QPot (version 1.5)

TSPlot: Plot simulation of two-dimensional stochastic differential equations

Description

This function plots the simulation of two-dimensional stochastic differential equations from TSTraj

Usage

TSPlot(mat, deltat, dim = 1, xlim = NULL, ylim = NULL, xaxt.1D = "time",
  dens = TRUE, lwd = 2, line.alpha = 130, zero.axes = TRUE,
  xlab.2D = "X", ylab.2D = "Y", ...)

Arguments

mat

a matrix output from TSTraj.

deltat

numeric value indicating the frequency of stochastic perturbation, as \(\Delta t\), used in the function to recaluculate axes if applicable.

dim

dimensions of the plot; dim = 1 to plot a timeseries with X and Y on the ordinate axis or dim = 2 to plot the trjectories in state space (i.e., X and Y respectively on the abscissa and ordinate axes).

xlim

numeric vectors of length 2, giving the x coordinate range. Default = NULL automatically sizes plot window.

ylim

numeric vectors of length 2, giving the y coordinate range. Default = NULL automatically sizes plot window.

xaxt.1D

for dim = 1, allows user to specify the axis as "time" or "steps," with steps being \(time \times \Delta t\)

dens

if dens = TRUE, plots a horizontal one-dimensional density plot adjacent to the timerseries.

lwd

line width. Defaults to 1.

line.alpha

transparency of lines from 0--255.

zero.axes

if TRUE, then axes plotted at X = 0 and Y = 0.

xlab.2D

a title for the x axis when dim = 2.

ylab.2D

a title for the y axis when dim = 2.

...

passes arguments to plot.

Examples

# NOT RUN {
# First, the parameter values, as found in TSTraj
model.state <- c(x = 3, y = 3)
model.sigma <- 0.2
model.deltat <- 0.05
model.time <- 100

# Second, write out the deterministic skeleton of the equations to be simulated, 
# as found in TSTraj
#Example 1 from article
equationx <- "1.54*x*(1.0-(x/10.14)) - (y*x*x)/(1.0 + x*x)"
equationy <- "((0.476*x*x*y)/(1 + x*x)) - 0.112590*y*y"

# Third, run it, as found in TSTraj
ModelOut <- TSTraj(y0 = model.state, time = model.time, deltat = model.deltat, 
	x.rhs = equationx, y.rhs = equationy, sigma = model.sigma)
# Fourth, plot it:
# in 1D
TSPlot(ModelOut, deltat = model.deltat, dim = 1)
# in 2D
TSPlot(ModelOut, deltat = model.deltat, dim = 2)
# }