Add mmkin for testing

3 files changed, 113 insertions, 1 deletions

diff --git a/NEWS.md b/NEWS.md
index ad3d631d..b00f5518 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,8 @@
 # CHANGES in mkin VERSION 0.9-39
 
- 
+## MAJOR CHANGES
+
+- New function `mmkin()`: This function takes a character vector of model shorthand names, or alternatively a list of mkinmod models, as well as a list of dataset as main arguments. It returns a matrix of mkinfit objects, with a row for each model and a column for each dataset.
 
 # CHANGES in mkin VERSION 0.9-38
 
diff --git a/R/mmkin.R b/R/mmkin.R
new file mode 100644
index 00000000..fe9db194
--- /dev/null
+++ b/R/mmkin.R
@@ -0,0 +1,46 @@
+mmkin <- function(models = c("SFO", "FOMC", "DFOP"), datasets, 
+                  cores = round(detectCores()/2), cluster = NULL, ...) 
+{
+  parent_models_available = c("SFO", "FOMC", "DFOP", "HS", "SFORB", "IORE") 
+  n.m <- length(models)
+  n.d <- length(datasets)
+  n.fits <- n.m * n.d
+  fit_indices <- matrix(1:n.fits, ncol = n.d)
+
+  # Check models and define their names
+  if (!all(sapply(models, function(x) inherits(x, "mkinmod")))) {
+    if (!all(models %in% parent_models_available)) {
+      stop("Please supply models as a list of mkinmod objects or a vector combined of\n  ",
+           paste(parent_models_available, collapse = ", ")) 
+    } else {
+      names(models) <- models
+    } 
+  } else {
+    if (is.null(names(models))) names(models) <- as.character(1:n.m)
+  }
+
+  # Check datasets and define their names
+  if (is.null(names(datasets))) names(datasets) <- as.character(1:n.d)
+
+  # Define names for fit index
+  dimnames(fit_indices) <- list(model = names(models),
+                                dataset = names(datasets))
+
+
+  fit_function <- function(fit_index) {
+    w <- which(fit_indices == fit_index, arr.ind = TRUE)
+    model_index <- w[1]
+    dataset_index <- w[2]
+    mkinfit(models[[model_index]], datasets[[dataset_index]], ...)
+  }
+
+  if (is.null(cluster)) {
+    results <- mclapply(as.list(1:n.fits), fit_function, mc.cores = cores)
+  } else {
+    results <- parLapply(cluster, list(1:n.fit), fit_function)
+  }
+
+  attributes(results) <- attributes(fit_indices)
+  class(results) <- "mmkin"
+  return(results)
+}
diff --git a/man/mmkin.Rd b/man/mmkin.Rd
new file mode 100644
index 00000000..64e7ae27
--- /dev/null
+++ b/man/mmkin.Rd
@@ -0,0 +1,64 @@
+\name{mmkin}
+\alias{mmkin}
+\title{
+  Fit one or more kinetic models with one or more state variables to one or more datasets
+}
+\description{
+  This code calls \code{\link{mkinfit}} on each combination of model and dataset
+  given in its first two arguments.
+}
+\usage{
+mmkin(models, datasets,
+      cores = round(detectCores()/2), cluster = NULL, ...)
+}
+\arguments{
+  \item{models}{
+    Either a character vector of shorthand names ("SFO", "FOMC", "DFOP",
+    "HS", "SFORB"), or an optionally named list of \code{\link{mkinmod}}
+    objects.
+  }
+  \item{datasets}{
+    An optionally named list of datasets suitable as observed data for
+    \code{\link{mkinfit}}.
+  }
+  \item{cores}{
+    The number of cores to be used for multicore processing. This is only
+    used when the \code{cluster} argument is \code{NULL}.
+  }
+  \item{cluster}{
+    A cluster as returned by \code{link{makeCluster}} to be used for parallel 
+    execution.
+  }
+  \item{\dots}{
+    Further arguments that will be passed to \code{\link{mkinfit}}. 
+  }
+}
+\value{
+  A matrix of "mkinfit" objects that can be indexed using the 
+  model and dataset names as row and column indices.
+}
+\author{
+  Johannes Ranke
+}
+\examples{
+\dontrun{
+m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
+                           M1 = list(type = "SFO", to = "M2"),
+                           M2 = list(type = "SFO"), use_of_ff = "max")
+
+m_synth_FOMC_lin <- mkinmod(parent = list(type = "FOMC", to = "M1"),
+                           M1 = list(type = "SFO", to = "M2"),
+                           M2 = list(type = "SFO"), use_of_ff = "max")
+
+models <- list(SFO_lin = m_synth_SFO_lin, FOMC_lin = m_synth_FOMC_lin)
+datasets <- lapply(synthetic_data_for_UBA_2014[1:3], function(x) x$data)
+
+time_default <- system.time(fits <- mmkin(models, datasets))
+time_1 <- system.time(fits.1 <- mmkin(models, datasets, cores = 1))
+
+time_default
+time_1
+
+endpoints(fits[["SFO_lin", 2]])
+}
+\keyword{ optimize }