# Generating-functions (Constructors) to Create Objects of Classes `odeModel', `rwalkModel' and `gridModel'. These functions can be used to create `simObj` instances without using `new` explicitly. ```r 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 ## 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. ## Returns The function returns an S4 object of type `odeModel`, `rwalkModel`, `gridModel` ## See Also `new`, `simecol-package` ## Examples ```r ## (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) ```

odeModel function