## ==========================================================================
## ex. 1
## ccl4model
## ==========================================================================
# Parameter values and initial conditions
# see example(ccl4model) for a more comprehensive implementation
Parms <- c(0.182, 4.0, 4.0, 0.08, 0.04, 0.74, 0.05, 0.15, 0.32,
16.17, 281.48, 13.3, 16.17, 5.487, 153.8, 0.04321671,
0.4027255, 1000, 0.02, 1.0, 3.8)
yini <- c( AI=21, AAM=0, AT=0, AF=0, AL=0, CLT=0, AM=0 )
# the rate of change
DLLfunc(y = yini, dllname = "deSolve", func = "derivsccl4",
initfunc = "initccl4", parms = Parms, times = 1,
nout = 3, outnames = c("DOSE", "MASS", "CP") )
## ==========================================================================
## ex. 2
## SCOC model, in fortran - to see the FORTRAN code:
## ==========================================================================
# Forcing function "data"
Flux <- matrix(ncol=2,byrow=TRUE,data=c(1, 0.654, 2, 0.167))
parms <- c(k=0.01)
Yini <- 60
DLLfunc(y=Yini, times=1, func = "scocder",
parms = parms, dllname = "deSolve",
initforc="scocforc", forcings=Flux,
initfunc = "scocpar", nout = 2,
outnames = c("Mineralisation","Depo"))
# correct value = dy = flux-k*y = 0.654-0.01*60
DLLfunc(y=Yini, times=2, func = "scocder",
parms = parms, dllname = "deSolve",
initforc="scocforc", forcings=Flux,
initfunc = "scocpar", nout = 2,
outnames = c("Mineralisation","Depo"))
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