here:
when (wOld == undefW || dw < wOld) $ do
VGM.write dist i dw
when trackPrev $ do
VGM.write prev i v1
-- N times update
for_ [0 .. nVerts - 1] $ \via -> do
-- update
for_ [0 .. nVerts - 1] $ \from -> do
for_ [0 .. nVerts - 1] $ \to -> do
let !iFromTo = idx from to
!w1 <- VGM.read dist iFromTo
!w2 <- do
!d1 <- VGM.read dist $! idx from via
!d2 <- VGM.read dist $! idx via to
pure $! if d1 == undefW || d2 == undefW then undefW else d1 + d2
when (w2 /= undefW && (w1 == undefW || w2 < w1)) $ do
VGM.write dist iFromTo w2
when trackPrev $ do
VGM.write prev iFromTo =<< VGM.read prev (idx via to)
pure (dist, prev)
where
idx !from !to = nVerts * from + to
-- | \(O(n^2)\) Updates distance matrix of Floyd–Warshall on edge weight change or new edge addition.
--
-- ==== Constraints
-- - \(n \ge 1\)
--
-- @since 1.2.4.0
{-# INLINE updateEdgeFloydWarshall #-}
updateEdgeFloydWarshall ::
forall m w.
(HasCallStack, PrimMonad m, Num w, Ord w, VU.Unbox w) =>
-- | Distance matrix.
VUM.MVector (PrimState m) w ->
-- | The number of vertices.
Int ->
-- | Distance assignment \(d_0 \gt 0\) for unreachable vertices. It should be @maxBound `div` 2@
-- for `Int`.
w ->
-- | Edge information: @from@ vertex.
Int ->
-- | Edge information: @to@ vertex.
Int ->
-- | Edge information: @weight@ vertex.
w ->
-- | Distance array in one-dimensional index.
m ()
updateEdgeFloydWarshall mat nVerts undefW a b w = do
prev <- VUM.replicate @_ @Int 0 (-1 :: Int)
stToPrim $ updateEdgeFloydWarshallST False mat prev nVerts undefW a b w
-- | \(O(n^2)\) Updates distance matrix of Floyd–Warshall on edge weight chaneg or new edge addition.
--
-- ==== Constraints
-- - \(n \ge 1\)
--
-- @since 1.2.4.0
{-# INLINE updateEdgeTrackingFloydWarshall #-}
updateEdgeTrackingFloydWarshall ::
forall m w.
(HasCallStack, PrimMonad m, Num w, Ord w, VU.Unbox w) =>
-- | Distance matrix.
VUM.MVector (PrimState m) w ->
-- | Predecessor matrix.
VUM.MVector (PrimState m) Int ->
-- | The number of vertices.
Int ->
-- | Distance assignment \(d_0 \gt 0\) for unreachable vertices. It should be @maxBound `div` 2@
-- for `Int`.
w ->
-- | Edge information: @from@ vertex.
Int ->
-- | Edge information: @to@ vertex.
Int ->
-- | Edge information: @weight@ vertex.
w ->
-- | Distance array in one-dimensional index.
m ()
updateEdgeTrackingFloydWarshall mat prev nVerts undefW a b w = do
stToPrim $ updateEdgeFloydWarshallST True mat prev nVerts undefW a b w
-- O(2) update floyd warshall on edge weight decreasement or edge addition
-- https://www.slideshare.net/chokudai/arc035 - C
{-# INLINEABLE updateEdgeFloydWarshallST #-}
updateEdgeFloydWarshallST ::
forall s w.
(HasCallStack, Num w, Ord w, VU.Unbox w) =>
Bool ->
VUM.MVector s w ->
VUM.MVector s Int ->
Int ->
w ->
Int ->
Int ->
w ->
ST s ()
updateEdgeFloydWarshallST trackPrev mat prev nVerts undefW a b dw = do
wOld0 <- VGM.read mat $! idx a b
when (wOld0 == undefW || dw < wOld0) $ do
VGM.write mat (idx a b) dw
when trackPrev $ do
VGM.write prev (idx a b) a
for_ [0 .. nVerts - 1] $ \from -> do
for_ [0 .. nVerts - 1] $ \to -> do
wOld <- VGM.read mat $! idx from to
w' <- do
ia <- VGM.read mat $! idx from a
bj <- VGM.read mat $! idx b to
let w1
| ia == undefW || bj == undefW = undefW
| otherwise = ia + dw + bj
ib <- VGM.read mat $! idx from b
aj <- VGM.read mat $! idx a to
let w2
| ib == undefW || aj == undefW = undefW
| otherwise = ib + dw + aj
pure $!
if
| w1 == undefW -> w2
| w2 == undefW -> w1
| otherwise -> min w1 w2
when (wOld /= undefW && w' < wOld) $ do
VGM.write mat (idx from to) w'
when trackPrev $ do
VGM.write prev (idx from to) =<< VGM.read prev (idx b to)
VGM.write prev (idx from b) a
where
idx !from !to = nVerts * from + to
-- | \(O(n)\) Given a predecessor array, reconstructs a path from the root to a vertex.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @sink@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINE constructPathFromRoot #-}
constructPathFromRoot :: (HasCallStack) => VU.Vector Int -> Int -> VU.Vector Int
constructPathFromRoot parents = VU.reverse . constructPathToRoot parents
-- | \(O(n)\) Given a predecessor array, reconstructs a path from a vertex to the root.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @sink@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINEABLE constructPathToRoot #-}
constructPathToRoot :: (HasCallStack) => VU.Vector Int -> Int -> VU.Vector Int
constructPathToRoot parents = VU.unfoldr f
where
f (-1) = Nothing
f v = Just (v, parents VG.! v)
-- | \(O(n)\) Given a NxN predecessor matrix (created with `trackingFloydWarshall`), reconstructs a
-- path from the root to a sink vertex.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @sink@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINE constructPathFromRootMat #-}
constructPathFromRootMat ::
(HasCallStack) =>
-- | Predecessor matrix.
VU.Vector Int ->
-- | Source vertex.
Int ->
-- | Sink vertex.
Int ->
-- | Path.
VU.Vector Int
constructPathFromRootMat parents source = VU.reverse . constructPathToRootMat parents source
-- | \(O(n)\) Given a NxN predecessor matrix(created with `trackingFloydWarshall`), reconstructs a
-- path from a vertex to the root.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @sink@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINEABLE constructPathToRootMat #-}
constructPathToRootMat ::
(HasCallStack) =>
-- | Predecessor matrix.
VU.Vector Int ->
-- | Source vertex.
Int ->
-- | Sink vertex.
Int ->
-- | Path.
VU.Vector Int
constructPathToRootMat parents source sink =
let parents' = VU.take n $ VU.drop (n * source) parents
in constructPathToRoot parents' sink
where
-- Assuming `n < 2^32`, it should always be correct:
-- https://zenn.dev/mod_poppo/articles/atcoder-beginner-contest-284-d#%E8%A7%A3%E6%B3%953%EF%BC%9Asqrt%E3%81%A8round%E3%82%92%E4%BD%BF%E3%81%86
n :: Int = round . sqrt $ (fromIntegral (VU.length parents) :: Double)
-- | \(O(n)\) Given a NxN predecessor matrix (created with `newTrackingFloydWarshall`), reconstructs
-- a path from the root to a sink vertex.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @nd@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINE constructPathFromRootMatM #-}
constructPathFromRootMatM ::
(HasCallStack, PrimMonad m) =>
-- | Predecessor matrix.
VUM.MVector (PrimState m) Int ->
-- | Source vertex.
Int ->
-- | Sink vertex.
Int ->
-- | Path.
m (VU.Vector Int)
constructPathFromRootMatM parents source = (VU.reverse <$>) . constructPathToRootMatM parents source
-- | \(O(n)\) Given a NxN predecessor matrix (created with `newTrackingFloydWarshall`),
-- reconstructs a path from a vertex to the root.
--
-- ==== Constraints
-- - The path must not make a cycle, otherwise this function loops forever.
-- - There must be a path from the root to the @sink@ vertex, otherwise the returned path is not
-- connected to the root.
--
-- @since 1.2.4.0
{-# INLINEABLE constructPathToRootMatM #-}
constructPathToRootMatM ::
(HasCallStack, PrimMonad m) =>
-- | Predecessor matrix.
VUM.MVector (PrimState m) Int ->
-- | Source vertex.
Int ->
-- | Sink vertex.
Int ->
-- | Path.
m (VU.Vector Int)
constructPathToRootMatM parents source sink = stToPrim $ do
parents' <- VU.unsafeFreeze parents
pure $ constructPathToRootMat parents' source sink