Running as unit: rb-build-arm64_5-79244.service ==================================================================================== Tue Jan 21 10:11:51 UTC 2025 - running /srv/jenkins/bin/reproducible_build.sh (for job reproducible_builder_arm64_5) on jenkins, called using "codethink03-arm64 codethink01-arm64" as arguments. Tue Jan 21 10:11:51 UTC 2025 - actually running "reproducible_build.sh" (md5sum 68e686e434c9ab7bc3ec047d8b309cbc) as "/tmp/jenkins-script-EgZfAB8t" $ git clone https://salsa.debian.org/qa/jenkins.debian.net.git ; more CONTRIBUTING Tue Jan 21 10:11:51 UTC 2025 - checking /var/lib/jenkins/offline_nodes if codethink03-arm64.debian.net is marked as down. Tue Jan 21 10:11:51 UTC 2025 - checking via ssh if codethink03-arm64.debian.net is up. removed '/tmp/read-only-fs-test-Zbfe3s' Tue Jan 21 10:11:52 UTC 2025 - checking /var/lib/jenkins/offline_nodes if codethink01-arm64.debian.net is marked as down. Tue Jan 21 10:11:52 UTC 2025 - checking via ssh if codethink01-arm64.debian.net is up. removed '/tmp/read-only-fs-test-hjPIQu' ok, let's check if pyusid is building anywhere yet… ok, pyusid is not building anywhere… UPDATE 1 ============================================================================= Initialising reproducibly build of pyusid in trixie on arm64 on jenkins now. 1st build will be done on codethink03-arm64.debian.net. 2nd build will be done on codethink01-arm64.debian.net. ============================================================================= Tue Jan 21 10:12:03 UTC 2025 I: starting to build pyusid/trixie/arm64 on jenkins on '2025-01-21 10:11' Tue Jan 21 10:12:03 UTC 2025 I: The jenkins build log is/was available at https://jenkins.debian.net/userContent/reproducible/debian/build_service/arm64_5/79244/console.log 1737454323 arm64 trixie pyusid Tue Jan 21 10:12:03 UTC 2025 I: Downloading source for trixie/pyusid=0.0.12-2 --2025-01-21 10:12:03-- http://deb.debian.org/debian/pool/main/p/pyusid/pyusid_0.0.12-2.dsc Connecting to 46.16.76.132:3128... connected. Proxy request sent, awaiting response... 200 OK Length: 2169 (2.1K) [text/prs.lines.tag] Saving to: ‘pyusid_0.0.12-2.dsc’ 0K .. 100% 305M=0s 2025-01-21 10:12:03 (305 MB/s) - ‘pyusid_0.0.12-2.dsc’ saved [2169/2169] --2025-01-21 10:12:03-- http://deb.debian.org/debian/pool/main/p/pyusid/pyusid_0.0.12-2.dsc Connecting to 46.16.76.132:3128... connected. Proxy request sent, awaiting response... 200 OK Length: 2169 (2.1K) [text/prs.lines.tag] Saving to: ‘pyusid_0.0.12-2.dsc’ 0K .. 100% 305M=0s 2025-01-21 10:12:03 (305 MB/s) - ‘pyusid_0.0.12-2.dsc’ saved [2169/2169] Tue Jan 21 10:12:03 UTC 2025 I: pyusid_0.0.12-2.dsc -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA512 Format: 3.0 (quilt) Source: pyusid Binary: python3-pyusid Architecture: all Version: 0.0.12-2 Maintainer: Debian PaN Maintainers Uploaders: Debian Python Team , Roland Mas Homepage: https://pycroscopy.github.io/pyUSID/about.html Standards-Version: 4.6.2.0 Vcs-Browser: https://salsa.debian.org/python-team/packages/pyusid Vcs-Git: https://salsa.debian.org/python-team/packages/pyusid.git Testsuite: autopkgtest-pkg-pybuild Build-Depends: debhelper-compat (= 13), dh-python, python3-all, python3-setuptools, pybuild-plugin-pyproject, python3-h5py, python3-numpy, python3-pil, python3-sidpy Package-List: python3-pyusid deb python optional arch=all Checksums-Sha1: 916696176ba96f7aefdd02d4076c24ffcf218446 54403049 pyusid_0.0.12.orig.tar.gz dd6e144bb157da8c6f18409a0cbead76612bf010 2600 pyusid_0.0.12-2.debian.tar.xz Checksums-Sha256: 303e4a348d572d5941ba61f16274653915b1dc19b3abdf749a243404c1997a1c 54403049 pyusid_0.0.12.orig.tar.gz 43a1df70d77f3cd34ef5fa42ba1fdad9ee78275eb4e19312a332c867bbd509bf 2600 pyusid_0.0.12-2.debian.tar.xz Files: c862536fd3dcdb5ba66a1d6d425d410a 54403049 pyusid_0.0.12.orig.tar.gz ccfcde97c30ebfaaf787d40691e2bfc5 2600 pyusid_0.0.12-2.debian.tar.xz -----BEGIN PGP SIGNATURE----- iQIzBAEBCgAdFiEEtBU2D1kett1zr/uD0w3s0lmTIvwFAmZAwWkACgkQ0w3s0lmT IvyAWg//fHqeSRyna1jZ1mEnMSlGzFTHk2Zi+7fimnc+1WoEclYWom97upUaEM/t 5+WU8eVhPeZX+DLZ85FEYe84sdlAn5FvrCb/E5w5S88a09A0ErWMOg7hwUV44/n6 i/j8v5HCJtpKColRWPjGJBhuF0h50yKIf310FvdgAaXFJEp5LRecyYJJcmwaMyRU YChF/l8fpQ7J5raODARPXYyeQ6MXm31nGz84D0hfdix1JOl5isz0sHn9EdOJn+le bK2f4WpLPUC9ZxCS0lr6bNwJK1Gprhww3BNoE4q3B8gI2KH1i6iOHhiwnm5F9G0S 4yxsKhOUP2+WnrYmNz/XftlsDIlB/RiFc44NNSeN0RMnoqhwsBD2pQYK5MixUDCx HFz0kMkYFAASXZaVOzjzG1fu/ZthEqcnCmkxN5EE6f8SkcHkg8ojKHD+LtYFR3ti WOzwYdbB/6tUVahi0WXJ/3rKtbEkSOEfxRzrLThR/zC5vJZ/2e6/2mrnusxtJfqd VejTVpXrwY+eRitsNOYYQCrPmhiK7LEMw5qGYThcBGXirKoTisWKTi5QRa4QXFeK /E1BdZZExwRRmHAbrOCSq1oShJUOK5mnrhaGrUMhpQZ4flKY8a1LqzAT2UUNgIpX 6dWM2PkMLtb7LUVV+u3CWsX+PvJUs7+Zf/q86YsFtUl884ouvY0= =45l5 -----END PGP SIGNATURE----- Tue Jan 21 10:12:03 UTC 2025 I: Checking whether the package is not for us Tue Jan 21 10:12:03 UTC 2025 I: Starting 1st build on remote node codethink03-arm64.debian.net. Tue Jan 21 10:12:03 UTC 2025 I: Preparing to do remote build '1' on codethink03-arm64.debian.net. Tue Jan 21 10:12:03 UTC 2025 - checking /var/lib/jenkins/offline_nodes if codethink03-arm64.debian.net is marked as down. Tue Jan 21 10:12:03 UTC 2025 - checking via ssh if codethink03-arm64.debian.net is up. removed '/tmp/read-only-fs-test-mrJsER' ==================================================================================== Mon Feb 23 16:35:04 UTC 2026 - running /srv/jenkins/bin/reproducible_build.sh (for job /srv/jenkins/bin/reproducible_build.sh) on codethink03-arm64, called using "1 pyusid trixie /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn 0.0.12-2" as arguments. Mon Feb 23 16:35:04 UTC 2026 - actually running "reproducible_build.sh" (md5sum 68e686e434c9ab7bc3ec047d8b309cbc) as "/tmp/jenkins-script-zkWuL29N" $ git clone https://salsa.debian.org/qa/jenkins.debian.net.git ; more CONTRIBUTING Mon Feb 23 16:35:05 UTC 2026 I: Downloading source for trixie/pyusid=0.0.12-2 Reading package lists... NOTICE: 'pyusid' packaging is maintained in the 'Git' version control system at: https://salsa.debian.org/python-team/packages/pyusid.git Please use: git clone https://salsa.debian.org/python-team/packages/pyusid.git to retrieve the latest (possibly unreleased) updates to the package. Need to get 54.4 MB of source archives. Get:1 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (dsc) [2169 B] Get:2 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (tar) [54.4 MB] Get:3 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (diff) [2600 B] Fetched 54.4 MB in 1s (40.3 MB/s) Download complete and in download only mode Reading package lists... NOTICE: 'pyusid' packaging is maintained in the 'Git' version control system at: https://salsa.debian.org/python-team/packages/pyusid.git Please use: git clone https://salsa.debian.org/python-team/packages/pyusid.git to retrieve the latest (possibly unreleased) updates to the package. Need to get 54.4 MB of source archives. Get:1 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (dsc) [2169 B] Get:2 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (tar) [54.4 MB] Get:3 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (diff) [2600 B] Fetched 54.4 MB in 1s (40.3 MB/s) Download complete and in download only mode ============================================================================= Building pyusid in trixie on arm64 on codethink03-arm64 now. Date: Mon Feb 23 16:35:06 GMT 2026 Date UTC: Mon Feb 23 16:35:06 UTC 2026 ============================================================================= W: /root/.pbuilderrc does not exist I: Logging to b1/build.log I: pbuilder: network access will be disabled during build I: Current time: Mon Feb 23 04:35:06 -12 2026 I: pbuilder-time-stamp: 1771864506 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/trixie-reproducible-base.tgz] I: copying local configuration W: --override-config is not set; not updating apt.conf Read the manpage for details. I: mounting /proc filesystem I: mounting /sys filesystem I: creating /{dev,run}/shm I: mounting /dev/pts filesystem I: redirecting /dev/ptmx to /dev/pts/ptmx I: policy-rc.d already exists I: Copying source file I: copying [pyusid_0.0.12-2.dsc] I: copying [./pyusid_0.0.12.orig.tar.gz] I: copying [./pyusid_0.0.12-2.debian.tar.xz] I: Extracting source dpkg-source: warning: cannot verify inline signature for ./pyusid_0.0.12-2.dsc: unsupported subcommand dpkg-source: info: extracting pyusid in pyusid-0.0.12 dpkg-source: info: unpacking pyusid_0.0.12.orig.tar.gz dpkg-source: info: unpacking pyusid_0.0.12-2.debian.tar.xz dpkg-source: info: using patch list from debian/patches/series dpkg-source: info: applying 0001-Remove-requirement-for-six-module.patch I: Not using root during the build. I: Installing the build-deps I: user script /srv/workspace/pbuilder/1266995/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='arm64' DEBIAN_FRONTEND='noninteractive' DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=12 ' DISTRIBUTION='trixie' HOME='/root' HOST_ARCH='arm64' IFS=' ' INVOCATION_ID='fd1b7fff5c924e7eb4682dd63d75ade9' LANG='C' LANGUAGE='en_US:en' LC_ALL='C' 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='1266995' PS1='# ' PS2='> ' 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.GzEM6mWn/pbuilderrc_riQL --distribution trixie --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1 --logfile b1/build.log pyusid_0.0.12-2.dsc' SUDO_GID='109' SUDO_UID='104' SUDO_USER='jenkins' TERM='unknown' TZ='/usr/share/zoneinfo/Etc/GMT+12' USER='root' _='/usr/bin/systemd-run' http_proxy='http://192.168.101.4:3128' I: uname -a Linux codethink03-arm64 6.1.0-30-cloud-arm64 #1 SMP Debian 6.1.124-1 (2025-01-12) aarch64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Nov 22 2024 /bin -> usr/bin I: user script /srv/workspace/pbuilder/1266995/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy Version: 0.invalid.0 Architecture: arm64 Maintainer: Debian Pbuilder Team Description: Dummy package to satisfy dependencies with aptitude - created by pbuilder This package was created automatically by pbuilder to satisfy the build-dependencies of the package being currently built. Depends: debhelper-compat (= 13), dh-python, python3-all, python3-setuptools, pybuild-plugin-pyproject, python3-h5py, python3-numpy, python3-pil, python3-sidpy dpkg-deb: building package 'pbuilder-satisfydepends-dummy' in '/tmp/satisfydepends-aptitude/pbuilder-satisfydepends-dummy.deb'. Selecting previously unselected package pbuilder-satisfydepends-dummy. (Reading database ... 19970 files and directories currently installed.) Preparing to unpack .../pbuilder-satisfydepends-dummy.deb ... Unpacking pbuilder-satisfydepends-dummy (0.invalid.0) ... dpkg: pbuilder-satisfydepends-dummy: dependency problems, but configuring anyway as you requested: pbuilder-satisfydepends-dummy depends on debhelper-compat (= 13); however: Package debhelper-compat is not installed. pbuilder-satisfydepends-dummy depends on dh-python; however: Package dh-python is not installed. pbuilder-satisfydepends-dummy depends on python3-all; however: Package python3-all is not installed. pbuilder-satisfydepends-dummy depends on python3-setuptools; however: Package python3-setuptools is not installed. pbuilder-satisfydepends-dummy depends on pybuild-plugin-pyproject; however: Package pybuild-plugin-pyproject is not installed. pbuilder-satisfydepends-dummy depends on python3-h5py; however: Package python3-h5py is not installed. pbuilder-satisfydepends-dummy depends on python3-numpy; however: Package python3-numpy is not installed. pbuilder-satisfydepends-dummy depends on python3-pil; however: Package python3-pil is not installed. pbuilder-satisfydepends-dummy depends on python3-sidpy; however: Package python3-sidpy is not installed. Setting up pbuilder-satisfydepends-dummy (0.invalid.0) ... Reading package lists... Building dependency tree... Reading state information... Initializing package states... Writing extended state information... Building tag database... pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) The following NEW packages will be installed: autoconf{a} automake{a} autopoint{a} autotools-dev{a} blt{a} bsdextrautils{a} ca-certificates{a} debhelper{a} dh-autoreconf{a} dh-python{a} dh-strip-nondeterminism{a} dwz{a} file{a} fontconfig-config{a} fonts-dejavu-core{a} fonts-dejavu-mono{a} fonts-font-awesome{a} fonts-glyphicons-halflings{a} fonts-lyx{a} gdb{a} gettext{a} gettext-base{a} groff-base{a} intltool-debian{a} libaec0{a} libarchive-zip-perl{a} libbabeltrace1{a} libblas3{a} libbrotli1{a} libcom-err2{a} libcurl3t64-gnutls{a} libcurl4t64{a} libdebhelper-perl{a} libdebuginfod-common{a} libdebuginfod1t64{a} libdeflate0{a} libdw1t64{a} libelf1t64{a} libexpat1{a} libffi8{a} libfile-stripnondeterminism-perl{a} libfontconfig1{a} libfreetype6{a} libfribidi0{a} libgcrypt20{a} libgfortran5{a} libglib2.0-0t64{a} libgnutls30t64{a} libgpg-error0{a} libgraphite2-3{a} libgssapi-krb5-2{a} libharfbuzz0b{a} libhdf5-310{a} libhdf5-hl-310{a} libicu72{a} libidn2-0{a} libimagequant0{a} libjbig0{a} libjpeg62-turbo{a} libjs-bootstrap{a} libjs-jquery{a} libjs-jquery-ui{a} libjson-c5{a} libk5crypto3{a} libkeyutils1{a} libkrb5-3{a} libkrb5support0{a} liblapack3{a} liblbfgsb0{a} liblcms2-2{a} libldap2{a} liblerc4{a} liblzf1{a} libmagic-mgc{a} libmagic1t64{a} libnghttp2-14{a} libnghttp3-9{a} libngtcp2-16{a} libngtcp2-crypto-gnutls8{a} libnorm1t64{a} libnsl2{a} libopenjp2-7{a} libp11-kit0{a} libpgm-5.3-0t64{a} libpipeline1{a} libpng16-16t64{a} libproc2-0{a} libpsl5t64{a} libpython3-stdlib{a} libpython3.12-minimal{a} libpython3.12-stdlib{a} libpython3.13{a} libpython3.13-minimal{a} libpython3.13-stdlib{a} libqhull-r8.0{a} libraqm0{a} libreadline8t64{a} librtmp1{a} libsasl2-2{a} libsasl2-modules-db{a} libsharpyuv0{a} libsodium23{a} libsource-highlight-common{a} libsource-highlight4t64{a} libssh2-1t64{a} libsymspg2{a} libsz2{a} libtasn1-6{a} libtcl8.6{a} libtext-charwidth-perl{a} libtext-wrapi18n-perl{a} libtiff6{a} libtirpc-common{a} libtirpc3t64{a} libtk8.6{a} libtool{a} libuchardet0{a} libunistring5{a} libwebp7{a} libwebpdemux2{a} libwebpmux3{a} libx11-6{a} libx11-data{a} libxau6{a} libxcb1{a} libxdmcp6{a} libxext6{a} libxft2{a} libxml2{a} libxrender1{a} libxslt1.1{a} libxss1{a} libyaml-0-2{a} libzmq5{a} m4{a} man-db{a} media-types{a} netbase{a} openssl{a} po-debconf{a} procps{a} pybuild-plugin-pyproject{a} python-matplotlib-data{a} python3{a} python3-all{a} python3-ase{a} python3-asttokens{a} python3-attr{a} python3-autocommand{a} python3-brotli{a} python3-build{a} python3-cffi-backend{a} python3-click{a} python3-cloudpickle{a} python3-comm{a} python3-contourpy{a} python3-coverage{a} python3-cycler{a} python3-cytoolz{a} python3-dask{a} python3-dateutil{a} python3-debugpy{a} python3-decorator{a} python3-distributed{a} python3-executing{a} python3-fonttools{a} python3-fs{a} python3-fsspec{a} python3-h5py{a} python3-h5py-serial{a} python3-inflect{a} python3-installer{a} python3-ipykernel{a} python3-ipython{a} python3-ipywidgets{a} python3-jaraco.context{a} python3-jaraco.functools{a} python3-jaraco.text{a} python3-jedi{a} python3-jinja2{a} python3-joblib{a} python3-jupyter-client{a} python3-jupyter-core{a} python3-kiwisolver{a} python3-locket{a} python3-lxml{a} python3-lz4{a} python3-markupsafe{a} python3-matplotlib{a} python3-matplotlib-inline{a} python3-minimal{a} python3-more-itertools{a} python3-mpmath{a} python3-msgpack{a} python3-nest-asyncio{a} python3-numpy{a} python3-packaging{a} python3-parso{a} python3-partd{a} python3-pexpect{a} python3-pil{a} python3-pil.imagetk{a} python3-pkg-resources{a} python3-platformdirs{a} python3-prompt-toolkit{a} python3-psutil{a} python3-ptyprocess{a} python3-pure-eval{a} python3-pygments{a} python3-pyparsing{a} python3-pyproject-hooks{a} python3-scipy{a} python3-setuptools{a} python3-sidpy{a} python3-sklearn{a} python3-sklearn-lib{a} python3-sortedcontainers{a} python3-spglib{a} python3-stack-data{a} python3-sympy{a} python3-tblib{a} python3-threadpoolctl{a} python3-tk{a} python3-toml{a} python3-toolz{a} python3-tornado{a} python3-traitlets{a} python3-typeguard{a} python3-typeshed{a} python3-typing-extensions{a} python3-tz{a} python3-ufolib2{a} python3-urllib3{a} python3-wcwidth{a} python3-wheel{a} python3-yaml{a} python3-zict{a} python3-zipp{a} python3-zmq{a} python3.12{a} python3.12-minimal{a} python3.12-tk{a} python3.13{a} python3.13-minimal{a} python3.13-tk{a} readline-common{a} sensible-utils{a} tk8.6-blt2.5{a} tzdata{a} ucf{a} unicode-data{a} x11-common{a} The following packages are RECOMMENDED but will NOT be installed: curl git isympy-common javascript-common krb5-locales libarchive-cpio-perl libc6-dbg libglib2.0-data libgpg-error-l10n libldap-common libltdl-dev libmail-sendmail-perl libsasl2-modules linux-sysctl-defaults lynx psmisc publicsuffix python3-babel python3-blosc python3-bs4 python3-cssselect python3-dropbox python3-html5lib python3-libarchive-c python3-olefile python3-pandas python3-paramiko python3-pooch python3-pygit2 python3-pytest python3-requests python3-simplejson shared-mime-info wget xdg-user-dirs 0 packages upgraded, 252 newly installed, 0 to remove and 0 not upgraded. Need to get 134 MB of archives. After unpacking 656 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main arm64 libtext-charwidth-perl arm64 0.04-11+b4 [9652 B] Get: 2 http://deb.debian.org/debian trixie/main arm64 libtext-wrapi18n-perl all 0.06-10 [8808 B] Get: 3 http://deb.debian.org/debian trixie/main arm64 libproc2-0 arm64 2:4.0.4-6 [62.3 kB] Get: 4 http://deb.debian.org/debian trixie/main arm64 procps arm64 2:4.0.4-6 [872 kB] Get: 5 http://deb.debian.org/debian trixie/main arm64 sensible-utils all 0.0.24 [24.8 kB] Get: 6 http://deb.debian.org/debian trixie/main arm64 ucf all 3.0048 [42.0 kB] Get: 7 http://deb.debian.org/debian trixie/main arm64 libdebuginfod-common all 0.192-4 [23.7 kB] Get: 8 http://deb.debian.org/debian trixie/main arm64 libpython3.12-minimal arm64 3.12.8-5 [810 kB] Get: 9 http://deb.debian.org/debian trixie/main arm64 libexpat1 arm64 2.6.4-1 [90.7 kB] Get: 10 http://deb.debian.org/debian trixie/main arm64 python3.12-minimal arm64 3.12.8-5 [1934 kB] Get: 11 http://deb.debian.org/debian trixie/main arm64 python3-minimal arm64 3.12.8-1 [26.9 kB] Get: 12 http://deb.debian.org/debian trixie/main arm64 media-types all 10.1.0 [26.9 kB] Get: 13 http://deb.debian.org/debian trixie/main arm64 netbase all 6.4 [12.8 kB] Get: 14 http://deb.debian.org/debian trixie/main arm64 tzdata all 2024b-6 [257 kB] Get: 15 http://deb.debian.org/debian trixie/main arm64 libffi8 arm64 3.4.6-1 [20.9 kB] Get: 16 http://deb.debian.org/debian trixie/main arm64 libkrb5support0 arm64 1.21.3-3 [32.1 kB] Get: 17 http://deb.debian.org/debian trixie/main arm64 libcom-err2 arm64 1.47.2-1 [23.9 kB] Get: 18 http://deb.debian.org/debian trixie/main arm64 libk5crypto3 arm64 1.21.3-3 [80.8 kB] Get: 19 http://deb.debian.org/debian trixie/main arm64 libkeyutils1 arm64 1.6.3-4 [9352 B] Get: 20 http://deb.debian.org/debian trixie/main arm64 libkrb5-3 arm64 1.21.3-3 [310 kB] Get: 21 http://deb.debian.org/debian trixie/main arm64 libgssapi-krb5-2 arm64 1.21.3-3 [126 kB] Get: 22 http://deb.debian.org/debian trixie/main arm64 libtirpc-common all 1.3.4+ds-1.3 [10.9 kB] Get: 23 http://deb.debian.org/debian trixie/main arm64 libtirpc3t64 arm64 1.3.4+ds-1.3+b1 [78.7 kB] Get: 24 http://deb.debian.org/debian trixie/main arm64 libnsl2 arm64 1.3.0-3+b3 [37.9 kB] Get: 25 http://deb.debian.org/debian trixie/main arm64 readline-common all 8.2-6 [69.4 kB] Get: 26 http://deb.debian.org/debian trixie/main arm64 libreadline8t64 arm64 8.2-6 [159 kB] Get: 27 http://deb.debian.org/debian trixie/main arm64 libpython3.12-stdlib arm64 3.12.8-5 [1904 kB] Get: 28 http://deb.debian.org/debian trixie/main arm64 python3.12 arm64 3.12.8-5 [677 kB] Get: 29 http://deb.debian.org/debian trixie/main arm64 libpython3-stdlib arm64 3.12.8-1 [9788 B] Get: 30 http://deb.debian.org/debian trixie/main arm64 python3 arm64 3.12.8-1 [27.9 kB] Get: 31 http://deb.debian.org/debian trixie/main arm64 libpython3.13-minimal arm64 3.13.1-3 [852 kB] Get: 32 http://deb.debian.org/debian trixie/main arm64 python3.13-minimal arm64 3.13.1-3 [1990 kB] Get: 33 http://deb.debian.org/debian trixie/main arm64 openssl arm64 3.4.0-2 [1385 kB] Get: 34 http://deb.debian.org/debian trixie/main arm64 ca-certificates all 20241223 [164 kB] Get: 35 http://deb.debian.org/debian trixie/main arm64 libmagic-mgc arm64 1:5.45-3+b1 [314 kB] Get: 36 http://deb.debian.org/debian trixie/main arm64 libmagic1t64 arm64 1:5.45-3+b1 [102 kB] Get: 37 http://deb.debian.org/debian trixie/main arm64 file arm64 1:5.45-3+b1 [43.4 kB] Get: 38 http://deb.debian.org/debian trixie/main arm64 gettext-base arm64 0.22.5-4 [198 kB] Get: 39 http://deb.debian.org/debian trixie/main arm64 libuchardet0 arm64 0.0.8-1+b2 [69.2 kB] Get: 40 http://deb.debian.org/debian trixie/main arm64 groff-base arm64 1.23.0-7 [1129 kB] Get: 41 http://deb.debian.org/debian trixie/main arm64 bsdextrautils arm64 2.40.4-1 [91.6 kB] Get: 42 http://deb.debian.org/debian trixie/main arm64 libpipeline1 arm64 1.5.8-1 [40.2 kB] Get: 43 http://deb.debian.org/debian trixie/main arm64 man-db arm64 2.13.0-1 [1404 kB] Get: 44 http://deb.debian.org/debian trixie/main arm64 m4 arm64 1.4.19-5 [284 kB] Get: 45 http://deb.debian.org/debian trixie/main arm64 autoconf all 2.72-3 [493 kB] Get: 46 http://deb.debian.org/debian trixie/main arm64 autotools-dev all 20220109.1 [51.6 kB] Get: 47 http://deb.debian.org/debian trixie/main arm64 automake all 1:1.16.5-1.3 [823 kB] Get: 48 http://deb.debian.org/debian trixie/main arm64 autopoint all 0.22.5-4 [723 kB] Get: 49 http://deb.debian.org/debian trixie/main arm64 libtcl8.6 arm64 8.6.16+dfsg-1 [984 kB] Get: 50 http://deb.debian.org/debian trixie/main arm64 libbrotli1 arm64 1.1.0-2+b6 [297 kB] Get: 51 http://deb.debian.org/debian trixie/main arm64 libpng16-16t64 arm64 1.6.44-3 [273 kB] Get: 52 http://deb.debian.org/debian trixie/main arm64 libfreetype6 arm64 2.13.3+dfsg-1 [422 kB] Get: 53 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-mono all 2.37-8 [489 kB] Get: 54 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-core all 2.37-8 [840 kB] Get: 55 http://deb.debian.org/debian trixie/main arm64 fontconfig-config arm64 2.15.0-2 [317 kB] Get: 56 http://deb.debian.org/debian trixie/main arm64 libfontconfig1 arm64 2.15.0-2 [386 kB] Get: 57 http://deb.debian.org/debian trixie/main arm64 libxau6 arm64 1:1.0.11-1 [20.6 kB] Get: 58 http://deb.debian.org/debian trixie/main arm64 libxdmcp6 arm64 1:1.1.5-1 [27.8 kB] Get: 59 http://deb.debian.org/debian trixie/main arm64 libxcb1 arm64 1.17.0-2+b1 [143 kB] Get: 60 http://deb.debian.org/debian trixie/main arm64 libx11-data all 2:1.8.10-2 [337 kB] Get: 61 http://deb.debian.org/debian trixie/main arm64 libx11-6 arm64 2:1.8.10-2 [789 kB] Get: 62 http://deb.debian.org/debian trixie/main arm64 libxrender1 arm64 1:0.9.10-1.1+b3 [27.2 kB] Get: 63 http://deb.debian.org/debian trixie/main arm64 libxft2 arm64 2.3.6-1+b3 [51.6 kB] Get: 64 http://deb.debian.org/debian trixie/main arm64 libxext6 arm64 2:1.3.4-1+b3 [49.2 kB] Get: 65 http://deb.debian.org/debian trixie/main arm64 x11-common all 1:7.7+23.2 [216 kB] Get: 66 http://deb.debian.org/debian trixie/main arm64 libxss1 arm64 1:1.2.3-1+b3 [17.1 kB] Get: 67 http://deb.debian.org/debian trixie/main arm64 libtk8.6 arm64 8.6.16-1 [741 kB] Get: 68 http://deb.debian.org/debian trixie/main arm64 tk8.6-blt2.5 arm64 2.5.3+dfsg-7+b1 [538 kB] Get: 69 http://deb.debian.org/debian trixie/main arm64 blt arm64 2.5.3+dfsg-7+b1 [6344 B] Get: 70 http://deb.debian.org/debian trixie/main arm64 libdebhelper-perl all 13.23 [90.6 kB] Get: 71 http://deb.debian.org/debian trixie/main arm64 libtool all 2.5.4-2 [539 kB] Get: 72 http://deb.debian.org/debian trixie/main arm64 dh-autoreconf all 20 [17.1 kB] Get: 73 http://deb.debian.org/debian trixie/main arm64 libarchive-zip-perl all 1.68-1 [104 kB] Get: 74 http://deb.debian.org/debian trixie/main arm64 libfile-stripnondeterminism-perl all 1.14.0-1 [19.5 kB] Get: 75 http://deb.debian.org/debian trixie/main arm64 dh-strip-nondeterminism all 1.14.0-1 [8448 B] Get: 76 http://deb.debian.org/debian trixie/main arm64 libelf1t64 arm64 0.192-4 [189 kB] Get: 77 http://deb.debian.org/debian trixie/main arm64 dwz arm64 0.15-1+b1 [102 kB] Get: 78 http://deb.debian.org/debian trixie/main arm64 libunistring5 arm64 1.3-1 [449 kB] Get: 79 http://deb.debian.org/debian trixie/main arm64 libicu72 arm64 72.1-6 [9239 kB] Get: 80 http://deb.debian.org/debian trixie/main arm64 libxml2 arm64 2.12.7+dfsg+really2.9.14-0.2+b1 [630 kB] Get: 81 http://deb.debian.org/debian trixie/main arm64 gettext arm64 0.22.5-4 [1532 kB] Get: 82 http://deb.debian.org/debian trixie/main arm64 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 83 http://deb.debian.org/debian trixie/main arm64 po-debconf all 1.0.21+nmu1 [248 kB] Get: 84 http://deb.debian.org/debian trixie/main arm64 debhelper all 13.23 [919 kB] Get: 85 http://deb.debian.org/debian trixie/main arm64 python3-autocommand all 2.2.2-3 [13.6 kB] Get: 86 http://deb.debian.org/debian trixie/main arm64 python3-more-itertools all 10.6.0-1 [65.3 kB] Get: 87 http://deb.debian.org/debian trixie/main arm64 python3-typing-extensions all 4.12.2-2 [73.0 kB] Get: 88 http://deb.debian.org/debian trixie/main arm64 python3-typeguard all 4.4.1-1 [37.0 kB] Get: 89 http://deb.debian.org/debian trixie/main arm64 python3-inflect all 7.3.1-2 [32.4 kB] Get: 90 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.context all 6.0.0-1 [7984 B] Get: 91 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.functools all 4.1.0-1 [12.0 kB] Get: 92 http://deb.debian.org/debian trixie/main arm64 python3-pkg-resources all 75.6.0-1 [222 kB] Get: 93 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.text all 4.0.0-1 [11.4 kB] Get: 94 http://deb.debian.org/debian trixie/main arm64 python3-zipp all 3.21.0-1 [10.6 kB] Get: 95 http://deb.debian.org/debian trixie/main arm64 python3-setuptools all 75.6.0-1 [720 kB] Get: 96 http://deb.debian.org/debian trixie/main arm64 dh-python all 6.20250108 [113 kB] Get: 97 http://deb.debian.org/debian trixie/main arm64 fonts-font-awesome all 5.0.10+really4.7.0~dfsg-4.1 [517 kB] Get: 98 http://deb.debian.org/debian trixie/main arm64 fonts-glyphicons-halflings all 1.009~3.4.1+dfsg-3 [162 kB] Get: 99 http://deb.debian.org/debian trixie/main arm64 fonts-lyx all 2.4.2.1-1 [190 kB] Get: 100 http://deb.debian.org/debian trixie/main arm64 libdw1t64 arm64 0.192-4 [237 kB] Get: 101 http://deb.debian.org/debian trixie/main arm64 libglib2.0-0t64 arm64 2.82.4-2 [1413 kB] Get: 102 http://deb.debian.org/debian trixie/main arm64 libbabeltrace1 arm64 1.5.11-4+b1 [164 kB] Get: 103 http://deb.debian.org/debian trixie/main arm64 libidn2-0 arm64 2.3.7-2+b1 [127 kB] Get: 104 http://deb.debian.org/debian trixie/main arm64 libp11-kit0 arm64 0.25.5-3 [409 kB] Get: 105 http://deb.debian.org/debian trixie/main arm64 libtasn1-6 arm64 4.19.0-3+b3 [46.9 kB] Get: 106 http://deb.debian.org/debian trixie/main arm64 libgnutls30t64 arm64 3.8.8-2 [1363 kB] Get: 107 http://deb.debian.org/debian trixie/main arm64 libsasl2-modules-db arm64 2.1.28+dfsg1-8+b1 [20.3 kB] Get: 108 http://deb.debian.org/debian trixie/main arm64 libsasl2-2 arm64 2.1.28+dfsg1-8+b1 [55.7 kB] Get: 109 http://deb.debian.org/debian trixie/main arm64 libldap2 arm64 2.6.9+dfsg-1 [179 kB] Get: 110 http://deb.debian.org/debian trixie/main arm64 libnghttp2-14 arm64 1.64.0-1 [71.3 kB] Get: 111 http://deb.debian.org/debian trixie/main arm64 libnghttp3-9 arm64 1.6.0-2 [60.5 kB] Get: 112 http://deb.debian.org/debian trixie/main arm64 libngtcp2-16 arm64 1.9.1-1 [109 kB] Get: 113 http://deb.debian.org/debian trixie/main arm64 libngtcp2-crypto-gnutls8 arm64 1.9.1-1 [17.3 kB] Get: 114 http://deb.debian.org/debian trixie/main arm64 libpsl5t64 arm64 0.21.2-1.1+b1 [57.1 kB] Get: 115 http://deb.debian.org/debian trixie/main arm64 librtmp1 arm64 2.4+20151223.gitfa8646d.1-2+b5 [56.8 kB] Get: 116 http://deb.debian.org/debian trixie/main arm64 libssh2-1t64 arm64 1.11.1-1 [235 kB] Get: 117 http://deb.debian.org/debian trixie/main arm64 libcurl3t64-gnutls arm64 8.11.1-1+b1 [331 kB] Get: 118 http://deb.debian.org/debian trixie/main arm64 libjson-c5 arm64 0.18+ds-1 [45.2 kB] Get: 119 http://deb.debian.org/debian trixie/main arm64 libdebuginfod1t64 arm64 0.192-4 [31.3 kB] Get: 120 http://deb.debian.org/debian trixie/main arm64 libpython3.13-stdlib arm64 3.13.1-3 [1912 kB] Get: 121 http://deb.debian.org/debian trixie/main arm64 libpython3.13 arm64 3.13.1-3 [1971 kB] Get: 122 http://deb.debian.org/debian trixie/main arm64 libsource-highlight-common all 3.1.9-4.3 [77.5 kB] Get: 123 http://deb.debian.org/debian trixie/main arm64 libsource-highlight4t64 arm64 3.1.9-4.3+b1 [294 kB] Get: 124 http://deb.debian.org/debian trixie/main arm64 gdb arm64 15.2-1+b1 [4159 kB] Get: 125 http://deb.debian.org/debian trixie/main arm64 libaec0 arm64 1.1.3-1+b1 [22.5 kB] Get: 126 http://deb.debian.org/debian trixie/main arm64 libblas3 arm64 3.12.0-4 [98.7 kB] Get: 127 http://deb.debian.org/debian trixie/main arm64 libcurl4t64 arm64 8.11.1-1+b1 [324 kB] Get: 128 http://deb.debian.org/debian trixie/main arm64 libdeflate0 arm64 1.23-1+b1 [42.5 kB] Get: 129 http://deb.debian.org/debian trixie/main arm64 libfribidi0 arm64 1.0.16-1 [26.5 kB] Get: 130 http://deb.debian.org/debian trixie/main arm64 libgpg-error0 arm64 1.51-3 [78.5 kB] Get: 131 http://deb.debian.org/debian trixie/main arm64 libgcrypt20 arm64 1.11.0-7 [742 kB] Get: 132 http://deb.debian.org/debian trixie/main arm64 libgfortran5 arm64 14.2.0-12 [361 kB] Get: 133 http://deb.debian.org/debian trixie/main arm64 libgraphite2-3 arm64 1.3.14-2+b1 [70.4 kB] Get: 134 http://deb.debian.org/debian trixie/main arm64 libharfbuzz0b arm64 10.2.0-1 [443 kB] Get: 135 http://deb.debian.org/debian trixie/main arm64 libsz2 arm64 1.1.3-1+b1 [8044 B] Get: 136 http://deb.debian.org/debian trixie/main arm64 libhdf5-310 arm64 1.14.5+repack-3 [1155 kB] Get: 137 http://deb.debian.org/debian trixie/main arm64 libhdf5-hl-310 arm64 1.14.5+repack-3 [66.1 kB] Get: 138 http://deb.debian.org/debian trixie/main arm64 libimagequant0 arm64 2.18.0-1+b2 [34.6 kB] Get: 139 http://deb.debian.org/debian trixie/main arm64 libjbig0 arm64 2.1-6.1+b2 [30.4 kB] Get: 140 http://deb.debian.org/debian trixie/main arm64 libjpeg62-turbo arm64 1:2.1.5-3+b1 [173 kB] Get: 141 http://deb.debian.org/debian trixie/main arm64 libjs-bootstrap all 3.4.1+dfsg-3 [172 kB] Get: 142 http://deb.debian.org/debian trixie/main arm64 libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [326 kB] Get: 143 http://deb.debian.org/debian trixie/main arm64 libjs-jquery-ui all 1.13.2+dfsg-1 [250 kB] Get: 144 http://deb.debian.org/debian trixie/main arm64 liblapack3 arm64 3.12.0-4 [1812 kB] Get: 145 http://deb.debian.org/debian trixie/main arm64 liblbfgsb0 arm64 3.0+dfsg.4-1+b2 [25.6 kB] Get: 146 http://deb.debian.org/debian trixie/main arm64 liblcms2-2 arm64 2.16-2 [151 kB] Get: 147 http://deb.debian.org/debian trixie/main arm64 liblerc4 arm64 4.0.0+ds-5 [146 kB] Get: 148 http://deb.debian.org/debian trixie/main arm64 liblzf1 arm64 3.6-4+b3 [10.1 kB] Get: 149 http://deb.debian.org/debian trixie/main arm64 libnorm1t64 arm64 1.5.9+dfsg-3.1+b2 [205 kB] Get: 150 http://deb.debian.org/debian trixie/main arm64 libopenjp2-7 arm64 2.5.0-2+b4 [185 kB] Get: 151 http://deb.debian.org/debian trixie/main arm64 libpgm-5.3-0t64 arm64 5.3.128~dfsg-2.1+b1 [152 kB] Get: 152 http://deb.debian.org/debian trixie/main arm64 libqhull-r8.0 arm64 2020.2-6+b2 [229 kB] Get: 153 http://deb.debian.org/debian trixie/main arm64 libraqm0 arm64 0.10.2-1 [13.6 kB] Get: 154 http://deb.debian.org/debian trixie/main arm64 libsharpyuv0 arm64 1.5.0-0.1 [114 kB] Get: 155 http://deb.debian.org/debian trixie/main arm64 libsodium23 arm64 1.0.18-1+b2 [121 kB] Get: 156 http://deb.debian.org/debian trixie/main arm64 libsymspg2 arm64 2.5.0-1+b1 [192 kB] Get: 157 http://deb.debian.org/debian trixie/main arm64 libwebp7 arm64 1.5.0-0.1 [271 kB] Get: 158 http://deb.debian.org/debian trixie/main arm64 libtiff6 arm64 4.5.1+git230720-5 [309 kB] Get: 159 http://deb.debian.org/debian trixie/main arm64 libwebpdemux2 arm64 1.5.0-0.1 [113 kB] Get: 160 http://deb.debian.org/debian trixie/main arm64 libwebpmux3 arm64 1.5.0-0.1 [125 kB] Get: 161 http://deb.debian.org/debian trixie/main arm64 libxslt1.1 arm64 1.1.35-1.1+b1 [222 kB] Get: 162 http://deb.debian.org/debian trixie/main arm64 libyaml-0-2 arm64 0.2.5-2 [49.2 kB] Get: 163 http://deb.debian.org/debian trixie/main arm64 libzmq5 arm64 4.3.5-1+b3 [253 kB] Get: 164 http://deb.debian.org/debian trixie/main arm64 python3-packaging all 24.2-1 [55.3 kB] Get: 165 http://deb.debian.org/debian trixie/main arm64 python3-pyproject-hooks all 1.2.0-1 [11.7 kB] Get: 166 http://deb.debian.org/debian trixie/main arm64 python3-toml all 0.10.2-1 [16.2 kB] Get: 167 http://deb.debian.org/debian trixie/main arm64 python3-wheel all 0.45.1-1 [56.7 kB] Get: 168 http://deb.debian.org/debian trixie/main arm64 python3-build all 1.2.2-1 [36.0 kB] Get: 169 http://deb.debian.org/debian trixie/main arm64 python3-installer all 0.7.0+dfsg1-3 [18.6 kB] Get: 170 http://deb.debian.org/debian trixie/main arm64 pybuild-plugin-pyproject all 6.20250108 [11.6 kB] Get: 171 http://deb.debian.org/debian trixie/main arm64 python-matplotlib-data all 3.8.3-3 [2731 kB] Get: 172 http://deb.debian.org/debian trixie/main arm64 python3.13 arm64 3.13.1-3 [740 kB] Get: 173 http://deb.debian.org/debian trixie/main arm64 python3-all arm64 3.12.8-1 [1048 B] Get: 174 http://deb.debian.org/debian trixie/main arm64 python3-numpy arm64 1:1.26.4+ds-12 [3816 kB] Get: 175 http://deb.debian.org/debian trixie/main arm64 python3-decorator all 5.1.1-5 [15.1 kB] Get: 176 http://deb.debian.org/debian trixie/main arm64 python3-scipy arm64 1.14.1-3 [18.5 MB] Get: 177 http://deb.debian.org/debian trixie/main arm64 python3-spglib arm64 2.5.0-1+b1 [52.1 kB] Get: 178 http://deb.debian.org/debian trixie/main arm64 python3-dateutil all 2.9.0-3 [79.3 kB] Get: 179 http://deb.debian.org/debian trixie/main arm64 python3-pil arm64 10.4.0-1.1 [498 kB] Get: 180 http://deb.debian.org/debian trixie/main arm64 python3.12-tk arm64 3.12.8-5 [111 kB] Get: 181 http://deb.debian.org/debian trixie/main arm64 python3.13-tk arm64 3.13.1-3 [101 kB] Get: 182 http://deb.debian.org/debian trixie/main arm64 python3-tk arm64 3.13.1-1 [9464 B] Get: 183 http://deb.debian.org/debian trixie/main arm64 python3-pil.imagetk arm64 10.4.0-1.1 [79.7 kB] Get: 184 http://deb.debian.org/debian trixie/main arm64 python3-pyparsing all 3.1.2-1 [146 kB] Get: 185 http://deb.debian.org/debian trixie/main arm64 python3-contourpy arm64 1.3.1-1 [237 kB] Get: 186 http://deb.debian.org/debian trixie/main arm64 python3-cycler all 0.12.1-1 [9496 B] Get: 187 http://deb.debian.org/debian trixie/main arm64 python3-brotli arm64 1.1.0-2+b6 [306 kB] Get: 188 http://deb.debian.org/debian trixie/main arm64 python3-tz all 2024.2-1 [31.0 kB] Get: 189 http://deb.debian.org/debian trixie/main arm64 python3-platformdirs all 4.3.6-1 [16.6 kB] Get: 190 http://deb.debian.org/debian trixie/main arm64 python3-fs all 2.4.16-6 [95.1 kB] Get: 191 http://deb.debian.org/debian trixie/main arm64 python3-lxml arm64 5.3.0-1+b1 [1433 kB] Get: 192 http://deb.debian.org/debian trixie/main arm64 python3-lz4 arm64 4.4.0+dfsg-1 [25.6 kB] Get: 193 http://deb.debian.org/debian trixie/main arm64 python3-mpmath all 1.3.0-1 [419 kB] Get: 194 http://deb.debian.org/debian trixie/main arm64 python3-sympy all 1.13.3-1 [4147 kB] Get: 195 http://deb.debian.org/debian trixie/main arm64 python3-attr all 24.3.0-1 [68.8 kB] Get: 196 http://deb.debian.org/debian trixie/main arm64 python3-ufolib2 all 0.17.0+dfsg1-1 [33.0 kB] Get: 197 http://deb.debian.org/debian trixie/main arm64 unicode-data all 15.1.0-1 [8547 kB] Get: 198 http://deb.debian.org/debian trixie/main arm64 python3-fonttools arm64 4.55.3-1 [1501 kB] Get: 199 http://deb.debian.org/debian trixie/main arm64 python3-kiwisolver arm64 1.4.7-2+b1 [71.6 kB] Get: 200 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib arm64 3.8.3-3+b1 [5586 kB] Get: 201 http://deb.debian.org/debian trixie/main arm64 python3-ase all 3.23.0-1 [1698 kB] Get: 202 http://deb.debian.org/debian trixie/main arm64 python3-asttokens all 3.0.0-1 [20.1 kB] Get: 203 http://deb.debian.org/debian trixie/main arm64 python3-cffi-backend arm64 1.17.1-2+b1 [94.8 kB] Get: 204 http://deb.debian.org/debian trixie/main arm64 python3-click all 8.1.8-1 [95.2 kB] Get: 205 http://deb.debian.org/debian trixie/main arm64 python3-cloudpickle all 3.1.0-1 [26.4 kB] Get: 206 http://deb.debian.org/debian trixie/main arm64 python3-traitlets all 5.14.3+really5.14.3-1 [70.9 kB] Get: 207 http://deb.debian.org/debian trixie/main arm64 python3-comm all 0.2.1-1 [8104 B] Get: 208 http://deb.debian.org/debian trixie/main arm64 python3-coverage arm64 7.6.0+dfsg1-2+b1 [177 kB] Get: 209 http://deb.debian.org/debian trixie/main arm64 python3-toolz all 1.0.0-2 [44.2 kB] Get: 210 http://deb.debian.org/debian trixie/main arm64 python3-cytoolz arm64 1.0.1-1 [351 kB] Get: 211 http://deb.debian.org/debian trixie/main arm64 python3-fsspec all 2024.10.0-1 [206 kB] Get: 212 http://deb.debian.org/debian trixie/main arm64 python3-locket all 1.0.0-2 [5820 B] Get: 213 http://deb.debian.org/debian trixie/main arm64 python3-partd all 1.4.2-1 [15.4 kB] Get: 214 http://deb.debian.org/debian trixie/main arm64 python3-yaml arm64 6.0.2-1+b1 [148 kB] Get: 215 http://deb.debian.org/debian trixie/main arm64 python3-dask all 2024.12.1+dfsg-1 [984 kB] Get: 216 http://deb.debian.org/debian trixie/main arm64 python3-debugpy arm64 1.8.8+ds-2 [980 kB] Get: 217 http://deb.debian.org/debian trixie/main arm64 python3-markupsafe arm64 2.1.5-1+b3 [14.0 kB] Get: 218 http://deb.debian.org/debian trixie/main arm64 python3-jinja2 all 3.1.3-2 [120 kB] Get: 219 http://deb.debian.org/debian trixie/main arm64 python3-msgpack arm64 1.0.3-3+b4 [96.8 kB] Get: 220 http://deb.debian.org/debian trixie/main arm64 python3-psutil arm64 5.9.8-2+b1 [226 kB] Get: 221 http://deb.debian.org/debian trixie/main arm64 python3-sortedcontainers all 2.4.0-2 [31.9 kB] Get: 222 http://deb.debian.org/debian trixie/main arm64 python3-tblib all 3.0.0-6 [13.8 kB] Get: 223 http://deb.debian.org/debian trixie/main arm64 python3-tornado arm64 6.4.2-1 [349 kB] Get: 224 http://deb.debian.org/debian trixie/main arm64 python3-urllib3 all 2.2.3-4 [112 kB] Get: 225 http://deb.debian.org/debian trixie/main arm64 python3-zict all 3.0.0-2 [29.7 kB] Get: 226 http://deb.debian.org/debian trixie/main arm64 python3-distributed all 2024.12.1+ds-1 [1162 kB] Get: 227 http://deb.debian.org/debian trixie/main arm64 python3-executing all 2.1.0-0.1 [23.9 kB] Get: 228 http://deb.debian.org/debian trixie/main arm64 python3-h5py-serial arm64 3.12.1-1+b1 [1244 kB] Get: 229 http://deb.debian.org/debian trixie/main arm64 python3-h5py all 3.12.1-1 [15.0 kB] Get: 230 http://deb.debian.org/debian trixie/main arm64 python3-parso all 0.8.4-1 [67.8 kB] Get: 231 http://deb.debian.org/debian trixie/main arm64 python3-typeshed all 0.0~git20241223.ea91db2-1 [1530 kB] Get: 232 http://deb.debian.org/debian trixie/main arm64 python3-jedi all 0.19.1+ds1-1 [691 kB] Get: 233 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib-inline all 0.1.6-2 [8652 B] Get: 234 http://deb.debian.org/debian trixie/main arm64 python3-wcwidth all 0.2.13+dfsg1-1 [24.9 kB] Get: 235 http://deb.debian.org/debian trixie/main arm64 python3-prompt-toolkit all 3.0.48-1 [277 kB] Get: 236 http://deb.debian.org/debian trixie/main arm64 python3-pygments all 2.18.0+dfsg-2 [836 kB] Get: 237 http://deb.debian.org/debian trixie/main arm64 python3-pure-eval all 0.2.3-1 [11.2 kB] Get: 238 http://deb.debian.org/debian trixie/main arm64 python3-stack-data all 0.6.3-1 [21.6 kB] Get: 239 http://deb.debian.org/debian trixie/main arm64 python3-ptyprocess all 0.7.0-6 [14.5 kB] Get: 240 http://deb.debian.org/debian trixie/main arm64 python3-pexpect all 4.9-3 [55.6 kB] Get: 241 http://deb.debian.org/debian trixie/main arm64 python3-ipython all 8.30.0-2 [568 kB] Get: 242 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-core all 5.7.2-5 [35.3 kB] Get: 243 http://deb.debian.org/debian trixie/main arm64 python3-zmq arm64 26.2.0-1 [193 kB] Get: 244 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-client all 8.6.3-2 [92.4 kB] Get: 245 http://deb.debian.org/debian trixie/main arm64 python3-nest-asyncio all 1.5.4-1 [6248 B] Get: 246 http://deb.debian.org/debian trixie/main arm64 python3-ipykernel all 6.29.5-2 [102 kB] Get: 247 http://deb.debian.org/debian trixie/main arm64 python3-ipywidgets all 8.1.5-3 [105 kB] Get: 248 http://deb.debian.org/debian trixie/main arm64 python3-joblib all 1.3.2-5 [216 kB] Get: 249 http://deb.debian.org/debian trixie/main arm64 python3-threadpoolctl all 3.1.0-1 [21.2 kB] Get: 250 http://deb.debian.org/debian trixie/main arm64 python3-sklearn-lib arm64 1.4.2+dfsg-7 [5392 kB] Get: 251 http://deb.debian.org/debian trixie/main arm64 python3-sklearn all 1.4.2+dfsg-7 [2248 kB] Get: 252 http://deb.debian.org/debian trixie/main arm64 python3-sidpy all 0.12.3-3 [76.9 kB] Fetched 134 MB in 1s (162 MB/s) Preconfiguring packages ... Selecting previously unselected package libtext-charwidth-perl:arm64. (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 ... 19970 files and directories currently installed.) Preparing to unpack .../0-libtext-charwidth-perl_0.04-11+b4_arm64.deb ... Unpacking libtext-charwidth-perl:arm64 (0.04-11+b4) ... Selecting previously unselected package libtext-wrapi18n-perl. Preparing to unpack .../1-libtext-wrapi18n-perl_0.06-10_all.deb ... Unpacking libtext-wrapi18n-perl (0.06-10) ... Selecting previously unselected package libproc2-0:arm64. Preparing to unpack .../2-libproc2-0_2%3a4.0.4-6_arm64.deb ... Unpacking libproc2-0:arm64 (2:4.0.4-6) ... Selecting previously unselected package procps. Preparing to unpack .../3-procps_2%3a4.0.4-6_arm64.deb ... Unpacking procps (2:4.0.4-6) ... Selecting previously unselected package sensible-utils. Preparing to unpack .../4-sensible-utils_0.0.24_all.deb ... Unpacking sensible-utils (0.0.24) ... Selecting previously unselected package ucf. Preparing to unpack .../5-ucf_3.0048_all.deb ... Moving old data out of the way Unpacking ucf (3.0048) ... Selecting previously unselected package libdebuginfod-common. Preparing to unpack .../6-libdebuginfod-common_0.192-4_all.deb ... Unpacking libdebuginfod-common (0.192-4) ... Selecting previously unselected package libpython3.12-minimal:arm64. Preparing to unpack .../7-libpython3.12-minimal_3.12.8-5_arm64.deb ... Unpacking libpython3.12-minimal:arm64 (3.12.8-5) ... Selecting previously unselected package libexpat1:arm64. Preparing to unpack .../8-libexpat1_2.6.4-1_arm64.deb ... Unpacking libexpat1:arm64 (2.6.4-1) ... Selecting previously unselected package python3.12-minimal. Preparing to unpack .../9-python3.12-minimal_3.12.8-5_arm64.deb ... Unpacking python3.12-minimal (3.12.8-5) ... Setting up libpython3.12-minimal:arm64 (3.12.8-5) ... Setting up libexpat1:arm64 (2.6.4-1) ... Setting up python3.12-minimal (3.12.8-5) ... Selecting previously unselected package python3-minimal. (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 ... 20560 files and directories currently installed.) Preparing to unpack .../00-python3-minimal_3.12.8-1_arm64.deb ... Unpacking python3-minimal (3.12.8-1) ... Selecting previously unselected package media-types. Preparing to unpack .../01-media-types_10.1.0_all.deb ... Unpacking media-types (10.1.0) ... Selecting previously unselected package netbase. Preparing to unpack .../02-netbase_6.4_all.deb ... Unpacking netbase (6.4) ... Selecting previously unselected package tzdata. Preparing to unpack .../03-tzdata_2024b-6_all.deb ... Unpacking tzdata (2024b-6) ... Selecting previously unselected package libffi8:arm64. Preparing to unpack .../04-libffi8_3.4.6-1_arm64.deb ... Unpacking libffi8:arm64 (3.4.6-1) ... Selecting previously unselected package libkrb5support0:arm64. Preparing to unpack .../05-libkrb5support0_1.21.3-3_arm64.deb ... Unpacking libkrb5support0:arm64 (1.21.3-3) ... Selecting previously unselected package libcom-err2:arm64. Preparing to unpack .../06-libcom-err2_1.47.2-1_arm64.deb ... Unpacking libcom-err2:arm64 (1.47.2-1) ... Selecting previously unselected package libk5crypto3:arm64. Preparing to unpack .../07-libk5crypto3_1.21.3-3_arm64.deb ... Unpacking libk5crypto3:arm64 (1.21.3-3) ... Selecting previously unselected package libkeyutils1:arm64. Preparing to unpack .../08-libkeyutils1_1.6.3-4_arm64.deb ... Unpacking libkeyutils1:arm64 (1.6.3-4) ... Selecting previously unselected package libkrb5-3:arm64. Preparing to unpack .../09-libkrb5-3_1.21.3-3_arm64.deb ... Unpacking libkrb5-3:arm64 (1.21.3-3) ... Selecting previously unselected package libgssapi-krb5-2:arm64. Preparing to unpack .../10-libgssapi-krb5-2_1.21.3-3_arm64.deb ... Unpacking libgssapi-krb5-2:arm64 (1.21.3-3) ... Selecting previously unselected package libtirpc-common. Preparing to unpack .../11-libtirpc-common_1.3.4+ds-1.3_all.deb ... Unpacking libtirpc-common (1.3.4+ds-1.3) ... Selecting previously unselected package libtirpc3t64:arm64. Preparing to unpack .../12-libtirpc3t64_1.3.4+ds-1.3+b1_arm64.deb ... Adding 'diversion of /lib/aarch64-linux-gnu/libtirpc.so.3 to /lib/aarch64-linux-gnu/libtirpc.so.3.usr-is-merged by libtirpc3t64' Adding 'diversion of /lib/aarch64-linux-gnu/libtirpc.so.3.0.0 to /lib/aarch64-linux-gnu/libtirpc.so.3.0.0.usr-is-merged by libtirpc3t64' Unpacking libtirpc3t64:arm64 (1.3.4+ds-1.3+b1) ... Selecting previously unselected package libnsl2:arm64. Preparing to unpack .../13-libnsl2_1.3.0-3+b3_arm64.deb ... Unpacking libnsl2:arm64 (1.3.0-3+b3) ... Selecting previously unselected package readline-common. Preparing to unpack .../14-readline-common_8.2-6_all.deb ... Unpacking readline-common (8.2-6) ... Selecting previously unselected package libreadline8t64:arm64. Preparing to unpack .../15-libreadline8t64_8.2-6_arm64.deb ... Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8 to /lib/aarch64-linux-gnu/libhistory.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8.2 to /lib/aarch64-linux-gnu/libhistory.so.8.2.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8 to /lib/aarch64-linux-gnu/libreadline.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8.2 to /lib/aarch64-linux-gnu/libreadline.so.8.2.usr-is-merged by libreadline8t64' Unpacking libreadline8t64:arm64 (8.2-6) ... Selecting previously unselected package libpython3.12-stdlib:arm64. Preparing to unpack .../16-libpython3.12-stdlib_3.12.8-5_arm64.deb ... Unpacking libpython3.12-stdlib:arm64 (3.12.8-5) ... Selecting previously unselected package python3.12. Preparing to unpack .../17-python3.12_3.12.8-5_arm64.deb ... Unpacking python3.12 (3.12.8-5) ... Selecting previously unselected package libpython3-stdlib:arm64. Preparing to unpack .../18-libpython3-stdlib_3.12.8-1_arm64.deb ... Unpacking libpython3-stdlib:arm64 (3.12.8-1) ... Setting up python3-minimal (3.12.8-1) ... Selecting previously unselected package python3. (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 ... 21628 files and directories currently installed.) Preparing to unpack .../000-python3_3.12.8-1_arm64.deb ... Unpacking python3 (3.12.8-1) ... Selecting previously unselected package libpython3.13-minimal:arm64. Preparing to unpack .../001-libpython3.13-minimal_3.13.1-3_arm64.deb ... Unpacking libpython3.13-minimal:arm64 (3.13.1-3) ... Selecting previously unselected package python3.13-minimal. Preparing to unpack .../002-python3.13-minimal_3.13.1-3_arm64.deb ... Unpacking python3.13-minimal (3.13.1-3) ... Selecting previously unselected package openssl. Preparing to unpack .../003-openssl_3.4.0-2_arm64.deb ... Unpacking openssl (3.4.0-2) ... Selecting previously unselected package ca-certificates. Preparing to unpack .../004-ca-certificates_20241223_all.deb ... Unpacking ca-certificates (20241223) ... Selecting previously unselected package libmagic-mgc. Preparing to unpack .../005-libmagic-mgc_1%3a5.45-3+b1_arm64.deb ... Unpacking libmagic-mgc (1:5.45-3+b1) ... Selecting previously unselected package libmagic1t64:arm64. Preparing to unpack .../006-libmagic1t64_1%3a5.45-3+b1_arm64.deb ... Unpacking libmagic1t64:arm64 (1:5.45-3+b1) ... Selecting previously unselected package file. Preparing to unpack .../007-file_1%3a5.45-3+b1_arm64.deb ... Unpacking file (1:5.45-3+b1) ... Selecting previously unselected package gettext-base. Preparing to unpack .../008-gettext-base_0.22.5-4_arm64.deb ... Unpacking gettext-base (0.22.5-4) ... Selecting previously unselected package libuchardet0:arm64. Preparing to unpack .../009-libuchardet0_0.0.8-1+b2_arm64.deb ... Unpacking libuchardet0:arm64 (0.0.8-1+b2) ... Selecting previously unselected package groff-base. Preparing to unpack .../010-groff-base_1.23.0-7_arm64.deb ... Unpacking groff-base (1.23.0-7) ... Selecting previously unselected package bsdextrautils. Preparing to unpack .../011-bsdextrautils_2.40.4-1_arm64.deb ... Unpacking bsdextrautils (2.40.4-1) ... Selecting previously unselected package libpipeline1:arm64. Preparing to unpack .../012-libpipeline1_1.5.8-1_arm64.deb ... Unpacking libpipeline1:arm64 (1.5.8-1) ... Selecting previously unselected package man-db. Preparing to unpack .../013-man-db_2.13.0-1_arm64.deb ... Unpacking man-db (2.13.0-1) ... Selecting previously unselected package m4. Preparing to unpack .../014-m4_1.4.19-5_arm64.deb ... Unpacking m4 (1.4.19-5) ... Selecting previously unselected package autoconf. Preparing to unpack .../015-autoconf_2.72-3_all.deb ... Unpacking autoconf (2.72-3) ... Selecting previously unselected package autotools-dev. Preparing to unpack .../016-autotools-dev_20220109.1_all.deb ... Unpacking autotools-dev (20220109.1) ... Selecting previously unselected package automake. Preparing to unpack .../017-automake_1%3a1.16.5-1.3_all.deb ... Unpacking automake (1:1.16.5-1.3) ... Selecting previously unselected package autopoint. Preparing to unpack .../018-autopoint_0.22.5-4_all.deb ... Unpacking autopoint (0.22.5-4) ... Selecting previously unselected package libtcl8.6:arm64. Preparing to unpack .../019-libtcl8.6_8.6.16+dfsg-1_arm64.deb ... Unpacking libtcl8.6:arm64 (8.6.16+dfsg-1) ... Selecting previously unselected package libbrotli1:arm64. Preparing to unpack .../020-libbrotli1_1.1.0-2+b6_arm64.deb ... Unpacking libbrotli1:arm64 (1.1.0-2+b6) ... Selecting previously unselected package libpng16-16t64:arm64. Preparing to unpack .../021-libpng16-16t64_1.6.44-3_arm64.deb ... Unpacking libpng16-16t64:arm64 (1.6.44-3) ... Selecting previously unselected package libfreetype6:arm64. Preparing to unpack .../022-libfreetype6_2.13.3+dfsg-1_arm64.deb ... Unpacking libfreetype6:arm64 (2.13.3+dfsg-1) ... Selecting previously unselected package fonts-dejavu-mono. Preparing to unpack .../023-fonts-dejavu-mono_2.37-8_all.deb ... Unpacking fonts-dejavu-mono (2.37-8) ... Selecting previously unselected package fonts-dejavu-core. Preparing to unpack .../024-fonts-dejavu-core_2.37-8_all.deb ... Unpacking fonts-dejavu-core (2.37-8) ... Selecting previously unselected package fontconfig-config. 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Setting up libffi8:arm64 (3.4.6-1) ... Setting up dwz (0.15-1+b1) ... Setting up sensible-utils (0.0.24) ... Setting up libtiff6:arm64 (4.5.1+git230720-5) ... Setting up libuchardet0:arm64 (0.0.8-1+b2) ... Setting up procps (2:4.0.4-6) ... Setting up libtasn1-6:arm64 (4.19.0-3+b3) ... Setting up libopenjp2-7:arm64 (2.5.0-2+b4) ... Setting up python3.13-minimal (3.13.1-3) ... Setting up libx11-6:arm64 (2:1.8.10-2) ... Setting up netbase (6.4) ... Setting up libngtcp2-16:arm64 (1.9.1-1) ... Setting up libkrb5-3:arm64 (1.21.3-3) ... Setting up libssh2-1t64:arm64 (1.11.1-1) ... Setting up libjs-jquery (3.6.1+dfsg+~3.5.14-1) ... Setting up python-matplotlib-data (3.8.3-3) ... Setting up openssl (3.4.0-2) ... Setting up libwebpmux3:arm64 (1.5.0-0.1) ... Setting up libjson-c5:arm64 (0.18+ds-1) ... Setting up readline-common (8.2-6) ... Setting up libxml2:arm64 (2.12.7+dfsg+really2.9.14-0.2+b1) ... Setting up fonts-font-awesome (5.0.10+really4.7.0~dfsg-4.1) ... Setting up libldap2:arm64 (2.6.9+dfsg-1) ... Setting up libsz2:arm64 (1.1.3-1+b1) ... Setting up libjs-bootstrap (3.4.1+dfsg-3) ... Setting up automake (1:1.16.5-1.3) ... update-alternatives: using /usr/bin/automake-1.16 to provide /usr/bin/automake (automake) in auto mode Setting up libfile-stripnondeterminism-perl (1.14.0-1) ... Setting up liblapack3:arm64 (3.12.0-4) ... update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/aarch64-linux-gnu/liblapack.so.3 (liblapack.so.3-aarch64-linux-gnu) in auto mode Setting up gettext (0.22.5-4) ... Setting up libxrender1:arm64 (1:0.9.10-1.1+b3) ... Setting up libtool (2.5.4-2) ... Setting up fontconfig-config (2.15.0-2) ... Setting up libwebpdemux2:arm64 (1.5.0-0.1) ... Setting up libxext6:arm64 (2:1.3.4-1+b3) ... Setting up libidn2-0:arm64 (2.3.7-2+b1) ... Setting up libsource-highlight4t64:arm64 (3.1.9-4.3+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up dh-autoreconf (20) ... Setting up ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 152 added, 0 removed; done. Setting up libglib2.0-0t64:arm64 (2.82.4-2) ... No schema files found: doing nothing. Setting up libjs-jquery-ui (1.13.2+dfsg-1) ... Setting up libfreetype6:arm64 (2.13.3+dfsg-1) ... Setting up libp11-kit0:arm64 (0.25.5-3) ... Setting up libgssapi-krb5-2:arm64 (1.21.3-3) ... Setting up ucf (3.0048) ... Setting up libbabeltrace1:arm64 (1.5.11-4+b1) ... Setting up libreadline8t64:arm64 (8.2-6) ... Setting up dh-strip-nondeterminism (1.14.0-1) ... Setting up groff-base (1.23.0-7) ... Setting up libxslt1.1:arm64 (1.1.35-1.1+b1) ... Setting up libharfbuzz0b:arm64 (10.2.0-1) ... Setting up libxss1:arm64 (1:1.2.3-1+b3) ... Setting up libfontconfig1:arm64 (2.15.0-2) ... Setting up libpython3.13-stdlib:arm64 (3.13.1-3) ... Setting up liblbfgsb0:arm64 (3.0+dfsg.4-1+b2) ... Setting up libpython3.13:arm64 (3.13.1-3) ... Setting up libgnutls30t64:arm64 (3.8.8-2) ... Setting up libxft2:arm64 (2.3.6-1+b3) ... Setting up libzmq5:arm64 (4.3.5-1+b3) ... Setting up libdebuginfod-common (0.192-4) ... Setting up libtirpc3t64:arm64 (1.3.4+ds-1.3+b1) ... Setting up python3.13 (3.13.1-3) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libtk8.6:arm64 (8.6.16-1) ... Setting up python3.12-tk (3.12.8-5) ... Setting up libpsl5t64:arm64 (0.21.2-1.1+b1) ... Setting up man-db (2.13.0-1) ... Not building database; man-db/auto-update is not 'true'. Setting up python3.13-tk (3.13.1-3) ... Setting up librtmp1:arm64 (2.4+20151223.gitfa8646d.1-2+b5) ... Setting up libraqm0:arm64 (0.10.2-1) ... Setting up libnsl2:arm64 (1.3.0-3+b3) ... Setting up libngtcp2-crypto-gnutls8:arm64 (1.9.1-1) ... Setting up tk8.6-blt2.5 (2.5.3+dfsg-7+b1) ... Setting up libpython3.12-stdlib:arm64 (3.12.8-5) ... Setting up libcurl4t64:arm64 (8.11.1-1+b1) ... Setting up blt (2.5.3+dfsg-7+b1) ... Setting up python3.12 (3.12.8-5) ... Setting up libcurl3t64-gnutls:arm64 (8.11.1-1+b1) ... Setting up debhelper (13.23) ... Setting up libhdf5-310:arm64 (1.14.5+repack-3) ... Setting up libpython3-stdlib:arm64 (3.12.8-1) ... Setting up libhdf5-hl-310:arm64 (1.14.5+repack-3) ... Setting up libdebuginfod1t64:arm64 (0.192-4) ... Setting up python3 (3.12.8-1) ... Setting up python3-sortedcontainers (2.4.0-2) ... Setting up python3-zipp (3.21.0-1) ... Setting up python3-click (8.1.8-1) ... Setting up python3-autocommand (2.2.2-3) ... Setting up python3-markupsafe (2.1.5-1+b3) ... Setting up python3-wheel (0.45.1-1) ... Setting up python3-platformdirs (4.3.6-1) ... Setting up python3-psutil (5.9.8-2+b1) ... Setting up python3-tz (2024.2-1) ... Setting up python3-cloudpickle (3.1.0-1) ... Setting up python3-fs (2.4.16-6) ... Setting up python3-pil:arm64 (10.4.0-1.1) ... Setting up python3-decorator (5.1.1-5) ... Setting up python3-jinja2 (3.1.3-2) ... Setting up python3-pygments (2.18.0+dfsg-2) ... Setting up python3-packaging (24.2-1) ... Setting up gdb (15.2-1+b1) ... Setting up python3-wcwidth (0.2.13+dfsg1-1) ... Setting up python3-pyproject-hooks (1.2.0-1) ... Setting up python3-pyparsing (3.1.2-1) ... Setting up python3-typeshed (0.0~git20241223.ea91db2-1) ... Setting up python3-nest-asyncio (1.5.4-1) ... Setting up python3-brotli (1.1.0-2+b6) ... Setting up python3-cycler (0.12.1-1) ... Setting up python3-kiwisolver (1.4.7-2+b1) ... Setting up python3-typing-extensions (4.12.2-2) ... Setting up python3-toml (0.10.2-1) ... Setting up python3-installer (0.7.0+dfsg1-3) ... Setting up python3-urllib3 (2.2.3-4) ... Setting up python3-lxml:arm64 (5.3.0-1+b1) ... Setting up python3-traitlets (5.14.3+really5.14.3-1) ... Setting up python3-toolz (1.0.0-2) ... Setting up python3-dateutil (2.9.0-3) ... Setting up python3-msgpack (1.0.3-3+b4) ... Setting up python3-mpmath (1.3.0-1) ... Setting up python3-build (1.2.2-1) ... Setting up python3-zict (3.0.0-2) ... Setting up python3-locket (1.0.0-2) ... Setting up python3-jupyter-core (5.7.2-5) ... Setting up python3-cffi-backend:arm64 (1.17.1-2+b1) ... Setting up python3-cytoolz (1.0.1-1) ... /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 Setting up python3-ptyprocess (0.7.0-6) ... Setting up python3-prompt-toolkit (3.0.48-1) ... Setting up python3-partd (1.4.2-1) ... Setting up python3-more-itertools (10.6.0-1) ... Setting up python3-sympy (1.13.3-1) ... Setting up python3-attr (24.3.0-1) ... Setting up python3-tornado (6.4.2-1) ... Setting up python3-pure-eval (0.2.3-1) ... Setting up python3-jaraco.functools (4.1.0-1) ... Setting up python3-tblib (3.0.0-6) ... Setting up python3-jaraco.context (6.0.0-1) ... Setting up python3-parso (0.8.4-1) ... Setting up python3-lz4 (4.4.0+dfsg-1) ... Setting up python3-asttokens (3.0.0-1) ... Setting up python3-fsspec (2024.10.0-1) ... Setting up python3-typeguard (4.4.1-1) ... Setting up python3-threadpoolctl (3.1.0-1) ... Setting up python3-all (3.12.8-1) ... Setting up python3-coverage (7.6.0+dfsg1-2+b1) ... Setting up python3-yaml (6.0.2-1+b1) ... Setting up python3-tk:arm64 (3.13.1-1) ... Setting up python3-debugpy (1.8.8+ds-2) ... Setting up python3-matplotlib-inline (0.1.6-2) ... Setting up python3-comm (0.2.1-1) ... Setting up python3-inflect (7.3.1-2) ... Setting up python3-pil.imagetk:arm64 (10.4.0-1.1) ... Setting up python3-executing (2.1.0-0.1) ... Setting up python3-jaraco.text (4.0.0-1) ... Setting up python3-pexpect (4.9-3) ... Setting up python3-zmq (26.2.0-1) ... Setting up python3-jupyter-client (8.6.3-2) ... Setting up python3-stack-data (0.6.3-1) ... Setting up python3-pkg-resources (75.6.0-1) ... Setting up python3-setuptools (75.6.0-1) ... Setting up python3-jedi (0.19.1+ds1-1) ... Setting up python3-joblib (1.3.2-5) ... Setting up python3-dask (2024.12.1+dfsg-1) ... Setting up python3-distributed (2024.12.1+ds-1) ... Setting up python3-ipython (8.30.0-2) ... Setting up python3-ipykernel (6.29.5-2) ... Setting up python3-numpy (1:1.26.4+ds-12) ... Setting up python3-contourpy (1.3.1-1) ... Setting up python3-spglib (2.5.0-1+b1) ... Setting up dh-python (6.20250108) ... Setting up python3-scipy (1.14.1-3) ... Setting up pybuild-plugin-pyproject (6.20250108) ... Setting up python3-sklearn-lib:arm64 (1.4.2+dfsg-7) ... Setting up python3-h5py-serial (3.12.1-1+b1) ... Setting up python3-ipywidgets (8.1.5-3) ... /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters Setting up python3-h5py (3.12.1-1) ... Setting up python3-sklearn (1.4.2+dfsg-7) ... Setting up python3-fonttools (4.55.3-1) ... Setting up python3-ufolib2 (0.17.0+dfsg1-1) ... Setting up python3-matplotlib (3.8.3-3+b1) ... Setting up python3-ase (3.23.0-1) ... Setting up python3-sidpy (0.12.3-3) ... Processing triggers for libc-bin (2.40-5) ... Processing triggers for ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 0 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d... done. Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initializing package states... Writing extended state information... Building tag database... -> Finished parsing the build-deps I: Building the package I: Running cd /build/reproducible-path/pyusid-0.0.12/ && 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 > ../pyusid_0.0.12-2_source.changes dpkg-buildpackage: info: source package pyusid dpkg-buildpackage: info: source version 0.0.12-2 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Roland Mas dpkg-source --before-build . dpkg-buildpackage: info: host architecture arm64 dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ debian/rules clean dh clean --with python3 --buildsystem=pybuild dh_auto_clean -O--buildsystem=pybuild dh_autoreconf_clean -O--buildsystem=pybuild dh_clean -O--buildsystem=pybuild debian/rules binary dh binary --with python3 --buildsystem=pybuild dh_update_autotools_config -O--buildsystem=pybuild dh_autoreconf -O--buildsystem=pybuild dh_auto_configure -O--buildsystem=pybuild dh_auto_build -O--buildsystem=pybuild I: pybuild plugin_pyproject:129: Building wheel for python3.13 with "build" module I: pybuild base:311: python3.13 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py creating build/lib/pyUSID copying pyUSID/__version__.py -> build/lib/pyUSID copying pyUSID/__init__.py -> build/lib/pyUSID creating build/lib/pyUSID/processing copying pyUSID/processing/process.py -> build/lib/pyUSID/processing copying pyUSID/processing/comp_utils.py -> build/lib/pyUSID/processing copying pyUSID/processing/__init__.py -> build/lib/pyUSID/processing creating build/lib/pyUSID/io copying pyUSID/io/usi_data.py -> build/lib/pyUSID/io copying pyUSID/io/reg_ref.py -> build/lib/pyUSID/io copying pyUSID/io/image.py -> build/lib/pyUSID/io copying pyUSID/io/dimension.py -> build/lib/pyUSID/io copying pyUSID/io/array_translator.py -> build/lib/pyUSID/io copying pyUSID/io/anc_build_utils.py -> build/lib/pyUSID/io copying pyUSID/io/__init__.py -> build/lib/pyUSID/io creating build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/simple.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/model.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/base.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/__init__.py -> build/lib/pyUSID/io/hdf_utils running egg_info creating pyUSID.egg-info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt writing manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/.tmp-cnxxuntq/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.13 with "installer" module I: pybuild plugin_pyproject:129: Building wheel for python3.12 with "build" module I: pybuild base:311: python3.12 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py running egg_info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-tc2s051z/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.12 with "installer" module dh_auto_test -O--buildsystem=pybuild I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build; python3.13 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [146 37] [[146] [ 37]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [111 135] [[111 135]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 95 135] [[ 95] [135]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [165 193] [[165 193]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [160 80] [[160] [ 80]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 36 224] [[ 36 224]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 4 38] [[ 4] [38]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [67 64] [[67 64]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[ 42 205 100] [149 90 0]] [[ 42] [205] [100] [149] [ 90] [ 0]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[ 6 59 135] [133 88 69]] [[ 6 59 135 133 88 69]] Position dimensions: ['Position Dimension 0'] Position sort order: [0]ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 24 24 226 226 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 49.78 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 49.78 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.842s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build; python3.12 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [132 155] [[132] [155]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [222 35] [[222 35]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [220 40] [[220] [ 40]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [202 214] [[202 214]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [218 3] [[218] [ 3]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [151 29] [[151 29]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [160 215] [[160] [215]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 8 149] [[ 8 149]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[ 6 79 113] [151 226 202]] [[ 6] [ 79] [113] [151] [226] [202]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[ 19 116 234] [ 93 250 156]] [[ 19 116 234 93 250 156]] Position dimensions: ['Position Dimension 0'] Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 28 28 224 224 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 49.64 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 49.64 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.925s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file create-stamp debian/debhelper-build-stamp dh_testroot -O--buildsystem=pybuild dh_prep -O--buildsystem=pybuild dh_auto_install --destdir=debian/python3-pyusid/ -O--buildsystem=pybuild I: pybuild plugin_pyproject:178: Copying package built for python3.13 to destdir I: pybuild plugin_pyproject:178: Copying package built for python3.12 to destdir dh_installdocs -O--buildsystem=pybuild dh_installchangelogs -O--buildsystem=pybuild dh_python3 -O--buildsystem=pybuild dh_installsystemduser -O--buildsystem=pybuild dh_perl -O--buildsystem=pybuild dh_link -O--buildsystem=pybuild dh_strip_nondeterminism -O--buildsystem=pybuild dh_compress -O--buildsystem=pybuild dh_fixperms -O--buildsystem=pybuild dh_missing -O--buildsystem=pybuild dh_installdeb -O--buildsystem=pybuild dh_gencontrol -O--buildsystem=pybuild dh_md5sums -O--buildsystem=pybuild dh_builddeb -O--buildsystem=pybuild dpkg-deb: building package 'python3-pyusid' in '../python3-pyusid_0.0.12-2_all.deb'. dpkg-genbuildinfo --build=binary -O../pyusid_0.0.12-2_arm64.buildinfo dpkg-genchanges --build=binary -O../pyusid_0.0.12-2_arm64.changes dpkg-genchanges: info: binary-only upload (no source code included) dpkg-source --after-build . dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ dpkg-buildpackage: info: binary-only upload (no source included) dpkg-genchanges: info: not including original source code in upload I: copying local configuration 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/1266995 and its subdirectories I: Current time: Mon Feb 23 04:38:00 -12 2026 I: pbuilder-time-stamp: 1771864680 Mon Feb 23 16:38:00 UTC 2026 I: Signing ./b1/pyusid_0.0.12-2_arm64.buildinfo as pyusid_0.0.12-2_arm64.buildinfo.asc Mon Feb 23 16:38:00 UTC 2026 I: Signed ./b1/pyusid_0.0.12-2_arm64.buildinfo as ./b1/pyusid_0.0.12-2_arm64.buildinfo.asc Mon Feb 23 16:38:00 UTC 2026 - build #1 for pyusid/trixie/arm64 on codethink03-arm64 done. Starting cleanup. All cleanup done. Mon Feb 23 16:38:00 UTC 2026 - reproducible_build.sh stopped running as /tmp/jenkins-script-zkWuL29N, removing. /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn: total 16 drwxr-xr-x 2 jenkins jenkins 4096 Jan 21 10:15 b1 drwxr-xr-x 2 jenkins jenkins 4096 Jan 21 10:12 b2 -rw-r--r-- 1 jenkins jenkins 2169 May 12 2024 pyusid_0.0.12-2.dsc -rw------- 1 jenkins jenkins 3272 Jan 21 10:12 rbuildlog.6NcZ1QY /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1: total 452 -rw-r--r-- 1 jenkins jenkins 356958 Jan 21 10:15 build.log -rw-r--r-- 1 jenkins jenkins 54056 Jan 21 10:15 python3-pyusid_0.0.12-2_all.deb -rw-r--r-- 1 jenkins jenkins 2600 Jan 21 10:15 pyusid_0.0.12-2.debian.tar.xz -rw-r--r-- 1 jenkins jenkins 2169 Jan 21 10:15 pyusid_0.0.12-2.dsc -rw-r--r-- 1 jenkins jenkins 11861 Jan 21 10:15 pyusid_0.0.12-2_arm64.buildinfo -rw-r--r-- 1 jenkins jenkins 12743 Jan 21 10:15 pyusid_0.0.12-2_arm64.buildinfo.asc -rw-r--r-- 1 jenkins jenkins 1164 Jan 21 10:15 pyusid_0.0.12-2_arm64.changes -rw-r--r-- 1 jenkins jenkins 1278 Jan 21 10:15 pyusid_0.0.12-2_source.changes /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2: total 0 Tue Jan 21 10:15:01 UTC 2025 I: Deleting $TMPDIR on codethink03-arm64.debian.net. I: pbuilder: network access will be disabled during build I: Current time: Mon Feb 23 04:35:06 -12 2026 I: pbuilder-time-stamp: 1771864506 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/trixie-reproducible-base.tgz] I: copying local configuration W: --override-config is not set; not updating apt.conf Read the manpage for details. I: mounting /proc filesystem I: mounting /sys filesystem I: creating /{dev,run}/shm I: mounting /dev/pts filesystem I: redirecting /dev/ptmx to /dev/pts/ptmx I: policy-rc.d already exists I: Copying source file I: copying [pyusid_0.0.12-2.dsc] I: copying [./pyusid_0.0.12.orig.tar.gz] I: copying [./pyusid_0.0.12-2.debian.tar.xz] I: Extracting source dpkg-source: warning: cannot verify inline signature for ./pyusid_0.0.12-2.dsc: unsupported subcommand dpkg-source: info: extracting pyusid in pyusid-0.0.12 dpkg-source: info: unpacking pyusid_0.0.12.orig.tar.gz dpkg-source: info: unpacking pyusid_0.0.12-2.debian.tar.xz dpkg-source: info: using patch list from debian/patches/series dpkg-source: info: applying 0001-Remove-requirement-for-six-module.patch I: Not using root during the build. I: Installing the build-deps I: user script /srv/workspace/pbuilder/1266995/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='arm64' DEBIAN_FRONTEND='noninteractive' DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=12 ' DISTRIBUTION='trixie' HOME='/root' HOST_ARCH='arm64' IFS=' ' INVOCATION_ID='fd1b7fff5c924e7eb4682dd63d75ade9' LANG='C' LANGUAGE='en_US:en' LC_ALL='C' 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='1266995' PS1='# ' PS2='> ' 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.GzEM6mWn/pbuilderrc_riQL --distribution trixie --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1 --logfile b1/build.log pyusid_0.0.12-2.dsc' SUDO_GID='109' SUDO_UID='104' SUDO_USER='jenkins' TERM='unknown' TZ='/usr/share/zoneinfo/Etc/GMT+12' USER='root' _='/usr/bin/systemd-run' http_proxy='http://192.168.101.4:3128' I: uname -a Linux codethink03-arm64 6.1.0-30-cloud-arm64 #1 SMP Debian 6.1.124-1 (2025-01-12) aarch64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Nov 22 2024 /bin -> usr/bin I: user script /srv/workspace/pbuilder/1266995/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy Version: 0.invalid.0 Architecture: arm64 Maintainer: Debian Pbuilder Team Description: Dummy package to satisfy dependencies with aptitude - created by pbuilder This package was created automatically by pbuilder to satisfy the build-dependencies of the package being currently built. Depends: debhelper-compat (= 13), dh-python, python3-all, python3-setuptools, pybuild-plugin-pyproject, python3-h5py, python3-numpy, python3-pil, python3-sidpy dpkg-deb: building package 'pbuilder-satisfydepends-dummy' in '/tmp/satisfydepends-aptitude/pbuilder-satisfydepends-dummy.deb'. Selecting previously unselected package pbuilder-satisfydepends-dummy. (Reading database ... 19970 files and directories currently installed.) Preparing to unpack .../pbuilder-satisfydepends-dummy.deb ... Unpacking pbuilder-satisfydepends-dummy (0.invalid.0) ... dpkg: pbuilder-satisfydepends-dummy: dependency problems, but configuring anyway as you requested: pbuilder-satisfydepends-dummy depends on debhelper-compat (= 13); however: Package debhelper-compat is not installed. pbuilder-satisfydepends-dummy depends on dh-python; however: Package dh-python is not installed. pbuilder-satisfydepends-dummy depends on python3-all; however: Package python3-all is not installed. pbuilder-satisfydepends-dummy depends on python3-setuptools; however: Package python3-setuptools is not installed. pbuilder-satisfydepends-dummy depends on pybuild-plugin-pyproject; however: Package pybuild-plugin-pyproject is not installed. pbuilder-satisfydepends-dummy depends on python3-h5py; however: Package python3-h5py is not installed. pbuilder-satisfydepends-dummy depends on python3-numpy; however: Package python3-numpy is not installed. pbuilder-satisfydepends-dummy depends on python3-pil; however: Package python3-pil is not installed. pbuilder-satisfydepends-dummy depends on python3-sidpy; however: Package python3-sidpy is not installed. Setting up pbuilder-satisfydepends-dummy (0.invalid.0) ... Reading package lists... Building dependency tree... Reading state information... Initializing package states... Writing extended state information... Building tag database... pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) The following NEW packages will be installed: autoconf{a} automake{a} autopoint{a} autotools-dev{a} blt{a} bsdextrautils{a} ca-certificates{a} debhelper{a} dh-autoreconf{a} dh-python{a} dh-strip-nondeterminism{a} dwz{a} file{a} fontconfig-config{a} fonts-dejavu-core{a} fonts-dejavu-mono{a} fonts-font-awesome{a} fonts-glyphicons-halflings{a} fonts-lyx{a} gdb{a} gettext{a} gettext-base{a} groff-base{a} intltool-debian{a} libaec0{a} libarchive-zip-perl{a} libbabeltrace1{a} libblas3{a} libbrotli1{a} libcom-err2{a} libcurl3t64-gnutls{a} libcurl4t64{a} libdebhelper-perl{a} libdebuginfod-common{a} libdebuginfod1t64{a} libdeflate0{a} libdw1t64{a} libelf1t64{a} libexpat1{a} libffi8{a} libfile-stripnondeterminism-perl{a} libfontconfig1{a} libfreetype6{a} libfribidi0{a} libgcrypt20{a} libgfortran5{a} libglib2.0-0t64{a} libgnutls30t64{a} libgpg-error0{a} libgraphite2-3{a} libgssapi-krb5-2{a} libharfbuzz0b{a} libhdf5-310{a} libhdf5-hl-310{a} libicu72{a} libidn2-0{a} libimagequant0{a} libjbig0{a} libjpeg62-turbo{a} libjs-bootstrap{a} libjs-jquery{a} libjs-jquery-ui{a} libjson-c5{a} libk5crypto3{a} libkeyutils1{a} libkrb5-3{a} libkrb5support0{a} liblapack3{a} liblbfgsb0{a} liblcms2-2{a} libldap2{a} liblerc4{a} liblzf1{a} libmagic-mgc{a} libmagic1t64{a} libnghttp2-14{a} libnghttp3-9{a} libngtcp2-16{a} libngtcp2-crypto-gnutls8{a} libnorm1t64{a} libnsl2{a} libopenjp2-7{a} libp11-kit0{a} libpgm-5.3-0t64{a} libpipeline1{a} libpng16-16t64{a} libproc2-0{a} libpsl5t64{a} libpython3-stdlib{a} libpython3.12-minimal{a} libpython3.12-stdlib{a} libpython3.13{a} libpython3.13-minimal{a} libpython3.13-stdlib{a} libqhull-r8.0{a} libraqm0{a} libreadline8t64{a} librtmp1{a} libsasl2-2{a} libsasl2-modules-db{a} libsharpyuv0{a} libsodium23{a} libsource-highlight-common{a} libsource-highlight4t64{a} libssh2-1t64{a} libsymspg2{a} libsz2{a} libtasn1-6{a} libtcl8.6{a} libtext-charwidth-perl{a} libtext-wrapi18n-perl{a} libtiff6{a} libtirpc-common{a} libtirpc3t64{a} libtk8.6{a} libtool{a} libuchardet0{a} libunistring5{a} libwebp7{a} libwebpdemux2{a} libwebpmux3{a} libx11-6{a} libx11-data{a} libxau6{a} libxcb1{a} libxdmcp6{a} libxext6{a} libxft2{a} libxml2{a} libxrender1{a} libxslt1.1{a} libxss1{a} libyaml-0-2{a} libzmq5{a} m4{a} man-db{a} media-types{a} netbase{a} openssl{a} po-debconf{a} procps{a} pybuild-plugin-pyproject{a} python-matplotlib-data{a} python3{a} python3-all{a} python3-ase{a} python3-asttokens{a} python3-attr{a} python3-autocommand{a} python3-brotli{a} python3-build{a} python3-cffi-backend{a} python3-click{a} python3-cloudpickle{a} python3-comm{a} python3-contourpy{a} python3-coverage{a} python3-cycler{a} python3-cytoolz{a} python3-dask{a} python3-dateutil{a} python3-debugpy{a} python3-decorator{a} python3-distributed{a} python3-executing{a} python3-fonttools{a} python3-fs{a} python3-fsspec{a} python3-h5py{a} python3-h5py-serial{a} python3-inflect{a} python3-installer{a} python3-ipykernel{a} python3-ipython{a} python3-ipywidgets{a} python3-jaraco.context{a} python3-jaraco.functools{a} python3-jaraco.text{a} python3-jedi{a} python3-jinja2{a} python3-joblib{a} python3-jupyter-client{a} python3-jupyter-core{a} python3-kiwisolver{a} python3-locket{a} python3-lxml{a} python3-lz4{a} python3-markupsafe{a} python3-matplotlib{a} python3-matplotlib-inline{a} python3-minimal{a} python3-more-itertools{a} python3-mpmath{a} python3-msgpack{a} python3-nest-asyncio{a} python3-numpy{a} python3-packaging{a} python3-parso{a} python3-partd{a} python3-pexpect{a} python3-pil{a} python3-pil.imagetk{a} python3-pkg-resources{a} python3-platformdirs{a} python3-prompt-toolkit{a} python3-psutil{a} python3-ptyprocess{a} python3-pure-eval{a} python3-pygments{a} python3-pyparsing{a} python3-pyproject-hooks{a} python3-scipy{a} python3-setuptools{a} python3-sidpy{a} python3-sklearn{a} python3-sklearn-lib{a} python3-sortedcontainers{a} python3-spglib{a} python3-stack-data{a} python3-sympy{a} python3-tblib{a} python3-threadpoolctl{a} python3-tk{a} python3-toml{a} python3-toolz{a} python3-tornado{a} python3-traitlets{a} python3-typeguard{a} python3-typeshed{a} python3-typing-extensions{a} python3-tz{a} python3-ufolib2{a} python3-urllib3{a} python3-wcwidth{a} python3-wheel{a} python3-yaml{a} python3-zict{a} python3-zipp{a} python3-zmq{a} python3.12{a} python3.12-minimal{a} python3.12-tk{a} python3.13{a} python3.13-minimal{a} python3.13-tk{a} readline-common{a} sensible-utils{a} tk8.6-blt2.5{a} tzdata{a} ucf{a} unicode-data{a} x11-common{a} The following packages are RECOMMENDED but will NOT be installed: curl git isympy-common javascript-common krb5-locales libarchive-cpio-perl libc6-dbg libglib2.0-data libgpg-error-l10n libldap-common libltdl-dev libmail-sendmail-perl libsasl2-modules linux-sysctl-defaults lynx psmisc publicsuffix python3-babel python3-blosc python3-bs4 python3-cssselect python3-dropbox python3-html5lib python3-libarchive-c python3-olefile python3-pandas python3-paramiko python3-pooch python3-pygit2 python3-pytest python3-requests python3-simplejson shared-mime-info wget xdg-user-dirs 0 packages upgraded, 252 newly installed, 0 to remove and 0 not upgraded. Need to get 134 MB of archives. After unpacking 656 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main arm64 libtext-charwidth-perl arm64 0.04-11+b4 [9652 B] Get: 2 http://deb.debian.org/debian trixie/main arm64 libtext-wrapi18n-perl all 0.06-10 [8808 B] Get: 3 http://deb.debian.org/debian trixie/main arm64 libproc2-0 arm64 2:4.0.4-6 [62.3 kB] Get: 4 http://deb.debian.org/debian trixie/main arm64 procps arm64 2:4.0.4-6 [872 kB] Get: 5 http://deb.debian.org/debian trixie/main arm64 sensible-utils all 0.0.24 [24.8 kB] Get: 6 http://deb.debian.org/debian trixie/main arm64 ucf all 3.0048 [42.0 kB] Get: 7 http://deb.debian.org/debian trixie/main arm64 libdebuginfod-common all 0.192-4 [23.7 kB] Get: 8 http://deb.debian.org/debian trixie/main arm64 libpython3.12-minimal arm64 3.12.8-5 [810 kB] Get: 9 http://deb.debian.org/debian trixie/main arm64 libexpat1 arm64 2.6.4-1 [90.7 kB] Get: 10 http://deb.debian.org/debian trixie/main arm64 python3.12-minimal arm64 3.12.8-5 [1934 kB] Get: 11 http://deb.debian.org/debian trixie/main arm64 python3-minimal arm64 3.12.8-1 [26.9 kB] Get: 12 http://deb.debian.org/debian trixie/main arm64 media-types all 10.1.0 [26.9 kB] Get: 13 http://deb.debian.org/debian trixie/main arm64 netbase all 6.4 [12.8 kB] Get: 14 http://deb.debian.org/debian trixie/main arm64 tzdata all 2024b-6 [257 kB] Get: 15 http://deb.debian.org/debian trixie/main arm64 libffi8 arm64 3.4.6-1 [20.9 kB] Get: 16 http://deb.debian.org/debian trixie/main arm64 libkrb5support0 arm64 1.21.3-3 [32.1 kB] Get: 17 http://deb.debian.org/debian trixie/main arm64 libcom-err2 arm64 1.47.2-1 [23.9 kB] Get: 18 http://deb.debian.org/debian trixie/main arm64 libk5crypto3 arm64 1.21.3-3 [80.8 kB] Get: 19 http://deb.debian.org/debian trixie/main arm64 libkeyutils1 arm64 1.6.3-4 [9352 B] Get: 20 http://deb.debian.org/debian trixie/main arm64 libkrb5-3 arm64 1.21.3-3 [310 kB] Get: 21 http://deb.debian.org/debian trixie/main arm64 libgssapi-krb5-2 arm64 1.21.3-3 [126 kB] Get: 22 http://deb.debian.org/debian trixie/main arm64 libtirpc-common all 1.3.4+ds-1.3 [10.9 kB] Get: 23 http://deb.debian.org/debian trixie/main arm64 libtirpc3t64 arm64 1.3.4+ds-1.3+b1 [78.7 kB] Get: 24 http://deb.debian.org/debian trixie/main arm64 libnsl2 arm64 1.3.0-3+b3 [37.9 kB] Get: 25 http://deb.debian.org/debian trixie/main arm64 readline-common all 8.2-6 [69.4 kB] Get: 26 http://deb.debian.org/debian trixie/main arm64 libreadline8t64 arm64 8.2-6 [159 kB] Get: 27 http://deb.debian.org/debian trixie/main arm64 libpython3.12-stdlib arm64 3.12.8-5 [1904 kB] Get: 28 http://deb.debian.org/debian trixie/main arm64 python3.12 arm64 3.12.8-5 [677 kB] Get: 29 http://deb.debian.org/debian trixie/main arm64 libpython3-stdlib arm64 3.12.8-1 [9788 B] Get: 30 http://deb.debian.org/debian trixie/main arm64 python3 arm64 3.12.8-1 [27.9 kB] Get: 31 http://deb.debian.org/debian trixie/main arm64 libpython3.13-minimal arm64 3.13.1-3 [852 kB] Get: 32 http://deb.debian.org/debian trixie/main arm64 python3.13-minimal arm64 3.13.1-3 [1990 kB] Get: 33 http://deb.debian.org/debian trixie/main arm64 openssl arm64 3.4.0-2 [1385 kB] Get: 34 http://deb.debian.org/debian trixie/main arm64 ca-certificates all 20241223 [164 kB] Get: 35 http://deb.debian.org/debian trixie/main arm64 libmagic-mgc arm64 1:5.45-3+b1 [314 kB] Get: 36 http://deb.debian.org/debian trixie/main arm64 libmagic1t64 arm64 1:5.45-3+b1 [102 kB] Get: 37 http://deb.debian.org/debian trixie/main arm64 file arm64 1:5.45-3+b1 [43.4 kB] Get: 38 http://deb.debian.org/debian trixie/main arm64 gettext-base arm64 0.22.5-4 [198 kB] Get: 39 http://deb.debian.org/debian trixie/main arm64 libuchardet0 arm64 0.0.8-1+b2 [69.2 kB] Get: 40 http://deb.debian.org/debian trixie/main arm64 groff-base arm64 1.23.0-7 [1129 kB] Get: 41 http://deb.debian.org/debian trixie/main arm64 bsdextrautils arm64 2.40.4-1 [91.6 kB] Get: 42 http://deb.debian.org/debian trixie/main arm64 libpipeline1 arm64 1.5.8-1 [40.2 kB] Get: 43 http://deb.debian.org/debian trixie/main arm64 man-db arm64 2.13.0-1 [1404 kB] Get: 44 http://deb.debian.org/debian trixie/main arm64 m4 arm64 1.4.19-5 [284 kB] Get: 45 http://deb.debian.org/debian trixie/main arm64 autoconf all 2.72-3 [493 kB] Get: 46 http://deb.debian.org/debian trixie/main arm64 autotools-dev all 20220109.1 [51.6 kB] Get: 47 http://deb.debian.org/debian trixie/main arm64 automake all 1:1.16.5-1.3 [823 kB] Get: 48 http://deb.debian.org/debian trixie/main arm64 autopoint all 0.22.5-4 [723 kB] Get: 49 http://deb.debian.org/debian trixie/main arm64 libtcl8.6 arm64 8.6.16+dfsg-1 [984 kB] Get: 50 http://deb.debian.org/debian trixie/main arm64 libbrotli1 arm64 1.1.0-2+b6 [297 kB] Get: 51 http://deb.debian.org/debian trixie/main arm64 libpng16-16t64 arm64 1.6.44-3 [273 kB] Get: 52 http://deb.debian.org/debian trixie/main arm64 libfreetype6 arm64 2.13.3+dfsg-1 [422 kB] Get: 53 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-mono all 2.37-8 [489 kB] Get: 54 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-core all 2.37-8 [840 kB] Get: 55 http://deb.debian.org/debian trixie/main arm64 fontconfig-config arm64 2.15.0-2 [317 kB] Get: 56 http://deb.debian.org/debian trixie/main arm64 libfontconfig1 arm64 2.15.0-2 [386 kB] Get: 57 http://deb.debian.org/debian trixie/main arm64 libxau6 arm64 1:1.0.11-1 [20.6 kB] Get: 58 http://deb.debian.org/debian trixie/main arm64 libxdmcp6 arm64 1:1.1.5-1 [27.8 kB] Get: 59 http://deb.debian.org/debian trixie/main arm64 libxcb1 arm64 1.17.0-2+b1 [143 kB] Get: 60 http://deb.debian.org/debian trixie/main arm64 libx11-data all 2:1.8.10-2 [337 kB] Get: 61 http://deb.debian.org/debian trixie/main arm64 libx11-6 arm64 2:1.8.10-2 [789 kB] Get: 62 http://deb.debian.org/debian trixie/main arm64 libxrender1 arm64 1:0.9.10-1.1+b3 [27.2 kB] Get: 63 http://deb.debian.org/debian trixie/main arm64 libxft2 arm64 2.3.6-1+b3 [51.6 kB] Get: 64 http://deb.debian.org/debian trixie/main arm64 libxext6 arm64 2:1.3.4-1+b3 [49.2 kB] Get: 65 http://deb.debian.org/debian trixie/main arm64 x11-common all 1:7.7+23.2 [216 kB] Get: 66 http://deb.debian.org/debian trixie/main arm64 libxss1 arm64 1:1.2.3-1+b3 [17.1 kB] Get: 67 http://deb.debian.org/debian trixie/main arm64 libtk8.6 arm64 8.6.16-1 [741 kB] Get: 68 http://deb.debian.org/debian trixie/main arm64 tk8.6-blt2.5 arm64 2.5.3+dfsg-7+b1 [538 kB] Get: 69 http://deb.debian.org/debian trixie/main arm64 blt arm64 2.5.3+dfsg-7+b1 [6344 B] Get: 70 http://deb.debian.org/debian trixie/main arm64 libdebhelper-perl all 13.23 [90.6 kB] Get: 71 http://deb.debian.org/debian trixie/main arm64 libtool all 2.5.4-2 [539 kB] Get: 72 http://deb.debian.org/debian trixie/main arm64 dh-autoreconf all 20 [17.1 kB] Get: 73 http://deb.debian.org/debian trixie/main arm64 libarchive-zip-perl all 1.68-1 [104 kB] Get: 74 http://deb.debian.org/debian trixie/main arm64 libfile-stripnondeterminism-perl all 1.14.0-1 [19.5 kB] Get: 75 http://deb.debian.org/debian trixie/main arm64 dh-strip-nondeterminism all 1.14.0-1 [8448 B] Get: 76 http://deb.debian.org/debian trixie/main arm64 libelf1t64 arm64 0.192-4 [189 kB] Get: 77 http://deb.debian.org/debian trixie/main arm64 dwz arm64 0.15-1+b1 [102 kB] Get: 78 http://deb.debian.org/debian trixie/main arm64 libunistring5 arm64 1.3-1 [449 kB] Get: 79 http://deb.debian.org/debian trixie/main arm64 libicu72 arm64 72.1-6 [9239 kB] Get: 80 http://deb.debian.org/debian trixie/main arm64 libxml2 arm64 2.12.7+dfsg+really2.9.14-0.2+b1 [630 kB] Get: 81 http://deb.debian.org/debian trixie/main arm64 gettext arm64 0.22.5-4 [1532 kB] Get: 82 http://deb.debian.org/debian trixie/main arm64 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 83 http://deb.debian.org/debian trixie/main arm64 po-debconf all 1.0.21+nmu1 [248 kB] Get: 84 http://deb.debian.org/debian trixie/main arm64 debhelper all 13.23 [919 kB] Get: 85 http://deb.debian.org/debian trixie/main arm64 python3-autocommand all 2.2.2-3 [13.6 kB] Get: 86 http://deb.debian.org/debian trixie/main arm64 python3-more-itertools all 10.6.0-1 [65.3 kB] Get: 87 http://deb.debian.org/debian trixie/main arm64 python3-typing-extensions all 4.12.2-2 [73.0 kB] Get: 88 http://deb.debian.org/debian trixie/main arm64 python3-typeguard all 4.4.1-1 [37.0 kB] Get: 89 http://deb.debian.org/debian trixie/main arm64 python3-inflect all 7.3.1-2 [32.4 kB] Get: 90 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.context all 6.0.0-1 [7984 B] Get: 91 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.functools all 4.1.0-1 [12.0 kB] Get: 92 http://deb.debian.org/debian trixie/main arm64 python3-pkg-resources all 75.6.0-1 [222 kB] Get: 93 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.text all 4.0.0-1 [11.4 kB] Get: 94 http://deb.debian.org/debian trixie/main arm64 python3-zipp all 3.21.0-1 [10.6 kB] Get: 95 http://deb.debian.org/debian trixie/main arm64 python3-setuptools all 75.6.0-1 [720 kB] Get: 96 http://deb.debian.org/debian trixie/main arm64 dh-python all 6.20250108 [113 kB] Get: 97 http://deb.debian.org/debian trixie/main arm64 fonts-font-awesome all 5.0.10+really4.7.0~dfsg-4.1 [517 kB] Get: 98 http://deb.debian.org/debian trixie/main arm64 fonts-glyphicons-halflings all 1.009~3.4.1+dfsg-3 [162 kB] Get: 99 http://deb.debian.org/debian trixie/main arm64 fonts-lyx all 2.4.2.1-1 [190 kB] Get: 100 http://deb.debian.org/debian trixie/main arm64 libdw1t64 arm64 0.192-4 [237 kB] Get: 101 http://deb.debian.org/debian trixie/main arm64 libglib2.0-0t64 arm64 2.82.4-2 [1413 kB] Get: 102 http://deb.debian.org/debian trixie/main arm64 libbabeltrace1 arm64 1.5.11-4+b1 [164 kB] Get: 103 http://deb.debian.org/debian trixie/main arm64 libidn2-0 arm64 2.3.7-2+b1 [127 kB] Get: 104 http://deb.debian.org/debian trixie/main arm64 libp11-kit0 arm64 0.25.5-3 [409 kB] Get: 105 http://deb.debian.org/debian trixie/main arm64 libtasn1-6 arm64 4.19.0-3+b3 [46.9 kB] Get: 106 http://deb.debian.org/debian trixie/main arm64 libgnutls30t64 arm64 3.8.8-2 [1363 kB] Get: 107 http://deb.debian.org/debian trixie/main arm64 libsasl2-modules-db arm64 2.1.28+dfsg1-8+b1 [20.3 kB] Get: 108 http://deb.debian.org/debian trixie/main arm64 libsasl2-2 arm64 2.1.28+dfsg1-8+b1 [55.7 kB] Get: 109 http://deb.debian.org/debian trixie/main arm64 libldap2 arm64 2.6.9+dfsg-1 [179 kB] Get: 110 http://deb.debian.org/debian trixie/main arm64 libnghttp2-14 arm64 1.64.0-1 [71.3 kB] Get: 111 http://deb.debian.org/debian trixie/main arm64 libnghttp3-9 arm64 1.6.0-2 [60.5 kB] Get: 112 http://deb.debian.org/debian trixie/main arm64 libngtcp2-16 arm64 1.9.1-1 [109 kB] Get: 113 http://deb.debian.org/debian trixie/main arm64 libngtcp2-crypto-gnutls8 arm64 1.9.1-1 [17.3 kB] Get: 114 http://deb.debian.org/debian trixie/main arm64 libpsl5t64 arm64 0.21.2-1.1+b1 [57.1 kB] Get: 115 http://deb.debian.org/debian trixie/main arm64 librtmp1 arm64 2.4+20151223.gitfa8646d.1-2+b5 [56.8 kB] Get: 116 http://deb.debian.org/debian trixie/main arm64 libssh2-1t64 arm64 1.11.1-1 [235 kB] Get: 117 http://deb.debian.org/debian trixie/main arm64 libcurl3t64-gnutls arm64 8.11.1-1+b1 [331 kB] Get: 118 http://deb.debian.org/debian trixie/main arm64 libjson-c5 arm64 0.18+ds-1 [45.2 kB] Get: 119 http://deb.debian.org/debian trixie/main arm64 libdebuginfod1t64 arm64 0.192-4 [31.3 kB] Get: 120 http://deb.debian.org/debian trixie/main arm64 libpython3.13-stdlib arm64 3.13.1-3 [1912 kB] Get: 121 http://deb.debian.org/debian trixie/main arm64 libpython3.13 arm64 3.13.1-3 [1971 kB] Get: 122 http://deb.debian.org/debian trixie/main arm64 libsource-highlight-common all 3.1.9-4.3 [77.5 kB] Get: 123 http://deb.debian.org/debian trixie/main arm64 libsource-highlight4t64 arm64 3.1.9-4.3+b1 [294 kB] Get: 124 http://deb.debian.org/debian trixie/main arm64 gdb arm64 15.2-1+b1 [4159 kB] Get: 125 http://deb.debian.org/debian trixie/main arm64 libaec0 arm64 1.1.3-1+b1 [22.5 kB] Get: 126 http://deb.debian.org/debian trixie/main arm64 libblas3 arm64 3.12.0-4 [98.7 kB] Get: 127 http://deb.debian.org/debian trixie/main arm64 libcurl4t64 arm64 8.11.1-1+b1 [324 kB] Get: 128 http://deb.debian.org/debian trixie/main arm64 libdeflate0 arm64 1.23-1+b1 [42.5 kB] Get: 129 http://deb.debian.org/debian trixie/main arm64 libfribidi0 arm64 1.0.16-1 [26.5 kB] Get: 130 http://deb.debian.org/debian trixie/main arm64 libgpg-error0 arm64 1.51-3 [78.5 kB] Get: 131 http://deb.debian.org/debian trixie/main arm64 libgcrypt20 arm64 1.11.0-7 [742 kB] Get: 132 http://deb.debian.org/debian trixie/main arm64 libgfortran5 arm64 14.2.0-12 [361 kB] Get: 133 http://deb.debian.org/debian trixie/main arm64 libgraphite2-3 arm64 1.3.14-2+b1 [70.4 kB] Get: 134 http://deb.debian.org/debian trixie/main arm64 libharfbuzz0b arm64 10.2.0-1 [443 kB] Get: 135 http://deb.debian.org/debian trixie/main arm64 libsz2 arm64 1.1.3-1+b1 [8044 B] Get: 136 http://deb.debian.org/debian trixie/main arm64 libhdf5-310 arm64 1.14.5+repack-3 [1155 kB] Get: 137 http://deb.debian.org/debian trixie/main arm64 libhdf5-hl-310 arm64 1.14.5+repack-3 [66.1 kB] Get: 138 http://deb.debian.org/debian trixie/main arm64 libimagequant0 arm64 2.18.0-1+b2 [34.6 kB] Get: 139 http://deb.debian.org/debian trixie/main arm64 libjbig0 arm64 2.1-6.1+b2 [30.4 kB] Get: 140 http://deb.debian.org/debian trixie/main arm64 libjpeg62-turbo arm64 1:2.1.5-3+b1 [173 kB] Get: 141 http://deb.debian.org/debian trixie/main arm64 libjs-bootstrap all 3.4.1+dfsg-3 [172 kB] Get: 142 http://deb.debian.org/debian trixie/main arm64 libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [326 kB] Get: 143 http://deb.debian.org/debian trixie/main arm64 libjs-jquery-ui all 1.13.2+dfsg-1 [250 kB] Get: 144 http://deb.debian.org/debian trixie/main arm64 liblapack3 arm64 3.12.0-4 [1812 kB] Get: 145 http://deb.debian.org/debian trixie/main arm64 liblbfgsb0 arm64 3.0+dfsg.4-1+b2 [25.6 kB] Get: 146 http://deb.debian.org/debian trixie/main arm64 liblcms2-2 arm64 2.16-2 [151 kB] Get: 147 http://deb.debian.org/debian trixie/main arm64 liblerc4 arm64 4.0.0+ds-5 [146 kB] Get: 148 http://deb.debian.org/debian trixie/main arm64 liblzf1 arm64 3.6-4+b3 [10.1 kB] Get: 149 http://deb.debian.org/debian trixie/main arm64 libnorm1t64 arm64 1.5.9+dfsg-3.1+b2 [205 kB] Get: 150 http://deb.debian.org/debian trixie/main arm64 libopenjp2-7 arm64 2.5.0-2+b4 [185 kB] Get: 151 http://deb.debian.org/debian trixie/main arm64 libpgm-5.3-0t64 arm64 5.3.128~dfsg-2.1+b1 [152 kB] Get: 152 http://deb.debian.org/debian trixie/main arm64 libqhull-r8.0 arm64 2020.2-6+b2 [229 kB] Get: 153 http://deb.debian.org/debian trixie/main arm64 libraqm0 arm64 0.10.2-1 [13.6 kB] Get: 154 http://deb.debian.org/debian trixie/main arm64 libsharpyuv0 arm64 1.5.0-0.1 [114 kB] Get: 155 http://deb.debian.org/debian trixie/main arm64 libsodium23 arm64 1.0.18-1+b2 [121 kB] Get: 156 http://deb.debian.org/debian trixie/main arm64 libsymspg2 arm64 2.5.0-1+b1 [192 kB] Get: 157 http://deb.debian.org/debian trixie/main arm64 libwebp7 arm64 1.5.0-0.1 [271 kB] Get: 158 http://deb.debian.org/debian trixie/main arm64 libtiff6 arm64 4.5.1+git230720-5 [309 kB] Get: 159 http://deb.debian.org/debian trixie/main arm64 libwebpdemux2 arm64 1.5.0-0.1 [113 kB] Get: 160 http://deb.debian.org/debian trixie/main arm64 libwebpmux3 arm64 1.5.0-0.1 [125 kB] Get: 161 http://deb.debian.org/debian trixie/main arm64 libxslt1.1 arm64 1.1.35-1.1+b1 [222 kB] Get: 162 http://deb.debian.org/debian trixie/main arm64 libyaml-0-2 arm64 0.2.5-2 [49.2 kB] Get: 163 http://deb.debian.org/debian trixie/main arm64 libzmq5 arm64 4.3.5-1+b3 [253 kB] Get: 164 http://deb.debian.org/debian trixie/main arm64 python3-packaging all 24.2-1 [55.3 kB] Get: 165 http://deb.debian.org/debian trixie/main arm64 python3-pyproject-hooks all 1.2.0-1 [11.7 kB] Get: 166 http://deb.debian.org/debian trixie/main arm64 python3-toml all 0.10.2-1 [16.2 kB] Get: 167 http://deb.debian.org/debian trixie/main arm64 python3-wheel all 0.45.1-1 [56.7 kB] Get: 168 http://deb.debian.org/debian trixie/main arm64 python3-build all 1.2.2-1 [36.0 kB] Get: 169 http://deb.debian.org/debian trixie/main arm64 python3-installer all 0.7.0+dfsg1-3 [18.6 kB] Get: 170 http://deb.debian.org/debian trixie/main arm64 pybuild-plugin-pyproject all 6.20250108 [11.6 kB] Get: 171 http://deb.debian.org/debian trixie/main arm64 python-matplotlib-data all 3.8.3-3 [2731 kB] Get: 172 http://deb.debian.org/debian trixie/main arm64 python3.13 arm64 3.13.1-3 [740 kB] Get: 173 http://deb.debian.org/debian trixie/main arm64 python3-all arm64 3.12.8-1 [1048 B] Get: 174 http://deb.debian.org/debian trixie/main arm64 python3-numpy arm64 1:1.26.4+ds-12 [3816 kB] Get: 175 http://deb.debian.org/debian trixie/main arm64 python3-decorator all 5.1.1-5 [15.1 kB] Get: 176 http://deb.debian.org/debian trixie/main arm64 python3-scipy arm64 1.14.1-3 [18.5 MB] Get: 177 http://deb.debian.org/debian trixie/main arm64 python3-spglib arm64 2.5.0-1+b1 [52.1 kB] Get: 178 http://deb.debian.org/debian trixie/main arm64 python3-dateutil all 2.9.0-3 [79.3 kB] Get: 179 http://deb.debian.org/debian trixie/main arm64 python3-pil arm64 10.4.0-1.1 [498 kB] Get: 180 http://deb.debian.org/debian trixie/main arm64 python3.12-tk arm64 3.12.8-5 [111 kB] Get: 181 http://deb.debian.org/debian trixie/main arm64 python3.13-tk arm64 3.13.1-3 [101 kB] Get: 182 http://deb.debian.org/debian trixie/main arm64 python3-tk arm64 3.13.1-1 [9464 B] Get: 183 http://deb.debian.org/debian trixie/main arm64 python3-pil.imagetk arm64 10.4.0-1.1 [79.7 kB] Get: 184 http://deb.debian.org/debian trixie/main arm64 python3-pyparsing all 3.1.2-1 [146 kB] Get: 185 http://deb.debian.org/debian trixie/main arm64 python3-contourpy arm64 1.3.1-1 [237 kB] Get: 186 http://deb.debian.org/debian trixie/main arm64 python3-cycler all 0.12.1-1 [9496 B] Get: 187 http://deb.debian.org/debian trixie/main arm64 python3-brotli arm64 1.1.0-2+b6 [306 kB] Get: 188 http://deb.debian.org/debian trixie/main arm64 python3-tz all 2024.2-1 [31.0 kB] Get: 189 http://deb.debian.org/debian trixie/main arm64 python3-platformdirs all 4.3.6-1 [16.6 kB] Get: 190 http://deb.debian.org/debian trixie/main arm64 python3-fs all 2.4.16-6 [95.1 kB] Get: 191 http://deb.debian.org/debian trixie/main arm64 python3-lxml arm64 5.3.0-1+b1 [1433 kB] Get: 192 http://deb.debian.org/debian trixie/main arm64 python3-lz4 arm64 4.4.0+dfsg-1 [25.6 kB] Get: 193 http://deb.debian.org/debian trixie/main arm64 python3-mpmath all 1.3.0-1 [419 kB] Get: 194 http://deb.debian.org/debian trixie/main arm64 python3-sympy all 1.13.3-1 [4147 kB] Get: 195 http://deb.debian.org/debian trixie/main arm64 python3-attr all 24.3.0-1 [68.8 kB] Get: 196 http://deb.debian.org/debian trixie/main arm64 python3-ufolib2 all 0.17.0+dfsg1-1 [33.0 kB] Get: 197 http://deb.debian.org/debian trixie/main arm64 unicode-data all 15.1.0-1 [8547 kB] Get: 198 http://deb.debian.org/debian trixie/main arm64 python3-fonttools arm64 4.55.3-1 [1501 kB] Get: 199 http://deb.debian.org/debian trixie/main arm64 python3-kiwisolver arm64 1.4.7-2+b1 [71.6 kB] Get: 200 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib arm64 3.8.3-3+b1 [5586 kB] Get: 201 http://deb.debian.org/debian trixie/main arm64 python3-ase all 3.23.0-1 [1698 kB] Get: 202 http://deb.debian.org/debian trixie/main arm64 python3-asttokens all 3.0.0-1 [20.1 kB] Get: 203 http://deb.debian.org/debian trixie/main arm64 python3-cffi-backend arm64 1.17.1-2+b1 [94.8 kB] Get: 204 http://deb.debian.org/debian trixie/main arm64 python3-click all 8.1.8-1 [95.2 kB] Get: 205 http://deb.debian.org/debian trixie/main arm64 python3-cloudpickle all 3.1.0-1 [26.4 kB] Get: 206 http://deb.debian.org/debian trixie/main arm64 python3-traitlets all 5.14.3+really5.14.3-1 [70.9 kB] Get: 207 http://deb.debian.org/debian trixie/main arm64 python3-comm all 0.2.1-1 [8104 B] Get: 208 http://deb.debian.org/debian trixie/main arm64 python3-coverage arm64 7.6.0+dfsg1-2+b1 [177 kB] Get: 209 http://deb.debian.org/debian trixie/main arm64 python3-toolz all 1.0.0-2 [44.2 kB] Get: 210 http://deb.debian.org/debian trixie/main arm64 python3-cytoolz arm64 1.0.1-1 [351 kB] Get: 211 http://deb.debian.org/debian trixie/main arm64 python3-fsspec all 2024.10.0-1 [206 kB] Get: 212 http://deb.debian.org/debian trixie/main arm64 python3-locket all 1.0.0-2 [5820 B] Get: 213 http://deb.debian.org/debian trixie/main arm64 python3-partd all 1.4.2-1 [15.4 kB] Get: 214 http://deb.debian.org/debian trixie/main arm64 python3-yaml arm64 6.0.2-1+b1 [148 kB] Get: 215 http://deb.debian.org/debian trixie/main arm64 python3-dask all 2024.12.1+dfsg-1 [984 kB] Get: 216 http://deb.debian.org/debian trixie/main arm64 python3-debugpy arm64 1.8.8+ds-2 [980 kB] Get: 217 http://deb.debian.org/debian trixie/main arm64 python3-markupsafe arm64 2.1.5-1+b3 [14.0 kB] Get: 218 http://deb.debian.org/debian trixie/main arm64 python3-jinja2 all 3.1.3-2 [120 kB] Get: 219 http://deb.debian.org/debian trixie/main arm64 python3-msgpack arm64 1.0.3-3+b4 [96.8 kB] Get: 220 http://deb.debian.org/debian trixie/main arm64 python3-psutil arm64 5.9.8-2+b1 [226 kB] Get: 221 http://deb.debian.org/debian trixie/main arm64 python3-sortedcontainers all 2.4.0-2 [31.9 kB] Get: 222 http://deb.debian.org/debian trixie/main arm64 python3-tblib all 3.0.0-6 [13.8 kB] Get: 223 http://deb.debian.org/debian trixie/main arm64 python3-tornado arm64 6.4.2-1 [349 kB] Get: 224 http://deb.debian.org/debian trixie/main arm64 python3-urllib3 all 2.2.3-4 [112 kB] Get: 225 http://deb.debian.org/debian trixie/main arm64 python3-zict all 3.0.0-2 [29.7 kB] Get: 226 http://deb.debian.org/debian trixie/main arm64 python3-distributed all 2024.12.1+ds-1 [1162 kB] Get: 227 http://deb.debian.org/debian trixie/main arm64 python3-executing all 2.1.0-0.1 [23.9 kB] Get: 228 http://deb.debian.org/debian trixie/main arm64 python3-h5py-serial arm64 3.12.1-1+b1 [1244 kB] Get: 229 http://deb.debian.org/debian trixie/main arm64 python3-h5py all 3.12.1-1 [15.0 kB] Get: 230 http://deb.debian.org/debian trixie/main arm64 python3-parso all 0.8.4-1 [67.8 kB] Get: 231 http://deb.debian.org/debian trixie/main arm64 python3-typeshed all 0.0~git20241223.ea91db2-1 [1530 kB] Get: 232 http://deb.debian.org/debian trixie/main arm64 python3-jedi all 0.19.1+ds1-1 [691 kB] Get: 233 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib-inline all 0.1.6-2 [8652 B] Get: 234 http://deb.debian.org/debian trixie/main arm64 python3-wcwidth all 0.2.13+dfsg1-1 [24.9 kB] Get: 235 http://deb.debian.org/debian trixie/main arm64 python3-prompt-toolkit all 3.0.48-1 [277 kB] Get: 236 http://deb.debian.org/debian trixie/main arm64 python3-pygments all 2.18.0+dfsg-2 [836 kB] Get: 237 http://deb.debian.org/debian trixie/main arm64 python3-pure-eval all 0.2.3-1 [11.2 kB] Get: 238 http://deb.debian.org/debian trixie/main arm64 python3-stack-data all 0.6.3-1 [21.6 kB] Get: 239 http://deb.debian.org/debian trixie/main arm64 python3-ptyprocess all 0.7.0-6 [14.5 kB] Get: 240 http://deb.debian.org/debian trixie/main arm64 python3-pexpect all 4.9-3 [55.6 kB] Get: 241 http://deb.debian.org/debian trixie/main arm64 python3-ipython all 8.30.0-2 [568 kB] Get: 242 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-core all 5.7.2-5 [35.3 kB] Get: 243 http://deb.debian.org/debian trixie/main arm64 python3-zmq arm64 26.2.0-1 [193 kB] Get: 244 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-client all 8.6.3-2 [92.4 kB] Get: 245 http://deb.debian.org/debian trixie/main arm64 python3-nest-asyncio all 1.5.4-1 [6248 B] Get: 246 http://deb.debian.org/debian trixie/main arm64 python3-ipykernel all 6.29.5-2 [102 kB] Get: 247 http://deb.debian.org/debian trixie/main arm64 python3-ipywidgets all 8.1.5-3 [105 kB] Get: 248 http://deb.debian.org/debian trixie/main arm64 python3-joblib all 1.3.2-5 [216 kB] Get: 249 http://deb.debian.org/debian trixie/main arm64 python3-threadpoolctl all 3.1.0-1 [21.2 kB] Get: 250 http://deb.debian.org/debian trixie/main arm64 python3-sklearn-lib arm64 1.4.2+dfsg-7 [5392 kB] Get: 251 http://deb.debian.org/debian trixie/main arm64 python3-sklearn all 1.4.2+dfsg-7 [2248 kB] Get: 252 http://deb.debian.org/debian trixie/main arm64 python3-sidpy all 0.12.3-3 [76.9 kB] Fetched 134 MB in 1s (162 MB/s) Preconfiguring packages ... Selecting previously unselected package libtext-charwidth-perl:arm64. (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 ... 19970 files and directories currently installed.) Preparing to unpack .../0-libtext-charwidth-perl_0.04-11+b4_arm64.deb ... Unpacking libtext-charwidth-perl:arm64 (0.04-11+b4) ... Selecting previously unselected package libtext-wrapi18n-perl. Preparing to unpack .../1-libtext-wrapi18n-perl_0.06-10_all.deb ... Unpacking libtext-wrapi18n-perl (0.06-10) ... 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(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 ... 20560 files and directories currently installed.) Preparing to unpack .../00-python3-minimal_3.12.8-1_arm64.deb ... Unpacking python3-minimal (3.12.8-1) ... Selecting previously unselected package media-types. Preparing to unpack .../01-media-types_10.1.0_all.deb ... Unpacking media-types (10.1.0) ... Selecting previously unselected package netbase. Preparing to unpack .../02-netbase_6.4_all.deb ... Unpacking netbase (6.4) ... 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Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8 to /lib/aarch64-linux-gnu/libhistory.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8.2 to /lib/aarch64-linux-gnu/libhistory.so.8.2.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8 to /lib/aarch64-linux-gnu/libreadline.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8.2 to /lib/aarch64-linux-gnu/libreadline.so.8.2.usr-is-merged by libreadline8t64' Unpacking libreadline8t64:arm64 (8.2-6) ... Selecting previously unselected package libpython3.12-stdlib:arm64. Preparing to unpack .../16-libpython3.12-stdlib_3.12.8-5_arm64.deb ... Unpacking libpython3.12-stdlib:arm64 (3.12.8-5) ... Selecting previously unselected package python3.12. Preparing to unpack .../17-python3.12_3.12.8-5_arm64.deb ... Unpacking python3.12 (3.12.8-5) ... 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Setting up libblas3:arm64 (3.12.0-4) ... update-alternatives: using /usr/lib/aarch64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/aarch64-linux-gnu/libblas.so.3 (libblas.so.3-aarch64-linux-gnu) in auto mode Setting up libjpeg62-turbo:arm64 (1:2.1.5-3+b1) ... Setting up libx11-data (2:1.8.10-2) ... Setting up liblzf1:arm64 (3.6-4+b3) ... Setting up libfribidi0:arm64 (1.0.16-1) ... Setting up libimagequant0:arm64 (2.18.0-1+b2) ... Setting up libproc2-0:arm64 (2:4.0.4-6) ... Setting up libunistring5:arm64 (1.3-1) ... Setting up fonts-dejavu-mono (2.37-8) ... Setting up libpng16-16t64:arm64 (1.6.44-3) ... Setting up libtcl8.6:arm64 (8.6.16+dfsg-1) ... Setting up autopoint (0.22.5-4) ... Setting up fonts-dejavu-core (2.37-8) ... Setting up libk5crypto3:arm64 (1.21.3-3) ... Setting up libsasl2-2:arm64 (2.1.28+dfsg1-8+b1) ... Setting up libgfortran5:arm64 (14.2.0-12) ... Setting up autoconf (2.72-3) ... Setting up libnghttp3-9:arm64 (1.6.0-2) ... Setting up libwebp7:arm64 (1.5.0-0.1) ... Setting up libffi8:arm64 (3.4.6-1) ... Setting up dwz (0.15-1+b1) ... Setting up sensible-utils (0.0.24) ... Setting up libtiff6:arm64 (4.5.1+git230720-5) ... Setting up libuchardet0:arm64 (0.0.8-1+b2) ... Setting up procps (2:4.0.4-6) ... Setting up libtasn1-6:arm64 (4.19.0-3+b3) ... Setting up libopenjp2-7:arm64 (2.5.0-2+b4) ... Setting up python3.13-minimal (3.13.1-3) ... Setting up libx11-6:arm64 (2:1.8.10-2) ... Setting up netbase (6.4) ... Setting up libngtcp2-16:arm64 (1.9.1-1) ... Setting up libkrb5-3:arm64 (1.21.3-3) ... Setting up libssh2-1t64:arm64 (1.11.1-1) ... Setting up libjs-jquery (3.6.1+dfsg+~3.5.14-1) ... Setting up python-matplotlib-data (3.8.3-3) ... Setting up openssl (3.4.0-2) ... Setting up libwebpmux3:arm64 (1.5.0-0.1) ... Setting up libjson-c5:arm64 (0.18+ds-1) ... Setting up readline-common (8.2-6) ... Setting up libxml2:arm64 (2.12.7+dfsg+really2.9.14-0.2+b1) ... Setting up fonts-font-awesome (5.0.10+really4.7.0~dfsg-4.1) ... Setting up libldap2:arm64 (2.6.9+dfsg-1) ... Setting up libsz2:arm64 (1.1.3-1+b1) ... Setting up libjs-bootstrap (3.4.1+dfsg-3) ... Setting up automake (1:1.16.5-1.3) ... update-alternatives: using /usr/bin/automake-1.16 to provide /usr/bin/automake (automake) in auto mode Setting up libfile-stripnondeterminism-perl (1.14.0-1) ... Setting up liblapack3:arm64 (3.12.0-4) ... update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/aarch64-linux-gnu/liblapack.so.3 (liblapack.so.3-aarch64-linux-gnu) in auto mode Setting up gettext (0.22.5-4) ... Setting up libxrender1:arm64 (1:0.9.10-1.1+b3) ... Setting up libtool (2.5.4-2) ... Setting up fontconfig-config (2.15.0-2) ... Setting up libwebpdemux2:arm64 (1.5.0-0.1) ... Setting up libxext6:arm64 (2:1.3.4-1+b3) ... Setting up libidn2-0:arm64 (2.3.7-2+b1) ... Setting up libsource-highlight4t64:arm64 (3.1.9-4.3+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up dh-autoreconf (20) ... Setting up ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 152 added, 0 removed; done. Setting up libglib2.0-0t64:arm64 (2.82.4-2) ... No schema files found: doing nothing. Setting up libjs-jquery-ui (1.13.2+dfsg-1) ... Setting up libfreetype6:arm64 (2.13.3+dfsg-1) ... Setting up libp11-kit0:arm64 (0.25.5-3) ... Setting up libgssapi-krb5-2:arm64 (1.21.3-3) ... Setting up ucf (3.0048) ... Setting up libbabeltrace1:arm64 (1.5.11-4+b1) ... Setting up libreadline8t64:arm64 (8.2-6) ... Setting up dh-strip-nondeterminism (1.14.0-1) ... Setting up groff-base (1.23.0-7) ... Setting up libxslt1.1:arm64 (1.1.35-1.1+b1) ... Setting up libharfbuzz0b:arm64 (10.2.0-1) ... Setting up libxss1:arm64 (1:1.2.3-1+b3) ... Setting up libfontconfig1:arm64 (2.15.0-2) ... Setting up libpython3.13-stdlib:arm64 (3.13.1-3) ... Setting up liblbfgsb0:arm64 (3.0+dfsg.4-1+b2) ... Setting up libpython3.13:arm64 (3.13.1-3) ... Setting up libgnutls30t64:arm64 (3.8.8-2) ... Setting up libxft2:arm64 (2.3.6-1+b3) ... Setting up libzmq5:arm64 (4.3.5-1+b3) ... Setting up libdebuginfod-common (0.192-4) ... Setting up libtirpc3t64:arm64 (1.3.4+ds-1.3+b1) ... Setting up python3.13 (3.13.1-3) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libtk8.6:arm64 (8.6.16-1) ... Setting up python3.12-tk (3.12.8-5) ... Setting up libpsl5t64:arm64 (0.21.2-1.1+b1) ... Setting up man-db (2.13.0-1) ... Not building database; man-db/auto-update is not 'true'. Setting up python3.13-tk (3.13.1-3) ... Setting up librtmp1:arm64 (2.4+20151223.gitfa8646d.1-2+b5) ... Setting up libraqm0:arm64 (0.10.2-1) ... Setting up libnsl2:arm64 (1.3.0-3+b3) ... Setting up libngtcp2-crypto-gnutls8:arm64 (1.9.1-1) ... Setting up tk8.6-blt2.5 (2.5.3+dfsg-7+b1) ... Setting up libpython3.12-stdlib:arm64 (3.12.8-5) ... Setting up libcurl4t64:arm64 (8.11.1-1+b1) ... Setting up blt (2.5.3+dfsg-7+b1) ... Setting up python3.12 (3.12.8-5) ... Setting up libcurl3t64-gnutls:arm64 (8.11.1-1+b1) ... Setting up debhelper (13.23) ... Setting up libhdf5-310:arm64 (1.14.5+repack-3) ... Setting up libpython3-stdlib:arm64 (3.12.8-1) ... Setting up libhdf5-hl-310:arm64 (1.14.5+repack-3) ... Setting up libdebuginfod1t64:arm64 (0.192-4) ... Setting up python3 (3.12.8-1) ... Setting up python3-sortedcontainers (2.4.0-2) ... Setting up python3-zipp (3.21.0-1) ... Setting up python3-click (8.1.8-1) ... Setting up python3-autocommand (2.2.2-3) ... Setting up python3-markupsafe (2.1.5-1+b3) ... Setting up python3-wheel (0.45.1-1) ... Setting up python3-platformdirs (4.3.6-1) ... Setting up python3-psutil (5.9.8-2+b1) ... Setting up python3-tz (2024.2-1) ... Setting up python3-cloudpickle (3.1.0-1) ... Setting up python3-fs (2.4.16-6) ... Setting up python3-pil:arm64 (10.4.0-1.1) ... Setting up python3-decorator (5.1.1-5) ... Setting up python3-jinja2 (3.1.3-2) ... Setting up python3-pygments (2.18.0+dfsg-2) ... Setting up python3-packaging (24.2-1) ... Setting up gdb (15.2-1+b1) ... Setting up python3-wcwidth (0.2.13+dfsg1-1) ... Setting up python3-pyproject-hooks (1.2.0-1) ... Setting up python3-pyparsing (3.1.2-1) ... Setting up python3-typeshed (0.0~git20241223.ea91db2-1) ... Setting up python3-nest-asyncio (1.5.4-1) ... Setting up python3-brotli (1.1.0-2+b6) ... Setting up python3-cycler (0.12.1-1) ... Setting up python3-kiwisolver (1.4.7-2+b1) ... Setting up python3-typing-extensions (4.12.2-2) ... Setting up python3-toml (0.10.2-1) ... Setting up python3-installer (0.7.0+dfsg1-3) ... Setting up python3-urllib3 (2.2.3-4) ... Setting up python3-lxml:arm64 (5.3.0-1+b1) ... Setting up python3-traitlets (5.14.3+really5.14.3-1) ... Setting up python3-toolz (1.0.0-2) ... Setting up python3-dateutil (2.9.0-3) ... Setting up python3-msgpack (1.0.3-3+b4) ... Setting up python3-mpmath (1.3.0-1) ... Setting up python3-build (1.2.2-1) ... Setting up python3-zict (3.0.0-2) ... Setting up python3-locket (1.0.0-2) ... Setting up python3-jupyter-core (5.7.2-5) ... Setting up python3-cffi-backend:arm64 (1.17.1-2+b1) ... Setting up python3-cytoolz (1.0.1-1) ... /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 Setting up python3-ptyprocess (0.7.0-6) ... Setting up python3-prompt-toolkit (3.0.48-1) ... Setting up python3-partd (1.4.2-1) ... Setting up python3-more-itertools (10.6.0-1) ... Setting up python3-sympy (1.13.3-1) ... Setting up python3-attr (24.3.0-1) ... Setting up python3-tornado (6.4.2-1) ... Setting up python3-pure-eval (0.2.3-1) ... Setting up python3-jaraco.functools (4.1.0-1) ... Setting up python3-tblib (3.0.0-6) ... Setting up python3-jaraco.context (6.0.0-1) ... Setting up python3-parso (0.8.4-1) ... Setting up python3-lz4 (4.4.0+dfsg-1) ... Setting up python3-asttokens (3.0.0-1) ... Setting up python3-fsspec (2024.10.0-1) ... Setting up python3-typeguard (4.4.1-1) ... Setting up python3-threadpoolctl (3.1.0-1) ... Setting up python3-all (3.12.8-1) ... Setting up python3-coverage (7.6.0+dfsg1-2+b1) ... Setting up python3-yaml (6.0.2-1+b1) ... Setting up python3-tk:arm64 (3.13.1-1) ... Setting up python3-debugpy (1.8.8+ds-2) ... Setting up python3-matplotlib-inline (0.1.6-2) ... Setting up python3-comm (0.2.1-1) ... Setting up python3-inflect (7.3.1-2) ... Setting up python3-pil.imagetk:arm64 (10.4.0-1.1) ... Setting up python3-executing (2.1.0-0.1) ... Setting up python3-jaraco.text (4.0.0-1) ... Setting up python3-pexpect (4.9-3) ... Setting up python3-zmq (26.2.0-1) ... Setting up python3-jupyter-client (8.6.3-2) ... Setting up python3-stack-data (0.6.3-1) ... Setting up python3-pkg-resources (75.6.0-1) ... Setting up python3-setuptools (75.6.0-1) ... Setting up python3-jedi (0.19.1+ds1-1) ... Setting up python3-joblib (1.3.2-5) ... Setting up python3-dask (2024.12.1+dfsg-1) ... Setting up python3-distributed (2024.12.1+ds-1) ... Setting up python3-ipython (8.30.0-2) ... Setting up python3-ipykernel (6.29.5-2) ... Setting up python3-numpy (1:1.26.4+ds-12) ... Setting up python3-contourpy (1.3.1-1) ... Setting up python3-spglib (2.5.0-1+b1) ... Setting up dh-python (6.20250108) ... Setting up python3-scipy (1.14.1-3) ... Setting up pybuild-plugin-pyproject (6.20250108) ... Setting up python3-sklearn-lib:arm64 (1.4.2+dfsg-7) ... Setting up python3-h5py-serial (3.12.1-1+b1) ... Setting up python3-ipywidgets (8.1.5-3) ... /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters Setting up python3-h5py (3.12.1-1) ... Setting up python3-sklearn (1.4.2+dfsg-7) ... Setting up python3-fonttools (4.55.3-1) ... Setting up python3-ufolib2 (0.17.0+dfsg1-1) ... Setting up python3-matplotlib (3.8.3-3+b1) ... Setting up python3-ase (3.23.0-1) ... Setting up python3-sidpy (0.12.3-3) ... Processing triggers for libc-bin (2.40-5) ... Processing triggers for ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 0 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d... done. Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initializing package states... Writing extended state information... Building tag database... -> Finished parsing the build-deps I: Building the package I: Running cd /build/reproducible-path/pyusid-0.0.12/ && 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 > ../pyusid_0.0.12-2_source.changes dpkg-buildpackage: info: source package pyusid dpkg-buildpackage: info: source version 0.0.12-2 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Roland Mas dpkg-source --before-build . dpkg-buildpackage: info: host architecture arm64 dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ debian/rules clean dh clean --with python3 --buildsystem=pybuild dh_auto_clean -O--buildsystem=pybuild dh_autoreconf_clean -O--buildsystem=pybuild dh_clean -O--buildsystem=pybuild debian/rules binary dh binary --with python3 --buildsystem=pybuild dh_update_autotools_config -O--buildsystem=pybuild dh_autoreconf -O--buildsystem=pybuild dh_auto_configure -O--buildsystem=pybuild dh_auto_build -O--buildsystem=pybuild I: pybuild plugin_pyproject:129: Building wheel for python3.13 with "build" module I: pybuild base:311: python3.13 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py creating build/lib/pyUSID copying pyUSID/__version__.py -> build/lib/pyUSID copying pyUSID/__init__.py -> build/lib/pyUSID creating build/lib/pyUSID/processing copying pyUSID/processing/process.py -> build/lib/pyUSID/processing copying pyUSID/processing/comp_utils.py -> build/lib/pyUSID/processing copying pyUSID/processing/__init__.py -> build/lib/pyUSID/processing creating build/lib/pyUSID/io copying pyUSID/io/usi_data.py -> build/lib/pyUSID/io copying pyUSID/io/reg_ref.py -> build/lib/pyUSID/io copying pyUSID/io/image.py -> build/lib/pyUSID/io copying pyUSID/io/dimension.py -> build/lib/pyUSID/io copying pyUSID/io/array_translator.py -> build/lib/pyUSID/io copying pyUSID/io/anc_build_utils.py -> build/lib/pyUSID/io copying pyUSID/io/__init__.py -> build/lib/pyUSID/io creating build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/simple.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/model.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/base.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/__init__.py -> build/lib/pyUSID/io/hdf_utils running egg_info creating pyUSID.egg-info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt writing manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/.tmp-cnxxuntq/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.13 with "installer" module I: pybuild plugin_pyproject:129: Building wheel for python3.12 with "build" module I: pybuild base:311: python3.12 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py running egg_info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-tc2s051z/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.12 with "installer" module dh_auto_test -O--buildsystem=pybuild I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build; python3.13 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [146 37] [[146] [ 37]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [111 135] [[111 135]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 95 135] [[ 95] [135]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [165 193] [[165 193]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [160 80] [[160] [ 80]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 36 224] [[ 36 224]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 4 38] [[ 4] [38]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [67 64] [[67 64]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[ 42 205 100] [149 90 0]] [[ 42] [205] [100] [149] [ 90] [ 0]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[ 6 59 135] [133 88 69]] [[ 6 59 135 133 88 69]] Position dimensions: ['Position Dimension 0'] Position sort order: [0]ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 24 24 226 226 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 49.78 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 49.78 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.78 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.842s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build; python3.12 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [132 155] [[132] [155]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [222 35] [[222 35]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [220 40] [[220] [ 40]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [202 214] [[202 214]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [218 3] [[218] [ 3]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [151 29] [[151 29]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [160 215] [[160] [215]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 8 149] [[ 8 149]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[ 6 79 113] [151 226 202]] [[ 6] [ 79] [113] [151] [226] [202]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[ 19 116 234] [ 93 250 156]] [[ 19 116 234 93 250 156]] Position dimensions: ['Position Dimension 0'] Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 28 28 224 224 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 49.64 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 49.64 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 49.64 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.925s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file create-stamp debian/debhelper-build-stamp dh_testroot -O--buildsystem=pybuild dh_prep -O--buildsystem=pybuild dh_auto_install --destdir=debian/python3-pyusid/ -O--buildsystem=pybuild I: pybuild plugin_pyproject:178: Copying package built for python3.13 to destdir I: pybuild plugin_pyproject:178: Copying package built for python3.12 to destdir dh_installdocs -O--buildsystem=pybuild dh_installchangelogs -O--buildsystem=pybuild dh_python3 -O--buildsystem=pybuild dh_installsystemduser -O--buildsystem=pybuild dh_perl -O--buildsystem=pybuild dh_link -O--buildsystem=pybuild dh_strip_nondeterminism -O--buildsystem=pybuild dh_compress -O--buildsystem=pybuild dh_fixperms -O--buildsystem=pybuild dh_missing -O--buildsystem=pybuild dh_installdeb -O--buildsystem=pybuild dh_gencontrol -O--buildsystem=pybuild dh_md5sums -O--buildsystem=pybuild dh_builddeb -O--buildsystem=pybuild dpkg-deb: building package 'python3-pyusid' in '../python3-pyusid_0.0.12-2_all.deb'. dpkg-genbuildinfo --build=binary -O../pyusid_0.0.12-2_arm64.buildinfo dpkg-genchanges --build=binary -O../pyusid_0.0.12-2_arm64.changes dpkg-genchanges: info: binary-only upload (no source code included) dpkg-source --after-build . dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ dpkg-buildpackage: info: binary-only upload (no source included) dpkg-genchanges: info: not including original source code in upload I: copying local configuration 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/1266995 and its subdirectories I: Current time: Mon Feb 23 04:38:00 -12 2026 I: pbuilder-time-stamp: 1771864680 Tue Jan 21 10:15:02 UTC 2025 I: 1st build successful. Starting 2nd build on remote node codethink01-arm64.debian.net. Tue Jan 21 10:15:02 UTC 2025 I: Preparing to do remote build '2' on codethink01-arm64.debian.net. Tue Jan 21 10:15:02 UTC 2025 - checking /var/lib/jenkins/offline_nodes if codethink01-arm64.debian.net is marked as down. Tue Jan 21 10:15:02 UTC 2025 - checking via ssh if codethink01-arm64.debian.net is up. removed '/tmp/read-only-fs-test-GsSRR9' ==================================================================================== Mon Feb 23 16:38:03 UTC 2026 - running /srv/jenkins/bin/reproducible_build.sh (for job /srv/jenkins/bin/reproducible_build.sh) on codethink01-arm64, called using "2 pyusid trixie /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn 0.0.12-2" as arguments. Mon Feb 23 16:38:03 UTC 2026 - actually running "reproducible_build.sh" (md5sum 68e686e434c9ab7bc3ec047d8b309cbc) as "/tmp/jenkins-script-l7DSX4SF" $ git clone https://salsa.debian.org/qa/jenkins.debian.net.git ; more CONTRIBUTING Mon Feb 23 16:38:03 UTC 2026 I: Downloading source for trixie/pyusid=0.0.12-2 Reading package lists... NOTICE: 'pyusid' packaging is maintained in the 'Git' version control system at: https://salsa.debian.org/python-team/packages/pyusid.git Please use: git clone https://salsa.debian.org/python-team/packages/pyusid.git to retrieve the latest (possibly unreleased) updates to the package. Need to get 54.4 MB of source archives. Get:1 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (dsc) [2169 B] Get:2 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (tar) [54.4 MB] Get:3 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (diff) [2600 B] Fetched 54.4 MB in 0s (119 MB/s) Download complete and in download only mode Reading package lists... NOTICE: 'pyusid' packaging is maintained in the 'Git' version control system at: https://salsa.debian.org/python-team/packages/pyusid.git Please use: git clone https://salsa.debian.org/python-team/packages/pyusid.git to retrieve the latest (possibly unreleased) updates to the package. Need to get 54.4 MB of source archives. Get:1 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (dsc) [2169 B] Get:2 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (tar) [54.4 MB] Get:3 http://deb.debian.org/debian trixie/main pyusid 0.0.12-2 (diff) [2600 B] Fetched 54.4 MB in 0s (119 MB/s) Download complete and in download only mode ============================================================================= Re-Building pyusid in trixie on arm64 on codethink01-arm64 now. Date: Mon Feb 23 16:38:04 GMT 2026 Date UTC: Mon Feb 23 16:38:04 UTC 2026 ============================================================================= ++ mktemp -t pbuilderrc_XXXX --tmpdir=/srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn + local TMPCFG=/srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pbuilderrc_dJMQ + case ${ARCH} in + case $ARCH in + locale=nl_BE + language=nl + case "${SUITE}" in + reproducible_buildflags=+all + extra_deb_build_options= + case "${SRCPACKAGE}" in + cat + echo BUILDDIR=/build/reproducible-path + '[' pyusid = debian-installer -o pyusid = debian-installer-netboot-images ']' + pbuilder_options=() + local pbuilder_options + DEBBUILDOPTS=-b + BINARYTARGET= + '[' pyusid = u-boot ']' + case "${SRCPACKAGE}" in + PBUILDERTIMEOUT=24 + local PRESULT=0 + sudo 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.GzEM6mWn/pbuilderrc_dJMQ --distribution trixie --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2 --logfile b2/build.log pyusid_0.0.12-2.dsc W: /root/.pbuilderrc does not exist I: Logging to b2/build.log I: pbuilder: network access will be disabled during build I: Current time: Tue Feb 24 06:38:04 +14 2026 I: pbuilder-time-stamp: 1771864684 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/trixie-reproducible-base.tgz] I: copying local configuration W: --override-config is not set; not updating apt.conf Read the manpage for details. I: mounting /proc filesystem I: mounting /sys filesystem I: creating /{dev,run}/shm I: mounting /dev/pts filesystem I: redirecting /dev/ptmx to /dev/pts/ptmx I: policy-rc.d already exists I: Copying source file I: copying [pyusid_0.0.12-2.dsc] I: copying [./pyusid_0.0.12.orig.tar.gz] I: copying [./pyusid_0.0.12-2.debian.tar.xz] I: Extracting source dpkg-source: warning: cannot verify inline signature for ./pyusid_0.0.12-2.dsc: unsupported subcommand dpkg-source: info: extracting pyusid in pyusid-0.0.12 dpkg-source: info: unpacking pyusid_0.0.12.orig.tar.gz dpkg-source: info: unpacking pyusid_0.0.12-2.debian.tar.xz dpkg-source: info: using patch list from debian/patches/series dpkg-source: info: applying 0001-Remove-requirement-for-six-module.patch I: Not using root during the build. I: Installing the build-deps I: user script /srv/workspace/pbuilder/888831/tmp/hooks/D01_modify_environment starting debug: Running on codethink01-arm64. 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 Feb 23 16:38 /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/888831/tmp/hooks/D01_modify_environment finished I: user script /srv/workspace/pbuilder/888831/tmp/hooks/D02_print_environment starting I: set 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]="37" [3]="1" [4]="release" [5]="aarch64-unknown-linux-gnu") BASH_VERSION='5.2.37(1)-release' BUILDDIR=/build/reproducible-path BUILDUSERGECOS='second user,second room,second work-phone,second home-phone,second other' BUILDUSERNAME=pbuilder2 BUILD_ARCH=arm64 DEBIAN_FRONTEND=noninteractive DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=12 ' DIRSTACK=() DISTRIBUTION=trixie EUID=0 FUNCNAME=([0]="Echo" [1]="main") GROUPS=() HOME=/root HOSTNAME=i-capture-the-hostname HOSTTYPE=aarch64 HOST_ARCH=arm64 IFS=' ' INVOCATION_ID=c9aff92549d34c048338ec3b3ca9ca0a LANG=C LANGUAGE=nl_BE:nl LC_ALL=C MACHTYPE=aarch64-unknown-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=888831 PS4='+ ' 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.GzEM6mWn/pbuilderrc_dJMQ --distribution trixie --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2 --logfile b2/build.log pyusid_0.0.12-2.dsc' SUDO_GID=109 SUDO_UID=104 SUDO_USER=jenkins TERM=unknown TZ=/usr/share/zoneinfo/Etc/GMT-14 UID=0 USER=root _='I: set' http_proxy=http://192.168.101.4:3128 I: uname -a Linux i-capture-the-hostname 6.1.0-30-cloud-arm64 #1 SMP Debian 6.1.124-1 (2025-01-12) aarch64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Nov 22 2024 /bin -> usr/bin I: user script /srv/workspace/pbuilder/888831/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy Version: 0.invalid.0 Architecture: arm64 Maintainer: Debian Pbuilder Team Description: Dummy package to satisfy dependencies with aptitude - created by pbuilder This package was created automatically by pbuilder to satisfy the build-dependencies of the package being currently built. Depends: debhelper-compat (= 13), dh-python, python3-all, python3-setuptools, pybuild-plugin-pyproject, python3-h5py, python3-numpy, python3-pil, python3-sidpy dpkg-deb: building package 'pbuilder-satisfydepends-dummy' in '/tmp/satisfydepends-aptitude/pbuilder-satisfydepends-dummy.deb'. Selecting previously unselected package pbuilder-satisfydepends-dummy. (Reading database ... 19970 files and directories currently installed.) Preparing to unpack .../pbuilder-satisfydepends-dummy.deb ... Unpacking pbuilder-satisfydepends-dummy (0.invalid.0) ... dpkg: pbuilder-satisfydepends-dummy: dependency problems, but configuring anyway as you requested: pbuilder-satisfydepends-dummy depends on debhelper-compat (= 13); however: Package debhelper-compat is not installed. pbuilder-satisfydepends-dummy depends on dh-python; however: Package dh-python is not installed. pbuilder-satisfydepends-dummy depends on python3-all; however: Package python3-all is not installed. pbuilder-satisfydepends-dummy depends on python3-setuptools; however: Package python3-setuptools is not installed. pbuilder-satisfydepends-dummy depends on pybuild-plugin-pyproject; however: Package pybuild-plugin-pyproject is not installed. pbuilder-satisfydepends-dummy depends on python3-h5py; however: Package python3-h5py is not installed. pbuilder-satisfydepends-dummy depends on python3-numpy; however: Package python3-numpy is not installed. pbuilder-satisfydepends-dummy depends on python3-pil; however: Package python3-pil is not installed. pbuilder-satisfydepends-dummy depends on python3-sidpy; however: Package python3-sidpy is not installed. Setting up pbuilder-satisfydepends-dummy (0.invalid.0) ... Reading package lists... Building dependency tree... Reading state information... Initializing package states... Writing extended state information... Building tag database... pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) The following NEW packages will be installed: autoconf{a} automake{a} autopoint{a} autotools-dev{a} blt{a} bsdextrautils{a} ca-certificates{a} debhelper{a} dh-autoreconf{a} dh-python{a} dh-strip-nondeterminism{a} dwz{a} file{a} fontconfig-config{a} fonts-dejavu-core{a} fonts-dejavu-mono{a} fonts-font-awesome{a} fonts-glyphicons-halflings{a} fonts-lyx{a} gdb{a} gettext{a} gettext-base{a} groff-base{a} intltool-debian{a} libaec0{a} libarchive-zip-perl{a} libbabeltrace1{a} libblas3{a} libbrotli1{a} libcom-err2{a} libcurl3t64-gnutls{a} libcurl4t64{a} libdebhelper-perl{a} libdebuginfod-common{a} libdebuginfod1t64{a} libdeflate0{a} libdw1t64{a} libelf1t64{a} libexpat1{a} libffi8{a} libfile-stripnondeterminism-perl{a} libfontconfig1{a} libfreetype6{a} libfribidi0{a} libgcrypt20{a} libgfortran5{a} libglib2.0-0t64{a} libgnutls30t64{a} libgpg-error0{a} libgraphite2-3{a} libgssapi-krb5-2{a} libharfbuzz0b{a} libhdf5-310{a} libhdf5-hl-310{a} libicu72{a} libidn2-0{a} libimagequant0{a} libjbig0{a} libjpeg62-turbo{a} libjs-bootstrap{a} libjs-jquery{a} libjs-jquery-ui{a} libjson-c5{a} libk5crypto3{a} libkeyutils1{a} libkrb5-3{a} libkrb5support0{a} liblapack3{a} liblbfgsb0{a} liblcms2-2{a} libldap2{a} liblerc4{a} liblzf1{a} libmagic-mgc{a} libmagic1t64{a} libnghttp2-14{a} libnghttp3-9{a} libngtcp2-16{a} libngtcp2-crypto-gnutls8{a} libnorm1t64{a} libnsl2{a} libopenjp2-7{a} libp11-kit0{a} libpgm-5.3-0t64{a} libpipeline1{a} libpng16-16t64{a} libproc2-0{a} libpsl5t64{a} libpython3-stdlib{a} libpython3.12-minimal{a} libpython3.12-stdlib{a} libpython3.13{a} libpython3.13-minimal{a} libpython3.13-stdlib{a} libqhull-r8.0{a} libraqm0{a} libreadline8t64{a} librtmp1{a} libsasl2-2{a} libsasl2-modules-db{a} libsharpyuv0{a} libsodium23{a} libsource-highlight-common{a} libsource-highlight4t64{a} libssh2-1t64{a} libsymspg2{a} libsz2{a} libtasn1-6{a} libtcl8.6{a} libtext-charwidth-perl{a} libtext-wrapi18n-perl{a} libtiff6{a} libtirpc-common{a} libtirpc3t64{a} libtk8.6{a} libtool{a} libuchardet0{a} libunistring5{a} libwebp7{a} libwebpdemux2{a} libwebpmux3{a} libx11-6{a} libx11-data{a} libxau6{a} libxcb1{a} libxdmcp6{a} libxext6{a} libxft2{a} libxml2{a} libxrender1{a} libxslt1.1{a} libxss1{a} libyaml-0-2{a} libzmq5{a} m4{a} man-db{a} media-types{a} netbase{a} openssl{a} po-debconf{a} procps{a} pybuild-plugin-pyproject{a} python-matplotlib-data{a} python3{a} python3-all{a} python3-ase{a} python3-asttokens{a} python3-attr{a} python3-autocommand{a} python3-brotli{a} python3-build{a} python3-cffi-backend{a} python3-click{a} python3-cloudpickle{a} python3-comm{a} python3-contourpy{a} python3-coverage{a} python3-cycler{a} python3-cytoolz{a} python3-dask{a} python3-dateutil{a} python3-debugpy{a} python3-decorator{a} python3-distributed{a} python3-executing{a} python3-fonttools{a} python3-fs{a} python3-fsspec{a} python3-h5py{a} python3-h5py-serial{a} python3-inflect{a} python3-installer{a} python3-ipykernel{a} python3-ipython{a} python3-ipywidgets{a} python3-jaraco.context{a} python3-jaraco.functools{a} python3-jaraco.text{a} python3-jedi{a} python3-jinja2{a} python3-joblib{a} python3-jupyter-client{a} python3-jupyter-core{a} python3-kiwisolver{a} python3-locket{a} python3-lxml{a} python3-lz4{a} python3-markupsafe{a} python3-matplotlib{a} python3-matplotlib-inline{a} python3-minimal{a} python3-more-itertools{a} python3-mpmath{a} python3-msgpack{a} python3-nest-asyncio{a} python3-numpy{a} python3-packaging{a} python3-parso{a} python3-partd{a} python3-pexpect{a} python3-pil{a} python3-pil.imagetk{a} python3-pkg-resources{a} python3-platformdirs{a} python3-prompt-toolkit{a} python3-psutil{a} python3-ptyprocess{a} python3-pure-eval{a} python3-pygments{a} python3-pyparsing{a} python3-pyproject-hooks{a} python3-scipy{a} python3-setuptools{a} python3-sidpy{a} python3-sklearn{a} python3-sklearn-lib{a} python3-sortedcontainers{a} python3-spglib{a} python3-stack-data{a} python3-sympy{a} python3-tblib{a} python3-threadpoolctl{a} python3-tk{a} python3-toml{a} python3-toolz{a} python3-tornado{a} python3-traitlets{a} python3-typeguard{a} python3-typeshed{a} python3-typing-extensions{a} python3-tz{a} python3-ufolib2{a} python3-urllib3{a} python3-wcwidth{a} python3-wheel{a} python3-yaml{a} python3-zict{a} python3-zipp{a} python3-zmq{a} python3.12{a} python3.12-minimal{a} python3.12-tk{a} python3.13{a} python3.13-minimal{a} python3.13-tk{a} readline-common{a} sensible-utils{a} tk8.6-blt2.5{a} tzdata{a} ucf{a} unicode-data{a} x11-common{a} The following packages are RECOMMENDED but will NOT be installed: curl git isympy-common javascript-common krb5-locales libarchive-cpio-perl libc6-dbg libglib2.0-data libgpg-error-l10n libldap-common libltdl-dev libmail-sendmail-perl libsasl2-modules linux-sysctl-defaults lynx psmisc publicsuffix python3-babel python3-blosc python3-bs4 python3-cssselect python3-dropbox python3-html5lib python3-libarchive-c python3-olefile python3-pandas python3-paramiko python3-pooch python3-pygit2 python3-pytest python3-requests python3-simplejson shared-mime-info wget xdg-user-dirs 0 packages upgraded, 252 newly installed, 0 to remove and 0 not upgraded. Need to get 134 MB of archives. After unpacking 656 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main arm64 libtext-charwidth-perl arm64 0.04-11+b4 [9652 B] Get: 2 http://deb.debian.org/debian trixie/main arm64 libtext-wrapi18n-perl all 0.06-10 [8808 B] Get: 3 http://deb.debian.org/debian trixie/main arm64 libproc2-0 arm64 2:4.0.4-6 [62.3 kB] Get: 4 http://deb.debian.org/debian trixie/main arm64 procps arm64 2:4.0.4-6 [872 kB] Get: 5 http://deb.debian.org/debian trixie/main arm64 sensible-utils all 0.0.24 [24.8 kB] Get: 6 http://deb.debian.org/debian trixie/main arm64 ucf all 3.0048 [42.0 kB] Get: 7 http://deb.debian.org/debian trixie/main arm64 libdebuginfod-common all 0.192-4 [23.7 kB] Get: 8 http://deb.debian.org/debian trixie/main arm64 libpython3.12-minimal arm64 3.12.8-5 [810 kB] Get: 9 http://deb.debian.org/debian trixie/main arm64 libexpat1 arm64 2.6.4-1 [90.7 kB] Get: 10 http://deb.debian.org/debian trixie/main arm64 python3.12-minimal arm64 3.12.8-5 [1934 kB] Get: 11 http://deb.debian.org/debian trixie/main arm64 python3-minimal arm64 3.12.8-1 [26.9 kB] Get: 12 http://deb.debian.org/debian trixie/main arm64 media-types all 10.1.0 [26.9 kB] Get: 13 http://deb.debian.org/debian trixie/main arm64 netbase all 6.4 [12.8 kB] Get: 14 http://deb.debian.org/debian trixie/main arm64 tzdata all 2024b-6 [257 kB] Get: 15 http://deb.debian.org/debian trixie/main arm64 libffi8 arm64 3.4.6-1 [20.9 kB] Get: 16 http://deb.debian.org/debian trixie/main arm64 libkrb5support0 arm64 1.21.3-3 [32.1 kB] Get: 17 http://deb.debian.org/debian trixie/main arm64 libcom-err2 arm64 1.47.2-1 [23.9 kB] Get: 18 http://deb.debian.org/debian trixie/main arm64 libk5crypto3 arm64 1.21.3-3 [80.8 kB] Get: 19 http://deb.debian.org/debian trixie/main arm64 libkeyutils1 arm64 1.6.3-4 [9352 B] Get: 20 http://deb.debian.org/debian trixie/main arm64 libkrb5-3 arm64 1.21.3-3 [310 kB] Get: 21 http://deb.debian.org/debian trixie/main arm64 libgssapi-krb5-2 arm64 1.21.3-3 [126 kB] Get: 22 http://deb.debian.org/debian trixie/main arm64 libtirpc-common all 1.3.4+ds-1.3 [10.9 kB] Get: 23 http://deb.debian.org/debian trixie/main arm64 libtirpc3t64 arm64 1.3.4+ds-1.3+b1 [78.7 kB] Get: 24 http://deb.debian.org/debian trixie/main arm64 libnsl2 arm64 1.3.0-3+b3 [37.9 kB] Get: 25 http://deb.debian.org/debian trixie/main arm64 readline-common all 8.2-6 [69.4 kB] Get: 26 http://deb.debian.org/debian trixie/main arm64 libreadline8t64 arm64 8.2-6 [159 kB] Get: 27 http://deb.debian.org/debian trixie/main arm64 libpython3.12-stdlib arm64 3.12.8-5 [1904 kB] Get: 28 http://deb.debian.org/debian trixie/main arm64 python3.12 arm64 3.12.8-5 [677 kB] Get: 29 http://deb.debian.org/debian trixie/main arm64 libpython3-stdlib arm64 3.12.8-1 [9788 B] Get: 30 http://deb.debian.org/debian trixie/main arm64 python3 arm64 3.12.8-1 [27.9 kB] Get: 31 http://deb.debian.org/debian trixie/main arm64 libpython3.13-minimal arm64 3.13.1-3 [852 kB] Get: 32 http://deb.debian.org/debian trixie/main arm64 python3.13-minimal arm64 3.13.1-3 [1990 kB] Get: 33 http://deb.debian.org/debian trixie/main arm64 openssl arm64 3.4.0-2 [1385 kB] Get: 34 http://deb.debian.org/debian trixie/main arm64 ca-certificates all 20241223 [164 kB] Get: 35 http://deb.debian.org/debian trixie/main arm64 libmagic-mgc arm64 1:5.45-3+b1 [314 kB] Get: 36 http://deb.debian.org/debian trixie/main arm64 libmagic1t64 arm64 1:5.45-3+b1 [102 kB] Get: 37 http://deb.debian.org/debian trixie/main arm64 file arm64 1:5.45-3+b1 [43.4 kB] Get: 38 http://deb.debian.org/debian trixie/main arm64 gettext-base arm64 0.22.5-4 [198 kB] Get: 39 http://deb.debian.org/debian trixie/main arm64 libuchardet0 arm64 0.0.8-1+b2 [69.2 kB] Get: 40 http://deb.debian.org/debian trixie/main arm64 groff-base arm64 1.23.0-7 [1129 kB] Get: 41 http://deb.debian.org/debian trixie/main arm64 bsdextrautils arm64 2.40.4-1 [91.6 kB] Get: 42 http://deb.debian.org/debian trixie/main arm64 libpipeline1 arm64 1.5.8-1 [40.2 kB] Get: 43 http://deb.debian.org/debian trixie/main arm64 man-db arm64 2.13.0-1 [1404 kB] Get: 44 http://deb.debian.org/debian trixie/main arm64 m4 arm64 1.4.19-5 [284 kB] Get: 45 http://deb.debian.org/debian trixie/main arm64 autoconf all 2.72-3 [493 kB] Get: 46 http://deb.debian.org/debian trixie/main arm64 autotools-dev all 20220109.1 [51.6 kB] Get: 47 http://deb.debian.org/debian trixie/main arm64 automake all 1:1.16.5-1.3 [823 kB] Get: 48 http://deb.debian.org/debian trixie/main arm64 autopoint all 0.22.5-4 [723 kB] Get: 49 http://deb.debian.org/debian trixie/main arm64 libtcl8.6 arm64 8.6.16+dfsg-1 [984 kB] Get: 50 http://deb.debian.org/debian trixie/main arm64 libbrotli1 arm64 1.1.0-2+b6 [297 kB] Get: 51 http://deb.debian.org/debian trixie/main arm64 libpng16-16t64 arm64 1.6.44-3 [273 kB] Get: 52 http://deb.debian.org/debian trixie/main arm64 libfreetype6 arm64 2.13.3+dfsg-1 [422 kB] Get: 53 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-mono all 2.37-8 [489 kB] Get: 54 http://deb.debian.org/debian trixie/main arm64 fonts-dejavu-core all 2.37-8 [840 kB] Get: 55 http://deb.debian.org/debian trixie/main arm64 fontconfig-config arm64 2.15.0-2 [317 kB] Get: 56 http://deb.debian.org/debian trixie/main arm64 libfontconfig1 arm64 2.15.0-2 [386 kB] Get: 57 http://deb.debian.org/debian trixie/main arm64 libxau6 arm64 1:1.0.11-1 [20.6 kB] Get: 58 http://deb.debian.org/debian trixie/main arm64 libxdmcp6 arm64 1:1.1.5-1 [27.8 kB] Get: 59 http://deb.debian.org/debian trixie/main arm64 libxcb1 arm64 1.17.0-2+b1 [143 kB] Get: 60 http://deb.debian.org/debian trixie/main arm64 libx11-data all 2:1.8.10-2 [337 kB] Get: 61 http://deb.debian.org/debian trixie/main arm64 libx11-6 arm64 2:1.8.10-2 [789 kB] Get: 62 http://deb.debian.org/debian trixie/main arm64 libxrender1 arm64 1:0.9.10-1.1+b3 [27.2 kB] Get: 63 http://deb.debian.org/debian trixie/main arm64 libxft2 arm64 2.3.6-1+b3 [51.6 kB] Get: 64 http://deb.debian.org/debian trixie/main arm64 libxext6 arm64 2:1.3.4-1+b3 [49.2 kB] Get: 65 http://deb.debian.org/debian trixie/main arm64 x11-common all 1:7.7+23.2 [216 kB] Get: 66 http://deb.debian.org/debian trixie/main arm64 libxss1 arm64 1:1.2.3-1+b3 [17.1 kB] Get: 67 http://deb.debian.org/debian trixie/main arm64 libtk8.6 arm64 8.6.16-1 [741 kB] Get: 68 http://deb.debian.org/debian trixie/main arm64 tk8.6-blt2.5 arm64 2.5.3+dfsg-7+b1 [538 kB] Get: 69 http://deb.debian.org/debian trixie/main arm64 blt arm64 2.5.3+dfsg-7+b1 [6344 B] Get: 70 http://deb.debian.org/debian trixie/main arm64 libdebhelper-perl all 13.23 [90.6 kB] Get: 71 http://deb.debian.org/debian trixie/main arm64 libtool all 2.5.4-2 [539 kB] Get: 72 http://deb.debian.org/debian trixie/main arm64 dh-autoreconf all 20 [17.1 kB] Get: 73 http://deb.debian.org/debian trixie/main arm64 libarchive-zip-perl all 1.68-1 [104 kB] Get: 74 http://deb.debian.org/debian trixie/main arm64 libfile-stripnondeterminism-perl all 1.14.0-1 [19.5 kB] Get: 75 http://deb.debian.org/debian trixie/main arm64 dh-strip-nondeterminism all 1.14.0-1 [8448 B] Get: 76 http://deb.debian.org/debian trixie/main arm64 libelf1t64 arm64 0.192-4 [189 kB] Get: 77 http://deb.debian.org/debian trixie/main arm64 dwz arm64 0.15-1+b1 [102 kB] Get: 78 http://deb.debian.org/debian trixie/main arm64 libunistring5 arm64 1.3-1 [449 kB] Get: 79 http://deb.debian.org/debian trixie/main arm64 libicu72 arm64 72.1-6 [9239 kB] Get: 80 http://deb.debian.org/debian trixie/main arm64 libxml2 arm64 2.12.7+dfsg+really2.9.14-0.2+b1 [630 kB] Get: 81 http://deb.debian.org/debian trixie/main arm64 gettext arm64 0.22.5-4 [1532 kB] Get: 82 http://deb.debian.org/debian trixie/main arm64 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 83 http://deb.debian.org/debian trixie/main arm64 po-debconf all 1.0.21+nmu1 [248 kB] Get: 84 http://deb.debian.org/debian trixie/main arm64 debhelper all 13.23 [919 kB] Get: 85 http://deb.debian.org/debian trixie/main arm64 python3-autocommand all 2.2.2-3 [13.6 kB] Get: 86 http://deb.debian.org/debian trixie/main arm64 python3-more-itertools all 10.6.0-1 [65.3 kB] Get: 87 http://deb.debian.org/debian trixie/main arm64 python3-typing-extensions all 4.12.2-2 [73.0 kB] Get: 88 http://deb.debian.org/debian trixie/main arm64 python3-typeguard all 4.4.1-1 [37.0 kB] Get: 89 http://deb.debian.org/debian trixie/main arm64 python3-inflect all 7.3.1-2 [32.4 kB] Get: 90 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.context all 6.0.0-1 [7984 B] Get: 91 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.functools all 4.1.0-1 [12.0 kB] Get: 92 http://deb.debian.org/debian trixie/main arm64 python3-pkg-resources all 75.6.0-1 [222 kB] Get: 93 http://deb.debian.org/debian trixie/main arm64 python3-jaraco.text all 4.0.0-1 [11.4 kB] Get: 94 http://deb.debian.org/debian trixie/main arm64 python3-zipp all 3.21.0-1 [10.6 kB] Get: 95 http://deb.debian.org/debian trixie/main arm64 python3-setuptools all 75.6.0-1 [720 kB] Get: 96 http://deb.debian.org/debian trixie/main arm64 dh-python all 6.20250108 [113 kB] Get: 97 http://deb.debian.org/debian trixie/main arm64 fonts-font-awesome all 5.0.10+really4.7.0~dfsg-4.1 [517 kB] Get: 98 http://deb.debian.org/debian trixie/main arm64 fonts-glyphicons-halflings all 1.009~3.4.1+dfsg-3 [162 kB] Get: 99 http://deb.debian.org/debian trixie/main arm64 fonts-lyx all 2.4.2.1-1 [190 kB] Get: 100 http://deb.debian.org/debian trixie/main arm64 libdw1t64 arm64 0.192-4 [237 kB] Get: 101 http://deb.debian.org/debian trixie/main arm64 libglib2.0-0t64 arm64 2.82.4-2 [1413 kB] Get: 102 http://deb.debian.org/debian trixie/main arm64 libbabeltrace1 arm64 1.5.11-4+b1 [164 kB] Get: 103 http://deb.debian.org/debian trixie/main arm64 libidn2-0 arm64 2.3.7-2+b1 [127 kB] Get: 104 http://deb.debian.org/debian trixie/main arm64 libp11-kit0 arm64 0.25.5-3 [409 kB] Get: 105 http://deb.debian.org/debian trixie/main arm64 libtasn1-6 arm64 4.19.0-3+b3 [46.9 kB] Get: 106 http://deb.debian.org/debian trixie/main arm64 libgnutls30t64 arm64 3.8.8-2 [1363 kB] Get: 107 http://deb.debian.org/debian trixie/main arm64 libsasl2-modules-db arm64 2.1.28+dfsg1-8+b1 [20.3 kB] Get: 108 http://deb.debian.org/debian trixie/main arm64 libsasl2-2 arm64 2.1.28+dfsg1-8+b1 [55.7 kB] Get: 109 http://deb.debian.org/debian trixie/main arm64 libldap2 arm64 2.6.9+dfsg-1 [179 kB] Get: 110 http://deb.debian.org/debian trixie/main arm64 libnghttp2-14 arm64 1.64.0-1 [71.3 kB] Get: 111 http://deb.debian.org/debian trixie/main arm64 libnghttp3-9 arm64 1.6.0-2 [60.5 kB] Get: 112 http://deb.debian.org/debian trixie/main arm64 libngtcp2-16 arm64 1.9.1-1 [109 kB] Get: 113 http://deb.debian.org/debian trixie/main arm64 libngtcp2-crypto-gnutls8 arm64 1.9.1-1 [17.3 kB] Get: 114 http://deb.debian.org/debian trixie/main arm64 libpsl5t64 arm64 0.21.2-1.1+b1 [57.1 kB] Get: 115 http://deb.debian.org/debian trixie/main arm64 librtmp1 arm64 2.4+20151223.gitfa8646d.1-2+b5 [56.8 kB] Get: 116 http://deb.debian.org/debian trixie/main arm64 libssh2-1t64 arm64 1.11.1-1 [235 kB] Get: 117 http://deb.debian.org/debian trixie/main arm64 libcurl3t64-gnutls arm64 8.11.1-1+b1 [331 kB] Get: 118 http://deb.debian.org/debian trixie/main arm64 libjson-c5 arm64 0.18+ds-1 [45.2 kB] Get: 119 http://deb.debian.org/debian trixie/main arm64 libdebuginfod1t64 arm64 0.192-4 [31.3 kB] Get: 120 http://deb.debian.org/debian trixie/main arm64 libpython3.13-stdlib arm64 3.13.1-3 [1912 kB] Get: 121 http://deb.debian.org/debian trixie/main arm64 libpython3.13 arm64 3.13.1-3 [1971 kB] Get: 122 http://deb.debian.org/debian trixie/main arm64 libsource-highlight-common all 3.1.9-4.3 [77.5 kB] Get: 123 http://deb.debian.org/debian trixie/main arm64 libsource-highlight4t64 arm64 3.1.9-4.3+b1 [294 kB] Get: 124 http://deb.debian.org/debian trixie/main arm64 gdb arm64 15.2-1+b1 [4159 kB] Get: 125 http://deb.debian.org/debian trixie/main arm64 libaec0 arm64 1.1.3-1+b1 [22.5 kB] Get: 126 http://deb.debian.org/debian trixie/main arm64 libblas3 arm64 3.12.0-4 [98.7 kB] Get: 127 http://deb.debian.org/debian trixie/main arm64 libcurl4t64 arm64 8.11.1-1+b1 [324 kB] Get: 128 http://deb.debian.org/debian trixie/main arm64 libdeflate0 arm64 1.23-1+b1 [42.5 kB] Get: 129 http://deb.debian.org/debian trixie/main arm64 libfribidi0 arm64 1.0.16-1 [26.5 kB] Get: 130 http://deb.debian.org/debian trixie/main arm64 libgpg-error0 arm64 1.51-3 [78.5 kB] Get: 131 http://deb.debian.org/debian trixie/main arm64 libgcrypt20 arm64 1.11.0-7 [742 kB] Get: 132 http://deb.debian.org/debian trixie/main arm64 libgfortran5 arm64 14.2.0-12 [361 kB] Get: 133 http://deb.debian.org/debian trixie/main arm64 libgraphite2-3 arm64 1.3.14-2+b1 [70.4 kB] Get: 134 http://deb.debian.org/debian trixie/main arm64 libharfbuzz0b arm64 10.2.0-1 [443 kB] Get: 135 http://deb.debian.org/debian trixie/main arm64 libsz2 arm64 1.1.3-1+b1 [8044 B] Get: 136 http://deb.debian.org/debian trixie/main arm64 libhdf5-310 arm64 1.14.5+repack-3 [1155 kB] Get: 137 http://deb.debian.org/debian trixie/main arm64 libhdf5-hl-310 arm64 1.14.5+repack-3 [66.1 kB] Get: 138 http://deb.debian.org/debian trixie/main arm64 libimagequant0 arm64 2.18.0-1+b2 [34.6 kB] Get: 139 http://deb.debian.org/debian trixie/main arm64 libjbig0 arm64 2.1-6.1+b2 [30.4 kB] Get: 140 http://deb.debian.org/debian trixie/main arm64 libjpeg62-turbo arm64 1:2.1.5-3+b1 [173 kB] Get: 141 http://deb.debian.org/debian trixie/main arm64 libjs-bootstrap all 3.4.1+dfsg-3 [172 kB] Get: 142 http://deb.debian.org/debian trixie/main arm64 libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [326 kB] Get: 143 http://deb.debian.org/debian trixie/main arm64 libjs-jquery-ui all 1.13.2+dfsg-1 [250 kB] Get: 144 http://deb.debian.org/debian trixie/main arm64 liblapack3 arm64 3.12.0-4 [1812 kB] Get: 145 http://deb.debian.org/debian trixie/main arm64 liblbfgsb0 arm64 3.0+dfsg.4-1+b2 [25.6 kB] Get: 146 http://deb.debian.org/debian trixie/main arm64 liblcms2-2 arm64 2.16-2 [151 kB] Get: 147 http://deb.debian.org/debian trixie/main arm64 liblerc4 arm64 4.0.0+ds-5 [146 kB] Get: 148 http://deb.debian.org/debian trixie/main arm64 liblzf1 arm64 3.6-4+b3 [10.1 kB] Get: 149 http://deb.debian.org/debian trixie/main arm64 libnorm1t64 arm64 1.5.9+dfsg-3.1+b2 [205 kB] Get: 150 http://deb.debian.org/debian trixie/main arm64 libopenjp2-7 arm64 2.5.0-2+b4 [185 kB] Get: 151 http://deb.debian.org/debian trixie/main arm64 libpgm-5.3-0t64 arm64 5.3.128~dfsg-2.1+b1 [152 kB] Get: 152 http://deb.debian.org/debian trixie/main arm64 libqhull-r8.0 arm64 2020.2-6+b2 [229 kB] Get: 153 http://deb.debian.org/debian trixie/main arm64 libraqm0 arm64 0.10.2-1 [13.6 kB] Get: 154 http://deb.debian.org/debian trixie/main arm64 libsharpyuv0 arm64 1.5.0-0.1 [114 kB] Get: 155 http://deb.debian.org/debian trixie/main arm64 libsodium23 arm64 1.0.18-1+b2 [121 kB] Get: 156 http://deb.debian.org/debian trixie/main arm64 libsymspg2 arm64 2.5.0-1+b1 [192 kB] Get: 157 http://deb.debian.org/debian trixie/main arm64 libwebp7 arm64 1.5.0-0.1 [271 kB] Get: 158 http://deb.debian.org/debian trixie/main arm64 libtiff6 arm64 4.5.1+git230720-5 [309 kB] Get: 159 http://deb.debian.org/debian trixie/main arm64 libwebpdemux2 arm64 1.5.0-0.1 [113 kB] Get: 160 http://deb.debian.org/debian trixie/main arm64 libwebpmux3 arm64 1.5.0-0.1 [125 kB] Get: 161 http://deb.debian.org/debian trixie/main arm64 libxslt1.1 arm64 1.1.35-1.1+b1 [222 kB] Get: 162 http://deb.debian.org/debian trixie/main arm64 libyaml-0-2 arm64 0.2.5-2 [49.2 kB] Get: 163 http://deb.debian.org/debian trixie/main arm64 libzmq5 arm64 4.3.5-1+b3 [253 kB] Get: 164 http://deb.debian.org/debian trixie/main arm64 python3-packaging all 24.2-1 [55.3 kB] Get: 165 http://deb.debian.org/debian trixie/main arm64 python3-pyproject-hooks all 1.2.0-1 [11.7 kB] Get: 166 http://deb.debian.org/debian trixie/main arm64 python3-toml all 0.10.2-1 [16.2 kB] Get: 167 http://deb.debian.org/debian trixie/main arm64 python3-wheel all 0.45.1-1 [56.7 kB] Get: 168 http://deb.debian.org/debian trixie/main arm64 python3-build all 1.2.2-1 [36.0 kB] Get: 169 http://deb.debian.org/debian trixie/main arm64 python3-installer all 0.7.0+dfsg1-3 [18.6 kB] Get: 170 http://deb.debian.org/debian trixie/main arm64 pybuild-plugin-pyproject all 6.20250108 [11.6 kB] Get: 171 http://deb.debian.org/debian trixie/main arm64 python-matplotlib-data all 3.8.3-3 [2731 kB] Get: 172 http://deb.debian.org/debian trixie/main arm64 python3.13 arm64 3.13.1-3 [740 kB] Get: 173 http://deb.debian.org/debian trixie/main arm64 python3-all arm64 3.12.8-1 [1048 B] Get: 174 http://deb.debian.org/debian trixie/main arm64 python3-numpy arm64 1:1.26.4+ds-12 [3816 kB] Get: 175 http://deb.debian.org/debian trixie/main arm64 python3-decorator all 5.1.1-5 [15.1 kB] Get: 176 http://deb.debian.org/debian trixie/main arm64 python3-scipy arm64 1.14.1-3 [18.5 MB] Get: 177 http://deb.debian.org/debian trixie/main arm64 python3-spglib arm64 2.5.0-1+b1 [52.1 kB] Get: 178 http://deb.debian.org/debian trixie/main arm64 python3-dateutil all 2.9.0-3 [79.3 kB] Get: 179 http://deb.debian.org/debian trixie/main arm64 python3-pil arm64 10.4.0-1.1 [498 kB] Get: 180 http://deb.debian.org/debian trixie/main arm64 python3.12-tk arm64 3.12.8-5 [111 kB] Get: 181 http://deb.debian.org/debian trixie/main arm64 python3.13-tk arm64 3.13.1-3 [101 kB] Get: 182 http://deb.debian.org/debian trixie/main arm64 python3-tk arm64 3.13.1-1 [9464 B] Get: 183 http://deb.debian.org/debian trixie/main arm64 python3-pil.imagetk arm64 10.4.0-1.1 [79.7 kB] Get: 184 http://deb.debian.org/debian trixie/main arm64 python3-pyparsing all 3.1.2-1 [146 kB] Get: 185 http://deb.debian.org/debian trixie/main arm64 python3-contourpy arm64 1.3.1-1 [237 kB] Get: 186 http://deb.debian.org/debian trixie/main arm64 python3-cycler all 0.12.1-1 [9496 B] Get: 187 http://deb.debian.org/debian trixie/main arm64 python3-brotli arm64 1.1.0-2+b6 [306 kB] Get: 188 http://deb.debian.org/debian trixie/main arm64 python3-tz all 2024.2-1 [31.0 kB] Get: 189 http://deb.debian.org/debian trixie/main arm64 python3-platformdirs all 4.3.6-1 [16.6 kB] Get: 190 http://deb.debian.org/debian trixie/main arm64 python3-fs all 2.4.16-6 [95.1 kB] Get: 191 http://deb.debian.org/debian trixie/main arm64 python3-lxml arm64 5.3.0-1+b1 [1433 kB] Get: 192 http://deb.debian.org/debian trixie/main arm64 python3-lz4 arm64 4.4.0+dfsg-1 [25.6 kB] Get: 193 http://deb.debian.org/debian trixie/main arm64 python3-mpmath all 1.3.0-1 [419 kB] Get: 194 http://deb.debian.org/debian trixie/main arm64 python3-sympy all 1.13.3-1 [4147 kB] Get: 195 http://deb.debian.org/debian trixie/main arm64 python3-attr all 24.3.0-1 [68.8 kB] Get: 196 http://deb.debian.org/debian trixie/main arm64 python3-ufolib2 all 0.17.0+dfsg1-1 [33.0 kB] Get: 197 http://deb.debian.org/debian trixie/main arm64 unicode-data all 15.1.0-1 [8547 kB] Get: 198 http://deb.debian.org/debian trixie/main arm64 python3-fonttools arm64 4.55.3-1 [1501 kB] Get: 199 http://deb.debian.org/debian trixie/main arm64 python3-kiwisolver arm64 1.4.7-2+b1 [71.6 kB] Get: 200 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib arm64 3.8.3-3+b1 [5586 kB] Get: 201 http://deb.debian.org/debian trixie/main arm64 python3-ase all 3.23.0-1 [1698 kB] Get: 202 http://deb.debian.org/debian trixie/main arm64 python3-asttokens all 3.0.0-1 [20.1 kB] Get: 203 http://deb.debian.org/debian trixie/main arm64 python3-cffi-backend arm64 1.17.1-2+b1 [94.8 kB] Get: 204 http://deb.debian.org/debian trixie/main arm64 python3-click all 8.1.8-1 [95.2 kB] Get: 205 http://deb.debian.org/debian trixie/main arm64 python3-cloudpickle all 3.1.0-1 [26.4 kB] Get: 206 http://deb.debian.org/debian trixie/main arm64 python3-traitlets all 5.14.3+really5.14.3-1 [70.9 kB] Get: 207 http://deb.debian.org/debian trixie/main arm64 python3-comm all 0.2.1-1 [8104 B] Get: 208 http://deb.debian.org/debian trixie/main arm64 python3-coverage arm64 7.6.0+dfsg1-2+b1 [177 kB] Get: 209 http://deb.debian.org/debian trixie/main arm64 python3-toolz all 1.0.0-2 [44.2 kB] Get: 210 http://deb.debian.org/debian trixie/main arm64 python3-cytoolz arm64 1.0.1-1 [351 kB] Get: 211 http://deb.debian.org/debian trixie/main arm64 python3-fsspec all 2024.10.0-1 [206 kB] Get: 212 http://deb.debian.org/debian trixie/main arm64 python3-locket all 1.0.0-2 [5820 B] Get: 213 http://deb.debian.org/debian trixie/main arm64 python3-partd all 1.4.2-1 [15.4 kB] Get: 214 http://deb.debian.org/debian trixie/main arm64 python3-yaml arm64 6.0.2-1+b1 [148 kB] Get: 215 http://deb.debian.org/debian trixie/main arm64 python3-dask all 2024.12.1+dfsg-1 [984 kB] Get: 216 http://deb.debian.org/debian trixie/main arm64 python3-debugpy arm64 1.8.8+ds-2 [980 kB] Get: 217 http://deb.debian.org/debian trixie/main arm64 python3-markupsafe arm64 2.1.5-1+b3 [14.0 kB] Get: 218 http://deb.debian.org/debian trixie/main arm64 python3-jinja2 all 3.1.3-2 [120 kB] Get: 219 http://deb.debian.org/debian trixie/main arm64 python3-msgpack arm64 1.0.3-3+b4 [96.8 kB] Get: 220 http://deb.debian.org/debian trixie/main arm64 python3-psutil arm64 5.9.8-2+b1 [226 kB] Get: 221 http://deb.debian.org/debian trixie/main arm64 python3-sortedcontainers all 2.4.0-2 [31.9 kB] Get: 222 http://deb.debian.org/debian trixie/main arm64 python3-tblib all 3.0.0-6 [13.8 kB] Get: 223 http://deb.debian.org/debian trixie/main arm64 python3-tornado arm64 6.4.2-1 [349 kB] Get: 224 http://deb.debian.org/debian trixie/main arm64 python3-urllib3 all 2.2.3-4 [112 kB] Get: 225 http://deb.debian.org/debian trixie/main arm64 python3-zict all 3.0.0-2 [29.7 kB] Get: 226 http://deb.debian.org/debian trixie/main arm64 python3-distributed all 2024.12.1+ds-1 [1162 kB] Get: 227 http://deb.debian.org/debian trixie/main arm64 python3-executing all 2.1.0-0.1 [23.9 kB] Get: 228 http://deb.debian.org/debian trixie/main arm64 python3-h5py-serial arm64 3.12.1-1+b1 [1244 kB] Get: 229 http://deb.debian.org/debian trixie/main arm64 python3-h5py all 3.12.1-1 [15.0 kB] Get: 230 http://deb.debian.org/debian trixie/main arm64 python3-parso all 0.8.4-1 [67.8 kB] Get: 231 http://deb.debian.org/debian trixie/main arm64 python3-typeshed all 0.0~git20241223.ea91db2-1 [1530 kB] Get: 232 http://deb.debian.org/debian trixie/main arm64 python3-jedi all 0.19.1+ds1-1 [691 kB] Get: 233 http://deb.debian.org/debian trixie/main arm64 python3-matplotlib-inline all 0.1.6-2 [8652 B] Get: 234 http://deb.debian.org/debian trixie/main arm64 python3-wcwidth all 0.2.13+dfsg1-1 [24.9 kB] Get: 235 http://deb.debian.org/debian trixie/main arm64 python3-prompt-toolkit all 3.0.48-1 [277 kB] Get: 236 http://deb.debian.org/debian trixie/main arm64 python3-pygments all 2.18.0+dfsg-2 [836 kB] Get: 237 http://deb.debian.org/debian trixie/main arm64 python3-pure-eval all 0.2.3-1 [11.2 kB] Get: 238 http://deb.debian.org/debian trixie/main arm64 python3-stack-data all 0.6.3-1 [21.6 kB] Get: 239 http://deb.debian.org/debian trixie/main arm64 python3-ptyprocess all 0.7.0-6 [14.5 kB] Get: 240 http://deb.debian.org/debian trixie/main arm64 python3-pexpect all 4.9-3 [55.6 kB] Get: 241 http://deb.debian.org/debian trixie/main arm64 python3-ipython all 8.30.0-2 [568 kB] Get: 242 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-core all 5.7.2-5 [35.3 kB] Get: 243 http://deb.debian.org/debian trixie/main arm64 python3-zmq arm64 26.2.0-1 [193 kB] Get: 244 http://deb.debian.org/debian trixie/main arm64 python3-jupyter-client all 8.6.3-2 [92.4 kB] Get: 245 http://deb.debian.org/debian trixie/main arm64 python3-nest-asyncio all 1.5.4-1 [6248 B] Get: 246 http://deb.debian.org/debian trixie/main arm64 python3-ipykernel all 6.29.5-2 [102 kB] Get: 247 http://deb.debian.org/debian trixie/main arm64 python3-ipywidgets all 8.1.5-3 [105 kB] Get: 248 http://deb.debian.org/debian trixie/main arm64 python3-joblib all 1.3.2-5 [216 kB] Get: 249 http://deb.debian.org/debian trixie/main arm64 python3-threadpoolctl all 3.1.0-1 [21.2 kB] Get: 250 http://deb.debian.org/debian trixie/main arm64 python3-sklearn-lib arm64 1.4.2+dfsg-7 [5392 kB] Get: 251 http://deb.debian.org/debian trixie/main arm64 python3-sklearn all 1.4.2+dfsg-7 [2248 kB] Get: 252 http://deb.debian.org/debian trixie/main arm64 python3-sidpy all 0.12.3-3 [76.9 kB] Fetched 134 MB in 1s (168 MB/s) Preconfiguring packages ... Selecting previously unselected package libtext-charwidth-perl:arm64. (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 ... 19970 files and directories currently installed.) Preparing to unpack .../0-libtext-charwidth-perl_0.04-11+b4_arm64.deb ... Unpacking libtext-charwidth-perl:arm64 (0.04-11+b4) ... Selecting previously unselected package libtext-wrapi18n-perl. Preparing to unpack .../1-libtext-wrapi18n-perl_0.06-10_all.deb ... Unpacking libtext-wrapi18n-perl (0.06-10) ... 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Selecting previously unselected package libexpat1:arm64. Preparing to unpack .../8-libexpat1_2.6.4-1_arm64.deb ... Unpacking libexpat1:arm64 (2.6.4-1) ... Selecting previously unselected package python3.12-minimal. Preparing to unpack .../9-python3.12-minimal_3.12.8-5_arm64.deb ... Unpacking python3.12-minimal (3.12.8-5) ... Setting up libpython3.12-minimal:arm64 (3.12.8-5) ... Setting up libexpat1:arm64 (2.6.4-1) ... Setting up python3.12-minimal (3.12.8-5) ... Selecting previously unselected package python3-minimal. (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 ... 20560 files and directories currently installed.) Preparing to unpack .../00-python3-minimal_3.12.8-1_arm64.deb ... Unpacking python3-minimal (3.12.8-1) ... Selecting previously unselected package media-types. Preparing to unpack .../01-media-types_10.1.0_all.deb ... Unpacking media-types (10.1.0) ... Selecting previously unselected package netbase. Preparing to unpack .../02-netbase_6.4_all.deb ... Unpacking netbase (6.4) ... 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Selecting previously unselected package libnsl2:arm64. Preparing to unpack .../13-libnsl2_1.3.0-3+b3_arm64.deb ... Unpacking libnsl2:arm64 (1.3.0-3+b3) ... Selecting previously unselected package readline-common. Preparing to unpack .../14-readline-common_8.2-6_all.deb ... Unpacking readline-common (8.2-6) ... Selecting previously unselected package libreadline8t64:arm64. Preparing to unpack .../15-libreadline8t64_8.2-6_arm64.deb ... Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8 to /lib/aarch64-linux-gnu/libhistory.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8.2 to /lib/aarch64-linux-gnu/libhistory.so.8.2.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8 to /lib/aarch64-linux-gnu/libreadline.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8.2 to /lib/aarch64-linux-gnu/libreadline.so.8.2.usr-is-merged by libreadline8t64' Unpacking libreadline8t64:arm64 (8.2-6) ... Selecting previously unselected package libpython3.12-stdlib:arm64. Preparing to unpack .../16-libpython3.12-stdlib_3.12.8-5_arm64.deb ... Unpacking libpython3.12-stdlib:arm64 (3.12.8-5) ... Selecting previously unselected package python3.12. Preparing to unpack .../17-python3.12_3.12.8-5_arm64.deb ... Unpacking python3.12 (3.12.8-5) ... Selecting previously unselected package libpython3-stdlib:arm64. Preparing to unpack .../18-libpython3-stdlib_3.12.8-1_arm64.deb ... Unpacking libpython3-stdlib:arm64 (3.12.8-1) ... Setting up python3-minimal (3.12.8-1) ... Selecting previously unselected package python3. (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 ... 21628 files and directories currently installed.) Preparing to unpack .../000-python3_3.12.8-1_arm64.deb ... Unpacking python3 (3.12.8-1) ... Selecting previously unselected package libpython3.13-minimal:arm64. Preparing to unpack .../001-libpython3.13-minimal_3.13.1-3_arm64.deb ... Unpacking libpython3.13-minimal:arm64 (3.13.1-3) ... Selecting previously unselected package python3.13-minimal. Preparing to unpack .../002-python3.13-minimal_3.13.1-3_arm64.deb ... Unpacking python3.13-minimal (3.13.1-3) ... Selecting previously unselected package openssl. Preparing to unpack .../003-openssl_3.4.0-2_arm64.deb ... Unpacking openssl (3.4.0-2) ... Selecting previously unselected package ca-certificates. Preparing to unpack .../004-ca-certificates_20241223_all.deb ... Unpacking ca-certificates (20241223) ... Selecting previously unselected package libmagic-mgc. Preparing to unpack .../005-libmagic-mgc_1%3a5.45-3+b1_arm64.deb ... Unpacking libmagic-mgc (1:5.45-3+b1) ... Selecting previously unselected package libmagic1t64:arm64. Preparing to unpack .../006-libmagic1t64_1%3a5.45-3+b1_arm64.deb ... Unpacking libmagic1t64:arm64 (1:5.45-3+b1) ... Selecting previously unselected package file. Preparing to unpack .../007-file_1%3a5.45-3+b1_arm64.deb ... Unpacking file (1:5.45-3+b1) ... Selecting previously unselected package gettext-base. Preparing to unpack .../008-gettext-base_0.22.5-4_arm64.deb ... Unpacking gettext-base (0.22.5-4) ... Selecting previously unselected package libuchardet0:arm64. Preparing to unpack .../009-libuchardet0_0.0.8-1+b2_arm64.deb ... Unpacking libuchardet0:arm64 (0.0.8-1+b2) ... Selecting previously unselected package groff-base. Preparing to unpack .../010-groff-base_1.23.0-7_arm64.deb ... Unpacking groff-base (1.23.0-7) ... Selecting previously unselected package bsdextrautils. Preparing to unpack .../011-bsdextrautils_2.40.4-1_arm64.deb ... Unpacking bsdextrautils (2.40.4-1) ... Selecting previously unselected package libpipeline1:arm64. Preparing to unpack .../012-libpipeline1_1.5.8-1_arm64.deb ... Unpacking libpipeline1:arm64 (1.5.8-1) ... 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Unpacking libtcl8.6:arm64 (8.6.16+dfsg-1) ... Selecting previously unselected package libbrotli1:arm64. Preparing to unpack .../020-libbrotli1_1.1.0-2+b6_arm64.deb ... Unpacking libbrotli1:arm64 (1.1.0-2+b6) ... Selecting previously unselected package libpng16-16t64:arm64. Preparing to unpack .../021-libpng16-16t64_1.6.44-3_arm64.deb ... Unpacking libpng16-16t64:arm64 (1.6.44-3) ... Selecting previously unselected package libfreetype6:arm64. Preparing to unpack .../022-libfreetype6_2.13.3+dfsg-1_arm64.deb ... Unpacking libfreetype6:arm64 (2.13.3+dfsg-1) ... Selecting previously unselected package fonts-dejavu-mono. Preparing to unpack .../023-fonts-dejavu-mono_2.37-8_all.deb ... Unpacking fonts-dejavu-mono (2.37-8) ... Selecting previously unselected package fonts-dejavu-core. Preparing to unpack .../024-fonts-dejavu-core_2.37-8_all.deb ... Unpacking fonts-dejavu-core (2.37-8) ... Selecting previously unselected package fontconfig-config. Preparing to unpack .../025-fontconfig-config_2.15.0-2_arm64.deb ... Unpacking fontconfig-config (2.15.0-2) ... Selecting previously unselected package libfontconfig1:arm64. Preparing to unpack .../026-libfontconfig1_2.15.0-2_arm64.deb ... Unpacking libfontconfig1:arm64 (2.15.0-2) ... Selecting previously unselected package libxau6:arm64. Preparing to unpack .../027-libxau6_1%3a1.0.11-1_arm64.deb ... Unpacking libxau6:arm64 (1:1.0.11-1) ... Selecting previously unselected package libxdmcp6:arm64. Preparing to unpack .../028-libxdmcp6_1%3a1.1.5-1_arm64.deb ... Unpacking libxdmcp6:arm64 (1:1.1.5-1) ... Selecting previously unselected package libxcb1:arm64. Preparing to unpack .../029-libxcb1_1.17.0-2+b1_arm64.deb ... Unpacking libxcb1:arm64 (1.17.0-2+b1) ... Selecting previously unselected package libx11-data. Preparing to unpack .../030-libx11-data_2%3a1.8.10-2_all.deb ... Unpacking libx11-data (2:1.8.10-2) ... Selecting previously unselected package libx11-6:arm64. 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Setting up libjbig0:arm64 (2.1-6.1+b2) ... Setting up libaec0:arm64 (1.1.3-1+b1) ... Setting up libsource-highlight-common (3.1.9-4.3) ... Setting up libelf1t64:arm64 (0.192-4) ... Setting up libkrb5support0:arm64 (1.21.3-3) ... Setting up libdw1t64:arm64 (0.192-4) ... Setting up libsasl2-modules-db:arm64 (2.1.28+dfsg1-8+b1) ... Setting up tzdata (2024b-6) ... Current default time zone: 'Etc/UTC' Local time is now: Mon Feb 23 16:38:38 UTC 2026. Universal Time is now: Mon Feb 23 16:38:38 UTC 2026. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up unicode-data (15.1.0-1) ... Setting up libsymspg2:arm64 (2.5.0-1+b1) ... Setting up libpython3.13-minimal:arm64 (3.13.1-3) ... Setting up libpgm-5.3-0t64:arm64 (5.3.128~dfsg-2.1+b1) ... Setting up autotools-dev (20220109.1) ... 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Setting up libldap2:arm64 (2.6.9+dfsg-1) ... Setting up libsz2:arm64 (1.1.3-1+b1) ... Setting up libjs-bootstrap (3.4.1+dfsg-3) ... Setting up automake (1:1.16.5-1.3) ... update-alternatives: using /usr/bin/automake-1.16 to provide /usr/bin/automake (automake) in auto mode Setting up libfile-stripnondeterminism-perl (1.14.0-1) ... Setting up liblapack3:arm64 (3.12.0-4) ... update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/aarch64-linux-gnu/liblapack.so.3 (liblapack.so.3-aarch64-linux-gnu) in auto mode Setting up gettext (0.22.5-4) ... Setting up libxrender1:arm64 (1:0.9.10-1.1+b3) ... Setting up libtool (2.5.4-2) ... Setting up fontconfig-config (2.15.0-2) ... Setting up libwebpdemux2:arm64 (1.5.0-0.1) ... Setting up libxext6:arm64 (2:1.3.4-1+b3) ... Setting up libidn2-0:arm64 (2.3.7-2+b1) ... Setting up libsource-highlight4t64:arm64 (3.1.9-4.3+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up dh-autoreconf (20) ... Setting up ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 152 added, 0 removed; done. Setting up libglib2.0-0t64:arm64 (2.82.4-2) ... No schema files found: doing nothing. Setting up libjs-jquery-ui (1.13.2+dfsg-1) ... Setting up libfreetype6:arm64 (2.13.3+dfsg-1) ... Setting up libp11-kit0:arm64 (0.25.5-3) ... Setting up libgssapi-krb5-2:arm64 (1.21.3-3) ... Setting up ucf (3.0048) ... Setting up libbabeltrace1:arm64 (1.5.11-4+b1) ... Setting up libreadline8t64:arm64 (8.2-6) ... Setting up dh-strip-nondeterminism (1.14.0-1) ... Setting up groff-base (1.23.0-7) ... Setting up libxslt1.1:arm64 (1.1.35-1.1+b1) ... Setting up libharfbuzz0b:arm64 (10.2.0-1) ... Setting up libxss1:arm64 (1:1.2.3-1+b3) ... Setting up libfontconfig1:arm64 (2.15.0-2) ... Setting up libpython3.13-stdlib:arm64 (3.13.1-3) ... Setting up liblbfgsb0:arm64 (3.0+dfsg.4-1+b2) ... Setting up libpython3.13:arm64 (3.13.1-3) ... Setting up libgnutls30t64:arm64 (3.8.8-2) ... Setting up libxft2:arm64 (2.3.6-1+b3) ... Setting up libzmq5:arm64 (4.3.5-1+b3) ... Setting up libdebuginfod-common (0.192-4) ... Setting up libtirpc3t64:arm64 (1.3.4+ds-1.3+b1) ... Setting up python3.13 (3.13.1-3) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libtk8.6:arm64 (8.6.16-1) ... Setting up python3.12-tk (3.12.8-5) ... Setting up libpsl5t64:arm64 (0.21.2-1.1+b1) ... Setting up man-db (2.13.0-1) ... Not building database; man-db/auto-update is not 'true'. Setting up python3.13-tk (3.13.1-3) ... Setting up librtmp1:arm64 (2.4+20151223.gitfa8646d.1-2+b5) ... Setting up libraqm0:arm64 (0.10.2-1) ... Setting up libnsl2:arm64 (1.3.0-3+b3) ... Setting up libngtcp2-crypto-gnutls8:arm64 (1.9.1-1) ... Setting up tk8.6-blt2.5 (2.5.3+dfsg-7+b1) ... Setting up libpython3.12-stdlib:arm64 (3.12.8-5) ... Setting up libcurl4t64:arm64 (8.11.1-1+b1) ... Setting up blt (2.5.3+dfsg-7+b1) ... Setting up python3.12 (3.12.8-5) ... Setting up libcurl3t64-gnutls:arm64 (8.11.1-1+b1) ... Setting up debhelper (13.23) ... Setting up libhdf5-310:arm64 (1.14.5+repack-3) ... Setting up libpython3-stdlib:arm64 (3.12.8-1) ... Setting up libhdf5-hl-310:arm64 (1.14.5+repack-3) ... Setting up libdebuginfod1t64:arm64 (0.192-4) ... Setting up python3 (3.12.8-1) ... Setting up python3-sortedcontainers (2.4.0-2) ... Setting up python3-zipp (3.21.0-1) ... Setting up python3-click (8.1.8-1) ... Setting up python3-autocommand (2.2.2-3) ... Setting up python3-markupsafe (2.1.5-1+b3) ... Setting up python3-wheel (0.45.1-1) ... Setting up python3-platformdirs (4.3.6-1) ... Setting up python3-psutil (5.9.8-2+b1) ... Setting up python3-tz (2024.2-1) ... Setting up python3-cloudpickle (3.1.0-1) ... Setting up python3-fs (2.4.16-6) ... Setting up python3-pil:arm64 (10.4.0-1.1) ... Setting up python3-decorator (5.1.1-5) ... Setting up python3-jinja2 (3.1.3-2) ... Setting up python3-pygments (2.18.0+dfsg-2) ... Setting up python3-packaging (24.2-1) ... Setting up gdb (15.2-1+b1) ... Setting up python3-wcwidth (0.2.13+dfsg1-1) ... Setting up python3-pyproject-hooks (1.2.0-1) ... Setting up python3-pyparsing (3.1.2-1) ... Setting up python3-typeshed (0.0~git20241223.ea91db2-1) ... Setting up python3-nest-asyncio (1.5.4-1) ... Setting up python3-brotli (1.1.0-2+b6) ... Setting up python3-cycler (0.12.1-1) ... Setting up python3-kiwisolver (1.4.7-2+b1) ... Setting up python3-typing-extensions (4.12.2-2) ... Setting up python3-toml (0.10.2-1) ... Setting up python3-installer (0.7.0+dfsg1-3) ... Setting up python3-urllib3 (2.2.3-4) ... Setting up python3-lxml:arm64 (5.3.0-1+b1) ... Setting up python3-traitlets (5.14.3+really5.14.3-1) ... Setting up python3-toolz (1.0.0-2) ... Setting up python3-dateutil (2.9.0-3) ... Setting up python3-msgpack (1.0.3-3+b4) ... Setting up python3-mpmath (1.3.0-1) ... Setting up python3-build (1.2.2-1) ... Setting up python3-zict (3.0.0-2) ... Setting up python3-locket (1.0.0-2) ... Setting up python3-jupyter-core (5.7.2-5) ... Setting up python3-cffi-backend:arm64 (1.17.1-2+b1) ... Setting up python3-cytoolz (1.0.1-1) ... /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 /usr/lib/python3/dist-packages/cytoolz/tests/test_inspect_args.py:505: SyntaxWarning: "is" with 'int' literal. Did you mean "=="? assert num_required_args(Wrapped) is 1 Setting up python3-ptyprocess (0.7.0-6) ... Setting up python3-prompt-toolkit (3.0.48-1) ... Setting up python3-partd (1.4.2-1) ... Setting up python3-more-itertools (10.6.0-1) ... Setting up python3-sympy (1.13.3-1) ... Setting up python3-attr (24.3.0-1) ... Setting up python3-tornado (6.4.2-1) ... Setting up python3-pure-eval (0.2.3-1) ... Setting up python3-jaraco.functools (4.1.0-1) ... Setting up python3-tblib (3.0.0-6) ... Setting up python3-jaraco.context (6.0.0-1) ... Setting up python3-parso (0.8.4-1) ... Setting up python3-lz4 (4.4.0+dfsg-1) ... Setting up python3-asttokens (3.0.0-1) ... Setting up python3-fsspec (2024.10.0-1) ... Setting up python3-typeguard (4.4.1-1) ... Setting up python3-threadpoolctl (3.1.0-1) ... Setting up python3-all (3.12.8-1) ... Setting up python3-coverage (7.6.0+dfsg1-2+b1) ... Setting up python3-yaml (6.0.2-1+b1) ... Setting up python3-tk:arm64 (3.13.1-1) ... Setting up python3-debugpy (1.8.8+ds-2) ... Setting up python3-matplotlib-inline (0.1.6-2) ... Setting up python3-comm (0.2.1-1) ... Setting up python3-inflect (7.3.1-2) ... Setting up python3-pil.imagetk:arm64 (10.4.0-1.1) ... Setting up python3-executing (2.1.0-0.1) ... Setting up python3-jaraco.text (4.0.0-1) ... Setting up python3-pexpect (4.9-3) ... Setting up python3-zmq (26.2.0-1) ... Setting up python3-jupyter-client (8.6.3-2) ... Setting up python3-stack-data (0.6.3-1) ... Setting up python3-pkg-resources (75.6.0-1) ... Setting up python3-setuptools (75.6.0-1) ... Setting up python3-jedi (0.19.1+ds1-1) ... Setting up python3-joblib (1.3.2-5) ... Setting up python3-dask (2024.12.1+dfsg-1) ... Setting up python3-distributed (2024.12.1+ds-1) ... Setting up python3-ipython (8.30.0-2) ... Setting up python3-ipykernel (6.29.5-2) ... Setting up python3-numpy (1:1.26.4+ds-12) ... Setting up python3-contourpy (1.3.1-1) ... Setting up python3-spglib (2.5.0-1+b1) ... Setting up dh-python (6.20250108) ... Setting up python3-scipy (1.14.1-3) ... Setting up pybuild-plugin-pyproject (6.20250108) ... Setting up python3-sklearn-lib:arm64 (1.4.2+dfsg-7) ... Setting up python3-h5py-serial (3.12.1-1+b1) ... Setting up python3-ipywidgets (8.1.5-3) ... /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters /usr/lib/python3/dist-packages/ipywidgets/widgets/tests/test_traits.py:61: SyntaxWarning: invalid escape sequence '\.' 'var(--my-color-\.)', # CSS variable with escaped characters Setting up python3-h5py (3.12.1-1) ... Setting up python3-sklearn (1.4.2+dfsg-7) ... Setting up python3-fonttools (4.55.3-1) ... Setting up python3-ufolib2 (0.17.0+dfsg1-1) ... Setting up python3-matplotlib (3.8.3-3+b1) ... Setting up python3-ase (3.23.0-1) ... Setting up python3-sidpy (0.12.3-3) ... Processing triggers for libc-bin (2.40-5) ... Processing triggers for ca-certificates (20241223) ... Updating certificates in /etc/ssl/certs... 0 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d... done. Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initializing package states... Writing extended state information... Building tag database... -> Finished parsing the build-deps I: Building the package I: user script /srv/workspace/pbuilder/888831/tmp/hooks/A99_set_merged_usr starting Not re-configuring usrmerge for trixie I: user script /srv/workspace/pbuilder/888831/tmp/hooks/A99_set_merged_usr finished hostname: Name or service not known I: Running cd /build/reproducible-path/pyusid-0.0.12/ && 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 > ../pyusid_0.0.12-2_source.changes dpkg-buildpackage: info: source package pyusid dpkg-buildpackage: info: source version 0.0.12-2 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Roland Mas dpkg-source --before-build . dpkg-buildpackage: info: host architecture arm64 dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ debian/rules clean dh clean --with python3 --buildsystem=pybuild dh_auto_clean -O--buildsystem=pybuild dh_autoreconf_clean -O--buildsystem=pybuild dh_clean -O--buildsystem=pybuild debian/rules binary dh binary --with python3 --buildsystem=pybuild dh_update_autotools_config -O--buildsystem=pybuild dh_autoreconf -O--buildsystem=pybuild dh_auto_configure -O--buildsystem=pybuild dh_auto_build -O--buildsystem=pybuild I: pybuild plugin_pyproject:129: Building wheel for python3.13 with "build" module I: pybuild base:311: python3.13 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py creating build/lib/pyUSID copying pyUSID/__version__.py -> build/lib/pyUSID copying pyUSID/__init__.py -> build/lib/pyUSID creating build/lib/pyUSID/processing copying pyUSID/processing/process.py -> build/lib/pyUSID/processing copying pyUSID/processing/comp_utils.py -> build/lib/pyUSID/processing copying pyUSID/processing/__init__.py -> build/lib/pyUSID/processing creating build/lib/pyUSID/io copying pyUSID/io/usi_data.py -> build/lib/pyUSID/io copying pyUSID/io/reg_ref.py -> build/lib/pyUSID/io copying pyUSID/io/image.py -> build/lib/pyUSID/io copying pyUSID/io/dimension.py -> build/lib/pyUSID/io copying pyUSID/io/array_translator.py -> build/lib/pyUSID/io copying pyUSID/io/anc_build_utils.py -> build/lib/pyUSID/io copying pyUSID/io/__init__.py -> build/lib/pyUSID/io creating build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/simple.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/model.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/base.py -> build/lib/pyUSID/io/hdf_utils copying pyUSID/io/hdf_utils/__init__.py -> build/lib/pyUSID/io/hdf_utils running egg_info creating pyUSID.egg-info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt writing manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/.tmp-0_zbq6u7/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.13 with "installer" module I: pybuild plugin_pyproject:129: Building wheel for python3.12 with "build" module I: pybuild base:311: python3.12 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid * Building wheel... /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'tests_require' warnings.warn(msg) /usr/lib/python3/dist-packages/setuptools/_distutils/dist.py:261: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) running bdist_wheel /usr/lib/python3/dist-packages/setuptools/_distutils/cmd.py:111: SetuptoolsDeprecationWarning: bdist_wheel.universal is deprecated !! ******************************************************************************** With Python 2.7 end-of-life, support for building universal wheels (i.e., wheels that support both Python 2 and Python 3) is being obviated. Please discontinue using this option, or if you still need it, file an issue with pypa/setuptools describing your use case. This deprecation is overdue, please update your project and remove deprecated calls to avoid build errors in the future. ******************************************************************************** !! self.finalize_options() running build running build_py running egg_info writing pyUSID.egg-info/PKG-INFO writing dependency_links to pyUSID.egg-info/dependency_links.txt writing requirements to pyUSID.egg-info/requires.txt writing top-level names to pyUSID.egg-info/top_level.txt reading manifest file 'pyUSID.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no previously-included files matching '*' found under directory 'tests' adding license file 'LICENSE' writing manifest file 'pyUSID.egg-info/SOURCES.txt' installing to build/bdist.linux-aarch64/wheel running install running install_lib creating build/bdist.linux-aarch64/wheel creating build/bdist.linux-aarch64/wheel/pyUSID creating build/bdist.linux-aarch64/wheel/pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/image.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-aarch64/wheel/./pyUSID/io creating build/bdist.linux-aarch64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-aarch64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-aarch64/wheel/./pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-aarch64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-yccmsa5u/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' adding 'pyUSID/io/anc_build_utils.py' adding 'pyUSID/io/array_translator.py' adding 'pyUSID/io/dimension.py' adding 'pyUSID/io/image.py' adding 'pyUSID/io/reg_ref.py' adding 'pyUSID/io/usi_data.py' adding 'pyUSID/io/hdf_utils/__init__.py' adding 'pyUSID/io/hdf_utils/base.py' adding 'pyUSID/io/hdf_utils/model.py' adding 'pyUSID/io/hdf_utils/simple.py' adding 'pyUSID/processing/__init__.py' adding 'pyUSID/processing/comp_utils.py' adding 'pyUSID/processing/process.py' adding 'pyUSID-0.0.12.dist-info/LICENSE' adding 'pyUSID-0.0.12.dist-info/METADATA' adding 'pyUSID-0.0.12.dist-info/WHEEL' adding 'pyUSID-0.0.12.dist-info/top_level.txt' adding 'pyUSID-0.0.12.dist-info/RECORD' removing build/bdist.linux-aarch64/wheel Successfully built pyUSID-0.0.12-py2.py3-none-any.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.12 with "installer" module dh_auto_test -O--buildsystem=pybuild I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build; python3.13 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 4 192] [[ 4] [192]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [232 212] [[232 212]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 30 199] [[ 30] [199]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [167 123] [[167 123]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [216 219] [[216] [219]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [186 124] [[186 124]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [19 81] [[19] [81]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [162 114] [[162 114]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[ 90 68 26] [168 100 224]] [[ 90] [ 68] [ 26] [168] [100] [224]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[106 67 101] [ 90 48 247]] [[106 67 101 90 48 247]] Position dimensions: ['Position Dimension 0'] Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 33 33 223 223 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 18.8 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 18.8 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.717s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file I: pybuild base:311: cd /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build; python3.12 -m unittest discover -v test_legal (tests.io.hdf_utils.test_base.TestFindDataset.test_legal) ... ok test_many (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_many) ... ok test_no_hdf5_datasets (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_no_hdf5_datasets) ... ok test_non_string_names (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_non_string_names) ... ok test_same_name (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_same_name) ... ok test_single (tests.io.hdf_utils.test_base.TestGetH5ObjRefs.test_single) ... ok test_root_all_dsets (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_all_dsets) ... ok test_root_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeBEPS.test_root_main_dsets_only) ... ok test_multi_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths) ... ok test_multi_level_rel_paths_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_rel_paths_grp_b) ... ok test_multi_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree) ... ok test_multi_level_tree_grp_a (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_a) ... ok test_multi_level_tree_grp_b (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_grp_b) ... ok test_multi_level_tree_main_dsets_only (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_multi_level_tree_main_dsets_only) ... ok test_not_a_group (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_not_a_group) ... ok test_single_level_rel_paths (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_rel_paths) ... ok test_single_level_tree (tests.io.hdf_utils.test_base.TestPrintTreeNoMain.test_single_level_tree) ... ok test_dset (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_dset) ... ok test_file (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_file) ... ok test_group (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_group) ... ok test_invalid (tests.io.hdf_utils.test_base.TestWriteBookKeepingAttrs.test_invalid) ... ok test_invalid_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_invalid_sort) ... ok test_legal_no_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_no_sort) ... ok test_legal_w_sort (tests.io.hdf_utils.test_model.TestGetDimensionality.test_legal_w_sort) ... ok test_not_hdf_dset (tests.io.hdf_utils.test_model.TestGetDimensionality.test_not_hdf_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_model.TestGetSortOrder.test_invalid_types) ... ok test_reversed (tests.io.hdf_utils.test_model.TestGetSortOrder.test_reversed) ... ok test_simple (tests.io.hdf_utils.test_model.TestGetSortOrder.test_simple) ... ok test_all_dim_names_not_provided (tests.io.hdf_utils.test_model.TestGetUnitValues.test_all_dim_names_not_provided) ... ok test_dependent_dim (tests.io.hdf_utils.test_model.TestGetUnitValues.test_dependent_dim) ... ok test_illegal_dset (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_dset) ... ok test_illegal_key (tests.io.hdf_utils.test_model.TestGetUnitValues.test_illegal_key) ... ok test_incomp_dim_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_incomp_dim_no_attr) ... ok test_source_pos_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_all) ... ok test_source_pos_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_pos_single) ... ok test_source_spec_all (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all) ... ok test_source_spec_all_explicit (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_all_explicit) ... ok test_source_spec_single (tests.io.hdf_utils.test_model.TestGetUnitValues.test_source_spec_single) ... ok test_sparse_samp_no_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_no_attr) ... ok test_sparse_samp_w_attr (tests.io.hdf_utils.test_model.TestGetUnitValues.test_sparse_samp_w_attr) ... ok test_pos_and_spec_may_may_not_be_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_may_may_not_be_provided) ... ok test_pos_and_spec_provided (tests.io.hdf_utils.test_model.TestReshapeFromNDims.test_pos_and_spec_provided) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:788: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(source_nd, h5_pos=source_pos_data, h5_spec=source_spec_data) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:799: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_pos_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:811: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_spec_sorted, h5_pos=source_pos_data, /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_model.py:823: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. ret_2d, success = hdf_utils.reshape_from_n_dims(main_not_sorted, h5_pos=source_pos_data, ok test_dask_all (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all) ... ok test_dask_all_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_both_inds_order_flipped) ... ok test_dask_all_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_pos) ... ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... ok test_dask_input (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_input) ... ok test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 7 77] [[ 7] [77]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 70 147] [[ 70 147]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [49 31] [[49] [31]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [239 32] [[239 32]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [214 5] [[214] [ 5]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [147 209] [[147 209]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2]ok test_dask_output (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_output) ... ok test_h5_already_sorted (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_already_sorted) ... ok test_h5_beps_field (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_beps_field) ... ok test_h5_both_inds_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_both_inds_flipped) ... ok test_h5_manually_provided_anc_dsets_h5 (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_manually_provided_anc_dsets_h5) ... ok test_h5_not_main_dset (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_h5_not_main_dset) ... ok test_numpy_both_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_both_inds_order_flipped) ... ok test_numpy_ordinary (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary) ... ok test_numpy_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_pos) ... ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) Position dimensions: ['X' 'Y'] Position sort order: [0 1] Spectroscopic Dimensions: ['Bias' 'Cycle'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['X' 'Y'] Position dimensionality (sort applied): [5, 3] Spectroscopic dimensions (sort applied): ['Bias' 'Cycle'] Spectroscopic dimensionality (sort applied): [7, 2] Will attempt to reshape main dataset from: (15, 14) to [3, 5, 2, 7] After reshaping, labels are ['Y' 'X' 'Cycle' 'Bias'] Data shape is (3, 5, 2, 7) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 3 2] New labels ordering: ['X' 'Y' 'Bias' 'Cycle'] Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 91 158] [[ 91] [158]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (2, 1) to [2, 1] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 80 210] [[ 80 210]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [2] Will attempt to reshape main dataset from: (1, 2) to [1, 2] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 0'] Data shape is (1, 2) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0'] Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[198 168 60] [ 56 17 180]] [[198] [168] [ 60] [ 56] [ 17] [180]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] Spectroscopic sort order: [0] Position dimensions (sort applied): ['Position Dimension 0' 'Position Dimension 1'] Position dimensionality (sort applied): [3, 2] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0'] Spectroscopic dimensionality (sort applied): [1] Will attempt to reshape main dataset from: (6, 1) to [2, 3, 1] After reshaping, labels are ['Position Dimension 1' 'Position Dimension 0' 'Spectral Dimension 0'] Data shape is (2, 3, 1) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [1 0 2] New labels ordering: ['Position Dimension 0' 'Position Dimension 1' 'Spectral Dimension 0'] Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[109 211 5] [ 62 14 84]] [[109 211 5 62 14 84]] Position dimensions: ['Position Dimension 0'] Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... ok test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] Position dimensions (sort applied): ['Position Dimension 0'] Position dimensionality (sort applied): [1] Spectroscopic dimensions (sort applied): ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic dimensionality (sort applied): [3, 2] Will attempt to reshape main dataset from: (1, 6) to [1, 2, 3] After reshaping, labels are ['Position Dimension 0' 'Spectral Dimension 1' 'Spectral Dimension 0'] Data shape is (1, 2, 3) Going to put dimensions back in the same order as in the file: Axes will permuted in this order: [0 2 1] New labels ordering: ['Position Dimension 0' 'Spectral Dimension 0' 'Spectral Dimension 1'] Dataset now of shape: (1, 3, 2) h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset: for writing Dask dataset: dask.array Dask array will be written to HDF5 dataset: "/Test_Main" in file: "test.h5" Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Selected empty dataset creation. OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created empty dataset for Main Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OKok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... ok test_existing (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_existing) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_invalid_dtypes) ... ok test_new (tests.io.hdf_utils.test_simple.TestAssignGroupIndex.test_new) ... ok test_h5_main_non_dset_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_non_dset_anc_names) ... ok test_h5_main_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_h5_main_not_dset) ... ok test_linking_main_legit_anc_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_linking_main_legit_anc_names) ... ok test_many_objs_to_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_many_objs_to_many_names) ... ok test_no_anc_refs_provided (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_no_anc_refs_provided) ... ok test_not_dset (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_not_dset) ... ok test_objs_and_refs_to_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_objs_and_refs_to_names) ... ok test_one_dset_to_name (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_one_dset_to_name) ... ok test_too_many_ancs (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_ancs) ... ok test_too_many_names (tests.io.hdf_utils.test_simple.TestCheckAndLinkAncillary.test_too_many_names) ... ok test_dset_matching_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_matching_attrs) ... ok test_dset_no_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_no_attrs) ... ok test_dset_one_mismatched_attrs (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_dset_one_mismatched_attrs) ... ok test_grp (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp) ... ok test_grp_mismatched_types_01 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_01) ... ok test_grp_mismatched_types_02 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_02) ... ok test_grp_mismatched_types_03 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_03) ... ok test_grp_mismatched_types_04 (tests.io.hdf_utils.test_simple.TestCheckForMatchingAttrs.test_grp_mismatched_types_04) ... ok test_exact_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match) ... ok test_exact_match_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_exact_match_02) ... ok test_fail_01 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_01) ... ok test_fail_02 (tests.io.hdf_utils.test_simple.TestCheckForOld.test_fail_02) ... ok test_invalid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_target_dset) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCheckForOld.test_invalid_types) ... ok test_subset_but_match (tests.io.hdf_utils.test_simple.TestCheckForOld.test_subset_but_match) ... ok test_valid_target_dset (tests.io.hdf_utils.test_simple.TestCheckForOld.test_valid_target_dset) ... ok test_anc_not_dsets (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_not_dsets) ... ok test_anc_shapes_not_matching (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_anc_shapes_not_matching) ... ok test_illegal_01 (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_illegal_01) ... ok test_invalid_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_invalid_str_attrs) ... ok test_legal (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_legal) ... ok test_missing_str_attrs (tests.io.hdf_utils.test_simple.TestCheckIfMain.test_missing_str_attrs) ... ok test_no_main_attrs (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_no_main_attrs) ... ok test_valid (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_valid) ... ok test_wrong_objects (tests.io.hdf_utils.test_simple.TestCopyMainAttributes.test_wrong_objects) ... ok test_diff_file_new_attrs_linked_dsets (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_file_new_attrs_linked_dsets) ... ok test_diff_groups (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_diff_groups) ... ok test_existing_dset_name (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_existing_dset_name) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_invalid_types) ... ok test_same_group_new_attrs (tests.io.hdf_utils.test_simple.TestCreateEmptyDataset.test_same_group_new_attrs) ... ok test_create_indexed_group_invalid_types (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_create_indexed_group_invalid_types) ... ok test_empty_base_name (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_empty_base_name) ... ok test_first_group (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_first_group) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_second) ... ok test_w_suffix_ (tests.io.hdf_utils.test_simple.TestCreateIndexedGroup.test_w_suffix_) ... ok test_dash_in_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_dash_in_name) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:778: UserWarning: tool_name should not contain the "-" character. Reformatted name from:Some-Tool to Some_Tool warn('tool_name should not contain the "-" character. Reformatted name from:{} to ' ok test_different_file (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_different_file) ... ok test_empty_tool_name (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_empty_tool_name) ... ok test_first (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_first) ... ok test_invalid_types (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_invalid_types) ... ok test_second (tests.io.hdf_utils.test_simple.TestCreateResultsGroup.test_second) ... ok test_legal (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_legal) ... ok test_no_dset (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_dset) ... ok test_no_such_tool (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_no_such_tool) ... ok test_not_string (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_not_string) ... ok test_results_in_diff_file (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file) ... ok test_results_in_diff_file_invalid_type (tests.io.hdf_utils.test_simple.TestFindResultsGroup.test_results_in_diff_file_invalid_type) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetAllMain.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetAllMain.test_legal) ... ok test_illegal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_illegal) ... ok test_invalid_type (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_invalid_type) ... ok test_legal (tests.io.hdf_utils.test_simple.TestGetSourceDataset.test_legal) ... ok test_anc_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_anc_args_not_h5_dset) ... ok test_ind_vals_not_same_shape (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_ind_vals_not_same_shape) ... ok test_pos_args_not_h5_dset (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_pos_args_not_h5_dset) ... ok test_typical_attrs_not_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_not_specified) ... ok test_typical_attrs_specified (tests.io.hdf_utils.test_simple.TestLinkAsMain.test_typical_attrs_specified) ... ok test_blah (tests.io.hdf_utils.test_simple.TestValidateAncDsetAttrs.test_blah) ... ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_dtypes) ... ok test_invalid_spec_pos_bool (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_invalid_spec_pos_bool) ... ok test_mismatched_anc_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_mismatched_anc_shapes) ... ok test_valid_shapes (tests.io.hdf_utils.test_simple.TestValidateAncH5Dsets.test_valid_shapes) ... ok test_invalid_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1536: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 25), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1540: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((25, 5), [Dimension('a', 'b', 5)], ok test_invalid_dtypes (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_dtypes) ... ok test_invalid_main_shape (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_invalid_main_shape) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1553: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func([-5, 1], Dimension('a', 'b', 5)) ok test_multi_dims (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_multi_dims) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1526: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 15), [Dimension('a', 'b', 5), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1529: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((15, 5), [Dimension('a', 'b', 5), ok test_single_dim (tests.io.hdf_utils.test_simple.TestValidateDimsAgainstMAin.test_single_dim) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1519: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((1, 5), Dimension('blah', 'meh', np.arange(5)), /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/tests/io/hdf_utils/test_simple.py:1521: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. func((5, 1), [Dimension('blah', 'meh', np.arange(5))], ok test_illegal (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_illegal) ... ok test_legal_bare_minimum_pos_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_f2s) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_legal_bare_minimum_pos_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_pos_s2f) ... ok test_legal_bare_minimum_spec_f2s (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_f2s) ... ok test_legal_bare_minimum_spec_s2f (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_bare_minimum_spec_s2f) ... ok test_legal_override_steps_offsets_base_name (tests.io.hdf_utils.test_simple.TestWriteIndValDsets.test_legal_override_steps_offsets_base_name) ... ok test_3d_to_1d_pos_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_pos_fastest_n_slowest) ... ok test_3d_to_1d_spec_fastest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest) ... ok test_3d_to_1d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_fastest_n_slowest) ... ok test_3d_to_1d_spec_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_1d_spec_slowest) ... ok test_3d_to_2d_spec_fastest_n_slowest (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_3d_to_2d_spec_fastest_n_slowest) ... ok test_spec_1d_to_0d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_1d_to_0d) ... ok test_spec_2d_to_1d (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d) ... ok test_spec_2d_to_1d_new_file (tests.io.hdf_utils.test_simple.TestWriteReducedAncDsets.test_spec_2d_to_1d_new_file) ... ok test_all_dsets_as_dask (tests.io.test_array_translator.TestBaseOperations.test_all_dsets_as_dask) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_preexisting_file_OK (tests.io.test_array_translator.TestBaseOperations.test_preexisting_file_OK) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... ok test_quick_numpy_tranlsation_plus_parms (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_tranlsation_plus_parms) ... /usr/lib/python3/dist-packages/sidpy/sid/translator.py:42: FutureWarning: Consider using sidpy.Reader instead of sidpy.Translator if possible and contribute your reader to ScopeReaders warn('Consider using sidpy.Reader instead of sidpy.Translator if ' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/array_translator.py:93: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(raw_data.shape, dimensions, dim_name == 'Spectroscopic') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, pos_dims, is_spectroscopic=False) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... ok test_empty_name (tests.io.test_array_translator.TestExtraDatasets.test_empty_name) ... ok test_not_arrays (tests.io.test_array_translator.TestExtraDatasets.test_not_arrays) ... ok test_not_dicts (tests.io.test_array_translator.TestExtraDatasets.test_not_dicts) ... ok test_not_str_names (tests.io.test_array_translator.TestExtraDatasets.test_not_str_names) ... ok test_reserved_names (tests.io.test_array_translator.TestExtraDatasets.test_reserved_names) ... ok test_object_single (tests.io.test_array_translator.TestIllegalDimensions.test_object_single) ... ok test_objects (tests.io.test_array_translator.TestIllegalDimensions.test_objects) ... ok test_position (tests.io.test_array_translator.TestIllegalDimensions.test_position) ... ok test_spec (tests.io.test_array_translator.TestIllegalDimensions.test_spec) ... ok test_main_dset_1D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_1D) ... ok test_main_dset_2D (tests.io.test_array_translator.TestIllegalMainDataset.test_main_dset_2D) ... ok test_not_numpy_or_dask_array_main (tests.io.test_array_translator.TestIllegalMainDataset.test_not_numpy_or_dask_array_main) ... ok test_not_strings (tests.io.test_array_translator.TestIllegalStringParms.test_not_strings) ... ok test_dim_type_invalid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_invalid_comparison) ... ok test_dim_type_valid_comparison (tests.io.test_dimension.TestDimType.test_dim_type_valid_comparison) ... ok test_default_mode (tests.io.test_dimension.TestDimension.test_default_mode) ... ok test_equality (tests.io.test_dimension.TestDimension.test_equality) ... ok test_illegal_instantiation (tests.io.test_dimension.TestDimension.test_illegal_instantiation) ... ok test_inequality (tests.io.test_dimension.TestDimension.test_inequality) ... ok test_invalid_mode (tests.io.test_dimension.TestDimension.test_invalid_mode) ... ok test_repr (tests.io.test_dimension.TestDimension.test_repr) ... ok test_values_as_array (tests.io.test_dimension.TestDimension.test_values_as_array) ... ok test_values_as_length (tests.io.test_dimension.TestDimension.test_values_as_length) ... ok test_basic_translate (tests.io.test_image_translator.TestBinning.test_basic_translate) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/image.py:48: FutureWarning: pyUSID.ImageTranslator will be removed shortly. Consider using SciFiReaders.ImageReader instead warn("pyUSID.ImageTranslator will be removed shortly. Consider using " ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... ok test_float_parms (tests.io.test_image_translator.TestBinning.test_float_parms) ... ok test_invalid_dtype (tests.io.test_image_translator.TestBinning.test_invalid_dtype) ... ok test_invalid_interp (tests.io.test_image_translator.TestBinning.test_invalid_interp) ... ok test_neg_parms (tests.io.test_image_translator.TestBinning.test_neg_parms) ... ok test_single_default_interp (tests.io.test_image_translator.TestBinning.test_single_default_interp) ... ok test_too_many_dims (tests.io.test_image_translator.TestBinning.test_too_many_dims) ... ok test_tuple_default_interp (tests.io.test_image_translator.TestBinning.test_tuple_default_interp) ... ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... ok test_invalid_h5_path (tests.io.test_image_translator.TestFile.test_invalid_h5_path) ... ok test_output_h5_file_already_exists (tests.io.test_image_translator.TestFile.test_output_h5_file_already_exists) ... ok test_path_does_not_exist (tests.io.test_image_translator.TestFile.test_path_does_not_exist) ... ok test_path_not_str (tests.io.test_image_translator.TestFile.test_path_not_str) ... ok test_valid_h5_path (tests.io.test_image_translator.TestFile.test_valid_h5_path) ... ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... ok test_color (tests.io.test_image_translator.TestReadImage.test_color) ... ok test_color_to_bw_image (tests.io.test_image_translator.TestReadImage.test_color_to_bw_image) ... ok test_text_complex_to_pillow (tests.io.test_image_translator.TestReadImage.test_text_complex_to_pillow) ... ok test_text_to_numpy_complex (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_complex) ... ok test_text_to_numpy_simple (tests.io.test_image_translator.TestReadImage.test_text_to_numpy_simple) ... ok test_to_numpy (tests.io.test_image_translator.TestReadImage.test_to_numpy) ... ok test_to_pillow (tests.io.test_image_translator.TestReadImage.test_to_pillow) ... ok test_copy_reg_ref_reduced_dim (tests.io.test_reg_ref.TestRegRef.test_copy_reg_ref_reduced_dim) ... ok test_correct_USIDataset (tests.io.test_usi_dataset.TestEquality.test_correct_USIDataset) ... ok test_correct_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_correct_h5_dataset) ... ok test_incorrect_USIDataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_USIDataset) ... ok test_incorrect_h5_dataset (tests.io.test_usi_dataset.TestEquality.test_incorrect_h5_dataset) ... ok test_incorrect_object (tests.io.test_usi_dataset.TestEquality.test_incorrect_object) ... ok test_all_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_all_dims_sliced) ... ok test_both_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_pos_dim_sliced) ... ok test_both_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_both_spec_dim_sliced) ... ok test_empty (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_empty) ... ok test_one_pos_one_spec_dims_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_one_pos_one_spec_dims_sliced) ... ok test_single_pos_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_sliced) ... ok test_single_pos_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_pos_dim_truncated) ... ok test_single_spec_dim_sliced (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_sliced) ... ok test_single_spec_dim_truncated (tests.io.test_usi_dataset.TestGetDimsForSliceReal.test_single_spec_dim_truncated) ... ok test_sorted_and_unsorted (tests.io.test_usi_dataset.TestGetNDimFormExistsReal.test_sorted_and_unsorted) ... ok test_get_pos_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values) ... ok test_get_pos_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_pos_values_illegal) ... ok test_get_spec_values (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values) ... ok test_get_spec_values_illegal (tests.io.test_usi_dataset.TestGetUnitValuesReal.test_get_spec_values_illegal) ... ok test_both_pos_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_both_pos_removed) ... ok test_empty_dict (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_empty_dict) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_incorrect_type) ... ok test_negative_index (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_negative_index) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_non_existent_dim) ... ok test_one_pos_dim_removed (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_removed) ... ok test_one_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_one_pos_dim_sliced) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_pos_and_spec_sliced_list) ... ok test_two_pos_dim_sliced (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced) ... ok test_two_pos_dim_sliced_list (tests.io.test_usi_dataset.TestPosSpecSlicesReal.test_two_pos_dim_sliced_list) ... ok test_one_pos (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos) ... ok test_one_pos_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_pos_one_spec) ... ok test_one_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_one_spec) ... ok test_two_pos_simple (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_pos_simple) ... ok test_two_spec (tests.io.test_usi_dataset.TestSimpleStaticVisualizationReal.test_two_spec) ... ok test_all_but_one_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_dask) ... ok test_all_but_one_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_2d_numpy) ... ok test_all_but_one_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_dask) ... ok test_all_but_one_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_but_one_dims_sliced_nd_numpy) ... ok test_all_dims_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_dask) ... ok test_all_dims_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_2d_numpy) ... ok test_all_dims_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_dask) ... ok test_all_dims_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_all_dims_sliced_nd_numpy) ... ok test_both_pos_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_dask) ... ok test_both_pos_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_2d_numpy) ... ok test_both_pos_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_dask) ... ok test_both_pos_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_both_pos_removed_nd_numpy) ... ok test_empty_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_dask) ... ok test_empty_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_2d_numpy) ... ok test_empty_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_dask) ... ok test_empty_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_empty_nd_numpy) ... ok test_incorrect_type (tests.io.test_usi_dataset.TestSliceReal.test_incorrect_type) ... ok test_negative_index_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_2d_numpy) ... ok test_negative_index_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_dask) ... ok test_negative_index_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_negative_index_nd_numpy) ... ok test_non_existent_dim (tests.io.test_usi_dataset.TestSliceReal.test_non_existent_dim) ... ok test_one_pos_dim_removed_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_dask) ... ok test_one_pos_dim_removed_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_2d_numpy) ... ok test_one_pos_dim_removed_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_dask) ... ok test_one_pos_dim_removed_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_removed_nd_numpy) ... ok test_one_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_dask) ... ok test_one_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_2d_numpy) ... ok test_one_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_dask) ... ok test_one_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_one_pos_dim_sliced_nd_numpy) ... ok test_out_of_bounds (tests.io.test_usi_dataset.TestSliceReal.test_out_of_bounds) ... ok test_pos_and_spec_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_dask) ... ok test_pos_and_spec_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_2d_numpy) ... ok test_pos_and_spec_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_dask) ... ok test_pos_and_spec_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_pos_and_spec_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_dask) ... ok test_two_pos_dim_sliced_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_2d_numpy) ... ok test_two_pos_dim_sliced_list_2d_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_dask) ... ok test_two_pos_dim_sliced_list_2d_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_2d_numpy) ... ok test_two_pos_dim_sliced_list_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_dask) ... ok test_two_pos_dim_sliced_list_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_list_nd_numpy) ... ok test_two_pos_dim_sliced_nd_dask (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_dask) ... ok test_two_pos_dim_sliced_nd_numpy (tests.io.test_usi_dataset.TestSliceReal.test_two_pos_dim_sliced_nd_numpy) ... ok test_get_current_sorting (tests.io.test_usi_dataset.TestSortingReal.test_get_current_sorting) ... ok test_toggle_sorting (tests.io.test_usi_dataset.TestSortingReal.test_toggle_sorting) ... ok test_string_representation (tests.io.test_usi_dataset.TestStringRepr.test_string_representation) ... ok test_1D (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D) ... ok test_1D_pos (tests.io.test_write_utils.TestBuildIndValMatrices.test_1D_pos) ... ok test_3D (tests.io.test_write_utils.TestBuildIndValMatrices.test_3D) ... ok test_empty (tests.io.test_write_utils.TestBuildIndValMatrices.test_empty) ... ok test_invalid_inputs (tests.io.test_write_utils.TestBuildIndValMatrices.test_invalid_inputs) ... ok test_invalid_types (tests.io.test_write_utils.TestCalcChunks.test_invalid_types) ... ok test_no_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk) ... ok test_no_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_no_unit_chunk_max_mem) ... ok test_shape_mismatch (tests.io.test_write_utils.TestCalcChunks.test_shape_mismatch) ... ok test_unit_chunk (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk) ... ok test_unit_chunk_max_mem (tests.io.test_write_utils.TestCalcChunks.test_unit_chunk_max_mem) ... ok test_unit_not_iterable (tests.io.test_write_utils.TestCalcChunks.test_unit_not_iterable) ... ok test_invalid_inputs (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_invalid_inputs) ... ok test_legal (tests.io.test_write_utils.TestCreateSpecIndsFromVals.test_legal) ... ok test_legal_multi_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_multi_dim) ... ok test_legal_single_dim (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_legal_single_dim) ... ok test_odd_input (tests.io.test_write_utils.TestGetAuxDsetSlicing.test_odd_input) ... ok test_2_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_2_dims) ... ok test_3_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_3_dims) ... ok test_dim_w_val_1 (tests.io.test_write_utils.TestMakeIndicesMatrix.test_dim_w_val_1) ... ok test_empty_list (tests.io.test_write_utils.TestMakeIndicesMatrix.test_empty_list) ... ok test_just_size_of_one_dim (tests.io.test_write_utils.TestMakeIndicesMatrix.test_just_size_of_one_dim) ... ok test_matrix_1_dims (tests.io.test_write_utils.TestMakeIndicesMatrix.test_matrix_1_dims) ... ok test_non_int_dim_sizes (tests.io.test_write_utils.TestMakeIndicesMatrix.test_non_int_dim_sizes) ... ok test_single_value_dimension_int_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_int_input) ... ok test_single_value_dimension_list_input (tests.io.test_write_utils.TestMakeIndicesMatrix.test_single_value_dimension_list_input) ... ok test_weird_inputs (tests.io.test_write_utils.TestMakeIndicesMatrix.test_weird_inputs) ... ok test_compute (tests.processing.test_process.TestCoreProcessNoTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Position_Indices at: with kwargs: {'shape': (15, 2), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Position_Values at: with kwargs: {'shape': (15, 2), 'dtype': dtype(' to destination dataset: Passed all pre-tests for creating spectroscopic datasets Indices: [[0 0 0 0 0 0 0 1 1 1 1 1 1 1] [0 1 2 3 4 5 6 0 1 2 3 4 5 6]] Values: [[0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1.] [0. 1. 2. 3. 4. 5. 6. 0. 1. 2. 3. 4. 5. 6.]] Created Spectroscopic datasets Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far Passed all pre-tests for creating position datasets Indices: [[0 0] [0 1] [0 2] [0 3] [0 4] [1 0] [1 1] [1 2] [1 3] [1 4] [2 0] [2 1] [2 2] [2 3] [2 4]] Values: [[0. 0.] [0. 1.] [0. 2.] [0. 3.] [0. 4.] [1. 0.] [1. 1.] [1. 2.] [1. 3.] [1. 4.] [2. 0.] [2. 1.] [2. 2.] [2. 3.] [2. 4.]] Created position datasets! The shapes of the provided h5 position indices and values are OK Need to copy over ancillary datasets: and to destination group: which is in a different HDF5 file Creating new HDF5 dataset named: Spectroscopic_Indices at: with kwargs: {'shape': (2, 14), 'dtype': dtype('uint32'), 'compression': None, 'chunks': None} dask.array will copy data from source dataset to new dataset Copying simple attributes of original dataset: to destination dataset: Creating new HDF5 dataset named: Spectroscopic_Values at: with kwargs: {'shape': (2, 14), 'dtype': dtype(' to destination dataset: Created main dataset with provided data Wrote quantity and units attributes to main dataset Successfully linked datasets - dataset should be main now [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] ['Meh'] ['Meh'] [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] [[0 1 2 0 1 2] [0 0 0 1 1 1]] [[0 1 0 1 0 1] [0 0 1 1 2 2]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0 0] [1 0] [2 0] [3 0] [4 0] [0 1] [1 1] [2 1] [3 1] [4 1] [0 2] [1 2] [2 2] [3 2] [4 2]] [[0 1 2 3 4 5 6 0 1 2 3 4 5 6] [0 0 0 0 0 0 0 1 1 1 1 1 1 1]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] NEAREST NEAREST False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 28 28 233 233 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 0 0 255 255 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] [[0]] [2 2] [2 2] BICUBIC BICUBIC True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] (3, 5, 2, 7) Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... ok test_invalid_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_invalid_parms_dict) ... ok test_invalid_process_name (tests.processing.test_process.TestInvalidInitialization.test_invalid_process_name) ... ok test_no_map_func (tests.processing.test_process.TestInvalidInitialization.test_no_map_func) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... ok test_not_main_dataset (tests.processing.test_process.TestInvalidInitialization.test_not_main_dataset) ... ok test_read_only_h5_main (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_main) ... ok test_read_only_h5_parent_group (tests.processing.test_process.TestInvalidInitialization.test_read_only_h5_parent_group) ... ok test_compute (tests.processing.test_process.TestMultiBatchCompute.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Creating HDF5 group and datasets to hold results Among the 15 positions in this dataset, the following positions need to be computed: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]. Each rank is required to work on 15 of the 15 (remaining) positions in this dataset. Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank: 0 - with nothing loaded has 19.69 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank: 0 - with only raw data loaded has 19.69 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. computational jobs per core = 1. For short computations, each core must have at least 20 jobs to warrant parallel computation. Computations are not lengthy. Not enough jobs per core. Reducing cores to 1 Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! Rank 0 - Finished computing all jobs! Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/model.py:886: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. validate_dims_against_main(main_shape, spec_dims, is_spectroscopic=True) /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1072: UserWarning: In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying warn('In the future write_ind_val_dsets will default to requiring dimensions to be arranged from slowest to fastest varying') /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/build/pyUSID/io/hdf_utils/simple.py:1129: UserWarning: pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer createsregion references for each dimension. Please use pyUSID.io.reg_ref.write_region_references to manually create region references warn('pyUSID.io.hdf_utils.simple.write_ind_val_dsets no longer creates' ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- Ran 359 tests in 11.465s OK Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed with the same parameters before. These results will be returned by compute() by default. Set override to True to force fresh computation [] Returned previously computed results at /Raw_Measurement/source_main-Mean_Val_000 Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [] Resuming computation in group: /Raw_Measurement/source_main-Mean_Val_000 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Group: had neither the status HDF5 dataset or the legacy attribute: "last_pixel". This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation in group: /source_main-Mean_Val_001 Resuming computation. 46% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file Note: Mean_Val has already been performed PARTIALLY with the same parameters. compute() will resuming computation in the last group below. To choose a different group call use_patial_computation()Set override to True to force fresh computation or resume from a data group besides the last in the list. [, ] Resuming computation. 73% completed already This class (likely) supports interruption and resuming of computations! If you are operating in a python console, press Ctrl+C or Cmd+C to abort If you are in a Jupyter notebook, click on "Kernel">>"Interrupt" If you are operating on a cluster and your job gets killed, re-run the job to resume Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file create-stamp debian/debhelper-build-stamp dh_testroot -O--buildsystem=pybuild dh_prep -O--buildsystem=pybuild dh_auto_install --destdir=debian/python3-pyusid/ -O--buildsystem=pybuild I: pybuild plugin_pyproject:178: Copying package built for python3.13 to destdir I: pybuild plugin_pyproject:178: Copying package built for python3.12 to destdir dh_installdocs -O--buildsystem=pybuild dh_installchangelogs -O--buildsystem=pybuild dh_python3 -O--buildsystem=pybuild dh_installsystemduser -O--buildsystem=pybuild dh_perl -O--buildsystem=pybuild dh_link -O--buildsystem=pybuild dh_strip_nondeterminism -O--buildsystem=pybuild dh_compress -O--buildsystem=pybuild dh_fixperms -O--buildsystem=pybuild dh_missing -O--buildsystem=pybuild dh_installdeb -O--buildsystem=pybuild dh_gencontrol -O--buildsystem=pybuild dh_md5sums -O--buildsystem=pybuild dh_builddeb -O--buildsystem=pybuild dpkg-deb: building package 'python3-pyusid' in '../python3-pyusid_0.0.12-2_all.deb'. dpkg-genbuildinfo --build=binary -O../pyusid_0.0.12-2_arm64.buildinfo dpkg-genchanges --build=binary -O../pyusid_0.0.12-2_arm64.changes dpkg-genchanges: info: binary-only upload (no source code included) dpkg-source --after-build . dpkg-source: info: using options from pyusid-0.0.12/debian/source/options: --extend-diff-ignore=^[^/]+.(egg-info|dist-info)/ 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/888831/tmp/hooks/B01_cleanup starting I: user script /srv/workspace/pbuilder/888831/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/888831 and its subdirectories I: Current time: Tue Feb 24 06:41:03 +14 2026 I: pbuilder-time-stamp: 1771864863 + false + set +x Mon Feb 23 16:41:03 UTC 2026 I: Signing ./b2/pyusid_0.0.12-2_arm64.buildinfo as pyusid_0.0.12-2_arm64.buildinfo.asc Mon Feb 23 16:41:03 UTC 2026 I: Signed ./b2/pyusid_0.0.12-2_arm64.buildinfo as ./b2/pyusid_0.0.12-2_arm64.buildinfo.asc Mon Feb 23 16:41:03 UTC 2026 - build #2 for pyusid/trixie/arm64 on codethink01-arm64 done. Starting cleanup. All cleanup done. Mon Feb 23 16:41:03 UTC 2026 - reproducible_build.sh stopped running as /tmp/jenkins-script-l7DSX4SF, removing. /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn: total 372 drwxr-xr-x 2 jenkins jenkins 4096 Jan 21 10:15 b1 drwxr-xr-x 2 jenkins jenkins 4096 Jan 21 10:18 b2 -rw-r--r-- 1 jenkins jenkins 2169 May 12 2024 pyusid_0.0.12-2.dsc -rw------- 1 jenkins jenkins 360531 Jan 21 10:15 rbuildlog.6NcZ1QY /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1: total 460 -rw-r--r-- 1 jenkins jenkins 356958 Jan 21 10:15 build.log -rw-r--r-- 1 jenkins jenkins 54056 Jan 21 10:15 python3-pyusid_0.0.12-2_all.deb -rw-r--r-- 1 jenkins jenkins 2600 Jan 21 10:15 pyusid_0.0.12-2.debian.tar.xz -rw-r--r-- 1 jenkins jenkins 2169 Jan 21 10:15 pyusid_0.0.12-2.dsc -rw-r--r-- 1 jenkins jenkins 11861 Jan 21 10:15 pyusid_0.0.12-2_arm64.buildinfo -rw-r--r-- 1 jenkins jenkins 12743 Jan 21 10:15 pyusid_0.0.12-2_arm64.buildinfo.asc -rw-r--r-- 1 jenkins jenkins 1164 Jan 21 10:15 pyusid_0.0.12-2_arm64.changes -rw-r--r-- 1 jenkins jenkins 1278 Jan 21 10:15 pyusid_0.0.12-2_source.changes /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2: total 452 -rw-r--r-- 1 jenkins jenkins 358879 Jan 21 10:18 build.log -rw-r--r-- 1 jenkins jenkins 54056 Jan 21 10:18 python3-pyusid_0.0.12-2_all.deb -rw-r--r-- 1 jenkins jenkins 2600 Jan 21 10:18 pyusid_0.0.12-2.debian.tar.xz -rw-r--r-- 1 jenkins jenkins 2169 Jan 21 10:18 pyusid_0.0.12-2.dsc -rw-r--r-- 1 jenkins jenkins 11861 Jan 21 10:18 pyusid_0.0.12-2_arm64.buildinfo -rw-r--r-- 1 jenkins jenkins 12743 Jan 21 10:18 pyusid_0.0.12-2_arm64.buildinfo.asc -rw-r--r-- 1 jenkins jenkins 1164 Jan 21 10:18 pyusid_0.0.12-2_arm64.changes -rw-r--r-- 1 jenkins jenkins 1278 Jan 21 10:18 pyusid_0.0.12-2_source.changes Tue Jan 21 10:18:05 UTC 2025 I: Deleting $TMPDIR on codethink01-arm64.debian.net. Tue Jan 21 10:18:05 UTC 2025 I: pyusid_0.0.12-2_arm64.changes: Format: 1.8 Date: Sun, 12 May 2024 15:10:46 +0200 Source: pyusid Binary: python3-pyusid Architecture: all Version: 0.0.12-2 Distribution: unstable Urgency: medium Maintainer: Debian PaN Maintainers Changed-By: Roland Mas Description: python3-pyusid - Universal Spectroscopic and Imaging Data (USID) for Python Closes: 1070675 Changes: pyusid (0.0.12-2) unstable; urgency=medium . * Bug fix: "pyusid generate an extraneous dependency on python3-six", thanks to Alexandre Detiste (Closes: #1070675). Checksums-Sha1: d10bfd4fcbcf17fcac77935c14d52780c79bc2f4 54056 python3-pyusid_0.0.12-2_all.deb 1992bbbfccd4c73f74cfe59959bb3239b5b0ff83 11861 pyusid_0.0.12-2_arm64.buildinfo Checksums-Sha256: e45b704998e7e926e163b43e9dc7a61c8c06a4fc868060761dd6d3a8827a9fca 54056 python3-pyusid_0.0.12-2_all.deb d194016ea1a46752576733a5f04f4fca85f7c2d1bb5be1ff6c0fc8fb866080b5 11861 pyusid_0.0.12-2_arm64.buildinfo Files: 3359ae406cc392b93ba5582c43660ab1 54056 python optional python3-pyusid_0.0.12-2_all.deb 72de17de819f04cd968659ae57bbe35b 11861 python optional pyusid_0.0.12-2_arm64.buildinfo removed '/var/lib/jenkins/userContent/reproducible/debian/rbuild/trixie/arm64/pyusid_0.0.12-2.rbuild.log' removed '/var/lib/jenkins/userContent/reproducible/debian/rbuild/trixie/arm64/pyusid_0.0.12-2.rbuild.log.gz' removed '/var/lib/jenkins/userContent/reproducible/debian/logs/trixie/arm64/pyusid_0.0.12-2.build1.log.gz' removed '/var/lib/jenkins/userContent/reproducible/debian/logs/trixie/arm64/pyusid_0.0.12-2.build2.log.gz' removed '/var/lib/jenkins/userContent/reproducible/debian/buildinfo/trixie/arm64/pyusid_0.0.12-2_arm64.buildinfo' removed '/var/lib/jenkins/userContent/reproducible/debian/logdiffs/trixie/arm64/pyusid_0.0.12-2.diff.gz' Diff of the two buildlogs: -- --- b1/build.log 2025-01-21 10:15:01.639422522 +0000 +++ b2/build.log 2025-01-21 10:18:05.067168587 +0000 @@ -1,6 +1,6 @@ I: pbuilder: network access will be disabled during build -I: Current time: Mon Feb 23 04:35:06 -12 2026 -I: pbuilder-time-stamp: 1771864506 +I: Current time: Tue Feb 24 06:38:04 +14 2026 +I: pbuilder-time-stamp: 1771864684 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/trixie-reproducible-base.tgz] I: copying local configuration @@ -24,52 +24,84 @@ dpkg-source: info: applying 0001-Remove-requirement-for-six-module.patch I: Not using root during the build. I: Installing the build-deps -I: user script /srv/workspace/pbuilder/1266995/tmp/hooks/D02_print_environment starting +I: user script /srv/workspace/pbuilder/888831/tmp/hooks/D01_modify_environment starting +debug: Running on codethink01-arm64. +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 Feb 23 16:38 /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/888831/tmp/hooks/D01_modify_environment finished +I: user script /srv/workspace/pbuilder/888831/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='arm64' - DEBIAN_FRONTEND='noninteractive' + 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]="37" [3]="1" [4]="release" [5]="aarch64-unknown-linux-gnu") + BASH_VERSION='5.2.37(1)-release' + BUILDDIR=/build/reproducible-path + BUILDUSERGECOS='second user,second room,second work-phone,second home-phone,second other' + BUILDUSERNAME=pbuilder2 + BUILD_ARCH=arm64 + DEBIAN_FRONTEND=noninteractive DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=12 ' - DISTRIBUTION='trixie' - HOME='/root' - HOST_ARCH='arm64' + DIRSTACK=() + DISTRIBUTION=trixie + EUID=0 + FUNCNAME=([0]="Echo" [1]="main") + GROUPS=() + HOME=/root + HOSTNAME=i-capture-the-hostname + HOSTTYPE=aarch64 + HOST_ARCH=arm64 IFS=' ' - INVOCATION_ID='fd1b7fff5c924e7eb4682dd63d75ade9' - LANG='C' - LANGUAGE='en_US:en' - LC_ALL='C' - 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='1266995' - PS1='# ' - PS2='> ' + INVOCATION_ID=c9aff92549d34c048338ec3b3ca9ca0a + LANG=C + LANGUAGE=nl_BE:nl + LC_ALL=C + MACHTYPE=aarch64-unknown-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=888831 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.GzEM6mWn/pbuilderrc_riQL --distribution trixie --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1 --logfile b1/build.log pyusid_0.0.12-2.dsc' - SUDO_GID='109' - SUDO_UID='104' - SUDO_USER='jenkins' - TERM='unknown' - TZ='/usr/share/zoneinfo/Etc/GMT+12' - USER='root' - _='/usr/bin/systemd-run' - http_proxy='http://192.168.101.4:3128' + 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.GzEM6mWn/pbuilderrc_dJMQ --distribution trixie --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2 --logfile b2/build.log pyusid_0.0.12-2.dsc' + SUDO_GID=109 + SUDO_UID=104 + SUDO_USER=jenkins + TERM=unknown + TZ=/usr/share/zoneinfo/Etc/GMT-14 + UID=0 + USER=root + _='I: set' + http_proxy=http://192.168.101.4:3128 I: uname -a - Linux codethink03-arm64 6.1.0-30-cloud-arm64 #1 SMP Debian 6.1.124-1 (2025-01-12) aarch64 GNU/Linux + Linux i-capture-the-hostname 6.1.0-30-cloud-arm64 #1 SMP Debian 6.1.124-1 (2025-01-12) aarch64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Nov 22 2024 /bin -> usr/bin -I: user script /srv/workspace/pbuilder/1266995/tmp/hooks/D02_print_environment finished +I: user script /srv/workspace/pbuilder/888831/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy @@ -373,7 +405,7 @@ Get: 250 http://deb.debian.org/debian trixie/main arm64 python3-sklearn-lib arm64 1.4.2+dfsg-7 [5392 kB] Get: 251 http://deb.debian.org/debian trixie/main arm64 python3-sklearn all 1.4.2+dfsg-7 [2248 kB] Get: 252 http://deb.debian.org/debian trixie/main arm64 python3-sidpy all 0.12.3-3 [76.9 kB] -Fetched 134 MB in 1s (162 MB/s) +Fetched 134 MB in 1s (168 MB/s) Preconfiguring packages ... Selecting previously unselected package libtext-charwidth-perl:arm64. (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 ... 19970 files and directories currently installed.) @@ -1192,8 +1224,8 @@ Setting up tzdata (2024b-6) ... Current default time zone: 'Etc/UTC' -Local time is now: Mon Feb 23 16:35:41 UTC 2026. -Universal Time is now: Mon Feb 23 16:35:41 UTC 2026. +Local time is now: Mon Feb 23 16:38:38 UTC 2026. +Universal Time is now: Mon Feb 23 16:38:38 UTC 2026. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up unicode-data (15.1.0-1) ... @@ -1431,7 +1463,11 @@ Building tag database... -> Finished parsing the build-deps I: Building the package -I: Running cd /build/reproducible-path/pyusid-0.0.12/ && 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 > ../pyusid_0.0.12-2_source.changes +I: user script /srv/workspace/pbuilder/888831/tmp/hooks/A99_set_merged_usr starting +Not re-configuring usrmerge for trixie +I: user script /srv/workspace/pbuilder/888831/tmp/hooks/A99_set_merged_usr finished +hostname: Name or service not known +I: Running cd /build/reproducible-path/pyusid-0.0.12/ && 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 > ../pyusid_0.0.12-2_source.changes dpkg-buildpackage: info: source package pyusid dpkg-buildpackage: info: source version 0.0.12-2 dpkg-buildpackage: info: source distribution unstable @@ -1536,7 +1572,7 @@ Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL -creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/.tmp-cnxxuntq/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it +creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/.tmp-0_zbq6u7/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' @@ -1625,7 +1661,7 @@ Copying pyUSID.egg-info to build/bdist.linux-aarch64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-aarch64/wheel/pyUSID-0.0.12.dist-info/WHEEL -creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-tc2s051z/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it +creating '/build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-yccmsa5u/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it adding 'pyUSID/__init__.py' adding 'pyUSID/__version__.py' adding 'pyUSID/io/__init__.py' @@ -1712,9 +1748,9 @@ test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[146 37] -[[146] - [ 37]] +[ 4 192] +[[ 4] + [192]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -1751,8 +1787,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[111 135] -[[111 135]] +[232 212] +[[232 212]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -1789,9 +1825,9 @@ Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[ 95 135] -[[ 95] - [135]] +[ 30 199] +[[ 30] + [199]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -1828,8 +1864,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[165 193] -[[165 193]] +[167 123] +[[167 123]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -1866,9 +1902,9 @@ Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[160 80] -[[160] - [ 80]] +[216 219] +[[216] + [219]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -1905,8 +1941,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[ 36 224] -[[ 36 224]] +[186 124] +[[186 124]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -2045,9 +2081,9 @@ Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[ 4 38] -[[ 4] - [38]] +[19 81] +[[19] + [81]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -2084,8 +2120,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[67 64] -[[67 64]] +[162 114] +[[162 114]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -2122,14 +2158,14 @@ Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) -[[ 42 205 100] - [149 90 0]] -[[ 42] - [205] +[[ 90 68 26] + [168 100 224]] +[[ 90] + [ 68] + [ 26] + [168] [100] - [149] - [ 90] - [ 0]] + [224]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -2166,11 +2202,11 @@ Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) -[[ 6 59 135] - [133 88 69]] -[[ 6 59 135 133 88 69]] +[[106 67 101] + [ 90 48 247]] +[[106 67 101 90 48 247]] Position dimensions: ['Position Dimension 0'] -Position sort order: [0]ok +Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok test_numpy_spec_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_spec_inds_order_flipped) ... ok test_dask_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_dask_small) ... /build/reproducible-path/pyusid-0.0.12/.pybuild/cpython3_3.13_pyusid/build/pyUSID/io/hdf_utils/model.py:867: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead. @@ -2187,7 +2223,7 @@ test_prod_sizes_mismatch (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_prod_sizes_mismatch) ... ok test_write_main_both_existing_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux) ... ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... ok -test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... +test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... [0] Spectroscopic Dimensions: ['Spectral Dimension 0' 'Spectral Dimension 1'] Spectroscopic sort order: [0 1] @@ -3127,8 +3163,8 @@ [2 2] [2 2] BICUBIC BICUBIC False False -24 24 -226 226 +33 33 +223 223 [[ 0 0] [ 1 0] [ 2 0] @@ -3375,11 +3411,11 @@ Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function -Rank: 0 - with nothing loaded has 49.78 GB free memory +Rank: 0 - with nothing loaded has 18.8 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. -Rank: 0 - with only raw data loaded has 49.78 GB free memory +Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 6.56 kB. +Rank: 0 - with only raw data loaded has 18.8 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -3389,12 +3425,12 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.78 GB free memory +Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 6.56 kB. +Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -3404,12 +3440,12 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.78 GB free memory +Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.78 GB. 10 workers on this socket will in total read ~ 3.28 kB. +Rank: 0 available memory: 18.8 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -3419,7 +3455,7 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.78 GB free memory +Rank: 0 - now holding onto raw data + results has 18.8 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! @@ -3527,7 +3563,7 @@ test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- -Ran 359 tests in 11.842s +Ran 359 tests in 11.717s OK @@ -3671,9 +3707,9 @@ test_dask_out_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_pos) ... ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[132 155] -[[132] - [155]] +[ 7 77] +[[ 7] + [77]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -3710,8 +3746,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[222 35] -[[222 35]] +[ 70 147] +[[ 70 147]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -3748,9 +3784,9 @@ Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[220 40] -[[220] - [ 40]] +[49 31] +[[49] + [31]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -3787,8 +3823,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[202 214] -[[202 214]] +[239 32] +[[239 32]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -3825,9 +3861,9 @@ Dataset now of shape: (1, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[218 3] -[[218] - [ 3]] +[214 5] +[[214] + [ 5]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -3864,8 +3900,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[151 29] -[[151 29]] +[147 209] +[[147 209]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -4004,9 +4040,9 @@ Dataset now of shape: (5, 3, 7, 2) 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) -[160 215] -[[160] - [215]] +[ 91 158] +[[ 91] + [158]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -4043,8 +4079,8 @@ Dataset now of shape: (2, 1) 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) -[ 8 149] -[[ 8 149]] +[ 80 210] +[[ 80 210]] Position dimensions: ['Position Dimension 0'] Position sort order: [0] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -4081,14 +4117,14 @@ Dataset now of shape: (1, 2) 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) -[[ 6 79 113] - [151 226 202]] -[[ 6] - [ 79] - [113] - [151] - [226] - [202]] +[[198 168 60] + [ 56 17 180]] +[[198] + [168] + [ 60] + [ 56] + [ 17] + [180]] Position dimensions: ['Position Dimension 0' 'Position Dimension 1'] Position sort order: [0 1] Spectroscopic Dimensions: ['Spectral Dimension 0'] @@ -4125,9 +4161,9 @@ Dataset now of shape: (3, 2, 1) 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) -[[ 19 116 234] - [ 93 250 156]] -[[ 19 116 234 93 250 156]] +[[109 211 5] + [ 62 14 84]] +[[109 211 5 62 14 84]] Position dimensions: ['Position Dimension 0'] Position sort order:ok test_numpy_pos_inds_order_flipped (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_pos_inds_order_flipped) ... ok @@ -5087,7 +5123,7 @@ BICUBIC BICUBIC False False 28 28 -224 224 +233 233 [[ 0 0] [ 1 0] [ 2 0] @@ -5334,11 +5370,11 @@ Rank 0 will read positions 0 to 15 of 15 This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function -Rank: 0 - with nothing loaded has 49.64 GB free memory +Rank: 0 - with nothing loaded has 19.69 GB free memory Rank 0 will read positions: [0 1 2 3 4 5] Rank 0 will read 672.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. -Rank: 0 - with only raw data loaded has 49.64 GB free memory +Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 6.56 kB. +Rank: 0 - with only raw data loaded has 19.69 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -5348,12 +5384,12 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.64 GB free memory +Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 40% complete. Time remaining: 0.0 msec Rank 0 will read positions: [ 6 7 8 9 10 11] Rank 0 will read 672.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 6.56 kB. +Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 6.56 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -5363,12 +5399,12 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.64 GB free memory +Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 6 pixel chunk in 0.0 msec Rank 0 - 80% complete. Time remaining: 0.0 msec Rank 0 will read positions: [12 13 14] Rank 0 will read 336.0 bytes of the SOURCE dataset. -Rank: 0 available memory: 49.64 GB. 10 workers on this socket will in total read ~ 3.28 kB. +Rank: 0 available memory: 19.69 GB. 10 workers on this socket will in total read ~ 3.28 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 2 given that the CPU has 12 logical cores. 10 cores requested. @@ -5378,7 +5414,7 @@ Rank 0 starting computing on 1 cores (requested 10 cores) Rank 0 computing serially ... Rank 0 - computed chunk in 0.0 msec or 0.0 msec per pixel. Average: 0.0 msec per pixel. -Rank: 0 - now holding onto raw data + results has 49.64 GB free memory +Rank: 0 - now holding onto raw data + results has 19.69 GB free memory Rank 0 - wrote its 3 pixel chunk in 0.0 msec Rank 0 - 100% complete. Time remaining: 0.0 msec Rank 0 - Finished reading all data! @@ -5486,7 +5522,7 @@ test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... ok ---------------------------------------------------------------------- -Ran 359 tests in 11.925s +Ran 359 tests in 11.465s OK @@ -5598,12 +5634,14 @@ 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/888831/tmp/hooks/B01_cleanup starting +I: user script /srv/workspace/pbuilder/888831/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/1266995 and its subdirectories -I: Current time: Mon Feb 23 04:38:00 -12 2026 -I: pbuilder-time-stamp: 1771864680 +I: removing directory /srv/workspace/pbuilder/888831 and its subdirectories +I: Current time: Tue Feb 24 06:41:03 +14 2026 +I: pbuilder-time-stamp: 1771864863 Compressing the 2nd log... /var/lib/jenkins/userContent/reproducible/debian/logdiffs/trixie/arm64/pyusid_0.0.12-2.diff: 78.2% -- replaced with /var/lib/jenkins/userContent/reproducible/debian/logdiffs/trixie/arm64/pyusid_0.0.12-2.diff.gz b2/build.log: 89.0% -- replaced with stdout Compressing the 1st log... b1/build.log: 89.2% -- replaced with stdout Tue Jan 21 10:18:07 UTC 2025 I: diffoscope 285 will be used to compare the two builds: ++ date -u +%s + DIFFOSCOPE_STAMP=/var/log/reproducible-builds/diffoscope_stamp_pyusid_trixie_arm64_1737454687 + touch /var/log/reproducible-builds/diffoscope_stamp_pyusid_trixie_arm64_1737454687 + RESULT=0 + systemd-run '--description=diffoscope on pyusid/0.0.12-2 in trixie/arm64' --slice=rb-build-diffoscope.slice -u rb-diffoscope-arm64_5-79244 '--property=SuccessExitStatus=1 124' --user --send-sighup --pipe --wait -E TMPDIR timeout 155m nice schroot --directory /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn --run-session -c jenkins-reproducible-trixie-diffoscope-8a58fbba-5b3c-4ac2-87c7-c46459487482 -- sh -c 'export TMPDIR=/srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/dbd-tmp-8gAbLsa ; timeout 150m diffoscope --timeout 7200 --html /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.html --text /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.txt --json /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.json --profile=- /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1/pyusid_0.0.12-2_arm64.changes /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2/pyusid_0.0.12-2_arm64.changes' + false + set +x Running as unit: rb-diffoscope-arm64_5-79244.service # Profiling output for: /usr/bin/diffoscope --timeout 7200 --html /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.html --text /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.txt --json /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/pyusid_0.0.12-2.diffoscope.json --profile=- /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b1/pyusid_0.0.12-2_arm64.changes /srv/reproducible-results/rbuild-debian/r-b-build.GzEM6mWn/b2/pyusid_0.0.12-2_arm64.changes ## command (total time: 0.000s) 0.000s 1 call cmp (internal) ## has_same_content_as (total time: 0.000s) 0.000s 1 call abc.DotChangesFile ## main (total time: 0.438s) 0.438s 2 calls outputs 0.000s 1 call cleanup ## recognizes (total time: 0.018s) 0.018s 12 calls diffoscope.comparators.binary.FilesystemFile ## specialize (total time: 0.000s) 0.000s 1 call specialize Finished with result: success Main processes terminated with: code=exited/status=0 Service runtime: 807ms CPU time consumed: 807ms _ _ _ __ _ _ _ _ ___(_) __| | | '_ \| | | | | | / __| |/ _` | | |_) | |_| | |_| \__ \ | (_| | | .__/ \__, |\__,_|___/_|\__,_| |_| |___/ Tue Jan 21 10:18:08 UTC 2025 I: diffoscope 285 found no differences in the changes files, and a .buildinfo file also exists. Tue Jan 21 10:18:08 UTC 2025 I: pyusid from trixie built successfully and reproducibly on arm64. INSERT 0 1 INSERT 0 1 DELETE 1 [2025-01-21 10:18:08] INFO: Starting at 2025-01-21 10:18:08.746187 [2025-01-21 10:18:08] INFO: Generating the pages of 1 package(s) [2025-01-21 10:18:08] CRITICAL: https://tests.reproducible-builds.org/debian/trixie/arm64/pyusid didn't produce a buildlog, even though it has been built. [2025-01-21 10:18:08] INFO: Finished at 2025-01-21 10:18:08.926948, took: 0:00:00.180765 Tue Jan 21 10:18:09 UTC 2025 - successfully updated the database and updated https://tests.reproducible-builds.org/debian/rb-pkg/trixie/arm64/pyusid.html Tue Jan 21 10:18:09 UTC 2025 I: Submitting .buildinfo files to external archives: Tue Jan 21 10:18:09 UTC 2025 I: Submitting 16K b1/pyusid_0.0.12-2_arm64.buildinfo.asc https://buildinfo.debian.net/1992bbbfccd4c73f74cfe59959bb3239b5b0ff83/pyusid_0.0.12-2_all Tue Jan 21 10:18:09 UTC 2025 I: Submitting 16K b2/pyusid_0.0.12-2_arm64.buildinfo.asc https://buildinfo.debian.net/694789f722e107c358d1f51095a3df3ff4bd0cc1/pyusid_0.0.12-2_all Tue Jan 21 10:18:10 UTC 2025 I: Done submitting .buildinfo files to http://buildinfo.debian.net/api/submit. Tue Jan 21 10:18:10 UTC 2025 I: Done submitting .buildinfo files. Tue Jan 21 10:18:10 UTC 2025 I: Removing signed pyusid_0.0.12-2_arm64.buildinfo.asc files: removed './b1/pyusid_0.0.12-2_arm64.buildinfo.asc' removed './b2/pyusid_0.0.12-2_arm64.buildinfo.asc' 1737454690 arm64 trixie pyusid Starting cleanup. /var/lib/jenkins/userContent/reproducible/debian/rbuild/trixie/arm64/pyusid_0.0.12-2.rbuild.log: 88.6% -- replaced with /var/lib/jenkins/userContent/reproducible/debian/rbuild/trixie/arm64/pyusid_0.0.12-2.rbuild.log.gz [2025-01-21 10:18:11] INFO: Starting at 2025-01-21 10:18:11.021580 [2025-01-21 10:18:11] INFO: Generating the pages of 1 package(s) [2025-01-21 10:18:11] INFO: Finished at 2025-01-21 10:18:11.294085, took: 0:00:00.272514 All cleanup done. Tue Jan 21 10:18:11 UTC 2025 - total duration: 0h 6m 17s. Tue Jan 21 10:18:11 UTC 2025 - reproducible_build.sh stopped running as /tmp/jenkins-script-EgZfAB8t, removing. Finished with result: success Main processes terminated with: code=exited/status=0 Service runtime: 6min 19.919s CPU time consumed: 7.236s