## ----------------------------------------------------------------------------- library(remify) # loading library data(randomREH) # loading data names(randomREH) # objects inside the list 'randomREH' ## ----------------------------------------------------------------------------- head(randomREH$edgelist) ## ----------------------------------------------------------------------------- randomREH$actors ## ----------------------------------------------------------------------------- randomREH$types ## ----------------------------------------------------------------------------- randomREH$origin ## ----------------------------------------------------------------------------- randomREH$omit_dyad[[1]]$time # start and stop time point defining the time window of interest ## ----------------------------------------------------------------------------- randomREH$omit_dyad[[1]]$dyad # dyads to be removed from the time points defined by the interval in `time` ## ----------------------------------------------------------------------------- randomREH$omit_dyad[[2]]$time # start and stop time point defining the time window of interest ## ----------------------------------------------------------------------------- randomREH$omit_dyad[[2]]$dyad # dyads to be removed from the time points defined by the interval in `time` ## ----------------------------------------------------------------------------- edgelist_reh <- remify(edgelist = randomREH$edgelist, directed = TRUE, # events are directed ordinal = FALSE, # model with waiting times model = "tie", # tie-oriented modeling actors = randomREH$actors, types = randomREH$types, riskset = "manual", origin = randomREH$origin, omit_dyad = randomREH$omit_dyad) ## ----------------------------------------------------------------------------- names(edgelist_reh) ## ----------------------------------------------------------------------------- edgelist_reh$M ## ----------------------------------------------------------------------------- edgelist_reh$N ## ----------------------------------------------------------------------------- edgelist_reh$C ## ----------------------------------------------------------------------------- edgelist_reh$D ## ----------------------------------------------------------------------------- head(edgelist_reh$intereventTime) ## ----------------------------------------------------------------------------- head(edgelist_reh$edgelist) ## ----------------------------------------------------------------------------- edgelist_reh$omit_dyad$riskset[,1:10] # printing out the risk set modifications of only the first 10 columns (dyads). A total number of 2 modifications of the risk set are observed (by row) ## ----------------------------------------------------------------------------- edgelist_reh$omit_dyad$time[1:10] # printing out the first 10 time points. We can see that in none of the 10 time points any modification takes place (-1) ## ----------------------------------------------------------------------------- edgelist_reh <- remify(edgelist = randomREH$edgelist, directed = TRUE, # events are directed ordinal = FALSE, # model with waiting times model = "tie", # tie-oriented modeling actors = randomREH$actors, types = randomREH$types, riskset = "active", origin = randomREH$origin) ## ----------------------------------------------------------------------------- names(attributes(edgelist_reh)) ## ----------------------------------------------------------------------------- attr(edgelist_reh, "names") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "class") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "with_type") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "weighted") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "directed") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "ordinal") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "model") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "riskset") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "dictionary") ## ----------------------------------------------------------------------------- str(attr(edgelist_reh, "origin")) # printing out only the str() of the attribute since the data.frame `value` is large ## ----------------------------------------------------------------------------- attr(edgelist_reh, "ncores") ## ----------------------------------------------------------------------------- attr(edgelist_reh, "dyadID")[[1]] # printing out dyads ID's observed at the first time point ## ----------------------------------------------------------------------------- attr(edgelist_reh, "actor1ID")[[1]] # printing out the actor1's/senders ID's observed at the first time point ## ----------------------------------------------------------------------------- attr(edgelist_reh, "actor2ID")[[1]] # printing out the actor2's/receivers ID's observed at the first time point ## ----------------------------------------------------------------------------- attr(edgelist_reh, "typeID")[[1]] # printing out the types ID's observed at the first time point ## ----------------------------------------------------------------------------- attr(edgelist_reh, "dyadIDactive")[[1]] # printing out the ID's of the active dyads at the first time point ## ----------------------------------------------------------------------------- time_points <- c(4,10,10,10,10,10) waiting_times <- diff(time_points) # waiting_times: [1] 6 0 0 0 0 calculated as t[m]-t[m-1] ## ----------------------------------------------------------------------------- rep(waiting_times[1]/5,5)# 5 is the number of events in the example observed at the same time (10) ## ----------------------------------------------------------------------------- time_points <- c(4,10,10,10,10,10) diff(time_points) # waiting times calculated as t[m]-t[m-1] which(diff(time_points)==0) # indices of simultaneous events, excluding the first simultaneous event ## ----------------------------------------------------------------------------- # attr(edgelist_reh, "evenly_spaced_interevent_time") # attr(edgelist_reh, "indices_simultaneous_events") ## ----------------------------------------------------------------------------- summary(edgelist_reh) # same output as `print(edgelist_reh)` or just `edgelist_reh` ## ----------------------------------------------------------------------------- dim(edgelist_reh) ## ----------------------------------------------------------------------------- getRiskset(x = edgelist_reh)$riskset[,1:10] # printing out the risk set modifications of only the first 10 columns (dyads). A total number of 2 modifications of the risk set are observed (by row) ## ----------------------------------------------------------------------------- getActorName(x = edgelist_reh, actorID = c(1,13,20)) ## ----------------------------------------------------------------------------- getTypeName(x = edgelist_reh, typeID = c(1,3)) ## ----------------------------------------------------------------------------- getDyad(x = edgelist_reh, dyadID = c(1,10,100), active = FALSE) ## ----------------------------------------------------------------------------- getActorID(x = edgelist_reh, actorName = c("Michaela","Alexander","Lexy")) ## ----------------------------------------------------------------------------- getTypeID(x = edgelist_reh, typeName = "cooperation") ## ----------------------------------------------------------------------------- getDyadID(x = edgelist_reh, actor1 = "Alexander", actor2 = "Charles", type = "cooperation") ## ----out.width="50%", fig.align = "center", dev=c("jpeg")--------------------- op <- par(no.readonly = TRUE) par(mai=rep(0.8,4), cex.main=0.9, cex.axis=0.75) plot(x=edgelist_reh,which=1,n_intervals=13) # histogram of inter-event times plot(x=edgelist_reh,which=2,n_intervals=13) # tile plot (counts of dyadic events) with in-/out- degree of actors on the sides plot(x=edgelist_reh,which=3,n_intervals=13) # (normalized) in-degree and out-degree of actors plot(x=edgelist_reh,which=4,n_intervals=13) # per time interval: number of events, proportion of observed dyads, proportion of active senders and active receivers plot(x=edgelist_reh,which=5,n_intervals=13,igraph.edge.color="#cfcece",igraph.vertex.color="#7bbfef") # networks par(op) ## ----------------------------------------------------------------------------- edgelist_reh <- remify(edgelist = randomREH$edgelist, directed = FALSE, # events are now considered undirected model = "tie") #op <- par(no.readonly = TRUE) #par(mai, rep(0.8,4), cex.main=0.9, cex.axis=0.75) #plot(x=edgelist_reh,which=1:5,n_intervals=13) #par(op)