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# vim:set ff=unix expandtab ts=2 sw=2:
TwopParallelModel<-structure(
function #Implementation of a linear two pool model with parallel structure
### This function creates a model for two independent (parallel) pools.
### It is a wrapper for the more general function \code{\link{ParallelModel}} that can handle an arbitrary number of pools.
##references<< Sierra, C.A., M. Mueller, S.E. Trumbore. 2012. Models of soil organic matter decomposition: the SoilR package version 1.0. Geoscientific Model Development 5, 1045-1060.
(t, ##<< A vector containing the points in time where the solution is sought.
ks, ##<< A vector of length 2 containing the decomposition rates for the 2 pools.
C0, ##<< A vector of length 2 containing the initial amount of carbon for the 2 pools.
In, ##<< A scalar or a data.frame object specifying the amount of litter inputs by time.
gam, ##<< A scalar representing the partitioning coefficient, i.e. the proportion from the total amount of inputs that goes to pool 1.
xi=1, ##<< A scalar or a data.frame specifying the external (environmental and/or edaphic) effects on decomposition rates.
solver=deSolve.lsoda.wrapper, ##<< A function that solves the system of ODEs. This can be \code{\link{euler}} or \code{\link{ode}} or any other user provided function with the same interface.
pass=FALSE ##<< Forces the constructor to create the model even if it is invalid
)
{
t_start=min(t)
t_stop=max(t)
if(length(ks)!=2) stop("ks must be of length = 2")
if(length(C0)!=2) stop("the vector with initial conditions must be of length = 2")
if(gam > 1 | gam < 0) stop("The the partitioning coefficient gam is outside the interval [0,1]")
if(length(In)==1) inputrates=BoundInFlux(
function(t){matrix(nrow=2,ncol=1,c(gam*In,(1-gam)*In))},
t_start,
t_stop
)
if(class(In)=="data.frame"){
x=In[,1]
y=In[,2]
inputrate=function(t0){as.numeric(spline(x,y,xout=t0)[2])}
inputrates=BoundInFlux(
function(t){
matrix(nrow=2,ncol=1,
c(
gam*inputrate(t),
(1-gam)*inputrate(t)
)
)
},
min(x),
max(x)
)
}
if(length(xi)==1) fX=function(t){xi}
if(class(xi)=="data.frame"){
X=xi[,1]
Y=xi[,2]
fX=function(t){as.numeric(spline(X,Y,xout=t)[2])}
}
coeffs=TimeMap(
function(t){fX(t)*(-1*abs(ks))},
t_start,
t_stop
)
obj=ParallelModel(t,coeffs,startvalues=C0,inputrates,solver,pass=pass)
### A Model Object that can be further queried
##seealso<< \code{\link{ThreepParallelModel}}
}
,
ex=function(){
t_start=0
t_end=10
tn=50
timestep=(t_end-t_start)/tn
t=seq(t_start,t_end,timestep)
Ex=TwopParallelModel(t,ks=c(k1=0.5,k2=0.2),C0=c(c10=100, c20=150),In=10,gam=0.7,xi=0.5)
Ct=getC(Ex)
plot(t,rowSums(Ct),type="l",lwd=2,
ylab="Carbon stocks (arbitrary units)",xlab="Time",ylim=c(0,sum(Ct[1,])))
lines(t,Ct[,1],col=2)
lines(t,Ct[,2],col=4)
legend("topright",c("Total C","C in pool 1", "C in pool 2"),
lty=c(1,1,1),col=c(1,2,4),lwd=c(2,1,1),bty="n")
Rt=getReleaseFlux(Ex)
plot(t,rowSums(Rt),type="l",ylab="Carbon released (arbitrary units)",
xlab="Time",lwd=2,ylim=c(0,sum(Rt[1,])))
lines(t,Rt[,1],col=2)
lines(t,Rt[,2],col=4)
legend("topleft",c("Total C release","C release from pool 1", "C release from pool 2"),
lty=c(1,1,1),col=c(1,2,4),lwd=c(2,1,1),bty="n")
}
)
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