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-rw-r--r--NAMESPACE2
-rw-r--r--NEWS.md2
-rw-r--r--R/mkinpredict.R77
-rw-r--r--man/mkinpredict.Rd42
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 }

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