Pending check-in of stuff started at east one month ago:

- avoid returning factors in the data frame in mkin_wide_to_long
- stop returning useless results with eigenvalue based solutions when observed absolute values are all very small
- better test case for schaefer97 data making use of stepwise fitting - but the solution obtained in one step is 
better...

git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@83 edb9625f-4e0d-4859-8d74-9fd3b1da38cb

2 files changed, 5 insertions, 2 deletions

diff --git a/R/mkin_wide_to_long.R b/R/mkin_wide_to_long.R
index 826aee2d..f1814fcb 100644
--- a/R/mkin_wide_to_long.R
+++ b/R/mkin_wide_to_long.R
@@ -27,8 +27,8 @@ mkin_wide_to_long <- function(wide_data, time = "t")
   n <- length(colnames) - 1

   long_data <- data.frame(

     name = rep(vars, each = length(wide_data[[time]])),

-    time = rep(wide_data[[time]], n),

-    value = unlist(wide_data[vars]),

+    time = as.numeric(rep(wide_data[[time]], n)),

+    value = as.numeric(unlist(wide_data[vars])),

     row.names = NULL)

   return(long_data)

 }

diff --git a/R/mkinfit.R b/R/mkinfit.R
index cf018f0e..cdf54291 100644
--- a/R/mkinfit.R
+++ b/R/mkinfit.R
@@ -108,6 +108,9 @@ mkinfit <- function(mkinmod, observed,
     } else {

       if (is.matrix(mkinmod$coefmat)) {

 	solution_type = "eigen"

+        if (max(observed$value, na.rm = TRUE) < 0.1) {

+	  stop("The combination of small observed values (all < 0.1) and solution_type = eigen is error-prone")

+	}

       } else {

 	solution_type = "deSolve"

       }