[R-sig-dyn-mod] changing state variable in simulations
Hi Andras: I default to using vode because I've found that it's usually faster than other numerical integrators. This may well vary between models or applications, but I think it's a good rule of thumb. That said, in this case the reduction in runtime is probably negligible since it's such a simple model. Not a bad habit to get into, though. Cheers, Daniel _______________________________ Daniel C. Reed, PhD. Postdoctoral Fellow, Dept. of Earth & Environmental Sciences, University of Michigan, Ann Arbor, MI, USA. email: reeddc at umich.edu web: www.danielreed.org
On Sep 13, 2013, at 3:41 PM, Andras Farkas <motyocska at yahoo.com> wrote:
Thanks a lot Daniel for the detailed break down of the code and modifications.... Just would like to ask one question: I see you have changed the solver to vode, may I ask why would that be your choice in this case?
thanks again
Andras
----- Original Message -----
From: Daniel Reed <reeddc at umich.edu>
To: Special Interest Group for Dynamic Simulation Models in R <r-sig-dynamic-models at r-project.org>
Cc:
Sent: Friday, September 13, 2013 3:28 PM
Subject: Re: [R-sig-dyn-mod] changing state variable in simulations
Hi Andras:
How about this?
#Load library
require(deSolve)
#Define parameters and initial conditions
plist<-matrix(c(0.08,0.07,0.09,15,20,25,3,5,6),ncol=3 )
colnames(plist)=c("K","V","state")
#Define "forc" function prior to "derivs", so it isn't redefined every time "derivs" is called
intimes<-c(0,0.5,12)
input<-c(1200,0,0)
forc<-approxfun(intimes, input, method="constant",rule=2)
#Derivatives to be integrated
derivs<-function(t,state,pars){
with(as.list(pars),{
inp <- forc(t)
dy1 <- inp/V - K * state[1]
return(list(c(dy1)))
})
}
#Define output times
times=seq(0,13,by=0.05)
#Model wrapper
model<-function(pars) {
state<-pars[3]
return(ode(y=state,times=times,func=derivs,parms=pars[1:2],method="vode",rtol=1e-8,atol=1e-8,hmax=0.05))
}
#Empty matrix
modelout<-matrix(ncol=nrow(plist),nrow=length(times))
#Loop through parameters & initial conditions
for(i in 1:nrow(plist))
modelout[,i]<-model(plist[i,])[,2]
#Plot output
plot(times,modelout[,1],type="l",lty="solid")
lines(times,modelout[,2],lty="dashed")
lines(times,modelout[,3],lty="dotted")
Cheers,
Daniel
_______________________________
Daniel C. Reed, PhD.
Postdoctoral Fellow,
Dept. of Earth & Environmental Sciences,
University of Michigan,
Ann Arbor, MI, USA.
email: reeddc at umich.edu
web: www.danielreed.org
On Sep 13, 2013, at 1:34 PM, Andras Farkas <motyocska at yahoo.com> wrote:
Dear All,
have this simple model:
require(deSolve)
plist <-matrix(c(0.08,0.07,0.09,15,20,25),ncol=2 )
colnames(plist)=c("K","V")
derivs <- function(t, state, pars) {
with(as.list(pars), {
intimes <- c(0,0.5,12)
input <- c(1200,0,0)
forc <- approxfun(intimes, input, method="constant",rule=2)
inp <- forc(t)
dy1 <- inp/V - K * state[1]
return(list(c(dy1)))
})
}
model <- function(pars, times=seq(0, 13, by = 0.05)) {
state <- c(a = 5 )
return(ode(y = state, times = times, func = derivs, parms = plist[i,],method="lsoda",rtol = 1e-8,atol =1e-8,hmax=0.05))
}
modelout <- list()
for (i in 1:nrow(plist))
modelout[[i]] <- model(plist)
out <-data.frame(modelout)
time <-out$time
out <-out[, grepl("^a", colnames(out))]
plot(time,out[,3],type="l")
Please provide some insights for the following: I would like to change the initial state variable during simulations for each time we move down one row in plist, ie: just like the parameters K and V change from row to row, I would also like the initial state variable to change by "putting" the initial state variables into plist like this:
plist <-matrix(c(0.08,0.07,0.09,15,20,25,3,5,6),ncol=3 )
colnames(plist)=c("K","V","state")
I would greatly appreciate your thoughts on how to incorporate this into the above model,
thanks,
Andras
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_______________________________________________
R-sig-dynamic-models mailing list
R-sig-dynamic-models at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-dynamic-models
_______________________________________________
R-sig-dynamic-models mailing list
R-sig-dynamic-models at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-dynamic-models