network: Coercion between `diffnet`, `network` and `networkDynamic`

Description

Coercion between diffnet, network and networkDynamic

Usage

diffnet_to_network(graph, slices = 1:nslices(graph), ...)
diffnet_to_networkDynamic(
  graph,
  slices = 1:nslices(graph),
  diffnet2net.args = list(),
  netdyn.args = list()
)
networkDynamic_to_diffnet(graph, toavar)
network_to_diffnet(
  graph = NULL,
  graph.list = NULL,
  toavar,
  t0 = NULL,
  t1 = NULL
)

Value

diffnet_to_network returns a list of length length(slices) in which each element is a network object corresponding a slice of the graph (diffnet object). The attributes list will include toa (time of adoption).

An object of class networkDynamic.

Arguments

graph: An object of class diffnet
slices: An integer vector indicating the slices to subset
...: Further arguments passed to networkDynamic
diffnet2net.args: List of arguments passed to diffnet_to_network.
netdyn.args: List of arguments passed to networkDynamic
toavar: Character scalar. Name of the vertex attribute that holds the times of adoption.
graph.list: A list of network objects.
t0: Integer scalar. Passed to new_diffnet.
t1: Integer scalar. Passed to new_diffnet.

Caveats

Since diffnet does not support edges attributes, these will be lost when converting from network-type objects. The same applies to network attributes.

Details

diffnet_to_networkDynamic calls diffnet_to_network and uses the output to call networkDynamic, passing the resulting list of network objects as network.list (see networkDynamic).

By default, diffnet_to_networkDynamic passes net.obs.period as


  net.obs.period = list(
    observations = list(range(graph$meta$pers)),
    mode="discrete",
    time.increment = 1,
    time.unit = "step"
  )

By default, networkDynamic_to_diffnet uses the first slice as reference for vertex attributes and times of adoption.

By default, network_to_diffnet uses the first element of graph (a list) as reference for vertex attributes and times of adoption.

Examples

Run this code

# Cohersing a diffnet to a list of networks ---------------------------------
set.seed(1)
ans <- diffnet_to_network(rdiffnet(20, 2))
ans

# and back
network_to_diffnet(graph.list = ans, toavar="toa")

# If it was static, we can use -graph- instead
network_to_diffnet(ans[[1]], toavar="toa")

# A random diffusion network ------------------------------------------------
set.seed(87)
dn  <- rdiffnet(50, 4)
ans <- diffnet_to_networkDynamic(dn)

# and back
networkDynamic_to_diffnet(ans, toavar = "toa")

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