0s autopkgtest [11:44:16]: starting date and time: 2025-11-17 11:44:16+0000 0s autopkgtest [11:44:16]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [11:44:16]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.2nwz5fay/out --timeout-copy=6000 --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:con-duct,src:python3-defaults --apt-upgrade con-duct --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 '--env=ADT_TEST_TRIGGERS=con-duct/0.17.0-1 python3-defaults/3.13.7-2' -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest-s390x --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@bos03-s390x-5.secgroup --name adt-resolute-s390x-con-duct-20251117-114416-juju-7f2275-prod-proposed-migration-environment-2-7adfd633-5ddd-47f2-9bde-9d9047dcedac --image adt/ubuntu-resolute-s390x-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-proposed-migration-s390x -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 4s Creating nova instance adt-resolute-s390x-con-duct-20251117-114416-juju-7f2275-prod-proposed-migration-environment-2-7adfd633-5ddd-47f2-9bde-9d9047dcedac from image adt/ubuntu-resolute-s390x-server-20251117.img (UUID a3a3e3b9-e6ba-478c-a5e9-fce6f0982a95)... 49s autopkgtest [11:45:05]: testbed dpkg architecture: s390x 49s autopkgtest [11:45:05]: testbed apt version: 3.1.11 50s autopkgtest [11:45:06]: @@@@@@@@@@@@@@@@@@@@ test bed setup 50s autopkgtest [11:45:06]: testbed release detected to be: None 51s autopkgtest [11:45:07]: updating testbed package index (apt update) 51s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [87.8 kB] 51s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 51s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 51s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 51s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [81.1 kB] 52s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/restricted Sources [9848 B] 52s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [868 kB] 52s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [22.9 kB] 52s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main s390x Packages [138 kB] 52s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted s390x Packages [940 B] 52s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe s390x Packages [545 kB] 52s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse s390x Packages [10.6 kB] 52s Fetched 1764 kB in 1s (1648 kB/s) 53s Reading package lists... 53s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 53s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 54s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 54s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 54s Reading package lists... 54s Reading package lists... 54s Building dependency tree... 54s Reading state information... 54s Calculating upgrade... 55s The following packages will be upgraded: 55s libpython3-stdlib python3 python3-minimal usbutils 55s 4 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 55s Need to get 148 kB of archives. 55s After this operation, 4096 B disk space will be freed. 55s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed/main s390x python3-minimal s390x 3.13.7-2 [27.8 kB] 55s Get:2 http://ftpmaster.internal/ubuntu resolute-proposed/main s390x python3 s390x 3.13.7-2 [23.9 kB] 55s Get:3 http://ftpmaster.internal/ubuntu resolute-proposed/main s390x libpython3-stdlib s390x 3.13.7-2 [10.6 kB] 55s Get:4 http://ftpmaster.internal/ubuntu resolute/main s390x usbutils s390x 1:019-1 [85.6 kB] 55s dpkg-preconfigure: unable to re-open stdin: No such file or directory 55s Fetched 148 kB in 0s (362 kB/s) 56s (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 ... 61309 files and directories currently installed.) 56s Preparing to unpack .../python3-minimal_3.13.7-2_s390x.deb ... 56s Unpacking python3-minimal (3.13.7-2) over (3.13.7-1) ... 56s Setting up python3-minimal (3.13.7-2) ... 56s (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 ... 61309 files and directories currently installed.) 56s Preparing to unpack .../python3_3.13.7-2_s390x.deb ... 56s running python pre-rtupdate hooks for python3.13... 56s Unpacking python3 (3.13.7-2) over (3.13.7-1) ... 56s Preparing to unpack .../libpython3-stdlib_3.13.7-2_s390x.deb ... 56s Unpacking libpython3-stdlib:s390x (3.13.7-2) over (3.13.7-1) ... 56s Preparing to unpack .../usbutils_1%3a019-1_s390x.deb ... 56s Unpacking usbutils (1:019-1) over (1:018-2) ... 56s Setting up usbutils (1:019-1) ... 56s Setting up libpython3-stdlib:s390x (3.13.7-2) ... 56s Setting up python3 (3.13.7-2) ... 56s running python rtupdate hooks for python3.13... 56s running python post-rtupdate hooks for python3.13... 56s Processing triggers for man-db (2.13.1-1) ... 57s autopkgtest [11:45:13]: upgrading testbed (apt dist-upgrade and autopurge) 57s Reading package lists... 57s Building dependency tree... 57s Reading state information... 57s Calculating upgrade... 57s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 58s Reading package lists... 58s Building dependency tree... 58s Reading state information... 58s Solving dependencies... 58s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 60s autopkgtest [11:45:16]: testbed running kernel: Linux 6.17.0-5-generic #5-Ubuntu SMP Mon Sep 22 08:56:47 UTC 2025 61s autopkgtest [11:45:17]: @@@@@@@@@@@@@@@@@@@@ apt-source con-duct 62s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed/universe con-duct 0.17.0-1 (dsc) [2831 B] 62s Get:2 http://ftpmaster.internal/ubuntu resolute-proposed/universe con-duct 0.17.0-1 (tar) [63.8 kB] 62s Get:3 http://ftpmaster.internal/ubuntu resolute-proposed/universe con-duct 0.17.0-1 (diff) [4260 B] 62s gpgv: Signature made Fri Oct 31 00:40:32 2025 UTC 62s gpgv: using RSA key 13796755BBC72BB8ABE2AEB5FA9DEC5DE11C63F1 62s gpgv: issuer "eamanu@debian.org" 62s gpgv: Can't check signature: No public key 62s dpkg-source: warning: cannot verify inline signature for ./con-duct_0.17.0-1.dsc: no acceptable signature found 62s autopkgtest [11:45:18]: testing package con-duct version 0.17.0-1 62s autopkgtest [11:45:18]: build not needed 64s autopkgtest [11:45:20]: test pybuild-autopkgtest: preparing testbed 64s Reading package lists... 64s Building dependency tree... 64s Reading state information... 64s Solving dependencies... 64s The following NEW packages will be installed: 64s autoconf automake autopoint autotools-dev blt build-essential con-duct cpp 64s cpp-15 cpp-15-s390x-linux-gnu cpp-s390x-linux-gnu debhelper debugedit 64s dh-autoreconf dh-python dh-strip-nondeterminism dwz fontconfig-config 64s fonts-dejavu-core fonts-dejavu-mono fonts-lyx g++ g++-15 64s g++-15-s390x-linux-gnu g++-s390x-linux-gnu gcc gcc-15 gcc-15-s390x-linux-gnu 64s gcc-s390x-linux-gnu gettext help2man intltool-debian libarchive-zip-perl 64s libasan8 libblas3 libcc1-0 libdebhelper-perl libdeflate0 64s libfile-stripnondeterminism-perl libfontconfig1 libfreetype6 libgcc-15-dev 64s libgfortran5 libgomp1 libgraphite2-3 libharfbuzz0b libimagequant0 libisl23 64s libitm1 libjbig0 libjpeg-turbo8 libjpeg8 libjs-jquery libjs-jquery-hotkeys 64s libjs-jquery-isonscreen libjs-jquery-metadata libjs-jquery-tablesorter 64s libjs-jquery-throttle-debounce liblapack3 liblcms2-2 libmpc3 libopenjp2-7 64s libpython3.14-minimal libpython3.14-stdlib libqhull-r8.0 libraqm0 64s libsharpyuv0 libstdc++-15-dev libtcl8.6 libtiff6 libtk8.6 libtool libubsan1 64s libwebp7 libwebpdemux2 libwebpmux3 libxft2 libxrender1 libxslt1.1 libxss1 64s libzopfli1 m4 po-debconf pybuild-plugin-autopkgtest pybuild-plugin-pyproject 64s python-matplotlib-data python3-all python3-blessed python3-brotli 64s python3-build python3-contourpy python3-coverage python3-cycler 64s python3-decorator python3-fonttools python3-fs python3-iniconfig 64s python3-installer python3-kiwisolver python3-lxml python3-lz4 64s python3-matplotlib python3-mpmath python3-numpy python3-numpy-dev 64s python3-pil python3-pil.imagetk python3-platformdirs python3-pluggy 64s python3-pyout python3-pyproject-hooks python3-pytest python3-pytest-cov 64s python3-pytest-rerunfailures python3-scipy python3-sympy python3-tk 64s python3-ufolib2 python3-wcwidth python3-wheel python3-zopfli python3.13-tk 64s python3.14 python3.14-minimal python3.14-tk tk8.6-blt2.5 unicode-data 64s x11-common 65s 0 upgraded, 128 newly installed, 0 to remove and 0 not upgraded. 65s Need to get 141 MB of archives. 65s After this operation, 544 MB of additional disk space will be used. 65s Get:1 http://ftpmaster.internal/ubuntu resolute/main s390x python3-numpy-dev s390x 1:2.2.4+ds-1ubuntu1 [147 kB] 65s Get:2 http://ftpmaster.internal/ubuntu resolute/main s390x libblas3 s390x 3.12.1-7 [254 kB] 65s Get:3 http://ftpmaster.internal/ubuntu resolute/main s390x libgfortran5 s390x 15.2.0-7ubuntu1 [629 kB] 65s Get:4 http://ftpmaster.internal/ubuntu resolute/main s390x liblapack3 s390x 3.12.1-7 [2983 kB] 66s Get:5 http://ftpmaster.internal/ubuntu resolute/main s390x python3-numpy s390x 1:2.2.4+ds-1ubuntu1 [4399 kB] 67s Get:6 http://ftpmaster.internal/ubuntu resolute/main s390x libpython3.14-minimal s390x 3.14.0-4 [904 kB] 67s Get:7 http://ftpmaster.internal/ubuntu resolute/main s390x python3.14-minimal s390x 3.14.0-4 [2509 kB] 67s Get:8 http://ftpmaster.internal/ubuntu resolute/main s390x m4 s390x 1.4.20-2 [223 kB] 67s Get:9 http://ftpmaster.internal/ubuntu resolute/main s390x autoconf all 2.72-3.1ubuntu1 [384 kB] 67s Get:10 http://ftpmaster.internal/ubuntu resolute/main s390x autotools-dev all 20240727.1 [43.4 kB] 67s Get:11 http://ftpmaster.internal/ubuntu resolute/main s390x automake all 1:1.18.1-2 [581 kB] 67s Get:12 http://ftpmaster.internal/ubuntu resolute/main s390x autopoint all 0.23.2-1 [620 kB] 67s Get:13 http://ftpmaster.internal/ubuntu resolute/main s390x libtcl8.6 s390x 8.6.17+dfsg-1 [1034 kB] 67s Get:14 http://ftpmaster.internal/ubuntu resolute/main s390x libfreetype6 s390x 2.13.3+dfsg-1build1 [430 kB] 67s Get:15 http://ftpmaster.internal/ubuntu resolute/main s390x fonts-dejavu-mono all 2.37-8 [502 kB] 67s Get:16 http://ftpmaster.internal/ubuntu resolute/main s390x fonts-dejavu-core all 2.37-8 [835 kB] 67s Get:17 http://ftpmaster.internal/ubuntu resolute/main s390x fontconfig-config s390x 2.15.0-2.3ubuntu1 [38.1 kB] 67s Get:18 http://ftpmaster.internal/ubuntu resolute/main s390x libfontconfig1 s390x 2.15.0-2.3ubuntu1 [149 kB] 67s Get:19 http://ftpmaster.internal/ubuntu resolute/main s390x libxrender1 s390x 1:0.9.12-1 [20.9 kB] 67s Get:20 http://ftpmaster.internal/ubuntu resolute/main s390x libxft2 s390x 2.3.6-1build1 [49.6 kB] 67s Get:21 http://ftpmaster.internal/ubuntu resolute/main s390x x11-common all 1:7.7+24ubuntu1 [22.4 kB] 67s Get:22 http://ftpmaster.internal/ubuntu resolute/main s390x libxss1 s390x 1:1.2.3-1build3 [7396 B] 67s Get:23 http://ftpmaster.internal/ubuntu resolute/main s390x libtk8.6 s390x 8.6.17-1 [828 kB] 67s Get:24 http://ftpmaster.internal/ubuntu resolute/main s390x tk8.6-blt2.5 s390x 2.5.3+dfsg-8 [657 kB] 68s Get:25 http://ftpmaster.internal/ubuntu resolute/main s390x blt s390x 2.5.3+dfsg-8 [4826 B] 68s Get:26 http://ftpmaster.internal/ubuntu resolute/main s390x libisl23 s390x 0.27-1 [704 kB] 68s Get:27 http://ftpmaster.internal/ubuntu resolute/main s390x libmpc3 s390x 1.3.1-2 [57.4 kB] 68s Get:28 http://ftpmaster.internal/ubuntu resolute/main s390x cpp-15-s390x-linux-gnu s390x 15.2.0-7ubuntu1 [10.2 MB] 68s Get:29 http://ftpmaster.internal/ubuntu resolute/main s390x cpp-15 s390x 15.2.0-7ubuntu1 [1022 B] 68s Get:30 http://ftpmaster.internal/ubuntu resolute/main s390x cpp-s390x-linux-gnu s390x 4:15.2.0-4ubuntu1 [5746 B] 68s Get:31 http://ftpmaster.internal/ubuntu resolute/main s390x cpp s390x 4:15.2.0-4ubuntu1 [22.4 kB] 68s Get:32 http://ftpmaster.internal/ubuntu resolute/main s390x libcc1-0 s390x 15.2.0-7ubuntu1 [50.0 kB] 68s Get:33 http://ftpmaster.internal/ubuntu resolute/main s390x libgomp1 s390x 15.2.0-7ubuntu1 [154 kB] 68s Get:34 http://ftpmaster.internal/ubuntu resolute/main s390x libitm1 s390x 15.2.0-7ubuntu1 [30.9 kB] 68s Get:35 http://ftpmaster.internal/ubuntu resolute/main s390x libasan8 s390x 15.2.0-7ubuntu1 [2968 kB] 68s Get:36 http://ftpmaster.internal/ubuntu resolute/main s390x libubsan1 s390x 15.2.0-7ubuntu1 [1211 kB] 68s Get:37 http://ftpmaster.internal/ubuntu resolute/main s390x libgcc-15-dev s390x 15.2.0-7ubuntu1 [1045 kB] 68s Get:38 http://ftpmaster.internal/ubuntu resolute/main s390x gcc-15-s390x-linux-gnu s390x 15.2.0-7ubuntu1 [19.9 MB] 69s Get:39 http://ftpmaster.internal/ubuntu resolute/main s390x gcc-15 s390x 15.2.0-7ubuntu1 [513 kB] 69s Get:40 http://ftpmaster.internal/ubuntu resolute/main s390x gcc-s390x-linux-gnu s390x 4:15.2.0-4ubuntu1 [1208 B] 69s Get:41 http://ftpmaster.internal/ubuntu resolute/main s390x gcc s390x 4:15.2.0-4ubuntu1 [5018 B] 69s Get:42 http://ftpmaster.internal/ubuntu resolute/main s390x libstdc++-15-dev s390x 15.2.0-7ubuntu1 [2659 kB] 69s Get:43 http://ftpmaster.internal/ubuntu resolute/main s390x g++-15-s390x-linux-gnu s390x 15.2.0-7ubuntu1 [11.7 MB] 69s Get:44 http://ftpmaster.internal/ubuntu resolute/main s390x g++-15 s390x 15.2.0-7ubuntu1 [23.7 kB] 69s Get:45 http://ftpmaster.internal/ubuntu resolute/main s390x g++-s390x-linux-gnu s390x 4:15.2.0-4ubuntu1 [956 B] 69s Get:46 http://ftpmaster.internal/ubuntu resolute/main s390x g++ s390x 4:15.2.0-4ubuntu1 [1078 B] 69s Get:47 http://ftpmaster.internal/ubuntu resolute/main s390x build-essential s390x 12.12ubuntu1 [5090 B] 69s Get:48 http://ftpmaster.internal/ubuntu resolute/main s390x python3-wcwidth all 0.2.13+dfsg1-1 [26.3 kB] 69s Get:49 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-blessed all 1.21.0-1 [50.4 kB] 69s Get:50 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pyout all 0.8.1-1 [41.9 kB] 69s Get:51 http://ftpmaster.internal/ubuntu resolute-proposed/universe s390x con-duct all 0.17.0-1 [26.5 kB] 69s Get:52 http://ftpmaster.internal/ubuntu resolute/main s390x libdebhelper-perl all 13.24.2ubuntu1 [95.7 kB] 69s Get:53 http://ftpmaster.internal/ubuntu resolute/main s390x libtool all 2.5.4-7 [169 kB] 69s Get:54 http://ftpmaster.internal/ubuntu resolute/main s390x dh-autoreconf all 21 [12.5 kB] 69s Get:55 http://ftpmaster.internal/ubuntu resolute/main s390x libarchive-zip-perl all 1.68-1 [90.2 kB] 69s Get:56 http://ftpmaster.internal/ubuntu resolute/main s390x libfile-stripnondeterminism-perl all 1.15.0-1 [20.5 kB] 70s Get:57 http://ftpmaster.internal/ubuntu resolute/main s390x dh-strip-nondeterminism all 1.15.0-1 [5090 B] 70s Get:58 http://ftpmaster.internal/ubuntu resolute/main s390x debugedit s390x 1:5.2-3 [52.8 kB] 70s Get:59 http://ftpmaster.internal/ubuntu resolute/main s390x dwz s390x 0.16-2 [121 kB] 70s Get:60 http://ftpmaster.internal/ubuntu resolute/main s390x gettext s390x 0.23.2-1 [1062 kB] 70s Get:61 http://ftpmaster.internal/ubuntu resolute/main s390x intltool-debian all 0.35.0+20060710.6 [23.2 kB] 70s Get:62 http://ftpmaster.internal/ubuntu resolute/main s390x po-debconf all 1.0.21+nmu1 [233 kB] 70s Get:63 http://ftpmaster.internal/ubuntu resolute/main s390x debhelper all 13.24.2ubuntu1 [896 kB] 70s Get:64 http://ftpmaster.internal/ubuntu resolute/universe s390x dh-python all 6.20250414 [119 kB] 70s Get:65 http://ftpmaster.internal/ubuntu resolute/universe s390x fonts-lyx all 2.4.4-2 [171 kB] 70s Get:66 http://ftpmaster.internal/ubuntu resolute/universe s390x help2man s390x 1.49.3 [201 kB] 70s Get:67 http://ftpmaster.internal/ubuntu resolute/main s390x libdeflate0 s390x 1.23-2 [46.0 kB] 70s Get:68 http://ftpmaster.internal/ubuntu resolute/main s390x libgraphite2-3 s390x 1.3.14-2ubuntu1 [79.8 kB] 70s Get:69 http://ftpmaster.internal/ubuntu resolute/main s390x libharfbuzz0b s390x 12.1.0-1 [576 kB] 70s Get:70 http://ftpmaster.internal/ubuntu resolute/main s390x libimagequant0 s390x 2.18.0-1build1 [43.3 kB] 70s Get:71 http://ftpmaster.internal/ubuntu resolute/main s390x libjpeg-turbo8 s390x 2.1.5-4ubuntu2 [147 kB] 70s Get:72 http://ftpmaster.internal/ubuntu resolute/main s390x libjpeg8 s390x 8c-2ubuntu11 [2146 B] 70s Get:73 http://ftpmaster.internal/ubuntu resolute/main s390x libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [328 kB] 70s Get:74 http://ftpmaster.internal/ubuntu resolute/universe s390x libjs-jquery-metadata all 12-4 [6582 B] 70s Get:75 http://ftpmaster.internal/ubuntu resolute/universe s390x libjs-jquery-tablesorter all 1:2.31.3+dfsg1-4 [192 kB] 70s Get:76 http://ftpmaster.internal/ubuntu resolute/universe s390x libjs-jquery-throttle-debounce all 1.1+dfsg.1-2 [12.5 kB] 70s Get:77 http://ftpmaster.internal/ubuntu resolute/main s390x liblcms2-2 s390x 2.17-1 [176 kB] 70s Get:78 http://ftpmaster.internal/ubuntu resolute/main s390x libpython3.14-stdlib s390x 3.14.0-4 [2373 kB] 70s Get:79 http://ftpmaster.internal/ubuntu resolute/universe s390x libqhull-r8.0 s390x 2020.2-7 [199 kB] 70s Get:80 http://ftpmaster.internal/ubuntu resolute/main s390x libraqm0 s390x 0.10.3-1 [15.6 kB] 70s Get:81 http://ftpmaster.internal/ubuntu resolute/main s390x libsharpyuv0 s390x 1.5.0-0.1 [16.7 kB] 70s Get:82 http://ftpmaster.internal/ubuntu resolute/main s390x libjbig0 s390x 2.1-6.1ubuntu2 [33.1 kB] 70s Get:83 http://ftpmaster.internal/ubuntu resolute/main s390x libwebp7 s390x 1.5.0-0.1 [210 kB] 70s Get:84 http://ftpmaster.internal/ubuntu resolute/main s390x libtiff6 s390x 4.7.0-3ubuntu3 [222 kB] 70s Get:85 http://ftpmaster.internal/ubuntu resolute/main s390x libwebpdemux2 s390x 1.5.0-0.1 [12.6 kB] 70s Get:86 http://ftpmaster.internal/ubuntu resolute/main s390x libwebpmux3 s390x 1.5.0-0.1 [25.8 kB] 70s Get:87 http://ftpmaster.internal/ubuntu resolute/main s390x libxslt1.1 s390x 1.1.43-0.3 [163 kB] 70s Get:88 http://ftpmaster.internal/ubuntu resolute/universe s390x libzopfli1 s390x 1.0.3-3 [124 kB] 70s Get:89 http://ftpmaster.internal/ubuntu resolute/universe s390x pybuild-plugin-autopkgtest all 6.20250414 [1746 B] 70s Get:90 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pyproject-hooks all 1.2.0-1 [10.2 kB] 70s Get:91 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-wheel all 0.46.1-2 [22.1 kB] 70s Get:92 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-build all 1.2.2-4 [31.0 kB] 70s Get:93 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-installer all 0.7.0+dfsg1-3 [17.4 kB] 70s Get:94 http://ftpmaster.internal/ubuntu resolute/universe s390x pybuild-plugin-pyproject all 6.20250414 [1728 B] 70s Get:95 http://ftpmaster.internal/ubuntu resolute/universe s390x python-matplotlib-data all 3.10.7+dfsg1-1 [2930 kB] 70s Get:96 http://ftpmaster.internal/ubuntu resolute/main s390x python3.14 s390x 3.14.0-4 [805 kB] 70s Get:97 http://ftpmaster.internal/ubuntu resolute-proposed/main s390x python3-all s390x 3.13.7-2 [892 B] 70s Get:98 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-brotli s390x 1.1.0-2build6 [386 kB] 70s Get:99 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-contourpy s390x 1.3.1-2 [266 kB] 70s Get:100 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-coverage s390x 7.8.2+dfsg1-1 [156 kB] 70s Get:101 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-cycler all 0.12.1-2 [9850 B] 70s Get:102 http://ftpmaster.internal/ubuntu resolute/main s390x python3-decorator all 5.2.1-2 [28.1 kB] 70s Get:103 http://ftpmaster.internal/ubuntu resolute/main s390x python3-platformdirs all 4.3.7-1 [16.9 kB] 70s Get:104 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-fs all 2.4.16-9ubuntu1 [91.5 kB] 70s Get:105 http://ftpmaster.internal/ubuntu resolute/main s390x python3-lxml s390x 6.0.2-1 [2478 kB] 71s Get:106 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-lz4 s390x 4.4.4+dfsg-3 [27.4 kB] 71s Get:107 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-scipy s390x 1.15.3-1ubuntu1 [21.3 MB] 72s Get:108 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-mpmath all 1.3.0-2 [423 kB] 72s Get:109 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-sympy all 1.14.0-2 [4306 kB] 72s Get:110 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-ufolib2 all 0.17.1+dfsg1-1 [33.5 kB] 72s Get:111 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-zopfli s390x 0.4.0-1 [11.2 kB] 72s Get:112 http://ftpmaster.internal/ubuntu resolute/universe s390x unicode-data all 16.0.0-1 [9513 kB] 73s Get:113 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-fonttools s390x 4.57.0-2build1 [1773 kB] 73s Get:114 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-iniconfig all 2.1.0-1 [6840 B] 73s Get:115 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-kiwisolver s390x 1.4.10~rc0-1 [65.0 kB] 73s Get:116 http://ftpmaster.internal/ubuntu resolute/main s390x libopenjp2-7 s390x 2.5.3-2.1 [207 kB] 73s Get:117 http://ftpmaster.internal/ubuntu resolute/main s390x python3-pil s390x 11.3.0-1ubuntu2 [542 kB] 73s Get:118 http://ftpmaster.internal/ubuntu resolute/main s390x python3.14-tk s390x 3.14.0-4 [109 kB] 73s Get:119 http://ftpmaster.internal/ubuntu resolute/main s390x python3.13-tk s390x 3.13.9-1 [109 kB] 73s Get:120 http://ftpmaster.internal/ubuntu resolute/main s390x python3-tk s390x 3.13.9-1 [8948 B] 73s Get:121 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pil.imagetk s390x 11.3.0-1ubuntu2 [9922 B] 73s Get:122 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-matplotlib s390x 3.10.7+dfsg1-1 [17.2 MB] 73s Get:123 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pluggy all 1.6.0-1 [21.0 kB] 73s Get:124 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pytest all 8.3.5-2 [252 kB] 73s Get:125 http://ftpmaster.internal/ubuntu resolute/universe s390x libjs-jquery-hotkeys all 0.2.0-1 [13.3 kB] 73s Get:126 http://ftpmaster.internal/ubuntu resolute/universe s390x libjs-jquery-isonscreen all 1.2.0-1.1 [3244 B] 73s Get:127 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pytest-cov all 5.0.0-1 [21.3 kB] 73s Get:128 http://ftpmaster.internal/ubuntu resolute/universe s390x python3-pytest-rerunfailures all 16.1-1 [14.9 kB] 74s Fetched 141 MB in 9s (16.0 MB/s) 74s Selecting previously unselected package python3-numpy-dev:s390x. 74s (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 ... 61309 files and directories currently installed.) 74s Preparing to unpack .../000-python3-numpy-dev_1%3a2.2.4+ds-1ubuntu1_s390x.deb ... 74s Unpacking python3-numpy-dev:s390x (1:2.2.4+ds-1ubuntu1) ... 74s Selecting previously unselected package libblas3:s390x. 74s Preparing to unpack .../001-libblas3_3.12.1-7_s390x.deb ... 74s Unpacking libblas3:s390x (3.12.1-7) ... 74s Selecting previously unselected package libgfortran5:s390x. 74s Preparing to unpack .../002-libgfortran5_15.2.0-7ubuntu1_s390x.deb ... 74s Unpacking libgfortran5:s390x (15.2.0-7ubuntu1) ... 74s Selecting previously unselected package liblapack3:s390x. 74s Preparing to unpack .../003-liblapack3_3.12.1-7_s390x.deb ... 74s Unpacking liblapack3:s390x (3.12.1-7) ... 74s Selecting previously unselected package python3-numpy. 74s Preparing to unpack .../004-python3-numpy_1%3a2.2.4+ds-1ubuntu1_s390x.deb ... 74s Unpacking python3-numpy (1:2.2.4+ds-1ubuntu1) ... 74s Selecting previously unselected package libpython3.14-minimal:s390x. 74s Preparing to unpack .../005-libpython3.14-minimal_3.14.0-4_s390x.deb ... 74s Unpacking libpython3.14-minimal:s390x (3.14.0-4) ... 74s Selecting previously unselected package python3.14-minimal. 74s Preparing to unpack .../006-python3.14-minimal_3.14.0-4_s390x.deb ... 74s Unpacking python3.14-minimal (3.14.0-4) ... 74s Selecting previously unselected package m4. 74s Preparing to unpack .../007-m4_1.4.20-2_s390x.deb ... 74s Unpacking m4 (1.4.20-2) ... 74s Selecting previously unselected package autoconf. 74s Preparing to unpack .../008-autoconf_2.72-3.1ubuntu1_all.deb ... 74s Unpacking autoconf (2.72-3.1ubuntu1) ... 74s Selecting previously unselected package autotools-dev. 74s Preparing to unpack .../009-autotools-dev_20240727.1_all.deb ... 74s Unpacking autotools-dev (20240727.1) ... 74s Selecting previously unselected package automake. 74s Preparing to unpack .../010-automake_1%3a1.18.1-2_all.deb ... 74s Unpacking automake (1:1.18.1-2) ... 74s Selecting previously unselected package autopoint. 74s Preparing to unpack .../011-autopoint_0.23.2-1_all.deb ... 74s Unpacking autopoint (0.23.2-1) ... 74s Selecting previously unselected package libtcl8.6:s390x. 74s Preparing to unpack .../012-libtcl8.6_8.6.17+dfsg-1_s390x.deb ... 74s Unpacking libtcl8.6:s390x (8.6.17+dfsg-1) ... 74s Selecting previously unselected package libfreetype6:s390x. 74s Preparing to unpack .../013-libfreetype6_2.13.3+dfsg-1build1_s390x.deb ... 74s Unpacking libfreetype6:s390x (2.13.3+dfsg-1build1) ... 74s Selecting previously unselected package fonts-dejavu-mono. 74s Preparing to unpack .../014-fonts-dejavu-mono_2.37-8_all.deb ... 74s Unpacking fonts-dejavu-mono (2.37-8) ... 74s Selecting previously unselected package fonts-dejavu-core. 74s Preparing to unpack .../015-fonts-dejavu-core_2.37-8_all.deb ... 74s Unpacking fonts-dejavu-core (2.37-8) ... 74s Selecting previously unselected package fontconfig-config. 74s Preparing to unpack .../016-fontconfig-config_2.15.0-2.3ubuntu1_s390x.deb ... 74s Unpacking fontconfig-config (2.15.0-2.3ubuntu1) ... 74s Selecting previously unselected package libfontconfig1:s390x. 74s Preparing to unpack .../017-libfontconfig1_2.15.0-2.3ubuntu1_s390x.deb ... 74s Unpacking libfontconfig1:s390x (2.15.0-2.3ubuntu1) ... 74s Selecting previously unselected package libxrender1:s390x. 74s Preparing to unpack .../018-libxrender1_1%3a0.9.12-1_s390x.deb ... 74s Unpacking libxrender1:s390x (1:0.9.12-1) ... 74s Selecting previously unselected package libxft2:s390x. 74s Preparing to unpack .../019-libxft2_2.3.6-1build1_s390x.deb ... 74s Unpacking libxft2:s390x (2.3.6-1build1) ... 74s Selecting previously unselected package x11-common. 74s Preparing to unpack .../020-x11-common_1%3a7.7+24ubuntu1_all.deb ... 74s Unpacking x11-common (1:7.7+24ubuntu1) ... 74s Selecting previously unselected package libxss1:s390x. 74s Preparing to unpack .../021-libxss1_1%3a1.2.3-1build3_s390x.deb ... 74s Unpacking libxss1:s390x (1:1.2.3-1build3) ... 74s Selecting previously unselected package libtk8.6:s390x. 74s Preparing to unpack .../022-libtk8.6_8.6.17-1_s390x.deb ... 74s Unpacking libtk8.6:s390x (8.6.17-1) ... 74s Selecting previously unselected package tk8.6-blt2.5. 74s Preparing to unpack .../023-tk8.6-blt2.5_2.5.3+dfsg-8_s390x.deb ... 74s Unpacking tk8.6-blt2.5 (2.5.3+dfsg-8) ... 74s Selecting previously unselected package blt. 74s Preparing to unpack .../024-blt_2.5.3+dfsg-8_s390x.deb ... 74s Unpacking blt (2.5.3+dfsg-8) ... 74s Selecting previously unselected package libisl23:s390x. 74s Preparing to unpack .../025-libisl23_0.27-1_s390x.deb ... 74s Unpacking libisl23:s390x (0.27-1) ... 74s Selecting previously unselected package libmpc3:s390x. 74s Preparing to unpack .../026-libmpc3_1.3.1-2_s390x.deb ... 74s Unpacking libmpc3:s390x (1.3.1-2) ... 74s Selecting previously unselected package cpp-15-s390x-linux-gnu. 74s Preparing to unpack .../027-cpp-15-s390x-linux-gnu_15.2.0-7ubuntu1_s390x.deb ... 74s Unpacking cpp-15-s390x-linux-gnu (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package cpp-15. 75s Preparing to unpack .../028-cpp-15_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking cpp-15 (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package cpp-s390x-linux-gnu. 75s Preparing to unpack .../029-cpp-s390x-linux-gnu_4%3a15.2.0-4ubuntu1_s390x.deb ... 75s Unpacking cpp-s390x-linux-gnu (4:15.2.0-4ubuntu1) ... 75s Selecting previously unselected package cpp. 75s Preparing to unpack .../030-cpp_4%3a15.2.0-4ubuntu1_s390x.deb ... 75s Unpacking cpp (4:15.2.0-4ubuntu1) ... 75s Selecting previously unselected package libcc1-0:s390x. 75s Preparing to unpack .../031-libcc1-0_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libcc1-0:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package libgomp1:s390x. 75s Preparing to unpack .../032-libgomp1_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libgomp1:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package libitm1:s390x. 75s Preparing to unpack .../033-libitm1_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libitm1:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package libasan8:s390x. 75s Preparing to unpack .../034-libasan8_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libasan8:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package libubsan1:s390x. 75s Preparing to unpack .../035-libubsan1_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libubsan1:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package libgcc-15-dev:s390x. 75s Preparing to unpack .../036-libgcc-15-dev_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libgcc-15-dev:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package gcc-15-s390x-linux-gnu. 75s Preparing to unpack .../037-gcc-15-s390x-linux-gnu_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking gcc-15-s390x-linux-gnu (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package gcc-15. 75s Preparing to unpack .../038-gcc-15_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking gcc-15 (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package gcc-s390x-linux-gnu. 75s Preparing to unpack .../039-gcc-s390x-linux-gnu_4%3a15.2.0-4ubuntu1_s390x.deb ... 75s Unpacking gcc-s390x-linux-gnu (4:15.2.0-4ubuntu1) ... 75s Selecting previously unselected package gcc. 75s Preparing to unpack .../040-gcc_4%3a15.2.0-4ubuntu1_s390x.deb ... 75s Unpacking gcc (4:15.2.0-4ubuntu1) ... 75s Selecting previously unselected package libstdc++-15-dev:s390x. 75s Preparing to unpack .../041-libstdc++-15-dev_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking libstdc++-15-dev:s390x (15.2.0-7ubuntu1) ... 75s Selecting previously unselected package g++-15-s390x-linux-gnu. 75s Preparing to unpack .../042-g++-15-s390x-linux-gnu_15.2.0-7ubuntu1_s390x.deb ... 75s Unpacking g++-15-s390x-linux-gnu (15.2.0-7ubuntu1) ... 76s Selecting previously unselected package g++-15. 76s Preparing to unpack .../043-g++-15_15.2.0-7ubuntu1_s390x.deb ... 76s Unpacking g++-15 (15.2.0-7ubuntu1) ... 76s Selecting previously unselected package g++-s390x-linux-gnu. 76s Preparing to unpack .../044-g++-s390x-linux-gnu_4%3a15.2.0-4ubuntu1_s390x.deb ... 76s Unpacking g++-s390x-linux-gnu (4:15.2.0-4ubuntu1) ... 76s Selecting previously unselected package g++. 76s Preparing to unpack .../045-g++_4%3a15.2.0-4ubuntu1_s390x.deb ... 76s Unpacking g++ (4:15.2.0-4ubuntu1) ... 76s Selecting previously unselected package build-essential. 76s Preparing to unpack .../046-build-essential_12.12ubuntu1_s390x.deb ... 76s Unpacking build-essential (12.12ubuntu1) ... 76s Selecting previously unselected package python3-wcwidth. 76s Preparing to unpack .../047-python3-wcwidth_0.2.13+dfsg1-1_all.deb ... 76s Unpacking python3-wcwidth (0.2.13+dfsg1-1) ... 76s Selecting previously unselected package python3-blessed. 76s Preparing to unpack .../048-python3-blessed_1.21.0-1_all.deb ... 76s Unpacking python3-blessed (1.21.0-1) ... 76s Selecting previously unselected package python3-pyout. 76s Preparing to unpack .../049-python3-pyout_0.8.1-1_all.deb ... 76s Unpacking python3-pyout (0.8.1-1) ... 76s Selecting previously unselected package con-duct. 76s Preparing to unpack .../050-con-duct_0.17.0-1_all.deb ... 76s Unpacking con-duct (0.17.0-1) ... 76s Selecting previously unselected package libdebhelper-perl. 76s Preparing to unpack .../051-libdebhelper-perl_13.24.2ubuntu1_all.deb ... 76s Unpacking libdebhelper-perl (13.24.2ubuntu1) ... 76s Selecting previously unselected package libtool. 76s Preparing to unpack .../052-libtool_2.5.4-7_all.deb ... 76s Unpacking libtool (2.5.4-7) ... 76s Selecting previously unselected package dh-autoreconf. 76s Preparing to unpack .../053-dh-autoreconf_21_all.deb ... 76s Unpacking dh-autoreconf (21) ... 76s Selecting previously unselected package libarchive-zip-perl. 76s Preparing to unpack .../054-libarchive-zip-perl_1.68-1_all.deb ... 76s Unpacking libarchive-zip-perl (1.68-1) ... 76s Selecting previously unselected package libfile-stripnondeterminism-perl. 76s Preparing to unpack .../055-libfile-stripnondeterminism-perl_1.15.0-1_all.deb ... 76s Unpacking libfile-stripnondeterminism-perl (1.15.0-1) ... 76s Selecting previously unselected package dh-strip-nondeterminism. 76s Preparing to unpack .../056-dh-strip-nondeterminism_1.15.0-1_all.deb ... 76s Unpacking dh-strip-nondeterminism (1.15.0-1) ... 76s Selecting previously unselected package debugedit. 76s Preparing to unpack .../057-debugedit_1%3a5.2-3_s390x.deb ... 76s Unpacking debugedit (1:5.2-3) ... 76s Selecting previously unselected package dwz. 76s Preparing to unpack .../058-dwz_0.16-2_s390x.deb ... 76s Unpacking dwz (0.16-2) ... 76s Selecting previously unselected package gettext. 76s Preparing to unpack .../059-gettext_0.23.2-1_s390x.deb ... 76s Unpacking gettext (0.23.2-1) ... 76s Selecting previously unselected package intltool-debian. 76s Preparing to unpack .../060-intltool-debian_0.35.0+20060710.6_all.deb ... 76s Unpacking intltool-debian (0.35.0+20060710.6) ... 76s Selecting previously unselected package po-debconf. 76s Preparing to unpack .../061-po-debconf_1.0.21+nmu1_all.deb ... 76s Unpacking po-debconf (1.0.21+nmu1) ... 76s Selecting previously unselected package debhelper. 76s Preparing to unpack .../062-debhelper_13.24.2ubuntu1_all.deb ... 76s Unpacking debhelper (13.24.2ubuntu1) ... 76s Selecting previously unselected package dh-python. 76s Preparing to unpack .../063-dh-python_6.20250414_all.deb ... 76s Unpacking dh-python (6.20250414) ... 76s Selecting previously unselected package fonts-lyx. 76s Preparing to unpack .../064-fonts-lyx_2.4.4-2_all.deb ... 76s Unpacking fonts-lyx (2.4.4-2) ... 76s Selecting previously unselected package help2man. 76s Preparing to unpack .../065-help2man_1.49.3_s390x.deb ... 76s Unpacking help2man (1.49.3) ... 76s Selecting previously unselected package libdeflate0:s390x. 76s Preparing to unpack .../066-libdeflate0_1.23-2_s390x.deb ... 76s Unpacking libdeflate0:s390x (1.23-2) ... 76s Selecting previously unselected package libgraphite2-3:s390x. 76s Preparing to unpack .../067-libgraphite2-3_1.3.14-2ubuntu1_s390x.deb ... 76s Unpacking libgraphite2-3:s390x (1.3.14-2ubuntu1) ... 76s Selecting previously unselected package libharfbuzz0b:s390x. 76s Preparing to unpack .../068-libharfbuzz0b_12.1.0-1_s390x.deb ... 76s Unpacking libharfbuzz0b:s390x (12.1.0-1) ... 76s Selecting previously unselected package libimagequant0:s390x. 76s Preparing to unpack .../069-libimagequant0_2.18.0-1build1_s390x.deb ... 76s Unpacking libimagequant0:s390x (2.18.0-1build1) ... 76s Selecting previously unselected package libjpeg-turbo8:s390x. 76s Preparing to unpack .../070-libjpeg-turbo8_2.1.5-4ubuntu2_s390x.deb ... 76s Unpacking libjpeg-turbo8:s390x (2.1.5-4ubuntu2) ... 76s Selecting previously unselected package libjpeg8:s390x. 76s Preparing to unpack .../071-libjpeg8_8c-2ubuntu11_s390x.deb ... 76s Unpacking libjpeg8:s390x (8c-2ubuntu11) ... 76s Selecting previously unselected package libjs-jquery. 76s Preparing to unpack .../072-libjs-jquery_3.6.1+dfsg+~3.5.14-1_all.deb ... 76s Unpacking libjs-jquery (3.6.1+dfsg+~3.5.14-1) ... 76s Selecting previously unselected package libjs-jquery-metadata. 76s Preparing to unpack .../073-libjs-jquery-metadata_12-4_all.deb ... 76s Unpacking libjs-jquery-metadata (12-4) ... 76s Selecting previously unselected package libjs-jquery-tablesorter. 76s Preparing to unpack .../074-libjs-jquery-tablesorter_1%3a2.31.3+dfsg1-4_all.deb ... 76s Unpacking libjs-jquery-tablesorter (1:2.31.3+dfsg1-4) ... 76s Selecting previously unselected package libjs-jquery-throttle-debounce. 76s Preparing to unpack .../075-libjs-jquery-throttle-debounce_1.1+dfsg.1-2_all.deb ... 76s Unpacking libjs-jquery-throttle-debounce (1.1+dfsg.1-2) ... 76s Selecting previously unselected package liblcms2-2:s390x. 76s Preparing to unpack .../076-liblcms2-2_2.17-1_s390x.deb ... 76s Unpacking liblcms2-2:s390x (2.17-1) ... 76s Selecting previously unselected package libpython3.14-stdlib:s390x. 76s Preparing to unpack .../077-libpython3.14-stdlib_3.14.0-4_s390x.deb ... 76s Unpacking libpython3.14-stdlib:s390x (3.14.0-4) ... 76s Selecting previously unselected package libqhull-r8.0:s390x. 76s Preparing to unpack .../078-libqhull-r8.0_2020.2-7_s390x.deb ... 76s Unpacking libqhull-r8.0:s390x (2020.2-7) ... 76s Selecting previously unselected package libraqm0:s390x. 76s Preparing to unpack .../079-libraqm0_0.10.3-1_s390x.deb ... 76s Unpacking libraqm0:s390x (0.10.3-1) ... 76s Selecting previously unselected package libsharpyuv0:s390x. 76s Preparing to unpack .../080-libsharpyuv0_1.5.0-0.1_s390x.deb ... 76s Unpacking libsharpyuv0:s390x (1.5.0-0.1) ... 76s Selecting previously unselected package libjbig0:s390x. 76s Preparing to unpack .../081-libjbig0_2.1-6.1ubuntu2_s390x.deb ... 76s Unpacking libjbig0:s390x (2.1-6.1ubuntu2) ... 76s Selecting previously unselected package libwebp7:s390x. 76s Preparing to unpack .../082-libwebp7_1.5.0-0.1_s390x.deb ... 76s Unpacking libwebp7:s390x (1.5.0-0.1) ... 76s Selecting previously unselected package libtiff6:s390x. 76s Preparing to unpack .../083-libtiff6_4.7.0-3ubuntu3_s390x.deb ... 76s Unpacking libtiff6:s390x (4.7.0-3ubuntu3) ... 76s Selecting previously unselected package libwebpdemux2:s390x. 76s Preparing to unpack .../084-libwebpdemux2_1.5.0-0.1_s390x.deb ... 76s Unpacking libwebpdemux2:s390x (1.5.0-0.1) ... 76s Selecting 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python3-matplotlib (3.10.7+dfsg1-1) ... 111s Processing triggers for libc-bin (2.42-2ubuntu2) ... 111s Processing triggers for systemd (257.9-0ubuntu2) ... 111s Processing triggers for man-db (2.13.1-1) ... 112s Processing triggers for install-info (7.2-5) ... 113s autopkgtest [11:46:09]: test pybuild-autopkgtest: pybuild-autopkgtest 113s autopkgtest [11:46:09]: test pybuild-autopkgtest: [----------------------- 114s pybuild-autopkgtest 114s I: pybuild pybuild:308: chmod +x /tmp/autopkgtest.7d5d64/build.e24/src/test/data/spawn_children.sh 114s I: pybuild base:311: cd /tmp/autopkgtest.7d5d64/autopkgtest_tmp/build; python3.14 -m pytest test 115s ============================= test session starts ============================== 115s platform linux -- Python 3.14.0, pytest-8.3.5, pluggy-1.6.0 115s rootdir: /tmp/autopkgtest.7d5d64/autopkgtest_tmp/build 115s configfile: pyproject.toml 115s plugins: typeguard-4.4.2, rerunfailures-16.1, cov-5.0.0 115s collected 289 items 115s 115s test/test_aggregation.py .............. [ 4%] 116s test/test_arg_parsing.py .............. [ 9%] 127s test/test_e2e.py ................ [ 15%] 146s test/test_execution.py .......................... [ 24%] 146s test/test_formatter.py ................................................. [ 41%] 146s ......... [ 44%] 146s test/test_log_paths.py .............. [ 49%] 146s test/test_ls.py ............ [ 53%] 147s test/test_plot_humanization.py FFFFFFFFFFFFFFFFFFFFFFF [ 61%] 147s test/test_prepare_outputs.py ................ [ 66%] 147s test/test_report.py ........................ [ 75%] 147s test/test_schema.py . [ 75%] 148s test/test_suite.py .............FFFFF.FFF.......... [ 86%] 151s test/test_tailpipe.py ............... [ 91%] 151s test/test_utils.py ........... [ 95%] 151s test/test_validation.py ............. [100%] 151s 151s =================================== FAILURES =================================== 151s __________________ test_pick_unit_with_varying_ratios[-1-2-s] __________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = -1, span_seconds = 2, expected_unit = 's' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ________________ test_pick_unit_with_varying_ratios[-1-3700-s] _________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = -1, span_seconds = 3700, expected_unit = 's' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[-1-259200-s] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = -1, span_seconds = 259200, expected_unit = 's' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ________________ test_pick_unit_with_varying_ratios[1.5-90-min] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 1.5, span_seconds = 90, expected_unit = 'min' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ________________ test_pick_unit_with_varying_ratios[1.5-5400-h] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 1.5, span_seconds = 5400, expected_unit = 'h' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[1.5-129600-d] _______________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 1.5, span_seconds = 129600, expected_unit = 'd' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _________________ test_pick_unit_with_varying_ratios[3.0-2-s] __________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 3.0, span_seconds = 2, expected_unit = 's' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[3.0-180-min] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 3.0, span_seconds = 180, expected_unit = 'min' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[3.0-10800-h] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 3.0, span_seconds = 10800, expected_unit = 'h' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[3.0-259200-d] _______________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 3.0, span_seconds = 259200, expected_unit = 'd' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ________________ test_pick_unit_with_varying_ratios[5.0-240-s] _________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 5.0, span_seconds = 240, expected_unit = 's' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[5.0-300-min] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 5.0, span_seconds = 300, expected_unit = 'min' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ______________ test_pick_unit_with_varying_ratios[5.0-14400-min] _______________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 5.0, span_seconds = 14400, expected_unit = 'min' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s _______________ test_pick_unit_with_varying_ratios[5.0-18000-h] ________________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s min_ratio = 5.0, span_seconds = 18000, expected_unit = 'h' 151s 151s @pytest.mark.parametrize( 151s "min_ratio,span_seconds,expected_unit", 151s [ 151s # min_ratio=-1: always use base unit 151s (-1, 2, "s"), # Small value 151s (-1, 3700, "s"), # More than 1 hour - still base unit 151s (-1, 3 * 60 * 60 * 24, "s"), # 3 days - still base unit 151s # min_ratio=1.5: switch units more aggressively 151s (1.5, 90, "min"), # 1.5 minutes meets threshold 151s (1.5, 90 * 60, "h"), # 1.5 hours meets threshold 151s (1.5, 36 * 60 * 60, "d"), # 1.5 days meets threshold 151s # min_ratio=3.0: standard threshold 151s (3.0, 2, "s"), # 2 seconds - stays in base unit 151s (3.0, 3 * 60, "min"), # 3 minutes - meets min_ratio for minutes 151s (3.0, 3 * 60 * 60, "h"), # 3 hours - meets min_ratio for hours 151s (3.0, 3 * 60 * 60 * 24, "d"), # 3 days - meets min_ratio for days 151s # min_ratio=5.0: more conservative switching 151s (5.0, 4 * 60, "s"), # 4 minutes - doesn't meet threshold, stays seconds 151s (5.0, 5 * 60, "min"), # 5 minutes - meets threshold 151s (5.0, 4 * 60 * 60, "min"), # 4 hours - doesn't meet hour threshold 151s (5.0, 5 * 60 * 60, "h"), # 5 hours - meets hour threshold 151s ], 151s ) 151s def test_pick_unit_with_varying_ratios( 151s min_ratio: float, span_seconds: float, expected_unit: str 151s ) -> None: 151s """Test pick_unit selects appropriate unit based on min_ratio.""" 151s > formatter: Any = plot.HumanizedAxisFormatter( 151s min_ratio=min_ratio, units=plot._TIME_UNITS 151s ) 151s 151s test/test_plot_humanization.py:36: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ______________ test_formatter_output[units0-axis_range0-15-15.0s] ______________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s units = [('s', 1), ('min', 60), ('h', 3600), ('d', 86400)], axis_range = (0, 30) 151s value = 15, expected = '15.0s' 151s 151s @pytest.mark.parametrize( 151s "units,axis_range,value,expected", 151s [ 151s # Time formatting tests 151s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 151s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 151s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 151s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 151s # Memory formatting tests 151s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 151s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 151s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 151s ], 151s ) 151s def test_formatter_output( 151s units: List[Tuple[str, float]], 151s axis_range: Tuple[float, float], 151s value: float, 151s expected: str, 151s ) -> None: 151s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 151s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 151s 151s test/test_plot_humanization.py:66: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ____________ test_formatter_output[units1-axis_range1-138.0-2.3min] ____________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s units = [('s', 1), ('min', 60), ('h', 3600), ('d', 86400)] 151s axis_range = (0, 300), value = 138.0, expected = '2.3min' 151s 151s @pytest.mark.parametrize( 151s "units,axis_range,value,expected", 151s [ 151s # Time formatting tests 151s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 151s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 151s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 151s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 151s # Memory formatting tests 151s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 151s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 151s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 151s ], 151s ) 151s def test_formatter_output( 151s units: List[Tuple[str, float]], 151s axis_range: Tuple[float, float], 151s value: float, 151s expected: str, 151s ) -> None: 151s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 151s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 151s 151s test/test_plot_humanization.py:66: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ____________ test_formatter_output[units2-axis_range2-28080.0-7.8h] ____________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s units = [('s', 1), ('min', 60), ('h', 3600), ('d', 86400)] 151s axis_range = (0, 11000), value = 28080.0, expected = '7.8h' 151s 151s @pytest.mark.parametrize( 151s "units,axis_range,value,expected", 151s [ 151s # Time formatting tests 151s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 151s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 151s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 151s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 151s # Memory formatting tests 151s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 151s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 151s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 151s ], 151s ) 151s def test_formatter_output( 151s units: List[Tuple[str, float]], 151s axis_range: Tuple[float, float], 151s value: float, 151s expected: str, 151s ) -> None: 151s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 151s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 151s 151s test/test_plot_humanization.py:66: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ___________ test_formatter_output[units3-axis_range3-276480.0-3.2d] ____________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s units = [('s', 1), ('min', 60), ('h', 3600), ('d', 86400)] 151s axis_range = (0, 260000), value = 276480.0, expected = '3.2d' 151s 151s @pytest.mark.parametrize( 151s "units,axis_range,value,expected", 151s [ 151s # Time formatting tests 151s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 151s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 151s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 151s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 151s # Memory formatting tests 151s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 151s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 151s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 151s ], 151s ) 151s def test_formatter_output( 151s units: List[Tuple[str, float]], 151s axis_range: Tuple[float, float], 151s value: float, 151s expected: str, 151s ) -> None: 151s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 151s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 151s 151s test/test_plot_humanization.py:66: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s from numpy.__config__ import show_config 151s except ImportError as e: 151s msg = """Error importing numpy: you should not try to import numpy from 151s its source directory; please exit the numpy source tree, and relaunch 151s your python interpreter from there.""" 151s > raise ImportError(msg) from e 151s E ImportError: Error importing numpy: you should not try to import numpy from 151s E its source directory; please exit the numpy source tree, and relaunch 151s E your python interpreter from there. 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 151s ____________ test_formatter_output[units4-axis_range4-2662.4-2.6KB] ____________ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s > from . import multiarray 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 151s from . import overrides 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """Implementation of __array_function__ overrides from NEP-18.""" 151s import collections 151s import functools 151s 151s from .._utils import set_module 151s from .._utils._inspect import getargspec 151s > from numpy._core._multiarray_umath import ( 151s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 151s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 151s 151s During handling of the above exception, another exception occurred: 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 151s if __NUMPY_SETUP__: 151s sys.stderr.write('Running from numpy source directory.\n') 151s else: 151s # Allow distributors to run custom init code before importing numpy._core 151s from . import _distributor_init 151s 151s try: 151s > from numpy.__config__ import show_config 151s 151s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 151s from numpy._core._multiarray_umath import ( 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 151s 151s Please note that this module is private. All functions and objects 151s are available in the main ``numpy`` namespace - use that instead. 151s 151s """ 151s 151s import os 151s 151s from numpy.version import version as __version__ 151s 151s 151s # disables OpenBLAS affinity setting of the main thread that limits 151s # python threads or processes to one core 151s env_added = [] 151s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 151s if envkey not in os.environ: 151s os.environ[envkey] = '1' 151s env_added.append(envkey) 151s 151s try: 151s from . import multiarray 151s except ImportError as exc: 151s import sys 151s msg = """ 151s 151s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s 151s Importing the numpy C-extensions failed. This error can happen for 151s many reasons, often due to issues with your setup or how NumPy was 151s installed. 151s 151s We have compiled some common reasons and troubleshooting tips at: 151s 151s https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s 151s Please note and check the following: 151s 151s * The Python version is: Python%d.%d from "%s" 151s * The NumPy version is: "%s" 151s 151s and make sure that they are the versions you expect. 151s Please carefully study the documentation linked above for further help. 151s 151s Original error was: %s 151s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 151s __version__, exc) 151s > raise ImportError(msg) 151s E ImportError: 151s E 151s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 151s E 151s E Importing the numpy C-extensions failed. This error can happen for 151s E many reasons, often due to issues with your setup or how NumPy was 151s E installed. 151s E 151s E We have compiled some common reasons and troubleshooting tips at: 151s E 151s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 151s E 151s E Please note and check the following: 151s E 151s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 151s E * The NumPy version is: "2.2.4" 151s E 151s E and make sure that they are the versions you expect. 151s E Please carefully study the documentation linked above for further help. 151s E 151s E Original error was: No module named 'numpy._core._multiarray_umath' 151s 151s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 151s 151s The above exception was the direct cause of the following exception: 151s 151s units = [('B', 1), ('KB', 1024), ('MB', 1048576), ('GB', 1073741824), ('TB', 1099511627776), ('PB', 1125899906842624)] 151s axis_range = (0, 5120), value = 2662.4, expected = '2.6KB' 151s 151s @pytest.mark.parametrize( 151s "units,axis_range,value,expected", 151s [ 151s # Time formatting tests 151s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 151s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 151s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 151s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 151s # Memory formatting tests 151s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 151s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 151s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 151s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 151s ], 151s ) 151s def test_formatter_output( 151s units: List[Tuple[str, float]], 151s axis_range: Tuple[float, float], 151s value: float, 151s expected: str, 151s ) -> None: 151s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 151s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 151s 151s test/test_plot_humanization.py:66: 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 151s from matplotlib.ticker import Formatter 151s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 151s from . import _api, _version, cbook, _docstring, rcsetup 151s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 151s import numpy as np 151s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 151s 151s """ 151s NumPy 151s ===== 151s 151s Provides 151s 1. An array object of arbitrary homogeneous items 151s 2. Fast mathematical operations over arrays 151s 3. Linear Algebra, Fourier Transforms, Random Number Generation 151s 151s How to use the documentation 151s ---------------------------- 151s Documentation is available in two forms: docstrings provided 151s with the code, and a loose standing reference guide, available from 151s `the NumPy homepage `_. 151s 151s We recommend exploring the docstrings using 151s `IPython `_, an advanced Python shell with 151s TAB-completion and introspection capabilities. See below for further 151s instructions. 151s 151s The docstring examples assume that `numpy` has been imported as ``np``:: 151s 151s >>> import numpy as np 151s 151s Code snippets are indicated by three greater-than signs:: 151s 151s >>> x = 42 151s >>> x = x + 1 151s 151s Use the built-in ``help`` function to view a function's docstring:: 151s 151s >>> help(np.sort) 151s ... # doctest: +SKIP 151s 151s For some objects, ``np.info(obj)`` may provide additional help. This is 151s particularly true if you see the line "Help on ufunc object:" at the top 151s of the help() page. Ufuncs are implemented in C, not Python, for speed. 151s The native Python help() does not know how to view their help, but our 151s np.info() function does. 151s 151s Available subpackages 151s --------------------- 151s lib 151s Basic functions used by several sub-packages. 151s random 151s Core Random Tools 151s linalg 151s Core Linear Algebra Tools 151s fft 151s Core FFT routines 151s polynomial 151s Polynomial tools 151s testing 151s NumPy testing tools 151s distutils 151s Enhancements to distutils with support for 151s Fortran compilers support and more (for Python <= 3.11) 151s 151s Utilities 151s --------- 151s test 151s Run numpy unittests 151s show_config 151s Show numpy build configuration 151s __version__ 151s NumPy version string 151s 151s Viewing documentation using IPython 151s ----------------------------------- 151s 151s Start IPython and import `numpy` usually under the alias ``np``: `import 151s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 151s examples into the shell. To see which functions are available in `numpy`, 151s type ``np.`` (where ```` refers to the TAB key), or use 151s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 151s down the list. To view the docstring for a function, use 151s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 151s the source code). 151s 151s Copies vs. in-place operation 151s ----------------------------- 151s Most of the functions in `numpy` return a copy of the array argument 151s (e.g., `np.sort`). In-place versions of these functions are often 151s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 151s Exceptions to this rule are documented. 151s 151s """ 151s import os 151s import sys 151s import warnings 151s 151s from ._globals import _NoValue, _CopyMode 151s from ._expired_attrs_2_0 import __expired_attributes__ 151s 151s 151s # If a version with git hash was stored, use that instead 151s from . import version 151s from .version import __version__ 151s 151s # We first need to detect if we're being called as part of the numpy setup 151s # procedure itself in a reliable manner. 151s try: 151s __NUMPY_SETUP__ 151s except NameError: 151s __NUMPY_SETUP__ = False 151s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s __________ test_formatter_output[units5-axis_range5-1572864.0-1.5MB] ___________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s 152s units = [('B', 1), ('KB', 1024), ('MB', 1048576), ('GB', 1073741824), ('TB', 1099511627776), ('PB', 1125899906842624)] 152s axis_range = (0, 4194304), value = 1572864.0, expected = '1.5MB' 152s 152s @pytest.mark.parametrize( 152s "units,axis_range,value,expected", 152s [ 152s # Time formatting tests 152s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 152s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 152s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 152s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 152s # Memory formatting tests 152s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 152s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 152s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 152s ], 152s ) 152s def test_formatter_output( 152s units: List[Tuple[str, float]], 152s axis_range: Tuple[float, float], 152s value: float, 152s expected: str, 152s ) -> None: 152s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 152s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 152s 152s test/test_plot_humanization.py:66: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 152s from matplotlib.ticker import Formatter 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _________ test_formatter_output[units6-axis_range6-8912057139.2-8.3GB] _________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s 152s units = [('B', 1), ('KB', 1024), ('MB', 1048576), ('GB', 1073741824), ('TB', 1099511627776), ('PB', 1125899906842624)] 152s axis_range = (0, 3221225472), value = 8912057139.2, expected = '8.3GB' 152s 152s @pytest.mark.parametrize( 152s "units,axis_range,value,expected", 152s [ 152s # Time formatting tests 152s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 152s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 152s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 152s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 152s # Memory formatting tests 152s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 152s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 152s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 152s ], 152s ) 152s def test_formatter_output( 152s units: List[Tuple[str, float]], 152s axis_range: Tuple[float, float], 152s value: float, 152s expected: str, 152s ) -> None: 152s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 152s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 152s 152s test/test_plot_humanization.py:66: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 152s from matplotlib.ticker import Formatter 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _______ test_formatter_output[units7-axis_range7-1429365116108.8-1.3TB] ________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s 152s units = [('B', 1), ('KB', 1024), ('MB', 1048576), ('GB', 1073741824), ('TB', 1099511627776), ('PB', 1125899906842624)] 152s axis_range = (0, 3298534883328), value = 1429365116108.8, expected = '1.3TB' 152s 152s @pytest.mark.parametrize( 152s "units,axis_range,value,expected", 152s [ 152s # Time formatting tests 152s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 152s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 152s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 152s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 152s # Memory formatting tests 152s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 152s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 152s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 152s ], 152s ) 152s def test_formatter_output( 152s units: List[Tuple[str, float]], 152s axis_range: Tuple[float, float], 152s value: float, 152s expected: str, 152s ) -> None: 152s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 152s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 152s 152s test/test_plot_humanization.py:66: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 152s from matplotlib.ticker import Formatter 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s ______ test_formatter_output[units8-axis_range8-7318349394477056.0-6.5PB] ______ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s 152s units = [('B', 1), ('KB', 1024), ('MB', 1048576), ('GB', 1073741824), ('TB', 1099511627776), ('PB', 1125899906842624)] 152s axis_range = (0, 3490289711212134.5), value = 7318349394477056.0 152s expected = '6.5PB' 152s 152s @pytest.mark.parametrize( 152s "units,axis_range,value,expected", 152s [ 152s # Time formatting tests 152s (plot._TIME_UNITS, (0, 30), 15, "15.0s"), 152s (plot._TIME_UNITS, (0, 300), 2.3 * 60, "2.3min"), 152s (plot._TIME_UNITS, (0, 11000), 7.8 * 60 * 60, "7.8h"), 152s (plot._TIME_UNITS, (0, 260000), 3.2 * 60 * 60 * 24, "3.2d"), 152s # Memory formatting tests 152s (plot._MEMORY_UNITS, (0, 5 * 1024), 2.6 * 1024, "2.6KB"), 152s (plot._MEMORY_UNITS, (0, 4 * 1024**2), 1.5 * (1024**2), "1.5MB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**3), 8.3 * 1024**3, "8.3GB"), 152s (plot._MEMORY_UNITS, (0, 3 * 1024**4), 1.3 * 1024**4, "1.3TB"), 152s (plot._MEMORY_UNITS, (0, 3.1 * 1024**5), 6.5 * 1024**5, "6.5PB"), 152s ], 152s ) 152s def test_formatter_output( 152s units: List[Tuple[str, float]], 152s axis_range: Tuple[float, float], 152s value: float, 152s expected: str, 152s ) -> None: 152s """Test HumanizedAxisFormatter formats values correctly for time and memory units.""" 152s > formatter: Any = plot.HumanizedAxisFormatter(min_ratio=3.0, units=units) 152s 152s test/test_plot_humanization.py:66: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/con_duct/suite/plot.py:31: in __new__ 152s from matplotlib.ticker import Formatter 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s ____________ TestPlotMatplotlib.test_matplotlib_plot_file_not_found ____________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s ______________ TestPlotMatplotlib.test_matplotlib_plot_info_json _______________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _ TestPlotMatplotlib.test_matplotlib_plot_interactive_backend_with_get_backend _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _____________ TestPlotMatplotlib.test_matplotlib_plot_invalid_json _____________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _________ TestPlotMatplotlib.test_matplotlib_plot_malformed_usage_file _________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _______ TestPlotMatplotlib.test_matplotlib_plot_non_interactive_backend ________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s _ TestPlotMatplotlib.test_matplotlib_plot_non_interactive_backend_with_get_backend _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s ________________ TestPlotMatplotlib.test_matplotlib_plot_sanity ________________ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s > from . import multiarray 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 152s from . import overrides 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """Implementation of __array_function__ overrides from NEP-18.""" 152s import collections 152s import functools 152s 152s from .._utils import set_module 152s from .._utils._inspect import getargspec 152s > from numpy._core._multiarray_umath import ( 152s add_docstring, _get_implementing_args, _ArrayFunctionDispatcher) 152s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: ModuleNotFoundError 152s 152s During handling of the above exception, another exception occurred: 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s > from numpy.__config__ import show_config 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:114: 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 152s from numpy._core._multiarray_umath import ( 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s Contains the core of NumPy: ndarray, ufuncs, dtypes, etc. 152s 152s Please note that this module is private. All functions and objects 152s are available in the main ``numpy`` namespace - use that instead. 152s 152s """ 152s 152s import os 152s 152s from numpy.version import version as __version__ 152s 152s 152s # disables OpenBLAS affinity setting of the main thread that limits 152s # python threads or processes to one core 152s env_added = [] 152s for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']: 152s if envkey not in os.environ: 152s os.environ[envkey] = '1' 152s env_added.append(envkey) 152s 152s try: 152s from . import multiarray 152s except ImportError as exc: 152s import sys 152s msg = """ 152s 152s IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s 152s Importing the numpy C-extensions failed. This error can happen for 152s many reasons, often due to issues with your setup or how NumPy was 152s installed. 152s 152s We have compiled some common reasons and troubleshooting tips at: 152s 152s https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s 152s Please note and check the following: 152s 152s * The Python version is: Python%d.%d from "%s" 152s * The NumPy version is: "%s" 152s 152s and make sure that they are the versions you expect. 152s Please carefully study the documentation linked above for further help. 152s 152s Original error was: %s 152s """ % (sys.version_info[0], sys.version_info[1], sys.executable, 152s __version__, exc) 152s > raise ImportError(msg) 152s E ImportError: 152s E 152s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 152s E 152s E Importing the numpy C-extensions failed. This error can happen for 152s E many reasons, often due to issues with your setup or how NumPy was 152s E installed. 152s E 152s E We have compiled some common reasons and troubleshooting tips at: 152s E 152s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 152s E 152s E Please note and check the following: 152s E 152s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 152s E * The NumPy version is: "2.2.4" 152s E 152s E and make sure that they are the versions you expect. 152s E Please carefully study the documentation linked above for further help. 152s E 152s E Original error was: No module named 'numpy._core._multiarray_umath' 152s 152s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: ImportError 152s 152s The above exception was the direct cause of the following exception: 152s /usr/lib/python3.14/unittest/mock.py:1429: in patched 152s with self.decoration_helper(patched, 152s /usr/lib/python3.14/contextlib.py:141: in __enter__ 152s return next(self.gen) 152s /usr/lib/python3.14/unittest/mock.py:1411: in decoration_helper 152s arg = exit_stack.enter_context(patching) 152s /usr/lib/python3.14/contextlib.py:530: in enter_context 152s result = _enter(cm) 152s /usr/lib/python3.14/unittest/mock.py:1487: in __enter__ 152s self.target = self.getter() 152s /usr/lib/python3.14/pkgutil.py:458: in resolve_name 152s mod = importlib.import_module(modname) 152s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 152s return _bootstrap._gcd_import(name[level:], package, level) 152s /usr/lib/python3/dist-packages/matplotlib/__init__.py:161: in 152s from . import _api, _version, cbook, _docstring, rcsetup 152s /usr/lib/python3/dist-packages/matplotlib/cbook.py:24: in 152s import numpy as np 152s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 152s 152s """ 152s NumPy 152s ===== 152s 152s Provides 152s 1. An array object of arbitrary homogeneous items 152s 2. Fast mathematical operations over arrays 152s 3. Linear Algebra, Fourier Transforms, Random Number Generation 152s 152s How to use the documentation 152s ---------------------------- 152s Documentation is available in two forms: docstrings provided 152s with the code, and a loose standing reference guide, available from 152s `the NumPy homepage `_. 152s 152s We recommend exploring the docstrings using 152s `IPython `_, an advanced Python shell with 152s TAB-completion and introspection capabilities. See below for further 152s instructions. 152s 152s The docstring examples assume that `numpy` has been imported as ``np``:: 152s 152s >>> import numpy as np 152s 152s Code snippets are indicated by three greater-than signs:: 152s 152s >>> x = 42 152s >>> x = x + 1 152s 152s Use the built-in ``help`` function to view a function's docstring:: 152s 152s >>> help(np.sort) 152s ... # doctest: +SKIP 152s 152s For some objects, ``np.info(obj)`` may provide additional help. This is 152s particularly true if you see the line "Help on ufunc object:" at the top 152s of the help() page. Ufuncs are implemented in C, not Python, for speed. 152s The native Python help() does not know how to view their help, but our 152s np.info() function does. 152s 152s Available subpackages 152s --------------------- 152s lib 152s Basic functions used by several sub-packages. 152s random 152s Core Random Tools 152s linalg 152s Core Linear Algebra Tools 152s fft 152s Core FFT routines 152s polynomial 152s Polynomial tools 152s testing 152s NumPy testing tools 152s distutils 152s Enhancements to distutils with support for 152s Fortran compilers support and more (for Python <= 3.11) 152s 152s Utilities 152s --------- 152s test 152s Run numpy unittests 152s show_config 152s Show numpy build configuration 152s __version__ 152s NumPy version string 152s 152s Viewing documentation using IPython 152s ----------------------------------- 152s 152s Start IPython and import `numpy` usually under the alias ``np``: `import 152s numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste 152s examples into the shell. To see which functions are available in `numpy`, 152s type ``np.`` (where ```` refers to the TAB key), or use 152s ``np.*cos*?`` (where ```` refers to the ENTER key) to narrow 152s down the list. To view the docstring for a function, use 152s ``np.cos?`` (to view the docstring) and ``np.cos??`` (to view 152s the source code). 152s 152s Copies vs. in-place operation 152s ----------------------------- 152s Most of the functions in `numpy` return a copy of the array argument 152s (e.g., `np.sort`). In-place versions of these functions are often 152s available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. 152s Exceptions to this rule are documented. 152s 152s """ 152s import os 152s import sys 152s import warnings 152s 152s from ._globals import _NoValue, _CopyMode 152s from ._expired_attrs_2_0 import __expired_attributes__ 152s 152s 152s # If a version with git hash was stored, use that instead 152s from . import version 152s from .version import __version__ 152s 152s # We first need to detect if we're being called as part of the numpy setup 152s # procedure itself in a reliable manner. 152s try: 152s __NUMPY_SETUP__ 152s except NameError: 152s __NUMPY_SETUP__ = False 152s 152s if __NUMPY_SETUP__: 152s sys.stderr.write('Running from numpy source directory.\n') 152s else: 152s # Allow distributors to run custom init code before importing numpy._core 152s from . import _distributor_init 152s 152s try: 152s from numpy.__config__ import show_config 152s except ImportError as e: 152s msg = """Error importing numpy: you should not try to import numpy from 152s its source directory; please exit the numpy source tree, and relaunch 152s your python interpreter from there.""" 152s > raise ImportError(msg) from e 152s E ImportError: Error importing numpy: you should not try to import numpy from 152s E its source directory; please exit the numpy source tree, and relaunch 152s E your python interpreter from there. 152s 152s /usr/lib/python3/dist-packages/numpy/__init__.py:119: ImportError 152s =========================== short test summary info ============================ 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[-1-2-s] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[-1-3700-s] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[-1-259200-s] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[1.5-90-min] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[1.5-5400-h] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[1.5-129600-d] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[3.0-2-s] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[3.0-180-min] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[3.0-10800-h] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[3.0-259200-d] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[5.0-240-s] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[5.0-300-min] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[5.0-14400-min] 152s FAILED test/test_plot_humanization.py::test_pick_unit_with_varying_ratios[5.0-18000-h] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units0-axis_range0-15-15.0s] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units1-axis_range1-138.0-2.3min] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units2-axis_range2-28080.0-7.8h] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units3-axis_range3-276480.0-3.2d] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units4-axis_range4-2662.4-2.6KB] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units5-axis_range5-1572864.0-1.5MB] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units6-axis_range6-8912057139.2-8.3GB] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units7-axis_range7-1429365116108.8-1.3TB] 152s FAILED test/test_plot_humanization.py::test_formatter_output[units8-axis_range8-7318349394477056.0-6.5PB] 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_file_not_found 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_info_json 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_interactive_backend_with_get_backend 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_invalid_json 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_malformed_usage_file 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_non_interactive_backend 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_non_interactive_backend_with_get_backend 152s FAILED test/test_suite.py::TestPlotMatplotlib::test_matplotlib_plot_sanity - ... 152s ======================= 31 failed, 258 passed in 37.11s ======================== 152s E: pybuild pybuild:389: test: plugin pyproject failed with: exit code=1: cd /tmp/autopkgtest.7d5d64/autopkgtest_tmp/build; python3.14 -m pytest test 152s I: pybuild pybuild:308: chmod +x /tmp/autopkgtest.7d5d64/build.e24/src/test/data/spawn_children.sh 152s I: pybuild base:311: cd /tmp/autopkgtest.7d5d64/autopkgtest_tmp/build; python3.13 -m pytest test 152s ============================= test session starts ============================== 152s platform linux -- Python 3.13.9, pytest-8.3.5, pluggy-1.6.0 152s rootdir: /tmp/autopkgtest.7d5d64/autopkgtest_tmp/build 152s configfile: pyproject.toml 152s plugins: typeguard-4.4.2, rerunfailures-16.1, cov-5.0.0 152s collected 289 items 152s 152s test/test_aggregation.py .............. [ 4%] 153s test/test_arg_parsing.py .............. [ 9%] 164s test/test_e2e.py ................ [ 15%] 183s test/test_execution.py .......................... [ 24%] 183s test/test_formatter.py ................................................. [ 41%] 183s ......... [ 44%] 183s test/test_log_paths.py .............. [ 49%] 183s test/test_ls.py ............ [ 53%] 183s test/test_plot_humanization.py ....................... [ 61%] 183s test/test_prepare_outputs.py ................ [ 66%] 183s test/test_report.py ........................ [ 75%] 183s test/test_schema.py . [ 75%] 184s test/test_suite.py ................................ [ 86%] 186s test/test_tailpipe.py ............... [ 91%] 186s test/test_utils.py ........... [ 95%] 186s test/test_validation.py ............. [100%] 186s 186s ============================= 289 passed in 34.98s ============================= 187s pybuild-autopkgtest: error: pybuild --autopkgtest --test-pytest -i python{version} -p "3.14 3.13" returned exit code 13 187s make: *** [/tmp/VO3WmPMUW8/run:4: pybuild-autopkgtest] Error 25 187s pybuild-autopkgtest: error: /tmp/VO3WmPMUW8/run pybuild-autopkgtest returned exit code 2 187s autopkgtest [11:47:23]: test pybuild-autopkgtest: -----------------------] 188s pybuild-autopkgtest FAIL non-zero exit status 25 188s autopkgtest [11:47:24]: test pybuild-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 188s autopkgtest [11:47:24]: @@@@@@@@@@@@@@@@@@@@ summary 188s pybuild-autopkgtest FAIL non-zero exit status 25