Directionality: Controlling edge directionality

In multinet: Analysis and mining of multilayer social networks

Controlling edge directionality

Description

Functions to get and set the edge directionality of one or more pairs of layers (that is, the directionality of edges connecting nodes in those layers).

Usage

set_directed_ml(n, directionalities)
is_directed_ml(n, layers1 = character(0), layers2 = character(0))

Arguments

n	A multilayer network.
directionalities	A dataframe with three columns where each row contains a pair of layers (l1,l2) and 0 or 1 (indicating resp. undirected and directed edges). Directionality is automatically set for both (l1,l2) and (l2,l1).
layers1	The layer(s) from where the edges start. If layers1 is not provided, all layers are considered.
layers2	The layer(s) where the edges end. If an empty list of layers is passed (default), the ending layers are set as equal to those in parameter layers1.

Value

is_directed_ml returns a data frame where each row contains the name of two layers and the corresponding type of edges (directed/undirected).

See Also

multinet.properties, multinet.attributes

Examples

net <- ml_empty()
# Adding some layers, one directed and one undirected
add_layers_ml(net,c("l1","l2"),c(TRUE,FALSE))
# Setting the directionality of inter-layer edges
layers = c("l1","l2")
dir <- data.frame(layers,layers,c(0,1))
set_directed_ml(net,dir)
# retrieving all directionalities
dir <- is_directed_ml(net)
# copying directionalities to a new network
net2 <- ml_empty()
add_layers_ml(net2,c("l1","l2"))
set_directed_ml(net2,dir)

multinet documentation built on Feb. 16, 2023, 10:57 p.m.