- Separated model prediction out into a separate function

- Created separate functions for parameter transformations (not documented yet)
- Fitting of analytical models works
- SFO_SFO model works, complex models do not at the moment
- summary.mkinfit not operational at the moment



git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@21 edb9625f-4e0d-4859-8d74-9fd3b1da38cb

1 files changed, 89 insertions, 0 deletions

diff --git a/R/predict.mkinmod.R b/R/predict.mkinmod.R
new file mode 100644
index 00000000..279fa525
--- /dev/null
+++ b/R/predict.mkinmod.R
@@ -0,0 +1,89 @@
+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)
+  }
+}