diff options
author | Johannes Ranke <jranke@uni-bremen.de> | 2020-11-11 11:48:38 +0100 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-11-11 11:48:38 +0100 |
commit | 158b2f02c6778bcb1b868497c6366924ec96102d (patch) | |
tree | 0c87d22c0d71427af267d9cf1c1d32a7c6a287ac /R/saemix.R | |
parent | 0cbabc98850e436b1e0703c659cf8a00b52d7503 (diff) |
Rename saemix file, option to suppress saemix messages
Diffstat (limited to 'R/saemix.R')
-rw-r--r-- | R/saemix.R | 416 |
1 files changed, 0 insertions, 416 deletions
diff --git a/R/saemix.R b/R/saemix.R deleted file mode 100644 index 50497423..00000000 --- a/R/saemix.R +++ /dev/null @@ -1,416 +0,0 @@ -#' Fit nonlinear mixed models with SAEM -#' -#' This function uses [saemix::saemix()] as a backend for fitting nonlinear mixed -#' effects models created from [mmkin] row objects using the Stochastic Approximation -#' Expectation Maximisation algorithm (SAEM). -#' -#' 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 using [mkinfit]. -#' -#' Starting values for the fixed effects (population mean parameters, argument -#' psi0 of [saemix::saemixModel()] are the mean values of the parameters found -#' using [mmkin]. -#' -#' @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 suppressPlot Should we suppress any plotting that is done -#' by the saemix function? -#' @param control Passed to [saemix::saemix] -#' @param \dots Further parameters passed to [saemix::saemixData] -#' and [saemix::saemixModel]. -#' @return An S3 object of class 'saem.mmkin', containing the fitted -#' [saemix::SaemixObject] as a list component named 'so'. The -#' object also inherits from 'mixed.mmkin'. -#' @seealso [summary.saem.mmkin] [plot.mixed.mmkin] -#' @examples -#' \dontrun{ -#' ds <- lapply(experimental_data_for_UBA_2019[6:10], -#' function(x) subset(x$data[c("name", "time", "value")])) -#' names(ds) <- paste("Dataset", 6:10) -#' f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, cores = 1, -#' state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE) -#' f_saem_p0_fixed <- saem(f_mmkin_parent_p0_fixed) -#' -#' f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) -#' f_saem_sfo <- saem(f_mmkin_parent["SFO", ]) -#' f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) -#' f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) -#' -#' # The returned saem.mmkin object contains an SaemixObject, therefore we can use -#' # functions from saemix -#' library(saemix) -#' compare.saemix(list(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so)) -#' plot(f_saem_fomc$so, plot.type = "convergence") -#' plot(f_saem_fomc$so, plot.type = "individual.fit") -#' plot(f_saem_fomc$so, plot.type = "npde") -#' plot(f_saem_fomc$so, plot.type = "vpc") -#' -#' f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") -#' f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ]) -#' compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)) -#' -#' sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), -#' A1 = mkinsub("SFO")) -#' fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"), -#' A1 = mkinsub("SFO")) -#' dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), -#' A1 = mkinsub("SFO")) -#' # The following fit uses analytical solutions for SFO-SFO and DFOP-SFO, -#' # and compiled ODEs for FOMC, both are fast -#' f_mmkin <- mmkin(list( -#' "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo), -#' ds, quiet = TRUE) -#' # These take about five seconds each on this system, as we use -#' # analytical solutions written for saemix. When using the analytical -#' # solutions written for mkin this took around four minutes -#' f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ]) -#' f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) -#' # We can use print, plot and summary methods to check the results -#' print(f_saem_dfop_sfo) -#' plot(f_saem_dfop_sfo) -#' summary(f_saem_dfop_sfo, data = FALSE) -#' -#' # Using a single core, the following takes about 6 minutes as we do not have an -#' # analytical solution. Using 10 cores it is slower instead of faster -#' #f_saem_fomc <- saem(f_mmkin["FOMC-SFO", ], cores = 1) -#' } -#' @export -saem <- function(object, control, ...) UseMethod("saem") - -#' @rdname saem -#' @export -saem.mmkin <- function(object, - control = list(displayProgress = FALSE, print = FALSE, - save = FALSE, save.graphs = FALSE), - cores = 1, - verbose = FALSE, suppressPlot = TRUE, ...) -{ - m_saemix <- saemix_model(object, cores = cores, verbose = verbose) - d_saemix <- saemix_data(object, verbose = verbose) - if (suppressPlot) { - # We suppress the log-likelihood curve that saemix currently - # produces at the end of the fit by plotting to a file - # that we discard afterwards - tmp <- tempfile() - grDevices::png(tmp) - } - fit_time <- system.time({ - f_saemix <- saemix::saemix(m_saemix, d_saemix, control) - f_pred <- try(saemix::saemix.predict(f_saemix), silent = TRUE) - if (!inherits(f_pred, "try-error")) { - f_saemix <- f_pred - } else { - warning("Creating predictions from the saemix model failed") - } - }) - if (suppressPlot) { - grDevices::dev.off() - unlink(tmp) - } - transparms_optim <- f_saemix@results@fixed.effects - names(transparms_optim) <- f_saemix@results@name.fixed - bparms_optim <- backtransform_odeparms(transparms_optim, - object[[1]]$mkinmod, - object[[1]]$transform_rates, - object[[1]]$transform_fractions) - - result <- list( - mkinmod = object[[1]]$mkinmod, - mmkin = object, - solution_type = object[[1]]$solution_type, - transform_rates = object[[1]]$transform_rates, - transform_fractions = object[[1]]$transform_fractions, - so = f_saemix, - time = fit_time, - mean_dp_start = attr(m_saemix, "mean_dp_start"), - bparms.optim = bparms_optim, - bparms.fixed = object[[1]]$bparms.fixed, - data = nlme_data(object), - err_mod = object[[1]]$err_mod, - date.fit = date(), - saemixversion = as.character(utils::packageVersion("saemix")), - mkinversion = as.character(utils::packageVersion("mkin")), - Rversion = paste(R.version$major, R.version$minor, sep=".") - ) - - class(result) <- c("saem.mmkin", "mixed.mmkin") - return(result) -} - -#' @export -#' @rdname saem -#' @param x An saem.mmkin object to print -#' @param digits Number of digits to use for printing -print.saem.mmkin <- function(x, digits = max(3, getOption("digits") - 3), ...) { - cat( "Kinetic nonlinear mixed-effects model fit by SAEM" ) - cat("\nStructural model:\n") - diffs <- x$mmkin[[1]]$mkinmod$diffs - nice_diffs <- gsub("^(d.*) =", "\\1/dt =", diffs) - writeLines(strwrap(nice_diffs, exdent = 11)) - cat("\nData:\n") - cat(nrow(x$data), "observations of", - length(unique(x$data$name)), "variable(s) grouped in", - length(unique(x$data$ds)), "datasets\n") - - cat("\nLikelihood computed by importance sampling\n") - print(data.frame( - AIC = AIC(x$so, type = "is"), - BIC = BIC(x$so, type = "is"), - logLik = logLik(x$so, type = "is"), - row.names = " "), digits = digits) - - cat("\nFitted parameters:\n") - conf.int <- x$so@results@conf.int[c("estimate", "lower", "upper")] - rownames(conf.int) <- x$so@results@conf.int[["name"]] - print(conf.int, digits = digits) - - invisible(x) -} - -#' @rdname saem -#' @return An [saemix::SaemixModel] object. -#' @export -saemix_model <- function(object, cores = 1, verbose = FALSE, ...) { - 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 - - # Model functions with analytical solutions - # Fixed parameters, use_of_ff = "min" and turning off sinks currently not supported here - # In general, we need to consider exactly how the parameters in mkinfit were specified, - # as the parameters are currently mapped by position in these solutions - sinks <- sapply(mkin_model$spec, function(x) x$sink) - if (length(odeparms_fixed) == 0 & mkin_model$use_of_ff == "max" & all(sinks)) { - # Parent only - if (length(mkin_model$spec) == 1) { - 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 (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))) - } - } - } - } - - # Parent with one metabolite - # Parameter names used in the model functions are as in - # https://nbviewer.jupyter.org/urls/jrwb.de/nb/Symbolic%20ODE%20solutions%20for%20mkin.ipynb - if (length(mkin_model$spec) == 2) { - types <- unname(sapply(mkin_model$spec, function(x) x$type)) - # Initial value for the metabolite (n20) must be fixed - if (names(odeini_fixed) == names(mkin_model$spec)[2]) { - n20 <- odeini_fixed - parent_name <- names(mkin_model$spec)[1] - if (identical(types, c("SFO", "SFO"))) { - model_function <- function(psi, id, xidep) { - t <- xidep[, "time"] - n10 <- psi[id, 1] - k1 <- exp(psi[id, 2]) - k2 <- exp(psi[id, 3]) - f12 <- plogis(psi[id, 4]) - ifelse(xidep[, "name"] == parent_name, - n10 * exp(- k1 * t), - (((k2 - k1) * n20 - f12 * k1 * n10) * exp(- k2 * t)) / (k2 - k1) + - (f12 * k1 * n10 * exp(- k1 * t)) / (k2 - k1) - ) - } - } - if (identical(types, c("DFOP", "SFO"))) { - model_function <- function(psi, id, xidep) { - t <- xidep[, "time"] - n10 <- psi[id, 1] - k2 <- exp(psi[id, 2]) - f12 <- plogis(psi[id, 3]) - l1 <- exp(psi[id, 4]) - l2 <- exp(psi[id, 5]) - g <- plogis(psi[id, 6]) - ifelse(xidep[, "name"] == parent_name, - n10 * (g * exp(- l1 * t) + (1 - g) * exp(- l2 * t)), - ((f12 * g - f12) * l2 * n10 * exp(- l2 * t)) / (l2 - k2) - - (f12 * g * l1 * n10 * exp(- l1 * t)) / (l1 - k2) + - ((((l1 - k2) * l2 - k2 * l1 + k2^2) * n20 + - ((f12 * l1 + (f12 * g - f12) * k2) * l2 - - f12 * g * k2 * l1) * n10) * exp( - k2 * t)) / - ((l1 - k2) * l2 - k2 * l1 + k2^2) - ) - } - } - } - } - } - - if (is.function(model_function)) { - solution_type = "analytical saemix" - } else { - model_function <- function(psi, id, xidep) { - - uid <- unique(id) - - res_list <- parallel::mclapply(uid, function(i) { - transparms_optim <- psi[i, ] - names(transparms_optim) <- names(degparms_optim) - - odeini_optim <- transparms_optim[odeini_optim_parm_names] - names(odeini_optim) <- gsub('_0$', '', 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)), - na_stop = FALSE - ) - - 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$errparms)), b = 1)) - - psi0_matrix <- matrix(degparms_optim, nrow = 1) - colnames(psi0_matrix) <- names(degparms_optim) - - res <- saemix::saemixModel(model_function, - psi0 = psi0_matrix, - "Mixed model generated from mmkin object", - transform.par = transform.par, - error.model = error.model, - verbose = verbose - ) - attr(res, "mean_dp_start") <- degparms_optim - return(res) -} - -#' @rdname saem -#' @return An [saemix::SaemixData] object. -#' @export -saemix_data <- function(object, verbose = FALSE, ...) { - if (nrow(object) > 1) stop("Only row objects allowed") - ds_names <- colnames(object) - - ds_list <- lapply(object, function(x) x$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 <- saemix::saemixData(ds_saemix, - name.group = "ds", - name.predictors = c("time", "name"), - name.response = "value", - verbose = verbose, - ...) - return(res) -} |