odeModel: Generating-functions (Constructors) to Create Objects of Classes `odeModel', `rwalkModel' and `gridModel'.

Description

These functions can be used to create simObj instances without using new explicitly.

Usage

odeModel(obj = NULL, main = NULL,
        equations = NULL, times = c(from = 0, to = 10, by = 1),
        init = numeric(0), parms = numeric(0),
        inputs = NULL, solver = "rk4", initfunc = NULL)
gridModel(obj = NULL, main = NULL,
        equations = NULL, times = c(from=0, to=10, by=1),
        init = matrix(0), parms = list(),
        inputs = NULL, solver = "iteration", initfunc = NULL)
rwalkModel(obj = NULL, main = NULL, 
        equations = NULL, times = c(from = 0, to = 10, by = 1),
        init = NULL, parms = list(),
        inputs = NULL, solver = "iteration", initfunc = NULL)
        
indbasedModel(obj = NULL, main = NULL, 
        equations = NULL, times = c(from = 0, to = 10, by = 1),
        init = NULL, parms = list(),
        inputs = NULL, solver = "iteration", initfunc = NULL)

Arguments

obj

Unnamed arguments are regarded as objects of the corresponding class. If obj is omitted, the new object is created from scratch.

main

The main equations of the model.

equations

The sub-models (sub-equations and of the model).

times

A vector of time steps or a vector with three named values from, to, by specifying the simulation time steps. The `from-to-by' form can be edited with editParms.

init

Initial values (start values) of the state variable given as named vector.

parms

A vector or list (depending on the respective class) of constant parameters.

inputs

Optional time-dependend input variables (matrix or data frame).

solver

The solver used to integrate the model.

initfunc

The function is called by the initialize mechanism and allows direct access and manipulation of all slots of the object in creation

Value

The function returns an S4 object of type odeModel, rwalkModel, gridModel

Details

These functions provide an alternative way to create simObj instances in addition to the standard S4 new mechanism. The functions are provided mainly for compatibility with older versions of simecol.

See simecol-package and the examples for details about the slots.

Examples

Run this code

# NOT RUN {
## (1) Define and run your own simecol model with new ==================

lv <- new("odeModel", 
  main = function (time, init, parms) {
    with(as.list(c(init, parms)), {
      dn1 <-   k1 * N1 - k2 * N1 * N2
      dn2 <- - k3 * N2 + k2 * N1 * N2
      list(c(dn1, dn2))
    })
  },
  parms  = c(k1 = 0.2, k2 = 0.2, k3 = 0.2),
  times  = c(from = 0, to = 100, by = 0.5),
  init   = c(N1 = 0.5, N2 = 1),
  solver = "lsoda"
)

## ... or use the generating function ----------------------------------

lv <- odeModel( 
  main = function (time, init, parms) {
    with(as.list(c(init, parms)), {
      dn1 <-   k1 * N1 - k2 * N1 * N2
      dn2 <- - k3 * N2 + k2 * N1 * N2
      list(c(dn1, dn2))
    })
  },
  parms  = c(k1 = 0.2, k2 = 0.2, k3 = 0.2),
  times  = c(from = 0, to = 100, by = 0.5),
  init   = c(N1 = 0.5, N2 = 1),
  solver = "lsoda"
)

lv <- sim(lv)
plot(lv)

## (2) Conway's Game of Life ==========================================

set.seed(23)  # to make it reproducible

conway <- new("gridModel",
  main = function(time, x, parms) {
    nb     <- eightneighbours(x)
    surviv <- (x >  0 & (nb %in% parms$srv))
    gener  <- (x == 0 & (nb %in% parms$gen))
    x      <- (surviv + gener) > 0
    return(x)
  },
  parms  = list(srv = c(2, 3), gen = 3),
  times  = 1:17,
  init   = matrix(round(runif(1000)), ncol=40),
  solver = "iteration"
)

sim(conway, animate=TRUE)

# }

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