R/ThreepParallelModel.R

#
# vim:set ff=unix expandtab ts=2 sw=2:
ThreepParallelModel=structure(
      function #Implementation of a three pool model with parallel structure
        ### The function creates a model for three 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 3 containing the decomposition rates for the 3 pools. 
       C0,	##<< A vector of length 3 containing the initial amount of carbon for the 3 pools.
       In,     ##<< A scalar or a data.frame object specifying the amount of litter inputs by time.
       gam1,   ##<< A scalar representing the partitioning coefficient, i.e. the proportion from the total amount of inputs that goes to pool 1.
       gam2,   ##<< A scalar representing the partitioning coefficient, i.e. the proportion from the total amount of inputs that goes to pool 2.
       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
      )
      {
        t_start=min(t)
        t_end=max(t)
        if(length(ks)!=3) stop("ks must be of length = 3")
        if(length(C0)!=3) stop("the vector with initial conditions must be of length = 3")
        if((gam1+gam2)^2 > 1) stop("The sum of the partitioning coefficients gam is outside the interval [0,1]")
        if(gam1 < 0 | gam2 < 0) stop("Partitioning coefficients gam must be positive")
        
        if(length(In)==1) inputrates_tm=BoundInFlux(
            function(t){matrix(nrow=3,ncol=1,c(gam1*In,gam2*In,(1-gam1-gam2)*In))},
            t_start,
            t_end
        )
        if(class(In)=="data.frame"){
         x=In[,1]  
         y=In[,2]  
         inputrate=function(t0){as.numeric(spline(x,y,xout=t0)[2])}
         inputrates_tm=BoundInFlux(
            function(t){matrix(nrow=3,ncol=1,c(gam1*inputrate(t),gam2*inputrate(t),(1-gam1-gam2)*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_tm=TimeMap.new(min(t),max(t),function(times){fX(t)*(-1*abs(ks))})  
        
     res=ParallelModel(t,coeffs_tm,startvalues=C0,inputrates_tm,solver,pass=pass)
   ### A  Model Object that can be further queried
   ##seealso<< \code{\link{TwopParallelModel}} and \code{\link{ParallelModel}} 
}
,
ex=function(){
      t_start=0 
      t_end=10 
      tn=50
      timestep=(t_end-t_start)/tn 
      t=seq(t_start,t_end,timestep) 

      Ex=ThreepParallelModel(t,ks=c(k1=0.5,k2=0.2,k3=0.1),
                             C0=c(c10=100, c20=150,c30=50),In=20,gam1=0.7,gam2=0.1,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)
      lines(t,Ct[,3],col=3)
      legend("topright",c("Total C","C in pool 1", "C in pool 2","C in pool 3"),
             lty=c(1,1,1,1),col=c(1,2,4,3),lwd=c(2,1,1,1),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)
      lines(t,Rt[,3],col=3)
      legend("topright",c("Total C release","C release from pool 1",
             "C release from pool 2","C release from pool 3"),
              lty=c(1,1,1,1),col=c(1,2,4,3),lwd=c(2,1,1,1),bty="n")
}
)       

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SoilR documentation built on May 29, 2017, 10:57 a.m.