plot_simulation: Plots the SIR epidemic from the simulation

In qleclerc/epicspatial: Flexible Spatial Modelling of Epidemics

Description

Plots the total fraction of Susceptible, Infected and Recovered individuals at each time step.

Usage

plot_simulation(results, num_areas, num_ages, by_age = F, step = 1,
  pretty = F, title = NULL)

Arguments

results	The object containing the results from the simulation.
num_areas	The number of areas in the simulation. Easy way to get it for your current simulation is to use the dimension of your transmission kernel (e.g. if you have 4 age groups: dim(expanded_D)[1]/4).
num_ages	The number of ages in the simulation.
by_age	Logical. If TRUE, will create a plot for each age category (only works with pretty = FALSE).
step	Timestep used for the simulation, in days (default is 1 day).
pretty	Logical. If TRUE, will render using ggplot (longer but nicer).
title	Title to use for the plot.

Details

The Infected category has a separate y-axis to make visualisation easier, due to the relatively low fraction of Infected at any given time compared to Susceptible and Recovered.

Value

Creates a plot.

Examples

#Create a spatial dataset:
test_data = raster(nrow=10, ncol=10, xmn=1, xmx=100000, ymn=1, ymx=100000)
values(test_data) = runif(100, 1, 1000)

#Calculate the parameters for the simulation:
prep_simulation(test_data)

#Run the simulation:
results = run_simulation(test_data, expanded_D, contact_mat, beta)

plot_simulation(results, dim(expanded_D)[1]/4, 4, pretty=T, title="SIR plot")

qleclerc/epicspatial documentation built on May 21, 2019, 4:06 a.m.