debspawn 0.6.5 on fennel at 2024-10-16 15:32:33 UTC-0700 gpgv: Signature made Sun 12 May 2024 06:17:29 AM PDT gpgv: using RSA key B415360F591EB6DD73AFFB83D30DECD2599322FC gpgv: Can't check signature: No public key dpkg-source: warning: cannot verify inline signature for /var/lib/lkspark/workspaces/1b73613e-ad96-48cc-a8bc-823788b173e8/pyusid_0.0.12-2.dsc: no acceptable signature found 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 ╔═══════════════════════╗ ║ Package build ║ ╚═══════════════════════╝ Package: pyusid Version: 0.0.12-2 Distribution: landing Architecture: amd64 Free space in workspace: 65.4GiB ┌───────────────────────────────────────┐ │ Preparing container for build │ └───────────────────────────────────────┘ Get:1 https://repo.pureos.net/pureos landing InRelease [9625 B] Get:2 https://repo.pureos.net/pureos landing/main all Packages [3880 kB] Get:3 https://repo.pureos.net/pureos landing/main amd64 Packages [4390 kB] Fetched 8279 kB in 2s (4919 kB/s) Reading package lists... Reading package lists... Building dependency tree... Reading state information... Calculating upgrade... The following packages will be upgraded: gpgv 1 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. Need to get 0 B/218 kB of archives. After this operation, 1024 B disk space will be freed. debconf: delaying package configuration, since apt-utils is not installed (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 ... 13780 files and directories currently installed.) Preparing to unpack .../gpgv_2.2.44-1_amd64.deb ... Unpacking gpgv (2.2.44-1) over (2.2.43-8+b1) ... Setting up gpgv (2.2.44-1) ... Reading package lists... Building dependency tree... Reading state information... build-essential is already the newest version (12.10). dpkg-dev is already the newest version (1.21.22pureos1). fakeroot is already the newest version (1.36-1). 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. ┌───────────────────────────────────────────────┐ │ Installing package build-dependencies │ └───────────────────────────────────────────────┘ Note, using directory './' to get the build dependencies Reading package lists... Building dependency tree... Reading state information... The following NEW packages will be installed: autoconf automake autopoint autotools-dev blt bsdextrautils debhelper dh-autoreconf dh-python dh-strip-nondeterminism dwz eslint file fontconfig-config fonts-dejavu-core fonts-dejavu-mono fonts-font-awesome fonts-glyphicons-halflings fonts-lyx gdb gettext gettext-base groff-base gyp handlebars intltool-debian jest libaec0 libarchive-zip-perl libbabeltrace1 libblas3 libbrotli1 libcares2 libcurl3t64-gnutls libcurl4t64 libdebhelper-perl libdebuginfod-common libdebuginfod1t64 libdeflate0 libdw1t64 libelf1t64 libfile-stripnondeterminism-perl libfontconfig1 libfreetype6 libfribidi0 libgfortran5 libglib2.0-0t64 libgraphite2-3 libgssapi-krb5-2 libharfbuzz0b libhdf5-103-1t64 libhdf5-hl-100t64 libicu72 libimagequant0 libipt2 libjbig0 libjpeg62-turbo libjs-backbone libjs-bootstrap libjs-d3-format libjs-events libjs-inherits libjs-is-typedarray libjs-jquery libjs-jquery-ui libjs-prettify libjs-psl libjs-regenerate libjs-simulate-event libjs-source-map libjs-sprintf-js libjs-typedarray-to-buffer libjs-underscore libjs-util libk5crypto3 libkeyutils1 libkrb5-3 libkrb5support0 liblapack3 liblbfgsb0 liblcms2-2 libldap-2.5-0 liblerc4 liblzf1 libmagic-mgc libmagic1t64 libncursesw6 libnghttp2-14 libnghttp3-9 libngtcp2-16 libngtcp2-crypto-gnutls8 libnode-dev libnode115 libnorm1t64 libnsl2 libopenjp2-7 libpgm-5.3-0t64 libpipeline1 libpng16-16t64 libproc2-0 libpsl5t64 libpython3-stdlib libpython3.12-stdlib libpython3.12t64 libqhull-r8.0 libraqm0 libreadline8t64 librtmp1 libsasl2-2 libsasl2-modules-db libsharpyuv0 libsodium23 libsource-highlight-common libsource-highlight4t64 libsqlite3-0 libssh2-1t64 libssl-dev libsymspg2 libsz2 libtcl8.6 libtiff6 libtirpc-common libtirpc3t64 libtk8.6 libtool libuchardet0 libuv1-dev libuv1t64 libwebp7 libwebpdemux2 libwebpmux3 libx11-6 libx11-data libxau6 libxcb1 libxdmcp6 libxext6 libxft2 libxml2 libxrender1 libxslt1.1 libxss1 libyaml-0-2 libzmq5 m4 man-db media-types netbase node-abab node-abbrev node-acorn node-agent-base node-ajv node-ajv-keywords node-ampproject-remapping node-ansi-escapes node-ansi-regex node-ansi-styles node-anymatch node-aproba node-archy node-are-we-there-yet node-argparse node-array-from node-arrify node-assert node-async node-async-each node-asynckit node-babel-helper-define-polyfill-provider node-babel-plugin-add-module-exports node-babel-plugin-lodash node-babel-plugin-polyfill-corejs2 node-babel-plugin-polyfill-corejs3 node-babel-plugin-polyfill-regenerator node-babel7 node-babel7-runtime node-backbone node-balanced-match node-base16 node-big.js node-binary-extensions node-brace-expansion node-braces node-browserslist node-camelcase node-caniuse-lite node-chalk node-change-case node-chokidar node-chownr node-chrome-trace-event node-ci-info node-cjs-module-lexer node-cliui node-clone node-clone-deep node-co node-codemirror-autocomplete node-codemirror-commands node-codemirror-lang-cpp node-codemirror-lang-css node-codemirror-lang-html node-codemirror-lang-java node-codemirror-lang-javascript node-codemirror-lang-json node-codemirror-lang-markdown node-codemirror-lang-php node-codemirror-lang-python node-codemirror-lang-rust node-codemirror-lang-sql node-codemirror-lang-wast node-codemirror-lang-xml node-codemirror-language node-codemirror-legacy-modes node-codemirror-lint node-codemirror-search node-codemirror-state node-codemirror-view node-color node-color-convert node-color-name node-color-string node-combined-stream node-commander node-commondir node-concat-stream node-console-control-strings node-convert-source-map node-core-js node-core-js-compat node-core-js-pure node-core-util-is node-cosmiconfig node-crelt node-css-loader node-css-selector-tokenizer node-cssom node-cssstyle node-csstype node-d node-d3-array node-d3-collection node-d3-color node-d3-delaunay node-d3-dispatch node-d3-dsv node-d3-force node-d3-format node-d3-geo node-d3-geo-projection node-d3-hierarchy node-d3-interpolate node-d3-path node-d3-quadtree node-d3-queue node-d3-scale node-d3-shape node-d3-time node-d3-time-format node-d3-timer node-data-uri-to-buffer node-debbundle-es-to-primitive node-debug node-decamelize node-deep-equal node-deep-is node-deepmerge node-defaults node-define-properties node-define-property node-defined node-del node-delayed-stream node-delegates node-detect-newline node-diff node-doctrine node-dom-serializer node-domelementtype node-domhandler node-domutils node-electron-to-chromium node-emittery node-emojis-list node-encoding node-enhanced-resolve node-entities node-envinfo node-errno node-error-ex node-es-abstract node-es-module-lexer node-es5-ext node-es6-error node-es6-iterator node-es6-symbol node-escape-html node-escape-string-regexp node-escodegen node-eslint-scope node-eslint-utils node-eslint-visitor-keys node-espree node-esprima node-esquery node-esrecurse node-estraverse node-esutils node-event-emitter node-events node-execa node-exit node-extend-shallow node-fancy-log node-fast-deep-equal node-fast-json-patch node-fast-json-stable-stringify node-fast-levenshtein node-fetch node-file-entry-cache node-fill-range node-find-cache-dir node-find-up node-flat-cache node-flatted node-for-in node-for-own node-foreground-child node-form-data node-fortawesome-fontawesome-free node-free-style node-fs-extra node-fs-readdir-recursive node-fs.realpath node-function-bind node-functional-red-black-tree node-gauge node-get-caller-file node-get-stream node-glob node-glob-parent node-global node-globals node-globby node-graceful-fs node-gyp node-has-flag node-has-unicode node-hosted-git-info node-htmlparser2 node-http-proxy-agent node-https-proxy-agent node-iconv-lite node-icss-utils node-ignore node-imurmurhash node-indent-string node-inflight node-inherits node-interpret node-is-arrayish node-is-binary-path node-is-buffer node-is-descriptor node-is-extendable node-is-extglob node-is-generator-fn node-is-glob node-is-number node-is-object node-is-path-cwd node-is-path-inside node-is-plain-obj node-is-plain-object node-is-stream node-is-typedarray node-is-windows node-isarray node-isexe node-isobject node-isomorphic.js node-istanbul node-jest-debbundle node-jest-worker node-jquery node-js-tokens node-js-yaml node-jsdom node-jsesc node-json-parse-better-errors node-json-schema node-json-schema-traverse node-json-stable-stringify node-json5 node-jsonfile node-jsonify node-jsonparse node-jupyter-widgets-base node-jupyterlab node-kind-of node-klaw node-leven node-levn node-lezer-common node-lezer-cpp node-lezer-css node-lezer-generator node-lezer-html node-lezer-java node-lezer-javascript node-lezer-json node-lezer-markdown node-lezer-php node-lezer-python node-lezer-rust node-lezer-xml node-lib0 node-loader-runner node-loader-utils node-locate-path node-lodash node-lodash-packages node-loose-envify node-lru-cache node-lumino node-make-dir node-make-error node-markdown-to-jsx node-marked node-mathjax-full node-memfs node-memory-fs node-merge-descriptors node-merge-stream node-micromatch node-mime node-mime-types node-mimic-fn node-min-document node-mini-css-extract-plugin node-minimatch node-minimist node-minipass node-mj-context-menu node-mkdirp node-ms node-mute-stream node-n3 node-neo-async node-nopt node-normalize-package-data node-normalize-path node-npm-run-path node-npmlog node-object-assign node-object-inspect node-once node-optimist node-optionator node-osenv node-p-limit node-p-locate node-p-map node-parse-json node-parse-srcset node-parse5 node-path-browserify node-path-dirname node-path-exists node-path-is-absolute node-path-is-inside node-path-to-regexp node-path-type node-picocolors node-pify node-pkg-dir node-playwright node-postcss node-postcss-modules-extract-imports node-postcss-modules-values node-postcss-value-parser node-prelude-ls node-process node-process-nextick-args node-progress node-prompts node-prop-types node-prr node-psl node-punycode node-pure-rand node-querystringify node-quick-lru node-randombytes node-react node-react-base16-styling node-react-dom node-react-highlight-words node-react-is node-react-json-tree node-react-paginate node-react-shallow-renderer node-react-test-renderer node-react-toastify node-read node-read-pkg node-readable-stream node-readdirp node-rechoir node-regenerate node-regenerate-unicode-properties node-regenerator-runtime node-regenerator-transform node-regex-not node-regexp-match-indices node-regexpp node-regexpu-core node-regjsgen node-regjsparser node-repeat-string node-require-directory node-requires-port node-resolve node-resolve-cwd node-resolve-from node-resumer node-rimraf node-rjsf node-rw node-safe-buffer node-sane node-sanitize-html node-scheduler node-schema-utils node-semver node-serialize-javascript node-set-blocking node-set-immediate-shim node-shebang-command node-shebang-regex node-signal-exit node-simple-swizzle node-sinclair-typebox node-sinon node-slash node-slice-ansi node-source-list-map node-source-map node-source-map-loader node-source-map-support node-spdx-correct node-spdx-exceptions node-spdx-expression-parse node-spdx-license-ids node-speech-rule-engine node-sprintf-js node-stack-utils node-stdlib node-string-decoder node-string-width node-strip-ansi node-strip-bom node-strip-eof node-strip-json-comments node-style-loader node-style-mod node-supports-color node-tapable node-tape node-tar node-terser node-through node-time-stamp node-to-fast-properties node-to-regex node-to-regex-range node-tough-cookie node-tslib node-type-check node-type-detect node-typedarray node-typedarray-to-buffer node-typescript node-typestyle node-underscore node-undici node-unicode-canonical-property-names-ecmascript node-unicode-match-property-ecmascript node-unicode-match-property-value-ecmascript node-unicode-property-aliases-ecmascript node-universalify node-uri-js node-url-parse node-util node-util-deprecate node-uuid node-v8-compile-cache node-v8flags node-validate-npm-package-license node-vdom-to-html node-vega node-vega-embed node-vega-lite node-vega-themes node-vega-tooltip node-vscode-debugprotocol node-vscode-jsonrpc node-vscode-languageserver-protocol node-vscode-languageserver-types node-w3c-keyname node-warning node-watchpack node-wcwidth.js node-webassemblyjs node-webidl-conversions node-webpack-merge node-webpack-sources node-which node-wide-align node-wordwrap node-worker-loader node-wrap-ansi node-wrappy node-write node-write-file-atomic node-ws node-xtend node-xterm node-y-protocols node-y18n node-yallist node-yaml node-yargs node-yargs-parser node-yjs nodejs po-debconf procps pybuild-plugin-pyproject python-matplotlib-data python3 python3-all python3-appdirs python3-ase python3-asttokens python3-attr python3-autocommand python3-brotli python3-build python3-cffi-backend python3-click python3-cloudpickle python3-colorama python3-comm python3-contourpy python3-coverage python3-cycler python3-cytoolz python3-dask python3-dateutil python3-debugpy python3-decorator python3-distributed python3-executing python3-fonttools python3-fs python3-fsspec python3-h5py python3-h5py-serial python3-inflect python3-installer python3-ipykernel python3-ipython python3-ipywidgets python3-jaraco.context python3-jaraco.functools python3-jedi python3-jinja2 python3-joblib python3-jupyter-client python3-jupyter-core python3-kiwisolver python3-locket python3-lxml python3-lz4 python3-markupsafe python3-matplotlib python3-matplotlib-inline python3-more-itertools python3-mpmath python3-msgpack python3-nest-asyncio python3-numpy python3-packaging python3-parso python3-partd python3-pexpect python3-pil python3-pil.imagetk python3-pkg-resources python3-platformdirs python3-prompt-toolkit python3-psutil python3-ptyprocess python3-pure-eval python3-py python3-pygments python3-pyparsing python3-pyproject-hooks python3-scipy python3-setuptools python3-sidpy python3-six python3-sklearn python3-sklearn-lib python3-sortedcontainers python3-spglib python3-stack-data python3-sympy python3-tblib python3-threadpoolctl python3-tk python3-toml python3-toolz python3-tornado python3-traitlets python3-typeguard python3-typeshed python3-typing-extensions python3-tz python3-ufolib2 python3-urllib3 python3-wcwidth python3-wheel python3-yaml python3-zict python3-zipp python3-zmq python3.12 python3.12-tk python3.13-tk readline-common sensible-utils terser tk8.6-blt2.5 ts-jest ucf unicode-data webpack x11-common 0 upgraded, 751 newly installed, 0 to remove and 0 not upgraded. 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Adding 'diversion of /lib/x86_64-linux-gnu/libtirpc.so.3 to /lib/x86_64-linux-gnu/libtirpc.so.3.usr-is-merged by libtirpc3t64' Adding 'diversion of /lib/x86_64-linux-gnu/libtirpc.so.3.0.0 to /lib/x86_64-linux-gnu/libtirpc.so.3.0.0.usr-is-merged by libtirpc3t64' Unpacking libtirpc3t64:amd64 (1.3.4+ds-1.3) ... Selecting previously unselected package libnsl2:amd64. Preparing to unpack .../013-libnsl2_1.3.0-3+b2_amd64.deb ... Unpacking libnsl2:amd64 (1.3.0-3+b2) ... Selecting previously unselected package readline-common. Preparing to unpack .../014-readline-common_8.2-5_all.deb ... Unpacking readline-common (8.2-5) ... Selecting previously unselected package libreadline8t64:amd64. Preparing to unpack .../015-libreadline8t64_8.2-5_amd64.deb ... 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Setting up libglib2.0-0t64:amd64 (2.82.1-1) ... No schema files found: doing nothing. Setting up node-safe-buffer (5.2.1+~cs2.1.2-3) ... Setting up libblas3:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/x86_64-linux-gnu/libblas.so.3 (libblas.so.3-x86_64-linux-gnu) in auto mode Setting up node-rw (1.3.3-5) ... Setting up node-d3-delaunay (6.0.4+~cs19.0.3-2) ... Setting up node-rechoir (0.8.0+~0.6.1-2) ... Setting up node-json-parse-better-errors (1.0.2+~cs3.3.1-3) ... Setting up libjpeg62-turbo:amd64 (1:2.1.5-3) ... Setting up node-unicode-canonical-property-names-ecmascript (2.0.0-2) ... Setting up node-lezer-markdown (1.3.0~1.4.16+~cs14.25.46-1) ... Setting up node-sprintf-js (1.1.2+ds1+~1.1.2-1) ... Setting up node-flatted (3.2.7~ds-1) ... Setting up node-y18n (5.0.8+~5.0.0-3) ... Setting up node-detect-newline (3.1.0-2) ... Setting up node-fast-deep-equal (3.1.3-3) ... Setting up node-exit (0.1.2+~0.1.31-2) ... 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Setting up node-readable-stream (3.6.0+~cs3.0.0-4) ... Setting up liblapack3:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode Setting up gettext (0.22.5-2) ... Setting up node-supports-color (8.1.1+~8.1.1-1) ... Setting up node-d3-format (1:1.4.5+~1.4.2-2) ... Setting up node-error-ex (1.3.2-4) ... Setting up node-once (1.4.1-1) ... Setting up node-webpack-sources (3.2.3+~3.2.0-2) ... Setting up node-psl (1.8.0+ds-9) ... Setting up libxrender1:amd64 (1:0.9.10-1.1+b1) ... Setting up node-n3 (1.16.3+~1.2.3+~1.10.4-1) ... Setting up libtool (2.4.7-7) ... Setting up node-global (4.13.1+really-4.4.0~4.13.1+~cs12.12.4-2) ... Setting up node-lezer-xml (1.0.5~1.4.16+~cs14.25.46-1) ... Setting up node-parse5 (7.1.2+dfsg-2) ... Setting up node-vscode-languageserver-protocol (3.17.4~next.0~1.0.0~git20230424.1320922-3) ... 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'var(--my-color-\.)', # CSS variable with escaped characters Setting up python3-sidpy (0.12.3-3) ... Processing triggers for libc-bin (2.40-3) ... ┌───────────────┐ │ Build │ └───────────────┘ dpkg-buildpackage: info: source package pyusid dpkg-buildpackage: info: source version 0.0.12-2 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: host architecture amd64  dpkg-source --before-build . 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 python3.12 with "build" module I: pybuild base:311: python3.12 -m build --skip-dependency-check --no-isolation --wheel --outdir /srv/build/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 running build running build_py creating build creating build/lib creating build/lib/pyUSID copying pyUSID/__version__.py -> build/lib/pyUSID copying pyUSID/__init__.py -> build/lib/pyUSID creating build/lib/pyUSID/io copying pyUSID/io/image.py -> build/lib/pyUSID/io copying pyUSID/io/array_translator.py -> build/lib/pyUSID/io copying pyUSID/io/__init__.py -> 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/anc_build_utils.py -> build/lib/pyUSID/io copying pyUSID/io/dimension.py -> build/lib/pyUSID/io creating build/lib/pyUSID/processing copying pyUSID/processing/__init__.py -> build/lib/pyUSID/processing copying pyUSID/processing/comp_utils.py -> build/lib/pyUSID/processing copying pyUSID/processing/process.py -> build/lib/pyUSID/processing creating 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 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 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-x86_64/wheel running install running install_lib creating build/bdist.linux-x86_64 creating build/bdist.linux-x86_64/wheel creating build/bdist.linux-x86_64/wheel/pyUSID copying build/lib/pyUSID/__version__.py -> build/bdist.linux-x86_64/wheel/./pyUSID creating build/bdist.linux-x86_64/wheel/pyUSID/io creating build/bdist.linux-x86_64/wheel/pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/base.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/__init__.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/simple.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/hdf_utils/model.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io/hdf_utils copying build/lib/pyUSID/io/image.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/array_translator.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/__init__.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/usi_data.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/reg_ref.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/anc_build_utils.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io copying build/lib/pyUSID/io/dimension.py -> build/bdist.linux-x86_64/wheel/./pyUSID/io creating build/bdist.linux-x86_64/wheel/pyUSID/processing copying build/lib/pyUSID/processing/__init__.py -> build/bdist.linux-x86_64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/comp_utils.py -> build/bdist.linux-x86_64/wheel/./pyUSID/processing copying build/lib/pyUSID/processing/process.py -> build/bdist.linux-x86_64/wheel/./pyUSID/processing copying build/lib/pyUSID/__init__.py -> build/bdist.linux-x86_64/wheel/./pyUSID running install_egg_info Copying pyUSID.egg-info to build/bdist.linux-x86_64/wheel/./pyUSID-0.0.12.egg-info running install_scripts creating build/bdist.linux-x86_64/wheel/pyUSID-0.0.12.dist-info/WHEEL creating '/srv/build/pyusid-0.0.12/.pybuild/cpython3_3.12_pyusid/.tmp-zjx64stp/pyUSID-0.0.12-py2.py3-none-any.whl' and adding 'build/bdist.linux-x86_64/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-x86_64/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 /srv/build/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) ... /srv/build/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) /srv/build/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, /srv/build/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, /srv/build/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) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [236 230] [[236] [230]] 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) ok test_dask_all_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_all_ordinary_1d_spec) ... 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 44 120] [[ 44 120]] 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) ok test_dask_in_ordinary_1d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_pos) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [254 137] [[254] [137]] 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) ok test_dask_in_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_in_ordinary_1d_spec) ... 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [ 99 236] [[ 99 236]] 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) 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) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [ 65 217] [[ 65] [217]] 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) ok test_dask_out_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_dask_out_ordinary_1d_spec) ... 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [136 222] [[136 222]] 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) 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) ... 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) 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) ... 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) 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) ... 2D: False, Spec: False, Flip: False Main data shapes ND: (2,), 2D: (2, 1) [177 66] [[177] [ 66]] 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) ok test_numpy_ordinary_1d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_1d_spec) ... 2D: False, Spec: True, Flip: False Main data shapes ND: (2,), 2D: (1, 2) [219 14] [[219 14]] 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) ok test_numpy_ordinary_2d_pos (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_pos) ... 2D: True, Spec: False, Flip: False Main data shapes ND: (2, 3), 2D: (6, 1) [[156 119 33] [137 187 82]] [[156] [119] [ 33] [137] [187] [ 82]] 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) ok test_numpy_ordinary_2d_spec (tests.io.hdf_utils.test_model.TestReshapeToNDims.test_numpy_ordinary_2d_spec) ... 2D: True, Spec: True, Flip: False Main data shapes ND: (2, 3), 2D: (1, 6) [[199 42 61] [153 159 158]] [[199 42 61 153 159 158]] 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) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 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) 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) ... h5 group and file OK quantity, units, main_data_name all OK Provided numpy or Dask array for main_data OK so far /srv/build/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) Passed all pre-tests for creating position datasets /srv/build/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') 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.]] /srv/build/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' Created position datasets! /srv/build/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) 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]] ok test_empty_main (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_empty_main) ... 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]] ok test_numpy_small (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_numpy_small) ... 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]] 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) ... 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]] ok test_write_main_both_existing_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_both_existing_aux_diff_file) ... 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]] ok test_write_main_existing_pos_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux) ... 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 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]] ok test_write_main_existing_pos_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_pos_aux_diff_file) ... 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]] ok test_write_main_existing_spec_aux (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux) ... 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]] ok test_write_main_existing_spec_aux_diff_file (tests.io.hdf_utils.test_model.TestWriteMainDataset.test_write_main_existing_spec_aux_diff_file) ... 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]] 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) ... ['Meh'] ['Meh'] 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) ... /srv/build/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) ... /srv/build/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), /srv/build/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) ... /srv/build/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) ... /srv/build/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), /srv/build/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) ... /srv/build/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)), /srv/build/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) ... /srv/build/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') /srv/build/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' [[0 0] [1 0] [2 0] [0 1] [1 1] [2 1]] 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) ... [[0 1 2 0 1 2] [0 0 0 1 1 1]] 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) ... [[0 1 0 1 0 1] [0 0 1 1 2 2]] 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 ' /srv/build/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') /srv/build/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) /srv/build/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) [[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]] 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 ' /srv/build/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') /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) [[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]] ok test_quick_dask_main_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_dask_main_translation) ... [[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]] 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 ' /srv/build/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') /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) [[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]] ok test_quick_numpy_translation (tests.io.test_array_translator.TestBaseOperations.test_quick_numpy_translation) ... [[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]] 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) ... /srv/build/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 " [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] ok test_custom_interp (tests.io.test_image_translator.TestBinning.test_custom_interp) ... [[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]] 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) ... [[0]] [2 2] [2 2] BICUBIC BICUBIC False False 25 25 222 222 [[ 0 0] [ 1 0] [ 2 0] ... [ 61 127] [ 62 127] [ 63 127]] 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) ... [[0]] [1 2] [1 2] BICUBIC BICUBIC False False 3 3 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 127] [126 127] [127 127]] ok test_basic_translate (tests.io.test_image_translator.TestFile.test_basic_translate) ... [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] 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) ... [[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]] ok test_basic_translate (tests.io.test_image_translator.TestImageTranslator.test_basic_translate) ... [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] ok test_basic_translate (tests.io.test_image_translator.TestNormalization.test_basic_translate) ... [[0]] False False 0 0 254 254 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] ok test_normalize_and_default_interp (tests.io.test_image_translator.TestNormalization.test_normalize_and_default_interp) ... [[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]] ok test_normalize_only (tests.io.test_image_translator.TestNormalization.test_normalize_only) ... [[0]] True True 0.0 0.0 1.0 1.0 [[ 0 0] [ 1 0] [ 2 0] ... [125 255] [126 255] [127 255]] 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) ... (3, 5, 2, 7) 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) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_tfunc (tests.processing.test_process.TestCoreProcessNoTest.test_tfunc) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file ok test_compute (tests.processing.test_process.TestCoreProcessWDuplicateResultsOverride.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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 [] /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_duplicate_partial_results (tests.processing.test_process.TestCoreProcessWExistResultsDiffParms.test_duplicate_partial_results) ... /srv/build/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) /srv/build/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') /srv/build/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' Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file ok test_compute (tests.processing.test_process.TestCoreProcessWExistingPartResults.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestCoreProcessWExistingResults.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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 ok test_compute (tests.processing.test_process.TestCoreProcessWTest.test_compute) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_tfunc (tests.processing.test_process.TestCoreProcessWTest.test_tfunc) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file 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) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file /srv/build/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) /srv/build/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') /srv/build/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' This class does NOT support interruption and resuming of computations. In order to enable this feature, simply implement the _get_existing_datasets() function ok test_none_parms_dict (tests.processing.test_process.TestInvalidInitialization.test_none_parms_dict) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file 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) ... 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 /srv/build/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) /srv/build/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') /srv/build/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' 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 6.8 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: 6.8 GB. 3 workers on this socket will in total read ~ 1.97 kB. Rank: 0 - with only raw data loaded has 6.8 GB free memory Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 1 given that the CPU has 4 logical cores. 3 cores requested. computational jobs per core = 2. 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 3 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 6.8 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: 6.8 GB. 3 workers on this socket will in total read ~ 1.97 kB. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 1 given that the CPU has 4 logical cores. 3 cores requested. computational jobs per core = 2. 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 3 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 6.8 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: 6.8 GB. 3 workers on this socket will in total read ~ 1008.0 bytes. Rank 0 at Process class' default _unit_computation() that will call parallel_compute() Number of CPU free cores set to: 1 given that the CPU has 4 logical cores. 3 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 3 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 6.8 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! ok test_tfunc (tests.processing.test_process.TestMultiBatchCompute.test_tfunc) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file ok test_compute (tests.processing.test_process.TestProcLastPartialResult.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) /srv/build/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') /srv/build/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' 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 Rank 0 - 100% complete. Time remaining: 0.0 msec Finished processing the entire dataset! ok test_compute (tests.processing.test_process.TestProcReturnCompletedNotPartial.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) /srv/build/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') /srv/build/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' 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 ok test_compute (tests.processing.test_process.TestProcWLegacyResultsComplete.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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 ok test_compute (tests.processing.test_process.TestProcWLegacyResultsPartial.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestProcWoStatus.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' 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". /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestProcessWExistingResultsDiffFile.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestUsePartialComputationIllegal.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) /srv/build/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') /srv/build/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' 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. [, ] ok test_compute (tests.processing.test_process.TestUsePartialComputationLegit.test_compute) ... /srv/build/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) /srv/build/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') /srv/build/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' /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_compute (tests.processing.test_process.TestWriteResultsToNewH5File.test_compute) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file /srv/build/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) /srv/build/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') /srv/build/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' 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! ok test_tfunc (tests.processing.test_process.TestWriteResultsToNewH5File.test_tfunc) ... Consider calling test() to check results before calling compute() which computes on the entire dataset and writes results to the HDF5 file ok ---------------------------------------------------------------------- Ran 359 tests in 11.170s OK 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 python3.12 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_amd64.buildinfo  dpkg-genchanges -DDistribution=landing --build=binary -mDebian PaN Maintainers -eDebian PaN Maintainers -O../pyusid_0.0.12-2_amd64.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) This build required 111.4MiB of dedicated disk space. ┌────────────────────────────────────┐ │ Retrieving build artifacts │ └────────────────────────────────────┘ Copied 4 files. Done.