migraph (version 0.8.13)

coercion: Coercion between graph/network/edgelist/matrix object classes

Description

The as_ functions in {migraph} coerce objects between several common classes of social network objects. These include:

• edgelists, as data frames or tibbles

• adjacency and incidence matrices

• {igraph} graph objects

• {tidygraph} tbl_graph objects

• {network} network objects

Usage

as_edgelist(object, weight = FALSE)
as_matrix(object, weight = FALSE)
as_igraph(object, weight = FALSE, twomode = FALSE)
as_tidygraph(object, twomode = FALSE)
as_network(object)

Arguments

object

A data frame edgelist, matrix, igraph, tidygraph, or network object.

weight

An option to override the heuristics for distinguishing weighted networks. By default FALSE.

twomode

An option to override the heuristics for distinguishing incidence from adjacency matrices. By default FALSE.

Value

The currently implemented coercions or translations are:

to/from	edgelists	matrices	igraph	tidygraph	network
edgelists (data frames)		X	X	X	X
matrices	X	X	X	X	X
igraph	X	X	X	X	X
tidygraph	X	X	X	X	X
network	X	X	X	X	X

Details

An effort is made for all of these coercion routines to be as lossless as possible, though some object classes are better at retaining certain kinds of information than others. Note also that there are some reserved column names in one or more object classes, which could otherwise lead to some unexpected results.

Behaviour is a little different depending on the data format.

If the data frame is a 2 column edgelist, the first column will become the rows and the second column will become the columns. If the data frame is a 3 column edgelist, then the third column will be used as the cell values or tie weights.

Incidence matrices are typically inferred from unequal dimensions, but since in rare cases a matrix with equal dimensions may still be an incidence matrix, an additional argument twomode can be specified to override this heuristic. This information is usually already embedded in {igraph}, {tidygraph}, and {network} objects.

See Also

Other manipulation: is(), project, to

Examples

# NOT RUN {
test <- data.frame(id1 = c("A","B","B","C","C"),
                   id2 = c("I","G","I","G","H"))
as_matrix(test)
as_igraph(test)
as_tidygraph(test)
as_network(test)
# }