# `rodeo` Class This documents the `rodeo` class to represent an ODE-based model. See the `rodeo-package` main page or type `help(package="rodeo")` for an introduction to the package of the same name. ## Fields - **`prosTbl`**: A data frame with fields 'name', 'unit', 'description', and 'expression' defining the process rates. - **`stoiTbl`**: A data frame with fields 'variable', 'process', and 'expression' reprenting the stoichiometry matrix in data base format. - **`varsTbl`**: A data frame with fields 'name', 'unit', 'description' declaring the state variables of the model. The declared names become valid identifiers to be used in the expression fields of `prosTbl` or `stoiTbl`. - **`parsTbl`**: A data frame of the same structure as `vars` declaring the parameters of the model. The declared names become valid identifiers to be used in the expression fields of `prosTbl` or `stoiTbl`. - **`funsTbl`**: A data frame of the same structure as `vars` declaring any functions referenced in the expression fields of `prosTbl` or `stoiTbl`. - **`dim`**: Integer vector specifying the spatial dimensions. - **`vars`**: Numeric vector, holding values of state variables. - **`pars`**: Numeric vector, holding values of parameters. ## Class methods For most of the methods below, a separate help page is available describing its arguments and usage. * `initialize` Initialization method for new objects. * `namesVars, namesPars, namesFuns, namesPros` Functions returning the names of declared state variables, parameters, functions, and processes, respectively (character vectors). No arguments. * `lenVars, lenPars, lenFuns, lenPros` Functions returning the number of declared state variables, parameters, functions and processes, respectively (integer). No arguments. * `getVarsTable, getParsTable, getFunsTable, getProsTable, getStoiTable` Functions returning the data frames used to initialize the object. No arguments * `getDim` Returns the spatial dimensions as an integer vector. No arguments. * `compile` Compiles a Fortran library for use with numerical methods from packages `deSolve` or `rootSolve`. * `generate` Translate the ODE-model specification into a function that computes process rates and the state variables' derivatives (either in R or Fortran). Consider to use the high-level method `compile`. * `setVars` Assign values to state variables. * `setPars` Assign values to parameters. * `getVars` Returns the values of state variables. * `getPars` Returns the values of parameters. * `stoichiometry` Returns the stoichiometry matrix, either evaluated (numeric) or as text. * `plotStoichiometry` Plots qualitative stoichiometry information. ## Examples ```r ## Example using high-level functions: Epidemiological SEIR model # Import model from workbook shipped with this package m <- buildFromWorkbook(system.file("models/SEIR.xlsx", package="rodeo")) # Set parameters and initial state (defaults stored in workbook) p <- m$getParsTable() m$setPars(setNames(p$default, p$name)) v <- m$getVarsTable() m$setVars(setNames(v$default, v$name)) # Run a dynamic simulations and print parts of the result sim <- m$dynamics(time=1:30, fortran=FALSE) print(head(sim)) print(tail(sim)) ### Example using low-level functions: Bacterial growth in bioreactor # Creation of model object (data frames shipped as package data) data(vars, pars, funs, pros, stoi) model <- rodeo$new(vars, pars, funs, pros, stoi, dim=c(1)) # Assignment of parameters and initial values model$setPars(c(mu=0.8, half=0.1, yield= 0.1, vol=1000, flow=50, sub_in=1)) model$setVars(c(bac=0.01, sub=0)) # Implementation of functions declared in 'funs' monod <- function(c,h) {c/(c+h)} # Creation of derivatives function in a low-level way; calling # the 'compile' method is a more convenient alternative code <- model$generate(name="derivs", lang="r") derivs <- eval(parse(text=code)) # Explicit call of an integrator from the deSolve package times <- 0:96 out <- deSolve::ode(y=model$getVars(), times=times, func=derivs, parms=model$getPars()) colnames(out) <- c("time", model$namesVars(), model$namesPros()) plot(out) ``` ## See Also See the `rodeo-package` main page or type `help(package="rodeo")` to find the documentation of any non-class methods contained in the `rodeo` package.

rodeo-class function