multinet.transformation | R Documentation |
These functions merge multiple layers into one. The new layer is added to the network. If the input layers are no longer necessary, they must be explicitely erased.
flatten_ml
adds a new layer with the actors in the input layers and an edge between A and B if they are connected in any of the merged layers.
project_ml
adds a new layer with the actors in the first input layer and an edge between A and B if they are connected to the same actor in the second layer.
flatten_ml(n, new.layer = "flattening", layers = character(0),
method = "weighted", force.directed = FALSE, all.actors = FALSE)
project_ml(n, new.layer = "projection", layer1, layer2,
method = "clique")
n |
A multilayer network. |
new.layer |
Name of the new layer. |
layers |
An array of layers belonging to the network. |
layer1 |
Name of a layer belonging to the network. |
layer2 |
Name of a layer belonging to the network. |
method |
This argument can take values "weighted" or "or" for |
force.directed |
The new layer is set as directed. If this is false, the new layer is set as directed if at least one of the merged layers is directed. |
all.actors |
If TRUE, then all the actors are included in the new layer, even if they are not present in any of the merged layers. |
These functions return no value: they modify the input network.
Dickison, Magnani, and Rossi, 2016. Multilayer Social Networks. Cambridge University Press. ISBN: 978-1107438750
multinet.conversion
net <- ml_aucs()
# A new layer is added to the network, with a flattening of all the other layers
flatten_ml(net, layers = layers_ml(net))
# Bipartite network
from_actor=c("A","B")
to_actor=c("1","1")
from_layer=c("l1","l1")
to_layer=c("l2","l2")
edges = data.frame(from_actor, from_layer, to_actor, to_layer)
n = ml_empty()
add_edges_ml(n, edges)
project_ml(n, layer1 = "l1", layer2="l2")
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