diff options
| -rw-r--r-- | DESCRIPTION | 2 | ||||
| -rw-r--r-- | NAMESPACE | 3 | ||||
| -rw-r--r-- | R/memkin.R | 170 | ||||
| -rw-r--r-- | check.log | 72 | ||||
| -rw-r--r-- | man/memkin.Rd | 84 | 
5 files changed, 322 insertions, 9 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 5576e5bf..1aa5cac2 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -17,7 +17,7 @@ Description: Calculation routines based on the FOCUS Kinetics Report (2006,    note that no warranty is implied for correctness of results or fitness for a    particular purpose.  Imports: stats, graphics, methods, deSolve, R6, inline, parallel, numDeriv, -  lmtest, pkgbuild +  lmtest, pkgbuild, nlme, purrr  Suggests: knitr, rbenchmark, tikzDevice, testthat, rmarkdown, covr, vdiffr,    benchmarkme, tibble, stats4  License: GPL @@ -45,6 +45,7 @@ export(max_twa_fomc)  export(max_twa_hs)  export(max_twa_parent)  export(max_twa_sfo) +export(memkin)  export(mkin_long_to_wide)  export(mkin_wide_to_long)  export(mkinds) @@ -67,6 +68,7 @@ export(sigma_twocomp)  export(transform_odeparms)  import(deSolve)  import(graphics) +import(nlme)  importFrom(R6,R6Class)  importFrom(grDevices,dev.cur)  importFrom(inline,cfunction) @@ -77,6 +79,7 @@ importFrom(parallel,detectCores)  importFrom(parallel,mclapply)  importFrom(parallel,parLapply)  importFrom(pkgbuild,has_compiler) +importFrom(purrr,map_dfr)  importFrom(stats,AIC)  importFrom(stats,BIC)  importFrom(stats,aggregate) diff --git a/R/memkin.R b/R/memkin.R new file mode 100644 index 00000000..8a71484e --- /dev/null +++ b/R/memkin.R @@ -0,0 +1,170 @@ +#' Estimation of parameter distributions from mmkin row objects +#' +#' This function sets up and attempts to fit a mixed effects model to +#' an mmkin row object which is essentially a list of mkinfit objects +#' that have been obtained by fitting the same model to a list of +#' datasets. +#' +#' @param object An mmkin row object containing several fits of the same model to different datasets +#' @param random_spec Either "auto" or a specification of random effects for \code{\link{nlme}} +#'   given as a character vector +#' @param ... Additional arguments passed to \code{\link{nlme}} +#' @import nlme +#' @importFrom purrr map_dfr +#' @return An nlme object +#' @examples +#' sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) +#' m_SFO <- mkinmod(parent = mkinsub("SFO")) +#' d_SFO_1 <- mkinpredict(m_SFO, +#'   c(k_parent_sink = 0.1), +#'   c(parent = 98), sampling_times) +#' d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time") +#' d_SFO_2 <- mkinpredict(m_SFO, +#'   c(k_parent_sink = 0.05), +#'   c(parent = 102), sampling_times) +#' d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time") +#' d_SFO_3 <- mkinpredict(m_SFO, +#'   c(k_parent_sink = 0.02), +#'   c(parent = 103), sampling_times) +#' d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time") +#' +#' d1 <- add_err(d_SFO_1, function(value) 3, n = 1) +#' d2 <- add_err(d_SFO_2, function(value) 2, n = 1) +#' d3 <- add_err(d_SFO_3, function(value) 4, n = 1) +#' ds <- c(d1 = d1, d2 = d2, d3 = d3) +#' +#' f <- mmkin("SFO", ds) +#' x <- memkin(f) +#' summary(x) +#' +#' ds_2 <- lapply(experimental_data_for_UBA_2019[6:10], +#'  function(x) x$data[c("name", "time", "value")]) +#' m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), +#'   A1 = mkinsub("SFO"), use_of_ff = "min") +#' m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), +#'   A1 = mkinsub("SFO"), use_of_ff = "max") +#' m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"), +#'   A1 = mkinsub("SFO")) +#' m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), +#'   A1 = mkinsub("SFO")) +#' m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"), +#'   A1 = mkinsub("SFO")) +#' +#' f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo, +#'  "SFO-SFO-ff" = m_sfo_sfo_ff, +#'  "FOMC-SFO" = m_fomc_sfo, +#'  "DFOP-SFO" = m_dfop_sfo, +#'  "SFORB-SFO" = m_sforb_sfo), +#'   ds_2) +#' +#' f_nlme_sfo_sfo <- memkin(f_2[1, ]) +#' f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit +#' f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced +#' f_nlme_sfo_sfo_4 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink ~ 1)") # further reduced +#' \dontrun{ +#'   f_nlme_sfo_sfo_ff <- memkin(f_2[2, ]) # does not converge with maxIter = 50 +#' } +#' f_nlme_fomc_sfo <- memkin(f_2[3, ]) +#' \dontrun{ +#'   f_nlme_dfop_sfo <- memkin(f_2[4, ])  # apparently underdetermined +#'   f_nlme_sforb_sfo <- memkin(f_2[5, ]) # also does not converge +#' } +#' anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo, f_nlme_sfo_sfo_4) +#' @export +memkin <- function(object, random_spec = "auto", ...) { +  if (nrow(object) > 1) stop("Only row objects allowed") +  ds_names <- colnames(object) + +  p_mat_start_trans <- sapply(object, parms, transformed = TRUE) +  colnames(p_mat_start_trans) <- ds_names + +  p_names_mean_function <- setdiff(rownames(p_mat_start_trans), names(object[[1]]$errparms)) +  p_start_mean_function <- apply(p_mat_start_trans[p_names_mean_function, ], 1, mean) + +  ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")]) +  names(ds_list) <- ds_names +  ds_nlme <- purrr::map_dfr(ds_list, function(x) x, .id = "ds") +  ds_nlme$variable <- as.character(ds_nlme$variable) +  ds_nlme_grouped <- groupedData(observed ~ time | ds, ds_nlme) + +  mkin_model <- object[[1]]$mkinmod + +  # Inspired by https://stackoverflow.com/a/12983961/3805440 +  # and https://stackoverflow.com/a/26280789/3805440 +  model_function_alist <- replicate(length(p_names_mean_function) + 2, substitute()) +  names(model_function_alist) <- c("name", "time", p_names_mean_function) + +  model_function_body <- quote({ +    arg_frame <- as.data.frame(as.list((environment())), stringsAsFactors = FALSE) +    res_frame <- arg_frame[1:2] +    parm_frame <- arg_frame[-(1:2)] +    parms_unique <- unique(parm_frame) + +    n_unique <- nrow(parms_unique) + +    times_ds <- list() +    names_ds <- list() +    for (i in 1:n_unique) { +      times_ds[[i]] <- +        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "time"] +      names_ds[[i]] <- +        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "name"] +    } + +    res_list <- lapply(1:n_unique, function(x) { +      transparms_optim <- unlist(parms_unique[x, , drop = TRUE]) +      parms_fixed <- object[[1]]$bparms.fixed + +      odeini_optim_parm_names <- grep('_0$', names(transparms_optim), value = TRUE) +      odeini_optim <- transparms_optim[odeini_optim_parm_names] +      names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names) +      odeini_fixed_parm_names <- grep('_0$', names(parms_fixed), value = TRUE) +      odeini_fixed <- parms_fixed[odeini_fixed_parm_names] +      names(odeini_fixed) <- gsub('_0$', '', odeini_fixed_parm_names) +      odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$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_fixed_names <- setdiff(names(parms_fixed), odeini_fixed_parm_names) +      odeparms_fixed <- parms_fixed[odeparms_fixed_names] +      odeparms <- c(odeparms_optim, odeparms_fixed) + +      out_wide <- mkinpredict(mkin_model, +        odeparms = odeparms, odeini = odeini, +        solution_type = object[[1]]$solution_type, +        outtimes = sort(unique(times_ds[[x]]))) +      out_array <- out_wide[, -1, drop = FALSE] +      rownames(out_array) <- as.character(unique(times_ds[[x]])) +      out_times <- as.character(times_ds[[x]]) +      out_names <- as.character(names_ds[[x]]) +      out_values <- mapply(function(times, names) out_array[times, names], +        out_times, out_names) +      return(as.numeric(out_values)) +    }) +    res <- unlist(res_list) +    return(res) +  }) +  model_function <- as.function(c(model_function_alist, model_function_body)) +  # For some reason, using envir = parent.frame() here is not enough, +  # we need to use assign +  assign("model_function", model_function, envir = parent.frame()) + +  random_spec <- if (random_spec[1] == "auto") { +      paste0("pdDiag(", paste(p_names_mean_function, collapse = " + "), " ~ 1),\n") +  } else { +      paste0(random_spec, ",\n") +  } +  nlme_call_text <- paste0( +    "nlme(observed ~ model_function(variable, time, ", +      paste(p_names_mean_function, collapse = ", "), "),\n", +    "  data = ds_nlme_grouped,\n", +    "  fixed = ", paste(p_names_mean_function, collapse = " + "), " ~ 1,\n", +    "  random = ", random_spec, "\n", +    "  start = p_start_mean_function)\n") + +  f_nlme <- eval(parse(text = nlme_call_text)) + +  return(f_nlme) +} @@ -24,7 +24,27 @@ Maintainer: ‘Johannes Ranke <jranke@uni-bremen.de>’  * checking for future file timestamps ... OK  * checking ‘build’ directory ... OK  * checking DESCRIPTION meta-information ... OK -* checking top-level files ... OK +* checking top-level files ... WARNING +Conversion of ‘README.md’ failed: +[WARNING] This document format requires a nonempty <title> element. +  Please specify either ‘title’ or ‘pagetitle’ in the metadata. +  Falling back to ‘README’ +Could not fetch https://codecov.io/github/jranke/mkin/branch/master/graphs/badge.svg +HttpExceptionRequest Request { +  host                 = "codecov.io" +  port                 = 443 +  secure               = True +  requestHeaders       = [] +  path                 = "/github/jranke/mkin/branch/master/graphs/badge.svg" +  queryString          = "" +  method               = "GET" +  proxy                = Nothing +  rawBody              = False +  redirectCount        = 10 +  responseTimeout      = ResponseTimeoutDefault +  requestVersion       = HTTP/1.1 +} + ConnectionTimeout  * checking for left-over files ... OK  * checking index information ... OK  * checking package subdirectories ... OK @@ -44,7 +64,13 @@ Maintainer: ‘Johannes Ranke <jranke@uni-bremen.de>’  * checking R code for possible problems ... OK  * checking Rd files ... OK  * checking Rd metadata ... OK -* checking Rd line widths ... OK +* checking Rd line widths ... NOTE +Rd file 'memkin.Rd': +  \examples lines wider than 100 characters: +     f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit +     f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced + +These lines will be truncated in the PDF manual.  * checking Rd cross-references ... OK  * checking for missing documentation entries ... OK  * checking for code/documentation mismatches ... OK @@ -56,10 +82,41 @@ Maintainer: ‘Johannes Ranke <jranke@uni-bremen.de>’  * checking data for ASCII and uncompressed saves ... OK  * checking installed files from ‘inst/doc’ ... OK  * checking files in ‘vignettes’ ... OK -* checking examples ... NOTE -Examples with CPU or elapsed time > 5s -         user system elapsed -mkinsub 2.015  4.083   0.703 +* checking examples ... ERROR +Running examples in ‘mkin-Ex.R’ failed +The error most likely occurred in: + +> base::assign(".ptime", proc.time(), pos = "CheckExEnv") +> ### Name: memkin +> ### Title: Estimation of parameter distributions from mmkin row objects +> ### Aliases: memkin +>  +> ### ** Examples +>  +> sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) +> m_SFO <- mkinmod(parent = mkinsub("SFO")) +> d_SFO_1 <- mkinpredict(m_SFO, ++   c(k_parent_sink = 0.1), ++   c(parent = 98), sampling_times) +> d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time") +> d_SFO_2 <- mkinpredict(m_SFO, ++   c(k_parent_sink = 0.05), ++   c(parent = 102), sampling_times) +> d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time") +> d_SFO_3 <- mkinpredict(m_SFO, ++   c(k_parent_sink = 0.02), ++   c(parent = 103), sampling_times) +> d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time") +>  +> d1 <- add_err(d_SFO_1, function(value) 3, n = 1) +> d2 <- add_err(d_SFO_2, function(value) 2, n = 1) +> d3 <- add_err(d_SFO_3, function(value) 4, n = 1) +> ds <- c(d1 = d1, d2 = d2, d3 = d3) +>  +> f <- mmkin("SFO", ds) +Error in .check_ncores(cores) : 8 simultaneous processes spawned +Calls: mmkin -> mclapply -> .check_ncores +Execution halted  * checking for unstated dependencies in ‘tests’ ... OK  * checking tests ... SKIPPED  * checking for unstated dependencies in vignettes ... OK @@ -69,9 +126,8 @@ mkinsub 2.015  4.083   0.703  * checking for detritus in the temp directory ... OK  * DONE -Status: 1 NOTE +Status: 1 ERROR, 1 WARNING, 1 NOTE  See    ‘/home/jranke/git/mkin/mkin.Rcheck/00check.log’  for details. - diff --git a/man/memkin.Rd b/man/memkin.Rd new file mode 100644 index 00000000..8ae6100a --- /dev/null +++ b/man/memkin.Rd @@ -0,0 +1,84 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/memkin.R +\name{memkin} +\alias{memkin} +\title{Estimation of parameter distributions from mmkin row objects} +\usage{ +memkin(object, random_spec = "auto", ...) +} +\arguments{ +\item{object}{An mmkin row object containing several fits of the same model to different datasets} + +\item{random_spec}{Either "auto" or a specification of random effects for \code{\link{nlme}} +given as a character vector} + +\item{...}{Additional arguments passed to \code{\link{nlme}}} +} +\value{ +An nlme object +} +\description{ +This function sets up and attempts to fit a mixed effects model to +an mmkin row object which is essentially a list of mkinfit objects +that have been obtained by fitting the same model to a list of +datasets. +} +\examples{ +sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) +m_SFO <- mkinmod(parent = mkinsub("SFO")) +d_SFO_1 <- mkinpredict(m_SFO, +  c(k_parent_sink = 0.1), +  c(parent = 98), sampling_times) +d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time") +d_SFO_2 <- mkinpredict(m_SFO, +  c(k_parent_sink = 0.05), +  c(parent = 102), sampling_times) +d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time") +d_SFO_3 <- mkinpredict(m_SFO, +  c(k_parent_sink = 0.02), +  c(parent = 103), sampling_times) +d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time") + +d1 <- add_err(d_SFO_1, function(value) 3, n = 1) +d2 <- add_err(d_SFO_2, function(value) 2, n = 1) +d3 <- add_err(d_SFO_3, function(value) 4, n = 1) +ds <- c(d1 = d1, d2 = d2, d3 = d3) + +f <- mmkin("SFO", ds) +x <- memkin(f) +summary(x) + +ds_2 <- lapply(experimental_data_for_UBA_2019[6:10], + function(x) x$data[c("name", "time", "value")]) +m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), +  A1 = mkinsub("SFO"), use_of_ff = "min") +m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), +  A1 = mkinsub("SFO"), use_of_ff = "max") +m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"), +  A1 = mkinsub("SFO")) +m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), +  A1 = mkinsub("SFO")) +m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"), +  A1 = mkinsub("SFO")) + +f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo, + "SFO-SFO-ff" = m_sfo_sfo_ff, + "FOMC-SFO" = m_fomc_sfo, + "DFOP-SFO" = m_dfop_sfo, + "SFORB-SFO" = m_sforb_sfo), +  ds_2) + +f_nlme_sfo_sfo <- memkin(f_2[1, ]) +f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit +f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced +f_nlme_sfo_sfo_4 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink ~ 1)") # further reduced +\dontrun{ +  f_nlme_sfo_sfo_ff <- memkin(f_2[2, ]) # does not converge with maxIter = 50 +} +f_nlme_fomc_sfo <- memkin(f_2[3, ]) +\dontrun{ +  f_nlme_dfop_sfo <- memkin(f_2[4, ])  # apparently underdetermined +  f_nlme_sforb_sfo <- memkin(f_2[5, ]) # also does not converge +} +anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo, f_nlme_sfo_sfo_4) +}  | 
