generatelatencies: Generates vector-clock latencies for each individual at each...

In bblonder/timeordered: Time-Ordered and Time-Aggregated Network Analyses

Generates vector-clock latencies for each individual at each time.

Description

Vector clock latencies describe the minimum time delay between one individual broadcasting a signal and another individual receiving it, at a given time, through any causally permitted path in the time-ordered network. Smaller values indicate individuals that are connected by shorter causally-permitted paths at a given time.

Usage

generatelatencies(raw, allindivs)

Arguments

raw	An event list, consisting of a data frame with four columns: VertexFrom, VertexTo, TimeStart, and TimeStop. Each row in this data frame represents a single directed interaction event between VertexFrom and VertexTo beginning at TimeStart and ending at TimeStop. Assumes that no event begins at a time less than zero.
allindivs	A list of all possible vertices including ones not observed interacting during the range of time reported in raw.

Value

A n x n x m array, where n is the number of vertices and m is the maximum start time in the raw event list. The [i,j,k] entry of the array describes the latency from i to j at time k. NA is returned if there is not causally permitted path between i and j by time k.

Note

Return value can require large memory allocation depending on the data set. Ensure that data contains no times < 0 before running.

Author(s)

Benjamin Blonder [e-mail].

References

Kossinets et al. The structure of information pathways in a social communication network. KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (2008)

Examples

data(ants)
allindivs <- c(union(ants$VertexFrom, ants$VertexTo), "NULL1", "NULL2")
l <- generatelatencies(ants, allindivs)
image(l[,,1000],axes=FALSE,frame=TRUE,col=rainbow(100))
axis(1, at = (1:ncol(l))/ncol(l), labels=colnames(l),tick=FALSE,las=2,cex.axis=0.2)
axis(2, at = (1:nrow(l))/nrow(l), labels=rownames(l),tick=FALSE,las=2,cex.axis=0.2)

bblonder/timeordered documentation built on Aug. 29, 2023, 9:15 a.m.