Add possibility to control more mkinfit arguments from the GUI

1 files changed, 38 insertions, 7 deletions

diff --git a/inst/GUI/mkinGUI.R b/inst/GUI/mkinGUI.R
index d6fb82e3..07f892e0 100644
--- a/inst/GUI/mkinGUI.R
+++ b/inst/GUI/mkinGUI.R
@@ -236,7 +236,14 @@ gbutton("Configure fit for selected model and dataset", cont = dsm,
           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) <<- "manual"

+          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

@@ -614,14 +621,22 @@ run_fit <- function() {
   } 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)

+                   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)

@@ -651,16 +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")

-weights <- c("manual", "none", "std", "mean")

 f.gg.opts.st <- gcombobox(solution_types, selected = 1, 

                           label = "solution_type", width = 200, 

                           cont = f.gg.opts)

-f.gg.opts.weight <- gcombobox(weights, selected = 1, 

-                          label = "weight", 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, 

@@ -730,6 +756,11 @@ update_plotting_and_fitting <- function() {
   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)

 }