Copyright | (c) Andrey Mokhov 2016-2022 |
---|---|
License | MIT (see the file LICENSE) |
Maintainer | andrey.mokhov@gmail.com |
Stability | experimental |
Safe Haskell | None |
Language | Haskell2010 |
Alga is a library for algebraic construction and manipulation of graphs in Haskell. See this paper for the motivation behind the library, the underlying theory, and implementation details.
This module defines the data type AdjacencyMap
for graphs that are known
to be non-empty at compile time. To avoid name clashes with
Algebra.Graph.AdjacencyMap, this module can be imported qualified:
import qualified Algebra.Graph.NonEmpty.AdjacencyMap as NonEmpty
The naming convention generally follows that of Data.List.NonEmpty: we use
suffix 1
to indicate the functions whose interface must be changed compared
to Algebra.Graph.AdjacencyMap, e.g. vertices1
.
Synopsis
- data AdjacencyMap a
- toNonEmpty :: AdjacencyMap a -> Maybe (AdjacencyMap a)
- fromNonEmpty :: AdjacencyMap a -> AdjacencyMap a
- vertex :: a -> AdjacencyMap a
- edge :: Ord a => a -> a -> AdjacencyMap a
- overlay :: Ord a => AdjacencyMap a -> AdjacencyMap a -> AdjacencyMap a
- connect :: Ord a => AdjacencyMap a -> AdjacencyMap a -> AdjacencyMap a
- vertices1 :: Ord a => NonEmpty a -> AdjacencyMap a
- edges1 :: Ord a => NonEmpty (a, a) -> AdjacencyMap a
- overlays1 :: Ord a => NonEmpty (AdjacencyMap a) -> AdjacencyMap a
- connects1 :: Ord a => NonEmpty (AdjacencyMap a) -> AdjacencyMap a
- isSubgraphOf :: Ord a => AdjacencyMap a -> AdjacencyMap a -> Bool
- hasVertex :: Ord a => a -> AdjacencyMap a -> Bool
- hasEdge :: Ord a => a -> a -> AdjacencyMap a -> Bool
- vertexCount :: AdjacencyMap a -> Int
- edgeCount :: AdjacencyMap a -> Int
- vertexList1 :: AdjacencyMap a -> NonEmpty a
- edgeList :: AdjacencyMap a -> [(a, a)]
- vertexSet :: AdjacencyMap a -> Set a
- edgeSet :: Ord a => AdjacencyMap a -> Set (a, a)
- preSet :: Ord a => a -> AdjacencyMap a -> Set a
- postSet :: Ord a => a -> AdjacencyMap a -> Set a
- path1 :: Ord a => NonEmpty a -> AdjacencyMap a
- circuit1 :: Ord a => NonEmpty a -> AdjacencyMap a
- clique1 :: Ord a => NonEmpty a -> AdjacencyMap a
- biclique1 :: Ord a => NonEmpty a -> NonEmpty a -> AdjacencyMap a
- star :: Ord a => a -> [a] -> AdjacencyMap a
- stars1 :: Ord a => NonEmpty (a, [a]) -> AdjacencyMap a
- tree :: Ord a => Tree a -> AdjacencyMap a
- removeVertex1 :: Ord a => a -> AdjacencyMap a -> Maybe (AdjacencyMap a)
- removeEdge :: Ord a => a -> a -> AdjacencyMap a -> AdjacencyMap a
- replaceVertex :: Ord a => a -> a -> AdjacencyMap a -> AdjacencyMap a
- mergeVertices :: Ord a => (a -> Bool) -> a -> AdjacencyMap a -> AdjacencyMap a
- transpose :: Ord a => AdjacencyMap a -> AdjacencyMap a
- gmap :: (Ord a, Ord b) => (a -> b) -> AdjacencyMap a -> AdjacencyMap b
- induce1 :: (a -> Bool) -> AdjacencyMap a -> Maybe (AdjacencyMap a)
- induceJust1 :: Ord a => AdjacencyMap (Maybe a) -> Maybe (AdjacencyMap a)
- closure :: Ord a => AdjacencyMap a -> AdjacencyMap a
- reflexiveClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a
- symmetricClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a
- transitiveClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a
- consistent :: Ord a => AdjacencyMap a -> Bool
Data structure
data AdjacencyMap a Source #
The AdjacencyMap
data type represents a graph by a map of vertices to
their adjacency sets. We define a Num
instance as a convenient notation for
working with graphs:
0 ==vertex
0 1 + 2 ==overlay
(vertex
1) (vertex
2) 1 * 2 ==connect
(vertex
1) (vertex
2) 1 + 2 * 3 ==overlay
(vertex
1) (connect
(vertex
2) (vertex
3)) 1 * (2 + 3) ==connect
(vertex
1) (overlay
(vertex
2) (vertex
3))
Note: the signum
method of the type class Num
cannot be implemented and
will throw an error. Furthermore, the Num
instance does not satisfy several
"customary laws" of Num
, which dictate that fromInteger
0
and
fromInteger
1
should act as additive and multiplicative identities, and
negate
as additive inverse. Nevertheless, overloading fromInteger
, +
and
*
is very convenient when working with algebraic graphs; we hope that in
future Haskell's Prelude will provide a more fine-grained class hierarchy for
algebraic structures, which we would be able to utilise without violating any
laws.
The Show
instance is defined using basic graph construction primitives:
show (1 :: AdjacencyMap Int) == "vertex 1" show (1 + 2 :: AdjacencyMap Int) == "vertices1 [1,2]" show (1 * 2 :: AdjacencyMap Int) == "edge 1 2" show (1 * 2 * 3 :: AdjacencyMap Int) == "edges1 [(1,2),(1,3),(2,3)]" show (1 * 2 + 3 :: AdjacencyMap Int) == "overlay (vertex 3) (edge 1 2)"
The Eq
instance satisfies the following laws of algebraic graphs:
overlay
is commutative, associative and idempotent:x + y == y + x x + (y + z) == (x + y) + z x + x == x
connect
is associative:x * (y * z) == (x * y) * z
connect
distributes overoverlay
:x * (y + z) == x * y + x * z (x + y) * z == x * z + y * z
connect
can be decomposed:x * y * z == x * y + x * z + y * z
connect
satisfies absorption and saturation:x * y + x + y == x * y x * x * x == x * x
When specifying the time and memory complexity of graph algorithms, n and m will denote the number of vertices and edges in the graph, respectively.
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
2vertex
3 <edge
1 2vertex
1 <edge
1 1edge
1 1 <edge
1 2edge
1 2 <edge
1 1 +edge
2 2edge
1 2 <edge
1 3
Note that the resulting order refines the
isSubgraphOf
relation and is compatible
with overlay
and
connect
operations:
isSubgraphOf
x y ==> x <= y
x <= x + y x + y <= x * y
Instances
toNonEmpty :: AdjacencyMap a -> Maybe (AdjacencyMap a) Source #
Convert a possibly empty AdjacencyMap
into NonEmpty.AdjacencyMap
.
Returns Nothing
if the argument is empty
.
Complexity: O(1) time, memory and size.
toNonEmptyempty
==Nothing
toNonEmpty .fromNonEmpty
==Just
fromNonEmpty :: AdjacencyMap a -> AdjacencyMap a Source #
Convert a NonEmpty.AdjacencyMap
into an AdjacencyMap
. The resulting
graph is guaranteed to be non-empty.
Complexity: O(1) time, memory and size.
isEmpty
. fromNonEmpty ==const
False
toNonEmpty
. fromNonEmpty ==Just
Basic graph construction primitives
vertex :: a -> AdjacencyMap a Source #
Construct the graph comprising a single isolated vertex.
hasVertex
x (vertex y) == (x == y)vertexCount
(vertex x) == 1edgeCount
(vertex x) == 0
edge :: Ord a => a -> a -> AdjacencyMap a Source #
Construct the graph comprising a single edge.
edge x y ==connect
(vertex
x) (vertex
y)hasEdge
x y (edge x y) == TrueedgeCount
(edge x y) == 1vertexCount
(edge 1 1) == 1vertexCount
(edge 1 2) == 2
overlay :: Ord a => AdjacencyMap a -> AdjacencyMap a -> AdjacencyMap a Source #
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.
hasVertex
z (overlay x y) ==hasVertex
z x ||hasVertex
z yvertexCount
(overlay x y) >=vertexCount
xvertexCount
(overlay x y) <=vertexCount
x +vertexCount
yedgeCount
(overlay x y) >=edgeCount
xedgeCount
(overlay x y) <=edgeCount
x +edgeCount
yvertexCount
(overlay 1 2) == 2edgeCount
(overlay 1 2) == 0
connect :: Ord a => AdjacencyMap a -> AdjacencyMap a -> AdjacencyMap a Source #
Connect two graphs. This is an 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).
hasVertex
z (connect x y) ==hasVertex
z x ||hasVertex
z yvertexCount
(connect x y) >=vertexCount
xvertexCount
(connect x y) <=vertexCount
x +vertexCount
yedgeCount
(connect x y) >=edgeCount
xedgeCount
(connect x y) >=edgeCount
yedgeCount
(connect x y) >=vertexCount
x *vertexCount
yedgeCount
(connect x y) <=vertexCount
x *vertexCount
y +edgeCount
x +edgeCount
yvertexCount
(connect 1 2) == 2edgeCount
(connect 1 2) == 1
vertices1 :: Ord a => NonEmpty a -> AdjacencyMap a Source #
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.
vertices1 [x] ==vertex
xhasVertex
x . vertices1 ==elem
xvertexCount
. vertices1 ==length
.nub
vertexSet
. vertices1 == Set.fromList
.toList
overlays1 :: Ord a => NonEmpty (AdjacencyMap a) -> AdjacencyMap a Source #
Overlay a given list of graphs. Complexity: O((n + m) * log(n)) time and O(n + m) memory.
overlays1 [x] == x
overlays1 [x,y] == overlay
x y
connects1 :: Ord a => NonEmpty (AdjacencyMap a) -> AdjacencyMap a Source #
Connect a given list of graphs. Complexity: O((n + m) * log(n)) time and O(n + m) memory.
connects1 [x] == x
connects1 [x,y] == connect
x y
Relations on graphs
isSubgraphOf :: Ord a => AdjacencyMap a -> AdjacencyMap a -> Bool Source #
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 x (overlay
x y) == True isSubgraphOf (overlay
x y) (connect
x y) == True isSubgraphOf (path1
xs) (circuit1
xs) == True isSubgraphOf x y ==> x <= y
Graph properties
hasVertex :: Ord a => a -> AdjacencyMap a -> Bool Source #
Check if a graph contains a given vertex. Complexity: O(log(n)) time.
hasVertex x (vertex
y) == (x == y)
vertexCount :: AdjacencyMap a -> Int Source #
edgeCount :: AdjacencyMap a -> Int Source #
vertexList1 :: AdjacencyMap a -> NonEmpty a Source #
edgeList :: AdjacencyMap a -> [(a, a)] Source #
vertexSet :: AdjacencyMap a -> Set a Source #
Standard families of graphs
star :: Ord a => a -> [a] -> AdjacencyMap a Source #
stars1 :: Ord a => NonEmpty (a, [a]) -> AdjacencyMap a Source #
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.
stars1 [(x, [] )] ==vertex
x stars1 [(x, [y])] ==edge
x y stars1 [(x, ys )] ==star
x ys stars1 ==overlays1
.fmap
(uncurry
star
)overlay
(stars1 xs) (stars1 ys) == stars1 (xs<>
ys)
tree :: Ord a => Tree a -> AdjacencyMap a Source #
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 []]]) ==path1
[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 []]]) ==edges1
[(1,2), (1,3), (3,4), (3,5)]
Graph transformation
removeVertex1 :: Ord a => a -> AdjacencyMap a -> Maybe (AdjacencyMap a) Source #
removeEdge :: Ord a => a -> a -> AdjacencyMap a -> AdjacencyMap a Source #
replaceVertex :: Ord a => a -> a -> AdjacencyMap a -> AdjacencyMap a Source #
The function
replaces vertex replaceVertex
x yx
with vertex y
in a
given AdjacencyMap
. 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 -> AdjacencyMap a -> AdjacencyMap a Source #
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 mergeVerticeseven
1 (0 * 2) == 1 * 1 mergeVerticesodd
1 (3 + 4 * 5) == 4 * 1
transpose :: Ord a => AdjacencyMap a -> AdjacencyMap a Source #
gmap :: (Ord a, Ord b) => (a -> b) -> AdjacencyMap a -> AdjacencyMap b Source #
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
AdjacencyMap
.
Complexity: O((n + m) * log(n)) time.
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)
induce1 :: (a -> Bool) -> AdjacencyMap a -> Maybe (AdjacencyMap a) Source #
Construct the induced subgraph of a given graph by removing the vertices that do not satisfy a given predicate. Complexity: O(m) time, assuming that the predicate takes constant time.
induce1 (const
True ) x == Just x induce1 (const
False) x == Nothing induce1 (/= x) ==removeVertex1
x induce1 p>=>
induce1 q == induce1 (\x -> p x && q x)
induceJust1 :: Ord a => AdjacencyMap (Maybe a) -> Maybe (AdjacencyMap a) Source #
Construct the induced subgraph of a given graph by removing the vertices
that are Nothing
. Returns Nothing
if the resulting graph is empty.
Complexity: O(n + m) time.
induceJust1 (vertex
Nothing
) ==Nothing
induceJust1 (edge
(Just
x)Nothing
) ==Just
(vertex
x) induceJust1 .gmap
Just
==Just
induceJust1 .gmap
(\x -> if p x thenJust
x elseNothing
) ==induce1
p
Graph closure
closure :: Ord a => AdjacencyMap a -> AdjacencyMap a Source #
Compute the reflexive and transitive closure of a graph. Complexity: O(n * m * log(n)^2) time.
closure (vertex
x) ==edge
x x closure (edge
x x) ==edge
x x closure (edge
x y) ==edges1
[(x,x), (x,y), (y,y)] closure (path1
$nub
xs) ==reflexiveClosure
(clique1
$nub
xs) closure ==reflexiveClosure
.transitiveClosure
closure ==transitiveClosure
.reflexiveClosure
closure . closure == closurepostSet
x (closure y) == Set.fromList
(reachable
x y)
reflexiveClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a Source #
Compute the reflexive closure of a graph by adding a self-loop to every vertex. Complexity: O(n * log(n)) time.
reflexiveClosure (vertex
x) ==edge
x x reflexiveClosure (edge
x x) ==edge
x x reflexiveClosure (edge
x y) ==edges1
[(x,x), (x,y), (y,y)] reflexiveClosure . reflexiveClosure == reflexiveClosure
symmetricClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a Source #
Compute the symmetric closure of a graph by overlaying it with its own transpose. Complexity: O((n + m) * log(n)) time.
symmetricClosure (vertex
x) ==vertex
x symmetricClosure (edge
x y) ==edges1
[(x,y), (y,x)] symmetricClosure x ==overlay
x (transpose
x) symmetricClosure . symmetricClosure == symmetricClosure
transitiveClosure :: Ord a => AdjacencyMap a -> AdjacencyMap a Source #
Miscellaneous
consistent :: Ord a => AdjacencyMap a -> Bool Source #
Check that the internal graph representation is consistent, i.e. that all edges refer to existing vertices, and the graph is non-empty. It should be impossible to create an inconsistent adjacency map, and we use this function in testing.
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