View source: R/diffnet-methods.r
plot_infectsuscep | R Documentation |
After calculating infectiousness and susceptibility of each individual on the
network, it creates an 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 = 20,
nlevels = round(bins/2),
h = NULL,
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) viridisLite::viridis(n),
include.grid = TRUE,
exclude.zeros = FALSE,
valued = getOption("diffnet.valued", FALSE),
...
)
graph |
A dynamic graph (see |
toa |
Integer vector of length |
t0 |
Integer scalar. See |
normalize |
Logical scalar. Passed to infection/susceptibility. |
K |
Integer scalar. Passed to infection/susceptibility. |
r |
Numeric scalar. Passed to infection/susceptibility. |
expdiscount |
Logical scalar. Passed to infection/susceptibility. |
bins |
Integer scalar. Size of the grid ( |
nlevels |
Integer scalar. Number of levels to plot (see |
h |
Numeric vector of length 2. Passed to |
logscale |
Logical scalar. When TRUE the axis of the plot will be presented in log-scale. |
main |
Character scalar. Title of the graph. |
xlab |
Character scalar. Title of the x-axis. |
ylab |
Character scalar. Title of the y-axis. |
sub |
Character scalar. Subtitle of the graph. |
color.palette |
a color palette function to be used to assign colors in the plot (see |
include.grid |
Logical scalar. When TRUE, the grid of the graph is drawn. |
exclude.zeros |
Logical scalar. When TRUE, observations with zero values |
valued |
Logical scalar. When FALSE non-zero values in the adjmat are set to one.
in infect or suscept are excluded from the graph. This is done explicitly when |
... |
Additional parameters to be passed to |
This plotting function was inspired by Aral, S., & Walker, D. (2012).
By default the function will try to apply a kernel smooth function via
kde2d
. If not possible (because not enought data points), then
the user should try changing the parameter h
or set it equal to zero.
toa
is passed to infection/susceptibility
.
A list with three elements:
infect |
A numeric vector of size |
suscep |
A numeric vector of size |
coords |
A list containing the class marks and counts used to draw the
plot via |
complete |
A logical vector with |
George G. Vega Yon
Aral, S., & Walker, D. (2012). "Identifying Influential and Susceptible Members of Social Networks". Science, 337(6092), 337–341. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1126/science.1215842")}
Infectiousness and susceptibility are computed via infection
and
susceptibility
.
Other visualizations:
dgr()
,
diffusionMap()
,
drawColorKey()
,
grid_distribution()
,
hazard_rate()
,
plot_adopters()
,
plot_diffnet()
,
plot_diffnet2()
,
plot_threshold()
,
rescale_vertex_igraph()
# 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 = FALSE)
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