combine_networks {ergm.multi}

A single block-diagonal network created by combining multiple networks

Description

Given a list of compatible networks, the combine_networks() returns a single block-diagonal network, preserving attributes that can be preserved.

Usage

combine_networks(
  nwl,
  ignore.nattr = c("mnext"),
  ignore.vattr = c(),
  ignore.eattr = c(),
  blockID.vattr = ".NetworkID",
  blockName.vattr = NULL,
  detect.edgecov = FALSE,
  keep.unshared.attr = FALSE,
  subnet.cache = FALSE
)

## S3 method for class 'combined_networks'
print(x, ...)

## S3 method for class 'combined_networks'
summary(object, ...)

## S3 method for class 'summary.combined_networks'
print(x, ...)

Arguments

nwl

a list of network::networks to be combined; they must have similar fundamental properties: directedness and bipartedness, though their sizes (and the size of each bipartite group) can vary.

ignore.nattr, ignore.vattr, ignore.eattr

network, vertex, and edge attributes not to be processed as described below.

blockID.vattr

name of the vertex attribute into which to store the index of the network to which that vertex originally belonged.

blockName.vattr

if not NULL, the name of the vertex attribute into which to store the name of the network to which that vertex originally belonged.

detect.edgecov

if TRUE, combine network attributes that look like dyadic covariate (ergm::edgecov) matrices into a block-diagonal matrix.

keep.unshared.attr

whether to keep those network, vertex, and edge attributes not shared by all networks in the list; if TRUE, positions corresponding to networks lacking the attribute are replaced with NA, NULL, or some other placeholder; incompatible with detect.edgecov==TRUE.

subnet.cache

whether to save the input network list as an attribute of the combined network, so that if the network is resplit using on the same attribute (e.g. using uncombine_network()), an expensive call to split.network() can be avoided, at the cost of storage.

x, object

a combined network.

...

additional arguments to methods.

Value

an object of class combined_networks inheriting from network::network with a block-diagonal structure (or its bipartite equivalent) comprising the networks passed in nwl. In particular,

• the returned network's size is the sum of the input networks';

• its basic properties (directedness and bipartednes) are the same;

• the input networks' sociomatrices (both edge presence and edge attributes) are the blocks in the sociomatrix of the returned network;

• vertex attributes are concatenated;

• edge attributes are assigned to their respective edges in the returned network;

• network attributes are stored in a list; but if detect.edgecov==TRUE, those network attributes that have the same dimension as the sociomatrices of the constituent networks, they are combined into a single block-diagonal matrix that is then stored as that attribute.

In addition, two new vertex attributes, specified by blockID.vattr and (optionally) blockName.vattr contain, respectively, the index in nwl of the network from which that vertex came and its name, determined as follows:

1. If nwl is a named list, names from the list are used.

2. If not 1, but the network has an attribute title, it is used.

3. Otherwise, a numerical index is used.

If blockID.vattr already exists on the constituent networks, the index is prepended to the attribute.

The values of blockID.vattr and blockName.vattr are stored in network attributes ".blockID.vattr" and ".blockName.vattr".

Functions

• print(combined_networks): A wrapper around network::print.network() to print constituent network information and omit some internal variables.

• summary(combined_networks): A wrapper around network::summary.network() to print constituent network information and omit some internal variables.

• print(summary.combined_networks): A wrapper around network::print.summary.network() to print constituent network information and omit some internal variables.

Examples

data(samplk)

o1 <- combine_networks(list(samplk1, samplk2, samplk3))
image(as.matrix(o1))
head(get.vertex.attribute(o1, ".NetworkID"))
o2 <- combine_networks(list(o1, o1))
image(as.matrix(o2))
head(get.vertex.attribute(o2, ".NetworkID", unlist=FALSE))

data(florentine)
f1 <- combine_networks(list(business=flobusiness, marriage=flomarriage),
                       blockName.vattr=".NetworkName")
image(as.matrix(f1))
head(get.vertex.attribute(f1, ".NetworkID"))
head(get.vertex.attribute(f1, ".NetworkName"))