Note: the module "R" cannot be unloaded because it was not loaded.

WARNING: ignoring environment value of R_HOME

R Under development (unstable) (2025-05-15 r88204) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> cargs <- commandArgs(trailingOnly=TRUE)
> if(length(cargs)==0){
+   ## before running interactively, make sure to start emacs/R with
+   ## environment defined in /scratch/...check_one.sh, particularly
+   ## R_LIBS_USER=/tmp/... otherwise we get error when installing
+   ## data.table.
+   base <- "/scratch/th798/data.table-revdeps/*"
+   cargs <- c(
+     Sys.glob(file.path(base,"deps.csv")),
+     "349",
+     Sys.glob(file.path(base, "data.table_release_*tar.gz")),
+     Sys.glob(file.path(base, "data.table_master_*tar.gz"))
+   )
+ }
> names(cargs) <- c("deps.csv", "task.str", "release", "master")
> dput(cargs)
c(deps.csv = "/scratch/th798/data.table-revdeps/2025-05-16/deps.csv", 
task.str = "847", release = "/scratch/th798/data.table-revdeps/2025-05-16/data.table_release_1.17.2.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-05-16/data.table_master_1.17.99.9c54bd073decac61dbd284c7a22d65d0f719aa19.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/17266796/R-devel/847"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/17266796/R-devel/847/R.cache"
> task.id <- as.integer(cargs[["task.str"]])
> deps.df <- read.csv(cargs[["deps.csv"]])
> (rev.dep <- deps.df$Package[task.id])
[1] "mlr3learners"
> job.dir <- file.path(dirname(cargs[["deps.csv"]]), "tasks", task.id)
> setwd(task.dir)
> .libPaths()
[1] "/tmp/th798/17266796/R-devel/847/library"
[2] "/projects/genomic-ml/R/R-devel/library" 
> options(repos=c(#this should be in ~/.Rprofile too.
+   CRAN="http://cloud.r-project.org"))
> print(Sys.time())
[1] "2025-05-16 01:22:20 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/17266796/R-devel/847/library'
(as 'lib' is unspecified)
also installing the dependencies 'mlr3', 'DiceKriging', 'rgenoud'

trying URL 'http://cloud.r-project.org/src/contrib/mlr3_0.23.0.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/DiceKriging_1.6.0.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/rgenoud_5.9-0.11.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/mlr3learners_0.10.0.tar.gz'
* installing *source* package 'mlr3' ...
** this is package 'mlr3' version '0.23.0'
** package 'mlr3' successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mlr3)
* installing *source* package 'DiceKriging' ...
** this is package 'DiceKriging' version '1.6.0'
** package 'DiceKriging' successfully unpacked and MD5 sums checked
** using staged installation
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c CovFuns.c -o CovFuns.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c Scaling.c -o Scaling.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o DiceKriging.so CovFuns.o Scaling.o init.o
installing to /tmp/th798/17266796/R-devel/847/library/00LOCK-DiceKriging/00new/DiceKriging/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Note: ... may be used in an incorrect context 
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (DiceKriging)
* installing *source* package 'rgenoud' ...
** this is package 'rgenoud' version '5.9-0.11'
** package 'rgenoud' successfully unpacked and MD5 sums checked
** using staged installation
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
using C++ compiler: 'g++ (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c change_order.cpp -o change_order.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c eval.cpp -o eval.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c evaluate.cpp -o evaluate.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c frange_ran.cpp -o frange_ran.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c genoud.cpp -o genoud.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c gradient.cpp -o gradient.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c math.cpp -o math.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c multiply.cpp -o multiply.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c numerics.cpp -o numerics.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c operators.cpp -o operators.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c print_format.cpp -o print_format.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c rgenoud.cpp -o rgenoud.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o rgenoud.so change_order.o eval.o evaluate.o frange_ran.o genoud.o gradient.o init.o math.o multiply.o numerics.o operators.o print_format.o rgenoud.o
installing to /tmp/th798/17266796/R-devel/847/library/00LOCK-rgenoud/00new/rgenoud/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (rgenoud)
* installing *source* package 'mlr3learners' ...
** this is package 'mlr3learners' version '0.10.0'
** package 'mlr3learners' successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mlr3learners)

The downloaded source packages are in
	'/tmp/th798/17266796/RtmpucWKyt/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 55.229   2.780  75.355 
> print(Sys.time())
[1] "2025-05-16 01:23:36 MST"
> downloaded_packages <- file.path(
+   tempdir(),
+   "downloaded_packages")
> dl.glob <- file.path(
+   downloaded_packages,
+   paste0(rev.dep,"_*.tar.gz"))
> rev.dep.dl.row <- cbind(rev.dep, Sys.glob(dl.glob))
> colnames(rev.dep.dl.row) <- c("pkg","path")
> rev.dep.release.tar.gz <- normalizePath(rev.dep.dl.row[,"path"], mustWork=TRUE)
> pkg.Rcheck <- paste0(rev.dep, ".Rcheck")
> 
> proj.dir <- "~/genomic-ml/data.table-revdeps"
> source(file.path(proj.dir, "myStatus.R"))
> Rvers <- gsub("[()]", "", gsub(" ", "_", R.version[["version.string"]]))
> dir.create(Rvers, showWarnings=FALSE)
> Rcheck.list <- list()
> for(dt.version.short in c("release", "master")){
+   dt.tar.gz <- cargs[[dt.version.short]]
+   dt.version <- gsub(".tar.gz|/.*?_", "", dt.tar.gz)
+   print(Sys.time())
+   install.packages(dt.tar.gz, repos=NULL)
+   print(Sys.time())
+   check.cmd <- get_check_cmd(rev.dep.release.tar.gz)
+   system(check.cmd)
+   print(Sys.time())
+   dest.Rcheck <- file.path(
+     Rvers,
+     paste0(dt.version, ".Rcheck"))
+   unlink(dest.Rcheck, recursive=TRUE)
+   file.rename(pkg.Rcheck, dest.Rcheck)
+   Rcheck.list[[dt.version]] <- file.path(dest.Rcheck, "00check.log")
+ }
[1] "2025-05-16 01:23:36 MST"
Installing package into '/tmp/th798/17266796/R-devel/847/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** this is package 'data.table' version '1.17.2'
** package 'data.table' successfully unpacked and MD5 sums checked
** using staged installation
zlib 1.2.13 is available ok
* checking if R installation supports OpenMP without any extra hints... yes
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c assign.c -o assign.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c between.c -o between.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c bmerge.c -o bmerge.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c chmatch.c -o chmatch.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c cj.c -o cj.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c coalesce.c -o coalesce.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c dogroups.c -o dogroups.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fastmean.c -o fastmean.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fcast.c -o fcast.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fifelse.c -o fifelse.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fmelt.c -o fmelt.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c forder.c -o forder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frank.c -o frank.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fread.c -o fread.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c freadR.c -o freadR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c froll.c -o froll.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frollR.c -o frollR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frolladaptive.c -o frolladaptive.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fsort.c -o fsort.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fwrite.c -o fwrite.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fwriteR.c -o fwriteR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c gsumm.c -o gsumm.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c idatetime.c -o idatetime.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c ijoin.c -o ijoin.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c inrange.c -o inrange.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nafill.c -o nafill.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c negate.c -o negate.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nqrecreateindices.c -o nqrecreateindices.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c openmp-utils.c -o openmp-utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c programming.c -o programming.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c quickselect.c -o quickselect.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c rbindlist.c -o rbindlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c reorder.c -o reorder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c shift.c -o shift.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c snprintf.c -o snprintf.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c subset.c -o subset.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c transpose.c -o transpose.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c types.c -o types.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c uniqlist.c -o uniqlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c utils.c -o utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c vecseq.c -o vecseq.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c wrappers.c -o wrappers.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o data.table.so assign.o between.o bmerge.o chmatch.o cj.o coalesce.o dogroups.o fastmean.o fcast.o fifelse.o fmelt.o forder.o frank.o fread.o freadR.o froll.o frollR.o frolladaptive.o fsort.o fwrite.o fwriteR.o gsumm.o idatetime.o ijoin.o init.o inrange.o nafill.o negate.o nqrecreateindices.o openmp-utils.o programming.o quickselect.o rbindlist.o reorder.o shift.o snprintf.o subset.o transpose.o types.o uniqlist.o utils.o vecseq.o wrappers.o -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
PKG_CFLAGS = -fopenmp -I/home/th798/.conda/envs/emacs1/include
PKG_LIBS = -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
if [ "data.table.so" != "data_table.so" ]; then mv data.table.so data_table.so; fi
if [ "" != "Windows_NT" ] && [ `uname -s` = 'Darwin' ]; then install_name_tool -id data_table.so data_table.so; fi
installing to /tmp/th798/17266796/R-devel/847/library/00LOCK-data.table/00new/data.table/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (data.table)
[1] "2025-05-16 01:24:01 MST"
* using log directory '/tmp/th798/17266796/R-devel/847/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-05-15 r88204)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Spack GCC) 12.2.0
    GNU Fortran (Spack GCC) 12.2.0
* running under: Red Hat Enterprise Linux 8.10 (Ootpa)
* using session charset: ASCII
* checking for file 'mlr3learners/DESCRIPTION' ... OK
* this is package 'mlr3learners' version '0.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package 'mlr3learners' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                                 user system elapsed
mlr_learners_classif.cv_glmnet 28.153  0.093  28.845
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'testthat.R'
 ERROR
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("mlr3learners")
  +   test_check("mlr3learners")
  + }
  Loading required package: mlr3
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.880405 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.880405 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.239713 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.239713 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  6 (5 variable)
  initial  value 9.464337 
  iter  10 value 7.466459
  final  value 7.466412 
  converged
  # weights:  6 (5 variable)
  initial  value 9.464337 
  iter  10 value 7.466459
  final  value 7.466412 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 18.942852
  iter  10 value 18.942852
  iter  10 value 18.942852
  final  value 18.942852 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.504055 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.504055 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.516431 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.516431 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  18 (10 variable)
  initial  value 19.511501 
  iter  10 value 18.280758
  final  value 18.273177 
  converged
  # weights:  18 (10 variable)
  initial  value 19.511501 
  iter  10 value 18.280758
  final  value 18.273177 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.733537
  final  value 30.730891 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -429.6893 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       429.69  |proj g|=        8.534
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       71.777  |proj g|=        1.3998
  ys=-3.115e+01  -gs= 1.905e+01, BFGS update SKIPPED
  At iterate     3  f =         69.5  |proj g|=        0.8825
  At iterate     4  f =       69.483  |proj g|=        0.0264
  At iterate     5  f =       69.483  |proj g|=     0.0020212
  At iterate     6  f =       69.483  |proj g|=    4.0354e-06
  
  iterations 6
  function evaluations 23
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.03545e-06
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -429.6893 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       429.69  |proj g|=        8.534
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       71.777  |proj g|=        1.3998
  ys=-3.115e+01  -gs= 1.905e+01, BFGS update SKIPPED
  At iterate     3  f =         69.5  |proj g|=        0.8825
  At iterate     4  f =       69.483  |proj g|=        0.0264
  At iterate     5  f =       69.483  |proj g|=     0.0020212
  At iterate     6  f =       69.483  |proj g|=    4.0354e-06
  
  iterations 6
  function evaluations 23
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.03545e-06
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -288.5696 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       288.57  |proj g|=       8.6429
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       70.192  |proj g|=        1.1125
  ys=-1.851e+01  -gs= 1.972e+01, BFGS update SKIPPED
  At iterate     3  f =       69.684  |proj g|=        0.9773
  At iterate     4  f =       69.492  |proj g|=       0.68197
  At iterate     5  f =       69.484  |proj g|=       0.21932
  At iterate     6  f =       69.483  |proj g|=      0.011811
  At iterate     7  f =       69.483  |proj g|=    0.00019171
  At iterate     8  f =       69.483  |proj g|=    1.7104e-07
  
  iterations 8
  function evaluations 22
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.71042e-07
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -288.5696 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       288.57  |proj g|=       8.6429
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       70.192  |proj g|=        1.1125
  ys=-1.851e+01  -gs= 1.972e+01, BFGS update SKIPPED
  At iterate     3  f =       69.684  |proj g|=        0.9773
  At iterate     4  f =       69.492  |proj g|=       0.68197
  At iterate     5  f =       69.484  |proj g|=       0.21932
  At iterate     6  f =       69.483  |proj g|=      0.011811
  At iterate     7  f =       69.483  |proj g|=    0.00019171
  At iterate     8  f =       69.483  |proj g|=    1.7104e-07
  
  iterations 8
  function evaluations 22
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.71042e-07
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -4791.757 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       4791.8  |proj g|=       8.3946
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       70.915  |proj g|=        1.2539
  ys=-2.679e+01  -gs= 1.939e+01, BFGS update SKIPPED
  At iterate     3  f =       70.418  |proj g|=        1.1601
  At iterate     4  f =       69.519  |proj g|=       0.89962
  At iterate     5  f =       69.484  |proj g|=       0.13142
  At iterate     6  f =       69.483  |proj g|=      0.015236
  At iterate     7  f =       69.483  |proj g|=    0.00015276
  At iterate     8  f =       69.483  |proj g|=    1.7536e-07
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.75358e-07
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.623887e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.86271 
    - variance bounds :  0.09598233 9.623887 
    - best initial criterion value(s) :  -21938.36 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        21938  |proj g|=       8.2049
  At iterate     1  f =          105  |proj g|=        2.3431
  At iterate     2  f =       69.485  |proj g|=       0.27409
  At iterate     3  f =       69.483  |proj g|=      0.014664
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       69.483  |proj g|=    0.00014121
  At iterate     5  f =       69.483  |proj g|=    1.5646e-07
  
  iterations 5
  function evaluations 20
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.56457e-07
  final function value 69.4834
  
  F = 69.4834
  final  value 69.483438 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -720.0667 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       720.07  |proj g|=       10.181
  At iterate     1  f =       324.02  |proj g|=       0.35502
  At iterate     2  f =       319.15  |proj g|=       0.21712
  At iterate     3  f =       318.23  |proj g|=      0.019869
  At iterate     4  f =       318.22  |proj g|=      0.010191
  At iterate     5  f =       318.22  |proj g|=    0.00028014
  At iterate     6  f =       318.22  |proj g|=    3.8193e-06
  At iterate     7  f =       318.22  |proj g|=    1.4561e-09
  
  iterations 7
  function evaluations 15
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.45614e-09
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -7294.309 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       7294.3  |proj g|=       110.29
  At iterate     1  f =       359.98  |proj g|=       0.22962
  At iterate     2  f =       318.31  |proj g|=      0.082145
  At iterate     3  f =       318.22  |proj g|=     0.0080639
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=     0.0063548
  At iterate     5  f =       318.22  |proj g|=    7.1459e-05
  At iterate     6  f =       318.22  |proj g|=    6.2439e-07
  
  iterations 6
  function evaluations 22
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 6.24392e-07
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -718.3307 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       718.33  |proj g|=       15.466
  At iterate     1  f =       321.04  |proj g|=       0.30837
  At iterate     2  f =       318.64  |proj g|=       0.15992
  At iterate     3  f =       318.22  |proj g|=      0.013997
  At iterate     4  f =       318.22  |proj g|=     0.0043856
  At iterate     5  f =       318.22  |proj g|=    8.4899e-05
  At iterate     6  f =       318.22  |proj g|=     5.028e-07
  
  iterations 6
  function evaluations 12
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 5.02798e-07
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -2744.085 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       2744.1  |proj g|=       86.353
  At iterate     1  f =       344.49  |proj g|=       0.30339
  At iterate     2  f =       318.42  |proj g|=       0.11556
  At iterate     3  f =       318.22  |proj g|=      0.012065
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=      0.009533
  At iterate     5  f =       318.22  |proj g|=    0.00016241
  At iterate     6  f =       318.22  |proj g|=    2.1402e-06
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.14023e-06
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -69.81058 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.811  |proj g|=       1.8498
  At iterate     1  f =       67.974  |proj g|=        1.8332
  At iterate     2  f =        67.64  |proj g|=        2.9914
  At iterate     3  f =       67.583  |proj g|=        3.5009
  At iterate     4  f =       67.492  |proj g|=        3.7535
  At iterate     5  f =       67.003  |proj g|=        4.3078
  At iterate     6  f =         66.2  |proj g|=        3.9867
  At iterate     7  f =       64.544  |proj g|=        1.6971
  At iterate     8  f =       62.756  |proj g|=        1.0856
  At iterate     9  f =       62.349  |proj g|=        1.0148
  At iterate    10  f =       62.198  |proj g|=        1.8275
  At iterate    11  f =       62.006  |proj g|=        1.8278
  At iterate    12  f =       61.981  |proj g|=       0.94542
  At iterate    13  f =       61.813  |proj g|=       0.90014
  At iterate    14  f =       61.415  |proj g|=       0.75246
  At iterate    15  f =       61.353  |proj g|=       0.78278
  At iterate    16  f =       61.325  |proj g|=        1.8324
  At iterate    17  f =       61.315  |proj g|=        1.8323
  At iterate    18  f =       61.309  |proj g|=       0.10786
  At iterate    19  f =       61.309  |proj g|=      0.020988
  At iterate    20  f =       61.309  |proj g|=     0.0096561
  At iterate    21  f =       61.309  |proj g|=     0.0042517
  
  iterations 21
  function evaluations 31
  segments explored during Cauchy searches 24
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.00425172
  final function value 61.3093
  
  F = 61.3093
  final  value 61.309269 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -69.81058 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.811  |proj g|=       1.8498
  At iterate     1  f =       67.974  |proj g|=        1.8332
  At iterate     2  f =        67.64  |proj g|=        2.9914
  At iterate     3  f =       67.583  |proj g|=        3.5009
  At iterate     4  f =       67.492  |proj g|=        3.7535
  At iterate     5  f =       67.003  |proj g|=        4.3078
  At iterate     6  f =         66.2  |proj g|=        3.9867
  At iterate     7  f =       64.544  |proj g|=        1.6971
  At iterate     8  f =       62.756  |proj g|=        1.0856
  At iterate     9  f =       62.349  |proj g|=        1.0148
  At iterate    10  f =       62.198  |proj g|=        1.8275
  At iterate    11  f =       62.006  |proj g|=        1.8278
  At iterate    12  f =       61.981  |proj g|=       0.94542
  At iterate    13  f =       61.813  |proj g|=       0.90014
  At iterate    14  f =       61.415  |proj g|=       0.75246
  At iterate    15  f =       61.353  |proj g|=       0.78278
  At iterate    16  f =       61.325  |proj g|=        1.8324
  At iterate    17  f =       61.315  |proj g|=        1.8323
  At iterate    18  f =       61.309  |proj g|=       0.10786
  At iterate    19  f =       61.309  |proj g|=      0.020988
  At iterate    20  f =       61.309  |proj g|=     0.0096561
  At iterate    21  f =       61.309  |proj g|=     0.0042517
  
  iterations 21
  function evaluations 31
  segments explored during Cauchy searches 24
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.00425172
  final function value 61.3093
  
  F = 61.3093
  final  value 61.309269 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -67.26564 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       67.266  |proj g|=        1.854
  At iterate     1  f =        63.85  |proj g|=        1.8298
  At iterate     2  f =       63.663  |proj g|=        1.3228
  At iterate     3  f =       63.654  |proj g|=        1.3396
  At iterate     4  f =        63.63  |proj g|=        1.3592
  At iterate     5  f =       63.561  |proj g|=        1.3732
  At iterate     6  f =       63.393  |proj g|=        1.3353
  At iterate     7  f =       62.991  |proj g|=        1.1003
  At iterate     8  f =       62.314  |proj g|=        1.2176
  At iterate     9  f =       61.607  |proj g|=        3.1901
  At iterate    10  f =       61.373  |proj g|=        0.8194
  At iterate    11  f =       61.373  |proj g|=       0.75093
  At iterate    12  f =       61.364  |proj g|=       0.80471
  At iterate    13  f =       61.328  |proj g|=       0.50692
  At iterate    14  f =       61.316  |proj g|=       0.22312
  At iterate    15  f =       61.313  |proj g|=        1.0873
  At iterate    16  f =       61.312  |proj g|=       0.15577
  At iterate    17  f =       61.312  |proj g|=       0.18388
  At iterate    18  f =       61.312  |proj g|=       0.20785
  At iterate    19  f =       61.311  |proj g|=       0.11205
  At iterate    20  f =        61.31  |proj g|=       0.10757
  At iterate    21  f =       61.309  |proj g|=      0.046736
  At iterate    22  f =       61.309  |proj g|=      0.030551
  At iterate    23  f =       61.309  |proj g|=      0.011367
  At iterate    24  f =       61.309  |proj g|=      0.021079
  At iterate    25  f =       61.309  |proj g|=      0.030563
  At iterate    26  f =       61.309  |proj g|=      0.094226
  At iterate    27  f =       61.309  |proj g|=      0.082851
  At iterate    28  f =       61.309  |proj g|=       0.18583
  At iterate    29  f =       61.309  |proj g|=       0.12565
  At iterate    30  f =       61.309  |proj g|=      0.026596
  At iterate    31  f =       61.309  |proj g|=    0.00067763
  At iterate    32  f =       61.309  |proj g|=    0.00039448
  
  iterations 32
  function evaluations 40
  segments explored during Cauchy searches 35
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.000394482
  final function value 61.3093
  
  F = 61.3093
  final  value 61.309269 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -67.26564 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       67.266  |proj g|=        1.854
  At iterate     1  f =        63.85  |proj g|=        1.8298
  At iterate     2  f =       63.663  |proj g|=        1.3228
  At iterate     3  f =       63.654  |proj g|=        1.3396
  At iterate     4  f =        63.63  |proj g|=        1.3592
  At iterate     5  f =       63.561  |proj g|=        1.3732
  At iterate     6  f =       63.393  |proj g|=        1.3353
  At iterate     7  f =       62.991  |proj g|=        1.1003
  At iterate     8  f =       62.314  |proj g|=        1.2176
  At iterate     9  f =       61.607  |proj g|=        3.1901
  At iterate    10  f =       61.373  |proj g|=        0.8194
  At iterate    11  f =       61.373  |proj g|=       0.75093
  At iterate    12  f =       61.364  |proj g|=       0.80471
  At iterate    13  f =       61.328  |proj g|=       0.50692
  At iterate    14  f =       61.316  |proj g|=       0.22312
  At iterate    15  f =       61.313  |proj g|=        1.0873
  At iterate    16  f =       61.312  |proj g|=       0.15577
  At iterate    17  f =       61.312  |proj g|=       0.18388
  At iterate    18  f =       61.312  |proj g|=       0.20785
  At iterate    19  f =       61.311  |proj g|=       0.11205
  At iterate    20  f =        61.31  |proj g|=       0.10757
  At iterate    21  f =       61.309  |proj g|=      0.046736
  At iterate    22  f =       61.309  |proj g|=      0.030551
  At iterate    23  f =       61.309  |proj g|=      0.011367
  At iterate    24  f =       61.309  |proj g|=      0.021079
  At iterate    25  f =       61.309  |proj g|=      0.030563
  At iterate    26  f =       61.309  |proj g|=      0.094226
  At iterate    27  f =       61.309  |proj g|=      0.082851
  At iterate    28  f =       61.309  |proj g|=       0.18583
  At iterate    29  f =       61.309  |proj g|=       0.12565
  At iterate    30  f =       61.309  |proj g|=      0.026596
  At iterate    31  f =       61.309  |proj g|=    0.00067763
  At iterate    32  f =       61.309  |proj g|=    0.00039448
  
  iterations 32
  function evaluations 40
  segments explored during Cauchy searches 35
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.000394482
  final function value 61.3093
  
  F = 61.3093
  final  value 61.309269 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -74.01697 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       74.017  |proj g|=        7.915
  At iterate     1  f =       70.298  |proj g|=        1.2504
  At iterate     2  f =        66.57  |proj g|=       0.78941
  At iterate     3  f =       66.539  |proj g|=      0.046995
  At iterate     4  f =       66.539  |proj g|=     7.007e-09
  At iterate     5  f =       66.539  |proj g|=    2.1995e-11
  
  iterations 5
  function evaluations 9
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 2.19949e-11
  final function value 66.5392
  
  F = 66.5392
  final  value 66.539158 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.554668e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.865628 
    - variance bounds :  0.08150369 8.554668 
    - best initial criterion value(s) :  -79.16497 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       79.165  |proj g|=       8.0227
  At iterate     1  f =       74.187  |proj g|=        7.9048
  At iterate     2  f =       70.877  |proj g|=        7.8443
  At iterate     3  f =       67.812  |proj g|=        7.6884
  At iterate     4  f =       65.647  |proj g|=        4.3175
  At iterate     5  f =       64.442  |proj g|=        1.6664
  At iterate     6  f =       63.704  |proj g|=        1.8244
  At iterate     7  f =       62.989  |proj g|=        1.8242
  At iterate     8  f =       62.943  |proj g|=        1.8262
  At iterate     9  f =       62.434  |proj g|=        1.8279
  At iterate    10  f =       61.514  |proj g|=       0.82711
  At iterate    11  f =       61.379  |proj g|=       0.72649
  At iterate    12  f =       61.363  |proj g|=        1.8315
  At iterate    13  f =       61.338  |proj g|=        1.8321
  At iterate    14  f =        61.31  |proj g|=         1.832
  At iterate    15  f =       61.309  |proj g|=       0.25743
  At iterate    16  f =       61.309  |proj g|=      0.028638
  At iterate    17  f =       61.309  |proj g|=      0.015752
  At iterate    18  f =       61.309  |proj g|=    0.00073988
  
  iterations 18
  function evaluations 22
  segments explored during Cauchy searches 21
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.000739876
  final function value 61.3093
  
  F = 61.3093
  final  value 61.309269 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -6418.497 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       6418.5  |proj g|=       162.93
  At iterate     1  f =        365.6  |proj g|=       0.20635
  At iterate     2  f =       318.23  |proj g|=        0.0174
  At iterate     3  f =       318.22  |proj g|=    8.9228e-05
  At iterate     4  f =       318.22  |proj g|=    2.1769e-06
  
  iterations 4
  function evaluations 15
  segments explored during Cauchy searches 6
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.17691e-06
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -904.3254 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       904.33  |proj g|=       10.103
  At iterate     1  f =       333.02  |proj g|=       0.35669
  At iterate     2  f =       318.74  |proj g|=       0.17449
  At iterate     3  f =       318.22  |proj g|=      0.015634
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=      0.012382
  At iterate     5  f =       318.22  |proj g|=     0.0002765
  At iterate     6  f =       318.22  |proj g|=    4.7553e-06
  At iterate     7  f =       318.22  |proj g|=    1.7877e-09
  
  iterations 7
  function evaluations 18
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.78768e-09
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/17266796/R-devel/847/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-16 01:33:02 MST"
[1] "2025-05-16 01:33:02 MST"
Installing package into '/tmp/th798/17266796/R-devel/847/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** this is package 'data.table' version '1.17.99'
** using staged installation
zlib 1.2.13 is available ok
* checking if R installation supports OpenMP without any extra hints... yes
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c assign.c -o assign.o
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/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c quickselect.c -o quickselect.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c rbindlist.c -o rbindlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c reorder.c -o reorder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c shift.c -o shift.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c snprintf.c -o snprintf.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c subset.c -o subset.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c transpose.c -o transpose.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c types.c -o types.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c uniqlist.c -o uniqlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c utils.c -o utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c vecseq.c -o vecseq.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c wrappers.c -o wrappers.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o data.table.so assign.o between.o bmerge.o chmatch.o cj.o coalesce.o dogroups.o fastmean.o fcast.o fifelse.o fmelt.o forder.o frank.o fread.o freadR.o froll.o frollR.o frolladaptive.o fsort.o fwrite.o fwriteR.o gsumm.o idatetime.o ijoin.o init.o inrange.o nafill.o negate.o nqrecreateindices.o openmp-utils.o programming.o quickselect.o rbindlist.o reorder.o shift.o snprintf.o subset.o transpose.o types.o uniqlist.o utils.o vecseq.o wrappers.o -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
PKG_CFLAGS = -fopenmp -I/home/th798/.conda/envs/emacs1/include
PKG_LIBS = -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
if [ "data.table.so" != "data_table.so" ]; then mv data.table.so data_table.so; fi
if [ "" != "Windows_NT" ] && [ `uname -s` = 'Darwin' ]; then install_name_tool -id data_table.so data_table.so; fi
installing to /tmp/th798/17266796/R-devel/847/library/00LOCK-data.table/00new/data.table/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (data.table)
[1] "2025-05-16 01:33:29 MST"
* using log directory '/tmp/th798/17266796/R-devel/847/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-05-15 r88204)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Spack GCC) 12.2.0
    GNU Fortran (Spack GCC) 12.2.0
* running under: Red Hat Enterprise Linux 8.10 (Ootpa)
* using session charset: ASCII
* checking for file 'mlr3learners/DESCRIPTION' ... OK
* this is package 'mlr3learners' version '0.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package 'mlr3learners' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                                 user system elapsed
mlr_learners_classif.cv_glmnet 27.726  0.099  28.275
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'testthat.R'
 ERROR
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("mlr3learners")
  +   test_check("mlr3learners")
  + }
  Loading required package: mlr3
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.190350 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.190350 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.794415 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.794415 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.553673 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.553673 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.190350 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.190350 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  6 (5 variable)
  initial  value 10.311061 
  iter  10 value 9.192773
  final  value 9.192772 
  converged
  # weights:  6 (5 variable)
  initial  value 10.311061 
  iter  10 value 9.192773
  final  value 9.192772 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.335028 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 28.852852
  iter  10 value 28.852852
  final  value 28.852852 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 28.852852
  iter  10 value 28.852852
  final  value 28.852852 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.487046 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.487046 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 27.632069
  iter  10 value 27.632069
  final  value 27.632069 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 27.632069
  iter  10 value 27.632069
  final  value 27.632069 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  18 (10 variable)
  initial  value 16.240751 
  iter  10 value 10.352086
  iter  20 value 10.178804
  iter  30 value 10.176830
  final  value 10.176813 
  converged
  # weights:  18 (10 variable)
  initial  value 16.240751 
  iter  10 value 10.352086
  iter  20 value 10.178804
  iter  30 value 10.176830
  final  value 10.176813 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 20.474106
  iter  20 value 20.275043
  final  value 20.275022 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -70821.6 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        70822  |proj g|=       11.434
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       76.237  |proj g|=        1.2966
  ys=-6.352e+00  -gs= 2.000e+01, BFGS update SKIPPED
  At iterate     3  f =       76.162  |proj g|=        1.2626
  At iterate     4  f =       76.017  |proj g|=        1.0398
  At iterate     5  f =        75.99  |proj g|=         0.244
  At iterate     6  f =       75.988  |proj g|=      0.022685
  At iterate     7  f =       75.988  |proj g|=    0.00056005
  At iterate     8  f =       75.988  |proj g|=    1.2468e-06
  
  iterations 8
  function evaluations 30
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.24681e-06
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -70821.6 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        70822  |proj g|=       11.434
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       76.237  |proj g|=        1.2966
  ys=-6.352e+00  -gs= 2.000e+01, BFGS update SKIPPED
  At iterate     3  f =       76.162  |proj g|=        1.2626
  At iterate     4  f =       76.017  |proj g|=        1.0398
  At iterate     5  f =        75.99  |proj g|=         0.244
  At iterate     6  f =       75.988  |proj g|=      0.022685
  At iterate     7  f =       75.988  |proj g|=    0.00056005
  At iterate     8  f =       75.988  |proj g|=    1.2468e-06
  
  iterations 8
  function evaluations 30
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.24681e-06
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -66114.67 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        66115  |proj g|=       11.334
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       77.319  |proj g|=        1.6104
  ys=-2.599e+01  -gs= 1.943e+01, BFGS update SKIPPED
  At iterate     3  f =       76.784  |proj g|=        1.4751
  At iterate     4  f =       76.013  |proj g|=       0.86704
  At iterate     5  f =       76.003  |proj g|=       0.72941
  At iterate     6  f =       75.988  |proj g|=      0.063259
  At iterate     7  f =       75.988  |proj g|=     0.0041798
  At iterate     8  f =       75.988  |proj g|=    2.6094e-05
  At iterate     9  f =       75.988  |proj g|=     1.068e-08
  
  iterations 9
  function evaluations 30
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.06801e-08
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -66114.67 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        66115  |proj g|=       11.334
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       77.319  |proj g|=        1.6104
  ys=-2.599e+01  -gs= 1.943e+01, BFGS update SKIPPED
  At iterate     3  f =       76.784  |proj g|=        1.4751
  At iterate     4  f =       76.013  |proj g|=       0.86704
  At iterate     5  f =       76.003  |proj g|=       0.72941
  At iterate     6  f =       75.988  |proj g|=      0.063259
  At iterate     7  f =       75.988  |proj g|=     0.0041798
  At iterate     8  f =       75.988  |proj g|=    2.6094e-05
  At iterate     9  f =       75.988  |proj g|=     1.068e-08
  
  iterations 9
  function evaluations 30
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.06801e-08
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -38764.39 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        38764  |proj g|=       11.407
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       77.282  |proj g|=        1.6017
  ys=-2.568e+01  -gs= 1.945e+01, BFGS update SKIPPED
  At iterate     3  f =       76.744  |proj g|=        1.4638
  At iterate     4  f =        76.01  |proj g|=       0.81161
  At iterate     5  f =           76  |proj g|=       0.64871
  At iterate     6  f =       75.988  |proj g|=      0.052789
  At iterate     7  f =       75.988  |proj g|=     0.0031263
  At iterate     8  f =       75.988  |proj g|=    1.6264e-05
  At iterate     9  f =       75.988  |proj g|=    4.9784e-09
  
  iterations 9
  function evaluations 32
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.97838e-09
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.248383e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869687 
    - variance bounds :  0.1170728 12.48383 
    - best initial criterion value(s) :  -1573.437 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1573.4  |proj g|=        11.48
  At iterate     1  f =       111.51  |proj g|=        1.8063
  At iterate     2  f =       76.924  |proj g|=         7.944
  At iterate     3  f =       76.172  |proj g|=        1.2677
  At iterate     4  f =       76.025  |proj g|=        1.0274
  At iterate     5  f =       75.991  |proj g|=       0.34437
  At iterate     6  f =       75.988  |proj g|=      0.037939
  At iterate     7  f =       75.988  |proj g|=     0.0012328
  At iterate     8  f =       75.988  |proj g|=    4.5999e-06
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.59987e-06
  final function value 75.9881
  
  F = 75.9881
  final  value 75.988097 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -310.0152 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       310.02  |proj g|=       44.179
  At iterate     1  f =       308.54  |proj g|=         44.17
  At iterate     2  f =       305.51  |proj g|=        1.4107
  At iterate     3  f =       305.29  |proj g|=         1.404
  At iterate     4  f =       303.51  |proj g|=        44.142
  At iterate     5  f =       300.18  |proj g|=        44.152
  At iterate     6  f =       295.82  |proj g|=        44.151
  At iterate     7  f =       293.28  |proj g|=        44.132
  At iterate     8  f =       287.64  |proj g|=        44.068
  At iterate     9  f =       283.37  |proj g|=         43.99
  At iterate    10  f =        281.1  |proj g|=        43.939
  At iterate    11  f =       275.76  |proj g|=        43.794
  At iterate    12  f =       260.01  |proj g|=        31.233
  At iterate    13  f =       256.47  |proj g|=         1.363
  At iterate    14  f =       248.67  |proj g|=        1.6946
  At iterate    15  f =       248.59  |proj g|=        0.2335
  At iterate    16  f =       248.59  |proj g|=        1.7007
  At iterate    17  f =       248.59  |proj g|=       0.23631
  At iterate    18  f =       248.59  |proj g|=        0.2361
  At iterate    19  f =       248.58  |proj g|=       0.23446
  At iterate    20  f =       248.57  |proj g|=       0.23242
  At iterate    21  f =       248.53  |proj g|=       0.35283
  At iterate    22  f =       248.45  |proj g|=       0.63456
  At iterate    23  f =       248.22  |proj g|=        1.5433
  At iterate    24  f =       247.69  |proj g|=        3.4246
  At iterate    25  f =       246.66  |proj g|=        5.8087
  At iterate    26  f =       245.94  |proj g|=         12.83
  At iterate    27  f =       244.64  |proj g|=        9.9535
  At iterate    28  f =       243.54  |proj g|=       0.76537
  At iterate    29  f =       243.27  |proj g|=       0.49396
  At iterate    30  f =       243.26  |proj g|=      0.055811
  At iterate    31  f =       243.26  |proj g|=     0.0091265
  At iterate    32  f =       243.26  |proj g|=     0.0051811
  At iterate    33  f =       243.26  |proj g|=    7.5203e-05
  
  iterations 33
  function evaluations 47
  segments explored during Cauchy searches 35
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 7.52026e-05
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -295.1124 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       295.11  |proj g|=       2.7186
  At iterate     1  f =       254.19  |proj g|=        1.7351
  At iterate     2  f =       252.87  |proj g|=        1.7228
  At iterate     3  f =       251.42  |proj g|=        1.7907
  At iterate     4  f =       251.36  |proj g|=        1.0343
  At iterate     5  f =       251.35  |proj g|=       0.21456
  At iterate     6  f =       251.35  |proj g|=       0.53878
  At iterate     7  f =       251.35  |proj g|=        1.3929
  At iterate     8  f =       251.35  |proj g|=        1.6915
  At iterate     9  f =       251.34  |proj g|=        1.6921
  At iterate    10  f =       251.32  |proj g|=        1.6932
  At iterate    11  f =       251.28  |proj g|=        2.2769
  At iterate    12  f =       251.15  |proj g|=        4.0363
  At iterate    13  f =       250.84  |proj g|=        7.1562
  At iterate    14  f =       250.18  |proj g|=        12.235
  At iterate    15  f =       248.83  |proj g|=        19.592
  At iterate    16  f =       247.81  |proj g|=        23.807
  At iterate    17  f =       247.48  |proj g|=         19.93
  At iterate    18  f =       246.47  |proj g|=        18.142
  At iterate    19  f =       243.68  |proj g|=         1.739
  At iterate    20  f =       243.41  |proj g|=       0.52456
  At iterate    21  f =       243.28  |proj g|=       0.17101
  At iterate    22  f =       243.27  |proj g|=      0.066458
  At iterate    23  f =       243.27  |proj g|=       0.89423
  At iterate    24  f =       243.26  |proj g|=      0.069314
  At iterate    25  f =       243.26  |proj g|=    0.00057487
  At iterate    26  f =       243.26  |proj g|=    0.00019312
  
  iterations 26
  function evaluations 32
  segments explored during Cauchy searches 28
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000193118
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -2710.663 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       2710.7  |proj g|=       53.618
  At iterate     1  f =       339.66  |proj g|=        0.3275
  At iterate     2  f =       319.48  |proj g|=       0.24199
  At iterate     3  f =       318.54  |proj g|=       0.19102
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.38  |proj g|=        0.1312
  At iterate     5  f =       318.23  |proj g|=      0.022048
  At iterate     6  f =       318.22  |proj g|=       0.00313
  At iterate     7  f =       318.22  |proj g|=    9.0029e-05
  At iterate     8  f =       318.22  |proj g|=    3.8122e-07
  
  iterations 8
  function evaluations 18
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.81225e-07
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -1729.7 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1729.7  |proj g|=       24.122
  At iterate     1  f =        335.1  |proj g|=       0.34855
  At iterate     2  f =       318.83  |proj g|=       0.27987
  At iterate     3  f =       318.24  |proj g|=      0.040347
  At iterate     4  f =       318.22  |proj g|=      0.011126
  At iterate     5  f =       318.22  |proj g|=    0.00066944
  At iterate     6  f =       318.22  |proj g|=    1.0315e-05
  At iterate     7  f =       318.22  |proj g|=    9.3829e-09
  
  iterations 7
  function evaluations 22
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 9.38291e-09
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -17876.79 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        17877  |proj g|=       7.2175
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       64.423  |proj g|=       0.25184
  At iterate     3  f =       64.422  |proj g|=      0.081437
  At iterate     4  f =       64.422  |proj g|=     0.0012475
  At iterate     5  f =       64.422  |proj g|=    6.3007e-06
  
  iterations 5
  function evaluations 21
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.30067e-06
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -17876.79 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        17877  |proj g|=       7.2175
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       64.423  |proj g|=       0.25184
  At iterate     3  f =       64.422  |proj g|=      0.081437
  At iterate     4  f =       64.422  |proj g|=     0.0012475
  At iterate     5  f =       64.422  |proj g|=    6.3007e-06
  
  iterations 5
  function evaluations 21
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.30067e-06
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -1690.294 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1690.3  |proj g|=       6.9512
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       64.485  |proj g|=       0.74907
  At iterate     3  f =       64.423  |proj g|=       0.21233
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       64.422  |proj g|=     0.0091594
  At iterate     5  f =       64.422  |proj g|=    0.00012193
  At iterate     6  f =       64.422  |proj g|=    6.8869e-08
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.88688e-08
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -1690.294 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1690.3  |proj g|=       6.9512
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       64.485  |proj g|=       0.74907
  At iterate     3  f =       64.423  |proj g|=       0.21233
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       64.422  |proj g|=     0.0091594
  At iterate     5  f =       64.422  |proj g|=    0.00012193
  At iterate     6  f =       64.422  |proj g|=    6.8869e-08
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.88688e-08
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -5026636 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   5.0266e+06  |proj g|=       6.7527
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       66.172  |proj g|=        1.0696
  ys=-2.884e+01  -gs= 1.926e+01, BFGS update SKIPPED
  At iterate     3  f =       65.406  |proj g|=       0.95547
  At iterate     4  f =       64.452  |proj g|=       0.73058
  At iterate     5  f =       64.422  |proj g|=       0.13622
  At iterate     6  f =       64.422  |proj g|=      0.014225
  At iterate     7  f =       64.422  |proj g|=    0.00012054
  At iterate     8  f =       64.422  |proj g|=    1.0555e-07
  
  iterations 8
  function evaluations 35
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.0555e-07
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.860036e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.984075 
    - variance bounds :  0.07848071 7.860036 
    - best initial criterion value(s) :  -506.8752 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       506.88  |proj g|=       7.1763
  At iterate     1  f =       99.942  |proj g|=        2.8689
  At iterate     2  f =       65.581  |proj g|=       0.98313
  ys=-2.443e+01  -gs= 1.950e+01, BFGS update SKIPPED
  At iterate     3  f =       64.906  |proj g|=       0.86552
  At iterate     4  f =       64.428  |proj g|=       0.70816
  At iterate     5  f =       64.424  |proj g|=       0.38655
  At iterate     6  f =       64.422  |proj g|=      0.017313
  At iterate     7  f =       64.422  |proj g|=    0.00040103
  At iterate     8  f =       64.422  |proj g|=    4.2842e-07
  
  iterations 8
  function evaluations 30
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.28425e-07
  final function value 64.422
  
  F = 64.422
  final  value 64.422011 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -286.1792 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       286.18  |proj g|=       2.1953
  At iterate     1  f =       265.64  |proj g|=        3.9954
  At iterate     2  f =       265.27  |proj g|=        2.3085
  At iterate     3  f =       265.27  |proj g|=         2.332
  At iterate     4  f =       265.26  |proj g|=        2.4325
  At iterate     5  f =       265.24  |proj g|=        2.5651
  At iterate     6  f =        265.2  |proj g|=        2.7512
  At iterate     7  f =       265.08  |proj g|=        2.9504
  At iterate     8  f =       264.77  |proj g|=        3.0496
  At iterate     9  f =       262.27  |proj g|=        1.8132
  At iterate    10  f =       262.23  |proj g|=        2.4058
  At iterate    11  f =        260.5  |proj g|=         1.936
  At iterate    12  f =       257.45  |proj g|=        8.3715
  At iterate    13  f =       256.06  |proj g|=        14.554
  At iterate    14  f =       249.28  |proj g|=        1.7078
  At iterate    15  f =       249.13  |proj g|=       0.48317
  At iterate    16  f =       249.13  |proj g|=       0.36469
  At iterate    17  f =       249.13  |proj g|=       0.23289
  At iterate    18  f =       249.12  |proj g|=        0.2332
  At iterate    19  f =       249.11  |proj g|=       0.39402
  At iterate    20  f =       249.08  |proj g|=       0.86529
  At iterate    21  f =       249.01  |proj g|=        1.6622
  At iterate    22  f =       248.81  |proj g|=        4.3447
  At iterate    23  f =        248.7  |proj g|=        2.8002
  At iterate    24  f =       248.23  |proj g|=         5.412
  At iterate    25  f =       246.12  |proj g|=        12.271
  At iterate    26  f =       243.61  |proj g|=        3.0725
  At iterate    27  f =       243.39  |proj g|=        1.7362
  At iterate    28  f =       243.33  |proj g|=        1.7274
  At iterate    29  f =       243.29  |proj g|=       0.79667
  At iterate    30  f =       243.26  |proj g|=       0.15264
  At iterate    31  f =       243.26  |proj g|=      0.079048
  At iterate    32  f =       243.26  |proj g|=     0.0012854
  At iterate    33  f =       243.26  |proj g|=    0.00049154
  
  iterations 33
  function evaluations 50
  segments explored during Cauchy searches 34
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000491541
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -267.051 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       267.05  |proj g|=       1.3667
  At iterate     1  f =       260.54  |proj g|=          16.3
  At iterate     2  f =       259.23  |proj g|=        13.413
  At iterate     3  f =       255.26  |proj g|=        2.1399
  At iterate     4  f =       252.88  |proj g|=       0.20339
  At iterate     5  f =       252.77  |proj g|=       0.26446
  At iterate     6  f =       252.77  |proj g|=       0.20178
  At iterate     7  f =       252.77  |proj g|=       0.20233
  At iterate     8  f =       252.77  |proj g|=       0.46354
  At iterate     9  f =       252.77  |proj g|=       0.98931
  At iterate    10  f =       252.77  |proj g|=        1.6863
  At iterate    11  f =       252.77  |proj g|=        1.6863
  At iterate    12  f =       252.76  |proj g|=        1.6863
  At iterate    13  f =       252.74  |proj g|=        1.8828
  At iterate    14  f =       252.69  |proj g|=        3.0787
  At iterate    15  f =       252.56  |proj g|=        4.9361
  At iterate    16  f =       252.52  |proj g|=         6.594
  At iterate    17  f =       252.21  |proj g|=        8.2462
  At iterate    18  f =       250.53  |proj g|=        13.604
  At iterate    19  f =       248.53  |proj g|=        16.365
  At iterate    20  f =       247.75  |proj g|=         15.96
  At iterate    21  f =       245.88  |proj g|=        11.887
  At iterate    22  f =       245.51  |proj g|=        12.526
  At iterate    23  f =       243.33  |proj g|=         1.577
  At iterate    24  f =       243.28  |proj g|=        1.7278
  At iterate    25  f =       243.26  |proj g|=        0.1526
  At iterate    26  f =       243.26  |proj g|=       0.36889
  At iterate    27  f =       243.26  |proj g|=      0.043292
  At iterate    28  f =       243.26  |proj g|=     0.0010969
  
  iterations 28
  function evaluations 35
  segments explored during Cauchy searches 31
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00109685
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/17266796/R-devel/847/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-16 01:42:22 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_Under_development_unstable_2025-05-15_r88204/release_1.17.2.Rcheck/00check.log	2025-05-16 01:33:02.426604585 -0700
+++ R_Under_development_unstable_2025-05-15_r88204/master_1.17.99.9c54bd073decac61dbd284c7a22d65d0f719aa19.Rcheck/00check.log	2025-05-16 01:42:22.910973588 -0700
@@ -49,7 +49,7 @@
 * checking examples ... OK
 Examples with CPU (user + system) or elapsed time > 5s
                                  user system elapsed
-mlr_learners_classif.cv_glmnet 28.153  0.093  28.845
+mlr_learners_classif.cv_glmnet 27.726  0.099  28.275
 * checking for unstated dependencies in 'tests' ... OK
 * checking tests ... ERROR
   Running 'testthat.R'
@@ -63,87 +63,69 @@
   Loading required package: mlr3
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.880405 
+  final  value 20.794415 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.880405 
+  final  value 20.794415 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.239713 
+  final  value 20.553673 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.239713 
+  final  value 20.553673 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.464337 
-  iter  10 value 7.466459
-  final  value 7.466412 
+  initial  value 10.311061 
+  iter  10 value 9.192773
+  final  value 9.192772 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.464337 
-  iter  10 value 7.466459
-  final  value 7.466412 
+  initial  value 10.311061 
+  iter  10 value 9.192773
+  final  value 9.192772 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  iter  10 value 18.942852
-  final  value 18.942852 
+  final  value 19.335028 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
@@ -155,67 +137,85 @@
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.504055 
+  iter  10 value 28.852852
+  iter  10 value 28.852852
+  final  value 28.852852 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.504055 
+  iter  10 value 28.852852
+  iter  10 value 28.852852
+  final  value 28.852852 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.516431 
+  final  value 31.487046 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.516431 
+  final  value 31.487046 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  iter  10 value 27.632069
+  iter  10 value 27.632069
+  final  value 27.632069 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  iter  10 value 27.632069
+  iter  10 value 27.632069
+  final  value 27.632069 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  18 (10 variable)
-  initial  value 19.511501 
-  iter  10 value 18.280758
-  final  value 18.273177 
+  initial  value 16.240751 
+  iter  10 value 10.352086
+  iter  20 value 10.178804
+  iter  30 value 10.176830
+  final  value 10.176813 
   converged
   # weights:  18 (10 variable)
-  initial  value 19.511501 
-  iter  10 value 18.280758
-  final  value 18.273177 
+  initial  value 16.240751 
+  iter  10 value 10.352086
+  iter  20 value 10.178804
+  iter  30 value 10.176830
+  final  value 10.176813 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.733537
-  final  value 30.730891 
+  iter  10 value 20.474106
+  iter  20 value 20.275043
+  final  value 20.275022 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -324,33 +324,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -429.6893 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -70821.6 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       429.69  |proj g|=        8.534
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       71.777  |proj g|=        1.3998
-  ys=-3.115e+01  -gs= 1.905e+01, BFGS update SKIPPED
-  At iterate     3  f =         69.5  |proj g|=        0.8825
-  At iterate     4  f =       69.483  |proj g|=        0.0264
-  At iterate     5  f =       69.483  |proj g|=     0.0020212
-  At iterate     6  f =       69.483  |proj g|=    4.0354e-06
+  At iterate     0  f=        70822  |proj g|=       11.434
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       76.237  |proj g|=        1.2966
+  ys=-6.352e+00  -gs= 2.000e+01, BFGS update SKIPPED
+  At iterate     3  f =       76.162  |proj g|=        1.2626
+  At iterate     4  f =       76.017  |proj g|=        1.0398
+  At iterate     5  f =        75.99  |proj g|=         0.244
+  At iterate     6  f =       75.988  |proj g|=      0.022685
+  At iterate     7  f =       75.988  |proj g|=    0.00056005
+  At iterate     8  f =       75.988  |proj g|=    1.2468e-06
   
-  iterations 6
-  function evaluations 23
-  segments explored during Cauchy searches 9
+  iterations 8
+  function evaluations 30
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.03545e-06
-  final function value 69.4834
+  norm of the final projected gradient 1.24681e-06
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -361,33 +363,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -429.6893 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -70821.6 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       429.69  |proj g|=        8.534
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       71.777  |proj g|=        1.3998
-  ys=-3.115e+01  -gs= 1.905e+01, BFGS update SKIPPED
-  At iterate     3  f =         69.5  |proj g|=        0.8825
-  At iterate     4  f =       69.483  |proj g|=        0.0264
-  At iterate     5  f =       69.483  |proj g|=     0.0020212
-  At iterate     6  f =       69.483  |proj g|=    4.0354e-06
+  At iterate     0  f=        70822  |proj g|=       11.434
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       76.237  |proj g|=        1.2966
+  ys=-6.352e+00  -gs= 2.000e+01, BFGS update SKIPPED
+  At iterate     3  f =       76.162  |proj g|=        1.2626
+  At iterate     4  f =       76.017  |proj g|=        1.0398
+  At iterate     5  f =        75.99  |proj g|=         0.244
+  At iterate     6  f =       75.988  |proj g|=      0.022685
+  At iterate     7  f =       75.988  |proj g|=    0.00056005
+  At iterate     8  f =       75.988  |proj g|=    1.2468e-06
   
-  iterations 6
-  function evaluations 23
-  segments explored during Cauchy searches 9
+  iterations 8
+  function evaluations 30
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.03545e-06
-  final function value 69.4834
+  norm of the final projected gradient 1.24681e-06
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -398,35 +402,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -288.5696 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -66114.67 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       288.57  |proj g|=       8.6429
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       70.192  |proj g|=        1.1125
-  ys=-1.851e+01  -gs= 1.972e+01, BFGS update SKIPPED
-  At iterate     3  f =       69.684  |proj g|=        0.9773
-  At iterate     4  f =       69.492  |proj g|=       0.68197
-  At iterate     5  f =       69.484  |proj g|=       0.21932
-  At iterate     6  f =       69.483  |proj g|=      0.011811
-  At iterate     7  f =       69.483  |proj g|=    0.00019171
-  At iterate     8  f =       69.483  |proj g|=    1.7104e-07
-  
-  iterations 8
-  function evaluations 22
-  segments explored during Cauchy searches 11
+  At iterate     0  f=        66115  |proj g|=       11.334
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       77.319  |proj g|=        1.6104
+  ys=-2.599e+01  -gs= 1.943e+01, BFGS update SKIPPED
+  At iterate     3  f =       76.784  |proj g|=        1.4751
+  At iterate     4  f =       76.013  |proj g|=       0.86704
+  At iterate     5  f =       76.003  |proj g|=       0.72941
+  At iterate     6  f =       75.988  |proj g|=      0.063259
+  At iterate     7  f =       75.988  |proj g|=     0.0041798
+  At iterate     8  f =       75.988  |proj g|=    2.6094e-05
+  At iterate     9  f =       75.988  |proj g|=     1.068e-08
+  
+  iterations 9
+  function evaluations 30
+  segments explored during Cauchy searches 12
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.71042e-07
-  final function value 69.4834
+  norm of the final projected gradient 1.06801e-08
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -437,35 +442,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -288.5696 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -66114.67 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       288.57  |proj g|=       8.6429
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       70.192  |proj g|=        1.1125
-  ys=-1.851e+01  -gs= 1.972e+01, BFGS update SKIPPED
-  At iterate     3  f =       69.684  |proj g|=        0.9773
-  At iterate     4  f =       69.492  |proj g|=       0.68197
-  At iterate     5  f =       69.484  |proj g|=       0.21932
-  At iterate     6  f =       69.483  |proj g|=      0.011811
-  At iterate     7  f =       69.483  |proj g|=    0.00019171
-  At iterate     8  f =       69.483  |proj g|=    1.7104e-07
-  
-  iterations 8
-  function evaluations 22
-  segments explored during Cauchy searches 11
+  At iterate     0  f=        66115  |proj g|=       11.334
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       77.319  |proj g|=        1.6104
+  ys=-2.599e+01  -gs= 1.943e+01, BFGS update SKIPPED
+  At iterate     3  f =       76.784  |proj g|=        1.4751
+  At iterate     4  f =       76.013  |proj g|=       0.86704
+  At iterate     5  f =       76.003  |proj g|=       0.72941
+  At iterate     6  f =       75.988  |proj g|=      0.063259
+  At iterate     7  f =       75.988  |proj g|=     0.0041798
+  At iterate     8  f =       75.988  |proj g|=    2.6094e-05
+  At iterate     9  f =       75.988  |proj g|=     1.068e-08
+  
+  iterations 9
+  function evaluations 30
+  segments explored during Cauchy searches 12
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.71042e-07
-  final function value 69.4834
+  norm of the final projected gradient 1.06801e-08
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -476,35 +482,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -4791.757 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -38764.39 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       4791.8  |proj g|=       8.3946
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       70.915  |proj g|=        1.2539
-  ys=-2.679e+01  -gs= 1.939e+01, BFGS update SKIPPED
-  At iterate     3  f =       70.418  |proj g|=        1.1601
-  At iterate     4  f =       69.519  |proj g|=       0.89962
-  At iterate     5  f =       69.484  |proj g|=       0.13142
-  At iterate     6  f =       69.483  |proj g|=      0.015236
-  At iterate     7  f =       69.483  |proj g|=    0.00015276
-  At iterate     8  f =       69.483  |proj g|=    1.7536e-07
-  
-  iterations 8
-  function evaluations 24
-  segments explored during Cauchy searches 11
+  At iterate     0  f=        38764  |proj g|=       11.407
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       77.282  |proj g|=        1.6017
+  ys=-2.568e+01  -gs= 1.945e+01, BFGS update SKIPPED
+  At iterate     3  f =       76.744  |proj g|=        1.4638
+  At iterate     4  f =        76.01  |proj g|=       0.81161
+  At iterate     5  f =           76  |proj g|=       0.64871
+  At iterate     6  f =       75.988  |proj g|=      0.052789
+  At iterate     7  f =       75.988  |proj g|=     0.0031263
+  At iterate     8  f =       75.988  |proj g|=    1.6264e-05
+  At iterate     9  f =       75.988  |proj g|=    4.9784e-09
+  
+  iterations 9
+  function evaluations 32
+  segments explored during Cauchy searches 12
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.75358e-07
-  final function value 69.4834
+  norm of the final projected gradient 4.97838e-09
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -515,33 +522,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.623887e-09 
+    - nugget : 1.248383e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.86271 
-    - variance bounds :  0.09598233 9.623887 
-    - best initial criterion value(s) :  -21938.36 
+    - parameters upper bounds :  4 2 1.869687 
+    - variance bounds :  0.1170728 12.48383 
+    - best initial criterion value(s) :  -1573.437 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        21938  |proj g|=       8.2049
-  At iterate     1  f =          105  |proj g|=        2.3431
-  At iterate     2  f =       69.485  |proj g|=       0.27409
-  At iterate     3  f =       69.483  |proj g|=      0.014664
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       69.483  |proj g|=    0.00014121
-  At iterate     5  f =       69.483  |proj g|=    1.5646e-07
+  At iterate     0  f=       1573.4  |proj g|=        11.48
+  At iterate     1  f =       111.51  |proj g|=        1.8063
+  At iterate     2  f =       76.924  |proj g|=         7.944
+  At iterate     3  f =       76.172  |proj g|=        1.2677
+  At iterate     4  f =       76.025  |proj g|=        1.0274
+  At iterate     5  f =       75.991  |proj g|=       0.34437
+  At iterate     6  f =       75.988  |proj g|=      0.037939
+  At iterate     7  f =       75.988  |proj g|=     0.0012328
+  At iterate     8  f =       75.988  |proj g|=    4.5999e-06
   
-  iterations 5
-  function evaluations 20
-  segments explored during Cauchy searches 10
+  iterations 8
+  function evaluations 24
+  segments explored during Cauchy searches 11
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.56457e-07
-  final function value 69.4834
+  norm of the final projected gradient 4.59987e-06
+  final function value 75.9881
   
-  F = 69.4834
-  final  value 69.483438 
+  F = 75.9881
+  final  value 75.988097 
   converged
   
   optimisation start
@@ -556,29 +564,55 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -720.0667 
+    - best initial criterion value(s) :  -310.0152 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       720.07  |proj g|=       10.181
-  At iterate     1  f =       324.02  |proj g|=       0.35502
-  At iterate     2  f =       319.15  |proj g|=       0.21712
-  At iterate     3  f =       318.23  |proj g|=      0.019869
-  At iterate     4  f =       318.22  |proj g|=      0.010191
-  At iterate     5  f =       318.22  |proj g|=    0.00028014
-  At iterate     6  f =       318.22  |proj g|=    3.8193e-06
-  At iterate     7  f =       318.22  |proj g|=    1.4561e-09
+  At iterate     0  f=       310.02  |proj g|=       44.179
+  At iterate     1  f =       308.54  |proj g|=         44.17
+  At iterate     2  f =       305.51  |proj g|=        1.4107
+  At iterate     3  f =       305.29  |proj g|=         1.404
+  At iterate     4  f =       303.51  |proj g|=        44.142
+  At iterate     5  f =       300.18  |proj g|=        44.152
+  At iterate     6  f =       295.82  |proj g|=        44.151
+  At iterate     7  f =       293.28  |proj g|=        44.132
+  At iterate     8  f =       287.64  |proj g|=        44.068
+  At iterate     9  f =       283.37  |proj g|=         43.99
+  At iterate    10  f =        281.1  |proj g|=        43.939
+  At iterate    11  f =       275.76  |proj g|=        43.794
+  At iterate    12  f =       260.01  |proj g|=        31.233
+  At iterate    13  f =       256.47  |proj g|=         1.363
+  At iterate    14  f =       248.67  |proj g|=        1.6946
+  At iterate    15  f =       248.59  |proj g|=        0.2335
+  At iterate    16  f =       248.59  |proj g|=        1.7007
+  At iterate    17  f =       248.59  |proj g|=       0.23631
+  At iterate    18  f =       248.59  |proj g|=        0.2361
+  At iterate    19  f =       248.58  |proj g|=       0.23446
+  At iterate    20  f =       248.57  |proj g|=       0.23242
+  At iterate    21  f =       248.53  |proj g|=       0.35283
+  At iterate    22  f =       248.45  |proj g|=       0.63456
+  At iterate    23  f =       248.22  |proj g|=        1.5433
+  At iterate    24  f =       247.69  |proj g|=        3.4246
+  At iterate    25  f =       246.66  |proj g|=        5.8087
+  At iterate    26  f =       245.94  |proj g|=         12.83
+  At iterate    27  f =       244.64  |proj g|=        9.9535
+  At iterate    28  f =       243.54  |proj g|=       0.76537
+  At iterate    29  f =       243.27  |proj g|=       0.49396
+  At iterate    30  f =       243.26  |proj g|=      0.055811
+  At iterate    31  f =       243.26  |proj g|=     0.0091265
+  At iterate    32  f =       243.26  |proj g|=     0.0051811
+  At iterate    33  f =       243.26  |proj g|=    7.5203e-05
   
-  iterations 7
-  function evaluations 15
-  segments explored during Cauchy searches 9
+  iterations 33
+  function evaluations 47
+  segments explored during Cauchy searches 35
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.45614e-09
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 7.52026e-05
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -593,30 +627,48 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -7294.309 
+    - best initial criterion value(s) :  -295.1124 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       7294.3  |proj g|=       110.29
-  At iterate     1  f =       359.98  |proj g|=       0.22962
-  At iterate     2  f =       318.31  |proj g|=      0.082145
-  At iterate     3  f =       318.22  |proj g|=     0.0080639
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.22  |proj g|=     0.0063548
-  At iterate     5  f =       318.22  |proj g|=    7.1459e-05
-  At iterate     6  f =       318.22  |proj g|=    6.2439e-07
-  
-  iterations 6
-  function evaluations 22
-  segments explored during Cauchy searches 10
+  At iterate     0  f=       295.11  |proj g|=       2.7186
+  At iterate     1  f =       254.19  |proj g|=        1.7351
+  At iterate     2  f =       252.87  |proj g|=        1.7228
+  At iterate     3  f =       251.42  |proj g|=        1.7907
+  At iterate     4  f =       251.36  |proj g|=        1.0343
+  At iterate     5  f =       251.35  |proj g|=       0.21456
+  At iterate     6  f =       251.35  |proj g|=       0.53878
+  At iterate     7  f =       251.35  |proj g|=        1.3929
+  At iterate     8  f =       251.35  |proj g|=        1.6915
+  At iterate     9  f =       251.34  |proj g|=        1.6921
+  At iterate    10  f =       251.32  |proj g|=        1.6932
+  At iterate    11  f =       251.28  |proj g|=        2.2769
+  At iterate    12  f =       251.15  |proj g|=        4.0363
+  At iterate    13  f =       250.84  |proj g|=        7.1562
+  At iterate    14  f =       250.18  |proj g|=        12.235
+  At iterate    15  f =       248.83  |proj g|=        19.592
+  At iterate    16  f =       247.81  |proj g|=        23.807
+  At iterate    17  f =       247.48  |proj g|=         19.93
+  At iterate    18  f =       246.47  |proj g|=        18.142
+  At iterate    19  f =       243.68  |proj g|=         1.739
+  At iterate    20  f =       243.41  |proj g|=       0.52456
+  At iterate    21  f =       243.28  |proj g|=       0.17101
+  At iterate    22  f =       243.27  |proj g|=      0.066458
+  At iterate    23  f =       243.27  |proj g|=       0.89423
+  At iterate    24  f =       243.26  |proj g|=      0.069314
+  At iterate    25  f =       243.26  |proj g|=    0.00057487
+  At iterate    26  f =       243.26  |proj g|=    0.00019312
+  
+  iterations 26
+  function evaluations 32
+  segments explored during Cauchy searches 28
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 6.24392e-07
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.000193118
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -631,24 +683,28 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -718.3307 
+    - best initial criterion value(s) :  -2710.663 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       718.33  |proj g|=       15.466
-  At iterate     1  f =       321.04  |proj g|=       0.30837
-  At iterate     2  f =       318.64  |proj g|=       0.15992
-  At iterate     3  f =       318.22  |proj g|=      0.013997
-  At iterate     4  f =       318.22  |proj g|=     0.0043856
-  At iterate     5  f =       318.22  |proj g|=    8.4899e-05
-  At iterate     6  f =       318.22  |proj g|=     5.028e-07
+  At iterate     0  f=       2710.7  |proj g|=       53.618
+  At iterate     1  f =       339.66  |proj g|=        0.3275
+  At iterate     2  f =       319.48  |proj g|=       0.24199
+  At iterate     3  f =       318.54  |proj g|=       0.19102
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.38  |proj g|=        0.1312
+  At iterate     5  f =       318.23  |proj g|=      0.022048
+  At iterate     6  f =       318.22  |proj g|=       0.00313
+  At iterate     7  f =       318.22  |proj g|=    9.0029e-05
+  At iterate     8  f =       318.22  |proj g|=    3.8122e-07
   
-  iterations 6
-  function evaluations 12
-  segments explored during Cauchy searches 8
+  iterations 8
+  function evaluations 18
+  segments explored during Cauchy searches 12
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 5.02798e-07
+  norm of the final projected gradient 3.81225e-07
   final function value 318.222
   
   F = 318.222
@@ -667,26 +723,25 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -2744.085 
+    - best initial criterion value(s) :  -1729.7 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       2744.1  |proj g|=       86.353
-  At iterate     1  f =       344.49  |proj g|=       0.30339
-  At iterate     2  f =       318.42  |proj g|=       0.11556
-  At iterate     3  f =       318.22  |proj g|=      0.012065
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.22  |proj g|=      0.009533
-  At iterate     5  f =       318.22  |proj g|=    0.00016241
-  At iterate     6  f =       318.22  |proj g|=    2.1402e-06
+  At iterate     0  f=       1729.7  |proj g|=       24.122
+  At iterate     1  f =        335.1  |proj g|=       0.34855
+  At iterate     2  f =       318.83  |proj g|=       0.27987
+  At iterate     3  f =       318.24  |proj g|=      0.040347
+  At iterate     4  f =       318.22  |proj g|=      0.011126
+  At iterate     5  f =       318.22  |proj g|=    0.00066944
+  At iterate     6  f =       318.22  |proj g|=    1.0315e-05
+  At iterate     7  f =       318.22  |proj g|=    9.3829e-09
   
-  iterations 6
-  function evaluations 19
-  segments explored during Cauchy searches 10
+  iterations 7
+  function evaluations 22
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 2.14023e-06
+  norm of the final projected gradient 9.38291e-09
   final function value 318.222
   
   F = 318.222
@@ -701,47 +756,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -69.81058 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -17876.79 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       69.811  |proj g|=       1.8498
-  At iterate     1  f =       67.974  |proj g|=        1.8332
-  At iterate     2  f =        67.64  |proj g|=        2.9914
-  At iterate     3  f =       67.583  |proj g|=        3.5009
-  At iterate     4  f =       67.492  |proj g|=        3.7535
-  At iterate     5  f =       67.003  |proj g|=        4.3078
-  At iterate     6  f =         66.2  |proj g|=        3.9867
-  At iterate     7  f =       64.544  |proj g|=        1.6971
-  At iterate     8  f =       62.756  |proj g|=        1.0856
-  At iterate     9  f =       62.349  |proj g|=        1.0148
-  At iterate    10  f =       62.198  |proj g|=        1.8275
-  At iterate    11  f =       62.006  |proj g|=        1.8278
-  At iterate    12  f =       61.981  |proj g|=       0.94542
-  At iterate    13  f =       61.813  |proj g|=       0.90014
-  At iterate    14  f =       61.415  |proj g|=       0.75246
-  At iterate    15  f =       61.353  |proj g|=       0.78278
-  At iterate    16  f =       61.325  |proj g|=        1.8324
-  At iterate    17  f =       61.315  |proj g|=        1.8323
-  At iterate    18  f =       61.309  |proj g|=       0.10786
-  At iterate    19  f =       61.309  |proj g|=      0.020988
-  At iterate    20  f =       61.309  |proj g|=     0.0096561
-  At iterate    21  f =       61.309  |proj g|=     0.0042517
-  
-  iterations 21
-  function evaluations 31
-  segments explored during Cauchy searches 24
+  At iterate     0  f=        17877  |proj g|=       7.2175
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       64.423  |proj g|=       0.25184
+  At iterate     3  f =       64.422  |proj g|=      0.081437
+  At iterate     4  f =       64.422  |proj g|=     0.0012475
+  At iterate     5  f =       64.422  |proj g|=    6.3007e-06
+  
+  iterations 5
+  function evaluations 21
+  segments explored during Cauchy searches 8
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 0.00425172
-  final function value 61.3093
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 6.30067e-06
+  final function value 64.422
   
-  F = 61.3093
-  final  value 61.309269 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -752,47 +791,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -69.81058 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -17876.79 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       69.811  |proj g|=       1.8498
-  At iterate     1  f =       67.974  |proj g|=        1.8332
-  At iterate     2  f =        67.64  |proj g|=        2.9914
-  At iterate     3  f =       67.583  |proj g|=        3.5009
-  At iterate     4  f =       67.492  |proj g|=        3.7535
-  At iterate     5  f =       67.003  |proj g|=        4.3078
-  At iterate     6  f =         66.2  |proj g|=        3.9867
-  At iterate     7  f =       64.544  |proj g|=        1.6971
-  At iterate     8  f =       62.756  |proj g|=        1.0856
-  At iterate     9  f =       62.349  |proj g|=        1.0148
-  At iterate    10  f =       62.198  |proj g|=        1.8275
-  At iterate    11  f =       62.006  |proj g|=        1.8278
-  At iterate    12  f =       61.981  |proj g|=       0.94542
-  At iterate    13  f =       61.813  |proj g|=       0.90014
-  At iterate    14  f =       61.415  |proj g|=       0.75246
-  At iterate    15  f =       61.353  |proj g|=       0.78278
-  At iterate    16  f =       61.325  |proj g|=        1.8324
-  At iterate    17  f =       61.315  |proj g|=        1.8323
-  At iterate    18  f =       61.309  |proj g|=       0.10786
-  At iterate    19  f =       61.309  |proj g|=      0.020988
-  At iterate    20  f =       61.309  |proj g|=     0.0096561
-  At iterate    21  f =       61.309  |proj g|=     0.0042517
-  
-  iterations 21
-  function evaluations 31
-  segments explored during Cauchy searches 24
+  At iterate     0  f=        17877  |proj g|=       7.2175
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       64.423  |proj g|=       0.25184
+  At iterate     3  f =       64.422  |proj g|=      0.081437
+  At iterate     4  f =       64.422  |proj g|=     0.0012475
+  At iterate     5  f =       64.422  |proj g|=    6.3007e-06
+  
+  iterations 5
+  function evaluations 21
+  segments explored during Cauchy searches 8
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 0.00425172
-  final function value 61.3093
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 6.30067e-06
+  final function value 64.422
   
-  F = 61.3093
-  final  value 61.309269 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -803,58 +826,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -67.26564 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -1690.294 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       67.266  |proj g|=        1.854
-  At iterate     1  f =        63.85  |proj g|=        1.8298
-  At iterate     2  f =       63.663  |proj g|=        1.3228
-  At iterate     3  f =       63.654  |proj g|=        1.3396
-  At iterate     4  f =        63.63  |proj g|=        1.3592
-  At iterate     5  f =       63.561  |proj g|=        1.3732
-  At iterate     6  f =       63.393  |proj g|=        1.3353
-  At iterate     7  f =       62.991  |proj g|=        1.1003
-  At iterate     8  f =       62.314  |proj g|=        1.2176
-  At iterate     9  f =       61.607  |proj g|=        3.1901
-  At iterate    10  f =       61.373  |proj g|=        0.8194
-  At iterate    11  f =       61.373  |proj g|=       0.75093
-  At iterate    12  f =       61.364  |proj g|=       0.80471
-  At iterate    13  f =       61.328  |proj g|=       0.50692
-  At iterate    14  f =       61.316  |proj g|=       0.22312
-  At iterate    15  f =       61.313  |proj g|=        1.0873
-  At iterate    16  f =       61.312  |proj g|=       0.15577
-  At iterate    17  f =       61.312  |proj g|=       0.18388
-  At iterate    18  f =       61.312  |proj g|=       0.20785
-  At iterate    19  f =       61.311  |proj g|=       0.11205
-  At iterate    20  f =        61.31  |proj g|=       0.10757
-  At iterate    21  f =       61.309  |proj g|=      0.046736
-  At iterate    22  f =       61.309  |proj g|=      0.030551
-  At iterate    23  f =       61.309  |proj g|=      0.011367
-  At iterate    24  f =       61.309  |proj g|=      0.021079
-  At iterate    25  f =       61.309  |proj g|=      0.030563
-  At iterate    26  f =       61.309  |proj g|=      0.094226
-  At iterate    27  f =       61.309  |proj g|=      0.082851
-  At iterate    28  f =       61.309  |proj g|=       0.18583
-  At iterate    29  f =       61.309  |proj g|=       0.12565
-  At iterate    30  f =       61.309  |proj g|=      0.026596
-  At iterate    31  f =       61.309  |proj g|=    0.00067763
-  At iterate    32  f =       61.309  |proj g|=    0.00039448
+  At iterate     0  f=       1690.3  |proj g|=       6.9512
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       64.485  |proj g|=       0.74907
+  At iterate     3  f =       64.423  |proj g|=       0.21233
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       64.422  |proj g|=     0.0091594
+  At iterate     5  f =       64.422  |proj g|=    0.00012193
+  At iterate     6  f =       64.422  |proj g|=    6.8869e-08
   
-  iterations 32
-  function evaluations 40
-  segments explored during Cauchy searches 35
+  iterations 6
+  function evaluations 19
+  segments explored during Cauchy searches 11
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 0.000394482
-  final function value 61.3093
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 6.88688e-08
+  final function value 64.422
   
-  F = 61.3093
-  final  value 61.309269 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -865,58 +864,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -67.26564 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -1690.294 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       67.266  |proj g|=        1.854
-  At iterate     1  f =        63.85  |proj g|=        1.8298
-  At iterate     2  f =       63.663  |proj g|=        1.3228
-  At iterate     3  f =       63.654  |proj g|=        1.3396
-  At iterate     4  f =        63.63  |proj g|=        1.3592
-  At iterate     5  f =       63.561  |proj g|=        1.3732
-  At iterate     6  f =       63.393  |proj g|=        1.3353
-  At iterate     7  f =       62.991  |proj g|=        1.1003
-  At iterate     8  f =       62.314  |proj g|=        1.2176
-  At iterate     9  f =       61.607  |proj g|=        3.1901
-  At iterate    10  f =       61.373  |proj g|=        0.8194
-  At iterate    11  f =       61.373  |proj g|=       0.75093
-  At iterate    12  f =       61.364  |proj g|=       0.80471
-  At iterate    13  f =       61.328  |proj g|=       0.50692
-  At iterate    14  f =       61.316  |proj g|=       0.22312
-  At iterate    15  f =       61.313  |proj g|=        1.0873
-  At iterate    16  f =       61.312  |proj g|=       0.15577
-  At iterate    17  f =       61.312  |proj g|=       0.18388
-  At iterate    18  f =       61.312  |proj g|=       0.20785
-  At iterate    19  f =       61.311  |proj g|=       0.11205
-  At iterate    20  f =        61.31  |proj g|=       0.10757
-  At iterate    21  f =       61.309  |proj g|=      0.046736
-  At iterate    22  f =       61.309  |proj g|=      0.030551
-  At iterate    23  f =       61.309  |proj g|=      0.011367
-  At iterate    24  f =       61.309  |proj g|=      0.021079
-  At iterate    25  f =       61.309  |proj g|=      0.030563
-  At iterate    26  f =       61.309  |proj g|=      0.094226
-  At iterate    27  f =       61.309  |proj g|=      0.082851
-  At iterate    28  f =       61.309  |proj g|=       0.18583
-  At iterate    29  f =       61.309  |proj g|=       0.12565
-  At iterate    30  f =       61.309  |proj g|=      0.026596
-  At iterate    31  f =       61.309  |proj g|=    0.00067763
-  At iterate    32  f =       61.309  |proj g|=    0.00039448
+  At iterate     0  f=       1690.3  |proj g|=       6.9512
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       64.485  |proj g|=       0.74907
+  At iterate     3  f =       64.423  |proj g|=       0.21233
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       64.422  |proj g|=     0.0091594
+  At iterate     5  f =       64.422  |proj g|=    0.00012193
+  At iterate     6  f =       64.422  |proj g|=    6.8869e-08
   
-  iterations 32
-  function evaluations 40
-  segments explored during Cauchy searches 35
+  iterations 6
+  function evaluations 19
+  segments explored during Cauchy searches 11
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 0.000394482
-  final function value 61.3093
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 6.88688e-08
+  final function value 64.422
   
-  F = 61.3093
-  final  value 61.309269 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -927,31 +902,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -74.01697 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -5026636 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       74.017  |proj g|=        7.915
-  At iterate     1  f =       70.298  |proj g|=        1.2504
-  At iterate     2  f =        66.57  |proj g|=       0.78941
-  At iterate     3  f =       66.539  |proj g|=      0.046995
-  At iterate     4  f =       66.539  |proj g|=     7.007e-09
-  At iterate     5  f =       66.539  |proj g|=    2.1995e-11
+  At iterate     0  f=   5.0266e+06  |proj g|=       6.7527
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       66.172  |proj g|=        1.0696
+  ys=-2.884e+01  -gs= 1.926e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.406  |proj g|=       0.95547
+  At iterate     4  f =       64.452  |proj g|=       0.73058
+  At iterate     5  f =       64.422  |proj g|=       0.13622
+  At iterate     6  f =       64.422  |proj g|=      0.014225
+  At iterate     7  f =       64.422  |proj g|=    0.00012054
+  At iterate     8  f =       64.422  |proj g|=    1.0555e-07
   
-  iterations 5
-  function evaluations 9
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 2.19949e-11
-  final function value 66.5392
+  iterations 8
+  function evaluations 35
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 1.0555e-07
+  final function value 64.422
   
-  F = 66.5392
-  final  value 66.539158 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -962,44 +941,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.554668e-09 
+    - nugget : 7.860036e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.865628 
-    - variance bounds :  0.08150369 8.554668 
-    - best initial criterion value(s) :  -79.16497 
+    - parameters upper bounds :  4 2 1.984075 
+    - variance bounds :  0.07848071 7.860036 
+    - best initial criterion value(s) :  -506.8752 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       79.165  |proj g|=       8.0227
-  At iterate     1  f =       74.187  |proj g|=        7.9048
-  At iterate     2  f =       70.877  |proj g|=        7.8443
-  At iterate     3  f =       67.812  |proj g|=        7.6884
-  At iterate     4  f =       65.647  |proj g|=        4.3175
-  At iterate     5  f =       64.442  |proj g|=        1.6664
-  At iterate     6  f =       63.704  |proj g|=        1.8244
-  At iterate     7  f =       62.989  |proj g|=        1.8242
-  At iterate     8  f =       62.943  |proj g|=        1.8262
-  At iterate     9  f =       62.434  |proj g|=        1.8279
-  At iterate    10  f =       61.514  |proj g|=       0.82711
-  At iterate    11  f =       61.379  |proj g|=       0.72649
-  At iterate    12  f =       61.363  |proj g|=        1.8315
-  At iterate    13  f =       61.338  |proj g|=        1.8321
-  At iterate    14  f =        61.31  |proj g|=         1.832
-  At iterate    15  f =       61.309  |proj g|=       0.25743
-  At iterate    16  f =       61.309  |proj g|=      0.028638
-  At iterate    17  f =       61.309  |proj g|=      0.015752
-  At iterate    18  f =       61.309  |proj g|=    0.00073988
+  At iterate     0  f=       506.88  |proj g|=       7.1763
+  At iterate     1  f =       99.942  |proj g|=        2.8689
+  At iterate     2  f =       65.581  |proj g|=       0.98313
+  ys=-2.443e+01  -gs= 1.950e+01, BFGS update SKIPPED
+  At iterate     3  f =       64.906  |proj g|=       0.86552
+  At iterate     4  f =       64.428  |proj g|=       0.70816
+  At iterate     5  f =       64.424  |proj g|=       0.38655
+  At iterate     6  f =       64.422  |proj g|=      0.017313
+  At iterate     7  f =       64.422  |proj g|=    0.00040103
+  At iterate     8  f =       64.422  |proj g|=    4.2842e-07
   
-  iterations 18
-  function evaluations 22
-  segments explored during Cauchy searches 21
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 0.000739876
-  final function value 61.3093
+  iterations 8
+  function evaluations 30
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 4.28425e-07
+  final function value 64.422
   
-  F = 61.3093
-  final  value 61.309269 
+  F = 64.422
+  final  value 64.422011 
   converged
   
   optimisation start
@@ -1014,26 +984,55 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -6418.497 
+    - best initial criterion value(s) :  -286.1792 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       6418.5  |proj g|=       162.93
-  At iterate     1  f =        365.6  |proj g|=       0.20635
-  At iterate     2  f =       318.23  |proj g|=        0.0174
-  At iterate     3  f =       318.22  |proj g|=    8.9228e-05
-  At iterate     4  f =       318.22  |proj g|=    2.1769e-06
-  
-  iterations 4
-  function evaluations 15
-  segments explored during Cauchy searches 6
+  At iterate     0  f=       286.18  |proj g|=       2.1953
+  At iterate     1  f =       265.64  |proj g|=        3.9954
+  At iterate     2  f =       265.27  |proj g|=        2.3085
+  At iterate     3  f =       265.27  |proj g|=         2.332
+  At iterate     4  f =       265.26  |proj g|=        2.4325
+  At iterate     5  f =       265.24  |proj g|=        2.5651
+  At iterate     6  f =        265.2  |proj g|=        2.7512
+  At iterate     7  f =       265.08  |proj g|=        2.9504
+  At iterate     8  f =       264.77  |proj g|=        3.0496
+  At iterate     9  f =       262.27  |proj g|=        1.8132
+  At iterate    10  f =       262.23  |proj g|=        2.4058
+  At iterate    11  f =        260.5  |proj g|=         1.936
+  At iterate    12  f =       257.45  |proj g|=        8.3715
+  At iterate    13  f =       256.06  |proj g|=        14.554
+  At iterate    14  f =       249.28  |proj g|=        1.7078
+  At iterate    15  f =       249.13  |proj g|=       0.48317
+  At iterate    16  f =       249.13  |proj g|=       0.36469
+  At iterate    17  f =       249.13  |proj g|=       0.23289
+  At iterate    18  f =       249.12  |proj g|=        0.2332
+  At iterate    19  f =       249.11  |proj g|=       0.39402
+  At iterate    20  f =       249.08  |proj g|=       0.86529
+  At iterate    21  f =       249.01  |proj g|=        1.6622
+  At iterate    22  f =       248.81  |proj g|=        4.3447
+  At iterate    23  f =        248.7  |proj g|=        2.8002
+  At iterate    24  f =       248.23  |proj g|=         5.412
+  At iterate    25  f =       246.12  |proj g|=        12.271
+  At iterate    26  f =       243.61  |proj g|=        3.0725
+  At iterate    27  f =       243.39  |proj g|=        1.7362
+  At iterate    28  f =       243.33  |proj g|=        1.7274
+  At iterate    29  f =       243.29  |proj g|=       0.79667
+  At iterate    30  f =       243.26  |proj g|=       0.15264
+  At iterate    31  f =       243.26  |proj g|=      0.079048
+  At iterate    32  f =       243.26  |proj g|=     0.0012854
+  At iterate    33  f =       243.26  |proj g|=    0.00049154
+  
+  iterations 33
+  function evaluations 50
+  segments explored during Cauchy searches 34
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 2.17691e-06
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.000491541
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -1048,31 +1047,50 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -904.3254 
+    - best initial criterion value(s) :  -267.051 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       904.33  |proj g|=       10.103
-  At iterate     1  f =       333.02  |proj g|=       0.35669
-  At iterate     2  f =       318.74  |proj g|=       0.17449
-  At iterate     3  f =       318.22  |proj g|=      0.015634
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.22  |proj g|=      0.012382
-  At iterate     5  f =       318.22  |proj g|=     0.0002765
-  At iterate     6  f =       318.22  |proj g|=    4.7553e-06
-  At iterate     7  f =       318.22  |proj g|=    1.7877e-09
-  
-  iterations 7
-  function evaluations 18
-  segments explored during Cauchy searches 11
+  At iterate     0  f=       267.05  |proj g|=       1.3667
+  At iterate     1  f =       260.54  |proj g|=          16.3
+  At iterate     2  f =       259.23  |proj g|=        13.413
+  At iterate     3  f =       255.26  |proj g|=        2.1399
+  At iterate     4  f =       252.88  |proj g|=       0.20339
+  At iterate     5  f =       252.77  |proj g|=       0.26446
+  At iterate     6  f =       252.77  |proj g|=       0.20178
+  At iterate     7  f =       252.77  |proj g|=       0.20233
+  At iterate     8  f =       252.77  |proj g|=       0.46354
+  At iterate     9  f =       252.77  |proj g|=       0.98931
+  At iterate    10  f =       252.77  |proj g|=        1.6863
+  At iterate    11  f =       252.77  |proj g|=        1.6863
+  At iterate    12  f =       252.76  |proj g|=        1.6863
+  At iterate    13  f =       252.74  |proj g|=        1.8828
+  At iterate    14  f =       252.69  |proj g|=        3.0787
+  At iterate    15  f =       252.56  |proj g|=        4.9361
+  At iterate    16  f =       252.52  |proj g|=         6.594
+  At iterate    17  f =       252.21  |proj g|=        8.2462
+  At iterate    18  f =       250.53  |proj g|=        13.604
+  At iterate    19  f =       248.53  |proj g|=        16.365
+  At iterate    20  f =       247.75  |proj g|=         15.96
+  At iterate    21  f =       245.88  |proj g|=        11.887
+  At iterate    22  f =       245.51  |proj g|=        12.526
+  At iterate    23  f =       243.33  |proj g|=         1.577
+  At iterate    24  f =       243.28  |proj g|=        1.7278
+  At iterate    25  f =       243.26  |proj g|=        0.1526
+  At iterate    26  f =       243.26  |proj g|=       0.36889
+  At iterate    27  f =       243.26  |proj g|=      0.043292
+  At iterate    28  f =       243.26  |proj g|=     0.0010969
+  
+  iterations 28
+  function evaluations 35
+  segments explored during Cauchy searches 31
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.78768e-09
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.00109685
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
   
> library(data.table, lib.loc=R.home("library"))
> (sig.diff.dt <- myDiff(Rvers))
Key: <checking>
Empty data.table (0 rows and 3 cols): checking,master,release
> 
> ## If there are significant differences, use git bisect to find when
> ## they started.
> if(nrow(sig.diff.dt)){
+   dt.git <- file.path(task.dir, "data.table.git")
+   system(paste("cd ~/R/data.table && git fetch --tags"))
+   system(paste("git clone ~/R/data.table", dt.git))
+   release.tag <- gsub(".tar.gz|.*_", "", cargs[["release"]])
+   rev.parse.cmd <- paste(
+     "cd", dt.git, "&& git rev-parse master")
+   master.sha <- system(rev.parse.cmd, intern=TRUE)
+   merge.base.cmd <- paste(
+     "cd", dt.git, "&& git merge-base master", release.tag)
+   merge.base.sha <- system(merge.base.cmd, intern=TRUE)
+   old.sha <- merge.base.sha
+   run_R <- file.path(proj.dir, "install_dt_then_check_dep.R")
+   sig.diff.dt[, first.bad.commit := NA_character_]
+   sig.diff.dt[, comments := NA_character_]
+   for(diff.i in 1:nrow(sig.diff.dt)){
+     sig.diff.row <- sig.diff.dt[diff.i]
+     bisect.cmd <- paste(
+       "cd", dt.git, "&&",
+       "git bisect start &&",
+       "git bisect old", old.sha, "&&",
+       "git bisect new master &&",
+       "git bisect run",
+       R.home('bin/Rscript'),
+       run_R,
+       shQuote(sig.diff.row$checking),
+       sig.diff.row$release,
+       rev.dep.release.tar.gz,
+       release.tag)
+     print(bisect.cmd)
+     bisect.out <- system(bisect.cmd, intern=TRUE)
+     cat(bisect.out,sep="\n")
+     if(is.null(attr(bisect.out,"status"))){
+       first.bad.sha <- nc::capture_all_str(
+         bisect.out,
+         sha="[0-9a-f]+",
+         " is the first new commit")$sha
+       parent.cmd <- paste(
+         "cd ~/R/data.table && git log --pretty=%P -n 1",
+         first.bad.sha)
+       parent.sha <- system(parent.cmd, intern=TRUE)
+       sig.diff.dt[diff.i, first.bad.commit := first.bad.sha]
+       parent.msg <- paste0("parent=", parent.sha)
+       this.comment <- if(parent.sha==old.sha){
+         paste(parent.msg, "same as git bisect old")
+       }else if(first.bad.sha==master.sha){
+         paste("same as git bisect new=master,", parent.msg)
+       }else{
+         parent.msg
+       }
+       sig.diff.dt[diff.i, comments := this.comment]
+     }
+   }
+   ## add CRAN column.
+   sig.diff.dt[, CRAN := {
+     flavor <- get_flavor(Rvers)
+     details <- data.table(flavor=unique(flavor))[, {
+       base <- "https://www.r-project.org/nosvn/R.check/"
+       u <- paste0(base, flavor, "/", rev.dep, "-00check.txt")
+       check.txt <- tempfile()
+       tryCatch({
+         download.file(u, check.txt, quiet=TRUE)
+       }, error=function(e){
+         NULL
+       })
+       check.lines <- if(file.exists(check.txt)){
+         readLines(check.txt,encoding="UTF-8")
+       }else{
+         ""
+       }
+       repl.lines <- gsub("[\u2018\u2019]", "'", check.lines)
+       ##gsub("[‘’]", "'", check.lines) does not work with LC_ALL=C.
+       myStatus(line.vec=repl.lines)
+     }, by=flavor]
+     select.dt <- data.table(flavor, checking)
+     details[select.dt, msg, on=.(flavor, checking)]
+   }]
+   dir.create(file.path(job.dir, Rvers))
+   diffs.csv <- file.path(job.dir, Rvers, "significant_differences.csv")
+   data.table::fwrite(sig.diff.dt, diffs.csv)
+   print(sig.diff.dt)
+ }
> 
WARNING: ignoring environment value of R_HOME

R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> cargs <- commandArgs(trailingOnly=TRUE)
> if(length(cargs)==0){
+   ## before running interactively, make sure to start emacs/R with
+   ## environment defined in /scratch/...check_one.sh, particularly
+   ## R_LIBS_USER=/tmp/... otherwise we get error when installing
+   ## data.table.
+   base <- "/scratch/th798/data.table-revdeps/*"
+   cargs <- c(
+     Sys.glob(file.path(base,"deps.csv")),
+     "349",
+     Sys.glob(file.path(base, "data.table_release_*tar.gz")),
+     Sys.glob(file.path(base, "data.table_master_*tar.gz"))
+   )
+ }
> names(cargs) <- c("deps.csv", "task.str", "release", "master")
> dput(cargs)
c(deps.csv = "/scratch/th798/data.table-revdeps/2025-05-16/deps.csv", 
task.str = "847", release = "/scratch/th798/data.table-revdeps/2025-05-16/data.table_release_1.17.2.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-05-16/data.table_master_1.17.99.9c54bd073decac61dbd284c7a22d65d0f719aa19.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/17266796/R-release/847"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/17266796/R-release/847/R.cache"
> task.id <- as.integer(cargs[["task.str"]])
> deps.df <- read.csv(cargs[["deps.csv"]])
> (rev.dep <- deps.df$Package[task.id])
[1] "mlr3learners"
> job.dir <- file.path(dirname(cargs[["deps.csv"]]), "tasks", task.id)
> setwd(task.dir)
> .libPaths()
[1] "/tmp/th798/17266796/R-release/847/library"
[2] "/projects/genomic-ml/R/R-release/library" 
> options(repos=c(#this should be in ~/.Rprofile too.
+   CRAN="http://cloud.r-project.org"))
> print(Sys.time())
[1] "2025-05-16 01:42:28 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/17266796/R-release/847/library'
(as 'lib' is unspecified)
also installing the dependencies 'mlr3measures', 'mlr3', 'paradox', 'DiceKriging', 'rgenoud'

trying URL 'http://cloud.r-project.org/src/contrib/mlr3measures_1.0.0.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/mlr3_0.23.0.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/paradox_1.0.1.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/DiceKriging_1.6.0.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/rgenoud_5.9-0.11.tar.gz'
trying URL 'http://cloud.r-project.org/src/contrib/mlr3learners_0.10.0.tar.gz'
* installing *source* package 'mlr3measures' ...
** this is package 'mlr3measures' version '1.0.0'
** package 'mlr3measures' successfully unpacked and MD5 sums checked
** using staged installation
** R
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mlr3measures)
* installing *source* package 'paradox' ...
** this is package 'paradox' version '1.0.1'
** package 'paradox' successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (paradox)
* installing *source* package 'DiceKriging' ...
** this is package 'DiceKriging' version '1.6.0'
** package 'DiceKriging' successfully unpacked and MD5 sums checked
** using staged installation
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c CovFuns.c -o CovFuns.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c Scaling.c -o Scaling.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o DiceKriging.so CovFuns.o Scaling.o init.o
installing to /tmp/th798/17266796/R-release/847/library/00LOCK-DiceKriging/00new/DiceKriging/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Note: ... may be used in an incorrect context 
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (DiceKriging)
* installing *source* package 'rgenoud' ...
** this is package 'rgenoud' version '5.9-0.11'
** package 'rgenoud' successfully unpacked and MD5 sums checked
** using staged installation
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
using C++ compiler: 'g++ (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c change_order.cpp -o change_order.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c eval.cpp -o eval.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c evaluate.cpp -o evaluate.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c frange_ran.cpp -o frange_ran.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c genoud.cpp -o genoud.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c gradient.cpp -o gradient.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c math.cpp -o math.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c multiply.cpp -o multiply.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c numerics.cpp -o numerics.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c operators.cpp -o operators.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c print_format.cpp -o print_format.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include    -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include   -c rgenoud.cpp -o rgenoud.o
/packages/gcc/12.2.0-nnbserq/bin/g++ -std=gnu++17 -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o rgenoud.so change_order.o eval.o evaluate.o frange_ran.o genoud.o gradient.o init.o math.o multiply.o numerics.o operators.o print_format.o rgenoud.o
installing to /tmp/th798/17266796/R-release/847/library/00LOCK-rgenoud/00new/rgenoud/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (rgenoud)
* installing *source* package 'mlr3' ...
** this is package 'mlr3' version '0.23.0'
** package 'mlr3' successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mlr3)
* installing *source* package 'mlr3learners' ...
** this is package 'mlr3learners' version '0.10.0'
** package 'mlr3learners' successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mlr3learners)

The downloaded source packages are in
	'/tmp/th798/17266796/RtmpkUutdY/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 66.561   3.471  82.750 
> print(Sys.time())
[1] "2025-05-16 01:43:51 MST"
> downloaded_packages <- file.path(
+   tempdir(),
+   "downloaded_packages")
> dl.glob <- file.path(
+   downloaded_packages,
+   paste0(rev.dep,"_*.tar.gz"))
> rev.dep.dl.row <- cbind(rev.dep, Sys.glob(dl.glob))
> colnames(rev.dep.dl.row) <- c("pkg","path")
> rev.dep.release.tar.gz <- normalizePath(rev.dep.dl.row[,"path"], mustWork=TRUE)
> pkg.Rcheck <- paste0(rev.dep, ".Rcheck")
> 
> proj.dir <- "~/genomic-ml/data.table-revdeps"
> source(file.path(proj.dir, "myStatus.R"))
> Rvers <- gsub("[()]", "", gsub(" ", "_", R.version[["version.string"]]))
> dir.create(Rvers, showWarnings=FALSE)
> Rcheck.list <- list()
> for(dt.version.short in c("release", "master")){
+   dt.tar.gz <- cargs[[dt.version.short]]
+   dt.version <- gsub(".tar.gz|/.*?_", "", dt.tar.gz)
+   print(Sys.time())
+   install.packages(dt.tar.gz, repos=NULL)
+   print(Sys.time())
+   check.cmd <- get_check_cmd(rev.dep.release.tar.gz)
+   system(check.cmd)
+   print(Sys.time())
+   dest.Rcheck <- file.path(
+     Rvers,
+     paste0(dt.version, ".Rcheck"))
+   unlink(dest.Rcheck, recursive=TRUE)
+   file.rename(pkg.Rcheck, dest.Rcheck)
+   Rcheck.list[[dt.version]] <- file.path(dest.Rcheck, "00check.log")
+ }
[1] "2025-05-16 01:43:51 MST"
Installing package into '/tmp/th798/17266796/R-release/847/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** this is package 'data.table' version '1.17.2'
** package 'data.table' successfully unpacked and MD5 sums checked
** using staged installation
zlib 1.2.13 is available ok
* checking if R installation supports OpenMP without any extra hints... yes
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c assign.c -o assign.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c between.c -o between.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c bmerge.c -o bmerge.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c chmatch.c -o chmatch.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c cj.c -o cj.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c coalesce.c -o coalesce.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c dogroups.c -o dogroups.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fastmean.c -o fastmean.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fcast.c -o fcast.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fifelse.c -o fifelse.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fmelt.c -o fmelt.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c forder.c -o forder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frank.c -o frank.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fread.c -o fread.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c freadR.c -o freadR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c froll.c -o froll.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frollR.c -o frollR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c frolladaptive.c -o frolladaptive.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fsort.c -o fsort.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fwrite.c -o fwrite.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fwriteR.c -o fwriteR.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c gsumm.c -o gsumm.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c idatetime.c -o idatetime.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c ijoin.c -o ijoin.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c inrange.c -o inrange.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nafill.c -o nafill.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c negate.c -o negate.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nqrecreateindices.c -o nqrecreateindices.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c openmp-utils.c -o openmp-utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c programming.c -o programming.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c quickselect.c -o quickselect.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c rbindlist.c -o rbindlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c reorder.c -o reorder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c shift.c -o shift.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c snprintf.c -o snprintf.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c subset.c -o subset.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c transpose.c -o transpose.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c types.c -o types.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c uniqlist.c -o uniqlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c utils.c -o utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c vecseq.c -o vecseq.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c wrappers.c -o wrappers.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o data.table.so assign.o between.o bmerge.o chmatch.o cj.o coalesce.o dogroups.o fastmean.o fcast.o fifelse.o fmelt.o forder.o frank.o fread.o freadR.o froll.o frollR.o frolladaptive.o fsort.o fwrite.o fwriteR.o gsumm.o idatetime.o ijoin.o init.o inrange.o nafill.o negate.o nqrecreateindices.o openmp-utils.o programming.o quickselect.o rbindlist.o reorder.o shift.o snprintf.o subset.o transpose.o types.o uniqlist.o utils.o vecseq.o wrappers.o -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
PKG_CFLAGS = -fopenmp -I/home/th798/.conda/envs/emacs1/include
PKG_LIBS = -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
if [ "data.table.so" != "data_table.so" ]; then mv data.table.so data_table.so; fi
if [ "" != "Windows_NT" ] && [ `uname -s` = 'Darwin' ]; then install_name_tool -id data_table.so data_table.so; fi
installing to /tmp/th798/17266796/R-release/847/library/00LOCK-data.table/00new/data.table/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (data.table)
[1] "2025-05-16 01:44:19 MST"
* using log directory '/tmp/th798/17266796/R-release/847/mlr3learners.Rcheck'
* using R version 4.5.0 (2025-04-11)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Spack GCC) 12.2.0
    GNU Fortran (Spack GCC) 12.2.0
* running under: Red Hat Enterprise Linux 8.10 (Ootpa)
* using session charset: ASCII
* checking for file 'mlr3learners/DESCRIPTION' ... OK
* this is package 'mlr3learners' version '0.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package 'mlr3learners' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking examples ... OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'testthat.R'
 ERROR
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("mlr3learners")
  +   test_check("mlr3learners")
  + }
  Loading required package: mlr3
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.095425 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.095425 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.337575 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.337575 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  6 (5 variable)
  initial  value 10.530912 
  iter  10 value 8.568546
  final  value 8.568120 
  converged
  # weights:  6 (5 variable)
  initial  value 10.530912 
  iter  10 value 8.568546
  final  value 8.568120 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.764002 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.807897 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.807897 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.433973
  iter  10 value 32.433973
  final  value 32.433973 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.433973
  iter  10 value 32.433973
  final  value 32.433973 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  18 (10 variable)
  initial  value 17.514254 
  iter  10 value 14.200052
  iter  20 value 14.138291
  final  value 14.138290 
  converged
  # weights:  18 (10 variable)
  initial  value 17.514254 
  iter  10 value 14.200052
  iter  20 value 14.138291
  final  value 14.138290 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.730850
  final  value 28.715949 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -102.426 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       102.43  |proj g|=       6.7925
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       62.287  |proj g|=        0.6774
  At iterate     3  f =       62.243  |proj g|=       0.18866
  At iterate     4  f =       62.243  |proj g|=      0.024301
  At iterate     5  f =       62.243  |proj g|=    0.00026198
  At iterate     6  f =       62.243  |proj g|=    3.5896e-07
  
  iterations 6
  function evaluations 16
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.58957e-07
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -102.426 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       102.43  |proj g|=       6.7925
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       62.287  |proj g|=        0.6774
  At iterate     3  f =       62.243  |proj g|=       0.18866
  At iterate     4  f =       62.243  |proj g|=      0.024301
  At iterate     5  f =       62.243  |proj g|=    0.00026198
  At iterate     6  f =       62.243  |proj g|=    3.5896e-07
  
  iterations 6
  function evaluations 16
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.58957e-07
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -137.417 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       137.42  |proj g|=       7.1254
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       62.316  |proj g|=       0.69076
  At iterate     3  f =       62.244  |proj g|=       0.25096
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       62.243  |proj g|=      0.037089
  At iterate     5  f =       62.243  |proj g|=     0.0005338
  At iterate     6  f =       62.243  |proj g|=    1.1153e-06
  
  iterations 6
  function evaluations 16
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.1153e-06
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -137.417 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       137.42  |proj g|=       7.1254
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       62.316  |proj g|=       0.69076
  At iterate     3  f =       62.244  |proj g|=       0.25096
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       62.243  |proj g|=      0.037089
  At iterate     5  f =       62.243  |proj g|=     0.0005338
  At iterate     6  f =       62.243  |proj g|=    1.1153e-06
  
  iterations 6
  function evaluations 16
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.1153e-06
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -674.0514 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       674.05  |proj g|=       7.2811
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       63.729  |proj g|=       0.94575
  ys=-3.087e+01  -gs= 1.973e+01, BFGS update SKIPPED
  At iterate     3  f =        63.08  |proj g|=       0.85316
  At iterate     4  f =       62.272  |proj g|=       0.66915
  At iterate     5  f =       62.261  |proj g|=         1.418
  At iterate     6  f =       62.243  |proj g|=       0.13074
  At iterate     7  f =       62.243  |proj g|=     0.0096097
  At iterate     8  f =       62.243  |proj g|=    7.1669e-05
  At iterate     9  f =       62.243  |proj g|=    3.8924e-08
  
  iterations 9
  function evaluations 24
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.89239e-08
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.203931e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.916562 
    - variance bounds :  0.07203931 7.742276 
    - best initial criterion value(s) :  -1274.015 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         1274  |proj g|=       6.8779
  At iterate     1  f =       99.394  |proj g|=        2.9346
  At iterate     2  f =       62.491  |proj g|=        5.9978
  At iterate     3  f =       62.258  |proj g|=       0.65912
  At iterate     4  f =       62.244  |proj g|=       0.30302
  At iterate     5  f =       62.243  |proj g|=      0.022513
  At iterate     6  f =       62.243  |proj g|=     0.0003931
  At iterate     7  f =       62.243  |proj g|=    4.9906e-07
  
  iterations 7
  function evaluations 21
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.9906e-07
  final function value 62.2429
  
  F = 62.2429
  final  value 62.242903 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -355.764 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       355.76  |proj g|=       3.9349
  At iterate     1  f =       320.33  |proj g|=       0.28483
  At iterate     2  f =       319.11  |proj g|=       0.21435
  At iterate     3  f =       318.23  |proj g|=      0.026539
  At iterate     4  f =       318.22  |proj g|=      0.013548
  At iterate     5  f =       318.22  |proj g|=    0.00050042
  At iterate     6  f =       318.22  |proj g|=    9.0225e-06
  At iterate     7  f =       318.22  |proj g|=     6.147e-09
  
  iterations 7
  function evaluations 17
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 6.14702e-09
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -38629.64 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        38630  |proj g|=       570.18
  At iterate     1  f =       416.28  |proj g|=      0.075984
  At iterate     2  f =       323.97  |proj g|=       0.35459
  ys=-1.574e+02  -gs= 4.292e+01, BFGS update SKIPPED
  At iterate     3  f =       318.61  |proj g|=       0.21538
  At iterate     4  f =       318.22  |proj g|=     0.0024514
  At iterate     5  f =       318.22  |proj g|=    0.00053224
  At iterate     6  f =       318.22  |proj g|=    1.7838e-06
  At iterate     7  f =       318.22  |proj g|=    1.2927e-09
  
  iterations 7
  function evaluations 36
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.29265e-09
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -1765.816 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1765.8  |proj g|=        36.98
  At iterate     1  f =        332.4  |proj g|=       0.35882
  At iterate     2  f =       319.54  |proj g|=       0.24581
  At iterate     3  f =       318.51  |proj g|=       0.18089
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.37  |proj g|=       0.12514
  At iterate     5  f =       318.23  |proj g|=      0.020272
  At iterate     6  f =       318.22  |proj g|=     0.0027738
  At iterate     7  f =       318.22  |proj g|=    7.3612e-05
  At iterate     8  f =       318.22  |proj g|=    2.7641e-07
  
  iterations 8
  function evaluations 16
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.76412e-07
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -270.5591 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       270.56  |proj g|=       2.9968
  At iterate     1  f =       259.12  |proj g|=        1.7856
  At iterate     2  f =       249.97  |proj g|=        6.4706
  At iterate     3  f =       249.32  |proj g|=        1.4468
  At iterate     4  f =       249.23  |proj g|=        0.2317
  At iterate     5  f =       249.23  |proj g|=       0.23214
  At iterate     6  f =       249.23  |proj g|=       0.38697
  At iterate     7  f =       249.23  |proj g|=        1.0606
  At iterate     8  f =       249.23  |proj g|=        1.6985
  At iterate     9  f =       249.23  |proj g|=        1.6992
  At iterate    10  f =       249.22  |proj g|=        1.7002
  At iterate    11  f =        249.2  |proj g|=        1.7019
  At iterate    12  f =       249.15  |proj g|=        1.7049
  At iterate    13  f =          249  |proj g|=        1.7103
  At iterate    14  f =       248.61  |proj g|=        2.1541
  At iterate    15  f =       247.54  |proj g|=        1.7423
  At iterate    16  f =       246.52  |proj g|=        1.7594
  At iterate    17  f =       245.38  |proj g|=        1.7521
  At iterate    18  f =        245.3  |proj g|=        1.6575
  At iterate    19  f =       244.87  |proj g|=         1.736
  At iterate    20  f =       244.78  |proj g|=        1.7398
  At iterate    21  f =       243.92  |proj g|=        1.7369
  At iterate    22  f =       243.29  |proj g|=        1.2632
  At iterate    23  f =       243.28  |proj g|=        1.7276
  At iterate    24  f =       243.26  |proj g|=       0.20283
  At iterate    25  f =       243.26  |proj g|=      0.050785
  At iterate    26  f =       243.26  |proj g|=    0.00094883
  At iterate    27  f =       243.26  |proj g|=    0.00011095
  
  iterations 27
  function evaluations 36
  segments explored during Cauchy searches 29
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000110948
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -779.8272 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       779.83  |proj g|=       7.2044
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =       66.504  |proj g|=       0.88331
  ys=-7.765e+00  -gs= 1.997e+01, BFGS update SKIPPED
  At iterate     3  f =       66.421  |proj g|=        0.8593
  At iterate     4  f =        66.26  |proj g|=        1.8444
  At iterate     5  f =       66.223  |proj g|=       0.45698
  At iterate     6  f =        66.22  |proj g|=      0.050241
  At iterate     7  f =        66.22  |proj g|=     0.0015872
  At iterate     8  f =        66.22  |proj g|=    5.3015e-06
  
  iterations 8
  function evaluations 26
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.30151e-06
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -779.8272 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       779.83  |proj g|=       7.2044
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =       66.504  |proj g|=       0.88331
  ys=-7.765e+00  -gs= 1.997e+01, BFGS update SKIPPED
  At iterate     3  f =       66.421  |proj g|=        0.8593
  At iterate     4  f =        66.26  |proj g|=        1.8444
  At iterate     5  f =       66.223  |proj g|=       0.45698
  At iterate     6  f =        66.22  |proj g|=      0.050241
  At iterate     7  f =        66.22  |proj g|=     0.0015872
  At iterate     8  f =        66.22  |proj g|=    5.3015e-06
  
  iterations 8
  function evaluations 26
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.30151e-06
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -815.385 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       815.39  |proj g|=       7.7715
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =       67.147  |proj g|=        1.0181
  ys=-2.178e+01  -gs= 1.961e+01, BFGS update SKIPPED
  At iterate     3  f =       66.543  |proj g|=       0.89351
  At iterate     4  f =       66.221  |proj g|=       0.31233
  At iterate     5  f =        66.22  |proj g|=       0.12675
  At iterate     6  f =        66.22  |proj g|=     0.0026627
  At iterate     7  f =        66.22  |proj g|=    2.2121e-05
  
  iterations 7
  function evaluations 25
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.21214e-05
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -815.385 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       815.39  |proj g|=       7.7715
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =       67.147  |proj g|=        1.0181
  ys=-2.178e+01  -gs= 1.961e+01, BFGS update SKIPPED
  At iterate     3  f =       66.543  |proj g|=       0.89351
  At iterate     4  f =       66.221  |proj g|=       0.31233
  At iterate     5  f =        66.22  |proj g|=       0.12675
  At iterate     6  f =        66.22  |proj g|=     0.0026627
  At iterate     7  f =        66.22  |proj g|=    2.2121e-05
  
  iterations 7
  function evaluations 25
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.21214e-05
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -2237.103 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       2237.1  |proj g|=       7.5707
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =        66.23  |proj g|=       0.76928
  At iterate     3  f =        66.22  |proj g|=       0.06417
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =        66.22  |proj g|=     0.0028313
  At iterate     5  f =        66.22  |proj g|=    1.2098e-05
  
  iterations 5
  function evaluations 20
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.20978e-05
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.446094e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.953603 
    - variance bounds :  0.08285841 8.446094 
    - best initial criterion value(s) :  -222.0419 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       222.04  |proj g|=       7.2313
  At iterate     1  f =       101.74  |proj g|=        2.6699
  At iterate     2  f =       68.371  |proj g|=        1.2096
  ys=-3.066e+01  -gs= 1.910e+01, BFGS update SKIPPED
  At iterate     3  f =        66.22  |proj g|=     0.0054038
  At iterate     4  f =        66.22  |proj g|=    6.0529e-07
  At iterate     5  f =        66.22  |proj g|=    2.1669e-10
  
  iterations 5
  function evaluations 22
  segments explored during Cauchy searches 8
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.16694e-10
  final function value 66.2198
  
  F = 66.2198
  final  value 66.219833 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -307.8548 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       307.85  |proj g|=       7.1327
  At iterate     1  f =       264.95  |proj g|=        1.8506
  At iterate     2  f =       263.39  |proj g|=         1.848
  At iterate     3  f =       260.58  |proj g|=        1.8395
  At iterate     4  f =       260.07  |proj g|=        1.8359
  At iterate     5  f =       259.94  |proj g|=        1.6462
  At iterate     6  f =       258.51  |proj g|=         2.176
  At iterate     7  f =       258.36  |proj g|=        3.8718
  At iterate     8  f =       255.14  |proj g|=        6.8721
  At iterate     9  f =       254.18  |proj g|=         8.119
  At iterate    10  f =       246.13  |proj g|=        4.7006
  At iterate    11  f =       245.71  |proj g|=        1.6477
  At iterate    12  f =        245.2  |proj g|=        1.9236
  At iterate    13  f =       245.11  |proj g|=       0.41668
  At iterate    14  f =        245.1  |proj g|=       0.22301
  At iterate    15  f =        245.1  |proj g|=       0.22425
  At iterate    16  f =        245.1  |proj g|=       0.22466
  At iterate    17  f =        245.1  |proj g|=       0.97571
  At iterate    18  f =       245.09  |proj g|=        1.7134
  At iterate    19  f =       245.08  |proj g|=        1.1888
  At iterate    20  f =       245.07  |proj g|=        1.8133
  At iterate    21  f =       245.04  |proj g|=        2.3836
  At iterate    22  f =       244.91  |proj g|=        3.9515
  At iterate    23  f =       244.61  |proj g|=        5.7492
  At iterate    24  f =       244.02  |proj g|=        7.1677
  At iterate    25  f =        243.6  |proj g|=        4.9903
  At iterate    26  f =       243.52  |proj g|=         6.046
  At iterate    27  f =       243.27  |proj g|=       0.60864
  At iterate    28  f =       243.26  |proj g|=      0.068743
  At iterate    29  f =       243.26  |proj g|=     0.0035857
  At iterate    30  f =       243.26  |proj g|=    0.00022292
  
  iterations 30
  function evaluations 41
  segments explored during Cauchy searches 32
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00022292
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -223738.7 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   2.2374e+05  |proj g|=       571.95
  At iterate     1  f =       416.28  |proj g|=      0.075984
  At iterate     2  f =       326.13  |proj g|=       0.36549
  ys=-1.618e+02  -gs= 4.246e+01, BFGS update SKIPPED
  At iterate     3  f =       318.45  |proj g|=       0.12275
  At iterate     4  f =       318.22  |proj g|=      0.014005
  At iterate     5  f =       318.22  |proj g|=     0.0030673
  At iterate     6  f =       318.22  |proj g|=    5.9546e-05
  At iterate     7  f =       318.22  |proj g|=    2.4718e-07
  
  iterations 7
  function evaluations 36
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.47179e-07
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/17266796/R-release/847/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-16 01:46:33 MST"
[1] "2025-05-16 01:46:33 MST"
Installing package into '/tmp/th798/17266796/R-release/847/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** this is package 'data.table' version '1.17.99'
** using staged installation
zlib 1.2.13 is available ok
* checking if R installation supports OpenMP without any extra hints... yes
** libs
using C compiler: 'gcc (Spack GCC) 12.2.0'
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c assign.c -o assign.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c between.c -o between.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c bmerge.c -o bmerge.o
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/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c coalesce.c -o coalesce.o
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/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fifelse.c -o fifelse.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c fmelt.c -o fmelt.o
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/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c init.c -o init.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c inrange.c -o inrange.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nafill.c -o nafill.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c negate.c -o negate.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c nqrecreateindices.c -o nqrecreateindices.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c openmp-utils.c -o openmp-utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c programming.c -o programming.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c quickselect.c -o quickselect.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c rbindlist.c -o rbindlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c reorder.c -o reorder.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c shift.c -o shift.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c snprintf.c -o snprintf.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c subset.c -o subset.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c transpose.c -o transpose.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c types.c -o types.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c uniqlist.c -o uniqlist.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c utils.c -o utils.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c vecseq.c -o vecseq.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-release/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c wrappers.c -o wrappers.o
/packages/gcc/12.2.0-nnbserq/bin/gcc -shared -L/home/th798/.conda/envs/emacs1/lib -Wl,-rpath=/home/th798/.conda/envs/emacs1/lib -L/home/th798/lib -Wl,-rpath=/home/th798/lib -L/home/th798/lib64 -Wl,-rpath=/home/th798/lib64 -o data.table.so assign.o between.o bmerge.o chmatch.o cj.o coalesce.o dogroups.o fastmean.o fcast.o fifelse.o fmelt.o forder.o frank.o fread.o freadR.o froll.o frollR.o frolladaptive.o fsort.o fwrite.o fwriteR.o gsumm.o idatetime.o ijoin.o init.o inrange.o nafill.o negate.o nqrecreateindices.o openmp-utils.o programming.o quickselect.o rbindlist.o reorder.o shift.o snprintf.o subset.o transpose.o types.o uniqlist.o utils.o vecseq.o wrappers.o -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
PKG_CFLAGS = -fopenmp -I/home/th798/.conda/envs/emacs1/include
PKG_LIBS = -fopenmp -L/home/th798/.conda/envs/emacs1/lib -lz
if [ "data.table.so" != "data_table.so" ]; then mv data.table.so data_table.so; fi
if [ "" != "Windows_NT" ] && [ `uname -s` = 'Darwin' ]; then install_name_tool -id data_table.so data_table.so; fi
installing to /tmp/th798/17266796/R-release/847/library/00LOCK-data.table/00new/data.table/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (data.table)
[1] "2025-05-16 01:46:56 MST"
* using log directory '/tmp/th798/17266796/R-release/847/mlr3learners.Rcheck'
* using R version 4.5.0 (2025-04-11)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Spack GCC) 12.2.0
    GNU Fortran (Spack GCC) 12.2.0
* running under: Red Hat Enterprise Linux 8.10 (Ootpa)
* using session charset: ASCII
* checking for file 'mlr3learners/DESCRIPTION' ... OK
* this is package 'mlr3learners' version '0.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package 'mlr3learners' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking examples ... OK
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'testthat.R'
 ERROR
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("mlr3learners")
  +   test_check("mlr3learners")
  + }
  Loading required package: mlr3
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.391705 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.391705 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.541703 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.541703 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  6 (5 variable)
  initial  value 11.411563 
  iter  10 value 10.625300
  iter  10 value 10.625300
  iter  10 value 10.625300
  final  value 10.625300 
  converged
  # weights:  6 (5 variable)
  initial  value 11.411563 
  iter  10 value 10.625300
  iter  10 value 10.625300
  iter  10 value 10.625300
  final  value 10.625300 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 19.844829 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.884179 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.884179 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.553033
  iter  10 value 32.553033
  final  value 32.553033 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.553033
  iter  10 value 32.553033
  final  value 32.553033 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.312711 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.312711 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  18 (10 variable)
  initial  value 17.184021 
  iter  10 value 16.113683
  iter  20 value 16.106118
  iter  20 value 16.106118
  iter  20 value 16.106118
  final  value 16.106118 
  converged
  # weights:  18 (10 variable)
  initial  value 17.184021 
  iter  10 value 16.113683
  iter  20 value 16.106118
  iter  20 value 16.106118
  iter  20 value 16.106118
  final  value 16.106118 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.987793
  final  value 29.979298 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -47838.29 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        47838  |proj g|=       7.9214
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       66.786  |proj g|=       0.98026
  ys=-1.937e+01  -gs= 1.969e+01, BFGS update SKIPPED
  At iterate     3  f =       66.249  |proj g|=       0.85952
  At iterate     4  f =       66.039  |proj g|=       0.76573
  At iterate     5  f =       66.028  |proj g|=       0.31883
  At iterate     6  f =       66.026  |proj g|=      0.020208
  At iterate     7  f =       66.026  |proj g|=    0.00041323
  At iterate     8  f =       66.026  |proj g|=    5.4961e-07
  
  iterations 8
  function evaluations 28
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.49611e-07
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -47838.29 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        47838  |proj g|=       7.9214
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       66.786  |proj g|=       0.98026
  ys=-1.937e+01  -gs= 1.969e+01, BFGS update SKIPPED
  At iterate     3  f =       66.249  |proj g|=       0.85952
  At iterate     4  f =       66.039  |proj g|=       0.76573
  At iterate     5  f =       66.028  |proj g|=       0.31883
  At iterate     6  f =       66.026  |proj g|=      0.020208
  At iterate     7  f =       66.026  |proj g|=    0.00041323
  At iterate     8  f =       66.026  |proj g|=    5.4961e-07
  
  iterations 8
  function evaluations 28
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.49611e-07
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -1778.239 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1778.2  |proj g|=       7.6806
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       66.586  |proj g|=       0.94079
  ys=-1.562e+01  -gs= 1.980e+01, BFGS update SKIPPED
  At iterate     3  f =       66.149  |proj g|=       0.82657
  At iterate     4  f =        66.08  |proj g|=        2.1775
  At iterate     5  f =       66.028  |proj g|=       0.40108
  At iterate     6  f =       66.026  |proj g|=      0.050288
  At iterate     7  f =       66.026  |proj g|=     0.0013764
  At iterate     8  f =       66.026  |proj g|=    4.5665e-06
  
  iterations 8
  function evaluations 27
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.56649e-06
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -1778.239 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1778.2  |proj g|=       7.6806
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       66.586  |proj g|=       0.94079
  ys=-1.562e+01  -gs= 1.980e+01, BFGS update SKIPPED
  At iterate     3  f =       66.149  |proj g|=       0.82657
  At iterate     4  f =        66.08  |proj g|=        2.1775
  At iterate     5  f =       66.028  |proj g|=       0.40108
  At iterate     6  f =       66.026  |proj g|=      0.050288
  At iterate     7  f =       66.026  |proj g|=     0.0013764
  At iterate     8  f =       66.026  |proj g|=    4.5665e-06
  
  iterations 8
  function evaluations 27
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.56649e-06
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -5112.41 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       5112.4  |proj g|=       7.3301
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       67.908  |proj g|=        1.1616
  ys=-2.951e+01  -gs= 1.920e+01, BFGS update SKIPPED
  At iterate     3  f =       67.136  |proj g|=        1.0418
  At iterate     4  f =       66.047  |proj g|=       0.77388
  At iterate     5  f =       66.026  |proj g|=      0.096131
  At iterate     6  f =       66.026  |proj g|=     0.0083118
  At iterate     7  f =       66.026  |proj g|=    5.2883e-05
  At iterate     8  f =       66.026  |proj g|=    2.8862e-08
  
  iterations 8
  function evaluations 31
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.88617e-08
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.380925e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.961949 
    - variance bounds :  0.08193392 8.380925 
    - best initial criterion value(s) :  -938602.3 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=    9.386e+05  |proj g|=       7.6415
  At iterate     1  f =       101.55  |proj g|=        2.6906
  At iterate     2  f =       67.378  |proj g|=        1.0811
  ys=-2.616e+01  -gs= 1.942e+01, BFGS update SKIPPED
  At iterate     3  f =       66.853  |proj g|=       0.99266
  At iterate     4  f =       66.054  |proj g|=       0.77942
  At iterate     5  f =       66.043  |proj g|=        1.1777
  At iterate     6  f =       66.026  |proj g|=       0.10641
  At iterate     7  f =       66.026  |proj g|=      0.007577
  At iterate     8  f =       66.026  |proj g|=     5.348e-05
  At iterate     9  f =       66.026  |proj g|=    2.6642e-08
  
  iterations 9
  function evaluations 36
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.66418e-08
  final function value 66.0262
  
  F = 66.0262
  final  value 66.026189 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -306.6687 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       306.67  |proj g|=       1.4461
  At iterate     1  f =       300.96  |proj g|=         44.16
  At iterate     2  f =       294.31  |proj g|=        44.143
  At iterate     3  f =       286.42  |proj g|=        44.054
  At iterate     4  f =       284.15  |proj g|=       0.53361
  At iterate     5  f =       277.11  |proj g|=        43.848
  At iterate     6  f =       273.75  |proj g|=        43.808
  At iterate     7  f =       252.98  |proj g|=        22.655
  At iterate     8  f =       251.15  |proj g|=        1.5922
  At iterate     9  f =       250.44  |proj g|=        1.8193
  At iterate    10  f =       248.21  |proj g|=        2.6031
  At iterate    11  f =       248.14  |proj g|=       0.37117
  At iterate    12  f =       248.13  |proj g|=       0.52204
  At iterate    13  f =       248.13  |proj g|=       0.54444
  At iterate    14  f =       248.13  |proj g|=        1.1417
  At iterate    15  f =       248.12  |proj g|=        1.7012
  At iterate    16  f =        248.1  |proj g|=        1.7008
  At iterate    17  f =       248.04  |proj g|=        2.7484
  At iterate    18  f =          248  |proj g|=        4.4433
  At iterate    19  f =       247.83  |proj g|=        5.7716
  At iterate    20  f =       247.09  |proj g|=        9.3284
  At iterate    21  f =       245.79  |proj g|=        13.291
  At iterate    22  f =       244.79  |proj g|=        10.437
  At iterate    23  f =       243.98  |proj g|=        1.7406
  At iterate    24  f =       243.27  |proj g|=        0.3078
  At iterate    25  f =       243.27  |proj g|=        1.5143
  At iterate    26  f =       243.26  |proj g|=       0.15254
  At iterate    27  f =       243.26  |proj g|=       0.11076
  At iterate    28  f =       243.26  |proj g|=     0.0014392
  At iterate    29  f =       243.26  |proj g|=    1.3536e-05
  
  iterations 29
  function evaluations 33
  segments explored during Cauchy searches 31
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 1.35358e-05
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -1063.095 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1063.1  |proj g|=       23.465
  At iterate     1  f =        325.4  |proj g|=        0.3631
  At iterate     2  f =       319.99  |proj g|=       0.27039
  At iterate     3  f =       318.35  |proj g|=       0.11367
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.29  |proj g|=      0.082441
  At iterate     5  f =       318.22  |proj g|=     0.0095626
  At iterate     6  f =       318.22  |proj g|=    0.00092863
  At iterate     7  f =       318.22  |proj g|=    1.1868e-05
  At iterate     8  f =       318.22  |proj g|=    1.4967e-08
  
  iterations 8
  function evaluations 21
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.49674e-08
  final function value 318.222
  
  F = 318.222
  final  value 318.221782 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -319.7074 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       319.71  |proj g|=       9.9456
  At iterate     1  f =       296.61  |proj g|=         2.743
  At iterate     2  f =       282.96  |proj g|=        2.4363
  At iterate     3  f =       275.03  |proj g|=        1.8527
  At iterate     4  f =       268.33  |proj g|=        4.7597
  At iterate     5  f =       265.62  |proj g|=        1.8302
  At iterate     6  f =       264.79  |proj g|=        3.9809
  At iterate     7  f =        263.7  |proj g|=        1.8114
  At iterate     8  f =       258.95  |proj g|=        8.2488
  At iterate     9  f =       256.57  |proj g|=        16.365
  At iterate    10  f =       250.69  |proj g|=        1.7025
  At iterate    11  f =       250.57  |proj g|=       0.46233
  At iterate    12  f =       250.57  |proj g|=        0.2903
  At iterate    13  f =       250.57  |proj g|=       0.22198
  At iterate    14  f =       250.56  |proj g|=       0.22145
  At iterate    15  f =       250.55  |proj g|=       0.21991
  At iterate    16  f =        250.5  |proj g|=       0.38559
  At iterate    17  f =       250.39  |proj g|=       0.65827
  At iterate    18  f =        250.1  |proj g|=        1.5195
  At iterate    19  f =       249.34  |proj g|=        3.1419
  At iterate    20  f =       247.89  |proj g|=        4.6275
  At iterate    21  f =       246.94  |proj g|=        11.927
  At iterate    22  f =       245.31  |proj g|=        13.704
  At iterate    23  f =       243.53  |proj g|=        4.7115
  At iterate    24  f =       243.31  |proj g|=         1.368
  At iterate    25  f =       243.27  |proj g|=       0.15327
  At iterate    26  f =       243.26  |proj g|=        1.6632
  At iterate    27  f =       243.26  |proj g|=       0.15256
  At iterate    28  f =       243.26  |proj g|=       0.02056
  At iterate    29  f =       243.26  |proj g|=      0.022855
  
  iterations 29
  function evaluations 38
  segments explored during Cauchy searches 30
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0228551
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -277.8428 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       277.84  |proj g|=       3.3735
  At iterate     1  f =       262.87  |proj g|=        1.7855
  At iterate     2  f =       262.48  |proj g|=        1.7814
  At iterate     3  f =       252.69  |proj g|=        1.8953
  At iterate     4  f =        252.4  |proj g|=        3.3403
  At iterate     5  f =       252.34  |proj g|=       0.96018
  At iterate     6  f =        252.3  |proj g|=       0.20666
  At iterate     7  f =        252.3  |proj g|=       0.20653
  At iterate     8  f =        252.3  |proj g|=       0.20645
  At iterate     9  f =        252.3  |proj g|=       0.57348
  At iterate    10  f =        252.3  |proj g|=        1.1591
  At iterate    11  f =        252.3  |proj g|=        1.6893
  At iterate    12  f =       252.29  |proj g|=        1.3814
  At iterate    13  f =       252.28  |proj g|=        1.6923
  At iterate    14  f =       252.25  |proj g|=        1.6928
  At iterate    15  f =       252.02  |proj g|=        1.8596
  At iterate    16  f =       251.55  |proj g|=        1.9003
  At iterate    17  f =       250.24  |proj g|=        1.9384
  At iterate    18  f =       248.98  |proj g|=        1.8831
  At iterate    19  f =       246.12  |proj g|=        1.7339
  At iterate    20  f =       244.26  |proj g|=       0.89527
  At iterate    21  f =       244.03  |proj g|=         2.099
  At iterate    22  f =       243.52  |proj g|=        1.9615
  At iterate    23  f =       243.29  |proj g|=        1.3898
  At iterate    24  f =       243.27  |proj g|=       0.62454
  At iterate    25  f =       243.26  |proj g|=       0.14565
  At iterate    26  f =       243.26  |proj g|=       0.13482
  At iterate    27  f =       243.26  |proj g|=      0.060037
  At iterate    28  f =       243.26  |proj g|=    0.00070883
  
  iterations 28
  function evaluations 37
  segments explored during Cauchy searches 30
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000708832
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -309551.8 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   3.0955e+05  |proj g|=       8.3786
  At iterate     1  f =        103.3  |proj g|=        2.5088
  At iterate     2  f =       68.915  |proj g|=        1.1261
  ys=-2.424e+01  -gs= 1.951e+01, BFGS update SKIPPED
  At iterate     3  f =       68.246  |proj g|=       0.99196
  At iterate     4  f =       67.781  |proj g|=        0.5903
  At iterate     5  f =       67.777  |proj g|=       0.31537
  At iterate     6  f =       67.776  |proj g|=      0.013455
  At iterate     7  f =       67.775  |proj g|=     0.0002913
  At iterate     8  f =       67.775  |proj g|=    2.7653e-07
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.76534e-07
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -309551.8 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   3.0955e+05  |proj g|=       8.3786
  At iterate     1  f =        103.3  |proj g|=        2.5088
  At iterate     2  f =       68.915  |proj g|=        1.1261
  ys=-2.424e+01  -gs= 1.951e+01, BFGS update SKIPPED
  At iterate     3  f =       68.246  |proj g|=       0.99196
  At iterate     4  f =       67.781  |proj g|=        0.5903
  At iterate     5  f =       67.777  |proj g|=       0.31537
  At iterate     6  f =       67.776  |proj g|=      0.013455
  At iterate     7  f =       67.775  |proj g|=     0.0002913
  At iterate     8  f =       67.775  |proj g|=    2.7653e-07
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.76534e-07
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -71.33537 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       71.335  |proj g|=       1.0462
  At iterate     1  f =       69.695  |proj g|=        6.6997
  At iterate     2  f =       68.515  |proj g|=        1.0505
  At iterate     3  f =       67.817  |proj g|=       0.84895
  At iterate     4  f =       67.798  |proj g|=        1.2717
  At iterate     5  f =       67.776  |proj g|=       0.13924
  At iterate     6  f =       67.775  |proj g|=      0.011364
  At iterate     7  f =       67.775  |proj g|=    0.00011301
  At iterate     8  f =       67.775  |proj g|=    9.0592e-08
  
  iterations 8
  function evaluations 10
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 9.05925e-08
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -71.33537 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       71.335  |proj g|=       1.0462
  At iterate     1  f =       69.695  |proj g|=        6.6997
  At iterate     2  f =       68.515  |proj g|=        1.0505
  At iterate     3  f =       67.817  |proj g|=       0.84895
  At iterate     4  f =       67.798  |proj g|=        1.2717
  At iterate     5  f =       67.776  |proj g|=       0.13924
  At iterate     6  f =       67.775  |proj g|=      0.011364
  At iterate     7  f =       67.775  |proj g|=    0.00011301
  At iterate     8  f =       67.775  |proj g|=    9.0592e-08
  
  iterations 8
  function evaluations 10
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 9.05925e-08
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -3861.001 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         3861  |proj g|=       8.2762
  At iterate     1  f =        103.3  |proj g|=        2.5088
  At iterate     2  f =       69.934  |proj g|=         1.292
  ys=-3.068e+01  -gs= 1.910e+01, BFGS update SKIPPED
  At iterate     3  f =       67.776  |proj g|=      0.062918
  At iterate     4  f =       67.775  |proj g|=     8.872e-05
  At iterate     5  f =       67.775  |proj g|=    3.9556e-07
  
  iterations 5
  function evaluations 26
  segments explored during Cauchy searches 8
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.95557e-07
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.988362e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.740798 
    - variance bounds :  0.08452361 8.988362 
    - best initial criterion value(s) :  -121.9529 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       121.95  |proj g|=       8.0858
  At iterate     1  f =        103.3  |proj g|=        2.5088
  At iterate     2  f =       67.826  |proj g|=       0.85475
  At iterate     3  f =       67.776  |proj g|=       0.16462
  At iterate     4  f =       67.776  |proj g|=      0.022935
  At iterate     5  f =       67.775  |proj g|=    0.00026943
  At iterate     6  f =       67.775  |proj g|=    4.3458e-07
  
  iterations 6
  function evaluations 20
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 4.34577e-07
  final function value 67.7755
  
  F = 67.7755
  final  value 67.775498 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -291.0725 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       291.07  |proj g|=       22.717
  At iterate     1  f =        290.8  |proj g|=       0.63526
  At iterate     2  f =       289.97  |proj g|=       0.60768
  At iterate     3  f =       285.85  |proj g|=        43.937
  At iterate     4  f =       284.86  |proj g|=        43.908
  At iterate     5  f =       283.31  |proj g|=        43.852
  At iterate     6  f =          279  |proj g|=        43.735
  At iterate     7  f =        261.9  |proj g|=        25.551
  At iterate     8  f =       252.77  |proj g|=        9.8247
  At iterate     9  f =       251.72  |proj g|=        5.8967
  At iterate    10  f =       251.38  |proj g|=       0.21555
  At iterate    11  f =       251.38  |proj g|=       0.21508
  At iterate    12  f =       251.38  |proj g|=       0.21505
  At iterate    13  f =       251.38  |proj g|=       0.21492
  At iterate    14  f =       251.38  |proj g|=       0.21478
  At iterate    15  f =       251.37  |proj g|=       0.21452
  At iterate    16  f =       251.37  |proj g|=       0.32015
  At iterate    17  f =       251.35  |proj g|=       0.66113
  At iterate    18  f =       251.32  |proj g|=        1.0267
  At iterate    19  f =       251.22  |proj g|=         2.439
  At iterate    20  f =        251.2  |proj g|=        1.4138
  At iterate    21  f =       250.97  |proj g|=          3.18
  At iterate    22  f =       249.11  |proj g|=        7.3686
  At iterate    23  f =       246.88  |proj g|=        9.1278
  At iterate    24  f =       246.02  |proj g|=         8.552
  At iterate    25  f =       243.98  |proj g|=        7.6995
  At iterate    26  f =        243.5  |proj g|=        1.7387
  At iterate    27  f =       243.34  |proj g|=        1.4201
  At iterate    28  f =       243.27  |proj g|=       0.15279
  At iterate    29  f =       243.27  |proj g|=        1.7283
  At iterate    30  f =       243.26  |proj g|=      0.024592
  At iterate    31  f =       243.26  |proj g|=      0.001511
  
  iterations 31
  function evaluations 42
  segments explored during Cauchy searches 32
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00151099
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 3.435024e-07 
    - parameters lower bounds :  1e-10 1e-10 
    - parameters upper bounds :  1.880582 44.27959 
    - variance bounds :  3.435024 622.0591 
    - best initial criterion value(s) :  -267.3647 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       267.36  |proj g|=       3.1625
  At iterate     1  f =       258.61  |proj g|=        1.8021
  At iterate     2  f =       250.83  |proj g|=        9.2592
  At iterate     3  f =       250.67  |proj g|=        19.987
  At iterate     4  f =       247.43  |proj g|=        2.9896
  At iterate     5  f =       247.09  |proj g|=       0.24321
  At iterate     6  f =       247.09  |proj g|=       0.24059
  At iterate     7  f =       247.07  |proj g|=        1.7059
  At iterate     8  f =       246.83  |proj g|=        2.8534
  At iterate     9  f =       246.25  |proj g|=        6.4317
  At iterate    10  f =       244.86  |proj g|=         11.88
  At iterate    11  f =       244.37  |proj g|=        11.878
  At iterate    12  f =       243.41  |proj g|=        3.5478
  At iterate    13  f =       243.29  |proj g|=       0.55478
  At iterate    14  f =       243.26  |proj g|=       0.15255
  At iterate    15  f =       243.26  |proj g|=       0.16809
  At iterate    16  f =       243.26  |proj g|=      0.014126
  At iterate    17  f =       243.26  |proj g|=    0.00098104
  
  iterations 17
  function evaluations 25
  segments explored during Cauchy searches 19
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00098104
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/17266796/R-release/847/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-16 01:49:22 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_version_4.5.0_2025-04-11/release_1.17.2.Rcheck/00check.log	2025-05-16 01:46:33.619335513 -0700
+++ R_version_4.5.0_2025-04-11/master_1.17.99.9c54bd073decac61dbd284c7a22d65d0f719aa19.Rcheck/00check.log	2025-05-16 01:49:22.425241117 -0700
@@ -60,27 +60,27 @@
   Loading required package: mlr3
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.095425 
+  final  value 20.727699 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.095425 
+  final  value 20.727699 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.694248 
+  final  value 20.391705 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.694248 
+  final  value 20.391705 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.337575 
+  final  value 20.541703 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.337575 
+  final  value 20.541703 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
@@ -92,115 +92,123 @@
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  6 (5 variable)
-  initial  value 10.530912 
-  iter  10 value 8.568546
-  final  value 8.568120 
+  initial  value 11.411563 
+  iter  10 value 10.625300
+  iter  10 value 10.625300
+  iter  10 value 10.625300
+  final  value 10.625300 
   converged
   # weights:  6 (5 variable)
-  initial  value 10.530912 
-  iter  10 value 8.568546
-  final  value 8.568120 
+  initial  value 11.411563 
+  iter  10 value 10.625300
+  iter  10 value 10.625300
+  iter  10 value 10.625300
+  final  value 10.625300 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.764002 
+  final  value 19.844829 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.732830 
+  final  value 32.555658 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.732830 
+  final  value 32.555658 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.807897 
+  final  value 31.884179 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.807897 
+  final  value 31.884179 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 32.433973
-  iter  10 value 32.433973
-  final  value 32.433973 
+  iter  10 value 32.553033
+  iter  10 value 32.553033
+  final  value 32.553033 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 32.433973
-  iter  10 value 32.433973
-  final  value 32.433973 
+  iter  10 value 32.553033
+  iter  10 value 32.553033
+  final  value 32.553033 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.732830 
+  final  value 31.312711 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.732830 
+  final  value 31.312711 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  18 (10 variable)
-  initial  value 17.514254 
-  iter  10 value 14.200052
-  iter  20 value 14.138291
-  final  value 14.138290 
+  initial  value 17.184021 
+  iter  10 value 16.113683
+  iter  20 value 16.106118
+  iter  20 value 16.106118
+  iter  20 value 16.106118
+  final  value 16.106118 
   converged
   # weights:  18 (10 variable)
-  initial  value 17.514254 
-  iter  10 value 14.200052
-  iter  20 value 14.138291
-  final  value 14.138290 
+  initial  value 17.184021 
+  iter  10 value 16.113683
+  iter  20 value 16.106118
+  iter  20 value 16.106118
+  iter  20 value 16.106118
+  final  value 16.106118 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.730850
-  final  value 28.715949 
+  iter  10 value 29.987793
+  final  value 29.979298 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -309,32 +317,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -102.426 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -47838.29 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       102.43  |proj g|=       6.7925
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       62.287  |proj g|=        0.6774
-  At iterate     3  f =       62.243  |proj g|=       0.18866
-  At iterate     4  f =       62.243  |proj g|=      0.024301
-  At iterate     5  f =       62.243  |proj g|=    0.00026198
-  At iterate     6  f =       62.243  |proj g|=    3.5896e-07
+  At iterate     0  f=        47838  |proj g|=       7.9214
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       66.786  |proj g|=       0.98026
+  ys=-1.937e+01  -gs= 1.969e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.249  |proj g|=       0.85952
+  At iterate     4  f =       66.039  |proj g|=       0.76573
+  At iterate     5  f =       66.028  |proj g|=       0.31883
+  At iterate     6  f =       66.026  |proj g|=      0.020208
+  At iterate     7  f =       66.026  |proj g|=    0.00041323
+  At iterate     8  f =       66.026  |proj g|=    5.4961e-07
   
-  iterations 6
-  function evaluations 16
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 3.58957e-07
-  final function value 62.2429
+  iterations 8
+  function evaluations 28
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 5.49611e-07
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -345,32 +356,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -102.426 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -47838.29 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       102.43  |proj g|=       6.7925
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       62.287  |proj g|=        0.6774
-  At iterate     3  f =       62.243  |proj g|=       0.18866
-  At iterate     4  f =       62.243  |proj g|=      0.024301
-  At iterate     5  f =       62.243  |proj g|=    0.00026198
-  At iterate     6  f =       62.243  |proj g|=    3.5896e-07
+  At iterate     0  f=        47838  |proj g|=       7.9214
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       66.786  |proj g|=       0.98026
+  ys=-1.937e+01  -gs= 1.969e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.249  |proj g|=       0.85952
+  At iterate     4  f =       66.039  |proj g|=       0.76573
+  At iterate     5  f =       66.028  |proj g|=       0.31883
+  At iterate     6  f =       66.026  |proj g|=      0.020208
+  At iterate     7  f =       66.026  |proj g|=    0.00041323
+  At iterate     8  f =       66.026  |proj g|=    5.4961e-07
   
-  iterations 6
-  function evaluations 16
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 3.58957e-07
-  final function value 62.2429
+  iterations 8
+  function evaluations 28
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 5.49611e-07
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -381,34 +395,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -137.417 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -1778.239 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       137.42  |proj g|=       7.1254
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       62.316  |proj g|=       0.69076
-  At iterate     3  f =       62.244  |proj g|=       0.25096
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       62.243  |proj g|=      0.037089
-  At iterate     5  f =       62.243  |proj g|=     0.0005338
-  At iterate     6  f =       62.243  |proj g|=    1.1153e-06
+  At iterate     0  f=       1778.2  |proj g|=       7.6806
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       66.586  |proj g|=       0.94079
+  ys=-1.562e+01  -gs= 1.980e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.149  |proj g|=       0.82657
+  At iterate     4  f =        66.08  |proj g|=        2.1775
+  At iterate     5  f =       66.028  |proj g|=       0.40108
+  At iterate     6  f =       66.026  |proj g|=      0.050288
+  At iterate     7  f =       66.026  |proj g|=     0.0013764
+  At iterate     8  f =       66.026  |proj g|=    4.5665e-06
   
-  iterations 6
-  function evaluations 16
+  iterations 8
+  function evaluations 27
   segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.1153e-06
-  final function value 62.2429
+  norm of the final projected gradient 4.56649e-06
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -419,34 +434,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -137.417 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -1778.239 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       137.42  |proj g|=       7.1254
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       62.316  |proj g|=       0.69076
-  At iterate     3  f =       62.244  |proj g|=       0.25096
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       62.243  |proj g|=      0.037089
-  At iterate     5  f =       62.243  |proj g|=     0.0005338
-  At iterate     6  f =       62.243  |proj g|=    1.1153e-06
+  At iterate     0  f=       1778.2  |proj g|=       7.6806
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       66.586  |proj g|=       0.94079
+  ys=-1.562e+01  -gs= 1.980e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.149  |proj g|=       0.82657
+  At iterate     4  f =        66.08  |proj g|=        2.1775
+  At iterate     5  f =       66.028  |proj g|=       0.40108
+  At iterate     6  f =       66.026  |proj g|=      0.050288
+  At iterate     7  f =       66.026  |proj g|=     0.0013764
+  At iterate     8  f =       66.026  |proj g|=    4.5665e-06
   
-  iterations 6
-  function evaluations 16
+  iterations 8
+  function evaluations 27
   segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.1153e-06
-  final function value 62.2429
+  norm of the final projected gradient 4.56649e-06
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -457,36 +473,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -674.0514 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -5112.41 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       674.05  |proj g|=       7.2811
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       63.729  |proj g|=       0.94575
-  ys=-3.087e+01  -gs= 1.973e+01, BFGS update SKIPPED
-  At iterate     3  f =        63.08  |proj g|=       0.85316
-  At iterate     4  f =       62.272  |proj g|=       0.66915
-  At iterate     5  f =       62.261  |proj g|=         1.418
-  At iterate     6  f =       62.243  |proj g|=       0.13074
-  At iterate     7  f =       62.243  |proj g|=     0.0096097
-  At iterate     8  f =       62.243  |proj g|=    7.1669e-05
-  At iterate     9  f =       62.243  |proj g|=    3.8924e-08
+  At iterate     0  f=       5112.4  |proj g|=       7.3301
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       67.908  |proj g|=        1.1616
+  ys=-2.951e+01  -gs= 1.920e+01, BFGS update SKIPPED
+  At iterate     3  f =       67.136  |proj g|=        1.0418
+  At iterate     4  f =       66.047  |proj g|=       0.77388
+  At iterate     5  f =       66.026  |proj g|=      0.096131
+  At iterate     6  f =       66.026  |proj g|=     0.0083118
+  At iterate     7  f =       66.026  |proj g|=    5.2883e-05
+  At iterate     8  f =       66.026  |proj g|=    2.8862e-08
   
-  iterations 9
-  function evaluations 24
-  segments explored during Cauchy searches 12
+  iterations 8
+  function evaluations 31
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 3.89239e-08
-  final function value 62.2429
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 2.88617e-08
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -497,33 +512,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.203931e-09 
+    - nugget : 8.380925e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.916562 
-    - variance bounds :  0.07203931 7.742276 
-    - best initial criterion value(s) :  -1274.015 
+    - parameters upper bounds :  4 2 1.961949 
+    - variance bounds :  0.08193392 8.380925 
+    - best initial criterion value(s) :  -938602.3 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         1274  |proj g|=       6.8779
-  At iterate     1  f =       99.394  |proj g|=        2.9346
-  At iterate     2  f =       62.491  |proj g|=        5.9978
-  At iterate     3  f =       62.258  |proj g|=       0.65912
-  At iterate     4  f =       62.244  |proj g|=       0.30302
-  At iterate     5  f =       62.243  |proj g|=      0.022513
-  At iterate     6  f =       62.243  |proj g|=     0.0003931
-  At iterate     7  f =       62.243  |proj g|=    4.9906e-07
+  At iterate     0  f=    9.386e+05  |proj g|=       7.6415
+  At iterate     1  f =       101.55  |proj g|=        2.6906
+  At iterate     2  f =       67.378  |proj g|=        1.0811
+  ys=-2.616e+01  -gs= 1.942e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.853  |proj g|=       0.99266
+  At iterate     4  f =       66.054  |proj g|=       0.77942
+  At iterate     5  f =       66.043  |proj g|=        1.1777
+  At iterate     6  f =       66.026  |proj g|=       0.10641
+  At iterate     7  f =       66.026  |proj g|=      0.007577
+  At iterate     8  f =       66.026  |proj g|=     5.348e-05
+  At iterate     9  f =       66.026  |proj g|=    2.6642e-08
   
-  iterations 7
-  function evaluations 21
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 0
+  iterations 9
+  function evaluations 36
+  segments explored during Cauchy searches 12
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.9906e-07
-  final function value 62.2429
+  norm of the final projected gradient 2.66418e-08
+  final function value 66.0262
   
-  F = 62.2429
-  final  value 62.242903 
+  F = 66.0262
+  final  value 66.026189 
   converged
   
   optimisation start
@@ -538,29 +556,51 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -355.764 
+    - best initial criterion value(s) :  -306.6687 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       355.76  |proj g|=       3.9349
-  At iterate     1  f =       320.33  |proj g|=       0.28483
-  At iterate     2  f =       319.11  |proj g|=       0.21435
-  At iterate     3  f =       318.23  |proj g|=      0.026539
-  At iterate     4  f =       318.22  |proj g|=      0.013548
-  At iterate     5  f =       318.22  |proj g|=    0.00050042
-  At iterate     6  f =       318.22  |proj g|=    9.0225e-06
-  At iterate     7  f =       318.22  |proj g|=     6.147e-09
-  
-  iterations 7
-  function evaluations 17
-  segments explored during Cauchy searches 9
+  At iterate     0  f=       306.67  |proj g|=       1.4461
+  At iterate     1  f =       300.96  |proj g|=         44.16
+  At iterate     2  f =       294.31  |proj g|=        44.143
+  At iterate     3  f =       286.42  |proj g|=        44.054
+  At iterate     4  f =       284.15  |proj g|=       0.53361
+  At iterate     5  f =       277.11  |proj g|=        43.848
+  At iterate     6  f =       273.75  |proj g|=        43.808
+  At iterate     7  f =       252.98  |proj g|=        22.655
+  At iterate     8  f =       251.15  |proj g|=        1.5922
+  At iterate     9  f =       250.44  |proj g|=        1.8193
+  At iterate    10  f =       248.21  |proj g|=        2.6031
+  At iterate    11  f =       248.14  |proj g|=       0.37117
+  At iterate    12  f =       248.13  |proj g|=       0.52204
+  At iterate    13  f =       248.13  |proj g|=       0.54444
+  At iterate    14  f =       248.13  |proj g|=        1.1417
+  At iterate    15  f =       248.12  |proj g|=        1.7012
+  At iterate    16  f =        248.1  |proj g|=        1.7008
+  At iterate    17  f =       248.04  |proj g|=        2.7484
+  At iterate    18  f =          248  |proj g|=        4.4433
+  At iterate    19  f =       247.83  |proj g|=        5.7716
+  At iterate    20  f =       247.09  |proj g|=        9.3284
+  At iterate    21  f =       245.79  |proj g|=        13.291
+  At iterate    22  f =       244.79  |proj g|=        10.437
+  At iterate    23  f =       243.98  |proj g|=        1.7406
+  At iterate    24  f =       243.27  |proj g|=        0.3078
+  At iterate    25  f =       243.27  |proj g|=        1.5143
+  At iterate    26  f =       243.26  |proj g|=       0.15254
+  At iterate    27  f =       243.26  |proj g|=       0.11076
+  At iterate    28  f =       243.26  |proj g|=     0.0014392
+  At iterate    29  f =       243.26  |proj g|=    1.3536e-05
+  
+  iterations 29
+  function evaluations 33
+  segments explored during Cauchy searches 31
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 6.14702e-09
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 1.35358e-05
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -575,26 +615,28 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -38629.64 
+    - best initial criterion value(s) :  -1063.095 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        38630  |proj g|=       570.18
-  At iterate     1  f =       416.28  |proj g|=      0.075984
-  At iterate     2  f =       323.97  |proj g|=       0.35459
-  ys=-1.574e+02  -gs= 4.292e+01, BFGS update SKIPPED
-  At iterate     3  f =       318.61  |proj g|=       0.21538
-  At iterate     4  f =       318.22  |proj g|=     0.0024514
-  At iterate     5  f =       318.22  |proj g|=    0.00053224
-  At iterate     6  f =       318.22  |proj g|=    1.7838e-06
-  At iterate     7  f =       318.22  |proj g|=    1.2927e-09
+  At iterate     0  f=       1063.1  |proj g|=       23.465
+  At iterate     1  f =        325.4  |proj g|=        0.3631
+  At iterate     2  f =       319.99  |proj g|=       0.27039
+  At iterate     3  f =       318.35  |proj g|=       0.11367
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.29  |proj g|=      0.082441
+  At iterate     5  f =       318.22  |proj g|=     0.0095626
+  At iterate     6  f =       318.22  |proj g|=    0.00092863
+  At iterate     7  f =       318.22  |proj g|=    1.1868e-05
+  At iterate     8  f =       318.22  |proj g|=    1.4967e-08
   
-  iterations 7
-  function evaluations 36
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 1
+  iterations 8
+  function evaluations 21
+  segments explored during Cauchy searches 12
+  BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.29265e-09
+  norm of the final projected gradient 1.49674e-08
   final function value 318.222
   
   F = 318.222
@@ -613,32 +655,51 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -1765.816 
+    - best initial criterion value(s) :  -319.7074 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1765.8  |proj g|=        36.98
-  At iterate     1  f =        332.4  |proj g|=       0.35882
-  At iterate     2  f =       319.54  |proj g|=       0.24581
-  At iterate     3  f =       318.51  |proj g|=       0.18089
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.37  |proj g|=       0.12514
-  At iterate     5  f =       318.23  |proj g|=      0.020272
-  At iterate     6  f =       318.22  |proj g|=     0.0027738
-  At iterate     7  f =       318.22  |proj g|=    7.3612e-05
-  At iterate     8  f =       318.22  |proj g|=    2.7641e-07
-  
-  iterations 8
-  function evaluations 16
-  segments explored during Cauchy searches 12
+  At iterate     0  f=       319.71  |proj g|=       9.9456
+  At iterate     1  f =       296.61  |proj g|=         2.743
+  At iterate     2  f =       282.96  |proj g|=        2.4363
+  At iterate     3  f =       275.03  |proj g|=        1.8527
+  At iterate     4  f =       268.33  |proj g|=        4.7597
+  At iterate     5  f =       265.62  |proj g|=        1.8302
+  At iterate     6  f =       264.79  |proj g|=        3.9809
+  At iterate     7  f =        263.7  |proj g|=        1.8114
+  At iterate     8  f =       258.95  |proj g|=        8.2488
+  At iterate     9  f =       256.57  |proj g|=        16.365
+  At iterate    10  f =       250.69  |proj g|=        1.7025
+  At iterate    11  f =       250.57  |proj g|=       0.46233
+  At iterate    12  f =       250.57  |proj g|=        0.2903
+  At iterate    13  f =       250.57  |proj g|=       0.22198
+  At iterate    14  f =       250.56  |proj g|=       0.22145
+  At iterate    15  f =       250.55  |proj g|=       0.21991
+  At iterate    16  f =        250.5  |proj g|=       0.38559
+  At iterate    17  f =       250.39  |proj g|=       0.65827
+  At iterate    18  f =        250.1  |proj g|=        1.5195
+  At iterate    19  f =       249.34  |proj g|=        3.1419
+  At iterate    20  f =       247.89  |proj g|=        4.6275
+  At iterate    21  f =       246.94  |proj g|=        11.927
+  At iterate    22  f =       245.31  |proj g|=        13.704
+  At iterate    23  f =       243.53  |proj g|=        4.7115
+  At iterate    24  f =       243.31  |proj g|=         1.368
+  At iterate    25  f =       243.27  |proj g|=       0.15327
+  At iterate    26  f =       243.26  |proj g|=        1.6632
+  At iterate    27  f =       243.26  |proj g|=       0.15256
+  At iterate    28  f =       243.26  |proj g|=       0.02056
+  At iterate    29  f =       243.26  |proj g|=      0.022855
+  
+  iterations 29
+  function evaluations 38
+  segments explored during Cauchy searches 30
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 2.76412e-07
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.0228551
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -653,45 +714,46 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -270.5591 
+    - best initial criterion value(s) :  -277.8428 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       270.56  |proj g|=       2.9968
-  At iterate     1  f =       259.12  |proj g|=        1.7856
-  At iterate     2  f =       249.97  |proj g|=        6.4706
-  At iterate     3  f =       249.32  |proj g|=        1.4468
-  At iterate     4  f =       249.23  |proj g|=        0.2317
-  At iterate     5  f =       249.23  |proj g|=       0.23214
-  At iterate     6  f =       249.23  |proj g|=       0.38697
-  At iterate     7  f =       249.23  |proj g|=        1.0606
-  At iterate     8  f =       249.23  |proj g|=        1.6985
-  At iterate     9  f =       249.23  |proj g|=        1.6992
-  At iterate    10  f =       249.22  |proj g|=        1.7002
-  At iterate    11  f =        249.2  |proj g|=        1.7019
-  At iterate    12  f =       249.15  |proj g|=        1.7049
-  At iterate    13  f =          249  |proj g|=        1.7103
-  At iterate    14  f =       248.61  |proj g|=        2.1541
-  At iterate    15  f =       247.54  |proj g|=        1.7423
-  At iterate    16  f =       246.52  |proj g|=        1.7594
-  At iterate    17  f =       245.38  |proj g|=        1.7521
-  At iterate    18  f =        245.3  |proj g|=        1.6575
-  At iterate    19  f =       244.87  |proj g|=         1.736
-  At iterate    20  f =       244.78  |proj g|=        1.7398
-  At iterate    21  f =       243.92  |proj g|=        1.7369
-  At iterate    22  f =       243.29  |proj g|=        1.2632
-  At iterate    23  f =       243.28  |proj g|=        1.7276
-  At iterate    24  f =       243.26  |proj g|=       0.20283
-  At iterate    25  f =       243.26  |proj g|=      0.050785
-  At iterate    26  f =       243.26  |proj g|=    0.00094883
-  At iterate    27  f =       243.26  |proj g|=    0.00011095
-  
-  iterations 27
-  function evaluations 36
-  segments explored during Cauchy searches 29
+  At iterate     0  f=       277.84  |proj g|=       3.3735
+  At iterate     1  f =       262.87  |proj g|=        1.7855
+  At iterate     2  f =       262.48  |proj g|=        1.7814
+  At iterate     3  f =       252.69  |proj g|=        1.8953
+  At iterate     4  f =        252.4  |proj g|=        3.3403
+  At iterate     5  f =       252.34  |proj g|=       0.96018
+  At iterate     6  f =        252.3  |proj g|=       0.20666
+  At iterate     7  f =        252.3  |proj g|=       0.20653
+  At iterate     8  f =        252.3  |proj g|=       0.20645
+  At iterate     9  f =        252.3  |proj g|=       0.57348
+  At iterate    10  f =        252.3  |proj g|=        1.1591
+  At iterate    11  f =        252.3  |proj g|=        1.6893
+  At iterate    12  f =       252.29  |proj g|=        1.3814
+  At iterate    13  f =       252.28  |proj g|=        1.6923
+  At iterate    14  f =       252.25  |proj g|=        1.6928
+  At iterate    15  f =       252.02  |proj g|=        1.8596
+  At iterate    16  f =       251.55  |proj g|=        1.9003
+  At iterate    17  f =       250.24  |proj g|=        1.9384
+  At iterate    18  f =       248.98  |proj g|=        1.8831
+  At iterate    19  f =       246.12  |proj g|=        1.7339
+  At iterate    20  f =       244.26  |proj g|=       0.89527
+  At iterate    21  f =       244.03  |proj g|=         2.099
+  At iterate    22  f =       243.52  |proj g|=        1.9615
+  At iterate    23  f =       243.29  |proj g|=        1.3898
+  At iterate    24  f =       243.27  |proj g|=       0.62454
+  At iterate    25  f =       243.26  |proj g|=       0.14565
+  At iterate    26  f =       243.26  |proj g|=       0.13482
+  At iterate    27  f =       243.26  |proj g|=      0.060037
+  At iterate    28  f =       243.26  |proj g|=    0.00070883
+  
+  iterations 28
+  function evaluations 37
+  segments explored during Cauchy searches 30
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000110948
+  norm of the final projected gradient 0.000708832
   final function value 243.264
   
   F = 243.264
@@ -706,35 +768,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -779.8272 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -309551.8 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       779.83  |proj g|=       7.2044
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =       66.504  |proj g|=       0.88331
-  ys=-7.765e+00  -gs= 1.997e+01, BFGS update SKIPPED
-  At iterate     3  f =       66.421  |proj g|=        0.8593
-  At iterate     4  f =        66.26  |proj g|=        1.8444
-  At iterate     5  f =       66.223  |proj g|=       0.45698
-  At iterate     6  f =        66.22  |proj g|=      0.050241
-  At iterate     7  f =        66.22  |proj g|=     0.0015872
-  At iterate     8  f =        66.22  |proj g|=    5.3015e-06
+  At iterate     0  f=   3.0955e+05  |proj g|=       8.3786
+  At iterate     1  f =        103.3  |proj g|=        2.5088
+  At iterate     2  f =       68.915  |proj g|=        1.1261
+  ys=-2.424e+01  -gs= 1.951e+01, BFGS update SKIPPED
+  At iterate     3  f =       68.246  |proj g|=       0.99196
+  At iterate     4  f =       67.781  |proj g|=        0.5903
+  At iterate     5  f =       67.777  |proj g|=       0.31537
+  At iterate     6  f =       67.776  |proj g|=      0.013455
+  At iterate     7  f =       67.775  |proj g|=     0.0002913
+  At iterate     8  f =       67.775  |proj g|=    2.7653e-07
   
   iterations 8
-  function evaluations 26
+  function evaluations 34
   segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 5.30151e-06
-  final function value 66.2198
+  norm of the final projected gradient 2.76534e-07
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -745,35 +807,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -779.8272 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -309551.8 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       779.83  |proj g|=       7.2044
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =       66.504  |proj g|=       0.88331
-  ys=-7.765e+00  -gs= 1.997e+01, BFGS update SKIPPED
-  At iterate     3  f =       66.421  |proj g|=        0.8593
-  At iterate     4  f =        66.26  |proj g|=        1.8444
-  At iterate     5  f =       66.223  |proj g|=       0.45698
-  At iterate     6  f =        66.22  |proj g|=      0.050241
-  At iterate     7  f =        66.22  |proj g|=     0.0015872
-  At iterate     8  f =        66.22  |proj g|=    5.3015e-06
+  At iterate     0  f=   3.0955e+05  |proj g|=       8.3786
+  At iterate     1  f =        103.3  |proj g|=        2.5088
+  At iterate     2  f =       68.915  |proj g|=        1.1261
+  ys=-2.424e+01  -gs= 1.951e+01, BFGS update SKIPPED
+  At iterate     3  f =       68.246  |proj g|=       0.99196
+  At iterate     4  f =       67.781  |proj g|=        0.5903
+  At iterate     5  f =       67.777  |proj g|=       0.31537
+  At iterate     6  f =       67.776  |proj g|=      0.013455
+  At iterate     7  f =       67.775  |proj g|=     0.0002913
+  At iterate     8  f =       67.775  |proj g|=    2.7653e-07
   
   iterations 8
-  function evaluations 26
+  function evaluations 34
   segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 5.30151e-06
-  final function value 66.2198
+  norm of the final projected gradient 2.76534e-07
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -784,34 +846,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -815.385 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -71.33537 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       815.39  |proj g|=       7.7715
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =       67.147  |proj g|=        1.0181
-  ys=-2.178e+01  -gs= 1.961e+01, BFGS update SKIPPED
-  At iterate     3  f =       66.543  |proj g|=       0.89351
-  At iterate     4  f =       66.221  |proj g|=       0.31233
-  At iterate     5  f =        66.22  |proj g|=       0.12675
-  At iterate     6  f =        66.22  |proj g|=     0.0026627
-  At iterate     7  f =        66.22  |proj g|=    2.2121e-05
+  At iterate     0  f=       71.335  |proj g|=       1.0462
+  At iterate     1  f =       69.695  |proj g|=        6.6997
+  At iterate     2  f =       68.515  |proj g|=        1.0505
+  At iterate     3  f =       67.817  |proj g|=       0.84895
+  At iterate     4  f =       67.798  |proj g|=        1.2717
+  At iterate     5  f =       67.776  |proj g|=       0.13924
+  At iterate     6  f =       67.775  |proj g|=      0.011364
+  At iterate     7  f =       67.775  |proj g|=    0.00011301
+  At iterate     8  f =       67.775  |proj g|=    9.0592e-08
   
-  iterations 7
-  function evaluations 25
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.21214e-05
-  final function value 66.2198
+  iterations 8
+  function evaluations 10
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 9.05925e-08
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -822,34 +884,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -815.385 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -71.33537 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       815.39  |proj g|=       7.7715
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =       67.147  |proj g|=        1.0181
-  ys=-2.178e+01  -gs= 1.961e+01, BFGS update SKIPPED
-  At iterate     3  f =       66.543  |proj g|=       0.89351
-  At iterate     4  f =       66.221  |proj g|=       0.31233
-  At iterate     5  f =        66.22  |proj g|=       0.12675
-  At iterate     6  f =        66.22  |proj g|=     0.0026627
-  At iterate     7  f =        66.22  |proj g|=    2.2121e-05
+  At iterate     0  f=       71.335  |proj g|=       1.0462
+  At iterate     1  f =       69.695  |proj g|=        6.6997
+  At iterate     2  f =       68.515  |proj g|=        1.0505
+  At iterate     3  f =       67.817  |proj g|=       0.84895
+  At iterate     4  f =       67.798  |proj g|=        1.2717
+  At iterate     5  f =       67.776  |proj g|=       0.13924
+  At iterate     6  f =       67.775  |proj g|=      0.011364
+  At iterate     7  f =       67.775  |proj g|=    0.00011301
+  At iterate     8  f =       67.775  |proj g|=    9.0592e-08
   
-  iterations 7
-  function evaluations 25
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.21214e-05
-  final function value 66.2198
+  iterations 8
+  function evaluations 10
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 9.05925e-08
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -860,33 +922,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -2237.103 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -3861.001 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       2237.1  |proj g|=       7.5707
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =        66.23  |proj g|=       0.76928
-  At iterate     3  f =        66.22  |proj g|=       0.06417
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =        66.22  |proj g|=     0.0028313
-  At iterate     5  f =        66.22  |proj g|=    1.2098e-05
+  At iterate     0  f=         3861  |proj g|=       8.2762
+  At iterate     1  f =        103.3  |proj g|=        2.5088
+  At iterate     2  f =       69.934  |proj g|=         1.292
+  ys=-3.068e+01  -gs= 1.910e+01, BFGS update SKIPPED
+  At iterate     3  f =       67.776  |proj g|=      0.062918
+  At iterate     4  f =       67.775  |proj g|=     8.872e-05
+  At iterate     5  f =       67.775  |proj g|=    3.9556e-07
   
   iterations 5
-  function evaluations 20
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.20978e-05
-  final function value 66.2198
+  function evaluations 26
+  segments explored during Cauchy searches 8
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 3.95557e-07
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -897,32 +958,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.446094e-09 
+    - nugget : 8.988362e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.953603 
-    - variance bounds :  0.08285841 8.446094 
-    - best initial criterion value(s) :  -222.0419 
+    - parameters upper bounds :  4 2 1.740798 
+    - variance bounds :  0.08452361 8.988362 
+    - best initial criterion value(s) :  -121.9529 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       222.04  |proj g|=       7.2313
-  At iterate     1  f =       101.74  |proj g|=        2.6699
-  At iterate     2  f =       68.371  |proj g|=        1.2096
-  ys=-3.066e+01  -gs= 1.910e+01, BFGS update SKIPPED
-  At iterate     3  f =        66.22  |proj g|=     0.0054038
-  At iterate     4  f =        66.22  |proj g|=    6.0529e-07
-  At iterate     5  f =        66.22  |proj g|=    2.1669e-10
+  At iterate     0  f=       121.95  |proj g|=       8.0858
+  At iterate     1  f =        103.3  |proj g|=        2.5088
+  At iterate     2  f =       67.826  |proj g|=       0.85475
+  At iterate     3  f =       67.776  |proj g|=       0.16462
+  At iterate     4  f =       67.776  |proj g|=      0.022935
+  At iterate     5  f =       67.775  |proj g|=    0.00026943
+  At iterate     6  f =       67.775  |proj g|=    4.3458e-07
   
-  iterations 5
-  function evaluations 22
-  segments explored during Cauchy searches 8
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.16694e-10
-  final function value 66.2198
+  iterations 6
+  function evaluations 20
+  segments explored during Cauchy searches 10
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 4.34577e-07
+  final function value 67.7755
   
-  F = 66.2198
-  final  value 66.219833 
+  F = 67.7755
+  final  value 67.775498 
   converged
   
   optimisation start
@@ -937,48 +998,49 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -307.8548 
+    - best initial criterion value(s) :  -291.0725 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       307.85  |proj g|=       7.1327
-  At iterate     1  f =       264.95  |proj g|=        1.8506
-  At iterate     2  f =       263.39  |proj g|=         1.848
-  At iterate     3  f =       260.58  |proj g|=        1.8395
-  At iterate     4  f =       260.07  |proj g|=        1.8359
-  At iterate     5  f =       259.94  |proj g|=        1.6462
-  At iterate     6  f =       258.51  |proj g|=         2.176
-  At iterate     7  f =       258.36  |proj g|=        3.8718
-  At iterate     8  f =       255.14  |proj g|=        6.8721
-  At iterate     9  f =       254.18  |proj g|=         8.119
-  At iterate    10  f =       246.13  |proj g|=        4.7006
-  At iterate    11  f =       245.71  |proj g|=        1.6477
-  At iterate    12  f =        245.2  |proj g|=        1.9236
-  At iterate    13  f =       245.11  |proj g|=       0.41668
-  At iterate    14  f =        245.1  |proj g|=       0.22301
-  At iterate    15  f =        245.1  |proj g|=       0.22425
-  At iterate    16  f =        245.1  |proj g|=       0.22466
-  At iterate    17  f =        245.1  |proj g|=       0.97571
-  At iterate    18  f =       245.09  |proj g|=        1.7134
-  At iterate    19  f =       245.08  |proj g|=        1.1888
-  At iterate    20  f =       245.07  |proj g|=        1.8133
-  At iterate    21  f =       245.04  |proj g|=        2.3836
-  At iterate    22  f =       244.91  |proj g|=        3.9515
-  At iterate    23  f =       244.61  |proj g|=        5.7492
-  At iterate    24  f =       244.02  |proj g|=        7.1677
-  At iterate    25  f =        243.6  |proj g|=        4.9903
-  At iterate    26  f =       243.52  |proj g|=         6.046
-  At iterate    27  f =       243.27  |proj g|=       0.60864
-  At iterate    28  f =       243.26  |proj g|=      0.068743
-  At iterate    29  f =       243.26  |proj g|=     0.0035857
-  At iterate    30  f =       243.26  |proj g|=    0.00022292
+  At iterate     0  f=       291.07  |proj g|=       22.717
+  At iterate     1  f =        290.8  |proj g|=       0.63526
+  At iterate     2  f =       289.97  |proj g|=       0.60768
+  At iterate     3  f =       285.85  |proj g|=        43.937
+  At iterate     4  f =       284.86  |proj g|=        43.908
+  At iterate     5  f =       283.31  |proj g|=        43.852
+  At iterate     6  f =          279  |proj g|=        43.735
+  At iterate     7  f =        261.9  |proj g|=        25.551
+  At iterate     8  f =       252.77  |proj g|=        9.8247
+  At iterate     9  f =       251.72  |proj g|=        5.8967
+  At iterate    10  f =       251.38  |proj g|=       0.21555
+  At iterate    11  f =       251.38  |proj g|=       0.21508
+  At iterate    12  f =       251.38  |proj g|=       0.21505
+  At iterate    13  f =       251.38  |proj g|=       0.21492
+  At iterate    14  f =       251.38  |proj g|=       0.21478
+  At iterate    15  f =       251.37  |proj g|=       0.21452
+  At iterate    16  f =       251.37  |proj g|=       0.32015
+  At iterate    17  f =       251.35  |proj g|=       0.66113
+  At iterate    18  f =       251.32  |proj g|=        1.0267
+  At iterate    19  f =       251.22  |proj g|=         2.439
+  At iterate    20  f =        251.2  |proj g|=        1.4138
+  At iterate    21  f =       250.97  |proj g|=          3.18
+  At iterate    22  f =       249.11  |proj g|=        7.3686
+  At iterate    23  f =       246.88  |proj g|=        9.1278
+  At iterate    24  f =       246.02  |proj g|=         8.552
+  At iterate    25  f =       243.98  |proj g|=        7.6995
+  At iterate    26  f =        243.5  |proj g|=        1.7387
+  At iterate    27  f =       243.34  |proj g|=        1.4201
+  At iterate    28  f =       243.27  |proj g|=       0.15279
+  At iterate    29  f =       243.27  |proj g|=        1.7283
+  At iterate    30  f =       243.26  |proj g|=      0.024592
+  At iterate    31  f =       243.26  |proj g|=      0.001511
   
-  iterations 30
-  function evaluations 41
+  iterations 31
+  function evaluations 42
   segments explored during Cauchy searches 32
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.00022292
+  norm of the final projected gradient 0.00151099
   final function value 243.264
   
   F = 243.264
@@ -997,30 +1059,39 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -223738.7 
+    - best initial criterion value(s) :  -267.3647 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   2.2374e+05  |proj g|=       571.95
-  At iterate     1  f =       416.28  |proj g|=      0.075984
-  At iterate     2  f =       326.13  |proj g|=       0.36549
-  ys=-1.618e+02  -gs= 4.246e+01, BFGS update SKIPPED
-  At iterate     3  f =       318.45  |proj g|=       0.12275
-  At iterate     4  f =       318.22  |proj g|=      0.014005
-  At iterate     5  f =       318.22  |proj g|=     0.0030673
-  At iterate     6  f =       318.22  |proj g|=    5.9546e-05
-  At iterate     7  f =       318.22  |proj g|=    2.4718e-07
+  At iterate     0  f=       267.36  |proj g|=       3.1625
+  At iterate     1  f =       258.61  |proj g|=        1.8021
+  At iterate     2  f =       250.83  |proj g|=        9.2592
+  At iterate     3  f =       250.67  |proj g|=        19.987
+  At iterate     4  f =       247.43  |proj g|=        2.9896
+  At iterate     5  f =       247.09  |proj g|=       0.24321
+  At iterate     6  f =       247.09  |proj g|=       0.24059
+  At iterate     7  f =       247.07  |proj g|=        1.7059
+  At iterate     8  f =       246.83  |proj g|=        2.8534
+  At iterate     9  f =       246.25  |proj g|=        6.4317
+  At iterate    10  f =       244.86  |proj g|=         11.88
+  At iterate    11  f =       244.37  |proj g|=        11.878
+  At iterate    12  f =       243.41  |proj g|=        3.5478
+  At iterate    13  f =       243.29  |proj g|=       0.55478
+  At iterate    14  f =       243.26  |proj g|=       0.15255
+  At iterate    15  f =       243.26  |proj g|=       0.16809
+  At iterate    16  f =       243.26  |proj g|=      0.014126
+  At iterate    17  f =       243.26  |proj g|=    0.00098104
   
-  iterations 7
-  function evaluations 36
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 2.47179e-07
-  final function value 318.222
+  iterations 17
+  function evaluations 25
+  segments explored during Cauchy searches 19
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.00098104
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
   
> library(data.table, lib.loc=R.home("library"))
> (sig.diff.dt <- myDiff(Rvers))
Key: <checking>
Empty data.table (0 rows and 3 cols): checking,master,release
> 
> ## If there are significant differences, use git bisect to find when
> ## they started.
> if(nrow(sig.diff.dt)){
+   dt.git <- file.path(task.dir, "data.table.git")
+   system(paste("cd ~/R/data.table && git fetch --tags"))
+   system(paste("git clone ~/R/data.table", dt.git))
+   release.tag <- gsub(".tar.gz|.*_", "", cargs[["release"]])
+   rev.parse.cmd <- paste(
+     "cd", dt.git, "&& git rev-parse master")
+   master.sha <- system(rev.parse.cmd, intern=TRUE)
+   merge.base.cmd <- paste(
+     "cd", dt.git, "&& git merge-base master", release.tag)
+   merge.base.sha <- system(merge.base.cmd, intern=TRUE)
+   old.sha <- merge.base.sha
+   run_R <- file.path(proj.dir, "install_dt_then_check_dep.R")
+   sig.diff.dt[, first.bad.commit := NA_character_]
+   sig.diff.dt[, comments := NA_character_]
+   for(diff.i in 1:nrow(sig.diff.dt)){
+     sig.diff.row <- sig.diff.dt[diff.i]
+     bisect.cmd <- paste(
+       "cd", dt.git, "&&",
+       "git bisect start &&",
+       "git bisect old", old.sha, "&&",
+       "git bisect new master &&",
+       "git bisect run",
+       R.home('bin/Rscript'),
+       run_R,
+       shQuote(sig.diff.row$checking),
+       sig.diff.row$release,
+       rev.dep.release.tar.gz,
+       release.tag)
+     print(bisect.cmd)
+     bisect.out <- system(bisect.cmd, intern=TRUE)
+     cat(bisect.out,sep="\n")
+     if(is.null(attr(bisect.out,"status"))){
+       first.bad.sha <- nc::capture_all_str(
+         bisect.out,
+         sha="[0-9a-f]+",
+         " is the first new commit")$sha
+       parent.cmd <- paste(
+         "cd ~/R/data.table && git log --pretty=%P -n 1",
+         first.bad.sha)
+       parent.sha <- system(parent.cmd, intern=TRUE)
+       sig.diff.dt[diff.i, first.bad.commit := first.bad.sha]
+       parent.msg <- paste0("parent=", parent.sha)
+       this.comment <- if(parent.sha==old.sha){
+         paste(parent.msg, "same as git bisect old")
+       }else if(first.bad.sha==master.sha){
+         paste("same as git bisect new=master,", parent.msg)
+       }else{
+         parent.msg
+       }
+       sig.diff.dt[diff.i, comments := this.comment]
+     }
+   }
+   ## add CRAN column.
+   sig.diff.dt[, CRAN := {
+     flavor <- get_flavor(Rvers)
+     details <- data.table(flavor=unique(flavor))[, {
+       base <- "https://www.r-project.org/nosvn/R.check/"
+       u <- paste0(base, flavor, "/", rev.dep, "-00check.txt")
+       check.txt <- tempfile()
+       tryCatch({
+         download.file(u, check.txt, quiet=TRUE)
+       }, error=function(e){
+         NULL
+       })
+       check.lines <- if(file.exists(check.txt)){
+         readLines(check.txt,encoding="UTF-8")
+       }else{
+         ""
+       }
+       repl.lines <- gsub("[\u2018\u2019]", "'", check.lines)
+       ##gsub("[‘’]", "'", check.lines) does not work with LC_ALL=C.
+       myStatus(line.vec=repl.lines)
+     }, by=flavor]
+     select.dt <- data.table(flavor, checking)
+     details[select.dt, msg, on=.(flavor, checking)]
+   }]
+   dir.create(file.path(job.dir, Rvers))
+   diffs.csv <- file.path(job.dir, Rvers, "significant_differences.csv")
+   data.table::fwrite(sig.diff.dt, diffs.csv)
+   print(sig.diff.dt)
+ }
>