Make mkinpredict generic and write a method for fits

4 files changed, 82 insertions, 41 deletions

diff --git a/NAMESPACE b/NAMESPACE
index 458d5310..cfbe2851 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -7,6 +7,8 @@ S3method(summary, mkinfit)
 S3method(print, summary.mkinfit)
 S3method(plot, mmkin)
 S3method("[", mmkin)
+S3method(mkinpredict, mkinmod)
+S3method(mkinpredict, mkinfit)
 
 import(
   stats,
diff --git a/NEWS.md b/NEWS.md
index 780ee5ac..8372a8b5 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -4,6 +4,8 @@
 
 - 'max_twa_parent': Support maximum time weighted average concentration calculations for the hockey stick (HS) model
 
+- 'mkinpredict': Make the function generic and create a method for mkinfit objects
+
 # mkin 0.9.47.5 (2018-09-14)
 
 - Make the two-component error model stop in cases where it is inadequate to avoid nls crashes on windows
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, ...)
+}
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index 524abbb5..24b918dc 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -1,5 +1,7 @@
 \name{mkinpredict}
 \alias{mkinpredict}
+\alias{mkinpredict.mkinmod}
+\alias{mkinpredict.mkinfit}
 \title{
   Produce predictions from a kinetic model using specific parameters
 }
@@ -9,13 +11,15 @@
   kinetic parameters and initial values for the state variables.
 }
 \usage{
-  mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve",
-	      use_compiled = "auto", method.ode = "lsoda", atol = 1e-08, rtol = 1e-10,
-        map_output = TRUE, ...)
+  mkinpredict(x, odeparms, odeini, outtimes = seq(0, 120, by = 0.1),
+    solution_type = "deSolve", use_compiled = "auto", method.ode = "lsoda",
+    atol = 1e-08, rtol = 1e-10, map_output = TRUE, ...)
 }
 \arguments{
-  \item{mkinmod}{
-    A kinetic model as produced by \code{\link{mkinmod}}.
+  \item{x}{
+    A kinetic model as produced by \code{\link{mkinmod}}, or a kinetic
+    fit as fitted by \code{\link{mkinfit}}. In the latter case, the fitted
+    parameters are used for the prediction.
   }
   \item{odeparms}{
     A numeric vector specifying the parameters used in the kinetic model, which
@@ -69,35 +73,35 @@
   Johannes Ranke
 }
 \examples{
-  SFO <- mkinmod(degradinol = list(type = "SFO"))
+  SFO <- mkinmod(degradinol = mkinsub("SFO"))
   # Compare solution types
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      solution_type = "analytical")
+        solution_type = "analytical")
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      solution_type = "deSolve")
+        solution_type = "deSolve")
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      solution_type = "deSolve", use_compiled = FALSE)
+        solution_type = "deSolve", use_compiled = FALSE)
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      solution_type = "eigen")
+        solution_type = "eigen")
 
 
   # Compare integration methods to analytical solution
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      solution_type = "analytical")[21,]
+        solution_type = "analytical")[21,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      method = "lsoda")[21,]
+        method = "lsoda")[21,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      method = "ode45")[21,]
+        method = "ode45")[21,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-	      method = "rk4")[21,]
+        method = "rk4")[21,]
  # rk4 is not as precise here
 
   # The number of output times used to make a lot of difference until the
   # default for atol was adjusted
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
-	      seq(0, 20, by = 0.1))[201,]
+        seq(0, 20, by = 0.1))[201,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
-	      seq(0, 20, by = 0.01))[2001,]
+        seq(0, 20, by = 0.01))[2001,]
 
   # Check compiled model versions - they are faster than the eigenvalue based solutions!
   SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
@@ -114,5 +118,11 @@
     print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
                 c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
                 solution_type = "deSolve", use_compiled = FALSE)[201,]))
+
+  \dontrun{
+    # Predict from a fitted model
+    f <- mkinfit(SFO_SFO, FOCUS_2006_C)
+    head(mkinpredict(f))
+  }
 }
 \keyword{ manip }