#' Create saemix models from mmkin row objects #' #' This function sets up a nonlinear mixed effects model for an mmkin row #' object for use with the saemix package. An mmkin row object is essentially a #' list of mkinfit objects that have been obtained by fitting the same model to #' a list of datasets. #' #' Starting values for the fixed effects (population mean parameters, argument psi0 of #' [saemix::saemixModel()] are the mean values of the parameters found using #' mmkin. Starting variances of the random effects (argument omega.init) are the #' variances of the deviations of the parameters from these mean values. #' #' @param object An mmkin row object containing several fits of the same model #' to different datasets #' @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. #' @rdname saemix #' @importFrom saemix saemixData saemixModel #' @importFrom stats var #' @examples #' \dontrun{ #' library(saemix) #' ds <- lapply(experimental_data_for_UBA_2019[6:10], #' function(x) subset(x$data[c("name", "time", "value")])) #' names(ds) <- paste("Dataset", 6:10) #' f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, cores = 1, #' state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE) #' m_saemix_p0_fixed <- saemix_model(f_mmkin_parent_p0_fixed["FOMC", ]) #' d_saemix_parent <- saemix_data(f_mmkin_parent_p0_fixed) #' saemix_options <- list(seed = 123456, displayProgress = FALSE, #' save = FALSE, save.graphs = FALSE, nbiter.saemix = c(200, 80)) #' f_saemix_p0_fixed <- saemix(m_saemix_p0_fixed, d_saemix_parent, saemix_options) #' #' f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) #' m_saemix_sfo <- saemix_model(f_mmkin_parent["SFO", ]) #' m_saemix_fomc <- saemix_model(f_mmkin_parent["FOMC", ]) #' m_saemix_dfop <- saemix_model(f_mmkin_parent["DFOP", ]) #' d_saemix_parent <- saemix_data(f_mmkin_parent["SFO", ]) #' f_saemix_sfo <- saemix(m_saemix_sfo, d_saemix_parent, saemix_options) #' f_saemix_fomc <- saemix(m_saemix_fomc, d_saemix_parent, saemix_options) #' f_saemix_dfop <- saemix(m_saemix_dfop, d_saemix_parent, saemix_options) #' compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop)) #' f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") #' m_saemix_fomc_tc <- saemix_model(f_mmkin_parent_tc["FOMC", ]) #' f_saemix_fomc_tc <- saemix(m_saemix_fomc_tc, d_saemix_parent, saemix_options) #' compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc)) #' #' dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), #' A1 = mkinsub("SFO")) #' f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE) #' m_saemix <- saemix_model(f_mmkin) #' d_saemix <- saemix_data(f_mmkin) #' f_saemix <- saemix(m_saemix, d_saemix, saemix_options) #' #' } #' @return An [saemix::SaemixModel] object. #' @export saemix_model <- function(object, cores = 1) { if (nrow(object) > 1) stop("Only row objects allowed") mkin_model <- object[[1]]$mkinmod solution_type <- object[[1]]$solution_type degparms_optim <- mean_degparms(object) degparms_fixed <- object[[1]]$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) odeparms_fixed_names <- setdiff(names(degparms_fixed), odeini_fixed_parm_names) odeparms_fixed <- degparms_fixed[odeparms_fixed_names] odeini_fixed <- degparms_fixed[odeini_fixed_parm_names] names(odeini_fixed) <- gsub('_0$', '', odeini_fixed_parm_names) model_function <- FALSE if (length(mkin_model$spec) == 1 & mkin_model$use_of_ff == "max") { parent_type <- mkin_model$spec[[1]]$type if (length(odeini_fixed) == 1) { if (parent_type == "SFO") { stop("saemix needs at least two parameters to work on.") } if (parent_type == "FOMC") { model_function <- function(psi, id, xidep) { odeini_fixed / (xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id, 1]) } } if (parent_type == "DFOP") { model_function <- function(psi, id, xidep) { g <- plogis(psi[id, 3]) t = xidep[, "time"] odeini_fixed * (g * exp(- exp(psi[id, 1]) * t) + (1 - g) * exp(- exp(psi[id, 2]) * t)) } } if (parent_type == "HS") { model_function <- function(psi, id, xidep) { tb <- exp(psi[id, 3]) t = xidep[, "time"] k1 = exp(psi[id, 1]) odeini_fixed * ifelse(t <= tb, exp(- k1 * t), exp(- k1 * t) * exp(- exp(psi[id, 2]) * (t - tb))) } } } else { if (length(odeparms_fixed) == 0) { if (parent_type == "SFO") { model_function <- function(psi, id, xidep) { psi[id, 1] * exp( - exp(psi[id, 2]) * xidep[, "time"]) } } if (parent_type == "FOMC") { model_function <- function(psi, id, xidep) { psi[id, 1] / (xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id, 2]) } } if (parent_type == "DFOP") { model_function <- function(psi, id, xidep) { g <- plogis(psi[id, 4]) t = xidep[, "time"] psi[id, 1] * (g * exp(- exp(psi[id, 2]) * t) + (1 - g) * exp(- exp(psi[id, 3]) * t)) } } if (parent_type == "HS") { model_function <- function(psi, id, xidep) { tb <- exp(psi[id, 4]) t = xidep[, "time"] k1 = exp(psi[id, 2]) psi[id, 1] * ifelse(t <= tb, exp(- k1 * t), exp(- k1 * t) * exp(- exp(psi[id, 3]) * (t - tb))) } } } } } if (!is.function(model_function)) { model_function <- function(psi, id, xidep) { uid <- unique(id) res_list <- parallel::mclapply(uid, function(i) { transparms_optim <- psi[i, ] names(transparms_optim) <- names(degparms_optim) odeini_optim <- transparms_optim[odeini_optim_parm_names] names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names) odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)] ode_transparms_optim_names <- setdiff(names(transparms_optim), odeini_optim_parm_names) odeparms_optim <- backtransform_odeparms(transparms_optim[ode_transparms_optim_names], mkin_model, transform_rates = object[[1]]$transform_rates, transform_fractions = object[[1]]$transform_fractions) odeparms <- c(odeparms_optim, odeparms_fixed) xidep_i <- subset(xidep, id == i) if (solution_type == "analytical") { out_values <- mkin_model$deg_func(xidep_i, odeini, odeparms) } else { i_time <- xidep_i$time i_name <- xidep_i$name out_wide <- mkinpredict(mkin_model, odeparms = odeparms, odeini = odeini, solution_type = solution_type, outtimes = sort(unique(i_time))) 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]]$err_mod, const = "constant", tc = "combined", obs = "constant") if (object[[1]]$err_mod == "obs") { warning("The error model 'obs' (variance by variable) can currently not be transferred to an saemix model") } error.init <- switch(object[[1]]$err_mod, const = c(a = mean(sapply(object, function(x) x$errparms)), b = 1), tc = c(a = mean(sapply(object, function(x) x$errparms[1])), b = mean(sapply(object, function(x) x$errparms[2]))), obs = c(a = mean(sapply(object, function(x) x$errparms)), b = 1)) psi0_matrix <- matrix(degparms_optim, nrow = 1) colnames(psi0_matrix) <- names(degparms_optim) res <- saemixModel(model_function, psi0 = psi0_matrix, "Mixed model generated from mmkin object", transform.par = transform.par, error.model = error.model, error.init = error.init ) return(res) } #' @rdname saemix #' @param \dots Further parameters passed to [saemix::saemixData] #' @return An [saemix::SaemixData] object. #' @export saemix_data <- function(object, ...) { if (nrow(object) > 1) stop("Only row objects allowed") ds_names <- colnames(object) ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")]) names(ds_list) <- ds_names ds_saemix_all <- purrr::map_dfr(ds_list, function(x) x, .id = "ds") ds_saemix <- data.frame(ds = ds_saemix_all$ds, name = as.character(ds_saemix_all$variable), time = ds_saemix_all$time, value = ds_saemix_all$observed, stringsAsFactors = FALSE) res <- saemixData(ds_saemix, name.group = "ds", name.predictors = c("time", "name"), name.response = "value", ...) return(res) }