Squashed commit of the following:

commit d8dbf2ad866fb9d34cd1100000b9c116219ecef6
Author: Johannes Ranke <jranke@uni-bremen.de>
Date:   Wed Nov 13 22:09:41 2013 +0100

    Add possibility to control more mkinfit arguments from the GUI

commit 8f1bae2142b37a0ff6b8989b2d1569686937f68e
Author: Johannes Ranke <jranke@uni-bremen.de>
Date:   Wed Nov 13 20:30:11 2013 +0100

    Add initial weighting choice to GUI

commit c99b5c298713a7c14e8ab5604c68613d0b7af27a
Author: Johannes Ranke <jranke@uni-bremen.de>
Date:   Wed Nov 13 16:25:31 2013 +0100

    Update of TODO from git bash on Windows

commit 8bf2a6f8f6bd752433f06b26b5da334e958f5166
Author: Johannes Ranke <jranke@uni-bremen.de>
Date:   Wed Nov 13 16:00:01 2013 +0100

    Update of README using TortoiseGit

git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@162 edb9625f-4e0d-4859-8d74-9fd3b1da38cb

4 files changed, 56 insertions, 11 deletions

diff --git a/R/mkinfit.R b/R/mkinfit.R
index d04d1ea6..3e47479f 100644
--- a/R/mkinfit.R
+++ b/R/mkinfit.R
@@ -281,6 +281,8 @@ mkinfit <- function(mkinmod, observed,
   fit$rtol <- rtol

   fit$weight.ini <- weight.ini

   fit$reweight.method <- reweight.method

+  fit$reweight.tol <- reweight.tol

+  fit$reweight.max.iter <- reweight.max.iter

 

   # Return all backtransformed parameters for summary

   fit$bparms.optim <- bparms.optim 

diff --git a/README.md b/README.md
index 5e884870..4c0e745a 100644
--- a/README.md
+++ b/README.md
@@ -113,11 +113,10 @@ website](http://projects.tessella.com/cake), where you can also
 find a zip archive of the R scripts derived from `mkin`, published under the GPL
 license.
 
-Finally, I just (2013-11-11) noticed the github repositories
-[StudyKin](http://github.com/zhenglei-gao/StudyKin) and
-[KineticEval](http://github.com/zhenglei-gao/KineticEval), the latter of which appears to be 
-actively developed, so the different tools will hopefully be able to learn
-from each other in the future as well.
+Finally, there is 
+[KineticEval](http://github.com/zhenglei-gao/KineticEval), which contains 
+a further development of the scripts used for KinGUII, so the different tools
+will hopefully be able to learn from each other in the future as well.
 
 ## Contribute
 
diff --git a/TODO b/TODO
index a56ca55f..54d135a5 100644
--- a/TODO
+++ b/TODO
@@ -2,13 +2,13 @@ TODO for version 1.0
 - Transfer (some?) unit tests to examples to make them more easily accessible
   for the user - they will be tested during R CMD check anyway
 - Let mkin call mkin_wide_to_long automatically, if observed data are suitably defined
+- Convert package vignettes to knitr and Rmd
 - Think about what a user would expect from version 1.0
-- Check the chi2 error calculation in mkinerrmin.R. KinGUII does this without iteration
+- Move the GUI to a separate package as it has special dependencies and should have it own versioning
 
 Nice to have:
 - Improve choice of starting parameters, in order to avoid failure of eigenvalue based solutions
   due to singular matrix
-- Consider reverting to deSolve in case eigenvalue based solution fails due to singular matrix
 - Calculate confidence intervals for DT50 and DT90 values when only one parameter is involved
 - Calculate transformation only DT50 values (exclude pathways to sink) as additional information
 - Calculate DT50 values from smaller rate constant/eigenvalue of DFOP, HS and SFORB models
diff --git a/inst/GUI/mkinGUI.R b/inst/GUI/mkinGUI.R
index fb8f22ab..07f892e0 100644
--- a/inst/GUI/mkinGUI.R
+++ b/inst/GUI/mkinGUI.R
@@ -235,7 +235,15 @@ gbutton("Configure fit for selected model and dataset", cont = dsm,
           stmp <<- summary(ftmp)

           svalue(pf) <- paste0("Dataset ", ds.i, ", Model ", m[[m.i]]$name)

           show_plot("Initial", default = TRUE)

-          svalue(f.gg.opts.st) <<- "auto"

+          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

@@ -568,7 +576,6 @@ show_plot <- function(type, default = FALSE) {
     ftmp$ds <<- ds[[ds.i]]

   } 

 

-  #tmp <- get_tempfile(ext=".svg")

   svg(tf, width = 7, height = 5)

   plot(ftmp, main = ftmp$ds$title,

        xlab = ifelse(ftmp$ds$time_unit == "", "Time", 

@@ -608,18 +615,34 @@ run_fit <- function() {
   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),

-                   err = "err")

+                   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)

 }

@@ -643,12 +666,27 @@ tf <- get_tempfile(ext=".svg")
 svg(tf, width = 7, height = 5)

 plot(ftmp)

 dev.off()

-plot.gs <- gsvg(tf, container = f.gg.mid, width = 490, height = 350)

+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, 

@@ -717,6 +755,12 @@ update_plotting_and_fitting <- function() {
                        ", 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)

 }