# gWidgetsWWW2 GUI for mkin {{{1 # Copyright (C) 2013,2014 Johannes Ranke # Portions of this file are copyright (C) 2013 Eurofins Regulatory AG, Switzerland # Contact: jranke@uni-bremen.de # This file is part of the R package mkin # mkin is free software: you can redistribute it and/or modify it under the # terms of the GNU General Public License as published by the Free Software # Foundation, either version 3 of the License, or (at your option) any later # version. # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU General Public License for more # details. # You should have received a copy of the GNU General Public License along with # this program. If not, see require(mkin) # {{{1 # Set the GUI title and create the basic widget layout {{{1 w <- gwindow("gmkin - Browser based GUI for kinetic evaluations using mkin") sb <- gstatusbar(paste("Powered by gWidgetsWWW2, ExtJS, Rook, FME, deSolve and minpack.lm --- Working directory is", getwd()), cont = w) pg <- gpanedgroup(cont = w, default.size = 300) center <- gnotebook(cont = pg) left <- gvbox(cont = pg) # Helper functions {{{1 # Override function for making it possible to override original data in the GUI {{{2 override <- function(d) { data.frame(name = d$name, time = d$time, value = ifelse(is.na(d$override), d$value, d$override), err = d$err) } # Set default values for project data {{{1 # Initial project file name {{{2 project_name <- "mkin_FOCUS_2006" project_file <- paste0(project_name, ".RData") # Initial studies {{{2 studies.df <- data.frame(Index = as.integer(1), Citation = "FOCUS (2006) Guidance on degradation kinetics", stringsAsFactors = FALSE) # Initial datasets {{{2 ds <- list() observed.all <- vector() for (i in 1:2) { ds.letter = LETTERS[i + 2] ds.index <- as.character(i) ds.name = paste0("FOCUS_2006_", ds.letter) ds[[ds.index]] <- list( study_nr = 1, title = paste("FOCUS example dataset", ds.letter), sampling_times = unique(get(ds.name)$time), time_unit = "", observed = as.character(unique(get(ds.name)$name)), unit = "% AR", replicates = 1, data = get(ds.name) ) ds[[ds.index]]$data$name <- as.character(ds[[ds.index]]$data$name) ds[[ds.index]]$data$override = as.numeric(NA) ds[[ds.index]]$data$err = 1 } # Dataframe with datasets for selection {{{2 update_ds.df <- function() { ds.n <- length(ds) ds.df <<- data.frame(Index = 1:ds.n, Title = character(ds.n), Study = character(ds.n), stringsAsFactors = FALSE) for (i in 1:ds.n) { ds.index <- names(ds)[[i]] ds.df[i, "Title"] <<- ds[[ds.index]]$title ds.df[i, "Study"] <<- ds[[ds.index]]$study_nr observed = as.character(unique(ds[[ds.index]]$data$name)) observed.all <<- union(observed, observed.all) } } ds.df <- data.frame() update_ds.df() ds.cur = "1" # Initial models {{{2 m <- list() m[["1"]] <- mkinmod(parent = list(type = "SFO")) m[["1"]]$name = "SFO" m[["2"]] <- mkinmod(parent = list(type = "FOMC")) m[["2"]]$name = "FOMC" m[["3"]] <- mkinmod(parent = list(type = "DFOP")) m[["3"]]$name = "DFOP" m[["4"]] <- mkinmod(parent = list(type = "SFO", to = "m1"), m1 = list(type = "SFO"), use_of_ff = "max") m[["4"]]$name = "SFO_SFO" # Dataframe with models for selection {{{2 update_m.df <- function() { m.n <- length(m) m.df <<- data.frame(Index = 1:m.n, Name = character(m.n), stringsAsFactors = FALSE) for (i in 1:m.n) { m.index <- names(m)[[i]] m.df[i, "Name"] <<- m[[m.index]]$name } } m.df <- data.frame() update_m.df() m.cur = "1" # Initial fit lists {{{2 # The fits and summaries are collected in lists of lists f <- s <- list() # Dataframe with fits for selection {{{2 update_f.df <- function() { f.df <<- data.frame(Fit = character(), Dataset = character(), Model = character(), stringsAsFactors = FALSE) f.count <- 0 for (fit.index in names(f)) { f.count <- f.count + 1 ftmp <- f[[fit.index]] f.df[f.count, ] <<- c(as.character(f.count), ftmp$ds.index, ftmp$mkinmod$name) } } f.df.empty <- f.df <- data.frame(Fit = "0", Dataset = "", Model = "", stringsAsFactors = FALSE) # Widgets and handlers for project data {{{1 prg <- gexpandgroup("Project file management", cont = left, horizontal = FALSE) # Project data management handler functions {{{2 upload_file_handler <- function(h, ...) { # General tmpfile <- normalizePath(svalue(h$obj), winslash = "/") project_file <<- pr.gf$filename project_name <<- try(load(tmpfile)) if (inherits(project_name, "try-error")) { galert(paste("Failed to load", project_file, "from", getwd()), parent = w) } svalue(sb) <- paste("Loaded project file", project_file, "from working directory", getwd()) svalue(pr.ge) <- project_name workspace <- get(project_name) # Studies studies.gdf[,] <- studies.df <- workspace$studies.df # Datasets ds.cur <<- workspace$ds.cur ds <<- workspace$ds update_ds.df() ds.gtable[,] <- ds.df update_ds_editor() # Models m.cur <<- workspace$m.cur m <<- workspace$m update_m.df() m.gtable[,] <- m.df update_m_editor() # Fits f.cur <<- workspace$f.cur f <<- workspace$f s <<- workspace$s if (length(f) > 0) { update_f.df() ftmp <<- f[[f.cur]] stmp <<- s[[f.cur]] ds.i <<- ds.cur update_plotting_and_fitting() } else { f.df <<- f.df.empty update_ds_editor() svalue(center) <- 1 } f.gtable[,] <- f.df } save_to_file_handler <- function(h, ...) { studies.df <- data.frame(studies.gdf[,], stringsAsFactors = FALSE) workspace <- list( studies.df = studies.df, ds = ds, ds.cur = ds.cur, m = m, m.cur = m.cur, f = f, f.cur = f.cur, s = s) assign(project_name, workspace) save(list = project_name, file = project_file) svalue(sb) <- paste("Saved project contents to", project_file, "in working directory", getwd()) } change_project_name_handler = function(h, ...) { project_name <<- as.character(svalue(h$obj)) project_file <<- paste0(project_name, ".RData") } # Project data management GUI elements {{{2 pr.gf <- gfile(text = "Select project file", cont = prg, handler = upload_file_handler) pr.ge <- gedit(project_name, cont = prg, label = "Project", width = 240, handler = change_project_name_handler) # The save button is always visible {{{1 gbutton("Save current project contents", cont = left, handler = save_to_file_handler) # GUI widgets and a function for Studies {{{1 stg <- gexpandgroup("Studies", cont = left) visible(stg) <- FALSE update_study_selector <- function(h, ...) { delete(ds.e.1, ds.study.gc) ds.study.gc <<- gcombobox(paste("Study", studies.gdf[,1]), cont = ds.e.1) svalue(ds.study.gc, index = TRUE) <- ds[[ds.cur]]$study_nr } studies.gdf <- gdf(studies.df, name = "Edit studies in the project", width = 290, height = 200, cont = stg) studies.gdf$set_column_width(1, 40) studies.gdf$set_column_width(2, 240) addHandlerChanged(studies.gdf, update_study_selector) # Datasets and models {{{1 dsm <- gframe("Datasets and models", cont = left, horizontal = FALSE) # Dataset table with handler {{{2 ds.switcher <- function(h, ...) { ds.cur <<- as.character(svalue(h$obj)) update_ds_editor() svalue(center) <- 1 } ds.gtable <- gtable(ds.df, width = 290, cont = dsm) addHandlerDoubleClick(ds.gtable, ds.switcher) size(ds.gtable) <- list(columnWidths = c(40, 200, 40)) ds.gtable$value <- 1 # Model table with handler {{{2 m.switcher <- function(h, ...) { m.cur <<- as.character(svalue(h$obj)) update_m_editor() svalue(center) <- 2 } m.gtable <- gtable(m.df, width = 290, cont = dsm) addHandlerDoubleClick(m.gtable, m.switcher) size(m.gtable) <- list(columnWidths = c(40, 240)) m.gtable$value <- 1 # Button for setting up a fit for the selected dataset and model gbutton("Configure fit for selected model and dataset", cont = dsm, handler = function(h, ...) { ds.i <<- as.character(svalue(ds.gtable)) m.i <<- as.character(svalue(m.gtable)) ftmp <<- suppressWarnings(mkinfit(m[[m.i]], override(ds[[ds.i]]$data), err = "err", control.modFit = list(maxiter = 0))) ftmp$ds.index <<- ds.i ftmp$ds <<- ds[[ds.i]] stmp <<- summary(ftmp) svalue(pf) <- paste0("Dataset ", ds.i, ", Model ", m[[m.i]]$name) show_plot("Initial", default = TRUE) svalue(f.gg.opts.st) <<- ftmp$solution_type svalue(f.gg.opts.weight) <<- ftmp$weight svalue(f.gg.opts.atol) <<- ftmp$atol svalue(f.gg.opts.rtol) <<- ftmp$rtol svalue(f.gg.opts.reweight.method) <<- ifelse( is.null(ftmp$reweight.method), "none", ftmp$reweight.method) svalue(f.gg.opts.reweight.tol) <<- ftmp$reweight.tol svalue(f.gg.opts.reweight.max.iter) <<- ftmp$reweight.max.iter f.gg.parms[,] <- get_Parameters(stmp, FALSE) svalue(f.gg.summary) <- capture.output(stmp) svalue(center) <- 3 }) # Fits {{{1 f.gf <- gframe("Fits", cont = left, horizontal = FALSE) # Fit table with handler {{{2 f.switcher <- function(h, ...) { if (svalue(h$obj) != "0") { f.cur <<- svalue(h$obj) ftmp <<- f[[f.cur]] stmp <<- s[[f.cur]] ds.i <<- ftmp$ds.index update_plotting_and_fitting() } svalue(center) <- 3 } f.gtable <- gtable(f.df, width = 290, cont = f.gf) addHandlerDoubleClick(f.gtable, f.switcher) size(f.gtable) <- list(columnWidths = c(40, 60, 180)) # Dataset editor {{{1 ds.editor <- gframe("Dataset 1", horizontal = FALSE, cont = center, label = "Dataset editor") # Handler functions {{{3 copy_dataset_handler <- function(h, ...) { ds.old <- ds.cur ds.cur <<- as.character(1 + length(ds)) svalue(ds.editor) <- paste("Dataset", ds.cur) ds[[ds.cur]] <<- ds[[ds.old]] update_ds.df() ds.gtable[,] <- ds.df } delete_dataset_handler <- function(h, ...) { ds[[ds.cur]] <<- NULL names(ds) <<- as.character(1:length(ds)) ds.cur <<- names(ds)[[1]] update_ds.df() ds.gtable[,] <- ds.df update_ds_editor() } new_dataset_handler <- function(h, ...) { ds.cur <<- as.character(1 + length(ds)) ds[[ds.cur]] <<- list( study_nr = 1, title = "", sampling_times = c(0, 1), time_unit = "", observed = "parent", unit = "", replicates = 1, data = data.frame( name = "parent", time = c(0, 1), value = c(100, NA), override = "NA", err = 1, stringsAsFactors = FALSE ) ) update_ds.df() ds.gtable[,] <- ds.df update_ds_editor() } new_ds_from_csv_handler <- function(h, ...) { tmpfile <- normalizePath(svalue(h$obj), winslash = "/") tmpd <- try(read.table(tmpfile, sep = "\t", header = TRUE, stringsAsFactors = FALSE)) tmpdw <- mkin_wide_to_long(tmpd) if (class(tmpd) != "try-error") { ds.cur <<- as.character(1 + length(ds)) ds[[ds.cur]] <<- list( study_nr = NA, title = "New upload", sampling_times = sort(unique(tmpd$t)), time_unit = "", observed = unique(tmpdw$name), unit = "", replicates = max(aggregate(tmpdw$time, list(tmpdw$time, tmpdw$name), length)$x), data = tmpdw) ds[[ds.cur]]$data$override <<- as.numeric(NA) ds[[ds.cur]]$data$err <<- 1 update_ds.df() ds.gtable[,] <- ds.df update_ds_editor() } else { galert("Uploading failed", parent = "w") } } empty_grid_handler <- function(h, ...) { obs <- strsplit(svalue(ds.e.obs), ", ")[[1]] sampling_times <- strsplit(svalue(ds.e.st), ", ")[[1]] replicates <- as.numeric(svalue(ds.e.rep)) new.data = data.frame( name = rep(obs, each = replicates * length(sampling_times)), time = as.numeric(rep(sampling_times, each = replicates, times = length(obs))), value = as.numeric(NA), override = as.numeric(NA), err = 1, stringsAsFactors = FALSE ) ds.e.gdf[,] <- new.data } keep_ds_changes_handler <- function(h, ...) { ds[[ds.cur]]$title <<- svalue(ds.title.ge) ds[[ds.cur]]$study_nr <<- as.numeric(gsub("Study ", "", svalue(ds.study.gc))) update_ds.df() ds.gtable[,] <- ds.df tmpd <- ds.e.gdf[,] ds[[ds.cur]]$data <<- tmpd ds[[ds.cur]]$sampling_times <<- sort(unique(tmpd$time)) ds[[ds.cur]]$time_unit <<- svalue(ds.e.stu) ds[[ds.cur]]$observed <<- unique(tmpd$name) ds[[ds.cur]]$unit <<- svalue(ds.e.obu) ds[[ds.cur]]$replicates <<- max(aggregate(tmpd$time, list(tmpd$time, tmpd$name), length)$x) update_ds_editor() } # Widget setup {{{3 # Line 1 {{{4 ds.e.1 <- ggroup(cont = ds.editor, horizontal = TRUE) glabel("Title: ", cont = ds.e.1) ds.title.ge <- gedit(ds[[ds.cur]]$title, cont = ds.e.1) glabel(" from ", cont = ds.e.1) ds.study.gc <- gcombobox(paste("Study", studies.gdf[,1]), cont = ds.e.1) # Line 2 {{{4 ds.e.2 <- ggroup(cont = ds.editor, horizontal = TRUE) gbutton("Copy dataset", cont = ds.e.2, handler = copy_dataset_handler) gbutton("Delete dataset", cont = ds.e.2, handler = delete_dataset_handler) gbutton("New dataset", cont = ds.e.2, handler = new_dataset_handler) upload_dataset.gf <- gfile(text = "Upload text file", cont = ds.e.2, handler = new_ds_from_csv_handler) # Line 3 with forms {{{4 ds.e.forms <- ggroup(cont= ds.editor, horizontal = TRUE) ds.e.3a <- gvbox(cont = ds.e.forms) ds.e.3a.gfl <- gformlayout(cont = ds.e.3a) ds.e.st <- gedit(paste(ds[[ds.cur]]$sampling_times, collapse = ", "), width = 40, label = "Sampling times", cont = ds.e.3a.gfl) ds.e.stu <- gedit(ds[[ds.cur]]$time_unit, width = 20, label = "Unit", cont = ds.e.3a.gfl) ds.e.rep <- gedit(ds[[ds.cur]]$replicates, width = 20, label = "Replicates", cont = ds.e.3a.gfl) ds.e.3b <- gvbox(cont = ds.e.forms) ds.e.3b.gfl <- gformlayout(cont = ds.e.3b) ds.e.obs <- gedit(paste(ds[[ds.cur]]$observed, collapse = ", "), width = 50, label = "Observed", cont = ds.e.3b.gfl) ds.e.obu <- gedit(ds[[ds.cur]]$unit, width = 20, label = "Unit", cont = ds.e.3b.gfl) generate_grid.gb <- gbutton("Generate empty grid for kinetic data", cont = ds.e.3b, handler = empty_grid_handler) tooltip(generate_grid.gb) <- "Overwrites the kinetic data shown below" # Keep button {{{4 gbutton("Keep changes", cont = ds.editor, handler = keep_ds_changes_handler) # Kinetic Data {{{4 ds.e.gdf <- gdf(ds[[ds.cur]]$data, name = "Kinetic data", width = 500, height = 700, cont = ds.editor) ds.e.gdf$set_column_width(2, 70) # Update the dataset editor {{{3 update_ds_editor <- function() { svalue(ds.editor) <- paste("Dataset", ds.cur) svalue(ds.title.ge) <- ds[[ds.cur]]$title svalue(ds.study.gc, index = TRUE) <- ds[[ds.cur]]$study_nr svalue(ds.e.st) <- paste(ds[[ds.cur]]$sampling_times, collapse = ", ") svalue(ds.e.stu) <- ds[[ds.cur]]$time_unit svalue(ds.e.obs) <- paste(ds[[ds.cur]]$observed, collapse = ", ") svalue(ds.e.obu) <- ds[[ds.cur]]$unit svalue(ds.e.rep) <- ds[[ds.cur]]$replicates ds.e.gdf[,] <- ds[[ds.cur]]$data } # Model editor {{{1 m.editor <- gframe("Model 1", horizontal = FALSE, cont = center, label = "Model editor") # Handler functions {{{3 copy_model_handler <- function(h, ...) { m.old <- m.cur m.cur <<- as.character(1 + length(m)) svalue(m.editor) <- paste("Model", m.cur) m[[m.cur]] <<- m[[m.old]] update_m.df() m.gtable[,] <- m.df } delete_model_handler <- function(h, ...) { m[[m.cur]] <<- NULL names(m) <<- as.character(1:length(m)) m.cur <<- "1" update_m.df() m.gtable[,] <- m.df update_m_editor() } add_observed_handler <- function(h, ...) { obs.i <- length(m.e.rows) + 1 m.e.rows[[obs.i]] <<- ggroup(cont = m.editor, horizontal = TRUE) m.e.obs[[obs.i]] <<- gcombobox(observed.all, selected = obs.i, cont = m.e.rows[[obs.i]]) m.e.type[[obs.i]] <<- gcombobox(c("SFO", "FOMC", "DFOP", "HS", "SFORB"), cont = m.e.rows[[obs.i]]) svalue(m.e.type[[obs.i]]) <- "SFO" glabel("to", cont = m.e.rows[[obs.i]]) m.e.to[[obs.i]] <<- gedit("", cont = m.e.rows[[obs.i]]) m.e.sink[[obs.i]] <<- gcheckbox("Path to sink", checked = TRUE, cont = m.e.rows[[obs.i]]) gbutton("Remove compound", handler = remove_compound_handler, action = obs.i, cont = m.e.rows[[obs.i]]) } remove_compound_handler <- function(h, ...) { m[[m.cur]]$spec[[h$action]] <<- NULL update_m_editor() } keep_m_changes_handler <- function(h, ...) { spec <- list() for (obs.i in 1:length(m.e.rows)) { to_vector = strsplit(svalue(m.e.to[[obs.i]]), ", ")[[1]] if (length(to_vector) == 0) to_vector = "" spec[[obs.i]] <- list(type = svalue(m.e.type[[obs.i]]), to = to_vector, sink = svalue(m.e.sink[[obs.i]])) if(spec[[obs.i]]$to == "") spec[[obs.i]]$to = NULL names(spec)[[obs.i]] <- svalue(m.e.obs[[obs.i]]) } m[[m.cur]] <<- mkinmod(use_of_ff = svalue(m.ff.gc), speclist = spec) m[[m.cur]]$name <<- svalue(m.name.ge) update_m.df() m.gtable[,] <- m.df } # Widget setup {{{3 m.e.0 <- ggroup(cont = m.editor, horizontal = TRUE) glabel("Model name: ", cont = m.e.0) m.name.ge <- gedit(m[[m.cur]]$name, cont = m.e.0) glabel("Use of formation fractions: ", cont = m.e.0) m.ff.gc <- gcombobox(c("min", "max"), cont = m.e.0) svalue(m.ff.gc) <- m[[m.cur]]$use_of_ff # Model handling buttons {{{4 m.e.b <- ggroup(cont = m.editor, horizontal = TRUE) gbutton("Copy model", cont = m.e.b, handler = copy_model_handler) gbutton("Delete model", cont = m.e.b, handler = delete_model_handler) gbutton("Add transformation product", cont = m.e.b, handler = add_observed_handler) gbutton("Keep changes", cont = m.e.b, handler = keep_m_changes_handler) m.observed <- names(m[[m.cur]]$spec) m.e.rows <- m.e.obs <- m.e.type <- m.e.to <- m.e.sink <- list() obs.to <- "" # Show the model specification {{{4 show_m_spec <- function() { for (obs.i in 1:length(m[[m.cur]]$spec)) { obs.name <- names(m[[m.cur]]$spec)[[obs.i]] m.e.rows[[obs.i]] <<- ggroup(cont = m.editor, horizontal = TRUE) m.e.obs[[obs.i]] <<- gcombobox(observed.all, selected = 0, cont = m.e.rows[[obs.i]]) svalue(m.e.obs[[obs.i]]) <<- obs.name m.e.type[[obs.i]] <<- gcombobox(c("SFO", "FOMC", "DFOP", "HS", "SFORB"), cont = m.e.rows[[obs.i]]) svalue(m.e.type[[obs.i]]) <<- m[[m.cur]]$spec[[obs.i]]$type glabel("to", cont = m.e.rows[[obs.i]]) obs.to <<- ifelse(is.null(m[[m.cur]]$spec[[obs.i]]$to), "", paste(m[[m.cur]]$spec[[obs.i]]$to, collapse = ", ")) m.e.to[[obs.i]] <<- gedit(obs.to, cont = m.e.rows[[obs.i]]) m.e.sink[[obs.i]] <<- gcheckbox("Path to sink", checked = m[[m.cur]]$spec[[obs.i]]$sink, cont = m.e.rows[[obs.i]]) if (obs.i > 1) { gbutton("Remove compound", handler = remove_compound_handler, action = obs.i, cont = m.e.rows[[obs.i]]) } } } show_m_spec() # Update the model editor {{{3 update_m_editor <- function() { svalue(m.editor) <- paste("Model", m.cur) svalue(m.name.ge) <- m[[m.cur]]$name svalue(m.ff.gc) <- m[[m.cur]]$use_of_ff for (oldrow.i in 1:length(m.e.rows)) { delete(m.editor, m.e.rows[[oldrow.i]]) } m.observed <<- names(m[[m.cur]]$spec) m.e.rows <<- m.e.obs <<- m.e.type <<- m.e.to <<- m.e.sink <<- list() show_m_spec() } # 3}}} # 2}}} # Plotting and fitting {{{1 show_plot <- function(type, default = FALSE) { Parameters <- f.gg.parms[,] Parameters.de <- subset(Parameters, Type == "deparm", type) stateparms <- subset(Parameters, Type == "state")[[type]] deparms <- as.numeric(Parameters.de[[type]]) names(deparms) <- rownames(Parameters.de) if (type == "Initial" & default == FALSE) { ftmp <<- suppressWarnings(mkinfit(ftmp$mkinmod, override(ds[[ds.i]]$data), state.ini = stateparms, parms.ini = deparms, err = "err", control.modFit = list(maxiter = 0))) ftmp$ds.index <<- ds.i ftmp$ds <<- ds[[ds.i]] } svg(tf, width = 7, height = 5) plot(ftmp, main = ftmp$ds$title, xlab = ifelse(ftmp$ds$time_unit == "", "Time", paste("Time in", ftmp$ds$time_unit)), ylab = ifelse(ds[[ds.i]]$unit == "", "Observed", paste("Observed in", ftmp$ds$unit))) dev.off() svalue(plot.gs) <<- tf } get_Parameters <- function(stmp, optimised) { pars <- rbind(stmp$start[1:2], stmp$fixed) pars$fixed <- c(rep(FALSE, length(stmp$start$value)), rep(TRUE, length(stmp$fixed$value))) pars$name <- rownames(pars) Parameters <- data.frame(Name = pars$name, Type = pars$type, Initial = pars$value, Fixed = pars$fixed, Optimised = as.numeric(NA)) Parameters <- rbind(subset(Parameters, Type == "state"), subset(Parameters, Type == "deparm")) rownames(Parameters) <- Parameters$Name if (optimised) { Parameters[rownames(stmp$bpar), "Optimised"] <- stmp$bpar[, "Estimate"] } return(Parameters) } run_fit <- function() { Parameters <- f.gg.parms[,] Parameters.de <- subset(Parameters, Type == "deparm") deparms <- Parameters.de$Initial names(deparms) <- Parameters.de$Name defixed <- names(deparms[Parameters.de$Fixed]) Parameters.ini <- subset(Parameters, Type == "state") iniparms <- Parameters.ini$Initial names(iniparms) <- sub("_0", "", Parameters.ini$Name) inifixed <- names(iniparms[Parameters.ini$Fixed]) weight <- svalue(f.gg.opts.weight) if (weight == "manual") { err = "err" } else { err = NULL } reweight.method <- svalue(f.gg.opts.reweight.method) if (reweight.method == "none") reweight.method = NULL ftmp <<- mkinfit(ftmp$mkinmod, override(ds[[ds.i]]$data), state.ini = iniparms, fixed_initials = inifixed, parms.ini = deparms, fixed_parms = defixed, solution_type = svalue(f.gg.opts.st), atol = as.numeric(svalue(f.gg.opts.atol)), rtol = as.numeric(svalue(f.gg.opts.rtol)), weight = weight, err = err, reweight.method = reweight.method, reweight.tol = as.numeric(svalue(f.gg.opts.reweight.tol)), reweight.max.iter = as.numeric(svalue(f.gg.opts.reweight.max.iter)) ) ftmp$ds.index <<- ds.i ftmp$ds <<- ds[[ds.i]] stmp <<- summary(ftmp) show_plot("Optimised") svalue(f.gg.opts.st) <- ftmp$solution_type svalue(f.gg.opts.weight) <- ftmp$weight.ini f.gg.parms[,] <- get_Parameters(stmp, TRUE) svalue(f.gg.summary) <- capture.output(stmp) } ds.i <- m.i <- "1" f.cur <- "0" # GUI widgets {{{2 pf <- gframe("Dataset 1, Model SFO", horizontal = FALSE, cont = center, label = "Plotting and fitting") # Mid group with plot and options {{{3 f.gg.mid <- ggroup(cont = pf) ftmp <- suppressWarnings(mkinfit(m[[m.cur]], override(ds[[ds.i]]$data), err = "err", control.modFit = list(maxiter = 0))) ftmp$ds.index = ds.i ftmp$ds = ds[[ds.i]] stmp <- summary(ftmp) Parameters <- get_Parameters(stmp, FALSE) tf <- get_tempfile(ext=".svg") svg(tf, width = 7, height = 5) plot(ftmp) dev.off() plot.gs <- gsvg(tf, container = f.gg.mid, width = 420, height = 300) f.gg.opts <- gformlayout(cont = f.gg.mid) solution_types <- c("auto", "analytical", "eigen", "deSolve") f.gg.opts.st <- gcombobox(solution_types, selected = 1, label = "solution_type", width = 200, cont = f.gg.opts) f.gg.opts.atol <- gedit(ftmp$atol, label = "atol", width = 20, cont = f.gg.opts) f.gg.opts.rtol <- gedit(ftmp$rtol, label = "rtol", width = 20, cont = f.gg.opts) weights <- c("manual", "none", "std", "mean") f.gg.opts.weight <- gcombobox(weights, selected = 1, label = "weight", width = 200, cont = f.gg.opts) f.gg.opts.reweight.method <- gcombobox(c("none", "obs"), selected = 1, label = "reweight.method", width = 200, cont = f.gg.opts) f.gg.opts.reweight.tol <- gedit(1e-8, label = "reweight.tol", width = 20, cont = f.gg.opts) f.gg.opts.reweight.max.iter <- gedit(10, label = "reweight.max.iter", width = 20, cont = f.gg.opts) # Dataframe with initial and optimised parameters {{{3 f.gg.parms <- gdf(Parameters, width = 420, height = 300, cont = pf, do_add_remove_buttons = FALSE) f.gg.parms$set_column_width(1, 200) f.gg.parms$set_column_width(2, 50) f.gg.parms$set_column_width(3, 60) f.gg.parms$set_column_width(4, 50) f.gg.parms$set_column_width(5, 60) # Row with buttons {{{3 f.gg.buttons <- ggroup(cont = pf) show.initial.gb <- gbutton("Show initial", handler = function(h, ...) show_plot("Initial"), cont = f.gg.buttons) tooltip(show.initial.gb) <- "Show model with current inital settings for current dataset" run.fit.gb <- gbutton("Run", handler = function(h, ...) run_fit(), cont = f.gg.buttons) tooltip(run.fit.gb) <- "Fit with current settings on the current dataset, with the original model" keep.fit.gb <- gbutton("Keep", handler = function(h, ...) { f.cur <<- as.character(length(f) + 1) f[[f.cur]] <<- ftmp s[[f.cur]] <<- stmp update_f.df() f.gtable[,] <<- f.df }, cont = f.gg.buttons) tooltip(keep.fit.gb) <- "Store the optimised model with all settings and the current dataset in the fit list" show.plots.gb <- gbutton("Show plots", handler = function(h, ...) show_plot_window(), cont = f.gg.buttons) tooltip(show.plots.gb) <- "Show a window with plots including residual plots" # Summary {{{3 f.gg.summary <- gtext(capture.output(stmp), cont = pf, use.codemirror = TRUE) delete.fit.gb <- gbutton("Delete", handler = function(h, ...) { if (length(f) > 0) { f[[f.cur]] <<- NULL s[[f.cur]] <<- NULL } if (length(f) > 0) { names(f) <<- as.character(1:length(f)) names(s) <<- as.character(1:length(f)) update_f.df() f.cur <<- "1" ftmp <<- f[[f.cur]] stmp <<- s[[f.cur]] ds.i <<- ftmp$ds.index update_plotting_and_fitting() } else { f.df <<- f.df.empty f.cur <<- "0" } f.gtable[,] <<- f.df }, cont = f.gg.buttons) tooltip(delete.fit.gb) <- "Delete the currently loaded fit from the fit list" # Update the plotting and fitting area {{{3 update_plotting_and_fitting <- function() { svalue(pf) <- paste0("Fit ", f.cur, ": Dataset ", ftmp$ds.index, ", Model ", ftmp$mkinmod$name) show_plot("Optimised") svalue(f.gg.opts.st) <- ftmp$solution_type svalue(f.gg.opts.weight) <- ftmp$weight.ini svalue(f.gg.opts.reweight.method) <- ifelse(is.null(ftmp$reweight.method), "none", ftmp$reweight.method) svalue(f.gg.opts.reweight.tol) <- ftmp$reweight.tol svalue(f.gg.opts.reweight.max.iter) <- ftmp$reweight.max.iter f.gg.parms[,] <- get_Parameters(stmp, TRUE) svalue(f.gg.summary) <- capture.output(stmp) } # Show plot window with residual plots {{{3 show_plot_window <- function(h, ...) { n.obs = length(ftmp$mkinmod$spec) obs.vars = names(ftmp$mkinmod$spec) parent = obs.vars[1] if(n.obs == 1) { n.rows = 1 ps = 7 } else { n.rows = 1 + ceiling(n.obs / 2) ps = 10 } imgwidth = 800 imgheight = 360 * n.rows pw <- gwindow("Plot window", parent = w, width = imgwidth + 20, height = imgheight + 100) pwg <- ggroup(cont = pw, horizontal = FALSE) make_plots <- function() { par(mfrow = c(n.rows, 2)) plot(ftmp, main = ftmp$ds$title, xlab = ifelse(ftmp$ds$time_unit == "", "Time", paste("Time in", ftmp$ds$time_unit)), ylab = ifelse(ds[[ds.i]]$unit == "", "Observed", paste("Observed in", ftmp$ds$unit))) if (n.obs > 1) { plot(ftmp, legend = FALSE, main = paste0("Zoomed in on metabolite", ifelse(n.obs > 2, "s", "")), xlab = ifelse(ftmp$ds$time_unit == "", "Time", paste("Time in", ftmp$ds$time_unit)), ylab = ifelse(ds[[ds.i]]$unit == "", "Observed", paste("Observed in", ftmp$ds$unit)), ylim = c(0, max(subset(ftmp$data, variable != parent)$observed))) for (met in obs.vars[-1]) { mkinresplot(ftmp, met, legend = FALSE, main = paste("Residual plot for", met)) } } else { mkinresplot(ftmp, parent, legend = FALSE, main = paste("Residual plot for", parent), xlab = ifelse(ftmp$ds$time_unit == "", "Time", paste("Time in", ftmp$ds$time_unit)), ylab = ifelse(ds[[ds.i]]$unit == "", "Residuals", paste("Residuals in", ftmp$ds$unit))) } } tf2 <- get_tempfile(ext = ".png") png(tf2, width = imgwidth / 50 , height = imgheight / 50, units = "cm", res = 300, pointsize = ps) make_plots() dev.off() ghtml(paste0(""), cont = pwg) } # vim: set foldmethod=marker ts=2 sw=2 expandtab: {{{1