%
% (c) The University of Glasgow 2006
%
\begin{code}
module Digraph(
Graph, graphFromVerticesAndAdjacency, graphFromEdgedVertices,
SCC(..), Node, flattenSCC, flattenSCCs,
stronglyConnCompG, stronglyConnCompFromG,
topologicalSortG, dfsTopSortG,
verticesG, edgesG, hasVertexG,
reachableG, transposeG,
outdegreeG, indegreeG,
vertexGroupsG, emptyG,
componentsG,
findCycle,
stronglyConnCompFromEdgedVertices, stronglyConnCompFromEdgedVerticesR,
tabulate, preArr,
components, undirected,
back, cross, forward,
path,
bcc, do_label, bicomps, collect
) where
#include "HsVersions.h"
import Util ( minWith, count )
import Outputable
import Maybes ( expectJust )
import MonadUtils ( allM )
import Control.Monad ( filterM, liftM, liftM2 )
import Control.Monad.ST
import Data.Maybe
import Data.Array
import Data.List hiding (transpose)
import Data.Ord
import Data.Array.ST
import qualified Data.Map as Map
import qualified Data.Set as Set
\end{code}
%************************************************************************
%* *
%* Graphs and Graph Construction
%* *
%************************************************************************
Note [Nodes, keys, vertices]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* A 'node' is a big blob of client-stuff
* Each 'node' has a unique (client) 'key', but the latter
is in Ord and has fast comparison
* Digraph then maps each 'key' to a Vertex (Int) which is
arranged densely in 0.n
\begin{code}
data Graph node = Graph {
gr_int_graph :: IntGraph,
gr_vertex_to_node :: Vertex -> node,
gr_node_to_vertex :: node -> Maybe Vertex
}
data Edge node = Edge node node
type Node key payload = (payload, key, [key])
emptyGraph :: Graph a
emptyGraph = Graph (array (1, 0) []) (error "emptyGraph") (const Nothing)
graphFromVerticesAndAdjacency
:: Ord key
=> [(node, key)]
-> [(key, key)]
-> Graph (node, key)
graphFromVerticesAndAdjacency [] _ = emptyGraph
graphFromVerticesAndAdjacency vertices edges = Graph graph vertex_node (key_vertex . key_extractor)
where key_extractor = snd
(bounds, vertex_node, key_vertex, _) = reduceNodesIntoVertices vertices key_extractor
key_vertex_pair (a, b) = (expectJust "graphFromVerticesAndAdjacency" $ key_vertex a,
expectJust "graphFromVerticesAndAdjacency" $ key_vertex b)
reduced_edges = map key_vertex_pair edges
graph = buildG bounds reduced_edges
graphFromEdgedVertices
:: Ord key
=> [Node key payload]
-> Graph (Node key payload)
graphFromEdgedVertices [] = emptyGraph
graphFromEdgedVertices edged_vertices = Graph graph vertex_fn (key_vertex . key_extractor)
where key_extractor (_, k, _) = k
(bounds, vertex_fn, key_vertex, numbered_nodes) = reduceNodesIntoVertices edged_vertices key_extractor
graph = array bounds [(v, mapMaybe key_vertex ks) | (v, (_, _, ks)) <- numbered_nodes]
reduceNodesIntoVertices
:: Ord key
=> [node]
-> (node -> key)
-> (Bounds, Vertex -> node, key -> Maybe Vertex, [(Int, node)])
reduceNodesIntoVertices nodes key_extractor = (bounds, (!) vertex_map, key_vertex, numbered_nodes)
where
max_v = length nodes 1
bounds = (0, max_v) :: (Vertex, Vertex)
sorted_nodes = sortBy (comparing key_extractor) nodes
numbered_nodes = zipWith (,) [0..] sorted_nodes
key_map = array bounds [(i, key_extractor node) | (i, node) <- numbered_nodes]
vertex_map = array bounds numbered_nodes
key_vertex k = find 0 max_v
where
find a b | a > b = Nothing
| otherwise = let mid = (a + b) `div` 2
in case compare k (key_map ! mid) of
LT -> find a (mid 1)
EQ -> Just mid
GT -> find (mid + 1) b
\end{code}
%************************************************************************
%* *
%* SCC
%* *
%************************************************************************
\begin{code}
type WorkItem key payload
= (Node key payload,
[payload])
findCycle :: forall payload key. Ord key
=> [Node key payload]
-> Maybe [payload]
findCycle graph
= go Set.empty (new_work root_deps []) []
where
env :: Map.Map key (Node key payload)
env = Map.fromList [ (key, node) | node@(_, key, _) <- graph ]
root :: Node key payload
root = fst (minWith snd [ (node, count (`Map.member` env) deps)
| node@(_,_,deps) <- graph ])
(root_payload,root_key,root_deps) = root
go :: Set.Set key
-> [WorkItem key payload]
-> [WorkItem key payload]
-> Maybe [payload]
go _ [] [] = Nothing
go visited [] qs = go visited qs []
go visited (((payload,key,deps), path) : ps) qs
| key == root_key = Just (root_payload : reverse path)
| key `Set.member` visited = go visited ps qs
| key `Map.notMember` env = go visited ps qs
| otherwise = go (Set.insert key visited)
ps (new_qs ++ qs)
where
new_qs = new_work deps (payload : path)
new_work :: [key] -> [payload] -> [WorkItem key payload]
new_work deps path = [ (n, path) | Just n <- map (`Map.lookup` env) deps ]
\end{code}
%************************************************************************
%* *
%* SCC
%* *
%************************************************************************
\begin{code}
data SCC vertex = AcyclicSCC vertex
| CyclicSCC [vertex]
instance Functor SCC where
fmap f (AcyclicSCC v) = AcyclicSCC (f v)
fmap f (CyclicSCC vs) = CyclicSCC (fmap f vs)
flattenSCCs :: [SCC a] -> [a]
flattenSCCs = concatMap flattenSCC
flattenSCC :: SCC a -> [a]
flattenSCC (AcyclicSCC v) = [v]
flattenSCC (CyclicSCC vs) = vs
instance Outputable a => Outputable (SCC a) where
ppr (AcyclicSCC v) = text "NONREC" $$ (nest 3 (ppr v))
ppr (CyclicSCC vs) = text "REC" $$ (nest 3 (vcat (map ppr vs)))
\end{code}
%************************************************************************
%* *
%* Strongly Connected Component wrappers for Graph
%* *
%************************************************************************
Note: the components are returned topologically sorted: later components
depend on earlier ones, but not vice versa i.e. later components only have
edges going from them to earlier ones.
\begin{code}
stronglyConnCompG :: Graph node -> [SCC node]
stronglyConnCompG graph = decodeSccs graph forest
where forest = scc (gr_int_graph graph)
stronglyConnCompFromG :: Graph node -> [node] -> [SCC node]
stronglyConnCompFromG graph roots = decodeSccs graph forest
where forest = sccFrom (gr_int_graph graph) vs
vs = [ v | Just v <- map (gr_node_to_vertex graph) roots ]
decodeSccs :: Graph node -> Forest Vertex -> [SCC node]
decodeSccs Graph { gr_int_graph = graph, gr_vertex_to_node = vertex_fn } forest
= map decode forest
where
decode (Node v []) | mentions_itself v = CyclicSCC [vertex_fn v]
| otherwise = AcyclicSCC (vertex_fn v)
decode other = CyclicSCC (dec other [])
where dec (Node v ts) vs = vertex_fn v : foldr dec vs ts
mentions_itself v = v `elem` (graph ! v)
stronglyConnCompFromEdgedVertices
:: Ord key
=> [Node key payload]
-> [SCC payload]
stronglyConnCompFromEdgedVertices
= map (fmap get_node) . stronglyConnCompFromEdgedVerticesR
where get_node (n, _, _) = n
stronglyConnCompFromEdgedVerticesR
:: Ord key
=> [Node key payload]
-> [SCC (Node key payload)]
stronglyConnCompFromEdgedVerticesR = stronglyConnCompG . graphFromEdgedVertices
\end{code}
%************************************************************************
%* *
%* Misc wrappers for Graph
%* *
%************************************************************************
\begin{code}
topologicalSortG :: Graph node -> [node]
topologicalSortG graph = map (gr_vertex_to_node graph) result
where result = topSort (gr_int_graph graph)
dfsTopSortG :: Graph node -> [[node]]
dfsTopSortG graph =
map (map (gr_vertex_to_node graph) . flattenTree) $ dfs g (topSort g)
where
g = gr_int_graph graph
reachableG :: Graph node -> node -> [node]
reachableG graph from = map (gr_vertex_to_node graph) result
where from_vertex = expectJust "reachableG" (gr_node_to_vertex graph from)
result = reachable (gr_int_graph graph) from_vertex
hasVertexG :: Graph node -> node -> Bool
hasVertexG graph node = isJust $ gr_node_to_vertex graph node
verticesG :: Graph node -> [node]
verticesG graph = map (gr_vertex_to_node graph) $ vertices (gr_int_graph graph)
edgesG :: Graph node -> [Edge node]
edgesG graph = map (\(v1, v2) -> Edge (v2n v1) (v2n v2)) $ edges (gr_int_graph graph)
where v2n = gr_vertex_to_node graph
transposeG :: Graph node -> Graph node
transposeG graph = Graph (transpose (gr_int_graph graph)) (gr_vertex_to_node graph) (gr_node_to_vertex graph)
outdegreeG :: Graph node -> node -> Maybe Int
outdegreeG = degreeG outdegree
indegreeG :: Graph node -> node -> Maybe Int
indegreeG = degreeG indegree
degreeG :: (IntGraph -> Table Int) -> Graph node -> node -> Maybe Int
degreeG degree graph node = let table = degree (gr_int_graph graph)
in fmap ((!) table) $ gr_node_to_vertex graph node
vertexGroupsG :: Graph node -> [[node]]
vertexGroupsG graph = map (map (gr_vertex_to_node graph)) result
where result = vertexGroups (gr_int_graph graph)
emptyG :: Graph node -> Bool
emptyG g = graphEmpty (gr_int_graph g)
componentsG :: Graph node -> [[node]]
componentsG graph = map (map (gr_vertex_to_node graph) . flattenTree) $ components (gr_int_graph graph)
\end{code}
%************************************************************************
%* *
%* Showing Graphs
%* *
%************************************************************************
\begin{code}
instance Outputable node => Outputable (Graph node) where
ppr graph = vcat [
hang (text "Vertices:") 2 (vcat (map ppr $ verticesG graph)),
hang (text "Edges:") 2 (vcat (map ppr $ edgesG graph))
]
instance Outputable node => Outputable (Edge node) where
ppr (Edge from to) = ppr from <+> text "->" <+> ppr to
\end{code}
%************************************************************************
%* *
%* IntGraphs
%* *
%************************************************************************
\begin{code}
type Vertex = Int
type Table a = Array Vertex a
type IntGraph = Table [Vertex]
type Bounds = (Vertex, Vertex)
type IntEdge = (Vertex, Vertex)
\end{code}
\begin{code}
vertices :: IntGraph -> [Vertex]
vertices = indices
edges :: IntGraph -> [IntEdge]
edges g = [ (v, w) | v <- vertices g, w <- g!v ]
mapT :: (Vertex -> a -> b) -> Table a -> Table b
mapT f t = array (bounds t) [ (v, f v (t ! v)) | v <- indices t ]
buildG :: Bounds -> [IntEdge] -> IntGraph
buildG bounds edges = accumArray (flip (:)) [] bounds edges
transpose :: IntGraph -> IntGraph
transpose g = buildG (bounds g) (reverseE g)
reverseE :: IntGraph -> [IntEdge]
reverseE g = [ (w, v) | (v, w) <- edges g ]
outdegree :: IntGraph -> Table Int
outdegree = mapT numEdges
where numEdges _ ws = length ws
indegree :: IntGraph -> Table Int
indegree = outdegree . transpose
graphEmpty :: IntGraph -> Bool
graphEmpty g = lo > hi
where (lo, hi) = bounds g
\end{code}
%************************************************************************
%* *
%* Trees and forests
%* *
%************************************************************************
\begin{code}
data Tree a = Node a (Forest a)
type Forest a = [Tree a]
mapTree :: (a -> b) -> (Tree a -> Tree b)
mapTree f (Node x ts) = Node (f x) (map (mapTree f) ts)
flattenTree :: Tree a -> [a]
flattenTree (Node x ts) = x : concatMap flattenTree ts
\end{code}
\begin{code}
instance Show a => Show (Tree a) where
showsPrec _ t s = showTree t ++ s
showTree :: Show a => Tree a -> String
showTree = drawTree . mapTree show
drawTree :: Tree String -> String
drawTree = unlines . draw
draw :: Tree String -> [String]
draw (Node x ts) = grp this (space (length this)) (stLoop ts)
where this = s1 ++ x ++ " "
space n = replicate n ' '
stLoop [] = [""]
stLoop [t] = grp s2 " " (draw t)
stLoop (t:ts) = grp s3 s4 (draw t) ++ [s4] ++ rsLoop ts
rsLoop [] = []
rsLoop [t] = grp s5 " " (draw t)
rsLoop (t:ts) = grp s6 s4 (draw t) ++ [s4] ++ rsLoop ts
grp fst rst = zipWith (++) (fst:repeat rst)
[s1,s2,s3,s4,s5,s6] = ["- ", "--", "-+", " |", " `", " +"]
\end{code}
%************************************************************************
%* *
%* Depth first search
%* *
%************************************************************************
\begin{code}
type Set s = STArray s Vertex Bool
mkEmpty :: Bounds -> ST s (Set s)
mkEmpty bnds = newArray bnds False
contains :: Set s -> Vertex -> ST s Bool
contains m v = readArray m v
include :: Set s -> Vertex -> ST s ()
include m v = writeArray m v True
\end{code}
\begin{code}
dff :: IntGraph -> Forest Vertex
dff g = dfs g (vertices g)
dfs :: IntGraph -> [Vertex] -> Forest Vertex
dfs g vs = prune (bounds g) (map (generate g) vs)
generate :: IntGraph -> Vertex -> Tree Vertex
generate g v = Node v (map (generate g) (g!v))
prune :: Bounds -> Forest Vertex -> Forest Vertex
prune bnds ts = runST (mkEmpty bnds >>= \m ->
chop m ts)
chop :: Set s -> Forest Vertex -> ST s (Forest Vertex)
chop _ [] = return []
chop m (Node v ts : us)
= contains m v >>= \visited ->
if visited then
chop m us
else
include m v >>= \_ ->
chop m ts >>= \as ->
chop m us >>= \bs ->
return (Node v as : bs)
\end{code}
%************************************************************************
%* *
%* Algorithms
%* *
%************************************************************************
------------------------------------------------------------
-- Algorithm 1: depth first search numbering
------------------------------------------------------------
\begin{code}
preorder :: Tree a -> [a]
preorder (Node a ts) = a : preorderF ts
preorderF :: Forest a -> [a]
preorderF ts = concat (map preorder ts)
tabulate :: Bounds -> [Vertex] -> Table Int
tabulate bnds vs = array bnds (zip vs [1..])
preArr :: Bounds -> Forest Vertex -> Table Int
preArr bnds = tabulate bnds . preorderF
\end{code}
------------------------------------------------------------
-- Algorithm 2: topological sorting
------------------------------------------------------------
\begin{code}
postorder :: Tree a -> [a] -> [a]
postorder (Node a ts) = postorderF ts . (a :)
postorderF :: Forest a -> [a] -> [a]
postorderF ts = foldr (.) id $ map postorder ts
postOrd :: IntGraph -> [Vertex]
postOrd g = postorderF (dff g) []
postOrdFrom :: IntGraph -> [Vertex] -> [Vertex]
postOrdFrom g vs = postorderF (dfs g vs) []
topSort :: IntGraph -> [Vertex]
topSort = reverse . postOrd
\end{code}
------------------------------------------------------------
-- Algorithm 3: connected components
------------------------------------------------------------
\begin{code}
components :: IntGraph -> Forest Vertex
components = dff . undirected
undirected :: IntGraph -> IntGraph
undirected g = buildG (bounds g) (edges g ++ reverseE g)
\end{code}
------------------------------------------------------------
-- Algorithm 4: strongly connected components
------------------------------------------------------------
\begin{code}
scc :: IntGraph -> Forest Vertex
scc g = dfs g (reverse (postOrd (transpose g)))
sccFrom :: IntGraph -> [Vertex] -> Forest Vertex
sccFrom g vs = reverse (dfs (transpose g) (reverse (postOrdFrom g vs)))
\end{code}
------------------------------------------------------------
-- Algorithm 5: Classifying edges
------------------------------------------------------------
\begin{code}
back :: IntGraph -> Table Int -> IntGraph
back g post = mapT select g
where select v ws = [ w | w <- ws, post!v < post!w ]
cross :: IntGraph -> Table Int -> Table Int -> IntGraph
cross g pre post = mapT select g
where select v ws = [ w | w <- ws, post!v > post!w, pre!v > pre!w ]
forward :: IntGraph -> IntGraph -> Table Int -> IntGraph
forward g tree pre = mapT select g
where select v ws = [ w | w <- ws, pre!v < pre!w ] \\ tree!v
\end{code}
------------------------------------------------------------
-- Algorithm 6: Finding reachable vertices
------------------------------------------------------------
\begin{code}
reachable :: IntGraph -> Vertex -> [Vertex]
reachable g v = preorderF (dfs g [v])
path :: IntGraph -> Vertex -> Vertex -> Bool
path g v w = w `elem` (reachable g v)
\end{code}
------------------------------------------------------------
-- Algorithm 7: Biconnected components
------------------------------------------------------------
\begin{code}
bcc :: IntGraph -> Forest [Vertex]
bcc g = (concat . map bicomps . map (do_label g dnum)) forest
where forest = dff g
dnum = preArr (bounds g) forest
do_label :: IntGraph -> Table Int -> Tree Vertex -> Tree (Vertex,Int,Int)
do_label g dnum (Node v ts) = Node (v,dnum!v,lv) us
where us = map (do_label g dnum) ts
lv = minimum ([dnum!v] ++ [dnum!w | w <- g!v]
++ [lu | Node (_,_,lu) _ <- us])
bicomps :: Tree (Vertex, Int, Int) -> Forest [Vertex]
bicomps (Node (v,_,_) ts)
= [ Node (v:vs) us | (_,Node vs us) <- map collect ts]
collect :: Tree (Vertex, Int, Int) -> (Int, Tree [Vertex])
collect (Node (v,dv,lv) ts) = (lv, Node (v:vs) cs)
where collected = map collect ts
vs = concat [ ws | (lw, Node ws _) <- collected, lw<dv]
cs = concat [ if lw<dv then us else [Node (v:ws) us]
| (lw, Node ws us) <- collected ]
\end{code}
------------------------------------------------------------
-- Algorithm 8: Total ordering on groups of vertices
------------------------------------------------------------
The plan here is to extract a list of groups of elements of the graph
such that each group has no dependence except on nodes in previous
groups (i.e. in particular they may not depend on nodes in their own
group) and is maximal such group.
Clearly we cannot provide a solution for cyclic graphs.
We proceed by iteratively removing elements with no outgoing edges
and their associated edges from the graph.
This probably isn't very efficient and certainly isn't very clever.
\begin{code}
vertexGroups :: IntGraph -> [[Vertex]]
vertexGroups g = runST (mkEmpty (bounds g) >>= \provided -> vertexGroupsS provided g next_vertices)
where next_vertices = noOutEdges g
noOutEdges :: IntGraph -> [Vertex]
noOutEdges g = [ v | v <- vertices g, null (g!v)]
vertexGroupsS :: Set s -> IntGraph -> [Vertex] -> ST s [[Vertex]]
vertexGroupsS provided g to_provide
= if null to_provide
then do {
all_provided <- allM (provided `contains`) (vertices g)
; if all_provided
then return []
else error "vertexGroup: cyclic graph"
}
else do {
mapM_ (include provided) to_provide
; to_provide' <- filterM (vertexReady provided g) (vertices g)
; rest <- vertexGroupsS provided g to_provide'
; return $ to_provide : rest
}
vertexReady :: Set s -> IntGraph -> Vertex -> ST s Bool
vertexReady provided g v = liftM2 (&&) (liftM not $ provided `contains` v) (allM (provided `contains`) (g!v))
\end{code}