Description Usage Arguments Value See Also Examples

This function creates a function for advancing the state of an SPN model
using a simple Euler-Maruyama discretisation of the CLE on a 1D regular grid. 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.

1 |

`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). |

`dt` |
Time step for the Euler-Maruyama discretisation. |

An R function which can be used to advance the state of the SPN model
`N`

by using a simple Euler-Maruyama 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.

`StepGillespie1D`

,`StepCLE`

,
`simTs1D`

, `StepCLE2D`

1 2 3 4 5 6 7 8 9 10 11 12 | ```
N=200
T=40
data(spnModels)
x0=matrix(0,nrow=2,ncol=N)
rownames(x0)=c("x1","x2")
x0[,round(N/2)]=LV$M
stepLV1D = StepCLE1D(LV,c(0.6,0.6),dt=0.05)
xx = simTs1D(x0,0,T,0.2,stepLV1D)
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)
``` |

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