get_network | R Documentation |
Extracts the network object from either a network epidemic model
object generated with netsim
, a network diagnostic
simulation generated with netdx
, or a netsim_dat
object used internally in netsim
. For netdx
or
netsim
with tergmLite == FALSE
, the extracted
network object is a networkDynamic
, which can be
collapsed down to a static network
object with the
collapse
and at
arguments. For netsim
with
tergmLite == TRUE
, the extracted network object is the
final networkLite
, the collapse
argument should be
FALSE
, and the at
argument should be missing. For
netsim_dat
, the collapse
and at
arguments
are not supported, and the network object is either the current
networkLite
(if tergmLite == TRUE
) or the current
networkDynamic
(if tergmLite == FALSE
).
get_network(x, ...)
## S3 method for class 'netdx'
get_network(x, sim = 1, collapse = FALSE, at, ...)
## S3 method for class 'netsim'
get_network(x, sim = 1, network = 1, collapse = FALSE, at, ...)
## S3 method for class 'netsim_dat'
get_network(x, network = 1L, ...)
x |
An |
... |
Additional arguments. |
sim |
Simulation number of extracted network, for |
collapse |
If |
at |
If |
network |
Network number, for |
This function requires that the network object is saved during the network
simulation while running either netsim
or netdx
.
For the former, that is specified by setting the save.network
parameter in control.net
to TRUE
. For the latter, that
is specified with the keep.tnetwork
parameter directly in
netdx
.
For netdx
or netsim
with tergmLite == FALSE
, a
networkDynamic
object (if collapse = FALSE
) or a
static network
object (if collapse = TRUE
). For
netsim
with tergmLite == TRUE
or netsim_dat
with
tergmLite == TRUE
, a networkLite
object. For
netsim_dat
with tergmLite == FALSE
, a
networkDynamic
object.
# Set up network and TERGM formula
nw <- network_initialize(n = 100)
nw <- set_vertex_attribute(nw, "group", rep(1:2, each = 50))
formation <- ~edges
target.stats <- 50
coef.diss <- dissolution_coefs(dissolution = ~offset(edges), duration = 20)
# Estimate the model
est <- netest(nw, formation, target.stats, coef.diss)
# Run diagnostics, saving the networkDynamic objects
dx <- netdx(est, nsteps = 10, nsims = 3, keep.tnetwork = TRUE,
verbose = FALSE)
# Extract the network for simulation 2 from dx object
get_network(dx, sim = 2)
# Extract and collapse the network from simulation 1 at time step 5
get_network(dx, collapse = TRUE, at = 5)
# Parameterize the epidemic model, and simulate it
param <- param.net(inf.prob = 0.3, inf.prob.g2 = 0.15)
init <- init.net(i.num = 10, i.num.g2 = 10)
control <- control.net(type = "SI", nsteps = 10, nsims = 3, verbose = FALSE)
mod <- netsim(est, param, init, control)
# Extract the network for simulation 2 from mod object
get_network(mod, sim = 2)
## Extract and collapse the network from simulation 1 at time step 5
get_network(mod, collapse = TRUE, at = 5)
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