nlevels by nlevels matrix indicating the
number of individuals that lie within each cell, and draws a heatmap.plot_infectsuscep(graph, toa, t0 = NULL, normalize = TRUE, K = 1L,
r = 0.5, expdiscount = FALSE, bins = 50, nlevels = round(bins/2),
logscale = TRUE,
main = "Distribution of Infectiousness and\nSusceptibility",
xlab = "Infectiousness of ego", ylab = "Susceptibility of ego",
sub = ifelse(logscale, "(in log-scale)", NA), color.palette = function(n)
grey(n:1/n), include.grid = TRUE, exclude.zeros = FALSE,
valued = getOption("diffnet.valued", FALSE), ...)netdiffuseR-graphs).toa_mat.filled.contour).filled.contour).logscale=TRUE.filled.contour.filled.contour (see grid_distribution)TRUE when the case was included in
the plot. (this is relevant whenever logscale=TRUE)infection and
susceptibility.Other visualizations: hazard_rate,
plot_adopters, plot_diffnet,
plot_threshold
# Generating a random graph
set.seed(1234)
n <- 100
nper <- 20
graph <- rgraph_er(n,nper, p=.2, undirected = FALSE)
toa <- sample(1:(1+nper-1), n, TRUE)
# Visualizing distribution of suscep/infect
out <- plot_infectsuscep(graph, toa, K=3, logscale = TRUE)Run the code above in your browser using DataLab