StepGillespie1D {smfsb} | R Documentation |
Create a function for advancing the state of an SPN by using the Gillespie algorithm on a 1D regular grid
Description
This function creates a function for advancing the state of an SPN model
using the Gillespie algorithm. The resulting function (closure) can be
used in conjunction with other functions (such as simTs1D
)
for simulating realisations of SPN models in space and time.
Usage
StepGillespie1D(N,d)
Arguments
N |
An R list with named components representing a stochastic
Petri net (SPN). Should contain |
d |
A vector of diffusion coefficients - one coefficient for each reacting species, in order. The coefficient is the reaction rate for a reaction for a molecule moving into an adjacent compartment. The hazard for a given molecule leaving the compartment is therefore twice this value (as it can leave to the left or the right). |
Value
An R function which can be used to advance the state of the SPN model
N
by using the Gillespie algorithm. The function closure has
interface function(x0,t0,deltat,...)
, where x0
is a matrix
with rows corresponding to species and columns corresponding to voxels,
representing the initial condition, t0
represent the initial state and time, and deltat
represents the amount of time by which the process should be advanced. The function closure returns a matrix representing the simulated state of the system at the new time.
See Also
StepGillespie
,
simTs1D
, StepGillespie2D
Examples
data(spnModels)
N=20; T=30
x0=matrix(0,nrow=2,ncol=N)
rownames(x0)=c("x1","x2")
x0[,round(N/2)]=LV$M
stepLV1D = StepGillespie1D(LV,c(0.6,0.6))
xx = simTs1D(x0,0,T,0.2,stepLV1D,verb=TRUE)
op=par(mfrow=c(1,2))
image(xx[1,,],main="Prey",xlab="Space",ylab="Time")
image(xx[2,,],main="Predator",xlab="Space",ylab="Time")
par(op)