# 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 <http://www.gnu.org/licenses/>
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 = 260)
center <- gnotebook(cont = pg)
left <- gvbox(cont = pg, use.scrollwindow = TRUE)
# Set initial values {{{1
# Initial project workspace contents {{{2
project_name <- "FOCUS_2006_gmkin"
project_file <- paste0(project_name, ".RData")
workspace <- get(project_name) # From dataset distributed with mkin
studies.df <- workspace$studies.df # dataframe containing study titles
ds <- workspace$ds # list of datasets
ds.cur <- workspace$ds.cur # current dataset index
m <- workspace$m # list with mkinmod models, amended with mkinmod$name
m.cur <- workspace$m.cur # m.cur current model index
f <- workspace$f # f list of fitted mkinfit objects
f.cur <- workspace$f.cur # current fit index
s <- workspace$s # list of summaries of the fitted mkinfit objects
# Initialise meta data objects so assignments within functions using <<- will {{{2
# update them in the right environment
observed.all <- vector() # vector of names of observed variables in datasets
ds.df <- data.frame()
m.df <- data.frame()
f.df <- data.frame()
# Empty versions of meta data {{{2
f.df.empty <- data.frame(Fit = "0",
Dataset = "",
Model = "",
stringsAsFactors = FALSE)
# Helper functions {{{1
# Override function for making it possible to override original data in the GUI {{{2
override <- function(d) {
data.frame(name = d$name, time = d$time,
value = ifelse(is.na(d$override), d$value, d$override),
err = d$err)
}
# Update dataframe with datasets for selection {{{2
update_ds.df <- function() {
ds.n <- length(ds)
ds.df <<- data.frame(Index = 1:ds.n,
Title = character(ds.n),
Study = character(ds.n),
stringsAsFactors = FALSE)
for (i in 1:ds.n)
{
ds.index <- names(ds)[[i]]
ds.df[i, "Title"] <<- ds[[ds.index]]$title
ds.df[i, "Study"] <<- ds[[ds.index]]$study_nr
observed = as.character(unique(ds[[ds.index]]$data$name))
observed.all <<- union(observed, observed.all)
}
}
# Update dataframe with models for selection {{{2
update_m.df <- function() {
m.n <- length(m)
m.df <<- data.frame(Index = 1:m.n,
Name = character(m.n),
stringsAsFactors = FALSE)
for (i in 1:m.n) {
m.index <- names(m)[[i]]
m.df[i, "Name"] <<- m[[m.index]]$name
}
}
# Update dataframe with fits for selection {{{2
update_f.df <- function() {
f.df <<- f.df.empty
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$name)
}
}
# Initialise meta data objects {{{1
update_ds.df()
update_m.df()
update_f.df()
# Widgets and handlers for project data {{{1
prg <- gexpandgroup("Project file management", cont = left, horizontal = FALSE)
# Project data management handler functions {{{2
upload_file_handler <- function(h, ...)
{
# General
tmpfile <- normalizePath(svalue(h$obj), winslash = "/")
project_file <<- pr.gf$filename
project_name <<- try(load(tmpfile))
if (inherits(project_name, "try-error")) {
galert(paste("Failed to load", project_file), parent = w)
}
svalue(sb) <- paste("Loaded project file", project_file)
svalue(pr.ge) <- project_name
workspace <- get(project_name)
# Studies
studies.gdf[,] <- studies.df <- workspace$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$s
if (length(f) > 0) {
update_f.df()
ftmp <<- f[[f.cur]]
stmp <<- s[[f.cur]]
ds.i <<- ds.cur
delete(f.gg.plotopts, f.gg.po.obssel)
f.gg.po.obssel <<- gcheckboxgroup(names(ftmp$mkinmod$spec), cont = f.gg.plotopts,
checked = TRUE)
update_plotting_and_fitting()
} else {
f.df <<- f.df.empty
update_ds_editor()
svalue(center) <- 1
}
f.gtable[,] <- f.df
}
save_to_file_handler <- function(h, ...)
{
studies.df <- data.frame(studies.gdf[,], stringsAsFactors = FALSE)
workspace <- list(
studies.df = studies.df,
ds = ds,
ds.cur = ds.cur,
m = m,
m.cur = m.cur,
f = f,
f.cur = f.cur,
s = s)
assign(project_name, workspace)
save(list = project_name, file = project_file)
svalue(sb) <- paste("Saved project contents to", project_file, "in working directory", getwd())
}
change_project_name_handler = function(h, ...) {
project_name <<- as.character(svalue(h$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",
handler = change_project_name_handler)
# The save button is always visible {{{2
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]]$study_nr
}
studies.gdf <- gdf(studies.df, name = "Edit studies in the project",
width = 235,
height = 180, cont = stg)
studies.gdf$set_column_width(1, 40)
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$obj))
update_ds_editor()
svalue(center) <- 1
}
ds.gtable <- gtable(ds.df, cont = dsm)
addHandlerDoubleClick(ds.gtable, ds.switcher)
size(ds.gtable) <- list(columnWidths = c(40, 150, 30))
ds.gtable$value <- 1
# Model table with handler {{{2
m.switcher <- function(h, ...) {
m.cur <<- as.character(svalue(h$obj))
update_m_editor()
svalue(center) <- 2
}
m.gtable <- gtable(m.df, cont = dsm)
addHandlerDoubleClick(m.gtable, m.switcher)
m.gtable$set_column_width(1, 40)
m.gtable$value <- 1
# Button for setting up a fit for the selected dataset and model {{{2
gbutton("Configure fit for selected model and dataset", cont = dsm,
handler = function(h, ...) {
ds.i <<- as.character(svalue(ds.gtable))
m.i <<- as.character(svalue(m.gtable))
ftmp <<- suppressWarnings(mkinfit(m[[m.i]],
override(ds[[ds.i]]$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]]$name)
svalue(f.gg.opts.st) <<- ftmp$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$reweight.max.iter
f.gg.parms[,] <- get_Parameters(stmp, FALSE)
delete(f.gg.plotopts, f.gg.po.obssel)
f.gg.po.obssel <<- gcheckboxgroup(names(ftmp$mkinmod$spec), cont = f.gg.plotopts,
checked = TRUE)
show_plot("Initial", default = TRUE)
oldwidth <<- options()$width
options(width = 90)
svalue(f.gg.summary) <- c("<pre>", capture.output(stmp), "</pre>")
options(width = oldwidth)
svalue(center) <- 3
})
# Fits {{{1
f.gf <- gframe("Fits", cont = left, horizontal = FALSE)
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$ds.index
update_plotting_and_fitting()
}
svalue(center) <- 3
}
f.gtable <- gtable(f.df, cont = f.gf)
addHandlerDoubleClick(f.gtable, f.switcher)
f.gtable$set_column_width(1, 40)
f.gtable$set_column_width(2, 60)
# Dataset editor {{{1
ds.editor <- gframe("Dataset 1", horizontal = FALSE, cont = center,
label = "Dataset editor")
# Handler functions {{{3
copy_dataset_handler <- function(h, ...) {
ds.old <- ds.cur
ds.cur <<- as.character(1 + length(ds))
svalue(ds.editor) <- paste("Dataset", ds.cur)
ds[[ds.cur]] <<- ds[[ds.old]]
update_ds.df()
ds.gtable[,] <- ds.df
}
delete_dataset_handler <- function(h, ...) {
ds[[ds.cur]] <<- NULL
names(ds) <<- as.character(1:length(ds))
ds.cur <<- names(ds)[[1]]
update_ds.df()
ds.gtable[,] <- ds.df
update_ds_editor()
}
new_dataset_handler <- function(h, ...) {
ds.cur <<- as.character(1 + length(ds))
ds[[ds.cur]] <<- list(
study_nr = 1,
title = "",
sampling_times = c(0, 1),
time_unit = "",
observed = "parent",
unit = "",
replicates = 1,
data = data.frame(
name = "parent",
time = c(0, 1),
value = c(100, NA),
override = "NA",
err = 1,
stringsAsFactors = FALSE
)
)
update_ds.df()
ds.gtable[,] <- ds.df
update_ds_editor()
}
load_text_file_with_data <- function(h, ...) {
tmptextfile <<- normalizePath(svalue(h$obj), winslash = "/")
tmptext <- readLines(tmptextfile, warn = FALSE)
tmptextskip <<- 0
for (tmptextline in tmptext) {
if (grepl(":|#|/", tmptextline)) tmptextskip <<- tmptextskip + 1
else break()
}
svalue(ds.e.up.skip) <- tmptextskip
if (svalue(ds.e.up.header)) {
tmptextheader <<- strsplit(tmptext[tmptextskip + 1],
" |\t|;|,")[[1]]
}
svalue(ds.e.up.wide.time) <- tmptextheader[[1]]
svalue(ds.e.up.long.time) <- tmptextheader[[2]]
svalue(ds.e.up.text) <- c("<pre>", tmptext, "</pre>")
svalue(ds.e.stack) <- 2
}
new_ds_from_csv_handler <- function(h, ...) {
tmpd <- try(read.table(tmptextfile,
skip = as.numeric(svalue(ds.e.up.skip)),
dec = svalue(ds.e.up.dec),
sep = switch(svalue(ds.e.up.sep),
whitespace = "",
";" = ";",
"," = ","),
header = svalue(ds.e.up.header),
stringsAsFactors = FALSE))
if(svalue(ds.e.up.widelong) == "wide") {
tmpdl <- mkin_wide_to_long(tmpd, time = as.character(svalue(ds.e.up.wide.time)))
} else {
tmpdl <- 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$t)),
time_unit = "",
observed = unique(tmpdl$name),
unit = "",
replicates = max(aggregate(tmpdl$time,
list(tmpdl$time,
tmpdl$name),
length)$x),
data = tmpdl)
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()
observed.all <<- union(observed.all, ds[[ds.cur]]$observed)
update_m_editor()
}
# Widget setup {{{3
# Line 1 {{{4
ds.e.1 <- ggroup(cont = ds.editor, horizontal = TRUE)
glabel("Title: ", cont = ds.e.1)
ds.title.ge <- gedit(ds[[ds.cur]]$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)
ds.e.2a <- ggroup(cont = ds.e.2, horizontal = FALSE)
gbutton("Copy dataset", cont = ds.e.2a, handler = copy_dataset_handler)
gbutton("Delete dataset", cont = ds.e.2a, handler = delete_dataset_handler)
gbutton("New dataset", cont = ds.e.2a, handler = new_dataset_handler)
ds.e.2b <- ggroup(cont = ds.e.2)
tmptextfile <- "" # Initialize file name for imported data
tmptextskip <- 0 # Initialize number of lines to be skipped
tmptexttime <- "V1" # Initialize name of time variable if no header row
upload_dataset.gf <- gfile(text = "Upload text file", cont = ds.e.2b,
handler = load_text_file_with_data)
gbutton("Keep changes", cont = ds.e.2, handler = keep_ds_changes_handler)
# Line 3 with forms or upload area {{{4
ds.e.stack <- gstackwidget(cont = ds.editor)
# Forms for meta data {{{5
ds.e.forms <- ggroup(cont = ds.e.stack, 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]]$unit,
width = 20, label = "Unit",
cont = ds.e.3b.gfl)
generate_grid.gb <- gbutton("Generate empty grid for kinetic data", cont = ds.e.3b,
handler = empty_grid_handler)
tooltip(generate_grid.gb) <- "Overwrites the kinetic data shown below"
# Data upload area {{{5
ds.e.upload <- ggroup(cont = ds.e.stack, horizontal = TRUE)
ds.e.up.text <- ghtml("<pre></pre>", cont = ds.e.upload, width = 400, height = 400)
ds.e.up.options <- ggroup(cont = ds.e.upload, horizontal = FALSE)
ds.e.up.import <- gbutton("Import using options specified below", cont = ds.e.up.options,
handler = new_ds_from_csv_handler)
ds.e.up.skip <- gedit(tmptextskip, label = "Comment lines", cont = ds.e.up.options)
ds.e.up.header <- gcheckbox(cont = ds.e.up.options, label = "Column names",
checked = TRUE)
ds.e.up.sep <- gcombobox(c("whitespace", ";", ","), cont = ds.e.up.options,
selected = 1, label = "Separator")
ds.e.up.dec <- gcombobox(c(".", ","), cont = ds.e.up.options,
selected = 1, label = "Decimal")
ds.e.up.widelong <- gradio(c("wide", "long"), horizontal = TRUE,
label = "Format", cont = ds.e.up.options,
handler = function(h, ...) {
widelong = svalue(h$obj, index = TRUE)
svalue(ds.e.up.wlstack) <- widelong
})
ds.e.up.wlstack <- gstackwidget(cont = ds.e.up.options)
ds.e.up.wide <- ggroup(cont = ds.e.up.wlstack, horizontal = FALSE, width = 300)
ds.e.up.wide.time <- gedit(tmptexttime, cont = ds.e.up.wide, label = "Time column")
ds.e.up.long <- ggroup(cont = ds.e.up.wlstack, horizontal = FALSE, width = 300)
ds.e.up.long.name <- gedit("name", cont = ds.e.up.long, label = "Observed variables")
ds.e.up.long.time <- gedit(tmptexttime, cont = ds.e.up.long, label = "Time column")
ds.e.up.long.value <- gedit("value", cont = ds.e.up.long, label = "Value column")
ds.e.up.long.err <- gedit("err", cont = ds.e.up.long, label = "Relative errors")
svalue(ds.e.up.wlstack) <- 1
svalue(ds.e.stack) <- 1
# 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]]$replicates
svalue(ds.e.stack) <- 1
ds.e.gdf[,] <- ds[[ds.cur]]$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]]$data),
parms.ini = deparms,
state.ini = stateparms,
fixed_parms = names(deparms),
fixed_initials = names(stateparms),
err = "err",
control.modFit = list(maxiter = 0)))
ftmp$ds.index <<- ds.i
ftmp$ds <<- ds[[ds.i]]
}
svalue(plot.ftmp.gi) <<- plot_ftmp_png()
svalue(plot.confint.gi) <<- plot_confint_png()
}
get_Parameters <- function(stmp, optimised)
{
pars <- rbind(stmp$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)),
transform_rates = svalue(f.gg.opts.transform_rates),
transform_fractions = svalue(f.gg.opts.transform_fractions),
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) <- c("<pre>", capture.output(stmp), "</pre>")
}
ds.i <- m.i <- "1"
f.cur <- "0"
# GUI widgets {{{2
pf <- gframe("Dataset 1, Model SFO", horizontal = TRUE,
cont = center, label = "Plotting and fitting")
# Plot area to the left {{{3
pf.p <- ggroup(cont = pf, horizontal = FALSE)
ftmp <- suppressWarnings(mkinfit(m[[m.cur]], override(ds[[ds.i]]$data),
err = "err",
control.modFit = list(maxiter = 0)))
ftmp$ds.index = ds.i
ftmp$ds = ds[[ds.i]]
stmp <- summary(ftmp)
Parameters <- get_Parameters(stmp, FALSE)
plot_ftmp_png <- function() {
tf <- get_tempfile(ext=".png")
if(exists("f.gg.po.obssel")) {
obs_vars_plot = svalue(f.gg.po.obssel)
} else {
obs_vars_plot = names(ftmp$mkinmod$spec)
}
png(tf, width = 400, height = 400)
plot(ftmp, main = ftmp$ds$title, obs_vars = obs_vars_plot,
xlab = ifelse(ftmp$ds$time_unit == "", "Time",
paste("Time in", ftmp$ds$time_unit)),
ylab = ifelse(ds[[ds.i]]$unit == "", "Observed",
paste("Observed in", ftmp$ds$unit)),
show_residuals = TRUE)
dev.off()
return(tf)
}
plot_confint_png <- function() {
tf <- get_tempfile(ext=".png")
png(tf, width = 400, height = 400)
mkinparplot(ftmp)
dev.off()
return(tf)
}
plot.ftmp.gi <- gimage(plot_ftmp_png(), container = pf.p, width = 400, height = 400)
plot.confint.gi <- gimage(plot_confint_png(), container = pf.p, width = 400, height = 400)
# Buttons and notebook area to the right {{{3
p.gg <- ggroup(cont = pf, horizontal = FALSE)
# Row with buttons {{{4
f.gg.buttons <- ggroup(cont = p.gg)
run.fit.gb <- gbutton("Run", width = 100,
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
delete(f.gg.plotopts, f.gg.po.obssel)
f.gg.po.obssel <<- gcheckboxgroup(names(ftmp$mkinmod$spec),
cont = f.gg.plotopts,
checked = TRUE)
}, cont = f.gg.buttons)
tooltip(keep.fit.gb) <- "Store the optimised model with all settings and the current dataset in the fit list"
delete.fit.gb <- gbutton("Delete fit", 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$ds.index
update_plotting_and_fitting()
} else {
f.df <<- f.df.empty
f.cur <<- "0"
}
f.gtable[,] <<- f.df
}, cont = f.gg.buttons)
tooltip(delete.fit.gb) <- "Delete the currently loaded fit from the fit list"
show.initial.gb <- gbutton("Show initial",
handler = function(h, ...) show_plot("Initial"),
cont = f.gg.buttons)
tooltip(show.initial.gb) <- "Show model with current inital settings for current dataset"
get_initials_handler <- function(h, ...)
{
f.i <- svalue(get.initials.gc, index = TRUE)
if (length(f) > 0) {
got_initials <- c(f[[f.i]]$bparms.fixed, f[[f.i]]$bparms.optim)
parnames <- f.gg.parms[,"Name"]
newparnames <- names(got_initials)
commonparnames <- intersect(parnames, newparnames)
f.gg.parms[commonparnames, "Initial"] <<- got_initials[commonparnames]
}
}
get.initials.gb <- gbutton("Get initials from", cont = f.gg.buttons,
handler = get_initials_handler)
get.initials.gc <- gcombobox(paste("Fit", f.df$Fit), cont = f.gg.buttons)
# Notebook to the right {{{3
f.gn <- gnotebook(cont = p.gg, width = 680, height = 790)
# Dataframe with initial and optimised parameters {{{4
f.gg.parms <- gdf(Parameters, cont = f.gn,
width = 670, height = 750,
do_add_remove_buttons = FALSE, label = "Parameters")
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$set_column_width(5, 60)
# Fit options form {{{4
f.gg.opts <- gformlayout(cont = f.gn, label = "Fit options")
solution_types <- c("auto", "analytical", "eigen", "deSolve")
f.gg.opts.st <- gcombobox(solution_types, selected = 1,
label = "solution_type", width = 200,
cont = f.gg.opts)
f.gg.opts.atol <- gedit(ftmp$atol, label = "atol", width = 20,
cont = f.gg.opts)
f.gg.opts.rtol <- gedit(ftmp$rtol, label = "rtol", width = 20,
cont = f.gg.opts)
f.gg.opts.transform_rates <- gcheckbox("transform_rates",
cont = f.gg.opts, checked = TRUE)
f.gg.opts.transform_fractions <- gcheckbox("transform_fractions",
cont = f.gg.opts, checked = TRUE)
weights <- c("manual", "none", "std", "mean")
f.gg.opts.weight <- gcombobox(weights, selected = 1, label = "weight",
width = 200, cont = f.gg.opts)
f.gg.opts.reweight.method <- gcombobox(c("none", "obs"), selected = 1,
label = "reweight.method",
width = 200,
cont = f.gg.opts)
f.gg.opts.reweight.tol <- gedit(1e-8, label = "reweight.tol",
width = 20, cont = f.gg.opts)
f.gg.opts.reweight.max.iter <- gedit(10, label = "reweight.max.iter",
width = 20, cont = f.gg.opts)
# Summary {{{3
oldwidth <- options()$width
options(width = 90)
f.gg.summary <- ghtml(c("<pre>", capture.output(stmp), "</pre>"),
cont = f.gn, label = "Summary")
options(width = oldwidth)
# Plot options {{{4
f.gg.plotopts <- ggroup(cont = f.gn, label = "Plot options", horizontal = FALSE)
f.gg.po.update <- gbutton("Update plot",
handler = function(h, ...) show_plot("Optimised"),
cont = f.gg.plotopts)
f.gg.po.obssel <- gcheckboxgroup(names(m[[m.cur]]$spec), cont = f.gg.plotopts,
checked = TRUE)
svalue(f.gn) <- 1
# Update the plotting and fitting area {{{3
update_plotting_and_fitting <- function() {
svalue(pf) <- paste0("Fit ", f.cur, ": Dataset ", ftmp$ds.index,
", Model ", ftmp$mkinmod$name)
# Parameters
f.gg.parms[,] <- get_Parameters(stmp, TRUE)
# Fit options
delete(f.gg.buttons, get.initials.gc)
get.initials.gc <<- gcombobox(paste("Fit", f.df$Fit), cont = f.gg.buttons)
svalue(f.gg.opts.st) <- ftmp$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$reweight.max.iter
# Summary
oldwidth <<- options()$width
options(width = 90)
svalue(f.gg.summary) <- c("<pre>", capture.output(stmp), "</pre>")
options(width = oldwidth)
# Plot options
delete(f.gg.plotopts, f.gg.po.obssel)
f.gg.po.obssel <<- gcheckboxgroup(names(ftmp$mkinmod$spec), cont = f.gg.plotopts,
checked = TRUE)
# Plot
show_plot("Optimised")
}
# vim: set foldmethod=marker ts=2 sw=2 expandtab: {{{1