| Copyright | (c) Andrey Mokhov 2016-2019 |
|---|---|
| License | MIT (see the file LICENSE) |
| Maintainer | andrey.mokhov@gmail.com |
| Stability | unstable |
| Safe Haskell | None |
| Language | Haskell2010 |
Algebra.Graph.Relation.Internal
Contents
Description
This module exposes the implementation of the Relation data type. The API
is unstable and unsafe, and is exposed only for documentation. You should
use the non-internal module Algebra.Graph.Relation instead.
Synopsis
- data Relation a = Relation {}
- empty :: Relation a
- vertex :: a -> Relation a
- overlay :: Ord a => Relation a -> Relation a -> Relation a
- connect :: Ord a => Relation a -> Relation a -> Relation a
- setProduct :: Set a -> Set b -> Set (a, b)
- consistent :: Ord a => Relation a -> Bool
- referredToVertexSet :: Ord a => Set (a, a) -> Set a
Binary relation implementation
The Relation data type represents a graph as a binary relation. 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 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 (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 (1 * 2 * 3 :: Relation Int) == "edges [(1,2),(1,3),(2,3)]" show (1 * 2 + 3 :: Relation Int) == "overlay (vertex 3) (edge 1 2)"
The Eq instance satisfies all axioms of algebraic graphs:
overlayis commutative and associative:x + y == y + x x + (y + z) == (x + y) + z
connectis associative and hasemptyas the identity:x * empty == x empty * x == x x * (y * z) == (x * y) * z
connectdistributes overoverlay:x * (y + z) == x * y + x * z (x + y) * z == x * z + y * z
connectcan be decomposed:x * y * z == x * y + x * z + y * z
The following useful theorems can be proved from the above set of axioms.
overlayhasemptyas the identity and is idempotent:x + empty == x empty + x == x x + x == xAbsorption and saturation of
connect: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:
vertex1 <vertex2vertex3 <edge1 2vertex1 <edge1 1edge1 1 <edge1 2edge1 2 <edge1 1 +edge2 2edge1 2 <edge1 3
Note that the resulting order refines the
isSubgraphOf relation and is compatible with
overlay and connect operations:
isSubgraphOf x y ==> x <= yempty <= x
x <= x + y
x + y <= x * yConstructors
| Relation | |
Instances
Construct the empty graph. Complexity: O(1) time and memory.
isEmptyempty == TruehasVertexx empty == FalsevertexCountempty == 0edgeCountempty == 0
vertex :: a -> Relation a Source #
Construct the graph comprising a single isolated vertex. Complexity: O(1) time and memory.
isEmpty(vertex x) == FalsehasVertexx (vertex x) == TruevertexCount(vertex x) == 1edgeCount(vertex x) == 0
overlay :: Ord a => Relation a -> Relation a -> Relation 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.
isEmpty(overlay x y) ==isEmptyx && 'iAlgebra.Graph.Relation.sEmpty' yhasVertexz (overlay x y) ==hasVertexz x ||hasVertexz yvertexCount(overlay x y) >=vertexCountxvertexCount(overlay x y) <=vertexCountx +vertexCountyedgeCount(overlay x y) >=edgeCountxedgeCount(overlay x y) <=edgeCountx +edgeCountyvertexCount(overlay 1 2) == 2edgeCount(overlay 1 2) == 0
connect :: Ord a => Relation a -> Relation a -> Relation 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).
isEmpty(connect x y) ==isEmptyx &&isEmptyyhasVertexz (connect x y) ==hasVertexz x ||hasVertexz yvertexCount(connect x y) >=vertexCountxvertexCount(connect x y) <=vertexCountx +vertexCountyedgeCount(connect x y) >=edgeCountxedgeCount(connect x y) >=edgeCountyedgeCount(connect x y) >=vertexCountx *vertexCountyedgeCount(connect x y) <=vertexCountx *vertexCounty +edgeCountx +edgeCountyvertexCount(connect 1 2) == 2edgeCount(connect 1 2) == 1
consistent :: Ord a => Relation a -> Bool Source #
Check if the internal representation of a relation is consistent, i.e. if all
pairs of elements in the relation refer to existing elements in the domain.
It should be impossible to create an inconsistent Relation, and we use this
function in testing.
Note: this function is for internal use only.
consistentempty== True consistent (vertexx) == True consistent (overlayx y) == True consistent (connectx y) == True consistent (edgex y) == True consistent (edgesxs) == True consistent (starsxs) == True