ccl4model {deSolve} | R Documentation |
the CCl4 inhalation model implemented in .Fortran
ccl4model(times, y, parms, ...)
times |
time sequence for which the model has to be integrated |
y |
the initial values for the state variables ("AI","AAM","AT","AF","AL","CLT" and "AM"), in that order. |
parms |
vector or list holding the ccl4 model parameters; see the example for the order in which these have to be defined |
... |
any other parameters passed to the integrator ode (which solves the model) |
The model is implemented primarily to demonstrate the linking of FORTRAN with R-code.
The source can be found in the ‘dynload’ subdirectory of the package.
R. Woodrow Setzer <setzer.woodrow@epa.gov>
try demo(CCL4model) for how this model has been fitted to the dataset ccl4data
aquaphy
, another Fortran model, describing growth in aquatic phytoplankton.
##==================================== ## parameter values ##==================================== Pm <- c( ### Physiological parameters BW= 0.182, # Body weight (kg) QP= 4.0 , # Alveolar ventilation rate (hr^-1) QC= 4.0 , # Cardiac output (hr^-1) VFC= 0.08, # Fraction fat tissue (kg/(kg/BW)) VLC= 0.04, # Fraction liver tissue (kg/(kg/BW)) VMC= 0.74, # Fraction of muscle tissue (kg/(kg/BW)) QFC= 0.05, # Fractional blood flow to fat ((hr^-1)/QC QLC= 0.15, # Fractional blood flow to liver ((hr^-1)/QC) QMC= 0.32, # Fractional blood flow to muscle ((hr^-1)/QC) ## Chemical specific parameters for chemical PLA= 16.17, # Liver/air partition coefficient PFA= 281.48, # Fat/air partition coefficient PMA= 13.3, # Muscle/air partition coefficient PTA= 16.17, # Viscera/air partition coefficient PB= 5.487, # Blood/air partition coefficient MW= 153.8, # Molecular weight (g/mol) VMAX= 0.04321671, # Max. velocity of metabolism (mg/hr) -calibrated KM= 0.4027255, # Michaelis-Menten constant (mg/l) -calibrated # Parameters for simulated experiment CONC= 1000, # Inhaled concentration KL= 0.02, # Loss rate from empty chamber /hr RATS= 1.0, # Number of rats enclosed in chamber VCHC= 3.8 # Volume of closed chamber (l) ) ##==================================== ## state variables ##==================================== y <- c(AI = 21, # total mass , mg AAM = 0, AT = 0, AF = 0, AL = 0, CLT = 0, ### area under the conc.-time curve in the liver AM = 0 ### the amount metabolized (AM) ) ##==================================== ## Model application ##==================================== times <- seq(0,6,by=0.1) # initial inhaled concentration-calibrated conc <- c(26.496,90.197,245.15,951.46) plot(ChamberConc ~ time,data=ccl4data,xlab="Time (hours)", xlim=range(c(0,ccl4data$time)), ylab="Chamber Concentration (ppm)", log="y",main = "ccl4model") for (cc in conc) { Pm["CONC"] <-cc VCH <- Pm[["VCHC"]] - Pm[["RATS"]]*Pm[["BW"]] AI0 <- VCH * Pm[["CONC"]]*Pm[["MW"]]/24450 y["AI"] <- AI0 # run the model: out <- as.data.frame(ccl4model(times,y,Pm)) lines(out$time,out$CP,lwd=2) } legend("topright",lty=c(NA,1),pch=c(1,NA),lwd=c(NA,2), legend=c("data","model"))