Visualize adopters and cumulative adopters

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Description

Visualize adopters and cumulative adopters

Usage

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plot_adopters(obj, freq = FALSE, what = c("adopt", "cumadopt"),
  add = FALSE, include.legend = TRUE, include.grid = TRUE, pch = c(21,
  24), type = c("b", "b"), ylim = if (!freq) c(0, 1) else NULL, lty = c(1,
  1), col = c("black", "black"), bg = c("lightblue", "gray"),
  xlab = "Time", ylab = ifelse(freq, "Frequency", "Proportion"),
  main = "Adopters and Cumulative Adopters", ...)

Arguments

obj

Either a diffnet object or a cumulative a doption matrix.

freq

Logical scalar. When TRUE frequencies are plotted instead of proportions.

what

Character vector of length 2. What to plot.

add

Logical scalar. When TRUE lines and dots are added to the current graph.

include.legend

Logical scalar. When TRUE a legend of the graph is plotted.

include.grid

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

pch

Integer vector of length 2. See matplot.

type

Character vector of length 2. See matplot.

ylim

Numeric vector of length 2. Sets the plotting limit for the y-axis.

lty

Numeric vector of length 2. See matplot.

col

Character vector of length 2. See matplot.

bg

Character vector of length 2. See matplot.

xlab

Character scalar. Name of the x-axis.

ylab

Character scalar. Name of the y-axis.

main

Character scalar. Title of the plot

...

Further arguments passed to matplot.

Value

A matrix as described in cumulative_adopt_count.

Author(s)

George G. Vega Yon

See Also

Other visualizations: dgr, diffusionMap, drawColorKey, grid_distribution, hazard_rate, plot_diffnet2, plot_diffnet, plot_infectsuscep, plot_threshold, rescale_vertex_igraph

Examples

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# Generating a random diffnet -----------------------------------------------
set.seed(821)
diffnet <- rdiffnet(100, 5, seed.graph="small-world", seed.nodes="central")

plot_adopters(diffnet)

# Alternatively, we can use a TOA Matrix
toa <- sample(c(NA, 2010L,2015L), 20, TRUE)
mat <- toa_mat(toa)
plot_adopters(mat$cumadopt)

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