Use this if you are using igraph from R
This function can conveniently plot the results of multiple SIR model simulations.
## S3 method for class 'sir'
plot(
  x,
  comp = c("NI", "NS", "NR"),
  median = TRUE,
  quantiles = c(0.1, 0.9),
  color = NULL,
  median_color = NULL,
  quantile_color = NULL,
  lwd.median = 2,
  lwd.quantile = 2,
  lty.quantile = 3,
  xlim = NULL,
  ylim = NULL,
  xlab = "Time",
  ylab = NULL,
  ...
)
x | 
 The output of the SIR simulation, coming from the   | 
comp | 
 Character scalar, which component to plot. Either ‘NI’ (infected, default), ‘NS’ (susceptible) or ‘NR’ (recovered).  | 
median | 
 Logical scalar, whether to plot the (binned) median.  | 
quantiles | 
 A vector of (binned) quantiles to plot.  | 
color | 
 Color of the individual simulation curves.  | 
median_color | 
 Color of the median curve.  | 
quantile_color | 
 Color(s) of the quantile curves. (It is recycled if needed and non-needed entries are ignored if too long.)  | 
lwd.median | 
 Line width of the median.  | 
lwd.quantile | 
 Line width of the quantile curves.  | 
lty.quantile | 
 Line type of the quantile curves.  | 
xlim | 
 The x limits, a two-element numeric vector. If   | 
ylim | 
 The y limits, a two-element numeric vector. If   | 
xlab | 
 The x label.  | 
ylab | 
 The y label. If   | 
... | 
 Additional arguments are passed to   | 
The number of susceptible/infected/recovered individuals is plotted over time, for multiple simulations.
Nothing.
Eric Kolaczyk (http://math.bu.edu/people/kolaczyk/) and Gabor Csardi csardi.gabor@gmail.com.
Bailey, Norman T. J. (1975). The mathematical theory of infectious diseases and its applications (2nd ed.). London: Griffin.
sir for running the actual simulation.
g <- sample_gnm(100, 100) sm <- sir(g, beta=5, gamma=1) plot(sm)