\dontrun{
##############################################################################################
## 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)
}
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