diff options
Diffstat (limited to 'R/saemix.R')
| -rw-r--r-- | R/saemix.R | 213 |
1 files changed, 137 insertions, 76 deletions
@@ -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) } |