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

WARNING: ignoring environment value of R_HOME

R Under development (unstable) (2025-05-13 r88200) -- "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/2025-05-15/deps.csv", 
task.str = "846", release = "/scratch/th798/data.table-revdeps/2025-05-15/data.table_release_1.17.2.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-05-15/data.table_master_1.17.99.15932214095653a70048efdc41545968b38a100a.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/17244922/R-devel/846"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/17244922/R-devel/846/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/th798/17244922/R-devel/846/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] "2025-05-15 00:44:12 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/17244922/R-devel/846/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/th798/17244922/R-devel/846/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/th798/17244922/R-devel/846/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/th798/17244922/RtmpDGElDH/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 49.592   2.321 114.441 
> print(Sys.time())
[1] "2025-05-15 00:46:06 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] "2025-05-15 00:46:07 MST"
Installing package into '/tmp/th798/17244922/R-devel/846/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/th798/17244922/R-devel/846/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] "2025-05-15 00:46:46 MST"
* using log directory '/tmp/th798/17244922/R-devel/846/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-05-13 r88200)
* 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 26.844  0.106   27.51
* 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 20.694084 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.694084 
  converged
  # 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:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  6 (5 variable)
  initial  value 11.307889 
  iter  10 value 9.606159
  final  value 9.606128 
  converged
  # weights:  6 (5 variable)
  initial  value 11.307889 
  iter  10 value 9.606159
  final  value 9.606128 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.242647
  final  value 17.242646 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 30.006737 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 30.006737 
  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 
  final  value 32.825398 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.825398 
  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 28.723803
  final  value 28.721798 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.723803
  final  value 28.721798 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.723803
  final  value 28.721798 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.723803
  final  value 28.721798 
  converged
  # weights:  18 (10 variable)
  initial  value 17.957534 
  iter  10 value 15.594665
  iter  20 value 15.578564
  final  value 15.578563 
  converged
  # weights:  18 (10 variable)
  initial  value 17.957534 
  iter  10 value 15.594665
  iter  20 value 15.578564
  final  value 15.578563 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.723803
  final  value 28.721798 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 28.723803
  final  value 28.721798 
  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 : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -165652.5 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.6565e+05  |proj g|=       8.3345
  At iterate     1  f =       104.15  |proj g|=        2.4246
  At iterate     2  f =       68.164  |proj g|=       0.57824
  At iterate     3  f =       68.158  |proj g|=      0.039588
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       68.158  |proj g|=     0.0010484
  At iterate     5  f =       68.158  |proj g|=    2.9809e-06
  
  iterations 5
  function evaluations 18
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.98086e-06
  final function value 68.1584
  
  F = 68.1584
  final  value 68.158425 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -165652.5 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.6565e+05  |proj g|=       8.3345
  At iterate     1  f =       104.15  |proj g|=        2.4246
  At iterate     2  f =       68.164  |proj g|=       0.57824
  At iterate     3  f =       68.158  |proj g|=      0.039588
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       68.158  |proj g|=     0.0010484
  At iterate     5  f =       68.158  |proj g|=    2.9809e-06
  
  iterations 5
  function evaluations 18
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.98086e-06
  final function value 68.1584
  
  F = 68.1584
  final  value 68.158425 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -69.73836 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.738  |proj g|=        1.868
  At iterate     1  f =       69.727  |proj g|=        1.2457
  At iterate     2  f =       69.725  |proj g|=        1.2457
  At iterate     3  f =       69.725  |proj g|=        1.2457
  At iterate     4  f =       69.722  |proj g|=        1.2451
  At iterate     5  f =       69.716  |proj g|=        1.2434
  At iterate     6  f =       69.699  |proj g|=        1.2384
  At iterate     7  f =       69.656  |proj g|=        1.2248
  At iterate     8  f =       69.542  |proj g|=        1.1885
  At iterate     9  f =       69.271  |proj g|=        1.0985
  At iterate    10  f =       68.784  |proj g|=       0.92625
  At iterate    11  f =       68.222  |proj g|=        2.2587
  At iterate    12  f =       68.041  |proj g|=        1.8683
  At iterate    13  f =       68.028  |proj g|=        1.8682
  At iterate    14  f =       68.026  |proj g|=      0.071838
  At iterate    15  f =       68.026  |proj g|=        0.3466
  At iterate    16  f =       68.026  |proj g|=      0.090392
  
  iterations 16
  function evaluations 20
  segments explored during Cauchy searches 18
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0903919
  final function value 68.0264
  
  F = 68.0264
  final  value 68.026393 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -69.73836 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.738  |proj g|=        1.868
  At iterate     1  f =       69.727  |proj g|=        1.2457
  At iterate     2  f =       69.725  |proj g|=        1.2457
  At iterate     3  f =       69.725  |proj g|=        1.2457
  At iterate     4  f =       69.722  |proj g|=        1.2451
  At iterate     5  f =       69.716  |proj g|=        1.2434
  At iterate     6  f =       69.699  |proj g|=        1.2384
  At iterate     7  f =       69.656  |proj g|=        1.2248
  At iterate     8  f =       69.542  |proj g|=        1.1885
  At iterate     9  f =       69.271  |proj g|=        1.0985
  At iterate    10  f =       68.784  |proj g|=       0.92625
  At iterate    11  f =       68.222  |proj g|=        2.2587
  At iterate    12  f =       68.041  |proj g|=        1.8683
  At iterate    13  f =       68.028  |proj g|=        1.8682
  At iterate    14  f =       68.026  |proj g|=      0.071838
  At iterate    15  f =       68.026  |proj g|=        0.3466
  At iterate    16  f =       68.026  |proj g|=      0.090392
  
  iterations 16
  function evaluations 20
  segments explored during Cauchy searches 18
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0903919
  final function value 68.0264
  
  F = 68.0264
  final  value 68.026393 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -24994.07 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        24994  |proj g|=       8.6405
  At iterate     1  f =       104.15  |proj g|=        2.4246
  At iterate     2  f =       69.053  |proj g|=        1.0921
  ys=-2.225e+01  -gs= 1.973e+01, BFGS update SKIPPED
  At iterate     3  f =       68.429  |proj g|=       0.94889
  At iterate     4  f =       68.159  |proj g|=       0.21943
  At iterate     5  f =       68.159  |proj g|=      0.079393
  At iterate     6  f =       68.158  |proj g|=     0.0012625
  At iterate     7  f =       68.158  |proj g|=    7.1228e-06
  
  iterations 7
  function evaluations 25
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 7.12278e-06
  final function value 68.1584
  
  F = 68.1584
  final  value 68.158425 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.127098e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.869053 
    - variance bounds :  0.09127098 9.32139 
    - best initial criterion value(s) :  -78.14485 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       78.145  |proj g|=       4.4159
  At iterate     1  f =       77.334  |proj g|=        2.1715
  At iterate     2  f =       68.799  |proj g|=       0.89006
  At iterate     3  f =       68.412  |proj g|=        1.8058
  At iterate     4  f =       68.203  |proj g|=        1.8682
  At iterate     5  f =       68.157  |proj g|=        1.8682
  At iterate     6  f =       68.156  |proj g|=        1.8682
  At iterate     7  f =       68.155  |proj g|=        1.8679
  At iterate     8  f =       68.155  |proj g|=       0.15381
  At iterate     9  f =       68.155  |proj g|=       0.50163
  At iterate    10  f =       68.152  |proj g|=      0.024396
  At iterate    11  f =       68.152  |proj g|=     0.0097706
  At iterate    12  f =       68.152  |proj g|=        1.3395
  At iterate    13  f =       68.152  |proj g|=      0.097492
  At iterate    14  f =       68.152  |proj g|=     0.0089864
  
  iterations 14
  function evaluations 23
  segments explored during Cauchy searches 17
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00898641
  final function value 68.152
  
  F = 68.152
  final  value 68.152010 
  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) :  -270.132 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       270.13  |proj g|=        36.77
  At iterate     1  f =       266.97  |proj g|=        1.3605
  At iterate     2  f =        256.5  |proj g|=        10.765
  At iterate     3  f =       253.37  |proj g|=        10.868
  At iterate     4  f =       252.58  |proj g|=        6.0852
  At iterate     5  f =       252.25  |proj g|=       0.57009
  At iterate     6  f =       252.25  |proj g|=       0.39789
  At iterate     7  f =       252.25  |proj g|=       0.20722
  At iterate     8  f =       252.25  |proj g|=       0.20708
  At iterate     9  f =       252.25  |proj g|=        0.2061
  At iterate    10  f =       252.25  |proj g|=       0.20685
  At iterate    11  f =       252.24  |proj g|=       0.40535
  At iterate    12  f =       252.24  |proj g|=       0.72467
  At iterate    13  f =       252.23  |proj g|=        1.2549
  At iterate    14  f =       252.21  |proj g|=        1.8039
  At iterate    15  f =       252.15  |proj g|=        1.8242
  At iterate    16  f =       252.03  |proj g|=        1.8555
  At iterate    17  f =       251.96  |proj g|=        1.8582
  At iterate    18  f =       251.58  |proj g|=        1.8907
  At iterate    19  f =       250.07  |proj g|=         1.932
  At iterate    20  f =       248.86  |proj g|=        1.8913
  At iterate    21  f =       246.39  |proj g|=        1.7331
  At iterate    22  f =       244.25  |proj g|=        1.4636
  At iterate    23  f =        243.3  |proj g|=        1.7323
  At iterate    24  f =       243.27  |proj g|=         1.729
  At iterate    25  f =       243.26  |proj g|=       0.15271
  At iterate    26  f =       243.26  |proj g|=     0.0067746
  At iterate    27  f =       243.26  |proj g|=    0.00033732
  
  iterations 27
  function evaluations 38
  segments explored during Cauchy searches 28
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000337323
  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) :  -396.8135 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       396.81  |proj g|=       3.0938
  At iterate     1  f =       326.01  |proj g|=       0.36516
  At iterate     2  f =        320.4  |proj g|=       0.28781
  At iterate     3  f =       318.26  |proj g|=      0.063393
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.25  |proj g|=      0.047602
  At iterate     5  f =       318.22  |proj g|=     0.0034534
  At iterate     6  f =       318.22  |proj g|=    0.00020587
  At iterate     7  f =       318.22  |proj g|=    9.6111e-07
  
  iterations 7
  function evaluations 17
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 9.61114e-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) :  -278.4219 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       278.42  |proj g|=      0.75608
  At iterate     1  f =       264.92  |proj g|=        31.358
  At iterate     2  f =        257.3  |proj g|=        17.489
  At iterate     3  f =       249.31  |proj g|=        18.911
  At iterate     4  f =       246.87  |proj g|=        10.809
  At iterate     5  f =       246.23  |proj g|=        1.7202
  At iterate     6  f =       245.93  |proj g|=       0.79661
  At iterate     7  f =       245.91  |proj g|=        1.7111
  At iterate     8  f =        245.9  |proj g|=       0.23526
  At iterate     9  f =        245.9  |proj g|=       0.23533
  At iterate    10  f =        245.9  |proj g|=       0.23548
  At iterate    11  f =        245.9  |proj g|=       0.23595
  At iterate    12  f =        245.9  |proj g|=       0.23645
  At iterate    13  f =        245.9  |proj g|=       0.36971
  At iterate    14  f =       245.88  |proj g|=       0.84779
  At iterate    15  f =       245.88  |proj g|=         0.421
  At iterate    16  f =       245.84  |proj g|=        1.2606
  At iterate    17  f =        245.7  |proj g|=        3.1217
  At iterate    18  f =       245.27  |proj g|=        5.8381
  At iterate    19  f =       244.19  |proj g|=        8.7801
  At iterate    20  f =       243.42  |proj g|=        3.6239
  At iterate    21  f =       243.32  |proj g|=        1.7317
  At iterate    22  f =       243.32  |proj g|=        1.3731
  At iterate    23  f =       243.27  |proj g|=        1.3579
  At iterate    24  f =       243.26  |proj g|=      0.025188
  At iterate    25  f =       243.26  |proj g|=     0.0070734
  At iterate    26  f =       243.26  |proj g|=     0.0038967
  
  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 0.00389671
  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) :  -639.072 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       639.07  |proj g|=       19.569
  At iterate     1  f =       320.47  |proj g|=       0.29014
  At iterate     2  f =       319.07  |proj g|=       0.21065
  At iterate     3  f =       318.23  |proj g|=      0.026548
  At iterate     4  f =       318.22  |proj g|=      0.013152
  At iterate     5  f =       318.22  |proj g|=    0.00048631
  At iterate     6  f =       318.22  |proj g|=    8.5173e-06
  At iterate     7  f =       318.22  |proj g|=     5.639e-09
  
  iterations 7
  function evaluations 12
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 5.639e-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 : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -76.09958 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         76.1  |proj g|=       10.271
  At iterate     1  f =       74.618  |proj g|=        1.4138
  At iterate     2  f =       72.978  |proj g|=        1.0279
  At iterate     3  f =       72.949  |proj g|=       0.23114
  At iterate     4  f =       72.947  |proj g|=      0.024807
  At iterate     5  f =       72.947  |proj g|=    0.00050833
  At iterate     6  f =       72.947  |proj g|=      1.09e-06
  
  iterations 6
  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 1.09e-06
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -76.09958 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         76.1  |proj g|=       10.271
  At iterate     1  f =       74.618  |proj g|=        1.4138
  At iterate     2  f =       72.978  |proj g|=        1.0279
  At iterate     3  f =       72.949  |proj g|=       0.23114
  At iterate     4  f =       72.947  |proj g|=      0.024807
  At iterate     5  f =       72.947  |proj g|=    0.00050833
  At iterate     6  f =       72.947  |proj g|=      1.09e-06
  
  iterations 6
  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 1.09e-06
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -141.8006 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        141.8  |proj g|=       10.055
  At iterate     1  f =       108.65  |proj g|=        2.0254
  At iterate     2  f =       75.402  |proj g|=        10.426
  At iterate     3  f =       73.634  |proj g|=         1.272
  At iterate     4  f =       73.226  |proj g|=        1.1521
  At iterate     5  f =       72.965  |proj g|=       0.83255
  At iterate     6  f =        72.95  |proj g|=       0.33978
  At iterate     7  f =       72.947  |proj g|=      0.025954
  At iterate     8  f =       72.947  |proj g|=    0.00073927
  At iterate     9  f =       72.947  |proj g|=    1.6677e-06
  
  iterations 9
  function evaluations 25
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.66768e-06
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -141.8006 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        141.8  |proj g|=       10.055
  At iterate     1  f =       108.65  |proj g|=        2.0254
  At iterate     2  f =       75.402  |proj g|=        10.426
  At iterate     3  f =       73.634  |proj g|=         1.272
  At iterate     4  f =       73.226  |proj g|=        1.1521
  At iterate     5  f =       72.965  |proj g|=       0.83255
  At iterate     6  f =        72.95  |proj g|=       0.33978
  At iterate     7  f =       72.947  |proj g|=      0.025954
  At iterate     8  f =       72.947  |proj g|=    0.00073927
  At iterate     9  f =       72.947  |proj g|=    1.6677e-06
  
  iterations 9
  function evaluations 25
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.66768e-06
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -198.5605 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       198.56  |proj g|=       9.5909
  At iterate     1  f =       108.65  |proj g|=        2.0254
  At iterate     2  f =       73.033  |proj g|=        2.1347
  At iterate     3  f =       72.948  |proj g|=       0.12164
  At iterate     4  f =       72.947  |proj g|=      0.018567
  At iterate     5  f =       72.947  |proj g|=    0.00019875
  At iterate     6  f =       72.947  |proj g|=    3.2045e-07
  
  iterations 6
  function evaluations 23
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 3.20449e-07
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.105408e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.942939 
    - variance bounds :  0.1105408 11.14339 
    - best initial criterion value(s) :  -5453166 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   5.4532e+06  |proj g|=       10.514
  At iterate     1  f =       108.65  |proj g|=        2.0254
  At iterate     2  f =       74.711  |proj g|=        1.5068
  ys=-2.933e+01  -gs= 1.929e+01, BFGS update SKIPPED
  At iterate     3  f =       73.924  |proj g|=        1.3419
  At iterate     4  f =       72.976  |proj g|=        1.0265
  At iterate     5  f =       72.947  |proj g|=      0.093634
  At iterate     6  f =       72.947  |proj g|=     0.0096325
  At iterate     7  f =       72.947  |proj g|=    7.8884e-05
  At iterate     8  f =       72.947  |proj g|=    6.5784e-08
  
  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 6.57837e-08
  final function value 72.9472
  
  F = 72.9472
  final  value 72.947217 
  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) :  -284.1933 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       284.19  |proj g|=       2.6648
  At iterate     1  f =       252.96  |proj g|=        1.9522
  At iterate     2  f =       251.19  |proj g|=         1.895
  At iterate     3  f =       249.14  |proj g|=        2.6217
  At iterate     4  f =       248.46  |proj g|=       0.23349
  At iterate     5  f =       248.46  |proj g|=       0.23603
  At iterate     6  f =       248.46  |proj g|=       0.23638
  At iterate     7  f =       248.46  |proj g|=       0.25534
  At iterate     8  f =       248.46  |proj g|=       0.75998
  At iterate     9  f =       248.46  |proj g|=        1.5116
  At iterate    10  f =       248.46  |proj g|=        1.7006
  At iterate    11  f =       248.46  |proj g|=        1.7006
  At iterate    12  f =       248.44  |proj g|=        1.7004
  At iterate    13  f =       248.41  |proj g|=         2.479
  At iterate    14  f =       248.32  |proj g|=        4.0597
  At iterate    15  f =        248.3  |proj g|=        5.2148
  At iterate    16  f =        248.1  |proj g|=        6.6626
  At iterate    17  f =          247  |proj g|=        11.065
  At iterate    18  f =       245.63  |proj g|=        13.626
  At iterate    19  f =       244.86  |proj g|=        11.896
  At iterate    20  f =        243.4  |proj g|=        2.0703
  At iterate    21  f =        243.4  |proj g|=        2.2324
  At iterate    22  f =       243.28  |proj g|=        1.7282
  At iterate    23  f =       243.26  |proj g|=       0.17317
  At iterate    24  f =       243.26  |proj g|=      0.076924
  At iterate    25  f =       243.26  |proj g|=     0.0042552
  At iterate    26  f =       243.26  |proj g|=    0.00018506
  
  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 0.000185062
  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) :  -7444.827 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       7444.8  |proj g|=       140.38
  At iterate     1  f =       363.73  |proj g|=       0.21387
  At iterate     2  f =       318.32  |proj g|=      0.098165
  At iterate     3  f =       318.27  |proj g|=      0.063288
  At iterate     4  f =       318.22  |proj g|=     0.0080437
  At iterate     5  f =       318.22  |proj g|=    0.00078911
  At iterate     6  f =       318.22  |proj g|=    8.7422e-06
  At iterate     7  f =       318.22  |proj g|=    9.3715e-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 9.37149e-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/th798/17244922/R-devel/846/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-15 00:55:58 MST"
[1] "2025-05-15 00:55:58 MST"
Installing package into '/tmp/th798/17244922/R-devel/846/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
/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/th798/17244922/R-devel/846/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] "2025-05-15 00:56:26 MST"
* using log directory '/tmp/th798/17244922/R-devel/846/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-05-13 r88200)
* 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 27.712  0.094  28.428
* 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 20.794415 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.794415 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.135280 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.135280 
  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 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  6 (5 variable)
  initial  value 9.545453 
  iter  10 value 8.827706
  final  value 8.827689 
  converged
  # weights:  6 (5 variable)
  initial  value 9.545453 
  iter  10 value 8.827706
  final  value 8.827689 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.129576
  iter  10 value 19.129576
  iter  10 value 19.129576
  final  value 19.129576 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.350660 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.350660 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.734788 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.734788 
  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 31.872437
  final  value 31.870812 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 31.872437
  final  value 31.870812 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 31.872437
  final  value 31.870812 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 31.872437
  final  value 31.870812 
  converged
  # weights:  18 (10 variable)
  initial  value 16.933802 
  iter  10 value 15.848628
  iter  20 value 15.842393
  iter  20 value 15.842393
  iter  20 value 15.842393
  final  value 15.842393 
  converged
  # weights:  18 (10 variable)
  initial  value 16.933802 
  iter  10 value 15.848628
  iter  20 value 15.842393
  iter  20 value 15.842393
  iter  20 value 15.842393
  final  value 15.842393 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 31.872437
  final  value 31.870812 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 31.872437
  final  value 31.870812 
  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 : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -69.24373 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.244  |proj g|=        7.774
  At iterate     1  f =       66.844  |proj g|=        1.0623
  At iterate     2  f =       66.168  |proj g|=       0.89788
  At iterate     3  f =       65.785  |proj g|=       0.36215
  At iterate     4  f =       65.784  |proj g|=       0.16449
  At iterate     5  f =       65.783  |proj g|=     0.0039404
  At iterate     6  f =       65.783  |proj g|=    4.1633e-05
  At iterate     7  f =       65.783  |proj g|=    1.0678e-08
  
  iterations 7
  function evaluations 10
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 1.06785e-08
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -69.24373 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       69.244  |proj g|=        7.774
  At iterate     1  f =       66.844  |proj g|=        1.0623
  At iterate     2  f =       66.168  |proj g|=       0.89788
  At iterate     3  f =       65.785  |proj g|=       0.36215
  At iterate     4  f =       65.784  |proj g|=       0.16449
  At iterate     5  f =       65.783  |proj g|=     0.0039404
  At iterate     6  f =       65.783  |proj g|=    4.1633e-05
  At iterate     7  f =       65.783  |proj g|=    1.0678e-08
  
  iterations 7
  function evaluations 10
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 1.06785e-08
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -144533.8 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.4453e+05  |proj g|=       7.1304
  At iterate     1  f =        101.3  |proj g|=        2.7169
  At iterate     2  f =        66.25  |proj g|=       0.91663
  ys=-1.345e+01  -gs= 1.985e+01, BFGS update SKIPPED
  At iterate     3  f =       66.133  |proj g|=       0.88957
  At iterate     4  f =       65.802  |proj g|=       0.76938
  At iterate     5  f =       65.787  |proj g|=       0.53713
  At iterate     6  f =       65.783  |proj g|=      0.041932
  At iterate     7  f =       65.783  |proj g|=     0.0014092
  At iterate     8  f =       65.783  |proj g|=    3.8587e-06
  
  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 3.85871e-06
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -144533.8 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.4453e+05  |proj g|=       7.1304
  At iterate     1  f =        101.3  |proj g|=        2.7169
  At iterate     2  f =        66.25  |proj g|=       0.91663
  ys=-1.345e+01  -gs= 1.985e+01, BFGS update SKIPPED
  At iterate     3  f =       66.133  |proj g|=       0.88957
  At iterate     4  f =       65.802  |proj g|=       0.76938
  At iterate     5  f =       65.787  |proj g|=       0.53713
  At iterate     6  f =       65.783  |proj g|=      0.041932
  At iterate     7  f =       65.783  |proj g|=     0.0014092
  At iterate     8  f =       65.783  |proj g|=    3.8587e-06
  
  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 3.85871e-06
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -42864.23 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        42864  |proj g|=       7.6105
  At iterate     1  f =        101.3  |proj g|=        2.7169
  At iterate     2  f =       65.886  |proj g|=       0.81503
  At iterate     3  f =       65.784  |proj g|=       0.25992
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       65.783  |proj g|=      0.004867
  At iterate     5  f =       65.783  |proj g|=    8.4064e-05
  At iterate     6  f =       65.783  |proj g|=    2.6613e-08
  
  iterations 6
  function evaluations 22
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.6613e-08
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.299896e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.948068 
    - variance bounds :  0.07659806 8.299896 
    - best initial criterion value(s) :  -1236737 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.2367e+06  |proj g|=        7.661
  At iterate     1  f =        101.3  |proj g|=        2.7169
  At iterate     2  f =       66.048  |proj g|=         5.413
  At iterate     3  f =       65.795  |proj g|=       0.76232
  At iterate     4  f =       65.784  |proj g|=       0.23798
  At iterate     5  f =       65.783  |proj g|=      0.015491
  At iterate     6  f =       65.783  |proj g|=    0.00024433
  At iterate     7  f =       65.783  |proj g|=    2.4598e-07
  
  iterations 7
  function evaluations 25
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.4598e-07
  final function value 65.7833
  
  F = 65.7833
  final  value 65.783306 
  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) :  -488.2821 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       488.28  |proj g|=       4.4402
  At iterate     1  f =       328.88  |proj g|=       0.36703
  At iterate     2  f =       318.81  |proj g|=       0.18288
  At iterate     3  f =        318.4  |proj g|=       0.13907
  At iterate     4  f =       318.24  |proj g|=       0.03912
  At iterate     5  f =       318.22  |proj g|=     0.0063781
  At iterate     6  f =       318.22  |proj g|=    0.00036802
  At iterate     7  f =       318.22  |proj g|=    3.2259e-06
  At iterate     8  f =       318.22  |proj g|=    1.6139e-09
  
  iterations 8
  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 1.61392e-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) :  -653.5744 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       653.57  |proj g|=       6.8028
  At iterate     1  f =        329.1  |proj g|=       0.36678
  At iterate     2  f =       320.51  |proj g|=       0.29177
  At iterate     3  f =       318.25  |proj g|=      0.051605
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.24  |proj g|=      0.039064
  At iterate     5  f =       318.22  |proj g|=      0.002376
  At iterate     6  f =       318.22  |proj g|=    0.00011799
  At iterate     7  f =       318.22  |proj g|=    3.7975e-07
  
  iterations 7
  function evaluations 16
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.79747e-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) :  -294.9406 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       294.94  |proj g|=       7.1001
  At iterate     1  f =       270.53  |proj g|=        3.2897
  At iterate     2  f =       265.99  |proj g|=        2.3439
  At iterate     3  f =       260.05  |proj g|=        2.2724
  At iterate     4  f =       259.18  |proj g|=        1.8398
  At iterate     5  f =       258.58  |proj g|=         1.835
  At iterate     6  f =       256.46  |proj g|=        2.9137
  At iterate     7  f =       256.16  |proj g|=        5.0425
  At iterate     8  f =       254.91  |proj g|=        11.217
  At iterate     9  f =       250.75  |proj g|=        12.304
  At iterate    10  f =       244.92  |proj g|=        1.7493
  At iterate    11  f =       243.94  |proj g|=        6.5133
  At iterate    12  f =       243.39  |proj g|=       0.57754
  At iterate    13  f =       243.39  |proj g|=        1.0701
  At iterate    14  f =       243.39  |proj g|=      0.091865
  At iterate    15  f =       243.39  |proj g|=      0.091614
  At iterate    16  f =       243.39  |proj g|=       0.15581
  At iterate    17  f =       243.39  |proj g|=       0.20621
  At iterate    18  f =       243.39  |proj g|=       0.36675
  At iterate    19  f =       243.39  |proj g|=       0.63847
  At iterate    20  f =       243.38  |proj g|=        1.0482
  At iterate    21  f =       243.37  |proj g|=        1.4199
  At iterate    22  f =       243.37  |proj g|=        1.4179
  At iterate    23  f =       243.35  |proj g|=        1.4176
  At iterate    24  f =       243.29  |proj g|=        1.3961
  At iterate    25  f =       243.27  |proj g|=       0.52026
  At iterate    26  f =       243.26  |proj g|=      0.080389
  At iterate    27  f =       243.26  |proj g|=     0.0022993
  At iterate    28  f =       243.26  |proj g|=      0.037077
  
  iterations 28
  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 0.0370771
  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) :  -281.0411 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       281.04  |proj g|=       33.223
  At iterate     1  f =       249.13  |proj g|=        1.7718
  At iterate     2  f =       247.74  |proj g|=        1.3593
  At iterate     3  f =       244.43  |proj g|=        5.8999
  At iterate     4  f =       244.17  |proj g|=        1.7212
  At iterate     5  f =       244.15  |proj g|=       0.18753
  At iterate     6  f =       244.15  |proj g|=       0.18886
  At iterate     7  f =       244.15  |proj g|=       0.24086
  At iterate     8  f =       244.15  |proj g|=       0.75479
  At iterate     9  f =       244.15  |proj g|=         1.719
  At iterate    10  f =       244.15  |proj g|=        1.7194
  At iterate    11  f =       244.15  |proj g|=        1.7201
  At iterate    12  f =       244.13  |proj g|=        1.7213
  At iterate    13  f =       244.11  |proj g|=        1.7235
  At iterate    14  f =       244.04  |proj g|=        1.7272
  At iterate    15  f =       243.88  |proj g|=        1.7325
  At iterate    16  f =       243.65  |proj g|=        1.7366
  At iterate    17  f =       243.45  |proj g|=        1.4426
  At iterate    18  f =       243.42  |proj g|=        1.4454
  At iterate    19  f =        243.4  |proj g|=        1.4417
  At iterate    20  f =       243.31  |proj g|=        1.7308
  At iterate    21  f =       243.27  |proj g|=          1.73
  At iterate    22  f =       243.27  |proj g|=       0.42666
  At iterate    23  f =       243.26  |proj g|=        0.2388
  At iterate    24  f =       243.26  |proj g|=       0.51516
  At iterate    25  f =       243.26  |proj g|=       0.23932
  At iterate    26  f =       243.26  |proj g|=      0.086039
  At iterate    27  f =       243.26  |proj g|=      0.015297
  At iterate    28  f =       243.26  |proj g|=    0.00062308
  
  iterations 28
  function evaluations 35
  segments explored during Cauchy searches 29
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000623078
  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 : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -74.55289 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       74.553  |proj g|=      0.80871
  At iterate     1  f =       69.851  |proj g|=       0.93886
  At iterate     2  f =       69.806  |proj g|=        0.9108
  At iterate     3  f =       69.772  |proj g|=       0.26807
  At iterate     4  f =       69.771  |proj g|=      0.029549
  At iterate     5  f =       69.771  |proj g|=    0.00059118
  At iterate     6  f =       69.771  |proj g|=    1.3371e-06
  
  iterations 6
  function evaluations 7
  segments explored during Cauchy searches 7
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 1.33713e-06
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -74.55289 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       74.553  |proj g|=      0.80871
  At iterate     1  f =       69.851  |proj g|=       0.93886
  At iterate     2  f =       69.806  |proj g|=        0.9108
  At iterate     3  f =       69.772  |proj g|=       0.26807
  At iterate     4  f =       69.771  |proj g|=      0.029549
  At iterate     5  f =       69.771  |proj g|=    0.00059118
  At iterate     6  f =       69.771  |proj g|=    1.3371e-06
  
  iterations 6
  function evaluations 7
  segments explored during Cauchy searches 7
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 1.33713e-06
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -82.67366 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       82.674  |proj g|=       8.9411
  At iterate     1  f =       81.521  |proj g|=        3.3946
  At iterate     2  f =       69.777  |proj g|=       0.56649
  At iterate     3  f =       69.776  |proj g|=        0.5243
  At iterate     4  f =       69.771  |proj g|=      0.025297
  At iterate     5  f =       69.771  |proj g|=     0.0010633
  At iterate     6  f =       69.771  |proj g|=    2.0483e-06
  
  iterations 6
  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 2.04826e-06
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -82.67366 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       82.674  |proj g|=       8.9411
  At iterate     1  f =       81.521  |proj g|=        3.3946
  At iterate     2  f =       69.777  |proj g|=       0.56649
  At iterate     3  f =       69.776  |proj g|=        0.5243
  At iterate     4  f =       69.771  |proj g|=      0.025297
  At iterate     5  f =       69.771  |proj g|=     0.0010633
  At iterate     6  f =       69.771  |proj g|=    2.0483e-06
  
  iterations 6
  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 2.04826e-06
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -156.689 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       156.69  |proj g|=       8.7053
  At iterate     1  f =       105.29  |proj g|=        2.3163
  At iterate     2  f =       70.309  |proj g|=        1.0869
  ys=-1.515e+01  -gs= 1.981e+01, BFGS update SKIPPED
  At iterate     3  f =       69.886  |proj g|=       0.95578
  At iterate     4  f =       69.818  |proj g|=        1.7421
  At iterate     5  f =       69.773  |proj g|=       0.31291
  At iterate     6  f =       69.771  |proj g|=      0.036747
  At iterate     7  f =       69.771  |proj g|=    0.00090796
  At iterate     8  f =       69.771  |proj g|=    2.5553e-06
  
  iterations 8
  function evaluations 23
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.55527e-06
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.735149e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.857192 
    - variance bounds :  0.0958632 9.735149 
    - best initial criterion value(s) :  -2725.805 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       2725.8  |proj g|=       9.0624
  At iterate     1  f =       105.29  |proj g|=        2.3163
  At iterate     2  f =       69.771  |proj g|=      0.024547
  At iterate     3  f =       69.771  |proj g|=    0.00027707
  At iterate     4  f =       69.771  |proj g|=    5.1788e-07
  
  iterations 4
  function evaluations 18
  segments explored during Cauchy searches 7
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.17878e-07
  final function value 69.7708
  
  F = 69.7708
  final  value 69.770806 
  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) :  -2292.525 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       2292.5  |proj g|=        42.95
  At iterate     1  f =       336.53  |proj g|=       0.34229
  At iterate     2  f =        320.7  |proj g|=       0.29829
  At iterate     3  f =       318.23  |proj g|=      0.031819
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.23  |proj g|=      0.024412
  At iterate     5  f =       318.22  |proj g|=    0.00096443
  At iterate     6  f =       318.22  |proj g|=    3.0707e-05
  At iterate     7  f =       318.22  |proj g|=    4.0215e-08
  
  iterations 7
  function evaluations 16
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 4.02153e-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) :  -478.195 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       478.19  |proj g|=       10.446
  At iterate     1  f =       318.62  |proj g|=       0.15581
  At iterate     2  f =       318.34  |proj g|=      0.090405
  At iterate     3  f =       318.23  |proj g|=      0.033039
  At iterate     4  f =       318.22  |proj g|=     0.0045315
  At iterate     5  f =       318.22  |proj g|=    0.00019433
  At iterate     6  f =       318.22  |proj g|=    1.2076e-06
  
  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 1.20758e-06
  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/th798/17244922/R-devel/846/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-15 01:05:44 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_Under_development_unstable_2025-05-13_r88200/release_1.17.2.Rcheck/00check.log	2025-05-15 00:55:58.514450037 -0700
+++ R_Under_development_unstable_2025-05-13_r88200/master_1.17.99.15932214095653a70048efdc41545968b38a100a.Rcheck/00check.log	2025-05-15 01:05:44.974585835 -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 26.844  0.106   27.51
+mlr_learners_classif.cv_glmnet 27.712  0.094  28.428
 * checking for unstated dependencies in 'tests' ... OK
 * checking tests ... ERROR
   Running 'testthat.R'
@@ -71,91 +71,103 @@
   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 20.694084 
+  final  value 20.135280 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.694084 
+  final  value 20.135280 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.095425 
+  final  value 20.190350 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.095425 
+  final  value 20.190350 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  6 (5 variable)
-  initial  value 11.307889 
-  iter  10 value 9.606159
-  final  value 9.606128 
+  initial  value 9.545453 
+  iter  10 value 8.827706
+  final  value 8.827689 
   converged
   # weights:  6 (5 variable)
-  initial  value 11.307889 
-  iter  10 value 9.606159
-  final  value 9.606128 
+  initial  value 9.545453 
+  iter  10 value 8.827706
+  final  value 8.827689 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.242647
-  final  value 17.242646 
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  iter  10 value 19.129576
+  final  value 19.129576 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 30.006737 
+  final  value 32.958369 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 30.006737 
+  final  value 32.958369 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.884179 
+  final  value 32.350660 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.884179 
+  final  value 32.350660 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.825398 
+  final  value 32.734788 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.825398 
+  final  value 32.734788 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
@@ -167,45 +179,49 @@
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  18 (10 variable)
-  initial  value 17.957534 
-  iter  10 value 15.594665
-  iter  20 value 15.578564
-  final  value 15.578563 
+  initial  value 16.933802 
+  iter  10 value 15.848628
+  iter  20 value 15.842393
+  iter  20 value 15.842393
+  iter  20 value 15.842393
+  final  value 15.842393 
   converged
   # weights:  18 (10 variable)
-  initial  value 17.957534 
-  iter  10 value 15.594665
-  iter  20 value 15.578564
-  final  value 15.578563 
+  initial  value 16.933802 
+  iter  10 value 15.848628
+  iter  20 value 15.842393
+  iter  20 value 15.842393
+  iter  20 value 15.842393
+  final  value 15.842393 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 28.723803
-  final  value 28.721798 
+  iter  10 value 31.872437
+  final  value 31.870812 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -314,33 +330,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -165652.5 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -69.24373 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   1.6565e+05  |proj g|=       8.3345
-  At iterate     1  f =       104.15  |proj g|=        2.4246
-  At iterate     2  f =       68.164  |proj g|=       0.57824
-  At iterate     3  f =       68.158  |proj g|=      0.039588
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       68.158  |proj g|=     0.0010484
-  At iterate     5  f =       68.158  |proj g|=    2.9809e-06
+  At iterate     0  f=       69.244  |proj g|=        7.774
+  At iterate     1  f =       66.844  |proj g|=        1.0623
+  At iterate     2  f =       66.168  |proj g|=       0.89788
+  At iterate     3  f =       65.785  |proj g|=       0.36215
+  At iterate     4  f =       65.784  |proj g|=       0.16449
+  At iterate     5  f =       65.783  |proj g|=     0.0039404
+  At iterate     6  f =       65.783  |proj g|=    4.1633e-05
+  At iterate     7  f =       65.783  |proj g|=    1.0678e-08
   
-  iterations 5
-  function evaluations 18
+  iterations 7
+  function evaluations 10
   segments explored during Cauchy searches 10
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.98086e-06
-  final function value 68.1584
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 1.06785e-08
+  final function value 65.7833
   
-  F = 68.1584
-  final  value 68.158425 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -351,33 +367,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -165652.5 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -69.24373 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   1.6565e+05  |proj g|=       8.3345
-  At iterate     1  f =       104.15  |proj g|=        2.4246
-  At iterate     2  f =       68.164  |proj g|=       0.57824
-  At iterate     3  f =       68.158  |proj g|=      0.039588
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       68.158  |proj g|=     0.0010484
-  At iterate     5  f =       68.158  |proj g|=    2.9809e-06
+  At iterate     0  f=       69.244  |proj g|=        7.774
+  At iterate     1  f =       66.844  |proj g|=        1.0623
+  At iterate     2  f =       66.168  |proj g|=       0.89788
+  At iterate     3  f =       65.785  |proj g|=       0.36215
+  At iterate     4  f =       65.784  |proj g|=       0.16449
+  At iterate     5  f =       65.783  |proj g|=     0.0039404
+  At iterate     6  f =       65.783  |proj g|=    4.1633e-05
+  At iterate     7  f =       65.783  |proj g|=    1.0678e-08
   
-  iterations 5
-  function evaluations 18
+  iterations 7
+  function evaluations 10
   segments explored during Cauchy searches 10
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.98086e-06
-  final function value 68.1584
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 1.06785e-08
+  final function value 65.7833
   
-  F = 68.1584
-  final  value 68.158425 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -388,42 +404,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -69.73836 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -144533.8 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       69.738  |proj g|=        1.868
-  At iterate     1  f =       69.727  |proj g|=        1.2457
-  At iterate     2  f =       69.725  |proj g|=        1.2457
-  At iterate     3  f =       69.725  |proj g|=        1.2457
-  At iterate     4  f =       69.722  |proj g|=        1.2451
-  At iterate     5  f =       69.716  |proj g|=        1.2434
-  At iterate     6  f =       69.699  |proj g|=        1.2384
-  At iterate     7  f =       69.656  |proj g|=        1.2248
-  At iterate     8  f =       69.542  |proj g|=        1.1885
-  At iterate     9  f =       69.271  |proj g|=        1.0985
-  At iterate    10  f =       68.784  |proj g|=       0.92625
-  At iterate    11  f =       68.222  |proj g|=        2.2587
-  At iterate    12  f =       68.041  |proj g|=        1.8683
-  At iterate    13  f =       68.028  |proj g|=        1.8682
-  At iterate    14  f =       68.026  |proj g|=      0.071838
-  At iterate    15  f =       68.026  |proj g|=        0.3466
-  At iterate    16  f =       68.026  |proj g|=      0.090392
+  At iterate     0  f=   1.4453e+05  |proj g|=       7.1304
+  At iterate     1  f =        101.3  |proj g|=        2.7169
+  At iterate     2  f =        66.25  |proj g|=       0.91663
+  ys=-1.345e+01  -gs= 1.985e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.133  |proj g|=       0.88957
+  At iterate     4  f =       65.802  |proj g|=       0.76938
+  At iterate     5  f =       65.787  |proj g|=       0.53713
+  At iterate     6  f =       65.783  |proj g|=      0.041932
+  At iterate     7  f =       65.783  |proj g|=     0.0014092
+  At iterate     8  f =       65.783  |proj g|=    3.8587e-06
   
-  iterations 16
-  function evaluations 20
-  segments explored during Cauchy searches 18
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.0903919
-  final function value 68.0264
+  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 3.85871e-06
+  final function value 65.7833
   
-  F = 68.0264
-  final  value 68.026393 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -434,42 +443,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -69.73836 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -144533.8 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       69.738  |proj g|=        1.868
-  At iterate     1  f =       69.727  |proj g|=        1.2457
-  At iterate     2  f =       69.725  |proj g|=        1.2457
-  At iterate     3  f =       69.725  |proj g|=        1.2457
-  At iterate     4  f =       69.722  |proj g|=        1.2451
-  At iterate     5  f =       69.716  |proj g|=        1.2434
-  At iterate     6  f =       69.699  |proj g|=        1.2384
-  At iterate     7  f =       69.656  |proj g|=        1.2248
-  At iterate     8  f =       69.542  |proj g|=        1.1885
-  At iterate     9  f =       69.271  |proj g|=        1.0985
-  At iterate    10  f =       68.784  |proj g|=       0.92625
-  At iterate    11  f =       68.222  |proj g|=        2.2587
-  At iterate    12  f =       68.041  |proj g|=        1.8683
-  At iterate    13  f =       68.028  |proj g|=        1.8682
-  At iterate    14  f =       68.026  |proj g|=      0.071838
-  At iterate    15  f =       68.026  |proj g|=        0.3466
-  At iterate    16  f =       68.026  |proj g|=      0.090392
+  At iterate     0  f=   1.4453e+05  |proj g|=       7.1304
+  At iterate     1  f =        101.3  |proj g|=        2.7169
+  At iterate     2  f =        66.25  |proj g|=       0.91663
+  ys=-1.345e+01  -gs= 1.985e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.133  |proj g|=       0.88957
+  At iterate     4  f =       65.802  |proj g|=       0.76938
+  At iterate     5  f =       65.787  |proj g|=       0.53713
+  At iterate     6  f =       65.783  |proj g|=      0.041932
+  At iterate     7  f =       65.783  |proj g|=     0.0014092
+  At iterate     8  f =       65.783  |proj g|=    3.8587e-06
   
-  iterations 16
-  function evaluations 20
-  segments explored during Cauchy searches 18
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.0903919
-  final function value 68.0264
+  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 3.85871e-06
+  final function value 65.7833
   
-  F = 68.0264
-  final  value 68.026393 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -480,34 +482,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -24994.07 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -42864.23 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        24994  |proj g|=       8.6405
-  At iterate     1  f =       104.15  |proj g|=        2.4246
-  At iterate     2  f =       69.053  |proj g|=        1.0921
-  ys=-2.225e+01  -gs= 1.973e+01, BFGS update SKIPPED
-  At iterate     3  f =       68.429  |proj g|=       0.94889
-  At iterate     4  f =       68.159  |proj g|=       0.21943
-  At iterate     5  f =       68.159  |proj g|=      0.079393
-  At iterate     6  f =       68.158  |proj g|=     0.0012625
-  At iterate     7  f =       68.158  |proj g|=    7.1228e-06
+  At iterate     0  f=        42864  |proj g|=       7.6105
+  At iterate     1  f =        101.3  |proj g|=        2.7169
+  At iterate     2  f =       65.886  |proj g|=       0.81503
+  At iterate     3  f =       65.784  |proj g|=       0.25992
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       65.783  |proj g|=      0.004867
+  At iterate     5  f =       65.783  |proj g|=    8.4064e-05
+  At iterate     6  f =       65.783  |proj g|=    2.6613e-08
   
-  iterations 7
-  function evaluations 25
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 7.12278e-06
-  final function value 68.1584
+  iterations 6
+  function evaluations 22
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 2.6613e-08
+  final function value 65.7833
   
-  F = 68.1584
-  final  value 68.158425 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -518,40 +520,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 9.127098e-09 
+    - nugget : 8.299896e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.869053 
-    - variance bounds :  0.09127098 9.32139 
-    - best initial criterion value(s) :  -78.14485 
+    - parameters upper bounds :  4 2 1.948068 
+    - variance bounds :  0.07659806 8.299896 
+    - best initial criterion value(s) :  -1236737 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       78.145  |proj g|=       4.4159
-  At iterate     1  f =       77.334  |proj g|=        2.1715
-  At iterate     2  f =       68.799  |proj g|=       0.89006
-  At iterate     3  f =       68.412  |proj g|=        1.8058
-  At iterate     4  f =       68.203  |proj g|=        1.8682
-  At iterate     5  f =       68.157  |proj g|=        1.8682
-  At iterate     6  f =       68.156  |proj g|=        1.8682
-  At iterate     7  f =       68.155  |proj g|=        1.8679
-  At iterate     8  f =       68.155  |proj g|=       0.15381
-  At iterate     9  f =       68.155  |proj g|=       0.50163
-  At iterate    10  f =       68.152  |proj g|=      0.024396
-  At iterate    11  f =       68.152  |proj g|=     0.0097706
-  At iterate    12  f =       68.152  |proj g|=        1.3395
-  At iterate    13  f =       68.152  |proj g|=      0.097492
-  At iterate    14  f =       68.152  |proj g|=     0.0089864
+  At iterate     0  f=   1.2367e+06  |proj g|=        7.661
+  At iterate     1  f =        101.3  |proj g|=        2.7169
+  At iterate     2  f =       66.048  |proj g|=         5.413
+  At iterate     3  f =       65.795  |proj g|=       0.76232
+  At iterate     4  f =       65.784  |proj g|=       0.23798
+  At iterate     5  f =       65.783  |proj g|=      0.015491
+  At iterate     6  f =       65.783  |proj g|=    0.00024433
+  At iterate     7  f =       65.783  |proj g|=    2.4598e-07
   
-  iterations 14
-  function evaluations 23
-  segments explored during Cauchy searches 17
+  iterations 7
+  function evaluations 25
+  segments explored during Cauchy searches 10
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.00898641
-  final function value 68.152
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 2.4598e-07
+  final function value 65.7833
   
-  F = 68.152
-  final  value 68.152010 
+  F = 65.7833
+  final  value 65.783306 
   converged
   
   optimisation start
@@ -566,49 +561,30 @@
     - 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) :  -270.132 
+    - best initial criterion value(s) :  -488.2821 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       270.13  |proj g|=        36.77
-  At iterate     1  f =       266.97  |proj g|=        1.3605
-  At iterate     2  f =        256.5  |proj g|=        10.765
-  At iterate     3  f =       253.37  |proj g|=        10.868
-  At iterate     4  f =       252.58  |proj g|=        6.0852
-  At iterate     5  f =       252.25  |proj g|=       0.57009
-  At iterate     6  f =       252.25  |proj g|=       0.39789
-  At iterate     7  f =       252.25  |proj g|=       0.20722
-  At iterate     8  f =       252.25  |proj g|=       0.20708
-  At iterate     9  f =       252.25  |proj g|=        0.2061
-  At iterate    10  f =       252.25  |proj g|=       0.20685
-  At iterate    11  f =       252.24  |proj g|=       0.40535
-  At iterate    12  f =       252.24  |proj g|=       0.72467
-  At iterate    13  f =       252.23  |proj g|=        1.2549
-  At iterate    14  f =       252.21  |proj g|=        1.8039
-  At iterate    15  f =       252.15  |proj g|=        1.8242
-  At iterate    16  f =       252.03  |proj g|=        1.8555
-  At iterate    17  f =       251.96  |proj g|=        1.8582
-  At iterate    18  f =       251.58  |proj g|=        1.8907
-  At iterate    19  f =       250.07  |proj g|=         1.932
-  At iterate    20  f =       248.86  |proj g|=        1.8913
-  At iterate    21  f =       246.39  |proj g|=        1.7331
-  At iterate    22  f =       244.25  |proj g|=        1.4636
-  At iterate    23  f =        243.3  |proj g|=        1.7323
-  At iterate    24  f =       243.27  |proj g|=         1.729
-  At iterate    25  f =       243.26  |proj g|=       0.15271
-  At iterate    26  f =       243.26  |proj g|=     0.0067746
-  At iterate    27  f =       243.26  |proj g|=    0.00033732
+  At iterate     0  f=       488.28  |proj g|=       4.4402
+  At iterate     1  f =       328.88  |proj g|=       0.36703
+  At iterate     2  f =       318.81  |proj g|=       0.18288
+  At iterate     3  f =        318.4  |proj g|=       0.13907
+  At iterate     4  f =       318.24  |proj g|=       0.03912
+  At iterate     5  f =       318.22  |proj g|=     0.0063781
+  At iterate     6  f =       318.22  |proj g|=    0.00036802
+  At iterate     7  f =       318.22  |proj g|=    3.2259e-06
+  At iterate     8  f =       318.22  |proj g|=    1.6139e-09
   
-  iterations 27
-  function evaluations 38
-  segments explored during Cauchy searches 28
+  iterations 8
+  function evaluations 19
+  segments explored during Cauchy searches 10
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000337323
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 1.61392e-09
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   
   optimisation start
@@ -623,27 +599,27 @@
     - 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) :  -396.8135 
+    - best initial criterion value(s) :  -653.5744 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       396.81  |proj g|=       3.0938
-  At iterate     1  f =       326.01  |proj g|=       0.36516
-  At iterate     2  f =        320.4  |proj g|=       0.28781
-  At iterate     3  f =       318.26  |proj g|=      0.063393
+  At iterate     0  f=       653.57  |proj g|=       6.8028
+  At iterate     1  f =        329.1  |proj g|=       0.36678
+  At iterate     2  f =       320.51  |proj g|=       0.29177
+  At iterate     3  f =       318.25  |proj g|=      0.051605
   Nonpositive definiteness in Cholesky factorization in formk;
      refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.25  |proj g|=      0.047602
-  At iterate     5  f =       318.22  |proj g|=     0.0034534
-  At iterate     6  f =       318.22  |proj g|=    0.00020587
-  At iterate     7  f =       318.22  |proj g|=    9.6111e-07
+  At iterate     4  f =       318.24  |proj g|=      0.039064
+  At iterate     5  f =       318.22  |proj g|=      0.002376
+  At iterate     6  f =       318.22  |proj g|=    0.00011799
+  At iterate     7  f =       318.22  |proj g|=    3.7975e-07
   
   iterations 7
-  function evaluations 17
+  function evaluations 16
   segments explored during Cauchy searches 11
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 9.61114e-07
+  norm of the final projected gradient 3.79747e-07
   final function value 318.222
   
   F = 318.222
@@ -662,44 +638,46 @@
     - 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) :  -278.4219 
+    - best initial criterion value(s) :  -294.9406 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       278.42  |proj g|=      0.75608
-  At iterate     1  f =       264.92  |proj g|=        31.358
-  At iterate     2  f =        257.3  |proj g|=        17.489
-  At iterate     3  f =       249.31  |proj g|=        18.911
-  At iterate     4  f =       246.87  |proj g|=        10.809
-  At iterate     5  f =       246.23  |proj g|=        1.7202
-  At iterate     6  f =       245.93  |proj g|=       0.79661
-  At iterate     7  f =       245.91  |proj g|=        1.7111
-  At iterate     8  f =        245.9  |proj g|=       0.23526
-  At iterate     9  f =        245.9  |proj g|=       0.23533
-  At iterate    10  f =        245.9  |proj g|=       0.23548
-  At iterate    11  f =        245.9  |proj g|=       0.23595
-  At iterate    12  f =        245.9  |proj g|=       0.23645
-  At iterate    13  f =        245.9  |proj g|=       0.36971
-  At iterate    14  f =       245.88  |proj g|=       0.84779
-  At iterate    15  f =       245.88  |proj g|=         0.421
-  At iterate    16  f =       245.84  |proj g|=        1.2606
-  At iterate    17  f =        245.7  |proj g|=        3.1217
-  At iterate    18  f =       245.27  |proj g|=        5.8381
-  At iterate    19  f =       244.19  |proj g|=        8.7801
-  At iterate    20  f =       243.42  |proj g|=        3.6239
-  At iterate    21  f =       243.32  |proj g|=        1.7317
-  At iterate    22  f =       243.32  |proj g|=        1.3731
-  At iterate    23  f =       243.27  |proj g|=        1.3579
-  At iterate    24  f =       243.26  |proj g|=      0.025188
-  At iterate    25  f =       243.26  |proj g|=     0.0070734
-  At iterate    26  f =       243.26  |proj g|=     0.0038967
-  
-  iterations 26
-  function evaluations 32
-  segments explored during Cauchy searches 28
+  At iterate     0  f=       294.94  |proj g|=       7.1001
+  At iterate     1  f =       270.53  |proj g|=        3.2897
+  At iterate     2  f =       265.99  |proj g|=        2.3439
+  At iterate     3  f =       260.05  |proj g|=        2.2724
+  At iterate     4  f =       259.18  |proj g|=        1.8398
+  At iterate     5  f =       258.58  |proj g|=         1.835
+  At iterate     6  f =       256.46  |proj g|=        2.9137
+  At iterate     7  f =       256.16  |proj g|=        5.0425
+  At iterate     8  f =       254.91  |proj g|=        11.217
+  At iterate     9  f =       250.75  |proj g|=        12.304
+  At iterate    10  f =       244.92  |proj g|=        1.7493
+  At iterate    11  f =       243.94  |proj g|=        6.5133
+  At iterate    12  f =       243.39  |proj g|=       0.57754
+  At iterate    13  f =       243.39  |proj g|=        1.0701
+  At iterate    14  f =       243.39  |proj g|=      0.091865
+  At iterate    15  f =       243.39  |proj g|=      0.091614
+  At iterate    16  f =       243.39  |proj g|=       0.15581
+  At iterate    17  f =       243.39  |proj g|=       0.20621
+  At iterate    18  f =       243.39  |proj g|=       0.36675
+  At iterate    19  f =       243.39  |proj g|=       0.63847
+  At iterate    20  f =       243.38  |proj g|=        1.0482
+  At iterate    21  f =       243.37  |proj g|=        1.4199
+  At iterate    22  f =       243.37  |proj g|=        1.4179
+  At iterate    23  f =       243.35  |proj g|=        1.4176
+  At iterate    24  f =       243.29  |proj g|=        1.3961
+  At iterate    25  f =       243.27  |proj g|=       0.52026
+  At iterate    26  f =       243.26  |proj g|=      0.080389
+  At iterate    27  f =       243.26  |proj g|=     0.0022993
+  At iterate    28  f =       243.26  |proj g|=      0.037077
+  
+  iterations 28
+  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 0.00389671
+  norm of the final projected gradient 0.0370771
   final function value 243.264
   
   F = 243.264
@@ -718,29 +696,50 @@
     - 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) :  -639.072 
+    - best initial criterion value(s) :  -281.0411 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       639.07  |proj g|=       19.569
-  At iterate     1  f =       320.47  |proj g|=       0.29014
-  At iterate     2  f =       319.07  |proj g|=       0.21065
-  At iterate     3  f =       318.23  |proj g|=      0.026548
-  At iterate     4  f =       318.22  |proj g|=      0.013152
-  At iterate     5  f =       318.22  |proj g|=    0.00048631
-  At iterate     6  f =       318.22  |proj g|=    8.5173e-06
-  At iterate     7  f =       318.22  |proj g|=     5.639e-09
+  At iterate     0  f=       281.04  |proj g|=       33.223
+  At iterate     1  f =       249.13  |proj g|=        1.7718
+  At iterate     2  f =       247.74  |proj g|=        1.3593
+  At iterate     3  f =       244.43  |proj g|=        5.8999
+  At iterate     4  f =       244.17  |proj g|=        1.7212
+  At iterate     5  f =       244.15  |proj g|=       0.18753
+  At iterate     6  f =       244.15  |proj g|=       0.18886
+  At iterate     7  f =       244.15  |proj g|=       0.24086
+  At iterate     8  f =       244.15  |proj g|=       0.75479
+  At iterate     9  f =       244.15  |proj g|=         1.719
+  At iterate    10  f =       244.15  |proj g|=        1.7194
+  At iterate    11  f =       244.15  |proj g|=        1.7201
+  At iterate    12  f =       244.13  |proj g|=        1.7213
+  At iterate    13  f =       244.11  |proj g|=        1.7235
+  At iterate    14  f =       244.04  |proj g|=        1.7272
+  At iterate    15  f =       243.88  |proj g|=        1.7325
+  At iterate    16  f =       243.65  |proj g|=        1.7366
+  At iterate    17  f =       243.45  |proj g|=        1.4426
+  At iterate    18  f =       243.42  |proj g|=        1.4454
+  At iterate    19  f =        243.4  |proj g|=        1.4417
+  At iterate    20  f =       243.31  |proj g|=        1.7308
+  At iterate    21  f =       243.27  |proj g|=          1.73
+  At iterate    22  f =       243.27  |proj g|=       0.42666
+  At iterate    23  f =       243.26  |proj g|=        0.2388
+  At iterate    24  f =       243.26  |proj g|=       0.51516
+  At iterate    25  f =       243.26  |proj g|=       0.23932
+  At iterate    26  f =       243.26  |proj g|=      0.086039
+  At iterate    27  f =       243.26  |proj g|=      0.015297
+  At iterate    28  f =       243.26  |proj g|=    0.00062308
   
-  iterations 7
-  function evaluations 12
-  segments explored during Cauchy searches 8
+  iterations 28
+  function evaluations 35
+  segments explored during Cauchy searches 29
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 5.639e-09
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.000623078
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -751,32 +750,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -76.09958 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -74.55289 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         76.1  |proj g|=       10.271
-  At iterate     1  f =       74.618  |proj g|=        1.4138
-  At iterate     2  f =       72.978  |proj g|=        1.0279
-  At iterate     3  f =       72.949  |proj g|=       0.23114
-  At iterate     4  f =       72.947  |proj g|=      0.024807
-  At iterate     5  f =       72.947  |proj g|=    0.00050833
-  At iterate     6  f =       72.947  |proj g|=      1.09e-06
+  At iterate     0  f=       74.553  |proj g|=      0.80871
+  At iterate     1  f =       69.851  |proj g|=       0.93886
+  At iterate     2  f =       69.806  |proj g|=        0.9108
+  At iterate     3  f =       69.772  |proj g|=       0.26807
+  At iterate     4  f =       69.771  |proj g|=      0.029549
+  At iterate     5  f =       69.771  |proj g|=    0.00059118
+  At iterate     6  f =       69.771  |proj g|=    1.3371e-06
   
   iterations 6
-  function evaluations 9
-  segments explored during Cauchy searches 9
+  function evaluations 7
+  segments explored during Cauchy searches 7
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 1.09e-06
-  final function value 72.9472
+  norm of the final projected gradient 1.33713e-06
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -787,32 +786,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -76.09958 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -74.55289 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         76.1  |proj g|=       10.271
-  At iterate     1  f =       74.618  |proj g|=        1.4138
-  At iterate     2  f =       72.978  |proj g|=        1.0279
-  At iterate     3  f =       72.949  |proj g|=       0.23114
-  At iterate     4  f =       72.947  |proj g|=      0.024807
-  At iterate     5  f =       72.947  |proj g|=    0.00050833
-  At iterate     6  f =       72.947  |proj g|=      1.09e-06
+  At iterate     0  f=       74.553  |proj g|=      0.80871
+  At iterate     1  f =       69.851  |proj g|=       0.93886
+  At iterate     2  f =       69.806  |proj g|=        0.9108
+  At iterate     3  f =       69.772  |proj g|=       0.26807
+  At iterate     4  f =       69.771  |proj g|=      0.029549
+  At iterate     5  f =       69.771  |proj g|=    0.00059118
+  At iterate     6  f =       69.771  |proj g|=    1.3371e-06
   
   iterations 6
-  function evaluations 9
-  segments explored during Cauchy searches 9
+  function evaluations 7
+  segments explored during Cauchy searches 7
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 1.09e-06
-  final function value 72.9472
+  norm of the final projected gradient 1.33713e-06
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -823,35 +822,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -141.8006 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -82.67366 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        141.8  |proj g|=       10.055
-  At iterate     1  f =       108.65  |proj g|=        2.0254
-  At iterate     2  f =       75.402  |proj g|=        10.426
-  At iterate     3  f =       73.634  |proj g|=         1.272
-  At iterate     4  f =       73.226  |proj g|=        1.1521
-  At iterate     5  f =       72.965  |proj g|=       0.83255
-  At iterate     6  f =        72.95  |proj g|=       0.33978
-  At iterate     7  f =       72.947  |proj g|=      0.025954
-  At iterate     8  f =       72.947  |proj g|=    0.00073927
-  At iterate     9  f =       72.947  |proj g|=    1.6677e-06
+  At iterate     0  f=       82.674  |proj g|=       8.9411
+  At iterate     1  f =       81.521  |proj g|=        3.3946
+  At iterate     2  f =       69.777  |proj g|=       0.56649
+  At iterate     3  f =       69.776  |proj g|=        0.5243
+  At iterate     4  f =       69.771  |proj g|=      0.025297
+  At iterate     5  f =       69.771  |proj g|=     0.0010633
+  At iterate     6  f =       69.771  |proj g|=    2.0483e-06
   
-  iterations 9
-  function evaluations 25
-  segments explored during Cauchy searches 12
+  iterations 6
+  function evaluations 9
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.66768e-06
-  final function value 72.9472
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 2.04826e-06
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -862,35 +858,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -141.8006 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -82.67366 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        141.8  |proj g|=       10.055
-  At iterate     1  f =       108.65  |proj g|=        2.0254
-  At iterate     2  f =       75.402  |proj g|=        10.426
-  At iterate     3  f =       73.634  |proj g|=         1.272
-  At iterate     4  f =       73.226  |proj g|=        1.1521
-  At iterate     5  f =       72.965  |proj g|=       0.83255
-  At iterate     6  f =        72.95  |proj g|=       0.33978
-  At iterate     7  f =       72.947  |proj g|=      0.025954
-  At iterate     8  f =       72.947  |proj g|=    0.00073927
-  At iterate     9  f =       72.947  |proj g|=    1.6677e-06
+  At iterate     0  f=       82.674  |proj g|=       8.9411
+  At iterate     1  f =       81.521  |proj g|=        3.3946
+  At iterate     2  f =       69.777  |proj g|=       0.56649
+  At iterate     3  f =       69.776  |proj g|=        0.5243
+  At iterate     4  f =       69.771  |proj g|=      0.025297
+  At iterate     5  f =       69.771  |proj g|=     0.0010633
+  At iterate     6  f =       69.771  |proj g|=    2.0483e-06
   
-  iterations 9
-  function evaluations 25
-  segments explored during Cauchy searches 12
+  iterations 6
+  function evaluations 9
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.66768e-06
-  final function value 72.9472
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 2.04826e-06
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -901,32 +894,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -198.5605 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -156.689 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       198.56  |proj g|=       9.5909
-  At iterate     1  f =       108.65  |proj g|=        2.0254
-  At iterate     2  f =       73.033  |proj g|=        2.1347
-  At iterate     3  f =       72.948  |proj g|=       0.12164
-  At iterate     4  f =       72.947  |proj g|=      0.018567
-  At iterate     5  f =       72.947  |proj g|=    0.00019875
-  At iterate     6  f =       72.947  |proj g|=    3.2045e-07
+  At iterate     0  f=       156.69  |proj g|=       8.7053
+  At iterate     1  f =       105.29  |proj g|=        2.3163
+  At iterate     2  f =       70.309  |proj g|=        1.0869
+  ys=-1.515e+01  -gs= 1.981e+01, BFGS update SKIPPED
+  At iterate     3  f =       69.886  |proj g|=       0.95578
+  At iterate     4  f =       69.818  |proj g|=        1.7421
+  At iterate     5  f =       69.773  |proj g|=       0.31291
+  At iterate     6  f =       69.771  |proj g|=      0.036747
+  At iterate     7  f =       69.771  |proj g|=    0.00090796
+  At iterate     8  f =       69.771  |proj g|=    2.5553e-06
   
-  iterations 6
+  iterations 8
   function evaluations 23
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 0
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 3.20449e-07
-  final function value 72.9472
+  norm of the final projected gradient 2.55527e-06
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -937,35 +933,30 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.105408e-08 
+    - nugget : 9.735149e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.942939 
-    - variance bounds :  0.1105408 11.14339 
-    - best initial criterion value(s) :  -5453166 
+    - parameters upper bounds :  4 2 1.857192 
+    - variance bounds :  0.0958632 9.735149 
+    - best initial criterion value(s) :  -2725.805 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   5.4532e+06  |proj g|=       10.514
-  At iterate     1  f =       108.65  |proj g|=        2.0254
-  At iterate     2  f =       74.711  |proj g|=        1.5068
-  ys=-2.933e+01  -gs= 1.929e+01, BFGS update SKIPPED
-  At iterate     3  f =       73.924  |proj g|=        1.3419
-  At iterate     4  f =       72.976  |proj g|=        1.0265
-  At iterate     5  f =       72.947  |proj g|=      0.093634
-  At iterate     6  f =       72.947  |proj g|=     0.0096325
-  At iterate     7  f =       72.947  |proj g|=    7.8884e-05
-  At iterate     8  f =       72.947  |proj g|=    6.5784e-08
+  At iterate     0  f=       2725.8  |proj g|=       9.0624
+  At iterate     1  f =       105.29  |proj g|=        2.3163
+  At iterate     2  f =       69.771  |proj g|=      0.024547
+  At iterate     3  f =       69.771  |proj g|=    0.00027707
+  At iterate     4  f =       69.771  |proj g|=    5.1788e-07
   
-  iterations 8
-  function evaluations 35
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 1
+  iterations 4
+  function evaluations 18
+  segments explored during Cauchy searches 7
+  BFGS updates skipped 0
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 6.57837e-08
-  final function value 72.9472
+  norm of the final projected gradient 5.17878e-07
+  final function value 69.7708
   
-  F = 72.9472
-  final  value 72.947217 
+  F = 69.7708
+  final  value 69.770806 
   converged
   
   optimisation start
@@ -980,48 +971,31 @@
     - 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) :  -284.1933 
+    - best initial criterion value(s) :  -2292.525 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       284.19  |proj g|=       2.6648
-  At iterate     1  f =       252.96  |proj g|=        1.9522
-  At iterate     2  f =       251.19  |proj g|=         1.895
-  At iterate     3  f =       249.14  |proj g|=        2.6217
-  At iterate     4  f =       248.46  |proj g|=       0.23349
-  At iterate     5  f =       248.46  |proj g|=       0.23603
-  At iterate     6  f =       248.46  |proj g|=       0.23638
-  At iterate     7  f =       248.46  |proj g|=       0.25534
-  At iterate     8  f =       248.46  |proj g|=       0.75998
-  At iterate     9  f =       248.46  |proj g|=        1.5116
-  At iterate    10  f =       248.46  |proj g|=        1.7006
-  At iterate    11  f =       248.46  |proj g|=        1.7006
-  At iterate    12  f =       248.44  |proj g|=        1.7004
-  At iterate    13  f =       248.41  |proj g|=         2.479
-  At iterate    14  f =       248.32  |proj g|=        4.0597
-  At iterate    15  f =        248.3  |proj g|=        5.2148
-  At iterate    16  f =        248.1  |proj g|=        6.6626
-  At iterate    17  f =          247  |proj g|=        11.065
-  At iterate    18  f =       245.63  |proj g|=        13.626
-  At iterate    19  f =       244.86  |proj g|=        11.896
-  At iterate    20  f =        243.4  |proj g|=        2.0703
-  At iterate    21  f =        243.4  |proj g|=        2.2324
-  At iterate    22  f =       243.28  |proj g|=        1.7282
-  At iterate    23  f =       243.26  |proj g|=       0.17317
-  At iterate    24  f =       243.26  |proj g|=      0.076924
-  At iterate    25  f =       243.26  |proj g|=     0.0042552
-  At iterate    26  f =       243.26  |proj g|=    0.00018506
-  
-  iterations 26
-  function evaluations 32
-  segments explored during Cauchy searches 28
+  At iterate     0  f=       2292.5  |proj g|=        42.95
+  At iterate     1  f =       336.53  |proj g|=       0.34229
+  At iterate     2  f =        320.7  |proj g|=       0.29829
+  At iterate     3  f =       318.23  |proj g|=      0.031819
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.23  |proj g|=      0.024412
+  At iterate     5  f =       318.22  |proj g|=    0.00096443
+  At iterate     6  f =       318.22  |proj g|=    3.0707e-05
+  At iterate     7  f =       318.22  |proj g|=    4.0215e-08
+  
+  iterations 7
+  function evaluations 16
+  segments explored during Cauchy searches 11
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000185062
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 4.02153e-08
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   
   optimisation start
@@ -1036,25 +1010,24 @@
     - 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) :  -7444.827 
+    - best initial criterion value(s) :  -478.195 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       7444.8  |proj g|=       140.38
-  At iterate     1  f =       363.73  |proj g|=       0.21387
-  At iterate     2  f =       318.32  |proj g|=      0.098165
-  At iterate     3  f =       318.27  |proj g|=      0.063288
-  At iterate     4  f =       318.22  |proj g|=     0.0080437
-  At iterate     5  f =       318.22  |proj g|=    0.00078911
-  At iterate     6  f =       318.22  |proj g|=    8.7422e-06
-  At iterate     7  f =       318.22  |proj g|=    9.3715e-09
+  At iterate     0  f=       478.19  |proj g|=       10.446
+  At iterate     1  f =       318.62  |proj g|=       0.15581
+  At iterate     2  f =       318.34  |proj g|=      0.090405
+  At iterate     3  f =       318.23  |proj g|=      0.033039
+  At iterate     4  f =       318.22  |proj g|=     0.0045315
+  At iterate     5  f =       318.22  |proj g|=    0.00019433
+  At iterate     6  f =       318.22  |proj g|=    1.2076e-06
   
-  iterations 7
-  function evaluations 22
-  segments explored during Cauchy searches 9
+  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 9.37149e-09
+  norm of the final projected gradient 1.20758e-06
   final function value 318.222
   
   F = 318.222
> 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/2025-05-15/deps.csv", 
task.str = "846", release = "/scratch/th798/data.table-revdeps/2025-05-15/data.table_release_1.17.2.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-05-15/data.table_master_1.17.99.15932214095653a70048efdc41545968b38a100a.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/17244922/R-release/846"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/17244922/R-release/846/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/th798/17244922/R-release/846/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] "2025-05-15 01:05:53 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/17244922/R-release/846/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/th798/17244922/R-release/846/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/th798/17244922/R-release/846/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/th798/17244922/RtmpilzQbC/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 58.491   2.591 115.044 
> print(Sys.time())
[1] "2025-05-15 01:07:49 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] "2025-05-15 01:07:49 MST"
Installing package into '/tmp/th798/17244922/R-release/846/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/th798/17244922/R-release/846/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] "2025-05-15 01:08:17 MST"
* using log directory '/tmp/th798/17244922/R-release/846/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 20.735569 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.735569 
  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 20.286745 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 20.286745 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 20.286745 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 20.286745 
  converged
  # weights:  6 (5 variable)
  initial  value 11.279303 
  iter  10 value 10.003473
  final  value 10.003464 
  converged
  # weights:  6 (5 variable)
  initial  value 11.279303 
  iter  10 value 10.003473
  final  value 10.003464 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 20.286745 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 20.286745 
  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:  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 
  final  value 32.837452 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.837452 
  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 30.535397
  final  value 30.530542 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.535397
  final  value 30.530542 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.535397
  final  value 30.530542 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.535397
  final  value 30.530542 
  converged
  # weights:  18 (10 variable)
  initial  value 16.703197 
  iter  10 value 15.005217
  iter  20 value 14.920712
  final  value 14.920709 
  converged
  # weights:  18 (10 variable)
  initial  value 16.703197 
  iter  10 value 15.005217
  iter  20 value 14.920712
  final  value 14.920709 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.535397
  final  value 30.530542 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.535397
  final  value 30.530542 
  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 : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -799.0149 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       799.01  |proj g|=       10.119
  At iterate     1  f =       107.62  |proj g|=         2.111
  At iterate     2  f =       73.108  |proj g|=        1.3664
  ys=-2.754e+01  -gs= 1.949e+01, BFGS update SKIPPED
  At iterate     3  f =        71.88  |proj g|=        1.0621
  At iterate     4  f =       71.694  |proj g|=       0.20162
  At iterate     5  f =       71.693  |proj g|=        0.0587
  At iterate     6  f =       71.693  |proj g|=    0.00099014
  At iterate     7  f =       71.693  |proj g|=    4.7623e-06
  
  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 4.76225e-06
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -799.0149 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       799.01  |proj g|=       10.119
  At iterate     1  f =       107.62  |proj g|=         2.111
  At iterate     2  f =       73.108  |proj g|=        1.3664
  ys=-2.754e+01  -gs= 1.949e+01, BFGS update SKIPPED
  At iterate     3  f =        71.88  |proj g|=        1.0621
  At iterate     4  f =       71.694  |proj g|=       0.20162
  At iterate     5  f =       71.693  |proj g|=        0.0587
  At iterate     6  f =       71.693  |proj g|=    0.00099014
  At iterate     7  f =       71.693  |proj g|=    4.7623e-06
  
  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 4.76225e-06
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -94.2585 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       94.259  |proj g|=       9.2433
  At iterate     1  f =       86.519  |proj g|=        3.3716
  At iterate     2  f =        72.69  |proj g|=        1.2807
  ys=-5.482e+00  -gs= 8.119e+00, BFGS update SKIPPED
  At iterate     3  f =       71.706  |proj g|=       0.74401
  At iterate     4  f =       71.693  |proj g|=       0.04299
  At iterate     5  f =       71.693  |proj g|=      0.002871
  At iterate     6  f =       71.693  |proj g|=    1.0216e-05
  At iterate     7  f =       71.693  |proj g|=    2.4167e-09
  
  iterations 7
  function evaluations 13
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 2.4167e-09
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -94.2585 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       94.259  |proj g|=       9.2433
  At iterate     1  f =       86.519  |proj g|=        3.3716
  At iterate     2  f =        72.69  |proj g|=        1.2807
  ys=-5.482e+00  -gs= 8.119e+00, BFGS update SKIPPED
  At iterate     3  f =       71.706  |proj g|=       0.74401
  At iterate     4  f =       71.693  |proj g|=       0.04299
  At iterate     5  f =       71.693  |proj g|=      0.002871
  At iterate     6  f =       71.693  |proj g|=    1.0216e-05
  At iterate     7  f =       71.693  |proj g|=    2.4167e-09
  
  iterations 7
  function evaluations 13
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 2.4167e-09
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -82.5918 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       82.592  |proj g|=       6.3624
  At iterate     1  f =       81.872  |proj g|=         2.904
  At iterate     2  f =       72.794  |proj g|=        1.3028
  ys=-1.739e+00  -gs= 5.887e+00, BFGS update SKIPPED
  At iterate     3  f =       72.758  |proj g|=        1.2951
  At iterate     4  f =       71.728  |proj g|=       0.98205
  At iterate     5  f =       71.693  |proj g|=       0.12957
  At iterate     6  f =       71.693  |proj g|=      0.014926
  At iterate     7  f =       71.693  |proj g|=    0.00016131
  At iterate     8  f =       71.693  |proj g|=    1.9815e-07
  
  iterations 8
  function evaluations 13
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.98153e-07
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.051314e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.960338 
    - variance bounds :  0.1051314 10.70278 
    - best initial criterion value(s) :  -179.526 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       179.53  |proj g|=       9.5794
  At iterate     1  f =       107.62  |proj g|=         2.111
  At iterate     2  f =       72.988  |proj g|=        1.3425
  ys=-2.654e+01  -gs= 1.954e+01, BFGS update SKIPPED
  At iterate     3  f =       72.424  |proj g|=        1.2205
  At iterate     4  f =       71.713  |proj g|=        0.9305
  At iterate     5  f =       71.703  |proj g|=       0.72206
  At iterate     6  f =       71.693  |proj g|=      0.056801
  At iterate     7  f =       71.693  |proj g|=     0.0031658
  At iterate     8  f =       71.693  |proj g|=    1.4913e-05
  At iterate     9  f =       71.693  |proj g|=    3.8926e-09
  
  iterations 9
  function evaluations 26
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.89259e-09
  final function value 71.6929
  
  F = 71.6929
  final  value 71.692869 
  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) :  -274.3572 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       274.36  |proj g|=       5.2571
  At iterate     1  f =       265.15  |proj g|=        1.8338
  At iterate     2  f =       264.98  |proj g|=        1.8323
  At iterate     3  f =       264.85  |proj g|=        1.8303
  At iterate     4  f =       261.72  |proj g|=        1.8011
  At iterate     5  f =       261.48  |proj g|=        3.6812
  At iterate     6  f =       260.71  |proj g|=        5.4414
  At iterate     7  f =       259.82  |proj g|=        9.1406
  At iterate     8  f =          257  |proj g|=        13.797
  At iterate     9  f =       249.93  |proj g|=        2.5537
  At iterate    10  f =       249.83  |proj g|=         1.462
  At iterate    11  f =       249.82  |proj g|=       0.22903
  At iterate    12  f =       249.82  |proj g|=       0.26926
  At iterate    13  f =       249.82  |proj g|=       0.22784
  At iterate    14  f =       249.82  |proj g|=       0.22617
  At iterate    15  f =       249.81  |proj g|=       0.22454
  At iterate    16  f =       249.81  |proj g|=       0.32585
  At iterate    17  f =        249.8  |proj g|=       0.54106
  At iterate    18  f =       249.77  |proj g|=        0.8601
  At iterate    19  f =        249.7  |proj g|=        1.2503
  At iterate    20  f =       249.52  |proj g|=        1.5275
  At iterate    21  f =       249.08  |proj g|=       0.98493
  At iterate    22  f =        248.2  |proj g|=        1.8061
  At iterate    23  f =       247.03  |proj g|=        8.0793
  At iterate    24  f =       245.91  |proj g|=        14.216
  At iterate    25  f =       245.67  |proj g|=        15.765
  At iterate    26  f =       245.41  |proj g|=        16.333
  At iterate    27  f =       244.64  |proj g|=        13.502
  At iterate    28  f =       244.23  |proj g|=        7.6834
  At iterate    29  f =       243.35  |proj g|=        3.3672
  At iterate    30  f =       243.27  |proj g|=       0.25481
  At iterate    31  f =       243.26  |proj g|=      0.093561
  At iterate    32  f =       243.26  |proj g|=       0.14408
  At iterate    33  f =       243.26  |proj g|=       0.14157
  At iterate    34  f =       243.26  |proj g|=        0.1002
  At iterate    35  f =       243.26  |proj g|=     0.0059349
  At iterate    36  f =       243.26  |proj g|=    0.00034231
  
  iterations 36
  function evaluations 48
  segments explored during Cauchy searches 38
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000342312
  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) :  -301.5385 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       301.54  |proj g|=       1.0425
  At iterate     1  f =       270.81  |proj g|=        30.143
  At iterate     2  f =        269.1  |proj g|=        25.165
  At iterate     3  f =       258.88  |proj g|=          11.1
  At iterate     4  f =       253.72  |proj g|=        11.118
  At iterate     5  f =       252.84  |proj g|=        4.9108
  At iterate     6  f =       252.66  |proj g|=        1.7875
  At iterate     7  f =       252.55  |proj g|=        1.1561
  At iterate     8  f =       252.55  |proj g|=       0.20369
  At iterate     9  f =       252.55  |proj g|=       0.20317
  At iterate    10  f =       252.55  |proj g|=       0.23194
  At iterate    11  f =       252.55  |proj g|=        0.4107
  At iterate    12  f =       252.54  |proj g|=       0.66917
  At iterate    13  f =       252.53  |proj g|=        1.1189
  At iterate    14  f =       252.51  |proj g|=        1.8053
  At iterate    15  f =       252.46  |proj g|=        1.8232
  At iterate    16  f =       252.35  |proj g|=        1.8532
  At iterate    17  f =       252.11  |proj g|=        1.8854
  At iterate    18  f =        251.5  |proj g|=        1.9424
  At iterate    19  f =       251.32  |proj g|=        1.9366
  At iterate    20  f =       250.14  |proj g|=        1.9341
  At iterate    21  f =       247.96  |proj g|=        1.8354
  At iterate    22  f =       245.37  |proj g|=        1.6217
  At iterate    23  f =       245.35  |proj g|=        15.767
  At iterate    24  f =        243.3  |proj g|=        1.7311
  At iterate    25  f =       243.27  |proj g|=        1.4132
  At iterate    26  f =       243.27  |proj g|=       0.15219
  At iterate    27  f =       243.26  |proj g|=      0.010618
  At iterate    28  f =       243.26  |proj g|=    0.00048804
  At iterate    29  f =       243.26  |proj g|=    8.4073e-05
  
  iterations 29
  function evaluations 37
  segments explored during Cauchy searches 31
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 8.40728e-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) :  -567.6699 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       567.67  |proj g|=       5.3801
  At iterate     1  f =       327.99  |proj g|=       0.36757
  At iterate     2  f =       318.76  |proj g|=       0.17667
  At iterate     3  f =       318.26  |proj g|=      0.060123
  At iterate     4  f =       318.23  |proj g|=      0.018593
  At iterate     5  f =       318.22  |proj g|=      0.001423
  At iterate     6  f =       318.22  |proj g|=     3.726e-05
  At iterate     7  f =       318.22  |proj g|=    7.2293e-08
  
  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 7.22926e-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) :  -270.0123 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       270.01  |proj g|=       43.738
  At iterate     1  f =       263.56  |proj g|=        1.0266
  At iterate     2  f =        252.8  |proj g|=         16.32
  At iterate     3  f =       250.38  |proj g|=        16.547
  At iterate     4  f =       248.94  |proj g|=        10.651
  At iterate     5  f =       248.03  |proj g|=        1.6339
  At iterate     6  f =       247.94  |proj g|=        1.7038
  At iterate     7  f =       247.94  |proj g|=       0.23986
  At iterate     8  f =       247.94  |proj g|=       0.23931
  At iterate     9  f =       247.94  |proj g|=        1.7029
  At iterate    10  f =       247.93  |proj g|=        1.7038
  At iterate    11  f =       247.89  |proj g|=        1.7065
  At iterate    12  f =       247.81  |proj g|=        1.7103
  At iterate    13  f =       247.57  |proj g|=        1.7177
  At iterate    14  f =       246.95  |proj g|=        2.0412
  At iterate    15  f =       245.72  |proj g|=        1.7579
  At iterate    16  f =       244.72  |proj g|=        1.7519
  At iterate    17  f =       244.06  |proj g|=        1.5346
  At iterate    18  f =       243.88  |proj g|=        1.5026
  At iterate    19  f =       243.46  |proj g|=        1.7334
  At iterate    20  f =       243.32  |proj g|=        1.7288
  At iterate    21  f =       243.27  |proj g|=       0.89966
  At iterate    22  f =       243.26  |proj g|=       0.14435
  At iterate    23  f =       243.26  |proj g|=       0.15253
  At iterate    24  f =       243.26  |proj g|=     0.0085929
  At iterate    25  f =       243.26  |proj g|=    0.00014291
  
  iterations 25
  function evaluations 32
  segments explored during Cauchy searches 27
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000142912
  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 : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -21942.37 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        21942  |proj g|=       8.0858
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       68.706  |proj g|=        1.2326
  ys=-3.075e+01  -gs= 1.909e+01, BFGS update SKIPPED
  At iterate     3  f =        66.53  |proj g|=       0.20738
  At iterate     4  f =        66.53  |proj g|=    0.00095168
  At iterate     5  f =        66.53  |proj g|=    1.3467e-05
  
  iterations 5
  function evaluations 28
  segments explored during Cauchy searches 8
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.34669e-05
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -21942.37 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        21942  |proj g|=       8.0858
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       68.706  |proj g|=        1.2326
  ys=-3.075e+01  -gs= 1.909e+01, BFGS update SKIPPED
  At iterate     3  f =        66.53  |proj g|=       0.20738
  At iterate     4  f =        66.53  |proj g|=    0.00095168
  At iterate     5  f =        66.53  |proj g|=    1.3467e-05
  
  iterations 5
  function evaluations 28
  segments explored during Cauchy searches 8
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.34669e-05
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -22874.63 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        22875  |proj g|=       7.7079
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       67.604  |proj g|=        7.9177
  At iterate     3  f =        66.76  |proj g|=       0.88334
  At iterate     4  f =       66.581  |proj g|=       0.81439
  At iterate     5  f =       66.536  |proj g|=       0.69693
  At iterate     6  f =        66.53  |proj g|=      0.090404
  At iterate     7  f =        66.53  |proj g|=     0.0040216
  At iterate     8  f =        66.53  |proj g|=    2.4569e-05
  At iterate     9  f =        66.53  |proj g|=    6.6267e-09
  
  iterations 9
  function evaluations 27
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.62666e-09
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -22874.63 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        22875  |proj g|=       7.7079
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       67.604  |proj g|=        7.9177
  At iterate     3  f =        66.76  |proj g|=       0.88334
  At iterate     4  f =       66.581  |proj g|=       0.81439
  At iterate     5  f =       66.536  |proj g|=       0.69693
  At iterate     6  f =        66.53  |proj g|=      0.090404
  At iterate     7  f =        66.53  |proj g|=     0.0040216
  At iterate     8  f =        66.53  |proj g|=    2.4569e-05
  At iterate     9  f =        66.53  |proj g|=    6.6267e-09
  
  iterations 9
  function evaluations 27
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.62666e-09
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -3743.261 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       3743.3  |proj g|=       7.6482
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       68.242  |proj g|=        1.1636
  ys=-2.863e+01  -gs= 1.927e+01, BFGS update SKIPPED
  At iterate     3  f =       67.481  |proj g|=        1.0394
  At iterate     4  f =        66.56  |proj g|=       0.80116
  At iterate     5  f =        66.53  |proj g|=       0.12609
  At iterate     6  f =        66.53  |proj g|=      0.013371
  At iterate     7  f =        66.53  |proj g|=    0.00011411
  At iterate     8  f =        66.53  |proj g|=    1.0218e-07
  
  iterations 8
  function evaluations 29
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.02179e-07
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.55138e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.91418 
    - variance bounds :  0.07969634 8.55138 
    - best initial criterion value(s) :  -1086.136 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1086.1  |proj g|=       7.6322
  At iterate     1  f =       102.05  |proj g|=         2.637
  At iterate     2  f =       68.067  |proj g|=        1.1366
  ys=-2.754e+01  -gs= 1.934e+01, BFGS update SKIPPED
  At iterate     3  f =        66.58  |proj g|=        0.8141
  At iterate     4  f =        66.53  |proj g|=      0.061654
  At iterate     5  f =        66.53  |proj g|=     0.0085268
  At iterate     6  f =        66.53  |proj g|=    3.5403e-05
  At iterate     7  f =        66.53  |proj g|=    2.0224e-08
  
  iterations 7
  function evaluations 27
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.02238e-08
  final function value 66.5295
  
  F = 66.5295
  final  value 66.529549 
  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) :  -276.0305 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       276.03  |proj g|=       10.838
  At iterate     1  f =       275.89  |proj g|=       0.41168
  At iterate     2  f =       259.96  |proj g|=        43.712
  At iterate     3  f =       258.02  |proj g|=        43.437
  At iterate     4  f =       245.57  |proj g|=        10.992
  At iterate     5  f =       244.39  |proj g|=        1.7506
  At iterate     6  f =       243.32  |proj g|=         1.139
  At iterate     7  f =       243.28  |proj g|=        1.3584
  At iterate     8  f =       243.28  |proj g|=      0.080222
  At iterate     9  f =       243.28  |proj g|=      0.030963
  At iterate    10  f =       243.28  |proj g|=       0.16118
  At iterate    11  f =       243.28  |proj g|=       0.67201
  At iterate    12  f =       243.28  |proj g|=        1.4866
  At iterate    13  f =       243.27  |proj g|=        1.7276
  At iterate    14  f =       243.27  |proj g|=         1.728
  At iterate    15  f =       243.27  |proj g|=        1.7284
  At iterate    16  f =       243.27  |proj g|=        1.7281
  At iterate    17  f =       243.27  |proj g|=        1.2176
  At iterate    18  f =       243.27  |proj g|=       0.30048
  At iterate    19  f =       243.27  |proj g|=       0.18227
  At iterate    20  f =       243.26  |proj g|=       0.15281
  At iterate    21  f =       243.26  |proj g|=       0.15267
  At iterate    22  f =       243.26  |proj g|=       0.15256
  At iterate    23  f =       243.26  |proj g|=      0.027161
  At iterate    24  f =       243.26  |proj g|=    0.00034888
  
  iterations 24
  function evaluations 31
  segments explored during Cauchy searches 25
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000348875
  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) :  -2357.034 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         2357  |proj g|=       32.934
  At iterate     1  f =       339.36  |proj g|=       0.32897
  At iterate     2  f =       318.34  |proj g|=      0.092365
  At iterate     3  f =       318.22  |proj g|=     0.0043693
  At iterate     4  f =       318.22  |proj g|=     0.0006595
  At iterate     5  f =       318.22  |proj g|=    3.9446e-06
  At iterate     6  f =       318.22  |proj g|=    3.5347e-09
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.53474e-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/th798/17244922/R-release/846/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-15 01:11:12 MST"
[1] "2025-05-15 01:11:12 MST"
Installing package into '/tmp/th798/17244922/R-release/846/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
/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/th798/17244922/R-release/846/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] "2025-05-15 01:11:49 MST"
* using log directory '/tmp/th798/17244922/R-release/846/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 20.190350 
  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 20.025398 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.025398 
  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 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  6 (5 variable)
  initial  value 11.805512 
  iter  10 value 10.917889
  final  value 10.917887 
  converged
  # weights:  6 (5 variable)
  initial  value 11.805512 
  iter  10 value 10.917889
  final  value 10.917887 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 19.336596
  iter  10 value 19.336596
  iter  10 value 19.336596
  final  value 19.336596 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  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 
  final  value 32.218418 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.218418 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.958369 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  converged
  # weights:  18 (10 variable)
  initial  value 17.969302 
  iter  10 value 16.014918
  final  value 15.984180 
  converged
  # weights:  18 (10 variable)
  initial  value 17.969302 
  iter  10 value 16.014918
  final  value 15.984180 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.395500
  final  value 30.387902 
  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 : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -32209.14 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        32209  |proj g|=       7.2554
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =       67.395  |proj g|=        1.1753
  ys=-3.109e+01  -gs= 1.905e+01, BFGS update SKIPPED
  At iterate     3  f =       65.133  |proj g|=       0.73931
  At iterate     4  f =       65.121  |proj g|=      0.022959
  At iterate     5  f =       65.121  |proj g|=     0.0015082
  At iterate     6  f =       65.121  |proj g|=     2.198e-06
  
  iterations 6
  function evaluations 27
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.19799e-06
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -32209.14 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        32209  |proj g|=       7.2554
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =       67.395  |proj g|=        1.1753
  ys=-3.109e+01  -gs= 1.905e+01, BFGS update SKIPPED
  At iterate     3  f =       65.133  |proj g|=       0.73931
  At iterate     4  f =       65.121  |proj g|=      0.022959
  At iterate     5  f =       65.121  |proj g|=     0.0015082
  At iterate     6  f =       65.121  |proj g|=     2.198e-06
  
  iterations 6
  function evaluations 27
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.19799e-06
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -4086.068 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       4086.1  |proj g|=       7.0247
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =       65.825  |proj g|=       0.93592
  ys=-1.844e+01  -gs= 1.972e+01, BFGS update SKIPPED
  At iterate     3  f =       65.315  |proj g|=        0.8213
  At iterate     4  f =       65.129  |proj g|=       0.73447
  At iterate     5  f =       65.121  |proj g|=       0.24694
  At iterate     6  f =       65.121  |proj g|=      0.012823
  At iterate     7  f =       65.121  |proj g|=    0.00019701
  At iterate     8  f =       65.121  |proj g|=    1.6025e-07
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.6025e-07
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -4086.068 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       4086.1  |proj g|=       7.0247
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =       65.825  |proj g|=       0.93592
  ys=-1.844e+01  -gs= 1.972e+01, BFGS update SKIPPED
  At iterate     3  f =       65.315  |proj g|=        0.8213
  At iterate     4  f =       65.129  |proj g|=       0.73447
  At iterate     5  f =       65.121  |proj g|=       0.24694
  At iterate     6  f =       65.121  |proj g|=      0.012823
  At iterate     7  f =       65.121  |proj g|=    0.00019701
  At iterate     8  f =       65.121  |proj g|=    1.6025e-07
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.6025e-07
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -6271.222 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       6271.2  |proj g|=       7.5336
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =         67.1  |proj g|=        1.1347
  ys=-2.996e+01  -gs= 1.917e+01, BFGS update SKIPPED
  At iterate     3  f =       66.326  |proj g|=        1.0206
  At iterate     4  f =        65.13  |proj g|=       0.73639
  At iterate     5  f =       65.121  |proj g|=      0.048623
  At iterate     6  f =       65.121  |proj g|=     0.0028297
  At iterate     7  f =       65.121  |proj g|=    8.7505e-06
  
  iterations 7
  function evaluations 28
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 8.75051e-06
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.082742e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.879493 
    - variance bounds :  0.07835163 8.082742 
    - best initial criterion value(s) :  -148.3024 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        148.3  |proj g|=       7.6393
  At iterate     1  f =       100.64  |proj g|=        2.7899
  At iterate     2  f =        65.86  |proj g|=       0.94234
  ys=-1.903e+01  -gs= 1.970e+01, BFGS update SKIPPED
  At iterate     3  f =       65.334  |proj g|=       0.82683
  At iterate     4  f =       65.131  |proj g|=       0.73748
  At iterate     5  f =       65.122  |proj g|=       0.29997
  At iterate     6  f =       65.121  |proj g|=      0.017789
  At iterate     7  f =       65.121  |proj g|=    0.00033077
  At iterate     8  f =       65.121  |proj g|=     3.734e-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 3.73403e-07
  final function value 65.1205
  
  F = 65.1205
  final  value 65.120512 
  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) :  -317.1527 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       317.15  |proj g|=       44.197
  At iterate     1  f =       315.39  |proj g|=        44.189
  At iterate     2  f =       310.59  |proj g|=        1.5395
  At iterate     3  f =       310.22  |proj g|=        1.5328
  At iterate     4  f =       309.41  |proj g|=        34.801
  At iterate     5  f =       306.76  |proj g|=        44.163
  At iterate     6  f =       301.66  |proj g|=        44.174
  At iterate     7  f =       295.98  |proj g|=        44.173
  At iterate     8  f =       289.58  |proj g|=         44.13
  At iterate     9  f =       285.09  |proj g|=         2.423
  At iterate    10  f =       281.65  |proj g|=         37.66
  At iterate    11  f =       279.41  |proj g|=        43.972
  At iterate    12  f =       277.84  |proj g|=        43.918
  At iterate    13  f =       271.87  |proj g|=        43.781
  At iterate    14  f =       257.31  |proj g|=        3.2125
  At iterate    15  f =       249.69  |proj g|=        18.633
  At iterate    16  f =       247.39  |proj g|=        8.0025
  At iterate    17  f =        246.7  |proj g|=        1.9219
  At iterate    18  f =       246.65  |proj g|=       0.25094
  At iterate    19  f =       246.65  |proj g|=       0.24063
  At iterate    20  f =       246.65  |proj g|=       0.24188
  At iterate    21  f =       246.65  |proj g|=       0.56064
  At iterate    22  f =       246.64  |proj g|=        1.1643
  At iterate    23  f =       246.64  |proj g|=        1.0239
  At iterate    24  f =       246.62  |proj g|=        2.7802
  At iterate    25  f =       246.47  |proj g|=        1.7998
  At iterate    26  f =       245.99  |proj g|=       0.27449
  At iterate    27  f =       244.89  |proj g|=        1.3735
  At iterate    28  f =       244.05  |proj g|=        1.3767
  At iterate    29  f =       243.39  |proj g|=        1.3536
  At iterate    30  f =       243.29  |proj g|=        1.7298
  At iterate    31  f =       243.26  |proj g|=       0.80112
  At iterate    32  f =       243.26  |proj g|=       0.12414
  At iterate    33  f =       243.26  |proj g|=       0.11268
  At iterate    34  f =       243.26  |proj g|=       0.16003
  At iterate    35  f =       243.26  |proj g|=        0.0404
  At iterate    36  f =       243.26  |proj g|=     0.0017258
  At iterate    37  f =       243.26  |proj g|=     0.0093348
  
  iterations 37
  function evaluations 47
  segments explored during Cauchy searches 39
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00933481
  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) :  -279.1881 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       279.19  |proj g|=       34.646
  At iterate     1  f =       276.28  |proj g|=        24.154
  At iterate     2  f =       259.29  |proj g|=       0.55373
  At iterate     3  f =       251.38  |proj g|=         9.178
  At iterate     4  f =       250.66  |proj g|=         6.776
  At iterate     5  f =       250.35  |proj g|=         3.618
  At iterate     6  f =       250.23  |proj g|=       0.22176
  At iterate     7  f =       250.23  |proj g|=       0.22502
  At iterate     8  f =       250.23  |proj g|=       0.22494
  At iterate     9  f =       250.23  |proj g|=       0.22446
  At iterate    10  f =       250.23  |proj g|=       0.22398
  At iterate    11  f =       250.23  |proj g|=       0.22325
  At iterate    12  f =       250.23  |proj g|=       0.22243
  At iterate    13  f =       250.22  |proj g|=       0.22208
  At iterate    14  f =       250.21  |proj g|=        0.5184
  At iterate    15  f =       250.19  |proj g|=        0.8323
  At iterate    16  f =       250.14  |proj g|=        1.9296
  At iterate    17  f =       250.11  |proj g|=        1.1771
  At iterate    18  f =       249.96  |proj g|=         2.833
  At iterate    19  f =       249.21  |proj g|=        6.7775
  At iterate    20  f =       246.59  |proj g|=         12.55
  At iterate    21  f =       244.67  |proj g|=        9.9411
  At iterate    22  f =       243.55  |proj g|=         5.102
  At iterate    23  f =       243.36  |proj g|=       0.15804
  At iterate    24  f =       243.33  |proj g|=        1.7318
  At iterate    25  f =       243.26  |proj g|=       0.24234
  At iterate    26  f =       243.26  |proj g|=      0.043386
  At iterate    27  f =       243.26  |proj g|=     0.0091332
  At iterate    28  f =       243.26  |proj g|=     0.0032768
  
  iterations 28
  function evaluations 38
  segments explored during Cauchy searches 29
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00327675
  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) :  -530.4161 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       530.42  |proj g|=       7.5622
  At iterate     1  f =       326.82  |proj g|=       0.36686
  At iterate     2  f =       320.39  |proj g|=       0.28736
  At iterate     3  f =       318.27  |proj g|=      0.064738
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.25  |proj g|=      0.048567
  At iterate     5  f =       318.22  |proj g|=     0.0035864
  At iterate     6  f =       318.22  |proj g|=    0.00021776
  At iterate     7  f =       318.22  |proj g|=    1.0555e-06
  
  iterations 7
  function evaluations 20
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.05551e-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) :  -8138.239 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       8138.2  |proj g|=        188.1
  At iterate     1  f =       371.36  |proj g|=       0.18465
  At iterate     2  f =        318.4  |proj g|=       0.11119
  At iterate     3  f =       318.22  |proj g|=      0.011579
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=     0.0091461
  At iterate     5  f =       318.22  |proj g|=    0.00014931
  At iterate     6  f =       318.22  |proj g|=    1.8865e-06
  
  iterations 6
  function evaluations 21
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.88653e-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 : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -11202.44 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        11202  |proj g|=       7.2374
  At iterate     1  f =       100.87  |proj g|=        2.7651
  At iterate     2  f =       66.471  |proj g|=         1.055
  ys=-2.794e+01  -gs= 1.945e+01, BFGS update SKIPPED
  At iterate     3  f =       65.948  |proj g|=       0.97291
  At iterate     4  f =       65.027  |proj g|=       0.75209
  At iterate     5  f =        64.99  |proj g|=       0.16516
  At iterate     6  f =       64.989  |proj g|=      0.019477
  At iterate     7  f =       64.989  |proj g|=    0.00020514
  At iterate     8  f =       64.989  |proj g|=    2.5148e-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 2.51483e-07
  final function value 64.9894
  
  F = 64.9894
  final  value 64.989407 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -11202.44 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        11202  |proj g|=       7.2374
  At iterate     1  f =       100.87  |proj g|=        2.7651
  At iterate     2  f =       66.471  |proj g|=         1.055
  ys=-2.794e+01  -gs= 1.945e+01, BFGS update SKIPPED
  At iterate     3  f =       65.948  |proj g|=       0.97291
  At iterate     4  f =       65.027  |proj g|=       0.75209
  At iterate     5  f =        64.99  |proj g|=       0.16516
  At iterate     6  f =       64.989  |proj g|=      0.019477
  At iterate     7  f =       64.989  |proj g|=    0.00020514
  At iterate     8  f =       64.989  |proj g|=    2.5148e-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 2.51483e-07
  final function value 64.9894
  
  F = 64.9894
  final  value 64.989407 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -30223.74 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        30224  |proj g|=       7.4408
  At iterate     1  f =       100.87  |proj g|=        2.7651
  At iterate     2  f =       65.026  |proj g|=        1.8447
  At iterate     3  f =       64.989  |proj g|=      0.030566
  At iterate     4  f =       64.989  |proj g|=     0.0031162
  At iterate     5  f =       64.989  |proj g|=    6.0203e-06
  
  iterations 5
  function evaluations 19
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.02027e-06
  final function value 64.9894
  
  F = 64.9894
  final  value 64.989407 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -30223.74 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        30224  |proj g|=       7.4408
  At iterate     1  f =       100.87  |proj g|=        2.7651
  At iterate     2  f =       65.026  |proj g|=        1.8447
  At iterate     3  f =       64.989  |proj g|=      0.030566
  At iterate     4  f =       64.989  |proj g|=     0.0031162
  At iterate     5  f =       64.989  |proj g|=    6.0203e-06
  
  iterations 5
  function evaluations 19
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.02027e-06
  final function value 64.9894
  
  F = 64.9894
  final  value 64.989407 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -3151.295 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       3151.3  |proj g|=       7.7181
  At iterate     1  f =       100.87  |proj g|=        2.7651
  At iterate     2  f =       65.021  |proj g|=       0.74824
  At iterate     3  f =        64.99  |proj g|=       0.13767
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       64.989  |proj g|=      0.010439
  At iterate     5  f =       64.989  |proj g|=    9.1667e-05
  At iterate     6  f =       64.989  |proj g|=    6.0371e-08
  
  iterations 6
  function evaluations 20
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.03711e-08
  final function value 64.9894
  
  F = 64.9894
  final  value 64.989407 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 8.040466e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.97183 
    - variance bounds :  0.08040466 8.169152 
    - best initial criterion value(s) :  -63.99869 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       63.999  |proj g|=       1.9628
  At iterate     1  f =       63.962  |proj g|=       0.88834
  At iterate     2  f =       63.962  |proj g|=       0.88809
  At iterate     3  f =       63.957  |proj g|=       0.88629
  At iterate     4  f =       63.943  |proj g|=       0.88035
  At iterate     5  f =        63.91  |proj g|=       0.86503
  At iterate     6  f =       63.839  |proj g|=        0.8287
  At iterate     7  f =       63.735  |proj g|=       0.31638
  At iterate     8  f =        63.64  |proj g|=        1.9627
  At iterate     9  f =       63.638  |proj g|=       0.30585
  At iterate    10  f =       63.638  |proj g|=       0.30616
  At iterate    11  f =       63.546  |proj g|=       0.34609
  At iterate    12  f =       63.543  |proj g|=       0.10591
  At iterate    13  f =       63.543  |proj g|=       0.10451
  At iterate    14  f =       63.543  |proj g|=       0.14869
  At iterate    15  f =       63.543  |proj g|=       0.10477
  At iterate    16  f =       63.543  |proj g|=       0.10507
  At iterate    17  f =       63.543  |proj g|=       0.10555
  At iterate    18  f =       63.543  |proj g|=       0.10678
  At iterate    19  f =       63.542  |proj g|=        0.1492
  At iterate    20  f =       63.542  |proj g|=       0.25338
  At iterate    21  f =       63.539  |proj g|=       0.44945
  At iterate    22  f =       63.534  |proj g|=       0.71998
  At iterate    23  f =       63.532  |proj g|=       0.68264
  At iterate    24  f =       63.523  |proj g|=       0.79018
  At iterate    25  f =       63.512  |proj g|=       0.71576
  At iterate    26  f =       63.502  |proj g|=      0.054795
  At iterate    27  f =       63.502  |proj g|=     0.0088703
  At iterate    28  f =       63.502  |proj g|=     0.0012491
  At iterate    29  f =       63.502  |proj g|=     0.0018937
  
  iterations 29
  function evaluations 40
  segments explored during Cauchy searches 32
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 0.00189369
  final function value 63.5017
  
  F = 63.5017
  final  value 63.501718 
  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) :  -313.0482 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       313.05  |proj g|=       44.255
  At iterate     1  f =       280.05  |proj g|=        37.077
  At iterate     2  f =       279.01  |proj g|=        19.549
  At iterate     3  f =       264.48  |proj g|=        43.756
  At iterate     4  f =       264.03  |proj g|=        43.692
  At iterate     5  f =       260.22  |proj g|=        40.885
  At iterate     6  f =        250.6  |proj g|=        4.2167
  At iterate     7  f =       244.74  |proj g|=        5.9914
  At iterate     8  f =        244.5  |proj g|=        1.7204
  At iterate     9  f =       244.49  |proj g|=       0.39125
  At iterate    10  f =       244.48  |proj g|=       0.20593
  At iterate    11  f =       244.48  |proj g|=        0.2057
  At iterate    12  f =       244.48  |proj g|=       0.20368
  At iterate    13  f =       244.47  |proj g|=        0.6912
  At iterate    14  f =       244.44  |proj g|=        1.5071
  At iterate    15  f =       244.38  |proj g|=        1.5237
  At iterate    16  f =       244.23  |proj g|=         1.541
  At iterate    17  f =       244.19  |proj g|=        1.5411
  At iterate    18  f =       243.93  |proj g|=        1.5328
  At iterate    19  f =       243.54  |proj g|=        1.4681
  At iterate    20  f =        243.3  |proj g|=        1.7315
  At iterate    21  f =       243.26  |proj g|=       0.38381
  At iterate    22  f =       243.26  |proj g|=      0.096999
  At iterate    23  f =       243.26  |proj g|=      0.015238
  At iterate    24  f =       243.26  |proj g|=     0.0015599
  
  iterations 24
  function evaluations 33
  segments explored during Cauchy searches 26
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00155994
  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) :  -545.9777 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       545.98  |proj g|=       7.4418
  At iterate     1  f =       323.39  |proj g|=       0.34934
  At iterate     2  f =       320.87  |proj g|=       0.30341
  At iterate     3  f =       318.22  |proj g|=      0.015903
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=      0.012333
  At iterate     5  f =       318.22  |proj g|=    0.00025457
  At iterate     6  f =       318.22  |proj g|=    4.1814e-06
  At iterate     7  f =       318.22  |proj g|=    1.4473e-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 1.4473e-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/th798/17244922/R-release/846/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-05-15 01:14:27 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_version_4.5.0_2025-04-11/release_1.17.2.Rcheck/00check.log	2025-05-15 01:11:12.518544360 -0700
+++ R_version_4.5.0_2025-04-11/master_1.17.99.15932214095653a70048efdc41545968b38a100a.Rcheck/00check.log	2025-05-15 01:14:27.443925064 -0700
@@ -60,27 +60,27 @@
   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 20.391705 
+  final  value 20.794415 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.391705 
+  final  value 20.794415 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.735569 
+  final  value 20.025398 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.735569 
+  final  value 20.025398 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
@@ -92,111 +92,127 @@
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  6 (5 variable)
-  initial  value 11.279303 
-  iter  10 value 10.003473
-  final  value 10.003464 
+  initial  value 11.805512 
+  iter  10 value 10.917889
+  final  value 10.917887 
   converged
   # weights:  6 (5 variable)
-  initial  value 11.279303 
-  iter  10 value 10.003473
-  final  value 10.003464 
+  initial  value 11.805512 
+  iter  10 value 10.917889
+  final  value 10.917887 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 20.286745 
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  iter  10 value 19.336596
+  final  value 19.336596 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.312711 
+  final  value 32.958369 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.312711 
+  final  value 32.958369 
   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 
-  final  value 32.837452 
+  final  value 32.218418 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.837452 
+  final  value 32.218418 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  final  value 32.958369 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  final  value 32.958369 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  18 (10 variable)
-  initial  value 16.703197 
-  iter  10 value 15.005217
-  iter  20 value 14.920712
-  final  value 14.920709 
+  initial  value 17.969302 
+  iter  10 value 16.014918
+  final  value 15.984180 
   converged
   # weights:  18 (10 variable)
-  initial  value 16.703197 
-  iter  10 value 15.005217
-  iter  20 value 14.920712
-  final  value 14.920709 
+  initial  value 17.969302 
+  iter  10 value 16.014918
+  final  value 15.984180 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 30.535397
-  final  value 30.530542 
+  iter  10 value 30.395500
+  final  value 30.387902 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -305,34 +321,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -799.0149 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -32209.14 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       799.01  |proj g|=       10.119
-  At iterate     1  f =       107.62  |proj g|=         2.111
-  At iterate     2  f =       73.108  |proj g|=        1.3664
-  ys=-2.754e+01  -gs= 1.949e+01, BFGS update SKIPPED
-  At iterate     3  f =        71.88  |proj g|=        1.0621
-  At iterate     4  f =       71.694  |proj g|=       0.20162
-  At iterate     5  f =       71.693  |proj g|=        0.0587
-  At iterate     6  f =       71.693  |proj g|=    0.00099014
-  At iterate     7  f =       71.693  |proj g|=    4.7623e-06
+  At iterate     0  f=        32209  |proj g|=       7.2554
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =       67.395  |proj g|=        1.1753
+  ys=-3.109e+01  -gs= 1.905e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.133  |proj g|=       0.73931
+  At iterate     4  f =       65.121  |proj g|=      0.022959
+  At iterate     5  f =       65.121  |proj g|=     0.0015082
+  At iterate     6  f =       65.121  |proj g|=     2.198e-06
   
-  iterations 7
-  function evaluations 25
-  segments explored during Cauchy searches 10
+  iterations 6
+  function evaluations 27
+  segments explored during Cauchy searches 9
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.76225e-06
-  final function value 71.6929
+  norm of the final projected gradient 2.19799e-06
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -343,34 +358,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -799.0149 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -32209.14 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       799.01  |proj g|=       10.119
-  At iterate     1  f =       107.62  |proj g|=         2.111
-  At iterate     2  f =       73.108  |proj g|=        1.3664
-  ys=-2.754e+01  -gs= 1.949e+01, BFGS update SKIPPED
-  At iterate     3  f =        71.88  |proj g|=        1.0621
-  At iterate     4  f =       71.694  |proj g|=       0.20162
-  At iterate     5  f =       71.693  |proj g|=        0.0587
-  At iterate     6  f =       71.693  |proj g|=    0.00099014
-  At iterate     7  f =       71.693  |proj g|=    4.7623e-06
+  At iterate     0  f=        32209  |proj g|=       7.2554
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =       67.395  |proj g|=        1.1753
+  ys=-3.109e+01  -gs= 1.905e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.133  |proj g|=       0.73931
+  At iterate     4  f =       65.121  |proj g|=      0.022959
+  At iterate     5  f =       65.121  |proj g|=     0.0015082
+  At iterate     6  f =       65.121  |proj g|=     2.198e-06
   
-  iterations 7
-  function evaluations 25
-  segments explored during Cauchy searches 10
+  iterations 6
+  function evaluations 27
+  segments explored during Cauchy searches 9
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.76225e-06
-  final function value 71.6929
+  norm of the final projected gradient 2.19799e-06
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -381,34 +395,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -94.2585 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -4086.068 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       94.259  |proj g|=       9.2433
-  At iterate     1  f =       86.519  |proj g|=        3.3716
-  At iterate     2  f =        72.69  |proj g|=        1.2807
-  ys=-5.482e+00  -gs= 8.119e+00, BFGS update SKIPPED
-  At iterate     3  f =       71.706  |proj g|=       0.74401
-  At iterate     4  f =       71.693  |proj g|=       0.04299
-  At iterate     5  f =       71.693  |proj g|=      0.002871
-  At iterate     6  f =       71.693  |proj g|=    1.0216e-05
-  At iterate     7  f =       71.693  |proj g|=    2.4167e-09
+  At iterate     0  f=       4086.1  |proj g|=       7.0247
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =       65.825  |proj g|=       0.93592
+  ys=-1.844e+01  -gs= 1.972e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.315  |proj g|=        0.8213
+  At iterate     4  f =       65.129  |proj g|=       0.73447
+  At iterate     5  f =       65.121  |proj g|=       0.24694
+  At iterate     6  f =       65.121  |proj g|=      0.012823
+  At iterate     7  f =       65.121  |proj g|=    0.00019701
+  At iterate     8  f =       65.121  |proj g|=    1.6025e-07
   
-  iterations 7
-  function evaluations 13
-  segments explored during Cauchy searches 10
+  iterations 8
+  function evaluations 24
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 2.4167e-09
-  final function value 71.6929
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 1.6025e-07
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -419,34 +434,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -94.2585 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -4086.068 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       94.259  |proj g|=       9.2433
-  At iterate     1  f =       86.519  |proj g|=        3.3716
-  At iterate     2  f =        72.69  |proj g|=        1.2807
-  ys=-5.482e+00  -gs= 8.119e+00, BFGS update SKIPPED
-  At iterate     3  f =       71.706  |proj g|=       0.74401
-  At iterate     4  f =       71.693  |proj g|=       0.04299
-  At iterate     5  f =       71.693  |proj g|=      0.002871
-  At iterate     6  f =       71.693  |proj g|=    1.0216e-05
-  At iterate     7  f =       71.693  |proj g|=    2.4167e-09
+  At iterate     0  f=       4086.1  |proj g|=       7.0247
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =       65.825  |proj g|=       0.93592
+  ys=-1.844e+01  -gs= 1.972e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.315  |proj g|=        0.8213
+  At iterate     4  f =       65.129  |proj g|=       0.73447
+  At iterate     5  f =       65.121  |proj g|=       0.24694
+  At iterate     6  f =       65.121  |proj g|=      0.012823
+  At iterate     7  f =       65.121  |proj g|=    0.00019701
+  At iterate     8  f =       65.121  |proj g|=    1.6025e-07
   
-  iterations 7
-  function evaluations 13
-  segments explored during Cauchy searches 10
+  iterations 8
+  function evaluations 24
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 1
-  norm of the final projected gradient 2.4167e-09
-  final function value 71.6929
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 1.6025e-07
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -457,35 +473,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -82.5918 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -6271.222 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       82.592  |proj g|=       6.3624
-  At iterate     1  f =       81.872  |proj g|=         2.904
-  At iterate     2  f =       72.794  |proj g|=        1.3028
-  ys=-1.739e+00  -gs= 5.887e+00, BFGS update SKIPPED
-  At iterate     3  f =       72.758  |proj g|=        1.2951
-  At iterate     4  f =       71.728  |proj g|=       0.98205
-  At iterate     5  f =       71.693  |proj g|=       0.12957
-  At iterate     6  f =       71.693  |proj g|=      0.014926
-  At iterate     7  f =       71.693  |proj g|=    0.00016131
-  At iterate     8  f =       71.693  |proj g|=    1.9815e-07
+  At iterate     0  f=       6271.2  |proj g|=       7.5336
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =         67.1  |proj g|=        1.1347
+  ys=-2.996e+01  -gs= 1.917e+01, BFGS update SKIPPED
+  At iterate     3  f =       66.326  |proj g|=        1.0206
+  At iterate     4  f =        65.13  |proj g|=       0.73639
+  At iterate     5  f =       65.121  |proj g|=      0.048623
+  At iterate     6  f =       65.121  |proj g|=     0.0028297
+  At iterate     7  f =       65.121  |proj g|=    8.7505e-06
   
-  iterations 8
-  function evaluations 13
-  segments explored during Cauchy searches 11
+  iterations 7
+  function evaluations 28
+  segments explored during Cauchy searches 10
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.98153e-07
-  final function value 71.6929
+  norm of the final projected gradient 8.75051e-06
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -496,36 +511,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.051314e-08 
+    - nugget : 8.082742e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.960338 
-    - variance bounds :  0.1051314 10.70278 
-    - best initial criterion value(s) :  -179.526 
+    - parameters upper bounds :  4 2 1.879493 
+    - variance bounds :  0.07835163 8.082742 
+    - best initial criterion value(s) :  -148.3024 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       179.53  |proj g|=       9.5794
-  At iterate     1  f =       107.62  |proj g|=         2.111
-  At iterate     2  f =       72.988  |proj g|=        1.3425
-  ys=-2.654e+01  -gs= 1.954e+01, BFGS update SKIPPED
-  At iterate     3  f =       72.424  |proj g|=        1.2205
-  At iterate     4  f =       71.713  |proj g|=        0.9305
-  At iterate     5  f =       71.703  |proj g|=       0.72206
-  At iterate     6  f =       71.693  |proj g|=      0.056801
-  At iterate     7  f =       71.693  |proj g|=     0.0031658
-  At iterate     8  f =       71.693  |proj g|=    1.4913e-05
-  At iterate     9  f =       71.693  |proj g|=    3.8926e-09
+  At iterate     0  f=        148.3  |proj g|=       7.6393
+  At iterate     1  f =       100.64  |proj g|=        2.7899
+  At iterate     2  f =        65.86  |proj g|=       0.94234
+  ys=-1.903e+01  -gs= 1.970e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.334  |proj g|=       0.82683
+  At iterate     4  f =       65.131  |proj g|=       0.73748
+  At iterate     5  f =       65.122  |proj g|=       0.29997
+  At iterate     6  f =       65.121  |proj g|=      0.017789
+  At iterate     7  f =       65.121  |proj g|=    0.00033077
+  At iterate     8  f =       65.121  |proj g|=     3.734e-07
   
-  iterations 9
-  function evaluations 26
-  segments explored during Cauchy searches 12
+  iterations 8
+  function evaluations 24
+  segments explored during Cauchy searches 11
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 3.89259e-09
-  final function value 71.6929
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 3.73403e-07
+  final function value 65.1205
   
-  F = 71.6929
-  final  value 71.692869 
+  F = 65.1205
+  final  value 65.120512 
   converged
   
   optimisation start
@@ -540,54 +554,55 @@
     - 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) :  -274.3572 
+    - best initial criterion value(s) :  -317.1527 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       274.36  |proj g|=       5.2571
-  At iterate     1  f =       265.15  |proj g|=        1.8338
-  At iterate     2  f =       264.98  |proj g|=        1.8323
-  At iterate     3  f =       264.85  |proj g|=        1.8303
-  At iterate     4  f =       261.72  |proj g|=        1.8011
-  At iterate     5  f =       261.48  |proj g|=        3.6812
-  At iterate     6  f =       260.71  |proj g|=        5.4414
-  At iterate     7  f =       259.82  |proj g|=        9.1406
-  At iterate     8  f =          257  |proj g|=        13.797
-  At iterate     9  f =       249.93  |proj g|=        2.5537
-  At iterate    10  f =       249.83  |proj g|=         1.462
-  At iterate    11  f =       249.82  |proj g|=       0.22903
-  At iterate    12  f =       249.82  |proj g|=       0.26926
-  At iterate    13  f =       249.82  |proj g|=       0.22784
-  At iterate    14  f =       249.82  |proj g|=       0.22617
-  At iterate    15  f =       249.81  |proj g|=       0.22454
-  At iterate    16  f =       249.81  |proj g|=       0.32585
-  At iterate    17  f =        249.8  |proj g|=       0.54106
-  At iterate    18  f =       249.77  |proj g|=        0.8601
-  At iterate    19  f =        249.7  |proj g|=        1.2503
-  At iterate    20  f =       249.52  |proj g|=        1.5275
-  At iterate    21  f =       249.08  |proj g|=       0.98493
-  At iterate    22  f =        248.2  |proj g|=        1.8061
-  At iterate    23  f =       247.03  |proj g|=        8.0793
-  At iterate    24  f =       245.91  |proj g|=        14.216
-  At iterate    25  f =       245.67  |proj g|=        15.765
-  At iterate    26  f =       245.41  |proj g|=        16.333
-  At iterate    27  f =       244.64  |proj g|=        13.502
-  At iterate    28  f =       244.23  |proj g|=        7.6834
-  At iterate    29  f =       243.35  |proj g|=        3.3672
-  At iterate    30  f =       243.27  |proj g|=       0.25481
-  At iterate    31  f =       243.26  |proj g|=      0.093561
-  At iterate    32  f =       243.26  |proj g|=       0.14408
-  At iterate    33  f =       243.26  |proj g|=       0.14157
-  At iterate    34  f =       243.26  |proj g|=        0.1002
-  At iterate    35  f =       243.26  |proj g|=     0.0059349
-  At iterate    36  f =       243.26  |proj g|=    0.00034231
-  
-  iterations 36
-  function evaluations 48
-  segments explored during Cauchy searches 38
+  At iterate     0  f=       317.15  |proj g|=       44.197
+  At iterate     1  f =       315.39  |proj g|=        44.189
+  At iterate     2  f =       310.59  |proj g|=        1.5395
+  At iterate     3  f =       310.22  |proj g|=        1.5328
+  At iterate     4  f =       309.41  |proj g|=        34.801
+  At iterate     5  f =       306.76  |proj g|=        44.163
+  At iterate     6  f =       301.66  |proj g|=        44.174
+  At iterate     7  f =       295.98  |proj g|=        44.173
+  At iterate     8  f =       289.58  |proj g|=         44.13
+  At iterate     9  f =       285.09  |proj g|=         2.423
+  At iterate    10  f =       281.65  |proj g|=         37.66
+  At iterate    11  f =       279.41  |proj g|=        43.972
+  At iterate    12  f =       277.84  |proj g|=        43.918
+  At iterate    13  f =       271.87  |proj g|=        43.781
+  At iterate    14  f =       257.31  |proj g|=        3.2125
+  At iterate    15  f =       249.69  |proj g|=        18.633
+  At iterate    16  f =       247.39  |proj g|=        8.0025
+  At iterate    17  f =        246.7  |proj g|=        1.9219
+  At iterate    18  f =       246.65  |proj g|=       0.25094
+  At iterate    19  f =       246.65  |proj g|=       0.24063
+  At iterate    20  f =       246.65  |proj g|=       0.24188
+  At iterate    21  f =       246.65  |proj g|=       0.56064
+  At iterate    22  f =       246.64  |proj g|=        1.1643
+  At iterate    23  f =       246.64  |proj g|=        1.0239
+  At iterate    24  f =       246.62  |proj g|=        2.7802
+  At iterate    25  f =       246.47  |proj g|=        1.7998
+  At iterate    26  f =       245.99  |proj g|=       0.27449
+  At iterate    27  f =       244.89  |proj g|=        1.3735
+  At iterate    28  f =       244.05  |proj g|=        1.3767
+  At iterate    29  f =       243.39  |proj g|=        1.3536
+  At iterate    30  f =       243.29  |proj g|=        1.7298
+  At iterate    31  f =       243.26  |proj g|=       0.80112
+  At iterate    32  f =       243.26  |proj g|=       0.12414
+  At iterate    33  f =       243.26  |proj g|=       0.11268
+  At iterate    34  f =       243.26  |proj g|=       0.16003
+  At iterate    35  f =       243.26  |proj g|=        0.0404
+  At iterate    36  f =       243.26  |proj g|=     0.0017258
+  At iterate    37  f =       243.26  |proj g|=     0.0093348
+  
+  iterations 37
+  function evaluations 47
+  segments explored during Cauchy searches 39
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000342312
+  norm of the final projected gradient 0.00933481
   final function value 243.264
   
   F = 243.264
@@ -606,47 +621,46 @@
     - 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) :  -301.5385 
+    - best initial criterion value(s) :  -279.1881 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       301.54  |proj g|=       1.0425
-  At iterate     1  f =       270.81  |proj g|=        30.143
-  At iterate     2  f =        269.1  |proj g|=        25.165
-  At iterate     3  f =       258.88  |proj g|=          11.1
-  At iterate     4  f =       253.72  |proj g|=        11.118
-  At iterate     5  f =       252.84  |proj g|=        4.9108
-  At iterate     6  f =       252.66  |proj g|=        1.7875
-  At iterate     7  f =       252.55  |proj g|=        1.1561
-  At iterate     8  f =       252.55  |proj g|=       0.20369
-  At iterate     9  f =       252.55  |proj g|=       0.20317
-  At iterate    10  f =       252.55  |proj g|=       0.23194
-  At iterate    11  f =       252.55  |proj g|=        0.4107
-  At iterate    12  f =       252.54  |proj g|=       0.66917
-  At iterate    13  f =       252.53  |proj g|=        1.1189
-  At iterate    14  f =       252.51  |proj g|=        1.8053
-  At iterate    15  f =       252.46  |proj g|=        1.8232
-  At iterate    16  f =       252.35  |proj g|=        1.8532
-  At iterate    17  f =       252.11  |proj g|=        1.8854
-  At iterate    18  f =        251.5  |proj g|=        1.9424
-  At iterate    19  f =       251.32  |proj g|=        1.9366
-  At iterate    20  f =       250.14  |proj g|=        1.9341
-  At iterate    21  f =       247.96  |proj g|=        1.8354
-  At iterate    22  f =       245.37  |proj g|=        1.6217
-  At iterate    23  f =       245.35  |proj g|=        15.767
-  At iterate    24  f =        243.3  |proj g|=        1.7311
-  At iterate    25  f =       243.27  |proj g|=        1.4132
-  At iterate    26  f =       243.27  |proj g|=       0.15219
-  At iterate    27  f =       243.26  |proj g|=      0.010618
-  At iterate    28  f =       243.26  |proj g|=    0.00048804
-  At iterate    29  f =       243.26  |proj g|=    8.4073e-05
-  
-  iterations 29
-  function evaluations 37
-  segments explored during Cauchy searches 31
+  At iterate     0  f=       279.19  |proj g|=       34.646
+  At iterate     1  f =       276.28  |proj g|=        24.154
+  At iterate     2  f =       259.29  |proj g|=       0.55373
+  At iterate     3  f =       251.38  |proj g|=         9.178
+  At iterate     4  f =       250.66  |proj g|=         6.776
+  At iterate     5  f =       250.35  |proj g|=         3.618
+  At iterate     6  f =       250.23  |proj g|=       0.22176
+  At iterate     7  f =       250.23  |proj g|=       0.22502
+  At iterate     8  f =       250.23  |proj g|=       0.22494
+  At iterate     9  f =       250.23  |proj g|=       0.22446
+  At iterate    10  f =       250.23  |proj g|=       0.22398
+  At iterate    11  f =       250.23  |proj g|=       0.22325
+  At iterate    12  f =       250.23  |proj g|=       0.22243
+  At iterate    13  f =       250.22  |proj g|=       0.22208
+  At iterate    14  f =       250.21  |proj g|=        0.5184
+  At iterate    15  f =       250.19  |proj g|=        0.8323
+  At iterate    16  f =       250.14  |proj g|=        1.9296
+  At iterate    17  f =       250.11  |proj g|=        1.1771
+  At iterate    18  f =       249.96  |proj g|=         2.833
+  At iterate    19  f =       249.21  |proj g|=        6.7775
+  At iterate    20  f =       246.59  |proj g|=         12.55
+  At iterate    21  f =       244.67  |proj g|=        9.9411
+  At iterate    22  f =       243.55  |proj g|=         5.102
+  At iterate    23  f =       243.36  |proj g|=       0.15804
+  At iterate    24  f =       243.33  |proj g|=        1.7318
+  At iterate    25  f =       243.26  |proj g|=       0.24234
+  At iterate    26  f =       243.26  |proj g|=      0.043386
+  At iterate    27  f =       243.26  |proj g|=     0.0091332
+  At iterate    28  f =       243.26  |proj g|=     0.0032768
+  
+  iterations 28
+  function evaluations 38
+  segments explored during Cauchy searches 29
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 8.40728e-05
+  norm of the final projected gradient 0.00327675
   final function value 243.264
   
   F = 243.264
@@ -665,25 +679,27 @@
     - 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) :  -567.6699 
+    - best initial criterion value(s) :  -530.4161 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       567.67  |proj g|=       5.3801
-  At iterate     1  f =       327.99  |proj g|=       0.36757
-  At iterate     2  f =       318.76  |proj g|=       0.17667
-  At iterate     3  f =       318.26  |proj g|=      0.060123
-  At iterate     4  f =       318.23  |proj g|=      0.018593
-  At iterate     5  f =       318.22  |proj g|=      0.001423
-  At iterate     6  f =       318.22  |proj g|=     3.726e-05
-  At iterate     7  f =       318.22  |proj g|=    7.2293e-08
+  At iterate     0  f=       530.42  |proj g|=       7.5622
+  At iterate     1  f =       326.82  |proj g|=       0.36686
+  At iterate     2  f =       320.39  |proj g|=       0.28736
+  At iterate     3  f =       318.27  |proj g|=      0.064738
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.25  |proj g|=      0.048567
+  At iterate     5  f =       318.22  |proj g|=     0.0035864
+  At iterate     6  f =       318.22  |proj g|=    0.00021776
+  At iterate     7  f =       318.22  |proj g|=    1.0555e-06
   
   iterations 7
-  function evaluations 15
-  segments explored during Cauchy searches 9
+  function evaluations 20
+  segments explored during Cauchy searches 11
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 7.22926e-08
+  norm of the final projected gradient 1.05551e-06
   final function value 318.222
   
   F = 318.222
@@ -702,47 +718,30 @@
     - 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) :  -270.0123 
+    - best initial criterion value(s) :  -8138.239 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       270.01  |proj g|=       43.738
-  At iterate     1  f =       263.56  |proj g|=        1.0266
-  At iterate     2  f =        252.8  |proj g|=         16.32
-  At iterate     3  f =       250.38  |proj g|=        16.547
-  At iterate     4  f =       248.94  |proj g|=        10.651
-  At iterate     5  f =       248.03  |proj g|=        1.6339
-  At iterate     6  f =       247.94  |proj g|=        1.7038
-  At iterate     7  f =       247.94  |proj g|=       0.23986
-  At iterate     8  f =       247.94  |proj g|=       0.23931
-  At iterate     9  f =       247.94  |proj g|=        1.7029
-  At iterate    10  f =       247.93  |proj g|=        1.7038
-  At iterate    11  f =       247.89  |proj g|=        1.7065
-  At iterate    12  f =       247.81  |proj g|=        1.7103
-  At iterate    13  f =       247.57  |proj g|=        1.7177
-  At iterate    14  f =       246.95  |proj g|=        2.0412
-  At iterate    15  f =       245.72  |proj g|=        1.7579
-  At iterate    16  f =       244.72  |proj g|=        1.7519
-  At iterate    17  f =       244.06  |proj g|=        1.5346
-  At iterate    18  f =       243.88  |proj g|=        1.5026
-  At iterate    19  f =       243.46  |proj g|=        1.7334
-  At iterate    20  f =       243.32  |proj g|=        1.7288
-  At iterate    21  f =       243.27  |proj g|=       0.89966
-  At iterate    22  f =       243.26  |proj g|=       0.14435
-  At iterate    23  f =       243.26  |proj g|=       0.15253
-  At iterate    24  f =       243.26  |proj g|=     0.0085929
-  At iterate    25  f =       243.26  |proj g|=    0.00014291
-  
-  iterations 25
-  function evaluations 32
-  segments explored during Cauchy searches 27
+  At iterate     0  f=       8138.2  |proj g|=        188.1
+  At iterate     1  f =       371.36  |proj g|=       0.18465
+  At iterate     2  f =        318.4  |proj g|=       0.11119
+  At iterate     3  f =       318.22  |proj g|=      0.011579
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.22  |proj g|=     0.0091461
+  At iterate     5  f =       318.22  |proj g|=    0.00014931
+  At iterate     6  f =       318.22  |proj g|=    1.8865e-06
+  
+  iterations 6
+  function evaluations 21
+  segments explored during Cauchy searches 10
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000142912
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 1.88653e-06
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   
   optimisation start
@@ -753,32 +752,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -21942.37 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -11202.44 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        21942  |proj g|=       8.0858
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       68.706  |proj g|=        1.2326
-  ys=-3.075e+01  -gs= 1.909e+01, BFGS update SKIPPED
-  At iterate     3  f =        66.53  |proj g|=       0.20738
-  At iterate     4  f =        66.53  |proj g|=    0.00095168
-  At iterate     5  f =        66.53  |proj g|=    1.3467e-05
+  At iterate     0  f=        11202  |proj g|=       7.2374
+  At iterate     1  f =       100.87  |proj g|=        2.7651
+  At iterate     2  f =       66.471  |proj g|=         1.055
+  ys=-2.794e+01  -gs= 1.945e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.948  |proj g|=       0.97291
+  At iterate     4  f =       65.027  |proj g|=       0.75209
+  At iterate     5  f =        64.99  |proj g|=       0.16516
+  At iterate     6  f =       64.989  |proj g|=      0.019477
+  At iterate     7  f =       64.989  |proj g|=    0.00020514
+  At iterate     8  f =       64.989  |proj g|=    2.5148e-07
   
-  iterations 5
-  function evaluations 28
-  segments explored during Cauchy searches 8
+  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 1.34669e-05
-  final function value 66.5295
+  norm of the final projected gradient 2.51483e-07
+  final function value 64.9894
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 64.9894
+  final  value 64.989407 
   converged
   
   optimisation start
@@ -789,32 +791,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -21942.37 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -11202.44 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        21942  |proj g|=       8.0858
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       68.706  |proj g|=        1.2326
-  ys=-3.075e+01  -gs= 1.909e+01, BFGS update SKIPPED
-  At iterate     3  f =        66.53  |proj g|=       0.20738
-  At iterate     4  f =        66.53  |proj g|=    0.00095168
-  At iterate     5  f =        66.53  |proj g|=    1.3467e-05
+  At iterate     0  f=        11202  |proj g|=       7.2374
+  At iterate     1  f =       100.87  |proj g|=        2.7651
+  At iterate     2  f =       66.471  |proj g|=         1.055
+  ys=-2.794e+01  -gs= 1.945e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.948  |proj g|=       0.97291
+  At iterate     4  f =       65.027  |proj g|=       0.75209
+  At iterate     5  f =        64.99  |proj g|=       0.16516
+  At iterate     6  f =       64.989  |proj g|=      0.019477
+  At iterate     7  f =       64.989  |proj g|=    0.00020514
+  At iterate     8  f =       64.989  |proj g|=    2.5148e-07
   
-  iterations 5
-  function evaluations 28
-  segments explored during Cauchy searches 8
+  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 1.34669e-05
-  final function value 66.5295
+  norm of the final projected gradient 2.51483e-07
+  final function value 64.9894
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 64.9894
+  final  value 64.989407 
   converged
   
   optimisation start
@@ -825,35 +830,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -22874.63 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -30223.74 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        22875  |proj g|=       7.7079
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       67.604  |proj g|=        7.9177
-  At iterate     3  f =        66.76  |proj g|=       0.88334
-  At iterate     4  f =       66.581  |proj g|=       0.81439
-  At iterate     5  f =       66.536  |proj g|=       0.69693
-  At iterate     6  f =        66.53  |proj g|=      0.090404
-  At iterate     7  f =        66.53  |proj g|=     0.0040216
-  At iterate     8  f =        66.53  |proj g|=    2.4569e-05
-  At iterate     9  f =        66.53  |proj g|=    6.6267e-09
+  At iterate     0  f=        30224  |proj g|=       7.4408
+  At iterate     1  f =       100.87  |proj g|=        2.7651
+  At iterate     2  f =       65.026  |proj g|=        1.8447
+  At iterate     3  f =       64.989  |proj g|=      0.030566
+  At iterate     4  f =       64.989  |proj g|=     0.0031162
+  At iterate     5  f =       64.989  |proj g|=    6.0203e-06
   
-  iterations 9
-  function evaluations 27
-  segments explored during Cauchy searches 12
+  iterations 5
+  function evaluations 19
+  segments explored during Cauchy searches 8
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 6.62666e-09
-  final function value 66.5295
+  norm of the final projected gradient 6.02027e-06
+  final function value 64.9894
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 64.9894
+  final  value 64.989407 
   converged
   
   optimisation start
@@ -864,35 +865,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -22874.63 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -30223.74 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        22875  |proj g|=       7.7079
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       67.604  |proj g|=        7.9177
-  At iterate     3  f =        66.76  |proj g|=       0.88334
-  At iterate     4  f =       66.581  |proj g|=       0.81439
-  At iterate     5  f =       66.536  |proj g|=       0.69693
-  At iterate     6  f =        66.53  |proj g|=      0.090404
-  At iterate     7  f =        66.53  |proj g|=     0.0040216
-  At iterate     8  f =        66.53  |proj g|=    2.4569e-05
-  At iterate     9  f =        66.53  |proj g|=    6.6267e-09
+  At iterate     0  f=        30224  |proj g|=       7.4408
+  At iterate     1  f =       100.87  |proj g|=        2.7651
+  At iterate     2  f =       65.026  |proj g|=        1.8447
+  At iterate     3  f =       64.989  |proj g|=      0.030566
+  At iterate     4  f =       64.989  |proj g|=     0.0031162
+  At iterate     5  f =       64.989  |proj g|=    6.0203e-06
   
-  iterations 9
-  function evaluations 27
-  segments explored during Cauchy searches 12
+  iterations 5
+  function evaluations 19
+  segments explored during Cauchy searches 8
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 6.62666e-09
-  final function value 66.5295
+  norm of the final projected gradient 6.02027e-06
+  final function value 64.9894
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 64.9894
+  final  value 64.989407 
   converged
   
   optimisation start
@@ -903,35 +900,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -3743.261 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -3151.295 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       3743.3  |proj g|=       7.6482
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       68.242  |proj g|=        1.1636
-  ys=-2.863e+01  -gs= 1.927e+01, BFGS update SKIPPED
-  At iterate     3  f =       67.481  |proj g|=        1.0394
-  At iterate     4  f =        66.56  |proj g|=       0.80116
-  At iterate     5  f =        66.53  |proj g|=       0.12609
-  At iterate     6  f =        66.53  |proj g|=      0.013371
-  At iterate     7  f =        66.53  |proj g|=    0.00011411
-  At iterate     8  f =        66.53  |proj g|=    1.0218e-07
+  At iterate     0  f=       3151.3  |proj g|=       7.7181
+  At iterate     1  f =       100.87  |proj g|=        2.7651
+  At iterate     2  f =       65.021  |proj g|=       0.74824
+  At iterate     3  f =        64.99  |proj g|=       0.13767
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       64.989  |proj g|=      0.010439
+  At iterate     5  f =       64.989  |proj g|=    9.1667e-05
+  At iterate     6  f =       64.989  |proj g|=    6.0371e-08
   
-  iterations 8
-  function evaluations 29
+  iterations 6
+  function evaluations 20
   segments explored during Cauchy searches 11
-  BFGS updates skipped 1
+  BFGS updates skipped 0
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.02179e-07
-  final function value 66.5295
+  norm of the final projected gradient 6.03711e-08
+  final function value 64.9894
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 64.9894
+  final  value 64.989407 
   converged
   
   optimisation start
@@ -942,34 +938,55 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 8.55138e-09 
+    - nugget : 8.040466e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.91418 
-    - variance bounds :  0.07969634 8.55138 
-    - best initial criterion value(s) :  -1086.136 
+    - parameters upper bounds :  4 2 1.97183 
+    - variance bounds :  0.08040466 8.169152 
+    - best initial criterion value(s) :  -63.99869 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1086.1  |proj g|=       7.6322
-  At iterate     1  f =       102.05  |proj g|=         2.637
-  At iterate     2  f =       68.067  |proj g|=        1.1366
-  ys=-2.754e+01  -gs= 1.934e+01, BFGS update SKIPPED
-  At iterate     3  f =        66.58  |proj g|=        0.8141
-  At iterate     4  f =        66.53  |proj g|=      0.061654
-  At iterate     5  f =        66.53  |proj g|=     0.0085268
-  At iterate     6  f =        66.53  |proj g|=    3.5403e-05
-  At iterate     7  f =        66.53  |proj g|=    2.0224e-08
+  At iterate     0  f=       63.999  |proj g|=       1.9628
+  At iterate     1  f =       63.962  |proj g|=       0.88834
+  At iterate     2  f =       63.962  |proj g|=       0.88809
+  At iterate     3  f =       63.957  |proj g|=       0.88629
+  At iterate     4  f =       63.943  |proj g|=       0.88035
+  At iterate     5  f =        63.91  |proj g|=       0.86503
+  At iterate     6  f =       63.839  |proj g|=        0.8287
+  At iterate     7  f =       63.735  |proj g|=       0.31638
+  At iterate     8  f =        63.64  |proj g|=        1.9627
+  At iterate     9  f =       63.638  |proj g|=       0.30585
+  At iterate    10  f =       63.638  |proj g|=       0.30616
+  At iterate    11  f =       63.546  |proj g|=       0.34609
+  At iterate    12  f =       63.543  |proj g|=       0.10591
+  At iterate    13  f =       63.543  |proj g|=       0.10451
+  At iterate    14  f =       63.543  |proj g|=       0.14869
+  At iterate    15  f =       63.543  |proj g|=       0.10477
+  At iterate    16  f =       63.543  |proj g|=       0.10507
+  At iterate    17  f =       63.543  |proj g|=       0.10555
+  At iterate    18  f =       63.543  |proj g|=       0.10678
+  At iterate    19  f =       63.542  |proj g|=        0.1492
+  At iterate    20  f =       63.542  |proj g|=       0.25338
+  At iterate    21  f =       63.539  |proj g|=       0.44945
+  At iterate    22  f =       63.534  |proj g|=       0.71998
+  At iterate    23  f =       63.532  |proj g|=       0.68264
+  At iterate    24  f =       63.523  |proj g|=       0.79018
+  At iterate    25  f =       63.512  |proj g|=       0.71576
+  At iterate    26  f =       63.502  |proj g|=      0.054795
+  At iterate    27  f =       63.502  |proj g|=     0.0088703
+  At iterate    28  f =       63.502  |proj g|=     0.0012491
+  At iterate    29  f =       63.502  |proj g|=     0.0018937
   
-  iterations 7
-  function evaluations 27
-  segments explored during Cauchy searches 10
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.02238e-08
-  final function value 66.5295
+  iterations 29
+  function evaluations 40
+  segments explored during Cauchy searches 32
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 0.00189369
+  final function value 63.5017
   
-  F = 66.5295
-  final  value 66.529549 
+  F = 63.5017
+  final  value 63.501718 
   converged
   
   optimisation start
@@ -984,42 +1001,42 @@
     - 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) :  -276.0305 
+    - best initial criterion value(s) :  -313.0482 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       276.03  |proj g|=       10.838
-  At iterate     1  f =       275.89  |proj g|=       0.41168
-  At iterate     2  f =       259.96  |proj g|=        43.712
-  At iterate     3  f =       258.02  |proj g|=        43.437
-  At iterate     4  f =       245.57  |proj g|=        10.992
-  At iterate     5  f =       244.39  |proj g|=        1.7506
-  At iterate     6  f =       243.32  |proj g|=         1.139
-  At iterate     7  f =       243.28  |proj g|=        1.3584
-  At iterate     8  f =       243.28  |proj g|=      0.080222
-  At iterate     9  f =       243.28  |proj g|=      0.030963
-  At iterate    10  f =       243.28  |proj g|=       0.16118
-  At iterate    11  f =       243.28  |proj g|=       0.67201
-  At iterate    12  f =       243.28  |proj g|=        1.4866
-  At iterate    13  f =       243.27  |proj g|=        1.7276
-  At iterate    14  f =       243.27  |proj g|=         1.728
-  At iterate    15  f =       243.27  |proj g|=        1.7284
-  At iterate    16  f =       243.27  |proj g|=        1.7281
-  At iterate    17  f =       243.27  |proj g|=        1.2176
-  At iterate    18  f =       243.27  |proj g|=       0.30048
-  At iterate    19  f =       243.27  |proj g|=       0.18227
-  At iterate    20  f =       243.26  |proj g|=       0.15281
-  At iterate    21  f =       243.26  |proj g|=       0.15267
-  At iterate    22  f =       243.26  |proj g|=       0.15256
-  At iterate    23  f =       243.26  |proj g|=      0.027161
-  At iterate    24  f =       243.26  |proj g|=    0.00034888
+  At iterate     0  f=       313.05  |proj g|=       44.255
+  At iterate     1  f =       280.05  |proj g|=        37.077
+  At iterate     2  f =       279.01  |proj g|=        19.549
+  At iterate     3  f =       264.48  |proj g|=        43.756
+  At iterate     4  f =       264.03  |proj g|=        43.692
+  At iterate     5  f =       260.22  |proj g|=        40.885
+  At iterate     6  f =        250.6  |proj g|=        4.2167
+  At iterate     7  f =       244.74  |proj g|=        5.9914
+  At iterate     8  f =        244.5  |proj g|=        1.7204
+  At iterate     9  f =       244.49  |proj g|=       0.39125
+  At iterate    10  f =       244.48  |proj g|=       0.20593
+  At iterate    11  f =       244.48  |proj g|=        0.2057
+  At iterate    12  f =       244.48  |proj g|=       0.20368
+  At iterate    13  f =       244.47  |proj g|=        0.6912
+  At iterate    14  f =       244.44  |proj g|=        1.5071
+  At iterate    15  f =       244.38  |proj g|=        1.5237
+  At iterate    16  f =       244.23  |proj g|=         1.541
+  At iterate    17  f =       244.19  |proj g|=        1.5411
+  At iterate    18  f =       243.93  |proj g|=        1.5328
+  At iterate    19  f =       243.54  |proj g|=        1.4681
+  At iterate    20  f =        243.3  |proj g|=        1.7315
+  At iterate    21  f =       243.26  |proj g|=       0.38381
+  At iterate    22  f =       243.26  |proj g|=      0.096999
+  At iterate    23  f =       243.26  |proj g|=      0.015238
+  At iterate    24  f =       243.26  |proj g|=     0.0015599
   
   iterations 24
-  function evaluations 31
-  segments explored during Cauchy searches 25
+  function evaluations 33
+  segments explored during Cauchy searches 26
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000348875
+  norm of the final projected gradient 0.00155994
   final function value 243.264
   
   F = 243.264
@@ -1038,24 +1055,27 @@
     - 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) :  -2357.034 
+    - best initial criterion value(s) :  -545.9777 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         2357  |proj g|=       32.934
-  At iterate     1  f =       339.36  |proj g|=       0.32897
-  At iterate     2  f =       318.34  |proj g|=      0.092365
-  At iterate     3  f =       318.22  |proj g|=     0.0043693
-  At iterate     4  f =       318.22  |proj g|=     0.0006595
-  At iterate     5  f =       318.22  |proj g|=    3.9446e-06
-  At iterate     6  f =       318.22  |proj g|=    3.5347e-09
+  At iterate     0  f=       545.98  |proj g|=       7.4418
+  At iterate     1  f =       323.39  |proj g|=       0.34934
+  At iterate     2  f =       320.87  |proj g|=       0.30341
+  At iterate     3  f =       318.22  |proj g|=      0.015903
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.22  |proj g|=      0.012333
+  At iterate     5  f =       318.22  |proj g|=    0.00025457
+  At iterate     6  f =       318.22  |proj g|=    4.1814e-06
+  At iterate     7  f =       318.22  |proj g|=    1.4473e-09
   
-  iterations 6
-  function evaluations 19
-  segments explored during Cauchy searches 8
+  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 3.53474e-09
+  norm of the final projected gradient 1.4473e-09
   final function value 318.222
   
   F = 318.222
> 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)
+ }
>