NAME

Graph - graph data structures and algorithms

SYNOPSIS

	use Graph;
	my $g0 = Graph->new;             # A directed graph.

	use Graph::Directed;
	my $g1 = Graph::Directed->new;   # A directed graph.

	use Graph::Undirected;
	my $g2 = Graph::Undirected->new; # An undirected graph.

        $g->add_edge(...);
        $g->has_edge(...)
        $g->delete_edge(...);

        $g->add_vertex(...);
        $g->has_vertex(...);
        $g->delete_vertex(...);

        $g->vertices(...)
        $g->edges(...)

        # And many, many more, see below.

DESCRIPTION

Non-Description

This module is not for drawing any sort of graphics, business or otherwise.

Description

Instead, this module is for creating abstract data structures called graphs, and for doing various operations on those.

Perl 5.6.0 minimum

The implementation depends on a Perl feature called "weak references" and Perl 5.6.0 was the first to have those.

Constructors

new

Create an empty graph.

Graph->new(%options)

The options are a hash with option names as the hash keys and the option values as the hash values.

The following options are available:

directed

A boolean option telling that a directed graph should be created. Often somewhat redundant because a directed graph is the default for the Graph class or one could simply use the new() constructor of the Graph::Directed class.

You can test the directness of a graph with $g->is_directed() and $g->is_undirected().
undirected

A boolean option telling that an undirected graph should be created. One could also use the new() constructor the Graph::Undirected class instead.

Note that while often it is possible to think undirected graphs as bidirectional graphs, or as directed graphs with edges going both ways, in this module directed graphs and undirected graphs are two different things that often behave differently.

You can test the directness of a graph with $g->is_directed() and $g->is_undirected().
refvertexed

If you want to use references (including Perl objects) as vertices.
unionfind

If the graph is undirected, you can specify the unionfind parameter to use the so-called union-find scheme to speed up the computation of connected components of the graph (see "is_connected", "connected_components", "connected_component_by_vertex", "connected_component_by_index", and "same_connected_components"). If unionfind is used, adding edges (and vertices) becomes slower, but connectedness queries become faster. You can test a graph for "union-findness" with
has_union_find
```
has_union_find
```
vertices

An array reference of vertices to add.
edges

An array reference of array references of edge vertices to add.

copy

copy_graph

my $c = $g->copy_graph;

Create a shallow copy of the structure (vertices and edges) of the graph. If you want a deep copy that includes attributes, see "deep_copy". The copy will have the same directedness as the original.

deep_copy

deep_copy_graph

my $c = $g->deep_copy_graph;

Create a deep copy of the graph (vertices, edges, and attributes) of the graph. If you want a shallow copy that does not include attributes, see "copy". (Uses Data::Dumper behind the scenes. Note that copying code references only works with Perls 5.8 or later, and even then only if B::Deparse can reconstruct your code.)

undirected_copy

undirected_copy_graph

my $c = $g->undirected_copy_graph;

Create an undirected shallow copy (vertices and edges) of the directed graph so that for any directed edge (u, v) there is an undirected edge (u, v).

directed_copy

directed_copy_graph

my $c = $g->directed_copy_graph;

Create a directed shallow copy (vertices and edges) of the undirected graph so that for any undirected edge (u, v) there are two directed edges (u, v) and (v, u).

transpose

transpose_graph

my $t = $g->transpose_graph;

Create a directed shallow transposed copy (vertices and edges) of the directed graph so that for any directed edge (u, v) there is a directed edge (v, u).

You can also transpose a single edge with

transpose_edge

$g->transpose_edge($u, $v)

complete_graph

complete

my $c = $g->complete_graph;

Create a complete graph that has the same vertices as the original graph. A complete graph has an edge between every pair of vertices.

complement_graph

complement

my $c = $g->complement_graph;

Create a complement graph that has the same vertices as the original graph. A complement graph has an edge (u,v) if and only if the original graph does not have edge (u,v).

See also "random_graph" for a random constructor.

Basics

add_vertex

$g->add_vertex($v)

Add the vertex to the graph. Returns the graph.

By default idempotent, but a graph can be created countvertexed.

A vertex is also known as a node.

add_edge

$g->add_edge($u, $v)

Add the edge to the graph. Implicitly first adds the vertices if the graph does not have them. Returns the graph.

By default idempotent, but a graph can be created countedged.

An edge is also known as an arc.

has_vertex

$g->has_vertex($v)

Return true if the vertex exists in the graph, false otherwise.

has_edge

$g->has_edge($u, $v)

Return true if the edge exists in the graph, false otherwise.

delete_vertex

$g->delete_vertex($v)

Delete the vertex from the graph. Returns the graph, even if the vertex did not exist in the graph.

If the graph has been created multivertexed or countvertexed and a vertex has been added multiple times, the vertex will require at least an equal number of deletions to become completely deleteted.

delete_vertices

$g->delete_vertices($v1, $v2, ...)

Delete the vertices from the graph. Returns the graph.

delete_edge

$g->delete_edge($u, $v)

Delete the edge from the graph. Returns the graph, even if the edge did not exist in the graph.

If the graph has been created multivertexed or countedged and an edge has been added multiple times, the edge will require at least an equal number of deletions to become completely deleted.

delete_edges

$g->delete_edges($u1, $v1, $u2, $v2, ...)

Delete the edges from the graph. Returns the graph.

If the graph has been created multivertexed or countedged and an edge has been added multiple times, the edge will require at least an equal number of deletions to become completely deleted.

Displaying

Graphs have stringification overload, so you can do things like

print "The graph is $g\n"

One-way (directed, unidirected) edges are shown as '-', two-way (undirected, bidirected) edges are shown as '='. If you want to, you can call the stringification via the method

stringify

Comparing

Testing for equality can be done either by the overloaded eq operator

$g eq "a-b,a-c,d"

or by the method

eq

$g->eq("a-b,a-c,d")

The equality testing compares the stringified forms, and therefore it assumes total equality, not isomorphism: all the vertices must be named the same, and they must have identical edges between them.

For unequality there are correspondingly the overloaded ne operator and the method

ne

Paths and Cycles

Paths and cycles are simple extensions of edges: paths are edges starting from where the previous edge ended, and cycles are paths returning back to the start vertex of the first edge.

add_path

$g->add_path($a, $b, $c, ..., $x, $y, $z)

Add the edges $a-$b, $b-$c, ..., $x-$y, $y-$z to the graph. Returns the graph.

has_path

$g->has_path($a, $b, $c, ..., $x, $y, $z)

Return true if the graph has all the edges $a-$b, $b-$c, ..., $x-$y, $y-$z, false otherwise.

delete_path

$g->delete_path($a, $b, $c, ..., $x, $y, $z)

Delete all the edges edges $a-$b, $b-$c, ..., $x-$y, $y-$z (regardless of whether they exist or not). Returns the graph.

add_cycle

$g->add_cycle($a, $b, $c, ..., $x, $y, $z)

Add the edges $a-$b, $b-$c, ..., $x-$y, $y-$z, and $z-$a to the graph. Returns the graph.

has_cycle

$g->has_cycle($a, $b, $c, ..., $x, $y, $z)

Return true if the graph has all the edges $a-$b, $b-$c, ..., $x-$y, $y-$z, and $z-$a, false otherwise.

NOTE: This does not detect cycles, see "has_a_cycle" and "find_a_cycle".

delete_cycle

$g->delete_cycle($a, $b, $c, ..., $x, $y, $z)

Delete all the edges edges $a-$b, $b-$c, ..., $x-$y, $y-$z, and $z-$a (regardless of whether they exist or not). Returns the graph.

has_a_cycle

$g->has_a_cycle

Returns true if the graph has a cycle, false if not.

find_a_cycle

$g->find_a_cycle

Returns a cycle if the graph has one (as a list of vertices), an empty list if no cycle can be found.

Note that this just returns the vertices of a cycle: not any particular cycle, just the first one it finds. A repeated call might find the same cycle, or it might find a different one, and you cannot call this repeatedly to find all the cycles.

Graph Types

is_simple_graph

$g->is_simple_graph

Return true if the graph has no multiedges, false otherwise.

is_pseudo_graph

$g->is_pseudo_graph

Return true if the graph has any multiedges or any self-loops, false otherwise.

is_multi_graph

$g->is_multi_graph

Return true if the graph has any multiedges but no self-loops, false otherwise.

is_directed_acyclic_graph

is_dag

$g->is_directed_acyclic_graph
$g->is_dag

Return true if the graph is directed and acyclic, false otherwise.

is_cyclic

$g->is_cyclic

Return true if the graph is cyclic (contains at least one cycle). (This is identical to has_a_cycle.)

To find at least that one cycle, see "find_a_cycle".

is_acyclic

Return true if the graph is acyclic (does not contain any cycles).

To find a cycle, use find_a_cycle.

Transitivity

is_transitive

$g->is_transitive

Return true if the graph is transitive, false otherwise.

TransitiveClosure_Floyd_Warshall

transitive_closure

$tcg = $g->TransitiveClosure_Floyd_Warshall

Return the transitive closure graph of the graph.

You can query the reachability from $u to $v with

is_reachable

$tcg->is_reachable($u, $v)

See Graph::TransitiveClosure for more information about creating and querying transitive closures.

With

transitive_closure_matrix

$tcm = $g->transitive_closure_matrix;

you can (create if not existing and) query the transitive closure matrix that underlies the transitive closure graph. See Graph::TransitiveClosure::Matrix for more information.

Mutators

add_vertices

$g->add_vertices('d', 'e', 'f')

Add zero or more vertices to the graph.

add_edges

$g->add_edges(['d', 'e'], ['f', 'g'])

Add zero or more edges to the graph. The edges are specified as a list of array references.

Accessors

is_directed

directed

$g->is_directed()
$g->directed()

Return true if the graph is directed, false otherwise.

is_undirected

undirected

$g->is_undirected()
$g->undirected()

Return true if the graph is undirected, false otherwise.

is_refvertexed

refvertexed

Return true if the graph can handle references (including Perl objects) as vertices.

vertices

my $V = $g->vertices
my @V = $g->vertices

In scalar context, return the number of vertices in the graph. In list context, return the vertices, in no particular order.

has_vertices

$g->has_vertices()

Return true if the graph has any vertices, false otherwise.

edges

my $E = $g->edges
my @E = $g->edges

In scalar context, return the number of edges in the graph. In list context, return the edges, in no particular order. The edges are returned as anonymous arrays listing the vertices.

has_edges

$g->has_edges()

Return true if the graph has any edges, false otherwise.

is_connected

$g->is_connected

For an undirected graph, return true is the graph is connected, false otherwise. Being connected means that from every vertex it is possible to reach every other vertex.

If the graph has been created with a true unionfind parameter, the time complexity is (essentially) O(V), otherwise O(V log V).

For directed graphs, see "is_strongly_connected" and "is_weakly_connected".

connected_components

@cc = $g->connected_components()

For an undirected graph, returns the vertices of the connected components of the graph as a list of anonymous arrays. The ordering of the anonymous arrays or the ordering of the vertices inside the anonymous arrays (the components) is undefined.

For directed graphs, see "strongly_connected_components" and "weakly_connected_components".

connected_component_by_vertex

$i = $g->connected_component_by_vertex($v)

For an undirected graph, return an index identifying the connected component the vertex belongs to, the indexing starting from zero.

For the inverse, see "connected_component_by_index".

If the graph has been created with a true unionfind parameter, the time complexity is (essentially) O(1), otherwise O(V log V).

Degree

A vertex has a degree based on the number of incoming and outgoing edges. This really makes sense only for directed graphs.

degree

vertex_degree

$d = $g->degree($v)
$d = $g->vertex_degree($v)

For directed graphs: the in-degree minus the out-degree at the vertex. For undirected graphs: the number of edges at the vertex.

in_degree

$d = $g->in_degree($v)

The number of incoming edges at the vertex.

out_degree

$o = $g->out_degree($v)

The number of outgoing edges at the vertex.

average_degree

my $ad = $g->average_degree;

Return the average degree taken over all vertices.

Related methods are

edges_at

@e = $g->edges_at($v)

The union of edges from and edges to at the vertex.

edges_from

@e = $g->edges_from($v)

The edges leaving the vertex.

edges_to

@e = $g->edges_to($v)

The edges entering the vertex.

Counted Vertices

Counted vertices are vertices with more than one instance, normally adding vertices is idempotent. To enable counted vertices on a graph, give the countvertexed parameter a true value

use Graph;
my $g = Graph->new(countvertexed => 1);

To find out how many times the vertex has been added:

get_vertex_count

my $c = $g->get_vertex_count($v);

Return the count of the vertex, or undef if the vertex does not exist.

Multiedges, Multivertices, Multigraphs

Multiedges are edges with more than one "life", meaning that one has to delete them as many times as they have been added. Normally adding edges is idempotent (in other words, adding edges more than once makes no difference).

There are two kinds or degrees of creating multiedges and multivertices. The two kinds are mutually exclusive.

The weaker kind is called counted, in which the edge or vertex has a count on it: add operations increase the count, and delete operations decrease the count, and once the count goes to zero, the edge or vertex is deleted. You can think of this as the graph elements being refcounted, or reference counted, if that sounds more familiar.

The stronger kind is called (true) multi, in which the edge or vertex really has multiple separate identities, so that you can for example attach different attributes to different instances.

To enable multiedges on a graph:

use Graph;
my $g0 = Graph->new(countedged => 1);
my $g0 = Graph->new(multiedged => 1);

Similarly for vertices

use Graph;
my $g1 = Graph->new(countvertexed => 1);
my $g1 = Graph->new(multivertexed => 1);

You can test for these by

is_countedged

countedged

$g->is_countedged
$g->countedged

Return true if the graph is countedged.

is_countvertexed

countvertexed

$g->is_countvertexed
$g->countvertexed

Return true if the graph is countvertexed.

is_multiedged

multiedged

$g->is_multiedged
$g->multiedged

Return true if the graph is multiedged.

is_multivertexed

multivertexed

$g->is_multivertexed
$g->multivertexed

Return true if the graph is multivertexed.

A multiedged (either the weak or the strong kind) graph is a multigraph, for which you can test with is_multi_graph().

NOTE: The various graph algorithms do not in general work well with multigraphs, and no effort has been made to test the algorithms with multigraphs.

vertices() and edges() will return the multiple elements: if you want just the unique elements, use

unique_vertices

unique_edges

@uv = $g->unique_vertices; # unique
@mv = $g->vertices;        # possible multiples
@ue = $g->unique_edges;
@me = $g->edges;

If you are using (the stronger kind of) multielements, you should use the by_id variants:

add_vertex_by_id
has_vertex_by_id
delete_vertex_by_id
add_edge_by_id
has_edge_by_id
delete_edge_by_id

$g->add_vertex_by_id($v, $id)
$g->has_vertex_by_id($v, $id)
$g->delete_vertex_by_id($v, $id)

$g->add_edge_by_id($u, $v, $id)
$g->has_edge_by_id($u, $v, $id)
$g->delete_edge_by_id($u, $v, $id)

When you delete the last vertex/edge in a multivertex/edge, the whole vertex/edge is deleted. You can use add_vertex()/add_edge() on a multivertex/multiedge graph, in which case an id is generated automatically. To find out which the generated id was, you need to use

add_vertex_get_id
add_edge_get_id

$idv = $g->add_vertex_get_id($v)
$ide = $g->add_edge_get_id($u, $v)

To return all the ids of vertices/edges in a multivertex/multiedge, use

get_multivertex_ids
get_multiedge_ids

$g->get_multivertex_ids($v)
$g->get_multiedge_ids($u, $v)

The ids are returned in random order.

To find out how many times the edge has been added (this works for either kind of multiedges):

get_edge_count

my $c = $g->get_edge_count($u, $v);

Return the count (the "countedness") of the edge, or undef if the edge does not exist.

The following multi-entity utility functions exist, mirroring the non-multi vertices and edges:

add_weighted_edge_by_id
add_weighted_edges_by_id
add_weighted_path_by_id
add_weighted_vertex_by_id
add_weighted_vertices_by_id
delete_edge_weight_by_id
delete_vertex_weight_by_id
get_edge_weight_by_id
get_vertex_weight_by_id
has_edge_weight_by_id
has_vertex_weight_by_id
set_edge_weight_by_id
set_vertex_weight_by_id

Topological Sort

topological_sort

toposort

my @ts = $g->topological_sort;

Return the vertices of the graph sorted topologically. Note that there may be several possible topological orderings; one of them is returned.

If the graph contains a cycle, a fatal error is thrown, you can either use eval to trap that, or supply the empty_if_cyclic argument with a true value

my @ts = $g->topological_sort(empty_if_cyclic => 1);

in which case an empty array is returned if the graph is cyclic.

Minimum Spanning Trees (MST)

Minimum Spanning Trees or MSTs are tree subgraphs derived from an undirected graph. MSTs "span the graph" (covering all the vertices) using as lightly weighted (hence the "minimum") edges as possible.

MST_Kruskal

$mstg = $g->MST_Kruskal;

Returns the Kruskal MST of the graph.

MST_Prim

$mstg = $g->MST_Prim(%opt);

Returns the Prim MST of the graph.

You can choose the first vertex with $opt{ first_root }.

MST_Dijkstra

minimum_spanning_tree

$mstg = $g->MST_Dijkstra;
$mstg = $g->minimum_spanning_tree;

Aliases for MST_Prim.

Single-Source Shortest Paths (SSSP)

Single-source shortest paths, also known as Shortest Path Trees (SPTs). For either a directed or an undirected graph, return a (tree) subgraph that from a single start vertex (the "single source") travels the shortest possible paths (the paths with the lightest weights) to all the other vertices. Note that the SSSP is neither reflexive (the shortest paths do not include the zero-length path from the source vertex to the source vertex) nor transitive (the shortest paths do not include transitive closure paths). If no weight is defined for an edge, 1 (one) is assumed.

SPT_Dijkstra

$sptg = $g->SPT_Dijkstra($root)
$sptg = $g->SPT_Dijkstra(%opt)

Return as a graph the the single-source shortest paths of the graph using Dijkstra's algorithm. The graph cannot contain negative edges (negative edges cause the algorithm to abort with an error message Graph::SPT_Dijkstra: edge ... is negative).

You can choose the first vertex of the result with either a single vertex argument or with $opt{ first_root }, otherwise a random vertex is chosen.

The result weights of vertices can be retrieved from the result graph by

my $w = $sptg->get_vertex_attribute($v, 'weight');

The predecessor vertex of a vertex in the result graph can be retrieved by

my $u = $sptg->get_vertex_attribute($v, 'p');

("A successor vertex" cannot be retrieved as simply because a single vertex can have several successors. You can first find the neighbors() vertices and then remove the predecessor vertex.)

If you want to find the shortes path between two vertices, see "SP_Dijkstra".

SSSP_Dijkstra

single_source_shortest_paths

Aliases for SPT_Dijkstra.

SP_Dijkstra

@path = $g->SP_Dijkstra($u, $v)

Return the vertices in the shortest path in the graph $g between the two vertices $u, $v. If no path can be found, an empty list is returned.

Uses SPT_Dijkstra().

SPT_Bellman_Ford

$sptg = $g->SPT_Bellman_Ford(%opt)

Return as a graph the single-source shortest paths of the graph using Bellman-Ford's algorithm. The graph can contain negative edges but not negative cycles (negative cycles cause the algorithm to abort with an error message Graph::SPT_Bellman_Ford: negative cycle exists/).

You can choose the first vertex of the result with either a single vertex argument or with $opt{ first_root }, otherwise a random vertex is chosen.

The result weights of vertices can be retrieved from the result graph by

my $w = $sptg->get_vertex_attribute($v, 'weight');

The predecessor vertex of a vertex in the result graph can be retrieved by

my $u = $sptg->get_vertex_attribute($v, 'p');

("A successor vertex" cannot be retrieved as simply because a single vertex can have several successors. You can first find the neighbors() vertices and then remove the predecessor vertex.)

If you want to find the shortes path between two vertices, see "SP_Bellman_Ford".

SSSP_Bellman_Ford

Alias for SPT_Bellman_Ford.

SP_Bellman_Ford

@path = $g->SP_Bellman_Ford($u, $v)

Return the vertices in the shortest path in the graph $g between the two vertices $u, $v. If no path can be found, an empty list is returned.

Uses SPT_Bellman_Ford().

All-Pairs Shortest Paths (APSP)

For either a directed or an undirected graph, return the APSP object describing all the possible paths between any two vertices of the graph. If no weight is defined for an edge, 1 (one) is assumed.

APSP_Floyd_Warshall

all_pairs_shortest_paths

my $apsp = $g->APSP_Floyd_Warshall(...);

Return the all-pairs shortest path object computed from the graph using Floyd-Warshall's algorithm. The length is the sum of weight attribute of the edges along the shortest path. If no weight attribute name is specified explicitly

$g->APSP_Floyd_Warshall(attribute_name => 'height');

the attribute weight is assumed.

If an edge has no defined weight attribute, the value of one is assumed when getting the attribute.

Once computed, you can query the APSP object with

path_length

my $l = $apsp->path_length($u, $v);

Return the length of the shortest path between the two vertices.

path_vertices

my @v = $apsp->path_vertices($u, $v);

Return the list of vertices along the shortest path.

path_predecessor

my $u = $apsp->path_predecessor($v);

Returns the predecessor of vertex $v in the all-pairs shortest paths.

average_path_length

my $apl = $g->average_path_length;

Return the average (shortest) path length over all the vertex pairs of the graph. Note that this recomputes the APSP each time when called.

longest_path

graph_diameter

my @lp = $g->longest_path;
my $lp = $g->longest_path;
my $dm = $g->graph_diameter;

In scalar context return the longest (shortest) path length over all the vertex pairs of the graph. In list context return the vertices along the shortest path. Note that this recomputes the APSP each time when called.

This measure is also known as the graph diameter.

shortest_path

my @sp = $g->shortest_path;
my $sp = $g->shortest_path;

In scalar context return the shortest (shortest) length over all the vertex pairs of the graph. In list context return the vertices along the shortest path. Note that this recomputes the APSP each time when called.

You can walk through the matrix of the shortest paths by using

for_shortest_paths

$n = $g->for_shortest_paths($callback)

The number of shortest paths is returned (this should be equal to V*V). The $callback is a sub reference that receives four arguments: the transitive closure object from Graph::TransitiveClosure, the two vertices, and the index to the current shortest paths (0..V*V-1).

Random

You can either ask for random elements of existing graphs or create random graphs.

random_vertex

my $v = $g->random_vertex;

Return a random vertex of the graph, or undef if there are no vertices.

random_edge

my $e = $g->random_edge;

Return a random edge of the graph as an array reference having the vertices as elements, or undef if there are no edges.

random_successor

my $v = $g->random_successor($v);

Return a random successor of the vertex in the graph, or undef if there are no successors.

random_predecessor

my $u = $g->random_predecessor($v);

Return a random predeceessor of the vertex in the graph, or undef if there are no predeceessors.

random_graph

my $g = Graph->random_graph(%opt);

Construct a random graph. The %opt must contain the vertices argument

vertices => vertices_def

where the vertices_def is one of

an array reference where the elements of the array reference are the vertices
a number N in which case the vertices will be integers 0..N-1

The %opt may have either of the argument edges or the argument edges_fill. Both are used to define how many random edges to add to the graph; edges is an absolute number, while edges_fill is a relative number (relative to the number of edges in a complete graph, C). The number of edges can be larger than C, but only if the graph is countedged. The random edges will not include self-loops. If neither edges nor edges_fill is specified, an edges_fill of 0.5 is assumed.

If you want repeatable randomness (what is an oxymoron?) you can use the random_seed option:

$g = Graph->random_graph(vertices => 10, random_seed => 1234);

As this uses the standard Perl srand(), the usual caveat applies: use it sparingly, and consider instead using a single srand() call at the top level of your application.

The default random distribution of edges is flat, that is, any pair of vertices is equally likely to appear. To define your own distribution, use the random_edge option:

$g = Graph->random_graph(vertices => 10, random_edge => \&d);

where d is a code reference receiving ($g, $u, $v, $p) as parameters, where the $g is the random graph, $u and $v are the vertices, and the $p is the probability ([0,1]) for a flat distribution. It must return a probability ([0,1]) that the vertices $u and $v have an edge between them. Note that returning one for a particular pair of vertices doesn't guarantee that the edge will be present in the resulting graph because the required number of edges might be reached before that particular pair is tested for the possibility of an edge. Be very careful to adjust also edges or edges_fill so that there is a possibility of the filling process terminating.

Attributes

You can attach free-form attributes (key-value pairs, in effect a full Perl hash) to each vertex, edge, and the graph itself.

Note that attaching attributes does slow down some other operations on the graph by a factor of three to ten. For example adding edge attributes does slow down anything that walks through all the edges.

For vertex attributes:

set_vertex_attribute

$g->set_vertex_attribute($v, $name, $value)

Set the named vertex attribute.

If the vertex does not exist, the set_...() will create it, and the other vertex attribute methods will return false or empty.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_vertex_attribute

$value = $g->get_vertex_attribute($v, $name)

Return the named vertex attribute.

has_vertex_attribute

$g->has_vertex_attribute($v, $name)

Return true if the vertex has an attribute, false if not.

delete_vertex_attribute

$g->delete_vertex_attribute($v, $name)

Delete the named vertex attribute.

set_vertex_attributes

$g->set_vertex_attributes($v, $attr)

Set all the attributes of the vertex from the anonymous hash $attr.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_vertex_attributes

$attr = $g->get_vertex_attributes($v)

Return all the attributes of the vertex as an anonymous hash.

get_vertex_attribute_names

@name = $g->get_vertex_attribute_names($v)

Return the names of vertex attributes.

get_vertex_attribute_values

@value = $g->get_vertex_attribute_values($v)

Return the values of vertex attributes.

has_vertex_attributes

$g->has_vertex_attributes($v)

Return true if the vertex has any attributes, false if not.

delete_vertex_attributes

$g->delete_vertex_attributes($v)

Delete all the attributes of the named vertex.

If you are using multivertices, use the by_id variants:

set_vertex_attribute_by_id

get_vertex_attribute_by_id

has_vertex_attribute_by_id

delete_vertex_attribute_by_id

set_vertex_attributes_by_id

get_vertex_attributes_by_id

get_vertex_attribute_names_by_id

get_vertex_attribute_values_by_id

has_vertex_attributes_by_id

delete_vertex_attributes_by_id

$g->set_vertex_attribute_by_id($v, $id, $name, $value)
$g->get_vertex_attribute_by_id($v, $id, $name)
$g->has_vertex_attribute_by_id($v, $id, $name)
$g->delete_vertex_attribute_by_id($v, $id, $name)
$g->set_vertex_attributes_by_id($v, $id, $attr)
$g->get_vertex_attributes_by_id($v, $id)
$g->get_vertex_attribute_values_by_id($v, $id)
$g->get_vertex_attribute_names_by_id($v, $id)
$g->has_vertex_attributes_by_id($v, $id)
$g->delete_vertex_attributes_by_id($v, $id)

For edge attributes:

set_edge_attribute

$g->set_edge_attribute($u, $v, $name, $value)

Set the named edge attribute.

If the edge does not exist, the set_...() will create it, and the other edge attribute methods will return false or empty.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_edge_attribute

$value = $g->get_edge_attribute($u, $v, $name)

Return the named edge attribute.

has_edge_attribute

$g->has_edge_attribute($u, $v, $name)

Return true if the edge has an attribute, false if not.

delete_edge_attribute

$g->delete_edge_attribute($u, $v, $name)

Delete the named edge attribute.

set_edge_attributes

$g->set_edge_attributes($u, $v, $attr)

Set all the attributes of the edge from the anonymous hash $attr.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_edge_attributes

$attr = $g->get_edge_attributes($u, $v)

Return all the attributes of the edge as an anonymous hash.

get_edge_attribute_names

@name = $g->get_edge_attribute_names($u, $v)

Return the names of edge attributes.

get_edge_attribute_values

@value = $g->get_edge_attribute_values($u, $v)

Return the values of edge attributes.

has_edge_attributes

$g->has_edge_attributes($u, $v)

Return true if the edge has any attributes, false if not.

delete_edge_attributes

$g->delete_edge_attributes($u, $v)

Delete all the attributes of the named edge.

If you are using multiedges, use the by_id variants:

set_edge_attribute_by_id

get_edge_attribute_by_id

has_edge_attribute_by_id

delete_edge_attribute_by_id

set_edge_attributes_by_id

get_edge_attributes_by_id

get_edge_attribute_names_by_id

get_edge_attribute_values_by_id

has_edge_attributes_by_id

delete_edge_attributes_by_id

$g->set_edge_attribute_by_id($u, $v, $id, $name, $value)
$g->get_edge_attribute_by_id($u, $v, $id, $name)
$g->has_edge_attribute_by_id($u, $v, $id, $name)
$g->delete_edge_attribute_by_id($u, $v, $id, $name)
$g->set_edge_attributes_by_id($u, $v, $id, $attr)
$g->get_edge_attributes_by_id($u, $v, $id)
$g->get_edge_attribute_values_by_id($u, $v, $id)
$g->get_edge_attribute_names_by_id($u, $v, $id)
$g->has_edge_attributes_by_id($u, $v, $id)
$g->delete_edge_attributes_by_id($u, $v, $id)

For graph attributes:

set_graph_attribute

$g->set_graph_attribute($name, $value)

Set the named graph attribute.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_graph_attribute

$value = $g->get_graph_attribute($name)

Return the named graph attribute.

has_graph_attribute

$g->has_graph_attribute($name)

Return true if the graph has an attribute, false if not.

delete_graph_attribute

$g->delete_graph_attribute($name)

Delete the named graph attribute.

set_graph_attributes

$g->get_graph_attributes($attr)

Set all the attributes of the graph from the anonymous hash $attr.

NOTE: any attributes beginning with an underscore (_) are reserved for the internal use of the Graph module.

get_graph_attributes

$attr = $g->get_graph_attributes()

Return all the attributes of the graph as an anonymous hash.

get_graph_attribute_names

@name = $g->get_graph_attribute_names()

Return the names of graph attributes.

get_graph_attribute_values

@value = $g->get_graph_attribute_values()

Return the values of graph attributes.

has_graph_attributes

$g->has_graph_attributes()

Return true if the graph has any attributes, false if not.

delete_graph_attributes

$g->delete_graph_attributes()

Delete all the attributes of the named graph.

Weighted

As convenient shortcuts the following methods add, query, and manipulate the attribute weight with the specified value to the respective Graph elements.

add_weighted_edge

$g->add_weighted_edge($u, $v, $weight)

add_weighted_edges

$g->add_weighted_edges($u1, $v1, $weight1, ...)

add_weighted_path

$g->add_weighted_path($v1, $weight1, $v2, $weight2, $v3, ...)

add_weighted_vertex

$g->add_weighted_vertex($v, $weight)

add_weighted_vertices

$g->add_weighted_vertices($v1, $weight1, $v2, $weight2, ...)

delete_edge_weight

$g->delete_edge_weight($u, $v)

delete_vertex_weight

$g->delete_vertex_weight($v)

get_edge_weight

$g->get_edge_weight($u, $v)

get_vertex_weight

$g->get_vertex_weight($v)

has_edge_weight

$g->has_edge_weight($u, $v)

has_vertex_weight

$g->has_vertex_weight($v)

set_edge_weight

$g->set_edge_weight($u, $v, $weight)

set_vertex_weight

$g->set_vertex_weight($v, $weight)

Isomorphism

Two graphs being isomorphic means that they are structurally the same graph, the difference being that the vertices might have been renamed or substituted. For example in the below example $g0 and $g1 are isomorphic: the vertices b c d have been renamed as z x y.

$g0 = Graph->new;
$g0->add_edges(qw(a b a c c d));
$g1 = Graph->new;
$g1->add_edges(qw(a x x y a z));

In the general case determining isomorphism is NP-hard, in other words, really hard (time-consuming), no other ways of solving the problem are known than brute force check of of all the possibilities (with possible optimization tricks, of course, but brute force still rules at the end of the day).

A very rough guess at whether two graphs could be isomorphic is possible via the method

could_be_isomorphic

$g0->could_be_isomorphic($g1)

If the graphs do not have the same number of vertices and edges, false is returned. If the distribution of in-degrees and out-degrees at the vertices of the graphs does not match, false is returned. Otherwise, true is returned.

What is actually returned is the maximum number of possible isomorphic graphs between the two graphs, after the above sanity checks have been conducted. It is basically the product of the factorials of the absolute values of in-degrees and out-degree pairs at each vertex, with the isolated vertices ignored (since they could be renamed arbitrarily.) Note that for large graphs the product of these factorials can overflow the maximum presentable number (the floating point number) in the computer and you might get for example Infinity as the result.

Miscellaneous

The "expect" methods can be used to test a graph and croak if the graph is not as expected.

expect_acyclic
expect_dag
expect_directed
expect_multiedged
expect_multivertexed
expect_non_multiedged
expect_non_multivertexed
expect_undirected

Size Requirements

A graph takes up at least 1160 bytes of memory.

A vertex takes up at least 110 bytes of memory.

An edge takes up at least 390 bytes of memory.

(A Perl scalar value takes 16 bytes, or 12 bytes if it's a reference.)

These size approximations are very approximate and optimistic (they are based on total_size() of Devel::Size). In real life many factors affect these numbers, for example how Perl is configured. In practice you can expect at least about 200 bytes per vertex, and twice that for an edge. The numbers are for a 32-bit platform.

Roughly, the above numbers mean that in a megabyte you can fit for example a graph of about 1000 vertices and about 2500 edges.

Hyperedges, hypervertices, hypergraphs

BEWARE: this is a rather thinly tested feature, and the theory is even less so. Do not expect this to stay as it is (or at all) in future releases.

Hyperedges are edges that connect a number of vertices different from the usual two.

Hypervertices are vertices that consist of a number of vertices different from the usual one.

Note that for hypervertices there is an asymmetry: when adding hypervertices, the single vertices are also implicitly added.

Hypergraphs are graphs with hyperedges.

To enable hyperness when constructing Graphs use the hyperedged and hypervertexed attributes:

my $h = Graph->new(hyperedged => 1, hypervertexed => 1);

To add hypervertexes, either explicitly use more than one vertex (or, indeed, no vertices) when using add_vertex()

$h->add_vertex("a", "b")
$h->add_vertex()

or implicitly with array references when using add_edge()

$h->add_edge(["a", "b"], "c")
$h->add_edge()

Testing for existence and deletion of hypervertices and hyperedges works similarly.

To test for hyperness of a graph use the

is_hypervertexed

hypervertexed

$g->is_hypervertexed
$g->hypervertexed

is_hyperedged

hyperedged

$g->is_hyperedged
$g->hyperedged

Since hypervertices consist of more than one vertex:

vertices_at

$g->vertices_at($v)

Return the vertices at the vertex. This may return just the vertex or also other vertices.

NOTE: most usual graph algorithms (and basic concepts) break horribly (or at least will look funny) with hyperthingies.

To go with the concept of undirected in normal (non-hyper) graphs, there is a similar concept of omnidirected (this is my own coinage, "all-directions") for hypergraphs, and you can naturally test for it by

is_omnidirected

omnidirected

is_omniedged

omniedged

$g->is_omniedged

$g->omniedged

$g->is_omnidirected

$g->omnidirected

Return true if the graph is omnidirected (edges have no direction), false if not.

You may be wondering why on earth did I make up this new concept, why didn't the "undirected" work for me? Well, because of this:

$g = Graph->new(hypervertexed => 1, omnivertexed => 1);

That's right, vertices can be omni, too - and that is indeed the default. You can turn it off and then $g->add_vertex(qw(a b)) no more means adding also a vertex qw(b a).

is_omnivertexed
omnivertexed

Another oddity that fell out of the implementation is the uniqueness attribute, that comes naturally in uniqedged and uniqvertexed flavours. It does what it sounds like, to unique or not the vertices participating in edges and vertices. Without too much explanation:

is_uniqedged
uniqedged
is_uniqvertexed
uniqvertexed

Backward compatibility with Graph 0.2

The Graph 0.2 (and 0.2xxxx) had the following features

vertices() always sorted the vertex list, which most of the time is unnecessary and wastes CPU.
edges() returned a flat list where the begin and end vertices of the edges were intermingled: every even index had an edge begin vertex, and every odd index had an edge end vertex. This had the unfortunate consequence of scalar(@e = edges) being twice the number of edges, and complicating any algorithm walking through the edges.
The vertex list returned by edges() was sorted, the primary key being the edge begin vertices, and the secondary key being the edge end vertices.
The attribute API was oddly position dependent and dependent on the number of arguments. Use ..._graph_attribute(), ..._vertex_attribute(), ..._edge_attribute() instead.

In future releases of Graph (any release after 0.50) the 0.2xxxx compatibility will be removed. Upgrade your code now.

If you want to continue using these (mis)features you can use the compat02 flag when creating a graph:

my $g = Graph->new(compat02 => 1);

This will change the vertices() and edges() appropriately. This, however, is not recommended, since it complicates all the code using vertices() and edges(). Instead it is recommended that the vertices02() and edges02() methods are used. The corresponding new style (unsorted, and edges() returning a list of references) methods are called vertices05() and edges05().

To test whether a graph has the compatibility turned on

is_compat02

compat02

$g->is_compat02
$g->compat02

The following are not backward compatibility methods, strictly speaking, because they did not exist before.

edges02: Return the edges as a flat list of vertices, elements at even indices being the start vertices and elements at odd indices being the end vertices.
edges05: Return the edges as a list of array references, each element containing the vertices of each edge. (This is not a backward compatibility interface as such since it did not exist before.)
vertices02: Return the vertices in sorted order.
vertices05: Return the vertices in random order.

For the attributes the recommended way is to use the new API.

Do not expect new methods to work for compat02 graphs.

The following compatibility methods exist:

has_attribute

has_attributes

get_attribute

get_attributes

set_attribute

set_attributes

delete_attribute

delete_attributes

Do not use the above, use the new attribute interfaces instead.

vertices_unsorted

Alias for vertices() (or rather, vertices05()) since the vertices() now always returns the vertices in an unsorted order. You can also use the unsorted_vertices import, but only with a true value (false values will cause an error).

density_limits

my ($sparse, $dense, $complete) = $g->density_limits;

Return the "density limits" used to classify graphs as "sparse" or "dense". The first limit is C/4 and the second limit is 3C/4, where C is the number of edges in a complete graph (the last "limit").

density

my $density = $g->density;

Return the density of the graph, the ratio of the number of edges to the number of edges in a complete graph.

vertex

my $v = $g->vertex($v);

Return the vertex if the graph has the vertex, undef otherwise.

out_edges

in_edges

edges($v)

This is now called edges_at($v).

DIAGNOSTICS

Graph::...Map...: arguments X expected Y ...

If you see these (more user-friendly error messages should have been triggered above and before these) please report any such occurrences, but in general you should be happy to see these since it means that an attempt to call something with a wrong number of arguments was caught in time.
Graph::add_edge: graph is not hyperedged ...

Maybe you used add_weighted_edge() with only the two vertex arguments.
Not an ARRAY reference at lib/Graph.pm ...

One possibility is that you have code based on Graph 0.2xxxx that assumes Graphs being blessed hash references, possibly also assuming that certain hash keys are available to use for your own purposes. In Graph 0.50 none of this is true. Please do not expect any particular internal implementation of Graphs. Use inheritance and graph/vertex/edge attributes instead.

Another possibility is that you meant to have objects (blessed references) as graph vertices, but forgot to use refvertexed (see "refvertexed") when creating the graph.

POSSIBLE FUTURES

A possible future direction is a new graph module written for speed: this may very possibly mean breaking or limiting some of the APIs or behaviour as compared with this release of the module.

What definitely won't happen in future releases is carrying over the Graph 0.2xxxx backward compatibility API.

ACKNOWLEDGEMENTS

All bad terminology, bugs, and inefficiencies are naturally mine, all mine, and not the fault of the below.

Thanks to Nathan Goodman and Andras Salamon for bravely betatesting my pre-0.50 code. If they missed something, that was only because of my fiendish code.

The following literature for algorithms and some test cases:

Algorithms in C, Third Edition, Part 5, Graph Algorithms, Robert Sedgewick, Addison Wesley
Introduction to Algorithms, First Edition, Cormen-Leiserson-Rivest, McGraw Hill
Graphs, Networks and Algorithms, Dieter Jungnickel, Springer

AUTHOR AND COPYRIGHT

Jarkko Hietaniemi jhi@iki.fi

LICENSE

This module is licensed under the same terms as Perl itself.

To install Graph, copy and paste the appropriate command in to your terminal.

cpanm

cpanm Graph

CPAN shell

perl -MCPAN -e shell
install Graph

For more information on module installation, please visit the detailed CPAN module installation guide.

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NAME

SYNOPSIS

DESCRIPTION

Non-Description

Description

Perl 5.6.0 minimum

Constructors

Basics

Displaying

Comparing

Paths and Cycles

Graph Types

Transitivity

Mutators

Accessors

Degree

Counted Vertices

Multiedges, Multivertices, Multigraphs

Topological Sort

Minimum Spanning Trees (MST)

Single-Source Shortest Paths (SSSP)

All-Pairs Shortest Paths (APSP)

Random

Attributes

Weighted

Isomorphism

Miscellaneous

Size Requirements

Hyperedges, hypervertices, hypergraphs

Backward compatibility with Graph 0.2

DIAGNOSTICS

POSSIBLE FUTURES

ACKNOWLEDGEMENTS

AUTHOR AND COPYRIGHT

LICENSE

Module Install Instructions