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+predict.mkinmod <- function(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve", map_output = TRUE, atol = 1e-6) {
+
+ # Get the names of the state variables in the model
+ mod_vars <- names(mkinmod$diffs)
+
+ # Create function for evaluation of expressions with ode parameters and initial values
+ evalparse <- function(string)
+ {
+ eval(parse(text=string), as.list(c(odeparms, odeini)))
+ }
+
+ # Create a function calculating the differentials specified by the model
+ # if necessary
+ if (solution_type == "analytical") {
+ parent.type = names(mkinmod$map[[1]])[1]
+ parent.name = names(mkinmod$diffs)[[1]]
+ o <- switch(parent.type,
+ SFO = SFO.solution(outtimes,
+ evalparse(parent.name),
+ evalparse(paste("k", parent.name, sep="_"))),
+ FOMC = FOMC.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("alpha"), evalparse("beta")),
+ DFOP = DFOP.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("k1"), evalparse("k2"),
+ evalparse("g")),
+ HS = HS.solution(outtimes,
+ evalparse(parent.name),
+ evalparse("k1"), evalparse("k2"),
+ evalparse("tb")),
+ SFORB = SFORB.solution(outtimes,
+ evalparse(parent.name),
+ evalparse(paste("k", parent.name, "bound", sep="_")),
+ evalparse(paste("k", sub("free", "bound", parent.name), "free", sep="_")),
+ evalparse(paste("k", parent.name, sep="_")))
+ )
+ out <- cbind(outtimes, o)
+ dimnames(out) <- list(outtimes, c("time", sub("_free", "", parent.name)))
+ }
+ if (solution_type == "eigen") {
+ coefmat.num <- matrix(sapply(as.vector(mkinmod$coefmat), evalparse),
+ nrow = length(mod_vars))
+ e <- eigen(coefmat.num)
+ c <- solve(e$vectors, odeini)
+ f.out <- function(t) {
+ e$vectors %*% diag(exp(e$values * t), nrow=length(mod_vars)) %*% c
+ }
+ o <- matrix(mapply(f.out, outtimes),
+ nrow = length(mod_vars), ncol = length(outtimes))
+ dimnames(o) <- list(mod_vars, outtimes)
+ out <- cbind(time = outtimes, t(o))
+ }
+ if (solution_type == "deSolve") {
+ mkindiff <- function(t, state, parms) {
+
+ time <- t
+ diffs <- vector()
+ for (box in names(mkinmod$diffs))
+ {
+ diffname <- paste("d", box, sep="_")
+ diffs[diffname] <- with(as.list(c(time, state, parms)),
+ eval(parse(text=mkinmod$diffs[[box]])))
+ }
+ return(list(c(diffs)))
+ }
+ out <- ode(
+ y = odeini,
+ times = outtimes,
+ func = mkindiff,
+ parms = odeparms,
+ atol = atol
+ )
+ }
+ if (map_output) {
+ # Output transformation for models with unobserved compartments like SFORB
+ out_mapped <- data.frame(time = out[,"time"])
+ for (var in names(mkinmod$map)) {
+ if((length(mkinmod$map[[var]]) == 1) || solution == "analytical") {
+ out_mapped[var] <- out[, var]
+ } else {
+ out_mapped[var] <- rowSums(out[, mkinmod$map[[var]]])
+ }
+ }
+ return(out_mapped)
+ } else {
+ return(out)
+ }
+}

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