# Interface to ode() ```r odeC(y, times, func, parms, ...) ``` ## Arguments - `y`: named vector of type numeric. Initial values for the integration - `times`: vector of type numeric. Integration times. If `includeTimeZero` is `TRUE` (see funC ), the times vector is augmented by t = 0. If `nGridpoints` (see funC ) was set >= 0, uniformly distributed time points between the first and last time point are introduced and the solution is returned for these time points, too. Any additional time points that are introduced during integration (e.g. event time points) are returned unless nGridpoints = -1 (the default). - `func`: return value from funC() - `parms`: named vector of type numeric. - `...`: further arguments going to `ode()` ## Returns matrix with times and states ## Details See deSolve-package for a full description of possible arguments ## Examples ```r ## Not run: ###################################################################### ## Ozone formation and decay, modified by external forcings ###################################################################### library(deSolve) data(forcData) forcData$value <- forcData$value + 1 # O2 + O <-> O3 f <- c( O3 = " (build_O3 + u_build) * O2 * O - (decay_O3 + u_degrade) * O3", O2 = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3", O = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3" ) # Generate ODE function forcings <- c("u_build", "u_degrade") func <- funC(f, forcings = forcings, modelname = "test", fcontrol = "nospline", nGridpoints = 10) # Initialize times, states, parameters and forcings times <- seq(0, 8, by = .1) yini <- c(O3 = 0, O2 = 3, O = 2) pars <- c(build_O3 = 1/6, decay_O3 = 1) forc <- setForcings(func, forcData) # Solve ODE out <- odeC(y = yini, times = times, func = func, parms = pars, forcings = forc) # Plot solution par(mfcol=c(1,2)) t1 <- unique(forcData[,2]) M1 <- matrix(forcData[,3], ncol=2) t2 <- out[,1] M2 <- out[,2:4] M3 <- out[,5:6] matplot(t1, M1, type="l", lty=1, col=1:2, xlab="time", ylab="value", main="forcings", ylim=c(0, 4)) matplot(t2, M3, type="l", lty=2, col=1:2, xlab="time", ylab="value", main="forcings", add=TRUE) legend("topleft", legend = c("u_build", "u_degrade"), lty=1, col=1:2) matplot(t2, M2, type="l", lty=1, col=1:3, xlab="time", ylab="value", main="response") legend("topright", legend = c("O3", "O2", "O"), lty=1, col=1:3) ###################################################################### ## Ozone formation and decay, modified by events ###################################################################### f <- c( O3 = " (build_O3 + u_build) * O2 * O - (decay_O3 + u_degrade) * O3", O2 = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3", O = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3", u_build = "0", # piecewise constant u_degrade = "0" # piecewise constant ) # Define parametric events events.pars <- data.frame( var = c("u_degrade", "u_degrade", "u_build"), time = c("t_on", "t_off", "2"), value = c("plus", "minus", "2"), method = "replace" ) # Declar parameteric events when generating funC object func <- funC(f, forcings = NULL, events = events.pars, modelname = "test", fcontrol = "nospline", nGridpoints = -1) # Set Parameters yini <- c(O3 = 0, O2 = 3, O = 2, u_build = 1, u_degrade = 1) times <- seq(0, 8, by = .1) pars <- c(build_O3 = 1/6, decay_O3 = 1, t_on = exp(rnorm(1, 0)), t_off = 6, plus = 3, minus = 1) # Solve ODE with additional fixed-value events out <- odeC(y = yini, times = times, func = func, parms = pars) # Plot solution par(mfcol=c(1,2)) t2 <- out[,1] M2 <- out[,2:4] M3 <- out[,5:6] matplot(t2, M3, type="l", lty=2, col=1:2, xlab="time", ylab="value", main="events") legend("topleft", legend = c("u_build", "u_degrade"), lty=1, col=1:2) matplot(t2, M2, type="l", lty=1, col=1:3, xlab="time", ylab="value", main="response") legend("topright", legend = c("O3", "O2", "O"), lty=1, col=1:3) ###################################################################### ## Ozone formation and decay, modified by events triggered by root ###################################################################### f <- c( O3 = " (build_O3 + u_build) * O2 * O - (decay_O3 + u_degrade) * O3", O2 = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3", O = "-(build_O3 + u_build) * O2 * O + (decay_O3 + u_degrade) * O3", u_build = "0", # piecewise constant u_degrade = "0" # piecewise constant ) # Define parametric events events.pars <- data.frame( var = c("u_degrade", "u_degrade", "u_build", "O3"), time = c("t_on", "t_off", "2", "t_thres_O3"), value = c("plus", "minus", "2", "0"), root = c(NA, NA, NA, "O3 - thres_O3"), method = "replace" ) # Declar parameteric events when generating funC object func <- funC(f, forcings = NULL, events = events.pars, modelname = "test", fcontrol = "nospline", nGridpoints = -1) # Set Parameters yini <- c(O3 = 0, O2 = 3, O = 2, u_build = 1, u_degrade = 1) times <- seq(0, 8, by = .01) pars <- c(build_O3 = 1/6, decay_O3 = 1, t_on = exp(rnorm(1, 0)), t_off = 6, plus = 3, minus = 1, thres_O3 = 0.5, t_thres_O3 = 1) # Solve ODE with additional fixed-value events out <- odeC(y = yini, times = times, func = func, parms = pars, method = "lsode") class(out) <- c("deSolve") plot(out) # Plot solution par(mfcol=c(1,2)) t2 <- out[,1] M2 <- out[,2:4] M3 <- out[,5:6] matplot(t2, M3, type="l", lty=2, col=1:2, xlab="time", ylab="value", main="events") legend("topleft", legend = c("u_build", "u_degrade"), lty=1, col=1:2) matplot(t2, M2, type="l", lty=1, col=1:3, xlab="time", ylab="value", main="response") legend("topright", legend = c("O3", "O2", "O"), lty=1, col=1:3) ## End(Not run) ```

odeC function