Algebra.Graph.Relation.Symmetric

algebraic-graphs-0.7: A library for algebraic graph construction and transformation

Copyright | (c) Andrey Mokhov 2016-2022
License | MIT (see the file LICENSE)
Maintainer | andrey.mokhov@gmail.com
Stability | experimental
Safe Haskell | None
Language | Haskell2010

Algebra.Graph.Relation.Symmetric

Contents

- Data structure
- Basic graph construction primitives
- Relations on graphs
- Graph properties
- Standard families of graphs
- Graph transformation
- Miscellaneous

Description

An abstract implementation of symmetric binary relations. To avoid name clashes with Algebra.Graph.Relation, this module can be imported qualified:

    import qualified Algebra.Graph.Relation.Symmetric as Symmetric

`Relation` is an instance of the `Graph` type class, which can be used for polymorphic graph construction and manipulation.

Synopsis

- data Relation a
- toSymmetric :: Ord a => Relation a -> Relation a
- fromSymmetric :: Relation a -> Relation a
- empty :: Relation a
- vertex :: a -> Relation a
- edge :: Ord a => a -> a -> Relation a
- overlay :: Ord a => Relation a -> Relation a -> Relation a
- connect :: Ord a => Relation a -> Relation a -> Relation a
- vertices :: Ord a => [a] -> Relation a
- edges :: Ord a => [(a, a)] -> Relation a
- overlays :: Ord a => [Relation a] -> Relation a
- connects :: Ord a => [Relation a] -> Relation a
- isSubgraphOf :: Ord a => Relation a -> Relation a -> Bool
- isEmpty :: Relation a -> Bool
- hasVertex :: Ord a => a -> Relation a -> Bool
- hasEdge :: Ord a => a -> a -> Relation a -> Bool
- vertexCount :: Relation a -> Int
- edgeCount :: Ord a => Relation a -> Int
- vertexList :: Relation a -> [a]
- edgeList :: Ord a => Relation a -> [(a, a)]
- adjacencyList :: Eq a => Relation a -> [(a, [a])]
- vertexSet :: Relation a -> Set a
- edgeSet :: Ord a => Relation a -> Set (a, a)
- neighbours :: Ord a => a -> Relation a -> Set a
- path :: Ord a => [a] -> Relation a
- circuit :: Ord a => [a] -> Relation a
- clique :: Ord a => [a] -> Relation a
- biclique :: Ord a => [a] -> [a] -> Relation a
- star :: Ord a => a -> [a] -> Relation a
- stars :: Ord a => [(a, [a])] -> Relation a
- tree :: Ord a => Tree a -> Relation a
- forest :: Ord a => Forest a -> Relation a
- removeVertex :: Ord a => a -> Relation a -> Relation a
- removeEdge :: Ord a => a -> a -> Relation a -> Relation a
- replaceVertex :: Ord a => a -> a -> Relation a -> Relation a
- mergeVertices :: Ord a => (a -> Bool) -> a -> Relation a -> Relation a
- gmap :: Ord b => (a -> b) -> Relation a -> Relation b
- induce :: (a -> Bool) -> Relation a -> Relation a
- induceJust :: Ord a => Relation (Maybe a) -> Relation a
- consistent :: Ord a => Relation a -> Bool

# Data structure

data Relation a #

This data type represents a symmetric binary relation over a set of elements of type `a`. Symmetric relations satisfy all laws of the `Undirected` type class, including the commutativity of `connect`:

    connect x y == connect y x

The `Show` instance lists edge vertices in non-decreasing order:

    show (empty     :: Relation Int) == "empty"
    show (1         :: Relation Int) == "vertex 1"
    show (1 + 2     :: Relation Int) == "vertices [1,2]"
    show (1 * 2     :: Relation Int) == "edge 1 2"
    show (2 * 1     :: Relation Int) == "edge 1 2"
    show (1 * 2 * 1 :: Relation Int) == "edges [(1,1),(1,2)]"
    show (3 * 2 * 1 :: Relation Int) == "edges [(1,2),(1,3),(2,3)]"
    show (1 * 2 + 3 :: Relation Int) == "overlay (vertex 3) (edge 1 2)"

The total order on graphs is defined using size-lexicographic comparison:

- Compare the number of vertices. In case of a tie, continue.
- Compare the sets of vertices. In case of a tie, continue.
- Compare the number of edges. In case of a tie, continue.
- Compare the sets of edges.

Here are a few examples:

    vertex 1 < vertex 2
    vertex 3 < edge 1 2
    vertex 1 < edge 1 1
    edge 1 1 < edge 1 2
    edge 1 2 < edge 1 1 + edge 2 2
    edge 2 1 < edge 1 3

    edge 1 2 == edge 2 1

Note that the resulting order refines the `isSubgraphOf` relation and is compatible with `overlay` and `connect` operations:

    isSubgraphOf x y ==> x <= y

    empty <= x
    x     <= x + y
    x + y <= x * y

#### Instances

Instances details

Ord a => Graph (Relation a) # |
Instance details Defined in Algebra.Graph.Class Associated Types
type Vertex (Relation a) |
Instance details Defined in Algebra.Graph.Class type Vertex (Relation a) = a
Methods empty :: Relation a # vertex :: Vertex (Relation a) -> Relation a # overlay :: Relation a -> Relation a -> Relation a # connect :: Relation a -> Relation a -> Relation a #
Ord a => Undirected (Relation a) # |
Instance details Defined in Algebra.Graph.Class
Ord a => ToGraph (Relation a) # | Defined via `fromSymmetric` and the `ToGraph` instance of `Relation`.
Instance details Defined in Algebra.Graph.Relation.Symmetric Associated Types
type ToVertex (Relation a) |
Instance details Defined in Algebra.Graph.Relation.Symmetric type ToVertex (Relation a) = a
Methods toGraph :: Relation a -> Graph (ToVertex (Relation a)) # foldg :: r -> (ToVertex (Relation a) -> r) -> (r -> r -> r) -> (r -> r -> r) -> Relation a -> r # isEmpty :: Relation a -> Bool # hasVertex :: ToVertex (Relation a) -> Relation a -> Bool # hasEdge :: ToVertex (Relation a) -> ToVertex (Relation a) -> Relation a -> Bool # vertexCount :: Relation a -> Int # edgeCount :: Relation a -> Int # vertexList :: Relation a -> [ToVertex (Relation a)] # edgeList :: Relation a -> [(ToVertex (Relation a), ToVertex (Relation a))] # vertexSet :: Relation a -> Set (ToVertex (Relation a)) # vertexIntSet :: Relation a -> IntSet # edgeSet :: Relation a -> Set (ToVertex (Relation a), ToVertex (Relation a)) # preSet :: ToVertex (Relation a) -> Relation a -> Set (ToVertex (Relation a)) # preIntSet :: Int -> Relation a -> IntSet # postSet :: ToVertex (Relation a) -> Relation a -> Set (ToVertex (Relation a)) # postIntSet :: Int -> Relation a -> IntSet # adjacencyList :: Relation a -> [(ToVertex (Relation a), [ToVertex (Relation a)])] # dfsForest :: Relation a -> Forest (ToVertex (Relation a)) # dfsForestFrom :: Relation a -> [ToVertex (Relation a)] -> Forest (ToVertex (Relation a)) # dfs :: Relation a -> [ToVertex (Relation a)] -> [ToVertex (Relation a)] # reachable :: Relation a -> ToVertex (Relation a) -> [ToVertex (Relation a)] # topSort :: Relation a -> Either (Cycle (ToVertex (Relation a))) [ToVertex (Relation a)] # isAcyclic :: Relation a -> Bool # toAdjacencyMap :: Relation a -> AdjacencyMap (ToVertex (Relation a)) # toAdjacencyMapTranspose :: Relation a -> AdjacencyMap (ToVertex (Relation a)) # toAdjacencyIntMap :: Relation a -> AdjacencyIntMap # toAdjacencyIntMapTranspose :: Relation a -> AdjacencyIntMap # isDfsForestOf :: Forest (ToVertex (Relation a)) -> Relation a -> Bool # isTopSortOf :: [ToVertex (Relation a)] -> Relation a -> Bool #
NFData a => NFData (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods rnf :: Relation a -> () #
Ord a => Monoid (Relation a) # | Defined via `overlay` and `empty`.
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods mempty :: Relation a # mappend :: Relation a -> Relation a -> Relation a # mconcat :: [Relation a] -> Relation a #
Ord a => Semigroup (Relation a) # | Defined via `overlay`.
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods (<>) :: Relation a -> Relation a -> Relation a # sconcat :: NonEmpty (Relation a) -> Relation a # stimes :: Integral b => b -> Relation a -> Relation a #
IsString a => IsString (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods fromString :: String -> Relation a #
(Ord a, Num a) => Num (Relation a) # | Note: this does not satisfy the usual ring laws; see `Relation` for more details.
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods (+) :: Relation a -> Relation a -> Relation a # (-) :: Relation a -> Relation a -> Relation a # (*) :: Relation a -> Relation a -> Relation a # negate :: Relation a -> Relation a # abs :: Relation a -> Relation a # signum :: Relation a -> Relation a # fromInteger :: Integer -> Relation a #
(Ord a, Show a) => Show (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods showsPrec :: Int -> Relation a -> ShowS # show :: Relation a -> String # showList :: [Relation a] -> ShowS #
Eq a => Eq (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods (==) :: Relation a -> Relation a -> Bool # (/=) :: Relation a -> Relation a -> Bool #
Ord a => Ord (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric Methods compare :: Relation a -> Relation a -> Ordering # (<) :: Relation a -> Relation a -> Bool # (<=) :: Relation a -> Relation a -> Bool # (>) :: Relation a -> Relation a -> Bool # (>=) :: Relation a -> Relation a -> Bool # max :: Relation a -> Relation a -> Relation a # min :: Relation a -> Relation a -> Relation a #
type Vertex (Relation a) # |
Instance details Defined in Algebra.Graph.Class type Vertex (Relation a) = a
type ToVertex (Relation a) # |
Instance details Defined in Algebra.Graph.Relation.Symmetric type ToVertex (Relation a) = a

toSymmetric :: Ord a => Relation a -> Relation a #

Construct a symmetric relation from a given Algebra.Graph.Relation. Complexity: O(m * log(m)) time.

    toSymmetric (edge 1 2)         == edge 1 2
    toSymmetric . fromSymmetric    == id
    fromSymmetric    . toSymmetric == symmetricClosure
    vertexCount      . toSymmetric == vertexCount
    (*2) . edgeCount . toSymmetric >= edgeCount

fromSymmetric :: Relation a -> Relation a #

Extract the underlying symmetric Algebra.Graph.Relation. Complexity: O(1) time and memory.

    fromSymmetric (edge 1 2)    == edges [(1,2), (2,1)]
    vertexCount . fromSymmetric == vertexCount
    edgeCount   . fromSymmetric <= (*2) . edgeCount

# Basic graph construction primitives

empty :: Relation a #

Construct the empty graph.

    isEmpty     empty == True
    hasVertex x empty == False
    vertexCount empty == 0
    edgeCount   empty == 0

vertex :: a -> Relation a #

Construct the graph comprising a single isolated vertex.

    isEmpty     (vertex x) == False
    hasVertex x (vertex y) == (x == y)
    vertexCount (vertex x) == 1
    edgeCount   (vertex x) == 0

edge :: Ord a => a -> a -> Relation a #

Construct the graph comprising a single edge.

    edge x y               == connect (vertex x) (vertex y)
    edge x y               == edge y x
    edge x y               == edges [(x,y), (y,x)]
    hasEdge x y (edge x y) == True
    edgeCount   (edge x y) == 1
    vertexCount (edge 1 1) == 1
    vertexCount (edge 1 2) == 2

overlay :: Ord a => Relation a -> Relation a -> Relation a #

Overlay two graphs. This is a commutative, associative and idempotent operation with the identity `empty`. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    isEmpty     (overlay x y) == isEmpty   x   && isEmpty   y
    hasVertex z (overlay x y) == hasVertex z x || hasVertex z y
    vertexCount (overlay x y) >= vertexCount x
    vertexCount (overlay x y) <= vertexCount x + vertexCount y
    edgeCount   (overlay x y) >= edgeCount x
    edgeCount   (overlay x y) <= edgeCount x   + edgeCount y
    vertexCount (overlay 1 2) == 2
    edgeCount   (overlay 1 2) == 0

connect :: Ord a => Relation a -> Relation a -> Relation a #

Connect two graphs. This is a commutative and associative operation with the identity `empty`, which distributes over `overlay` and obeys the decomposition axiom. Complexity: O((n + m) * log(n)) time and O(n + m) memory. Note that the number of edges in the resulting graph is quadratic with respect to the number of vertices of the arguments: m = O(m1 + m2 + n1 * n2).

    connect x y               == connect y x
    isEmpty     (connect x y) == isEmpty   x   && isEmpty   y
    hasVertex z (connect x y) == hasVertex z x || hasVertex z y
    vertexCount (connect x y) >= vertexCount x
    vertexCount (connect x y) <= vertexCount x + vertexCount y
    edgeCount   (connect x y) >= edgeCount x
    edgeCount   (connect x y) >= edgeCount y
    edgeCount   (connect x y) >= vertexCount x * vertexCount y `div` 2
    vertexCount (connect 1 2) == 2
    edgeCount   (connect 1 2) == 1

vertices :: Ord a => [a] -> Relation a #

Construct the graph comprising a given list of isolated vertices. Complexity: O(L * log(L)) time and O(L) memory, where L is the length of the given list.

    vertices []            == empty
    vertices [x]           == vertex x
    vertices               == overlays . map vertex
    hasVertex x . vertices == elem x
    vertexCount . vertices == length . nub
    vertexSet   . vertices == Set.fromList

edges :: Ord a => [(a, a)] -> Relation a #

Construct the graph from a list of edges. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    edges []             == empty
    edges [(x,y)]        == edge x y
    edges [(x,y), (y,x)] == edge x y

overlays :: Ord a => [Relation a] -> Relation a #

Overlay a given list of graphs. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    overlays []        == empty
    overlays [x]       == x
    overlays [x,y]     == overlay x y
    overlays           == foldr overlay empty
    isEmpty . overlays == all isEmpty

connects :: Ord a => [Relation a] -> Relation a #

Connect a given list of graphs. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    connects []        == empty
    connects [x]       == x
    connects [x,y]     == connect x y
    connects           == foldr connect empty
    isEmpty . connects == all isEmpty
    connects           == connects . reverse

# Relations on graphs

isSubgraphOf :: Ord a => Relation a -> Relation a -> Bool #

The `isSubgraphOf` function takes two graphs and returns `True` if the first graph is a subgraph of the second. Complexity: O((n + m) * log(n)) time.

    isSubgraphOf empty         x             ==  True
    isSubgraphOf (vertex x)    empty         ==  False
    isSubgraphOf x             (overlay x y) ==  True
    isSubgraphOf (overlay x y) (connect x y) ==  True
    isSubgraphOf (path xs)     (circuit xs)  ==  True
    isSubgraphOf (edge x y)    (edge y x)    ==  True
    isSubgraphOf x y                         ==> x <= y

# Graph properties

isEmpty :: Relation a -> Bool #

Check if a relation is empty. Complexity: O(1) time.

    isEmpty empty                       == True
    isEmpty (overlay empty empty)       == True
    isEmpty (vertex x)                  == False
    isEmpty (removeVertex x $ vertex x) == True
    isEmpty (removeEdge x y $ edge x y) == False

hasVertex :: Ord a => a -> Relation a -> Bool #

Check if a graph contains a given vertex. Complexity: O(log(n)) time.

    hasVertex x empty            == False
    hasVertex x (vertex y)       == (x == y)
    hasVertex x . removeVertex x == const False

hasEdge :: Ord a => a -> a -> Relation a -> Bool #

Check if a graph contains a given edge. Complexity: O(log(n)) time.

    hasEdge x y empty            == False
    hasEdge x y (vertex z)       == False
    hasEdge x y (edge x y)       == True
    hasEdge x y (edge y x)       == True
    hasEdge x y . removeEdge x y == const False
    hasEdge x y                  == elem (min x y, max x y) . edgeList

vertexCount :: Relation a -> Int #

The number of vertices in a graph. Complexity: O(1) time.

    vertexCount empty             ==  0
    vertexCount (vertex x)        ==  1
    vertexCount                   ==  length . vertexList
    vertexCount x < vertexCount y ==> x < y

edgeCount :: Ord a => Relation a -> Int #

The number of edges in a graph. Complexity: O(1) time.

    edgeCount empty      == 0
    edgeCount (vertex x) == 0
    edgeCount (edge x y) == 1
    edgeCount            == length . edgeList

vertexList :: Relation a -> [a] #

The sorted list of vertices of a given graph. Complexity: O(n) time and memory.

    vertexList empty      == []
    vertexList (vertex x) == [x]
    vertexList . vertices == nub . sort

edgeList :: Ord a => Relation a -> [(a, a)] #

The sorted list of edges of a graph, where edge vertices appear in the non-decreasing order. Complexity: O(n + m) time and O(m) memory.

Note: If you need the sorted list of edges where an edge appears in both directions, use ``edgeList` . `fromSymmetric``.

    edgeList empty          == []
    edgeList (vertex x)     == []
    edgeList (edge x y)     == [(min x y, max y x)]
    edgeList (star 2 [3,1]) == [(1,2), (2,3)]

adjacencyList :: Eq a => Relation a -> [(a, [a])] #

The sorted adjacency list of a graph. Complexity: O(n + m) time and memory.

    adjacencyList empty          == []
    adjacencyList (vertex x)     == [(x, [])]
    adjacencyList (edge 1 2)     == [(1, [2]), (2, [1])]
    adjacencyList (star 2 [3,1]) == [(1, [2]), (2, [1,3]), (3, [2])]
    stars . adjacencyList        == id

vertexSet :: Relation a -> Set a #

The set of vertices of a given graph. Complexity: O(1) time.

    vertexSet empty      == Set.empty
    vertexSet . vertex   == Set.singleton
    vertexSet . vertices == Set.fromList

edgeSet :: Ord a => Relation a -> Set (a, a) #

The set of edges of a given graph, where edge vertices appear in the non-decreasing order. Complexity: O(m) time.

Note: If you need the set of edges where an edge appears in both directions, use ``relation` . `fromSymmetric``. The latter is much faster than this function, and takes only O(1) time and memory.

    edgeSet empty      == Set.empty
    edgeSet (vertex x) == Set.empty
    edgeSet (edge x y) == Set.singleton (min x y, max x y)

neighbours :: Ord a => a -> Relation a -> Set a #

The set of neighbours of an element `x` is the set of elements that are related to it, i.e. `neighbours x == { a | aRx }`. In the context of undirected graphs, this corresponds to the set of adjacent vertices of vertex `x`.

    neighbours x empty      == Set.empty
    neighbours x (vertex x) == Set.empty
    neighbours x (edge x y) == Set.fromList [y]
    neighbours y (edge x y) == Set.fromList [x]

# Standard families of graphs

path :: Ord a => [a] -> Relation a #

The path on a list of vertices. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    path []    == empty
    path [x]   == vertex x
    path [x,y] == edge x y
    path       == path . reverse

circuit :: Ord a => [a] -> Relation a #

The circuit on a list of vertices. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    circuit []    == empty
    circuit [x]   == edge x x
    circuit [x,y] == edge x y
    circuit       == circuit . reverse

clique :: Ord a => [a] -> Relation a #

The clique on a list of vertices. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    clique []         == empty
    clique [x]        == vertex x
    clique [x,y]      == edge x y
    clique [x,y,z]    == edges [(x,y), (x,z), (y,z)]
    clique (xs ++ ys) == connect (clique xs) (clique ys)
    clique            == clique . reverse

biclique :: Ord a => [a] -> [a] -> Relation a #

The biclique on two lists of vertices. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    biclique []      []      == empty
    biclique [x]     []      == vertex x
    biclique []      [y]     == vertex y
    biclique [x1,x2] [y1,y2] == edges [(x1,y1), (x1,y2), (x2,x2), (x2,y2)]
    biclique xs      ys      == connect (vertices xs) (vertices ys)

star :: Ord a => a -> [a] -> Relation a #

The star formed by a centre vertex connected to a list of leaves. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    star x []    == vertex x
    star x [y]   == edge x y
    star x [y,z] == edges [(x,y), (x,z)]
    star x ys    == connect (vertex x) (vertices ys)

stars :: Ord a => [(a, [a])] -> Relation a #

The stars formed by overlaying a list of `star`s. An inverse of `adjacencyList`. Complexity: O(L * log(n)) time, memory and size, where L is the total size of the input.

    stars []                      == empty
    stars [(x, [])]               == vertex x
    stars [(x, [y])]              == edge x y
    stars [(x, ys)]               == star x ys
    stars                         == overlays . map (uncurry star)
    stars . adjacencyList         == id
    overlay (stars xs) (stars ys) == stars (xs ++ ys)

tree :: Ord a => Tree a -> Relation a #

The tree graph constructed from a given `Tree` data structure. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    tree (Node x [])                                         == vertex x
    tree (Node x [Node y [Node z []]])                       == path [x,y,z]
    tree (Node x [Node y [], Node z []])                     == star x [y,z]
    tree (Node 1 [Node 2 [], Node 3 [Node 4 [], Node 5 []]]) == edges [(1,2), (1,3), (3,4), (3,5)]

forest :: Ord a => Forest a -> Relation a #

The forest graph constructed from a given `Forest` data structure. Complexity: O((n + m) * log(n)) time and O(n + m) memory.

    forest []                                                  == empty
    forest [x]                                                 == tree x
    forest [Node 1 [Node 2 [], Node 3 []], Node 4 [Node 5 []]] == edges [(1,2), (1,3), (4,5)]
    forest                                                     == overlays . map tree

# Graph transformation

removeVertex :: Ord a => a -> Relation a -> Relation a #

Remove a vertex from a given graph. Complexity: O(n + m) time.

    removeVertex x (vertex x)       == empty
    removeVertex 1 (vertex 2)       == vertex 2
    removeVertex x (edge x x)       == empty
    removeVertex 1 (edge 1 2)       == vertex 2
    removeVertex x . removeVertex x == removeVertex x

removeEdge :: Ord a => a -> a -> Relation a -> Relation a #

Remove an edge from a given graph. Complexity: O(log(m)) time.

    removeEdge x y (edge x y)       == vertices [x,y]
    removeEdge x y . removeEdge x y == removeEdge x y
    removeEdge x y                  == removeEdge y x
    removeEdge x y . removeVertex x == removeVertex x
    removeEdge 1 1 (1 * 1 * 2 * 2)  == 1 * 2 * 2
    removeEdge 1 2 (1 * 1 * 2 * 2)  == 1 * 1 + 2 * 2

replaceVertex :: Ord a => a -> a -> Relation a -> Relation a #

The function ``replaceVertex` x y` replaces vertex `x` with vertex `y` in a given `Relation`. If `y` already exists, `x` and `y` will be merged. Complexity: O((n + m) * log(n)) time.

    replaceVertex x x            == id
    replaceVertex x y (vertex x) == vertex y
    replaceVertex x y            == mergeVertices (== x) y

mergeVertices :: Ord a => (a -> Bool) -> a -> Relation a -> Relation a #

Merge vertices satisfying a given predicate into a given vertex. Complexity: O((n + m) * log(n)) time, assuming that the predicate takes constant time.

    mergeVertices (const False) x    == id
    mergeVertices (== x) y           == replaceVertex x y
    mergeVertices even 1 (0 * 2)     == 1 * 1
    mergeVertices odd  1 (3 + 4 * 5) == 4 * 1

gmap :: Ord b => (a -> b) -> Relation a -> Relation b #

Transform a graph by applying a function to each of its vertices. This is similar to `Functor`'s `fmap` but can be used with non-fully-parametric `Relation`. Complexity: O((n + m) * log(n)) time.

    gmap f empty      == empty
    gmap f (vertex x) == vertex (f x)
    gmap f (edge x y) == edge (f x) (f y)
    gmap id           == id
    gmap f . gmap g   == gmap (f . g)

induce :: (a -> Bool) -> Relation a -> Relation a #

Construct the induced subgraph of a given graph by removing the vertices that do not satisfy a given predicate. Complexity: O(n + m) time, assuming that the predicate takes constant time.

    induce (const True ) x      == x
    induce (const False) x      == empty
    induce (/= x)               == removeVertex x
    induce p . induce q         == induce (\x -> p x && q x)
    isSubgraphOf (induce p x) x == True

induceJust :: Ord a => Relation (Maybe a) -> Relation a #

Construct the induced subgraph of a given graph by removing the vertices that are `Nothing`. Complexity: O(n + m) time.

    induceJust (vertex Nothing)                               == empty
    induceJust (edge (Just x) Nothing)                        == vertex x
    induceJust . gmap Just                                    == id
    induceJust . gmap (\x -> if p x then Just x else Nothing) == induce p

# Miscellaneous

consistent :: Ord a => Relation a -> Bool #

Check that the internal representation of a symmetric relation is consistent, i.e. that (i) that all edges refer to existing vertices, and (ii) all edges have their symmetric counterparts. It should be impossible to create an inconsistent `Relation`, and we use this function in testing.

    consistent empty         == True
    consistent (vertex x)    == True
    consistent (overlay x y) == True
    consistent (connect x y) == True
    consistent (edge x y)    == True
    consistent (edges xs)    == True
    consistent (stars xs)    == True