[R] Error in eval(expr, envir, enclos) : object 'N' not found

[Uwe Ligges]

hansoffate wrote:
> I'm running an LSODA to generate some graphs, but I need to stop at a certain
> point and use those values to generate another LSODA output.  This is
> working fine, but when I try to run the second LSODA, I get the "Error in
> eval(expr, envir, enclos) : object 'N' not found".  Any ideas what can be
> causing this? I have no object 'N' anywhere in the script.  

At least I see capital N in both model and model2 - roughly 10 times ...

Uwe Ligges



I made an
> identical version of models states, parameters, and everything just by
> adding 2 after each one, and I'm still getting this error.  
> 
> Thanks,
> -Hans
> 
> ::CODE::
> require(odesolve);
> ###Params for running script ##
> iniT=1E3; iniN=10; iniM=0; iniC=1E3;
> num_days = 30; interval_size = .1; OF_prcnt = .10;
> 
> model <- function(t, state, pars)
> {
>   with (as.list(c(state, pars)), {
> 	dT=(a*T-a*T*b*T) - (c1*N*T) - (Kt*M*T)
> 	dN=a1 - (f*N) + g * (T/(h+T)) * N - (p * N * T) - (Kn * M * N)
> 	dC=a2 - (beta * C) - (Kc * M  * C)
> 	dM= -(gamma) * M + Vm 
> 	
>     return(list(c(dT,dN,dC,dM)))
>   })
> }
> 
> model2 <- function(t, state2, pars2)
> {
>   with (as.list(c(state2, pars2)), {
> 	dT=(a*T-a*T*b*T) - (c1*N*T) - (Kt*M*T)
> 	dN=a1 - (f*N) + g * (T/(h+T)) * N - (p * N * T) - (Kn * M * N)
> 	dC=a2 - (beta * C) - (Kc * M  * C)
> 	dM= -(gamma) * M + Vm 
> 	
>     return(list(c(dT,dN,dC,dM)))
>   })
> }
> 
> ### First Half - Tumor growth to 10%
> pars <- list( Tini=iniT, Nini=iniN, Mini=iniM, Cini=iniC,
> 		  a=4.31E-3, b=1.02E-14, c1=3.41E-10, Kt=8E-1,
>               f=4.12E-2, g=1.5E-2, h=2.02E1, beta=1.20E-2, gamma=9E-1,
> 		  Kc=6E-1, Kn=6E-1, p=2E-11, a1=1.2E4, a2=7.5E8, Vm=0 )
> 
> tout    <- seq(0, num_days, by=interval_size)
> state   <- c(T = pars$Tini, N = pars$Nini, C = pars$Cini, M = pars$Mini)
> out     <- lsoda(state, tout, model, pars)
> 
> ## Finding position at which OF function is reached
> final_matrix = out;
> loopsize = (num_days / interval_size) + 1
> OF_tumor_size = iniT + (OF_prcnt * iniT)
> 
> ## Sentinel Value to find at which row in the matrix reaches OF_tumor_size
> OF_row=-1;  
> for(i in 1:loopsize) {
>   if( out[i,2] >= OF_tumor_size) {
>     OF_row=i;
>     break;
>   }
> }
> 
> if(OF_row != -1) {
>   ##Params setup
>   OF_iniT=out[OF_row,2]; OF_iniN=out[OF_row,3]; OF_iniC=out[OF_row,4];
> OF_iniM=out[OF_row,5];
>   pars2 <- list( Tini=OF_iniT, Nini=OF_iniN, Mini=OF_iniM, Cini=OF_iniC,
> 	          a=4.31E-3, b=1.02E-14, c1=3.41E-10, Kt=8E-1,
>                 f=4.12E-2, g=1.5E-2, h=2.02E1, beta=1.20E-2, gamma=9E-1,
> 		    Kc=6E-1, Kn=6E-1, p=2E-11, a1=1.2E4, a2=7.5E8, Vm=0 )
>   state2   <- c(T = pars2$Tini, N = pars2$Nini, C = pars2$Cini, M =
> pars2$Mini)
>   out2     <- lsoda(state2, tout, model2, pars2)
> }
>