R/calcD.R

In TIMP: Fitting Separable Nonlinear Models in Spectroscopy and Microscopy

"calcD" <- function(kincoeffs, times, cstart, rsmatrix, smatrix) {
  ## contributed by David Nicolaides <dnicolaides@accelrys.com>
  ## in modified form, along with other options for 2nd order modeling
  ns <- length(cstart)
  np <- length(kincoeffs)

  ## we need to pass our kinetic model the stoichiometry matrices,
  ## as well as the kinetic coefficients
  parms <- c(rsmatrix, smatrix, kincoeffs, ns, np)

  Model <- function(times, conc, parms) {
    ## get s-matrices as matrices first
    rsm <- rsmatrix
    dim(rsm) <- c(ns, np)
    rsm <- t(rsm)
    sm <- smatrix
    dim(sm) <- c(ns, np)
    sm <- t(sm)
    ## now calculate the nu vectors
    nu <- rep(0, np)
    ## Note: R correctly handles 0^0 (= 1)
    for (j in 1:np) {
      nu[j] <- kincoeffs[j] * prod(conc^rsm[j, ])
    }

    ## then calculate the sums over the nu variables to get the derivatives
    result <- rep(0, ns)
    for (j in 1:np) {
      result <- result + sm[j, ] * nu[j]
    }
    list(result)
  }

  c.temp <- lsoda(y = cstart, times = times, func = Model, parms = parms)
  c.temp <- c.temp[, -1]
  colnames(c.temp) <- vector()

  c.temp
}