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

WARNING: ignoring environment value of R_HOME

R Under development (unstable) (2025-03-29 r88074) -- "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/2025-03-30/deps.csv", 
task.str = "843", release = "/scratch/th798/data.table-revdeps/2025-03-30/data.table_release_1.17.0.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-03-30/data.table_master_1.17.99.2cb03162a21328cc5f68a8c3b0e554f5edfcb5b9.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/16189871/R-devel/843"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/16189871/R-devel/843/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/th798/16189871/R-devel/843/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] "2025-03-30 01:01:17 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/16189871/R-devel/843/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/th798/16189871/R-devel/843/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/th798/16189871/R-devel/843/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/th798/16189871/Rtmp2vt6i7/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 48.640   4.242 130.452 
> print(Sys.time())
[1] "2025-03-30 01:03:27 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] "2025-03-30 01:03:27 MST"
Installing package into '/tmp/th798/16189871/R-devel/843/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** this is package 'data.table' version '1.17.0'
** 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/th798/16189871/R-devel/843/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] "2025-03-30 01:03:54 MST"
* using log directory '/tmp/th798/16189871/R-devel/843/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-03-29 r88074)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Spack GCC) 12.2.0
    GNU Fortran (Spack GCC) 12.2.0
* running under: Red Hat Enterprise Linux 8.10 (Ootpa)
* using session charset: ASCII
* checking for file 'mlr3learners/DESCRIPTION' ... OK
* this is package 'mlr3learners' version '0.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package 'mlr3learners' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                                 user system elapsed
mlr_learners_classif.cv_glmnet 28.001  0.135  29.133
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'testthat.R'
 ERROR
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("mlr3learners")
  +   test_check("mlr3learners")
  + }
  Loading required package: mlr3
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.095425 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.095425 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.391705 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.391705 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.466475 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.466475 
  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 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  6 (5 variable)
  initial  value 9.585772 
  iter  10 value 7.495272
  final  value 7.494072 
  converged
  # weights:  6 (5 variable)
  initial  value 9.585772 
  iter  10 value 7.495272
  final  value 7.494072 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.965401
  iter  10 value 17.965401
  iter  10 value 17.965401
  final  value 17.965401 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 29.565084
  iter  10 value 29.565084
  final  value 29.565084 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 29.565084
  iter  10 value 29.565084
  final  value 29.565084 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.653969 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.653969 
  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 26.671247
  final  value 26.666138 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.671247
  final  value 26.666138 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.671247
  final  value 26.666138 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.671247
  final  value 26.666138 
  converged
  # weights:  18 (10 variable)
  initial  value 14.825588 
  iter  10 value 10.399592
  iter  20 value 10.344227
  iter  30 value 10.344176
  final  value 10.344174 
  converged
  # weights:  18 (10 variable)
  initial  value 14.825588 
  iter  10 value 10.399592
  iter  20 value 10.344227
  iter  30 value 10.344176
  final  value 10.344174 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.671247
  final  value 26.666138 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.671247
  final  value 26.666138 
  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 : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -19150.23 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        19150  |proj g|=       11.938
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       77.415  |proj g|=        1.5929
  ys=-2.575e+01  -gs= 1.953e+01, BFGS update SKIPPED
  At iterate     3  f =       76.697  |proj g|=        1.3974
  At iterate     4  f =       76.183  |proj g|=        0.5133
  At iterate     5  f =       76.177  |proj g|=       0.29894
  At iterate     6  f =       76.174  |proj g|=      0.015561
  At iterate     7  f =       76.174  |proj g|=    0.00044327
  At iterate     8  f =       76.174  |proj g|=    6.8148e-07
  
  iterations 8
  function evaluations 32
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.8148e-07
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -19150.23 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        19150  |proj g|=       11.938
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       77.415  |proj g|=        1.5929
  ys=-2.575e+01  -gs= 1.953e+01, BFGS update SKIPPED
  At iterate     3  f =       76.697  |proj g|=        1.3974
  At iterate     4  f =       76.183  |proj g|=        0.5133
  At iterate     5  f =       76.177  |proj g|=       0.29894
  At iterate     6  f =       76.174  |proj g|=      0.015561
  At iterate     7  f =       76.174  |proj g|=    0.00044327
  At iterate     8  f =       76.174  |proj g|=    6.8148e-07
  
  iterations 8
  function evaluations 32
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 6.8148e-07
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -125647.2 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.2565e+05  |proj g|=        11.46
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       77.143  |proj g|=        8.0675
  At iterate     3  f =       76.379  |proj g|=        1.2792
  At iterate     4  f =       76.216  |proj g|=        1.0882
  At iterate     5  f =       76.179  |proj g|=       0.39435
  At iterate     6  f =       76.174  |proj g|=      0.046494
  At iterate     7  f =       76.174  |proj g|=     0.0017341
  At iterate     8  f =       76.174  |proj g|=    7.9978e-06
  
  iterations 8
  function evaluations 25
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 7.99782e-06
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -125647.2 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   1.2565e+05  |proj g|=        11.46
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       77.143  |proj g|=        8.0675
  At iterate     3  f =       76.379  |proj g|=        1.2792
  At iterate     4  f =       76.216  |proj g|=        1.0882
  At iterate     5  f =       76.179  |proj g|=       0.39435
  At iterate     6  f =       76.174  |proj g|=      0.046494
  At iterate     7  f =       76.174  |proj g|=     0.0017341
  At iterate     8  f =       76.174  |proj g|=    7.9978e-06
  
  iterations 8
  function evaluations 25
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 7.99782e-06
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -38289.68 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        38290  |proj g|=       11.731
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       78.162  |proj g|=        1.7635
  ys=-3.061e+01  -gs= 1.923e+01, BFGS update SKIPPED
  At iterate     3  f =       77.355  |proj g|=        1.5783
  At iterate     4  f =       76.184  |proj g|=       0.55743
  At iterate     5  f =       76.174  |proj g|=      0.031967
  At iterate     6  f =       76.174  |proj g|=     0.0018958
  At iterate     7  f =       76.174  |proj g|=     5.998e-06
  
  iterations 7
  function evaluations 32
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.99801e-06
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.257707e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.905068 
    - variance bounds :  0.1257707 12.72364 
    - best initial criterion value(s) :  -34103.76 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        34104  |proj g|=       11.265
  At iterate     1  f =       111.96  |proj g|=        1.7745
  At iterate     2  f =       78.551  |proj g|=        1.8466
  ys=-3.204e+01  -gs= 1.908e+01, BFGS update SKIPPED
  At iterate     3  f =       76.188  |proj g|=       0.64069
  At iterate     4  f =       76.174  |proj g|=      0.017005
  At iterate     5  f =       76.174  |proj g|=       0.00117
  At iterate     6  f =       76.174  |proj g|=    1.9656e-06
  
  iterations 6
  function evaluations 29
  segments explored during Cauchy searches 9
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.9656e-06
  final function value 76.1741
  
  F = 76.1741
  final  value 76.174122 
  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) :  -308.0488 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       308.05  |proj g|=       2.8748
  At iterate     1  f =       268.73  |proj g|=        4.0974
  At iterate     2  f =       267.31  |proj g|=        3.9889
  At iterate     3  f =       267.09  |proj g|=        1.8206
  At iterate     4  f =       267.09  |proj g|=        1.8203
  At iterate     5  f =       267.09  |proj g|=        1.8534
  At iterate     6  f =       267.08  |proj g|=        2.0593
  At iterate     7  f =       267.04  |proj g|=        2.6268
  At iterate     8  f =       254.52  |proj g|=        4.6525
  At iterate     9  f =       254.52  |proj g|=         4.872
  At iterate    10  f =        253.3  |proj g|=        3.4816
  At iterate    11  f =       252.48  |proj g|=       0.85695
  At iterate    12  f =       252.47  |proj g|=       0.79473
  At iterate    13  f =       252.47  |proj g|=       0.26568
  At iterate    14  f =       252.47  |proj g|=       0.20728
  At iterate    15  f =       252.47  |proj g|=       0.54211
  At iterate    16  f =       252.46  |proj g|=         1.097
  At iterate    17  f =       252.45  |proj g|=        1.3292
  At iterate    18  f =       252.41  |proj g|=        1.8204
  At iterate    19  f =       252.29  |proj g|=        1.8507
  At iterate    20  f =       251.94  |proj g|=         1.893
  At iterate    21  f =       251.05  |proj g|=        1.9407
  At iterate    22  f =       249.52  |proj g|=        1.9454
  At iterate    23  f =       249.45  |proj g|=        1.9418
  At iterate    24  f =        247.6  |proj g|=        1.8268
  At iterate    25  f =        243.6  |proj g|=        1.7336
  At iterate    26  f =       243.38  |proj g|=        1.7354
  At iterate    27  f =       243.28  |proj g|=        1.7275
  At iterate    28  f =       243.26  |proj g|=        1.2946
  At iterate    29  f =       243.26  |proj g|=       0.15271
  At iterate    30  f =       243.26  |proj g|=      0.014453
  At iterate    31  f =       243.26  |proj g|=    0.00052813
  
  iterations 31
  function evaluations 43
  segments explored during Cauchy searches 32
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000528131
  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) :  -341.9434 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       341.94  |proj g|=        13.79
  At iterate     1  f =        329.1  |proj g|=       0.36677
  At iterate     2  f =       320.63  |proj g|=       0.29572
  At iterate     3  f =       318.24  |proj g|=      0.039665
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.23  |proj g|=       0.03027
  At iterate     5  f =       318.22  |proj g|=     0.0014597
  At iterate     6  f =       318.22  |proj g|=    5.7041e-05
  At iterate     7  f =       318.22  |proj g|=    1.1297e-07
  
  iterations 7
  function evaluations 21
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.12969e-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) :  -877.7414 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       877.74  |proj g|=       16.974
  At iterate     1  f =       324.51  |proj g|=       0.35852
  At iterate     2  f =       318.25  |proj g|=      0.043167
  At iterate     3  f =       318.22  |proj g|=     0.0014373
  At iterate     4  f =       318.22  |proj g|=    9.1388e-05
  At iterate     5  f =       318.22  |proj g|=    1.7909e-07
  
  iterations 5
  function evaluations 16
  segments explored during Cauchy searches 7
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.79087e-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) :  -253.6072 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       253.61  |proj g|=       8.8846
  At iterate     1  f =       252.58  |proj g|=        1.2125
  At iterate     2  f =       252.57  |proj g|=       0.49054
  At iterate     3  f =       252.57  |proj g|=       0.20579
  At iterate     4  f =       252.57  |proj g|=        1.0169
  At iterate     5  f =       252.56  |proj g|=       0.22107
  At iterate     6  f =       252.56  |proj g|=       0.23144
  At iterate     7  f =       252.55  |proj g|=       0.78684
  At iterate     8  f =        252.5  |proj g|=        1.8179
  At iterate     9  f =       252.39  |proj g|=        1.8451
  At iterate    10  f =        252.1  |proj g|=        1.8863
  At iterate    11  f =       251.86  |proj g|=        1.8948
  At iterate    12  f =       250.82  |proj g|=        1.9078
  At iterate    13  f =       247.89  |proj g|=        1.8458
  At iterate    14  f =       245.63  |proj g|=        1.7495
  At iterate    15  f =       244.73  |proj g|=        1.7489
  At iterate    16  f =       243.79  |proj g|=        1.7449
  At iterate    17  f =       243.27  |proj g|=       0.81273
  At iterate    18  f =       243.26  |proj g|=       0.15256
  At iterate    19  f =       243.26  |proj g|=       0.15254
  At iterate    20  f =       243.26  |proj g|=      0.030993
  At iterate    21  f =       243.26  |proj g|=    7.6542e-05
  
  iterations 21
  function evaluations 32
  segments explored during Cauchy searches 22
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 7.65424e-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 : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -73.66206 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       73.662  |proj g|=        1.302
  At iterate     1  f =       72.874  |proj g|=        2.2858
  At iterate     2  f =       72.817  |proj g|=        1.9254
  At iterate     3  f =       72.793  |proj g|=       0.56293
  At iterate     4  f =       72.789  |proj g|=         1.925
  At iterate     5  f =       72.789  |proj g|=       0.27324
  At iterate     6  f =       72.789  |proj g|=       0.27038
  At iterate     7  f =       72.789  |proj g|=       0.26972
  At iterate     8  f =       72.789  |proj g|=        1.4056
  At iterate     9  f =       72.789  |proj g|=        1.9249
  At iterate    10  f =       72.788  |proj g|=         1.925
  At iterate    11  f =       72.787  |proj g|=         1.925
  At iterate    12  f =       72.784  |proj g|=         1.925
  At iterate    13  f =       72.777  |proj g|=         1.925
  At iterate    14  f =        72.76  |proj g|=        1.9249
  At iterate    15  f =       72.725  |proj g|=        1.9248
  At iterate    16  f =       72.693  |proj g|=        1.9239
  At iterate    17  f =        72.65  |proj g|=        1.9237
  At iterate    18  f =       72.631  |proj g|=        1.9233
  At iterate    19  f =        72.63  |proj g|=        1.9232
  At iterate    20  f =       72.629  |proj g|=       0.40949
  At iterate    21  f =       72.629  |proj g|=       0.41375
  At iterate    22  f =       72.628  |proj g|=         1.923
  At iterate    23  f =       72.624  |proj g|=        1.9229
  At iterate    24  f =       72.561  |proj g|=        1.9211
  At iterate    25  f =        72.55  |proj g|=        1.9205
  At iterate    26  f =       72.382  |proj g|=        1.9195
  At iterate    27  f =       72.362  |proj g|=        1.9197
  At iterate    28  f =       72.355  |proj g|=       0.83558
  At iterate    29  f =       72.341  |proj g|=       0.77087
  At iterate    30  f =       72.307  |proj g|=       0.12553
  At iterate    31  f =       72.304  |proj g|=      0.029847
  At iterate    32  f =       72.303  |proj g|=      0.025757
  At iterate    33  f =       72.303  |proj g|=      0.012045
  At iterate    34  f =       72.303  |proj g|=       0.52756
  At iterate    35  f =       72.303  |proj g|=      0.013649
  At iterate    36  f =       72.303  |proj g|=     0.0066307
  At iterate    37  f =       72.303  |proj g|=     0.0062946
  At iterate    38  f =       72.303  |proj g|=      0.080847
  
  iterations 38
  function evaluations 47
  segments explored during Cauchy searches 41
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0808473
  final function value 72.3028
  
  F = 72.3028
  final  value 72.302755 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -73.66206 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       73.662  |proj g|=        1.302
  At iterate     1  f =       72.874  |proj g|=        2.2858
  At iterate     2  f =       72.817  |proj g|=        1.9254
  At iterate     3  f =       72.793  |proj g|=       0.56293
  At iterate     4  f =       72.789  |proj g|=         1.925
  At iterate     5  f =       72.789  |proj g|=       0.27324
  At iterate     6  f =       72.789  |proj g|=       0.27038
  At iterate     7  f =       72.789  |proj g|=       0.26972
  At iterate     8  f =       72.789  |proj g|=        1.4056
  At iterate     9  f =       72.789  |proj g|=        1.9249
  At iterate    10  f =       72.788  |proj g|=         1.925
  At iterate    11  f =       72.787  |proj g|=         1.925
  At iterate    12  f =       72.784  |proj g|=         1.925
  At iterate    13  f =       72.777  |proj g|=         1.925
  At iterate    14  f =        72.76  |proj g|=        1.9249
  At iterate    15  f =       72.725  |proj g|=        1.9248
  At iterate    16  f =       72.693  |proj g|=        1.9239
  At iterate    17  f =        72.65  |proj g|=        1.9237
  At iterate    18  f =       72.631  |proj g|=        1.9233
  At iterate    19  f =        72.63  |proj g|=        1.9232
  At iterate    20  f =       72.629  |proj g|=       0.40949
  At iterate    21  f =       72.629  |proj g|=       0.41375
  At iterate    22  f =       72.628  |proj g|=         1.923
  At iterate    23  f =       72.624  |proj g|=        1.9229
  At iterate    24  f =       72.561  |proj g|=        1.9211
  At iterate    25  f =        72.55  |proj g|=        1.9205
  At iterate    26  f =       72.382  |proj g|=        1.9195
  At iterate    27  f =       72.362  |proj g|=        1.9197
  At iterate    28  f =       72.355  |proj g|=       0.83558
  At iterate    29  f =       72.341  |proj g|=       0.77087
  At iterate    30  f =       72.307  |proj g|=       0.12553
  At iterate    31  f =       72.304  |proj g|=      0.029847
  At iterate    32  f =       72.303  |proj g|=      0.025757
  At iterate    33  f =       72.303  |proj g|=      0.012045
  At iterate    34  f =       72.303  |proj g|=       0.52756
  At iterate    35  f =       72.303  |proj g|=      0.013649
  At iterate    36  f =       72.303  |proj g|=     0.0066307
  At iterate    37  f =       72.303  |proj g|=     0.0062946
  At iterate    38  f =       72.303  |proj g|=      0.080847
  
  iterations 38
  function evaluations 47
  segments explored during Cauchy searches 41
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0808473
  final function value 72.3028
  
  F = 72.3028
  final  value 72.302755 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -1133.953 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         1134  |proj g|=       9.9637
  At iterate     1  f =       108.79  |proj g|=        2.0139
  At iterate     2  f =       73.501  |proj g|=        1.2434
  ys=-1.670e+01  -gs= 1.986e+01, BFGS update SKIPPED
  At iterate     3  f =       73.038  |proj g|=        1.0849
  At iterate     4  f =       72.973  |proj g|=        1.6756
  At iterate     5  f =        72.92  |proj g|=       0.30349
  At iterate     6  f =       72.918  |proj g|=      0.038493
  At iterate     7  f =       72.918  |proj g|=     0.0010502
  At iterate     8  f =       72.918  |proj g|=    3.5138e-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 3.51379e-06
  final function value 72.9182
  
  F = 72.9182
  final  value 72.918193 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -1133.953 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=         1134  |proj g|=       9.9637
  At iterate     1  f =       108.79  |proj g|=        2.0139
  At iterate     2  f =       73.501  |proj g|=        1.2434
  ys=-1.670e+01  -gs= 1.986e+01, BFGS update SKIPPED
  At iterate     3  f =       73.038  |proj g|=        1.0849
  At iterate     4  f =       72.973  |proj g|=        1.6756
  At iterate     5  f =        72.92  |proj g|=       0.30349
  At iterate     6  f =       72.918  |proj g|=      0.038493
  At iterate     7  f =       72.918  |proj g|=     0.0010502
  At iterate     8  f =       72.918  |proj g|=    3.5138e-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 3.51379e-06
  final function value 72.9182
  
  F = 72.9182
  final  value 72.918193 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -17359.3 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        17359  |proj g|=       9.9673
  At iterate     1  f =       108.79  |proj g|=        2.0139
  At iterate     2  f =       73.085  |proj g|=        1.1067
  ys=-2.660e+00  -gs= 2.014e+01, BFGS update SKIPPED
  At iterate     3  f =       73.027  |proj g|=        1.0794
  At iterate     4  f =       72.928  |proj g|=       0.68483
  At iterate     5  f =       72.919  |proj g|=       0.13157
  At iterate     6  f =       72.918  |proj g|=      0.007365
  At iterate     7  f =       72.918  |proj g|=    8.5161e-05
  At iterate     8  f =       72.918  |proj g|=    5.4337e-08
  
  iterations 8
  function evaluations 25
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.43368e-08
  final function value 72.9182
  
  F = 72.9182
  final  value 72.918193 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.104125e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.926668 
    - variance bounds :  0.1104125 11.21586 
    - best initial criterion value(s) :  -11680.76 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        11681  |proj g|=       10.272
  At iterate     1  f =       108.79  |proj g|=        2.0139
  At iterate     2  f =       75.213  |proj g|=         1.606
  ys=-3.201e+01  -gs= 1.913e+01, BFGS update SKIPPED
  At iterate     3  f =       72.918  |proj g|=      0.065358
  At iterate     4  f =       72.918  |proj g|=    0.00012724
  At iterate     5  f =       72.918  |proj g|=      7.25e-07
  
  iterations 5
  function evaluations 24
  segments explored during Cauchy searches 8
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 7.25003e-07
  final function value 72.9182
  
  F = 72.9182
  final  value 72.918193 
  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) :  -336.3525 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       336.35  |proj g|=       44.231
  At iterate     1  f =       319.26  |proj g|=       0.22617
  At iterate     2  f =       318.75  |proj g|=       0.17549
  At iterate     3  f =       318.24  |proj g|=      0.042526
  At iterate     4  f =       318.22  |proj g|=      0.016358
  At iterate     5  f =       318.22  |proj g|=    0.00099165
  At iterate     6  f =       318.22  |proj g|=    2.1506e-05
  At iterate     7  f =       318.22  |proj g|=     2.906e-08
  
  iterations 7
  function evaluations 12
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.90599e-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) :  -279.1848 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       279.18  |proj g|=       43.177
  At iterate     1  f =       250.97  |proj g|=        3.7377
  At iterate     2  f =       250.87  |proj g|=        1.6957
  At iterate     3  f =       250.86  |proj g|=        1.7644
  At iterate     4  f =       250.83  |proj g|=       0.22003
  At iterate     5  f =       250.83  |proj g|=        0.2191
  At iterate     6  f =       250.83  |proj g|=       0.39683
  At iterate     7  f =       250.81  |proj g|=       0.98006
  At iterate     8  f =       250.78  |proj g|=        1.7643
  At iterate     9  f =        250.7  |proj g|=        1.7878
  At iterate    10  f =       250.51  |proj g|=        1.8386
  At iterate    11  f =        250.1  |proj g|=        1.8662
  At iterate    12  f =       249.14  |proj g|=         1.851
  At iterate    13  f =       246.89  |proj g|=        1.7537
  At iterate    14  f =       245.46  |proj g|=        1.6366
  At iterate    15  f =       244.82  |proj g|=        5.2221
  At iterate    16  f =       243.33  |proj g|=        1.7337
  At iterate    17  f =       243.27  |proj g|=       0.34435
  At iterate    18  f =       243.27  |proj g|=       0.15288
  At iterate    19  f =       243.27  |proj g|=       0.21463
  At iterate    20  f =       243.26  |proj g|=      0.024106
  At iterate    21  f =       243.26  |proj g|=    3.0972e-05
  At iterate    22  f =       243.26  |proj g|=    5.4364e-07
  
  iterations 22
  function evaluations 32
  segments explored during Cauchy searches 23
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 5.43638e-07
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/16189871/R-devel/843/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-03-30 01:12:58 MST"
[1] "2025-03-30 01:12:58 MST"
Installing package into '/tmp/th798/16189871/R-devel/843/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
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/packages/gcc/12.2.0-nnbserq/bin/gcc -I"/home/th798/R/R-devel/include" -DNDEBUG   -I/home/th798/.conda/envs/emacs1/include -I/home/th798/include   -fopenmp -I/home/th798/.conda/envs/emacs1/include -fpic  -I/packages/gcc/12.2.0-nnbserq/include -I/packages/zstd/1.5.2-cs5ansz/include -I/packages/zlib/1.2.13-po6bkge/include -I/packages/mpc/1.2.1-nnfoiwh/include -I/packages/mpfr/4.1.0-yfsqqka/include -I/packages/gmp/6.2.1-7ydtie6/include  -c 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/th798/16189871/R-devel/843/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] "2025-03-30 01:13:20 MST"
* using log directory '/tmp/th798/16189871/R-devel/843/mlr3learners.Rcheck'
* using R Under development (unstable) (2025-03-29 r88074)
* 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 27.624  0.136  28.408
* 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 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.327135 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.327135 
  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 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  converged
  # weights:  6 (5 variable)
  initial  value 9.337399 
  iter  10 value 5.723161
  final  value 5.723094 
  converged
  # weights:  6 (5 variable)
  initial  value 9.337399 
  iter  10 value 5.723161
  final  value 5.723094 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.675448
  iter  10 value 17.675448
  iter  10 value 17.675448
  final  value 17.675448 
  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 30.423450 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 30.423450 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 29.695240
  final  value 29.695225 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 29.695240
  final  value 29.695225 
  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 26.353393
  final  value 26.226700 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.353393
  final  value 26.226700 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.353393
  final  value 26.226700 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.353393
  final  value 26.226700 
  converged
  # weights:  18 (10 variable)
  initial  value 19.094038 
  iter  10 value 15.834215
  iter  20 value 15.773234
  final  value 15.773233 
  converged
  # weights:  18 (10 variable)
  initial  value 19.094038 
  iter  10 value 15.834215
  iter  20 value 15.773234
  final  value 15.773233 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.353393
  final  value 26.226700 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 26.353393
  final  value 26.226700 
  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 : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -17598.98 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        17599  |proj g|=        11.71
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =       77.312  |proj g|=        1.2241
  At iterate     3  f =       77.253  |proj g|=       0.12376
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       77.252  |proj g|=     0.0062735
  At iterate     5  f =       77.252  |proj g|=    8.1294e-05
  At iterate     6  f =       77.252  |proj g|=    5.2546e-08
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.25457e-08
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -17598.98 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        17599  |proj g|=        11.71
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =       77.312  |proj g|=        1.2241
  At iterate     3  f =       77.253  |proj g|=       0.12376
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       77.252  |proj g|=     0.0062735
  At iterate     5  f =       77.252  |proj g|=    8.1294e-05
  At iterate     6  f =       77.252  |proj g|=    5.2546e-08
  
  iterations 6
  function evaluations 19
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 5.25457e-08
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -73705.36 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        73705  |proj g|=       11.283
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =       78.733  |proj g|=         1.723
  ys=-2.715e+01  -gs= 1.937e+01, BFGS update SKIPPED
  At iterate     3  f =       78.244  |proj g|=        1.5984
  At iterate     4  f =       77.292  |proj g|=          1.01
  At iterate     5  f =       77.253  |proj g|=       0.10994
  At iterate     6  f =       77.252  |proj g|=      0.013385
  At iterate     7  f =       77.252  |proj g|=    0.00015341
  At iterate     8  f =       77.252  |proj g|=    2.1104e-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 2.11038e-07
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -73705.36 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        73705  |proj g|=       11.283
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =       78.733  |proj g|=         1.723
  ys=-2.715e+01  -gs= 1.937e+01, BFGS update SKIPPED
  At iterate     3  f =       78.244  |proj g|=        1.5984
  At iterate     4  f =       77.292  |proj g|=          1.01
  At iterate     5  f =       77.253  |proj g|=       0.10994
  At iterate     6  f =       77.252  |proj g|=      0.013385
  At iterate     7  f =       77.252  |proj g|=    0.00015341
  At iterate     8  f =       77.252  |proj g|=    2.1104e-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 2.11038e-07
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -1658.431 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1658.4  |proj g|=       12.207
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =        78.57  |proj g|=         1.683
  ys=-2.589e+01  -gs= 1.943e+01, BFGS update SKIPPED
  At iterate     3  f =       78.047  |proj g|=        1.5432
  At iterate     4  f =       77.277  |proj g|=       0.81971
  At iterate     5  f =       77.267  |proj g|=       0.68756
  At iterate     6  f =       77.252  |proj g|=      0.059305
  At iterate     7  f =       77.252  |proj g|=     0.0038876
  At iterate     8  f =       77.252  |proj g|=     2.393e-05
  At iterate     9  f =       77.252  |proj g|=     9.582e-09
  
  iterations 9
  function evaluations 26
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 9.58202e-09
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 1.313133e-08 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.970775 
    - variance bounds :  0.1309862 13.13133 
    - best initial criterion value(s) :  -5986.749 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       5986.7  |proj g|=       11.848
  At iterate     1  f =       112.77  |proj g|=        1.7173
  At iterate     2  f =       78.267  |proj g|=        7.9704
  At iterate     3  f =       77.463  |proj g|=        1.3384
  At iterate     4  f =       77.297  |proj g|=        1.0707
  At iterate     5  f =       77.257  |proj g|=       0.39627
  At iterate     6  f =       77.252  |proj g|=      0.048079
  At iterate     7  f =       77.252  |proj g|=      0.001878
  At iterate     8  f =       77.252  |proj g|=    9.3557e-06
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 9.35568e-06
  final function value 77.2523
  
  F = 77.2523
  final  value 77.252256 
  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) :  -28891.41 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        28891  |proj g|=        458.3
  At iterate     1  f =       407.94  |proj g|=      0.089708
  At iterate     2  f =       318.27  |proj g|=      0.070929
  At iterate     3  f =       318.22  |proj g|=     0.0038623
  At iterate     4  f =       318.22  |proj g|=    0.00033503
  At iterate     5  f =       318.22  |proj g|=    1.7728e-06
  At iterate     6  f =       318.22  |proj g|=     8.084e-10
  
  iterations 6
  function evaluations 21
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 8.08396e-10
  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) :  -372.0202 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       372.02  |proj g|=       5.1071
  At iterate     1  f =       326.67  |proj g|=       0.36663
  At iterate     2  f =       324.95  |proj g|=       0.36102
  At iterate     3  f =       319.09  |proj g|=       0.21252
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.88  |proj g|=       0.19099
  At iterate     5  f =       318.25  |proj g|=      0.048843
  At iterate     6  f =       318.23  |proj g|=      0.021811
  At iterate     7  f =       318.22  |proj g|=     0.0015218
  At iterate     8  f =       318.22  |proj g|=    4.3653e-05
  At iterate     9  f =       318.22  |proj g|=    9.0609e-08
  
  iterations 9
  function evaluations 17
  segments explored during Cauchy searches 12
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 9.06087e-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) :  -267.4841 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       267.48  |proj g|=       1.8287
  At iterate     1  f =       267.36  |proj g|=        1.6027
  At iterate     2  f =       267.35  |proj g|=        1.2439
  At iterate     3  f =       267.35  |proj g|=        1.2298
  At iterate     4  f =       267.35  |proj g|=        1.6852
  At iterate     5  f =       267.35  |proj g|=         1.826
  At iterate     6  f =       267.35  |proj g|=        1.8261
  At iterate     7  f =       267.35  |proj g|=        1.8262
  At iterate     8  f =       267.34  |proj g|=        1.8264
  At iterate     9  f =       267.32  |proj g|=        1.8265
  At iterate    10  f =       267.25  |proj g|=        1.8261
  At iterate    11  f =       267.09  |proj g|=        1.8242
  At iterate    12  f =       266.81  |proj g|=        2.6139
  At iterate    13  f =       265.11  |proj g|=        3.7464
  At iterate    14  f =       264.08  |proj g|=        2.7859
  At iterate    15  f =       253.05  |proj g|=        3.9887
  At iterate    16  f =       252.93  |proj g|=        6.3701
  At iterate    17  f =       252.32  |proj g|=        2.8151
  At iterate    18  f =       252.18  |proj g|=       0.33436
  At iterate    19  f =       252.18  |proj g|=       0.20823
  At iterate    20  f =       252.18  |proj g|=       0.20811
  At iterate    21  f =       252.18  |proj g|=       0.20718
  At iterate    22  f =       252.18  |proj g|=       0.20627
  At iterate    23  f =       252.17  |proj g|=       0.20497
  At iterate    24  f =       252.17  |proj g|=       0.21245
  At iterate    25  f =       252.17  |proj g|=       0.24768
  At iterate    26  f =       252.15  |proj g|=       0.19913
  At iterate    27  f =       252.12  |proj g|=       0.23365
  At iterate    28  f =       252.05  |proj g|=        1.5838
  At iterate    29  f =       251.88  |proj g|=        3.7768
  At iterate    30  f =       251.56  |proj g|=        7.2715
  At iterate    31  f =       251.05  |proj g|=        10.881
  At iterate    32  f =       248.98  |proj g|=        19.319
  At iterate    33  f =       247.66  |proj g|=        23.377
  At iterate    34  f =       247.54  |proj g|=        23.181
  At iterate    35  f =       246.66  |proj g|=        20.639
  At iterate    36  f =       244.08  |proj g|=        4.4672
  At iterate    37  f =       243.66  |proj g|=        1.7409
  At iterate    38  f =       243.27  |proj g|=       0.93986
  At iterate    39  f =       243.26  |proj g|=       0.15266
  At iterate    40  f =       243.26  |proj g|=      0.086432
  At iterate    41  f =       243.26  |proj g|=    0.00045616
  At iterate    42  f =       243.26  |proj g|=    1.5485e-05
  
  iterations 42
  function evaluations 54
  segments explored during Cauchy searches 43
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 1.5485e-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) :  -703.4283 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       703.43  |proj g|=       24.601
  At iterate     1  f =       329.27  |proj g|=       0.36655
  At iterate     2  f =        318.9  |proj g|=       0.19325
  At iterate     3  f =       318.27  |proj g|=       0.06348
  At iterate     4  f =       318.23  |proj g|=      0.030077
  At iterate     5  f =       318.22  |proj g|=     0.0027629
  At iterate     6  f =       318.22  |proj g|=    0.00010806
  At iterate     7  f =       318.22  |proj g|=    4.0812e-07
  
  iterations 7
  function evaluations 24
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 4.08117e-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 : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -45438.54 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        45439  |proj g|=       8.9482
  At iterate     1  f =       105.76  |proj g|=        2.2733
  At iterate     2  f =        71.63  |proj g|=        1.2885
  ys=-2.647e+01  -gs= 1.940e+01, BFGS update SKIPPED
  At iterate     3  f =       71.108  |proj g|=        1.1854
  At iterate     4  f =       70.271  |proj g|=       0.92716
  At iterate     5  f =        70.24  |proj g|=       0.10408
  At iterate     6  f =        70.24  |proj g|=      0.011136
  At iterate     7  f =        70.24  |proj g|=    9.0967e-05
  At iterate     8  f =        70.24  |proj g|=      7.87e-08
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 7.86995e-08
  final function value 70.2402
  
  F = 70.2402
  final  value 70.240169 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -45438.54 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        45439  |proj g|=       8.9482
  At iterate     1  f =       105.76  |proj g|=        2.2733
  At iterate     2  f =        71.63  |proj g|=        1.2885
  ys=-2.647e+01  -gs= 1.940e+01, BFGS update SKIPPED
  At iterate     3  f =       71.108  |proj g|=        1.1854
  At iterate     4  f =       70.271  |proj g|=       0.92716
  At iterate     5  f =        70.24  |proj g|=       0.10408
  At iterate     6  f =        70.24  |proj g|=      0.011136
  At iterate     7  f =        70.24  |proj g|=    9.0967e-05
  At iterate     8  f =        70.24  |proj g|=      7.87e-08
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 7.86995e-08
  final function value 70.2402
  
  F = 70.2402
  final  value 70.240169 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -826.1615 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       826.16  |proj g|=       9.1391
  At iterate     1  f =       105.76  |proj g|=        2.2733
  At iterate     2  f =       72.676  |proj g|=        1.4704
  ys=-3.158e+01  -gs= 1.899e+01, BFGS update SKIPPED
  At iterate     3  f =       70.305  |proj g|=       0.95082
  At iterate     4  f =        70.24  |proj g|=        0.1139
  At iterate     5  f =        70.24  |proj g|=      0.018181
  At iterate     6  f =        70.24  |proj g|=    0.00016256
  At iterate     7  f =        70.24  |proj g|=    2.2945e-07
  
  iterations 7
  function evaluations 26
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.29446e-07
  final function value 70.2402
  
  F = 70.2402
  final  value 70.240169 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -826.1615 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       826.16  |proj g|=       9.1391
  At iterate     1  f =       105.76  |proj g|=        2.2733
  At iterate     2  f =       72.676  |proj g|=        1.4704
  ys=-3.158e+01  -gs= 1.899e+01, BFGS update SKIPPED
  At iterate     3  f =       70.305  |proj g|=       0.95082
  At iterate     4  f =        70.24  |proj g|=        0.1139
  At iterate     5  f =        70.24  |proj g|=      0.018181
  At iterate     6  f =        70.24  |proj g|=    0.00016256
  At iterate     7  f =        70.24  |proj g|=    2.2945e-07
  
  iterations 7
  function evaluations 26
  segments explored during Cauchy searches 10
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.29446e-07
  final function value 70.2402
  
  F = 70.2402
  final  value 70.240169 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -155.2631 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       155.26  |proj g|=       8.8847
  At iterate     1  f =       105.76  |proj g|=        2.2733
  At iterate     2  f =       70.887  |proj g|=        1.1364
  ys=-1.739e+01  -gs= 1.975e+01, BFGS update SKIPPED
  At iterate     3  f =       70.404  |proj g|=       0.99734
  At iterate     4  f =       70.245  |proj g|=       0.50443
  At iterate     5  f =       70.241  |proj g|=       0.14127
  At iterate     6  f =        70.24  |proj g|=     0.0057478
  At iterate     7  f =        70.24  |proj g|=     6.233e-05
  At iterate     8  f =        70.24  |proj g|=    2.7878e-08
  
  iterations 8
  function evaluations 28
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 2.78775e-08
  final function value 70.2402
  
  F = 70.2402
  final  value 70.240169 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.919649e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.904165 
    - variance bounds :  0.09510111 9.919648 
    - best initial criterion value(s) :  -70.62084 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       70.621  |proj g|=       1.9032
  At iterate     1  f =       70.581  |proj g|=        1.1036
  At iterate     2  f =       70.581  |proj g|=        1.1036
  At iterate     3  f =       70.581  |proj g|=        1.1035
  At iterate     4  f =       70.581  |proj g|=        1.9029
  At iterate     5  f =        70.58  |proj g|=        1.9029
  At iterate     6  f =       70.578  |proj g|=        1.9029
  At iterate     7  f =       70.573  |proj g|=         1.903
  At iterate     8  f =        70.56  |proj g|=        1.9031
  At iterate     9  f =       70.526  |proj g|=        1.9033
  At iterate    10  f =       70.437  |proj g|=        1.9035
  At iterate    11  f =       70.262  |proj g|=        1.9037
  At iterate    12  f =       70.233  |proj g|=        1.9039
  At iterate    13  f =       70.104  |proj g|=        1.9031
  At iterate    14  f =         70.1  |proj g|=         1.903
  At iterate    15  f =       70.067  |proj g|=         1.903
  At iterate    16  f =        70.05  |proj g|=       0.14007
  At iterate    17  f =       70.049  |proj g|=       0.12761
  At iterate    18  f =       70.049  |proj g|=         0.125
  At iterate    19  f =       70.049  |proj g|=       0.12502
  At iterate    20  f =       70.049  |proj g|=         1.903
  At iterate    21  f =       70.049  |proj g|=        1.9029
  At iterate    22  f =       70.049  |proj g|=       0.12743
  At iterate    23  f =       70.048  |proj g|=       0.13166
  At iterate    24  f =       70.046  |proj g|=       0.15281
  At iterate    25  f =       70.044  |proj g|=       0.16506
  At iterate    26  f =       70.041  |proj g|=       0.16643
  At iterate    27  f =       70.038  |proj g|=        0.1349
  At iterate    28  f =       70.038  |proj g|=       0.11047
  At iterate    29  f =       70.038  |proj g|=      0.090562
  At iterate    30  f =       70.038  |proj g|=       0.87932
  At iterate    31  f =       70.037  |proj g|=        1.0391
  At iterate    32  f =       70.037  |proj g|=      0.012187
  At iterate    33  f =       70.037  |proj g|=     0.0015148
  At iterate    34  f =       70.037  |proj g|=       0.10983
  At iterate    35  f =       70.037  |proj g|=       0.13307
  At iterate    36  f =       70.037  |proj g|=     0.0046522
  At iterate    37  f =       70.037  |proj g|=     0.0014781
  At iterate    38  f =       70.037  |proj g|=     0.0014772
  
  iterations 38
  function evaluations 50
  segments explored during Cauchy searches 40
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00147716
  final function value 70.0373
  
  F = 70.0373
  final  value 70.037295 
  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) :  -618.8492 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       618.85  |proj g|=       7.5455
  At iterate     1  f =       326.78  |proj g|=       0.36679
  At iterate     2  f =       321.01  |proj g|=       0.30743
  At iterate     3  f =       318.22  |proj g|=     0.0032143
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       318.22  |proj g|=      0.002514
  At iterate     5  f =       318.22  |proj g|=    1.0886e-05
  At iterate     6  f =       318.22  |proj g|=    3.7069e-08
  
  iterations 6
  function evaluations 18
  segments explored during Cauchy searches 10
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 3.70692e-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) :  -773.7709 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       773.77  |proj g|=       10.536
  At iterate     1  f =       328.04  |proj g|=       0.36756
  At iterate     2  f =       318.73  |proj g|=       0.17246
  At iterate     3  f =       318.25  |proj g|=      0.050631
  At iterate     4  f =       318.22  |proj g|=      0.015409
  At iterate     5  f =       318.22  |proj g|=     0.0010027
  At iterate     6  f =       318.22  |proj g|=    2.1622e-05
  At iterate     7  f =       318.22  |proj g|=    2.9539e-08
  
  iterations 7
  function evaluations 18
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.95394e-08
  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/th798/16189871/R-devel/843/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-03-30 01:21:58 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_Under_development_unstable_2025-03-29_r88074/release_1.17.0.Rcheck/00check.log	2025-03-30 01:12:58.484415456 -0700
+++ R_Under_development_unstable_2025-03-29_r88074/master_1.17.99.2cb03162a21328cc5f68a8c3b0e554f5edfcb5b9.Rcheck/00check.log	2025-03-30 01:21:58.855874797 -0700
@@ -49,7 +49,7 @@
 * checking examples ... OK
 Examples with CPU (user + system) or elapsed time > 5s
                                  user system elapsed
-mlr_learners_classif.cv_glmnet 28.001  0.135  29.133
+mlr_learners_classif.cv_glmnet 27.624  0.136  28.408
 * checking for unstated dependencies in 'tests' ... OK
 * checking tests ... ERROR
   Running 'testthat.R'
@@ -63,115 +63,113 @@
   Loading required package: mlr3
   # 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:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.391705 
+  final  value 20.694248 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.391705 
+  final  value 20.694248 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.466475 
+  final  value 20.327135 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.466475 
+  final  value 20.327135 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 20.190350 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.585772 
-  iter  10 value 7.495272
-  final  value 7.494072 
+  initial  value 9.337399 
+  iter  10 value 5.723161
+  final  value 5.723094 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.585772 
-  iter  10 value 7.495272
-  final  value 7.494072 
+  initial  value 9.337399 
+  iter  10 value 5.723161
+  final  value 5.723094 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  iter  10 value 17.965401
-  final  value 17.965401 
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  iter  10 value 17.675448
+  final  value 17.675448 
   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:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 29.565084
-  iter  10 value 29.565084
-  final  value 29.565084 
+  final  value 30.423450 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 29.565084
-  iter  10 value 29.565084
-  final  value 29.565084 
+  final  value 30.423450 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.653969 
+  iter  10 value 29.695240
+  final  value 29.695225 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.653969 
+  iter  10 value 29.695240
+  final  value 29.695225 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
@@ -183,47 +181,45 @@
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  18 (10 variable)
-  initial  value 14.825588 
-  iter  10 value 10.399592
-  iter  20 value 10.344227
-  iter  30 value 10.344176
-  final  value 10.344174 
+  initial  value 19.094038 
+  iter  10 value 15.834215
+  iter  20 value 15.773234
+  final  value 15.773233 
   converged
   # weights:  18 (10 variable)
-  initial  value 14.825588 
-  iter  10 value 10.399592
-  iter  20 value 10.344227
-  iter  30 value 10.344176
-  final  value 10.344174 
+  initial  value 19.094038 
+  iter  10 value 15.834215
+  iter  20 value 15.773234
+  final  value 15.773233 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 26.671247
-  final  value 26.666138 
+  iter  10 value 26.353393
+  final  value 26.226700 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -332,35 +328,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -19150.23 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -17598.98 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        19150  |proj g|=       11.938
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       77.415  |proj g|=        1.5929
-  ys=-2.575e+01  -gs= 1.953e+01, BFGS update SKIPPED
-  At iterate     3  f =       76.697  |proj g|=        1.3974
-  At iterate     4  f =       76.183  |proj g|=        0.5133
-  At iterate     5  f =       76.177  |proj g|=       0.29894
-  At iterate     6  f =       76.174  |proj g|=      0.015561
-  At iterate     7  f =       76.174  |proj g|=    0.00044327
-  At iterate     8  f =       76.174  |proj g|=    6.8148e-07
+  At iterate     0  f=        17599  |proj g|=        11.71
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =       77.312  |proj g|=        1.2241
+  At iterate     3  f =       77.253  |proj g|=       0.12376
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       77.252  |proj g|=     0.0062735
+  At iterate     5  f =       77.252  |proj g|=    8.1294e-05
+  At iterate     6  f =       77.252  |proj g|=    5.2546e-08
   
-  iterations 8
-  function evaluations 32
+  iterations 6
+  function evaluations 19
   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 6.8148e-07
-  final function value 76.1741
+  norm of the final projected gradient 5.25457e-08
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -371,35 +366,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -19150.23 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -17598.98 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        19150  |proj g|=       11.938
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       77.415  |proj g|=        1.5929
-  ys=-2.575e+01  -gs= 1.953e+01, BFGS update SKIPPED
-  At iterate     3  f =       76.697  |proj g|=        1.3974
-  At iterate     4  f =       76.183  |proj g|=        0.5133
-  At iterate     5  f =       76.177  |proj g|=       0.29894
-  At iterate     6  f =       76.174  |proj g|=      0.015561
-  At iterate     7  f =       76.174  |proj g|=    0.00044327
-  At iterate     8  f =       76.174  |proj g|=    6.8148e-07
+  At iterate     0  f=        17599  |proj g|=        11.71
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =       77.312  |proj g|=        1.2241
+  At iterate     3  f =       77.253  |proj g|=       0.12376
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       77.252  |proj g|=     0.0062735
+  At iterate     5  f =       77.252  |proj g|=    8.1294e-05
+  At iterate     6  f =       77.252  |proj g|=    5.2546e-08
   
-  iterations 8
-  function evaluations 32
+  iterations 6
+  function evaluations 19
   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 6.8148e-07
-  final function value 76.1741
+  norm of the final projected gradient 5.25457e-08
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -410,34 +404,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -125647.2 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -73705.36 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   1.2565e+05  |proj g|=        11.46
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       77.143  |proj g|=        8.0675
-  At iterate     3  f =       76.379  |proj g|=        1.2792
-  At iterate     4  f =       76.216  |proj g|=        1.0882
-  At iterate     5  f =       76.179  |proj g|=       0.39435
-  At iterate     6  f =       76.174  |proj g|=      0.046494
-  At iterate     7  f =       76.174  |proj g|=     0.0017341
-  At iterate     8  f =       76.174  |proj g|=    7.9978e-06
+  At iterate     0  f=        73705  |proj g|=       11.283
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =       78.733  |proj g|=         1.723
+  ys=-2.715e+01  -gs= 1.937e+01, BFGS update SKIPPED
+  At iterate     3  f =       78.244  |proj g|=        1.5984
+  At iterate     4  f =       77.292  |proj g|=          1.01
+  At iterate     5  f =       77.253  |proj g|=       0.10994
+  At iterate     6  f =       77.252  |proj g|=      0.013385
+  At iterate     7  f =       77.252  |proj g|=    0.00015341
+  At iterate     8  f =       77.252  |proj g|=    2.1104e-07
   
   iterations 8
-  function evaluations 25
+  function evaluations 30
   segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 7.99782e-06
-  final function value 76.1741
+  norm of the final projected gradient 2.11038e-07
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -448,34 +443,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -125647.2 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -73705.36 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   1.2565e+05  |proj g|=        11.46
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       77.143  |proj g|=        8.0675
-  At iterate     3  f =       76.379  |proj g|=        1.2792
-  At iterate     4  f =       76.216  |proj g|=        1.0882
-  At iterate     5  f =       76.179  |proj g|=       0.39435
-  At iterate     6  f =       76.174  |proj g|=      0.046494
-  At iterate     7  f =       76.174  |proj g|=     0.0017341
-  At iterate     8  f =       76.174  |proj g|=    7.9978e-06
+  At iterate     0  f=        73705  |proj g|=       11.283
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =       78.733  |proj g|=         1.723
+  ys=-2.715e+01  -gs= 1.937e+01, BFGS update SKIPPED
+  At iterate     3  f =       78.244  |proj g|=        1.5984
+  At iterate     4  f =       77.292  |proj g|=          1.01
+  At iterate     5  f =       77.253  |proj g|=       0.10994
+  At iterate     6  f =       77.252  |proj g|=      0.013385
+  At iterate     7  f =       77.252  |proj g|=    0.00015341
+  At iterate     8  f =       77.252  |proj g|=    2.1104e-07
   
   iterations 8
-  function evaluations 25
+  function evaluations 30
   segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 7.99782e-06
-  final function value 76.1741
+  norm of the final projected gradient 2.11038e-07
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -486,34 +482,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -38289.68 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -1658.431 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        38290  |proj g|=       11.731
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       78.162  |proj g|=        1.7635
-  ys=-3.061e+01  -gs= 1.923e+01, BFGS update SKIPPED
-  At iterate     3  f =       77.355  |proj g|=        1.5783
-  At iterate     4  f =       76.184  |proj g|=       0.55743
-  At iterate     5  f =       76.174  |proj g|=      0.031967
-  At iterate     6  f =       76.174  |proj g|=     0.0018958
-  At iterate     7  f =       76.174  |proj g|=     5.998e-06
-  
-  iterations 7
-  function evaluations 32
-  segments explored during Cauchy searches 10
+  At iterate     0  f=       1658.4  |proj g|=       12.207
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =        78.57  |proj g|=         1.683
+  ys=-2.589e+01  -gs= 1.943e+01, BFGS update SKIPPED
+  At iterate     3  f =       78.047  |proj g|=        1.5432
+  At iterate     4  f =       77.277  |proj g|=       0.81971
+  At iterate     5  f =       77.267  |proj g|=       0.68756
+  At iterate     6  f =       77.252  |proj g|=      0.059305
+  At iterate     7  f =       77.252  |proj g|=     0.0038876
+  At iterate     8  f =       77.252  |proj g|=     2.393e-05
+  At iterate     9  f =       77.252  |proj g|=     9.582e-09
+  
+  iterations 9
+  function evaluations 26
+  segments explored during Cauchy searches 12
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 5.99801e-06
-  final function value 76.1741
+  norm of the final projected gradient 9.58202e-09
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -524,33 +522,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.257707e-08 
+    - nugget : 1.313133e-08 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.905068 
-    - variance bounds :  0.1257707 12.72364 
-    - best initial criterion value(s) :  -34103.76 
+    - parameters upper bounds :  4 2 1.970775 
+    - variance bounds :  0.1309862 13.13133 
+    - best initial criterion value(s) :  -5986.749 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        34104  |proj g|=       11.265
-  At iterate     1  f =       111.96  |proj g|=        1.7745
-  At iterate     2  f =       78.551  |proj g|=        1.8466
-  ys=-3.204e+01  -gs= 1.908e+01, BFGS update SKIPPED
-  At iterate     3  f =       76.188  |proj g|=       0.64069
-  At iterate     4  f =       76.174  |proj g|=      0.017005
-  At iterate     5  f =       76.174  |proj g|=       0.00117
-  At iterate     6  f =       76.174  |proj g|=    1.9656e-06
+  At iterate     0  f=       5986.7  |proj g|=       11.848
+  At iterate     1  f =       112.77  |proj g|=        1.7173
+  At iterate     2  f =       78.267  |proj g|=        7.9704
+  At iterate     3  f =       77.463  |proj g|=        1.3384
+  At iterate     4  f =       77.297  |proj g|=        1.0707
+  At iterate     5  f =       77.257  |proj g|=       0.39627
+  At iterate     6  f =       77.252  |proj g|=      0.048079
+  At iterate     7  f =       77.252  |proj g|=      0.001878
+  At iterate     8  f =       77.252  |proj g|=    9.3557e-06
   
-  iterations 6
-  function evaluations 29
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.9656e-06
-  final function value 76.1741
+  iterations 8
+  function evaluations 24
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 9.35568e-06
+  final function value 77.2523
   
-  F = 76.1741
-  final  value 76.174122 
+  F = 77.2523
+  final  value 77.252256 
   converged
   
   optimisation start
@@ -565,53 +564,28 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -308.0488 
+    - best initial criterion value(s) :  -28891.41 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       308.05  |proj g|=       2.8748
-  At iterate     1  f =       268.73  |proj g|=        4.0974
-  At iterate     2  f =       267.31  |proj g|=        3.9889
-  At iterate     3  f =       267.09  |proj g|=        1.8206
-  At iterate     4  f =       267.09  |proj g|=        1.8203
-  At iterate     5  f =       267.09  |proj g|=        1.8534
-  At iterate     6  f =       267.08  |proj g|=        2.0593
-  At iterate     7  f =       267.04  |proj g|=        2.6268
-  At iterate     8  f =       254.52  |proj g|=        4.6525
-  At iterate     9  f =       254.52  |proj g|=         4.872
-  At iterate    10  f =        253.3  |proj g|=        3.4816
-  At iterate    11  f =       252.48  |proj g|=       0.85695
-  At iterate    12  f =       252.47  |proj g|=       0.79473
-  At iterate    13  f =       252.47  |proj g|=       0.26568
-  At iterate    14  f =       252.47  |proj g|=       0.20728
-  At iterate    15  f =       252.47  |proj g|=       0.54211
-  At iterate    16  f =       252.46  |proj g|=         1.097
-  At iterate    17  f =       252.45  |proj g|=        1.3292
-  At iterate    18  f =       252.41  |proj g|=        1.8204
-  At iterate    19  f =       252.29  |proj g|=        1.8507
-  At iterate    20  f =       251.94  |proj g|=         1.893
-  At iterate    21  f =       251.05  |proj g|=        1.9407
-  At iterate    22  f =       249.52  |proj g|=        1.9454
-  At iterate    23  f =       249.45  |proj g|=        1.9418
-  At iterate    24  f =        247.6  |proj g|=        1.8268
-  At iterate    25  f =        243.6  |proj g|=        1.7336
-  At iterate    26  f =       243.38  |proj g|=        1.7354
-  At iterate    27  f =       243.28  |proj g|=        1.7275
-  At iterate    28  f =       243.26  |proj g|=        1.2946
-  At iterate    29  f =       243.26  |proj g|=       0.15271
-  At iterate    30  f =       243.26  |proj g|=      0.014453
-  At iterate    31  f =       243.26  |proj g|=    0.00052813
-  
-  iterations 31
-  function evaluations 43
-  segments explored during Cauchy searches 32
+  At iterate     0  f=        28891  |proj g|=        458.3
+  At iterate     1  f =       407.94  |proj g|=      0.089708
+  At iterate     2  f =       318.27  |proj g|=      0.070929
+  At iterate     3  f =       318.22  |proj g|=     0.0038623
+  At iterate     4  f =       318.22  |proj g|=    0.00033503
+  At iterate     5  f =       318.22  |proj g|=    1.7728e-06
+  At iterate     6  f =       318.22  |proj g|=     8.084e-10
+  
+  iterations 6
+  function evaluations 21
+  segments explored during Cauchy searches 8
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000528131
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 8.08396e-10
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   
   optimisation start
@@ -626,27 +600,29 @@
     - 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) :  -341.9434 
+    - best initial criterion value(s) :  -372.0202 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       341.94  |proj g|=        13.79
-  At iterate     1  f =        329.1  |proj g|=       0.36677
-  At iterate     2  f =       320.63  |proj g|=       0.29572
-  At iterate     3  f =       318.24  |proj g|=      0.039665
+  At iterate     0  f=       372.02  |proj g|=       5.1071
+  At iterate     1  f =       326.67  |proj g|=       0.36663
+  At iterate     2  f =       324.95  |proj g|=       0.36102
+  At iterate     3  f =       319.09  |proj g|=       0.21252
   Nonpositive definiteness in Cholesky factorization in formk;
      refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       318.23  |proj g|=       0.03027
-  At iterate     5  f =       318.22  |proj g|=     0.0014597
-  At iterate     6  f =       318.22  |proj g|=    5.7041e-05
-  At iterate     7  f =       318.22  |proj g|=    1.1297e-07
-  
-  iterations 7
-  function evaluations 21
-  segments explored during Cauchy searches 11
+  At iterate     4  f =       318.88  |proj g|=       0.19099
+  At iterate     5  f =       318.25  |proj g|=      0.048843
+  At iterate     6  f =       318.23  |proj g|=      0.021811
+  At iterate     7  f =       318.22  |proj g|=     0.0015218
+  At iterate     8  f =       318.22  |proj g|=    4.3653e-05
+  At iterate     9  f =       318.22  |proj g|=    9.0609e-08
+  
+  iterations 9
+  function evaluations 17
+  segments explored during Cauchy searches 12
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.12969e-07
+  norm of the final projected gradient 9.06087e-08
   final function value 318.222
   
   F = 318.222
@@ -665,27 +641,64 @@
     - 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) :  -877.7414 
+    - best initial criterion value(s) :  -267.4841 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       877.74  |proj g|=       16.974
-  At iterate     1  f =       324.51  |proj g|=       0.35852
-  At iterate     2  f =       318.25  |proj g|=      0.043167
-  At iterate     3  f =       318.22  |proj g|=     0.0014373
-  At iterate     4  f =       318.22  |proj g|=    9.1388e-05
-  At iterate     5  f =       318.22  |proj g|=    1.7909e-07
-  
-  iterations 5
-  function evaluations 16
-  segments explored during Cauchy searches 7
+  At iterate     0  f=       267.48  |proj g|=       1.8287
+  At iterate     1  f =       267.36  |proj g|=        1.6027
+  At iterate     2  f =       267.35  |proj g|=        1.2439
+  At iterate     3  f =       267.35  |proj g|=        1.2298
+  At iterate     4  f =       267.35  |proj g|=        1.6852
+  At iterate     5  f =       267.35  |proj g|=         1.826
+  At iterate     6  f =       267.35  |proj g|=        1.8261
+  At iterate     7  f =       267.35  |proj g|=        1.8262
+  At iterate     8  f =       267.34  |proj g|=        1.8264
+  At iterate     9  f =       267.32  |proj g|=        1.8265
+  At iterate    10  f =       267.25  |proj g|=        1.8261
+  At iterate    11  f =       267.09  |proj g|=        1.8242
+  At iterate    12  f =       266.81  |proj g|=        2.6139
+  At iterate    13  f =       265.11  |proj g|=        3.7464
+  At iterate    14  f =       264.08  |proj g|=        2.7859
+  At iterate    15  f =       253.05  |proj g|=        3.9887
+  At iterate    16  f =       252.93  |proj g|=        6.3701
+  At iterate    17  f =       252.32  |proj g|=        2.8151
+  At iterate    18  f =       252.18  |proj g|=       0.33436
+  At iterate    19  f =       252.18  |proj g|=       0.20823
+  At iterate    20  f =       252.18  |proj g|=       0.20811
+  At iterate    21  f =       252.18  |proj g|=       0.20718
+  At iterate    22  f =       252.18  |proj g|=       0.20627
+  At iterate    23  f =       252.17  |proj g|=       0.20497
+  At iterate    24  f =       252.17  |proj g|=       0.21245
+  At iterate    25  f =       252.17  |proj g|=       0.24768
+  At iterate    26  f =       252.15  |proj g|=       0.19913
+  At iterate    27  f =       252.12  |proj g|=       0.23365
+  At iterate    28  f =       252.05  |proj g|=        1.5838
+  At iterate    29  f =       251.88  |proj g|=        3.7768
+  At iterate    30  f =       251.56  |proj g|=        7.2715
+  At iterate    31  f =       251.05  |proj g|=        10.881
+  At iterate    32  f =       248.98  |proj g|=        19.319
+  At iterate    33  f =       247.66  |proj g|=        23.377
+  At iterate    34  f =       247.54  |proj g|=        23.181
+  At iterate    35  f =       246.66  |proj g|=        20.639
+  At iterate    36  f =       244.08  |proj g|=        4.4672
+  At iterate    37  f =       243.66  |proj g|=        1.7409
+  At iterate    38  f =       243.27  |proj g|=       0.93986
+  At iterate    39  f =       243.26  |proj g|=       0.15266
+  At iterate    40  f =       243.26  |proj g|=      0.086432
+  At iterate    41  f =       243.26  |proj g|=    0.00045616
+  At iterate    42  f =       243.26  |proj g|=    1.5485e-05
+  
+  iterations 42
+  function evaluations 54
+  segments explored during Cauchy searches 43
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.79087e-07
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 1.5485e-05
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -700,43 +713,29 @@
     - 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) :  -253.6072 
+    - best initial criterion value(s) :  -703.4283 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       253.61  |proj g|=       8.8846
-  At iterate     1  f =       252.58  |proj g|=        1.2125
-  At iterate     2  f =       252.57  |proj g|=       0.49054
-  At iterate     3  f =       252.57  |proj g|=       0.20579
-  At iterate     4  f =       252.57  |proj g|=        1.0169
-  At iterate     5  f =       252.56  |proj g|=       0.22107
-  At iterate     6  f =       252.56  |proj g|=       0.23144
-  At iterate     7  f =       252.55  |proj g|=       0.78684
-  At iterate     8  f =        252.5  |proj g|=        1.8179
-  At iterate     9  f =       252.39  |proj g|=        1.8451
-  At iterate    10  f =        252.1  |proj g|=        1.8863
-  At iterate    11  f =       251.86  |proj g|=        1.8948
-  At iterate    12  f =       250.82  |proj g|=        1.9078
-  At iterate    13  f =       247.89  |proj g|=        1.8458
-  At iterate    14  f =       245.63  |proj g|=        1.7495
-  At iterate    15  f =       244.73  |proj g|=        1.7489
-  At iterate    16  f =       243.79  |proj g|=        1.7449
-  At iterate    17  f =       243.27  |proj g|=       0.81273
-  At iterate    18  f =       243.26  |proj g|=       0.15256
-  At iterate    19  f =       243.26  |proj g|=       0.15254
-  At iterate    20  f =       243.26  |proj g|=      0.030993
-  At iterate    21  f =       243.26  |proj g|=    7.6542e-05
-  
-  iterations 21
-  function evaluations 32
-  segments explored during Cauchy searches 22
+  At iterate     0  f=       703.43  |proj g|=       24.601
+  At iterate     1  f =       329.27  |proj g|=       0.36655
+  At iterate     2  f =        318.9  |proj g|=       0.19325
+  At iterate     3  f =       318.27  |proj g|=       0.06348
+  At iterate     4  f =       318.23  |proj g|=      0.030077
+  At iterate     5  f =       318.22  |proj g|=     0.0027629
+  At iterate     6  f =       318.22  |proj g|=    0.00010806
+  At iterate     7  f =       318.22  |proj g|=    4.0812e-07
+  
+  iterations 7
+  function evaluations 24
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 7.65424e-05
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 4.08117e-07
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   
   optimisation start
@@ -747,64 +746,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -73.66206 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -45438.54 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       73.662  |proj g|=        1.302
-  At iterate     1  f =       72.874  |proj g|=        2.2858
-  At iterate     2  f =       72.817  |proj g|=        1.9254
-  At iterate     3  f =       72.793  |proj g|=       0.56293
-  At iterate     4  f =       72.789  |proj g|=         1.925
-  At iterate     5  f =       72.789  |proj g|=       0.27324
-  At iterate     6  f =       72.789  |proj g|=       0.27038
-  At iterate     7  f =       72.789  |proj g|=       0.26972
-  At iterate     8  f =       72.789  |proj g|=        1.4056
-  At iterate     9  f =       72.789  |proj g|=        1.9249
-  At iterate    10  f =       72.788  |proj g|=         1.925
-  At iterate    11  f =       72.787  |proj g|=         1.925
-  At iterate    12  f =       72.784  |proj g|=         1.925
-  At iterate    13  f =       72.777  |proj g|=         1.925
-  At iterate    14  f =        72.76  |proj g|=        1.9249
-  At iterate    15  f =       72.725  |proj g|=        1.9248
-  At iterate    16  f =       72.693  |proj g|=        1.9239
-  At iterate    17  f =        72.65  |proj g|=        1.9237
-  At iterate    18  f =       72.631  |proj g|=        1.9233
-  At iterate    19  f =        72.63  |proj g|=        1.9232
-  At iterate    20  f =       72.629  |proj g|=       0.40949
-  At iterate    21  f =       72.629  |proj g|=       0.41375
-  At iterate    22  f =       72.628  |proj g|=         1.923
-  At iterate    23  f =       72.624  |proj g|=        1.9229
-  At iterate    24  f =       72.561  |proj g|=        1.9211
-  At iterate    25  f =        72.55  |proj g|=        1.9205
-  At iterate    26  f =       72.382  |proj g|=        1.9195
-  At iterate    27  f =       72.362  |proj g|=        1.9197
-  At iterate    28  f =       72.355  |proj g|=       0.83558
-  At iterate    29  f =       72.341  |proj g|=       0.77087
-  At iterate    30  f =       72.307  |proj g|=       0.12553
-  At iterate    31  f =       72.304  |proj g|=      0.029847
-  At iterate    32  f =       72.303  |proj g|=      0.025757
-  At iterate    33  f =       72.303  |proj g|=      0.012045
-  At iterate    34  f =       72.303  |proj g|=       0.52756
-  At iterate    35  f =       72.303  |proj g|=      0.013649
-  At iterate    36  f =       72.303  |proj g|=     0.0066307
-  At iterate    37  f =       72.303  |proj g|=     0.0062946
-  At iterate    38  f =       72.303  |proj g|=      0.080847
+  At iterate     0  f=        45439  |proj g|=       8.9482
+  At iterate     1  f =       105.76  |proj g|=        2.2733
+  At iterate     2  f =        71.63  |proj g|=        1.2885
+  ys=-2.647e+01  -gs= 1.940e+01, BFGS update SKIPPED
+  At iterate     3  f =       71.108  |proj g|=        1.1854
+  At iterate     4  f =       70.271  |proj g|=       0.92716
+  At iterate     5  f =        70.24  |proj g|=       0.10408
+  At iterate     6  f =        70.24  |proj g|=      0.011136
+  At iterate     7  f =        70.24  |proj g|=    9.0967e-05
+  At iterate     8  f =        70.24  |proj g|=      7.87e-08
   
-  iterations 38
-  function evaluations 47
-  segments explored during Cauchy searches 41
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.0808473
-  final function value 72.3028
+  iterations 8
+  function evaluations 34
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 7.86995e-08
+  final function value 70.2402
   
-  F = 72.3028
-  final  value 72.302755 
+  F = 70.2402
+  final  value 70.240169 
   converged
   
   optimisation start
@@ -815,64 +785,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -73.66206 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -45438.54 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       73.662  |proj g|=        1.302
-  At iterate     1  f =       72.874  |proj g|=        2.2858
-  At iterate     2  f =       72.817  |proj g|=        1.9254
-  At iterate     3  f =       72.793  |proj g|=       0.56293
-  At iterate     4  f =       72.789  |proj g|=         1.925
-  At iterate     5  f =       72.789  |proj g|=       0.27324
-  At iterate     6  f =       72.789  |proj g|=       0.27038
-  At iterate     7  f =       72.789  |proj g|=       0.26972
-  At iterate     8  f =       72.789  |proj g|=        1.4056
-  At iterate     9  f =       72.789  |proj g|=        1.9249
-  At iterate    10  f =       72.788  |proj g|=         1.925
-  At iterate    11  f =       72.787  |proj g|=         1.925
-  At iterate    12  f =       72.784  |proj g|=         1.925
-  At iterate    13  f =       72.777  |proj g|=         1.925
-  At iterate    14  f =        72.76  |proj g|=        1.9249
-  At iterate    15  f =       72.725  |proj g|=        1.9248
-  At iterate    16  f =       72.693  |proj g|=        1.9239
-  At iterate    17  f =        72.65  |proj g|=        1.9237
-  At iterate    18  f =       72.631  |proj g|=        1.9233
-  At iterate    19  f =        72.63  |proj g|=        1.9232
-  At iterate    20  f =       72.629  |proj g|=       0.40949
-  At iterate    21  f =       72.629  |proj g|=       0.41375
-  At iterate    22  f =       72.628  |proj g|=         1.923
-  At iterate    23  f =       72.624  |proj g|=        1.9229
-  At iterate    24  f =       72.561  |proj g|=        1.9211
-  At iterate    25  f =        72.55  |proj g|=        1.9205
-  At iterate    26  f =       72.382  |proj g|=        1.9195
-  At iterate    27  f =       72.362  |proj g|=        1.9197
-  At iterate    28  f =       72.355  |proj g|=       0.83558
-  At iterate    29  f =       72.341  |proj g|=       0.77087
-  At iterate    30  f =       72.307  |proj g|=       0.12553
-  At iterate    31  f =       72.304  |proj g|=      0.029847
-  At iterate    32  f =       72.303  |proj g|=      0.025757
-  At iterate    33  f =       72.303  |proj g|=      0.012045
-  At iterate    34  f =       72.303  |proj g|=       0.52756
-  At iterate    35  f =       72.303  |proj g|=      0.013649
-  At iterate    36  f =       72.303  |proj g|=     0.0066307
-  At iterate    37  f =       72.303  |proj g|=     0.0062946
-  At iterate    38  f =       72.303  |proj g|=      0.080847
+  At iterate     0  f=        45439  |proj g|=       8.9482
+  At iterate     1  f =       105.76  |proj g|=        2.2733
+  At iterate     2  f =        71.63  |proj g|=        1.2885
+  ys=-2.647e+01  -gs= 1.940e+01, BFGS update SKIPPED
+  At iterate     3  f =       71.108  |proj g|=        1.1854
+  At iterate     4  f =       70.271  |proj g|=       0.92716
+  At iterate     5  f =        70.24  |proj g|=       0.10408
+  At iterate     6  f =        70.24  |proj g|=      0.011136
+  At iterate     7  f =        70.24  |proj g|=    9.0967e-05
+  At iterate     8  f =        70.24  |proj g|=      7.87e-08
   
-  iterations 38
-  function evaluations 47
-  segments explored during Cauchy searches 41
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.0808473
-  final function value 72.3028
+  iterations 8
+  function evaluations 34
+  segments explored during Cauchy searches 11
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 7.86995e-08
+  final function value 70.2402
   
-  F = 72.3028
-  final  value 72.302755 
+  F = 70.2402
+  final  value 70.240169 
   converged
   
   optimisation start
@@ -883,35 +824,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -1133.953 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -826.1615 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         1134  |proj g|=       9.9637
-  At iterate     1  f =       108.79  |proj g|=        2.0139
-  At iterate     2  f =       73.501  |proj g|=        1.2434
-  ys=-1.670e+01  -gs= 1.986e+01, BFGS update SKIPPED
-  At iterate     3  f =       73.038  |proj g|=        1.0849
-  At iterate     4  f =       72.973  |proj g|=        1.6756
-  At iterate     5  f =        72.92  |proj g|=       0.30349
-  At iterate     6  f =       72.918  |proj g|=      0.038493
-  At iterate     7  f =       72.918  |proj g|=     0.0010502
-  At iterate     8  f =       72.918  |proj g|=    3.5138e-06
+  At iterate     0  f=       826.16  |proj g|=       9.1391
+  At iterate     1  f =       105.76  |proj g|=        2.2733
+  At iterate     2  f =       72.676  |proj g|=        1.4704
+  ys=-3.158e+01  -gs= 1.899e+01, BFGS update SKIPPED
+  At iterate     3  f =       70.305  |proj g|=       0.95082
+  At iterate     4  f =        70.24  |proj g|=        0.1139
+  At iterate     5  f =        70.24  |proj g|=      0.018181
+  At iterate     6  f =        70.24  |proj g|=    0.00016256
+  At iterate     7  f =        70.24  |proj g|=    2.2945e-07
   
-  iterations 8
-  function evaluations 23
-  segments explored during Cauchy searches 11
+  iterations 7
+  function evaluations 26
+  segments explored during Cauchy searches 10
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 3.51379e-06
-  final function value 72.9182
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 2.29446e-07
+  final function value 70.2402
   
-  F = 72.9182
-  final  value 72.918193 
+  F = 70.2402
+  final  value 70.240169 
   converged
   
   optimisation start
@@ -922,35 +862,34 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -1133.953 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -826.1615 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=         1134  |proj g|=       9.9637
-  At iterate     1  f =       108.79  |proj g|=        2.0139
-  At iterate     2  f =       73.501  |proj g|=        1.2434
-  ys=-1.670e+01  -gs= 1.986e+01, BFGS update SKIPPED
-  At iterate     3  f =       73.038  |proj g|=        1.0849
-  At iterate     4  f =       72.973  |proj g|=        1.6756
-  At iterate     5  f =        72.92  |proj g|=       0.30349
-  At iterate     6  f =       72.918  |proj g|=      0.038493
-  At iterate     7  f =       72.918  |proj g|=     0.0010502
-  At iterate     8  f =       72.918  |proj g|=    3.5138e-06
+  At iterate     0  f=       826.16  |proj g|=       9.1391
+  At iterate     1  f =       105.76  |proj g|=        2.2733
+  At iterate     2  f =       72.676  |proj g|=        1.4704
+  ys=-3.158e+01  -gs= 1.899e+01, BFGS update SKIPPED
+  At iterate     3  f =       70.305  |proj g|=       0.95082
+  At iterate     4  f =        70.24  |proj g|=        0.1139
+  At iterate     5  f =        70.24  |proj g|=      0.018181
+  At iterate     6  f =        70.24  |proj g|=    0.00016256
+  At iterate     7  f =        70.24  |proj g|=    2.2945e-07
   
-  iterations 8
-  function evaluations 23
-  segments explored during Cauchy searches 11
+  iterations 7
+  function evaluations 26
+  segments explored during Cauchy searches 10
   BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 3.51379e-06
-  final function value 72.9182
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 2.29446e-07
+  final function value 70.2402
   
-  F = 72.9182
-  final  value 72.918193 
+  F = 70.2402
+  final  value 70.240169 
   converged
   
   optimisation start
@@ -961,35 +900,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -17359.3 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -155.2631 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        17359  |proj g|=       9.9673
-  At iterate     1  f =       108.79  |proj g|=        2.0139
-  At iterate     2  f =       73.085  |proj g|=        1.1067
-  ys=-2.660e+00  -gs= 2.014e+01, BFGS update SKIPPED
-  At iterate     3  f =       73.027  |proj g|=        1.0794
-  At iterate     4  f =       72.928  |proj g|=       0.68483
-  At iterate     5  f =       72.919  |proj g|=       0.13157
-  At iterate     6  f =       72.918  |proj g|=      0.007365
-  At iterate     7  f =       72.918  |proj g|=    8.5161e-05
-  At iterate     8  f =       72.918  |proj g|=    5.4337e-08
+  At iterate     0  f=       155.26  |proj g|=       8.8847
+  At iterate     1  f =       105.76  |proj g|=        2.2733
+  At iterate     2  f =       70.887  |proj g|=        1.1364
+  ys=-1.739e+01  -gs= 1.975e+01, BFGS update SKIPPED
+  At iterate     3  f =       70.404  |proj g|=       0.99734
+  At iterate     4  f =       70.245  |proj g|=       0.50443
+  At iterate     5  f =       70.241  |proj g|=       0.14127
+  At iterate     6  f =        70.24  |proj g|=     0.0057478
+  At iterate     7  f =        70.24  |proj g|=     6.233e-05
+  At iterate     8  f =        70.24  |proj g|=    2.7878e-08
   
   iterations 8
-  function evaluations 25
+  function evaluations 28
   segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 5.43368e-08
-  final function value 72.9182
+  norm of the final projected gradient 2.78775e-08
+  final function value 70.2402
   
-  F = 72.9182
-  final  value 72.918193 
+  F = 70.2402
+  final  value 70.240169 
   converged
   
   optimisation start
@@ -1000,32 +939,64 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 1.104125e-08 
+    - nugget : 9.919649e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.926668 
-    - variance bounds :  0.1104125 11.21586 
-    - best initial criterion value(s) :  -11680.76 
+    - parameters upper bounds :  4 2 1.904165 
+    - variance bounds :  0.09510111 9.919648 
+    - best initial criterion value(s) :  -70.62084 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        11681  |proj g|=       10.272
-  At iterate     1  f =       108.79  |proj g|=        2.0139
-  At iterate     2  f =       75.213  |proj g|=         1.606
-  ys=-3.201e+01  -gs= 1.913e+01, BFGS update SKIPPED
-  At iterate     3  f =       72.918  |proj g|=      0.065358
-  At iterate     4  f =       72.918  |proj g|=    0.00012724
-  At iterate     5  f =       72.918  |proj g|=      7.25e-07
+  At iterate     0  f=       70.621  |proj g|=       1.9032
+  At iterate     1  f =       70.581  |proj g|=        1.1036
+  At iterate     2  f =       70.581  |proj g|=        1.1036
+  At iterate     3  f =       70.581  |proj g|=        1.1035
+  At iterate     4  f =       70.581  |proj g|=        1.9029
+  At iterate     5  f =        70.58  |proj g|=        1.9029
+  At iterate     6  f =       70.578  |proj g|=        1.9029
+  At iterate     7  f =       70.573  |proj g|=         1.903
+  At iterate     8  f =        70.56  |proj g|=        1.9031
+  At iterate     9  f =       70.526  |proj g|=        1.9033
+  At iterate    10  f =       70.437  |proj g|=        1.9035
+  At iterate    11  f =       70.262  |proj g|=        1.9037
+  At iterate    12  f =       70.233  |proj g|=        1.9039
+  At iterate    13  f =       70.104  |proj g|=        1.9031
+  At iterate    14  f =         70.1  |proj g|=         1.903
+  At iterate    15  f =       70.067  |proj g|=         1.903
+  At iterate    16  f =        70.05  |proj g|=       0.14007
+  At iterate    17  f =       70.049  |proj g|=       0.12761
+  At iterate    18  f =       70.049  |proj g|=         0.125
+  At iterate    19  f =       70.049  |proj g|=       0.12502
+  At iterate    20  f =       70.049  |proj g|=         1.903
+  At iterate    21  f =       70.049  |proj g|=        1.9029
+  At iterate    22  f =       70.049  |proj g|=       0.12743
+  At iterate    23  f =       70.048  |proj g|=       0.13166
+  At iterate    24  f =       70.046  |proj g|=       0.15281
+  At iterate    25  f =       70.044  |proj g|=       0.16506
+  At iterate    26  f =       70.041  |proj g|=       0.16643
+  At iterate    27  f =       70.038  |proj g|=        0.1349
+  At iterate    28  f =       70.038  |proj g|=       0.11047
+  At iterate    29  f =       70.038  |proj g|=      0.090562
+  At iterate    30  f =       70.038  |proj g|=       0.87932
+  At iterate    31  f =       70.037  |proj g|=        1.0391
+  At iterate    32  f =       70.037  |proj g|=      0.012187
+  At iterate    33  f =       70.037  |proj g|=     0.0015148
+  At iterate    34  f =       70.037  |proj g|=       0.10983
+  At iterate    35  f =       70.037  |proj g|=       0.13307
+  At iterate    36  f =       70.037  |proj g|=     0.0046522
+  At iterate    37  f =       70.037  |proj g|=     0.0014781
+  At iterate    38  f =       70.037  |proj g|=     0.0014772
   
-  iterations 5
-  function evaluations 24
-  segments explored during Cauchy searches 8
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 7.25003e-07
-  final function value 72.9182
+  iterations 38
+  function evaluations 50
+  segments explored during Cauchy searches 40
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 0.00147716
+  final function value 70.0373
   
-  F = 72.9182
-  final  value 72.918193 
+  F = 70.0373
+  final  value 70.037295 
   converged
   
   optimisation start
@@ -1040,25 +1011,26 @@
     - 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) :  -336.3525 
+    - best initial criterion value(s) :  -618.8492 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       336.35  |proj g|=       44.231
-  At iterate     1  f =       319.26  |proj g|=       0.22617
-  At iterate     2  f =       318.75  |proj g|=       0.17549
-  At iterate     3  f =       318.24  |proj g|=      0.042526
-  At iterate     4  f =       318.22  |proj g|=      0.016358
-  At iterate     5  f =       318.22  |proj g|=    0.00099165
-  At iterate     6  f =       318.22  |proj g|=    2.1506e-05
-  At iterate     7  f =       318.22  |proj g|=     2.906e-08
+  At iterate     0  f=       618.85  |proj g|=       7.5455
+  At iterate     1  f =       326.78  |proj g|=       0.36679
+  At iterate     2  f =       321.01  |proj g|=       0.30743
+  At iterate     3  f =       318.22  |proj g|=     0.0032143
+  Nonpositive definiteness in Cholesky factorization in formk;
+     refresh the lbfgs memory and restart the iteration.
+  At iterate     4  f =       318.22  |proj g|=      0.002514
+  At iterate     5  f =       318.22  |proj g|=    1.0886e-05
+  At iterate     6  f =       318.22  |proj g|=    3.7069e-08
   
-  iterations 7
-  function evaluations 12
-  segments explored during Cauchy searches 9
+  iterations 6
+  function evaluations 18
+  segments explored during Cauchy searches 10
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 2.90599e-08
+  norm of the final projected gradient 3.70692e-08
   final function value 318.222
   
   F = 318.222
@@ -1077,44 +1049,29 @@
     - 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) :  -279.1848 
+    - best initial criterion value(s) :  -773.7709 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       279.18  |proj g|=       43.177
-  At iterate     1  f =       250.97  |proj g|=        3.7377
-  At iterate     2  f =       250.87  |proj g|=        1.6957
-  At iterate     3  f =       250.86  |proj g|=        1.7644
-  At iterate     4  f =       250.83  |proj g|=       0.22003
-  At iterate     5  f =       250.83  |proj g|=        0.2191
-  At iterate     6  f =       250.83  |proj g|=       0.39683
-  At iterate     7  f =       250.81  |proj g|=       0.98006
-  At iterate     8  f =       250.78  |proj g|=        1.7643
-  At iterate     9  f =        250.7  |proj g|=        1.7878
-  At iterate    10  f =       250.51  |proj g|=        1.8386
-  At iterate    11  f =        250.1  |proj g|=        1.8662
-  At iterate    12  f =       249.14  |proj g|=         1.851
-  At iterate    13  f =       246.89  |proj g|=        1.7537
-  At iterate    14  f =       245.46  |proj g|=        1.6366
-  At iterate    15  f =       244.82  |proj g|=        5.2221
-  At iterate    16  f =       243.33  |proj g|=        1.7337
-  At iterate    17  f =       243.27  |proj g|=       0.34435
-  At iterate    18  f =       243.27  |proj g|=       0.15288
-  At iterate    19  f =       243.27  |proj g|=       0.21463
-  At iterate    20  f =       243.26  |proj g|=      0.024106
-  At iterate    21  f =       243.26  |proj g|=    3.0972e-05
-  At iterate    22  f =       243.26  |proj g|=    5.4364e-07
-  
-  iterations 22
-  function evaluations 32
-  segments explored during Cauchy searches 23
+  At iterate     0  f=       773.77  |proj g|=       10.536
+  At iterate     1  f =       328.04  |proj g|=       0.36756
+  At iterate     2  f =       318.73  |proj g|=       0.17246
+  At iterate     3  f =       318.25  |proj g|=      0.050631
+  At iterate     4  f =       318.22  |proj g|=      0.015409
+  At iterate     5  f =       318.22  |proj g|=     0.0010027
+  At iterate     6  f =       318.22  |proj g|=    2.1622e-05
+  At iterate     7  f =       318.22  |proj g|=    2.9539e-08
+  
+  iterations 7
+  function evaluations 18
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 5.43638e-07
-  final function value 243.264
+  active bounds at final generalized Cauchy point 2
+  norm of the final projected gradient 2.95394e-08
+  final function value 318.222
   
-  F = 243.264
-  final  value 243.264413 
+  F = 318.222
+  final  value 318.221782 
   converged
   [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
   
> library(data.table, lib.loc=R.home("library"))
> (sig.diff.dt <- myDiff(Rvers))
Key: <checking>
Empty data.table (0 rows and 3 cols): checking,master,release
> 
> ## If there are significant differences, use git bisect to find when
> ## they started.
> if(nrow(sig.diff.dt)){
+   dt.git <- file.path(task.dir, "data.table.git")
+   system(paste("cd ~/R/data.table && git fetch --tags"))
+   system(paste("git clone ~/R/data.table", dt.git))
+   release.tag <- gsub(".tar.gz|.*_", "", cargs[["release"]])
+   rev.parse.cmd <- paste(
+     "cd", dt.git, "&& git rev-parse master")
+   master.sha <- system(rev.parse.cmd, intern=TRUE)
+   merge.base.cmd <- paste(
+     "cd", dt.git, "&& git merge-base master", release.tag)
+   merge.base.sha <- system(merge.base.cmd, intern=TRUE)
+   old.sha <- merge.base.sha
+   run_R <- file.path(proj.dir, "install_dt_then_check_dep.R")
+   sig.diff.dt[, first.bad.commit := NA_character_]
+   sig.diff.dt[, comments := NA_character_]
+   for(diff.i in 1:nrow(sig.diff.dt)){
+     sig.diff.row <- sig.diff.dt[diff.i]
+     bisect.cmd <- paste(
+       "cd", dt.git, "&&",
+       "git bisect start &&",
+       "git bisect old", old.sha, "&&",
+       "git bisect new master &&",
+       "git bisect run",
+       R.home('bin/Rscript'),
+       run_R,
+       shQuote(sig.diff.row$checking),
+       sig.diff.row$release,
+       rev.dep.release.tar.gz,
+       release.tag)
+     print(bisect.cmd)
+     bisect.out <- system(bisect.cmd, intern=TRUE)
+     cat(bisect.out,sep="\n")
+     if(is.null(attr(bisect.out,"status"))){
+       first.bad.sha <- nc::capture_all_str(
+         bisect.out,
+         sha="[0-9a-f]+",
+         " is the first new commit")$sha
+       parent.cmd <- paste(
+         "cd ~/R/data.table && git log --pretty=%P -n 1",
+         first.bad.sha)
+       parent.sha <- system(parent.cmd, intern=TRUE)
+       sig.diff.dt[diff.i, first.bad.commit := first.bad.sha]
+       parent.msg <- paste0("parent=", parent.sha)
+       this.comment <- if(parent.sha==old.sha){
+         paste(parent.msg, "same as git bisect old")
+       }else if(first.bad.sha==master.sha){
+         paste("same as git bisect new=master,", parent.msg)
+       }else{
+         parent.msg
+       }
+       sig.diff.dt[diff.i, comments := this.comment]
+     }
+   }
+   ## add CRAN column.
+   sig.diff.dt[, CRAN := {
+     flavor <- get_flavor(Rvers)
+     details <- data.table(flavor=unique(flavor))[, {
+       base <- "https://www.r-project.org/nosvn/R.check/"
+       u <- paste0(base, flavor, "/", rev.dep, "-00check.txt")
+       check.txt <- tempfile()
+       tryCatch({
+         download.file(u, check.txt, quiet=TRUE)
+       }, error=function(e){
+         NULL
+       })
+       check.lines <- if(file.exists(check.txt)){
+         readLines(check.txt,encoding="UTF-8")
+       }else{
+         ""
+       }
+       repl.lines <- gsub("[\u2018\u2019]", "'", check.lines)
+       ##gsub("[‘’]", "'", check.lines) does not work with LC_ALL=C.
+       myStatus(line.vec=repl.lines)
+     }, by=flavor]
+     select.dt <- data.table(flavor, checking)
+     details[select.dt, msg, on=.(flavor, checking)]
+   }]
+   dir.create(file.path(job.dir, Rvers))
+   diffs.csv <- file.path(job.dir, Rvers, "significant_differences.csv")
+   data.table::fwrite(sig.diff.dt, diffs.csv)
+   print(sig.diff.dt)
+ }
> 
WARNING: ignoring environment value of R_HOME

R version 4.4.3 (2025-02-28) -- "Trophy Case"
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/2025-03-30/deps.csv", 
task.str = "843", release = "/scratch/th798/data.table-revdeps/2025-03-30/data.table_release_1.17.0.tar.gz", 
master = "/scratch/th798/data.table-revdeps/2025-03-30/data.table_master_1.17.99.2cb03162a21328cc5f68a8c3b0e554f5edfcb5b9.tar.gz"
)
> (task.dir <- dirname(.libPaths()[1]))#should be /tmp/th798/slurmid/R-vers
[1] "/tmp/th798/16189871/R-release/843"
> if(requireNamespace("R.cache"))R.cache::getCachePath()
Loading required namespace: R.cache
[1] "/tmp/th798/16189871/R-release/843/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/th798/16189871/R-release/843/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] "2025-03-30 01:22:04 MST"
> install.time <- system.time({
+   install.packages(rev.dep, dep=TRUE)
+ })
Installing package into '/tmp/th798/16189871/R-release/843/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'
Content type 'application/x-gzip' length 47134 bytes (46 KB)
==================================================
downloaded 46 KB

trying URL 'http://cloud.r-project.org/src/contrib/mlr3_0.23.0.tar.gz'
Content type 'application/x-gzip' length 948622 bytes (926 KB)
==================================================
downloaded 926 KB

trying URL 'http://cloud.r-project.org/src/contrib/paradox_1.0.1.tar.gz'
Content type 'application/x-gzip' length 386196 bytes (377 KB)
==================================================
downloaded 377 KB

trying URL 'http://cloud.r-project.org/src/contrib/DiceKriging_1.6.0.tar.gz'
Content type 'application/x-gzip' length 100520 bytes (98 KB)
==================================================
downloaded 98 KB

trying URL 'http://cloud.r-project.org/src/contrib/rgenoud_5.9-0.11.tar.gz'
Content type 'application/x-gzip' length 727266 bytes (710 KB)
==================================================
downloaded 710 KB

trying URL 'http://cloud.r-project.org/src/contrib/mlr3learners_0.10.0.tar.gz'
Content type 'application/x-gzip' length 67986 bytes (66 KB)
==================================================
downloaded 66 KB

* installing *source* package 'mlr3measures' ...
** 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' ...
** 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' ...
** 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/th798/16189871/R-release/843/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' ...
** 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/th798/16189871/R-release/843/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' ...
** 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' ...
** 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/th798/16189871/RtmpQXPp9r/downloaded_packages'
> cat("Time to install revdep:\n")
Time to install revdep:
> print(install.time)
   user  system elapsed 
 54.623   2.503  64.801 
> print(Sys.time())
[1] "2025-03-30 01:23:09 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] "2025-03-30 01:23:09 MST"
Installing package into '/tmp/th798/16189871/R-release/843/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** 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/th798/16189871/R-release/843/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] "2025-03-30 01:23:27 MST"
* using log directory '/tmp/th798/16189871/R-release/843/mlr3learners.Rcheck'
* using R version 4.4.3 (2025-02-28)
* 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 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 20.175741 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.175741 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.727699 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  6 (5 variable)
  initial  value 9.332863 
  iter  10 value 7.325056
  final  value 7.325044 
  converged
  # weights:  6 (5 variable)
  initial  value 9.332863 
  iter  10 value 7.325056
  final  value 7.325044 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  final  value 18.190606 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.555658 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.807897 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.807897 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 31.596629
  iter  10 value 31.596629
  final  value 31.596629 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 31.596629
  iter  10 value 31.596629
  final  value 31.596629 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.312711 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.312711 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  18 (10 variable)
  initial  value 15.435041 
  iter  10 value 12.723653
  iter  20 value 12.700980
  final  value 12.700979 
  converged
  # weights:  18 (10 variable)
  initial  value 15.435041 
  iter  10 value 12.723653
  iter  20 value 12.700980
  final  value 12.700979 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 29.311367
  final  value 29.310710 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -1795.619 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1795.6  |proj g|=        7.433
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       64.882  |proj g|=       0.78137
  At iterate     3  f =       64.768  |proj g|=       0.28144
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       64.767  |proj g|=      0.042776
  At iterate     5  f =       64.767  |proj g|=    0.00076652
  At iterate     6  f =       64.767  |proj g|=    2.0419e-06
  
  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 2.04188e-06
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -1795.619 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1795.6  |proj g|=        7.433
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       64.882  |proj g|=       0.78137
  At iterate     3  f =       64.768  |proj g|=       0.28144
  Nonpositive definiteness in Cholesky factorization in formk;
     refresh the lbfgs memory and restart the iteration.
  At iterate     4  f =       64.767  |proj g|=      0.042776
  At iterate     5  f =       64.767  |proj g|=    0.00076652
  At iterate     6  f =       64.767  |proj g|=    2.0419e-06
  
  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 2.04188e-06
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -303783.6 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   3.0378e+05  |proj g|=        7.573
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       66.255  |proj g|=        1.0465
  ys=-2.957e+01  -gs= 1.961e+01, BFGS update SKIPPED
  At iterate     3  f =       65.659  |proj g|=       0.95325
  At iterate     4  f =       64.799  |proj g|=       0.74266
  At iterate     5  f =       64.767  |proj g|=       0.13937
  At iterate     6  f =       64.767  |proj g|=      0.015341
  At iterate     7  f =       64.767  |proj g|=    0.00013489
  At iterate     8  f =       64.767  |proj g|=    1.2914e-07
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.29142e-07
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -303783.6 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   3.0378e+05  |proj g|=        7.573
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       66.255  |proj g|=        1.0465
  ys=-2.957e+01  -gs= 1.961e+01, BFGS update SKIPPED
  At iterate     3  f =       65.659  |proj g|=       0.95325
  At iterate     4  f =       64.799  |proj g|=       0.74266
  At iterate     5  f =       64.767  |proj g|=       0.13937
  At iterate     6  f =       64.767  |proj g|=      0.015341
  At iterate     7  f =       64.767  |proj g|=    0.00013489
  At iterate     8  f =       64.767  |proj g|=    1.2914e-07
  
  iterations 8
  function evaluations 34
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.29142e-07
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -1366.86 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1366.9  |proj g|=       7.8262
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       64.884  |proj g|=        3.5269
  At iterate     3  f =       64.768  |proj g|=       0.33533
  At iterate     4  f =       64.767  |proj g|=      0.059578
  At iterate     5  f =       64.767  |proj g|=      0.001288
  At iterate     6  f =       64.767  |proj g|=    4.8164e-06
  
  iterations 6
  function evaluations 20
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.81639e-06
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.96916e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.899998 
    - variance bounds :  0.0796916 8.353215 
    - best initial criterion value(s) :  -294.204 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        294.2  |proj g|=       7.8703
  At iterate     1  f =       101.35  |proj g|=         2.713
  At iterate     2  f =       66.289  |proj g|=        7.7917
  At iterate     3  f =       65.226  |proj g|=       0.87232
  At iterate     4  f =       64.903  |proj g|=       0.78902
  At iterate     5  f =       64.814  |proj g|=         2.125
  At iterate     6  f =       64.769  |proj g|=       0.42001
  At iterate     7  f =       64.767  |proj g|=      0.049395
  At iterate     8  f =       64.767  |proj g|=     0.0013457
  At iterate     9  f =       64.767  |proj g|=    4.1685e-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 4.16848e-06
  final function value 64.7667
  
  F = 64.7667
  final  value 64.766710 
  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) :  -1774.329 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       1774.3  |proj g|=       27.578
  At iterate     1  f =       334.18  |proj g|=       0.35231
  At iterate     2  f =       318.23  |proj g|=      0.028405
  At iterate     3  f =       318.22  |proj g|=      0.001693
  At iterate     4  f =       318.22  |proj g|=    6.8962e-05
  At iterate     5  f =       318.22  |proj g|=    1.5925e-07
  
  iterations 5
  function evaluations 21
  segments explored during Cauchy searches 7
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.59254e-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) :  -322.0715 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       322.07  |proj g|=       12.486
  At iterate     1  f =       253.61  |proj g|=         15.36
  At iterate     2  f =       251.33  |proj g|=        2.4225
  At iterate     3  f =       251.25  |proj g|=        1.0735
  At iterate     4  f =       251.21  |proj g|=        1.6905
  At iterate     5  f =       251.19  |proj g|=       0.23556
  At iterate     6  f =       251.19  |proj g|=       0.21681
  At iterate     7  f =       251.19  |proj g|=       0.21473
  At iterate     8  f =       251.18  |proj g|=       0.38392
  At iterate     9  f =       251.18  |proj g|=       0.76454
  At iterate    10  f =       251.17  |proj g|=        1.3508
  At iterate    11  f =       251.13  |proj g|=         1.771
  At iterate    12  f =       251.05  |proj g|=        1.7928
  At iterate    13  f =       250.85  |proj g|=        1.8249
  At iterate    14  f =       250.39  |proj g|=        1.8635
  At iterate    15  f =       249.41  |proj g|=        1.8966
  At iterate    16  f =       249.38  |proj g|=        1.8622
  At iterate    17  f =       247.82  |proj g|=        1.8232
  At iterate    18  f =       244.57  |proj g|=        1.7425
  At iterate    19  f =       243.28  |proj g|=        1.7298
  At iterate    20  f =       243.27  |proj g|=        1.2235
  At iterate    21  f =       243.26  |proj g|=       0.15275
  At iterate    22  f =       243.26  |proj g|=      0.046928
  At iterate    23  f =       243.26  |proj g|=    4.2376e-05
  At iterate    24  f =       243.26  |proj g|=    8.9789e-07
  
  iterations 24
  function evaluations 35
  segments explored during Cauchy searches 25
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 8.97888e-07
  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) :  -442.2915 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       442.29  |proj g|=       3.5197
  At iterate     1  f =       330.16  |proj g|=       0.36498
  At iterate     2  f =       318.79  |proj g|=       0.18093
  At iterate     3  f =       318.27  |proj g|=      0.058029
  At iterate     4  f =       318.23  |proj g|=      0.024365
  At iterate     5  f =       318.22  |proj g|=     0.0020454
  At iterate     6  f =       318.22  |proj g|=    6.5327e-05
  At iterate     7  f =       318.22  |proj g|=    1.8242e-07
  
  iterations 7
  function evaluations 20
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.82418e-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) :  -300.494 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       300.49  |proj g|=      0.75297
  At iterate     1  f =       285.37  |proj g|=        28.409
  At iterate     2  f =       281.92  |proj g|=        43.981
  At iterate     3  f =       280.58  |proj g|=        43.939
  At iterate     4  f =       278.06  |proj g|=        43.865
  At iterate     5  f =       267.81  |proj g|=        43.615
  At iterate     6  f =       261.39  |proj g|=        1.1855
  At iterate     7  f =       250.58  |proj g|=         17.01
  At iterate     8  f =       248.69  |proj g|=        8.4311
  At iterate     9  f =       248.04  |proj g|=        1.9377
  At iterate    10  f =       247.99  |proj g|=       0.25653
  At iterate    11  f =       247.98  |proj g|=         0.239
  At iterate    12  f =       247.98  |proj g|=        0.2395
  At iterate    13  f =       247.97  |proj g|=       0.52959
  At iterate    14  f =       247.95  |proj g|=        1.0385
  At iterate    15  f =       247.91  |proj g|=        2.9586
  At iterate    16  f =       247.81  |proj g|=        3.6337
  At iterate    17  f =       246.95  |proj g|=        5.8683
  At iterate    18  f =       244.68  |proj g|=        7.5379
  At iterate    19  f =       244.07  |proj g|=        6.6661
  At iterate    20  f =       243.48  |proj g|=        5.5749
  At iterate    21  f =        243.3  |proj g|=         2.473
  At iterate    22  f =       243.27  |proj g|=       0.17257
  At iterate    23  f =       243.26  |proj g|=      0.081305
  At iterate    24  f =       243.26  |proj g|=      0.062581
  At iterate    25  f =       243.26  |proj g|=      0.029342
  
  iterations 25
  function evaluations 33
  segments explored during Cauchy searches 27
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.0293424
  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 : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -145.7385 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       145.74  |proj g|=       6.8942
  At iterate     1  f =       99.548  |proj g|=        2.9145
  At iterate     2  f =       64.806  |proj g|=        7.1404
  At iterate     3  f =       64.161  |proj g|=       0.76633
  At iterate     4  f =       64.051  |proj g|=       0.71551
  At iterate     5  f =       64.029  |proj g|=       0.35344
  At iterate     6  f =       64.028  |proj g|=      0.030719
  At iterate     7  f =       64.028  |proj g|=    0.00064292
  At iterate     8  f =       64.028  |proj g|=    1.2009e-06
  
  iterations 8
  function evaluations 21
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.20087e-06
  final function value 64.028
  
  F = 64.028
  final  value 64.027980 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -145.7385 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       145.74  |proj g|=       6.8942
  At iterate     1  f =       99.548  |proj g|=        2.9145
  At iterate     2  f =       64.806  |proj g|=        7.1404
  At iterate     3  f =       64.161  |proj g|=       0.76633
  At iterate     4  f =       64.051  |proj g|=       0.71551
  At iterate     5  f =       64.029  |proj g|=       0.35344
  At iterate     6  f =       64.028  |proj g|=      0.030719
  At iterate     7  f =       64.028  |proj g|=    0.00064292
  At iterate     8  f =       64.028  |proj g|=    1.2009e-06
  
  iterations 8
  function evaluations 21
  segments explored during Cauchy searches 11
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.20087e-06
  final function value 64.028
  
  F = 64.028
  final  value 64.027980 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -311.7873 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       311.79  |proj g|=       7.3528
  At iterate     1  f =       99.548  |proj g|=        2.9145
  At iterate     2  f =       64.989  |proj g|=       0.93817
  ys=-2.222e+01  -gs= 1.959e+01, BFGS update SKIPPED
  At iterate     3  f =       64.404  |proj g|=       0.83064
  At iterate     4  f =        64.03  |proj g|=       0.43458
  At iterate     5  f =       64.028  |proj g|=       0.19571
  At iterate     6  f =       64.028  |proj g|=      0.005256
  At iterate     7  f =       64.028  |proj g|=    6.1511e-05
  At iterate     8  f =       64.028  |proj g|=    1.9619e-08
  
  iterations 8
  function evaluations 20
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.96191e-08
  final function value 64.028
  
  F = 64.028
  final  value 64.027980 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -311.7873 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       311.79  |proj g|=       7.3528
  At iterate     1  f =       99.548  |proj g|=        2.9145
  At iterate     2  f =       64.989  |proj g|=       0.93817
  ys=-2.222e+01  -gs= 1.959e+01, BFGS update SKIPPED
  At iterate     3  f =       64.404  |proj g|=       0.83064
  At iterate     4  f =        64.03  |proj g|=       0.43458
  At iterate     5  f =       64.028  |proj g|=       0.19571
  At iterate     6  f =       64.028  |proj g|=      0.005256
  At iterate     7  f =       64.028  |proj g|=    6.1511e-05
  At iterate     8  f =       64.028  |proj g|=    1.9619e-08
  
  iterations 8
  function evaluations 20
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 1.96191e-08
  final function value 64.028
  
  F = 64.028
  final  value 64.027980 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -93.78211 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       93.782  |proj g|=       6.6611
  At iterate     1  f =       80.025  |proj g|=        3.2063
  At iterate     2  f =       63.898  |proj g|=        1.9385
  At iterate     3  f =       63.686  |proj g|=        1.9389
  At iterate     4  f =       63.613  |proj g|=        1.9378
  At iterate     5  f =       63.605  |proj g|=       0.64422
  At iterate     6  f =       63.605  |proj g|=       0.62413
  At iterate     7  f =       63.605  |proj g|=       0.62484
  At iterate     8  f =       63.605  |proj g|=       0.62631
  At iterate     9  f =       63.604  |proj g|=       0.62896
  At iterate    10  f =       63.604  |proj g|=       0.63236
  At iterate    11  f =       63.604  |proj g|=       0.63697
  At iterate    12  f =       63.602  |proj g|=       0.64108
  At iterate    13  f =       63.598  |proj g|=       0.63697
  At iterate    14  f =       63.589  |proj g|=       0.99397
  At iterate    15  f =       63.571  |proj g|=        1.5631
  At iterate    16  f =        63.57  |proj g|=        1.5498
  At iterate    17  f =       63.543  |proj g|=        1.7792
  At iterate    18  f =       63.492  |proj g|=       0.28504
  At iterate    19  f =       63.491  |proj g|=       0.26763
  At iterate    20  f =       63.491  |proj g|=       0.26912
  At iterate    21  f =       63.483  |proj g|=       0.24303
  At iterate    22  f =       63.483  |proj g|=        1.9368
  At iterate    23  f =       63.458  |proj g|=        0.1673
  At iterate    24  f =       63.457  |proj g|=       0.26786
  At iterate    25  f =       63.454  |proj g|=      0.019495
  At iterate    26  f =       63.454  |proj g|=      0.012584
  At iterate    27  f =       63.454  |proj g|=      0.018948
  At iterate    28  f =       63.454  |proj g|=      0.011845
  At iterate    29  f =       63.454  |proj g|=      0.011403
  At iterate    30  f =       63.454  |proj g|=     0.0084383
  At iterate    31  f =       63.454  |proj g|=       0.11221
  At iterate    32  f =       63.454  |proj g|=      0.055405
  At iterate    33  f =       63.454  |proj g|=      0.020343
  At iterate    34  f =       63.454  |proj g|=    1.8655e-05
  
  iterations 34
  function evaluations 46
  segments explored during Cauchy searches 37
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 1.86547e-05
  final function value 63.4542
  
  F = 63.4542
  final  value 63.454173 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.737123e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.943579 
    - variance bounds :  0.0759119 7.737123 
    - best initial criterion value(s) :  -345.1696 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       345.17  |proj g|=       7.0477
  At iterate     1  f =       99.548  |proj g|=        2.9145
  At iterate     2  f =       65.239  |proj g|=       0.97695
  ys=-2.493e+01  -gs= 1.948e+01, BFGS update SKIPPED
  At iterate     3  f =       64.553  |proj g|=       0.86165
  At iterate     4  f =       64.036  |proj g|=       0.70231
  At iterate     5  f =       64.031  |proj g|=       0.48157
  At iterate     6  f =       64.028  |proj g|=      0.024773
  At iterate     7  f =       64.028  |proj g|=    0.00069955
  At iterate     8  f =       64.028  |proj g|=    1.0533e-06
  
  iterations 8
  function evaluations 24
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 1.05326e-06
  final function value 64.028
  
  F = 64.028
  final  value 64.027980 
  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) :  -739.8821 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       739.88  |proj g|=       14.162
  At iterate     1  f =       325.32  |proj g|=       0.36274
  At iterate     2  f =       318.37  |proj g|=       0.10176
  At iterate     3  f =       318.22  |proj g|=     0.0099363
  At iterate     4  f =       318.22  |proj g|=     0.0017052
  At iterate     5  f =       318.22  |proj g|=    2.3376e-05
  At iterate     6  f =       318.22  |proj g|=    5.4065e-08
  
  iterations 6
  function evaluations 21
  segments explored during Cauchy searches 8
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 5.40652e-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) :  -252.4233 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       252.42  |proj g|=        4.557
  At iterate     1  f =       248.35  |proj g|=        1.8638
  At iterate     2  f =       247.44  |proj g|=        1.8057
  At iterate     3  f =       246.32  |proj g|=        1.7316
  At iterate     4  f =       245.28  |proj g|=        1.5762
  At iterate     5  f =       245.22  |proj g|=       0.22515
  At iterate     6  f =       245.22  |proj g|=        0.2268
  At iterate     7  f =       245.22  |proj g|=       0.30687
  At iterate     8  f =       245.22  |proj g|=       0.62312
  At iterate     9  f =       245.22  |proj g|=        1.3794
  At iterate    10  f =       245.22  |proj g|=        1.7133
  At iterate    11  f =       245.21  |proj g|=        1.7134
  At iterate    12  f =       245.21  |proj g|=        1.7135
  At iterate    13  f =       245.19  |proj g|=        1.8593
  At iterate    14  f =       245.15  |proj g|=        2.9483
  At iterate    15  f =       245.06  |proj g|=        4.5269
  At iterate    16  f =       245.04  |proj g|=        5.5539
  At iterate    17  f =       244.84  |proj g|=        7.0866
  At iterate    18  f =        244.1  |proj g|=        9.1358
  At iterate    19  f =        243.6  |proj g|=        5.0163
  At iterate    20  f =       243.27  |proj g|=       0.67773
  At iterate    21  f =       243.26  |proj g|=       0.99123
  At iterate    22  f =       243.26  |proj g|=      0.087663
  At iterate    23  f =       243.26  |proj g|=      0.010182
  At iterate    24  f =       243.26  |proj g|=    0.00020481
  
  iterations 24
  function evaluations 30
  segments explored during Cauchy searches 25
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.000204809
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/16189871/R-release/843/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-03-30 01:25:20 MST"
[1] "2025-03-30 01:25:20 MST"
Installing package into '/tmp/th798/16189871/R-release/843/library'
(as 'lib' is unspecified)
* installing *source* package 'data.table' ...
** 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/th798/16189871/R-release/843/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] "2025-03-30 01:25:40 MST"
* using log directory '/tmp/th798/16189871/R-release/843/mlr3learners.Rcheck'
* using R version 4.4.3 (2025-02-28)
* 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 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 20.694248 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.519302 
  converged
  # weights:  3 (2 variable)
  initial  value 20.794415 
  final  value 19.519302 
  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 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  6 (5 variable)
  initial  value 10.311470 
  iter  10 value 7.309593
  final  value 7.309150 
  converged
  # weights:  6 (5 variable)
  initial  value 10.311470 
  iter  10 value 7.309593
  final  value 7.309150 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  6 (5 variable)
  initial  value 20.794415 
  iter  10 value 17.150681
  iter  10 value 17.150681
  iter  10 value 17.150681
  final  value 17.150681 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 31.732830 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.350660 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  final  value 32.350660 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.481702
  iter  10 value 32.481702
  final  value 32.481702 
  converged
  # weights:  9 (4 variable)
  initial  value 32.958369 
  iter  10 value 32.481702
  iter  10 value 32.481702
  final  value 32.481702 
  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 30.789517
  final  value 30.785664 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.789517
  final  value 30.785664 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.789517
  final  value 30.785664 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.789517
  final  value 30.785664 
  converged
  # weights:  18 (10 variable)
  initial  value 17.942661 
  iter  10 value 16.580849
  final  value 16.572018 
  converged
  # weights:  18 (10 variable)
  initial  value 17.942661 
  iter  10 value 16.580849
  final  value 16.572018 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.789517
  final  value 30.785664 
  converged
  # weights:  18 (10 variable)
  initial  value 32.958369 
  iter  10 value 30.789517
  final  value 30.785664 
  converged
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  4 (3 variable)
  initial  value 138.629436 
  iter  10 value 0.097335
  iter  20 value 0.008928
  iter  30 value 0.003213
  iter  40 value 0.002454
  iter  50 value 0.002153
  iter  60 value 0.001766
  iter  70 value 0.001529
  iter  80 value 0.001283
  iter  90 value 0.001169
  iter 100 value 0.000964
  final  value 0.000964 
  stopped after 100 iterations
  # weights:  18 (10 variable)
  initial  value 164.791843 
  iter  10 value 16.177348
  iter  20 value 7.111438
  iter  30 value 6.182999
  iter  40 value 5.984028
  iter  50 value 5.961278
  iter  60 value 5.954900
  iter  70 value 5.951851
  iter  80 value 5.950343
  iter  90 value 5.949904
  iter 100 value 5.949867
  final  value 5.949867 
  stopped after 100 iterations
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -32557.99 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        32558  |proj g|=       6.7446
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       65.457  |proj g|=         1.011
  ys=-2.671e+01  -gs= 1.939e+01, BFGS update SKIPPED
  At iterate     3  f =       64.729  |proj g|=         0.896
  At iterate     4  f =       64.056  |proj g|=       0.71611
  At iterate     5  f =       64.045  |proj g|=       0.91956
  At iterate     6  f =       64.036  |proj g|=       0.07089
  At iterate     7  f =       64.036  |proj g|=     0.0037185
  At iterate     8  f =       64.036  |proj g|=    1.6086e-05
  At iterate     9  f =       64.036  |proj g|=    3.6306e-09
  
  iterations 9
  function evaluations 29
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 3.63061e-09
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -32557.99 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        32558  |proj g|=       6.7446
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       65.457  |proj g|=         1.011
  ys=-2.671e+01  -gs= 1.939e+01, BFGS update SKIPPED
  At iterate     3  f =       64.729  |proj g|=         0.896
  At iterate     4  f =       64.056  |proj g|=       0.71611
  At iterate     5  f =       64.045  |proj g|=       0.91956
  At iterate     6  f =       64.036  |proj g|=       0.07089
  At iterate     7  f =       64.036  |proj g|=     0.0037185
  At iterate     8  f =       64.036  |proj g|=    1.6086e-05
  At iterate     9  f =       64.036  |proj g|=    3.6306e-09
  
  iterations 9
  function evaluations 29
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 3.63061e-09
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -209091.3 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   2.0909e+05  |proj g|=       6.7057
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       64.411  |proj g|=        7.0987
  At iterate     3  f =       64.065  |proj g|=       0.72281
  At iterate     4  f =       64.039  |proj g|=       0.46146
  At iterate     5  f =       64.036  |proj g|=       0.04862
  At iterate     6  f =       64.036  |proj g|=     0.0014057
  At iterate     7  f =       64.036  |proj g|=    4.1323e-06
  
  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 4.13227e-06
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -209091.3 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=   2.0909e+05  |proj g|=       6.7057
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       64.411  |proj g|=        7.0987
  At iterate     3  f =       64.065  |proj g|=       0.72281
  At iterate     4  f =       64.039  |proj g|=       0.46146
  At iterate     5  f =       64.036  |proj g|=       0.04862
  At iterate     6  f =       64.036  |proj g|=     0.0014057
  At iterate     7  f =       64.036  |proj g|=    4.1323e-06
  
  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 4.13227e-06
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -458.585 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       458.59  |proj g|=       6.6781
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       65.526  |proj g|=        1.0208
  ys=-2.721e+01  -gs= 1.936e+01, BFGS update SKIPPED
  At iterate     3  f =       65.031  |proj g|=       0.94662
  At iterate     4  f =       64.075  |proj g|=       0.72949
  At iterate     5  f =       64.036  |proj g|=       0.18703
  At iterate     6  f =       64.036  |proj g|=      0.022781
  At iterate     7  f =       64.036  |proj g|=     0.0002618
  At iterate     8  f =       64.036  |proj g|=    3.6127e-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 3.61271e-07
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 7.739599e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.829082 
    - variance bounds :  0.07316141 7.739599 
    - best initial criterion value(s) :  -20540.56 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        20541  |proj g|=       6.9524
  At iterate     1  f =       99.556  |proj g|=        2.9136
  At iterate     2  f =       65.414  |proj g|=        1.0048
  ys=-2.638e+01  -gs= 1.941e+01, BFGS update SKIPPED
  At iterate     3  f =       64.888  |proj g|=        0.9233
  At iterate     4  f =       64.066  |proj g|=       0.72363
  At iterate     5  f =       64.055  |proj g|=        1.3563
  At iterate     6  f =       64.036  |proj g|=       0.12635
  At iterate     7  f =       64.036  |proj g|=     0.0095228
  At iterate     8  f =       64.036  |proj g|=    7.3768e-05
  At iterate     9  f =       64.036  |proj g|=    4.2656e-08
  
  iterations 9
  function evaluations 30
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 4.26559e-08
  final function value 64.036
  
  F = 64.036
  final  value 64.035979 
  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) :  -602.1341 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       602.13  |proj g|=       15.211
  At iterate     1  f =       319.05  |proj g|=       0.20874
  At iterate     2  f =       318.63  |proj g|=       0.15795
  At iterate     3  f =       318.36  |proj g|=       0.11835
  At iterate     4  f =       318.23  |proj g|=      0.028156
  At iterate     5  f =       318.22  |proj g|=     0.0039526
  At iterate     6  f =       318.22  |proj g|=    0.00016016
  At iterate     7  f =       318.22  |proj g|=     8.667e-07
  
  iterations 7
  function evaluations 11
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 8.66703e-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) :  -265.3783 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       265.38  |proj g|=       3.4795
  At iterate     1  f =       263.07  |proj g|=        1.8056
  At iterate     2  f =       261.77  |proj g|=        2.5658
  At iterate     3  f =       256.47  |proj g|=        7.9732
  At iterate     4  f =       256.04  |proj g|=        12.386
  At iterate     5  f =        251.2  |proj g|=         3.716
  At iterate     6  f =       250.66  |proj g|=        1.6769
  At iterate     7  f =       250.64  |proj g|=       0.73078
  At iterate     8  f =       250.64  |proj g|=       0.22161
  At iterate     9  f =       250.64  |proj g|=       0.22098
  At iterate    10  f =       250.63  |proj g|=       0.21759
  At iterate    11  f =       250.62  |proj g|=       0.21455
  At iterate    12  f =        250.6  |proj g|=       0.38079
  At iterate    13  f =       250.53  |proj g|=       0.58929
  At iterate    14  f =       250.34  |proj g|=       0.62872
  At iterate    15  f =       249.88  |proj g|=       0.20538
  At iterate    16  f =       248.94  |proj g|=        3.0182
  At iterate    17  f =       247.76  |proj g|=        7.9867
  At iterate    18  f =       247.44  |proj g|=        13.607
  At iterate    19  f =       247.05  |proj g|=        14.601
  At iterate    20  f =       243.72  |proj g|=        1.7429
  At iterate    21  f =       243.49  |proj g|=       0.60214
  At iterate    22  f =       243.32  |proj g|=       0.17842
  At iterate    23  f =       243.27  |proj g|=        1.7301
  At iterate    24  f =       243.26  |proj g|=         0.034
  At iterate    25  f =       243.26  |proj g|=      0.044098
  At iterate    26  f =       243.26  |proj g|=      0.080905
  At iterate    27  f =       243.26  |proj g|=    0.00083096
  At iterate    28  f =       243.26  |proj g|=    9.4637e-05
  
  iterations 28
  function evaluations 40
  segments explored during Cauchy searches 30
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 9.46371e-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) :  -316.7978 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=        316.8  |proj g|=       3.1965
  At iterate     1  f =        256.3  |proj g|=        1.7787
  At iterate     2  f =       251.47  |proj g|=        1.9752
  At iterate     3  f =       249.21  |proj g|=        4.5553
  At iterate     4  f =       248.04  |proj g|=       0.94521
  At iterate     5  f =       248.04  |proj g|=       0.23737
  At iterate     6  f =       248.04  |proj g|=       0.23788
  At iterate     7  f =       248.04  |proj g|=       0.93772
  At iterate     8  f =       248.04  |proj g|=        1.7025
  At iterate     9  f =       248.04  |proj g|=        1.7029
  At iterate    10  f =       248.03  |proj g|=        1.7035
  At iterate    11  f =       248.02  |proj g|=        1.7046
  At iterate    12  f =       247.99  |proj g|=        1.7063
  At iterate    13  f =       247.91  |proj g|=        2.5518
  At iterate    14  f =       247.69  |proj g|=        4.6718
  At iterate    15  f =       247.14  |proj g|=        8.6703
  At iterate    16  f =       246.07  |proj g|=        15.797
  At iterate    17  f =       245.16  |proj g|=        16.055
  At iterate    18  f =       244.87  |proj g|=        7.2817
  At iterate    19  f =       244.64  |proj g|=        10.048
  At iterate    20  f =       244.49  |proj g|=        11.047
  At iterate    21  f =       244.04  |proj g|=        10.091
  At iterate    22  f =       243.39  |proj g|=        3.6179
  At iterate    23  f =       243.35  |proj g|=        1.9252
  At iterate    24  f =       243.26  |proj g|=       0.15282
  At iterate    25  f =       243.26  |proj g|=      0.063494
  At iterate    26  f =       243.26  |proj g|=     0.0019926
  At iterate    27  f =       243.26  |proj g|=    3.3056e-06
  
  iterations 27
  function evaluations 32
  segments explored during Cauchy searches 29
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 3.30561e-06
  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) :  -268.264 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       268.26  |proj g|=       3.7425
  At iterate     1  f =       265.68  |proj g|=        1.8046
  At iterate     2  f =       265.35  |proj g|=        1.8013
  At iterate     3  f =       259.22  |proj g|=        5.5748
  At iterate     4  f =        259.1  |proj g|=         6.428
  At iterate     5  f =       253.84  |proj g|=        6.5271
  At iterate     6  f =       253.18  |proj g|=        1.8598
  At iterate     7  f =       253.04  |proj g|=        1.6067
  At iterate     8  f =       253.04  |proj g|=       0.20003
  At iterate     9  f =       253.04  |proj g|=       0.19977
  At iterate    10  f =       253.04  |proj g|=       0.19894
  At iterate    11  f =       253.04  |proj g|=       0.19816
  At iterate    12  f =       253.04  |proj g|=       0.19692
  At iterate    13  f =       253.04  |proj g|=       0.23978
  At iterate    14  f =       253.03  |proj g|=       0.38358
  At iterate    15  f =          253  |proj g|=       0.52866
  At iterate    16  f =       252.93  |proj g|=       0.48101
  At iterate    17  f =       252.78  |proj g|=       0.37105
  At iterate    18  f =        252.5  |proj g|=        3.1195
  At iterate    19  f =        251.7  |proj g|=        7.6701
  At iterate    20  f =       249.51  |proj g|=        17.248
  At iterate    21  f =       247.92  |proj g|=        22.194
  At iterate    22  f =       247.25  |proj g|=        23.867
  At iterate    23  f =       246.55  |proj g|=        20.309
  At iterate    24  f =       244.23  |proj g|=        11.643
  At iterate    25  f =       243.43  |proj g|=        1.3771
  At iterate    26  f =       243.28  |proj g|=       0.18629
  At iterate    27  f =       243.27  |proj g|=        1.7284
  At iterate    28  f =       243.26  |proj g|=       0.41295
  At iterate    29  f =       243.26  |proj g|=      0.025676
  At iterate    30  f =       243.26  |proj g|=      0.044322
  At iterate    31  f =       243.26  |proj g|=     0.0055313
  At iterate    32  f =       243.26  |proj g|=      0.001114
  
  iterations 32
  function evaluations 42
  segments explored during Cauchy searches 34
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00111397
  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 : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -9376.76 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       9376.8  |proj g|=       8.8312
  At iterate     1  f =       104.62  |proj g|=        2.3796
  At iterate     2  f =       69.097  |proj g|=       0.13017
  At iterate     3  f =       69.097  |proj g|=     0.0039023
  At iterate     4  f =       69.097  |proj g|=    3.8214e-05
  At iterate     5  f =       69.097  |proj g|=    1.1083e-08
  
  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 1.10825e-08
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -9376.76 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       9376.8  |proj g|=       8.8312
  At iterate     1  f =       104.62  |proj g|=        2.3796
  At iterate     2  f =       69.097  |proj g|=       0.13017
  At iterate     3  f =       69.097  |proj g|=     0.0039023
  At iterate     4  f =       69.097  |proj g|=    3.8214e-05
  At iterate     5  f =       69.097  |proj g|=    1.1083e-08
  
  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 1.10825e-08
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -3402.244 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       3402.2  |proj g|=       8.2651
  At iterate     1  f =       104.62  |proj g|=        2.3796
  At iterate     2  f =       69.359  |proj g|=       0.98554
  ys=-6.903e+00  -gs= 1.999e+01, BFGS update SKIPPED
  At iterate     3  f =       69.281  |proj g|=       0.95929
  At iterate     4  f =       69.129  |proj g|=        1.4707
  At iterate     5  f =       69.099  |proj g|=       0.35276
  At iterate     6  f =       69.097  |proj g|=      0.035018
  At iterate     7  f =       69.097  |proj g|=    0.00095213
  At iterate     8  f =       69.097  |proj g|=    2.4849e-06
  
  iterations 8
  function evaluations 26
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.48494e-06
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -3402.244 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       3402.2  |proj g|=       8.2651
  At iterate     1  f =       104.62  |proj g|=        2.3796
  At iterate     2  f =       69.359  |proj g|=       0.98554
  ys=-6.903e+00  -gs= 1.999e+01, BFGS update SKIPPED
  At iterate     3  f =       69.281  |proj g|=       0.95929
  At iterate     4  f =       69.129  |proj g|=        1.4707
  At iterate     5  f =       69.099  |proj g|=       0.35276
  At iterate     6  f =       69.097  |proj g|=      0.035018
  At iterate     7  f =       69.097  |proj g|=    0.00095213
  At iterate     8  f =       69.097  |proj g|=    2.4849e-06
  
  iterations 8
  function evaluations 26
  segments explored during Cauchy searches 11
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 2
  norm of the final projected gradient 2.48494e-06
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -1338980 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=    1.339e+06  |proj g|=       8.6493
  At iterate     1  f =       104.62  |proj g|=        2.3796
  At iterate     2  f =       70.399  |proj g|=        1.2144
  ys=-2.575e+01  -gs= 1.944e+01, BFGS update SKIPPED
  At iterate     3  f =       69.866  |proj g|=        1.1112
  At iterate     4  f =        69.12  |proj g|=       0.87804
  At iterate     5  f =       69.109  |proj g|=       0.88887
  At iterate     6  f =       69.097  |proj g|=      0.073892
  At iterate     7  f =       69.097  |proj g|=     0.0045401
  At iterate     8  f =       69.097  |proj g|=    2.5107e-05
  At iterate     9  f =       69.097  |proj g|=    8.4721e-09
  
  iterations 9
  function evaluations 34
  segments explored during Cauchy searches 12
  BFGS updates skipped 1
  active bounds at final generalized Cauchy point 3
  norm of the final projected gradient 8.47206e-09
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  converged
  
  optimisation start
  ------------------
  * estimation method   : MLE 
  * optimisation method : BFGS 
  * analytical gradient : used
  * trend model : ~1
  * covariance model : 
    - type :  matern5_2 
    - nugget : 9.476219e-09 
    - parameters lower bounds :  1e-10 1e-10 1e-10 
    - parameters upper bounds :  4 2 1.992084 
    - variance bounds :  0.09174808 9.476219 
    - best initial criterion value(s) :  -76.53642 
  
  N = 4, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       76.536  |proj g|=       8.4714
  At iterate     1  f =       72.287  |proj g|=        1.6886
  At iterate     2  f =       69.274  |proj g|=       0.95683
  At iterate     3  f =       69.098  |proj g|=        0.2417
  At iterate     4  f =       69.097  |proj g|=      0.064623
  At iterate     5  f =       69.097  |proj g|=     0.0011417
  At iterate     6  f =       69.097  |proj g|=    5.5152e-06
  
  iterations 6
  function evaluations 10
  segments explored during Cauchy searches 9
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 1
  norm of the final projected gradient 5.51525e-06
  final function value 69.0969
  
  F = 69.0969
  final  value 69.096867 
  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) :  -252.9109 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       252.91  |proj g|=       6.5566
  At iterate     1  f =       250.66  |proj g|=        1.8345
  At iterate     2  f =       250.58  |proj g|=         1.823
  At iterate     3  f =       250.28  |proj g|=       0.22257
  At iterate     4  f =       250.28  |proj g|=       0.22453
  At iterate     5  f =       250.28  |proj g|=        0.3093
  At iterate     6  f =       250.28  |proj g|=       0.87748
  At iterate     7  f =       250.28  |proj g|=        1.6946
  At iterate     8  f =       250.28  |proj g|=        1.6948
  At iterate     9  f =       250.27  |proj g|=        1.6953
  At iterate    10  f =       250.27  |proj g|=        1.6959
  At iterate    11  f =       250.25  |proj g|=        1.6967
  At iterate    12  f =       250.21  |proj g|=        2.7325
  At iterate    13  f =       250.13  |proj g|=        4.3533
  At iterate    14  f =       249.96  |proj g|=        5.2926
  At iterate    15  f =        249.7  |proj g|=        5.9222
  At iterate    16  f =       249.42  |proj g|=        5.9231
  At iterate    17  f =       248.61  |proj g|=         5.762
  At iterate    18  f =       247.72  |proj g|=        3.2643
  At iterate    19  f =       246.41  |proj g|=        7.0078
  At iterate    20  f =          244  |proj g|=        9.1571
  At iterate    21  f =       243.67  |proj g|=        7.2571
  At iterate    22  f =        243.3  |proj g|=        1.7325
  At iterate    23  f =       243.27  |proj g|=       0.15421
  At iterate    24  f =       243.26  |proj g|=      0.095985
  At iterate    25  f =       243.26  |proj g|=      0.046297
  At iterate    26  f =       243.26  |proj g|=    0.00075281
  At iterate    27  f =       243.26  |proj g|=    2.5039e-05
  
  iterations 27
  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 2.50386e-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) :  -314.1912 
  
  N = 3, M = 5 machine precision = 2.22045e-16
  At X0, 0 variables are exactly at the bounds
  At iterate     0  f=       314.19  |proj g|=       44.171
  At iterate     1  f =       313.71  |proj g|=        44.167
  At iterate     2  f =       312.23  |proj g|=        1.6032
  At iterate     3  f =        307.1  |proj g|=        1.4273
  At iterate     4  f =       285.45  |proj g|=        42.537
  At iterate     5  f =       285.18  |proj g|=        44.066
  At iterate     6  f =       284.16  |proj g|=        44.044
  At iterate     7  f =       283.57  |proj g|=        44.041
  At iterate     8  f =       280.75  |proj g|=        40.837
  At iterate     9  f =       271.83  |proj g|=        43.764
  At iterate    10  f =       263.73  |proj g|=        39.489
  At iterate    11  f =       257.73  |proj g|=        14.955
  At iterate    12  f =       250.54  |proj g|=        16.192
  At iterate    13  f =       247.97  |proj g|=        9.5426
  At iterate    14  f =       247.13  |proj g|=       0.93041
  At iterate    15  f =       247.11  |proj g|=        1.5592
  At iterate    16  f =       247.11  |proj g|=       0.24109
  At iterate    17  f =       247.11  |proj g|=       0.24094
  At iterate    18  f =       247.11  |proj g|=       0.24027
  At iterate    19  f =       247.11  |proj g|=       0.34127
  At iterate    20  f =       247.11  |proj g|=       0.69054
  At iterate    21  f =        247.1  |proj g|=        1.2648
  At iterate    22  f =       247.07  |proj g|=        1.6365
  At iterate    23  f =       247.06  |proj g|=         1.637
  At iterate    24  f =       246.99  |proj g|=        1.6569
  At iterate    25  f =       246.68  |proj g|=        1.6833
  At iterate    26  f =       245.58  |proj g|=        1.6899
  At iterate    27  f =       244.59  |proj g|=        1.5713
  At iterate    28  f =       243.31  |proj g|=        1.7308
  At iterate    29  f =       243.29  |proj g|=        1.3948
  At iterate    30  f =       243.27  |proj g|=        0.6741
  At iterate    31  f =       243.26  |proj g|=       0.12836
  At iterate    32  f =       243.26  |proj g|=     0.0089258
  At iterate    33  f =       243.26  |proj g|=     0.0010326
  
  iterations 33
  function evaluations 44
  segments explored during Cauchy searches 35
  BFGS updates skipped 0
  active bounds at final generalized Cauchy point 0
  norm of the final projected gradient 0.00103256
  final function value 243.264
  
  F = 243.264
  final  value 243.264413 
  converged
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  
  == Skipped tests (4) ===========================================================
  * On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
    'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
  
  == Failed tests ================================================================
  -- Failure ('test_classif_ranger.R:8:3'): autotest -----------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'classif.ranger:response' on task 'missings_binary' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  -- Failure ('test_regr_ranger.R:7:3'): autotest --------------------------------
  `result` is not TRUE
  
  `actual` is a list
  `expected` is a logical vector (TRUE)
  [train()] learner 'regr.ranger:response' on task 'missings' failed: Error : Missing data in columns: character, factor, integer, logical, numeric, ordered.
  
  
  [ FAIL 2 | WARN 227 | SKIP 4 | PASS 547 ]
  Error: Test failures
  Execution halted
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR
See
  '/tmp/th798/16189871/R-release/843/mlr3learners.Rcheck/00check.log'
for details.

[1] "2025-03-30 01:27:24 MST"
> system(paste(c("diff -u", Rcheck.list), collapse=" "))
--- R_version_4.4.3_2025-02-28/release_1.17.0.Rcheck/00check.log	2025-03-30 01:25:20.015397967 -0700
+++ R_version_4.4.3_2025-02-28/master_1.17.99.2cb03162a21328cc5f68a8c3b0e554f5edfcb5b9.Rcheck/00check.log	2025-03-30 01:27:24.647761162 -0700
@@ -68,139 +68,155 @@
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.880405 
+  final  value 20.694248 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 19.880405 
+  final  value 20.694248 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.175741 
+  final  value 19.519302 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.175741 
+  final  value 19.519302 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 19.095425 
   converged
   # weights:  3 (2 variable)
   initial  value 20.794415 
-  final  value 20.727699 
+  final  value 19.095425 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.332863 
-  iter  10 value 7.325056
-  final  value 7.325044 
+  initial  value 10.311470 
+  iter  10 value 7.309593
+  final  value 7.309150 
   converged
   # weights:  6 (5 variable)
-  initial  value 9.332863 
-  iter  10 value 7.325056
-  final  value 7.325044 
+  initial  value 10.311470 
+  iter  10 value 7.309593
+  final  value 7.309150 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  6 (5 variable)
   initial  value 20.794415 
-  final  value 18.190606 
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  iter  10 value 17.150681
+  final  value 17.150681 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  final  value 31.732830 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.555658 
+  final  value 31.732830 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.807897 
+  final  value 32.350660 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 32.807897 
+  final  value 32.350660 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 31.596629
-  iter  10 value 31.596629
-  final  value 31.596629 
+  iter  10 value 32.481702
+  iter  10 value 32.481702
+  final  value 32.481702 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  iter  10 value 31.596629
-  iter  10 value 31.596629
-  final  value 31.596629 
+  iter  10 value 32.481702
+  iter  10 value 32.481702
+  final  value 32.481702 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.312711 
+  final  value 32.555658 
   converged
   # weights:  9 (4 variable)
   initial  value 32.958369 
-  final  value 31.312711 
+  final  value 32.555658 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  18 (10 variable)
-  initial  value 15.435041 
-  iter  10 value 12.723653
-  iter  20 value 12.700980
-  final  value 12.700979 
+  initial  value 17.942661 
+  iter  10 value 16.580849
+  final  value 16.572018 
   converged
   # weights:  18 (10 variable)
-  initial  value 15.435041 
-  iter  10 value 12.723653
-  iter  20 value 12.700980
-  final  value 12.700979 
+  initial  value 17.942661 
+  iter  10 value 16.580849
+  final  value 16.572018 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  18 (10 variable)
   initial  value 32.958369 
-  iter  10 value 29.311367
-  final  value 29.310710 
+  iter  10 value 30.789517
+  final  value 30.785664 
   converged
   # weights:  4 (3 variable)
   initial  value 138.629436 
@@ -309,34 +325,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -1795.619 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -32557.99 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1795.6  |proj g|=        7.433
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       64.882  |proj g|=       0.78137
-  At iterate     3  f =       64.768  |proj g|=       0.28144
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       64.767  |proj g|=      0.042776
-  At iterate     5  f =       64.767  |proj g|=    0.00076652
-  At iterate     6  f =       64.767  |proj g|=    2.0419e-06
+  At iterate     0  f=        32558  |proj g|=       6.7446
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       65.457  |proj g|=         1.011
+  ys=-2.671e+01  -gs= 1.939e+01, BFGS update SKIPPED
+  At iterate     3  f =       64.729  |proj g|=         0.896
+  At iterate     4  f =       64.056  |proj g|=       0.71611
+  At iterate     5  f =       64.045  |proj g|=       0.91956
+  At iterate     6  f =       64.036  |proj g|=       0.07089
+  At iterate     7  f =       64.036  |proj g|=     0.0037185
+  At iterate     8  f =       64.036  |proj g|=    1.6086e-05
+  At iterate     9  f =       64.036  |proj g|=    3.6306e-09
   
-  iterations 6
-  function evaluations 22
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  iterations 9
+  function evaluations 29
+  segments explored during Cauchy searches 12
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.04188e-06
-  final function value 64.7667
+  norm of the final projected gradient 3.63061e-09
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -347,34 +365,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -1795.619 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -32557.99 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1795.6  |proj g|=        7.433
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       64.882  |proj g|=       0.78137
-  At iterate     3  f =       64.768  |proj g|=       0.28144
-  Nonpositive definiteness in Cholesky factorization in formk;
-     refresh the lbfgs memory and restart the iteration.
-  At iterate     4  f =       64.767  |proj g|=      0.042776
-  At iterate     5  f =       64.767  |proj g|=    0.00076652
-  At iterate     6  f =       64.767  |proj g|=    2.0419e-06
+  At iterate     0  f=        32558  |proj g|=       6.7446
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       65.457  |proj g|=         1.011
+  ys=-2.671e+01  -gs= 1.939e+01, BFGS update SKIPPED
+  At iterate     3  f =       64.729  |proj g|=         0.896
+  At iterate     4  f =       64.056  |proj g|=       0.71611
+  At iterate     5  f =       64.045  |proj g|=       0.91956
+  At iterate     6  f =       64.036  |proj g|=       0.07089
+  At iterate     7  f =       64.036  |proj g|=     0.0037185
+  At iterate     8  f =       64.036  |proj g|=    1.6086e-05
+  At iterate     9  f =       64.036  |proj g|=    3.6306e-09
   
-  iterations 6
-  function evaluations 22
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 0
+  iterations 9
+  function evaluations 29
+  segments explored during Cauchy searches 12
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 2.04188e-06
-  final function value 64.7667
+  norm of the final projected gradient 3.63061e-09
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -385,35 +405,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -303783.6 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -209091.3 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   3.0378e+05  |proj g|=        7.573
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       66.255  |proj g|=        1.0465
-  ys=-2.957e+01  -gs= 1.961e+01, BFGS update SKIPPED
-  At iterate     3  f =       65.659  |proj g|=       0.95325
-  At iterate     4  f =       64.799  |proj g|=       0.74266
-  At iterate     5  f =       64.767  |proj g|=       0.13937
-  At iterate     6  f =       64.767  |proj g|=      0.015341
-  At iterate     7  f =       64.767  |proj g|=    0.00013489
-  At iterate     8  f =       64.767  |proj g|=    1.2914e-07
+  At iterate     0  f=   2.0909e+05  |proj g|=       6.7057
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       64.411  |proj g|=        7.0987
+  At iterate     3  f =       64.065  |proj g|=       0.72281
+  At iterate     4  f =       64.039  |proj g|=       0.46146
+  At iterate     5  f =       64.036  |proj g|=       0.04862
+  At iterate     6  f =       64.036  |proj g|=     0.0014057
+  At iterate     7  f =       64.036  |proj g|=    4.1323e-06
   
-  iterations 8
-  function evaluations 34
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.29142e-07
-  final function value 64.7667
+  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 4.13227e-06
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -424,35 +442,33 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -303783.6 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -209091.3 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=   3.0378e+05  |proj g|=        7.573
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       66.255  |proj g|=        1.0465
-  ys=-2.957e+01  -gs= 1.961e+01, BFGS update SKIPPED
-  At iterate     3  f =       65.659  |proj g|=       0.95325
-  At iterate     4  f =       64.799  |proj g|=       0.74266
-  At iterate     5  f =       64.767  |proj g|=       0.13937
-  At iterate     6  f =       64.767  |proj g|=      0.015341
-  At iterate     7  f =       64.767  |proj g|=    0.00013489
-  At iterate     8  f =       64.767  |proj g|=    1.2914e-07
+  At iterate     0  f=   2.0909e+05  |proj g|=       6.7057
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       64.411  |proj g|=        7.0987
+  At iterate     3  f =       64.065  |proj g|=       0.72281
+  At iterate     4  f =       64.039  |proj g|=       0.46146
+  At iterate     5  f =       64.036  |proj g|=       0.04862
+  At iterate     6  f =       64.036  |proj g|=     0.0014057
+  At iterate     7  f =       64.036  |proj g|=    4.1323e-06
   
-  iterations 8
-  function evaluations 34
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.29142e-07
-  final function value 64.7667
+  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 4.13227e-06
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -463,32 +479,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -1366.86 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -458.585 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1366.9  |proj g|=       7.8262
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       64.884  |proj g|=        3.5269
-  At iterate     3  f =       64.768  |proj g|=       0.33533
-  At iterate     4  f =       64.767  |proj g|=      0.059578
-  At iterate     5  f =       64.767  |proj g|=      0.001288
-  At iterate     6  f =       64.767  |proj g|=    4.8164e-06
+  At iterate     0  f=       458.59  |proj g|=       6.6781
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       65.526  |proj g|=        1.0208
+  ys=-2.721e+01  -gs= 1.936e+01, BFGS update SKIPPED
+  At iterate     3  f =       65.031  |proj g|=       0.94662
+  At iterate     4  f =       64.075  |proj g|=       0.72949
+  At iterate     5  f =       64.036  |proj g|=       0.18703
+  At iterate     6  f =       64.036  |proj g|=      0.022781
+  At iterate     7  f =       64.036  |proj g|=     0.0002618
+  At iterate     8  f =       64.036  |proj g|=    3.6127e-07
   
-  iterations 6
-  function evaluations 20
-  segments explored during Cauchy searches 9
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.81639e-06
-  final function value 64.7667
+  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 3.61271e-07
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -499,35 +518,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.96916e-09 
+    - nugget : 7.739599e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.899998 
-    - variance bounds :  0.0796916 8.353215 
-    - best initial criterion value(s) :  -294.204 
+    - parameters upper bounds :  4 2 1.829082 
+    - variance bounds :  0.07316141 7.739599 
+    - best initial criterion value(s) :  -20540.56 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=        294.2  |proj g|=       7.8703
-  At iterate     1  f =       101.35  |proj g|=         2.713
-  At iterate     2  f =       66.289  |proj g|=        7.7917
-  At iterate     3  f =       65.226  |proj g|=       0.87232
-  At iterate     4  f =       64.903  |proj g|=       0.78902
-  At iterate     5  f =       64.814  |proj g|=         2.125
-  At iterate     6  f =       64.769  |proj g|=       0.42001
-  At iterate     7  f =       64.767  |proj g|=      0.049395
-  At iterate     8  f =       64.767  |proj g|=     0.0013457
-  At iterate     9  f =       64.767  |proj g|=    4.1685e-06
+  At iterate     0  f=        20541  |proj g|=       6.9524
+  At iterate     1  f =       99.556  |proj g|=        2.9136
+  At iterate     2  f =       65.414  |proj g|=        1.0048
+  ys=-2.638e+01  -gs= 1.941e+01, BFGS update SKIPPED
+  At iterate     3  f =       64.888  |proj g|=        0.9233
+  At iterate     4  f =       64.066  |proj g|=       0.72363
+  At iterate     5  f =       64.055  |proj g|=        1.3563
+  At iterate     6  f =       64.036  |proj g|=       0.12635
+  At iterate     7  f =       64.036  |proj g|=     0.0095228
+  At iterate     8  f =       64.036  |proj g|=    7.3768e-05
+  At iterate     9  f =       64.036  |proj g|=    4.2656e-08
   
   iterations 9
-  function evaluations 25
+  function evaluations 30
   segments explored during Cauchy searches 12
-  BFGS updates skipped 0
+  BFGS updates skipped 1
   active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 4.16848e-06
-  final function value 64.7667
+  norm of the final projected gradient 4.26559e-08
+  final function value 64.036
   
-  F = 64.7667
-  final  value 64.766710 
+  F = 64.036
+  final  value 64.035979 
   converged
   
   optimisation start
@@ -542,23 +562,25 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -1774.329 
+    - best initial criterion value(s) :  -602.1341 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       1774.3  |proj g|=       27.578
-  At iterate     1  f =       334.18  |proj g|=       0.35231
-  At iterate     2  f =       318.23  |proj g|=      0.028405
-  At iterate     3  f =       318.22  |proj g|=      0.001693
-  At iterate     4  f =       318.22  |proj g|=    6.8962e-05
-  At iterate     5  f =       318.22  |proj g|=    1.5925e-07
+  At iterate     0  f=       602.13  |proj g|=       15.211
+  At iterate     1  f =       319.05  |proj g|=       0.20874
+  At iterate     2  f =       318.63  |proj g|=       0.15795
+  At iterate     3  f =       318.36  |proj g|=       0.11835
+  At iterate     4  f =       318.23  |proj g|=      0.028156
+  At iterate     5  f =       318.22  |proj g|=     0.0039526
+  At iterate     6  f =       318.22  |proj g|=    0.00016016
+  At iterate     7  f =       318.22  |proj g|=     8.667e-07
   
-  iterations 5
-  function evaluations 21
-  segments explored during Cauchy searches 7
+  iterations 7
+  function evaluations 11
+  segments explored during Cauchy searches 9
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.59254e-07
+  norm of the final projected gradient 8.66703e-07
   final function value 318.222
   
   F = 318.222
@@ -577,42 +599,46 @@
     - 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) :  -322.0715 
+    - best initial criterion value(s) :  -265.3783 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       322.07  |proj g|=       12.486
-  At iterate     1  f =       253.61  |proj g|=         15.36
-  At iterate     2  f =       251.33  |proj g|=        2.4225
-  At iterate     3  f =       251.25  |proj g|=        1.0735
-  At iterate     4  f =       251.21  |proj g|=        1.6905
-  At iterate     5  f =       251.19  |proj g|=       0.23556
-  At iterate     6  f =       251.19  |proj g|=       0.21681
-  At iterate     7  f =       251.19  |proj g|=       0.21473
-  At iterate     8  f =       251.18  |proj g|=       0.38392
-  At iterate     9  f =       251.18  |proj g|=       0.76454
-  At iterate    10  f =       251.17  |proj g|=        1.3508
-  At iterate    11  f =       251.13  |proj g|=         1.771
-  At iterate    12  f =       251.05  |proj g|=        1.7928
-  At iterate    13  f =       250.85  |proj g|=        1.8249
-  At iterate    14  f =       250.39  |proj g|=        1.8635
-  At iterate    15  f =       249.41  |proj g|=        1.8966
-  At iterate    16  f =       249.38  |proj g|=        1.8622
-  At iterate    17  f =       247.82  |proj g|=        1.8232
-  At iterate    18  f =       244.57  |proj g|=        1.7425
-  At iterate    19  f =       243.28  |proj g|=        1.7298
-  At iterate    20  f =       243.27  |proj g|=        1.2235
-  At iterate    21  f =       243.26  |proj g|=       0.15275
-  At iterate    22  f =       243.26  |proj g|=      0.046928
-  At iterate    23  f =       243.26  |proj g|=    4.2376e-05
-  At iterate    24  f =       243.26  |proj g|=    8.9789e-07
-  
-  iterations 24
-  function evaluations 35
-  segments explored during Cauchy searches 25
+  At iterate     0  f=       265.38  |proj g|=       3.4795
+  At iterate     1  f =       263.07  |proj g|=        1.8056
+  At iterate     2  f =       261.77  |proj g|=        2.5658
+  At iterate     3  f =       256.47  |proj g|=        7.9732
+  At iterate     4  f =       256.04  |proj g|=        12.386
+  At iterate     5  f =        251.2  |proj g|=         3.716
+  At iterate     6  f =       250.66  |proj g|=        1.6769
+  At iterate     7  f =       250.64  |proj g|=       0.73078
+  At iterate     8  f =       250.64  |proj g|=       0.22161
+  At iterate     9  f =       250.64  |proj g|=       0.22098
+  At iterate    10  f =       250.63  |proj g|=       0.21759
+  At iterate    11  f =       250.62  |proj g|=       0.21455
+  At iterate    12  f =        250.6  |proj g|=       0.38079
+  At iterate    13  f =       250.53  |proj g|=       0.58929
+  At iterate    14  f =       250.34  |proj g|=       0.62872
+  At iterate    15  f =       249.88  |proj g|=       0.20538
+  At iterate    16  f =       248.94  |proj g|=        3.0182
+  At iterate    17  f =       247.76  |proj g|=        7.9867
+  At iterate    18  f =       247.44  |proj g|=        13.607
+  At iterate    19  f =       247.05  |proj g|=        14.601
+  At iterate    20  f =       243.72  |proj g|=        1.7429
+  At iterate    21  f =       243.49  |proj g|=       0.60214
+  At iterate    22  f =       243.32  |proj g|=       0.17842
+  At iterate    23  f =       243.27  |proj g|=        1.7301
+  At iterate    24  f =       243.26  |proj g|=         0.034
+  At iterate    25  f =       243.26  |proj g|=      0.044098
+  At iterate    26  f =       243.26  |proj g|=      0.080905
+  At iterate    27  f =       243.26  |proj g|=    0.00083096
+  At iterate    28  f =       243.26  |proj g|=    9.4637e-05
+  
+  iterations 28
+  function evaluations 40
+  segments explored during Cauchy searches 30
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 8.97888e-07
+  norm of the final projected gradient 9.46371e-05
   final function value 243.264
   
   F = 243.264
@@ -631,29 +657,49 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -442.2915 
+    - best initial criterion value(s) :  -316.7978 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       442.29  |proj g|=       3.5197
-  At iterate     1  f =       330.16  |proj g|=       0.36498
-  At iterate     2  f =       318.79  |proj g|=       0.18093
-  At iterate     3  f =       318.27  |proj g|=      0.058029
-  At iterate     4  f =       318.23  |proj g|=      0.024365
-  At iterate     5  f =       318.22  |proj g|=     0.0020454
-  At iterate     6  f =       318.22  |proj g|=    6.5327e-05
-  At iterate     7  f =       318.22  |proj g|=    1.8242e-07
-  
-  iterations 7
-  function evaluations 20
-  segments explored during Cauchy searches 9
+  At iterate     0  f=        316.8  |proj g|=       3.1965
+  At iterate     1  f =        256.3  |proj g|=        1.7787
+  At iterate     2  f =       251.47  |proj g|=        1.9752
+  At iterate     3  f =       249.21  |proj g|=        4.5553
+  At iterate     4  f =       248.04  |proj g|=       0.94521
+  At iterate     5  f =       248.04  |proj g|=       0.23737
+  At iterate     6  f =       248.04  |proj g|=       0.23788
+  At iterate     7  f =       248.04  |proj g|=       0.93772
+  At iterate     8  f =       248.04  |proj g|=        1.7025
+  At iterate     9  f =       248.04  |proj g|=        1.7029
+  At iterate    10  f =       248.03  |proj g|=        1.7035
+  At iterate    11  f =       248.02  |proj g|=        1.7046
+  At iterate    12  f =       247.99  |proj g|=        1.7063
+  At iterate    13  f =       247.91  |proj g|=        2.5518
+  At iterate    14  f =       247.69  |proj g|=        4.6718
+  At iterate    15  f =       247.14  |proj g|=        8.6703
+  At iterate    16  f =       246.07  |proj g|=        15.797
+  At iterate    17  f =       245.16  |proj g|=        16.055
+  At iterate    18  f =       244.87  |proj g|=        7.2817
+  At iterate    19  f =       244.64  |proj g|=        10.048
+  At iterate    20  f =       244.49  |proj g|=        11.047
+  At iterate    21  f =       244.04  |proj g|=        10.091
+  At iterate    22  f =       243.39  |proj g|=        3.6179
+  At iterate    23  f =       243.35  |proj g|=        1.9252
+  At iterate    24  f =       243.26  |proj g|=       0.15282
+  At iterate    25  f =       243.26  |proj g|=      0.063494
+  At iterate    26  f =       243.26  |proj g|=     0.0019926
+  At iterate    27  f =       243.26  |proj g|=    3.3056e-06
+  
+  iterations 27
+  function evaluations 32
+  segments explored during Cauchy searches 29
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.82418e-07
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 3.30561e-06
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -668,43 +714,50 @@
     - 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) :  -300.494 
+    - best initial criterion value(s) :  -268.264 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       300.49  |proj g|=      0.75297
-  At iterate     1  f =       285.37  |proj g|=        28.409
-  At iterate     2  f =       281.92  |proj g|=        43.981
-  At iterate     3  f =       280.58  |proj g|=        43.939
-  At iterate     4  f =       278.06  |proj g|=        43.865
-  At iterate     5  f =       267.81  |proj g|=        43.615
-  At iterate     6  f =       261.39  |proj g|=        1.1855
-  At iterate     7  f =       250.58  |proj g|=         17.01
-  At iterate     8  f =       248.69  |proj g|=        8.4311
-  At iterate     9  f =       248.04  |proj g|=        1.9377
-  At iterate    10  f =       247.99  |proj g|=       0.25653
-  At iterate    11  f =       247.98  |proj g|=         0.239
-  At iterate    12  f =       247.98  |proj g|=        0.2395
-  At iterate    13  f =       247.97  |proj g|=       0.52959
-  At iterate    14  f =       247.95  |proj g|=        1.0385
-  At iterate    15  f =       247.91  |proj g|=        2.9586
-  At iterate    16  f =       247.81  |proj g|=        3.6337
-  At iterate    17  f =       246.95  |proj g|=        5.8683
-  At iterate    18  f =       244.68  |proj g|=        7.5379
-  At iterate    19  f =       244.07  |proj g|=        6.6661
-  At iterate    20  f =       243.48  |proj g|=        5.5749
-  At iterate    21  f =        243.3  |proj g|=         2.473
-  At iterate    22  f =       243.27  |proj g|=       0.17257
-  At iterate    23  f =       243.26  |proj g|=      0.081305
-  At iterate    24  f =       243.26  |proj g|=      0.062581
-  At iterate    25  f =       243.26  |proj g|=      0.029342
-  
-  iterations 25
-  function evaluations 33
-  segments explored during Cauchy searches 27
+  At iterate     0  f=       268.26  |proj g|=       3.7425
+  At iterate     1  f =       265.68  |proj g|=        1.8046
+  At iterate     2  f =       265.35  |proj g|=        1.8013
+  At iterate     3  f =       259.22  |proj g|=        5.5748
+  At iterate     4  f =        259.1  |proj g|=         6.428
+  At iterate     5  f =       253.84  |proj g|=        6.5271
+  At iterate     6  f =       253.18  |proj g|=        1.8598
+  At iterate     7  f =       253.04  |proj g|=        1.6067
+  At iterate     8  f =       253.04  |proj g|=       0.20003
+  At iterate     9  f =       253.04  |proj g|=       0.19977
+  At iterate    10  f =       253.04  |proj g|=       0.19894
+  At iterate    11  f =       253.04  |proj g|=       0.19816
+  At iterate    12  f =       253.04  |proj g|=       0.19692
+  At iterate    13  f =       253.04  |proj g|=       0.23978
+  At iterate    14  f =       253.03  |proj g|=       0.38358
+  At iterate    15  f =          253  |proj g|=       0.52866
+  At iterate    16  f =       252.93  |proj g|=       0.48101
+  At iterate    17  f =       252.78  |proj g|=       0.37105
+  At iterate    18  f =        252.5  |proj g|=        3.1195
+  At iterate    19  f =        251.7  |proj g|=        7.6701
+  At iterate    20  f =       249.51  |proj g|=        17.248
+  At iterate    21  f =       247.92  |proj g|=        22.194
+  At iterate    22  f =       247.25  |proj g|=        23.867
+  At iterate    23  f =       246.55  |proj g|=        20.309
+  At iterate    24  f =       244.23  |proj g|=        11.643
+  At iterate    25  f =       243.43  |proj g|=        1.3771
+  At iterate    26  f =       243.28  |proj g|=       0.18629
+  At iterate    27  f =       243.27  |proj g|=        1.7284
+  At iterate    28  f =       243.26  |proj g|=       0.41295
+  At iterate    29  f =       243.26  |proj g|=      0.025676
+  At iterate    30  f =       243.26  |proj g|=      0.044322
+  At iterate    31  f =       243.26  |proj g|=     0.0055313
+  At iterate    32  f =       243.26  |proj g|=      0.001114
+  
+  iterations 32
+  function evaluations 42
+  segments explored during Cauchy searches 34
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.0293424
+  norm of the final projected gradient 0.00111397
   final function value 243.264
   
   F = 243.264
@@ -719,34 +772,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -145.7385 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -9376.76 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       145.74  |proj g|=       6.8942
-  At iterate     1  f =       99.548  |proj g|=        2.9145
-  At iterate     2  f =       64.806  |proj g|=        7.1404
-  At iterate     3  f =       64.161  |proj g|=       0.76633
-  At iterate     4  f =       64.051  |proj g|=       0.71551
-  At iterate     5  f =       64.029  |proj g|=       0.35344
-  At iterate     6  f =       64.028  |proj g|=      0.030719
-  At iterate     7  f =       64.028  |proj g|=    0.00064292
-  At iterate     8  f =       64.028  |proj g|=    1.2009e-06
+  At iterate     0  f=       9376.8  |proj g|=       8.8312
+  At iterate     1  f =       104.62  |proj g|=        2.3796
+  At iterate     2  f =       69.097  |proj g|=       0.13017
+  At iterate     3  f =       69.097  |proj g|=     0.0039023
+  At iterate     4  f =       69.097  |proj g|=    3.8214e-05
+  At iterate     5  f =       69.097  |proj g|=    1.1083e-08
   
-  iterations 8
-  function evaluations 21
-  segments explored during Cauchy searches 11
+  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 1.20087e-06
-  final function value 64.028
+  norm of the final projected gradient 1.10825e-08
+  final function value 69.0969
   
-  F = 64.028
-  final  value 64.027980 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -757,34 +807,31 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -145.7385 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -9376.76 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       145.74  |proj g|=       6.8942
-  At iterate     1  f =       99.548  |proj g|=        2.9145
-  At iterate     2  f =       64.806  |proj g|=        7.1404
-  At iterate     3  f =       64.161  |proj g|=       0.76633
-  At iterate     4  f =       64.051  |proj g|=       0.71551
-  At iterate     5  f =       64.029  |proj g|=       0.35344
-  At iterate     6  f =       64.028  |proj g|=      0.030719
-  At iterate     7  f =       64.028  |proj g|=    0.00064292
-  At iterate     8  f =       64.028  |proj g|=    1.2009e-06
+  At iterate     0  f=       9376.8  |proj g|=       8.8312
+  At iterate     1  f =       104.62  |proj g|=        2.3796
+  At iterate     2  f =       69.097  |proj g|=       0.13017
+  At iterate     3  f =       69.097  |proj g|=     0.0039023
+  At iterate     4  f =       69.097  |proj g|=    3.8214e-05
+  At iterate     5  f =       69.097  |proj g|=    1.1083e-08
   
-  iterations 8
-  function evaluations 21
-  segments explored during Cauchy searches 11
+  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 1.20087e-06
-  final function value 64.028
+  norm of the final projected gradient 1.10825e-08
+  final function value 69.0969
   
-  F = 64.028
-  final  value 64.027980 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -795,35 +842,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -311.7873 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -3402.244 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       311.79  |proj g|=       7.3528
-  At iterate     1  f =       99.548  |proj g|=        2.9145
-  At iterate     2  f =       64.989  |proj g|=       0.93817
-  ys=-2.222e+01  -gs= 1.959e+01, BFGS update SKIPPED
-  At iterate     3  f =       64.404  |proj g|=       0.83064
-  At iterate     4  f =        64.03  |proj g|=       0.43458
-  At iterate     5  f =       64.028  |proj g|=       0.19571
-  At iterate     6  f =       64.028  |proj g|=      0.005256
-  At iterate     7  f =       64.028  |proj g|=    6.1511e-05
-  At iterate     8  f =       64.028  |proj g|=    1.9619e-08
+  At iterate     0  f=       3402.2  |proj g|=       8.2651
+  At iterate     1  f =       104.62  |proj g|=        2.3796
+  At iterate     2  f =       69.359  |proj g|=       0.98554
+  ys=-6.903e+00  -gs= 1.999e+01, BFGS update SKIPPED
+  At iterate     3  f =       69.281  |proj g|=       0.95929
+  At iterate     4  f =       69.129  |proj g|=        1.4707
+  At iterate     5  f =       69.099  |proj g|=       0.35276
+  At iterate     6  f =       69.097  |proj g|=      0.035018
+  At iterate     7  f =       69.097  |proj g|=    0.00095213
+  At iterate     8  f =       69.097  |proj g|=    2.4849e-06
   
   iterations 8
-  function evaluations 20
+  function evaluations 26
   segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.96191e-08
-  final function value 64.028
+  norm of the final projected gradient 2.48494e-06
+  final function value 69.0969
   
-  F = 64.028
-  final  value 64.027980 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -834,35 +881,35 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -311.7873 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -3402.244 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       311.79  |proj g|=       7.3528
-  At iterate     1  f =       99.548  |proj g|=        2.9145
-  At iterate     2  f =       64.989  |proj g|=       0.93817
-  ys=-2.222e+01  -gs= 1.959e+01, BFGS update SKIPPED
-  At iterate     3  f =       64.404  |proj g|=       0.83064
-  At iterate     4  f =        64.03  |proj g|=       0.43458
-  At iterate     5  f =       64.028  |proj g|=       0.19571
-  At iterate     6  f =       64.028  |proj g|=      0.005256
-  At iterate     7  f =       64.028  |proj g|=    6.1511e-05
-  At iterate     8  f =       64.028  |proj g|=    1.9619e-08
+  At iterate     0  f=       3402.2  |proj g|=       8.2651
+  At iterate     1  f =       104.62  |proj g|=        2.3796
+  At iterate     2  f =       69.359  |proj g|=       0.98554
+  ys=-6.903e+00  -gs= 1.999e+01, BFGS update SKIPPED
+  At iterate     3  f =       69.281  |proj g|=       0.95929
+  At iterate     4  f =       69.129  |proj g|=        1.4707
+  At iterate     5  f =       69.099  |proj g|=       0.35276
+  At iterate     6  f =       69.097  |proj g|=      0.035018
+  At iterate     7  f =       69.097  |proj g|=    0.00095213
+  At iterate     8  f =       69.097  |proj g|=    2.4849e-06
   
   iterations 8
-  function evaluations 20
+  function evaluations 26
   segments explored during Cauchy searches 11
   BFGS updates skipped 1
   active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 1.96191e-08
-  final function value 64.028
+  norm of the final projected gradient 2.48494e-06
+  final function value 69.0969
   
-  F = 64.028
-  final  value 64.027980 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -873,60 +920,36 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -93.78211 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -1338980 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       93.782  |proj g|=       6.6611
-  At iterate     1  f =       80.025  |proj g|=        3.2063
-  At iterate     2  f =       63.898  |proj g|=        1.9385
-  At iterate     3  f =       63.686  |proj g|=        1.9389
-  At iterate     4  f =       63.613  |proj g|=        1.9378
-  At iterate     5  f =       63.605  |proj g|=       0.64422
-  At iterate     6  f =       63.605  |proj g|=       0.62413
-  At iterate     7  f =       63.605  |proj g|=       0.62484
-  At iterate     8  f =       63.605  |proj g|=       0.62631
-  At iterate     9  f =       63.604  |proj g|=       0.62896
-  At iterate    10  f =       63.604  |proj g|=       0.63236
-  At iterate    11  f =       63.604  |proj g|=       0.63697
-  At iterate    12  f =       63.602  |proj g|=       0.64108
-  At iterate    13  f =       63.598  |proj g|=       0.63697
-  At iterate    14  f =       63.589  |proj g|=       0.99397
-  At iterate    15  f =       63.571  |proj g|=        1.5631
-  At iterate    16  f =        63.57  |proj g|=        1.5498
-  At iterate    17  f =       63.543  |proj g|=        1.7792
-  At iterate    18  f =       63.492  |proj g|=       0.28504
-  At iterate    19  f =       63.491  |proj g|=       0.26763
-  At iterate    20  f =       63.491  |proj g|=       0.26912
-  At iterate    21  f =       63.483  |proj g|=       0.24303
-  At iterate    22  f =       63.483  |proj g|=        1.9368
-  At iterate    23  f =       63.458  |proj g|=        0.1673
-  At iterate    24  f =       63.457  |proj g|=       0.26786
-  At iterate    25  f =       63.454  |proj g|=      0.019495
-  At iterate    26  f =       63.454  |proj g|=      0.012584
-  At iterate    27  f =       63.454  |proj g|=      0.018948
-  At iterate    28  f =       63.454  |proj g|=      0.011845
-  At iterate    29  f =       63.454  |proj g|=      0.011403
-  At iterate    30  f =       63.454  |proj g|=     0.0084383
-  At iterate    31  f =       63.454  |proj g|=       0.11221
-  At iterate    32  f =       63.454  |proj g|=      0.055405
-  At iterate    33  f =       63.454  |proj g|=      0.020343
-  At iterate    34  f =       63.454  |proj g|=    1.8655e-05
+  At iterate     0  f=    1.339e+06  |proj g|=       8.6493
+  At iterate     1  f =       104.62  |proj g|=        2.3796
+  At iterate     2  f =       70.399  |proj g|=        1.2144
+  ys=-2.575e+01  -gs= 1.944e+01, BFGS update SKIPPED
+  At iterate     3  f =       69.866  |proj g|=        1.1112
+  At iterate     4  f =        69.12  |proj g|=       0.87804
+  At iterate     5  f =       69.109  |proj g|=       0.88887
+  At iterate     6  f =       69.097  |proj g|=      0.073892
+  At iterate     7  f =       69.097  |proj g|=     0.0045401
+  At iterate     8  f =       69.097  |proj g|=    2.5107e-05
+  At iterate     9  f =       69.097  |proj g|=    8.4721e-09
   
-  iterations 34
-  function evaluations 46
-  segments explored during Cauchy searches 37
-  BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 1.86547e-05
-  final function value 63.4542
+  iterations 9
+  function evaluations 34
+  segments explored during Cauchy searches 12
+  BFGS updates skipped 1
+  active bounds at final generalized Cauchy point 3
+  norm of the final projected gradient 8.47206e-09
+  final function value 69.0969
   
-  F = 63.4542
-  final  value 63.454173 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -937,35 +960,32 @@
   * trend model : ~1
   * covariance model : 
     - type :  matern5_2 
-    - nugget : 7.737123e-09 
+    - nugget : 9.476219e-09 
     - parameters lower bounds :  1e-10 1e-10 1e-10 
-    - parameters upper bounds :  4 2 1.943579 
-    - variance bounds :  0.0759119 7.737123 
-    - best initial criterion value(s) :  -345.1696 
+    - parameters upper bounds :  4 2 1.992084 
+    - variance bounds :  0.09174808 9.476219 
+    - best initial criterion value(s) :  -76.53642 
   
   N = 4, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       345.17  |proj g|=       7.0477
-  At iterate     1  f =       99.548  |proj g|=        2.9145
-  At iterate     2  f =       65.239  |proj g|=       0.97695
-  ys=-2.493e+01  -gs= 1.948e+01, BFGS update SKIPPED
-  At iterate     3  f =       64.553  |proj g|=       0.86165
-  At iterate     4  f =       64.036  |proj g|=       0.70231
-  At iterate     5  f =       64.031  |proj g|=       0.48157
-  At iterate     6  f =       64.028  |proj g|=      0.024773
-  At iterate     7  f =       64.028  |proj g|=    0.00069955
-  At iterate     8  f =       64.028  |proj g|=    1.0533e-06
+  At iterate     0  f=       76.536  |proj g|=       8.4714
+  At iterate     1  f =       72.287  |proj g|=        1.6886
+  At iterate     2  f =       69.274  |proj g|=       0.95683
+  At iterate     3  f =       69.098  |proj g|=        0.2417
+  At iterate     4  f =       69.097  |proj g|=      0.064623
+  At iterate     5  f =       69.097  |proj g|=     0.0011417
+  At iterate     6  f =       69.097  |proj g|=    5.5152e-06
   
-  iterations 8
-  function evaluations 24
-  segments explored during Cauchy searches 11
-  BFGS updates skipped 1
-  active bounds at final generalized Cauchy point 3
-  norm of the final projected gradient 1.05326e-06
-  final function value 64.028
+  iterations 6
+  function evaluations 10
+  segments explored during Cauchy searches 9
+  BFGS updates skipped 0
+  active bounds at final generalized Cauchy point 1
+  norm of the final projected gradient 5.51525e-06
+  final function value 69.0969
   
-  F = 64.028
-  final  value 64.027980 
+  F = 69.0969
+  final  value 69.096867 
   converged
   
   optimisation start
@@ -980,28 +1000,49 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -739.8821 
+    - best initial criterion value(s) :  -252.9109 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       739.88  |proj g|=       14.162
-  At iterate     1  f =       325.32  |proj g|=       0.36274
-  At iterate     2  f =       318.37  |proj g|=       0.10176
-  At iterate     3  f =       318.22  |proj g|=     0.0099363
-  At iterate     4  f =       318.22  |proj g|=     0.0017052
-  At iterate     5  f =       318.22  |proj g|=    2.3376e-05
-  At iterate     6  f =       318.22  |proj g|=    5.4065e-08
-  
-  iterations 6
-  function evaluations 21
-  segments explored during Cauchy searches 8
+  At iterate     0  f=       252.91  |proj g|=       6.5566
+  At iterate     1  f =       250.66  |proj g|=        1.8345
+  At iterate     2  f =       250.58  |proj g|=         1.823
+  At iterate     3  f =       250.28  |proj g|=       0.22257
+  At iterate     4  f =       250.28  |proj g|=       0.22453
+  At iterate     5  f =       250.28  |proj g|=        0.3093
+  At iterate     6  f =       250.28  |proj g|=       0.87748
+  At iterate     7  f =       250.28  |proj g|=        1.6946
+  At iterate     8  f =       250.28  |proj g|=        1.6948
+  At iterate     9  f =       250.27  |proj g|=        1.6953
+  At iterate    10  f =       250.27  |proj g|=        1.6959
+  At iterate    11  f =       250.25  |proj g|=        1.6967
+  At iterate    12  f =       250.21  |proj g|=        2.7325
+  At iterate    13  f =       250.13  |proj g|=        4.3533
+  At iterate    14  f =       249.96  |proj g|=        5.2926
+  At iterate    15  f =        249.7  |proj g|=        5.9222
+  At iterate    16  f =       249.42  |proj g|=        5.9231
+  At iterate    17  f =       248.61  |proj g|=         5.762
+  At iterate    18  f =       247.72  |proj g|=        3.2643
+  At iterate    19  f =       246.41  |proj g|=        7.0078
+  At iterate    20  f =          244  |proj g|=        9.1571
+  At iterate    21  f =       243.67  |proj g|=        7.2571
+  At iterate    22  f =        243.3  |proj g|=        1.7325
+  At iterate    23  f =       243.27  |proj g|=       0.15421
+  At iterate    24  f =       243.26  |proj g|=      0.095985
+  At iterate    25  f =       243.26  |proj g|=      0.046297
+  At iterate    26  f =       243.26  |proj g|=    0.00075281
+  At iterate    27  f =       243.26  |proj g|=    2.5039e-05
+  
+  iterations 27
+  function evaluations 32
+  segments explored during Cauchy searches 28
   BFGS updates skipped 0
-  active bounds at final generalized Cauchy point 2
-  norm of the final projected gradient 5.40652e-08
-  final function value 318.222
+  active bounds at final generalized Cauchy point 0
+  norm of the final projected gradient 2.50386e-05
+  final function value 243.264
   
-  F = 318.222
-  final  value 318.221782 
+  F = 243.264
+  final  value 243.264413 
   converged
   
   optimisation start
@@ -1016,42 +1057,51 @@
     - parameters lower bounds :  1e-10 1e-10 
     - parameters upper bounds :  1.880582 44.27959 
     - variance bounds :  3.435024 622.0591 
-    - best initial criterion value(s) :  -252.4233 
+    - best initial criterion value(s) :  -314.1912 
   
   N = 3, M = 5 machine precision = 2.22045e-16
   At X0, 0 variables are exactly at the bounds
-  At iterate     0  f=       252.42  |proj g|=        4.557
-  At iterate     1  f =       248.35  |proj g|=        1.8638
-  At iterate     2  f =       247.44  |proj g|=        1.8057
-  At iterate     3  f =       246.32  |proj g|=        1.7316
-  At iterate     4  f =       245.28  |proj g|=        1.5762
-  At iterate     5  f =       245.22  |proj g|=       0.22515
-  At iterate     6  f =       245.22  |proj g|=        0.2268
-  At iterate     7  f =       245.22  |proj g|=       0.30687
-  At iterate     8  f =       245.22  |proj g|=       0.62312
-  At iterate     9  f =       245.22  |proj g|=        1.3794
-  At iterate    10  f =       245.22  |proj g|=        1.7133
-  At iterate    11  f =       245.21  |proj g|=        1.7134
-  At iterate    12  f =       245.21  |proj g|=        1.7135
-  At iterate    13  f =       245.19  |proj g|=        1.8593
-  At iterate    14  f =       245.15  |proj g|=        2.9483
-  At iterate    15  f =       245.06  |proj g|=        4.5269
-  At iterate    16  f =       245.04  |proj g|=        5.5539
-  At iterate    17  f =       244.84  |proj g|=        7.0866
-  At iterate    18  f =        244.1  |proj g|=        9.1358
-  At iterate    19  f =        243.6  |proj g|=        5.0163
-  At iterate    20  f =       243.27  |proj g|=       0.67773
-  At iterate    21  f =       243.26  |proj g|=       0.99123
-  At iterate    22  f =       243.26  |proj g|=      0.087663
-  At iterate    23  f =       243.26  |proj g|=      0.010182
-  At iterate    24  f =       243.26  |proj g|=    0.00020481
-  
-  iterations 24
-  function evaluations 30
-  segments explored during Cauchy searches 25
+  At iterate     0  f=       314.19  |proj g|=       44.171
+  At iterate     1  f =       313.71  |proj g|=        44.167
+  At iterate     2  f =       312.23  |proj g|=        1.6032
+  At iterate     3  f =        307.1  |proj g|=        1.4273
+  At iterate     4  f =       285.45  |proj g|=        42.537
+  At iterate     5  f =       285.18  |proj g|=        44.066
+  At iterate     6  f =       284.16  |proj g|=        44.044
+  At iterate     7  f =       283.57  |proj g|=        44.041
+  At iterate     8  f =       280.75  |proj g|=        40.837
+  At iterate     9  f =       271.83  |proj g|=        43.764
+  At iterate    10  f =       263.73  |proj g|=        39.489
+  At iterate    11  f =       257.73  |proj g|=        14.955
+  At iterate    12  f =       250.54  |proj g|=        16.192
+  At iterate    13  f =       247.97  |proj g|=        9.5426
+  At iterate    14  f =       247.13  |proj g|=       0.93041
+  At iterate    15  f =       247.11  |proj g|=        1.5592
+  At iterate    16  f =       247.11  |proj g|=       0.24109
+  At iterate    17  f =       247.11  |proj g|=       0.24094
+  At iterate    18  f =       247.11  |proj g|=       0.24027
+  At iterate    19  f =       247.11  |proj g|=       0.34127
+  At iterate    20  f =       247.11  |proj g|=       0.69054
+  At iterate    21  f =        247.1  |proj g|=        1.2648
+  At iterate    22  f =       247.07  |proj g|=        1.6365
+  At iterate    23  f =       247.06  |proj g|=         1.637
+  At iterate    24  f =       246.99  |proj g|=        1.6569
+  At iterate    25  f =       246.68  |proj g|=        1.6833
+  At iterate    26  f =       245.58  |proj g|=        1.6899
+  At iterate    27  f =       244.59  |proj g|=        1.5713
+  At iterate    28  f =       243.31  |proj g|=        1.7308
+  At iterate    29  f =       243.29  |proj g|=        1.3948
+  At iterate    30  f =       243.27  |proj g|=        0.6741
+  At iterate    31  f =       243.26  |proj g|=       0.12836
+  At iterate    32  f =       243.26  |proj g|=     0.0089258
+  At iterate    33  f =       243.26  |proj g|=     0.0010326
+  
+  iterations 33
+  function evaluations 44
+  segments explored during Cauchy searches 35
   BFGS updates skipped 0
   active bounds at final generalized Cauchy point 0
-  norm of the final projected gradient 0.000204809
+  norm of the final projected gradient 0.00103256
   final function value 243.264
   
   F = 243.264
> 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)
+ }
>