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authorJohannes Ranke <jranke@uni-bremen.de>2020-11-07 11:54:13 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2020-11-07 11:54:13 +0100
commitcda47972e2b6a9610e3118dcd2270d7a1c76de3d (patch)
tree171a0bf2f7386b5451a581a40667bdb6a5d5a991 /R/saemix.R
parentfcf06c40ec314e91ad3fdae3392f008509d70b2e (diff)
Make deSolve predictions within saemix robust
Also, exclude the saemix function when loading saemix in the example code, to prevent overriding our generic
Diffstat (limited to 'R/saemix.R')
-rw-r--r--R/saemix.R36
1 files changed, 23 insertions, 13 deletions
diff --git a/R/saemix.R b/R/saemix.R
index 7a225601..280490a0 100644
--- a/R/saemix.R
+++ b/R/saemix.R
@@ -18,13 +18,18 @@
#' @param object An [mmkin] row object containing several fits of the same
#' [mkinmod] model to different datasets
#' @param verbose Should we print information about created objects?
+#' @param cores The number of cores to be used for multicore processing using
+#' [parallel::mclapply()]. Using more than 1 core is experimental and may
+#' lead to uncontrolled forking, apparently depending on the BLAS version
+#' used.
#' @param \dots Further parameters passed to [saemix::saemixData]
#' and [saemix::saemixModel].
#' @return An [saemix::SaemixObject].
#' @examples
#' \dontrun{
-#' # We do not load the saemix package, as this would override our saemix
-#' # generic
+#' # We can load saemix, but should exclude the saemix function
+#' # as it would mask our generic version of it
+#' library(saemix, exclude = "saemix")
#' ds <- lapply(experimental_data_for_UBA_2019[6:10],
#' function(x) subset(x$data[c("name", "time", "value")]))
#' names(ds) <- paste("Dataset", 6:10)
@@ -37,18 +42,25 @@
#' f_saemix_fomc <- saemix(f_mmkin_parent["FOMC", ])
#' f_saemix_dfop <- saemix(f_mmkin_parent["DFOP", ])
#'
-#' # We can use functions from the saemix package by prepending saemix::
-#' saemix::compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop))
+#' # As this returns an SaemixObject, we can use functions from saemix
+#' compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop))
#'
#' f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
#' f_saemix_fomc_tc <- saemix(f_mmkin_parent_tc["FOMC", ])
-#' saemix::compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc))
+#' compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc))
#'
#' dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
#' A1 = mkinsub("SFO"))
-#' f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE)
+#' f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "analytical")
+#' # This takes about 4 minutes on my system
#' f_saemix <- saemix(f_mmkin)
#'
+#' # Using a single core, it takes about 6 minutes, using 10 cores it is slower
+#' # instead of faster
+#' f_mmkin_des <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "deSolve")
+#' f_saemix_des <- saemix(f_mmkin_des, cores = 1)
+#' compare.saemix(list(f_saemix, f_saemix_des))
+#'
#' }
#' @export
saemix <- function(model, data, control, ...) UseMethod("saemix")
@@ -58,9 +70,10 @@ saemix <- function(model, data, control, ...) UseMethod("saemix")
saemix.mmkin <- function(model, data,
control = list(displayProgress = FALSE, print = FALSE,
save = FALSE, save.graphs = FALSE),
+ cores = 1,
verbose = FALSE, suppressPlot = TRUE, ...)
{
- m_saemix <- saemix_model(model, verbose = verbose)
+ m_saemix <- saemix_model(model, cores = cores, verbose = verbose)
d_saemix <- saemix_data(model, verbose = verbose)
if (suppressPlot) {
# We suppress the log-likelihood curve that saemix currently
@@ -74,15 +87,10 @@ saemix.mmkin <- function(model, data,
dev.off()
unlink(tmp)
}
- class(result) <- c("saemix.mmkin", "saemix")
return(result)
}
#' @rdname saemix
-#' @param cores The number of cores to be used for multicore processing using
-#' [parallel::mclapply()]. Using more than 1 core is experimental and may
-#' lead to uncontrolled forking, apparently depending on the BLAS version
-#' used.
#' @return An [saemix::SaemixModel] object.
#' @export
saemix_model <- function(object, cores = 1, verbose = FALSE, ...) {
@@ -203,7 +211,9 @@ saemix_model <- function(object, cores = 1, verbose = FALSE, ...) {
out_wide <- mkinpredict(mkin_model,
odeparms = odeparms, odeini = odeini,
solution_type = solution_type,
- outtimes = sort(unique(i_time)))
+ outtimes = sort(unique(i_time)),
+ na_stop = FALSE
+ )
out_index <- cbind(as.character(i_time), as.character(i_name))
out_values <- out_wide[out_index]

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