Diff of the two buildlogs: -- --- b1/build.log 2024-11-18 19:40:52.126118086 +0000 +++ b2/build.log 2024-11-18 20:00:55.415680693 +0000 @@ -1,6 +1,6 @@ I: pbuilder: network access will be disabled during build -I: Current time: Mon Nov 18 07:34:39 -12 2024 -I: pbuilder-time-stamp: 1731958479 +I: Current time: Mon Dec 22 16:04:23 +14 2025 +I: pbuilder-time-stamp: 1766369063 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/unstable-reproducible-base.tgz] I: copying local configuration @@ -29,54 +29,86 @@ dpkg-source: info: applying 0003-Mark-expected-failure.patch I: Not using root during the build. I: Installing the build-deps -I: user script /srv/workspace/pbuilder/15186/tmp/hooks/D02_print_environment starting +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/D01_modify_environment starting +debug: Running on ionos16-i386. +I: Changing host+domainname to test build reproducibility +I: Adding a custom variable just for the fun of it... +I: Changing /bin/sh to bash +'/bin/sh' -> '/bin/bash' +lrwxrwxrwx 1 root root 9 Dec 22 02:07 /bin/sh -> /bin/bash +I: Setting pbuilder2's login shell to /bin/bash +I: Setting pbuilder2's GECOS to second user,second room,second work-phone,second home-phone,second other +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/D01_modify_environment finished +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/D02_print_environment starting I: set - BUILDDIR='/build/reproducible-path' - BUILDUSERGECOS='first user,first room,first work-phone,first home-phone,first other' - BUILDUSERNAME='pbuilder1' - BUILD_ARCH='i386' - DEBIAN_FRONTEND='noninteractive' - DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=11 ' - DISTRIBUTION='unstable' - HOME='/root' - HOST_ARCH='i386' + BASH=/bin/sh + BASHOPTS=checkwinsize:cmdhist:complete_fullquote:extquote:force_fignore:globasciiranges:globskipdots:hostcomplete:interactive_comments:patsub_replacement:progcomp:promptvars:sourcepath + BASH_ALIASES=() + BASH_ARGC=() + BASH_ARGV=() + BASH_CMDS=() + BASH_LINENO=([0]="12" [1]="0") + BASH_LOADABLES_PATH=/usr/local/lib/bash:/usr/lib/bash:/opt/local/lib/bash:/usr/pkg/lib/bash:/opt/pkg/lib/bash:. + BASH_SOURCE=([0]="/tmp/hooks/D02_print_environment" [1]="/tmp/hooks/D02_print_environment") + BASH_VERSINFO=([0]="5" [1]="2" [2]="32" [3]="1" [4]="release" [5]="i686-pc-linux-gnu") + BASH_VERSION='5.2.32(1)-release' + BUILDDIR=/build/reproducible-path + BUILDUSERGECOS='second user,second room,second work-phone,second home-phone,second other' + BUILDUSERNAME=pbuilder2 + BUILD_ARCH=i386 + DEBIAN_FRONTEND=noninteractive + DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=21 ' + DIRSTACK=() + DISTRIBUTION=unstable + EUID=0 + FUNCNAME=([0]="Echo" [1]="main") + GROUPS=() + HOME=/root + HOSTNAME=i-capture-the-hostname + HOSTTYPE=i686 + HOST_ARCH=i386 IFS=' ' - INVOCATION_ID='fb1ac8836fcb421f8af9743022f95f71' - LANG='C' - LANGUAGE='en_US:en' - LC_ALL='C' - LD_LIBRARY_PATH='/usr/lib/libeatmydata' - LD_PRELOAD='libeatmydata.so' - MAIL='/var/mail/root' - OPTIND='1' - PATH='/usr/sbin:/usr/bin:/sbin:/bin:/usr/games' - PBCURRENTCOMMANDLINEOPERATION='build' - PBUILDER_OPERATION='build' - PBUILDER_PKGDATADIR='/usr/share/pbuilder' - PBUILDER_PKGLIBDIR='/usr/lib/pbuilder' - PBUILDER_SYSCONFDIR='/etc' - PPID='15186' - PS1='# ' - PS2='> ' + INVOCATION_ID=aeff983bccbe403a9188e779969cf672 + LANG=C + LANGUAGE=de_CH:de + LC_ALL=C + LD_LIBRARY_PATH=/usr/lib/libeatmydata + LD_PRELOAD=libeatmydata.so + MACHTYPE=i686-pc-linux-gnu + MAIL=/var/mail/root + OPTERR=1 + OPTIND=1 + OSTYPE=linux-gnu + PATH=/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path + PBCURRENTCOMMANDLINEOPERATION=build + PBUILDER_OPERATION=build + PBUILDER_PKGDATADIR=/usr/share/pbuilder + PBUILDER_PKGLIBDIR=/usr/lib/pbuilder + PBUILDER_SYSCONFDIR=/etc + PIPESTATUS=([0]="0") + POSIXLY_CORRECT=y + PPID=49101 PS4='+ ' - PWD='/' - SHELL='/bin/bash' - SHLVL='2' - SUDO_COMMAND='/usr/bin/timeout -k 18.1h 18h /usr/bin/ionice -c 3 /usr/bin/nice /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.TGH5N7OA/pbuilderrc_pf56 --distribution unstable --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/unstable-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.TGH5N7OA/b1 --logfile b1/build.log octave-stk_2.8.1-3.dsc' - SUDO_GID='112' - SUDO_UID='107' - SUDO_USER='jenkins' - TERM='unknown' - TZ='/usr/share/zoneinfo/Etc/GMT+12' - USER='root' - _='/usr/bin/systemd-run' - http_proxy='http://46.16.76.132:3128' + PWD=/ + SHELL=/bin/bash + SHELLOPTS=braceexpand:errexit:hashall:interactive-comments:posix + SHLVL=3 + SUDO_COMMAND='/usr/bin/timeout -k 24.1h 24h /usr/bin/ionice -c 3 /usr/bin/nice -n 11 /usr/bin/unshare --uts -- /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.TGH5N7OA/pbuilderrc_zePB --distribution unstable --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/unstable-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.TGH5N7OA/b2 --logfile b2/build.log octave-stk_2.8.1-3.dsc' + SUDO_GID=112 + SUDO_UID=107 + SUDO_USER=jenkins + TERM=unknown + TZ=/usr/share/zoneinfo/Etc/GMT-14 + UID=0 + USER=root + _='I: set' + http_proxy=http://213.165.73.152:3128 I: uname -a - Linux ionos12-i386 6.1.0-27-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.115-1 (2024-11-01) x86_64 GNU/Linux + Linux i-capture-the-hostname 6.1.0-27-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.115-1 (2024-11-01) x86_64 GNU/Linux I: ls -l /bin - lrwxrwxrwx 1 root root 7 Aug 4 21:30 /bin -> usr/bin -I: user script /srv/workspace/pbuilder/15186/tmp/hooks/D02_print_environment finished + lrwxrwxrwx 1 root root 7 Aug 4 2024 /bin -> usr/bin +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy @@ -637,7 +669,7 @@ Get: 521 http://deb.debian.org/debian unstable/main i386 gfortran i386 4:14.2.0-1 [1432 B] Get: 522 http://deb.debian.org/debian unstable/main i386 octave-dev i386 9.2.0-3+b1 [1004 kB] Get: 523 http://deb.debian.org/debian unstable/main i386 dh-octave all 1.8.0 [22.7 kB] -Fetched 211 MB in 4s (53.1 MB/s) +Fetched 211 MB in 4s (48.8 MB/s) debconf: delaying package configuration, since apt-utils is not installed Selecting previously unselected package netbase. (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 19952 files and directories currently installed.) @@ -2783,7 +2815,11 @@ Building tag database... -> Finished parsing the build-deps I: Building the package -I: Running cd /build/reproducible-path/octave-stk-2.8.1/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-build" dpkg-genchanges -S > ../octave-stk_2.8.1-3_source.changes +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/A99_set_merged_usr starting +Not re-configuring usrmerge for unstable +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/A99_set_merged_usr finished +hostname: Name or service not known +I: Running cd /build/reproducible-path/octave-stk-2.8.1/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-genchanges -S > ../octave-stk_2.8.1-3_source.changes dpkg-buildpackage: info: source package octave-stk dpkg-buildpackage: info: source version 2.8.1-3 dpkg-buildpackage: info: source distribution unstable @@ -2824,47 +2860,47 @@ /usr/bin/mkoctfile --verbose --mex --output __stk_dist_matrixy__.mex stk_dist_matrixy.c /usr/bin/mkoctfile --verbose --mex --output __stk_filldist_discr_mex__.mex stk_filldist_discr_mex.c /usr/bin/mkoctfile --verbose --mex --output __stk_gpquadform_matrixy__.mex stk_gpquadform_matrixy.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_pairwise.c -o /tmp/oct-mJYQQ7.o /usr/bin/mkoctfile --verbose --mex --output __stk_isdominated_mex__.mex stk_isdominated_mex.c /usr/bin/mkoctfile --verbose --mex --output __stk_mindist_mex__.mex stk_mindist_mex.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG get_column_number.c -o /tmp/oct-NDdx7u.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_matrixy.c -o /tmp/oct-4ogkBN.o /usr/bin/mkoctfile --verbose --mex --output __stk_dist_matrixx__.mex stk_dist_matrixx.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_filldist_discr_mex.c -o /tmp/oct-JSMc9M.o /usr/bin/mkoctfile --verbose --mex --output __stk_gpquadform_matrixx__.mex stk_gpquadform_matrixx.c /usr/bin/mkoctfile --verbose --mex --output __stk_gpquadform_pairwise__.mex stk_gpquadform_pairwise.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_isdominated_mex.c -o /tmp/oct-ry91p7.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_filldist_discr_mex.c -o /tmp/oct-pANFbn.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_matrixy.c -o /tmp/oct-ClkjxZ.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_matrixy.c -o /tmp/oct-WKe6E1.o /usr/bin/mkoctfile --verbose --mex --output __stk_paretofind_mex__.mex stk_paretofind_mex.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_mindist_mex.c -o /tmp/oct-zvyEBB.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_matrixy.c -o /tmp/oct-MxqfF3.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG get_column_number.c -o /tmp/oct-n1cQ6h.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_pairwise.c -o /tmp/oct-CloXb9.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_mindist_mex.c -o /tmp/oct-IomZ7Y.o /usr/bin/mkoctfile --verbose --mex --output __stk_sampling_vdc_rr2__.mex stk_sampling_vdc_rr2.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_matrixx.c -o /tmp/oct-yztQW0.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_isdominated_mex.c -o /tmp/oct-5oISBH.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_matrixx.c -o /tmp/oct-OZkaat.o /usr/bin/mkoctfile --verbose --mex --output __stk_sampling_sobol_mex__.mex stk_sampling_sobol_mex.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_pairwise.c -o /tmp/oct-KSI573.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dist_matrixx.c -o /tmp/oct-5V4a2D.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_paretofind_mex.c -o /tmp/oct-rZJkaf.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_sampling_vdc_rr2.c -o /tmp/oct-9iOlN7.o -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_sampling_sobol_mex.c -o /tmp/oct-FkW5VL.o -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_mindist_mex__.mex /tmp/oct-zvyEBB.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_pairwise__.mex /tmp/oct-mJYQQ7.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_matrixy__.mex /tmp/oct-4ogkBN.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_pairwise__.mex /tmp/oct-KSI573.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_matrixx__.mex /tmp/oct-5V4a2D.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_matrixx__.mex /tmp/oct-yztQW0.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_filldist_discr_mex__.mex /tmp/oct-JSMc9M.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __get_column_number__.mex /tmp/oct-NDdx7u.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_matrixx.c -o /tmp/oct-nrBQ6l.o /usr/bin/mkoctfile --verbose --mex --output __stk_distrib_bivnorm0_cdf__.mex stk_distrib_bivnorm0_cdf.c -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_matrixy__.mex /tmp/oct-MxqfF3.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_distrib_bivnorm0_cdf.c -o /tmp/oct-O4LYK8.o /usr/bin/mkoctfile --verbose --mex --output __stk_dominatedhv_mex__.mex stk_dominatedhv_mex.c wfg.c -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dominatedhv_mex.c -o /tmp/oct-rKNoK0.o -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_sampling_vdc_rr2__.mex /tmp/oct-9iOlN7.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_sampling_sobol_mex__.mex /tmp/oct-FkW5VL.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_paretofind_mex__.mex /tmp/oct-rZJkaf.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_isdominated_mex__.mex /tmp/oct-ry91p7.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG wfg.c -o /tmp/oct-bzhFNs.o -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_distrib_bivnorm0_cdf__.mex /tmp/oct-O4LYK8.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro -g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dominatedhv_mex__.mex /tmp/oct-rKNoK0.o /tmp/oct-bzhFNs.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_gpquadform_pairwise.c -o /tmp/oct-BNUrJS.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_paretofind_mex.c -o /tmp/oct-Pp0MBK.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_sampling_vdc_rr2.c -o /tmp/oct-ASDqUs.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_sampling_sobol_mex.c -o /tmp/oct-fuLQiy.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_distrib_bivnorm0_cdf.c -o /tmp/oct-4cyVYW.o +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG stk_dominatedhv_mex.c -o /tmp/oct-jmLXQ4.o +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_matrixx__.mex /tmp/oct-OZkaat.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_matrixy__.mex /tmp/oct-WKe6E1.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +gcc -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -fexceptions -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -I. -DMEX_DEBUG wfg.c -o /tmp/oct-nVQtAS.o +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_pairwise__.mex /tmp/oct-BNUrJS.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dist_pairwise__.mex /tmp/oct-CloXb9.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_matrixy__.mex /tmp/oct-ClkjxZ.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __get_column_number__.mex /tmp/oct-n1cQ6h.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_sampling_sobol_mex__.mex /tmp/oct-fuLQiy.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_isdominated_mex__.mex /tmp/oct-5oISBH.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_filldist_discr_mex__.mex /tmp/oct-pANFbn.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_paretofind_mex__.mex /tmp/oct-Pp0MBK.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_gpquadform_matrixx__.mex /tmp/oct-nrBQ6l.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_mindist_mex__.mex /tmp/oct-IomZ7Y.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_sampling_vdc_rr2__.mex /tmp/oct-ASDqUs.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_distrib_bivnorm0_cdf__.mex /tmp/oct-4cyVYW.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro +g++ -I/usr/include/octave-9.2.0/octave/.. -I/usr/include/octave-9.2.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-stk-2.8.1=. -fstack-protector-strong -Wformat -Werror=format-security -o __stk_dominatedhv_mex__.mex /tmp/oct-jmLXQ4.o /tmp/oct-nVQtAS.o -shared -Wl,-Bsymbolic -Wl,-z,relro -flto=auto -ffat-lto-objects -Wl,-z,relro make[1]: Leaving directory '/build/reproducible-path/octave-stk-2.8.1/src' copyfile /build/reproducible-path/octave-stk-2.8.1/./src/__get_column_number__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_dist_matrixx__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_dist_matrixy__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_dist_pairwise__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_distrib_bivnorm0_cdf__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_dominatedhv_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_filldist_discr_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_gpquadform_matrixx__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_gpquadform_matrixy__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_gpquadform_pairwise__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_isdominated_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_mindist_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_paretofind_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_sampling_sobol_mex__.mex /build/reproducible-path/octave-stk-2.8.1/./src/__stk_sampling_vdc_rr2__.mex /build/reproducible-path/octave-stk-2.8.1/./inst/i686-pc-linux-gnu-api-v59 For information about changes from previous versions of the stk package, run 'news stk'. @@ -2873,300 +2909,1976 @@ Checking package... Run the unit tests... Checking m files ... -[inst/misc/dist/stk_gpquadform.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_gpquadform.m -***** shared x, y, z, rx, ry, rz - x = rand(5, 2); rx = rand(5, 2) + 1; - y = rand(6, 2); ry = rand(6, 2) + 1; - z = rand(5, 3); rz = rand(5, 3) + 1; -***** error Q = stk_gpquadform(x, ry, y, ry) -***** error Q = stk_gpquadform(x, rz, y, ry) -***** error Q = stk_gpquadform(x, rx, y, rx) -***** error Q = stk_gpquadform(x, rx, y, rz) -***** error Q = stk_gpquadform(x, rx, z, ry) -***** shared x, y, z, rx, ry, rz - x = zeros (11, 5); rx = 1/sqrt(2) * ones (11, 5); - y = zeros (13, 5); ry = 1/sqrt(2) * ones (13, 5); - z = ones ( 7, 5); rz = 1/sqrt(2) * ones ( 7, 5); +[inst/model/@stk_model_gpposterior/stk_model_update.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_model_update.m +***** shared x_obs, z_obs, ref, M_prior, x_new, z_new, lnv_new + [x_obs, z_obs, ref] = stk_dataset_twobumps ('noisy2'); + M_prior = stk_model (@stk_materncov52_iso); + M_prior.param = [-0.15; 0.38]; + M_prior.lognoisevariance = 2 * log (ref.noise_std); + x_new = [-0.79; -0.79]; + z_new = [-0.69; -0.85]; + lnv_new = ref.noise_std_func (x_new); +***** test % heteroscedastic + M_prior.lognoisevariance = 2 * log (ref.noise_std); + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); + M_post = stk_model_update (M_post, x_new, z_new, lnv_new); +***** error % using lnv_new / homoscedastic + M_prior.lognoisevariance = 0; + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); + M_post = stk_model_update (M_post, x_new, z_new, lnv_new); % NOT OK +***** error % using lnv_new / noiseless + M_prior.lognoisevariance = -inf; + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs) + M_post = stk_model_update (M_post, x_new, z_new, lnv_new); % NOT OK +***** error % not using lnv_new / heteroscedastic + M_prior.lognoisevariance = 2 * log (ref.noise_std); + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); + M_post = stk_model_update (M_post, x_new, z_new); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/model/@stk_model_gpposterior/stk_predict_leaveoneout.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_predict_leaveoneout.m +***** test % Check virtual Leave-One-Out formula + + n = 20; d = 1; + x_obs = stk_sampling_regulargrid (n, d, [0; 2*pi]); + z_obs = stk_feval (@sin, x_obs); + + lm_list = {stk_lm_null, stk_lm_constant, stk_lm_affine}; + + for j = 0:2 + for k = 1:(length (lm_list)) + + model = stk_model (@stk_materncov32_iso, d); + model.lm = lm_list{k}; + model.param = log ([1; 5]); + + switch j % test various scenarios for lognoisevariance + case 0 + model.lognoisevariance = -inf; + case 1 + model.lognoisevariance = 0; + case 2 + model.lognoisevariance = (1 + rand (n, 1)) * 1e-3; + end + + M_post = stk_model_gpposterior (model, x_obs, z_obs); + + [loo_pred, loo_res] = stk_predict_leaveoneout (M_post); + [direct_pred, direct_res] = stk_predict_leaveoneout_direct (M_post); + + assert (stk_isequal_tolrel (loo_pred, direct_pred)); + assert (stk_isequal_tolrel (loo_res, direct_res)); + + end + end +1 test, 1 passed, 0 known failure, 0 skipped +[inst/model/@stk_model_gpposterior/get.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/get.m +***** shared M_post + x_obs = (linspace (0, pi, 15))'; + z_obs = sin (x_obs); + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); +***** error value = get (M_post, 1.33); +***** error value = get (M_post, 'dudule'); +***** test value = get (M_post, 'prior_model'); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/model/@stk_model_gpposterior/stk_predict_.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_predict_.m +***** shared n, m, M_post, M_prior, x0, x_obs, z_obs, x_prd, y_prd, idx_obs, idx_prd + + n = 10; % number of observations + m = n + 1; % number of predictions + d = 1; % dimension of the input space + + x0 = (linspace (0, pi, n + m))'; + + idx_obs = (2:2:(n+m-1))'; + idx_prd = (1:2:(n+m))'; + + x_obs = x0(idx_obs); + z_obs = sin (x_obs); + x_prd = x0(idx_prd); + + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); +***** error y_prd = stk_predict (M_post); +***** test y_prd = stk_predict (M_post, x_prd); +***** error y_prd = stk_predict (M_post, [x_prd x_prd]); +***** test % nargout = 2 + [y_prd1, lambda] = stk_predict (M_post, x_prd); + assert (stk_isequal_tolrel (y_prd, y_prd1)); + assert (isequal (size (lambda), [n m])); +***** test % nargout = 3 + [y_prd1, lambda, mu] = stk_predict (M_post, x_prd); + assert (stk_isequal_tolrel (y_prd, y_prd1)); + assert (isequal (size (lambda), [n m])); + assert (isequal (size (mu), [1 m])); % ordinary kriging +***** test % nargout = 4 + [y_prd1, lambda, mu, K] = stk_predict (M_post, x_prd); + assert (stk_isequal_tolrel (y_prd, y_prd1)); + assert (isequal (size (lambda), [n m])); + assert (isequal (size (mu), [1 m])); % ordinary kriging + assert (isequal (size (K), [m m])); +***** test % nargout = 2, compute only variances + M_post1 = stk_model_gpposterior (M_prior, x_obs, []); + [y_prd_nan, lambda] = stk_predict (M_post1, x_prd); + assert (isequal (size (lambda), [n m])); + assert (all (isnan (y_prd_nan.mean))); +***** test % discrete model (prediction indices provided) + M_prior1 = stk_model (@stk_discretecov, M_prior, x0); + M_post1 = stk_model_gpposterior (M_prior1, idx_obs, z_obs); + y_prd1 = stk_predict (M_post1, idx_prd); + assert (stk_isequal_tolrel (y_prd, y_prd1)); +***** test % discrete model (prediction indices *not* provided) + M_prior1 = stk_model (@stk_discretecov, M_prior, x0); + M_post1 = stk_model_gpposterior (M_prior1, idx_obs, z_obs); + y_prd1 = stk_predict (M_post1, []); % predict them all! + assert (stk_isequal_tolrel (y_prd, y_prd1(idx_prd, :))); +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/model/@stk_model_gpposterior/set.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/set.m +***** shared M_post + x_obs = (linspace (0, pi, 15))'; + z_obs = sin (x_obs); + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); +***** error value = get (M_post, 1.33); +***** error value = get (M_post, 'dudule'); +***** test value = get (M_post, 'prior_model'); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/model/@stk_model_gpposterior/stk_model_gpposterior.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_model_gpposterior.m +***** test stk_test_class ('stk_model_gpposterior') +***** shared M_prior, x_obs, z_obs + x_obs = (linspace (0, pi, 15))'; + z_obs = sin (x_obs); + + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); +***** test M_post = stk_model_gpposterior (); +***** test M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); +***** error M_post = stk_model_gpposterior (M_prior, x_obs, [z_obs; z_obs]); +***** error M_post = stk_model_gpposterior (M_prior, x_obs, [z_obs; z_obs], 3.441); +***** test % hidden feature + kreq = stk_kreq_qr (M_prior, x_obs); + M_post = stk_model_gpposterior (M_prior, {x_obs, kreq}, z_obs); +***** test % NaNs in prior_model.param + DIM = 1; M = stk_model (@stk_materncov52_aniso, DIM); + M.param = nan (2, 1); % this is currently the default + x = stk_sampling_regulargrid (20, DIM, [0; 1]); + y = sin (double (x)); + zp = stk_predict (M, x, y, x); +7 tests, 7 passed, 0 known failure, 0 skipped +[inst/model/noise/@stk_gaussiannoise_het0/set.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/noise/@stk_gaussiannoise_het0/set.m +***** shared M_post + x_obs = (linspace (0, pi, 15))'; + z_obs = sin (x_obs); + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); +***** error value = get (M_post, 1.33); +***** error value = get (M_post, 'dudule'); +***** test value = get (M_post, 'prior_model'); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/model/prior_struct/stk_ortho_func.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_ortho_func.m +***** shared model, x, n, d + n = 15; d = 4; + model = stk_model (@stk_materncov_aniso, d); + x = stk_sampling_randunif (n, d); + model = rmfield (model, 'lm'); % Test the old .order approach +***** error P = stk_ortho_func (); +***** error P = stk_ortho_func (model); +***** test P = stk_ortho_func (model, x); ***** test - Qx = stk_gpquadform(x, [], rx); - assert(isequal(Qx, zeros(11))); + model.order = -1; P = stk_ortho_func (model, x); + assert (isequal (size (P), [n, 0])); ***** test - Qxx = stk_gpquadform(x, x, rx, rx); - assert(isequal(Qxx, zeros(11))); + model.order = 0; P = stk_ortho_func (model, x); + assert (isequal (size (P), [n, 1])); ***** test - Qxy = stk_gpquadform(x, y, rx, ry); - assert(isequal(Qxy, zeros(11, 13))); + model.order = 1; P = stk_ortho_func (model, x); + assert (isequal (size (P), [n, d + 1])); ***** test - Qzz = stk_gpquadform(z, [], rz); - assert(isequal(Qzz, zeros(7))); + model.order = 2; P = stk_ortho_func (model, x); + assert (isequal (size (P), [n, 1 + d * (d + 3) / 2])); ***** test - Qxz = stk_gpquadform(x, z, rx, rz); - assert(stk_isequal_tolabs(Qxz, 5 * ones(11, 7))); + model.order = 3; P = stk_ortho_func (model, x); + assert (isequal (size (P), [n, 1 + d * (11 + d * (6 + d)) / 6])); +***** error + model.order = 4; P = stk_ortho_func (model, x); + % model.order > 3 is not allowed +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/model/prior_struct/stk_covmat_noise.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_covmat_noise.m +***** shared model, model2, x1, x2, n1, n2, d, Ka, Kb, Kc, Pa, Pb, Pc, P1, P2, P3, K1, K2, K3 + n1 = 20; n2 = 10; d = 4; + model = stk_model (@stk_materncov52_aniso, d); + model.lm = stk_lm_affine; + model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); + model2 = model; model2.lognoisevariance = log(0.01); + x1 = stk_sampling_randunif (n1, d); + x2 = stk_sampling_randunif (n2, d); +***** error [KK, PP] = stk_covmat_noise (); +***** error [KK, PP] = stk_covmat_noise (model); +***** test [Ka, Pa] = stk_covmat_noise (model, x1); % (1) +***** test [K1, P1] = stk_covmat_noise (model, x1, []); +***** test [K2, P2] = stk_covmat_noise (model, x1, [], -1); +***** test [K3, P3] = stk_covmat_noise (model, x1, [], -1, false); +***** assert (isequal (size (Ka), [n1 n1])); +***** assert (isequal (size (Pa), [n1 0])); +***** assert (isequal (P1, Pa) && (isequal (K1, Ka))) +***** assert (isequal (P2, Pa) && (isequal (K2, Ka))) +***** assert (isequal (P3, Pa) && (isequal (K3, Ka))) +***** test [Kb, Pb] = stk_covmat_noise (model, x1, x1); % (2) +***** test [K1, P1] = stk_covmat_noise (model, x1, x1, -1); +***** test [K2, P2] = stk_covmat_noise (model, x1, x1, -1, false); +***** assert (isequal (size (Kb), [n1 n1])); +***** assert (isequal (size (Pb), [n1 0])); +***** assert (isequal (P1, Pb) && (isequal (K1, Kb))) +***** assert (isequal (P2, Pb) && (isequal (K2, Kb))) +***** test [Kc, Pc] = stk_covmat_noise (model, x1, x2); % (3) +***** test [K1, P1] = stk_covmat_noise (model, x1, x2, -1); +***** test [K2, P2] = stk_covmat_noise (model, x1, x2, -1, false); +***** assert (isequal (size (Kc), [n1 n2])); +***** assert (isequal (size (Pc), [n1 0])); +***** assert (isequal (P1, Pc) && (isequal (K1, Kc))) +***** assert (isequal (P2, Pc) && (isequal (K2, Kc))) +***** assert (isequal (Kb, Ka)); +***** test [Ka, Pa] = stk_covmat_noise (model2, x1); % (1') +***** test [Kb, Pb] = stk_covmat_noise (model2, x1, x1); % (2') +***** error assert (isequal (Kb, Ka)); +***** assert (isequal (Pa, Pb)); +***** assert (isequal (Pa, Pc)); +31 tests, 31 passed, 0 known failure, 0 skipped +[inst/model/prior_struct/stk_model.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_model.m +***** test model = stk_model (); +***** test model = stk_model (@stk_expcov_iso); +***** test model = stk_model (@stk_expcov_iso, 1); +***** test model = stk_model (@stk_expcov_iso, 3); +***** test model = stk_model (@stk_expcov_aniso); +***** test model = stk_model (@stk_expcov_aniso, 1); +***** test model = stk_model (@stk_expcov_aniso, 3); +***** test model = stk_model (@stk_materncov_iso); +***** test model = stk_model (@stk_materncov_iso, 1); +***** test model = stk_model (@stk_materncov_iso, 3); +***** test model = stk_model (@stk_materncov_aniso); +***** test model = stk_model (@stk_materncov_aniso, 1); +***** test model = stk_model (@stk_materncov_aniso, 3); +***** test model = stk_model (@stk_materncov32_iso); +***** test model = stk_model (@stk_materncov32_iso, 1); +***** test model = stk_model (@stk_materncov32_iso, 3); +***** test model = stk_model (@stk_materncov32_aniso); +***** test model = stk_model (@stk_materncov32_aniso, 1); +***** test model = stk_model (@stk_materncov32_aniso, 3); +***** test model = stk_model (@stk_materncov52_iso); +***** test model = stk_model (@stk_materncov52_iso, 1); +***** test model = stk_model (@stk_materncov52_iso, 3); +***** test model = stk_model (@stk_materncov52_aniso); +***** test model = stk_model (@stk_materncov52_aniso, 1); +***** test model = stk_model (@stk_materncov52_aniso, 3); +***** test model = stk_model (@stk_gausscov_iso); +***** test model = stk_model (@stk_gausscov_iso, 1); +***** test model = stk_model (@stk_gausscov_iso, 3); +***** test model = stk_model (@stk_gausscov_aniso); +***** test model = stk_model (@stk_gausscov_aniso, 1); +***** test model = stk_model (@stk_gausscov_aniso, 3); +***** test model = stk_model (@stk_sphcov_iso); +***** test model = stk_model (@stk_sphcov_iso, 1); +***** test model = stk_model (@stk_sphcov_iso, 3); +***** test model = stk_model (@stk_sphcov_aniso); +***** test model = stk_model (@stk_sphcov_aniso, 1); +***** test model = stk_model (@stk_sphcov_aniso, 3); +37 tests, 37 passed, 0 known failure, 0 skipped +[inst/core/stk_cholcov.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_cholcov.m +***** shared Q, K, L, U, epsi + Q = 0.25 * hadamard(4); +***** test + K = Q * diag ([1, 0.1, 0.01, 1e-7]) * Q'; + [U, epsi] = stk_cholcov (K); +***** assert (istriu (U)) +***** assert (epsi == 0) +***** test + K = Q * diag ([1, 0.1, 0.01, 1e-7]) * Q'; + [L, epsi] = stk_cholcov (K, 'lower'); +***** assert (istril (L)) +***** assert (epsi == 0) +***** test + K = Q * diag ([1, 0.1, 0.01, -1e-7]) * Q'; + [U, epsi] = stk_cholcov (K); +***** assert (istriu (U)) +***** assert (epsi > 0) +***** test + K = Q * diag ([1, 0.1, 0.01, -1e-7]) * Q'; + [L, epsi] = stk_cholcov (K, 'lower'); +***** assert (istril (L)) +***** assert (epsi > 0) +12 tests, 12 passed, 0 known failure, 0 skipped +[inst/core/stk_make_matcov.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_make_matcov.m +***** shared model, model2, x0, x1, n0, n1, d, Ka, Kb, Kc, Pa, Pb, Pc + n0 = 20; n1 = 10; d = 4; + model = stk_model (@stk_materncov52_aniso, d); + model.lm = stk_lm_affine; + model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); + model2 = model; model2.lognoisevariance = log(0.01); + x0 = stk_sampling_randunif (n0, d); + x1 = stk_sampling_randunif (n1, d); +***** error [KK, PP] = stk_make_matcov (); +***** error [KK, PP] = stk_make_matcov (model); +***** test [Ka, Pa] = stk_make_matcov (model, x0); % (1) +***** test [Kb, Pb] = stk_make_matcov (model, x0, x0); % (2) +***** test [Kc, Pc] = stk_make_matcov (model, x0, x1); % (3) +***** error [KK, PP] = stk_make_matcov (model, x0, x1, pi); +***** assert (isequal (size (Ka), [n0 n0])); +***** assert (isequal (size (Kb), [n0 n0])); +***** assert (isequal (size (Kc), [n0 n1])); +***** assert (isequal (size (Pa), [n0 d + 1])); +***** assert (isequal (size (Pb), [n0 d + 1])); +***** assert (isequal (size (Pc), [n0 d + 1])); +***** assert (isequal (Kb, Ka)); +***** test [Ka, Pa] = stk_make_matcov (model2, x0); % (1') +***** test [Kb, Pb] = stk_make_matcov (model2, x0, x0); % (2') +***** error assert (isequal (Kb, Ka)); +***** assert (isequal (Pa, Pb)); +***** assert (isequal (Pa, Pc)); +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/core/stk_model_update.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_model_update.m ***** test - x = randn(5, 3); rx = 1 + rand(5, 3); - y = randn(5, 3); ry = 1 + rand(5, 3); - Q1 = stk_gpquadform(x, y, rx, ry, true); % pairwise - Q2 = stk_gpquadform(x, y, rx, ry, false); - assert(isequal(size(Q1), [5 1])); - assert(isequal(size(Q2), [5 5])); - assert(stk_isequal_tolabs(Q1, diag(Q2))); + x1 = (linspace (0, 1, 15))'; z1 = sin (x1); + x2 = (linspace (2, 3, 15))'; z2 = sin (x2); + xt = (linspace (1, 2, 15))'; zt = sin (xt); + + % Prior model + M0 = stk_model (@stk_materncov32_iso); + M0.param = log ([1.0; 2.1]); + + M1 = stk_model_update (M0, x1, z1); + M1 = stk_model_update (M1, x2, z2); % this calls @stk_model_gpposterior/... + zp1 = stk_predict (M1, xt); + + M2 = stk_model_gpposterior (M0, [x1; x2], [z1; z2]); + zp2 = stk_predict (M2, xt); + + assert (stk_isequal_tolabs (double (zp2 - zp1), zeros (15, 2), 1e-10)) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/core/@stk_kreq_qr/stk_kreq_qr.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/@stk_kreq_qr/stk_kreq_qr.m +***** test stk_test_class ('stk_kreq_qr') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/core/stk_predict_leaveoneout.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_predict_leaveoneout.m +***** shared n, x_obs, z_obs, model + n = 20; + x_obs = stk_sampling_regulargrid (n, 1, [0; 2*pi]); + z_obs = stk_feval (@sin, x_obs); + model = stk_model (@stk_materncov32_iso); + model.param = log ([1; 5]); +***** test % one output + + loo_pred = stk_predict_leaveoneout (model, x_obs, z_obs); + + assert (isequal (size (loo_pred), [n 2])); + assert (isequal (loo_pred.colnames, {'mean', 'var'})); + assert (all (isfinite (loo_pred(:)))); +***** test % two outputs + + [loo_pred, loo_res] = stk_predict_leaveoneout (model, x_obs, z_obs); + + assert (isequal (size (loo_pred), [n 2])); + assert (isequal (loo_pred.colnames, {'mean', 'var'})); + assert (all (isfinite (loo_pred(:)))); + + assert (isequal (size (loo_res), [n 2])); + assert (isequal (loo_res.colnames, {'residuals', 'norm_res'})); + assert (all (isfinite (loo_res(:)))); +***** test % heteroscedastic noise case + + model.lognoisevariance = (1 + rand (n, 1)) * 1e-6; + [loo_pred, loo_res] = stk_predict_leaveoneout (model, x_obs, z_obs); + + assert (isequal (size (loo_pred), [n 2])); + assert (isequal (loo_pred.colnames, {'mean', 'var'})); + assert (all (isfinite (loo_pred(:)))); + + assert (isequal (size (loo_res), [n 2])); + assert (isequal (loo_res.colnames, {'residuals', 'norm_res'})); + assert (all (isfinite (loo_res(:)))); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/core/stk_predict.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_predict.m +***** shared n, m, model, x0, x_obs, z_obs, x_prd, y_prd1, idx_obs, idx_prd + + n = 10; % number of observations + m = n + 1; % number of predictions + d = 1; % dimension of the input space + + x0 = stk_sampling_regulargrid(n+m, d, [0; pi]); + + idx_obs = (2:2:(n+m-1))'; + idx_prd = (1:2:(n+m))'; + + x_obs = x0(idx_obs); + z_obs = sin (double (x_obs)); + x_prd = x0(idx_prd); + + model = stk_model (@stk_materncov32_iso); + model.param = log ([1.0; 2.1]); +***** error y_prd1 = stk_predict (); +***** error y_prd1 = stk_predict (model); +***** test y_prd1 = stk_predict (model, x_prd); +***** error y_prd1 = stk_predict (model, data, x_prd); +***** test y_prd1 = stk_predict (model, x_obs, z_obs, x_prd); +***** error y_prd1 = stk_predict (model, [x_obs; x_obs], [z_obs; z_obs], x_prd); +***** test % nargout = 2 + [y_prd1, lambda] = stk_predict (model, x_obs, z_obs, x_prd); + assert (isequal (size (lambda), [n m])); +***** test % nargout = 2, compute only variances + [y_prd1, lambda] = stk_predict (model, x_obs, [], x_prd); + assert (isequal (size (lambda), [n m])); + assert (all (isnan (y_prd1.mean))); +***** test % nargout = 3 + [y_prd1, lambda, mu] = stk_predict (model, x_obs, z_obs, x_prd); + assert (isequal (size (lambda), [n m])); + assert (isequal (size (mu), [1 m])); % ordinary kriging +***** test % nargout = 4 + [y_prd1, lambda, mu, K] = stk_predict (model, x_obs, z_obs, x_prd); + assert (isequal (size (lambda), [n m])); + assert (isequal (size (mu), [1 m])); % ordinary kriging + assert (isequal (size (K), [m m])); +***** test % predict on large set of locations + x_prd = stk_sampling_regulargrid (1e5, 1, [0; pi]); + y_prd = stk_predict (model, x_obs, z_obs, x_prd); +***** test % predict on an observation point + % https://sourceforge.net/p/kriging/tickets/49/ + [zp, lambda] = stk_predict (model, x_obs, z_obs, x_obs(4)); + assert (isequal (z_obs(4), zp.mean)) + assert (isequal (zp.var, 0)) + lambda_ref = zeros (n, 1); lambda_ref(4) = 1; + assert (isequal (lambda, lambda_ref)) +12 tests, 12 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampcrit_akg_eval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_akg_eval.m +***** shared zc_mean, zc_std, zr_mean, zr_std, zcr_cov, AKG, nc + xi = [0; 0.2; 0.7; 0.9]; + zi = [1; 0.9; 0.6; 0.1] - 10; + ni = 4; + + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + M_prior.lognoisevariance = 0.678; + + nc = 20; + xc = stk_sampling_regulargrid (nc, 1, [0; 1]); + [zp, ~, ~, K] = stk_predict (M_prior, xi, zi, [xi; xc]); + + ir = 1:ni; ic = ni + (1:nc); + + zc_mean = zp.mean(ic); + zc_std = sqrt (zp.var(ic)); + + % reference grid: current evaluation points ("KGCP") + zr_mean = zp.mean(ir); + zr_std = sqrt (zp.var(ir)); + + zcr_cov = K(ic, ir); +***** test AKG = stk_sampcrit_akg_eval (zc_mean, zc_std, zr_mean, zr_std, zcr_cov); +***** assert (isequal (size (AKG), [nc 1])) +***** assert (all (AKG >= 0)) +***** error AKG = stk_sampcrit_akg_eval (zc_mean, zc_std, zr_mean, zr_std); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_vdc_rr2.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_vdc_rr2.m +***** error __stk_sampling_vdc_rr2__() % two inputs required +***** error __stk_sampling_vdc_rr2__(10) % two inputs required +***** error __stk_sampling_vdc_rr2__(10, 3, -1) % two inputs required +***** test + n = 300; j = 25; + x = __stk_sampling_vdc_rr2__(n, j); + assert(isequal(size(x), [n 1])) ***** test - x = randn(5, 3); rx = 1 + rand(5, 3); - Q1 = stk_gpquadform(x, [], rx, [], true); % pairwise - assert(stk_isequal_tolabs(Q1, zeros(5, 1))); - Q1 = stk_gpquadform(x, x, rx, rx, true); % pairwise - assert(stk_isequal_tolabs(Q1, zeros(5, 1))); -***** shared x, y, z, rx, ry, rz - x = zeros (11, 5); rx = 2 * ones (11, 5); - y = zeros (13, 5); ry = 2 * ones (13, 5); - z = ones ( 7, 5); rz = 2 * ones ( 7, 5); + x = __stk_sampling_vdc_rr2__(2000, 7); + y = double (x(1998:2000, :)); + yref = [0.849786281294525; 0.085080398941584; 0.555668634235701]; + assert(stk_isequal_tolrel(y, yref, 1e-13)); +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampcrit_ei_eval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_ei_eval.m +***** error EI = stk_sampcrit_ei_eval () % not enough args +***** error EI = stk_sampcrit_ei_eval (0) % not enough args +***** shared xi, zi, M_prior, xt, zp, EIref, EI1, EI2, EI3 + xi = [0; 0.2; 0.7; 0.9]; + zi = [1; 0.9; 0.6; 0.1]; + M_prior = stk_model (@stk_materncov32_iso); + M_prior.param = log ([1.0; 2.1]); + xt = stk_sampling_regulargrid (20, 1, [0; 1]); + zp = stk_predict (M_prior, xi, zi, xt); + EIref = stk_distrib_normal_ei (min (zi), zp.mean, sqrt (zp.var), true); +***** test % Current syntax (STK 2.4.1 and later) + EI1 = stk_sampcrit_ei_eval (zp.mean, sqrt (zp.var), min (zi)); +***** assert (isequal (EI1, EIref)) +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_regulargrid.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_regulargrid.m +***** shared x, n, dim, box + n = 9; dim = 2; box = [0, 0; 1, 1]; +***** error x = stk_sampling_regulargrid (); +***** test x = stk_sampling_regulargrid (n); +***** test x = stk_sampling_regulargrid (n, dim); +***** test x = stk_sampling_regulargrid (n, dim, box); +***** assert (isa (x, 'stk_dataframe')); +***** assert (isa (x, 'stk_factorialdesign')); +***** assert (isequal (x.colnames, {})); ***** test - Qx = stk_gpquadform(x, [], rx); - assert(isequal(Qx, zeros(11))); + cn = {'W', 'H'}; box = stk_hrect (box, cn); + x = stk_sampling_regulargrid (n, dim, box); + assert (isequal (x.colnames, cn)); ***** test - Qxx = stk_gpquadform(x, x, rx, rx); - assert(isequal(Qxx, zeros(11))); + for dim = 1:3, + n = 3^dim; + x = stk_sampling_regulargrid(n, dim); + assert(isequal(size(x), [n dim])); + u = double(x); u = u(:); + assert(~any(isnan(u) | isinf(u))); + assert((min(u) >= 0) && (max(u) <= 1)); + end ***** test - Qxy = stk_gpquadform(x, y, rx, ry); - assert(isequal(Qxy, zeros(11, 13))); + nn = [3 4 5]; + for dim = 1:3, + x = stk_sampling_regulargrid(nn(1:dim), dim); + assert(isequal(size(x), [prod(nn(1:dim)) dim])); + u = double(x); u = u(:); + assert(~any(isnan(u) | isinf(u))); + assert((min(u) >= 0) && (max(u) <= 1)); + end +10 tests, 10 passed, 0 known failure, 0 skipped +[inst/sampling/stk_halfpintl.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_halfpintl.m +***** test % case #1 + a = 1; + b = 1; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (a_out == 1) + assert (b_out == 1) + assert (isempty (z_out)) +***** test % case #2: two lines, slopes not equal, already sorted + a = [1; -1]; + b = [0; 2]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +***** test % case #3: same as #2, but not sorted + a = [-1; 1]; + b = [ 2; 0]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +***** test % case #4: two lines, equal slopes, already sorted + a = [0; 0]; + b = [1; 2]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (a_out == 0) + assert (b_out == 1) + assert (isempty (z_out)) +***** test % case #5: same as #4, but not sorted + a = [0; 0]; + b = [2; 1]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (a_out == 0) + assert (b_out == 1) + assert (isempty (z_out)) +***** test % case #6: add a dominated line to #2 (the result does not change) + a = [1; -1; 0]; + b = [0; 2; 1]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +***** test % case #7: permutation of #6 + a = [1; 0; -1]; + b = [0; 1; 2]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +***** test % case #8: another permutation of #6 + a = [0; 1; -1]; + b = [1; 0; 2]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +***** test % case #9: same as #8, with some duplicated lines added + a = [0; 1; 0; -1; 0; -1; 1]; + b = [1; 0; 1; 2; 1; 2; 0]; + [a_out, b_out, z_out] = stk_halfpintl (a, b); + assert (isequal (a_out, [1; -1])) + assert (isequal (b_out, [0; 2])) + assert (z_out == 1) +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/sampling/@stk_sampcrit_ei/stk_sampcrit_ei.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_ei/stk_sampcrit_ei.m +***** shared F, M, EI + M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); +warning: Something went wrong during the optimization +crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt +***** test F = stk_sampcrit_ei () % ending ";" omitted on purpose, to test disp + +F = +| +| model: -- (not instantiated) +| current_minimum: Inf +| + +***** assert (isempty (F.model)) +***** assert (isempty (get (F, 'model'))) +***** assert (F.current_minimum == +inf) +***** assert (get (F, 'current_minimum') == +inf) +***** error F.toto +***** error get (F, 'toto') +***** error F.current_min = 1.234; % read-only +***** error F = set (F, 'current_min', 1.234); % read-only +***** error F.toto = 1.234; % field does not exist +***** error F = set (F, 'toto', 1.234); % field does not exist +***** error EI = feval (F, 1.0); +***** test F = stk_sampcrit_ei (); F.model = M; + assert (~ isempty (F.model)); +***** test F = stk_sampcrit_ei (); F = set (F, 'model', M); + assert (~ isempty (F.model)); +***** test F.model = []; % remove model + assert (isempty (F.model)); + assert (F.current_minimum == +inf); +***** test F = stk_sampcrit_ei (M) % ending ";" omitted on purpose, to test disp + +F = +| +| model: +| current_minimum: 1.234 +| + +***** assert (isequal (F.model, M)) +***** assert (F.current_minimum == 1.234); +***** test EI = feval (F, [1.0; 1.1; 1.2]); +***** assert (isequal (size (EI), [3 1])) +***** assert (all (EI >= 0)) +***** shared F +***** test F = stk_sampcrit_ei (stk_model ()); +***** assert (F.current_minimum == +inf); +***** error feval (F, 1.0); +24 tests, 24 passed, 0 known failure, 0 skipped +[inst/sampling/@stk_function/stk_function.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_function/stk_function.m +***** shared F +***** test F = stk_function () % ending ";" omitted on purpose, to test disp + +F = + +***** error [F F]; % arrays of sampling criterion objects are not supported +***** error [F; F]; % idem +***** error get (F, 'toto'); % field does not exist +***** error y = feval (F, 1.0); % not implemented for "pure" function objects +***** error dummy = F{2}; % illegal indexing +***** error dummy = F(1.0); % feval not implemented +***** error dummy = F.toto; % field does not exist +***** error F{2} = 1.234; % illegal indexing +***** error F(5) = 1.234; % illegal indexing +***** error F.toto = 1.234; % field does not exist +11 tests, 11 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_randunif.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_randunif.m +***** shared x, n, dim, box + n = 10; dim = 2; box = [0, 0; 2, 2]; +***** error x = stk_sampling_randunif (); +***** test x = stk_sampling_randunif (n); +***** test x = stk_sampling_randunif (n, dim); +***** test x = stk_sampling_randunif (n, dim, box); +***** assert (isa(x, 'stk_dataframe')); +***** assert (isequal (x.colnames, {})); ***** test - Qzz = stk_gpquadform(z, [], rz); - assert(isequal(Qzz, zeros(7))); + cn = {'W', 'H'}; box = stk_hrect (box, cn); + x = stk_sampling_randunif (n, dim, box); + assert (isequal (x.colnames, cn)); ***** test - Qxz = stk_gpquadform(x, z, rx, rz); - assert(stk_isequal_tolabs(Qxz, 5/8 * ones(11, 7))); -17 tests, 17 passed, 0 known failure, 0 skipped -[inst/misc/dist/stk_filldist_discretized.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist_discretized.m -***** error stk_filldist_discretized(0.0) % incorrect nb of arguments -***** error stk_filldist_discretized(0.0, []) % second arg is empty -***** error stk_filldist_discretized([], 0.0) % first arg is empty + for dim = 1:5, + x = stk_sampling_randunif(n, dim); + assert(isequal(size(x), [n dim])); + u = double(x); u = u(:); + assert(~any(isnan(u) | isinf(u))); + assert((min(u) >= 0) && (max(u) <= 1)); + end +8 tests, 8 passed, 0 known failure, 0 skipped +[inst/sampling/@stk_sampcrit_eqi/stk_sampcrit_eqi.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_eqi/stk_sampcrit_eqi.m +***** shared F, M, EQI + M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); +warning: Something went wrong during the optimization +crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt +***** test F = stk_sampcrit_eqi () % ending ";" omitted on purpose, to test disp + +F = +| +| model: -- (not instantiated) +| quantile_order: 0.5 +| point_batch_size: 1 +| current_minimum: Inf +| + +***** assert (isempty (F.model)) +***** assert (isempty (get (F, 'model'))) +***** assert (F.quantile_order == 0.5) +***** assert (get (F, 'quantile_order') == 0.5) +***** assert (F.current_minimum == +inf) +***** assert (get (F, 'current_minimum') == +inf) +***** error F.toto +***** error get (F, 'toto') +***** error F.current_min = 1.234; % read-only +***** error F = set (F, 'current_min', 1.234); % read-only +***** error F.toto = 1.234; % field does not exist +***** error F = set (F, 'toto', 1.234); % field does not exist +***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) +***** test F = set (F, 'quantile_order', 0.8); assert (F.quantile_order == 0.8) +***** error F.quantile_order = 1.1; +***** error F.quantile_order = -0.1; +***** error F.quantile_order = [1 2]; +***** error F.current_minimum = 3.333; % read-only +***** error F.quantile_value = 2.222; % read-only +***** error EQI = feval (F, 1.0); +***** test F = stk_sampcrit_eqi (); F.model = M; + assert (~ isempty (F.model)); +***** test F = stk_sampcrit_eqi (); F = set (F, 'model', M); + assert (~ isempty (F.model)); +***** test F.model = []; % remove model + assert (isempty (F.model)); + assert (F.current_minimum == +inf); +***** test F = stk_sampcrit_eqi (M) % ending ";" omitted on purpose, to test disp + +F = +| +| model: +| quantile_order: 0.5 +| point_batch_size: 1 +| current_minimum: 1.234 +| + +***** assert (isequal (F.model, M)) +***** assert (stk_isequal_tolrel (F.current_minimum, 1.234, 10 * eps)); +***** test EQI = feval (F, [1.0; 1.1; 1.2]); +***** assert (isequal (size (EQI), [3 1])) +***** assert (all (EQI >= 0)) +***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) +***** shared F, M, EQI + prior_model = stk_model (); + prior_model.lognoisevariance = 0.678; + M = stk_model_gpposterior (prior_model, [1 2 3]', [1.234 3 2]'); +***** test F = stk_sampcrit_eqi (M); +***** assert (isequal (F.model, M)) +***** assert (stk_isequal_tolrel (F.current_minimum, 2.077997, 1e-5)); +***** test EQI = feval (F, [1.0; 1.1; 1.2]); +***** assert (isequal (size (EQI), [3 1])) +***** assert (all (EQI >= 0)) +***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) +***** shared F +***** test F = stk_sampcrit_eqi (stk_model ()); +***** assert (F.current_minimum == +inf); +***** error feval (F, 1.0); +***** shared F, M + M = stk_model_gpposterior (stk_model (), [1 2 3]', [1.234 3 2]'); +warning: Something went wrong during the optimization +crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt +***** error F = stk_sampcrit_eqi (M, [], 0); +***** error F = stk_sampcrit_eqi (M, [], 1.5); +***** error F = stk_sampcrit_eqi (M, [], nan); +***** error F = stk_sampcrit_eqi (M, [], [10 20]); +***** test F = stk_sampcrit_eqi (M, [], 10); +***** assert (isequal (F.quantile_order, 0.5)); +***** assert (isequal (F.point_batch_size, 10)); +***** error F = stk_sampcrit_eqi (M, 0.8, 0); +***** error F = stk_sampcrit_eqi (M, 0.8, 1.5); +***** error F = stk_sampcrit_eqi (M, 0.8, nan); +***** error F = stk_sampcrit_eqi (M, 0.8, [10 20]); +***** test F = stk_sampcrit_eqi (M, 0.8, 5); +***** assert (isequal (F.quantile_order, 0.8)); +***** assert (isequal (F.point_batch_size, 5)); +***** shared F, M, EQI + prior_model = stk_model (); + prior_model.lognoisevariance = 0.678; + M = stk_model_gpposterior (prior_model, [1 2 3]', [1.234 3 2]'); + F = stk_sampcrit_eqi (M); +***** test F.point_batch_size = 10; % numeric +***** assert (isequal (F.point_batch_size, 10)) +***** test EQI = feval (F, [1.0; 1.1; 1.2]); +***** test F.point_batch_size = @(x, n) 100 - n; % function handle +***** assert (isa (F.point_batch_size, 'function_handle')) +***** test EQI = feval (F, [1.0; 1.1; 1.2]); +***** test F.point_batch_size = 'sin'; % char +***** assert (isa (F.point_batch_size, 'function_handle')) +63 tests, 63 passed, 0 known failure, 0 skipped +[inst/sampling/@stk_sampcrit_akg/stk_sampcrit_akg.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_akg/stk_sampcrit_akg.m +***** shared F, M, AKG + M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); +warning: Something went wrong during the optimization +crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt +***** test F = stk_sampcrit_akg () % ending ";" omitted on purpose, to test disp + +F = +| +| model: -- (not instantiated) +| reference_grid: -- (use current evaluation points) +| + +***** assert (isempty (F.model)) +***** assert (isempty (get (F, 'model'))) +***** assert (isempty (F.reference_grid)) +***** assert (isempty (get (F, 'reference_grid'))) +***** error F.toto +***** error get (F, 'toto') +***** error F.toto = 1.234; % field does not exist +***** error F = set (F, 'toto', 1.234); % field does not exist +***** error AKG = feval (F, 1.0); +***** test F = stk_sampcrit_akg (); F.model = M; + assert (isequal (F.model, M)); +***** test F = stk_sampcrit_akg (); F = set (F, 'model', M); + assert (isequal (F.model, M)); + assert (isequal (size (F.zr_mean), [3 1])) % n x 1 + assert (isequal (size (F.zr_std), [3 1])) % n x 1 + assert (isequal (size (F.zr_lambdamu), [4 3])) % (n+1) x n (constant mean) +***** test F.model = []; % remove model + assert (isempty (F.model)); + assert (isempty (F.zr_mean)) + assert (isempty (F.zr_std)) + assert (isempty (F.zr_lambdamu)) +***** test xr = [1 1.5 2 2.5 3]'; + F.reference_grid = xr % ending ";" omitted on purpose, to test disp + assert (isequal (F.reference_grid, xr)) + assert (isempty (F.zr_mean)) + assert (isempty (F.zr_std)) + assert (isempty (F.zr_lambdamu)) + +F = +| +| model: -- (not instantiated) +| reference_grid: <5x1 double array> +| + +***** test F.reference_grid = []; + assert (isempty (F.reference_grid)) +***** test F = stk_sampcrit_akg (); F.model = M; + assert (isequal (F.model, M)); + xr = [1 1.5 2 2.5 3]'; + F.reference_grid = xr % ending ";" omitted on purpose, to test disp + assert (isequal (F.reference_grid, xr)) + assert (isequal (size (F.zr_mean), [5 1])) % nr x 1 + assert (isequal (size (F.zr_std), [5 1])) % nr x 1 + assert (isequal (size (F.zr_lambdamu), [4 5])) % (n+1) x nr (constant mean) + +F = +| +| model: +| reference_grid: <5x1 double array> +| + +***** test F.reference_grid = []; + assert (isempty (F.reference_grid)) +***** test F = stk_sampcrit_akg (M) % ending ";" omitted on purpose, to test disp + +F = +| +| model: +| reference_grid: -- (use current evaluation points) +| + +***** assert (isequal (F.model, M)) +***** test AKG = feval (F, [1.0; 1.1; 1.2]); +***** assert (isequal (size (AKG), [3 1])) +***** assert (all (AKG >= 0)) +***** test [AKG2, zp] = feval (F, [1.0; 1.1; 1.2]); + assert (isequal (AKG2, AKG)); + assert (isa (zp, 'stk_dataframe') && isequal (size (zp), [3 2])) +***** shared F, xr + xr = [1 1.5 2 2.5 3]'; +***** test F = stk_sampcrit_akg (stk_model ()); +***** assert (isempty (F.reference_grid)) +***** test F.reference_grid = xr; +***** assert (isequal (F.reference_grid, xr)) +***** assert (isempty (F.zr_mean)) +***** assert (isempty (F.zr_std)) +***** assert (isempty (F.zr_lambdamu)) +***** error AKG = feval (F, 1.0); +***** shared F, M, xr + xr = [1 1.5 2 2.5 3]'; + M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); +warning: Something went wrong during the optimization +crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt +***** test F = stk_sampcrit_akg (M, xr); +***** assert (isequal (F.model, M)) +***** assert (isequal (F.reference_grid, xr)) +***** assert (isequal (size (F.zr_mean), [5 1])) % nr x 1 +***** assert (isequal (size (F.zr_std), [5 1])) % nr x 1 +***** assert (isequal (size (F.zr_lambdamu), [4 5])) % (n+1) x nr (constant mean) +37 tests, 37 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_nestedlhs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_nestedlhs.m +***** shared x, n, dim, box, niter, levels + n = [48; 12; 4; 2]; dim = 2; box = [0, 0; 4, 4]; niter = 10; + levels = [10.1; 15.2; -9.3; 2.4; 17.5]; +***** error x = stk_sampling_nestedlhs (); +***** test x = stk_sampling_nestedlhs (n); +***** test x = stk_sampling_nestedlhs (n, dim); +***** test x = stk_sampling_nestedlhs (n, dim, box); +***** test x = stk_sampling_nestedlhs (n, dim, box, niter); +***** test x = stk_sampling_nestedlhs (n, dim, box, niter, levels); +***** assert ( isequal(size(x), [sum(n), dim + 1]) ); +***** assert ( isa(x, 'stk_dataframe') ); + cn = [0; cumsum(n)]; + for lev = 1:length(n), + y = x( (cn(lev) + 1):(cn(lev + 1)), 1:dim ); + assert (isequal (size (y), [n(lev) dim])); + assert (stk_is_lhs (y, n(lev), dim, box)); + if lev > 1 + assert ( isequal(z((end - n(lev) + 1):end, :), y) ); + end + z = y; + end +***** assert (isequal (x.colnames{dim + 1}, 'Level')); + levels = stk_dataframe(levels, {'t'}); + box = stk_hrect(box, {'x1', 'x2', 'x3', 'x4'}); +***** test x = stk_sampling_nestedlhs (n, [], box, [], levels); +***** assert (isequal(x.colnames, {'x1', 'x2', 'x3', 'x4', 't'}) ); +11 tests, 11 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_randomlhs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_randomlhs.m +***** shared x, n, dim, box + n = 10; dim = 2; box = [0, 0; 1, 1]; +***** error x = stk_sampling_randomlhs (); +***** test x = stk_sampling_randomlhs (n); +***** test x = stk_sampling_randomlhs (n, dim); +***** test x = stk_sampling_randomlhs (n, dim, box); +***** assert (isa(x, 'stk_dataframe')); +***** assert (isequal (x.colnames, {})); ***** test - d = 3; x = rand(7, d); y = rand(20, d); - fd1 = stk_filldist_discretized(x, y); - fd2 = stk_filldist_discretized(stk_dataframe(x), stk_dataframe(y)); - assert(stk_isequal_tolabs(fd1, fd2)); + cn = {'W', 'H'}; box = stk_hrect (box, cn); + x = stk_sampling_randomlhs (n, dim, box); + assert (isequal (x.colnames, cn)); ***** test - n = 5; - for dim = 1:10, - x = rand(n, dim); - fd = stk_filldist_discretized(x, x); - assert(stk_isequal_tolabs(fd, 0.0)); + for dim = 1:5, + x = stk_sampling_randomlhs(n, dim); + assert(isequal(size(x), [n dim])); + u = double(x); u = u(:); + assert(~any(isnan(u) | isinf(u))); + assert((min(u) >= 0) && (max(u) <= 1)); + assert(stk_is_lhs(x, n, dim)); end +8 tests, 8 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_halton_rr2.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_halton_rr2.m +***** error stk_sampling_halton_rr2 () % nargin < 1 ***** test - for dim = 1:10, - x = rand(1, dim); - y = rand(1, dim); - fd = stk_filldist_discretized(x, y); - assert(stk_isequal_tolabs(fd, norm(x - y))); + n = 300; d = 25; + x = stk_sampling_halton_rr2 (n, d); + assert (isequal (size (x), [n d])) +***** test + x = stk_sampling_halton_rr2 (1000, 3); + y = double (x(end, :)); + yref = [0.9052734375 0.028349336991312 0.74848]; + assert (stk_isequal_tolrel (y, yref, 1e-13)); +***** test + dim = 2; box = stk_hrect (dim); + x = stk_sampling_halton_rr2 (5, dim, box); + assert (isequal (x.colnames, {})); +***** test + dim = 2; cn = {'W', 'H'}; box = stk_hrect (dim, cn); + x = stk_sampling_halton_rr2 (5, dim, box); + assert (isequal (x.colnames, cn)); +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_maximinlhs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_maximinlhs.m +***** shared x, n, dim, box, niter + n = 20; dim = 2; box = [0, 0; 1, 1]; niter = 1; +***** error x = stk_sampling_maximinlhs (); +***** test x = stk_sampling_maximinlhs (n); +***** test x = stk_sampling_maximinlhs (n, dim); +***** test x = stk_sampling_maximinlhs (n, dim, box); +***** test x = stk_sampling_maximinlhs (n, dim, box, niter); +***** assert (isa (x, 'stk_dataframe')); +***** assert (isequal (x.colnames, {})); +***** test + cn = {'W', 'H'}; box = stk_hrect (box, cn); + x = stk_sampling_maximinlhs (n, dim, box); + assert (isequal (x.colnames, cn)); +***** test + for dim = 1:5, + x = stk_sampling_randomlhs (n, dim); + assert (isequal (size (x), [n dim])); + u = double (x); u = u(:); + assert (~ any (isnan (u) | isinf (u))); + assert ((min (u) >= 0) && (max (u) <= 1)); + assert (stk_is_lhs (x, n, dim)); end +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_olhs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_olhs.m +***** shared x, n, d, box, permut + n = 5; d = 2; box = [0 0; 1, 1]; permut = 1:2; +***** error x = stk_sampling_olhs(); +***** test x = stk_sampling_olhs(n); +***** test x = stk_sampling_olhs(n, d); +***** test x = stk_sampling_olhs(n, d, box); +***** test x = stk_sampling_olhs(n, d, box, permut); +***** error x = stk_sampling_olhs(n, d, box, permut, pi); +***** assert (isa (x, 'stk_dataframe')); +***** assert (isequal (x.colnames, {})); ***** test - n = 4; - for dim = 2:10, - x = zeros(n, dim); - y = rand(1, dim); - fd = stk_filldist_discretized(x, y); - assert(stk_isequal_tolabs(fd, max(stk_dist(x, y)))); + cn = {'W', 'H'}; box = stk_hrect (box, cn); + x = stk_sampling_olhs (n, d, box); + assert (isequal (x.colnames, cn)); +***** test + for r = 1:5 + + n = 2 ^ (r + 1) + 1; d = 2 * r; + x = stk_sampling_olhs (n, d); + + assert (isequal (size (x), [n d])); + + box = repmat ([-1; 1], 1, d); + assert (stk_is_lhs (x, n, d, box)); + + x = double (x); w = x' * x; + assert (stk_isequal_tolabs (w / w(1,1), eye (d))); + + end +10 tests, 10 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampcrit_ehvi_eval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_ehvi_eval.m +***** shared zr, zi + zr = [1 1]; + zi = [0.25 0.75; 0.5 0.5; 0.75 0.25]; +***** test % no improvement (1 computation) + zp_mean = [0.6 0.6]; zp_std = [0 0]; + EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); + assert (stk_isequal_tolabs (EHVI, 0, 1e-12)); +***** test % guaranteed improvement (1 computation) + zp_mean = [0 0]; zp_std = [0 0]; + EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); + assert (stk_isequal_tolabs (EHVI, 10 * 0.25 ^ 2)); +***** test % no improvement again (2 computations) + zp_mean = [0.5 0.5; 0.6 0.6]; zp_std = [0 0; 0 0]; + EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); + assert (stk_isequal_tolabs (EHVI, [0; 0], 1e-12)); +***** test % no observation -> EHVI wrt zr + zp_mean = [0.6 0.6]; zp_std = 0.01 * [1 1]; zi = []; + EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); + assert (stk_isequal_tolabs (EHVI, (1 - 0.6)^2, 1e-12)); +***** test % no observation below zr -> EHVI wrt zr + zp_mean = [0.6 0.6]; zp_std = 0.01 * [1 1]; zi = [2 2]; + EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); + assert (stk_isequal_tolabs (EHVI, (1 - 0.6)^2, 1e-12)); +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/sampling/stk_sampling_nesteddesign.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_nesteddesign.m +***** shared x, n, dim, box, niter, levels + n = [23; 14; 5; 2]; dim = 2; box = [0, 0; 4, 4]; niter = 10; + levels = [10.1; 15.2; -9.3; 2.4; 17.5]; +***** error x = stk_sampling_nesteddesign (); +***** test x = stk_sampling_nesteddesign (n); +***** test x = stk_sampling_nesteddesign (n, dim); +***** test x = stk_sampling_nesteddesign (n, dim, box); +***** test x = stk_sampling_nesteddesign (n, dim, box, niter); +***** test x = stk_sampling_nesteddesign (n, dim, box, niter, levels); +***** assert ( isequal(size(x), [sum(n), dim + 1]) ); +***** assert ( isa(x, 'stk_dataframe') ); + cn = [0; cumsum(n)]; + for lev = 1:length(n), + y = x( (cn(lev) + 1):(cn(lev + 1)), 1:dim ); + assert (isequal (size (y), [n(lev) dim])); + if lev > 1 + assert ( isequal(z((end - n(lev) + 1):end, :), y) ); + end + if lev == length(n) + assert (stk_is_lhs (y, n(lev), dim, box)); + end + z = y; end +***** assert (isequal (x.colnames{dim + 1}, 'Level')); + levels = stk_dataframe(levels, {'t'}); + box = stk_hrect(box, {'x1', 'x2', 'x3', 'x4'}); +***** test x = stk_sampling_nesteddesign (n, [], box, [], levels); +***** assert (isequal(x.colnames, {'x1', 'x2', 'x3', 'x4', 't'}) ); +11 tests, 11 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_gausscov_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_gausscov_aniso.m +***** shared param, x, y, K1, K2, K3 + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (6, dim); +***** error K0 = stk_gausscov_aniso (); +***** error K0 = stk_gausscov_aniso (param); +***** error K0 = stk_gausscov_aniso (param, x); +***** test K1 = stk_gausscov_aniso (param, x, y); +***** test K2 = stk_gausscov_aniso (param, x, y, -1); +***** test K3 = stk_gausscov_aniso (param, x, y, -1, false); +***** assert (isequal (K1, K2)); +***** assert (isequal (K1, K3)); +***** test % df versus ordinary array + u = double (x); v = double (y); + K1 = stk_gausscov_aniso (param, u, v, -1); + K2 = stk_gausscov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); +***** error stk_gausscov_aniso (param, x, y, -2); +***** test stk_gausscov_aniso (param, x, y, -1); +***** error stk_gausscov_aniso (param, x, y, 0); +***** test stk_gausscov_aniso (param, x, y, 1); +***** test stk_gausscov_aniso (param, x, y, 2); +***** error stk_gausscov_aniso (param, x, y, 3); +***** error stk_gausscov_aniso (param, x, y, nan); +***** error stk_gausscov_aniso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5; 2.4; 2.6]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - for dim = [1 3 6], - x = 0.5 * ones(1, dim); - y = stk_sampling_regulargrid(2^dim, dim); % [0; 1]^d is the default box - fd = stk_filldist_discretized(x, y); - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + K1 = stk_gausscov_aniso (param, x, y); + K2 = stk_gausscov_aniso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:(dim + 1), + dK = stk_gausscov_aniso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end ***** test - for dim = [1 3 7], - x = zeros(1, dim); - y = stk_sampling_regulargrid(3^dim, dim); - [fd, ymax] = stk_filldist_discretized(x, y); - assert(stk_isequal_tolabs(fd, sqrt(dim))); - assert(stk_isequal_tolabs(ymax, ones(1, dim))); + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_gausscov_aniso (param, x, y); + K2 = stk_gausscov_aniso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:(dim + 1), + dK1 = stk_gausscov_aniso (param, x, y, i); + dK2 = stk_gausscov_aniso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); end -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/misc/dist/stk_filldist_exact.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist_exact.m +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov32_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov32_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error K = stk_materncov32_iso ([param; 1.234], x, y); +***** error stk_materncov32_iso (); +***** error stk_materncov32_iso (param); +***** error stk_materncov32_iso (param, x); +***** test stk_materncov32_iso (param, x, y); +***** test stk_materncov32_iso (param, x, y, -1); +***** test stk_materncov32_iso (param, x, y, -1, false); +***** error stk_materncov32_iso (param, x, y, -2); +***** test stk_materncov32_iso (param, x, y, -1); +***** error stk_materncov32_iso (param, x, y, 0); +***** test stk_materncov32_iso (param, x, y, 1); +***** test stk_materncov32_iso (param, x, y, 2); +***** error stk_materncov32_iso (param, x, y, 3); +***** error stk_materncov32_iso (param, x, y, nan); +***** error stk_materncov32_iso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - d = 3; x = rand(7, d); box = repmat([0; 1], 1, d); - fd1 = stk_filldist_exact(x, box); - fd2 = stk_filldist_exact(stk_dataframe(x), stk_dataframe(box)); - assert(stk_isequal_tolabs(fd1, fd2)); + K1 = stk_materncov32_iso (param, x, y); + K2 = stk_materncov32_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); ***** test - for dim = 1:6, - x = 0.5 * ones(1, dim); - fd = stk_filldist_exact(x); % [0; 1]^d is the default box - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + for i = 1:2, + dK = stk_materncov32_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end ***** test - for dim = [1 3 7], - box = repmat([1; 2], 1, dim); - x = 1 + 0.5 * ones(1, dim); - fd = stk_filldist_exact(x, box); - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_materncov32_iso (param, x, y); + K2 = stk_materncov32_iso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:2, + dK1 = stk_materncov32_iso (param, x, y, i); + dK2 = stk_materncov32_iso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov_aniso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 1.5; 2.8]); + x = stk_sampling_randunif(5, dim); + y = stk_sampling_randunif(5, dim); +***** error stk_materncov_aniso(); +***** error stk_materncov_aniso(param); +***** error stk_materncov_aniso(param, x); +***** test stk_materncov_aniso(param, x, y); +***** test stk_materncov_aniso(param, x, y, -1); +***** test stk_materncov_aniso(param, x, y, -1, false); +***** error stk_materncov_aniso(param, x, y, -2); +***** test stk_materncov_aniso(param, x, y, -1); +***** error stk_materncov_aniso(param, x, y, 0); +***** test stk_materncov_aniso(param, x, y, 1); +***** test stk_materncov_aniso(param, x, y, 2); +***** test stk_materncov_aniso(param, x, y, 3); +***** error stk_materncov_aniso(param, x, y, 4); +***** error stk_materncov_aniso(param, x, y, nan); +***** error stk_materncov_aniso(param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 1.5; 2.8; 2.7; 2.9]); + nx = 4; ny = 10; + x = stk_sampling_randunif(nx, dim); + y = stk_sampling_randunif(ny, dim); ***** test - for dim = [1 3 7], - x = zeros(1, dim); - [fd, ymax] = stk_filldist_exact(x); - assert(stk_isequal_tolabs(fd, sqrt(dim))); - assert(stk_isequal_tolabs(ymax, ones(1, dim))); - end -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/misc/dist/stk_dist.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_dist.m -***** error stk_dist(); -***** error stk_dist(0, 0, 0); -***** error stk_dist(0, 0, 0, 0); -***** error stk_dist(0, ones(1, 2)); -***** error stk_dist(eye(3), ones(1, 2)); -***** error stk_dist(ones(2, 1), zeros(2)); -***** shared x, y, z - x = zeros(11, 5); - y = zeros(13, 5); - z = ones(7, 5); + K1 = stk_materncov_aniso(param, x, y); + K2 = stk_materncov_aniso(param, x, y, -1); + assert(isequal(size(K1), [nx ny])); + assert(stk_isequal_tolabs(K1, K2)); ***** test - Dx = stk_dist(x); - assert(isequal(Dx, zeros(11))); + for i = 1:(dim+2), + dK = stk_materncov_aniso(param, x, y, i); + assert(isequal(size(dK), [nx ny])); + end ***** test - Dxx = stk_dist(x, x); - assert(isequal(Dxx, zeros(11))); + n = 7; + x = stk_sampling_randunif(n, dim); + y = stk_sampling_randunif(n, dim); + + K1 = stk_materncov_aniso(param, x, y); + K2 = stk_materncov_aniso(param, x, y, -1, true); + assert(isequal(size(K1), [n n])); + assert(stk_isequal_tolabs(K2, diag(K1))); + + for i = 1:(dim+2), + dK1 = stk_materncov_aniso(param, x, y, i); + dK2 = stk_materncov_aniso(param, x, y, i, true); + assert(isequal(size(dK1), [n n])); + assert(stk_isequal_tolabs(dK2, diag(dK1))); + end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov52_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov52_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error K = stk_materncov52_iso ([param; 1.234], x, y); +***** error stk_materncov52_iso (); +***** error stk_materncov52_iso (param); +***** error stk_materncov52_iso (param, x); +***** test stk_materncov52_iso (param, x, y); +***** test stk_materncov52_iso (param, x, y, -1); +***** test stk_materncov52_iso (param, x, y, -1, false); +***** error stk_materncov52_iso (param, x, y, -2); +***** test stk_materncov52_iso (param, x, y, -1); +***** error stk_materncov52_iso (param, x, y, 0); +***** test stk_materncov52_iso (param, x, y, 1); +***** test stk_materncov52_iso (param, x, y, 2); +***** error stk_materncov52_iso (param, x, y, 3); +***** error stk_materncov52_iso (param, x, y, nan); +***** error stk_materncov52_iso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - Dxy = stk_dist(x, y); - assert(isequal(Dxy, zeros(11, 13))); + K1 = stk_materncov52_iso (param, x, y); + K2 = stk_materncov52_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); ***** test - Dzz = stk_dist(z, z); - assert(isequal(Dzz, zeros(7))); + for i = 1:2, + dK = stk_materncov52_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); + end ***** test - Dxz = stk_dist(x, z); - assert(stk_isequal_tolabs(Dxz, sqrt(5)*ones(11, 7))); + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_materncov52_iso (param, x, y); + K2 = stk_materncov52_iso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:2, + dK1 = stk_materncov52_iso (param, x, y, i); + dK2 = stk_materncov52_iso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); + end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov32_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov32_aniso.m +***** shared param, x, y, K1, K2, K3 + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (6, dim); +***** error K0 = stk_materncov32_aniso (); +***** error K0 = stk_materncov32_aniso (param); +***** error K0 = stk_materncov32_aniso (param, x); +***** test K1 = stk_materncov32_aniso (param, x, y); +***** test K2 = stk_materncov32_aniso (param, x, y, -1); +***** test K3 = stk_materncov32_aniso (param, x, y, -1, false); +***** assert (isequal (K1, K2)); +***** assert (isequal (K1, K3)); +***** test % df versus ordinary array + u = double (x); v = double (y); + K1 = stk_materncov32_aniso (param, u, v, -1); + K2 = stk_materncov32_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); + assert (isequal (K1, K2)); +***** error stk_materncov32_aniso (param, x, y, -2); +***** test stk_materncov32_aniso (param, x, y, -1); +***** error stk_materncov32_aniso (param, x, y, 0); +***** test stk_materncov32_aniso (param, x, y, 1); +***** test stk_materncov32_aniso (param, x, y, 2); +***** error stk_materncov32_aniso (param, x, y, 3); +***** error stk_materncov32_aniso (param, x, y, nan); +***** error stk_materncov32_aniso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5; 2.4; 2.6]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - x = randn(5,3); - y = randn(5,3); - D1 = stk_dist(x, y, true); % pairwise - D2 = stk_dist(x, y); - assert(stk_isequal_tolabs(D1, diag(D2))); + K1 = stk_materncov32_aniso (param, x, y); + K2 = stk_materncov32_aniso (param, x, y, -1); + assert (isequal (size(K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); ***** test - x = randn(5,3); - D1 = stk_dist(x, [], true); % pairwise - assert(stk_isequal_tolabs(D1, zeros(5, 1))); - D1 = stk_dist(x, x, true); % pairwise - assert(stk_isequal_tolabs(D1, zeros(5, 1))); -13 tests, 13 passed, 0 known failure, 0 skipped -[inst/misc/dist/stk_filldist.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist.m -***** test %%% exact - d = 3; x = rand(7, d); box = repmat([0; 1], 1, d); - fd1 = stk_filldist(x, box); - fd2 = stk_filldist(stk_dataframe(x), stk_dataframe(box)); - assert(stk_isequal_tolabs(fd1, fd2)); -***** test %%% discretized - d = 3; x = rand(7, d); y = rand(20, d); - fd1 = stk_filldist(x, y); - fd2 = stk_filldist(stk_dataframe(x), stk_dataframe(y)); - assert(stk_isequal_tolabs(fd1, fd2)); + for i = 1:(dim + 1), + dK = stk_materncov32_aniso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); + end ***** test - n = 5; % must be bigger than 2 - for dim = 1:10, - x = rand(n, dim); - fd = stk_filldist(x, x); - assert(stk_isequal_tolabs(fd, 0.0)); + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_materncov32_aniso (param, x, y); + K2 = stk_materncov32_aniso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:(dim + 1), + dK1 = stk_materncov32_aniso (param, x, y, i); + dK2 = stk_materncov32_aniso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); end -***** test %%% exact - for dim = 1:6, - x = 0.5 * ones(1, dim); - fd = stk_filldist(x); % [0; 1]^d is the default box - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov52_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov52_aniso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error stk_materncov52_aniso (); +***** error stk_materncov52_aniso (param); +***** error stk_materncov52_aniso (param, x); +***** test stk_materncov52_aniso (param, x, y); +***** test stk_materncov52_aniso (param, x, y, -1); +***** test stk_materncov52_aniso (param, x, y, -1, false); +***** error stk_materncov52_aniso (param, x, y, -2); +***** test stk_materncov52_aniso (param, x, y, -1); +***** error stk_materncov52_aniso (param, x, y, 0); +***** test stk_materncov52_aniso (param, x, y, 1); +***** test stk_materncov52_aniso (param, x, y, 2); +***** error stk_materncov52_aniso (param, x, y, 3); +***** error stk_materncov52_aniso (param, x, y, nan); +***** error stk_materncov52_aniso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5; 2.4; 2.6]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); +***** test + K1 = stk_materncov52_aniso (param, x, y); + K2 = stk_materncov52_aniso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:(dim + 1), + dK = stk_materncov52_aniso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end -***** test %%% discretized - for dim = 1:6, - x = 0.5 * ones(1, dim); - y = stk_sampling_regulargrid(2^dim, dim); % [0; 1]^d is the default box - fd = stk_filldist(x, y); - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); +***** test + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_materncov52_aniso (param, x, y); + K2 = stk_materncov52_aniso(param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:(dim + 1), + dK1 = stk_materncov52_aniso (param, x, y, i); + dK2 = stk_materncov52_aniso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); end +17 tests, 17 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_expcov_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_expcov_aniso.m +***** shared param, x, y, K1, K2, K3 + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (6, dim); +***** error K0 = stk_expcov_aniso (); +***** error K0 = stk_expcov_aniso (param); +***** error K0 = stk_expcov_aniso (param, x); +***** test K1 = stk_expcov_aniso (param, x, y); +***** test K2 = stk_expcov_aniso (param, x, y, -1); +***** test K3 = stk_expcov_aniso (param, x, y, -1, false); +***** assert (isequal (K1, K2)); +***** assert (isequal (K1, K3)); +***** test % df versus ordinary array + u = double (x); v = double (y); + K1 = stk_expcov_aniso (param, u, v, -1); + K2 = stk_expcov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); +***** error stk_expcov_aniso (param, x, y, -2); +***** test stk_expcov_aniso (param, x, y, -1); +***** error stk_expcov_aniso (param, x, y, 0); +***** test stk_expcov_aniso (param, x, y, 1); +***** test stk_expcov_aniso (param, x, y, 2); +***** error stk_expcov_aniso (param, x, y, 3); +***** error stk_expcov_aniso (param, x, y, nan); +***** error stk_expcov_aniso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5; 2.4; 2.6]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - for dim = [1 3 7], - box = repmat([1; 2], 1, dim); - x = 1 + 0.5 * ones(1, dim); - fd = stk_filldist(x, box); - assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + K1 = stk_expcov_aniso (param, x, y); + K2 = stk_expcov_aniso (param, x, y, -1); + assert (isequal (size(K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:(dim + 1), + dK = stk_expcov_aniso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end ***** test + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_expcov_aniso (param, x, y); + K2 = stk_expcov_aniso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:(dim + 1), + dK1 = stk_expcov_aniso (param, x, y, i); + dK2 = stk_expcov_aniso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); + end +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_discretecov.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_discretecov.m +***** shared model, model2, x0 + n0 = 20; n1 = 10; dim = 4; + x0 = stk_sampling_randunif (n0, dim); + x1 = stk_sampling_randunif (n1, dim); + model = stk_model (@stk_materncov52_aniso, dim); + model.lm = stk_lm_affine (); + model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); +***** test % without noise, pairwise = false + model.lognoisevariance = - inf; + model2 = stk_model (@stk_discretecov, model, x0); + idx = [1 4 9]; + [K1, P1] = stk_make_matcov (model, x0(idx, :)); + [K2, P2] = stk_make_matcov (model2, idx'); + assert (stk_isequal_tolrel (K1, K2)); + assert (stk_isequal_tolrel (P1, P2)); +***** test % without noise, pairwise = true + K1 = stk_make_matcov (model, x0([2 5 6], :), [], true); + K2 = stk_make_matcov (model2, [2 5 6]', [], true); + assert (stk_isequal_tolrel (K1, K2)); +***** test % with noise, pairwise = false + model.lognoisevariance = log (0.01); + model2 = stk_model (@stk_discretecov, model, x0); + idx = [1 4 9]; + [K1, P1] = stk_make_matcov (model, x0(idx, :)); + [K2, P2] = stk_make_matcov (model2, idx'); + assert (stk_isequal_tolrel (K1, K2)); + assert (stk_isequal_tolrel (P1, P2)); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_noisecov.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_noisecov.m +***** shared ni, lognoisevariance, diff + ni = 5; + lognoisevariance = 0.0; + diff = -1; +***** error K = stk_noisecov (); +***** error K = stk_noisecov (ni); +***** test K = stk_noisecov (ni, lognoisevariance); +***** test K = stk_noisecov (ni, lognoisevariance, diff); +***** test K = stk_noisecov (ni, lognoisevariance, diff, true); +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_materncov_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 1.5; 2.9]); + x = stk_sampling_randunif(5, dim); + y = stk_sampling_randunif(5, dim); +***** error K = stk_materncov_iso ([param; 1.234], x, y); +***** error stk_materncov_iso(); +***** error stk_materncov_iso(param); +***** error stk_materncov_iso(param, x); +***** test stk_materncov_iso(param, x, y); +***** test stk_materncov_iso(param, x, y, -1); +***** test stk_materncov_iso(param, x, y, -1, false); +***** error stk_materncov_iso(param, x, y, -2); +***** test stk_materncov_iso(param, x, y, -1); +***** error stk_materncov_iso(param, x, y, 0); +***** test stk_materncov_iso(param, x, y, 1); +***** test stk_materncov_iso(param, x, y, 2); +***** test stk_materncov_iso(param, x, y, 3); +***** error stk_materncov_iso(param, x, y, 4); +***** error stk_materncov_iso(param, x, y, nan); +***** error stk_materncov_iso(param, x, y, inf); +***** shared dim, param, x, y, nx, ny dim = 3; - box = repmat([-1; 1], 1, dim); - x = stk_sampling_randunif(20, dim, box); - y = stk_sampling_regulargrid(3^dim, dim, box); - fd1 = stk_filldist(x, box); - fd2 = stk_filldist(x, y); - assert(fd1 >= fd2 - 10 * eps); -***** test %%% exact - for dim = [1 3 7], - x = zeros(1, dim); - [fd, ymax] = stk_filldist_exact(x); - assert(stk_isequal_tolabs(fd, sqrt(dim))); - assert(stk_isequal_tolabs(ymax, ones(1, dim))); + param = log ([1.0; 1.5; 2.9]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); +***** test + K1 = stk_materncov_iso (param, x, y); + K2 = stk_materncov_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:3, + dK = stk_materncov_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end -***** test %%% discretized - for dim = [1 3 7], - x = zeros(1, dim); - y = stk_sampling_regulargrid(3^dim, dim); - [fd, ymax] = stk_filldist(x, y); - assert(stk_isequal_tolabs(fd, sqrt(dim))); - assert(stk_isequal_tolabs(ymax, ones(1, dim))); +***** test + n = 7; + x = stk_sampling_randunif(n, dim); + y = stk_sampling_randunif(n, dim); + + K1 = stk_materncov_iso(param, x, y); + K2 = stk_materncov_iso(param, x, y, -1, true); + assert(isequal(size(K1), [n n])); + assert(stk_isequal_tolabs(K2, diag(K1))); + + for i = 1:3, + dK1 = stk_materncov_iso(param, x, y, i); + dK2 = stk_materncov_iso(param, x, y, i, true); + assert(isequal(size(dK1), [n n])); + assert(stk_isequal_tolabs(dK2, diag(dK1))); end -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/misc/dist/stk_mindist.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_mindist.m +19 tests, 19 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_sphcov_aniso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_sphcov_aniso.m +***** shared param, x, y, K1, K2, K3 + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (6, dim); +***** error K0 = stk_sphcov_aniso (); +***** error K0 = stk_sphcov_aniso (param); +***** error K0 = stk_sphcov_aniso (param, x); +***** test K1 = stk_sphcov_aniso (param, x, y); +***** test K2 = stk_sphcov_aniso (param, x, y, -1); +***** test K3 = stk_sphcov_aniso (param, x, y, -1, false); +***** assert (isequal (K1, K2)); +***** assert (isequal (K1, K3)); +***** test % df versus ordinary array + u = double (x); v = double (y); + K1 = stk_sphcov_aniso (param, u, v, -1); + K2 = stk_sphcov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); + assert (isequal (K1, K2)); +***** error stk_sphcov_aniso (param, x, y, -2); +***** test stk_sphcov_aniso (param, x, y, -1); +***** error stk_sphcov_aniso (param, x, y, 0); +***** test stk_sphcov_aniso (param, x, y, 1); +***** test stk_sphcov_aniso (param, x, y, 2); +***** error stk_sphcov_aniso (param, x, y, 3); +***** error stk_sphcov_aniso (param, x, y, nan); +***** error stk_sphcov_aniso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5; 2.4; 2.6]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - d = 3; x = rand(7, d); - md1 = stk_mindist(x); - md2 = stk_mindist(stk_dataframe(x)); - assert(stk_isequal_tolabs(md1, md2)); + K1 = stk_sphcov_aniso (param, x, y); + K2 = stk_sphcov_aniso (param, x, y, -1); + assert (isequal (size(K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); ***** test - for nc = [0 5 10], - x = zeros(0, nc); - d = stk_mindist(x); - assert(isempty(d)); + for i = 1:(dim + 1), + dK = stk_sphcov_aniso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end ***** test - for nc = [0 5 10], - x = rand(1, nc); - d = stk_mindist(x); - assert(isempty(d)); + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); + + K1 = stk_sphcov_aniso (param, x, y); + K2 = stk_sphcov_aniso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + + for i = 1:(dim + 1), + dK1 = stk_sphcov_aniso (param, x, y, i); + dK2 = stk_sphcov_aniso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); + end +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_matern.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern.m +***** shared nu, h, diff + nu = 1.0; h = 1.0; diff = -1; +***** error stk_rbf_matern (); +***** error stk_rbf_matern (nu); +***** test stk_rbf_matern (nu, h); +***** test stk_rbf_matern (nu, h, diff); +***** test %% h = 0.0 => correlation = 1.0 + for nu = 0.1:0.2:5.0, + x = stk_rbf_matern (nu, 0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); + end +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_matern52.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern52.m +***** shared h, diff + h = 1.0; diff = -1; +***** error stk_rbf_matern52 (); +***** test stk_rbf_matern52 (h); +***** test stk_rbf_matern52 (h, diff); +***** test %% h = 0.0 => correlation = 1.0 + x = stk_rbf_matern52 (0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); +***** test %% consistency with stk_rbf_matern: function values + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (5/2, h); + y = stk_rbf_matern52 (h); + assert (stk_isequal_tolrel (x, y, 1e-8)); + end +***** test %% consistency with stk_rbf_matern: derivatives + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (5/2, h, 2); + y = stk_rbf_matern52 (h, 1); + assert (stk_isequal_tolrel (x, y, 1e-8)); + end +***** assert (stk_rbf_matern52 (inf) == 0) +7 tests, 7 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_matern32.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern32.m +***** shared h, diff + h = 1.0; diff = -1; +***** error stk_rbf_matern32 (); +***** test stk_rbf_matern32 (h); +***** test stk_rbf_matern32 (h, diff); +***** test %% h = 0.0 => correlation = 1.0 + x = stk_rbf_matern32 (0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); +***** test %% consistency with stk_rbf_matern: function values + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (3/2, h); + y = stk_rbf_matern32 (h); + assert (stk_isequal_tolrel (x, y, 1e-8)); + end +***** test %% consistency with stk_rbf_matern: derivatives + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (3/2, h, 2); + y = stk_rbf_matern32 (h, 1); + assert (stk_isequal_tolrel (x, y, 1e-8)); + end +***** assert (stk_rbf_matern32 (inf) == 0) +7 tests, 7 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_gauss.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_gauss.m +***** shared h, diff + h = 1.0; diff = -1; +***** error stk_rbf_gauss (); +***** test stk_rbf_gauss (h); +***** test stk_rbf_gauss (h, diff); +***** test % h = 0.0 => correlation = 1.0 + x = stk_rbf_gauss (0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_spherical.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_spherical.m +***** shared h, diff + h = 1.0; diff = -1; +***** error stk_rbf_spherical (); +***** test stk_rbf_spherical (h); +***** test stk_rbf_spherical (h, diff); +***** test %% h = 0.0 => correlation = 1.0 + x = stk_rbf_spherical (0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); +***** test %% check derivative numerically + h = [-1 -0.5 -0.1 0.1 0.5 1]; delta = 1e-9; + d1 = (stk_rbf_spherical (h + delta) - stk_rbf_spherical (h)) / delta; + d2 = stk_rbf_spherical (h, 1); + assert (stk_isequal_tolabs (d1, d2, 1e-4)); +***** assert (stk_rbf_spherical (inf) == 0) +6 tests, 6 passed, 0 known failure, 0 skipped +[inst/covfcs/rbf/stk_rbf_exponential.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_exponential.m +***** shared h, diff + h = 1.0; diff = -1; +***** error stk_rbf_exponential (); +***** test stk_rbf_exponential (h); +***** test stk_rbf_exponential (h, diff); +***** test %% h = 0.0 => correlation = 1.0 + x = stk_rbf_exponential (0.0); + assert (stk_isequal_tolrel (x, 1.0, 1e-8)); +***** test %% check derivative numerically + h = [-1 -0.5 -0.1 0.1 0.5 1]; delta = 1e-9; + d1 = (stk_rbf_exponential (h + delta) - stk_rbf_exponential (h)) / delta; + d2 = stk_rbf_exponential (h, 1); + assert (stk_isequal_tolabs (d1, d2, 1e-4)); +***** test %% consistency with stk_rbf_matern: function values + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (1/2, h); + y = stk_rbf_exponential (h); + assert (stk_isequal_tolrel (x, y, 1e-8)); + end +***** test %% consistency with stk_rbf_matern: derivatives + for h = 0.1:0.1:2.0, + x = stk_rbf_matern (1/2, h, 2); + y = stk_rbf_exponential (h, 1); + assert (stk_isequal_tolrel (x, y, 1e-8)); end +***** assert (stk_rbf_exponential (inf) == 0) +8 tests, 8 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_gausscov_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_gausscov_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error K = stk_gausscov_iso ([param; 1.234], x, y); +***** error stk_gausscov_iso (); +***** error stk_gausscov_iso (param); +***** error stk_gausscov_iso (param, x); +***** test stk_gausscov_iso (param, x, y); +***** test stk_gausscov_iso (param, x, y, -1); +***** test stk_gausscov_iso (param, x, y, -1, false); +***** error stk_gausscov_iso (param, x, y, -2); +***** test stk_gausscov_iso (param, x, y, -1); +***** error stk_gausscov_iso (param, x, y, 0); +***** test stk_gausscov_iso (param, x, y, 1); +***** test stk_gausscov_iso (param, x, y, 2); +***** error stk_gausscov_iso (param, x, y, 3); +***** error stk_gausscov_iso (param, x, y, nan); +***** error stk_gausscov_iso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); ***** test - for nr = [2 5 10], - x = zeros(nr, 0); - d = stk_mindist(x); - assert(isequal(d, 0.0)); + K1 = stk_gausscov_iso (param, x, y); + K2 = stk_gausscov_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:2, + dK = stk_gausscov_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); end ***** test + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); - nrep = 20; - TOL_REL = 1e-15; + K1 = stk_gausscov_iso (param, x, y); + K2 = stk_gausscov_iso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); - for irep = 1:nrep, + for i = 1:2, + dK1 = stk_gausscov_iso (param, x, y, i); + dK2 = stk_gausscov_iso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); + end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_expcov_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_expcov_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error K = stk_expcov_iso ([param; 1.234], x, y); +***** error stk_expcov_iso (); +***** error stk_expcov_iso (param); +***** error stk_expcov_iso (param, x); +***** test stk_expcov_iso (param, x, y); +***** test stk_expcov_iso (param, x, y, -1); +***** test stk_expcov_iso (param, x, y, -1, false); +***** error stk_expcov_iso (param, x, y, -2); +***** test stk_expcov_iso (param, x, y, -1); +***** error stk_expcov_iso (param, x, y, 0); +***** test stk_expcov_iso (param, x, y, 1); +***** test stk_expcov_iso (param, x, y, 2); +***** error stk_expcov_iso (param, x, y, 3); +***** error stk_expcov_iso (param, x, y, nan); +***** error stk_expcov_iso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); +***** test + K1 = stk_expcov_iso (param, x, y); + K2 = stk_expcov_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:2, + dK = stk_expcov_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); + end +***** test + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); - n = 2 + floor(rand * 10); - d = 1 + floor(rand * 10); - x = rand(n, d); - z = stk_mindist(x); + K1 = stk_expcov_iso (param, x, y); + K2 = stk_expcov_iso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); - assert(isequal(size(d), [1, 1])); - assert(~isnan(d)); - assert(~isinf(d)); + for i = 1:2, + dK1 = stk_expcov_iso (param, x, y, i); + dK2 = stk_expcov_iso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); + end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/covfcs/stk_sphcov_iso.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_sphcov_iso.m +***** shared param, x, y + dim = 1; + param = log ([1.0; 2.5]); + x = stk_sampling_randunif (5, dim); + y = stk_sampling_randunif (5, dim); +***** error K = stk_sphcov_iso ([param; 1.234], x, y); +***** error stk_sphcov_iso (); +***** error stk_sphcov_iso (param); +***** error stk_sphcov_iso (param, x); +***** test stk_sphcov_iso (param, x, y); +***** test stk_sphcov_iso (param, x, y, -1); +***** test stk_sphcov_iso (param, x, y, -1, false); +***** error stk_sphcov_iso (param, x, y, -2); +***** test stk_sphcov_iso (param, x, y, -1); +***** error stk_sphcov_iso (param, x, y, 0); +***** test stk_sphcov_iso (param, x, y, 1); +***** test stk_sphcov_iso (param, x, y, 2); +***** error stk_sphcov_iso (param, x, y, 3); +***** error stk_sphcov_iso (param, x, y, nan); +***** error stk_sphcov_iso (param, x, y, inf); +***** shared dim, param, x, y, nx, ny + dim = 3; + param = log ([1.0; 2.5]); + nx = 4; ny = 10; + x = stk_sampling_randunif (nx, dim); + y = stk_sampling_randunif (ny, dim); +***** test + K1 = stk_sphcov_iso (param, x, y); + K2 = stk_sphcov_iso (param, x, y, -1); + assert (isequal (size (K1), [nx ny])); + assert (stk_isequal_tolabs (K1, K2)); +***** test + for i = 1:2, + dK = stk_sphcov_iso (param, x, y, i); + assert (isequal (size (dK), [nx ny])); + end +***** test + n = 7; + x = stk_sampling_randunif (n, dim); + y = stk_sampling_randunif (n, dim); - % check the result - mindist = Inf; - for i = 1:(n-1), - for j = (i+1):n, - mindist = min(mindist, norm(x(i,:) - x(j,:))); - end - end - assert(abs(z - mindist) <= TOL_REL * mindist); + K1 = stk_sphcov_iso (param, x, y); + K2 = stk_sphcov_iso (param, x, y, -1, true); + assert (isequal (size (K1), [n n])); + assert (stk_isequal_tolabs (K2, diag (K1))); + for i = 1:2, + dK1 = stk_sphcov_iso (param, x, y, i); + dK2 = stk_sphcov_iso (param, x, y, i, true); + assert (isequal (size (dK1), [n n])); + assert (stk_isequal_tolabs (dK2, diag (dK1))); end +18 tests, 18 passed, 0 known failure, 0 skipped +[inst/misc/design/stk_maxabscorr.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/design/stk_maxabscorr.m +***** assert (stk_isequal_tolabs (0.0, ... % Test on an OLHS(5) + stk_maxabscorr ([0.4 0.8 0 -0.4 -0.8; -0.8 0.4 0 0.8 -0.4]'))); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/misc/design/stk_phipcrit.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/design/stk_phipcrit.m +***** shared x + x = [0, 0.2, 0.4, 0.6, 0.8, 1.0; + 0, 0.6, 0.8, 1.0, 0.2, 0.4]'; +***** assert (stk_isequal_tolabs ... + (stk_phipcrit (x, 10), 3.946317664423303, 1e-15)) +***** assert (stk_isequal_tolabs ... + (stk_phipcrit (x, 50), 3.614077252813102, 1e-15)); +***** assert (stk_isequal_tolabs ... + (stk_phipcrit (x, 100), 3.574589859827413, 1e-15)); +***** assert (stk_isequal_tolabs ... + (stk_phipcrit (x, 1e9), 1 / stk_mindist (x), 1e-8)); +***** assert (isequal (stk_phipcrit (ones (2)), Inf)); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/misc/test/stk_test.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/test/stk_test.m @@ -3202,23 +4914,6 @@ ***** error stk_test('stk_mindist', 0.0) ***** error stk_test('stk_mindist', 'dudule') 24 tests, 24 passed, 0 known failure, 0 skipped -[inst/misc/test/stk_isequal_tolabs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/test/stk_isequal_tolabs.m -***** shared r1, r2, a, b, tolabs - a = 1.01; b = 1.02; tolabs = 0.1; -***** error rr = stk_isequal_tolabs(); -***** error rr = stk_isequal_tolabs(a); -***** test r1 = stk_isequal_tolabs(a, b); -***** test r2 = stk_isequal_tolabs(a, b, tolabs); -***** test assert(~r1); -***** test assert(r2); -***** test - a = struct('u', []); b = struct('v', []); - assert(~ stk_isequal_tolabs(a, b)) -***** test - a = struct('u', 1.01); b = struct('u', 1.02); - assert(stk_isequal_tolabs(a, b, tolabs)) -8 tests, 8 passed, 0 known failure, 0 skipped [inst/misc/test/stk_isequal_tolrel.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/test/stk_isequal_tolrel.m ***** shared r1, r2, r3, a, b, tolrel @@ -3238,26 +4933,23 @@ a = struct('u', 1.01); b = struct('u', 1.02); assert(stk_isequal_tolrel(a, b, tolrel)) 10 tests, 10 passed, 0 known failure, 0 skipped -[inst/misc/design/stk_phipcrit.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/design/stk_phipcrit.m -***** shared x - x = [0, 0.2, 0.4, 0.6, 0.8, 1.0; - 0, 0.6, 0.8, 1.0, 0.2, 0.4]'; -***** assert (stk_isequal_tolabs ... - (stk_phipcrit (x, 10), 3.946317664423303, 1e-15)) -***** assert (stk_isequal_tolabs ... - (stk_phipcrit (x, 50), 3.614077252813102, 1e-15)); -***** assert (stk_isequal_tolabs ... - (stk_phipcrit (x, 100), 3.574589859827413, 1e-15)); -***** assert (stk_isequal_tolabs ... - (stk_phipcrit (x, 1e9), 1 / stk_mindist (x), 1e-8)); -***** assert (isequal (stk_phipcrit (ones (2)), Inf)); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/misc/design/stk_maxabscorr.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/design/stk_maxabscorr.m -***** assert (stk_isequal_tolabs (0.0, ... % Test on an OLHS(5) - stk_maxabscorr ([0.4 0.8 0 -0.4 -0.8; -0.8 0.4 0 0.8 -0.4]'))); -1 test, 1 passed, 0 known failure, 0 skipped +[inst/misc/test/stk_isequal_tolabs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/test/stk_isequal_tolabs.m +***** shared r1, r2, a, b, tolabs + a = 1.01; b = 1.02; tolabs = 0.1; +***** error rr = stk_isequal_tolabs(); +***** error rr = stk_isequal_tolabs(a); +***** test r1 = stk_isequal_tolabs(a, b); +***** test r2 = stk_isequal_tolabs(a, b, tolabs); +***** test assert(~r1); +***** test assert(r2); +***** test + a = struct('u', []); b = struct('v', []); + assert(~ stk_isequal_tolabs(a, b)) +***** test + a = struct('u', 1.01); b = struct('u', 1.02); + assert(stk_isequal_tolabs(a, b, tolabs)) +8 tests, 8 passed, 0 known failure, 0 skipped [inst/misc/pareto/stk_dominatedhv.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/pareto/stk_dominatedhv.m ***** error hv = stk_dominatedhv (); @@ -3432,39 +5124,6 @@ end end 35 tests, 35 passed, 0 known failure, 0 skipped -[inst/misc/pareto/stk_isdominated.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/pareto/stk_isdominated.m -***** test - A = [1 3 2]; - B = [0 0 0]; - [isdom, dpos] = stk_isdominated (A, B); - assert (isdom == 1); - assert (dpos == 1); -***** test - A = [1 3 2]; - B = [0 0 3]; - [isdom, dpos] = stk_isdominated (A, B); - assert (isdom == 0); - assert (dpos == 0); -***** test - A = [1 3 2]; - B = [0 0 0; 0 0 3]; - [isdom, dpos] = stk_isdominated (A, B); - assert (isdom == 1); - assert (dpos == 1); -***** test - A = [1 3 2]; - B = [0 0 3; 0 0 0]; - [isdom, dpos] = stk_isdominated (A, B); - assert (isdom == 1); - assert (dpos == 2); -***** test - A = [1 3 2; 1 0 1; -1 0 0; 1 3 2]; - B = [1 0 0; 0 0 3; 0 0 0]; - [isdom, dpos] = stk_isdominated (A, B); - assert (isequal (isdom, logical ([1; 1; 0; 1]))); - assert (isequal (dpos, [3; 3; 0; 3])); -5 tests, 5 passed, 0 known failure, 0 skipped [inst/misc/pareto/stk_paretofind.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/pareto/stk_paretofind.m ***** shared x, ndpos, drank @@ -3506,6 +5165,39 @@ ***** assert (isequal (ndpos, [5; 3; 1])); ***** assert (isequal (drank, [0; 3; 0; 2; 0; 1; 2])); 12 tests, 12 passed, 0 known failure, 0 skipped +[inst/misc/pareto/stk_isdominated.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/pareto/stk_isdominated.m +***** test + A = [1 3 2]; + B = [0 0 0]; + [isdom, dpos] = stk_isdominated (A, B); + assert (isdom == 1); + assert (dpos == 1); +***** test + A = [1 3 2]; + B = [0 0 3]; + [isdom, dpos] = stk_isdominated (A, B); + assert (isdom == 0); + assert (dpos == 0); +***** test + A = [1 3 2]; + B = [0 0 0; 0 0 3]; + [isdom, dpos] = stk_isdominated (A, B); + assert (isdom == 1); + assert (dpos == 1); +***** test + A = [1 3 2]; + B = [0 0 3; 0 0 0]; + [isdom, dpos] = stk_isdominated (A, B); + assert (isdom == 1); + assert (dpos == 2); +***** test + A = [1 3 2; 1 0 1; -1 0 0; 1 3 2]; + B = [1 0 0; 0 0 3; 0 0 0]; + [isdom, dpos] = stk_isdominated (A, B); + assert (isequal (isdom, logical ([1; 1; 0; 1]))); + assert (isequal (dpos, [3; 3; 0; 3])); +5 tests, 5 passed, 0 known failure, 0 skipped [inst/misc/error/stk_error.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/error/stk_error.m ***** shared errmsg, mnemonic, badstack @@ -3516,6 +5208,18 @@ ***** error stk_error (errmsg, mnemonic, badstack); ***** error id=STK:stk_error:InvalidArgument stk_error (errmsg, mnemonic, badstack); 3 tests, 3 passed, 0 known failure, 0 skipped +[inst/misc/text/stk_sprintf_colvect.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_sprintf_colvect.m +***** shared s +***** test s = stk_sprintf_colvect ([1 1e1], 6); +***** assert (isequal (s, [' 1'; '10'])) +***** test s = stk_sprintf_colvect ([1 1e3], 6); +***** assert (isequal (s, [' 1'; '1000'])) +***** test s = stk_sprintf_colvect ([1 1e5], 6); +***** assert (isequal (s, [' 1'; '100000'])) +***** test s = stk_sprintf_colvect ([1 1e6], 6); +***** assert (isequal (s, ['1e+00'; '1e+06'])) +8 tests, 8 passed, 0 known failure, 0 skipped [inst/misc/text/stk_sprintf_colvect_scientific.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_sprintf_colvect_scientific.m ***** shared x, s @@ -3569,6 +5273,31 @@ s = stk_sprintf_colvect_scientific(x, 10); assert(isequal(s, [' 1e+006'; '-1e+010'; ' 1e-221'])); 41 tests, 41 passed, 0 known failure, 0 skipped +[inst/misc/text/stk_disp_progress.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_disp_progress.m +***** error stk_disp_progress ('toto ', 0, 1); +***** test stk_disp_progress ('toto ', 1, 1); +warning: implicit conversion from numeric to char +warning: called from + stk_disp_progress at line 53 column 1 + __test__ at line 2 column 3 + test at line 682 column 11 + /tmp/tmp.tlZGNdJ4JJ at line 526 column 31 + +toto +***** error stk_disp_progress ('toto ', 2, 1); +***** test + stk_disp_progress ('toto ', 1, 2); + stk_disp_progress ('toto ', 2, 2); +warning: implicit conversion from numeric to char +warning: called from + stk_disp_progress at line 53 column 1 + __test__ at line 3 column 2 + test at line 682 column 11 + /tmp/tmp.tlZGNdJ4JJ at line 526 column 31 + +toto toto +4 tests, 4 passed, 0 known failure, 0 skipped [inst/misc/text/stk_sprintf_colvect_fixedpoint.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_sprintf_colvect_fixedpoint.m ***** shared x, s @@ -3610,60 +5339,346 @@ ***** test s = stk_sprintf_colvect_fixedpoint(x, 5); ***** assert (isequal(s, ['0.20'; '0.48'])) 32 tests, 32 passed, 0 known failure, 0 skipped -[inst/misc/text/stk_disp_progress.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_disp_progress.m -***** error stk_disp_progress ('toto ', 0, 1); -***** test stk_disp_progress ('toto ', 1, 1); -warning: implicit conversion from numeric to char -warning: called from - stk_disp_progress at line 53 column 1 - __test__ at line 2 column 3 - test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 150 column 31 - -toto -***** error stk_disp_progress ('toto ', 2, 1); -***** test - stk_disp_progress ('toto ', 1, 2); - stk_disp_progress ('toto ', 2, 2); -warning: implicit conversion from numeric to char -warning: called from - stk_disp_progress at line 53 column 1 - __test__ at line 3 column 2 - test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 150 column 31 - -toto toto -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/misc/text/stk_sprintf_colvect.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/text/stk_sprintf_colvect.m -***** shared s -***** test s = stk_sprintf_colvect ([1 1e1], 6); -***** assert (isequal (s, [' 1'; '10'])) -***** test s = stk_sprintf_colvect ([1 1e3], 6); -***** assert (isequal (s, [' 1'; '1000'])) -***** test s = stk_sprintf_colvect ([1 1e5], 6); -***** assert (isequal (s, [' 1'; '100000'])) -***** test s = stk_sprintf_colvect ([1 1e6], 6); -***** assert (isequal (s, ['1e+00'; '1e+06'])) -8 tests, 8 passed, 0 known failure, 0 skipped [inst/misc/parallel/@stk_parallel_engine_none/stk_parallel_engine_none.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/parallel/@stk_parallel_engine_none/stk_parallel_engine_none.m ***** test stk_test_class ('stk_parallel_engine_none') 1 test, 1 passed, 0 known failure, 0 skipped -[inst/misc/distrib/stk_distrib_student_pdf.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_student_pdf.m -***** assert (stk_isequal_tolrel ( ... - stk_distrib_student_pdf ([1; 3], [1; 2], [0 1], [1 10]), ... - [0.50 / pi ... % tpdf ((1 - 1) / 10, 1) - 0.10 / pi; ... % tpdf ((1 - 1) / 10, 1) / 10 - 1 / (11 * sqrt(11)) ... % tpdf ((3 - 0) / 1, 2) / 1 - 3.4320590294804165e-02 ... % tpdf ((3 - 1) / 10, 2) / 10 - ], eps)); -***** assert (isequal (stk_distrib_student_pdf ( inf, 1.0), 0.0)); -***** assert (isequal (stk_distrib_student_pdf (-inf, 1.0), 0.0)); -***** assert (isnan (stk_distrib_student_pdf ( nan, 1.0))); +[inst/misc/dist/stk_gpquadform.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_gpquadform.m +***** shared x, y, z, rx, ry, rz + x = rand(5, 2); rx = rand(5, 2) + 1; + y = rand(6, 2); ry = rand(6, 2) + 1; + z = rand(5, 3); rz = rand(5, 3) + 1; +***** error Q = stk_gpquadform(x, ry, y, ry) +***** error Q = stk_gpquadform(x, rz, y, ry) +***** error Q = stk_gpquadform(x, rx, y, rx) +***** error Q = stk_gpquadform(x, rx, y, rz) +***** error Q = stk_gpquadform(x, rx, z, ry) +***** shared x, y, z, rx, ry, rz + x = zeros (11, 5); rx = 1/sqrt(2) * ones (11, 5); + y = zeros (13, 5); ry = 1/sqrt(2) * ones (13, 5); + z = ones ( 7, 5); rz = 1/sqrt(2) * ones ( 7, 5); +***** test + Qx = stk_gpquadform(x, [], rx); + assert(isequal(Qx, zeros(11))); +***** test + Qxx = stk_gpquadform(x, x, rx, rx); + assert(isequal(Qxx, zeros(11))); +***** test + Qxy = stk_gpquadform(x, y, rx, ry); + assert(isequal(Qxy, zeros(11, 13))); +***** test + Qzz = stk_gpquadform(z, [], rz); + assert(isequal(Qzz, zeros(7))); +***** test + Qxz = stk_gpquadform(x, z, rx, rz); + assert(stk_isequal_tolabs(Qxz, 5 * ones(11, 7))); +***** test + x = randn(5, 3); rx = 1 + rand(5, 3); + y = randn(5, 3); ry = 1 + rand(5, 3); + Q1 = stk_gpquadform(x, y, rx, ry, true); % pairwise + Q2 = stk_gpquadform(x, y, rx, ry, false); + assert(isequal(size(Q1), [5 1])); + assert(isequal(size(Q2), [5 5])); + assert(stk_isequal_tolabs(Q1, diag(Q2))); +***** test + x = randn(5, 3); rx = 1 + rand(5, 3); + Q1 = stk_gpquadform(x, [], rx, [], true); % pairwise + assert(stk_isequal_tolabs(Q1, zeros(5, 1))); + Q1 = stk_gpquadform(x, x, rx, rx, true); % pairwise + assert(stk_isequal_tolabs(Q1, zeros(5, 1))); +***** shared x, y, z, rx, ry, rz + x = zeros (11, 5); rx = 2 * ones (11, 5); + y = zeros (13, 5); ry = 2 * ones (13, 5); + z = ones ( 7, 5); rz = 2 * ones ( 7, 5); +***** test + Qx = stk_gpquadform(x, [], rx); + assert(isequal(Qx, zeros(11))); +***** test + Qxx = stk_gpquadform(x, x, rx, rx); + assert(isequal(Qxx, zeros(11))); +***** test + Qxy = stk_gpquadform(x, y, rx, ry); + assert(isequal(Qxy, zeros(11, 13))); +***** test + Qzz = stk_gpquadform(z, [], rz); + assert(isequal(Qzz, zeros(7))); +***** test + Qxz = stk_gpquadform(x, z, rx, rz); + assert(stk_isequal_tolabs(Qxz, 5/8 * ones(11, 7))); +17 tests, 17 passed, 0 known failure, 0 skipped +[inst/misc/dist/stk_filldist.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist.m +***** test %%% exact + d = 3; x = rand(7, d); box = repmat([0; 1], 1, d); + fd1 = stk_filldist(x, box); + fd2 = stk_filldist(stk_dataframe(x), stk_dataframe(box)); + assert(stk_isequal_tolabs(fd1, fd2)); +***** test %%% discretized + d = 3; x = rand(7, d); y = rand(20, d); + fd1 = stk_filldist(x, y); + fd2 = stk_filldist(stk_dataframe(x), stk_dataframe(y)); + assert(stk_isequal_tolabs(fd1, fd2)); +***** test + n = 5; % must be bigger than 2 + for dim = 1:10, + x = rand(n, dim); + fd = stk_filldist(x, x); + assert(stk_isequal_tolabs(fd, 0.0)); + end +***** test %%% exact + for dim = 1:6, + x = 0.5 * ones(1, dim); + fd = stk_filldist(x); % [0; 1]^d is the default box + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test %%% discretized + for dim = 1:6, + x = 0.5 * ones(1, dim); + y = stk_sampling_regulargrid(2^dim, dim); % [0; 1]^d is the default box + fd = stk_filldist(x, y); + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test + for dim = [1 3 7], + box = repmat([1; 2], 1, dim); + x = 1 + 0.5 * ones(1, dim); + fd = stk_filldist(x, box); + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test + dim = 3; + box = repmat([-1; 1], 1, dim); + x = stk_sampling_randunif(20, dim, box); + y = stk_sampling_regulargrid(3^dim, dim, box); + fd1 = stk_filldist(x, box); + fd2 = stk_filldist(x, y); + assert(fd1 >= fd2 - 10 * eps); +***** test %%% exact + for dim = [1 3 7], + x = zeros(1, dim); + [fd, ymax] = stk_filldist_exact(x); + assert(stk_isequal_tolabs(fd, sqrt(dim))); + assert(stk_isequal_tolabs(ymax, ones(1, dim))); + end +***** test %%% discretized + for dim = [1 3 7], + x = zeros(1, dim); + y = stk_sampling_regulargrid(3^dim, dim); + [fd, ymax] = stk_filldist(x, y); + assert(stk_isequal_tolabs(fd, sqrt(dim))); + assert(stk_isequal_tolabs(ymax, ones(1, dim))); + end +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/misc/dist/stk_mindist.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_mindist.m +***** test + d = 3; x = rand(7, d); + md1 = stk_mindist(x); + md2 = stk_mindist(stk_dataframe(x)); + assert(stk_isequal_tolabs(md1, md2)); +***** test + for nc = [0 5 10], + x = zeros(0, nc); + d = stk_mindist(x); + assert(isempty(d)); + end +***** test + for nc = [0 5 10], + x = rand(1, nc); + d = stk_mindist(x); + assert(isempty(d)); + end +***** test + for nr = [2 5 10], + x = zeros(nr, 0); + d = stk_mindist(x); + assert(isequal(d, 0.0)); + end +***** test + + nrep = 20; + TOL_REL = 1e-15; + + for irep = 1:nrep, + + n = 2 + floor(rand * 10); + d = 1 + floor(rand * 10); + x = rand(n, d); + z = stk_mindist(x); + + assert(isequal(size(d), [1, 1])); + assert(~isnan(d)); + assert(~isinf(d)); + + % check the result + mindist = Inf; + for i = 1:(n-1), + for j = (i+1):n, + mindist = min(mindist, norm(x(i,:) - x(j,:))); + end + end + assert(abs(z - mindist) <= TOL_REL * mindist); + + end +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/misc/dist/stk_filldist_exact.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist_exact.m +***** test + d = 3; x = rand(7, d); box = repmat([0; 1], 1, d); + fd1 = stk_filldist_exact(x, box); + fd2 = stk_filldist_exact(stk_dataframe(x), stk_dataframe(box)); + assert(stk_isequal_tolabs(fd1, fd2)); +***** test + for dim = 1:6, + x = 0.5 * ones(1, dim); + fd = stk_filldist_exact(x); % [0; 1]^d is the default box + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test + for dim = [1 3 7], + box = repmat([1; 2], 1, dim); + x = 1 + 0.5 * ones(1, dim); + fd = stk_filldist_exact(x, box); + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test + for dim = [1 3 7], + x = zeros(1, dim); + [fd, ymax] = stk_filldist_exact(x); + assert(stk_isequal_tolabs(fd, sqrt(dim))); + assert(stk_isequal_tolabs(ymax, ones(1, dim))); + end 4 tests, 4 passed, 0 known failure, 0 skipped +[inst/misc/dist/stk_dist.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_dist.m +***** error stk_dist(); +***** error stk_dist(0, 0, 0); +***** error stk_dist(0, 0, 0, 0); +***** error stk_dist(0, ones(1, 2)); +***** error stk_dist(eye(3), ones(1, 2)); +***** error stk_dist(ones(2, 1), zeros(2)); +***** shared x, y, z + x = zeros(11, 5); + y = zeros(13, 5); + z = ones(7, 5); +***** test + Dx = stk_dist(x); + assert(isequal(Dx, zeros(11))); +***** test + Dxx = stk_dist(x, x); + assert(isequal(Dxx, zeros(11))); +***** test + Dxy = stk_dist(x, y); + assert(isequal(Dxy, zeros(11, 13))); +***** test + Dzz = stk_dist(z, z); + assert(isequal(Dzz, zeros(7))); +***** test + Dxz = stk_dist(x, z); + assert(stk_isequal_tolabs(Dxz, sqrt(5)*ones(11, 7))); +***** test + x = randn(5,3); + y = randn(5,3); + D1 = stk_dist(x, y, true); % pairwise + D2 = stk_dist(x, y); + assert(stk_isequal_tolabs(D1, diag(D2))); +***** test + x = randn(5,3); + D1 = stk_dist(x, [], true); % pairwise + assert(stk_isequal_tolabs(D1, zeros(5, 1))); + D1 = stk_dist(x, x, true); % pairwise + assert(stk_isequal_tolabs(D1, zeros(5, 1))); +13 tests, 13 passed, 0 known failure, 0 skipped +[inst/misc/dist/stk_filldist_discretized.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/dist/stk_filldist_discretized.m +***** error stk_filldist_discretized(0.0) % incorrect nb of arguments +***** error stk_filldist_discretized(0.0, []) % second arg is empty +***** error stk_filldist_discretized([], 0.0) % first arg is empty +***** test + d = 3; x = rand(7, d); y = rand(20, d); + fd1 = stk_filldist_discretized(x, y); + fd2 = stk_filldist_discretized(stk_dataframe(x), stk_dataframe(y)); + assert(stk_isequal_tolabs(fd1, fd2)); +***** test + n = 5; + for dim = 1:10, + x = rand(n, dim); + fd = stk_filldist_discretized(x, x); + assert(stk_isequal_tolabs(fd, 0.0)); + end +***** test + for dim = 1:10, + x = rand(1, dim); + y = rand(1, dim); + fd = stk_filldist_discretized(x, y); + assert(stk_isequal_tolabs(fd, norm(x - y))); + end +***** test + n = 4; + for dim = 2:10, + x = zeros(n, dim); + y = rand(1, dim); + fd = stk_filldist_discretized(x, y); + assert(stk_isequal_tolabs(fd, max(stk_dist(x, y)))); + end +***** test + for dim = [1 3 6], + x = 0.5 * ones(1, dim); + y = stk_sampling_regulargrid(2^dim, dim); % [0; 1]^d is the default box + fd = stk_filldist_discretized(x, y); + assert(stk_isequal_tolabs(fd, 0.5 * sqrt(dim))); + end +***** test + for dim = [1 3 7], + x = zeros(1, dim); + y = stk_sampling_regulargrid(3^dim, dim); + [fd, ymax] = stk_filldist_discretized(x, y); + assert(stk_isequal_tolabs(fd, sqrt(dim))); + assert(stk_isequal_tolabs(ymax, ones(1, dim))); + end +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/misc/distrib/stk_distrib_normal_cdf.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_normal_cdf.m +***** assert (stk_isequal_tolrel (stk_distrib_normal_cdf ([1; 3], 1, [1 10]), ... + [0.5, ... % normcdf ((1 - 1) / 1) + 0.5; ... % normcdf ((1 - 1) / 10) + 0.5 * erfc(-sqrt(2)), ... % normcdf ((3 - 1) / 1) + 0.5 * erfc(-0.1*sqrt(2)) ... % normcdf ((3 - 1) / 10) + ], eps)); +***** test + [p, q] = stk_distrib_normal_cdf (10); + assert (isequal (p, 1.0)); + assert (stk_isequal_tolrel (q, 7.6198530241604975e-24, eps)); +***** assert (isequal (stk_distrib_normal_cdf ( 0.0), 0.5)); +***** assert (isequal (stk_distrib_normal_cdf ( inf), 1.0)); +***** assert (isequal (stk_distrib_normal_cdf (-inf), 0.0)); +***** assert (isnan (stk_distrib_normal_cdf ( nan))); +***** assert (isnan (stk_distrib_normal_cdf (0, 0, -1))); +***** assert (isequal (stk_distrib_normal_cdf (0, 0, 0), 1.0)); +***** assert (isequal (stk_distrib_normal_cdf (0, 1, 0), 0.0)); +***** assert (isequal (stk_distrib_normal_cdf (1, 0, 0), 1.0)); +10 tests, 10 passed, 0 known failure, 0 skipped +[inst/misc/distrib/stk_distrib_student_cdf.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_student_cdf.m +***** assert (stk_isequal_tolrel ( ... + stk_distrib_student_cdf ([-1; 0; 1], [1 2], 0, [1 10]), ... + [0.25, ... % tcdf ((-1 - 0)/1, 1) + 4.6473271920707004e-01; ... % tcdf ((-1 - 0)/10, 2) + 0.50, ... % tcdf (( 0 - 0)/1, 1) + 0.50; ... % tcdf (( 0 - 0)/10, 2) + 0.75, ... % tcdf (( 1 - 0)/1, 1) + 5.3526728079292996e-01 ... % tcdf (( 1 - 0)/10, 2) + ], 4 * eps)) +***** test + [p, q] = stk_distrib_student_cdf (1e10, 2); + assert (isequal (p, 1.0)); + assert (stk_isequal_tolrel (q, 4.999999999999999999925e-21, 10 * eps)); +***** assert (isequal (stk_distrib_student_cdf (0.0, 1), 0.5)); +***** assert (isequal (stk_distrib_student_cdf (inf, 1), 1.0)); +***** assert (isequal (stk_distrib_student_cdf (-inf, 1), 0.0)); +***** assert (isnan (stk_distrib_student_cdf (nan, 1))); +6 tests, 6 passed, 0 known failure, 0 skipped [inst/misc/distrib/stk_distrib_bivnorm_cdf.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_bivnorm_cdf.m ***** test @@ -3761,27 +5776,19 @@ ***** assert (isequal (ei, stk_distrib_student_ei (M, nu, mu, sigma, false))); ***** assert (isequal (ei, stk_distrib_student_ei (-M, nu, -mu, sigma, true))); 6 tests, 6 passed, 0 known failure, 0 skipped -[inst/misc/distrib/stk_distrib_normal_cdf.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_normal_cdf.m -***** assert (stk_isequal_tolrel (stk_distrib_normal_cdf ([1; 3], 1, [1 10]), ... - [0.5, ... % normcdf ((1 - 1) / 1) - 0.5; ... % normcdf ((1 - 1) / 10) - 0.5 * erfc(-sqrt(2)), ... % normcdf ((3 - 1) / 1) - 0.5 * erfc(-0.1*sqrt(2)) ... % normcdf ((3 - 1) / 10) +[inst/misc/distrib/stk_distrib_student_pdf.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_student_pdf.m +***** assert (stk_isequal_tolrel ( ... + stk_distrib_student_pdf ([1; 3], [1; 2], [0 1], [1 10]), ... + [0.50 / pi ... % tpdf ((1 - 1) / 10, 1) + 0.10 / pi; ... % tpdf ((1 - 1) / 10, 1) / 10 + 1 / (11 * sqrt(11)) ... % tpdf ((3 - 0) / 1, 2) / 1 + 3.4320590294804165e-02 ... % tpdf ((3 - 1) / 10, 2) / 10 ], eps)); -***** test - [p, q] = stk_distrib_normal_cdf (10); - assert (isequal (p, 1.0)); - assert (stk_isequal_tolrel (q, 7.6198530241604975e-24, eps)); -***** assert (isequal (stk_distrib_normal_cdf ( 0.0), 0.5)); -***** assert (isequal (stk_distrib_normal_cdf ( inf), 1.0)); -***** assert (isequal (stk_distrib_normal_cdf (-inf), 0.0)); -***** assert (isnan (stk_distrib_normal_cdf ( nan))); -***** assert (isnan (stk_distrib_normal_cdf (0, 0, -1))); -***** assert (isequal (stk_distrib_normal_cdf (0, 0, 0), 1.0)); -***** assert (isequal (stk_distrib_normal_cdf (0, 1, 0), 0.0)); -***** assert (isequal (stk_distrib_normal_cdf (1, 0, 0), 1.0)); -10 tests, 10 passed, 0 known failure, 0 skipped +***** assert (isequal (stk_distrib_student_pdf ( inf, 1.0), 0.0)); +***** assert (isequal (stk_distrib_student_pdf (-inf, 1.0), 0.0)); +***** assert (isnan (stk_distrib_student_pdf ( nan, 1.0))); +4 tests, 4 passed, 0 known failure, 0 skipped [inst/misc/distrib/stk_distrib_normal_crps.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_normal_crps.m ***** assert (stk_isequal_tolabs (stk_distrib_normal_crps (0.0, 0.0, 0.0), 0.0)) @@ -3823,26 +5830,37 @@ ***** assert (isequal (ei, stk_distrib_normal_ei (M, mu, sigma, false))); ***** assert (isequal (ei, stk_distrib_normal_ei (-M, -mu, sigma, true))); 6 tests, 6 passed, 0 known failure, 0 skipped -[inst/misc/distrib/stk_distrib_student_cdf.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/distrib/stk_distrib_student_cdf.m -***** assert (stk_isequal_tolrel ( ... - stk_distrib_student_cdf ([-1; 0; 1], [1 2], 0, [1 10]), ... - [0.25, ... % tcdf ((-1 - 0)/1, 1) - 4.6473271920707004e-01; ... % tcdf ((-1 - 0)/10, 2) - 0.50, ... % tcdf (( 0 - 0)/1, 1) - 0.50; ... % tcdf (( 0 - 0)/10, 2) - 0.75, ... % tcdf (( 1 - 0)/1, 1) - 5.3526728079292996e-01 ... % tcdf (( 1 - 0)/10, 2) - ], 4 * eps)) -***** test - [p, q] = stk_distrib_student_cdf (1e10, 2); - assert (isequal (p, 1.0)); - assert (stk_isequal_tolrel (q, 4.999999999999999999925e-21, 10 * eps)); -***** assert (isequal (stk_distrib_student_cdf (0.0, 1), 0.5)); -***** assert (isequal (stk_distrib_student_cdf (inf, 1), 1.0)); -***** assert (isequal (stk_distrib_student_cdf (-inf, 1), 0.0)); -***** assert (isnan (stk_distrib_student_cdf (nan, 1))); +[inst/misc/optim/stk_minimize_unconstrained.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/stk_minimize_unconstrained.m +***** test % Call fminsearch using function name + if stk_optim_isavailable ('fminsearch') + assert (stk_optim_testmin_unc ('fminsearch')); + end +***** test % Call fminsearch directly, using algorithm object + if stk_optim_isavailable ('fminsearch') + algo = stk_optim_fminsearch ('TolX', 1e-12, 'TolFun', 1e-12); + assert (stk_optim_testmin_unc (algo)); + end +***** test % Call sqp using function name + if stk_optim_isavailable ('octavesqp') + assert (stk_optim_testmin_unc ('octavesqp')); + end +***** test % Call sqp directly, using algorithm object + if stk_optim_isavailable ('octavesqp') + algo = stk_optim_octavesqp (); + assert (stk_optim_testmin_unc (algo)); + end +***** error assert (stk_optim_testmin_unc ('InexistentOptimizer')); +***** error assert (stk_optim_testmin_unc (100)); 6 tests, 6 passed, 0 known failure, 0 skipped +[inst/misc/optim/@stk_optim_fmincon/stk_optim_fmincon.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_fmincon/stk_optim_fmincon.m +***** test stk_test_class ('stk_optim_fmincon') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/misc/optim/@stk_optim_octavesqp/stk_optim_octavesqp.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_octavesqp/stk_optim_octavesqp.m +***** test stk_test_class ('stk_optim_octavesqp') +1 test, 1 passed, 0 known failure, 0 skipped [inst/misc/optim/stk_optim_testmin_unc.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/stk_optim_testmin_unc.m ***** shared algo @@ -3874,17 +5892,9 @@ ***** error assert (stk_optim_testmin_box ('InexistentOptimizer')); ***** error assert (stk_optim_testmin_box (100)); 6 tests, 6 passed, 0 known failure, 0 skipped -[inst/misc/optim/@stk_optim_fminsearch/stk_optim_fminsearch.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_fminsearch/stk_optim_fminsearch.m -***** test stk_test_class ('stk_optim_fminsearch') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/misc/optim/@stk_optim_fmincon/stk_optim_fmincon.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_fmincon/stk_optim_fmincon.m -***** test stk_test_class ('stk_optim_fmincon') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/misc/optim/@stk_optim_octavesqp/stk_optim_octavesqp.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_octavesqp/stk_optim_octavesqp.m -***** test stk_test_class ('stk_optim_octavesqp') +[inst/misc/optim/@stk_optim_optimizer_/stk_optim_optimizer_.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_optimizer_/stk_optim_optimizer_.m +***** test stk_test_class ('stk_optim_optimizer_') 1 test, 1 passed, 0 known failure, 0 skipped [inst/misc/optim/stk_optim_testmin_box.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/stk_optim_testmin_box.m @@ -3894,33 +5904,76 @@ ***** assert (stk_optim_testmin_box (algo)); ***** assert (~ stk_optim_testmin_box ('dudule')); 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/misc/optim/@stk_optim_optimizer_/stk_optim_optimizer_.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_optimizer_/stk_optim_optimizer_.m -***** test stk_test_class ('stk_optim_optimizer_') +[inst/misc/optim/@stk_optim_fminsearch/stk_optim_fminsearch.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/@stk_optim_fminsearch/stk_optim_fminsearch.m +***** test stk_test_class ('stk_optim_fminsearch') 1 test, 1 passed, 0 known failure, 0 skipped -[inst/misc/optim/stk_minimize_unconstrained.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/misc/optim/stk_minimize_unconstrained.m -***** test % Call fminsearch using function name - if stk_optim_isavailable ('fminsearch') - assert (stk_optim_testmin_unc ('fminsearch')); - end -***** test % Call fminsearch directly, using algorithm object - if stk_optim_isavailable ('fminsearch') - algo = stk_optim_fminsearch ('TolX', 1e-12, 'TolFun', 1e-12); - assert (stk_optim_testmin_unc (algo)); - end -***** test % Call sqp using function name - if stk_optim_isavailable ('octavesqp') - assert (stk_optim_testmin_unc ('octavesqp')); - end -***** test % Call sqp directly, using algorithm object - if stk_optim_isavailable ('octavesqp') - algo = stk_optim_octavesqp (); - assert (stk_optim_testmin_unc (algo)); +[inst/param/estim/stk_param_relik.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_relik.m +***** shared f, xi, zi, NI, model, C, dC1, dC2 + + f = @(x)(- (0.8 * x(:, 1) + sin (5 * x(:, 2) + 1) ... + + 0.1 * sin (10 * x(:, 3)))); + DIM = 3; NI = 20; box = repmat ([-1.0; 1.0], 1, DIM); + xi = stk_sampling_halton_rr2 (NI, DIM, box); + zi = stk_feval (f, xi); + + SIGMA2 = 1.0; % variance parameter + NU = 4.0; % regularity parameter + RHO1 = 0.4; % scale (range) parameter + + model = stk_model (@stk_materncov_aniso); + model.param = log ([SIGMA2; NU; 1/RHO1 * ones(DIM, 1)]); +***** error [C, dC1, dC2] = stk_param_relik (); +***** error [C, dC1, dC2] = stk_param_relik (model); +***** error [C, dC1, dC2] = stk_param_relik (model, xi); +***** test [C, dC1, dC2] = stk_param_relik (model, xi, zi); +***** test + TOL_REL = 0.01; + assert (stk_isequal_tolrel (C, 21.6, TOL_REL)); + assert (stk_isequal_tolrel (dC1, [4.387 -0.1803 0.7917 0.1392 2.580]', TOL_REL)); + assert (isequal (dC2, [])); +***** shared xi, zi, model, TOL_REL + xi = [-1 -.6 -.2 .2 .6 1]'; + zi = [-0.11 1.30 0.23 -1.14 0.36 -0.37]'; + model = stk_model (@stk_materncov_iso); + model.param = log ([1.0 4.0 2.5]); + model.lognoisevariance = log (0.01); + TOL_REL = 0.01; +***** test % Another simple 1D check + [C, dC1, dC2] = stk_param_relik (model, xi, zi); + assert (stk_isequal_tolrel (C, 6.327, TOL_REL)); + assert (stk_isequal_tolrel (dC1, [0.268 0.0149 -0.636]', TOL_REL)); + assert (stk_isequal_tolrel (dC2, -1.581e-04, TOL_REL)); +***** test % Same 1D test with simple kriging + model.lm = stk_lm_null; + [C, dC1, dC2] = stk_param_relik (model, xi, zi); + assert (stk_isequal_tolrel (C, 7.475, TOL_REL)); + assert (stk_isequal_tolrel (dC1, [0.765 0.0238 -1.019]', TOL_REL)); + assert (stk_isequal_tolrel (dC2, 3.0517e-03, TOL_REL)); +***** test % Check the gradient on a 2D test case + + f = @stk_testfun_braninhoo; + DIM = 2; + BOX = [[-5; 10], [0; 15]]; + NI = 20; + TOL_REL = 1e-2; + DELTA = 1e-6; + + model = stk_model (@stk_materncov52_iso, DIM); + model.param = [1 1]; + + xi = stk_sampling_halton_rr2 (NI, DIM, BOX); + zi = stk_feval (f, xi); + + for range = [0.3 2 10] + model.param(2) = - log (range); + for diff = 1:2 + assert (stk_test_critgrad ... + (@stk_param_relik, model, xi, zi, diff, 1e-6)); + end end -***** error assert (stk_optim_testmin_unc ('InexistentOptimizer')); -***** error assert (stk_optim_testmin_unc (100)); -6 tests, 6 passed, 0 known failure, 0 skipped +8 tests, 8 passed, 0 known failure, 0 skipped [inst/param/estim/stk_param_init.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_init.m ***** test @@ -3973,7 +6026,7 @@ stk_param_estim at line 139 column 15 __test__ at line 5 column 14 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 ***** test model = stk_model (@stk_materncov32_iso); @@ -4015,7 +6068,7 @@ stk_predict at line 104 column 16 __test__ at line 6 column 5 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 ***** test model = stk_model (@stk_gausscov_aniso); @@ -4033,7 +6086,7 @@ stk_predict at line 104 column 16 __test__ at line 6 column 5 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 ***** test % Homoscedastic case / do_estim_lnv = true model = stk_model (@stk_materncov32_iso); @@ -4050,7 +6103,7 @@ stk_param_init at line 87 column 18 __test__ at line 4 column 40 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 ***** error % Homoscedastic case / do_estim_lnv = false / model.lnv = nan model = stk_model (@stk_materncov32_iso); @@ -4080,7 +6133,7 @@ stk_param_init at line 87 column 18 __test__ at line 3 column 15 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 ***** test % Constant response, noisy model model.lognoisevariance = nan; @@ -4094,46 +6147,9 @@ stk_param_init at line 87 column 18 __test__ at line 4 column 15 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 302 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 734 column 31 15 tests, 15 passed, 0 known failure, 0 skipped -[inst/param/estim/stk_param_gls.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_gls.m -***** shared xi, zi, model, beta, sigma2 - xi = (1:10)'; zi = sin (xi); - model = stk_model (@stk_materncov52_iso); - model.param = [0.0 0.0]; -***** test - model.lm = stk_lm_constant (); - [beta, sigma2] = stk_param_gls (model, xi, zi); -***** assert (stk_isequal_tolabs (beta, 0.1346064, 1e-6)) -***** assert (stk_isequal_tolabs (sigma2, 0.4295288, 1e-6)) -***** test - model.lm = stk_lm_affine (); - [beta, sigma2] = stk_param_gls (model, xi, zi); -***** assert (stk_isequal_tolabs (beta, [0.4728342; -0.0614960], 1e-6)) -***** assert (stk_isequal_tolabs (sigma2, 0.4559431, 1e-6)) -***** test - model.lm = stk_lm_null (); - [beta, sigma2] = stk_param_gls (model, xi, zi); -***** assert (isequal (beta, zeros (0, 1))) -***** assert (stk_isequal_tolabs (sigma2, 0.3977993, 1e-6)) -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/param/estim/stk_param_init_lnv.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_init_lnv.m -***** test - f = @(x)(- (0.8 * x + sin (5 * x + 1) + 0.1 * sin (10 * x))); - ni = 20; - xi = (linspace (-1, 1, ni))' + 0.2 * (randn (ni, 1)); - zi = stk_feval (f, xi); - - model = stk_model (@stk_materncov_iso); - model.param = log ([1; 5/2; 1/0.4]); - model.lognoisevariance = nan; - lnv = stk_param_init_lnv (model, xi, zi); - - assert ((isscalar (lnv)) && (lnv > -30) && (lnv < 30)); -1 test, 1 passed, 0 known failure, 0 skipped [inst/param/estim/stk_param_estim.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_estim.m ***** shared f, xi, zi, NI, param0, param1, model @@ -4160,7 +6176,7 @@ stk_param_estim at line 139 column 15 __test__ at line 4 column 9 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 ***** test % same thing, with empty lnv0 (ok) param2 = stk_param_estim (model, xi, zi, param0, []); @@ -4173,7 +6189,7 @@ stk_param_estim at line 139 column 15 __test__ at line 3 column 9 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 ***** error % same thing, with lnv0 == NaN (not ok as a starting point) param2 = stk_param_estim (model, xi, zi, param0, nan); @@ -4190,7 +6206,7 @@ stk_param_estim at line 139 column 15 __test__ at line 3 column 9 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 ***** test % noiseless zi = stk_feval (f, xi); @@ -4207,7 +6223,7 @@ stk_param_estim at line 139 column 15 __test__ at line 4 column 9 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 warning: sqp: QP subproblem is non-convex and unbounded warning: called from @@ -4217,7 +6233,7 @@ stk_param_estim at line 139 column 15 __test__ at line 5 column 9 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 ***** test % noisy NOISE_STD_TRUE = 0.1; @@ -4239,7 +6255,7 @@ stk_param_estim at line 95 column 5 __test__ at line 5 column 8 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 warning: Parameter estimation is impossible with constant-response data. warning: called from @@ -4250,77 +6266,163 @@ stk_param_estim at line 110 column 30 __test__ at line 5 column 8 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 326 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 742 column 31 warning: Something went wrong during the optimization crit0 = -15.421654, crit_opt = -15.421654: crit0 < crit_opt 11 tests, 11 passed, 0 known failure, 0 skipped -[inst/param/estim/stk_param_relik.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_relik.m -***** shared f, xi, zi, NI, model, C, dC1, dC2 - - f = @(x)(- (0.8 * x(:, 1) + sin (5 * x(:, 2) + 1) ... - + 0.1 * sin (10 * x(:, 3)))); - DIM = 3; NI = 20; box = repmat ([-1.0; 1.0], 1, DIM); - xi = stk_sampling_halton_rr2 (NI, DIM, box); +[inst/param/estim/stk_param_init_lnv.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_init_lnv.m +***** test + f = @(x)(- (0.8 * x + sin (5 * x + 1) + 0.1 * sin (10 * x))); + ni = 20; + xi = (linspace (-1, 1, ni))' + 0.2 * (randn (ni, 1)); zi = stk_feval (f, xi); - SIGMA2 = 1.0; % variance parameter - NU = 4.0; % regularity parameter - RHO1 = 0.4; % scale (range) parameter + model = stk_model (@stk_materncov_iso); + model.param = log ([1; 5/2; 1/0.4]); + model.lognoisevariance = nan; + lnv = stk_param_init_lnv (model, xi, zi); - model = stk_model (@stk_materncov_aniso); - model.param = log ([SIGMA2; NU; 1/RHO1 * ones(DIM, 1)]); -***** error [C, dC1, dC2] = stk_param_relik (); -***** error [C, dC1, dC2] = stk_param_relik (model); -***** error [C, dC1, dC2] = stk_param_relik (model, xi); -***** test [C, dC1, dC2] = stk_param_relik (model, xi, zi); + assert ((isscalar (lnv)) && (lnv > -30) && (lnv < 30)); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/param/estim/stk_param_gls.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/param/estim/stk_param_gls.m +***** shared xi, zi, model, beta, sigma2 + xi = (1:10)'; zi = sin (xi); + model = stk_model (@stk_materncov52_iso); + model.param = [0.0 0.0]; ***** test - TOL_REL = 0.01; - assert (stk_isequal_tolrel (C, 21.6, TOL_REL)); - assert (stk_isequal_tolrel (dC1, [4.387 -0.1803 0.7917 0.1392 2.580]', TOL_REL)); - assert (isequal (dC2, [])); -***** shared xi, zi, model, TOL_REL - xi = [-1 -.6 -.2 .2 .6 1]'; - zi = [-0.11 1.30 0.23 -1.14 0.36 -0.37]'; - model = stk_model (@stk_materncov_iso); - model.param = log ([1.0 4.0 2.5]); - model.lognoisevariance = log (0.01); - TOL_REL = 0.01; -***** test % Another simple 1D check - [C, dC1, dC2] = stk_param_relik (model, xi, zi); - assert (stk_isequal_tolrel (C, 6.327, TOL_REL)); - assert (stk_isequal_tolrel (dC1, [0.268 0.0149 -0.636]', TOL_REL)); - assert (stk_isequal_tolrel (dC2, -1.581e-04, TOL_REL)); -***** test % Same 1D test with simple kriging - model.lm = stk_lm_null; - [C, dC1, dC2] = stk_param_relik (model, xi, zi); - assert (stk_isequal_tolrel (C, 7.475, TOL_REL)); - assert (stk_isequal_tolrel (dC1, [0.765 0.0238 -1.019]', TOL_REL)); - assert (stk_isequal_tolrel (dC2, 3.0517e-03, TOL_REL)); -***** test % Check the gradient on a 2D test case + model.lm = stk_lm_constant (); + [beta, sigma2] = stk_param_gls (model, xi, zi); +***** assert (stk_isequal_tolabs (beta, 0.1346064, 1e-6)) +***** assert (stk_isequal_tolabs (sigma2, 0.4295288, 1e-6)) +***** test + model.lm = stk_lm_affine (); + [beta, sigma2] = stk_param_gls (model, xi, zi); +***** assert (stk_isequal_tolabs (beta, [0.4728342; -0.0614960], 1e-6)) +***** assert (stk_isequal_tolabs (sigma2, 0.4559431, 1e-6)) +***** test + model.lm = stk_lm_null (); + [beta, sigma2] = stk_param_gls (model, xi, zi); +***** assert (isequal (beta, zeros (0, 1))) +***** assert (stk_isequal_tolabs (sigma2, 0.3977993, 1e-6)) +9 tests, 9 passed, 0 known failure, 0 skipped +[inst/utils/stk_generate_samplepaths.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/utils/stk_generate_samplepaths.m +***** shared model, xi, zi, xt, n, nb_paths + dim = 1; n = 50; nb_paths = 5; + model = stk_model (@stk_materncov32_iso, dim); + model.param = log ([1.0; 2.9]); + xt = stk_sampling_regulargrid (n, dim, [-1.0; 1.0]); + xi = [xt(1, :); xt(end, :)]; zi = [0; 0]; +***** error zsim = stk_generate_samplepaths (); +***** error zsim = stk_generate_samplepaths (model); +***** test zsim = stk_generate_samplepaths (model, xt); +***** test zsim = stk_generate_samplepaths (model, xt, nb_paths); +***** test zsim = stk_generate_samplepaths (model, xi, zi, xt); +***** test zsim = stk_generate_samplepaths (model, xi, zi, xt, nb_paths); +***** test + zsim = stk_generate_samplepaths (model, xt); + assert (isequal (size (zsim), [n, 1])); +***** test + zsim = stk_generate_samplepaths (model, xt, nb_paths); + assert (isequal (size (zsim), [n, nb_paths])); +***** test % duplicate simulation points + zsim = stk_generate_samplepaths (model, [xt; xt], nb_paths); + assert (isequal (size (zsim), [2 * n, nb_paths])); + assert (isequal (zsim(1:n, :), zsim((n + 1):end, :))); +***** test % simulation points equal to observation points (noiseless model) + % https://sourceforge.net/p/kriging/tickets/14/ + zsim = stk_generate_samplepaths (model, xt, zeros (n, 1), xt); + assert (isequal (zsim, zeros (n, 1))); +10 tests, 10 passed, 0 known failure, 0 skipped +[inst/utils/stk_conditioning.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/utils/stk_conditioning.m +***** shared n, m, ni, xi_ind, lambda, zsim, zi - f = @stk_testfun_braninhoo; - DIM = 2; - BOX = [[-5; 10], [0; 15]]; - NI = 20; - TOL_REL = 1e-2; - DELTA = 1e-6; + n = 50; m = 5; ni = 10; xi_ind = 1:ni; + lambda = 1/ni * ones (ni, n); % prediction == averaging + zsim = ones (n, m); % const unconditioned samplepaths + zi = zeros (ni, 1); % conditioning by zeros +***** error zsimc = stk_conditioning (); +***** error zsimc = stk_conditioning (lambda); +***** error zsimc = stk_conditioning (lambda, zi); +***** test zsimc = stk_conditioning (lambda, zi, zsim); +***** test zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); +***** test + zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); + assert (stk_isequal_tolabs (double (zsimc), zeros (n, m))); +***** test + zi = 2 * ones (ni, 1); % conditioning by twos + zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); + assert (stk_isequal_tolabs (double (zsimc), 2 * ones (n, m))); +***** test + DIM = 1; nt = 400; + xt = stk_sampling_regulargrid (nt, DIM, [-1.0; 1.0]); - model = stk_model (@stk_materncov52_iso, DIM); - model.param = [1 1]; + NI = 6; xi_ind = [1 20 90 200 300 350]; + xi = xt(xi_ind, 1); + zi = (1:NI)'; % linear response ;-) - xi = stk_sampling_halton_rr2 (NI, DIM, BOX); - zi = stk_feval (f, xi); + % Carry out the kriging prediction at points xt + model = stk_model (@stk_materncov52_iso); + model.param = log ([1.0; 2.9]); + [ignore_zp, lambda] = stk_predict (model, xi, [], xt); - for range = [0.3 2 10] - model.param(2) = - log (range); - for diff = 1:2 - assert (stk_test_critgrad ... - (@stk_param_relik, model, xi, zi, diff, 1e-6)); - end - end + % Generate (unconditional) sample paths according to the model + NB_PATHS = 10; + zsim = stk_generate_samplepaths (model, xt, NB_PATHS); + zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); 8 tests, 8 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_cubic/feval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_cubic/feval.m +***** test + n = 15; d = 4; + x = stk_sampling_randunif (n, d); + P = feval (stk_lm_cubic (), x); + assert (isequal (size (P), [n, 1 + d * (11 + d * (6 + d)) / 6])) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_cubic/stk_lm_cubic.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_cubic/stk_lm_cubic.m +***** test stk_test_class ('stk_lm_cubic') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_null/stk_lm_null.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_null/stk_lm_null.m +***** test stk_test_class ('stk_lm_null') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_null/feval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_null/feval.m +***** test + n = 15; d = 4; + x = stk_sampling_randunif (n, d); + P = feval (stk_lm_null (), x); + assert (isequal (size (P), [n, 0])); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_affine/stk_lm_affine.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_affine/stk_lm_affine.m +***** test stk_test_class ('stk_lm_affine') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_affine/feval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_affine/feval.m +***** test + n = 15; d = 4; + x = stk_sampling_randunif (n, d); + P = feval (stk_lm_affine (), x); + assert (isequal (size (P), [n, d + 1])); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_constant/stk_lm_constant.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_constant/stk_lm_constant.m +***** test stk_test_class ('stk_lm_constant') +1 test, 1 passed, 0 known failure, 0 skipped +[inst/lm/@stk_lm_constant/feval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_constant/feval.m +***** test + n = 15; d = 4; + x = stk_sampling_randunif (n, d); + P = feval (stk_lm_constant (), x); + assert (isequal (size (P), [n, 1])); +1 test, 1 passed, 0 known failure, 0 skipped [inst/lm/stk_lm_polynomial.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/stk_lm_polynomial.m ***** error lm = stk_lm_polynomial (); @@ -4340,18 +6442,6 @@ lm = stk_lm_polynomial (3); assert (isa (lm, 'stk_lm_cubic')); 6 tests, 6 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_cubic/feval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_cubic/feval.m -***** test - n = 15; d = 4; - x = stk_sampling_randunif (n, d); - P = feval (stk_lm_cubic (), x); - assert (isequal (size (P), [n, 1 + d * (11 + d * (6 + d)) / 6])) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_cubic/stk_lm_cubic.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_cubic/stk_lm_cubic.m -***** test stk_test_class ('stk_lm_cubic') -1 test, 1 passed, 0 known failure, 0 skipped [inst/lm/@stk_lm_quadratic/stk_lm_quadratic.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_quadratic/stk_lm_quadratic.m ***** test stk_test_class ('stk_lm_quadratic') @@ -4378,46 +6468,26 @@ assert (isa (lm, 'stk_lm_matrix')); assert (isequal (data(idx, :), feval (lm, idx))); 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_constant/feval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_constant/feval.m -***** test - n = 15; d = 4; - x = stk_sampling_randunif (n, d); - P = feval (stk_lm_constant (), x); - assert (isequal (size (P), [n, 1])); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_constant/stk_lm_constant.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_constant/stk_lm_constant.m -***** test stk_test_class ('stk_lm_constant') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_affine/feval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_affine/feval.m -***** test - n = 15; d = 4; - x = stk_sampling_randunif (n, d); - P = feval (stk_lm_affine (), x); - assert (isequal (size (P), [n, d + 1])); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_affine/stk_lm_affine.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_affine/stk_lm_affine.m -***** test stk_test_class ('stk_lm_affine') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_null/feval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_null/feval.m -***** test - n = 15; d = 4; - x = stk_sampling_randunif (n, d); - P = feval (stk_lm_null (), x); - assert (isequal (size (P), [n, 0])); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/lm/@stk_lm_null/stk_lm_null.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/lm/@stk_lm_null/stk_lm_null.m -***** test stk_test_class ('stk_lm_null') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/test_functions/stk_testfun_goldsteinprice.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_goldsteinprice.m -***** test % Use with nargin == 0 for visualisation - stk_testfun_goldsteinprice (); close all; +[inst/examples/01_kriging_basics/stk_example_kb07.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb07.m +***** test stk_example_kb07; close all; + +#========================# +# stk_example_kb07 # +#========================# + +'stk_example_kb07' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb07.m + + STK_EXAMPLE_KB07 Simulation of sample paths from a Matern process + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. warning: using the gnuplot graphics toolkit is discouraged The gnuplot graphics toolkit is not actively maintained and has a number @@ -4428,61 +6498,1048 @@ example, if the plot window is closed with a mouse click, Octave will not be notified and will not update its internal list of open figure windows. The qt toolkit is recommended instead. -***** assert (stk_isequal_tolabs ... - (stk_testfun_goldsteinprice ([0, -1]), 3.0, 1e-12)) -2 tests, 2 passed, 0 known failure, 0 skipped -[inst/examples/test_functions/stk_testfun_hartman4.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman4.m -***** test - x = [0.1873 0.1906 0.5566 0.2647 ; - 0.18744768 0.19414868 0.558005333 0.26476409]; - y = stk_testfun_hartman4 (x); - assert (stk_isequal_tolabs (y, ... - [-3.729722308557300; -3.729840440436292], 1e-15)); + line 0: warning: iconv failed to convert degree sign 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/test_functions/stk_testfun_hartman3.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman3.m -***** test - x1 = [0.1, 0.55592003, 0.85218259]; - y1 = -3.862634748621772; +[inst/examples/01_kriging_basics/stk_example_kb02.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb02.m +***** test stk_example_kb02; close all; - x2 = [0.114614 0.554649 0.852547]; - y2 = -3.862747199255087; +#========================# +# stk_example_kb02 # +#========================# - y = stk_testfun_hartman3 ([x1; x2]); - assert (stk_isequal_tolabs (y, [y1; y2], 1e-15)) +'stk_example_kb02' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb02.m + + STK_EXAMPLE_KB02 Ordinary kriging in 1D with parameter estimation + + This example shows how to estimate covariance parameters and compute + ordinary kriging predictions on a one-dimensional noiseless dataset. + + The model and data are the same as in stk_example_kb01, but this time the + parameters of the covariance function are estimated using the Restricted + Maximum Likelihood (ReML) method. + + See also: stk_example_kb01, stk_example_kb02n + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +model = + + scalar structure containing the fields: + + covariance_type = @stk_materncov_iso + lm = + + + + dim = 1 + param = + + -0.2108 + 2.3026 + 0.7562 + + lognoisevariance = -Inf + + line 0: warning: iconv failed to convert degree sign + + + | True function and observed data + 1.5 +|+ + | ***G* +--------------------+ + #|#######***#####***########################|***?***True function| + 1 +|+#####**#########***######################+---G---Observations-+ + #|####**#############***######################################### + #|###**################**######################################## + 0.5 +|+#**##################**############################***######## + #|#G*####################**########################****##*G**#### + #|**######################**#####################G**########***## + F1 0 *|+########################**###################**############*** + G|##########################**#################**###############** + #|###########################**###############**#################** + -0.5 +|+###########################**#############**################## + #|#############################**###########*#################### + #|##############################*G*#######**##################### + -1 +|+###############################**#####**###################### + #|#################################******######################## + +|------------------------------------------------------------------ + -1.5 +-+##############+###############+################+############## + + -1 -0.5 0 0.5 1 + 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/test_functions/stk_testcase_truss3.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testcase_truss3.m -***** shared tc, xd, n - tc = stk_testcase_truss3 (); n = 5; - xd = stk_sampling_randunif (n, [], tc.search_domain); -***** test - v = stk_testfun_truss3_vol (xd, tc.constants); - z = stk_testfun_truss3_bb (xd, tc.constants); - assert (isequal (size (v), [n 1])); - assert (isequal (size (z), [n 5])); -***** test - F = stk_dataframe (zeros (n, 2), {'F1' 'F2'}); - F(:, 1) = tc.constants.F1_mean + tc.constants.F1_std * randn (n, 1); - F(:, 2) = tc.constants.F2_mean + tc.constants.F2_std * randn (n, 1); - x = [xd F]; - v = stk_testfun_truss3_vol (x, tc.constants); - z = stk_testfun_truss3_bb (x, tc.constants); - assert (isequal (size (v), [n 1])); - assert (isequal (size (z), [n 5])); -2 tests, 2 passed, 0 known failure, 0 skipped -[inst/examples/test_functions/stk_testfun_hartman6.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman6.m -***** test - x1 = [0.20169 0.150011 0.476874 0.275332 0.311652 0.657300]; - y1 = -3.322368011391339; +[inst/examples/01_kriging_basics/stk_example_kb05.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb05.m +***** test stk_example_kb05; close all; - x2 = [0.20168952 0.15001069 0.47687398 0.27533243 0.31165162 0.65730054]; - y2 = -3.322368011415512; +#========================# +# stk_example_kb05 # +#========================# - y = stk_testfun_hartman6 ([x1; x2]); - assert (stk_isequal_tolabs (y, [y1; y2], 1e-15)) +'stk_example_kb05' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb05.m + + STK_EXAMPLE_KB05 Generation of conditioned sample paths + + A Matern Gaussian process model is used, with constant but unknown mean + (ordinary kriging) and known covariance parameters. + + Given noiseless observations from the unknown function, a batch of conditioned + sample paths is drawn using the "conditioning by kriging" technique. In short, + this means that unconditioned sample path are simulated first (using + stk_generate_samplepaths), and then conditioned on the observations by kriging + (using stk_conditioning). + + Note: in this example, for pedagogical purposes, conditioned samplepaths are + simulated in two steps: first, unconditioned samplepaths are simulated; + second, conditioned samplepaths are obtained using conditioning by kriging. + In practice, these two steps can be carried out all at once using + stk_generate_samplepath (see, e.g., stk_example_kb09). + + See also: stk_generate_samplepaths, stk_conditioning, stk_example_kb09 + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb03.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb03.m +***** test stk_example_kb03; close all; + +#========================# +# stk_example_kb03 # +#========================# + +'stk_example_kb03' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb03.m + + STK_EXAMPLE_KB03 Ordinary kriging in 2D + + An anisotropic Matern covariance function is used for the Gaussian Process + (GP) prior. The parameters of this covariance function (variance, regularity + and ranges) are estimated using the Restricted Maximum Likelihood (ReML) + method. + + The mean function of the GP prior is assumed to be constant and unknown. This + default choice can be overridden by means of the model.lm property. + + The function is sampled on a space-filling Latin Hypercube design, and the + data is assumed to be noiseless. + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. + +BOX = 2-dimensional hyper-rectangle (stk_hrect object): + + : x_1 x_2 + lower_bounds : -5 0 + upper_bounds : 10 15 + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb06.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb06.m +***** test stk_example_kb06; close all; + +#========================# +# stk_example_kb06 # +#========================# + +'stk_example_kb06' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb06.m + + STK_EXAMPLE_KB06 Ordinary kriging VS kriging with a linear trend + + The same dataset is analyzed using two variants of kriging. + + The left panel shows the result of ordinary kriging, in other words, Gaussian + process interpolation assuming a constant (but unknown) mean. The right panel + shows the result of adding a linear trend in the mean of the Gaussian process. + + The difference with the left plot is clear in extrapolation: the first predic- + tor exhibits a "mean reverting" behaviour, while the second one captures an + increasing trend in the data. + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb02n.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb02n.m +***** test stk_example_kb02n; close all; + +#=========================# +# stk_example_kb02n # +#=========================# + +'stk_example_kb02n' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb02n.m + + STK_EXAMPLE_KB02N Noisy ordinary kriging in 1D with parameter estimation + + This example shows how to estimate covariance parameters and compute + ordinary kriging predictions on a one-dimensional noisy dataset. + + The model and data are the same as in stk_example_kb02, but this time the + parameters of the covariance function and the variance of the noise are + jointly estimated using the Restricted Maximum Likelihood (ReML) method. + + See also: stk_example_kb01n, stk_example_kb02 + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +model = + + scalar structure containing the fields: + + covariance_type = @stk_materncov_iso + lm = + + + + dim = 1 + param = + + -0.098610 + 2.302585 + 0.613435 + + lognoisevariance = -3.0915 + +True noise variance = 0.0400 +Estimated noise variance = 0.0454 + + line 0: warning: iconv failed to convert degree sign + + + | True function and noisy observed data + 1.5 +|+ + | G ***** +--------------------+ + #|#######***##G##G**########################|***?***True function| + 1 +|+####G**#########**G######################+---G---Observations-+ + #|####**#############***######################################### + #|###**################**######################################## + 0.5 +|+#**##################G*##########################G#***######## + G|#**####################**########################****#G**G*##G# + #|*G######################**#####################***########***## + F1 0 *|+########################**###################**############*** + *|##########################**#################**G##############**G + #|###########################**G##############**#################** + -0.5 +|+#########################G#**#############**################## + #|#############################**###########*G################### + #|##############################***G######**##################### + -1 +|+###############################**#####*G###################### + #|#################################***G**######################## + +|------------------------------------------------------------------ + -1.5 +-+##############+###############+################+############## + + -1 -0.5 0 0.5 1 + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb08.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb08.m +***** test stk_example_kb08; close all; + +#========================# +# stk_example_kb08 # +#========================# + +'stk_example_kb08' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb08.m + + STK_EXAMPLE_KB08 Generation of conditioned sample paths made easy + + It has been demonstrated, in stk_example_kb05, how to generate conditioned + sample paths using unconditioned sample paths and conditioning by kriging. + + This example shows how to do the same in a more concise way, letting STK + take care of the details. + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb01.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb01.m +***** test stk_example_kb01; close all; + +#========================# +# stk_example_kb01 # +#========================# + +'stk_example_kb01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb01.m + + STK_EXAMPLE_KB01 Ordinary kriging in 1D, with noiseless data + + This example shows how to compute ordinary kriging predictions on a + one-dimensional noiseless dataset. + + The word 'ordinary' indicates that the mean function of the GP prior is + assumed to be constant and unknown. + + A Matern covariance function is used for the Gaussian Process (GP) prior. + The parameters of this covariance function are assumed to be known (i.e., + no parameter estimation is performed here). + + Note that the kriging predictor, which is the posterior mean of the GP, + interpolates the data in this noiseless example. + + See also: stk_example_kb01n, stk_example_kb02 + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +model = + + scalar structure containing the fields: + + covariance_type = @stk_materncov_iso + lm = + + + + dim = 1 + param = + + -0.6931 + 1.3863 + 0.9163 + + lognoisevariance = -Inf + + line 0: warning: iconv failed to convert degree sign + + + | True function and observed data + 1.5 +|+ + | ****G** +--------------------+ + #|#######***#####****#######################|***?***True function| + 1 +|+####***##########***#####################+---G---Observations-+ + #|####**##############**######################################### + #|###**################**######################################## + 0.5 +|+#**##################**###########################*****G###### + #|*G######################**######################***######***### + 0 +|*########################**####################G*##########***# + G|##########################**#################***#############*** + #|###########################**###############**#################** + -0.5 +|+###########################**#############**################## * + #|#############################**###########**################### + #|##############################*G#########**#################### + -1 +|+##############################***#####**###################### + #|#################################*******####################### + +|------------------------------------------------------------------ + -1.5 +-+##############+###############+################+############## + + -1 -0.5 0 0.5 1 + input variable x + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb01n.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb01n.m +***** test stk_example_kb01n; close all; + +#=========================# +# stk_example_kb01n # +#=========================# + +'stk_example_kb01n' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb01n.m + + STK_EXAMPLE_KB01N Ordinary kriging in 1D, with noisy data + + This example shows how to compute ordinary kriging predictions on a + one-dimensional noisy dataset. + + The Gaussian Process (GP) prior is the same as in stk_example_kb01. + + The observation noise is Gaussian and homoscedastic (constant variance). + Its variance is assumed to be known. + + Note that the kriging predictor, which is the posterior mean of the GP, + does NOT interpolate the data in this noisy example. + + See also: stk_example_kb01, stk_example_kb02n + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +model = + + scalar structure containing the fields: + + covariance_type = @stk_materncov_iso + lm = + + + + dim = 1 + param = + + -0.6931 + 1.3863 + 0.9163 + + lognoisevariance = -3.2189 + + line 0: warning: iconv failed to convert degree sign + + + | True function and observed data + 1.5 +|+ + | G******* +--------------------+ + #|#######***##G##G***#######################|***?***True function| + 1 +|+####G**##########*G*#####################+---G---Observations-+ + #|####**##############**######################################### + #|###**################*G###########################G############ + 0.5 G|+#**##################**###########################******G###G# + #|*G######################**######################***###G##***### + 0 +|*########################**####################**##########***# + *|##########################**#################**G#############*** + #|###########################**###############**#################*G + -0.5 +|+#########################G#*G#############**################## * + #|#############################**###########*G################### + #|##############################**#G#######**#################### + -1 +|+##############################***#####*G###################### + #|#################################***G***####################### + +|------------------------------------------------------------------ + -1.5 +-+##############+###############+################+############## + + -1 -0.5 0 0.5 1 + input variable x + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/01_kriging_basics/stk_example_kb09.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb09.m +***** test stk_example_kb09; close all; + +#========================# +# stk_example_kb09 # +#========================# + +'stk_example_kb09' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb09.m + + STK_EXAMPLE_KB09 Generation of sample paths conditioned on noisy observations + + A Matern Gaussian process model is used, with constant but unknown mean + (ordinary kriging) and known covariance parameters. + + Given noisy observations from the unknown function, a batch of conditioned + sample paths is drawn using the "conditioning by kriging" technique + (stk_generate_samplepaths function). + + See also: stk_generate_samplepaths, stk_conditioning, stk_example_kb05 + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/02_design_of_experiments/stk_example_doe06.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe06.m +***** test stk_example_doe06; close all; + +#=========================# +# stk_example_doe06 # +#=========================# + +'stk_example_doe06' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe06.m + + STK_EXAMPLE_DOE06 Sequential design for the estimation of an excursion set + + In this example, we consider the problem of estimating the set + + Gamma = { x in X | f(x) > z_crit }, + + where z_crit is a given value, and/or its volume. + + In a typical "structural reliability analysis" problem, Gamma would + represent the failure region of a certain system, and its volume would + correspond to the probability of failure (assuming a uniform distribution + for the input). + + A Matern 5/2 prior with known parameters is used for the function f, and + the evaluations points are chosen sequentially using any of the sampling + criterion described in [1] (see also [2], section 4.3). + + REFERENCE + + [1] B. Echard, N. Gayton and M. Lemaire (2011). AK-MCS: an active + learning reliability method combining Kriging and Monte Carlo + simulation. Structural Safety, 33(2), 145-154. + + [2] J. Bect, D. Ginsbourger, L. Li, V. Picheny and E. Vazquez (2012). + Sequential design of computer experiments for the estimation of a + probability of failure. Statistics and Computing, 22(3), 773-793. + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. +Volume (reference value): 21.01% + +data_init = <4x2 stk_dataframe array> + + : x z + initial design #1 : 0.000000 0.00000 + initial design #2 : 0.333333 -0.43063 + initial design #3 : 0.666667 -0.66886 + initial design #4 : 1.000000 -1.20558 + + line 0: warning: iconv failed to convert degree sign + + + |-------------------------Groung truth----------------------------| + 1 +|+ + + + + +-+| + +| + + + + +| + #|############################################################### | + 0.5 +|+#############################################################+-+| + #|############################################################### | + #|############################################################### | + $|$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$| + 0 *|*****##***####***#######**#######**##########**########**#####+-+| + #|####****########**#####**#########*##########*##########*###### | + z #|#################***#***###########*########**##########**##### | + -0.5 +|+##################***#############**######**############*####+-+| + #|####################################**####**#############**#### | + #|#####################################******###############**### | + #|----------------------------+##############################**## | + -1 +|***?***z = f(x), below zcrit|###############################*#+-+| + #|###?###z = f(x), above zcrit|###############################*****| + +|-----------------------------------------------------------------| + -1.5 +-+##########+############+#############+############+##########+-+ + 0 0.2 0.4 0.6 0.8 1 + x + +Iteration #1 +| Current sample size: n = 4 +| Volume estimate (plugin): 0.00000 [ref: 0.21010] +| Upper-bound on posterior std: 4.1105e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign +Iteration #2 +| Current sample size: n = 5 +| Volume estimate (plugin): 0.00000 [ref: 0.21010] +| Upper-bound on posterior std: 3.0234e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 4 +|+ + | ######## ######## + 2 +|+##########%%#########%&&&&&&&&&&&%#######%%&&&&&&&&%%### + 0 +|+########################################################## + z #|%%%##%&&&&&&&&&***G*********F*********G*******************G + -2 +|+####################%&&&&&&&&&&&&&&####%&&&&&&#####&&&&&& + -4 +|+#########################%%%%%%###########%%%&&&&&&&%%## + +|------------------------------------------------------------ + -6 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.25 +|+ + + **F* + + +-+| + +| + + *** *** + + | + 0.2 +|+######################**######***######################+-+| + 0.15 +|+########*****########**#########*###########*****######+-+| + #|########**###**#######*##########**########***###***##### | + 0.1 +|**#####**#####*######**###########**######**#######**###+-+| + 0.05 +|***####*######**#####*#############*#####**#########**##+-+| + +|-----------------------------------------------------------| + 0 **+#*****###+#####*****#+###########+#******####+########**** + 0 0.2 0.4 0.6 0.8 + x +Iteration #3 +| Current sample size: n = 6 +| Volume estimate (plugin): 0.10190 [ref: 0.21010] +| Upper-bound on posterior std: 2.7908e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 2 +|+ ####### + 1 +|+ ###### #%%%# %%%%# ##%%%%%%%%%%# + 0 +|+##############################F########################### + -1 +|+&&&&*************G***&&&&%###&===****G****########====&&&& + z #|########%&&&&&&&%######################&&&****************G + -2 +|+########################################%&&&&#######&&&&% + -3 +|+##########################################%%&&&&&&&&&%%# + -4 +|------------------------------------------------------------ + -5 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + * F + + +-+| + +| + + ** *** + + | + 0.4 +|+#######################***###*#*#######################+-+| + 0.3 +|+######################*##*###*#**######################+-+| +criterion #|######################**##*##**##*####################### | + 0.2 +|+#####################*###**#*###**#####################+-+| + 0.1 +|**###################**####*#*####*#####################+-+| + +|-----------------------------------------------------------| + 0 **+#******##+##*********+####***####+**********#+######****** + 0 0.2 0.4 0.6 0.8 + x +Iteration #4 +| Current sample size: n = 7 +| Volume estimate (plugin): 0.11580 [ref: 0.21010] +| Upper-bound on posterior std: 2.2392e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 3 +|+ + 2 +|+ ######## + 1 +|+###########################################%%&&&&&&%%### + 0 +|+#####################F#################################### + z &|&&=*G*************G***=&%#####*G******G**************==&&&# + -1 +|+######%&&&&&&&&&######################%&&&&&#######******G + -2 +|+##########################################%&&&&&&&&&&&&&# + -3 +|------------------------------------------------------------ + -4 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + F * + + +-+| + +| + * * + + | + 0.4 +|+####################***#####*##########################+-+| + 0.3 +|+####################*#*#####*##########################+-+| +criterion #|#####################*#*#####*########################### | + 0.2 +|+####################*#**####*#################**#######+-+| + 0.1 +|***##################*##*####*##############*********###+-+| + +|-----------------------------------------------------------| + 0 **+#*******************#+##******************###+#######***** + 0 0.2 0.4 0.6 0.8 + x +Iteration #5 +| Current sample size: n = 8 +| Volume estimate (plugin): 0.08510 [ref: 0.21010] +| Upper-bound on posterior std: 2.0895e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 3 +|+ + 2 +|+ ######## + 1 +|+##########################################%%&&&&&&&&%### + 0 +|+#######################F################################## + z &|&&**G*************G***G%######*G******G***************=&&&# + -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G + -2 +|+##########################################%&&&&&&&&&&&&&# + -3 +|------------------------------------------------------------ + -4 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + F * + + +-+| + +| + + * * + + | + 0.4 +|+#######################*####*##########################+-+| + 0.3 +|+#######################*####*##########################+-+| +criterion #|########################*####*########################### | + 0.2 +|+#######################*####*###############******#####+-+| + 0.1 +|+######################***###*#############***####***###+-+| + +|-----------------------------------------------------------| + 0 **+#******##+#************#******************###+#######***** + 0 0.2 0.4 0.6 0.8 + x +Iteration #6 +| Current sample size: n = 9 +| Volume estimate (plugin): 0.08790 [ref: 0.21010] +| Upper-bound on posterior std: 1.8957e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign +Iteration #7 +| Current sample size: n = 10 +| Volume estimate (plugin): 0.08860 [ref: 0.21010] +| Upper-bound on posterior std: 1.9751e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 3 +|+ + 2 +|+ ######## + 1 +|+##########################################%%&&&&&&&&%### + 0 +|+#######################F################################## + z &|&&**G*************G***G#######*G******G****************&&&# + -1 +|+#######%%&&&&%#########################&&&&&&########****G + -2 +|+##########################################%%&&&&&&&&&&&&# + -3 +|------------------------------------------------------------ + -4 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + F + + +-+| + +| + + * + + | + 0.4 +|+#######################*####*##########################+-+| + 0.3 +|+#######################*####*##########################+-+| +criterion #|########################*####*########################### | + 0.2 +|+#######################*####*###############*******####+-+| + 0.1 +|+#######################*####*#############***#####***##+-+| + +|-----------------------------------------------------------| + 0 **+#******##+##******************************###+#######***** + 0 0.2 0.4 0.6 0.8 + x +Iteration #8 +| Current sample size: n = 11 +| Volume estimate (plugin): 0.08860 [ref: 0.21010] +| Upper-bound on posterior std: 1.9669e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 3 +|+ + 2 +|+ ######## + 1 +|+##########################################%%&&&&&&&&%### + 0 +|+############################F############################# + z &|&***G*************G***G#######*G******G****************&&&# + -1 +|+#######%%&&&&%#########################&&&&&&########****G + -2 +|+##########################################%%&&&&&&&&&&&&# + -3 +|------------------------------------------------------------ + -4 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + + + +-+| + +| + + + + | + 0.4 +|+############################F##########################+-+| + 0.3 +|+############################*##########################+-+| +criterion #|#############################*########################### | + 0.2 +|+############################*###############*******####+-+| + 0.1 +|+############################*#############***#####***##+-+| + +|-----------------------------------------------------------| + 0 **+#******##+##******************************###+#######***** + 0 0.2 0.4 0.6 0.8 + x +Iteration #9 +| Current sample size: n = 12 +| Volume estimate (plugin): 0.08860 [ref: 0.21010] +| Upper-bound on posterior std: 1.9996e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 3 +|+ + 2 +|+ ######## + 1 +|+##########################################%%&&&&&&&&%### + 0 +|+########################################################## + z &|&***G*************G***G#######*G******G********F*******&&&# + -1 +|+#######%%&&&&%#########################&&&&&&########****G + -2 +|+##########################################%%&&&&&&&&&&&&# + -3 +|------------------------------------------------------------ + -4 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.25 +|+ + + + + +-+| + +| + + + *F* | + 0.2 +|+############################################**#***#####+-+| + 0.15 +|+###########################################**####**####+-+| + #|###########################################**######**#### | + 0.1 +|+########**################################*########**##+-+| + 0.05 +|***####******#############################**#########**#+-+| + +|-----------------------------------------------------------| + 0 **+#*****###+##*****************************####+########**** + 0 0.2 0.4 0.6 0.8 + x +Iteration #10 +| Current sample size: n = 13 +| Volume estimate (plugin): 0.22160 [ref: 0.21010] +| Upper-bound on posterior std: 2.1620e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1.5 +|+ + 1 +|+ ##### + #|###########################################%&&&%&&&&&&%## + 0.5 +|+&&###%&&&&&&%%#########****G*###########%==***G****#&&%# + z 0 +|+###########################################F############## + -0.5 +|+&&&&&************G***#########G**&&%#%****&&#####%==***&& + #|######%&&&&##&&&&&###############*****G*&&%#########===***# + -1 +|------------------------------------------------------------ + -1.5 +-+#########+###########+###########+###########+########### + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + + F + ** +-+| + +| + + + ** + ** | + 0.4 +|+##########################################**######**###+-+| + 0.3 +|+##########################################**######***##+-+| +criterion #|###########################################*#*####**#*### | + 0.2 +|+#########################################**#*####*##*##+-+| + 0.1 +|+#########################################*##*####*##**#+-+| + +|-----------------------------------------------------------| + 0 **+#******##+##******************************###****#####**** + 0 0.2 0.4 0.6 0.8 + x +Iteration #11 +| Current sample size: n = 14 +| Volume estimate (plugin): 0.22200 [ref: 0.21010] +| Upper-bound on posterior std: 1.5742e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1 +|+ + 0.5 +|+ #%%%%%# ***G*&&%%# + #|##################################################F######## + 0 +|+***G******#=====%#%**G*#####**G*######%***######&=***&&% + z -0.5 +|+&&%#&&&&#********G**%#########&***&&%G**%########%==***&% + -1 +|+######%&&&&&&&&&################&*****#############&==***& + #|#########%%%%%#######################################%===*G + -1.5 +|------------------------------------------------------------ + -2 +-+#########+###########+###########+###########+########## + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + + * + F +-+| + +| + + + * + * | + 0.4 +|+#########################################*#######*#####+-+| + 0.3 +|+#########################################*#######**####+-+| +criterion #|##########################################*######***##### | + 0.2 +|+#########################################*######*#*####+-+| + 0.1 +|+#########################################*######*#**###+-+| + +|-----------------------------------------------------------| + 0 **+#******##+##*************************************###****** + 0 0.2 0.4 0.6 0.8 + x +Iteration #12 +| Current sample size: n = 15 +| Volume estimate (plugin): 0.20860 [ref: 0.21010] +| Upper-bound on posterior std: 1.1167e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign +Iteration #13 +| Current sample size: n = 16 +| Volume estimate (plugin): 0.21010 [ref: 0.21010] +| Upper-bound on posterior std: 1.0666e-01 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1 +|+ + | ###### %*** + 0.5 +|+%%###%&&&&&&%##########****G#############&*G*&G**####### + 0 +|+#########################################F################ + z %|&&&*G*********====&****#######*G*######&**%#######***#### + -0.5 +|+#####&&&#####****G*&###########***&&&G**##########&**&%# + -1 +|+######%&&&&&&&&%################&*****#############&***&& + +|------------------------------------------------------------ + -1.5 +-+#########+###########+###########+###########+########%%% + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.5 +|+ + + + F + +-+| + +| + + + * + | + 0.4 +|+#########################################*#############+-+| + 0.3 +|+#########################################*#############+-+| +criterion 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0.21010] +| Upper-bound on posterior std: 2.8009e-02 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1 +|+ + | *** + 0.5 +|+#######################****G##############*G*&G**####### + 0 +|+##########F############################################### + z %|****G*=&#####&****&****#######*G*######&**########***#### + -0.5 +|+##############%&*G*&###########***&&&G**##########&**&%# + -1 +|+################################&*****#############&***&& + +|------------------------------------------------------------ + -1.5 +-+#########+###########+###########+###########+########%%% + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.04 +|+ + + + + +-+| + 0.035 +|+ +F* + + + +-+| + 0.03 +|+##########**###########################################+-+| + 0.025 +|+##########**###########################################+-+| + 0.02 +|+##########**####################################*######+-+| + 0.015 +|+##########**####################################*######+-+| + 0.01 +|+##########***###################################*######+-+| + 0.005 +|-----------------------------------------------------------| + 0 **+***********#********************************************** + 0 0.2 0.4 0.6 0.8 + x +Iteration #17 +| Current sample size: n = 20 +| Volume estimate (plugin): 0.21010 [ref: 0.21010] +| Upper-bound on posterior std: 1.0941e-02 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1 +|+ + | *** + 0.5 +|+#######################****G##############*G*&G**####### + 0 +|+################################################F######### + z %|****G*=&#####&****&****#######*G*######&**########***#### + -0.5 +|+###############&*G*&###########***&&&G**##########&**&%# + -1 +|+################################&*****#############&***&& + +|------------------------------------------------------------ + -1.5 +-+#########+###########+###########+###########+########%%% + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.03 +|+ + + + + +-+| + 0.025 +|+ + + + + +-+| + #|######################################################### | + 0.02 +|+################################################F######+-+| + 0.015 +|+################################################*######+-+| + 0.01 +|+################################################*######+-+| + #|#################################################*####### | + 0.005 +|-----------------------------------------------------------| + 0 **+********************************************************** + 0 0.2 0.4 0.6 0.8 + x +Iteration #18 +| Current sample size: n = 21 +| Volume estimate (plugin): 0.21010 [ref: 0.21010] +| Upper-bound on posterior std: 1.0829e-02 [target: 5.000e-04] + line 0: warning: iconv failed to convert degree sign + + | + 1 +|+ + | *** + 0.5 +|+#######################****G##############*G*&G**####### + 0 +|+########################################################## + z %|F***G*=&#####&****&****#######*G*######&**########***#### + -0.5 +|+###############&*G*&###########***&&&G**##########&**&%# + -1 +|+################################&*****#############%***&& + +|------------------------------------------------------------ + -1.5 +-+#########+###########+###########+###########+########%%% + 0 0.2 0.4 0.6 0.8 + |-----------------------------------------------------------| + 0.005 +|+ + + + + +-+| + +|F + + + + | + 0.004 +|**######################################################+-+| + 0.003 +|**######################################################+-+| + #|**####################################################### | + 0.002 +|+*######################################################+-+| + 0.001 +|+*######################################################+-+| + +|-----------------------------------------------------------| + 0 **+#********************************************************* + 0 0.2 0.4 0.6 0.8 + x +Iteration #19 +| Current sample size: n = 22 +| Volume estimate (plugin): 0.21010 [ref: 0.21010] +| Upper-bound on posterior std: 5.2116e-05 [target: 5.000e-04] + +history = <22x5 stk_dataframe array> + + : x z vol_estim vol_err nmisclass + initial design #1 : 0.000000 0.00000 NaN NaN NaN + initial design #2 : 0.333333 -0.43063 NaN NaN NaN + initial design #3 : 0.666667 -0.66886 NaN NaN NaN + initial design #4 : 1.000000 -1.20558 0.0000 -0.2101 2101 + MC point #07044 : 0.104139 -0.13300 0.0000 -0.2101 2101 + MC point #00165 : 0.497577 0.26517 0.1019 -0.1082 1716 + MC point #06513 : 0.548734 -0.19731 0.1158 -0.0943 1517 + MC point #01405 : 0.400420 -0.08805 0.0851 -0.1250 1250 + MC point #04574 : 0.431707 0.16916 0.0879 -0.1222 1222 + MC point #00505 : 0.513495 0.15925 0.0886 -0.1215 1215 + MC point #07431 : 0.429136 0.15047 0.0886 -0.1215 1215 + MC point #07997 : 0.514602 0.15025 0.0886 -0.1215 1215 + MC point #09432 : 0.823067 0.46672 0.2216 0.0115 671 + MC point #05149 : 0.762323 0.41198 0.2220 0.0119 119 + MC point #04645 : 0.867070 -0.02745 0.2086 -0.0015 15 + MC point #09771 : 0.853664 0.15862 0.2101 0.0000 0 + MC point #01002 : 0.736751 0.15120 0.2101 0.0000 0 + MC point #05596 : 0.191155 0.12427 0.2101 0.0000 0 + MC point #03945 : 0.210809 0.14262 0.2101 0.0000 0 + MC point #02256 : 0.224364 0.12073 0.2101 0.0000 0 + MC point #01998 : 0.854293 0.15044 0.2101 0.0000 0 + MC point #03807 : 0.035170 0.01558 0.2101 0.0000 0 + +Final result: +| Number of evaluations: 4 + 18 = 22. +| Volume estimate (plugin): 21.0100% [ref: 21.0100%] + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/examples/02_design_of_experiments/stk_example_doe01.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe01.m +***** test stk_example_doe01; close all; + +#=========================# +# stk_example_doe01 # +#=========================# + +'stk_example_doe01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe01.m + + STK_EXAMPLE_DOE01 Examples of two-dimensional designs + + All designs are constructed on the hyper-rectangle BOX = [0; 2] x [0; 4]. + + Examples of the following designs are shown: + a) Regular grid --> stk_sampling_regulargrid, + b) "Maximin" latin hypercube sample --> stk_sampling_maximinlhs, + c) RR2-scrambled Halton sequence --> stk_sampling_halton_rr2, + d) Uniformly distributed random sample --> stk_sampling_randunif. + + +Additional help for built-in functions and operators is +available in the online version of the manual. Use the command +'doc ' to search the manual index. + +Help and information about Octave is also available on the WWW +at https://www.octave.org and via the help@octave.org +mailing list. 1 test, 1 passed, 0 known failure, 0 skipped [inst/examples/02_design_of_experiments/stk_example_doe03.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe03.m @@ -4516,30 +7573,6 @@ at https://www.octave.org and via the help@octave.org mailing list. line 0: warning: iconv failed to convert degree sign - - | - 15 +|+ - 10 +|+ ####%%%%%%%%%%%##### ################ - 5 +|+%&&&&&&&&&&&&&&&&&&&&&&%#######%===========&&&&&%%%##### - 0 +|+*====F========########&&&&&#====&#########===##&&&&&&%%# - z &|&***************************G***********************##&&&& - -5 +|+&&&&&&##############====&&###&&&&&&############===*******G - -10 +|+###%%&&&&&&&&&&&&&&&&%%#########%%&&&&&&&&&&&&&&&=======# - -15 +|------------------------------------------------------------ - -20 +-+#######+#########+#########+#########+#########+######## + - 0 2 4 6 8 10 12 - |-----------------------------------------------------------| - 1 +|+ + + + + + +-+| - +| ***F******** + + + + +| - 0.8 +|+#**##########******####################################+-+| - 0.6 +|+*##################***############***********##########+-+| - EI #|*#####################**#########***#########***######### | - 0.4 +|*######################**#######**#############***######+-+| - 0.2 +|+#######################**#####**################**#####+-+| - *|-----------------------------------------------------------| - 0 *-+#######+#########+#######*****#######+#########+####****** - 0 2 4 6 8 10 12 - x line 0: warning: iconv failed to convert degree sign | @@ -4782,50 +7815,17 @@ Number of evaluations: 3 + 9 = 12. 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/02_design_of_experiments/stk_example_doe04.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe04.m -***** test stk_example_doe04; close all; +[inst/examples/02_design_of_experiments/stk_example_doe02.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe02.m +***** test stk_example_doe02; close all; #=========================# -# stk_example_doe04 # +# stk_example_doe02 # #=========================# -'stk_example_doe04' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe04.m +'stk_example_doe02' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe02.m - STK_EXAMPLE_DOE04 Probability of misclassification - - The upper panel shows posterior means and variances as usual, and the - threshold of interest, which is at T = 0.85 (dashed line). - - The lower panel shows the probability of misclassification as a function of x - (blue curve), i.e., the probability that the actual value of the function is - not on the same side of the threshold as the prediction (posterior mean). - - We also plot the expected future probability of misclassification (magenta - curve), should a new evaluation be made at x = 3. - - Note that both probabilities are obtained using stk_pmisclass. - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/02_design_of_experiments/stk_example_doe02.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe02.m -***** test stk_example_doe02; close all; - -#=========================# -# stk_example_doe02 # -#=========================# - -'stk_example_doe02' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe02.m - - STK_EXAMPLE_DOE02 "Sequential Maximin" design + STK_EXAMPLE_DOE02 "Sequential Maximin" design In this example, a two-dimensional space-filling design is progressively enriched with new points using a "sequential maximin" approach. More @@ -4864,26 +7864,26 @@ - |----------------------n = 10, fd = 3.30e-01-------------------------| - 1 +|+ + + + + +-+| - +| + + F + + +| - #|#################F################################################# | - #|################################################################### | - 0.8 +|+######################################################F##########+-+| + |----------------------n = 10, fd = 2.84e-01-------------------------| + 1 F|+ + + + + +-+| + +| + F + + + +| + #|##################################################F################ | #|################################################################### | - #|###########################F####################################### | + 0.8 +|+#################################################################+-+| + #|##F################################################################ | + #|#################################F################################# | 0.6 +|+#################################################################+-+| - #|####F############################################################## | + #|###########################################################F####### | #|################################################################### | - #|#####################################################F############# | - 0.4 +|+#####################F###########################################+-+| #|################################################################### | + 0.4 +|+####################################F############################+-+| + #|############F###################################################### | #|################################################################### | - 0.2 +|+#####F###########################################################+-+| + 0.2 +|+#################################################################F-+| + #|##############################################F#################### | #|################################################################### | - #|#############################################F##################### | +|---------------------------------------------------------------------| - 0 +-+###########+##########F##+#############+#############+###########+-+ + 0 +-+###########+#############+#############+#############+###########+-+ 0 0.2 0.4 0.6 0.8 1 line 0: warning: iconv failed to convert degree sign @@ -4894,26 +7894,26 @@ - |----------------------n = 11, fd = 3.03e-01-------------------------| + |----------------------n = 11, fd = 2.78e-01-------------------------| 1 F|+ + + + + +-+| - +| + + F + + +| - #|#################F################################################# | - #|################################################################### | - 0.8 +|+######################################################F##########+-+| + +| + F + + + +| + #|##################################################F################ | #|################################################################### | - #|###########################F####################################### | + 0.8 +|+#################################################################+-F| + #|##F################################################################ | + #|#################################F################################# | 0.6 +|+#################################################################+-+| - #|####F############################################################## | + #|###########################################################F####### | #|################################################################### | - #|#####################################################F############# | - 0.4 +|+#####################F###########################################+-+| #|################################################################### | + 0.4 +|+####################################F############################+-+| + #|############F###################################################### | #|################################################################### | - 0.2 +|+#####F###########################################################+-+| + 0.2 +|+#################################################################F-+| + #|##############################################F#################### | #|################################################################### | - #|#############################################F##################### | +|---------------------------------------------------------------------| - 0 +-+###########+##########F##+#############+#############+###########+-+ + 0 +-+###########+#############+#############+#############+###########+-+ 0 0.2 0.4 0.6 0.8 1 line 0: warning: iconv failed to convert degree sign @@ -4924,26 +7924,26 @@ - |----------------------n = 12, fd = 2.94e-01-------------------------| - 1 F|+ + + + + +-F| - +| + + F + + +| - #|#################F################################################# | - #|################################################################### | - 0.8 +|+######################################################F##########+-+| + |----------------------n = 12, fd = 2.65e-01-------------------------| + 1 F|+ + + + + +-+| + +| + F + + + +| + #|##################################################F################ | #|################################################################### | - #|###########################F####################################### | + 0.8 +|+#################################################################+-F| + #|##F################################################################ | + #|#################################F################################# | 0.6 +|+#################################################################+-+| - 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0.08 +|+ + + + + + F*-+| - +| + + + + + ** ** +| - 0.06 +|+#################################################*#*#*#*-+| - #|##################################################*#*#*#* | - AKG0.04 +|+#################################################*#*#*#+*+| - #|#################################################*###**##* | - 0.02 +|+################################################*###**#+*+| - +|-----------------------------------------------------------| - 0 ***************************************************####*##+-* + 0.06 +|+ + + + + + +-+| + 0.05 +|+ + + + + + F +-+| + #|####################################################**### | + 0.04 +|+###################################################**##+-+| + AKG0.03 +|+###################################################*#*#+-+| + 0.02 +|+###################################################*#*#+-+| + #|####################################################*#*## | + 0.01 +|-----------------------------------------------------------| + 0 ******************************************************####*** 0 2 4 6 8 10 12 x line 0: warning: iconv failed to convert degree sign @@ -5344,26 +8320,26 @@ | n = 5 + 25 = 30. - 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0.025 +|+ + + + + + ** F*-+| - #|###################################################**##** | - 0.02 +|+##################################################*#**#*-+| - AKG0.015 +|+##################################################*#**#*-+| - 0.01 +|+#################################################*##**#+*+| - #|##################################################*##**##* | - 0.005 +|-----------------------------------------------------------| - 0 *************************************************#***##*##+-* + 0.007 +|+ + + + + + * F+-+| + 0.006 +|+ + + + + + ** *+-+| + 0.005 +|+#################################################**##*#*-+| + 0.004 +|+#################################################*#*#*#*-+| + AKG #|##################################################*#*#*#* | + 0.003 +|+#################################################*#*#*#*-+| + 0.002 +|+###***###########################################*#*#*#*-+| + 0.001 +|-----------------------------------------------------------| + 0 ******####******************************************###*##*** 0 2 4 6 8 10 12 x line 0: warning: iconv failed to convert degree sign @@ -5494,26 +8470,26 @@ | n = 5 + 50 = 55. - 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0.02 +|+ + + + + + * F+-+| - +| + + + + + * * +| - 0.015 +|+##################################################*#*#**-+| - #|###################################################*#**#* | + 0.02 +|+ + + + + + +-+| + +| + + + + + +| + 0.015 +|+###################################################*##F+-+| + #|###################################################**#*#* | AKG 0.01 +|+##################################################*#**#*-+| #|###################################################*#**#* | - 0.005 +|+##################################################*#**#*-+| + 0.005 +|+#################################################*##**#+*+| +|-----------------------------------------------------------| - 0 *****************************************************##*##+** + 0 *************************************************#+**##*##+-* 0 2 4 6 8 10 12 x line 0: warning: iconv failed to convert degree sign @@ -5734,169 +8686,156 @@ | n = 5 + 90 = 95. - 20 +|+ - | ##%%%%%## - 10 +|+##############################%%&&&====&&&%############# - 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init002 : 3.00000 2.2566 - init003 : 6.00000 -1.5381 - init004 : 9.00000 4.0991 - init005 : 12.00000 -7.5930 - xg(186) : 11.15578 -11.6005 - xg(179) : 10.73367 -9.7786 - xg(200) : 12.00000 -4.2396 - xg(171) : 10.25126 -8.6369 - xg(171) : 10.25126 -6.7006 - xg(193) : 11.57789 -9.4808 - xg(171) : 10.25126 -7.0809 - xg(193) : 11.57789 -9.4529 - xg(172) : 10.31156 -6.6062 - xg(192) : 11.51759 -13.9782 - xg(022) : 1.26633 -2.4358 - xg(079) : 4.70352 -3.8670 - xg(182) : 10.91457 -11.8225 - xg(177) : 10.61307 -8.1522 - xg(191) : 11.45729 -7.3252 - xg(177) : 10.61307 -13.0495 - xg(191) : 11.45729 -10.8640 - xg(177) : 10.61307 -12.6572 - xg(191) : 11.45729 -9.2066 - xg(177) : 10.61307 -9.1813 - xg(191) : 11.45729 -8.3525 - xg(177) : 10.61307 -8.8850 - xg(191) : 11.45729 -11.5415 - xg(177) : 10.61307 -6.0860 - xg(191) : 11.45729 -9.7395 - xg(177) : 10.61307 -9.2440 - xg(191) : 11.45729 -12.3658 - xg(184) : 11.03518 -11.1414 - xg(178) : 10.67337 -12.0342 - xg(178) : 10.67337 -7.5374 - xg(191) : 11.45729 -13.0206 - xg(179) : 10.73367 -12.5400 - xg(178) : 10.67337 -6.8537 - xg(191) : 11.45729 -10.6560 - xg(179) : 10.73367 -11.3482 - xg(191) : 11.45729 -8.6349 - xg(179) : 10.73367 -12.4549 - xg(191) : 11.45729 -12.9261 - xg(179) : 10.73367 -9.5117 - xg(191) : 11.45729 -7.1169 - xg(179) : 10.73367 -9.9147 - xg(191) : 11.45729 -9.2496 - xg(179) : 10.73367 -11.2595 - xg(191) : 11.45729 -13.7598 - xg(179) : 10.73367 -10.3442 - xg(191) : 11.45729 -9.1602 - xg(179) : 10.73367 -8.8284 - xg(191) : 11.45729 -8.2570 - xg(179) : 10.73367 -10.4524 - xg(191) : 11.45729 -12.4279 - xg(179) : 10.73367 -10.2360 - xg(179) : 10.73367 -12.1092 - xg(191) : 11.45729 -11.7163 - xg(179) : 10.73367 -15.2699 - xg(191) : 11.45729 -10.7366 - xg(179) : 10.73367 -10.2558 - xg(191) : 11.45729 -9.0617 - xg(179) : 10.73367 -6.5326 - xg(191) : 11.45729 -10.4671 - xg(179) : 10.73367 -12.7939 - xg(191) : 11.45729 -12.1584 - xg(179) : 10.73367 -11.5490 - xg(191) : 11.45729 -11.4309 - xg(179) : 10.73367 -11.6439 - xg(191) : 11.45729 -8.8874 - xg(179) : 10.73367 -8.2855 - xg(191) : 11.45729 -14.0165 - xg(179) : 10.73367 -12.3163 - xg(191) : 11.45729 -8.3050 - xg(179) : 10.73367 -9.3477 - xg(191) : 11.45729 -11.0163 - xg(179) : 10.73367 -8.4633 - xg(179) : 10.73367 -11.0039 - xg(190) : 11.39698 -10.4036 - xg(179) : 10.73367 -8.0273 - xg(190) : 11.39698 -13.2612 - xg(179) : 10.73367 -11.7611 - xg(190) : 11.39698 -11.9324 - xg(179) : 10.73367 -11.3546 - xg(190) : 11.39698 -10.9979 - xg(180) : 10.79397 -13.8727 - xg(190) : 11.39698 -10.7473 - xg(180) : 10.79397 -13.5210 - xg(190) : 11.39698 -10.8811 - xg(180) : 10.79397 -6.2774 - xg(190) : 11.39698 -7.4990 - xg(180) : 10.79397 -8.4697 - xg(190) : 11.39698 -9.4950 - xg(180) : 10.79397 -9.7237 - xg(190) : 11.39698 -10.2458 - xg(180) : 10.79397 -9.3791 - xg(190) : 11.39698 -12.1184 - xg(180) : 10.79397 -9.5626 - xg(190) : 11.39698 -10.4699 - xg(180) : 10.79397 -12.6498 + init001 : 0.00000 -0.8106 + init002 : 3.00000 0.9657 + init003 : 6.00000 -2.3269 + init004 : 9.00000 0.1116 + init005 : 12.00000 -3.9051 + xg(200) : 12.00000 -3.2567 + xg(001) : 0.00000 -0.4431 + xg(096) : 5.72864 -2.9235 + xg(200) : 12.00000 -3.2995 + xg(096) : 5.72864 -1.7746 + xg(200) : 12.00000 -5.8069 + xg(001) : 0.00000 -1.2105 + xg(096) : 5.72864 -5.2589 + xg(200) : 12.00000 -2.1149 + xg(096) : 5.72864 -3.5154 + xg(112) : 6.69347 0.3659 + xg(083) : 4.94472 -3.1125 + xg(200) : 12.00000 -9.7578 + xg(179) : 10.73367 -9.7311 + xg(170) : 10.19095 -8.0875 + xg(169) : 10.13065 -6.8036 + xg(164) : 9.82915 -6.2147 + xg(158) : 9.46734 0.9577 + xg(170) : 10.19095 -6.3948 + xg(170) : 10.19095 -6.8035 + xg(182) : 10.91457 -9.7229 + xg(189) : 11.33668 -13.3083 + xg(184) : 11.03518 -11.3947 + xg(192) : 11.51759 -10.5110 + xg(192) : 11.51759 -10.0796 + xg(175) : 10.49246 -6.2329 + xg(176) : 10.55276 -12.2085 + xg(191) : 11.45729 -7.1657 + xg(191) : 11.45729 -11.8707 + xg(175) : 10.49246 -6.6043 + xg(179) : 10.73367 -11.9459 + xg(192) : 11.51759 -8.6365 + xg(178) : 10.67337 -11.5467 + xg(190) : 11.39698 -8.4712 + xg(190) : 11.39698 -9.4304 + xg(176) : 10.55276 -9.9211 + xg(190) : 11.39698 -10.7269 + xg(176) : 10.55276 -8.4723 + xg(189) : 11.33668 -8.8581 + xg(177) : 10.61307 -11.8296 + xg(190) : 11.39698 -13.3904 + xg(176) : 10.55276 -9.7906 + xg(190) : 11.39698 -11.8052 + xg(190) : 11.39698 -8.7752 + xg(176) : 10.55276 -10.2203 + xg(190) : 11.39698 -14.4882 + xg(177) : 10.61307 -8.0704 + xg(180) : 10.79397 -13.4276 + xg(189) : 11.33668 -8.8081 + xg(189) : 11.33668 -10.2822 + xg(177) : 10.61307 -8.3543 + xg(025) : 1.44724 1.2486 + xg(189) : 11.33668 -9.4026 + xg(177) : 10.61307 -11.0209 + xg(189) : 11.33668 -9.1788 + xg(177) : 10.61307 -11.6328 + xg(189) : 11.33668 -10.0355 + xg(177) : 10.61307 -7.8824 + xg(189) : 11.33668 -11.0620 + xg(177) : 10.61307 -6.9355 + xg(189) : 11.33668 -9.7495 + xg(177) : 10.61307 -9.6774 + xg(189) : 11.33668 -7.7170 + xg(177) : 10.61307 -10.5843 + xg(189) : 11.33668 -13.6378 + xg(177) : 10.61307 -8.5089 + xg(189) : 11.33668 -11.7544 + xg(181) : 10.85427 -14.0380 + xg(189) : 11.33668 -12.4327 + xg(177) : 10.61307 -11.7179 + xg(189) : 11.33668 -12.6924 + xg(177) : 10.61307 -7.8984 + xg(181) : 10.85427 -10.9026 + xg(189) : 11.33668 -13.5835 + xg(185) : 11.09548 -8.9202 + xg(179) : 10.73367 -8.2730 + xg(179) : 10.73367 -10.6049 + xg(179) : 10.73367 -13.8810 + xg(179) : 10.73367 -4.8696 + xg(179) : 10.73367 -10.9843 + xg(179) : 10.73367 -12.7946 + xg(179) : 10.73367 -9.5821 + xg(179) : 10.73367 -10.1562 + xg(179) : 10.73367 -13.2017 + xg(179) : 10.73367 -11.1523 + xg(190) : 11.39698 -9.3127 + xg(179) : 10.73367 -11.5416 + xg(190) : 11.39698 -12.5268 + xg(179) : 10.73367 -9.6776 + xg(179) : 10.73367 -10.0331 + xg(190) : 11.39698 -11.0155 + xg(179) : 10.73367 -9.4441 + xg(190) : 11.39698 -8.0498 + xg(179) : 10.73367 -15.0909 + xg(190) : 11.39698 -9.1764 Number of evaluations: 5 + 95 = 100. 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/02_design_of_experiments/stk_example_doe06.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe06.m -***** test stk_example_doe06; close all; +[inst/examples/02_design_of_experiments/stk_example_doe04.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe04.m +***** test stk_example_doe04; close all; #=========================# -# stk_example_doe06 # +# stk_example_doe04 # #=========================# -'stk_example_doe06' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe06.m - - STK_EXAMPLE_DOE06 Sequential design for the estimation of an excursion set - - In this example, we consider the problem of estimating the set - - Gamma = { x in X | f(x) > z_crit }, - - where z_crit is a given value, and/or its volume. +'stk_example_doe04' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe04.m - In a typical "structural reliability analysis" problem, Gamma would - represent the failure region of a certain system, and its volume would - correspond to the probability of failure (assuming a uniform distribution - for the input). + STK_EXAMPLE_DOE04 Probability of misclassification - A Matern 5/2 prior with known parameters is used for the function f, and - the evaluations points are chosen sequentially using any of the sampling - criterion described in [1] (see also [2], section 4.3). + The upper panel shows posterior means and variances as usual, and the + threshold of interest, which is at T = 0.85 (dashed line). - REFERENCE + The lower panel shows the probability of misclassification as a function of x + (blue curve), i.e., the probability that the actual value of the function is + not on the same side of the threshold as the prediction (posterior mean). - [1] B. Echard, N. Gayton and M. Lemaire (2011). AK-MCS: an active - learning reliability method combining Kriging and Monte Carlo - simulation. Structural Safety, 33(2), 145-154. + We also plot the expected future probability of misclassification (magenta + curve), should a new evaluation be made at x = 3. - [2] J. Bect, D. Ginsbourger, L. Li, V. Picheny and E. Vazquez (2012). - Sequential design of computer experiments for the estimation of a - probability of failure. Statistics and Computing, 22(3), 773-793. + Note that both probabilities are obtained using stk_pmisclass. Additional help for built-in functions and operators is @@ -5906,1745 +8845,105 @@ Help and information about Octave is also available on the WWW at https://www.octave.org and via the help@octave.org mailing list. -Volume (reference value): 20.15% - -data_init = <4x2 stk_dataframe array> - - : x z - initial design #1 : 0.000000 0.00000 - initial design #2 : 0.333333 -0.43063 - initial design #3 : 0.666667 -0.66886 - initial design #4 : 1.000000 -1.20558 - - line 0: warning: iconv failed to convert degree sign - - - |-------------------------Groung truth----------------------------| - 1 +|+ + + + + +-+| - +| + + + + +| - #|############################################################### | - 0.5 +|+#############################################################+-+| - #|############################################################### | - #|############################################################### | - $|$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$| - 0 *|*****##***####***#######**#######**##########**########**#####+-+| - #|####****########**#####**#########*##########*##########*###### | - z #|#################***#***###########*########**##########**##### | - -0.5 +|+##################***#############**######**############*####+-+| - #|####################################**####**#############**#### | - #|#####################################******###############**### | - #|----------------------------+##############################**## | - -1 +|***?***z = f(x), below zcrit|###############################*#+-+| - #|###?###z = f(x), above zcrit|###############################*****| - +|-----------------------------------------------------------------| - -1.5 +-+##########+############+#############+############+##########+-+ - 0 0.2 0.4 0.6 0.8 1 - x - -Iteration #1 -| Current sample size: n = 4 -| Volume estimate (plugin): 0.00000 [ref: 0.20150] -| Upper-bound on posterior std: 4.1282e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 4 +|+ ### - | #%%%%%%%%%## ###%%%### ######## - 2 +|+&&&&&&&&&&&&&&%#####%%&&&&&&&&&&&%#######%%&&&&&&&&%%### - 0 +|+###F###################################################### - z #|&&&&##########&***G*******************G*******************G - -2 +|+%%&&&&&&&&&&&&%#####%&&&&&&&&&&&&&&%###%&&&&&&#####&&&&&& - -4 +|+#####%%%%%##############%%%%%%%###########%%%&&&&&&&%%## - +|------------------------------------------------------------ - -6 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + + +-+| - +| + + + + | - 0.4 +|****F******#############################################+-+| - 0.3 +|*#########****##########################################+-+| -criterion #|#############**#########********######################### | - 0.2 +|+#############**######***######***############***#######+-+| - 0.1 +|+##############**####**##########**########****#*****###+-+| - *|-----------------------------------------------------------| - 0 *-+#########+#####*****#+###########+*******####+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #2 -| Current sample size: n = 5 -| Volume estimate (plugin): 0.00000 [ref: 0.20150] -| Upper-bound on posterior std: 3.0238e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 4 +|+ - | ######## ######## - 2 +|+##########%%#########%&&&&&&&&&&&%#######%%&&&&&&&&%%### - 0 +|+########################################################## - z #|%%%##%&&&&&&&&&***G*********F*********G*******************G - -2 +|+####################%&&&&&&&&&&&&&&####%&&&&&&#####&&&&&& - -4 +|+#########################%%%%%%###########%%%&&&&&&&%%## - +|------------------------------------------------------------ - -6 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + **F* + + +-+| - +| + + *** *** + + | - 0.2 +|+######################**######***######################+-+| - 0.15 +|+########*****########**#########*###########*****######+-+| - #|########**###**#######*##########**########***###***##### | - 0.1 +|**#####**#####*######**###########**######**#######**###+-+| - 0.05 +|***####*######**#####*#############*#####**#########**##+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+#####*****#+###########+#******####+########**** - 0 0.2 0.4 0.6 0.8 - x -Iteration #3 -| Current sample size: n = 6 -| Volume estimate (plugin): 0.09640 [ref: 0.20150] -| Upper-bound on posterior std: 2.7859e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 2 +|+ ####### - 1 +|+ ###### #%%%# %%%%# ##%%%%%%%%%%# - 0 +|+########################F################################# - -1 +|+&&&&*************G***&&&&%###&===****G****########====&&&& - z #|########%&&&&&&&%######################&&&****************G - -2 +|+########################################%&&&&#######&&&&% - -3 +|+##########################################%%&&&&&&&&&%%# - -4 +|------------------------------------------------------------ - -5 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + F * + + +-+| - +| + + ** *** + + | - 0.4 +|+#######################***###*#*#######################+-+| - 0.3 +|+######################*##*###*#**######################+-+| -criterion #|######################**##*##**##*####################### | - 0.2 +|+#####################*###**#*###**#####################+-+| - 0.1 +|**###################**####*#*####*#####################+-+| - +|-----------------------------------------------------------| - 0 **+#******##+##*********+####***####+**********#+######****** - 0 0.2 0.4 0.6 0.8 - x -Iteration #4 -| Current sample size: n = 7 -| Volume estimate (plugin): 0.10770 [ref: 0.20150] -| Upper-bound on posterior std: 2.0978e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 2 +|+ ####### - 1 +|+ #%%%%%%%%%%# - 0 +|+#############################F############################ - -1 +|+&&&&*************G**=&#######%==*****G*****#######====&&&& - z #|########%&&&&&&&#######################&&&&***************G - -2 +|+########################################%&&&&&######&&&&# - -3 +|+###########################################%%&&&&&&&&%## - -4 +|------------------------------------------------------------ - -5 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + +* F + + +-+| - +| + +* * + + | - 0.4 +|+######################*#####**#########################+-+| - 0.3 +|+######################*#####***########################+-+| -criterion #|#######################**####*#*######################### | - 0.2 +|+#####################***####*#**#######################+-+| - 0.1 +|**####################*#*####*##**######################+-+| - +|-----------------------------------------------------------| - 0 **+#*******#************+#******####***********#+######****** - 0 0.2 0.4 0.6 0.8 - x -Iteration #5 -| Current sample size: n = 8 -| Volume estimate (plugin): 0.08660 [ref: 0.20150] -| Upper-bound on posterior std: 1.9385e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%%&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****&######********G**************==&&&# - -1 +|+#######&&&&&&&&%##################%%##%&&&&&#######******G - -2 +|+#########################################%%&&&&&&&&&&&&&% - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + F * + + +-+| - +| + + * * + + | - 0.4 +|+######################**####*##########################+-+| - 0.3 +|+######################**####*##########################+-+| -criterion #|#######################**####*########################### | - 0.2 +|+######################**####*#################**#######+-+| - 0.1 +|**#####################**####*##############*********###+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#***********#*******************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #6 -| Current sample size: n = 9 -| Volume estimate (plugin): 0.08400 [ref: 0.20150] -| Upper-bound on posterior std: 1.7899e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+###########################################%%&&&&&&%%### - 0 +|+############################F############################# - z &|&&**G*************G****#######********G**************==&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&#######******G - -2 +|+#########################################%%&&&&&&&&&&&&&% - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + F + + +-+| - +| + + * * + + | - 0.4 +|+#######################*####*##########################+-+| - 0.3 +|+#######################*####*##########################+-+| -criterion #|########################*####*########################### | - 0.2 +|+#######################*####*##########################+-+| - 0.1 +|+#######################*####*##############*********###+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #7 -| Current sample size: n = 10 -| Volume estimate (plugin): 0.08500 [ref: 0.20150] -| Upper-bound on posterior std: 1.8651e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + F + + +-+| - +| + + * + + | - 0.4 +|+#######################*###############################+-+| - 0.3 +|+#######################*###############################+-+| -criterion #|########################*################################ | - 0.2 +|+#######################*#####################*****#####+-+| - 0.1 +|+#######################*###################***###***###+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #8 -| Current sample size: n = 11 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8600e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + + +-+| - +| + + F + + | - 0.4 +|+#######################*###############################+-+| - 0.3 +|+#######################*###############################+-+| -criterion #|########################*################################ | - 0.2 +|+#######################*#####################*****#####+-+| - 0.1 +|+#######################*###################***###***###+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #9 -| Current sample size: n = 12 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8607e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + + +-+| - +| + + + + | - 0.4 +|+#######################F###############################+-+| - 0.3 +|+#######################*###############################+-+| -criterion #|########################*################################ | - 0.2 +|+#######################*#####################*****#####+-+| - 0.1 +|+#######################*###################***###***###+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #10 -| Current sample size: n = 13 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8608e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.3 +|+ + + F + + +-+| - 0.25 +|+ + + * + + +-+| - #|########################*################################ | - 0.2 +|+#######################*######################***######+-+| - 0.15 +|+#######################*####################***#***####+-+| - 0.1 +|+#######################*###################**#####**###+-+| - #|***#####****############*##################**#######**### | - 0.05 +|-----------------------------------------------------------| - 0 **+#******##+##******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #11 -| Current sample size: n = 14 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8607e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.3 +|+ + + + + +-+| - 0.25 +|+ + + F + + +-+| - #|########################*################################ | - 0.2 +|+#######################*######################***######+-+| - 0.15 +|+#######################*####################***#***####+-+| - 0.1 +|+#######################*###################**#####**###+-+| - #|***#####****############*##################**#######**### | - 0.05 +|-----------------------------------------------------------| - 0 **+#******##+##******************************###+#######***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #12 -| Current sample size: n = 15 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8607e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + + + +-+| - +| + + F + + | - 0.2 +|+#######################*######################**#######+-+| - 0.15 +|+#######################*####################******#####+-+| - #|########################*###################**#####**#### | - 0.1 +|**######################*##################**#######**##+-+| - 0.05 +|***#####****############*#################**#########**#+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##******************************###+########**** - 0 0.2 0.4 0.6 0.8 - x -Iteration #13 -| Current sample size: n = 16 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8607e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + + + +-+| - +| + + F + + | - 0.2 +|+#######################*######################**#######+-+| - 0.15 +|+#######################*####################******#####+-+| - #|########################*###################**#####**#### | - 0.1 +|**######################*##################**#######**##+-+| - 0.05 +|***#####*****###########*#################**#########**#+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##******************************###+########**** - 0 0.2 0.4 0.6 0.8 - x -Iteration #14 -| Current sample size: n = 17 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8607e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+#######################F################################## - z &|&&**G*************G****#######********G***************=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + + + +-+| - +| + + + + | - 0.2 +|+#######################F######################**#######+-+| - 0.15 +|+#######################*####################******#####+-+| - #|########################*###################**#####**#### | - 0.1 +|**######################*##################**#######**##+-+| - 0.05 +|***#####*****###########*#################**#########**#+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##******************************###+########**** - 0 0.2 0.4 0.6 0.8 - x -Iteration #15 -| Current sample size: n = 18 -| Volume estimate (plugin): 0.08510 [ref: 0.20150] -| Upper-bound on posterior std: 1.8606e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 3 +|+ - 2 +|+ ######## - 1 +|+##########################################%%&&&&&&&%%### - 0 +|+########################################################## - z &|&&**G*************G****#######********G*********F*****=&&&# - -1 +|+#######%&&&&&&%###################%%##%&&&&&########*****G - -2 +|+##########################################%&&&&&&&&&&&&&# - -3 +|------------------------------------------------------------ - -4 +-+#########+###########+###########+###########+########## - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + + + +-+| - +| + + + + | - 0.2 +|+##############################################*F#######+-+| - 0.15 +|+#######################*####################******#####+-+| - #|########################*###################**#####**#### | - 0.1 +|**######################*##################**#######**##+-+| - 0.05 +|***#####*****###########*#################**#########**#+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##******************************###+########**** - 0 0.2 0.4 0.6 0.8 - x -Iteration #16 -| Current sample size: n = 19 -| Volume estimate (plugin): 0.21240 [ref: 0.20150] -| Upper-bound on posterior std: 2.1770e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1.5 +|+ - 1 +|+ #### - #|###########################################%&&&%&&&&&&%## - 0.5 +|+&&###%&&&&&&%%#########*G**G*###########%==****G***#&&%# - z 0 +|+###################################################F###### - -0.5 +|+&&&&&************G***&########***&&&%%****&&%####%==***&% - #|######%&&&####&&&&##############&*****G*&&&%########===***# - -1 +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+########### - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + * + *F +-+| - +| + + + * + ** | - 0.4 +|+##########################################***#####**###+-+| - 0.3 +|+##########################################*#*#####***##+-+| -criterion #|###########################################*#*####**#*### | - 0.2 +|+#######################*##################*#*####*##*##+-+| - 0.1 +|+#######################*#################**#**###*##**#+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*******************************###****####***** - 0 0.2 0.4 0.6 0.8 - x -Iteration #17 -| Current sample size: n = 20 -| Volume estimate (plugin): 0.19840 [ref: 0.20150] -| Upper-bound on posterior std: 1.4748e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ #### - | ###### %&&*** - 0.5 +|+&%####%&&&&&%##########*G**G############&&***&*G*####### - 0 +|+#########################################F################ - z %|&&&*G********#====&****#######***&%####&**&&######**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**&%########%G*&## - -1 +|+######%&&&&&&&&&################&*****#############%***&& - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+########%%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + F + * +-+| - +| + + + ** + * | - 0.4 +|+#########################################**#####*######+-+| - 0.3 +|+#########################################**#####*######+-+| -criterion #|##########################################**#####*####### | - 0.2 +|+#######################*#################**#####*######+-+| - 0.1 +|+#######################*################****####*######+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#******************************##*************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #18 -| Current sample size: n = 21 -| Volume estimate (plugin): 0.20040 [ref: 0.20150] -| Upper-bound on posterior std: 1.0601e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%####%&&&&&%##########*G**G##############***&*G*####### - 0 +|+################################################F######### - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**##########%G*&## - -1 +|+######%&&&&&&&&&################&*****##############***&& - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+########%%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + + F +-+| - +| + + + * + * | - 0.4 +|+#########################################*######*######+-+| - 0.3 +|+#########################################*######*######+-+| -criterion #|##########################################*######*####### | - 0.2 +|+#######################*#################*######*######+-+| - 0.1 +|+#######################*#################*######*######+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #19 -| Current sample size: n = 22 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.7073e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#########################################F################ - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.5 +|+ + + + F + +-+| - +| + + + * + | - 0.4 +|+#########################################*#############+-+| - 0.3 +|+#########################################*#############+-+| -criterion #|##########################################*############## | - 0.2 +|+#######################*#################*#############+-+| - 0.1 +|+#######################*#################*######*######+-+| - +|-----------------------------------------------------------| - 0 **+#******##+#*********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #20 -| Current sample size: n = 23 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5490e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.25 +|+ + + + + +-+| - +| + + + + | - 0.2 +|+#######################################################+-+| - 0.15 +|+#######################F###############################+-+| - #|########################*################################ | - 0.1 +|+#######################*########################*######+-+| - 0.05 +|***#####*****###########*########################*######+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #21 -| Current sample size: n = 24 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5484e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.2 +|+ + + + + +-+| - +| + + + + | - 0.15 +|+#######################F###############################+-+| - #|########################*################################ | - 0.1 +|+#######################*########################*######+-+| - #|**######****############*########################*####### | - 0.05 +|***####**##**###########*########################*######+-+| - +|-----------------------------------------------------------| - 0 **+#*****###+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #22 -| Current sample size: n = 25 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5478e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.16 +|+ + + + + +-+| - 0.14 +|+ + + F + + +-+| - 0.12 +|+#######################*###############################+-+| - 0.1 +|+#######################*########################*######+-+| - 0.08 +|**######################*########################*######+-+| - 0.06 +|***#####****############*########################*######+-+| - 0.04 +|*#*####**##**###########*########################*######+-+| - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #23 -| Current sample size: n = 26 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5472e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.16 +|+ + + + + +-+| - 0.14 +|+ + + + + +-+| - 0.12 +|+#######################F###############################+-+| - 0.1 +|+#######################*########################*######+-+| - 0.08 +|**######################*########################*######+-+| - 0.06 +|***#####****############*########################*######+-+| - 0.04 +|*#*####**##**###########*########################*######+-+| - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #24 -| Current sample size: n = 27 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5468e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.12 +|+ + + + + +-+| - 0.1 +|+ + + F + + +-+| - #|########################*########################*####### | - 0.08 +|**#######**#############*########################*######+-+| - 0.06 +|***#####****############*########################*######+-+| - 0.04 +|*#*####**##**###########*########################*######+-+| - #|##*####*####**##########*########################*####### | - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #25 -| Current sample size: n = 28 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5463e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.12 +|+ + + + + +-+| - 0.1 +|+ + + F + + +-+| - #|########################*########################*####### | - 0.08 +|**#######**#############*########################*######+-+| - 0.06 +|***#####****############*########################*######+-+| - 0.04 +|*#*####**##**###########*########################*######+-+| - #|##*####*####**##########*########################*####### | - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #26 -| Current sample size: n = 29 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5459e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+################################################F######### - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.12 +|+ + + + + +-+| - 0.1 +|+ + + + + +-+| - #|########################*########################F####### | - 0.08 +|**#######**#############*########################*######+-+| - 0.06 +|***#####****############*########################*######+-+| - 0.04 +|*#*####**##**###########*########################*######+-+| - #|##*####*####**##########*########################*####### | - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #27 -| Current sample size: n = 30 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5358e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.12 +|+ + + + + +-+| - 0.1 +|+ + + + + +-+| - #|########################F################################ | - 0.08 +|**#######**#############*###############################+-+| - 0.06 +|***#####****############*###############################+-+| - 0.04 +|*#*####**##**###########*###############################+-+| - #|##*####*####**##########*################################ | - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #28 -| Current sample size: n = 31 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5354e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.12 +|+ + + + + +-+| - 0.1 +|+ + + + + +-+| - #|########################F################################ | - 0.08 +|**#######**#############*###############################+-+| - 0.06 +|***#####****############*###############################+-+| - 0.04 +|*#*####**##**###########*###############################+-+| - #|##*####*####**##########*################################ | - 0.02 +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #29 -| Current sample size: n = 32 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 9.5351e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | ###### &*** - 0.5 +|+&%###%%&&&&&%##########*G**G##############***&*G*####### - 0 +|+F######################################################### - z %|&&&*G********#====&****#######***&#####&**########**##### - -0.5 +|+#####&&&###******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.08 +|*F + + * + + +-+| - +|** ** + * + + | - 0.06 +|***#####****############*###############################+-+| - #|*#*#####*##**###########*################################ | - 0.04 +|+#*####*####*###########*###############################+-+| - #|##*####*####**##########*################################ | - 0.02 +|+#*###**#####*##########*###############################+-+| - +|-----------------------------------------------------------| - 0 **+##****###+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #30 -| Current sample size: n = 33 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7410e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.08 +|+ + + F + + +-+| - +| + + * + + | - 0.06 +|+#######################*###############################+-+| - #|########################*################################ | - 0.04 +|+#######################*###############################+-+| - #|########################*################################ | - 0.02 +|+########****###########*###############################+-+| - +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #31 -| Current sample size: n = 34 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7401e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.08 +|+ + + + + +-+| - +| + + F + + | - 0.06 +|+#######################*###############################+-+| - #|########################*################################ | - 0.04 +|+#######################*###############################+-+| - #|########################*################################ | - 0.02 +|+########****###########*###############################+-+| - +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #32 -| Current sample size: n = 35 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7394e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.08 +|+ + + + + +-+| - 0.07 +|+ + + + + +-+| - 0.06 +|+#######################F###############################+-+| - 0.05 +|+#######################*###############################+-+| - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+########****###########*###############################+-+| - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #33 -| Current sample size: n = 36 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7387e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + F + + +-+| - 0.05 +|+ + + * + + +-+| - #|########################*################################ | - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+#########**############*###############################+-+| - #|#########****###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #34 -| Current sample size: n = 37 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7381e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + + + +-+| - 0.05 +|+ + + F + + +-+| - #|########################*################################ | - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+#########**############*###############################+-+| - #|#########****###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #35 -| Current sample size: n = 38 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7376e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + + + +-+| - 0.05 +|+ + + F + + +-+| - #|########################*################################ | - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+#########**############*###############################+-+| - #|#########****###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #36 -| Current sample size: n = 39 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7370e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + + + +-+| - 0.05 +|+ + + + + +-+| - #|########################F################################ | - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+#########**############*###############################+-+| - #|#########****###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #37 -| Current sample size: n = 40 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7366e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + + + +-+| - 0.05 +|+ + + + + +-+| - #|########################F################################ | - 0.04 +|+#######################*###############################+-+| - 0.03 +|+#######################*###############################+-+| - 0.02 +|+#########**############*###############################+-+| - #|#########****###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 ***********#+##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #38 -| Current sample size: n = 41 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7362e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.04 +|+ + + F + + +-+| - +| + + * + + | - 0.03 +|+#######################*###############################+-+| - #|########################*################################ | - 0.02 +|+########***############*###############################+-+| - #|#########*#**###########*################################ | - 0.01 +|+#######**##**##########*###############################+-+| - +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #39 -| Current sample size: n = 42 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7358e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.04 +|+ + + + + +-+| - +| + + F + + | - 0.03 +|+#######################*###############################+-+| - #|########################*################################ | - 0.02 +|+########***############*###############################+-+| - #|#########*#**###########*################################ | - 0.01 +|+#######**##**##########*###############################+-+| - +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #40 -| Current sample size: n = 43 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7354e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.04 +|+ + + + + +-+| - 0.035 +|+ + + F + + +-+| - 0.03 +|+#######################*###############################+-+| - 0.025 +|+#######################*###############################+-+| - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #41 -| Current sample size: n = 44 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7350e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + F + + +-+| - 0.025 +|+ + + * + + +-+| - #|########################*################################ | - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #42 -| Current sample size: n = 45 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7348e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + + + +-+| - 0.025 +|+ + + F + + +-+| - #|########################*################################ | - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #43 -| Current sample size: n = 46 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7345e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + + + +-+| - 0.025 +|+ + + F + + +-+| - #|########################*################################ | - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #44 -| Current sample size: n = 47 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7343e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + + + +-+| - 0.025 +|+ + + + + +-+| - #|########################F################################ | - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #45 -| Current sample size: n = 48 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7341e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + + + +-+| - 0.025 +|+ + + + + +-+| - #|########################F################################ | - 0.02 +|+########***############*###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #46 -| Current sample size: n = 49 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7338e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#********G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.03 +|+ + + + + +-+| - 0.025 +|+ + + + + +-+| - #|######################################################### | - 0.02 +|+########***############F###############################+-+| - 0.015 +|+########*#**###########*###############################+-+| - 0.01 +|+#######**##**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #47 -| Current sample size: n = 50 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.7337e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+########%%%%###########*G**G##############***&*G*####### - 0 +|+########################################################## - z #|##&=G******###====&****#######***&#####&**########**##### - -0.5 +|+#####&&&#F*******G=&###########***&&&G**###########G*### - -1 +|+######%&&&&&&&&&################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.02 +|+ F* + * + + +-+| - +| *** + * + + | - 0.015 +|+########*#**###########*###############################+-+| - #|#########*##*###########*################################ | - 0.01 +|+#######*###**##########*###############################+-+| - #|########*####*##########*################################ | - 0.005 +|+#######*####*##########*###############################+-+| - +|-----------------------------------------------------------| - 0 **********##+###********************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #48 -| Current sample size: n = 51 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 1.2502e-01 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+#######%%#%%%##########*G**G##############***&*G*####### - 0 +|+#########F################################################ - z #|##&*G**&&###&&****&****#######***&#####&**########**##### - -0.5 +|+#############%&&*G*&###########***&&&G**###########G*### - -1 +|+################################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.3 +|+ + + + + +-+| - 0.25 +|+ *F* + + + +-+| - #|#########****############################################ | - 0.2 +|+########****###########################################+-+| - 0.15 +|+########****###########################################+-+| - 0.1 +|+#######***#*###########################################+-+| - #|########*#*#**########################################### | - 0.05 +|-----------------------------------------------------------| - 0 **********##*##********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #49 -| Current sample size: n = 52 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 3.0376e-02 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+#######################*G**G##############***&*G*####### - 0 +|+##########F############################################### - z #|##&*G**&#####&****&****#######***&#####&**########**##### - -0.5 +|+##############%&*G*&###########***&&&G**###########G*### - -1 +|+################################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.06 +|+ + + + + +-+| - 0.05 +|+ + + + + +-+| - #|###########F############################################# | - 0.04 +|+##########**###########################################+-+| - 0.03 +|+##########**###########################################+-+| - 0.02 +|+##########**###########################################+-+| - #|###########**###########*################################ | - 0.01 +|-----------------------------------------------------------| - 0 **************#********************************************** - 0 0.2 0.4 0.6 0.8 - x -Iteration #50 -| Current sample size: n = 53 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 1.3425e-03 [target: 5.000e-04] - line 0: warning: iconv failed to convert degree sign - - | - 1 +|+ - | &*** - 0.5 +|+#######################*G**G##############***&*G*####### - 0 +|+#######################F################################## - z #|##&*G**&#####&****&****#######***&#####&**########**##### - -0.5 +|+##############%&*G*&###########***&&&G**###########G*### - -1 +|+################################&*****##############***&% - +|------------------------------------------------------------ - -1.5 +-+#########+###########+###########+###########+#########%% - 0 0.2 0.4 0.6 0.8 - |-----------------------------------------------------------| - 0.02 +|+ + + + + +-+| - +| + + F + + | - 0.015 +|+#######################*###############################+-+| - #|########################*################################ | - 0.01 +|+#######################*###############################+-+| - #|########################*################################ | - 0.005 +|+#######################*###############################+-+| - +|-----------------------------------------------------------| - 0 ************************************************************* - 0 0.2 0.4 0.6 0.8 - x -Iteration #51 -| Current sample size: n = 54 -| Volume estimate (plugin): 0.20150 [ref: 0.20150] -| Upper-bound on posterior std: 1.2794e-03 [target: 5.000e-04] - -history = <54x5 stk_dataframe array> - - : x z vol_estim vol_err nmisclass - initial design #1 : 0.000000 0.00000 NaN NaN NaN - initial design #2 : 0.333333 -0.43063 NaN NaN NaN - initial design #3 : 0.666667 -0.66886 NaN NaN NaN - initial design #4 : 1.000000 -1.20558 0.0000 -0.2015 2015 - MC point #01085 : 0.104147 -0.13301 0.0000 -0.2015 2015 - MC point #02769 : 0.497684 0.26462 0.0964 -0.1051 1689 - MC point #06170 : 0.446819 0.26191 0.1077 -0.0938 1390 - MC point #07004 : 0.530353 0.00369 0.0866 -0.1149 1189 - MC point #02324 : 0.426633 0.13162 0.0840 -0.1175 1175 - MC point #02909 : 0.514004 0.15514 0.0850 -0.1165 1165 - MC point #06003 : 0.429136 0.15047 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #01430 : 0.429073 0.15000 0.0851 -0.1164 1164 - MC point #03941 : 0.826815 0.43980 0.2124 0.0109 697 - MC point #04693 : 0.892770 -0.42500 0.1984 -0.0031 31 - MC point #09556 : 0.739433 0.18278 0.2004 -0.0011 11 - MC point #04224 : 0.852946 0.16789 0.2015 0.0000 0 - MC point #02846 : 0.736634 0.14980 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #02608 : 0.854388 0.14921 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #06055 : 0.041927 0.00882 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - MC point #00300 : 0.205780 0.14336 0.2015 0.0000 0 - MC point #06476 : 0.196767 0.13513 0.2015 0.0000 0 - MC point #05554 : 0.219631 0.13168 0.2015 0.0000 0 - MC point #01430 : 0.429073 0.15000 0.2015 0.0000 0 - -Final result: -| Number of evaluations: 4 + 50 = 54. -| Volume estimate (plugin): 20.1500% [ref: 20.1500%] - 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/02_design_of_experiments/stk_example_doe01.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/02_design_of_experiments/stk_example_doe01.m -***** test stk_example_doe01; close all; - -#=========================# -# stk_example_doe01 # -#=========================# - -'stk_example_doe01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/02_design_of_experiments/stk_example_doe01.m - - STK_EXAMPLE_DOE01 Examples of two-dimensional designs - - All designs are constructed on the hyper-rectangle BOX = [0; 2] x [0; 4]. - - Examples of the following designs are shown: - a) Regular grid --> stk_sampling_regulargrid, - b) "Maximin" latin hypercube sample --> stk_sampling_maximinlhs, - c) RR2-scrambled Halton sequence --> stk_sampling_halton_rr2, - d) Uniformly distributed random sample --> stk_sampling_randunif. - +[inst/examples/test_functions/stk_testfun_hartman6.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman6.m +***** test + x1 = [0.20169 0.150011 0.476874 0.275332 0.311652 0.657300]; + y1 = -3.322368011391339; -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. + x2 = [0.20168952 0.15001069 0.47687398 0.27533243 0.31165162 0.65730054]; + y2 = -3.322368011415512; -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. + y = stk_testfun_hartman6 ([x1; x2]); + assert (stk_isequal_tolabs (y, [y1; y2], 1e-15)) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb06.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb06.m -***** test stk_example_kb06; close all; - -#========================# -# stk_example_kb06 # -#========================# - -'stk_example_kb06' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb06.m - - STK_EXAMPLE_KB06 Ordinary kriging VS kriging with a linear trend - - The same dataset is analyzed using two variants of kriging. - - The left panel shows the result of ordinary kriging, in other words, Gaussian - process interpolation assuming a constant (but unknown) mean. The right panel - shows the result of adding a linear trend in the mean of the Gaussian process. - - The difference with the left plot is clear in extrapolation: the first predic- - tor exhibits a "mean reverting" behaviour, while the second one captures an - increasing trend in the data. - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. +[inst/examples/test_functions/stk_testcase_truss3.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testcase_truss3.m +***** shared tc, xd, n + tc = stk_testcase_truss3 (); n = 5; + xd = stk_sampling_randunif (n, [], tc.search_domain); +***** test + v = stk_testfun_truss3_vol (xd, tc.constants); + z = stk_testfun_truss3_bb (xd, tc.constants); + assert (isequal (size (v), [n 1])); + assert (isequal (size (z), [n 5])); +***** test + F = stk_dataframe (zeros (n, 2), {'F1' 'F2'}); + F(:, 1) = tc.constants.F1_mean + tc.constants.F1_std * randn (n, 1); + F(:, 2) = tc.constants.F2_mean + tc.constants.F2_std * randn (n, 1); + x = [xd F]; + v = stk_testfun_truss3_vol (x, tc.constants); + z = stk_testfun_truss3_bb (x, tc.constants); + assert (isequal (size (v), [n 1])); + assert (isequal (size (z), [n 5])); +2 tests, 2 passed, 0 known failure, 0 skipped +[inst/examples/test_functions/stk_testfun_hartman4.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman4.m +***** test + x = [0.1873 0.1906 0.5566 0.2647 ; + 0.18744768 0.19414868 0.558005333 0.26476409]; + y = stk_testfun_hartman4 (x); + assert (stk_isequal_tolabs (y, ... + [-3.729722308557300; -3.729840440436292], 1e-15)); 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb08.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb08.m -***** test stk_example_kb08; close all; - -#========================# -# stk_example_kb08 # -#========================# - -'stk_example_kb08' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb08.m - - STK_EXAMPLE_KB08 Generation of conditioned sample paths made easy - - It has been demonstrated, in stk_example_kb05, how to generate conditioned - sample paths using unconditioned sample paths and conditioning by kriging. - - This example shows how to do the same in a more concise way, letting STK - take care of the details. - +[inst/examples/test_functions/stk_testfun_goldsteinprice.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_goldsteinprice.m +***** test % Use with nargin == 0 for visualisation + stk_testfun_goldsteinprice (); close all; +***** assert (stk_isequal_tolabs ... + (stk_testfun_goldsteinprice ([0, -1]), 3.0, 1e-12)) +2 tests, 2 passed, 0 known failure, 0 skipped +[inst/examples/test_functions/stk_testfun_hartman3.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/test_functions/stk_testfun_hartman3.m +***** test + x1 = [0.1, 0.55592003, 0.85218259]; + y1 = -3.862634748621772; -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. + x2 = [0.114614 0.554649 0.852547]; + y2 = -3.862747199255087; -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. + y = stk_testfun_hartman3 ([x1; x2]); + assert (stk_isequal_tolabs (y, [y1; y2], 1e-15)) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb02.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb02.m -***** test stk_example_kb02; close all; - -#========================# -# stk_example_kb02 # -#========================# - -'stk_example_kb02' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb02.m - - STK_EXAMPLE_KB02 Ordinary kriging in 1D with parameter estimation - - This example shows how to estimate covariance parameters and compute - ordinary kriging predictions on a one-dimensional noiseless dataset. - - The model and data are the same as in stk_example_kb01, but this time the - parameters of the covariance function are estimated using the Restricted - Maximum Likelihood (ReML) method. - - See also: stk_example_kb01, stk_example_kb02n - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -model = - - scalar structure containing the fields: - - covariance_type = @stk_materncov_iso - lm = - - +[inst/examples/03_miscellaneous/stk_example_misc04.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc04.m +***** test stk_example_misc04; close all; - dim = 1 - param = +#==========================# +# stk_example_misc04 # +#==========================# - -0.2108 - 2.3026 - 0.7562 +'stk_example_misc04' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc04.m - lognoisevariance = -Inf + STK_EXAMPLE_MISC04 Pareto front simulation - line 0: warning: iconv failed to convert degree sign - - - | True function and observed data - 1.5 +|+ - | ***G* +--------------------+ - #|#######***#####***########################|***?***True function| - 1 +|+#####**#########***######################+---G---Observations-+ - #|####**#############***######################################### - #|###**################**######################################## - 0.5 +|+#**##################**############################***######## - #|#G*####################**########################****##*G**#### - #|**######################**#####################G**########***## - F1 0 *|+########################**###################**############*** - G|##########################**#################**###############** - #|###########################**###############**#################** - -0.5 +|+###########################**#############**################## - #|#############################**###########*#################### - #|##############################*G*#######**##################### - -1 +|+###############################**#####**###################### - #|#################################******######################## - +|------------------------------------------------------------------ - -1.5 +-+##############+###############+################+############## + - -1 -0.5 0 0.5 1 - -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb01.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb01.m -***** test stk_example_kb01; close all; + DESCRIPTION -#========================# -# stk_example_kb01 # -#========================# + We consider a bi-objective optimization problem, where the objective + functions are modeled as a pair of independent stationary Gaussian + processes with a Matern 5/2 anisotropic covariance function. -'stk_example_kb01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb01.m + Figure (a): represent unconditional realizations of the Pareto front and + and estimate of the probability of being non-dominated at each point + of the objective space. - STK_EXAMPLE_KB01 Ordinary kriging in 1D, with noiseless data + Figure (b): represent conditional realizations of the Pareto front and + and estimate of the posteriorior probability of being non-dominated + at each point of the objective space. - This example shows how to compute ordinary kriging predictions on a - one-dimensional noiseless dataset. + EXPERIMENTAL FUNCTION WARNING - The word 'ordinary' indicates that the mean function of the GP prior is - assumed to be constant and unknown. + This script uses the stk_plot_probdom2d function, which is currently + considered an experimental function. Read the help for more information. - A Matern covariance function is used for the Gaussian Process (GP) prior. - The parameters of this covariance function are assumed to be known (i.e., - no parameter estimation is performed here). + REFERENCE - Note that the kriging predictor, which is the posterior mean of the GP, - interpolates the data in this noiseless example. + [1] Michael Binois, David Ginsbourger and Olivier Roustant, Quantifying + uncertainty on Pareto fronts with Gaussian Process conditional simu- + lations, European J. of Operational Research, 2043(2):386-394, 2015. - See also: stk_example_kb01n, stk_example_kb02 + See also: stk_plot_probdom2d Additional help for built-in functions and operators is @@ -7654,118 +8953,56 @@ Help and information about Octave is also available on the WWW at https://www.octave.org and via the help@octave.org mailing list. -model = - - scalar structure containing the fields: - - covariance_type = @stk_materncov_iso - lm = - - - - dim = 1 - param = - - -0.6931 - 1.3863 - 0.9163 - - lognoisevariance = -Inf - line 0: warning: iconv failed to convert degree sign - - - | True function and observed data - 1.5 +|+ - | ****G** +--------------------+ - #|#######***#####****#######################|***?***True function| - 1 +|+####***##########***#####################+---G---Observations-+ - #|####**##############**######################################### - #|###**################**######################################## - 0.5 +|+#**##################**###########################*****G###### - #|*G######################**######################***######***### - 0 +|*########################**####################G*##########***# - G|##########################**#################***#############*** - #|###########################**###############**#################** - -0.5 +|+###########################**#############**################## * - #|#############################**###########**################### - #|##############################*G#########**#################### - -1 +|+##############################***#####**###################### - #|#################################*******####################### - +|------------------------------------------------------------------ - -1.5 +-+##############+###############+################+############## + - -1 -0.5 0 0.5 1 - input variable x - -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb07.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb07.m -***** test stk_example_kb07; close all; - -#========================# -# stk_example_kb07 # -#========================# -'stk_example_kb07' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb07.m - - STK_EXAMPLE_KB07 Simulation of sample paths from a Matern process - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. - line 0: warning: iconv failed to convert degree sign - - |--Matern, nu = 0.5------| |--Matern, nu = 1.5------| - 3 +|+== + + + *-+| 3 +|+ + + + +-+| - 2 #|#===+ $$$#$ + =***+| 2 +|+ + $@@@ + $$$$+#==##+| - 1 @|*=======%%%#######=*****| #|&&&&&$@@#======***====##| - 0 #|**&**=######*##*########| 1 *|#$*******########**@@###| -response z#|#**####&###*******####*response z*|##########****#*###*##@@| - -1 *|####*#************#*#*@@| -1 &|**====#=&&&%****&&###***| - -2 +|#####****#*#**##@@@**+-+| =|==#%==&&&#&&&&@@@#%%%&&*| - -3 +|------------------------| -2 +|------------------------| - -4 +-+###+######+#####+###+-+ -3 ##+###+######+#####+###+-+ - -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 - |--Matern, nu = 2.5------| |--Matern, nu = 10.0-----| - 3 *|* + + + +-+| 3 +|+ + + + +-+| - 2 +|** ## **** + $-+| 2 +|+ + + + ****| - *|=***###****########@$$$$| 1 *|**@@@&&&%*#####***=**==$| - 1 #|#*=*****##*###@===####@@| 0 #|@*******&&%#####==###$==| -response z@|###*##**=##=*********##response z=|===#########**#####*###@| - -1 +|%$########@*******&&****| -1 +|+###======@@***@**@@@*##| - *|#%%####@@***########&&&*| -2 #|##*########@@@***####+-+| - -2 +|------------------------| -3 +|------------------------| - -3 +-+###+######+#####+###+-+ -4 +-+###+######+#####+###+-+ - -1 -0.5 0 0.5 1 -1 -0.5 0 0.5 1 - input variable x input variable x +multiplot> set style increment default; + ^ + line 0: warning: deprecated command + Proba. of being dominated + simulated Pareto fronts--| || + +| #+@ + *==$@& &*$ +# +| ++-+--+--+---+--+--+ ++||00% + +| #+@ + *==$@& &*$ +# +| ||#|##|##|###|##|##| || + #|###@####*==$@&#&*$#### | +|#+##+##+###+##+##+ || + #|###@####*==$@&#&*$#### | |#################| || + 500 +|+##@####*==$@&#&*$###+-+| 500 +---+##########+---+ || + #|%%%%%%%%%%%%%%%%%%%%%%%%| |#################| ++||5% + #|###@@@@@*==$@&@&*$@@#@@@| |#################| || + #|########*==$@**&*$**#***| |#################| || + #|#################$######| |#################| || + 0 +|+########********$**second objective--+##########+---+ ++||0% + #|#########==$@%%&*$%%%%%%| |#################| || + #|#########==$@$$&*$&&&&&&| |#################| || + #|#########==#@@@@*$@@@@@@| |#################| || + #|#########=======*$******| |#################| || + #|#########========$==####| -500 |#################| ++||5% + -500 +|+############&&&&$&&&&&&| +---+##########+---+ || + #|#################$$$$$$$| |#################| || + #|###################### | +|#+##+##+###+##+##+ || + +|------------------------| |+-|--|--|---|--|--| || + +###+###+###+####+###+## + -30-20-100+01002003000++-0% + -300-200-1000 0 100020003000 + first objective first objective 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb03.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb03.m -***** test stk_example_kb03; close all; +[inst/examples/03_miscellaneous/stk_example_misc01.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc01.m +***** test stk_example_misc01; close all; -#========================# -# stk_example_kb03 # -#========================# +#==========================# +# stk_example_misc01 # +#==========================# -'stk_example_kb03' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb03.m +'stk_example_misc01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc01.m - STK_EXAMPLE_KB03 Ordinary kriging in 2D + STK_EXAMPLE_MISC01 Several correlation functions from the Matern family - An anisotropic Matern covariance function is used for the Gaussian Process - (GP) prior. The parameters of this covariance function (variance, regularity - and ranges) are estimated using the Restricted Maximum Likelihood (ReML) - method. + The Matern 1/2 correlation function is also known as the "exponential correla- + tion function". This is the correlation function of an Ornstein-Ulhenbeck pro- + cess. - The mean function of the GP prior is assumed to be constant and unknown. This - default choice can be overridden by means of the model.lm property. + The Matern covariance function tends to the Gaussian correlation function when + its regularity (smoothness) parameter tends to infinity. - The function is sampled on a space-filling Latin Hypercube design, and the - data is assumed to be noiseless. + See also: stk_materncov_iso, stk_materncov_aniso Additional help for built-in functions and operators is @@ -7775,38 +9012,18 @@ Help and information about Octave is also available on the WWW at https://www.octave.org and via the help@octave.org mailing list. - -BOX = 2-dimensional hyper-rectangle (stk_hrect object): - - : x_1 x_2 - lower_bounds : -5 0 - upper_bounds : 10 15 - 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb01n.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb01n.m -***** test stk_example_kb01n; close all; - -#=========================# -# stk_example_kb01n # -#=========================# - -'stk_example_kb01n' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb01n.m - - STK_EXAMPLE_KB01N Ordinary kriging in 1D, with noisy data - - This example shows how to compute ordinary kriging predictions on a - one-dimensional noisy dataset. - - The Gaussian Process (GP) prior is the same as in stk_example_kb01. +[inst/examples/03_miscellaneous/stk_example_misc03.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc03.m +***** test stk_example_misc03; close all; - The observation noise is Gaussian and homoscedastic (constant variance). - Its variance is assumed to be known. +#==========================# +# stk_example_misc03 # +#==========================# - Note that the kriging predictor, which is the posterior mean of the GP, - does NOT interpolate the data in this noisy example. +'stk_example_misc03' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc03.m - See also: stk_example_kb01, stk_example_kb02n + STK_EXAMPLE_MISC03 How to deal with (known) seasonality Additional help for built-in functions and operators is @@ -7820,7 +9037,7 @@ scalar structure containing the fields: - covariance_type = @stk_materncov_iso + covariance_type = @stk_materncov52_iso lm = @@ -7828,258 +9045,28 @@ dim = 1 param = - -0.6931 - 1.3863 - 0.9163 - - lognoisevariance = -3.2189 - - line 0: warning: iconv failed to convert degree sign - - - | True function and observed data - 1.5 +|+ - | G******* +--------------------+ - #|#######***##G##G***#######################|***?***True function| - 1 +|+####G**##########*G*#####################+---G---Observations-+ - #|####**##############**######################################### - #|###**################*G###########################G############ - 0.5 G|+#**##################**###########################******G###G# - #|*G######################**######################***###G##***### - 0 +|*########################**####################**##########***# - *|##########################**#################**G#############*** - #|###########################**###############**#################*G - -0.5 +|+#########################G#*G#############**################## * - #|#############################**###########*G################### - #|##############################**#G#######**#################### - -1 +|+##############################***#####*G###################### - #|#################################***G***####################### - +|------------------------------------------------------------------ - -1.5 +-+##############+###############+################+############## + - -1 -0.5 0 0.5 1 - input variable x - -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb05.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb05.m -***** test stk_example_kb05; close all; - -#========================# -# stk_example_kb05 # -#========================# - -'stk_example_kb05' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb05.m - - STK_EXAMPLE_KB05 Generation of conditioned sample paths - - A Matern Gaussian process model is used, with constant but unknown mean - (ordinary kriging) and known covariance parameters. - - Given noiseless observations from the unknown function, a batch of conditioned - sample paths is drawn using the "conditioning by kriging" technique. In short, - this means that unconditioned sample path are simulated first (using - stk_generate_samplepaths), and then conditioned on the observations by kriging - (using stk_conditioning). - - Note: in this example, for pedagogical purposes, conditioned samplepaths are - simulated in two steps: first, unconditioned samplepaths are simulated; - second, conditioned samplepaths are obtained using conditioning by kriging. - In practice, these two steps can be carried out all at once using - stk_generate_samplepath (see, e.g., stk_example_kb09). - - See also: stk_generate_samplepaths, stk_conditioning, stk_example_kb09 - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb02n.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb02n.m -***** test stk_example_kb02n; close all; - -#=========================# -# stk_example_kb02n # -#=========================# - -'stk_example_kb02n' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb02n.m - - STK_EXAMPLE_KB02N Noisy ordinary kriging in 1D with parameter estimation - - This example shows how to estimate covariance parameters and compute - ordinary kriging predictions on a one-dimensional noisy dataset. - - The model and data are the same as in stk_example_kb02, but this time the - parameters of the covariance function and the variance of the noise are - jointly estimated using the Restricted Maximum Likelihood (ReML) method. - - See also: stk_example_kb01n, stk_example_kb02 - + 1.9918 + -1.8765 -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. + lognoisevariance = -4.7202 -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -model = +model2 = scalar structure containing the fields: - covariance_type = @stk_materncov_iso + covariance_type = @stk_materncov52_iso lm = - +@(t) [ones(length (t), 1), sin(2 * pi * t / T0), cos(2 * pi * t / T0)] dim = 1 param = - -0.098610 - 2.302585 - 0.613435 - - lognoisevariance = -3.0915 - -True noise variance = 0.0400 -Estimated noise variance = 0.0454 - - line 0: warning: iconv failed to convert degree sign - - - | True function and noisy observed data - 1.5 +|+ - | G ***** +--------------------+ - #|#######***##G##G**########################|***?***True function| - 1 +|+####G**#########**G######################+---G---Observations-+ - #|####**#############***######################################### - #|###**################**######################################## - 0.5 +|+#**##################G*##########################G#***######## - G|#**####################**########################****#G**G*##G# - #|*G######################**#####################***########***## - F1 0 *|+########################**###################**############*** - *|##########################**#################**G##############**G - #|###########################**G##############**#################** - -0.5 +|+#########################G#**#############**################## - #|#############################**###########*G################### - #|##############################***G######**##################### - -1 +|+###############################**#####*G###################### - #|#################################***G**######################## - +|------------------------------------------------------------------ - -1.5 +-+##############+###############+################+############## + - -1 -0.5 0 0.5 1 - -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/01_kriging_basics/stk_example_kb09.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/01_kriging_basics/stk_example_kb09.m -***** test stk_example_kb09; close all; - -#========================# -# stk_example_kb09 # -#========================# - -'stk_example_kb09' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/01_kriging_basics/stk_example_kb09.m - - STK_EXAMPLE_KB09 Generation of sample paths conditioned on noisy observations - - A Matern Gaussian process model is used, with constant but unknown mean - (ordinary kriging) and known covariance parameters. - - Given noisy observations from the unknown function, a batch of conditioned - sample paths is drawn using the "conditioning by kriging" technique - (stk_generate_samplepaths function). - - See also: stk_generate_samplepaths, stk_conditioning, stk_example_kb05 - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/03_miscellaneous/stk_example_misc04.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc04.m -***** test stk_example_misc04; close all; - -#==========================# -# stk_example_misc04 # -#==========================# - -'stk_example_misc04' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc04.m - - STK_EXAMPLE_MISC04 Pareto front simulation - - DESCRIPTION - - We consider a bi-objective optimization problem, where the objective - functions are modeled as a pair of independent stationary Gaussian - processes with a Matern 5/2 anisotropic covariance function. - - Figure (a): represent unconditional realizations of the Pareto front and - and estimate of the probability of being non-dominated at each point - of the objective space. - - Figure (b): represent conditional realizations of the Pareto front and - and estimate of the posteriorior probability of being non-dominated - at each point of the objective space. - - EXPERIMENTAL FUNCTION WARNING - - This script uses the stk_plot_probdom2d function, which is currently - considered an experimental function. Read the help for more information. - - REFERENCE - - [1] Michael Binois, David Ginsbourger and Olivier Roustant, Quantifying - uncertainty on Pareto fronts with Gaussian Process conditional simu- - lations, European J. of Operational Research, 2043(2):386-394, 2015. - - See also: stk_plot_probdom2d - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. + -9.7350 + -8.1781 -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. - line 0: warning: iconv failed to convert degree sign + lognoisevariance = -4.7335 -multiplot> set style increment default; - ^ - line 0: warning: deprecated command - Proba. of being dominated - simulated Pareto fronts--| || - | $ *=+$#*=%* *+$ %+ | +-+---+---+--+---++ ++||00% - | $ *=+$#*=%*=*=$======| |#|###|###|##|###|| || - 500 +|+##$#*=#$#*&%****$******| |#+###+###+##+###+| || - #|###$#*=#$#@@@&@@@$@@@@@@| 500 +---+##########+---+ || - #|###$#*=#$#*&%&***$******| |#################| || - #|###$#*=#$#$&%&&&&$&&&&&&| |#################| ++||5% - #|%%%%%%%%%%%%%%%%%%%%%%%%| |#################| || - 0 +|+#####=####&###@#$##%+-+| 0 +---+##########+---+ || - #|######=####&###@#$$$$$$$| |#################| || - #|######=####&&&&&&&&second objective|#################| ++||0% - #|######=########@####%###| |#################| || - #|######=#################| -500 |#################| || - -500 +|+#####=########@####%+-+| +---+##########+---+ || - #|######==================| |#################| || - #|###################### | |#################| ++||5% - #|###################### | |#################| || - #|###################### | -1000 |#################| || - -1000 +|+####################+-+| +---+##+###+##++---+ || - #|------------------------| +-|---|---|--|---|+ || - #####+###+####+###+####+ -200-1000010002000 ++-0% - -200-1000 0 1000 2000 - first objective first objective 1 test, 1 passed, 0 known failure, 0 skipped [inst/examples/03_miscellaneous/stk_example_misc05.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc05.m @@ -8158,91 +9145,6 @@ | 1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/03_miscellaneous/stk_example_misc01.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc01.m -***** test stk_example_misc01; close all; - -#==========================# -# stk_example_misc01 # -#==========================# - -'stk_example_misc01' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc01.m - - STK_EXAMPLE_MISC01 Several correlation functions from the Matern family - - The Matern 1/2 correlation function is also known as the "exponential correla- - tion function". This is the correlation function of an Ornstein-Ulhenbeck pro- - cess. - - The Matern covariance function tends to the Gaussian correlation function when - its regularity (smoothness) parameter tends to infinity. - - See also: stk_materncov_iso, stk_materncov_aniso - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -1 test, 1 passed, 0 known failure, 0 skipped -[inst/examples/03_miscellaneous/stk_example_misc03.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc03.m -***** test stk_example_misc03; close all; - -#==========================# -# stk_example_misc03 # -#==========================# - -'stk_example_misc03' is a script from the file /build/reproducible-path/octave-stk-2.8.1/debian/octave-stk/usr/share/octave/packages/stk-2.8.1/examples/03_miscellaneous/stk_example_misc03.m - - STK_EXAMPLE_MISC03 How to deal with (known) seasonality - - -Additional help for built-in functions and operators is -available in the online version of the manual. Use the command -'doc ' to search the manual index. - -Help and information about Octave is also available on the WWW -at https://www.octave.org and via the help@octave.org -mailing list. -model = - - scalar structure containing the fields: - - covariance_type = @stk_materncov52_iso - lm = - - - - dim = 1 - param = - - 1.6282 - -1.8005 - - lognoisevariance = -4.5530 - -model2 = - - scalar structure containing the fields: - - covariance_type = @stk_materncov52_iso - lm = - -@(t) [ones(length (t), 1), sin(2 * pi * t / T0), cos(2 * pi * t / T0)] - - dim = 1 - param = - - -9.5640 - -8.1781 - - lognoisevariance = -4.5635 - -1 test, 1 passed, 0 known failure, 0 skipped [inst/examples/03_miscellaneous/stk_example_misc02.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/examples/03_miscellaneous/stk_example_misc02.m ***** test stk_example_misc02; close all; @@ -8300,1803 +9202,165 @@ 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 input x input x 1 test, 1 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_olhs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_olhs.m -***** shared x, n, d, box, permut - n = 5; d = 2; box = [0 0; 1, 1]; permut = 1:2; -***** error x = stk_sampling_olhs(); -***** test x = stk_sampling_olhs(n); -***** test x = stk_sampling_olhs(n, d); -***** test x = stk_sampling_olhs(n, d, box); -***** test x = stk_sampling_olhs(n, d, box, permut); -***** error x = stk_sampling_olhs(n, d, box, permut, pi); -***** assert (isa (x, 'stk_dataframe')); -***** assert (isequal (x.colnames, {})); -***** test - cn = {'W', 'H'}; box = stk_hrect (box, cn); - x = stk_sampling_olhs (n, d, box); - assert (isequal (x.colnames, cn)); -***** test - for r = 1:5 - - n = 2 ^ (r + 1) + 1; d = 2 * r; - x = stk_sampling_olhs (n, d); - - assert (isequal (size (x), [n d])); - - box = repmat ([-1; 1], 1, d); - assert (stk_is_lhs (x, n, d, box)); - - x = double (x); w = x' * x; - assert (stk_isequal_tolabs (w / w(1,1), eye (d))); - - end -10 tests, 10 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampcrit_akg_eval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_akg_eval.m -***** shared zc_mean, zc_std, zr_mean, zr_std, zcr_cov, AKG, nc - xi = [0; 0.2; 0.7; 0.9]; - zi = [1; 0.9; 0.6; 0.1] - 10; - ni = 4; - - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - M_prior.lognoisevariance = 0.678; - - nc = 20; - xc = stk_sampling_regulargrid (nc, 1, [0; 1]); - [zp, ~, ~, K] = stk_predict (M_prior, xi, zi, [xi; xc]); - - ir = 1:ni; ic = ni + (1:nc); - - zc_mean = zp.mean(ic); - zc_std = sqrt (zp.var(ic)); - - % reference grid: current evaluation points ("KGCP") - zr_mean = zp.mean(ir); - zr_std = sqrt (zp.var(ir)); - - zcr_cov = K(ic, ir); -***** test AKG = stk_sampcrit_akg_eval (zc_mean, zc_std, zr_mean, zr_std, zcr_cov); -***** assert (isequal (size (AKG), [nc 1])) -***** assert (all (AKG >= 0)) -***** error AKG = stk_sampcrit_akg_eval (zc_mean, zc_std, zr_mean, zr_std); -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/sampling/@stk_sampcrit_ei/stk_sampcrit_ei.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_ei/stk_sampcrit_ei.m -***** shared F, M, EI - M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); -warning: Something went wrong during the optimization -crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt -***** test F = stk_sampcrit_ei () % ending ";" omitted on purpose, to test disp - -F = -| -| model: -- (not instantiated) -| current_minimum: Inf -| - -***** assert (isempty (F.model)) -***** assert (isempty (get (F, 'model'))) -***** assert (F.current_minimum == +inf) -***** assert (get (F, 'current_minimum') == +inf) -***** error F.toto -***** error get (F, 'toto') -***** error F.current_min = 1.234; % read-only -***** error F = set (F, 'current_min', 1.234); % read-only -***** error F.toto = 1.234; % field does not exist -***** error F = set (F, 'toto', 1.234); % field does not exist -***** error EI = feval (F, 1.0); -***** test F = stk_sampcrit_ei (); F.model = M; - assert (~ isempty (F.model)); -***** test F = stk_sampcrit_ei (); F = set (F, 'model', M); - assert (~ isempty (F.model)); -***** test F.model = []; % remove model - assert (isempty (F.model)); - assert (F.current_minimum == +inf); -***** test F = stk_sampcrit_ei (M) % ending ";" omitted on purpose, to test disp - -F = -| -| model: -| current_minimum: 1.234 -| - -***** assert (isequal (F.model, M)) -***** assert (F.current_minimum == 1.234); -***** test EI = feval (F, [1.0; 1.1; 1.2]); -***** assert (isequal (size (EI), [3 1])) -***** assert (all (EI >= 0)) -***** shared F -***** test F = stk_sampcrit_ei (stk_model ()); -***** assert (F.current_minimum == +inf); -***** error feval (F, 1.0); -24 tests, 24 passed, 0 known failure, 0 skipped -[inst/sampling/stk_halfpintl.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_halfpintl.m -***** test % case #1 - a = 1; - b = 1; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (a_out == 1) - assert (b_out == 1) - assert (isempty (z_out)) -***** test % case #2: two lines, slopes not equal, already sorted - a = [1; -1]; - b = [0; 2]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -***** test % case #3: same as #2, but not sorted - a = [-1; 1]; - b = [ 2; 0]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -***** test % case #4: two lines, equal slopes, already sorted - a = [0; 0]; - b = [1; 2]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (a_out == 0) - assert (b_out == 1) - assert (isempty (z_out)) -***** test % case #5: same as #4, but not sorted - a = [0; 0]; - b = [2; 1]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (a_out == 0) - assert (b_out == 1) - assert (isempty (z_out)) -***** test % case #6: add a dominated line to #2 (the result does not change) - a = [1; -1; 0]; - b = [0; 2; 1]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -***** test % case #7: permutation of #6 - a = [1; 0; -1]; - b = [0; 1; 2]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -***** test % case #8: another permutation of #6 - a = [0; 1; -1]; - b = [1; 0; 2]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -***** test % case #9: same as #8, with some duplicated lines added - a = [0; 1; 0; -1; 0; -1; 1]; - b = [1; 0; 1; 2; 1; 2; 0]; - [a_out, b_out, z_out] = stk_halfpintl (a, b); - assert (isequal (a_out, [1; -1])) - assert (isequal (b_out, [0; 2])) - assert (z_out == 1) -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_maximinlhs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_maximinlhs.m -***** shared x, n, dim, box, niter - n = 20; dim = 2; box = [0, 0; 1, 1]; niter = 1; -***** error x = stk_sampling_maximinlhs (); -***** test x = stk_sampling_maximinlhs (n); -***** test x = stk_sampling_maximinlhs (n, dim); -***** test x = stk_sampling_maximinlhs (n, dim, box); -***** test x = stk_sampling_maximinlhs (n, dim, box, niter); -***** assert (isa (x, 'stk_dataframe')); -***** assert (isequal (x.colnames, {})); -***** test - cn = {'W', 'H'}; box = stk_hrect (box, cn); - x = stk_sampling_maximinlhs (n, dim, box); - assert (isequal (x.colnames, cn)); -***** test - for dim = 1:5, - x = stk_sampling_randomlhs (n, dim); - assert (isequal (size (x), [n dim])); - u = double (x); u = u(:); - assert (~ any (isnan (u) | isinf (u))); - assert ((min (u) >= 0) && (max (u) <= 1)); - assert (stk_is_lhs (x, n, dim)); - end -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_randunif.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_randunif.m -***** shared x, n, dim, box - n = 10; dim = 2; box = [0, 0; 2, 2]; -***** error x = stk_sampling_randunif (); -***** test x = stk_sampling_randunif (n); -***** test x = stk_sampling_randunif (n, dim); -***** test x = stk_sampling_randunif (n, dim, box); -***** assert (isa(x, 'stk_dataframe')); -***** assert (isequal (x.colnames, {})); -***** test - cn = {'W', 'H'}; box = stk_hrect (box, cn); - x = stk_sampling_randunif (n, dim, box); - assert (isequal (x.colnames, cn)); -***** test - for dim = 1:5, - x = stk_sampling_randunif(n, dim); - assert(isequal(size(x), [n dim])); - u = double(x); u = u(:); - assert(~any(isnan(u) | isinf(u))); - assert((min(u) >= 0) && (max(u) <= 1)); - end -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_nestedlhs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_nestedlhs.m -***** shared x, n, dim, box, niter, levels - n = [48; 12; 4; 2]; dim = 2; box = [0, 0; 4, 4]; niter = 10; - levels = [10.1; 15.2; -9.3; 2.4; 17.5]; -***** error x = stk_sampling_nestedlhs (); -***** test x = stk_sampling_nestedlhs (n); -***** test x = stk_sampling_nestedlhs (n, dim); -***** test x = stk_sampling_nestedlhs (n, dim, box); -***** test x = stk_sampling_nestedlhs (n, dim, box, niter); -***** test x = stk_sampling_nestedlhs (n, dim, box, niter, levels); -***** assert ( isequal(size(x), [sum(n), dim + 1]) ); -***** assert ( isa(x, 'stk_dataframe') ); - cn = [0; cumsum(n)]; - for lev = 1:length(n), - y = x( (cn(lev) + 1):(cn(lev + 1)), 1:dim ); - assert (isequal (size (y), [n(lev) dim])); - assert (stk_is_lhs (y, n(lev), dim, box)); - if lev > 1 - assert ( isequal(z((end - n(lev) + 1):end, :), y) ); - end - z = y; - end -***** assert (isequal (x.colnames{dim + 1}, 'Level')); - levels = stk_dataframe(levels, {'t'}); - box = stk_hrect(box, {'x1', 'x2', 'x3', 'x4'}); -***** test x = stk_sampling_nestedlhs (n, [], box, [], levels); -***** assert (isequal(x.colnames, {'x1', 'x2', 'x3', 'x4', 't'}) ); -11 tests, 11 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampcrit_ehvi_eval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_ehvi_eval.m -***** shared zr, zi - zr = [1 1]; - zi = [0.25 0.75; 0.5 0.5; 0.75 0.25]; -***** test % no improvement (1 computation) - zp_mean = [0.6 0.6]; zp_std = [0 0]; - EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); - assert (stk_isequal_tolabs (EHVI, 0, 1e-12)); -***** test % guaranteed improvement (1 computation) - zp_mean = [0 0]; zp_std = [0 0]; - EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); - assert (stk_isequal_tolabs (EHVI, 10 * 0.25 ^ 2)); -***** test % no improvement again (2 computations) - zp_mean = [0.5 0.5; 0.6 0.6]; zp_std = [0 0; 0 0]; - EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); - assert (stk_isequal_tolabs (EHVI, [0; 0], 1e-12)); -***** test % no observation -> EHVI wrt zr - zp_mean = [0.6 0.6]; zp_std = 0.01 * [1 1]; zi = []; - EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); - assert (stk_isequal_tolabs (EHVI, (1 - 0.6)^2, 1e-12)); -***** test % no observation below zr -> EHVI wrt zr - zp_mean = [0.6 0.6]; zp_std = 0.01 * [1 1]; zi = [2 2]; - EHVI = stk_sampcrit_ehvi_eval (zp_mean, zp_std, zi, zr); - assert (stk_isequal_tolabs (EHVI, (1 - 0.6)^2, 1e-12)); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/sampling/@stk_sampcrit_eqi/stk_sampcrit_eqi.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_eqi/stk_sampcrit_eqi.m -***** shared F, M, EQI - M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); -warning: Something went wrong during the optimization -crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt -***** test F = stk_sampcrit_eqi () % ending ";" omitted on purpose, to test disp - -F = -| -| model: -- (not instantiated) -| quantile_order: 0.5 -| point_batch_size: 1 -| current_minimum: Inf -| - -***** assert (isempty (F.model)) -***** assert (isempty (get (F, 'model'))) -***** assert (F.quantile_order == 0.5) -***** assert (get (F, 'quantile_order') == 0.5) -***** assert (F.current_minimum == +inf) -***** assert (get (F, 'current_minimum') == +inf) -***** error F.toto -***** error get (F, 'toto') -***** error F.current_min = 1.234; % read-only -***** error F = set (F, 'current_min', 1.234); % read-only -***** error F.toto = 1.234; % field does not exist -***** error F = set (F, 'toto', 1.234); % field does not exist -***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) -***** test F = set (F, 'quantile_order', 0.8); assert (F.quantile_order == 0.8) -***** error F.quantile_order = 1.1; -***** error F.quantile_order = -0.1; -***** error F.quantile_order = [1 2]; -***** error F.current_minimum = 3.333; % read-only -***** error F.quantile_value = 2.222; % read-only -***** error EQI = feval (F, 1.0); -***** test F = stk_sampcrit_eqi (); F.model = M; - assert (~ isempty (F.model)); -***** test F = stk_sampcrit_eqi (); F = set (F, 'model', M); - assert (~ isempty (F.model)); -***** test F.model = []; % remove model - assert (isempty (F.model)); - assert (F.current_minimum == +inf); -***** test F = stk_sampcrit_eqi (M) % ending ";" omitted on purpose, to test disp - -F = -| -| model: -| quantile_order: 0.5 -| point_batch_size: 1 -| current_minimum: 1.234 -| - -***** assert (isequal (F.model, M)) -***** assert (stk_isequal_tolrel (F.current_minimum, 1.234, 10 * eps)); -***** test EQI = feval (F, [1.0; 1.1; 1.2]); -***** assert (isequal (size (EQI), [3 1])) -***** assert (all (EQI >= 0)) -***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) -***** shared F, M, EQI - prior_model = stk_model (); - prior_model.lognoisevariance = 0.678; - M = stk_model_gpposterior (prior_model, [1 2 3]', [1.234 3 2]'); -***** test F = stk_sampcrit_eqi (M); -***** assert (isequal (F.model, M)) -***** assert (stk_isequal_tolrel (F.current_minimum, 2.077997, 1e-5)); -***** test EQI = feval (F, [1.0; 1.1; 1.2]); -***** assert (isequal (size (EQI), [3 1])) -***** assert (all (EQI >= 0)) -***** test F.quantile_order = 0.9; assert (F.quantile_order == 0.9) -***** shared F -***** test F = stk_sampcrit_eqi (stk_model ()); -***** assert (F.current_minimum == +inf); -***** error feval (F, 1.0); -***** shared F, M - M = stk_model_gpposterior (stk_model (), [1 2 3]', [1.234 3 2]'); -warning: Something went wrong during the optimization -crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt -***** error F = stk_sampcrit_eqi (M, [], 0); -***** error F = stk_sampcrit_eqi (M, [], 1.5); -***** error F = stk_sampcrit_eqi (M, [], nan); -***** error F = stk_sampcrit_eqi (M, [], [10 20]); -***** test F = stk_sampcrit_eqi (M, [], 10); -***** assert (isequal (F.quantile_order, 0.5)); -***** assert (isequal (F.point_batch_size, 10)); -***** error F = stk_sampcrit_eqi (M, 0.8, 0); -***** error F = stk_sampcrit_eqi (M, 0.8, 1.5); -***** error F = stk_sampcrit_eqi (M, 0.8, nan); -***** error F = stk_sampcrit_eqi (M, 0.8, [10 20]); -***** test F = stk_sampcrit_eqi (M, 0.8, 5); -***** assert (isequal (F.quantile_order, 0.8)); -***** assert (isequal (F.point_batch_size, 5)); -***** shared F, M, EQI - prior_model = stk_model (); - prior_model.lognoisevariance = 0.678; - M = stk_model_gpposterior (prior_model, [1 2 3]', [1.234 3 2]'); - F = stk_sampcrit_eqi (M); -***** test F.point_batch_size = 10; % numeric -***** assert (isequal (F.point_batch_size, 10)) -***** test EQI = feval (F, [1.0; 1.1; 1.2]); -***** test F.point_batch_size = @(x, n) 100 - n; % function handle -***** assert (isa (F.point_batch_size, 'function_handle')) -***** test EQI = feval (F, [1.0; 1.1; 1.2]); -***** test F.point_batch_size = 'sin'; % char -***** assert (isa (F.point_batch_size, 'function_handle')) -63 tests, 63 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_vdc_rr2.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_vdc_rr2.m -***** error __stk_sampling_vdc_rr2__() % two inputs required -***** error __stk_sampling_vdc_rr2__(10) % two inputs required -***** error __stk_sampling_vdc_rr2__(10, 3, -1) % two inputs required -***** test - n = 300; j = 25; - x = __stk_sampling_vdc_rr2__(n, j); - assert(isequal(size(x), [n 1])) -***** test - x = __stk_sampling_vdc_rr2__(2000, 7); - y = double (x(1998:2000, :)); - yref = [0.849786281294525; 0.085080398941584; 0.555668634235701]; - assert(stk_isequal_tolrel(y, yref, 1e-13)); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/sampling/@stk_sampcrit_akg/stk_sampcrit_akg.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_sampcrit_akg/stk_sampcrit_akg.m -***** shared F, M, AKG - M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); -warning: Something went wrong during the optimization -crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt -***** test F = stk_sampcrit_akg () % ending ";" omitted on purpose, to test disp - -F = -| -| model: -- (not instantiated) -| reference_grid: -- (use current evaluation points) -| - -***** assert (isempty (F.model)) -***** assert (isempty (get (F, 'model'))) -***** assert (isempty (F.reference_grid)) -***** assert (isempty (get (F, 'reference_grid'))) -***** error F.toto -***** error get (F, 'toto') -***** error F.toto = 1.234; % field does not exist -***** error F = set (F, 'toto', 1.234); % field does not exist -***** error AKG = feval (F, 1.0); -***** test F = stk_sampcrit_akg (); F.model = M; - assert (isequal (F.model, M)); -***** test F = stk_sampcrit_akg (); F = set (F, 'model', M); - assert (isequal (F.model, M)); - assert (isequal (size (F.zr_mean), [3 1])) % n x 1 - assert (isequal (size (F.zr_std), [3 1])) % n x 1 - assert (isequal (size (F.zr_lambdamu), [4 3])) % (n+1) x n (constant mean) -***** test F.model = []; % remove model - assert (isempty (F.model)); - assert (isempty (F.zr_mean)) - assert (isempty (F.zr_std)) - assert (isempty (F.zr_lambdamu)) -***** test xr = [1 1.5 2 2.5 3]'; - F.reference_grid = xr % ending ";" omitted on purpose, to test disp - assert (isequal (F.reference_grid, xr)) - assert (isempty (F.zr_mean)) - assert (isempty (F.zr_std)) - assert (isempty (F.zr_lambdamu)) - -F = -| -| model: -- (not instantiated) -| reference_grid: <5x1 double array> -| - -***** test F.reference_grid = []; - assert (isempty (F.reference_grid)) -***** test F = stk_sampcrit_akg (); F.model = M; - assert (isequal (F.model, M)); - xr = [1 1.5 2 2.5 3]'; - F.reference_grid = xr % ending ";" omitted on purpose, to test disp - assert (isequal (F.reference_grid, xr)) - assert (isequal (size (F.zr_mean), [5 1])) % nr x 1 - assert (isequal (size (F.zr_std), [5 1])) % nr x 1 - assert (isequal (size (F.zr_lambdamu), [4 5])) % (n+1) x nr (constant mean) - -F = -| -| model: -| reference_grid: <5x1 double array> -| - -***** test F.reference_grid = []; - assert (isempty (F.reference_grid)) -***** test F = stk_sampcrit_akg (M) % ending ";" omitted on purpose, to test disp - -F = -| -| model: -| reference_grid: -- (use current evaluation points) -| - -***** assert (isequal (F.model, M)) -***** test AKG = feval (F, [1.0; 1.1; 1.2]); -***** assert (isequal (size (AKG), [3 1])) -***** assert (all (AKG >= 0)) -***** test [AKG2, zp] = feval (F, [1.0; 1.1; 1.2]); - assert (isequal (AKG2, AKG)); - assert (isa (zp, 'stk_dataframe') && isequal (size (zp), [3 2])) -***** shared F, xr - xr = [1 1.5 2 2.5 3]'; -***** test F = stk_sampcrit_akg (stk_model ()); -***** assert (isempty (F.reference_grid)) -***** test F.reference_grid = xr; -***** assert (isequal (F.reference_grid, xr)) -***** assert (isempty (F.zr_mean)) -***** assert (isempty (F.zr_std)) -***** assert (isempty (F.zr_lambdamu)) -***** error AKG = feval (F, 1.0); -***** shared F, M, xr - xr = [1 1.5 2 2.5 3]'; - M = stk_model_gpposterior (stk_model, [1 2 3]', [1.234 3 2]'); -warning: Something went wrong during the optimization -crit0 = 2.594852, crit_opt = 2.594852: crit0 < crit_opt -***** test F = stk_sampcrit_akg (M, xr); -***** assert (isequal (F.model, M)) -***** assert (isequal (F.reference_grid, xr)) -***** assert (isequal (size (F.zr_mean), [5 1])) % nr x 1 -***** assert (isequal (size (F.zr_std), [5 1])) % nr x 1 -***** assert (isequal (size (F.zr_lambdamu), [4 5])) % (n+1) x nr (constant mean) -37 tests, 37 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_nesteddesign.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_nesteddesign.m -***** shared x, n, dim, box, niter, levels - n = [23; 14; 5; 2]; dim = 2; box = [0, 0; 4, 4]; niter = 10; - levels = [10.1; 15.2; -9.3; 2.4; 17.5]; -***** error x = stk_sampling_nesteddesign (); -***** test x = stk_sampling_nesteddesign (n); -***** test x = stk_sampling_nesteddesign (n, dim); -***** test x = stk_sampling_nesteddesign (n, dim, box); -***** test x = stk_sampling_nesteddesign (n, dim, box, niter); -***** test x = stk_sampling_nesteddesign (n, dim, box, niter, levels); -***** assert ( isequal(size(x), [sum(n), dim + 1]) ); -***** assert ( isa(x, 'stk_dataframe') ); - cn = [0; cumsum(n)]; - for lev = 1:length(n), - y = x( (cn(lev) + 1):(cn(lev + 1)), 1:dim ); - assert (isequal (size (y), [n(lev) dim])); - if lev > 1 - assert ( isequal(z((end - n(lev) + 1):end, :), y) ); - end - if lev == length(n) - assert (stk_is_lhs (y, n(lev), dim, box)); - end - z = y; - end -***** assert (isequal (x.colnames{dim + 1}, 'Level')); - levels = stk_dataframe(levels, {'t'}); - box = stk_hrect(box, {'x1', 'x2', 'x3', 'x4'}); -***** test x = stk_sampling_nesteddesign (n, [], box, [], levels); -***** assert (isequal(x.colnames, {'x1', 'x2', 'x3', 'x4', 't'}) ); -11 tests, 11 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_regulargrid.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_regulargrid.m -***** shared x, n, dim, box - n = 9; dim = 2; box = [0, 0; 1, 1]; -***** error x = stk_sampling_regulargrid (); -***** test x = stk_sampling_regulargrid (n); -***** test x = stk_sampling_regulargrid (n, dim); -***** test x = stk_sampling_regulargrid (n, dim, box); -***** assert (isa (x, 'stk_dataframe')); -***** assert (isa (x, 'stk_factorialdesign')); -***** assert (isequal (x.colnames, {})); -***** test - cn = {'W', 'H'}; box = stk_hrect (box, cn); - x = stk_sampling_regulargrid (n, dim, box); - assert (isequal (x.colnames, cn)); -***** test - for dim = 1:3, - n = 3^dim; - x = stk_sampling_regulargrid(n, dim); - assert(isequal(size(x), [n dim])); - u = double(x); u = u(:); - assert(~any(isnan(u) | isinf(u))); - assert((min(u) >= 0) && (max(u) <= 1)); - end -***** test - nn = [3 4 5]; - for dim = 1:3, - x = stk_sampling_regulargrid(nn(1:dim), dim); - assert(isequal(size(x), [prod(nn(1:dim)) dim])); - u = double(x); u = u(:); - assert(~any(isnan(u) | isinf(u))); - assert((min(u) >= 0) && (max(u) <= 1)); - end -10 tests, 10 passed, 0 known failure, 0 skipped -[inst/sampling/@stk_function/stk_function.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/@stk_function/stk_function.m -***** shared F -***** test F = stk_function () % ending ";" omitted on purpose, to test disp - -F = - -***** error [F F]; % arrays of sampling criterion objects are not supported -***** error [F; F]; % idem -***** error get (F, 'toto'); % field does not exist -***** error y = feval (F, 1.0); % not implemented for "pure" function objects -***** error dummy = F{2}; % illegal indexing -***** error dummy = F(1.0); % feval not implemented -***** error dummy = F.toto; % field does not exist -***** error F{2} = 1.234; % illegal indexing -***** error F(5) = 1.234; % illegal indexing -***** error F.toto = 1.234; % field does not exist -11 tests, 11 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampcrit_ei_eval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampcrit_ei_eval.m -***** error EI = stk_sampcrit_ei_eval () % not enough args -***** error EI = stk_sampcrit_ei_eval (0) % not enough args -***** shared xi, zi, M_prior, xt, zp, EIref, EI1, EI2, EI3 - xi = [0; 0.2; 0.7; 0.9]; - zi = [1; 0.9; 0.6; 0.1]; - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - xt = stk_sampling_regulargrid (20, 1, [0; 1]); - zp = stk_predict (M_prior, xi, zi, xt); - EIref = stk_distrib_normal_ei (min (zi), zp.mean, sqrt (zp.var), true); -***** test % Current syntax (STK 2.4.1 and later) - EI1 = stk_sampcrit_ei_eval (zp.mean, sqrt (zp.var), min (zi)); -***** assert (isequal (EI1, EIref)) -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_halton_rr2.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_halton_rr2.m -***** error stk_sampling_halton_rr2 () % nargin < 1 -***** test - n = 300; d = 25; - x = stk_sampling_halton_rr2 (n, d); - assert (isequal (size (x), [n d])) -***** test - x = stk_sampling_halton_rr2 (1000, 3); - y = double (x(end, :)); - yref = [0.9052734375 0.028349336991312 0.74848]; - assert (stk_isequal_tolrel (y, yref, 1e-13)); -***** test - dim = 2; box = stk_hrect (dim); - x = stk_sampling_halton_rr2 (5, dim, box); - assert (isequal (x.colnames, {})); -***** test - dim = 2; cn = {'W', 'H'}; box = stk_hrect (dim, cn); - x = stk_sampling_halton_rr2 (5, dim, box); - assert (isequal (x.colnames, cn)); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/sampling/stk_sampling_randomlhs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/sampling/stk_sampling_randomlhs.m -***** shared x, n, dim, box - n = 10; dim = 2; box = [0, 0; 1, 1]; -***** error x = stk_sampling_randomlhs (); -***** test x = stk_sampling_randomlhs (n); -***** test x = stk_sampling_randomlhs (n, dim); -***** test x = stk_sampling_randomlhs (n, dim, box); -***** assert (isa(x, 'stk_dataframe')); -***** assert (isequal (x.colnames, {})); -***** test - cn = {'W', 'H'}; box = stk_hrect (box, cn); - x = stk_sampling_randomlhs (n, dim, box); - assert (isequal (x.colnames, cn)); -***** test - for dim = 1:5, - x = stk_sampling_randomlhs(n, dim); - assert(isequal(size(x), [n dim])); - u = double(x); u = u(:); - assert(~any(isnan(u) | isinf(u))); - assert((min(u) >= 0) && (max(u) <= 1)); - assert(stk_is_lhs(x, n, dim)); - end -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/ismember.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/ismember.m -***** shared A, B, BB, b - - i_max = 10; n = 100; d = 5; - - A = randi (i_max, n, d); - - levels = repmat ({1:i_max}, 1, d); - levels{4} = 1:2:i_max; - B = stk_factorialdesign (levels); - - BB = double (B); -***** test b = ismember (A, B); -***** assert (isequal (b, ismember (A, BB))); -***** test b = ismember (A, B, 'rows'); -***** assert (isequal (b, ismember (A, BB, 'rows'))); -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/stk_factorialdesign.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_factorialdesign.m -***** test stk_test_class ('stk_factorialdesign') -***** test % constructor with two factors + column names - x = stk_factorialdesign ({[0 1], [1 2 3]}, {'a', 'b'}); - assert (isequal(x.colnames, {'a', 'b'})); - assert (isequal(get (x, 'colnames'), {'a', 'b'})); -***** error stk_factorialdesign ('bouh'); -***** error stk_factorialdesign ({{'a' 'b'}}); -***** shared x, fmt - fmt = stk_disp_getformat (); - x = stk_sampling_regulargrid (3^2, 2); -***** test format rat; disp (x); - : --- --- - * : 0.0 0.0 - * : 0.5 0.0 - * : 1.0 0.0 - * : 0.0 0.5 - * : 0.5 0.5 - * : 1.0 0.5 - * : 0.0 1.0 - * : 0.5 1.0 - * : 1.0 1.0 -***** test format long; disp (x); - : --- --- - * : 0.0 0.0 - * : 0.5 0.0 - * : 1.0 0.0 - * : 0.0 0.5 - * : 0.5 0.5 - * : 1.0 0.5 - * : 0.0 1.0 - * : 0.5 1.0 - * : 1.0 1.0 -***** test format short; disp (x); format (fmt); - : --- --- - * : 0.0 0.0 - * : 0.5 0.0 - * : 1.0 0.0 - * : 0.0 0.5 - * : 0.5 0.5 - * : 1.0 0.5 - * : 0.0 1.0 - * : 0.5 1.0 - * : 1.0 1.0 -***** test disp (stk_sampling_regulargrid (0^1, 1)); - Empty data frame with 0 rows and 0 columns -***** test disp (stk_sampling_regulargrid (0^2, 2)); - Empty data frame with 0 rows and 0 columns -***** test display (x); - -x = <9x2 stk_factorialdesign array> - - : --- --- - * : 0.0 0.0 - * : 0.5 0.0 - * : 1.0 0.0 - * : 0.0 0.5 - * : 0.5 0.5 - * : 1.0 0.5 - * : 0.0 1.0 - * : 0.5 1.0 - * : 1.0 1.0 - -***** error length (stk_sampling_regulargrid (7^2, 2)) % not defined -***** shared x - x = stk_factorialdesign ({[0 1], [0 1]}); -***** assert (isequal (x(2:end, :), x(2:4, :))) -***** assert (isequal (x(2, 1:end), x(2, :))) -***** assert (isequal (x(2:end, 2:end), x(2:4, 2))) -***** error x(1:end, 1:end, 1:end) -***** shared x, y - x = stk_sampling_regulargrid (3^2, 2); - y = x; -***** test %%%% vercat - z = vertcat (x, y); - assert (strcmp (class (z), 'stk_dataframe')); - assert (isequal (double (z), [double(x); double(y)])); -***** test %%%% same thing, using cat(1, ...) - z = cat (1, x, y); - assert (strcmp (class (z), 'stk_dataframe')); - assert (isequal (double (z), [double(x); double(y)])); -***** test %%%% horzcat - y.colnames = {'y1' 'y2'}; z = horzcat (x, y); - assert (strcmp (class (z), 'stk_dataframe')); - assert (isequal (double (z), [double(x) double(y)])); -***** test %%%% same thing, using cat (2, ...) - z = cat (2, x, y); - assert (strcmp (class (z), 'stk_dataframe')); - assert (isequal (double (z), [double(x) double(y)])); -***** error cat (3, x, y) -***** shared x, t - x = stk_sampling_regulargrid (3^2, 2); - t = double (x); -***** assert (isequal (apply (x, 1, @sum), sum (t, 1))) -***** assert (isequal (apply (x, 2, @sum), sum (t, 2))) -***** error u = apply (x, 3, @sum); -***** assert (isequal (apply (x, 1, @min, []), min (t, [], 1))) -***** assert (isequal (apply (x, 2, @min, []), min (t, [], 2))) -***** error u = apply (x, 3, @min, []); -***** assert (isequal (min (x), min (t))) -***** assert (isequal (max (x), max (t))) -***** assert (isequal (std (x), std (t))) -***** assert (isequal (var (x), var (t))) -***** assert (isequal (sum (x), sum (t))) -***** assert (isequal (mean (x), mean (t))) -***** assert (isequal (mode (x), mode (t))) -***** assert (isequal (prod (x), prod (t))) -***** assert (isequal (median (x), median (t))) -***** shared x1, x2, x3, u1, u2, u3 - x1 = stk_sampling_regulargrid ([4 3], 2); u1 = double (x1); - x2 = stk_sampling_regulargrid ([3 4], 2); u2 = double (x2); - x3 = x1 + 1; u3 = u1 + 1; -***** test - z = bsxfun (@plus, x1, u2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) -***** test - z = bsxfun (@plus, u1, x2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) -***** test - z = bsxfun (@plus, x1, x2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) -***** test z = min (x1, x2); assert (isequal (double (z), min (u1, u2))); -***** test z = max (x1, x2); assert (isequal (double (z), max (u1, u2))); -***** error z = min (x1, x2, 1); -***** error z = max (x1, x2, 1); -***** test z = x1 + x2; assert (isequal (double (z), u1 + u2)); -***** test z = x1 - x2; assert (isequal (double (z), u1 - u2)); -***** test z = x1 .* x2; assert (isequal (double (z), u1 .* u2)); -***** test z = x3 .\ x2; assert (isequal (double (z), u3 .\ u2)); -***** test z = x2 ./ x3; assert (isequal (double (z), u2 ./ u3)); -***** test z = x3 .^ x2; assert (isequal (double (z), u3 .^ u2)); -***** test z = realpow (x3, x2); assert (isequal (double (z), realpow (u3, u2))); -***** test z = (x1 == x2); assert (isequal (double (z), (u1 == u2))); -***** test z = (x1 ~= x2); assert (isequal (double (z), (u1 ~= u2))); -***** test z = (x1 <= x2); assert (isequal (double (z), (u1 <= u2))); -***** test z = (x1 >= x2); assert (isequal (double (z), (u1 >= u2))); -***** test z = (x1 < x2); assert (isequal (double (z), (u1 < u2))); -***** test z = (x1 > x2); assert (isequal (double (z), (u1 > u2))); -***** test z = x1 & x2; assert (isequal (double (z), u1 & u2)); -***** test z = x1 | x2; assert (isequal (double (z), u1 | u2)); -***** test z = xor (x1, x2); assert (isequal (double (z), xor (u1, u2))); -***** shared x - x = stk_factorialdesign ({[0 1], [0 1 2]}); -***** assert (strcmp (class (x'), 'stk_dataframe')) -***** assert (strcmp (class (x.'), 'stk_dataframe')) -60 tests, 60 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/ndgrid.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/ndgrid.m -***** shared data - data = stk_factorialdesign ({[0 1], [5 6 7]}); -***** test % nargout = 0 - ndgrid (data); - assert (isequal (ans, [0 0 0; 1 1 1])); -***** test % nargout = 1 - x = ndgrid (data); - assert (isequal (x, [0 0 0; 1 1 1])); -***** test % nargout = 2 - [x, y] = ndgrid (data); - assert (isequal ({x, y}, {[0 0 0; 1 1 1], [5 6 7; 5 6 7]})); -***** error % nargout = 3 - [x, y, z] = ndgrid (data); -***** test - data = stk_factorialdesign ({[], []}); - [x, y] = ndgrid (data); - assert (isequal ({x, y}, {[], []})); -***** test - data = stk_factorialdesign ({[1:3]}); - x = ndgrid (data); - assert (isequal (x, [1; 2; 3])); -6 tests, 6 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/stk_boundingbox.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_boundingbox.m -***** shared x, y, cn - cn = {'a', 'b', 'c'}; - x = stk_factorialdesign ({[1 2], [3 4 5], [0 2 8]}, cn); -***** error y = stk_boundingbox (); -***** test y = stk_boundingbox (x); -***** assert (isequal (y, stk_hrect ([1 3 0; 2 5 8], cn))); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/stk_dataframe.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_dataframe.m -***** shared x, cn, rn, y, cn2, rn2 - cn = {'x' 'y'}; - rn = {'a'; 'b'; 'c'; 'd'}; - x = stk_factorialdesign ({1:2, 1:2}, cn, rn); - cn2 = {'xx' 'yy'}; - rn2 = {'aa'; 'bb'; 'cc'; 'dd'}; -***** test y = stk_dataframe (x); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn)) -***** assert (isequal (y.rownames, rn)) -***** test y = stk_dataframe (x, cn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn2)) -***** assert (isequal (y.rownames, rn)) -***** test y = stk_dataframe (x, cn2, rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn2)) -***** assert (isequal (y.rownames, rn2)) -***** test y = stk_dataframe (x, [], rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn)) -***** assert (isequal (y.rownames, rn2)) -***** test y = stk_dataframe (x, {}, rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, {})) -***** assert (isequal (y.rownames, rn2)) -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/fieldnames.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/fieldnames.m -***** test - x = stk_factorialdesign ({0:1, 3:5}, {'u' 'v'}); - fn1 = sort (fieldnames (x)); - fn2 = {'colnames'; 'data'; 'info'; 'levels'; ... - 'rownames'; 'sample_size'; 'stk_dataframe'; 'u'; 'v'}; - assert (isequal (fn1, fn2)); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/stk_normalize.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_normalize.m -***** test - x = stk_factorialdesign ({[1 2], [5 6]}); - y = stk_factorialdesign ({[0 1], [0 1]}); - assert (stk_isequal_tolabs (stk_normalize (x), y)) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/uminus.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/uminus.m -***** test - x = stk_factorialdesign ({1:3, 1:2}); - y = stk_factorialdesign ({-(1:3), -(1:2)}); - assert (isequal (-x, y)) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_factorialdesign/stk_rescale.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_rescale.m -***** test - x = stk_factorialdesign ({[1 2], [5 6]}); - y = stk_factorialdesign ({[0 3], [0 3]}); - z = stk_rescale (x, [1 5; 2 6], [0 0; 3 3]); - assert (stk_isequal_tolabs (y, z)) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_get_sample_size.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_get_sample_size.m -***** assert (stk_get_sample_size ([1 2; 3 4; 5 6]) == 3); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_length.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_length.m -***** assert (isequal (stk_length ([1 2; 3 4; 5 6]), 3)); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_boundingbox.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_boundingbox.m -***** shared x, y, cn - cn = {'a', 'b', 'c'}; - x = [0 3 2; 1 4 1; 7 0 2]; -***** error y = stk_boundingbox (); -***** test y = stk_boundingbox (x); -***** assert (isequal (y.data, [0 0 1; 7 4 2])); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_feval.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_feval.m -***** shared f, xt - f = @(x)(- (0.7 * x + sin (5 * x + 1) + 0.1 * sin (10 * x))); - xt = stk_sampling_regulargrid (20, 1, [0; 1]); -***** error yt = stk_feval (); -***** error yt = stk_feval (f); -***** test yt = stk_feval (f, xt); -***** test yt = stk_feval (f, xt, false); -***** test yt = stk_feval (f, xt, false, false); -***** test yt = stk_feval (f, xt, false, false, false); -***** test - N = 15; - xt = stk_sampling_regulargrid (N, 1, [0; 1]); - yt = stk_feval (f, xt); - assert (isequal (size (yt), [N 1])); -***** test - x = stk_dataframe ([1; 2; 3], {'x'}, {'a'; 'b'; 'c'}); - y = stk_feval (@(u)(2 * u), x); - assert (isequal (y.data, [2; 4; 6])); - assert (isequal (y.rownames, {'a'; 'b'; 'c'})); -***** shared t, z_ref, n - n = 20; - t = stk_sampling_regulargrid (n, 1, [0; 2*pi]); - z_ref = [sin(t.data) cos(t.data)]; -***** test - t.colnames = {'time'}; - z = stk_feval ({@sin, @cos}, t); - assert (isa (z, 'stk_dataframe')); - assert (isequal (z.data, z_ref)); -***** test - F = @(x)([sin(x) cos(x)]); - z = stk_feval (F, t); - assert (isequal (z.data, z_ref)); -***** test - t = stk_sampling_regulargrid (n, 1, [0; 2*pi]); - F = {'sin', 'cos'}; - z = stk_feval (F, t); - assert (isequal (z.data, [sin(t.data) cos(t.data)])); - assert (isequal (z.colnames, {'sin' 'cos'})); -***** test % vectorized - F = @(t)([sin(t) cos(t)]); - G = @(t)(0.365 * t.^2 + (cos ((t - 1).*(t - 2) + 0.579033))); - z = stk_feval ({@sin, @cos, G, F, 'tan'}, t); - assert (isequal (z.colnames, {'sin' 'cos' 'F3' 'F4_1' 'F4_2' 'tan'})); -***** test % not vectorized - F = @(t)([sin(t) cos(t)]); - G = @(t)(0.365 * t^2 + (cos ((t - 1)*(t - 2) + 0.579033))); - z = stk_feval ({@sin, @cos, G, F, 'tan'}, t, [], [], false); - assert (isequal (z.colnames, {'sin' 'cos' 'F3' 'F4_1' 'F4_2' 'tan'})); -13 tests, 13 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_normalize.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_normalize.m -***** shared x, box, y1, y2, y3, y4 - n = 5; box = [2; 3]; x = box(1) + diff (box) * rand (n, 1); -***** error y1 = stk_normalize (); -***** test y2 = stk_normalize (x); -***** test y3 = stk_normalize (x, box); -***** test assert (~ any ((y2 < -10 * eps) | (y2 > 1 + 10 * eps))); -***** test assert (~ any ((y3 < -10 * eps) | (y3 > 1 + 10 * eps))); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/generic/stk_rescale.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_rescale.m -***** shared x - x = rand (10, 4); - y = stk_rescale (x, [], []); - assert (stk_isequal_tolabs (x, y)); -***** test - y = stk_rescale(0.5, [], [0; 2]); - assert (stk_isequal_tolabs (y, 1.0)); -***** test - y = stk_rescale (0.5, [0; 1], [0; 2]); - assert (stk_isequal_tolabs (y, 1.0)); -***** test - y = stk_rescale (0.5, [0; 2], []); - assert (stk_isequal_tolabs (y, 0.25)); -***** test - y = stk_rescale (0.5, [0; 2], [0; 1]); - assert (stk_isequal_tolabs (y, 0.25)); -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/stk_hrect.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_hrect.m -***** test stk_test_class ('stk_hrect') -***** shared dom -***** test dom = stk_hrect ([-1; 1], {'x'}); -***** assert (isequal (dom.colnames, {'x'})) -***** assert (isequal (dom.rownames, {'lower_bounds'; 'upper_bounds'})) -***** assert (isequal (dom.data, [-1; 1])) -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/ismember.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/ismember.m -***** shared n, box - n = 5; - box = stk_hrect (n); -***** assert (ismember (box(1, :), box)) -***** assert (ismember (box(2, :), box)) -***** assert (ismember (.5 * ones (1, 5), box)) -***** assert (~ ismember (box(1, :) - 1, box)) -***** assert (~ ismember (box(2, :) + 1, box)) -***** test - y = double (box); y = [y; y + 2]; - assert (isequal (ismember (y, box), [1; 1; 0; 0])) -6 tests, 6 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/vertcat.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/vertcat.m -***** shared d, x, y - d = 10; - x = stk_hrect (d); - y = double (x); -***** test - z = vertcat (x, x); - assert (isequal (size (z), [4 d])); - assert (strcmp (class (z), 'stk_dataframe')); -***** test - z = vertcat (x, y); - assert (isequal (size (z), [4 d])); - assert (strcmp (class (z), 'stk_dataframe')); -***** test - z = vertcat (y, x); - assert (isequal (size (z), [4 d])); - assert (strcmp (class (z), 'stk_dataframe')); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/subsref.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/subsref.m -***** test - B = stk_hrect ([0 0 0 0; 1 2 3 4]); - B = B(:, [1 3 4]); - assert (strcmp (class (B), 'stk_hrect')); - assert (isequal (double (B), [0 0 0; 1 3 4])); -***** test - B = stk_hrect ([0 0 0 0; 1 2 3 4]); - B = B(1, :); - assert (strcmp (class (B), 'stk_dataframe')); - assert (isequal (double (B), [0 0 0 0])); -2 tests, 2 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/stk_boundingbox.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_boundingbox.m -***** shared x, y - lb = rand (1, 5); - ub = lb + 1; - cn = {'a', 'b', 'c', 'd', 'e'}; - x = stk_hrect ([lb; ub], cn); -***** error y = stk_boundingbox (); -***** test y = stk_boundingbox (x); -***** assert (isequal (y, x)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/stk_dataframe.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_dataframe.m -***** shared x, cn, rn, y, cn2, rn2 - cn = {'x' 'y'}; - rn = {'lower_bounds'; 'upper_bounds'}; - x = stk_hrect ([0 0; 1 1], cn); - cn2 = {'xx' 'yy'}; - rn2 = {'aa'; 'bb'}; -***** test y = stk_dataframe (x); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn)) -***** assert (isequal (y.rownames, rn)) -***** test y = stk_dataframe (x, cn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn2)) -***** assert (isequal (y.rownames, rn)) -***** test y = stk_dataframe (x, cn2, rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn2)) -***** assert (isequal (y.rownames, rn2)) -***** test y = stk_dataframe (x, [], rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, cn)) -***** assert (isequal (y.rownames, rn2)) -***** test y = stk_dataframe (x, {}, rn2); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.colnames, {})) -***** assert (isequal (y.rownames, rn2)) -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/stk_normalize.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_normalize.m -***** shared x, box, y1, y2, y3, y4 - n = 5; box = stk_hrect ([2; 3]); - x = 2 + rand (n, 1); -***** error y1 = stk_normalize (); -***** test y2 = stk_normalize (x); -***** test y3 = stk_normalize (x, box); -***** test assert (~ any ((y2 < -10 * eps) | (y2 > 1 + 10 * eps))); -***** test assert (~ any ((y3 < -10 * eps) | (y3 > 1 + 10 * eps))); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/horzcat.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/horzcat.m -***** shared d, x1, x2, x3 - d = 10; - x1 = stk_hrect (d); - x2 = double (x1); - x3 = [1:d; 0:(d-1)]; % illegal bounds -***** test - y1 = horzcat (x1, x1); - assert (isequal (size (y1), [2 2*d])); - assert (strcmp (class (y1), 'stk_hrect')); -***** test - y2 = horzcat (x1, x2); - assert (isequal (size (y2), [2 2*d])); - assert (strcmp (class (y2), 'stk_hrect')); -***** test - y3 = horzcat (x2, x1); - assert (isequal (size (y3), [2 2*d])); - assert (strcmp (class (y3), 'stk_hrect')); -***** test - lastwarn ('') - y4 = horzcat (x1, x3); - assert (isequal (size (y4), [2 2*d])); - assert (strcmp (class (y4), 'stk_dataframe')); - [warn_msg, warn_id] = lastwarn (); - assert (strcmp (warn_id, 'STK:stk_hrect:horzcat:IllegalBounds')) -warning: Illegal bounds, the result is not an stk_hrect object. -warning: called from - horzcat at line 47 column 9 - __test__ at line 4 column 5 - test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 958 column 31 - -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_hrect/stk_rescale.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_rescale.m -***** shared x - x = rand (10, 4); - y = stk_rescale (x, [], []); - assert (stk_isequal_tolabs (x, y)); -***** test - y = stk_rescale(0.5, [], [0; 2]); - assert (stk_isequal_tolabs (y, 1.0)); -***** test - y = stk_rescale (0.5, [0; 1], [0; 2]); - assert (stk_isequal_tolabs (y, 1.0)); -***** test - y = stk_rescale (0.5, [0; 2], []); - assert (stk_isequal_tolabs (y, 0.25)); +[inst/arrays/@stk_dataframe/mrdivide.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mrdivide.m ***** test - y = stk_rescale (0.5, [0; 2], [0; 1]); - assert (stk_isequal_tolabs (y, 0.25)); + x1_data = [8 7; 58 49]; + x1 = stk_dataframe (x1_data, {'x' 'y'}, {'a'; 'b'}); + x2_data = [8 7; 2 0]; + x2 = stk_dataframe (x2_data, {'x' 'y'}, {'u'; 'v'}); + y = x1 / x2; + assert (stk_isequal_tolabs (y, ... + stk_dataframe ([1 0; 7 1], {'u'; 'v'}, {'a'; 'b'}))); +***** shared x_data, x, y_data, y + x_data = [3 3; 6 3; 9 12]; + y_data = [1 1; 2 1; 3 4]; + x = stk_dataframe (x_data, {'x' 'y'}, {'a'; 'b'; 'c'}); +***** test y = x / 3; +***** assert (isequal (y, stk_dataframe ([1 1; 2 1; 3 4], {'x' 'y'}, {'a'; 'b'; 'c'}))); +***** error y = 3 / x; 4 tests, 4 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/cosd.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cosd.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = cosd (x); - assert (strcmp (class (v), class (u)) && isequal (v, cosd (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/realpow.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/realpow.m -***** test stk_test_dfbinaryop(@realpow, rand(7, 2), .1 + rand(7, 2)); -***** test stk_test_dfbinaryop(@realpow, rand(7, 2), .1); -***** error stk_test_dfbinaryop(@realpow, rand(7, 2), .1 + rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/disp.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/disp.m -***** shared x, fmt - fmt = stk_disp_getformat (); - x = stk_dataframe (rand (3, 2)); -***** test format rat; disp (x); - : -------- -------- - * : 0.428867 0.672970 - * : 0.812848 0.945745 - * : 0.566627 0.085803 -***** test format long; disp (x); - : ---------------- ---------------- - * : 0.42886733631875 0.67296991005971 - * : 0.81284806135797 0.94574524185019 - * : 0.56662651170990 0.08580301125411 -***** test format short; disp (x); format (fmt); - : -------- -------- - * : 0.428867 0.672970 - * : 0.812848 0.945745 - * : 0.566627 0.085803 -***** test disp (stk_dataframe (zeros (0, 1))) - Empty data frame with 0 rows and 0 columns -***** test disp (stk_dataframe (zeros (0, 2))) - Empty data frame with 0 rows and 0 columns -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/acosd.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acosd.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = acosd (x); - assert (strcmp (class (v), class (u)) && isequal (v, acosd (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/unique.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/unique.m -***** test - cn = {'u' 'v' 'w'}; x = stk_dataframe (rand (4, 3), cn); - y = [x; x]; z = unique (y, 'rows'); - assert (isequal (z.colnames, cn)); - assert (isequal (z.data, unique (x.data, 'rows'))); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sin.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sin.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = sin (x); - assert (strcmp (class (v), class (u)) && isequal (v, sin (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/apply.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/apply.m -***** shared x, t, u - t = rand (3, 2); - x = stk_dataframe (t); -***** test u = apply (x, 1, @sum); -***** assert (isequal (u, sum (t, 1))) -***** test u = apply (x, 2, @sum); -***** assert (isequal (u, sum (t, 2))) -***** error u = apply (x, 3, @sum); -***** test u = apply (x, 1, @min, []); -***** assert (isequal (u, min (t, [], 1))) -***** test u = apply (x, 2, @min, []); -***** assert (isequal (u, min (t, [], 2))) -***** error u = apply (x, 3, @min, []); -***** test - t = [1; 3; 2]; - x = stk_dataframe (t); - [M, k] = apply (x, 1, @max, []); - assert ((M == 3) && (k == 2)); -11 tests, 11 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/log.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = log (x); - assert (strcmp (class (v), class (u)) && isequal (v, log (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/log10.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log10.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = log10 (x); - assert (strcmp (class (v), class (u)) && isequal (v, log10 (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/ismember.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/ismember.m -***** shared u, x, u1, x1, u2, x2 - u = rand (10, 4); - x = stk_dataframe (u); - x1 = x(1, :); - u1 = double (x1); - u2 = - ones (1, 4); - x2 = stk_dataframe (u2); -***** assert (ismember (u1, x, 'rows')) -***** assert (ismember (x1, u, 'rows')) -***** assert (ismember (x1, x, 'rows')) -***** assert (~ ismember (u2, x, 'rows')) -***** assert (~ ismember (x2, u, 'rows')) -***** assert (~ ismember (x2, x, 'rows')) -***** test - [b, idx] = ismember ([x2; x1; x1], x, 'rows'); - assert (isequal (b, [false; true; true])); - assert (isequal (idx, [0; 1; 1])) -7 tests, 7 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/cos.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cos.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = cos (x); - assert (strcmp (class (v), class (u)) && isequal (v, cos (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sind.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sind.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = sind (x); - assert (strcmp (class (v), class (u)) && isequal (v, sind (u))) -1 test, 1 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/tan.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/tan.m ***** test u = rand (4, 3); x = stk_dataframe (u); v = tan (x); assert (strcmp (class (v), class (u)) && isequal (v, tan (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/plot.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/plot.m -***** test % plot with x as a vector and z as a (univariate) dataframe - x = linspace(0, 2*pi, 30)'; - z = stk_dataframe(sin(x)); - figure; plot(x, z); close(gcf); -***** test % plot with x as a vector and z as a (multivariate) dataframe - x = linspace(0, 2*pi, 30)'; - z = stk_dataframe([sin(x) cos(x)], {'sin' 'cos'}); - figure; plot(x, z); close(gcf); -***** test % plot with x as a dataframe and z as a vector - x = stk_dataframe(linspace(0, 2*pi, 30)'); - z = sin(double(x)); - figure; plot(x, z); close(gcf); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/log2.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log2.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = log2 (x); - assert (strcmp (class (v), class (u)) && isequal (v, log2 (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/max.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/max.m -***** test stk_test_dfbinaryop ('max', rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop ('max', rand(7, 2), pi); -***** error stk_test_dfbinaryop ('max', rand(7, 2), rand(7, 3)); -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (max(df1), max(x1))) -***** assert (isequal (max(df1, [], 1), max(x1))) -***** assert (isequal (max(df1, [], 2), max(x1, [], 2))) -***** error (max(df1, df1, 2)) -***** test - x = stk_dataframe ([1; 3; 2]); - [M, k] = max (x); - assert ((M == 3) && (k == 2)); -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/plus.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/plus.m -***** test stk_test_dfbinaryop(@plus, rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop(@plus, rand(7, 2), pi); -***** error stk_test_dfbinaryop(@plus, rand(7, 2), rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/acos.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acos.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = acos (x); - assert (strcmp (class (v), class (u)) && isequal (v, acos (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/logical.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/logical.m -***** test - u = rand (4, 3); - x = stk_dataframe (u); - v = logical (x); - assert (strcmp (class(v), 'logical') && isequal (v, logical (u))) -***** test - u = (rand (4, 3) < 0.5); - x = stk_dataframe (u); - v = logical (x); - assert (strcmp (class (v), 'logical') && isequal (v, u)) -***** test - u = uint8 (rand (4, 3) * 5); - x = stk_dataframe (u); - v = logical (x); - assert (strcmp (class (v), 'logical') && isequal (v, logical (u))) -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/isfinite.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isfinite.m -***** test - u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isfinite (x); - assert (islogical (v) && isequal (v, isfinite (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/isinf.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isinf.m -***** test - u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isinf (x); - assert (islogical (v) && isequal (v, isinf (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/stk_sprintf.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_sprintf.m -***** shared x, fmt - fmt = stk_disp_getformat (); - x = stk_dataframe (rand (3, 2)); -***** test format rat; disp (x); - : -------- -------- - * : 0.619691 0.046468 - * : 0.784400 0.802878 - * : 0.248501 0.234271 -***** test format long; disp (x); - : ---------------- ---------------- - * : 0.61969111865825 0.04646814711704 - * : 0.78440005769241 0.80287808316366 - * : 0.24850085018332 0.23427121262489 -***** test format short; disp (x); format (fmt); - : -------- -------- - * : 0.619691 0.046468 - * : 0.784400 0.802878 - * : 0.248501 0.234271 -***** test disp (stk_dataframe (zeros (0, 1))) - Empty data frame with 0 rows and 0 columns -***** test disp (stk_dataframe (zeros (0, 2))) - Empty data frame with 0 rows and 0 columns -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/asind.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asind.m +[inst/arrays/@stk_dataframe/isnan.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isnan.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = asind (x); - assert (strcmp (class (v), class (u)) && isequal (v, asind (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/length.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/length.m -***** error length (stk_dataframe ([1 2; 3 4; 5 6])) + u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isnan (x); + assert (islogical (v) && isequal (v, isnan (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/size.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/size.m -***** shared x - x = stk_dataframe([1 2; 3 4; 5 6]); -***** assert (isequal (size(x), [3 2])) -***** assert (numel(x) == 1) -***** assert (ndims(x) == 2) -***** test size(x); % force exploration of branch nargout == 0 -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/times.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/times.m -***** test stk_test_dfbinaryop(@times, rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop(@times, rand(7, 2), pi); -***** error stk_test_dfbinaryop(@times, rand(7, 2), rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/stk_get_sample_size.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_get_sample_size.m ***** test x = stk_dataframe ([1 2; 3 4; 5 6]); assert (isequal (stk_get_sample_size (x), 3)); 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/stk_length.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_length.m -***** test - x = stk_dataframe ([1 2; 3 4; 5 6]); - assert (isequal (stk_length (x), 3)); -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/atanh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/atanh.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = atanh (x); - assert (strcmp (class (v), class (u)) && isequal (v, atanh (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/atand.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/atand.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = atand (x); - assert (strcmp (class (v), class (u)) && isequal (v, atand (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/asinh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asinh.m -***** test - u = rand (4, 3); x = stk_dataframe (u); v = asinh (x); - assert (strcmp (class (v), class (u)) && isequal (v, asinh (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/std.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/std.m -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (std(df1), std(x1))) -***** assert (isequal (std(df1, 0, 1), std(x1))) -***** assert (isequal (std(df1, 0, 2), std(x1, 0, 2))) -***** assert (isequal (std(df1, 1), std(x1, 1))) -***** assert (isequal (std(df1, 1, 1), std(x1, 1))) -***** assert (isequal (std(df1, 1, 2), std(x1, 1, 2))) -6 tests, 6 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sinh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sinh.m +[inst/arrays/@stk_dataframe/stk_dataframe.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_dataframe.m +***** test stk_test_class ('stk_dataframe') +***** test % default constructor + x = stk_dataframe (); + assert (isa (x, 'stk_dataframe') && isequal (size (x), [0 0])) ***** test - u = rand (4, 3); x = stk_dataframe (u); v = sinh (x); - assert (strcmp (class (v), class (u)) && isequal (v, sinh (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/rdivide.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/rdivide.m -***** test stk_test_dfbinaryop(@rdivide, rand(7, 2), 1 + rand(7, 2)); -***** test stk_test_dfbinaryop(@rdivide, rand(7, 2), pi); -***** error stk_test_dfbinaryop(@rdivide, rand(7, 2), 1 + rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/expm1.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/expm1.m + y = stk_dataframe (rand (3, 2)); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) ***** test - u = rand (4, 3); x = stk_dataframe (u); v = expm1 (x); - assert (strcmp (class (v), class (u)) && isequal (v, expm1 (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/display.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/display.m -***** test display (stk_dataframe (rand (3, 2))); - - = <3x2 stk_dataframe array> - - : -------- -------- - * : 0.409226 0.863330 - * : 0.756815 0.940586 - * : 0.216319 0.239090 - -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/quantile.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/quantile.m -***** shared x1, df1, p - x1 = rand (9, 3); - df1 = stk_dataframe (x1, {'a', 'b', 'c'}); - p = 0.95; -***** assert (isequal (quantile (df1, p), quantile (x1, p))) -***** assert (isequal (quantile (df1, p, 1), quantile (x1, p))) -***** assert (isequal (quantile (df1, p, 2), quantile (x1, p, 2))) -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/tand.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/tand.m + y = stk_dataframe (rand (3, 2), {'x', 'y'}); + assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) + assert (isequal (y.colnames, {'x' 'y'})) ***** test - u = rand (4, 3); x = stk_dataframe (u); v = tand (x); - assert (strcmp (class (v), class (u)) && isequal (v, tand (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/acosh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acosh.m + y = stk_dataframe (rand (3, 2), {'x', 'y'}, {'a', 'b', 'c'}); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'})) ***** test - u = rand (4, 3); x = stk_dataframe (u); v = acosh (x); - assert (strcmp (class (v), class (u)) && isequal (v, acosh (u))) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/vertcat.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/vertcat.m -***** shared u, v - u = rand (3, 2); - v = rand (3, 2); + x = stk_dataframe (rand (3, 2)); + y = stk_dataframe (x); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) +***** error + x = stk_dataframe (rand (3, 2)); + y = stk_dataframe (x, pi); +***** error + x = stk_dataframe (rand (3, 2)); + y = stk_dataframe (x, {}, pi); ***** test - x = stk_dataframe (u); - y = stk_dataframe (v); - z = vertcat (x, y); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); -***** test % the same, with row names this time - x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); - y = stk_dataframe (v, {}, {'d'; 'e'; 'f'}); - z = vertcat (x, y); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); - assert (all (strcmp (z.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'}))); -***** test % the same, with row names only for the first argument - x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); - y = stk_dataframe (v); - z = vertcat (x, y); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); -***** test % incompatible variable names - u = rand (3, 1); x = stk_dataframe (u, {'x'}); - v = rand (3, 1); y = stk_dataframe (v, {'y'}); - z = vertcat (x, y); - assert (isequal (z.colnames, {})); -warning: Incompatible column names ! -The output of vertcat will have no column names. -warning: called from - vertcat at line 82 column 9 - __test__ at line 5 column 4 - test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 1286 column 31 - + x = stk_dataframe (rand (3, 2)); + y = stk_dataframe (x, {'x' 'y'}); + assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) + assert (isequal (y.colnames, {'x' 'y'})) ***** test - x = stk_dataframe (u); - z = vertcat (x, v); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); -***** test % the same, with row names for the first argument - x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); - z = vertcat (x, v); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); + x = stk_dataframe (rand (3, 2)); + y = stk_dataframe (x, {'x' 'y'}, {'a', 'b', 'c'}); + assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'})) ***** test - y = stk_dataframe (v); - z = vertcat (u, y); - assert (isa (z, 'stk_dataframe') && (isequal (double (z), [u; v]))); + x = stk_dataframe (rand (3, 2), {'x' 'y'}); + y = stk_dataframe (x, [], {'a', 'b', 'c'}); + assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'})) ***** test - x = stk_dataframe (u); - y = stk_dataframe (v); - z = vertcat (x, y, u, v); - assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v; u; v])); -***** shared x, y - x = stk_dataframe (rand (2, 3), {'a', 'b', 'c'}); - y = stk_dataframe (rand (3, 2), {'a', 'b'}); - y = horzcat (y, rand(3, 1)); % last column name is missing + x = stk_dataframe (rand (3, 2), {'x' 'y'}); + y = stk_dataframe (x, {}, {'a', 'b', 'c'}); + assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) + assert (isequal (y.colnames, {})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'})) ***** test - z = vertcat (x, y); - assert (isequal (z.colnames, {'a' 'b' 'c'})) + x = stk_factorialdesign ({1:3, 1:2}, {'x' 'y'}); + y = stk_dataframe (x, [], {'a' 'b' 'c' 'd' 'e' 'f'}); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) ***** test - z = vertcat (y, x); - assert (isequal (z.colnames, {'a' 'b' 'c'})) -10 tests, 10 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/var.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/var.m -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (var(df1), var(x1))) -***** assert (isequal (var(df1, 0, 1), var(x1))) -***** assert (isequal (var(df1, 0, 2), var(x1, 0, 2))) -***** assert (isequal (var(df1, 1), var(x1, 1))) -***** assert (isequal (var(df1, 1, 1), var(x1, 1))) -***** assert (isequal (var(df1, 1, 2), var(x1, 1, 2))) -6 tests, 6 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/median.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/median.m -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (median(df1), median(x1))) -***** assert (isequal (median(df1, 1), median(x1))) -***** assert (isequal (median(df1, 2), median(x1, 2))) -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/bsxfun.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/bsxfun.m -***** shared x1, x2, data1, data2 - x1 = rand (3, 2); data1 = stk_dataframe (x1); - x2 = rand (3, 2); data2 = stk_dataframe (x2); + x = stk_factorialdesign ({1:3, 1:2}, {}, {'a' 'b' 'c' 'd' 'e' 'f'}); + y = stk_dataframe (x, {'x' 'y'}); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) ***** test - z = bsxfun (@plus, data1, x2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) + x = stk_factorialdesign ({1:3, 1:2}, {}, {'a' 'b' 'c' 'd' 'e' 'f'}); + y = stk_dataframe (x, {'x' 'y'}, []); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) ***** test - z = bsxfun (@plus, x1, data2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) + x = stk_factorialdesign ({1:3, 1:2}, {'x' 'y'}, {'a' 'b' 'c' 'd' 'e' 'f'}); + y = stk_dataframe (x); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) + assert (isequal (y.colnames, {'x' 'y'})) + assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) +***** error + x = stk_factorialdesign ({1:3, 1:2}); + y = stk_dataframe (x, pi); +***** error + x = stk_factorialdesign ({1:3, 1:2}); + y = stk_dataframe (x, {}, pi); ***** test - z = bsxfun (@plus, data1, data2); - assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) -***** shared x, y - x = stk_dataframe (randn (2), {'x1', 'x2'}, {'a'; 'b'}); - y = stk_dataframe (randn (2), {'y1', 'y2'}, {'c'; 'd'}); -***** test z = x + y; - assert (isequal (z.colnames, x.colnames)); - assert (isequal (z.rownames, x.rownames)); -***** test z = y + x; - assert (isequal (z.colnames, y.colnames)); - assert (isequal (z.rownames, y.rownames)); -5 tests, 5 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/cat.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cat.m -***** shared u, v, x, y - u = rand(3, 2); - v = rand(3, 2); - x = stk_dataframe(u); - y = stk_dataframe(v); -***** test % vertical - z = cat(1, x, y); - assert(isa(z, 'stk_dataframe')); - assert(isequal(double(z), [u; v])); -***** error z = cat(3, x, y); -***** test % horizontal - y = stk_dataframe(v, {'y1' 'y2'}); - z = cat(2, x, y); - assert(isa(z, 'stk_dataframe')); - assert(isequal(double(z), [u v])); - assert(all(strcmp(z.colnames, {'' '' 'y1' 'y2'}))); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/subsref.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/subsref.m -***** shared x, s, t, data - x = stk_dataframe(rand(3, 2)); - s = {'a'; 'b'; 'c'}; - t = {'xx' 'yy'}; + x = stk_dataframe ([], {'a', 'b'}); + assert (isequal (size (x), [0 2])) + assert (isequal (x.colnames, {'a' 'b'})); + assert (isequal (x.rownames, {})); ***** test - x = set(x, 'rownames', s); - assert (isequal (x.rownames, s)) - assert (isequal (x.rownames{2}, 'b')) + x = stk_dataframe ([], {'a', 'b'}, {'toto'}); + assert (isequal (size (x), [1 2])) + assert (isequal (x.colnames, {'a' 'b'})); + assert (isequal (x.rownames, {'toto'})); +***** shared x ***** test - x = set(x, 'colnames', t); - assert (isequal (x.rownames, s)) - assert (isequal (x.colnames, t)) - assert (isequal (x.colnames{2}, 'yy')) -***** shared u, data - u = rand(3, 2); - data = stk_dataframe(u, {'x1', 'x2'}); -***** assert (isequal (data.x2, u(:, 2))) -***** assert (data.x2(3) == u(3, 2)) -***** error t = data.toto; -***** error t = data(1, 1).zzz; % illegal multilevel indexing -***** error t = data(1, 1, 1); % too many indices -***** error t = data{1}; % curly braces not allowed -***** test % select rows and columns - x = stk_dataframe (reshape (1:15, 5, 3), {'u' 'v' 'w'}); - assert (isequal (x([3 5], 2), stk_dataframe ([8; 10], {'v'}))); -***** shared u, data - u = rand(3, 1); data = stk_dataframe(u, {'x'}); -***** assert (isequal (data.x, u)) -***** assert (isequal (double (data), u)) -***** assert (isequal (double (data(2)), u(2))) -***** assert (isequal (double (data(3, 1)), u(3))) -***** error t = data(1, 1, 1); % too many indices + x = stk_dataframe (randn (10, 1), 'NOx'); + assert (isequal (x.colnames, {'NOx'})); ***** test - x = stk_dataframe (randn (2, 2), {'u' 'v'}); - y = x ([], :); - assert (isa (y, 'stk_dataframe')); - assert (isequal (size (y), [0 2])); - assert (isequal (y.colnames, {'u' 'v'})); + y = stk_dataframe (x, 'toto'); + assert (isequal (y.colnames, {'toto'})); ***** test - x = stk_dataframe (randn (2, 2), [], {'a' 'b'}); - y = x (:, []); - assert (isa (y, 'stk_dataframe')); - assert (isequal (size (y), [2 0])); - assert (isequal (y.rownames, {'a'; 'b'})); -16 tests, 16 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/min.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/min.m -***** test stk_test_dfbinaryop ('min', rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop ('min', rand(7, 2), pi); -***** error stk_test_dfbinaryop ('min', rand(7, 2), rand(7, 3)); -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (min(df1), min(x1))) -***** assert (isequal (min(df1, [], 1), min(x1))) -***** assert (isequal (min(df1, [], 2), min(x1, [], 2))) -***** error (min(df1, df1, 2)) + x = stk_dataframe (randn (1, 2), {}, 'aaa'); + assert (isequal (x.rownames, {'aaa'})); ***** test - x = stk_dataframe ([5; 2; 4]); - [M, k] = min (x); - assert ((M == 2) && (k == 2)); -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/reshape.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/reshape.m + y = stk_dataframe (x, {}, 'tata'); + assert (isequal (y.rownames, {'tata'})); +24 tests, 24 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/asinh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asinh.m ***** test - x = stk_dataframe (randn (10, 3)); - y = reshape (x, 5, 6); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [5 6])) + u = rand (4, 3); x = stk_dataframe (u); v = asinh (x); + assert (strcmp (class (v), class (u)) && isequal (v, asinh (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/tanh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/tanh.m +[inst/arrays/@stk_dataframe/atand.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/atand.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = tanh (x); - assert (strcmp (class (v), class (u)) && isequal (v, tanh (u))) + u = rand (4, 3); x = stk_dataframe (u); v = atand (x); + assert (strcmp (class (v), class (u)) && isequal (v, atand (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/asin.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asin.m +[inst/arrays/@stk_dataframe/abs.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/abs.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = asin (x); - assert (strcmp (class (v), class (u)) && isequal (v, asin (u))) + u = rand (4, 3); x = stk_dataframe (u); v = abs (x); + assert (strcmp (class (v), class (u)) && isequal (v, abs (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sort.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sort.m -***** shared x, y - x = stk_dataframe ([3; 2; 1], {}, {'a', 'b', 'c'}); - y = sort (x); -***** assert (strcmp (class (y), 'stk_dataframe')) -***** assert (isequal (y.data, [1; 2; 3])) -***** assert (isequal (y.rownames, {'c'; 'b'; 'a'})) -***** error y = sort (x, []); -***** assert (isequal (sort (x, 1), y)) -***** assert (isequal (sort (x, 2), x)) -***** error sort (x, 3) -***** error y = sort (x, [], 'ascend'); -***** assert (isequal (sort (x, 1, 'ascend'), y)) -***** assert (isequal (sort (x, 2, 'ascend'), x)) -***** error y = sort (x, 3, 'ascend'); -***** error y = sort (x, [], 'descend'); -***** assert (isequal (sort (x, 1, 'descend'), x)) -***** assert (isequal (sort (x, 2, 'descend'), x)) -***** error sort (x, 3, 'descend') -15 tests, 15 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/mode.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mode.m -***** shared x1, df1 - x1 = floor(3 * rand(9, 3)); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (mode(df1), mode(x1))) -***** assert (isequal (mode(df1, 1), mode(x1))) -***** assert (isequal (mode(df1, 2), mode(x1, 2))) -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/stk_boundingbox.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_boundingbox.m -***** shared x, y, cn - cn = {'a', 'b', 'c'}; - x = stk_dataframe ([0 3 2; 1 4 1; 7 0 2], cn); -***** error y = stk_boundingbox (); -***** test y = stk_boundingbox (x); -***** assert (isequal (y, stk_hrect ([0 0 1; 7 4 2], cn))); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/end.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/end.m -***** shared x - x = stk_dataframe ([1; 2; 3]); -***** assert (isequal (double (x(2:end, :)), [2; 3])) -***** assert (isequal (double (x(2:end)), [2; 3])) -***** assert (isequal (double (x(2, 1:end)), 2)) -***** assert (isequal (double (x(end)), 3)) -***** shared x - x = stk_dataframe ([1 2; 3 4; 5 6]); -***** assert (isequal (x(2:end, :), x(2:3, :))) -***** assert (isequal (x(2, 1:end), x(2, :))) -***** assert (isequal (x(2:end, 2:end), x(2:3, 2))) -***** error x(1:end, 1:end, 1:end) -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/mldivide.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mldivide.m -***** test - x1_data = [57 7; 2 0]; - x1 = stk_dataframe (x1_data, {'x' 'y'}, {'a'; 'b'}); - x2_data = [8 7; 2 0]; - x2 = stk_dataframe (x2_data, {'w' 'z'}, {'a'; 'b'}); - y = x2 \ x1; - assert (stk_isequal_tolabs (y, ... - stk_dataframe ([1 0; 7 1], {'x'; 'y'}, {'w'; 'z'}))); -***** shared x_data, x, y_data, y - x_data = [3 3; 6 3; 9 12]; - y_data = [1 1; 2 1; 3 4]; - x = stk_dataframe (x_data, {'x' 'y'}, {'a'; 'b'; 'c'}); -***** test y = 3 \ x; -***** assert (isequal (y, stk_dataframe (y_data, {'x' 'y'}, {'a'; 'b'; 'c'}))); -***** error y = x \ 3; -4 tests, 4 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/subsasgn.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/subsasgn.m ***** shared x, s, t, data @@ -10246,141 +9510,130 @@ ***** assert (isequal (prod(df1, 1), prod(x1))) ***** assert (isequal (prod(df1, 2), prod(x1, 2))) 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/stk_dataframe.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_dataframe.m -***** test stk_test_class ('stk_dataframe') -***** test % default constructor - x = stk_dataframe (); - assert (isa (x, 'stk_dataframe') && isequal (size (x), [0 0])) -***** test - y = stk_dataframe (rand (3, 2)); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) -***** test - y = stk_dataframe (rand (3, 2), {'x', 'y'}); - assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) - assert (isequal (y.colnames, {'x' 'y'})) -***** test - y = stk_dataframe (rand (3, 2), {'x', 'y'}, {'a', 'b', 'c'}); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'})) -***** test - x = stk_dataframe (rand (3, 2)); - y = stk_dataframe (x); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [3 2])) -***** error - x = stk_dataframe (rand (3, 2)); - y = stk_dataframe (x, pi); -***** error - x = stk_dataframe (rand (3, 2)); - y = stk_dataframe (x, {}, pi); -***** test - x = stk_dataframe (rand (3, 2)); - y = stk_dataframe (x, {'x' 'y'}); - assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) - assert (isequal (y.colnames, {'x' 'y'})) +[inst/arrays/@stk_dataframe/asin.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asin.m ***** test + u = rand (4, 3); x = stk_dataframe (u); v = asin (x); + assert (strcmp (class (v), class (u)) && isequal (v, asin (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/disp.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/disp.m +***** shared x, fmt + fmt = stk_disp_getformat (); x = stk_dataframe (rand (3, 2)); - y = stk_dataframe (x, {'x' 'y'}, {'a', 'b', 'c'}); - assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'})) -***** test - x = stk_dataframe (rand (3, 2), {'x' 'y'}); - y = stk_dataframe (x, [], {'a', 'b', 'c'}); - assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'})) -***** test - x = stk_dataframe (rand (3, 2), {'x' 'y'}); - y = stk_dataframe (x, {}, {'a', 'b', 'c'}); - assert (isa (y, 'stk_dataframe') && isequal (size(y), [3 2])) - assert (isequal (y.colnames, {})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'})) -***** test - x = stk_factorialdesign ({1:3, 1:2}, {'x' 'y'}); - y = stk_dataframe (x, [], {'a' 'b' 'c' 'd' 'e' 'f'}); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) -***** test - x = stk_factorialdesign ({1:3, 1:2}, {}, {'a' 'b' 'c' 'd' 'e' 'f'}); - y = stk_dataframe (x, {'x' 'y'}); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) -***** test - x = stk_factorialdesign ({1:3, 1:2}, {}, {'a' 'b' 'c' 'd' 'e' 'f'}); - y = stk_dataframe (x, {'x' 'y'}, []); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) -***** test - x = stk_factorialdesign ({1:3, 1:2}, {'x' 'y'}, {'a' 'b' 'c' 'd' 'e' 'f'}); - y = stk_dataframe (x); - assert (isa (y, 'stk_dataframe') && isequal (size (y), [6 2])) - assert (isequal (y.colnames, {'x' 'y'})) - assert (isequal (y.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'})) -***** error - x = stk_factorialdesign ({1:3, 1:2}); - y = stk_dataframe (x, pi); -***** error - x = stk_factorialdesign ({1:3, 1:2}); - y = stk_dataframe (x, {}, pi); -***** test - x = stk_dataframe ([], {'a', 'b'}); - assert (isequal (size (x), [0 2])) - assert (isequal (x.colnames, {'a' 'b'})); - assert (isequal (x.rownames, {})); -***** test - x = stk_dataframe ([], {'a', 'b'}, {'toto'}); - assert (isequal (size (x), [1 2])) - assert (isequal (x.colnames, {'a' 'b'})); - assert (isequal (x.rownames, {'toto'})); -***** shared x -***** test - x = stk_dataframe (randn (10, 1), 'NOx'); - assert (isequal (x.colnames, {'NOx'})); +***** test format rat; disp (x); + : -------- -------- + * : 0.075568 0.135596 + * : 0.272842 0.666484 + * : 0.283186 0.698037 +***** test format long; disp (x); + : ---------------- ---------------- + * : 0.07556796334453 0.13559633914863 + * : 0.27284247197258 0.66648437813054 + * : 0.28318579456055 0.69803719965338 +***** test format short; disp (x); format (fmt); + : -------- -------- + * : 0.075568 0.135596 + * : 0.272842 0.666484 + * : 0.283186 0.698037 +***** test disp (stk_dataframe (zeros (0, 1))) + Empty data frame with 0 rows and 0 columns +***** test disp (stk_dataframe (zeros (0, 2))) + Empty data frame with 0 rows and 0 columns +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/tand.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/tand.m ***** test - y = stk_dataframe (x, 'toto'); - assert (isequal (y.colnames, {'toto'})); + u = rand (4, 3); x = stk_dataframe (u); v = tand (x); + assert (strcmp (class (v), class (u)) && isequal (v, tand (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/mean.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mean.m +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (mean(df1), mean(x1))) +***** assert (isequal (mean(df1, 1), mean(x1))) +***** assert (isequal (mean(df1, 2), mean(x1, 2))) +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/mldivide.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mldivide.m ***** test - x = stk_dataframe (randn (1, 2), {}, 'aaa'); - assert (isequal (x.rownames, {'aaa'})); + x1_data = [57 7; 2 0]; + x1 = stk_dataframe (x1_data, {'x' 'y'}, {'a'; 'b'}); + x2_data = [8 7; 2 0]; + x2 = stk_dataframe (x2_data, {'w' 'z'}, {'a'; 'b'}); + y = x2 \ x1; + assert (stk_isequal_tolabs (y, ... + stk_dataframe ([1 0; 7 1], {'x'; 'y'}, {'w'; 'z'}))); +***** shared x_data, x, y_data, y + x_data = [3 3; 6 3; 9 12]; + y_data = [1 1; 2 1; 3 4]; + x = stk_dataframe (x_data, {'x' 'y'}, {'a'; 'b'; 'c'}); +***** test y = 3 \ x; +***** assert (isequal (y, stk_dataframe (y_data, {'x' 'y'}, {'a'; 'b'; 'c'}))); +***** error y = x \ 3; +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/unique.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/unique.m +***** test + cn = {'u' 'v' 'w'}; x = stk_dataframe (rand (4, 3), cn); + y = [x; x]; z = unique (y, 'rows'); + assert (isequal (z.colnames, cn)); + assert (isequal (z.data, unique (x.data, 'rows'))); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/min.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/min.m +***** test stk_test_dfbinaryop ('min', rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop ('min', rand(7, 2), pi); +***** error stk_test_dfbinaryop ('min', rand(7, 2), rand(7, 3)); +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (min(df1), min(x1))) +***** assert (isequal (min(df1, [], 1), min(x1))) +***** assert (isequal (min(df1, [], 2), min(x1, [], 2))) +***** error (min(df1, df1, 2)) ***** test - y = stk_dataframe (x, {}, 'tata'); - assert (isequal (y.rownames, {'tata'})); -24 tests, 24 passed, 0 known failure, 0 skipped + x = stk_dataframe ([5; 2; 4]); + [M, k] = min (x); + assert ((M == 2) && (k == 2)); +8 tests, 8 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/log1p.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log1p.m ***** test u = rand (4, 3); x = stk_dataframe (u); v = log1p (x); assert (strcmp (class (v), class (u)) && isequal (v, log1p (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/isnan.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isnan.m +[inst/arrays/@stk_dataframe/exp.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/exp.m ***** test - u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isnan (x); - assert (islogical (v) && isequal (v, isnan (u))) + u = rand (4, 3); x = stk_dataframe (u); v = exp (x); + assert (strcmp (class (v), class (u)) && isequal (v, exp (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/ldivide.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/ldivide.m -***** test stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), pi); -***** error stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/power.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/power.m -***** test stk_test_dfbinaryop(@power, rand(7, 2), .1 + rand(7, 2)); -***** test stk_test_dfbinaryop(@power, rand(7, 2), .1); -***** error stk_test_dfbinaryop(@power, rand(7, 2), .1 + rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sqrt.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sqrt.m +[inst/arrays/@stk_dataframe/log.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = sqrt (x); - assert (strcmp (class (v), class (u)) && isequal (v, sqrt (u))) + u = rand (4, 3); x = stk_dataframe (u); v = log (x); + assert (strcmp (class (v), class (u)) && isequal (v, log (u))) 1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/max.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/max.m +***** test stk_test_dfbinaryop ('max', rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop ('max', rand(7, 2), pi); +***** error stk_test_dfbinaryop ('max', rand(7, 2), rand(7, 3)); +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (max(df1), max(x1))) +***** assert (isequal (max(df1, [], 1), max(x1))) +***** assert (isequal (max(df1, [], 2), max(x1, [], 2))) +***** error (max(df1, df1, 2)) +***** test + x = stk_dataframe ([1; 3; 2]); + [M, k] = max (x); + assert ((M == 3) && (k == 2)); +8 tests, 8 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/fieldnames.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/fieldnames.m ***** test @@ -10395,6 +9648,52 @@ {'toto'; 'aa'; 'bb'; 'data'; 'info'; ... 'rownames'; 'colnames'; 'sample_size'})); 2 tests, 2 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/transpose.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/transpose.m +***** test + u = rand(3, 2) + 1i * rand(3, 2); + data = stk_dataframe(u, {'x' 'y'}, {'obs1'; 'obs2'; 'obs3'}); + data = data.'; + assert (isa(data, 'stk_dataframe') && isequal(double(data), u.')); + assert (isequal(data.rownames, {'x'; 'y'})); + assert (isequal(data.colnames, {'obs1' 'obs2' 'obs3'})); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/plus.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/plus.m +***** test stk_test_dfbinaryop(@plus, rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop(@plus, rand(7, 2), pi); +***** error stk_test_dfbinaryop(@plus, rand(7, 2), rand(7, 3)); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/cosd.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cosd.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = cosd (x); + assert (strcmp (class (v), class (u)) && isequal (v, cosd (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/rdivide.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/rdivide.m +***** test stk_test_dfbinaryop(@rdivide, rand(7, 2), 1 + rand(7, 2)); +***** test stk_test_dfbinaryop(@rdivide, rand(7, 2), pi); +***** error stk_test_dfbinaryop(@rdivide, rand(7, 2), 1 + rand(7, 3)); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/display.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/display.m +***** test display (stk_dataframe (rand (3, 2))); + + = <3x2 stk_dataframe array> + + : -------- -------- + * : 0.069938 0.071536 + * : 0.605015 0.360658 + * : 0.963713 0.684781 + +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/acos.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acos.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = acos (x); + assert (strcmp (class (v), class (u)) && isequal (v, acos (u))) +1 test, 1 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/ctranspose.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/ctranspose.m ***** test @@ -10405,33 +9704,169 @@ assert (isequal(data.rownames, {'x'; 'y'})); assert (isequal(data.colnames, {'obs1' 'obs2' 'obs3'})); 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/sum.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sum.m +[inst/arrays/@stk_dataframe/std.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/std.m ***** shared x1, df1 x1 = rand(9, 3); df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (sum(df1), sum(x1))) -***** assert (isequal (sum(df1, 1), sum(x1))) -***** assert (isequal (sum(df1, 2), sum(x1, 2))) +***** assert (isequal (std(df1), std(x1))) +***** assert (isequal (std(df1, 0, 1), std(x1))) +***** assert (isequal (std(df1, 0, 2), std(x1, 0, 2))) +***** assert (isequal (std(df1, 1), std(x1, 1))) +***** assert (isequal (std(df1, 1, 1), std(x1, 1))) +***** assert (isequal (std(df1, 1, 2), std(x1, 1, 2))) +6 tests, 6 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/power.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/power.m +***** test stk_test_dfbinaryop(@power, rand(7, 2), .1 + rand(7, 2)); +***** test stk_test_dfbinaryop(@power, rand(7, 2), .1); +***** error stk_test_dfbinaryop(@power, rand(7, 2), .1 + rand(7, 3)); 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/mrdivide.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mrdivide.m +[inst/arrays/@stk_dataframe/sinh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sinh.m ***** test - x1_data = [8 7; 58 49]; - x1 = stk_dataframe (x1_data, {'x' 'y'}, {'a'; 'b'}); - x2_data = [8 7; 2 0]; - x2 = stk_dataframe (x2_data, {'x' 'y'}, {'u'; 'v'}); - y = x1 / x2; - assert (stk_isequal_tolabs (y, ... - stk_dataframe ([1 0; 7 1], {'u'; 'v'}, {'a'; 'b'}))); -***** shared x_data, x, y_data, y - x_data = [3 3; 6 3; 9 12]; - y_data = [1 1; 2 1; 3 4]; - x = stk_dataframe (x_data, {'x' 'y'}, {'a'; 'b'; 'c'}); -***** test y = x / 3; -***** assert (isequal (y, stk_dataframe ([1 1; 2 1; 3 4], {'x' 'y'}, {'a'; 'b'; 'c'}))); -***** error y = 3 / x; -4 tests, 4 passed, 0 known failure, 0 skipped + u = rand (4, 3); x = stk_dataframe (u); v = sinh (x); + assert (strcmp (class (v), class (u)) && isequal (v, sinh (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/sin.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sin.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = sin (x); + assert (strcmp (class (v), class (u)) && isequal (v, sin (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/isinf.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isinf.m +***** test + u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isinf (x); + assert (islogical (v) && isequal (v, isinf (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/vertcat.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/vertcat.m +***** shared u, v + u = rand (3, 2); + v = rand (3, 2); +***** test + x = stk_dataframe (u); + y = stk_dataframe (v); + z = vertcat (x, y); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); +***** test % the same, with row names this time + x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); + y = stk_dataframe (v, {}, {'d'; 'e'; 'f'}); + z = vertcat (x, y); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); + assert (all (strcmp (z.rownames, {'a'; 'b'; 'c'; 'd'; 'e'; 'f'}))); +***** test % the same, with row names only for the first argument + x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); + y = stk_dataframe (v); + z = vertcat (x, y); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); +***** test % incompatible variable names + u = rand (3, 1); x = stk_dataframe (u, {'x'}); + v = rand (3, 1); y = stk_dataframe (v, {'y'}); + z = vertcat (x, y); + assert (isequal (z.colnames, {})); +warning: Incompatible column names ! +The output of vertcat will have no column names. +warning: called from + vertcat at line 82 column 9 + __test__ at line 5 column 4 + test at line 682 column 11 + /tmp/tmp.tlZGNdJ4JJ at line 1358 column 31 + +***** test + x = stk_dataframe (u); + z = vertcat (x, v); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); +***** test % the same, with row names for the first argument + x = stk_dataframe (u, {}, {'a'; 'b'; 'c'}); + z = vertcat (x, v); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v])); +***** test + y = stk_dataframe (v); + z = vertcat (u, y); + assert (isa (z, 'stk_dataframe') && (isequal (double (z), [u; v]))); +***** test + x = stk_dataframe (u); + y = stk_dataframe (v); + z = vertcat (x, y, u, v); + assert (isa (z, 'stk_dataframe') && isequal (double (z), [u; v; u; v])); +***** shared x, y + x = stk_dataframe (rand (2, 3), {'a', 'b', 'c'}); + y = stk_dataframe (rand (3, 2), {'a', 'b'}); + y = horzcat (y, rand(3, 1)); % last column name is missing +***** test + z = vertcat (x, y); + assert (isequal (z.colnames, {'a' 'b' 'c'})) +***** test + z = vertcat (y, x); + assert (isequal (z.colnames, {'a' 'b' 'c'})) +10 tests, 10 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/quantile.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/quantile.m +***** shared x1, df1, p + x1 = rand (9, 3); + df1 = stk_dataframe (x1, {'a', 'b', 'c'}); + p = 0.95; +***** assert (isequal (quantile (df1, p), quantile (x1, p))) +***** assert (isequal (quantile (df1, p, 1), quantile (x1, p))) +***** assert (isequal (quantile (df1, p, 2), quantile (x1, p, 2))) +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/double.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/double.m +***** test + u = rand(4, 3); + x = stk_dataframe(u); + v = double(x); + assert (strcmp(class(v), 'double') && isequal(v, u)) +***** test + u = (rand(4, 3) < 0.5); + x = stk_dataframe(u); + v = double(x); + assert (strcmp(class(v), 'double') && isequal(v, double(u))) +***** test + u = uint8 (rand (4, 3) * 5); + x = stk_dataframe(u); + v = double(x); + assert (strcmp(class(v), 'double') && isequal(v, double(u))) +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/tanh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/tanh.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = tanh (x); + assert (strcmp (class (v), class (u)) && isequal (v, tanh (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/stk_sprintf.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_sprintf.m +***** shared x, fmt + fmt = stk_disp_getformat (); + x = stk_dataframe (rand (3, 2)); +***** test format rat; disp (x); + : -------- -------- + * : 0.035360 0.637567 + * : 0.088107 0.929757 + * : 0.136312 0.580236 +***** test format long; disp (x); + : ---------------- ---------------- + * : 0.03536015780978 0.63756695136017 + * : 0.08810717206796 0.92975674487966 + * : 0.13631204268174 0.58023625032879 +***** test format short; disp (x); format (fmt); + : -------- -------- + * : 0.035360 0.637567 + * : 0.088107 0.929757 + * : 0.136312 0.580236 +***** test disp (stk_dataframe (zeros (0, 1))) + Empty data frame with 0 rows and 0 columns +***** test disp (stk_dataframe (zeros (0, 2))) + Empty data frame with 0 rows and 0 columns +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/realpow.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/realpow.m +***** test stk_test_dfbinaryop(@realpow, rand(7, 2), .1 + rand(7, 2)); +***** test stk_test_dfbinaryop(@realpow, rand(7, 2), .1); +***** error stk_test_dfbinaryop(@realpow, rand(7, 2), .1 + rand(7, 3)); +3 tests, 3 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/mtimes.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mtimes.m ***** shared x, y, z, w @@ -10454,46 +9889,77 @@ ***** test y = x * 3; ***** assert (isequal (y, stk_dataframe (3 * x.data, {'x' 'y'}, {'a'; 'b'; 'c'}))); 8 tests, 8 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/minus.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/minus.m -***** test stk_test_dfbinaryop(@minus, rand(7, 2), rand(7, 2)); -***** test stk_test_dfbinaryop(@minus, rand(7, 2), pi); -***** error stk_test_dfbinaryop(@minus, rand(7, 2), rand(7, 3)); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/abs.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/abs.m +[inst/arrays/@stk_dataframe/log10.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log10.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = abs (x); - assert (strcmp (class (v), class (u)) && isequal (v, abs (u))) + u = rand (4, 3); x = stk_dataframe (u); v = log10 (x); + assert (strcmp (class (v), class (u)) && isequal (v, log10 (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/transpose.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/transpose.m +[inst/arrays/@stk_dataframe/acosd.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acosd.m ***** test - u = rand(3, 2) + 1i * rand(3, 2); - data = stk_dataframe(u, {'x' 'y'}, {'obs1'; 'obs2'; 'obs3'}); - data = data.'; - assert (isa(data, 'stk_dataframe') && isequal(double(data), u.')); - assert (isequal(data.rownames, {'x'; 'y'})); - assert (isequal(data.colnames, {'obs1' 'obs2' 'obs3'})); + u = rand (4, 3); x = stk_dataframe (u); v = acosd (x); + assert (strcmp (class (v), class (u)) && isequal (v, acosd (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/double.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/double.m +[inst/arrays/@stk_dataframe/mode.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mode.m +***** shared x1, df1 + x1 = floor(3 * rand(9, 3)); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (mode(df1), mode(x1))) +***** assert (isequal (mode(df1, 1), mode(x1))) +***** assert (isequal (mode(df1, 2), mode(x1, 2))) +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/isfinite.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/isfinite.m ***** test - u = rand(4, 3); - x = stk_dataframe(u); - v = double(x); - assert (strcmp(class(v), 'double') && isequal(v, u)) + u = [pi, NaN, Inf, -Inf]; x = stk_dataframe (u); v = isfinite (x); + assert (islogical (v) && isequal (v, isfinite (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/logical.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/logical.m ***** test - u = (rand(4, 3) < 0.5); - x = stk_dataframe(u); - v = double(x); - assert (strcmp(class(v), 'double') && isequal(v, double(u))) + u = rand (4, 3); + x = stk_dataframe (u); + v = logical (x); + assert (strcmp (class(v), 'logical') && isequal (v, logical (u))) +***** test + u = (rand (4, 3) < 0.5); + x = stk_dataframe (u); + v = logical (x); + assert (strcmp (class (v), 'logical') && isequal (v, u)) ***** test u = uint8 (rand (4, 3) * 5); - x = stk_dataframe(u); - v = double(x); - assert (strcmp(class(v), 'double') && isequal(v, double(u))) + x = stk_dataframe (u); + v = logical (x); + assert (strcmp (class (v), 'logical') && isequal (v, logical (u))) 3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/expm1.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/expm1.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = expm1 (x); + assert (strcmp (class (v), class (u)) && isequal (v, expm1 (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/ismember.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/ismember.m +***** shared u, x, u1, x1, u2, x2 + u = rand (10, 4); + x = stk_dataframe (u); + x1 = x(1, :); + u1 = double (x1); + u2 = - ones (1, 4); + x2 = stk_dataframe (u2); +***** assert (ismember (u1, x, 'rows')) +***** assert (ismember (x1, u, 'rows')) +***** assert (ismember (x1, x, 'rows')) +***** assert (~ ismember (u2, x, 'rows')) +***** assert (~ ismember (x2, u, 'rows')) +***** assert (~ ismember (x2, x, 'rows')) +***** test + [b, idx] = ismember ([x2; x1; x1], x, 'rows'); + assert (isequal (b, [false; true; true])); + assert (isequal (idx, [0; 1; 1])) +7 tests, 7 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/stk_normalize.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_normalize.m ***** test @@ -10503,12 +9969,119 @@ assert (isa (y, 'stk_dataframe') ... && stk_isequal_tolabs (double (y), stk_normalize (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/cosh.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cosh.m +[inst/arrays/@stk_dataframe/ldivide.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/ldivide.m +***** test stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), pi); +***** error stk_test_dfbinaryop(@ldivide, 1 + rand(7, 2), rand(7, 3)); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/atanh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/atanh.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = cosh (x); - assert (strcmp (class (v), class (u)) && isequal (v, cosh (u))) + u = rand (4, 3); x = stk_dataframe (u); v = atanh (x); + assert (strcmp (class (v), class (u)) && isequal (v, atanh (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/sind.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sind.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = sind (x); + assert (strcmp (class (v), class (u)) && isequal (v, sind (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/cos.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cos.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = cos (x); + assert (strcmp (class (v), class (u)) && isequal (v, cos (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/median.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/median.m +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (median(df1), median(x1))) +***** assert (isequal (median(df1, 1), median(x1))) +***** assert (isequal (median(df1, 2), median(x1, 2))) +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/acosh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/acosh.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = acosh (x); + assert (strcmp (class (v), class (u)) && isequal (v, acosh (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/sort.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sort.m +***** shared x, y + x = stk_dataframe ([3; 2; 1], {}, {'a', 'b', 'c'}); + y = sort (x); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.data, [1; 2; 3])) +***** assert (isequal (y.rownames, {'c'; 'b'; 'a'})) +***** error y = sort (x, []); +***** assert (isequal (sort (x, 1), y)) +***** assert (isequal (sort (x, 2), x)) +***** error sort (x, 3) +***** error y = sort (x, [], 'ascend'); +***** assert (isequal (sort (x, 1, 'ascend'), y)) +***** assert (isequal (sort (x, 2, 'ascend'), x)) +***** error y = sort (x, 3, 'ascend'); +***** error y = sort (x, [], 'descend'); +***** assert (isequal (sort (x, 1, 'descend'), x)) +***** assert (isequal (sort (x, 2, 'descend'), x)) +***** error sort (x, 3, 'descend') +15 tests, 15 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/length.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/length.m +***** error length (stk_dataframe ([1 2; 3 4; 5 6])) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/sqrt.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sqrt.m +***** test + u = rand (4, 3); x = stk_dataframe (u); v = sqrt (x); + assert (strcmp (class (v), class (u)) && isequal (v, sqrt (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/stk_length.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_length.m +***** test + x = stk_dataframe ([1 2; 3 4; 5 6]); + assert (isequal (stk_length (x), 3)); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/reshape.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/reshape.m +***** test + x = stk_dataframe (randn (10, 3)); + y = reshape (x, 5, 6); + assert (isa (y, 'stk_dataframe') && isequal (size (y), [5 6])) 1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/apply.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/apply.m +***** shared x, t, u + t = rand (3, 2); + x = stk_dataframe (t); +***** test u = apply (x, 1, @sum); +***** assert (isequal (u, sum (t, 1))) +***** test u = apply (x, 2, @sum); +***** assert (isequal (u, sum (t, 2))) +***** error u = apply (x, 3, @sum); +***** test u = apply (x, 1, @min, []); +***** assert (isequal (u, min (t, [], 1))) +***** test u = apply (x, 2, @min, []); +***** assert (isequal (u, min (t, [], 2))) +***** error u = apply (x, 3, @min, []); +***** test + t = [1; 3; 2]; + x = stk_dataframe (t); + [M, k] = apply (x, 1, @max, []); + assert ((M == 3) && (k == 2)); +11 tests, 11 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/sum.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/sum.m +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (sum(df1), sum(x1))) +***** assert (isequal (sum(df1, 1), sum(x1))) +***** assert (isequal (sum(df1, 2), sum(x1, 2))) +3 tests, 3 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/horzcat.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/horzcat.m ***** shared u, v @@ -10545,7 +10118,7 @@ horzcat at line 73 column 9 __test__ at line 5 column 4 test at line 682 column 11 - /tmp/tmp.DKCbKSb4oo at line 1558 column 31 + /tmp/tmp.tlZGNdJ4JJ at line 1582 column 31 ***** test x = stk_dataframe (u); @@ -10561,12 +10134,76 @@ z = horzcat (x, y, u, v); assert(isa(z, 'stk_dataframe') && isequal(double(z), [u v u v])); 7 tests, 7 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/exp.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/exp.m +[inst/arrays/@stk_dataframe/end.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/end.m +***** shared x + x = stk_dataframe ([1; 2; 3]); +***** assert (isequal (double (x(2:end, :)), [2; 3])) +***** assert (isequal (double (x(2:end)), [2; 3])) +***** assert (isequal (double (x(2, 1:end)), 2)) +***** assert (isequal (double (x(end)), 3)) +***** shared x + x = stk_dataframe ([1 2; 3 4; 5 6]); +***** assert (isequal (x(2:end, :), x(2:3, :))) +***** assert (isequal (x(2, 1:end), x(2, :))) +***** assert (isequal (x(2:end, 2:end), x(2:3, 2))) +***** error x(1:end, 1:end, 1:end) +8 tests, 8 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/stk_boundingbox.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_boundingbox.m +***** shared x, y, cn + cn = {'a', 'b', 'c'}; + x = stk_dataframe ([0 3 2; 1 4 1; 7 0 2], cn); +***** error y = stk_boundingbox (); +***** test y = stk_boundingbox (x); +***** assert (isequal (y, stk_hrect ([0 0 1; 7 4 2], cn))); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/cosh.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cosh.m ***** test - u = rand (4, 3); x = stk_dataframe (u); v = exp (x); - assert (strcmp (class (v), class (u)) && isequal (v, exp (u))) + u = rand (4, 3); x = stk_dataframe (u); v = cosh (x); + assert (strcmp (class (v), class (u)) && isequal (v, cosh (u))) 1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/plot.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/plot.m +***** test % plot with x as a vector and z as a (univariate) dataframe + x = linspace(0, 2*pi, 30)'; + z = stk_dataframe(sin(x)); + figure; plot(x, z); close(gcf); +***** test % plot with x as a vector and z as a (multivariate) dataframe + x = linspace(0, 2*pi, 30)'; + z = stk_dataframe([sin(x) cos(x)], {'sin' 'cos'}); + figure; plot(x, z); close(gcf); +***** test % plot with x as a dataframe and z as a vector + x = stk_dataframe(linspace(0, 2*pi, 30)'); + z = sin(double(x)); + figure; plot(x, z); close(gcf); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/cat.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/cat.m +***** shared u, v, x, y + u = rand(3, 2); + v = rand(3, 2); + x = stk_dataframe(u); + y = stk_dataframe(v); +***** test % vertical + z = cat(1, x, y); + assert(isa(z, 'stk_dataframe')); + assert(isequal(double(z), [u; v])); +***** error z = cat(3, x, y); +***** test % horizontal + y = stk_dataframe(v, {'y1' 'y2'}); + z = cat(2, x, y); + assert(isa(z, 'stk_dataframe')); + assert(isequal(double(z), [u v])); + assert(all(strcmp(z.colnames, {'' '' 'y1' 'y2'}))); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/times.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/times.m +***** test stk_test_dfbinaryop(@times, rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop(@times, rand(7, 2), pi); +***** error stk_test_dfbinaryop(@times, rand(7, 2), rand(7, 3)); +3 tests, 3 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/stk_rescale.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/stk_rescale.m ***** test @@ -10575,1389 +10212,636 @@ y = stk_rescale(x, [0; 2], [0; 3]); assert (isa (y, 'stk_dataframe') && isequal(double(y), u * 3/2)) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/arrays/@stk_dataframe/mean.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/mean.m -***** shared x1, df1 - x1 = rand(9, 3); - df1 = stk_dataframe(x1, {'a', 'b', 'c'}); -***** assert (isequal (mean(df1), mean(x1))) -***** assert (isequal (mean(df1, 1), mean(x1))) -***** assert (isequal (mean(df1, 2), mean(x1, 2))) -3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/size.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/size.m +***** shared x + x = stk_dataframe([1 2; 3 4; 5 6]); +***** assert (isequal (size(x), [3 2])) +***** assert (numel(x) == 1) +***** assert (ndims(x) == 2) +***** test size(x); % force exploration of branch nargout == 0 +4 tests, 4 passed, 0 known failure, 0 skipped [inst/arrays/@stk_dataframe/atan.m] >>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/atan.m ***** test u = rand (4, 3); x = stk_dataframe (u); v = atan (x); assert (strcmp (class (v), class (u)) && isequal (v, atan (u))) 1 test, 1 passed, 0 known failure, 0 skipped -[inst/core/stk_model_update.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_model_update.m -***** test - x1 = (linspace (0, 1, 15))'; z1 = sin (x1); - x2 = (linspace (2, 3, 15))'; z2 = sin (x2); - xt = (linspace (1, 2, 15))'; zt = sin (xt); - - % Prior model - M0 = stk_model (@stk_materncov32_iso); - M0.param = log ([1.0; 2.1]); - - M1 = stk_model_update (M0, x1, z1); - M1 = stk_model_update (M1, x2, z2); % this calls @stk_model_gpposterior/... - zp1 = stk_predict (M1, xt); - - M2 = stk_model_gpposterior (M0, [x1; x2], [z1; z2]); - zp2 = stk_predict (M2, xt); - - assert (stk_isequal_tolabs (double (zp2 - zp1), zeros (15, 2), 1e-10)) -1 test, 1 passed, 0 known failure, 0 skipped -[inst/core/@stk_kreq_qr/stk_kreq_qr.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/@stk_kreq_qr/stk_kreq_qr.m -***** test stk_test_class ('stk_kreq_qr') -1 test, 1 passed, 0 known failure, 0 skipped -[inst/core/stk_make_matcov.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_make_matcov.m -***** shared model, model2, x0, x1, n0, n1, d, Ka, Kb, Kc, Pa, Pb, Pc - n0 = 20; n1 = 10; d = 4; - model = stk_model (@stk_materncov52_aniso, d); - model.lm = stk_lm_affine; - model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); - model2 = model; model2.lognoisevariance = log(0.01); - x0 = stk_sampling_randunif (n0, d); - x1 = stk_sampling_randunif (n1, d); -***** error [KK, PP] = stk_make_matcov (); -***** error [KK, PP] = stk_make_matcov (model); -***** test [Ka, Pa] = stk_make_matcov (model, x0); % (1) -***** test [Kb, Pb] = stk_make_matcov (model, x0, x0); % (2) -***** test [Kc, Pc] = stk_make_matcov (model, x0, x1); % (3) -***** error [KK, PP] = stk_make_matcov (model, x0, x1, pi); -***** assert (isequal (size (Ka), [n0 n0])); -***** assert (isequal (size (Kb), [n0 n0])); -***** assert (isequal (size (Kc), [n0 n1])); -***** assert (isequal (size (Pa), [n0 d + 1])); -***** assert (isequal (size (Pb), [n0 d + 1])); -***** assert (isequal (size (Pc), [n0 d + 1])); -***** assert (isequal (Kb, Ka)); -***** test [Ka, Pa] = stk_make_matcov (model2, x0); % (1') -***** test [Kb, Pb] = stk_make_matcov (model2, x0, x0); % (2') -***** error assert (isequal (Kb, Ka)); -***** assert (isequal (Pa, Pb)); -***** assert (isequal (Pa, Pc)); -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/core/stk_predict.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_predict.m -***** shared n, m, model, x0, x_obs, z_obs, x_prd, y_prd1, idx_obs, idx_prd - - n = 10; % number of observations - m = n + 1; % number of predictions - d = 1; % dimension of the input space - - x0 = stk_sampling_regulargrid(n+m, d, [0; pi]); - - idx_obs = (2:2:(n+m-1))'; - idx_prd = (1:2:(n+m))'; - - x_obs = x0(idx_obs); - z_obs = sin (double (x_obs)); - x_prd = x0(idx_prd); - - model = stk_model (@stk_materncov32_iso); - model.param = log ([1.0; 2.1]); -***** error y_prd1 = stk_predict (); -***** error y_prd1 = stk_predict (model); -***** test y_prd1 = stk_predict (model, x_prd); -***** error y_prd1 = stk_predict (model, data, x_prd); -***** test y_prd1 = stk_predict (model, x_obs, z_obs, x_prd); -***** error y_prd1 = stk_predict (model, [x_obs; x_obs], [z_obs; z_obs], x_prd); -***** test % nargout = 2 - [y_prd1, lambda] = stk_predict (model, x_obs, z_obs, x_prd); - assert (isequal (size (lambda), [n m])); -***** test % nargout = 2, compute only variances - [y_prd1, lambda] = stk_predict (model, x_obs, [], x_prd); - assert (isequal (size (lambda), [n m])); - assert (all (isnan (y_prd1.mean))); -***** test % nargout = 3 - [y_prd1, lambda, mu] = stk_predict (model, x_obs, z_obs, x_prd); - assert (isequal (size (lambda), [n m])); - assert (isequal (size (mu), [1 m])); % ordinary kriging -***** test % nargout = 4 - [y_prd1, lambda, mu, K] = stk_predict (model, x_obs, z_obs, x_prd); - assert (isequal (size (lambda), [n m])); - assert (isequal (size (mu), [1 m])); % ordinary kriging - assert (isequal (size (K), [m m])); -***** test % predict on large set of locations - x_prd = stk_sampling_regulargrid (1e5, 1, [0; pi]); - y_prd = stk_predict (model, x_obs, z_obs, x_prd); -***** test % predict on an observation point - % https://sourceforge.net/p/kriging/tickets/49/ - [zp, lambda] = stk_predict (model, x_obs, z_obs, x_obs(4)); - assert (isequal (z_obs(4), zp.mean)) - assert (isequal (zp.var, 0)) - lambda_ref = zeros (n, 1); lambda_ref(4) = 1; - assert (isequal (lambda, lambda_ref)) -12 tests, 12 passed, 0 known failure, 0 skipped -[inst/core/stk_cholcov.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_cholcov.m -***** shared Q, K, L, U, epsi - Q = 0.25 * hadamard(4); -***** test - K = Q * diag ([1, 0.1, 0.01, 1e-7]) * Q'; - [U, epsi] = stk_cholcov (K); -***** assert (istriu (U)) -***** assert (epsi == 0) -***** test - K = Q * diag ([1, 0.1, 0.01, 1e-7]) * Q'; - [L, epsi] = stk_cholcov (K, 'lower'); -***** assert (istril (L)) -***** assert (epsi == 0) -***** test - K = Q * diag ([1, 0.1, 0.01, -1e-7]) * Q'; - [U, epsi] = stk_cholcov (K); -***** assert (istriu (U)) -***** assert (epsi > 0) -***** test - K = Q * diag ([1, 0.1, 0.01, -1e-7]) * Q'; - [L, epsi] = stk_cholcov (K, 'lower'); -***** assert (istril (L)) -***** assert (epsi > 0) -12 tests, 12 passed, 0 known failure, 0 skipped -[inst/core/stk_predict_leaveoneout.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/core/stk_predict_leaveoneout.m -***** shared n, x_obs, z_obs, model - n = 20; - x_obs = stk_sampling_regulargrid (n, 1, [0; 2*pi]); - z_obs = stk_feval (@sin, x_obs); - model = stk_model (@stk_materncov32_iso); - model.param = log ([1; 5]); -***** test % one output - - loo_pred = stk_predict_leaveoneout (model, x_obs, z_obs); - - assert (isequal (size (loo_pred), [n 2])); - assert (isequal (loo_pred.colnames, {'mean', 'var'})); - assert (all (isfinite (loo_pred(:)))); -***** test % two outputs - - [loo_pred, loo_res] = stk_predict_leaveoneout (model, x_obs, z_obs); - - assert (isequal (size (loo_pred), [n 2])); - assert (isequal (loo_pred.colnames, {'mean', 'var'})); - assert (all (isfinite (loo_pred(:)))); - - assert (isequal (size (loo_res), [n 2])); - assert (isequal (loo_res.colnames, {'residuals', 'norm_res'})); - assert (all (isfinite (loo_res(:)))); -***** test % heteroscedastic noise case - - model.lognoisevariance = (1 + rand (n, 1)) * 1e-6; - [loo_pred, loo_res] = stk_predict_leaveoneout (model, x_obs, z_obs); - - assert (isequal (size (loo_pred), [n 2])); - assert (isequal (loo_pred.colnames, {'mean', 'var'})); - assert (all (isfinite (loo_pred(:)))); - - assert (isequal (size (loo_res), [n 2])); - assert (isequal (loo_res.colnames, {'residuals', 'norm_res'})); - assert (all (isfinite (loo_res(:)))); +[inst/arrays/@stk_dataframe/minus.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/minus.m +***** test stk_test_dfbinaryop(@minus, rand(7, 2), rand(7, 2)); +***** test stk_test_dfbinaryop(@minus, rand(7, 2), pi); +***** error stk_test_dfbinaryop(@minus, rand(7, 2), rand(7, 3)); 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/model/prior_struct/stk_ortho_func.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_ortho_func.m -***** shared model, x, n, d - n = 15; d = 4; - model = stk_model (@stk_materncov_aniso, d); - x = stk_sampling_randunif (n, d); - model = rmfield (model, 'lm'); % Test the old .order approach -***** error P = stk_ortho_func (); -***** error P = stk_ortho_func (model); -***** test P = stk_ortho_func (model, x); -***** test - model.order = -1; P = stk_ortho_func (model, x); - assert (isequal (size (P), [n, 0])); -***** test - model.order = 0; P = stk_ortho_func (model, x); - assert (isequal (size (P), [n, 1])); -***** test - model.order = 1; P = stk_ortho_func (model, x); - assert (isequal (size (P), [n, d + 1])); +[inst/arrays/@stk_dataframe/subsref.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/subsref.m +***** shared x, s, t, data + x = stk_dataframe(rand(3, 2)); + s = {'a'; 'b'; 'c'}; + t = {'xx' 'yy'}; ***** test - model.order = 2; P = stk_ortho_func (model, x); - assert (isequal (size (P), [n, 1 + d * (d + 3) / 2])); + x = set(x, 'rownames', s); + assert (isequal (x.rownames, s)) + assert (isequal (x.rownames{2}, 'b')) ***** test - model.order = 3; P = stk_ortho_func (model, x); - assert (isequal (size (P), [n, 1 + d * (11 + d * (6 + d)) / 6])); -***** error - model.order = 4; P = stk_ortho_func (model, x); - % model.order > 3 is not allowed -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/model/prior_struct/stk_model.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_model.m -***** test model = stk_model (); -***** test model = stk_model (@stk_expcov_iso); -***** test model = stk_model (@stk_expcov_iso, 1); -***** test model = stk_model (@stk_expcov_iso, 3); -***** test model = stk_model (@stk_expcov_aniso); -***** test model = stk_model (@stk_expcov_aniso, 1); -***** test model = stk_model (@stk_expcov_aniso, 3); -***** test model = stk_model (@stk_materncov_iso); -***** test model = stk_model (@stk_materncov_iso, 1); -***** test model = stk_model (@stk_materncov_iso, 3); -***** test model = stk_model (@stk_materncov_aniso); -***** test model = stk_model (@stk_materncov_aniso, 1); -***** test model = stk_model (@stk_materncov_aniso, 3); -***** test model = stk_model (@stk_materncov32_iso); -***** test model = stk_model (@stk_materncov32_iso, 1); -***** test model = stk_model (@stk_materncov32_iso, 3); -***** test model = stk_model (@stk_materncov32_aniso); -***** test model = stk_model (@stk_materncov32_aniso, 1); -***** test model = stk_model (@stk_materncov32_aniso, 3); -***** test model = stk_model (@stk_materncov52_iso); -***** test model = stk_model (@stk_materncov52_iso, 1); -***** test model = stk_model (@stk_materncov52_iso, 3); -***** test model = stk_model (@stk_materncov52_aniso); -***** test model = stk_model (@stk_materncov52_aniso, 1); -***** test model = stk_model (@stk_materncov52_aniso, 3); -***** test model = stk_model (@stk_gausscov_iso); -***** test model = stk_model (@stk_gausscov_iso, 1); -***** test model = stk_model (@stk_gausscov_iso, 3); -***** test model = stk_model (@stk_gausscov_aniso); -***** test model = stk_model (@stk_gausscov_aniso, 1); -***** test model = stk_model (@stk_gausscov_aniso, 3); -***** test model = stk_model (@stk_sphcov_iso); -***** test model = stk_model (@stk_sphcov_iso, 1); -***** test model = stk_model (@stk_sphcov_iso, 3); -***** test model = stk_model (@stk_sphcov_aniso); -***** test model = stk_model (@stk_sphcov_aniso, 1); -***** test model = stk_model (@stk_sphcov_aniso, 3); -37 tests, 37 passed, 0 known failure, 0 skipped -[inst/model/prior_struct/stk_covmat_noise.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/prior_struct/stk_covmat_noise.m -***** shared model, model2, x1, x2, n1, n2, d, Ka, Kb, Kc, Pa, Pb, Pc, P1, P2, P3, K1, K2, K3 - n1 = 20; n2 = 10; d = 4; - model = stk_model (@stk_materncov52_aniso, d); - model.lm = stk_lm_affine; - model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); - model2 = model; model2.lognoisevariance = log(0.01); - x1 = stk_sampling_randunif (n1, d); - x2 = stk_sampling_randunif (n2, d); -***** error [KK, PP] = stk_covmat_noise (); -***** error [KK, PP] = stk_covmat_noise (model); -***** test [Ka, Pa] = stk_covmat_noise (model, x1); % (1) -***** test [K1, P1] = stk_covmat_noise (model, x1, []); -***** test [K2, P2] = stk_covmat_noise (model, x1, [], -1); -***** test [K3, P3] = stk_covmat_noise (model, x1, [], -1, false); -***** assert (isequal (size (Ka), [n1 n1])); -***** assert (isequal (size (Pa), [n1 0])); -***** assert (isequal (P1, Pa) && (isequal (K1, Ka))) -***** assert (isequal (P2, Pa) && (isequal (K2, Ka))) -***** assert (isequal (P3, Pa) && (isequal (K3, Ka))) -***** test [Kb, Pb] = stk_covmat_noise (model, x1, x1); % (2) -***** test [K1, P1] = stk_covmat_noise (model, x1, x1, -1); -***** test [K2, P2] = stk_covmat_noise (model, x1, x1, -1, false); -***** assert (isequal (size (Kb), [n1 n1])); -***** assert (isequal (size (Pb), [n1 0])); -***** assert (isequal (P1, Pb) && (isequal (K1, Kb))) -***** assert (isequal (P2, Pb) && (isequal (K2, Kb))) -***** test [Kc, Pc] = stk_covmat_noise (model, x1, x2); % (3) -***** test [K1, P1] = stk_covmat_noise (model, x1, x2, -1); -***** test [K2, P2] = stk_covmat_noise (model, x1, x2, -1, false); -***** assert (isequal (size (Kc), [n1 n2])); -***** assert (isequal (size (Pc), [n1 0])); -***** assert (isequal (P1, Pc) && (isequal (K1, Kc))) -***** assert (isequal (P2, Pc) && (isequal (K2, Kc))) -***** assert (isequal (Kb, Ka)); -***** test [Ka, Pa] = stk_covmat_noise (model2, x1); % (1') -***** test [Kb, Pb] = stk_covmat_noise (model2, x1, x1); % (2') -***** error assert (isequal (Kb, Ka)); -***** assert (isequal (Pa, Pb)); -***** assert (isequal (Pa, Pc)); -31 tests, 31 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/get.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/get.m -***** shared M_post - x_obs = (linspace (0, pi, 15))'; - z_obs = sin (x_obs); - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); -***** error value = get (M_post, 1.33); -***** error value = get (M_post, 'dudule'); -***** test value = get (M_post, 'prior_model'); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/stk_model_update.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_model_update.m -***** shared x_obs, z_obs, ref, M_prior, x_new, z_new, lnv_new - [x_obs, z_obs, ref] = stk_dataset_twobumps ('noisy2'); - M_prior = stk_model (@stk_materncov52_iso); - M_prior.param = [-0.15; 0.38]; - M_prior.lognoisevariance = 2 * log (ref.noise_std); - x_new = [-0.79; -0.79]; - z_new = [-0.69; -0.85]; - lnv_new = ref.noise_std_func (x_new); -***** test % heteroscedastic - M_prior.lognoisevariance = 2 * log (ref.noise_std); - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); - M_post = stk_model_update (M_post, x_new, z_new, lnv_new); -***** error % using lnv_new / homoscedastic - M_prior.lognoisevariance = 0; - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); - M_post = stk_model_update (M_post, x_new, z_new, lnv_new); % NOT OK -***** error % using lnv_new / noiseless - M_prior.lognoisevariance = -inf; - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs) - M_post = stk_model_update (M_post, x_new, z_new, lnv_new); % NOT OK -***** error % not using lnv_new / heteroscedastic - M_prior.lognoisevariance = 2 * log (ref.noise_std); - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); - M_post = stk_model_update (M_post, x_new, z_new); -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/stk_model_gpposterior.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_model_gpposterior.m -***** test stk_test_class ('stk_model_gpposterior') -***** shared M_prior, x_obs, z_obs - x_obs = (linspace (0, pi, 15))'; - z_obs = sin (x_obs); - - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); -***** test M_post = stk_model_gpposterior (); -***** test M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); -***** error M_post = stk_model_gpposterior (M_prior, x_obs, [z_obs; z_obs]); -***** error M_post = stk_model_gpposterior (M_prior, x_obs, [z_obs; z_obs], 3.441); -***** test % hidden feature - kreq = stk_kreq_qr (M_prior, x_obs); - M_post = stk_model_gpposterior (M_prior, {x_obs, kreq}, z_obs); -***** test % NaNs in prior_model.param - DIM = 1; M = stk_model (@stk_materncov52_aniso, DIM); - M.param = nan (2, 1); % this is currently the default - x = stk_sampling_regulargrid (20, DIM, [0; 1]); - y = sin (double (x)); - zp = stk_predict (M, x, y, x); -7 tests, 7 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/stk_predict_.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_predict_.m -***** shared n, m, M_post, M_prior, x0, x_obs, z_obs, x_prd, y_prd, idx_obs, idx_prd - - n = 10; % number of observations - m = n + 1; % number of predictions - d = 1; % dimension of the input space - - x0 = (linspace (0, pi, n + m))'; - - idx_obs = (2:2:(n+m-1))'; - idx_prd = (1:2:(n+m))'; - - x_obs = x0(idx_obs); - z_obs = sin (x_obs); - x_prd = x0(idx_prd); - - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); -***** error y_prd = stk_predict (M_post); -***** test y_prd = stk_predict (M_post, x_prd); -***** error y_prd = stk_predict (M_post, [x_prd x_prd]); -***** test % nargout = 2 - [y_prd1, lambda] = stk_predict (M_post, x_prd); - assert (stk_isequal_tolrel (y_prd, y_prd1)); - assert (isequal (size (lambda), [n m])); -***** test % nargout = 3 - [y_prd1, lambda, mu] = stk_predict (M_post, x_prd); - assert (stk_isequal_tolrel (y_prd, y_prd1)); - assert (isequal (size (lambda), [n m])); - assert (isequal (size (mu), [1 m])); % ordinary kriging -***** test % nargout = 4 - [y_prd1, lambda, mu, K] = stk_predict (M_post, x_prd); - assert (stk_isequal_tolrel (y_prd, y_prd1)); - assert (isequal (size (lambda), [n m])); - assert (isequal (size (mu), [1 m])); % ordinary kriging - assert (isequal (size (K), [m m])); -***** test % nargout = 2, compute only variances - M_post1 = stk_model_gpposterior (M_prior, x_obs, []); - [y_prd_nan, lambda] = stk_predict (M_post1, x_prd); - assert (isequal (size (lambda), [n m])); - assert (all (isnan (y_prd_nan.mean))); -***** test % discrete model (prediction indices provided) - M_prior1 = stk_model (@stk_discretecov, M_prior, x0); - M_post1 = stk_model_gpposterior (M_prior1, idx_obs, z_obs); - y_prd1 = stk_predict (M_post1, idx_prd); - assert (stk_isequal_tolrel (y_prd, y_prd1)); -***** test % discrete model (prediction indices *not* provided) - M_prior1 = stk_model (@stk_discretecov, M_prior, x0); - M_post1 = stk_model_gpposterior (M_prior1, idx_obs, z_obs); - y_prd1 = stk_predict (M_post1, []); % predict them all! - assert (stk_isequal_tolrel (y_prd, y_prd1(idx_prd, :))); -9 tests, 9 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/set.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/set.m -***** shared M_post - x_obs = (linspace (0, pi, 15))'; - z_obs = sin (x_obs); - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); -***** error value = get (M_post, 1.33); -***** error value = get (M_post, 'dudule'); -***** test value = get (M_post, 'prior_model'); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/model/@stk_model_gpposterior/stk_predict_leaveoneout.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/@stk_model_gpposterior/stk_predict_leaveoneout.m -***** test % Check virtual Leave-One-Out formula - - n = 20; d = 1; - x_obs = stk_sampling_regulargrid (n, d, [0; 2*pi]); - z_obs = stk_feval (@sin, x_obs); - - lm_list = {stk_lm_null, stk_lm_constant, stk_lm_affine}; - - for j = 0:2 - for k = 1:(length (lm_list)) - - model = stk_model (@stk_materncov32_iso, d); - model.lm = lm_list{k}; - model.param = log ([1; 5]); - - switch j % test various scenarios for lognoisevariance - case 0 - model.lognoisevariance = -inf; - case 1 - model.lognoisevariance = 0; - case 2 - model.lognoisevariance = (1 + rand (n, 1)) * 1e-3; - end - - M_post = stk_model_gpposterior (model, x_obs, z_obs); - - [loo_pred, loo_res] = stk_predict_leaveoneout (M_post); - [direct_pred, direct_res] = stk_predict_leaveoneout_direct (M_post); - - assert (stk_isequal_tolrel (loo_pred, direct_pred)); - assert (stk_isequal_tolrel (loo_res, direct_res)); - - end - end -1 test, 1 passed, 0 known failure, 0 skipped -[inst/model/noise/@stk_gaussiannoise_het0/set.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/model/noise/@stk_gaussiannoise_het0/set.m -***** shared M_post - x_obs = (linspace (0, pi, 15))'; - z_obs = sin (x_obs); - M_prior = stk_model (@stk_materncov32_iso); - M_prior.param = log ([1.0; 2.1]); - M_post = stk_model_gpposterior (M_prior, x_obs, z_obs); -***** error value = get (M_post, 1.33); -***** error value = get (M_post, 'dudule'); -***** test value = get (M_post, 'prior_model'); -3 tests, 3 passed, 0 known failure, 0 skipped -[inst/utils/stk_generate_samplepaths.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/utils/stk_generate_samplepaths.m -***** shared model, xi, zi, xt, n, nb_paths - dim = 1; n = 50; nb_paths = 5; - model = stk_model (@stk_materncov32_iso, dim); - model.param = log ([1.0; 2.9]); - xt = stk_sampling_regulargrid (n, dim, [-1.0; 1.0]); - xi = [xt(1, :); xt(end, :)]; zi = [0; 0]; -***** error zsim = stk_generate_samplepaths (); -***** error zsim = stk_generate_samplepaths (model); -***** test zsim = stk_generate_samplepaths (model, xt); -***** test zsim = stk_generate_samplepaths (model, xt, nb_paths); -***** test zsim = stk_generate_samplepaths (model, xi, zi, xt); -***** test zsim = stk_generate_samplepaths (model, xi, zi, xt, nb_paths); + x = set(x, 'colnames', t); + assert (isequal (x.rownames, s)) + assert (isequal (x.colnames, t)) + assert (isequal (x.colnames{2}, 'yy')) +***** shared u, data + u = rand(3, 2); + data = stk_dataframe(u, {'x1', 'x2'}); +***** assert (isequal (data.x2, u(:, 2))) +***** assert (data.x2(3) == u(3, 2)) +***** error t = data.toto; +***** error t = data(1, 1).zzz; % illegal multilevel indexing +***** error t = data(1, 1, 1); % too many indices +***** error t = data{1}; % curly braces not allowed +***** test % select rows and columns + x = stk_dataframe (reshape (1:15, 5, 3), {'u' 'v' 'w'}); + assert (isequal (x([3 5], 2), stk_dataframe ([8; 10], {'v'}))); +***** shared u, data + u = rand(3, 1); data = stk_dataframe(u, {'x'}); +***** assert (isequal (data.x, u)) +***** assert (isequal (double (data), u)) +***** assert (isequal (double (data(2)), u(2))) +***** assert (isequal (double (data(3, 1)), u(3))) +***** error t = data(1, 1, 1); % too many indices ***** test - zsim = stk_generate_samplepaths (model, xt); - assert (isequal (size (zsim), [n, 1])); + x = stk_dataframe (randn (2, 2), {'u' 'v'}); + y = x ([], :); + assert (isa (y, 'stk_dataframe')); + assert (isequal (size (y), [0 2])); + assert (isequal (y.colnames, {'u' 'v'})); ***** test - zsim = stk_generate_samplepaths (model, xt, nb_paths); - assert (isequal (size (zsim), [n, nb_paths])); -***** test % duplicate simulation points - zsim = stk_generate_samplepaths (model, [xt; xt], nb_paths); - assert (isequal (size (zsim), [2 * n, nb_paths])); - assert (isequal (zsim(1:n, :), zsim((n + 1):end, :))); -***** test % simulation points equal to observation points (noiseless model) - % https://sourceforge.net/p/kriging/tickets/14/ - zsim = stk_generate_samplepaths (model, xt, zeros (n, 1), xt); - assert (isequal (zsim, zeros (n, 1))); -10 tests, 10 passed, 0 known failure, 0 skipped -[inst/utils/stk_conditioning.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/utils/stk_conditioning.m -***** shared n, m, ni, xi_ind, lambda, zsim, zi - - n = 50; m = 5; ni = 10; xi_ind = 1:ni; - lambda = 1/ni * ones (ni, n); % prediction == averaging - zsim = ones (n, m); % const unconditioned samplepaths - zi = zeros (ni, 1); % conditioning by zeros -***** error zsimc = stk_conditioning (); -***** error zsimc = stk_conditioning (lambda); -***** error zsimc = stk_conditioning (lambda, zi); -***** test zsimc = stk_conditioning (lambda, zi, zsim); -***** test zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); + x = stk_dataframe (randn (2, 2), [], {'a' 'b'}); + y = x (:, []); + assert (isa (y, 'stk_dataframe')); + assert (isequal (size (y), [2 0])); + assert (isequal (y.rownames, {'a'; 'b'})); +16 tests, 16 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/bsxfun.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/bsxfun.m +***** shared x1, x2, data1, data2 + x1 = rand (3, 2); data1 = stk_dataframe (x1); + x2 = rand (3, 2); data2 = stk_dataframe (x2); ***** test - zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); - assert (stk_isequal_tolabs (double (zsimc), zeros (n, m))); + z = bsxfun (@plus, data1, x2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) ***** test - zi = 2 * ones (ni, 1); % conditioning by twos - zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); - assert (stk_isequal_tolabs (double (zsimc), 2 * ones (n, m))); + z = bsxfun (@plus, x1, data2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) ***** test - DIM = 1; nt = 400; - xt = stk_sampling_regulargrid (nt, DIM, [-1.0; 1.0]); - - NI = 6; xi_ind = [1 20 90 200 300 350]; - xi = xt(xi_ind, 1); - zi = (1:NI)'; % linear response ;-) - - % Carry out the kriging prediction at points xt - model = stk_model (@stk_materncov52_iso); - model.param = log ([1.0; 2.9]); - [ignore_zp, lambda] = stk_predict (model, xi, [], xt); - - % Generate (unconditional) sample paths according to the model - NB_PATHS = 10; - zsim = stk_generate_samplepaths (model, xt, NB_PATHS); - zsimc = stk_conditioning (lambda, zi, zsim, xi_ind); -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_noisecov.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_noisecov.m -***** shared ni, lognoisevariance, diff - ni = 5; - lognoisevariance = 0.0; - diff = -1; -***** error K = stk_noisecov (); -***** error K = stk_noisecov (ni); -***** test K = stk_noisecov (ni, lognoisevariance); -***** test K = stk_noisecov (ni, lognoisevariance, diff); -***** test K = stk_noisecov (ni, lognoisevariance, diff, true); + z = bsxfun (@plus, data1, data2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), x1 + x2)) +***** shared x, y + x = stk_dataframe (randn (2), {'x1', 'x2'}, {'a'; 'b'}); + y = stk_dataframe (randn (2), {'y1', 'y2'}, {'c'; 'd'}); +***** test z = x + y; + assert (isequal (z.colnames, x.colnames)); + assert (isequal (z.rownames, x.rownames)); +***** test z = y + x; + assert (isequal (z.colnames, y.colnames)); + assert (isequal (z.rownames, y.rownames)); 5 tests, 5 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov_aniso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 1.5; 2.8]); - x = stk_sampling_randunif(5, dim); - y = stk_sampling_randunif(5, dim); -***** error stk_materncov_aniso(); -***** error stk_materncov_aniso(param); -***** error stk_materncov_aniso(param, x); -***** test stk_materncov_aniso(param, x, y); -***** test stk_materncov_aniso(param, x, y, -1); -***** test stk_materncov_aniso(param, x, y, -1, false); -***** error stk_materncov_aniso(param, x, y, -2); -***** test stk_materncov_aniso(param, x, y, -1); -***** error stk_materncov_aniso(param, x, y, 0); -***** test stk_materncov_aniso(param, x, y, 1); -***** test stk_materncov_aniso(param, x, y, 2); -***** test stk_materncov_aniso(param, x, y, 3); -***** error stk_materncov_aniso(param, x, y, 4); -***** error stk_materncov_aniso(param, x, y, nan); -***** error stk_materncov_aniso(param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 1.5; 2.8; 2.7; 2.9]); - nx = 4; ny = 10; - x = stk_sampling_randunif(nx, dim); - y = stk_sampling_randunif(ny, dim); -***** test - K1 = stk_materncov_aniso(param, x, y); - K2 = stk_materncov_aniso(param, x, y, -1); - assert(isequal(size(K1), [nx ny])); - assert(stk_isequal_tolabs(K1, K2)); +[inst/arrays/@stk_dataframe/log2.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/log2.m ***** test - for i = 1:(dim+2), - dK = stk_materncov_aniso(param, x, y, i); - assert(isequal(size(dK), [nx ny])); - end + u = rand (4, 3); x = stk_dataframe (u); v = log2 (x); + assert (strcmp (class (v), class (u)) && isequal (v, log2 (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/asind.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/asind.m ***** test - n = 7; - x = stk_sampling_randunif(n, dim); - y = stk_sampling_randunif(n, dim); - - K1 = stk_materncov_aniso(param, x, y); - K2 = stk_materncov_aniso(param, x, y, -1, true); - assert(isequal(size(K1), [n n])); - assert(stk_isequal_tolabs(K2, diag(K1))); - - for i = 1:(dim+2), - dK1 = stk_materncov_aniso(param, x, y, i); - dK2 = stk_materncov_aniso(param, x, y, i, true); - assert(isequal(size(dK1), [n n])); - assert(stk_isequal_tolabs(dK2, diag(dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_gausscov_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_gausscov_aniso.m -***** shared param, x, y, K1, K2, K3 - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (6, dim); -***** error K0 = stk_gausscov_aniso (); -***** error K0 = stk_gausscov_aniso (param); -***** error K0 = stk_gausscov_aniso (param, x); -***** test K1 = stk_gausscov_aniso (param, x, y); -***** test K2 = stk_gausscov_aniso (param, x, y, -1); -***** test K3 = stk_gausscov_aniso (param, x, y, -1, false); -***** assert (isequal (K1, K2)); -***** assert (isequal (K1, K3)); -***** test % df versus ordinary array - u = double (x); v = double (y); - K1 = stk_gausscov_aniso (param, u, v, -1); - K2 = stk_gausscov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); -***** error stk_gausscov_aniso (param, x, y, -2); -***** test stk_gausscov_aniso (param, x, y, -1); -***** error stk_gausscov_aniso (param, x, y, 0); -***** test stk_gausscov_aniso (param, x, y, 1); -***** test stk_gausscov_aniso (param, x, y, 2); -***** error stk_gausscov_aniso (param, x, y, 3); -***** error stk_gausscov_aniso (param, x, y, nan); -***** error stk_gausscov_aniso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5; 2.4; 2.6]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + u = rand (4, 3); x = stk_dataframe (u); v = asind (x); + assert (strcmp (class (v), class (u)) && isequal (v, asind (u))) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_dataframe/var.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_dataframe/var.m +***** shared x1, df1 + x1 = rand(9, 3); + df1 = stk_dataframe(x1, {'a', 'b', 'c'}); +***** assert (isequal (var(df1), var(x1))) +***** assert (isequal (var(df1, 0, 1), var(x1))) +***** assert (isequal (var(df1, 0, 2), var(x1, 0, 2))) +***** assert (isequal (var(df1, 1), var(x1, 1))) +***** assert (isequal (var(df1, 1, 1), var(x1, 1))) +***** assert (isequal (var(df1, 1, 2), var(x1, 1, 2))) +6 tests, 6 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/stk_dataframe.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_dataframe.m +***** shared x, cn, rn, y, cn2, rn2 + cn = {'x' 'y'}; + rn = {'lower_bounds'; 'upper_bounds'}; + x = stk_hrect ([0 0; 1 1], cn); + cn2 = {'xx' 'yy'}; + rn2 = {'aa'; 'bb'}; +***** test y = stk_dataframe (x); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn)) +***** assert (isequal (y.rownames, rn)) +***** test y = stk_dataframe (x, cn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn2)) +***** assert (isequal (y.rownames, rn)) +***** test y = stk_dataframe (x, cn2, rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn2)) +***** assert (isequal (y.rownames, rn2)) +***** test y = stk_dataframe (x, [], rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn)) +***** assert (isequal (y.rownames, rn2)) +***** test y = stk_dataframe (x, {}, rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, {})) +***** assert (isequal (y.rownames, rn2)) +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/stk_hrect.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_hrect.m +***** test stk_test_class ('stk_hrect') +***** shared dom +***** test dom = stk_hrect ([-1; 1], {'x'}); +***** assert (isequal (dom.colnames, {'x'})) +***** assert (isequal (dom.rownames, {'lower_bounds'; 'upper_bounds'})) +***** assert (isequal (dom.data, [-1; 1])) +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/vertcat.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/vertcat.m +***** shared d, x, y + d = 10; + x = stk_hrect (d); + y = double (x); ***** test - K1 = stk_gausscov_aniso (param, x, y); - K2 = stk_gausscov_aniso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + z = vertcat (x, x); + assert (isequal (size (z), [4 d])); + assert (strcmp (class (z), 'stk_dataframe')); ***** test - for i = 1:(dim + 1), - dK = stk_gausscov_aniso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + z = vertcat (x, y); + assert (isequal (size (z), [4 d])); + assert (strcmp (class (z), 'stk_dataframe')); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_gausscov_aniso (param, x, y); - K2 = stk_gausscov_aniso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:(dim + 1), - dK1 = stk_gausscov_aniso (param, x, y, i); - dK2 = stk_gausscov_aniso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_discretecov.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_discretecov.m -***** shared model, model2, x0 - n0 = 20; n1 = 10; dim = 4; - x0 = stk_sampling_randunif (n0, dim); - x1 = stk_sampling_randunif (n1, dim); - model = stk_model (@stk_materncov52_aniso, dim); - model.lm = stk_lm_affine (); - model.param = log ([1.0; 2.1; 2.2; 2.3; 2.4]); -***** test % without noise, pairwise = false - model.lognoisevariance = - inf; - model2 = stk_model (@stk_discretecov, model, x0); - idx = [1 4 9]; - [K1, P1] = stk_make_matcov (model, x0(idx, :)); - [K2, P2] = stk_make_matcov (model2, idx'); - assert (stk_isequal_tolrel (K1, K2)); - assert (stk_isequal_tolrel (P1, P2)); -***** test % without noise, pairwise = true - K1 = stk_make_matcov (model, x0([2 5 6], :), [], true); - K2 = stk_make_matcov (model2, [2 5 6]', [], true); - assert (stk_isequal_tolrel (K1, K2)); -***** test % with noise, pairwise = false - model.lognoisevariance = log (0.01); - model2 = stk_model (@stk_discretecov, model, x0); - idx = [1 4 9]; - [K1, P1] = stk_make_matcov (model, x0(idx, :)); - [K2, P2] = stk_make_matcov (model2, idx'); - assert (stk_isequal_tolrel (K1, K2)); - assert (stk_isequal_tolrel (P1, P2)); + z = vertcat (y, x); + assert (isequal (size (z), [4 d])); + assert (strcmp (class (z), 'stk_dataframe')); 3 tests, 3 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_matern52.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern52.m -***** shared h, diff - h = 1.0; diff = -1; -***** error stk_rbf_matern52 (); -***** test stk_rbf_matern52 (h); -***** test stk_rbf_matern52 (h, diff); -***** test %% h = 0.0 => correlation = 1.0 - x = stk_rbf_matern52 (0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); -***** test %% consistency with stk_rbf_matern: function values - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (5/2, h); - y = stk_rbf_matern52 (h); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** test %% consistency with stk_rbf_matern: derivatives - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (5/2, h, 2); - y = stk_rbf_matern52 (h, 1); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** assert (stk_rbf_matern52 (inf) == 0) -7 tests, 7 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_spherical.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_spherical.m -***** shared h, diff - h = 1.0; diff = -1; -***** error stk_rbf_spherical (); -***** test stk_rbf_spherical (h); -***** test stk_rbf_spherical (h, diff); -***** test %% h = 0.0 => correlation = 1.0 - x = stk_rbf_spherical (0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); -***** test %% check derivative numerically - h = [-1 -0.5 -0.1 0.1 0.5 1]; delta = 1e-9; - d1 = (stk_rbf_spherical (h + delta) - stk_rbf_spherical (h)) / delta; - d2 = stk_rbf_spherical (h, 1); - assert (stk_isequal_tolabs (d1, d2, 1e-4)); -***** assert (stk_rbf_spherical (inf) == 0) +[inst/arrays/@stk_hrect/ismember.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/ismember.m +***** shared n, box + n = 5; + box = stk_hrect (n); +***** assert (ismember (box(1, :), box)) +***** assert (ismember (box(2, :), box)) +***** assert (ismember (.5 * ones (1, 5), box)) +***** assert (~ ismember (box(1, :) - 1, box)) +***** assert (~ ismember (box(2, :) + 1, box)) +***** test + y = double (box); y = [y; y + 2]; + assert (isequal (ismember (y, box), [1; 1; 0; 0])) 6 tests, 6 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_gauss.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_gauss.m -***** shared h, diff - h = 1.0; diff = -1; -***** error stk_rbf_gauss (); -***** test stk_rbf_gauss (h); -***** test stk_rbf_gauss (h, diff); -***** test % h = 0.0 => correlation = 1.0 - x = stk_rbf_gauss (0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); -4 tests, 4 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_matern.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern.m -***** shared nu, h, diff - nu = 1.0; h = 1.0; diff = -1; -***** error stk_rbf_matern (); -***** error stk_rbf_matern (nu); -***** test stk_rbf_matern (nu, h); -***** test stk_rbf_matern (nu, h, diff); -***** test %% h = 0.0 => correlation = 1.0 - for nu = 0.1:0.2:5.0, - x = stk_rbf_matern (nu, 0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); - end +[inst/arrays/@stk_hrect/stk_normalize.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_normalize.m +***** shared x, box, y1, y2, y3, y4 + n = 5; box = stk_hrect ([2; 3]); + x = 2 + rand (n, 1); +***** error y1 = stk_normalize (); +***** test y2 = stk_normalize (x); +***** test y3 = stk_normalize (x, box); +***** test assert (~ any ((y2 < -10 * eps) | (y2 > 1 + 10 * eps))); +***** test assert (~ any ((y3 < -10 * eps) | (y3 > 1 + 10 * eps))); 5 tests, 5 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_matern32.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_matern32.m -***** shared h, diff - h = 1.0; diff = -1; -***** error stk_rbf_matern32 (); -***** test stk_rbf_matern32 (h); -***** test stk_rbf_matern32 (h, diff); -***** test %% h = 0.0 => correlation = 1.0 - x = stk_rbf_matern32 (0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); -***** test %% consistency with stk_rbf_matern: function values - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (3/2, h); - y = stk_rbf_matern32 (h); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** test %% consistency with stk_rbf_matern: derivatives - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (3/2, h, 2); - y = stk_rbf_matern32 (h, 1); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** assert (stk_rbf_matern32 (inf) == 0) -7 tests, 7 passed, 0 known failure, 0 skipped -[inst/covfcs/rbf/stk_rbf_exponential.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/rbf/stk_rbf_exponential.m -***** shared h, diff - h = 1.0; diff = -1; -***** error stk_rbf_exponential (); -***** test stk_rbf_exponential (h); -***** test stk_rbf_exponential (h, diff); -***** test %% h = 0.0 => correlation = 1.0 - x = stk_rbf_exponential (0.0); - assert (stk_isequal_tolrel (x, 1.0, 1e-8)); -***** test %% check derivative numerically - h = [-1 -0.5 -0.1 0.1 0.5 1]; delta = 1e-9; - d1 = (stk_rbf_exponential (h + delta) - stk_rbf_exponential (h)) / delta; - d2 = stk_rbf_exponential (h, 1); - assert (stk_isequal_tolabs (d1, d2, 1e-4)); -***** test %% consistency with stk_rbf_matern: function values - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (1/2, h); - y = stk_rbf_exponential (h); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** test %% consistency with stk_rbf_matern: derivatives - for h = 0.1:0.1:2.0, - x = stk_rbf_matern (1/2, h, 2); - y = stk_rbf_exponential (h, 1); - assert (stk_isequal_tolrel (x, y, 1e-8)); - end -***** assert (stk_rbf_exponential (inf) == 0) -8 tests, 8 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 1.5; 2.9]); - x = stk_sampling_randunif(5, dim); - y = stk_sampling_randunif(5, dim); -***** error K = stk_materncov_iso ([param; 1.234], x, y); -***** error stk_materncov_iso(); -***** error stk_materncov_iso(param); -***** error stk_materncov_iso(param, x); -***** test stk_materncov_iso(param, x, y); -***** test stk_materncov_iso(param, x, y, -1); -***** test stk_materncov_iso(param, x, y, -1, false); -***** error stk_materncov_iso(param, x, y, -2); -***** test stk_materncov_iso(param, x, y, -1); -***** error stk_materncov_iso(param, x, y, 0); -***** test stk_materncov_iso(param, x, y, 1); -***** test stk_materncov_iso(param, x, y, 2); -***** test stk_materncov_iso(param, x, y, 3); -***** error stk_materncov_iso(param, x, y, 4); -***** error stk_materncov_iso(param, x, y, nan); -***** error stk_materncov_iso(param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 1.5; 2.9]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); -***** test - K1 = stk_materncov_iso (param, x, y); - K2 = stk_materncov_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); -***** test - for i = 1:3, - dK = stk_materncov_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end +[inst/arrays/@stk_hrect/horzcat.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/horzcat.m +***** shared d, x1, x2, x3 + d = 10; + x1 = stk_hrect (d); + x2 = double (x1); + x3 = [1:d; 0:(d-1)]; % illegal bounds ***** test - n = 7; - x = stk_sampling_randunif(n, dim); - y = stk_sampling_randunif(n, dim); - - K1 = stk_materncov_iso(param, x, y); - K2 = stk_materncov_iso(param, x, y, -1, true); - assert(isequal(size(K1), [n n])); - assert(stk_isequal_tolabs(K2, diag(K1))); - - for i = 1:3, - dK1 = stk_materncov_iso(param, x, y, i); - dK2 = stk_materncov_iso(param, x, y, i, true); - assert(isequal(size(dK1), [n n])); - assert(stk_isequal_tolabs(dK2, diag(dK1))); - end -19 tests, 19 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov32_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov32_aniso.m -***** shared param, x, y, K1, K2, K3 - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (6, dim); -***** error K0 = stk_materncov32_aniso (); -***** error K0 = stk_materncov32_aniso (param); -***** error K0 = stk_materncov32_aniso (param, x); -***** test K1 = stk_materncov32_aniso (param, x, y); -***** test K2 = stk_materncov32_aniso (param, x, y, -1); -***** test K3 = stk_materncov32_aniso (param, x, y, -1, false); -***** assert (isequal (K1, K2)); -***** assert (isequal (K1, K3)); -***** test % df versus ordinary array - u = double (x); v = double (y); - K1 = stk_materncov32_aniso (param, u, v, -1); - K2 = stk_materncov32_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); - assert (isequal (K1, K2)); -***** error stk_materncov32_aniso (param, x, y, -2); -***** test stk_materncov32_aniso (param, x, y, -1); -***** error stk_materncov32_aniso (param, x, y, 0); -***** test stk_materncov32_aniso (param, x, y, 1); -***** test stk_materncov32_aniso (param, x, y, 2); -***** error stk_materncov32_aniso (param, x, y, 3); -***** error stk_materncov32_aniso (param, x, y, nan); -***** error stk_materncov32_aniso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5; 2.4; 2.6]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + y1 = horzcat (x1, x1); + assert (isequal (size (y1), [2 2*d])); + assert (strcmp (class (y1), 'stk_hrect')); ***** test - K1 = stk_materncov32_aniso (param, x, y); - K2 = stk_materncov32_aniso (param, x, y, -1); - assert (isequal (size(K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + y2 = horzcat (x1, x2); + assert (isequal (size (y2), [2 2*d])); + assert (strcmp (class (y2), 'stk_hrect')); ***** test - for i = 1:(dim + 1), - dK = stk_materncov32_aniso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + y3 = horzcat (x2, x1); + assert (isequal (size (y3), [2 2*d])); + assert (strcmp (class (y3), 'stk_hrect')); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_materncov32_aniso (param, x, y); - K2 = stk_materncov32_aniso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); + lastwarn ('') + y4 = horzcat (x1, x3); + assert (isequal (size (y4), [2 2*d])); + assert (strcmp (class (y4), 'stk_dataframe')); + [warn_msg, warn_id] = lastwarn (); + assert (strcmp (warn_id, 'STK:stk_hrect:horzcat:IllegalBounds')) +warning: Illegal bounds, the result is not an stk_hrect object. +warning: called from + horzcat at line 47 column 9 + __test__ at line 4 column 5 + test at line 682 column 11 + /tmp/tmp.tlZGNdJ4JJ at line 1750 column 31 - for i = 1:(dim + 1), - dK1 = stk_materncov32_aniso (param, x, y, i); - dK2 = stk_materncov32_aniso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov52_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov52_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error K = stk_materncov52_iso ([param; 1.234], x, y); -***** error stk_materncov52_iso (); -***** error stk_materncov52_iso (param); -***** error stk_materncov52_iso (param, x); -***** test stk_materncov52_iso (param, x, y); -***** test stk_materncov52_iso (param, x, y, -1); -***** test stk_materncov52_iso (param, x, y, -1, false); -***** error stk_materncov52_iso (param, x, y, -2); -***** test stk_materncov52_iso (param, x, y, -1); -***** error stk_materncov52_iso (param, x, y, 0); -***** test stk_materncov52_iso (param, x, y, 1); -***** test stk_materncov52_iso (param, x, y, 2); -***** error stk_materncov52_iso (param, x, y, 3); -***** error stk_materncov52_iso (param, x, y, nan); -***** error stk_materncov52_iso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/stk_boundingbox.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_boundingbox.m +***** shared x, y + lb = rand (1, 5); + ub = lb + 1; + cn = {'a', 'b', 'c', 'd', 'e'}; + x = stk_hrect ([lb; ub], cn); +***** error y = stk_boundingbox (); +***** test y = stk_boundingbox (x); +***** assert (isequal (y, x)); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/stk_rescale.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/stk_rescale.m +***** shared x + x = rand (10, 4); + y = stk_rescale (x, [], []); + assert (stk_isequal_tolabs (x, y)); ***** test - K1 = stk_materncov52_iso (param, x, y); - K2 = stk_materncov52_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + y = stk_rescale(0.5, [], [0; 2]); + assert (stk_isequal_tolabs (y, 1.0)); ***** test - for i = 1:2, - dK = stk_materncov52_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + y = stk_rescale (0.5, [0; 1], [0; 2]); + assert (stk_isequal_tolabs (y, 1.0)); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_materncov52_iso (param, x, y); - K2 = stk_materncov52_iso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:2, - dK1 = stk_materncov52_iso (param, x, y, i); - dK2 = stk_materncov52_iso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov52_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov52_aniso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error stk_materncov52_aniso (); -***** error stk_materncov52_aniso (param); -***** error stk_materncov52_aniso (param, x); -***** test stk_materncov52_aniso (param, x, y); -***** test stk_materncov52_aniso (param, x, y, -1); -***** test stk_materncov52_aniso (param, x, y, -1, false); -***** error stk_materncov52_aniso (param, x, y, -2); -***** test stk_materncov52_aniso (param, x, y, -1); -***** error stk_materncov52_aniso (param, x, y, 0); -***** test stk_materncov52_aniso (param, x, y, 1); -***** test stk_materncov52_aniso (param, x, y, 2); -***** error stk_materncov52_aniso (param, x, y, 3); -***** error stk_materncov52_aniso (param, x, y, nan); -***** error stk_materncov52_aniso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5; 2.4; 2.6]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + y = stk_rescale (0.5, [0; 2], []); + assert (stk_isequal_tolabs (y, 0.25)); ***** test - K1 = stk_materncov52_aniso (param, x, y); - K2 = stk_materncov52_aniso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + y = stk_rescale (0.5, [0; 2], [0; 1]); + assert (stk_isequal_tolabs (y, 0.25)); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_hrect/subsref.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_hrect/subsref.m ***** test - for i = 1:(dim + 1), - dK = stk_materncov52_aniso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + B = stk_hrect ([0 0 0 0; 1 2 3 4]); + B = B(:, [1 3 4]); + assert (strcmp (class (B), 'stk_hrect')); + assert (isequal (double (B), [0 0 0; 1 3 4])); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_materncov52_aniso (param, x, y); - K2 = stk_materncov52_aniso(param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:(dim + 1), - dK1 = stk_materncov52_aniso (param, x, y, i); - dK2 = stk_materncov52_aniso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -17 tests, 17 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_sphcov_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_sphcov_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error K = stk_sphcov_iso ([param; 1.234], x, y); -***** error stk_sphcov_iso (); -***** error stk_sphcov_iso (param); -***** error stk_sphcov_iso (param, x); -***** test stk_sphcov_iso (param, x, y); -***** test stk_sphcov_iso (param, x, y, -1); -***** test stk_sphcov_iso (param, x, y, -1, false); -***** error stk_sphcov_iso (param, x, y, -2); -***** test stk_sphcov_iso (param, x, y, -1); -***** error stk_sphcov_iso (param, x, y, 0); -***** test stk_sphcov_iso (param, x, y, 1); -***** test stk_sphcov_iso (param, x, y, 2); -***** error stk_sphcov_iso (param, x, y, 3); -***** error stk_sphcov_iso (param, x, y, nan); -***** error stk_sphcov_iso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + B = stk_hrect ([0 0 0 0; 1 2 3 4]); + B = B(1, :); + assert (strcmp (class (B), 'stk_dataframe')); + assert (isequal (double (B), [0 0 0 0])); +2 tests, 2 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_get_sample_size.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_get_sample_size.m +***** assert (stk_get_sample_size ([1 2; 3 4; 5 6]) == 3); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_feval.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_feval.m +***** shared f, xt + f = @(x)(- (0.7 * x + sin (5 * x + 1) + 0.1 * sin (10 * x))); + xt = stk_sampling_regulargrid (20, 1, [0; 1]); +***** error yt = stk_feval (); +***** error yt = stk_feval (f); +***** test yt = stk_feval (f, xt); +***** test yt = stk_feval (f, xt, false); +***** test yt = stk_feval (f, xt, false, false); +***** test yt = stk_feval (f, xt, false, false, false); ***** test - K1 = stk_sphcov_iso (param, x, y); - K2 = stk_sphcov_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + N = 15; + xt = stk_sampling_regulargrid (N, 1, [0; 1]); + yt = stk_feval (f, xt); + assert (isequal (size (yt), [N 1])); ***** test - for i = 1:2, - dK = stk_sphcov_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + x = stk_dataframe ([1; 2; 3], {'x'}, {'a'; 'b'; 'c'}); + y = stk_feval (@(u)(2 * u), x); + assert (isequal (y.data, [2; 4; 6])); + assert (isequal (y.rownames, {'a'; 'b'; 'c'})); +***** shared t, z_ref, n + n = 20; + t = stk_sampling_regulargrid (n, 1, [0; 2*pi]); + z_ref = [sin(t.data) cos(t.data)]; ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_sphcov_iso (param, x, y); - K2 = stk_sphcov_iso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:2, - dK1 = stk_sphcov_iso (param, x, y, i); - dK2 = stk_sphcov_iso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_materncov32_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_materncov32_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error K = stk_materncov32_iso ([param; 1.234], x, y); -***** error stk_materncov32_iso (); -***** error stk_materncov32_iso (param); -***** error stk_materncov32_iso (param, x); -***** test stk_materncov32_iso (param, x, y); -***** test stk_materncov32_iso (param, x, y, -1); -***** test stk_materncov32_iso (param, x, y, -1, false); -***** error stk_materncov32_iso (param, x, y, -2); -***** test stk_materncov32_iso (param, x, y, -1); -***** error stk_materncov32_iso (param, x, y, 0); -***** test stk_materncov32_iso (param, x, y, 1); -***** test stk_materncov32_iso (param, x, y, 2); -***** error stk_materncov32_iso (param, x, y, 3); -***** error stk_materncov32_iso (param, x, y, nan); -***** error stk_materncov32_iso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + t.colnames = {'time'}; + z = stk_feval ({@sin, @cos}, t); + assert (isa (z, 'stk_dataframe')); + assert (isequal (z.data, z_ref)); ***** test - K1 = stk_materncov32_iso (param, x, y); - K2 = stk_materncov32_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + F = @(x)([sin(x) cos(x)]); + z = stk_feval (F, t); + assert (isequal (z.data, z_ref)); ***** test - for i = 1:2, - dK = stk_materncov32_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + t = stk_sampling_regulargrid (n, 1, [0; 2*pi]); + F = {'sin', 'cos'}; + z = stk_feval (F, t); + assert (isequal (z.data, [sin(t.data) cos(t.data)])); + assert (isequal (z.colnames, {'sin' 'cos'})); +***** test % vectorized + F = @(t)([sin(t) cos(t)]); + G = @(t)(0.365 * t.^2 + (cos ((t - 1).*(t - 2) + 0.579033))); + z = stk_feval ({@sin, @cos, G, F, 'tan'}, t); + assert (isequal (z.colnames, {'sin' 'cos' 'F3' 'F4_1' 'F4_2' 'tan'})); +***** test % not vectorized + F = @(t)([sin(t) cos(t)]); + G = @(t)(0.365 * t^2 + (cos ((t - 1)*(t - 2) + 0.579033))); + z = stk_feval ({@sin, @cos, G, F, 'tan'}, t, [], [], false); + assert (isequal (z.colnames, {'sin' 'cos' 'F3' 'F4_1' 'F4_2' 'tan'})); +13 tests, 13 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_normalize.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_normalize.m +***** shared x, box, y1, y2, y3, y4 + n = 5; box = [2; 3]; x = box(1) + diff (box) * rand (n, 1); +***** error y1 = stk_normalize (); +***** test y2 = stk_normalize (x); +***** test y3 = stk_normalize (x, box); +***** test assert (~ any ((y2 < -10 * eps) | (y2 > 1 + 10 * eps))); +***** test assert (~ any ((y3 < -10 * eps) | (y3 > 1 + 10 * eps))); +5 tests, 5 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_length.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_length.m +***** assert (isequal (stk_length ([1 2; 3 4; 5 6]), 3)); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_boundingbox.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_boundingbox.m +***** shared x, y, cn + cn = {'a', 'b', 'c'}; + x = [0 3 2; 1 4 1; 7 0 2]; +***** error y = stk_boundingbox (); +***** test y = stk_boundingbox (x); +***** assert (isequal (y.data, [0 0 1; 7 4 2])); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/generic/stk_rescale.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/generic/stk_rescale.m +***** shared x + x = rand (10, 4); + y = stk_rescale (x, [], []); + assert (stk_isequal_tolabs (x, y)); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_materncov32_iso (param, x, y); - K2 = stk_materncov32_iso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:2, - dK1 = stk_materncov32_iso (param, x, y, i); - dK2 = stk_materncov32_iso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_sphcov_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_sphcov_aniso.m -***** shared param, x, y, K1, K2, K3 - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (6, dim); -***** error K0 = stk_sphcov_aniso (); -***** error K0 = stk_sphcov_aniso (param); -***** error K0 = stk_sphcov_aniso (param, x); -***** test K1 = stk_sphcov_aniso (param, x, y); -***** test K2 = stk_sphcov_aniso (param, x, y, -1); -***** test K3 = stk_sphcov_aniso (param, x, y, -1, false); -***** assert (isequal (K1, K2)); -***** assert (isequal (K1, K3)); -***** test % df versus ordinary array - u = double (x); v = double (y); - K1 = stk_sphcov_aniso (param, u, v, -1); - K2 = stk_sphcov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); - assert (isequal (K1, K2)); -***** error stk_sphcov_aniso (param, x, y, -2); -***** test stk_sphcov_aniso (param, x, y, -1); -***** error stk_sphcov_aniso (param, x, y, 0); -***** test stk_sphcov_aniso (param, x, y, 1); -***** test stk_sphcov_aniso (param, x, y, 2); -***** error stk_sphcov_aniso (param, x, y, 3); -***** error stk_sphcov_aniso (param, x, y, nan); -***** error stk_sphcov_aniso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5; 2.4; 2.6]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + y = stk_rescale(0.5, [], [0; 2]); + assert (stk_isequal_tolabs (y, 1.0)); ***** test - K1 = stk_sphcov_aniso (param, x, y); - K2 = stk_sphcov_aniso (param, x, y, -1); - assert (isequal (size(K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + y = stk_rescale (0.5, [0; 1], [0; 2]); + assert (stk_isequal_tolabs (y, 1.0)); ***** test - for i = 1:(dim + 1), - dK = stk_sphcov_aniso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + y = stk_rescale (0.5, [0; 2], []); + assert (stk_isequal_tolabs (y, 0.25)); ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); + y = stk_rescale (0.5, [0; 2], [0; 1]); + assert (stk_isequal_tolabs (y, 0.25)); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/uminus.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/uminus.m +***** test + x = stk_factorialdesign ({1:3, 1:2}); + y = stk_factorialdesign ({-(1:3), -(1:2)}); + assert (isequal (-x, y)) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/stk_dataframe.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_dataframe.m +***** shared x, cn, rn, y, cn2, rn2 + cn = {'x' 'y'}; + rn = {'a'; 'b'; 'c'; 'd'}; + x = stk_factorialdesign ({1:2, 1:2}, cn, rn); + cn2 = {'xx' 'yy'}; + rn2 = {'aa'; 'bb'; 'cc'; 'dd'}; +***** test y = stk_dataframe (x); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn)) +***** assert (isequal (y.rownames, rn)) +***** test y = stk_dataframe (x, cn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn2)) +***** assert (isequal (y.rownames, rn)) +***** test y = stk_dataframe (x, cn2, rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn2)) +***** assert (isequal (y.rownames, rn2)) +***** test y = stk_dataframe (x, [], rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, cn)) +***** assert (isequal (y.rownames, rn2)) +***** test y = stk_dataframe (x, {}, rn2); +***** assert (strcmp (class (y), 'stk_dataframe')) +***** assert (isequal (y.colnames, {})) +***** assert (isequal (y.rownames, rn2)) +20 tests, 20 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/stk_factorialdesign.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_factorialdesign.m +***** test stk_test_class ('stk_factorialdesign') +***** test % constructor with two factors + column names + x = stk_factorialdesign ({[0 1], [1 2 3]}, {'a', 'b'}); + assert (isequal(x.colnames, {'a', 'b'})); + assert (isequal(get (x, 'colnames'), {'a', 'b'})); +***** error stk_factorialdesign ('bouh'); +***** error stk_factorialdesign ({{'a' 'b'}}); +***** shared x, fmt + fmt = stk_disp_getformat (); + x = stk_sampling_regulargrid (3^2, 2); +***** test format rat; disp (x); + : --- --- + * : 0.0 0.0 + * : 0.5 0.0 + * : 1.0 0.0 + * : 0.0 0.5 + * : 0.5 0.5 + * : 1.0 0.5 + * : 0.0 1.0 + * : 0.5 1.0 + * : 1.0 1.0 +***** test format long; disp (x); + : --- --- + * : 0.0 0.0 + * : 0.5 0.0 + * : 1.0 0.0 + * : 0.0 0.5 + * : 0.5 0.5 + * : 1.0 0.5 + * : 0.0 1.0 + * : 0.5 1.0 + * : 1.0 1.0 +***** test format short; disp (x); format (fmt); + : --- --- + * : 0.0 0.0 + * : 0.5 0.0 + * : 1.0 0.0 + * : 0.0 0.5 + * : 0.5 0.5 + * : 1.0 0.5 + * : 0.0 1.0 + * : 0.5 1.0 + * : 1.0 1.0 +***** test disp (stk_sampling_regulargrid (0^1, 1)); + Empty data frame with 0 rows and 0 columns +***** test disp (stk_sampling_regulargrid (0^2, 2)); + Empty data frame with 0 rows and 0 columns +***** test display (x); - K1 = stk_sphcov_aniso (param, x, y); - K2 = stk_sphcov_aniso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); +x = <9x2 stk_factorialdesign array> - for i = 1:(dim + 1), - dK1 = stk_sphcov_aniso (param, x, y, i); - dK2 = stk_sphcov_aniso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_expcov_aniso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_expcov_aniso.m -***** shared param, x, y, K1, K2, K3 - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (6, dim); -***** error K0 = stk_expcov_aniso (); -***** error K0 = stk_expcov_aniso (param); -***** error K0 = stk_expcov_aniso (param, x); -***** test K1 = stk_expcov_aniso (param, x, y); -***** test K2 = stk_expcov_aniso (param, x, y, -1); -***** test K3 = stk_expcov_aniso (param, x, y, -1, false); -***** assert (isequal (K1, K2)); -***** assert (isequal (K1, K3)); -***** test % df versus ordinary array - u = double (x); v = double (y); - K1 = stk_expcov_aniso (param, u, v, -1); - K2 = stk_expcov_aniso (param, stk_dataframe (u), stk_dataframe (v), -1); -***** error stk_expcov_aniso (param, x, y, -2); -***** test stk_expcov_aniso (param, x, y, -1); -***** error stk_expcov_aniso (param, x, y, 0); -***** test stk_expcov_aniso (param, x, y, 1); -***** test stk_expcov_aniso (param, x, y, 2); -***** error stk_expcov_aniso (param, x, y, 3); -***** error stk_expcov_aniso (param, x, y, nan); -***** error stk_expcov_aniso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5; 2.4; 2.6]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + : --- --- + * : 0.0 0.0 + * : 0.5 0.0 + * : 1.0 0.0 + * : 0.0 0.5 + * : 0.5 0.5 + * : 1.0 0.5 + * : 0.0 1.0 + * : 0.5 1.0 + * : 1.0 1.0 + +***** error length (stk_sampling_regulargrid (7^2, 2)) % not defined +***** shared x + x = stk_factorialdesign ({[0 1], [0 1]}); +***** assert (isequal (x(2:end, :), x(2:4, :))) +***** assert (isequal (x(2, 1:end), x(2, :))) +***** assert (isequal (x(2:end, 2:end), x(2:4, 2))) +***** error x(1:end, 1:end, 1:end) +***** shared x, y + x = stk_sampling_regulargrid (3^2, 2); + y = x; +***** test %%%% vercat + z = vertcat (x, y); + assert (strcmp (class (z), 'stk_dataframe')); + assert (isequal (double (z), [double(x); double(y)])); +***** test %%%% same thing, using cat(1, ...) + z = cat (1, x, y); + assert (strcmp (class (z), 'stk_dataframe')); + assert (isequal (double (z), [double(x); double(y)])); +***** test %%%% horzcat + y.colnames = {'y1' 'y2'}; z = horzcat (x, y); + assert (strcmp (class (z), 'stk_dataframe')); + assert (isequal (double (z), [double(x) double(y)])); +***** test %%%% same thing, using cat (2, ...) + z = cat (2, x, y); + assert (strcmp (class (z), 'stk_dataframe')); + assert (isequal (double (z), [double(x) double(y)])); +***** error cat (3, x, y) +***** shared x, t + x = stk_sampling_regulargrid (3^2, 2); + t = double (x); +***** assert (isequal (apply (x, 1, @sum), sum (t, 1))) +***** assert (isequal (apply (x, 2, @sum), sum (t, 2))) +***** error u = apply (x, 3, @sum); +***** assert (isequal (apply (x, 1, @min, []), min (t, [], 1))) +***** assert (isequal (apply (x, 2, @min, []), min (t, [], 2))) +***** error u = apply (x, 3, @min, []); +***** assert (isequal (min (x), min (t))) +***** assert (isequal (max (x), max (t))) +***** assert (isequal (std (x), std (t))) +***** assert (isequal (var (x), var (t))) +***** assert (isequal (sum (x), sum (t))) +***** assert (isequal (mean (x), mean (t))) +***** assert (isequal (mode (x), mode (t))) +***** assert (isequal (prod (x), prod (t))) +***** assert (isequal (median (x), median (t))) +***** shared x1, x2, x3, u1, u2, u3 + x1 = stk_sampling_regulargrid ([4 3], 2); u1 = double (x1); + x2 = stk_sampling_regulargrid ([3 4], 2); u2 = double (x2); + x3 = x1 + 1; u3 = u1 + 1; ***** test - K1 = stk_expcov_aniso (param, x, y); - K2 = stk_expcov_aniso (param, x, y, -1); - assert (isequal (size(K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + z = bsxfun (@plus, x1, u2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) ***** test - for i = 1:(dim + 1), - dK = stk_expcov_aniso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + z = bsxfun (@plus, u1, x2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); + z = bsxfun (@plus, x1, x2); + assert (isa (z, 'stk_dataframe') && isequal (double (z), u1 + u2)) +***** test z = min (x1, x2); assert (isequal (double (z), min (u1, u2))); +***** test z = max (x1, x2); assert (isequal (double (z), max (u1, u2))); +***** error z = min (x1, x2, 1); +***** error z = max (x1, x2, 1); +***** test z = x1 + x2; assert (isequal (double (z), u1 + u2)); +***** test z = x1 - x2; assert (isequal (double (z), u1 - u2)); +***** test z = x1 .* x2; assert (isequal (double (z), u1 .* u2)); +***** test z = x3 .\ x2; assert (isequal (double (z), u3 .\ u2)); +***** test z = x2 ./ x3; assert (isequal (double (z), u2 ./ u3)); +***** test z = x3 .^ x2; assert (isequal (double (z), u3 .^ u2)); +***** test z = realpow (x3, x2); assert (isequal (double (z), realpow (u3, u2))); +***** test z = (x1 == x2); assert (isequal (double (z), (u1 == u2))); +***** test z = (x1 ~= x2); assert (isequal (double (z), (u1 ~= u2))); +***** test z = (x1 <= x2); assert (isequal (double (z), (u1 <= u2))); +***** test z = (x1 >= x2); assert (isequal (double (z), (u1 >= u2))); +***** test z = (x1 < x2); assert (isequal (double (z), (u1 < u2))); +***** test z = (x1 > x2); assert (isequal (double (z), (u1 > u2))); +***** test z = x1 & x2; assert (isequal (double (z), u1 & u2)); +***** test z = x1 | x2; assert (isequal (double (z), u1 | u2)); +***** test z = xor (x1, x2); assert (isequal (double (z), xor (u1, u2))); +***** shared x + x = stk_factorialdesign ({[0 1], [0 1 2]}); +***** assert (strcmp (class (x'), 'stk_dataframe')) +***** assert (strcmp (class (x.'), 'stk_dataframe')) +60 tests, 60 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/fieldnames.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/fieldnames.m +***** test + x = stk_factorialdesign ({0:1, 3:5}, {'u' 'v'}); + fn1 = sort (fieldnames (x)); + fn2 = {'colnames'; 'data'; 'info'; 'levels'; ... + 'rownames'; 'sample_size'; 'stk_dataframe'; 'u'; 'v'}; + assert (isequal (fn1, fn2)); +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/ismember.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/ismember.m +***** shared A, B, BB, b - K1 = stk_expcov_aniso (param, x, y); - K2 = stk_expcov_aniso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); + i_max = 10; n = 100; d = 5; - for i = 1:(dim + 1), - dK1 = stk_expcov_aniso (param, x, y, i); - dK2 = stk_expcov_aniso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -20 tests, 20 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_expcov_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_expcov_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error K = stk_expcov_iso ([param; 1.234], x, y); -***** error stk_expcov_iso (); -***** error stk_expcov_iso (param); -***** error stk_expcov_iso (param, x); -***** test stk_expcov_iso (param, x, y); -***** test stk_expcov_iso (param, x, y, -1); -***** test stk_expcov_iso (param, x, y, -1, false); -***** error stk_expcov_iso (param, x, y, -2); -***** test stk_expcov_iso (param, x, y, -1); -***** error stk_expcov_iso (param, x, y, 0); -***** test stk_expcov_iso (param, x, y, 1); -***** test stk_expcov_iso (param, x, y, 2); -***** error stk_expcov_iso (param, x, y, 3); -***** error stk_expcov_iso (param, x, y, nan); -***** error stk_expcov_iso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); -***** test - K1 = stk_expcov_iso (param, x, y); - K2 = stk_expcov_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); -***** test - for i = 1:2, - dK = stk_expcov_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end -***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); + A = randi (i_max, n, d); - K1 = stk_expcov_iso (param, x, y); - K2 = stk_expcov_iso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); + levels = repmat ({1:i_max}, 1, d); + levels{4} = 1:2:i_max; + B = stk_factorialdesign (levels); - for i = 1:2, - dK1 = stk_expcov_iso (param, x, y, i); - dK2 = stk_expcov_iso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped -[inst/covfcs/stk_gausscov_iso.m] ->>>>> /build/reproducible-path/octave-stk-2.8.1/inst/covfcs/stk_gausscov_iso.m -***** shared param, x, y - dim = 1; - param = log ([1.0; 2.5]); - x = stk_sampling_randunif (5, dim); - y = stk_sampling_randunif (5, dim); -***** error K = stk_gausscov_iso ([param; 1.234], x, y); -***** error stk_gausscov_iso (); -***** error stk_gausscov_iso (param); -***** error stk_gausscov_iso (param, x); -***** test stk_gausscov_iso (param, x, y); -***** test stk_gausscov_iso (param, x, y, -1); -***** test stk_gausscov_iso (param, x, y, -1, false); -***** error stk_gausscov_iso (param, x, y, -2); -***** test stk_gausscov_iso (param, x, y, -1); -***** error stk_gausscov_iso (param, x, y, 0); -***** test stk_gausscov_iso (param, x, y, 1); -***** test stk_gausscov_iso (param, x, y, 2); -***** error stk_gausscov_iso (param, x, y, 3); -***** error stk_gausscov_iso (param, x, y, nan); -***** error stk_gausscov_iso (param, x, y, inf); -***** shared dim, param, x, y, nx, ny - dim = 3; - param = log ([1.0; 2.5]); - nx = 4; ny = 10; - x = stk_sampling_randunif (nx, dim); - y = stk_sampling_randunif (ny, dim); + BB = double (B); +***** test b = ismember (A, B); +***** assert (isequal (b, ismember (A, BB))); +***** test b = ismember (A, B, 'rows'); +***** assert (isequal (b, ismember (A, BB, 'rows'))); +4 tests, 4 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/ndgrid.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/ndgrid.m +***** shared data + data = stk_factorialdesign ({[0 1], [5 6 7]}); +***** test % nargout = 0 + ndgrid (data); + assert (isequal (ans, [0 0 0; 1 1 1])); +***** test % nargout = 1 + x = ndgrid (data); + assert (isequal (x, [0 0 0; 1 1 1])); +***** test % nargout = 2 + [x, y] = ndgrid (data); + assert (isequal ({x, y}, {[0 0 0; 1 1 1], [5 6 7; 5 6 7]})); +***** error % nargout = 3 + [x, y, z] = ndgrid (data); ***** test - K1 = stk_gausscov_iso (param, x, y); - K2 = stk_gausscov_iso (param, x, y, -1); - assert (isequal (size (K1), [nx ny])); - assert (stk_isequal_tolabs (K1, K2)); + data = stk_factorialdesign ({[], []}); + [x, y] = ndgrid (data); + assert (isequal ({x, y}, {[], []})); ***** test - for i = 1:2, - dK = stk_gausscov_iso (param, x, y, i); - assert (isequal (size (dK), [nx ny])); - end + data = stk_factorialdesign ({[1:3]}); + x = ndgrid (data); + assert (isequal (x, [1; 2; 3])); +6 tests, 6 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/stk_normalize.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_normalize.m ***** test - n = 7; - x = stk_sampling_randunif (n, dim); - y = stk_sampling_randunif (n, dim); - - K1 = stk_gausscov_iso (param, x, y); - K2 = stk_gausscov_iso (param, x, y, -1, true); - assert (isequal (size (K1), [n n])); - assert (stk_isequal_tolabs (K2, diag (K1))); - - for i = 1:2, - dK1 = stk_gausscov_iso (param, x, y, i); - dK2 = stk_gausscov_iso (param, x, y, i, true); - assert (isequal (size (dK1), [n n])); - assert (stk_isequal_tolabs (dK2, diag (dK1))); - end -18 tests, 18 passed, 0 known failure, 0 skipped + x = stk_factorialdesign ({[1 2], [5 6]}); + y = stk_factorialdesign ({[0 1], [0 1]}); + assert (stk_isequal_tolabs (stk_normalize (x), y)) +1 test, 1 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/stk_boundingbox.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_boundingbox.m +***** shared x, y, cn + cn = {'a', 'b', 'c'}; + x = stk_factorialdesign ({[1 2], [3 4 5], [0 2 8]}, cn); +***** error y = stk_boundingbox (); +***** test y = stk_boundingbox (x); +***** assert (isequal (y, stk_hrect ([1 3 0; 2 5 8], cn))); +3 tests, 3 passed, 0 known failure, 0 skipped +[inst/arrays/@stk_factorialdesign/stk_rescale.m] +>>>>> /build/reproducible-path/octave-stk-2.8.1/inst/arrays/@stk_factorialdesign/stk_rescale.m +***** test + x = stk_factorialdesign ({[1 2], [5 6]}); + y = stk_factorialdesign ({[0 3], [0 3]}); + z = stk_rescale (x, [1 5; 2 6], [0 0; 3 3]); + assert (stk_isequal_tolabs (y, z)) +1 test, 1 passed, 0 known failure, 0 skipped Checking C++ files ... Done running the unit tests. Summary: 1558 tests, 1558 passed, 0 known failures, 0 skipped @@ -11992,12 +10876,14 @@ dpkg-buildpackage: info: binary-only upload (no source included) dpkg-genchanges: info: not including original source code in upload I: copying local configuration +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/B01_cleanup starting +I: user script /srv/workspace/pbuilder/49101/tmp/hooks/B01_cleanup finished I: unmounting dev/ptmx filesystem I: unmounting dev/pts filesystem I: unmounting dev/shm filesystem I: unmounting proc filesystem I: unmounting sys filesystem I: cleaning the build env -I: removing directory /srv/workspace/pbuilder/15186 and its subdirectories -I: Current time: Mon Nov 18 07:40:51 -12 2024 -I: pbuilder-time-stamp: 1731958851 +I: removing directory /srv/workspace/pbuilder/49101 and its subdirectories +I: Current time: Mon Dec 22 16:23:48 +14 2025 +I: pbuilder-time-stamp: 1766370228