plot_threshold: Threshold levels through time

In srdyal/diffusiontest: Analysis of Diffusion and Contagion Processes on Networks

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, ...)

## S3 method for class 'diffnet'
plot_threshold(graph, expo, ...)

## S3 method for class 'array'
plot_threshold(graph, expo, ...)

## Default S3 method:
plot_threshold(
  graph,
  expo,
  toa,
  include_censored = FALSE,
  t0 = min(toa, na.rm = TRUE),
  attrs = NULL,
  undirected = getOption("diffnet.undirected"),
  no.contemporary = TRUE,
  main = "Time of Adoption by\nNetwork Threshold",
  xlab = "Time",
  ylab = "Threshold",
  vertex.size = "degree",
  vertex.color = NULL,
  vertex.label = "",
  vertex.label.pos = NULL,
  vertex.label.cex = 1,
  vertex.label.adj = c(0.5, 0.5),
  vertex.label.color = NULL,
  vertex.sides = 40L,
  vertex.rot = 0,
  edge.width = 2,
  edge.color = NULL,
  arrow.width = NULL,
  arrow.length = NULL,
  arrow.color = NULL,
  include.grid = FALSE,
  vertex.frame.color = NULL,
  bty = "n",
  jitter.factor = c(1, 1),
  jitter.amount = c(0.25, 0.025),
  xlim = NULL,
  ylim = NULL,
  edge.curved = NULL,
  background = NULL,
  ...
)

Arguments

graph	A dynamic graph (see netdiffuseR-graphs).
expo	n\times T matrix. Esposure to the innovation obtained from exposure
...	Additional arguments passed to plot.
toa	Integer vector of length n with the times of adoption.
include_censored	Logical scalar. Passed to threshold.
t0	Integer scalar. Passed to threshold.
attrs	Passed to exposure (via threshold).
undirected	Logical scalar. When TRUE only the lower triangle of the adjacency matrix will considered (faster).
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.size	Numeric vector of size n. Relative size of the vertices.
vertex.color	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.label.pos	Integer value to be passed to text via pos.
vertex.label.cex	Either a numeric scalar or vector of size n. Passed to text.
vertex.label.adj	Passed to text.
vertex.label.color	Passed to text.
vertex.sides	Either a vector of size n or a scalar indicating the number of sides of each vertex (see details).
vertex.rot	Either a vector of size n or a scalar indicating the rotation in radians of each vertex (see details).
edge.width	Numeric. Width of the edges.
edge.color	Character. Color of the edges.
arrow.width	Numeric value to be passed to arrows.
arrow.length	Numeric value to be passed to arrows.
arrow.color	Color.
include.grid	Logical. When TRUE, the grid of the graph is drawn.
vertex.frame.color	Either a vector of size n or a scalar indicating colors of vertices' borders.
bty	See par.
jitter.factor	Numeric vector of size 2 (for x and y) passed to jitter.
jitter.amount	Numeric vector of size 2 (for x and y) passed to jitter.
xlim	Passed to plot.
ylim	Passed to plot.
edge.curved	Logical scalar. When curved, generates curved edges.
background	TBD

Details

When vertex.label=NULL the function uses vertices ids as labels. By default vertex.label="" plots no labels.

Vertices are drawn using an internal function for generating polygons. Polygons are inscribed in a circle of radius vertex.size, and can be rotated using vertex.rot. The number of sides of each polygon is set via vertex.sides.

Value

Invisible. A data frame with the calculated coordinates, including: 'toa', 'threshold', and 'jit' (a jittered version of 'toa').

Author(s)

George G. Vega Yon

See Also

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

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

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.size = "indegree")

srdyal/diffusiontest documentation built on Sept. 2, 2023, 2:49 p.m.