Make mkinpredict generic and write a method for fits

1 files changed, 52 insertions, 25 deletions

diff --git a/R/mkinpredict.R b/R/mkinpredict.R
index 994af703..8e0823a8 100644
--- a/R/mkinpredict.R
+++ b/R/mkinpredict.R
@@ -1,4 +1,4 @@
-# Copyright (C) 2010-2015 Johannes Ranke
+# Copyright (C) 2010-2016,2018 Johannes Ranke
 # Some lines in this code are copyright (C) 2013 Eurofins Regulatory AG
 # Contact: jranke@uni-bremen.de
 
@@ -17,14 +17,28 @@
 # You should have received a copy of the GNU General Public License along with
 # this program. If not, see <http://www.gnu.org/licenses/>
 
-mkinpredict <- function(mkinmod, odeparms, odeini,
-			outtimes, solution_type = "deSolve",
-      use_compiled = "auto",
-			method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
-			map_output = TRUE, ...) {
+mkinpredict <- function(x, odeparms, odeini,
+  outtimes = seq(0, 120, by = 0.1),
+  solution_type = "deSolve",
+  use_compiled = "auto",
+  method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
+  map_output = TRUE, ...)
+{
+  UseMethod("mkinpredict", x)
+}
+
+mkinpredict.mkinmod <- function(x,
+  odeparms = c(k_parent_sink = 0.1),
+  odeini = c(parent = 100),
+  outtimes = seq(0, 120, by = 0.1),
+  solution_type = "deSolve",
+  use_compiled = "auto",
+  method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
+  map_output = TRUE, ...)
+{
 
   # Get the names of the state variables in the model
-  mod_vars <- names(mkinmod$diffs)
+  mod_vars <- names(x$diffs)
 
   # Order the inital values for state variables if they are named
   if (!is.null(names(odeini))) {
@@ -40,22 +54,22 @@ mkinpredict <- function(mkinmod, 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]]
+    parent.type = names(x$map[[1]])[1]
+    parent.name = names(x$diffs)[[1]]
     o <- switch(parent.type,
       SFO = SFO.solution(outtimes,
           evalparse(parent.name),
-          ifelse(mkinmod$use_of_ff == "min",
-	    evalparse(paste("k", parent.name, "sink", sep="_")),
-	    evalparse(paste("k", parent.name, sep="_")))),
+          ifelse(x$use_of_ff == "min",
+      evalparse(paste("k", parent.name, "sink", sep="_")),
+      evalparse(paste("k", parent.name, sep="_")))),
       FOMC = FOMC.solution(outtimes,
           evalparse(parent.name),
           evalparse("alpha"), evalparse("beta")),
       IORE = IORE.solution(outtimes,
           evalparse(parent.name),
-          ifelse(mkinmod$use_of_ff == "min",
-	    evalparse(paste("k__iore", parent.name, "sink", sep="_")),
-	    evalparse(paste("k__iore", parent.name, sep="_"))),
+          ifelse(x$use_of_ff == "min",
+      evalparse(paste("k__iore", parent.name, "sink", sep="_")),
+      evalparse(paste("k__iore", parent.name, sep="_"))),
             evalparse("N_parent")),
       DFOP = DFOP.solution(outtimes,
           evalparse(parent.name),
@@ -75,7 +89,7 @@ mkinpredict <- function(mkinmod, odeparms, odeini,
     names(out) <- c("time", sub("_free", "", parent.name))
   }
   if (solution_type == "eigen") {
-    coefmat.num <- matrix(sapply(as.vector(mkinmod$coefmat), evalparse),
+    coefmat.num <- matrix(sapply(as.vector(x$coefmat), evalparse),
       nrow = length(mod_vars))
     e <- eigen(coefmat.num)
     c <- solve(e$vectors, odeini)
@@ -88,14 +102,14 @@ mkinpredict <- function(mkinmod, odeparms, odeini,
     names(out) <- c("time", mod_vars)
   }
   if (solution_type == "deSolve") {
-    if (!is.null(mkinmod$cf) & use_compiled[1] != FALSE) {
+    if (!is.null(x$cf) & use_compiled[1] != FALSE) {
       out <- ode(
         y = odeini,
         times = outtimes,
         func = "func",
         initfunc = "initpar",
-        dllname = getDynLib(mkinmod$cf)[["name"]],
-        parms = odeparms[mkinmod$parms], # Order matters when using compiled models
+        dllname = getDynLib(x$cf)[["name"]],
+        parms = odeparms[x$parms], # Order matters when using compiled models
         method = method.ode,
         atol = atol,
         rtol = rtol,
@@ -106,11 +120,11 @@ mkinpredict <- function(mkinmod, odeparms, odeini,
 
         time <- t
         diffs <- vector()
-        for (box in names(mkinmod$diffs))
+        for (box in names(x$diffs))
         {
           diffname <- paste("d", box, sep="_")
           diffs[diffname] <- with(as.list(c(time, state, parms)),
-            eval(parse(text=mkinmod$diffs[[box]])))
+            eval(parse(text=x$diffs[[box]])))
         }
         return(list(c(diffs)))
       }
@@ -127,17 +141,17 @@ mkinpredict <- function(mkinmod, odeparms, odeini,
     }
     if (sum(is.na(out)) > 0) {
       stop("Differential equations were not integrated for all output times because\n",
-	   "NaN values occurred in output from ode()")
+     "NaN values occurred in output from ode()")
       }
   }
   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_type == "analytical") {
+    for (var in names(x$map)) {
+      if((length(x$map[[var]]) == 1) || solution_type == "analytical") {
         out_mapped[var] <- out[, var]
       } else {
-        out_mapped[var] <- rowSums(out[, mkinmod$map[[var]]])
+        out_mapped[var] <- rowSums(out[, x$map[[var]]])
       }
     }
     return(out_mapped)
@@ -145,3 +159,16 @@ mkinpredict <- function(mkinmod, odeparms, odeini,
     return(out)
   }
 }
+
+mkinpredict.mkinfit <- function(x,
+  odeparms = x$bparms.ode,
+  odeini = x$bparms.state,
+  outtimes = seq(0, 120, by = 0.1),
+  solution_type = "deSolve",
+  use_compiled = "auto",
+  method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
+  map_output = TRUE, ...)
+{
+  mkinpredict(x$mkinmod, odeparms, odeini, outtimes, solution_type, use_compiled,
+              method.ode, atol, rtol, map_output, ...)
+}