netdiffuseR (version 1.16.2)

plot_threshold: Threshold levels through time

Description

Draws a graph where the coordinates are given by time of adoption, x-axis, and threshold level, y-axis.

Usage

plot_threshold(graph, expo, toa, t0 = min(toa, na.rm = TRUE),
  undirected = getOption("diffnet.undirected"), no.contemporary = TRUE,
  main = "Time of Adoption by Network Threshold", xlab = "Time",
  ylab = "Threshold", vertex.cex = "degree", vertex.col = "blue",
  vertex.label = NULL, vertex.lab.pos = 3, edge.width = 2,
  edge.col = "gray", arrow.length = 0.2, include.grid = TRUE, bty = "n",
  ...)

Arguments

graph

A dynamic graph (see netdiffuseR-graphs).

expo

$n\times T$ matrix. Esposure to the innovation obtained from exposure

toa

Integer vector of size $n$. Times of Adoption

t0

Integer scalar. Passed to threshold.

undirected

Logical scalar.

no.contemporary

Logical scalar. When TRUE, edges for vertices with the same toa won't be plotted.

main

Character scalar. Title of the plot.

xlab

Character scalar. x-axis label.

ylab

Character scalar. y-axis label.

vertex.cex

Numeric vector of size $n$. Relative size of the vertices.

vertex.col

Either a vector of size $n$ or a scalar indicating colors of the vertices.

vertex.label

Character vector of size $n$. Labels of the vertices.

vertex.lab.pos

Integer value to be passed to text via pos.

edge.width

Numeric. Width of the edges.

edge.col

Character. Color of the edges.

arrow.length

Numeric value to be passed to arrows.

include.grid

Logical. When TRUE, the grid of the graph is drawn.

bty

See par.

...

Additional arguments passed to plot.

See Also

Use threshold to retrieve the corresponding threshold obtained returned by exposure.

Other visualizations: hazard_rate, plot_adopters, plot_diffnet, plot_infectsuscep

Examples

# Generating a random graph
set.seed(1234)
n <- 6
nper <- 5
graph <- rgraph_er(n,nper, p=.3, undirected = FALSE)
toa <- sample(2000:(2000+nper-1), n, TRUE)
adopt <- toa_mat(toa)

# Computing exposure
expos <- exposure(graph, adopt$cumadopt)

plot_threshold(graph, expos, toa)

# Calculating degree (for sizing the vertices)
plot_threshold(graph, expos, toa, vertex.cex = "indegree")