Did you know ... | Search Documentation: |

library(ugraphs): Graph manipulation library |

- Documentation
- Reference manual
- The SWI-Prolog library
- library(aggregate): Aggregation operators on backtrackable predicates
- library(ansi_term): Print decorated text to ANSI consoles
- library(apply): Apply predicates on a list
- library(assoc): Association lists
- library(broadcast): Broadcast and receive event notifications
- library(charsio): I/O on Lists of Character Codes
- library(check): Consistency checking
- library(clpb): CLP(B): Constraint Logic Programming over Boolean Variables
- library(clpfd): CLP(FD): Constraint Logic Programming over Finite Domains
- library(clpqr): Constraint Logic Programming over Rationals and Reals
- library(csv): Process CSV (Comma-Separated Values) data
- library(dcg/basics): Various general DCG utilities
- library(dcg/high_order): High order grammar operations
- library(debug): Print debug messages and test assertions
- library(dicts): Dict utilities
- library(error): Error generating support
- library(fastrw): Fast reading and writing of terms
- library(gensym): Generate unique symbols
- library(heaps): heaps/priority queues
- library(increval): Incremental dynamic predicate modification
- library(intercept): Intercept and signal interface
- library(iostream): Utilities to deal with streams
- library(listing): List programs and pretty print clauses
- library(lists): List Manipulation
- library(main): Provide entry point for scripts
- library(nb_set): Non-backtrackable set
- library(www_browser): Open a URL in the users browser
- library(occurs): Finding and counting sub-terms
- library(option): Option list processing
- library(optparse): command line parsing
- library(ordsets): Ordered set manipulation
- library(pairs): Operations on key-value lists
- library(persistency): Provide persistent dynamic predicates
- library(pio): Pure I/O
- library(portray_text): Portray text
- library(predicate_options): Declare option-processing of predicates
- library(prolog_debug): User level debugging tools
- library(prolog_jiti): Just In Time Indexing (JITI) utilities
- library(prolog_pack): A package manager for Prolog
- library(prolog_xref): Prolog cross-referencer data collection
- library(quasi_quotations): Define Quasi Quotation syntax
- library(random): Random numbers
- library(rbtrees): Red black trees
- library(readutil): Read utilities
- library(record): Access named fields in a term
- library(registry): Manipulating the Windows registry
- library(settings): Setting management
- library(statistics): Get information about resource usage
- library(strings): String utilities
- library(simplex): Solve linear programming problems
- library(solution_sequences): Modify solution sequences
- library(tables): XSB interface to tables
- library(terms): Term manipulation
- library(thread): High level thread primitives
- library(thread_pool): Resource bounded thread management
- library(ugraphs): Graph manipulation library
- library(url): Analysing and constructing URL
- library(varnumbers): Utilities for numbered terms
- library(yall): Lambda expressions

- The SWI-Prolog library
- Packages

- Reference manual

- author
- - R.A.O'Keefe

- Vitor Santos Costa

- Jan Wielemaker - license
- BSD-2 or Artistic 2.0

The S-representation of a graph is a list of (vertex-neighbours) pairs, where the pairs are in standard order (as produced by keysort) and the neighbours of each vertex are also in standard order (as produced by sort). This form is convenient for many calculations.

A new UGraph from raw data can be created using vertices_edges_to_ugraph/3.

Adapted to support some of the functionality of the SICStus ugraphs library by Vitor Santos Costa.

Ported from YAP 5.0.1 to SWI-Prolog by Jan Wielemaker.

**vertices**(`+Graph, -Vertices`)- Unify
`Vertices`with all vertices appearing in`Graph`. Example:?- vertices([1-[3,5],2-[4],3-[],4-[5],5-[]], L). L = [1, 2, 3, 4, 5]

- [det]
**vertices_edges_to_ugraph**(`+Vertices, +Edges, -UGraph`) - Create a
`UGraph`from`Vertices`and edges. Given a graph with a set of`Vertices`and a set of`Edges`, Graph must unify with the corresponding S-representation. Note that the vertices without edges will appear in`Vertices`but not in`Edges`. Moreover, it is sufficient for a vertice to appear in`Edges`.?- vertices_edges_to_ugraph([],[1-3,2-4,4-5,1-5], L). L = [1-[3,5], 2-[4], 3-[], 4-[5], 5-[]]

In this case all vertices are defined implicitly. The next example shows three unconnected vertices:

?- vertices_edges_to_ugraph([6,7,8],[1-3,2-4,4-5,1-5], L). L = [1-[3,5], 2-[4], 3-[], 4-[5], 5-[], 6-[], 7-[], 8-[]]

**add_vertices**(`+Graph, +Vertices, -NewGraph`)- Unify
`NewGraph`with a new graph obtained by adding the list of`Vertices`to`Graph`. Example:?- add_vertices([1-[3,5],2-[]], [0,1,2,9], NG). NG = [0-[], 1-[3,5], 2-[], 9-[]]

- [det]
**del_vertices**(`+Graph, +Vertices, -NewGraph`) - Unify
`NewGraph`with a new graph obtained by deleting the list of`Vertices`and all the edges that start from or go to a vertex in`Vertices`to the`Graph`. Example:?- del_vertices([1-[3,5],2-[4],3-[],4-[5],5-[],6-[],7-[2,6],8-[]], [2,1], NL). NL = [3-[],4-[5],5-[],6-[],7-[6],8-[]]

- Compatibility
- Upto 5.6.48 the argument order was (+
`Vertices`, +`Graph`, -`NewGraph`). Both YAP and SWI-Prolog have changed the argument order for compatibility with recent SICStus as well as consistency with del_edges/3.

**add_edges**(`+Graph, +Edges, -NewGraph`)- Unify
`NewGraph`with a new graph obtained by adding the list of`Edges`to`Graph`. Example:?- add_edges([1-[3,5],2-[4],3-[],4-[5], 5-[],6-[],7-[],8-[]], [1-6,2-3,3-2,5-7,3-2,4-5], NL). NL = [1-[3,5,6], 2-[3,4], 3-[2], 4-[5], 5-[7], 6-[], 7-[], 8-[]]

**ugraph_union**(`+Graph1, +Graph2, -NewGraph`)`NewGraph`is the union of`Graph1`and`Graph2`. Example:?- ugraph_union([1-[2],2-[3]],[2-[4],3-[1,2,4]],L). L = [1-[2], 2-[3,4], 3-[1,2,4]]

**del_edges**(`+Graph, +Edges, -NewGraph`)- Unify
`NewGraph`with a new graph obtained by removing the list of`Edges`from`Graph`. Notice that no vertices are deleted. Example:?- del_edges([1-[3,5],2-[4],3-[],4-[5],5-[],6-[],7-[],8-[]], [1-6,2-3,3-2,5-7,3-2,4-5,1-3], NL). NL = [1-[5],2-[4],3-[],4-[],5-[],6-[],7-[],8-[]]

**edges**(`+Graph, -Edges`)- Unify
`Edges`with all edges appearing in`Graph`. Example:?- edges([1-[3,5],2-[4],3-[],4-[5],5-[]], L). L = [1-3, 1-5, 2-4, 4-5]

**transitive_closure**(`+Graph, -Closure`)- Generate the graph
`Closure`as the transitive closure of`Graph`. Example:?- transitive_closure([1-[2,3],2-[4,5],4-[6]],L). L = [1-[2,3,4,5,6], 2-[4,5,6], 4-[6]]

- [det]
**transpose_ugraph**(`Graph, NewGraph`) - Unify
`NewGraph`with a new graph obtained from`Graph`by replacing all edges of the form V1-V2 by edges of the form V2-V1. The cost is O(`|`

V`|`

*log(`|`

V`|`

)). Notice that an undirected graph is its own transpose. Example:?- transpose([1-[3,5],2-[4],3-[],4-[5], 5-[],6-[],7-[],8-[]], NL). NL = [1-[],2-[],3-[1],4-[2],5-[1,4],6-[],7-[],8-[]]

- Compatibility
- This predicate used to be known as transpose/2. Following SICStus 4, we reserve transpose/2 for matrix transposition and renamed ugraph transposition to transpose_ugraph/2.

**compose**(`+LeftGraph, +RightGraph, -NewGraph`)- Compose
`NewGraph`by connecting the*drains*of`LeftGraph`to the*sources*of`RightGraph`. Example:?- compose([1-[2],2-[3]],[2-[4],3-[1,2,4]],L). L = [1-[4], 2-[1,2,4], 3-[]]

- [semidet]
**top_sort**(`+Graph, -Sorted`) - [semidet]
**top_sort**(`+Graph, -Sorted, ?Tail`) `Sorted`is a topological sorted list of nodes in`Graph`. A toplogical sort is possible if the graph is connected and acyclic. In the example we show how topological sorting works for a linear graph:?- top_sort([1-[2], 2-[3], 3-[]], L). L = [1, 2, 3]

The predicate top_sort/3 is a difference list version of top_sort/2.

- [det]
**neighbors**(`+Vertex, +Graph, -Neigbours`) - [det]
**neighbours**(`+Vertex, +Graph, -Neigbours`) `Neigbours`is a sorted list of the neighbours of`Vertex`in`Graph`. Example:?- neighbours(4,[1-[3,5],2-[4],3-[], 4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL). NL = [1,2,7,5]

- [det]
**connect_ugraph**(`+UGraphIn, -Start, -UGraphOut`) - Adds
`Start`as an additional vertex that is connected to all vertices in`UGraphIn`. This can be used to create an topological sort for a not connected graph.`Start`is before any vertex in`UGraphIn`in the standard order of terms. No vertex in`UGraphIn`can be a variable.Can be used to order a not-connected graph as follows:

top_sort_unconnected(Graph, Vertices) :- ( top_sort(Graph, Vertices) -> true ; connect_ugraph(Graph, Start, Connected), top_sort(Connected, Ordered0), Ordered0 = [Start|Vertices] ).

**complement**(`+UGraphIn, -UGraphOut`)`UGraphOut`is a ugraph with an edge between all vertices that are*not*connected in`UGraphIn`and all edges from`UGraphIn`removed. Example:?- complement([1-[3,5],2-[4],3-[], 4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL). NL = [1-[2,4,6,7,8],2-[1,3,5,6,7,8],3-[1,2,4,5,6,7,8], 4-[3,5,6,8],5-[1,2,3,4,6,7,8],6-[1,2,3,4,5,7,8], 7-[1,2,3,4,5,6,8],8-[1,2,3,4,5,6,7]]

- To be done
- Simple two-step algorithm. You could be smarter, I suppose.

**reachable**(`+Vertex, +UGraph, -Vertices`)- True when
`Vertices`is an ordered set of vertices reachable in`UGraph`, including`Vertex`. Example:?- reachable(1,[1-[3,5],2-[4],3-[],4-[5],5-[]],V). V = [1, 3, 5]

Tags are associated to your profile if you are logged in

Tags: