plot_infectsuscep {netdiffuseR}

Plot distribution of infect/suscep

Description

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.

Usage

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),
  ...
)

Arguments

graph

A dynamic graph (see netdiffuseR-graphs).

toa

Integer vector of length n with the times of adoption.

t0

Integer scalar. See toa_mat.

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 (n).

nlevels

Integer scalar. Number of levels to plot (see filled.contour).

h

Numeric vector of length 2. Passed to kde2d in the MASS package.

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 filled.contour).

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 logscale=TRUE.

...

Additional parameters to be passed to filled.contour.

Details

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.

Value

A list with three elements:

infect

A numeric vector of size n with infectiousness levels

suscep

A numeric vector of size n with susceptibility levels

coords

A list containing the class marks and counts used to draw the plot via filled.contour (see grid_distribution)

complete

A logical vector with TRUE when the case was included in the plot. (this is relevant whenever logscale=TRUE)

Author(s)

George G. Vega Yon

References

Aral, S., & Walker, D. (2012). "Identifying Influential and Susceptible Members of Social Networks". Science, 337(6092), 337–341. doi:10.1126/science.1215842

See Also

Infectiousness and susceptibility are computed via infection and susceptibility.

Other visualizations: dgr(), diffusionMap(), drawColorKey(), grid_distribution(), hazard_rate(), plot_adopters(), plot_diffnet2(), plot_diffnet(), plot_threshold(), rescale_vertex_igraph()

Examples

# 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)