| network | R Documentation |
diffnet, network and networkDynamicCoercion between diffnet, network and networkDynamic
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
)
graph |
An object of class |
slices |
An integer vector indicating the slices to subset |
... |
Further arguments passed to |
diffnet2net.args |
List of arguments passed to |
netdyn.args |
List of arguments passed to |
toavar |
Character scalar. Name of the vertex attribute that holds the times of adoption. |
graph.list |
A list of |
t0 |
Integer scalar. Passed to |
t1 |
Integer scalar. Passed to |
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.
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.
Since diffnet does not support edges attributes, these will be lost when
converting from network-type objects. The same applies to network
attributes.
Other Foreign:
igraph,
read_pajek(),
read_ucinet_head()
# 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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