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)
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