plot_infectsuscep function

Plot distribution of infect/suscep

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),
  ...
)

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.

Returns

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)

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.

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)

References

Aral, S., & Walker, D. (2012). "Identifying Influential and Susceptible Members of Social Networks". Science, 337(6092), 337–341. tools:::Rd_expr_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()

Author(s)

George G. Vega Yon