Obtain a list of collapsed networks sampled periodically from a networkDynamic object
Given a start time, end time, and increment (or vectors of onsets and termini) to express sampling intervals, return a list of collapsed networks from a networkDynamic object.
get.networks(dnet, start = NULL, end = NULL, time.increment = NULL,
onsets=NULL, termini=NULL,...)dnet |
A |
start |
numeric value giving the start of the sampling interval |
end |
numeric value giving the end of the sampling interval |
time.increment |
value for the offset (and duration) between sucessive samples. Will default to 1 if not otherwise specified |
onsets |
A numeric vector containing the onset times of the networks to be extracted. This must be accompanied by |
termini |
A numeric vector containing the terminus times of the networks to be extracted. This must be accompanied by |
... |
Additional arguments to |
The sampling ("slicing") intervals may be defined using either the start, end, and time.increment parameters, or by providing parallel vectors of onsets and termini. If values are not specefied but a net.obs.period attribute exists to describe the 'natural' sampling parameters, start and end will defult to the max an min of the observations element, with time.increment set to its corresponding value in the net.obs.period.
A list of static network objects corresponding to the specified sampling intervals of the networkDynamic
See Note in network.collapse.
Kirk Li, Skye Bender-deMoll
See Also as network.collapse for obtaining a slice of static network, network.extract for extracting sub-ranges of a networkDynamic, get.vertex.attribute.active for more on TEA attributes, and as.network.networkDynamic for stripping the the networkDynamic class from an object.
# create a networkDynamic with some basic activity and time extended attributes (TEA) test <- network.initialize(5) add.edges.active(test, tail=c(1,2,3), head=c(2,3,4),onset=0,terminus=1) activate.edges(test,onset=3,terminus=5) activate.edges(test,onset=-2,terminus=-1) activate.edge.attribute(test,'weight',5,onset=3,terminus=4) activate.edge.attribute(test,'weight',3,onset=4,terminus=5,e=1:2) # obtain the list of networks list <- get.networks(test,start=0, end=5) # aggregate over a longer time period with specified rule list <- get.networks(test,start=0, end=6,time.increment=2,rule='latest') # use 'at' style extraction of momentary slices via onsets & termini list <- get.networks(test,onsets=0:5,termini=0:5) # ensure that all networks returned will be the same size list <- get.networks(test,onsets=0:5,termini=0:5,retain.all.vertices=TRUE) # find out how many edges in each sampling point with apply sapply(get.networks(test,start=0,end=5),network.edgecount) # generate a list of matrices lapply(get.networks(test,start=0,end=5),as.matrix)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.