R/OnepModel.R

In SoilR: Models of Soil Organic Matter Decomposition

#' Implementation of a one pool model
#' 
#' This function creates a model for one pool. It is a wrapper for the more
#' general function \code{\link{GeneralModel}}.
#' 
#' 
#' @param t A vector containing the points in time where the solution is
#' sought.
#' @param k A scalar with the decomposition rate of the pool.
#' @param C0 A scalar containing the initial amount of carbon in the pool.
#' @param In A scalar or a data.frame object specifying the amount of litter
#' inputs by time.
#' @param xi A scalar or a data.frame specifying the external (environmental
#' and/or edaphic) effects on decomposition rates.
#' @param solver A function that solves the system of ODEs. This can be
#' \code{\link{euler}} or \code{\link{deSolve.lsoda.wrapper}} or any other user
#' provided function with the same interface.
#' @param pass if TRUE forces the constructor to create the model even if it is
#' invalid
#' @seealso There are other \code{\link{predefinedModels}} and also more
#' general functions like \code{\link{Model}}.
#' @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.
#' @examples
#' t_start=0 
#' t_end=10 
#' tn=50
#' timestep=(t_end-t_start)/tn 
#' t=seq(t_start,t_end,timestep) 
#' k=0.8
#' C0=100
#' In = 30
#' 
#' 
#' Ex=OnepModel(t,k,C0,In)
#' Ct=getC(Ex)
#' Rt=getReleaseFlux(Ex)
#' Rc=getAccumulatedRelease(Ex)
#' 
#' plot(
#' t,
#' Ct,
#' type="l",
#' ylab="Carbon stocks (arbitrary units)",
#' xlab="Time (arbitrary units)",
#' lwd=2
#' ) 
#' 
#' plot(
#' t,
#' Rt,
#' type="l",
#' ylab="Carbon released (arbitrary units)",
#' xlab="Time (arbitrary units)",
#' lwd=2
#' ) 
#' 
#' plot(
#' t,
#' Rc,
#' type="l",
#' ylab="Cummulative carbon released (arbitrary units)",
#' xlab="Time (arbitrary units)",
#' lwd=2
#' ) 
OnepModel<- function 
     (t,  		
      k,	
      C0,	
      In,     
      xi=1,   
      solver=deSolve.lsoda.wrapper,  
      pass=FALSE  
    )	
    { 
      t_start=min(t)
      t_end=max(t)
      if(length(k)!=1) stop("k must be a scalar (length == 1)")
      if(length(C0)!=1) stop("initial conditions must be of length = 1")
      C0=c(C0)
      if(length(In)==1){
          inputFluxes=BoundInFluxes(
            function(t){matrix(nrow=1,ncol=1,In)},
            t_start,
            t_end
        )
      }
      if(inherits(In, "data.frame")){
         x=In[,1]  
         y=In[,2]  
         inputFlux=splinefun(x,y)
          inputFluxes=BoundInFluxes(
            function(t){matrix(nrow=1,ncol=1,inputFlux(t))},
            min(x),
            max(x)
          )
        }
      A=-1*abs(matrix(k,1,1))
      if(length(xi)==1) fX=function(t){xi}
      if(inherits(xi, "data.frame")){
      X=xi[,1]
      Y=xi[,2]
      fX=splinefun(X,Y)
      }
      Af=BoundLinDecompOp(
        function(t){fX(t)*A},
        t_start,
        t_end
      )
      Mod=GeneralModel(t=t,A=Af,ivList=C0,inputFluxes=inputFluxes,solver,pass)
      return(Mod)
    }