simecol (version 0.6-6)

simecol-package: General Information about the `simecol' Package

Description

The simecol package is intended to give users (scientists and students) an interactive environment to implement, distribute, simulate and document ecological and other dynamic models without the need to write long simulation programs. For this purpose, an object oriented approach using the S4 class system is proposed, which should provide a consistent but still flexible and extensible way to implement simulation models of different types, namely:

• ordinary differential equation (ODE) models (classodeModel),
• grid-oriented individual-based models (classgridModel), and
• particle diffusion-type models (classrwalkModel),
• individual-based models (classindbasedModel),
• other model types by deriving a user specified subclass fromsimObj.

Each simulation model is implemented as S4 object (superclass simObj) with the following slots:

• main = function(time, init, parms, ...): a function holding the main equations of the model,
• equations: an optional non-nested list holding arbitrary sub-equations (sub-models) of the model. Sub-equations can be interdependent and can be called directly from withinmainorinitfunc.
• parms: a list (or vector for some classes) with constant model parameters,
• times: vector of time steps or vector with three named valuesfrom,to,byspecifying the simulation time steps. The from-to-by form can be edited withfixParms.
• init: initial state (start values) of the simulation. This is typically a named vector (state variables inodeModels) or matrix (e.g. initial grid ofgridModels).
• inputs: time dependend or spatially resolved external inputs can be specified as data frame or matrix (more efficient). It is up to the user to evaluate the corresponding values within themainfunction. Performance optimized versions ofapprox(seeapproxTime) are available.
• solver: character string specifying the numerical algorithm used, e.g."lsoda","rk4"or"euler"from packagedeSolve). In addition, solvers from package"ddesolve"can also be used. In contrast to"euler"that can be used for difference equations (i.e.mainreturns derivatives),"iterator"is intended for models where main returns the new state (i.e for individual-based models). It is also possible to reference own algorithms (solvers) that are defined in the useer workspace or to assign solver functions directly.
• observer: optional slot which determines the data stored during the simulation. A user-providedobserverfunction can also be used to write logging information to the screen or to the hard-disk, to perform run-time visualisation, or statistical analysis during the simulation. Note that theobserver-mechanism works only withiterationsolvers. It is generally not avalable forodeModels.
• out: this slot holds the simulation results after a simulation run as data frame (if the return value ofmainis a vector) or as list (otherwise). The type of data stored inoutcan be manipulated by providing a user-defindedobserverfunction.
• initfunc: this slot can hold an optional function which is called automatically when a new object is created bynewor when it is re-initialized byinitializeorsim.

simObj model objects should be defined and created using the common S4 mechanisms (new).

In this way, a simObj object may contain all data, which are needed to run simulations simply by entering the model object via source() or data() and then to run and plot the model for example via plot(sim(obj)).

Accessor functions (with names identical to the slot names) are provided to get or set model parameters, time steps, initial values, inputs, the solver, the main and sub-equations or initfunc or to extract the model outputs. It is also possible to modify the components of the simecol objects directly, e.g. the model equations of a model lv with lv@main, but there is no guarantee that this will work in a compatible way in future versions.

Models of different type are provided as data and some more in source code (see directory examples).

The examples are intended as a starting point to write your own simObj objects and to distribute them to whomever you wish.

The package is supplemented with several utility functions (e.g. seedfill or neighbours), which can be used independently from simObj objects.

References

Petzoldt, T and K. Rinke (2007) simecol: An Object-Oriented Framework for Ecological Modeling in R. Journal of Statistical Software, 22(9). URL http://www.jstatsoft.org/v22/i09/.

See Also

CA, chemostat, conway, diffusion, lv, lv3, upca.

Examples

## (1) Quick Start Examples ====================================================
data(lv)        # load basic Lotka-Volterra model

fixParms(lv)
parms(lv)
main(lv)
lv <- sim(lv)
plot(lv)
results <- out(lv)

data(conway)    # Conway's game of life
init(conway) <- matrix(0, 10, 10)
times(conway) <-  1:100
fixInit(conway) # enter some "1"
sim(conway, animate=TRUE, delay=100)

## (2) Additional Resources ====================================================
## open the directory with source code of demo
browseURL(paste(system.file(package="simecol"), "/demo", sep=""))

## run demo
demo(jss)

## open the directory with R sourcecode examples
browseURL(paste(system.file(package="simecol"), "/examples", sep=""))

## show package vignette with introductory article
vignette("simecol-introduction")
edit(vignette("simecol-introduction"))

## open the installation directory of simecol
##   (NEWS, THANKS, FAQ, ToDo, WISHLIST, ...)
browseURL(paste(system.file(package="simecol"), "/", sep=""))

## Open Project Homepage
browseURL("http://www.simecol.de")

## How to cite package simecol in publications
citation("simecol")