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-rw-r--r--R/saemix.R213
1 files changed, 137 insertions, 76 deletions
diff --git a/R/saemix.R b/R/saemix.R
index f8714cf2..8632c1a4 100644
--- a/R/saemix.R
+++ b/R/saemix.R
@@ -20,47 +20,40 @@
#' @importFrom saemix saemixData saemixModel
#' @importFrom stats var
#' @examples
+#' \dontrun{
+#' library(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)
-#' sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
+#' f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, cores = 1,
+#' state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE)
+#' m_saemix_p0_fixed <- saemix_model(f_mmkin_parent_p0_fixed["FOMC", ])
+#' d_saemix_parent <- saemix_data(f_mmkin_parent_p0_fixed)
+#' saemix_options <- list(seed = 123456, displayProgress = FALSE,
+#' save = FALSE, save.graphs = FALSE, nbiter.saemix = c(200, 80))
+#' f_saemix_p0_fixed <- saemix(m_saemix_p0_fixed, d_saemix_parent, saemix_options)
+#'
+#' f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
+#' m_saemix_sfo <- saemix_model(f_mmkin_parent["SFO", ])
+#' m_saemix_fomc <- saemix_model(f_mmkin_parent["FOMC", ])
+#' m_saemix_dfop <- saemix_model(f_mmkin_parent["DFOP", ])
+#' d_saemix_parent <- saemix_data(f_mmkin_parent["SFO", ])
+#' f_saemix_sfo <- saemix(m_saemix_sfo, d_saemix_parent, saemix_options)
+#' f_saemix_fomc <- saemix(m_saemix_fomc, d_saemix_parent, saemix_options)
+#' f_saemix_dfop <- saemix(m_saemix_dfop, d_saemix_parent, saemix_options)
+#' compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop))
+#' f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
+#' m_saemix_fomc_tc <- saemix_model(f_mmkin_parent_tc["FOMC", ])
+#' f_saemix_fomc_tc <- saemix(m_saemix_fomc_tc, d_saemix_parent, saemix_options)
+#' compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc))
+#'
+#' dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
#' A1 = mkinsub("SFO"))
-#' \dontrun{
-#' f_mmkin <- mmkin(list("SFO-SFO" = sfo_sfo), ds, quiet = TRUE)
-#' library(saemix)
-#' m_saemix <- saemix_model(f_mmkin, cores = 1)
+#' f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE)
+#' m_saemix <- saemix_model(f_mmkin)
#' d_saemix <- saemix_data(f_mmkin)
-#' saemix_options <- list(seed = 123456,
-#' save = FALSE, save.graphs = FALSE, displayProgress = FALSE,
-#' nbiter.saemix = c(200, 80))
#' f_saemix <- saemix(m_saemix, d_saemix, saemix_options)
-#' plot(f_saemix, plot.type = "convergence")
-#' }
-#' # Synthetic data with two-component error
-#' sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-#' dt50_sfo_in <- c(80, 90, 100, 111.111, 125)
-#' k_in <- log(2) / dt50_sfo_in
#'
-#' SFO <- mkinmod(parent = mkinsub("SFO"))
-#'
-#' pred_sfo <- function(k) {
-#' mkinpredict(SFO, c(k_parent = k),
-#' c(parent = 100), sampling_times)
-#' }
-#'
-#' ds_sfo_mean <- lapply(k_in, pred_sfo)
-#' set.seed(123456L)
-#' ds_sfo_syn <- lapply(ds_sfo_mean, function(ds) {
-#' add_err(ds, sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),
-#' n = 1)[[1]]
-#' })
-#' \dontrun{
-#' f_mmkin_syn <- mmkin("SFO", ds_sfo_syn, error_model = "tc", quiet = TRUE)
-#' # plot(f_mmkin_syn)
-#' m_saemix_tc <- saemix_model(f_mmkin_syn, cores = 1)
-#' d_saemix_tc <- saemix_data(f_mmkin_syn)
-#' f_saemix_tc <- saemix(m_saemix_tc, d_saemix_tc, saemix_options)
-#' plot(f_saemix_tc, plot.type = "convergence")
#' }
#' @return An [saemix::SaemixModel] object.
#' @export
@@ -68,14 +61,14 @@ saemix_model <- function(object, cores = 1) {
if (nrow(object) > 1) stop("Only row objects allowed")
mkin_model <- object[[1]]$mkinmod
- analytical <- is.function(mkin_model$deg_func)
+ solution_type <- object[[1]]$solution_type
degparms_optim <- mean_degparms(object)
- psi0 <- matrix(degparms_optim, nrow = 1)
- colnames(psi0) <- names(degparms_optim)
-
degparms_fixed <- object[[1]]$bparms.fixed
+ # Transformations are done in the degradation function
+ transform.par = rep(0, length(degparms_optim))
+
odeini_optim_parm_names <- grep('_0$', names(degparms_optim), value = TRUE)
odeini_fixed_parm_names <- grep('_0$', names(degparms_fixed), value = TRUE)
@@ -85,50 +78,114 @@ saemix_model <- function(object, cores = 1) {
odeini_fixed <- degparms_fixed[odeini_fixed_parm_names]
names(odeini_fixed) <- gsub('_0$', '', odeini_fixed_parm_names)
- model_function <- function(psi, id, xidep) {
+ model_function <- FALSE
+
+ if (length(mkin_model$spec) == 1 & mkin_model$use_of_ff == "max") {
+ parent_type <- mkin_model$spec[[1]]$type
+ if (length(odeini_fixed) == 1) {
+ if (parent_type == "SFO") {
+ stop("saemix needs at least two parameters to work on.")
+ }
+ if (parent_type == "FOMC") {
+ model_function <- function(psi, id, xidep) {
+ odeini_fixed / (xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id, 1])
+ }
+ }
+ if (parent_type == "DFOP") {
+ model_function <- function(psi, id, xidep) {
+ g <- plogis(psi[id, 3])
+ t = xidep[, "time"]
+ odeini_fixed * (g * exp(- exp(psi[id, 1]) * t) +
+ (1 - g) * exp(- exp(psi[id, 2]) * t))
+ }
+ }
+ if (parent_type == "HS") {
+ model_function <- function(psi, id, xidep) {
+ tb <- exp(psi[id, 3])
+ t = xidep[, "time"]
+ k1 = exp(psi[id, 1])
+ odeini_fixed * ifelse(t <= tb,
+ exp(- k1 * t),
+ exp(- k1 * t) * exp(- exp(psi[id, 2]) * (t - tb)))
+ }
+ }
+ } else {
+ if (length(odeparms_fixed) == 0) {
+ if (parent_type == "SFO") {
+ model_function <- function(psi, id, xidep) {
+ psi[id, 1] * exp( - exp(psi[id, 2]) * xidep[, "time"])
+ }
+ }
+ if (parent_type == "FOMC") {
+ model_function <- function(psi, id, xidep) {
+ psi[id, 1] / (xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id, 2])
+ }
+ }
+ if (parent_type == "DFOP") {
+ model_function <- function(psi, id, xidep) {
+ g <- plogis(psi[id, 4])
+ t = xidep[, "time"]
+ psi[id, 1] * (g * exp(- exp(psi[id, 2]) * t) +
+ (1 - g) * exp(- exp(psi[id, 3]) * t))
+ }
+ }
+ if (parent_type == "HS") {
+ model_function <- function(psi, id, xidep) {
+ tb <- exp(psi[id, 4])
+ t = xidep[, "time"]
+ k1 = exp(psi[id, 2])
+ psi[id, 1] * ifelse(t <= tb,
+ exp(- k1 * t),
+ exp(- k1 * t) * exp(- exp(psi[id, 3]) * (t - tb)))
+ }
+ }
+ }
+ }
+ }
- uid <- unique(id)
+ if (!is.function(model_function)) {
+ model_function <- function(psi, id, xidep) {
- res_list <- parallel::mclapply(uid, function(i) {
- transparms_optim <- psi[i, ]
- names(transparms_optim) <- names(degparms_optim)
+ uid <- unique(id)
- odeini_optim <- transparms_optim[odeini_optim_parm_names]
- names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names)
+ res_list <- parallel::mclapply(uid, function(i) {
+ transparms_optim <- psi[i, ]
+ names(transparms_optim) <- names(degparms_optim)
- odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
+ odeini_optim <- transparms_optim[odeini_optim_parm_names]
+ names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names)
- ode_transparms_optim_names <- setdiff(names(transparms_optim), odeini_optim_parm_names)
- odeparms_optim <- backtransform_odeparms(transparms_optim[ode_transparms_optim_names], mkin_model,
- transform_rates = object[[1]]$transform_rates,
- transform_fractions = object[[1]]$transform_fractions)
- odeparms <- c(odeparms_optim, odeparms_fixed)
+ odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
- xidep_i <- subset(xidep, id == i)
+ ode_transparms_optim_names <- setdiff(names(transparms_optim), odeini_optim_parm_names)
+ odeparms_optim <- backtransform_odeparms(transparms_optim[ode_transparms_optim_names], mkin_model,
+ transform_rates = object[[1]]$transform_rates,
+ transform_fractions = object[[1]]$transform_fractions)
+ odeparms <- c(odeparms_optim, odeparms_fixed)
- if (analytical) {
- out_values <- mkin_model$deg_func(xidep_i, odeini, odeparms)
- } else {
+ xidep_i <- subset(xidep, id == i)
- i_time <- xidep_i$time
- i_name <- xidep_i$name
+ if (solution_type == "analytical") {
+ out_values <- mkin_model$deg_func(xidep_i, odeini, odeparms)
+ } else {
- out_wide <- mkinpredict(mkin_model,
- odeparms = odeparms, odeini = odeini,
- solution_type = object[[1]]$solution_type,
- outtimes = sort(unique(i_time)))
+ i_time <- xidep_i$time
+ i_name <- xidep_i$name
- out_index <- cbind(as.character(i_time), as.character(i_name))
- out_values <- out_wide[out_index]
- }
- return(out_values)
- }, mc.cores = cores)
- res <- unlist(res_list)
- return(res)
- }
+ out_wide <- mkinpredict(mkin_model,
+ odeparms = odeparms, odeini = odeini,
+ solution_type = solution_type,
+ outtimes = sort(unique(i_time)))
- raneff_0 <- mean_degparms(object, random = TRUE)$random$ds
- var_raneff_0 <- apply(raneff_0, 2, var)
+ out_index <- cbind(as.character(i_time), as.character(i_name))
+ out_values <- out_wide[out_index]
+ }
+ return(out_values)
+ }, mc.cores = cores)
+ res <- unlist(res_list)
+ return(res)
+ }
+ }
error.model <- switch(object[[1]]$err_mod,
const = "constant",
@@ -136,7 +193,7 @@ saemix_model <- function(object, cores = 1) {
obs = "constant")
if (object[[1]]$err_mod == "obs") {
- warning("The error model 'obs' (variance by variable) was not transferred to the saemix model")
+ warning("The error model 'obs' (variance by variable) can currently not be transferred to an saemix model")
}
error.init <- switch(object[[1]]$err_mod,
@@ -145,11 +202,15 @@ saemix_model <- function(object, cores = 1) {
b = mean(sapply(object, function(x) x$errparms[2]))),
obs = c(a = mean(sapply(object, function(x) x$errparms)), b = 1))
- res <- saemixModel(model_function, psi0,
+ psi0_matrix <- matrix(degparms_optim, nrow = 1)
+ colnames(psi0_matrix) <- names(degparms_optim)
+
+ res <- saemixModel(model_function,
+ psi0 = psi0_matrix,
"Mixed model generated from mmkin object",
- transform.par = rep(0, length(degparms_optim)),
- error.model = error.model, error.init = error.init,
- omega.init = diag(var_raneff_0)
+ transform.par = transform.par,
+ error.model = error.model,
+ error.init = error.init
)
return(res)
}

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