Thank you very much for your answer. I'm not sure if I can use the function ode.2 because it's a solver for 2-D partial differential equation problems. My equations don't contain diffusion parameters.
Thank you for your help Marine ________________________________ De : David Winsemius <dwinsem...@comcast.net> Envoyé : mercredi 21 juin 2017 22:30 À : Marine Regis Cc : r-help@r-project.org Objet : Re: [R] How to apply a system of ordinary differential equations to a cell grid? > On Jun 21, 2017, at 12:48 PM, Marine Regis <marine.re...@hotmail.fr> wrote: > > Hello, > > I am developing an agent-based model to simulate the spread of infectious > diseases in heterogeneous landscapes composed of habitat polygons (or clumps > of connected cells). To simplify the model, I consider a habitat grid (or > raster) containing the polygon ID of each cell. In addition, I have > epidemiological parameters associated with each polygon ID. At each time > step, the parameter values change in the polygon. Thus, the data frame > �landscape� (see below) is updated at each time step. Here is an example at t > = 0: > > landscape <- data.frame(polygon_ID = seq(1, 10, by = 1), > beta = sample(c(100, 200, 400, 600), 10, replace = > TRUE), > gamma = sample(c(25, 26, 27, 28), 10, replace = TRUE)) > > To study the disease dynamics, I also am developing a compartmental model > based on a system of ordinary differential equations (ODEs). Here is an > example to represent the system of ODEs: > > solve_sir_model <- function (times, parameters) { > > sir_model <- function (times, states, parameters) { > > with(as.list(c(states, parameters)), { > > dSdt <- -beta*S*I > dIdt <- beta*S*I-gamma*I > dRdt <- gamma*I > dNdt <- dSdt + dIdt + dRdt > > return(list(c(dSdt, dIdt, dRdt, dNdt))) > > }) > } > > states <- c(S = 99, I = 1, R = 0, N = 100) > return(ode(y = states, times = times, func = sir_model, parms = parameters)) > } > > require(deSolve) > output <- as.data.frame(solve_sir_model(times = seq(0, 5, by = 1), parameters > = c(beta = 400, gamma = 28))) > > Here is my question: at each time step, is it possible to apply the system of > ODEs to each habitat polygon (thus each row) in the data frame �landscape�? I > am using lsoda as an ODE solver. Do I need to use another solver to apply the > ODEs at each time step? > > Thank you very much for your advice. > Have a nice day > Marine > There's also ode.2D in the same package {deSolve} and it's help page has a 2-d diffusion example that might be cognate. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help R-help Info Page - Homepage - SfS – Seminar for Statistics<https://stat.ethz.ch/mailman/listinfo/r-help> stat.ethz.ch The main R mailing list, for announcements about the development of R and the availability of new code, questions and answers about problems and solutions using R ... > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. David Winsemius Alameda, CA, USA [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.