A matching in a graph means the selection of a set of edges that are pairwise non-adjacent, i.e. they have no common incident vertices. A matching is maximal if it is not a proper subset of any other matching.
is_matching(graph, matching, types = NULL)
is_max_matching(graph, matching, types = NULL)
max_bipartite_match(
graph,
types = NULL,
weights = NULL,
eps = .Machine$double.eps
)
The input graph. It might be directed, but edge directions will be ignored.
A potential matching. An integer vector that gives the
pair in the matching for each vertex. For vertices without a pair,
supply NA
here.
Vertex types, if the graph is bipartite. By default they
are taken from the ‘type
’ vertex attribute, if present.
Potential edge weights. If the graph has an edge
attribute called ‘weight
’, and this argument is
NULL
, then the edge attribute is used automatically.
In weighted matching, the weights of the edges must match as
much as possible.
A small real number used in equality tests in the weighted
bipartite matching algorithm. Two real numbers are considered equal in
the algorithm if their difference is smaller than eps
. This is
required to avoid the accumulation of numerical errors. By default it is
set to the smallest \(x\), such that \(1+x \ne 1\)
holds. If you are running the algorithm with no weights, this argument
is ignored.
is_matching()
and is_max_matching()
return a logical
scalar.
max_bipartite_match()
returns a list with components:
The size of the matching, i.e. the number of edges connecting the matched vertices.
The weights of the matching, if the graph was weighted. For unweighted graphs this is the same as the size of the matching.
The matching itself. Numeric vertex id, or vertex
names if the graph was named. Non-matched vertices are denoted by
NA
.
is_matching()
checks a matching vector and verifies whether its
length matches the number of vertices in the given graph, its values are
between zero (inclusive) and the number of vertices (inclusive), and
whether there exists a corresponding edge in the graph for every matched
vertex pair. For bipartite graphs, it also verifies whether the matched
vertices are in different parts of the graph.
is_max_matching()
checks whether a matching is maximal. A matching
is maximal if and only if there exists no unmatched vertex in a graph
such that one of its neighbors is also unmatched.
max_bipartite_match()
calculates a maximum matching in a bipartite
graph. A matching in a bipartite graph is a partial assignment of
vertices of the first kind to vertices of the second kind such that each
vertex of the first kind is matched to at most one vertex of the second
kind and vice versa, and matched vertices must be connected by an edge
in the graph. The size (or cardinality) of a matching is the number of
edges. A matching is a maximum matching if there exists no other
matching with larger cardinality. For weighted graphs, a maximum
matching is a matching whose edges have the largest possible total
weight among all possible matchings.
Maximum matchings in bipartite graphs are found by the push-relabel algorithm with greedy initialization and a global relabeling after every \(n/2\) steps where \(n\) is the number of vertices in the graph.
Other structural.properties:
bfs()
,
component_distribution()
,
connect()
,
constraint()
,
coreness()
,
degree()
,
dfs()
,
distance_table()
,
edge_density()
,
feedback_arc_set()
,
girth()
,
is_acyclic()
,
is_dag()
,
k_shortest_paths()
,
knn()
,
reciprocity()
,
subcomponent()
,
subgraph()
,
topo_sort()
,
transitivity()
,
unfold_tree()
,
which_multiple()
,
which_mutual()
g <- graph_from_literal(a - b - c - d - e - f)
m1 <- c("b", "a", "d", "c", "f", "e") # maximal matching
m2 <- c("b", "a", "d", "c", NA, NA) # non-maximal matching
m3 <- c("b", "c", "d", "c", NA, NA) # not a matching
is_matching(g, m1)
#> [1] TRUE
is_matching(g, m2)
#> [1] TRUE
is_matching(g, m3)
#> [1] FALSE
is_max_matching(g, m1)
#> [1] TRUE
is_max_matching(g, m2)
#> [1] FALSE
is_max_matching(g, m3)
#> [1] FALSE
V(g)$type <- rep(c(FALSE, TRUE), 3)
print_all(g, v = TRUE)
#> IGRAPH 428e35c UN-B 6 5 --
#> + attr: name (v/c), type (v/l)
#> + vertex attributes:
#> | name type
#> | [1] a FALSE
#> | [2] b TRUE
#> | [3] c FALSE
#> | [4] d TRUE
#> | [5] e FALSE
#> | [6] f TRUE
#> + edges from 428e35c (vertex names):
#> [1] a--b b--c c--d d--e e--f
max_bipartite_match(g)
#> $matching_size
#> [1] 3
#>
#> $matching_weight
#> [1] 3
#>
#> $matching
#> a b c d e f
#> "b" "a" "d" "c" "f" "e"
#>
g2 <- graph_from_literal(a - b - c - d - e - f - g)
V(g2)$type <- rep(c(FALSE, TRUE), length.out = vcount(g2))
print_all(g2, v = TRUE)
#> IGRAPH a411060 UN-B 7 6 --
#> + attr: name (v/c), type (v/l)
#> + vertex attributes:
#> | name type
#> | [1] a FALSE
#> | [2] b TRUE
#> | [3] c FALSE
#> | [4] d TRUE
#> | [5] e FALSE
#> | [6] f TRUE
#> | [7] g FALSE
#> + edges from a411060 (vertex names):
#> [1] a--b b--c c--d d--e e--f f--g
max_bipartite_match(g2)
#> $matching_size
#> [1] 3
#>
#> $matching_weight
#> [1] 3
#>
#> $matching
#> a b c d e f g
#> "b" "a" "d" "c" "f" "e" NA
#>
#' @keywords graphs