0s autopkgtest [13:06:38]: starting date and time: 2025-11-17 13:06:38+0000 0s autopkgtest [13:06:38]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [13:06:38]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work._rrdg_kt/out --timeout-copy=6000 --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:python3-defaults --apt-upgrade cnvkit --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=python3-defaults/3.13.7-2 -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest-ppc64el --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@bos03-ppc64el-9.secgroup --name adt-resolute-ppc64el-cnvkit-20251117-130637-juju-7f2275-prod-proposed-migration-environment-2-fa732215-0de0-4013-80e1-79492d6d8cdc --image adt/ubuntu-resolute-ppc64el-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-proposed-migration-ppc64el -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 3s Creating nova instance adt-resolute-ppc64el-cnvkit-20251117-130637-juju-7f2275-prod-proposed-migration-environment-2-fa732215-0de0-4013-80e1-79492d6d8cdc from image adt/ubuntu-resolute-ppc64el-server-20251117.img (UUID c6f5b741-c77a-45db-84cb-f00b40e77676)... 68s autopkgtest [13:07:46]: testbed dpkg architecture: ppc64el 68s autopkgtest [13:07:46]: testbed apt version: 3.1.11 68s autopkgtest [13:07:46]: @@@@@@@@@@@@@@@@@@@@ test bed setup 69s autopkgtest [13:07:47]: testbed release detected to be: None 69s autopkgtest [13:07:47]: updating testbed package index (apt update) 70s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [87.8 kB] 70s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 70s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 70s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 70s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [81.1 kB] 70s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [22.9 kB] 70s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/restricted Sources [9848 B] 70s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [868 kB] 70s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el Packages [140 kB] 70s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted ppc64el Packages [940 B] 70s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el Packages [562 kB] 71s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse ppc64el Packages [11.0 kB] 71s Fetched 1784 kB in 1s (1635 kB/s) 71s Reading package lists... 72s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 72s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 72s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 73s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 73s Reading package lists... 73s Reading package lists... 74s Building dependency tree... 74s Reading state information... 74s Calculating upgrade... 74s The following packages will be upgraded: 74s libpython3-stdlib python3 python3-minimal usbutils 74s 4 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 74s Need to get 154 kB of archives. 74s After this operation, 0 B of additional disk space will be used. 74s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el python3-minimal ppc64el 3.13.7-2 [27.8 kB] 74s Get:2 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el python3 ppc64el 3.13.7-2 [23.9 kB] 74s Get:3 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el libpython3-stdlib ppc64el 3.13.7-2 [10.6 kB] 74s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el usbutils ppc64el 1:019-1 [91.5 kB] 74s dpkg-preconfigure: unable to re-open stdin: No such file or directory 74s Fetched 154 kB in 0s (339 kB/s) 75s (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 ... 81022 files and directories currently installed.) 75s Preparing to unpack .../python3-minimal_3.13.7-2_ppc64el.deb ... 75s Unpacking python3-minimal (3.13.7-2) over (3.13.7-1) ... 75s Setting up python3-minimal (3.13.7-2) ... 75s (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 ... 81022 files and directories currently installed.) 75s Preparing to unpack .../python3_3.13.7-2_ppc64el.deb ... 75s running python pre-rtupdate hooks for python3.13... 75s Unpacking python3 (3.13.7-2) over (3.13.7-1) ... 75s Preparing to unpack .../libpython3-stdlib_3.13.7-2_ppc64el.deb ... 75s Unpacking libpython3-stdlib:ppc64el (3.13.7-2) over (3.13.7-1) ... 75s Preparing to unpack .../usbutils_1%3a019-1_ppc64el.deb ... 75s Unpacking usbutils (1:019-1) over (1:018-2) ... 75s Setting up usbutils (1:019-1) ... 75s Setting up libpython3-stdlib:ppc64el (3.13.7-2) ... 75s Setting up python3 (3.13.7-2) ... 75s running python rtupdate hooks for python3.13... 75s running python post-rtupdate hooks for python3.13... 75s Processing triggers for man-db (2.13.1-1) ... 77s autopkgtest [13:07:55]: upgrading testbed (apt dist-upgrade and autopurge) 77s Reading package lists... 77s Building dependency tree... 77s Reading state information... 77s Calculating upgrade... 77s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 77s Reading package lists... 77s Building dependency tree... 77s Reading state information... 78s Solving dependencies... 78s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 80s autopkgtest [13:07:58]: testbed running kernel: Linux 6.17.0-5-generic #5-Ubuntu SMP PREEMPT_DYNAMIC Mon Sep 22 10:02:41 UTC 2025 80s autopkgtest [13:07:58]: @@@@@@@@@@@@@@@@@@@@ apt-source cnvkit 89s Get:1 http://ftpmaster.internal/ubuntu resolute/universe cnvkit 0.9.12-1 (dsc) [2483 B] 89s Get:2 http://ftpmaster.internal/ubuntu resolute/universe cnvkit 0.9.12-1 (tar) [32.1 MB] 89s Get:3 http://ftpmaster.internal/ubuntu resolute/universe cnvkit 0.9.12-1 (diff) [20.8 kB] 89s gpgv: Signature made Thu Feb 6 14:25:04 2025 UTC 89s gpgv: using RSA key 724D609337113C710550D7473C26763F6C67E6E2 89s gpgv: issuer "crusoe@debian.org" 89s gpgv: Can't check signature: No public key 89s dpkg-source: warning: cannot verify inline signature for ./cnvkit_0.9.12-1.dsc: no acceptable signature found 91s autopkgtest [13:08:09]: testing package cnvkit version 0.9.12-1 91s autopkgtest [13:08:09]: build not needed 96s autopkgtest [13:08:14]: test run-unit-test: preparing testbed 96s Reading package lists... 96s Building dependency tree... 96s Reading state information... 96s Solving dependencies... 96s The following NEW packages will be installed: 96s blt cnvkit cython3 fontconfig fontconfig-config fonts-dejavu-core 96s fonts-dejavu-mono fonts-lyx fonts-urw-base35 libblas3 libcairo2 libdatrie1 96s libdeflate0 libfontconfig1 libfontenc1 libgfortran5 libgomp1 libgpgmepp6t64 96s libgraphite2-3 libharfbuzz0b libhts3t64 libhtscodecs2 libice6 libimagequant0 96s libjbig0 libjpeg-turbo8 libjpeg8 liblapack3 liblcms2-2 liblerc4 libopenjp2-7 96s libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils 96s libpaper2 libpixman-1-0 libpoppler147 libqhull-r8.0 libraqm0 libsharpyuv0 96s libsm6 libtcl8.6 libthai-data libthai0 libtiff6 libtk8.6 libwebp7 96s libwebpdemux2 libwebpmux3 libxcb-render0 libxcb-shm0 libxft2 libxrender1 96s libxslt1.1 libxss1 libxt6t64 libzopfli1 poppler-utils python-matplotlib-data 96s python3-biopython python3-brotli python3-cairo python3-charset-normalizer 96s python3-contourpy python3-cycler python3-decorator python3-fonttools 96s python3-freetype python3-fs python3-joblib python3-kiwisolver python3-lxml 96s python3-lz4 python3-matplotlib python3-mpmath python3-networkx python3-numpy 96s python3-numpy-dev python3-pandas python3-pandas-lib python3-pil 96s python3-pil.imagetk python3-platformdirs python3-pomegranate python3-pyfaidx 96s python3-pysam python3-pytz python3-reportlab python3-rlpycairo python3-scipy 96s python3-sklearn python3-sklearn-lib python3-sympy python3-threadpoolctl 96s python3-tk python3-ufolib2 python3-unicodedata2 python3-zopfli python3.13-tk 96s python3.14-tk r-base-core r-bioc-biocgenerics r-bioc-dnacopy sgml-base 96s tk8.6-blt2.5 unicode-data unzip w3c-sgml-lib x11-common xdg-utils 96s xfonts-encodings xfonts-utils xml-core zip 96s 0 upgraded, 115 newly installed, 0 to remove and 0 not upgraded. 96s Need to get 196 MB of archives. 96s After this operation, 946 MB of additional disk space will be used. 96s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-numpy-dev ppc64el 1:2.2.4+ds-1ubuntu1 [153 kB] 97s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el libblas3 ppc64el 3.12.1-7 [291 kB] 97s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgfortran5 ppc64el 15.2.0-7ubuntu1 [620 kB] 97s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblapack3 ppc64el 3.12.1-7 [2960 kB] 98s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-numpy ppc64el 1:2.2.4+ds-1ubuntu1 [4887 kB] 98s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtcl8.6 ppc64el 8.6.17+dfsg-1 [1239 kB] 99s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-mono all 2.37-8 [502 kB] 99s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-core all 2.37-8 [835 kB] 99s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontenc1 ppc64el 1:1.1.8-1build1 [15.8 kB] 99s Get:10 http://ftpmaster.internal/ubuntu resolute/main ppc64el x11-common all 1:7.7+24ubuntu1 [22.4 kB] 99s Get:11 http://ftpmaster.internal/ubuntu resolute/main ppc64el xfonts-encodings all 1:1.0.5-0ubuntu2 [578 kB] 99s Get:12 http://ftpmaster.internal/ubuntu resolute/main ppc64el xfonts-utils ppc64el 1:7.7+7 [114 kB] 99s Get:13 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-urw-base35 all 20200910-8 [11.0 MB] 102s Get:14 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig-config ppc64el 2.15.0-2.3ubuntu1 [38.1 kB] 102s Get:15 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontconfig1 ppc64el 2.15.0-2.3ubuntu1 [188 kB] 102s Get:16 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxrender1 ppc64el 1:0.9.12-1 [23.0 kB] 102s Get:17 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxft2 ppc64el 2.3.6-1build1 [61.5 kB] 102s Get:18 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxss1 ppc64el 1:1.2.3-1build3 [7980 B] 102s Get:19 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtk8.6 ppc64el 8.6.17-1 [968 kB] 103s Get:20 http://ftpmaster.internal/ubuntu resolute/main ppc64el tk8.6-blt2.5 ppc64el 2.5.3+dfsg-8 [778 kB] 103s Get:21 http://ftpmaster.internal/ubuntu resolute/main ppc64el blt ppc64el 2.5.3+dfsg-8 [4830 B] 103s Get:22 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-charset-normalizer ppc64el 3.4.3-1 [174 kB] 103s Get:23 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.14-tk ppc64el 3.14.0-4 [109 kB] 103s Get:24 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.13-tk ppc64el 3.13.9-1 [108 kB] 103s Get:25 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-tk ppc64el 3.13.9-1 [8948 B] 103s Get:26 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pil.imagetk ppc64el 11.3.0-1ubuntu2 [10.3 kB] 103s Get:27 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgomp1 ppc64el 15.2.0-7ubuntu1 [169 kB] 103s Get:28 http://ftpmaster.internal/ubuntu resolute/main ppc64el libimagequant0 ppc64el 2.18.0-1build1 [43.2 kB] 103s Get:29 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-turbo8 ppc64el 2.1.5-4ubuntu2 [215 kB] 103s Get:30 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg8 ppc64el 8c-2ubuntu11 [2148 B] 103s Get:31 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblcms2-2 ppc64el 2.17-1 [246 kB] 103s Get:32 http://ftpmaster.internal/ubuntu resolute/main ppc64el libopenjp2-7 ppc64el 2.5.3-2.1 [251 kB] 103s Get:33 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgraphite2-3 ppc64el 1.3.14-2ubuntu1 [84.6 kB] 103s Get:34 http://ftpmaster.internal/ubuntu resolute/main ppc64el libharfbuzz0b ppc64el 12.1.0-1 [679 kB] 104s Get:35 http://ftpmaster.internal/ubuntu resolute/main ppc64el libraqm0 ppc64el 0.10.3-1 [19.6 kB] 104s Get:36 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdeflate0 ppc64el 1.23-2 [63.3 kB] 104s Get:37 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjbig0 ppc64el 2.1-6.1ubuntu2 [35.9 kB] 104s Get:38 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblerc4 ppc64el 4.0.0+ds-5ubuntu1 [298 kB] 104s Get:39 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsharpyuv0 ppc64el 1.5.0-0.1 [22.3 kB] 104s Get:40 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebp7 ppc64el 1.5.0-0.1 [315 kB] 104s Get:41 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtiff6 ppc64el 4.7.0-3ubuntu3 [307 kB] 104s Get:42 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebpdemux2 ppc64el 1.5.0-0.1 [14.6 kB] 104s Get:43 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebpmux3 ppc64el 1.5.0-0.1 [31.1 kB] 104s Get:44 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-pil ppc64el 11.3.0-1ubuntu2 [654 kB] 104s Get:45 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpixman-1-0 ppc64el 0.46.4-1 [347 kB] 104s Get:46 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-render0 ppc64el 1.17.0-2build1 [17.2 kB] 104s Get:47 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-shm0 ppc64el 1.17.0-2build1 [6078 B] 104s Get:48 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcairo2 ppc64el 1.18.4-1build1 [759 kB] 105s Get:49 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-cairo ppc64el 1.27.0-2build1 [150 kB] 105s Get:50 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-freetype all 2.5.1-2 [92.2 kB] 105s Get:51 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-rlpycairo all 0.3.0-4 [9332 B] 105s Get:52 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-reportlab all 4.4.4-2 [1147 kB] 105s Get:53 http://ftpmaster.internal/ubuntu resolute/main ppc64el sgml-base all 1.31+nmu1 [11.0 kB] 105s Get:54 http://ftpmaster.internal/ubuntu resolute/main ppc64el xml-core all 0.19 [20.3 kB] 105s Get:55 http://ftpmaster.internal/ubuntu resolute/universe ppc64el w3c-sgml-lib all 1.3-3 [280 kB] 105s Get:56 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-biopython ppc64el 1.85+dfsg-4 [1764 kB] 106s Get:57 http://ftpmaster.internal/ubuntu resolute/universe ppc64el fonts-lyx all 2.4.4-2 [171 kB] 106s Get:58 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python-matplotlib-data all 3.10.7+dfsg1-1 [2930 kB] 107s Get:59 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-contourpy ppc64el 1.3.1-2 [274 kB] 107s Get:60 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-cycler all 0.12.1-2 [9850 B] 107s Get:61 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-brotli ppc64el 1.1.0-2build6 [430 kB] 107s Get:62 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-platformdirs all 4.3.7-1 [16.9 kB] 107s Get:63 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-fs all 2.4.16-9ubuntu1 [91.5 kB] 107s Get:64 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxslt1.1 ppc64el 1.1.43-0.3 [190 kB] 107s Get:65 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-lxml ppc64el 6.0.2-1 [2452 kB] 108s Get:66 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-lz4 ppc64el 4.4.4+dfsg-3 [28.9 kB] 108s Get:67 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-decorator all 5.2.1-2 [28.1 kB] 108s Get:68 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-scipy ppc64el 1.15.3-1ubuntu1 [22.0 MB] 114s Get:69 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-mpmath all 1.3.0-2 [423 kB] 115s Get:70 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sympy all 1.14.0-2 [4306 kB] 116s Get:71 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-ufolib2 all 0.17.1+dfsg1-1 [33.5 kB] 116s Get:72 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-unicodedata2 ppc64el 16.0.0+ds-1build1 [400 kB] 116s Get:73 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libzopfli1 ppc64el 1.0.3-3 [160 kB] 116s Get:74 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-zopfli ppc64el 0.4.0-1 [11.3 kB] 116s Get:75 http://ftpmaster.internal/ubuntu resolute/universe ppc64el unicode-data all 16.0.0-1 [9513 kB] 119s Get:76 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-fonttools ppc64el 4.57.0-2build1 [1745 kB] 119s Get:77 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-kiwisolver ppc64el 1.4.10~rc0-1 [72.4 kB] 119s Get:78 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libqhull-r8.0 ppc64el 2020.2-7 [227 kB] 119s Get:79 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-matplotlib ppc64el 3.10.7+dfsg1-1 [17.2 MB] 123s Get:80 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-pytz all 2025.2-4 [32.3 kB] 123s Get:81 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pandas-lib ppc64el 2.3.3+dfsg-1ubuntu1 [7666 kB] 124s Get:82 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pandas all 2.3.3+dfsg-1ubuntu1 [2948 kB] 124s Get:83 http://ftpmaster.internal/ubuntu resolute/universe ppc64el cython3 ppc64el 3.1.6+dfsg-1ubuntu1 [3539 kB] 124s Get:84 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-joblib all 1.4.2-4 [205 kB] 124s Get:85 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-networkx all 3.2.1-4ubuntu1 [11.5 MB] 125s Get:86 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pomegranate ppc64el 0.15.0-2 [4794 kB] 126s Get:87 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pyfaidx all 0.8.1.3-2 [29.7 kB] 126s Get:88 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libhtscodecs2 ppc64el 1.6.1-2 [113 kB] 126s Get:89 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libhts3t64 ppc64el 1.22.1+ds2-1 [617 kB] 127s Get:90 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pysam ppc64el 0.23.3+ds-2 [5011 kB] 128s Get:91 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sklearn-lib ppc64el 1.7.2+dfsg-3ubuntu1 [6203 kB] 130s Get:92 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-threadpoolctl all 3.1.0-1 [21.3 kB] 130s Get:93 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sklearn all 1.7.2+dfsg-3ubuntu1 [2616 kB] 131s Get:94 http://ftpmaster.internal/ubuntu resolute/main ppc64el zip ppc64el 3.0-15ubuntu2 [198 kB] 131s Get:95 http://ftpmaster.internal/ubuntu resolute/main ppc64el unzip ppc64el 6.0-28ubuntu7 [201 kB] 131s Get:96 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper2 ppc64el 2.2.5-0.3 [18.0 kB] 131s Get:97 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper-utils ppc64el 2.2.5-0.3 [15.6 kB] 131s Get:98 http://ftpmaster.internal/ubuntu resolute/main ppc64el xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 131s Get:99 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig ppc64el 2.15.0-2.3ubuntu1 [192 kB] 131s Get:100 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai-data all 0.1.29-2build1 [158 kB] 131s Get:101 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdatrie1 ppc64el 0.2.13-4 [22.2 kB] 131s Get:102 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai0 ppc64el 0.1.29-2build1 [21.8 kB] 132s Get:103 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpango-1.0-0 ppc64el 1.56.3-2 [281 kB] 132s Get:104 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangoft2-1.0-0 ppc64el 1.56.3-2 [59.1 kB] 132s Get:105 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangocairo-1.0-0 ppc64el 1.56.3-2 [31.0 kB] 132s Get:106 http://ftpmaster.internal/ubuntu resolute/main ppc64el libice6 ppc64el 2:1.1.1-1 [49.9 kB] 132s Get:107 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsm6 ppc64el 2:1.2.6-1 [18.6 kB] 132s Get:108 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxt6t64 ppc64el 1:1.2.1-1.3 [203 kB] 132s Get:109 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-base-core ppc64el 4.5.2-1 [29.3 MB] 136s Get:110 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-biocgenerics all 0.52.0-2 [624 kB] 136s Get:111 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-dnacopy ppc64el 1.80.0-2 [504 kB] 136s Get:112 http://ftpmaster.internal/ubuntu resolute/universe ppc64el cnvkit all 0.9.12-1 [20.6 MB] 136s Get:113 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgpgmepp6t64 ppc64el 1.24.2-3ubuntu2 [135 kB] 136s Get:114 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpoppler147 ppc64el 25.03.0-11.1 [1442 kB] 136s Get:115 http://ftpmaster.internal/ubuntu resolute/main ppc64el poppler-utils ppc64el 25.03.0-11.1 [250 kB] 137s Preconfiguring packages ... 137s Fetched 196 MB in 40s (4875 kB/s) 137s Selecting previously unselected package python3-numpy-dev:ppc64el. 137s (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 ... 81022 files and directories currently installed.) 137s Preparing to unpack .../000-python3-numpy-dev_1%3a2.2.4+ds-1ubuntu1_ppc64el.deb ... 137s Unpacking python3-numpy-dev:ppc64el (1:2.2.4+ds-1ubuntu1) ... 137s Selecting previously unselected package libblas3:ppc64el. 137s Preparing to unpack .../001-libblas3_3.12.1-7_ppc64el.deb ... 137s Unpacking libblas3:ppc64el (3.12.1-7) ... 137s Selecting previously unselected package libgfortran5:ppc64el. 137s Preparing to unpack .../002-libgfortran5_15.2.0-7ubuntu1_ppc64el.deb ... 137s Unpacking libgfortran5:ppc64el (15.2.0-7ubuntu1) ... 137s Selecting previously unselected package liblapack3:ppc64el. 137s Preparing to unpack .../003-liblapack3_3.12.1-7_ppc64el.deb ... 137s Unpacking liblapack3:ppc64el (3.12.1-7) ... 137s Selecting previously unselected package python3-numpy. 137s Preparing to unpack .../004-python3-numpy_1%3a2.2.4+ds-1ubuntu1_ppc64el.deb ... 137s Unpacking python3-numpy (1:2.2.4+ds-1ubuntu1) ... 137s Selecting previously unselected package libtcl8.6:ppc64el. 137s Preparing to unpack .../005-libtcl8.6_8.6.17+dfsg-1_ppc64el.deb ... 137s Unpacking libtcl8.6:ppc64el (8.6.17+dfsg-1) ... 137s Selecting previously unselected package fonts-dejavu-mono. 137s Preparing to unpack .../006-fonts-dejavu-mono_2.37-8_all.deb ... 137s Unpacking fonts-dejavu-mono (2.37-8) ... 137s Selecting previously unselected package fonts-dejavu-core. 137s Preparing to unpack .../007-fonts-dejavu-core_2.37-8_all.deb ... 137s Unpacking fonts-dejavu-core (2.37-8) ... 137s Selecting previously unselected package libfontenc1:ppc64el. 137s Preparing to unpack .../008-libfontenc1_1%3a1.1.8-1build1_ppc64el.deb ... 137s Unpacking libfontenc1:ppc64el (1:1.1.8-1build1) ... 137s Selecting previously unselected package x11-common. 137s Preparing to unpack .../009-x11-common_1%3a7.7+24ubuntu1_all.deb ... 137s Unpacking x11-common (1:7.7+24ubuntu1) ... 137s Selecting previously unselected package xfonts-encodings. 137s Preparing to unpack .../010-xfonts-encodings_1%3a1.0.5-0ubuntu2_all.deb ... 137s Unpacking xfonts-encodings (1:1.0.5-0ubuntu2) ... 137s Selecting previously unselected package xfonts-utils. 137s Preparing to unpack .../011-xfonts-utils_1%3a7.7+7_ppc64el.deb ... 137s Unpacking xfonts-utils (1:7.7+7) ... 137s Selecting previously unselected package fonts-urw-base35. 137s Preparing to unpack .../012-fonts-urw-base35_20200910-8_all.deb ... 137s Unpacking fonts-urw-base35 (20200910-8) ... 137s Selecting previously unselected package fontconfig-config. 137s Preparing to unpack .../013-fontconfig-config_2.15.0-2.3ubuntu1_ppc64el.deb ... 138s Unpacking fontconfig-config (2.15.0-2.3ubuntu1) ... 138s Selecting previously unselected package libfontconfig1:ppc64el. 138s Preparing to unpack .../014-libfontconfig1_2.15.0-2.3ubuntu1_ppc64el.deb ... 138s Unpacking libfontconfig1:ppc64el (2.15.0-2.3ubuntu1) ... 138s Selecting previously unselected package libxrender1:ppc64el. 138s Preparing to unpack .../015-libxrender1_1%3a0.9.12-1_ppc64el.deb ... 138s Unpacking libxrender1:ppc64el (1:0.9.12-1) ... 138s Selecting previously unselected package libxft2:ppc64el. 138s Preparing to unpack .../016-libxft2_2.3.6-1build1_ppc64el.deb ... 138s Unpacking libxft2:ppc64el (2.3.6-1build1) ... 138s Selecting previously unselected package libxss1:ppc64el. 138s Preparing to unpack .../017-libxss1_1%3a1.2.3-1build3_ppc64el.deb ... 138s Unpacking libxss1:ppc64el (1:1.2.3-1build3) ... 138s Selecting previously unselected package libtk8.6:ppc64el. 138s Preparing to unpack .../018-libtk8.6_8.6.17-1_ppc64el.deb ... 138s Unpacking libtk8.6:ppc64el (8.6.17-1) ... 138s Selecting previously unselected package tk8.6-blt2.5. 138s Preparing to unpack .../019-tk8.6-blt2.5_2.5.3+dfsg-8_ppc64el.deb ... 138s Unpacking tk8.6-blt2.5 (2.5.3+dfsg-8) ... 138s Selecting previously unselected package blt. 138s Preparing to unpack .../020-blt_2.5.3+dfsg-8_ppc64el.deb ... 138s Unpacking blt (2.5.3+dfsg-8) ... 138s Selecting previously unselected package python3-charset-normalizer. 138s Preparing to unpack .../021-python3-charset-normalizer_3.4.3-1_ppc64el.deb ... 138s Unpacking python3-charset-normalizer (3.4.3-1) ... 138s Selecting previously unselected package python3.14-tk. 138s Preparing to unpack .../022-python3.14-tk_3.14.0-4_ppc64el.deb ... 138s Unpacking python3.14-tk (3.14.0-4) ... 138s Selecting previously unselected package python3.13-tk. 138s Preparing to unpack .../023-python3.13-tk_3.13.9-1_ppc64el.deb ... 138s Unpacking python3.13-tk (3.13.9-1) ... 138s Selecting previously unselected package python3-tk:ppc64el. 138s Preparing to unpack .../024-python3-tk_3.13.9-1_ppc64el.deb ... 138s Unpacking python3-tk:ppc64el (3.13.9-1) ... 138s Selecting previously unselected package python3-pil.imagetk:ppc64el. 138s Preparing to unpack .../025-python3-pil.imagetk_11.3.0-1ubuntu2_ppc64el.deb ... 138s Unpacking python3-pil.imagetk:ppc64el (11.3.0-1ubuntu2) ... 138s Selecting previously unselected package libgomp1:ppc64el. 138s Preparing to unpack .../026-libgomp1_15.2.0-7ubuntu1_ppc64el.deb ... 138s Unpacking libgomp1:ppc64el (15.2.0-7ubuntu1) ... 138s Selecting previously unselected package libimagequant0:ppc64el. 138s Preparing to unpack .../027-libimagequant0_2.18.0-1build1_ppc64el.deb ... 138s Unpacking libimagequant0:ppc64el (2.18.0-1build1) ... 138s Selecting previously unselected package libjpeg-turbo8:ppc64el. 138s Preparing to unpack .../028-libjpeg-turbo8_2.1.5-4ubuntu2_ppc64el.deb ... 138s Unpacking libjpeg-turbo8:ppc64el (2.1.5-4ubuntu2) ... 138s Selecting previously unselected package libjpeg8:ppc64el. 138s Preparing to unpack .../029-libjpeg8_8c-2ubuntu11_ppc64el.deb ... 138s Unpacking libjpeg8:ppc64el (8c-2ubuntu11) ... 138s Selecting previously unselected package liblcms2-2:ppc64el. 138s Preparing to unpack .../030-liblcms2-2_2.17-1_ppc64el.deb ... 138s Unpacking liblcms2-2:ppc64el (2.17-1) ... 138s Selecting previously unselected package libopenjp2-7:ppc64el. 138s Preparing to unpack .../031-libopenjp2-7_2.5.3-2.1_ppc64el.deb ... 138s Unpacking libopenjp2-7:ppc64el (2.5.3-2.1) ... 138s Selecting previously unselected package libgraphite2-3:ppc64el. 138s Preparing to unpack .../032-libgraphite2-3_1.3.14-2ubuntu1_ppc64el.deb ... 138s Unpacking libgraphite2-3:ppc64el (1.3.14-2ubuntu1) ... 138s Selecting previously unselected package libharfbuzz0b:ppc64el. 138s Preparing to unpack .../033-libharfbuzz0b_12.1.0-1_ppc64el.deb ... 138s Unpacking libharfbuzz0b:ppc64el (12.1.0-1) ... 138s Selecting previously unselected package libraqm0:ppc64el. 138s Preparing to unpack .../034-libraqm0_0.10.3-1_ppc64el.deb ... 138s Unpacking libraqm0:ppc64el (0.10.3-1) ... 138s Selecting previously unselected package libdeflate0:ppc64el. 138s Preparing to unpack .../035-libdeflate0_1.23-2_ppc64el.deb ... 138s Unpacking libdeflate0:ppc64el (1.23-2) ... 138s Selecting previously unselected package libjbig0:ppc64el. 138s Preparing to unpack .../036-libjbig0_2.1-6.1ubuntu2_ppc64el.deb ... 138s Unpacking libjbig0:ppc64el (2.1-6.1ubuntu2) ... 138s Selecting previously unselected package liblerc4:ppc64el. 138s Preparing to unpack .../037-liblerc4_4.0.0+ds-5ubuntu1_ppc64el.deb ... 138s Unpacking liblerc4:ppc64el (4.0.0+ds-5ubuntu1) ... 138s Selecting previously unselected package libsharpyuv0:ppc64el. 138s Preparing to unpack .../038-libsharpyuv0_1.5.0-0.1_ppc64el.deb ... 138s Unpacking libsharpyuv0:ppc64el (1.5.0-0.1) ... 138s Selecting previously unselected package libwebp7:ppc64el. 138s Preparing to unpack .../039-libwebp7_1.5.0-0.1_ppc64el.deb ... 138s Unpacking libwebp7:ppc64el (1.5.0-0.1) ... 138s Selecting previously unselected package libtiff6:ppc64el. 138s Preparing to unpack .../040-libtiff6_4.7.0-3ubuntu3_ppc64el.deb ... 138s Unpacking libtiff6:ppc64el (4.7.0-3ubuntu3) ... 138s Selecting previously unselected package libwebpdemux2:ppc64el. 138s Preparing to unpack .../041-libwebpdemux2_1.5.0-0.1_ppc64el.deb ... 138s Unpacking libwebpdemux2:ppc64el (1.5.0-0.1) ... 138s Selecting previously unselected package libwebpmux3:ppc64el. 138s Preparing to unpack .../042-libwebpmux3_1.5.0-0.1_ppc64el.deb ... 138s Unpacking libwebpmux3:ppc64el (1.5.0-0.1) ... 138s Selecting previously unselected package python3-pil:ppc64el. 138s Preparing to unpack .../043-python3-pil_11.3.0-1ubuntu2_ppc64el.deb ... 138s Unpacking python3-pil:ppc64el (11.3.0-1ubuntu2) ... 138s Selecting previously unselected package libpixman-1-0:ppc64el. 138s Preparing to unpack .../044-libpixman-1-0_0.46.4-1_ppc64el.deb ... 138s Unpacking libpixman-1-0:ppc64el (0.46.4-1) ... 138s Selecting previously unselected package libxcb-render0:ppc64el. 138s Preparing to unpack .../045-libxcb-render0_1.17.0-2build1_ppc64el.deb ... 138s Unpacking libxcb-render0:ppc64el (1.17.0-2build1) ... 138s Selecting previously unselected package libxcb-shm0:ppc64el. 138s Preparing to unpack .../046-libxcb-shm0_1.17.0-2build1_ppc64el.deb ... 138s Unpacking libxcb-shm0:ppc64el (1.17.0-2build1) ... 138s Selecting previously unselected package libcairo2:ppc64el. 138s Preparing to unpack .../047-libcairo2_1.18.4-1build1_ppc64el.deb ... 138s Unpacking libcairo2:ppc64el (1.18.4-1build1) ... 138s Selecting previously unselected package python3-cairo. 138s Preparing to unpack .../048-python3-cairo_1.27.0-2build1_ppc64el.deb ... 138s Unpacking python3-cairo (1.27.0-2build1) ... 138s Selecting previously unselected package python3-freetype. 138s Preparing to unpack .../049-python3-freetype_2.5.1-2_all.deb ... 138s Unpacking python3-freetype (2.5.1-2) ... 138s Selecting previously unselected package python3-rlpycairo. 138s Preparing to unpack .../050-python3-rlpycairo_0.3.0-4_all.deb ... 138s Unpacking python3-rlpycairo (0.3.0-4) ... 138s Selecting previously unselected package python3-reportlab. 138s Preparing to unpack .../051-python3-reportlab_4.4.4-2_all.deb ... 138s Unpacking python3-reportlab (4.4.4-2) ... 138s Selecting previously unselected package sgml-base. 138s Preparing to unpack .../052-sgml-base_1.31+nmu1_all.deb ... 138s Unpacking sgml-base (1.31+nmu1) ... 138s Selecting previously unselected package xml-core. 138s Preparing to unpack .../053-xml-core_0.19_all.deb ... 138s Unpacking xml-core (0.19) ... 138s Selecting previously unselected package w3c-sgml-lib. 138s Preparing to unpack .../054-w3c-sgml-lib_1.3-3_all.deb ... 138s Unpacking w3c-sgml-lib (1.3-3) ... 138s Selecting previously unselected package python3-biopython. 138s Preparing to unpack .../055-python3-biopython_1.85+dfsg-4_ppc64el.deb ... 138s Unpacking python3-biopython (1.85+dfsg-4) ... 139s Selecting previously unselected package fonts-lyx. 139s Preparing to unpack .../056-fonts-lyx_2.4.4-2_all.deb ... 139s Unpacking fonts-lyx (2.4.4-2) ... 139s Selecting previously unselected package python-matplotlib-data. 139s Preparing to unpack .../057-python-matplotlib-data_3.10.7+dfsg1-1_all.deb ... 139s Unpacking python-matplotlib-data (3.10.7+dfsg1-1) ... 139s Selecting previously unselected package python3-contourpy. 139s Preparing to unpack .../058-python3-contourpy_1.3.1-2_ppc64el.deb ... 139s Unpacking python3-contourpy (1.3.1-2) ... 139s Selecting previously unselected package python3-cycler. 139s Preparing to unpack .../059-python3-cycler_0.12.1-2_all.deb ... 139s Unpacking python3-cycler (0.12.1-2) ... 139s Selecting previously unselected package python3-brotli. 139s Preparing to unpack .../060-python3-brotli_1.1.0-2build6_ppc64el.deb ... 139s Unpacking python3-brotli (1.1.0-2build6) ... 139s Selecting previously unselected package python3-platformdirs. 139s Preparing to unpack .../061-python3-platformdirs_4.3.7-1_all.deb ... 139s Unpacking python3-platformdirs (4.3.7-1) ... 139s Selecting previously unselected package python3-fs. 139s Preparing to unpack .../062-python3-fs_2.4.16-9ubuntu1_all.deb ... 139s Unpacking python3-fs (2.4.16-9ubuntu1) ... 139s Selecting previously unselected package libxslt1.1:ppc64el. 139s Preparing to unpack .../063-libxslt1.1_1.1.43-0.3_ppc64el.deb ... 139s Unpacking libxslt1.1:ppc64el (1.1.43-0.3) ... 139s Selecting previously unselected package python3-lxml:ppc64el. 139s Preparing to unpack .../064-python3-lxml_6.0.2-1_ppc64el.deb ... 139s Unpacking python3-lxml:ppc64el (6.0.2-1) ... 139s Selecting previously unselected package python3-lz4. 139s Preparing to unpack .../065-python3-lz4_4.4.4+dfsg-3_ppc64el.deb ... 139s Unpacking python3-lz4 (4.4.4+dfsg-3) ... 139s Selecting previously unselected package python3-decorator. 139s Preparing to unpack .../066-python3-decorator_5.2.1-2_all.deb ... 139s Unpacking python3-decorator (5.2.1-2) ... 139s Selecting previously unselected package python3-scipy. 139s Preparing to unpack .../067-python3-scipy_1.15.3-1ubuntu1_ppc64el.deb ... 139s Unpacking python3-scipy (1.15.3-1ubuntu1) ... 140s Selecting previously unselected package python3-mpmath. 140s Preparing to unpack .../068-python3-mpmath_1.3.0-2_all.deb ... 140s Unpacking python3-mpmath (1.3.0-2) ... 140s Selecting previously unselected package python3-sympy. 140s Preparing to unpack .../069-python3-sympy_1.14.0-2_all.deb ... 140s Unpacking python3-sympy (1.14.0-2) ... 140s Selecting previously unselected package python3-ufolib2. 140s Preparing to unpack .../070-python3-ufolib2_0.17.1+dfsg1-1_all.deb ... 140s Unpacking python3-ufolib2 (0.17.1+dfsg1-1) ... 140s Selecting previously unselected package python3-unicodedata2. 140s Preparing to unpack .../071-python3-unicodedata2_16.0.0+ds-1build1_ppc64el.deb ... 140s Unpacking python3-unicodedata2 (16.0.0+ds-1build1) ... 140s Selecting previously unselected package libzopfli1. 140s Preparing to unpack .../072-libzopfli1_1.0.3-3_ppc64el.deb ... 140s Unpacking libzopfli1 (1.0.3-3) ... 140s Selecting previously unselected package python3-zopfli. 140s Preparing to unpack .../073-python3-zopfli_0.4.0-1_ppc64el.deb ... 140s Unpacking python3-zopfli (0.4.0-1) ... 140s Selecting previously unselected package unicode-data. 140s Preparing to unpack .../074-unicode-data_16.0.0-1_all.deb ... 140s Unpacking unicode-data (16.0.0-1) ... 140s Selecting previously unselected package python3-fonttools. 140s Preparing to unpack .../075-python3-fonttools_4.57.0-2build1_ppc64el.deb ... 140s Unpacking python3-fonttools (4.57.0-2build1) ... 140s Selecting previously unselected package python3-kiwisolver. 140s Preparing to unpack .../076-python3-kiwisolver_1.4.10~rc0-1_ppc64el.deb ... 140s Unpacking python3-kiwisolver (1.4.10~rc0-1) ... 140s Selecting previously unselected package libqhull-r8.0:ppc64el. 140s Preparing to unpack .../077-libqhull-r8.0_2020.2-7_ppc64el.deb ... 140s Unpacking libqhull-r8.0:ppc64el (2020.2-7) ... 140s Selecting previously unselected package python3-matplotlib. 140s Preparing to unpack .../078-python3-matplotlib_3.10.7+dfsg1-1_ppc64el.deb ... 140s Unpacking python3-matplotlib (3.10.7+dfsg1-1) ... 141s Selecting previously unselected package python3-pytz. 141s Preparing to unpack .../079-python3-pytz_2025.2-4_all.deb ... 141s Unpacking python3-pytz (2025.2-4) ... 141s Selecting previously unselected package python3-pandas-lib:ppc64el. 141s Preparing to unpack .../080-python3-pandas-lib_2.3.3+dfsg-1ubuntu1_ppc64el.deb ... 141s Unpacking python3-pandas-lib:ppc64el (2.3.3+dfsg-1ubuntu1) ... 141s Selecting previously unselected package python3-pandas. 141s Preparing to unpack .../081-python3-pandas_2.3.3+dfsg-1ubuntu1_all.deb ... 141s Unpacking python3-pandas (2.3.3+dfsg-1ubuntu1) ... 141s Selecting previously unselected package cython3. 141s Preparing to unpack .../082-cython3_3.1.6+dfsg-1ubuntu1_ppc64el.deb ... 141s Unpacking cython3 (3.1.6+dfsg-1ubuntu1) ... 141s Selecting previously unselected package python3-joblib. 141s Preparing to unpack .../083-python3-joblib_1.4.2-4_all.deb ... 141s Unpacking python3-joblib (1.4.2-4) ... 141s Selecting previously unselected package python3-networkx. 141s Preparing to unpack .../084-python3-networkx_3.2.1-4ubuntu1_all.deb ... 141s Unpacking python3-networkx (3.2.1-4ubuntu1) ... 142s Selecting previously unselected package python3-pomegranate. 142s Preparing to unpack .../085-python3-pomegranate_0.15.0-2_ppc64el.deb ... 142s Unpacking python3-pomegranate (0.15.0-2) ... 142s Selecting previously unselected package python3-pyfaidx. 142s Preparing to unpack .../086-python3-pyfaidx_0.8.1.3-2_all.deb ... 142s Unpacking 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up libblas3:ppc64el (3.12.1-7) ... 147s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/blas/libblas.so.3 to provide /usr/lib/powerpc64le-linux-gnu/libblas.so.3 (libblas.so.3-powerpc64le-linux-gnu) in auto mode 147s Setting up libzopfli1 (1.0.3-3) ... 147s Setting up python3-brotli (1.1.0-2build6) ... 147s Setting up xfonts-encodings (1:1.0.5-0ubuntu2) ... 147s Setting up python3-cycler (0.12.1-2) ... 147s Setting up libimagequant0:ppc64el (2.18.0-1build1) ... 147s Setting up fonts-dejavu-mono (2.37-8) ... 147s Setting up python3-kiwisolver (1.4.10~rc0-1) ... 147s Setting up python3-numpy-dev:ppc64el (1:2.2.4+ds-1ubuntu1) ... 147s Setting up cython3 (3.1.6+dfsg-1ubuntu1) ... 148s Setting up libtcl8.6:ppc64el (8.6.17+dfsg-1) ... 148s Setting up fonts-dejavu-core (2.37-8) ... 148s Setting up libjpeg-turbo8:ppc64el (2.1.5-4ubuntu2) ... 148s Setting up libgfortran5:ppc64el (15.2.0-7ubuntu1) ... 148s Setting up libwebp7:ppc64el (1.5.0-0.1) ... 148s Setting up libxslt1.1:ppc64el 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python3.14-tk (3.14.0-4) ... 170s Setting up python3-cairo (1.27.0-2build1) ... 170s Setting up blt (2.5.3+dfsg-8) ... 170s Setting up python3-tk:ppc64el (3.13.9-1) ... 170s Setting up python3-pil.imagetk:ppc64el (11.3.0-1ubuntu2) ... 170s Setting up python3-rlpycairo (0.3.0-4) ... 170s Setting up r-base-core (4.5.2-1) ... 170s Creating config file /etc/R/Renviron with new version 171s Setting up python3-reportlab (4.4.4-2) ... 171s Setting up r-bioc-biocgenerics (0.52.0-2) ... 171s Setting up r-bioc-dnacopy (1.80.0-2) ... 171s Setting up python3-fonttools (4.57.0-2build1) ... 172s Setting up python3-ufolib2 (0.17.1+dfsg1-1) ... 172s Setting up python3-matplotlib (3.10.7+dfsg1-1) ... 174s Processing triggers for man-db (2.13.1-1) ... 175s Processing triggers for install-info (7.2-5) ... 175s Processing triggers for libc-bin (2.42-2ubuntu2) ... 175s Processing triggers for sgml-base (1.31+nmu1) ... 175s Setting up w3c-sgml-lib (1.3-3) ... 203s Setting up python3-biopython (1.85+dfsg-4) ... 204s Setting up cnvkit (0.9.12-1) ... 205s autopkgtest [13:10:03]: test run-unit-test: [----------------------- 206s cnvkit.py batch -n -f formats/chrM-Y-trunc.hg19.fa -m wgs formats/na12878-chrM-Y-trunc.bam -d build 208s CNVkit 0.9.12 208s WGS protocol: recommend '--annotate' option (e.g. refFlat.txt) to help locate genes in output files. 208s chrM: Scanning for accessible regions 208s Accessible region chrM:0-121 (size 121) 208s Accessible region chrM:122-1271 (size 1149) 208s Accessible region chrM:1274-1288 (size 14) 208s Accessible region chrM:1289-1547 (size 258) 208s Accessible region chrM:1553-16571 (size 15018) 208s chrY: Scanning for accessible regions 208s Accessible region chrY:500-14900 (size 14400) 208s Accessible region chrY:15600-22966 (size 7366) 208s chrY: Joining over small gaps 208s Joining chrY 500-14900 and 15600-22966 (gap size 700) 208s Wrote chrM-Y-trunc.hg19.bed with 1 regions 208s Detected file format: bed 208s Splitting large targets 208s Created directory build 208s Wrote build/chrM-Y-trunc.hg19.target.bed with 4 regions 208s Wrote build/chrM-Y-trunc.hg19.antitarget.bed with 0 regions 208s Building a flat reference... 208s Detected file format: bed 208s Calculating GC and RepeatMasker content in formats/chrM-Y-trunc.hg19.fa ... 208s Extracting sequences from chromosome chrY 208s Wrote build/reference.cnn with 4 regions 208s Running 1 samples in serial 208s Running the CNVkit pipeline on formats/na12878-chrM-Y-trunc.bam ... 208s Indexing BAM file formats/na12878-chrM-Y-trunc.bam 208s Processing reads in na12878-chrM-Y-trunc.bam 208s Time: 0.009 seconds (4165 reads/sec, 450 bins/sec) 208s Summary: #bins=4, #reads=37, mean=9.2500, min=0.0, max=21.0 208s Percent reads in regions: 0.063 (of 58636 mapped) 208s Wrote build/na12878-chrM-Y-trunc.targetcoverage.cnn with 4 regions 208s Skip processing na12878-chrM-Y-trunc.bam with empty regions file build/chrM-Y-trunc.hg19.antitarget.bed 208s Wrote build/na12878-chrM-Y-trunc.antitargetcoverage.cnn with 0 regions 208s Processing target: na12878-chrM-Y-trunc 208s Keeping 4 of 4 bins 208s Correcting for GC bias... 208s Processing antitarget: na12878-chrM-Y-trunc 208s Wrote build/na12878-chrM-Y-trunc.cnr with 4 regions 208s Segmenting build/na12878-chrM-Y-trunc.cnr ... 208s Segmenting with method 'cbs', significance threshold 1e-06, in 1 processes 208s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 208s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 208s A typical example is when you are setting values in a column of a DataFrame, like: 208s 208s df["col"][row_indexer] = value 208s 208s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 208s 208s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 208s 208s segments.start.iat[0] = bins_start 208s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 208s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 208s A typical example is when you are setting values in a column of a DataFrame, like: 208s 208s df["col"][row_indexer] = value 208s 208s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 208s 208s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 208s 208s segments.end.iat[-1] = bins_end 208s Post-processing build/na12878-chrM-Y-trunc.cns ... 208s Wrote build/na12878-chrM-Y-trunc.cns with 1 regions 208s Applying filter 'ci' 208s Filtered by 'ci' from 1 to 1 rows 208s Calling copy number with thresholds: -1.1 => 0, -0.25 => 1, 0.2 => 2, 0.7 => 3 208s Wrote build/na12878-chrM-Y-trunc.call.cns with 1 regions 208s Significant hits in 4/4 bins (100%) 208s Wrote build/na12878-chrM-Y-trunc.bintest.cns with 4 regions 209s cnvkit.py import-picard picard/p2-20_5.antitargetcoverage.csv picard/p2-20_5.targetcoverage.csv picard/p2-5_5.antitargetcoverage.csv picard/p2-5_5.targetcoverage.csv picard/p2-9_5.antitargetcoverage.csv picard/p2-9_5.targetcoverage.csv -d build/ 210s Wrote build/p2-20_5.antitargetcoverage.cnn with 12563 regions 210s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 210s Wrote build/p2-20_5.targetcoverage.cnn with 6646 regions 211s Wrote build/p2-5_5.antitargetcoverage.cnn with 12563 regions 211s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 211s Wrote build/p2-5_5.targetcoverage.cnn with 6646 regions 211s Wrote build/p2-9_5.antitargetcoverage.cnn with 12563 regions 211s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 211s Wrote build/p2-9_5.targetcoverage.cnn with 6646 regions 211s cnvkit.py reference build/p2-*_5.*targetcoverage.cnn -y -o build/reference-picard.cnn 212s Number of target and antitarget files: 3, 3 212s No FASTA reference genome provided; skipping GC, RM calculations 212s Sample sex not provided; inferring from samples. 213s Relative log2 coverage of chrX=-0.325, chrY=-6.57 (maleness=0.0191 x 0.532 = 0.0102) --> assuming female 213s Relative log2 coverage of chrX=-0.324, chrY=-11 (maleness=0.0317 x 0.532 = 0.0168) --> assuming female 213s Relative log2 coverage of chrX=-0.17, chrY=-17.9 (maleness=0.0141 x 0.532 = 0.00752) --> assuming female 213s Relative log2 coverage of chrX=-0.522, chrY=-11.2 (maleness=0.179 x 0.809 = 0.145) --> assuming female 213s Relative log2 coverage of chrX=-0.531, chrY=-12.6 (maleness=0.11 x 0.895 = 0.0984) --> assuming female 213s Relative log2 coverage of chrX=-0.412, chrY=-16.1 (maleness=0.0599 x 0.895 = 0.0536) --> assuming female 213s Loading build/p2-20_5.targetcoverage.cnn 213s Correcting for GC bias for p2-20_5... 213s Correcting for density bias for p2-20_5... 213s Loading build/p2-5_5.targetcoverage.cnn 213s Correcting for GC bias for p2-5_5... 213s Correcting for density bias for p2-5_5... 213s Loading build/p2-9_5.targetcoverage.cnn 213s Correcting for GC bias for p2-9_5... 213s Correcting for density bias for p2-9_5... 213s Loading build/p2-20_5.antitargetcoverage.cnn 213s Correcting for GC bias for p2-20_5... 213s Loading build/p2-5_5.antitargetcoverage.cnn 213s Correcting for GC bias for p2-5_5... 214s Loading build/p2-9_5.antitargetcoverage.cnn 214s Correcting for GC bias for p2-9_5... 214s Calculating average bin coverages 224s Calculating bin spreads 225s Targets: 338 (5.086%) bins failed filters (log2 < -5.0, log2 > 5.0, spread > 1.0) 225s PLCH2 chr1:2433503-2433878 log2=-0.586 spread=0.505 225s " chr1:2435319-2436685 log2=-0.709 spread=0.503 225s ARID1A chr1:27022844-27024053 log2=-1.481 spread=0.110 225s MYCL1 chr1:40366439-40367601 log2=0.085 spread=0.245 225s LRRC8B chr1:90000112-90000296 log2=0.225 spread=0.274 225s CGH chr1:106510773-106510953 log2=-0.394 spread=0.325 225s NOTCH2 chr1:120572470-120572622 log2=-2.593 spread=1.502 225s " chr1:120611883-120612051 log2=0.070 spread=0.050 225s NTRK1 chr1:156830676-156830968 log2=-0.814 spread=0.513 225s " chr1:156842391-156842479 log2=-0.398 spread=0.290 225s MPC2 chr1:167906099-167906278 log2=0.166 spread=0.393 225s ABL2 chr1:179198326-179198565 log2=-0.546 spread=0.389 225s SMG7 chr1:183441669-183441848 log2=0.368 spread=0.171 225s " chr1:183481886-183481951 log2=-0.040 spread=0.119 225s CDC73 chr1:193219724-193219907 log2=0.087 spread=0.141 225s AKT3 chr1:243675572-243675743 log2=0.222 spread=0.106 225s " chr1:243800859-243801066 log2=0.023 spread=0.063 225s MYCN chr2:16082132-16082989 log2=-1.145 spread=0.371 225s DNMT3A chr2:25475011-25475213 log2=-1.033 spread=0.468 225s " chr2:25536716-25536891 log2=0.702 spread=0.033 225s MSH2 chr2:47698049-47698231 log2=0.129 spread=0.196 225s MSH6 chr2:48010322-48010657 log2=-0.616 spread=0.644 225s VRK2 chr2:58386820-58386989 log2=0.422 spread=0.287 225s REL chr2:61108881-61109061 log2=1.026 spread=0.559 225s " chr2:61128072-61128256 log2=0.115 spread=0.173 225s " chr2:61145275-61145462 log2=0.014 spread=0.099 225s CGH chr2:82511447-82511627 log2=-0.205 spread=0.129 225s DUSP2 chr2:96810448-96811208 log2=-0.655 spread=0.435 225s MAP3K2 chr2:128081427-128081603 log2=-0.218 spread=0.144 225s " chr2:128095237-128095425 log2=0.215 spread=0.212 225s METTL8 chr2:172291040-172291240 log2=-0.027 spread=0.068 225s VHL chr3:10183481-10183898 log2=-0.155 spread=0.209 225s TGFBR2 chr3:30648320-30648501 log2=0.496 spread=0.504 225s EPHA6 chr3:96585608-96585773 log2=0.045 spread=0.100 225s " chr3:97160189-97160367 log2=-0.050 spread=0.191 225s ATR chr3:142254935-142255077 log2=0.024 spread=0.027 225s " chr3:142286854-142287031 log2=-0.076 spread=0.116 225s GAK chr4:896278-896357 log2=-1.505 spread=1.261 225s FGFR3 chr4:1795608-1795799 log2=-0.750 spread=0.491 225s " chr4:1803044-1803507 log2=-0.073 spread=0.117 225s " chr4:1808792-1809022 log2=0.252 spread=0.108 225s CGH chr4:31509625-31509802 log2=-0.057 spread=0.101 225s EPHA5 chr4:66535226-66535490 log2=-0.681 spread=0.567 225s CGH chr4:163514273-163514460 log2=-0.403 spread=0.271 225s " chr4:178514600-178514725 log2=-0.098 spread=0.096 225s TERT chr5:1293376-1294792 log2=-0.724 spread=0.511 225s TERT Promoter chr5:1294836-1295203 log2=-1.970 spread=0.777 225s " chr5:1295312-1295381 log2=-0.690 spread=0.462 225s CGH chr5:12000292-12000462 log2=-0.342 spread=0.056 225s " chr5:25519857-25520034 log2=-0.015 spread=0.095 225s RICTOR chr5:38958717-38958965 log2=0.011 spread=0.018 225s " chr5:38962338-38962525 log2=0.005 spread=0.019 225s " chr5:38966685-38966862 log2=0.006 spread=0.165 225s " chr5:38978620-38978763 log2=0.040 spread=0.030 225s " chr5:39074133-39074327 log2=-0.158 spread=0.139 225s CGH chr5:42002796-42002944 log2=-0.083 spread=0.071 225s " chr5:51030131-51030313 log2=-0.034 spread=0.192 225s MAP3K1 chr5:56111354-56111894 log2=-1.478 spread=1.050 225s " chr5:56168412-56168590 log2=0.479 spread=0.038 225s CGH chr5:61573234-61573421 log2=-0.072 spread=0.161 225s PIK3R1 chr5:67589487-67589699 log2=0.349 spread=0.264 225s RASA1 chr5:86633752-86633938 log2=0.119 spread=0.112 225s " chr5:86637023-86637168 log2=0.054 spread=0.111 225s " chr5:86642414-86642592 log2=0.254 spread=0.162 225s " chr5:86648912-86649096 log2=0.092 spread=0.062 225s " chr5:86670598-86670778 log2=0.222 spread=0.198 225s MCTP1 chr5:94619518-94620311 log2=-1.064 spread=0.754 225s CGH chr5:99008357-99008506 log2=-0.069 spread=0.390 225s APC chr5:112101965-112102138 log2=0.104 spread=0.217 225s NPM1 chr5:170832371-170832440 log2=-0.398 spread=0.335 225s " chr5:170837567-170837631 log2=0.085 spread=0.349 225s FLT4 chr5:180045962-180046145 log2=-0.884 spread=0.532 225s " chr5:180046203-180046404 log2=-1.531 spread=0.722 225s " chr5:180076418-180076603 log2=-2.224 spread=1.416 225s TPMT chr6:18130863-18131048 log2=0.022 spread=0.099 225s DOM3Z chr6:31938905-31939081 log2=-20.014 spread=0.042 225s " chr6:31939599-31940313 log2=-19.582 spread=0.181 225s STK19 chr6:31940351-31940562 log2=-18.990 spread=0.181 225s " chr6:31946632-31946824 log2=-20.052 spread=0.088 225s " chr6:31947142-31947366 log2=-20.114 spread=0.066 225s " chr6:31948176-31948360 log2=-19.982 spread=0.149 225s " chr6:31948382-31948612 log2=-19.757 spread=0.165 225s " chr6:31948730-31949253 log2=-20.048 spread=0.014 225s NOTCH4 chr6:32163159-32163956 log2=-19.306 spread=0.203 225s " chr6:32164046-32164227 log2=-19.755 spread=0.189 225s " chr6:32164652-32164888 log2=-19.984 spread=0.154 226s " chr6:32165021-32165403 log2=-19.625 spread=0.196 226s " chr6:32166163-32166545 log2=-20.043 spread=0.072 226s " chr6:32166648-32166962 log2=-3.514 spread=5.742 226s " chr6:32168554-32168821 log2=-19.601 spread=0.197 226s " chr6:32168844-32169306 log2=-19.683 spread=0.166 226s " chr6:32169801-32170391 log2=-19.405 spread=0.205 226s " chr6:32171492-32171691 log2=-20.095 spread=0.101 226s " chr6:32171861-32172198 log2=-3.141 spread=7.288 226s " chr6:32178478-32178749 log2=-19.927 spread=0.164 226s " chr6:32180197-32180441 log2=-10.902 spread=9.532 226s " chr6:32180544-32180722 log2=-19.675 spread=0.186 226s " chr6:32180857-32181062 log2=-19.562 spread=0.227 226s " chr6:32181411-32181646 log2=-19.966 spread=0.171 226s " chr6:32181832-32182066 log2=-19.961 spread=0.172 226s " chr6:32182948-32183194 log2=-19.935 spread=0.168 226s " chr6:32184667-32185079 log2=-19.923 spread=0.165 226s " chr6:32185720-32185919 log2=-19.707 spread=0.197 226s " chr6:32187317-32187601 log2=-19.765 spread=0.173 226s " chr6:32187871-32188094 log2=-19.660 spread=0.188 226s " chr6:32188127-32188451 log2=-19.622 spread=0.169 226s " chr6:32188481-32188693 log2=-19.902 spread=0.132 226s " chr6:32188704-32189133 log2=-19.501 spread=0.193 226s " chr6:32190258-32190616 log2=-19.570 spread=0.209 226s " chr6:32190724-32190908 log2=-19.540 spread=0.232 226s " chr6:32191570-32191668 log2=-19.773 spread=0.178 226s " chr6:32191676-32191753 log2=-19.374 spread=0.201 226s FOXP4 chr6:41565467-41565725 log2=-0.259 spread=0.369 226s CCND3 chr6:41909139-41909415 log2=0.039 spread=0.240 226s NFKBIE chr6:44232672-44233479 log2=0.034 spread=0.050 226s CGH chr6:49502071-49502248 log2=-0.093 spread=0.241 226s POU3F2 chr6:99282701-99283145 log2=-1.559 spread=0.536 226s ROS1 chr6:117657131-117657335 log2=-0.377 spread=0.282 226s RSPO3 chr6:127510871-127511054 log2=-0.128 spread=0.105 226s PTPRK chr6:128313744-128313923 log2=0.177 spread=0.190 226s " chr6:128316545-128316699 log2=-0.070 spread=0.050 226s MAP3K5 chr6:137026207-137026289 log2=0.053 spread=0.094 226s ARID1B chr6:157099014-157099324 log2=-0.621 spread=0.410 226s " chr6:157099442-157099991 log2=-0.846 spread=0.504 226s " chr6:157100042-157100634 log2=-1.570 spread=0.825 226s IGF2R chr6:160390228-160390461 log2=-2.660 spread=0.959 226s RAC1 chr7:6414287-6414459 log2=0.162 spread=0.232 226s COL28A1 chr7:7521080-7521229 log2=0.015 spread=0.050 226s FKBP9 chr7:32997131-32997427 log2=-0.367 spread=0.272 226s CGH chr7:52520101-52520286 log2=-1.525 spread=1.176 226s EGFR chr7:55086913-55087091 log2=-0.081 spread=0.180 226s CDK6 chr7:92462355-92462676 log2=0.309 spread=0.198 226s TRRAP chr7:98479525-98479705 log2=0.060 spread=0.087 226s " chr7:98491365-98491541 log2=0.209 spread=0.153 226s " chr7:98493314-98493496 log2=0.389 spread=0.207 226s SMO chr7:128828938-128829041 log2=-2.056 spread=1.317 226s " chr7:128829048-128829358 log2=-0.474 spread=0.315 226s BRAF chr7:140481968-140482374 log2=0.013 spread=0.017 226s " chr7:140484736-140484912 log2=0.081 spread=0.150 226s " chr7:140487956-140488430 log2=-0.089 spread=0.142 226s " chr7:140493336-140493442 log2=-0.340 spread=0.283 226s " chr7:140624315-140624540 log2=-0.497 spread=0.342 226s TNKS chr8:9609998-9610174 log2=0.021 spread=0.082 226s WRN chr8:30925752-30925890 log2=0.120 spread=0.158 226s " chr8:30941153-30941335 log2=0.079 spread=0.294 226s " chr8:30942625-30942802 log2=0.044 spread=0.247 226s " chr8:30947918-30948092 log2=0.151 spread=0.124 226s " chr8:31000128-31000252 log2=-0.099 spread=0.098 226s " chr8:31001006-31001182 log2=-0.002 spread=0.062 226s GPR124 chr8:37654740-37655077 log2=-1.617 spread=1.020 226s " chr8:37698557-37699898 log2=-0.612 spread=0.029 226s ADAM32 chr8:39022338-39022511 log2=-0.103 spread=0.127 226s PRKDC chr8:48827831-48828019 log2=0.018 spread=0.101 226s " chr8:48845528-48845758 log2=0.056 spread=0.196 226s " chr8:48866846-48867043 log2=-0.067 spread=0.097 226s " chr8:48868369-48868526 log2=-0.239 spread=0.174 226s " chr8:48872485-48872722 log2=-0.636 spread=0.464 226s CGH chr8:88503010-88503173 log2=-0.137 spread=0.254 226s FBXO43 chr8:101149746-101149928 log2=0.049 spread=0.082 226s SMARCA2 chr9:2047182-2047507 log2=-0.353 spread=0.368 226s " chr9:2101491-2101640 log2=0.244 spread=0.104 226s JAK2 chr9:5064539-5066968 log2=0.119 spread=0.077 226s " chr9:5067014-5067883 log2=0.146 spread=0.089 226s " chr9:5068184-5070306 log2=0.133 spread=0.092 226s " chr9:5076944-5077152 log2=0.046 spread=0.137 226s PTPRD chr9:8527276-8527424 log2=-0.239 spread=0.237 226s CDKN2A chr9:21973657-21973843 log2=0.148 spread=0.043 226s " chr9:21986759-21986899 log2=0.058 spread=0.175 226s LINGO2 chr9:28505910-28506090 log2=-0.396 spread=0.123 226s CGH chr9:39011524-39011705 log2=-0.205 spread=0.230 226s TRPM3 chr9:73240339-73240498 log2=0.009 spread=0.086 226s NTRK2 chr9:87356721-87356908 log2=0.166 spread=0.265 226s " chr9:87425375-87425452 log2=0.494 spread=0.066 226s PTCH1 chr9:98278654-98278833 log2=-0.560 spread=0.038 226s GPSM1 chr9:139222089-139222248 log2=-4.879 spread=2.118 226s " chr9:139250747-139251032 log2=-0.223 spread=0.273 226s " chr9:139252418-139252703 log2=-0.512 spread=0.264 226s NOTCH1 chr9:139396674-139396979 log2=-0.595 spread=0.295 226s " chr9:139417262-139417677 log2=-0.173 spread=0.191 226s " chr9:139440110-139440287 log2=-1.257 spread=0.500 226s MRC1 chr10:18136438-18136613 log2=-1.945 spread=3.242 226s CGH chr10:22505654-22505837 log2=0.072 spread=0.107 226s RET chr10:43572644-43572830 log2=-1.376 spread=1.092 226s " chr10:43600360-43600677 log2=-0.341 spread=0.222 226s PTEN chr10:89653722-89653907 log2=0.394 spread=0.030 226s " chr10:89685254-89685374 log2=0.244 spread=0.259 226s TNKS2 chr10:93558396-93558682 log2=-0.037 spread=0.051 226s " chr10:93579008-93579121 log2=0.166 spread=0.220 226s SUFU chr10:104263859-104264127 log2=0.269 spread=0.224 226s SHOC2 chr10:112679251-112679451 log2=-0.434 spread=0.304 226s " chr10:112679716-112679934 log2=-0.008 spread=0.028 226s CGH chr10:114003863-114003979 log2=-0.115 spread=0.290 226s WT1 chr11:32456191-32456924 log2=-1.020 spread=0.782 226s CCND1 chr11:69465991-69466081 log2=0.058 spread=0.209 226s GAB2 chr11:78128632-78128813 log2=-0.754 spread=0.552 226s MRE11A chr11:94153219-94153345 log2=-0.021 spread=0.076 226s " chr11:94170270-94170454 log2=0.095 spread=0.285 226s YAP1 chr11:101981528-101981920 log2=-0.331 spread=0.340 226s GUCY1A2 chr11:106888426-106888817 log2=-1.400 spread=0.707 226s ATM chr11:108153392-108153639 log2=0.113 spread=0.136 226s " chr11:108164020-108164234 log2=-0.056 spread=0.040 226s " chr11:108217986-108218135 log2=0.359 spread=0.277 226s MLL chr11:118307178-118307688 log2=-1.486 spread=0.278 226s ARHGAP32 chr11:129003788-129003964 log2=0.053 spread=0.102 226s ETV6 chr12:12018196-12018602 log2=-0.014 spread=0.112 226s KRAS chr12:25362676-25362878 log2=0.128 spread=0.150 226s " chr12:25391004-25391186 log2=0.368 spread=0.128 226s DIP2B chr12:51002431-51002557 log2=0.344 spread=0.188 226s ATF1 chr12:51206642-51206737 log2=0.009 spread=0.024 226s " chr12:51206782-51207287 log2=-0.012 spread=0.101 226s PTPN11 chr12:112856822-112857002 log2=-0.268 spread=0.071 226s CDK8 chr13:26911641-26911828 log2=-0.125 spread=0.167 226s " chr13:26970356-26970536 log2=0.137 spread=0.121 226s FLT3 chr13:28674525-28674708 log2=-2.257 spread=1.745 226s FLT1 chr13:29068850-29069036 log2=-0.914 spread=0.672 226s BRCA2 chr13:32900164-32900478 log2=-0.076 spread=0.110 226s " chr13:32903506-32903689 log2=0.019 spread=0.232 226s " chr13:32918645-32918823 log2=0.158 spread=0.114 226s " chr13:32920899-32921077 log2=0.014 spread=0.247 226s RB1 chr13:48877994-48878223 log2=-0.155 spread=0.250 226s " chr13:48919164-48919369 log2=0.025 spread=0.094 226s " chr13:48921877-48922044 log2=0.106 spread=0.147 226s " chr13:48923026-48923204 log2=0.360 spread=0.016 226s " chr13:48938965-48939147 log2=0.084 spread=0.356 226s " chr13:48941578-48941767 log2=0.238 spread=0.212 226s " chr13:48947486-48947665 log2=0.025 spread=0.126 226s " chr13:48954166-48954251 log2=0.061 spread=0.273 226s " chr13:49037815-49038005 log2=0.063 spread=0.062 226s " chr13:49047410-49047589 log2=0.053 spread=0.170 226s CGH chr13:63016375-63016514 log2=-0.434 spread=0.282 226s " chr13:85527771-85527948 log2=0.007 spread=0.222 226s GPC5 chr13:93003992-93004180 log2=-0.192 spread=0.289 226s IRS2 chr13:110434582-110438324 log2=-0.768 spread=0.252 226s " chr13:110438332-110438432 log2=-3.643 spread=2.325 226s CGH chr14:19220933-19221047 log2=-1.230 spread=1.205 226s " chr14:20291466-20291612 log2=0.697 spread=0.248 226s NKX2-1 chr14:36986433-36987264 log2=-1.444 spread=0.135 226s " chr14:36989195-36989373 log2=0.023 spread=0.162 226s SOS2 chr14:50596601-50596777 log2=0.237 spread=0.146 226s " chr14:50619741-50619923 log2=0.003 spread=0.272 226s " chr14:50697856-50698044 log2=0.277 spread=0.334 226s MAP3K9 chr14:71275435-71275784 log2=-0.385 spread=0.461 226s " chr14:71275790-71275923 log2=-2.815 spread=1.938 226s TSHR chr14:81528428-81528609 log2=0.070 spread=0.244 226s CGH chr15:20870700-20870881 log2=1.102 spread=0.611 226s " chr15:38544477-38545455 log2=-0.348 spread=0.179 226s SPRED1 chr15:38647081-38647177 log2=0.225 spread=0.350 226s LTK chr15:41803310-41803809 log2=-1.956 spread=1.443 226s " chr15:41803968-41804185 log2=-2.202 spread=0.188 226s " chr15:41804261-41804494 log2=-0.402 spread=0.392 226s NTRK3 chr15:88532873-88532940 log2=-0.337 spread=0.240 226s IDH2 chr15:90645456-90645663 log2=-0.951 spread=0.705 226s PDPK1 chr16:2588022-2588201 log2=-1.782 spread=1.082 226s " chr16:2611404-2611585 log2=-5.171 spread=1.963 226s " chr16:2611721-2611943 log2=-11.810 spread=9.172 226s " chr16:2615504-2615725 log2=-20.113 spread=0.007 226s " chr16:2616307-2616486 log2=-20.054 spread=0.072 226s " chr16:2631267-2631414 log2=-20.009 spread=0.061 226s " chr16:2631583-2631734 log2=-20.089 spread=0.090 226s " chr16:2633363-2633616 log2=-20.101 spread=0.089 226s CREBBP chr16:3799553-3799731 log2=0.082 spread=0.155 226s SOCS1 chr16:11349442-11349617 log2=0.110 spread=0.079 226s BOLA2B chr16:29466011-29466278 log2=-18.994 spread=0.172 226s CGH chr16:31526705-31526886 log2=0.057 spread=0.074 226s CYLD chr16:50821673-50821804 log2=0.007 spread=0.188 226s " chr16:50826460-50826650 log2=0.239 spread=0.204 226s CGH chr16:51098326-51098475 log2=-0.578 spread=0.376 226s " chr16:60005694-60005857 log2=-0.366 spread=0.298 226s CDH1 chr16:68771239-68771428 log2=-0.813 spread=0.625 226s CGH chr16:81005282-81005469 log2=-0.134 spread=0.229 226s MAP2K4 chr17:11924151-11924355 log2=-2.093 spread=1.900 226s " chr17:12011053-12011253 log2=0.028 spread=0.232 226s NF1 chr17:29422259-29422433 log2=-0.466 spread=0.381 226s " chr17:29496854-29497046 log2=0.226 spread=0.193 226s RHOT1 chr17:30469629-30469811 log2=-0.034 spread=0.252 226s " chr17:30519172-30519355 log2=0.163 spread=0.289 226s " chr17:30525911-30526093 log2=-0.157 spread=0.046 226s ERBB2 chr17:37856430-37856609 log2=0.221 spread=0.369 226s RPTOR chr17:78896472-78896661 log2=0.267 spread=0.290 226s C18orf56 chr18:657548-657727 log2=-2.406 spread=0.189 226s CDH2 chr18:25756859-25757030 log2=-3.262 spread=0.283 226s KIAA1328 chr18:34512037-34512192 log2=0.081 spread=0.180 226s CGH chr18:42005882-42006049 log2=-0.031 spread=0.038 226s SMAD4 chr18:48575581-48575754 log2=0.224 spread=0.215 226s CGH chr18:58519179-58519311 log2=-0.254 spread=0.214 226s STK11 chr19:1226401-1226680 log2=-0.501 spread=0.149 226s DOT1L chr19:2164127-2164302 log2=-1.071 spread=0.866 226s " chr19:2210351-2210545 log2=-0.860 spread=0.261 226s " chr19:2226130-2227152 log2=-0.113 spread=0.120 226s GNA11 chr19:3094603-3094817 log2=-0.229 spread=0.152 226s GIPC3 chr19:3585549-3585853 log2=-1.516 spread=1.086 226s MAP2K2 chr19:4123728-4123907 log2=-0.004 spread=0.187 226s INSR chr19:7293751-7294042 log2=-2.020 spread=1.538 226s SMARCA4 chr19:11098288-11098630 log2=-0.647 spread=0.206 226s PODNL1 chr19:14063277-14063492 log2=-0.226 spread=0.272 226s NOTCH3 chr19:15288281-15288927 log2=-1.510 spread=0.106 226s " chr19:15311544-15311749 log2=-1.887 spread=1.202 226s JAK3 chr19:17953074-17953444 log2=-0.886 spread=0.423 226s CCNE1 chr19:30303376-30303718 log2=-0.486 spread=0.368 226s CEBPA chr19:33792189-33792764 log2=-0.086 spread=0.251 226s " chr19:33792774-33793010 log2=-1.781 spread=0.127 226s " chr19:33793014-33793356 log2=-0.541 spread=0.385 226s CD79A chr19:42384673-42384848 log2=-1.881 spread=1.227 226s ERCC2 chr19:45866950-45867408 log2=-0.750 spread=0.536 226s " chr19:45873698-45873881 log2=-0.522 spread=0.327 226s BCL2L12 chr19:50173423-50173770 log2=-0.005 spread=0.243 226s SRC chr20:36012507-36012834 log2=-0.373 spread=0.448 226s TOP1 chr20:39657625-39657796 log2=-0.187 spread=0.282 226s PLCG1 chr20:39766233-39766531 log2=-0.105 spread=0.074 226s AURKA chr20:54959250-54959432 log2=0.185 spread=0.183 226s SYCP2 chr20:58505615-58505798 log2=-0.018 spread=0.034 226s ARFRP1 chr20:62339169-62339402 log2=-1.471 spread=0.976 226s RUNX1 chr21:36164379-36164936 log2=0.163 spread=0.307 226s " chr21:36265140-36265318 log2=0.042 spread=0.039 226s CHEK2 chr22:29105918-29106101 log2=0.091 spread=0.114 226s " chr22:29115325-29115465 log2=0.055 spread=0.390 226s SOX10 chr22:38379312-38379815 log2=-0.427 spread=0.308 226s CGH chr22:41487738-41489134 log2=-0.174 spread=0.116 226s EP300 chr22:41562534-41562711 log2=0.160 spread=0.125 226s CRLF2 chrX:1314835-1315039 log2=-21.107 spread=0.037 226s " chrX:1317372-1317594 log2=-21.121 spread=0.049 226s " chrX:1321225-1321435 log2=-20.851 spread=0.196 226s " chrX:1325274-1325530 log2=-21.121 spread=0.011 226s " chrX:1327651-1327830 log2=-21.000 spread=0.029 226s " chrX:1331391-1331576 log2=-21.018 spread=0.052 226s KDM6A chrX:44820507-44820671 log2=-0.582 spread=0.279 226s PAK3 chrX:110435687-110435871 log2=-1.172 spread=0.053 226s STAG2 chrX:123182790-123182965 log2=-0.941 spread=0.228 226s " chrX:123185143-123185290 log2=-1.018 spread=0.062 226s " chrX:123202378-123202544 log2=-0.959 spread=0.103 226s FAM58A chrX:152864353-152864586 log2=-2.437 spread=0.754 226s CGH chrY:4564417-4564597 log2=-1.004 spread=0.063 226s " chrY:9008607-9008759 log2=-1.012 spread=0.097 226s " chrY:13131970-13132039 log2=-1.004 spread=0.074 226s " chrY:19506485-19506650 log2=-1.018 spread=0.034 226s " chrY:21033918-21034071 log2=-1.013 spread=0.057 226s " chrY:28463435-28463622 log2=-0.952 spread=0.039 226s " chrY:28514033-28514208 log2=-0.992 spread=0.026 226s Antitargets: 108 (0.8597%) bins failed filters 226s Wrote build/reference-picard.cnn with 19209 regions 226s cnvkit.py fix build/p2-5_5.targetcoverage.cnn build/p2-5_5.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-5_5.cnr 227s Processing target: p2-5_5 227s Keeping 6308 of 6646 bins 227s Correcting for GC bias... 228s Correcting for density bias... 228s Processing antitarget: p2-5_5 228s Keeping 12455 of 12563 bins 228s Correcting for GC bias... 228s WARNING: Skipping correction for RepeatMasker bias 228s Targets are 1.18 x more variable than antitargets 228s Wrote build/p2-5_5.cnr with 18763 regions 228s cnvkit.py import-picard picard/p2-9_2.targetcoverage.csv -d build/ 230s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 230s Wrote build/p2-9_2.targetcoverage.cnn with 6646 regions 230s cnvkit.py import-picard picard/p2-9_2.antitargetcoverage.csv -d build/ 232s Wrote build/p2-9_2.antitargetcoverage.cnn with 12563 regions 232s cnvkit.py fix build/p2-9_2.targetcoverage.cnn build/p2-9_2.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-9_2.cnr 233s Processing target: p2-9_2 233s Keeping 6308 of 6646 bins 233s Correcting for GC bias... 234s Correcting for density bias... 234s Processing antitarget: p2-9_2 234s Keeping 12455 of 12563 bins 234s Correcting for GC bias... 234s WARNING: Skipping correction for RepeatMasker bias 234s Targets are 1.72 x more variable than antitargets 234s Wrote build/p2-9_2.cnr with 18763 regions 234s cnvkit.py import-picard picard/p2-20_1.targetcoverage.csv -d build/ 236s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 236s Wrote build/p2-20_1.targetcoverage.cnn with 6646 regions 236s cnvkit.py import-picard picard/p2-20_1.antitargetcoverage.csv -d build/ 238s Wrote build/p2-20_1.antitargetcoverage.cnn with 12563 regions 238s cnvkit.py fix build/p2-20_1.targetcoverage.cnn build/p2-20_1.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-20_1.cnr 239s Processing target: p2-20_1 239s Keeping 6308 of 6646 bins 240s Correcting for GC bias... 240s Correcting for density bias... 240s Processing antitarget: p2-20_1 240s Keeping 12455 of 12563 bins 240s Correcting for GC bias... 240s WARNING: Skipping correction for RepeatMasker bias 240s Targets are 1.12 x more variable than antitargets 240s Wrote build/p2-20_1.cnr with 18763 regions 240s cnvkit.py import-picard picard/p2-20_2.targetcoverage.csv -d build/ 242s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 242s Wrote build/p2-20_2.targetcoverage.cnn with 6646 regions 242s cnvkit.py import-picard picard/p2-20_2.antitargetcoverage.csv -d build/ 244s Wrote build/p2-20_2.antitargetcoverage.cnn with 12563 regions 244s cnvkit.py fix build/p2-20_2.targetcoverage.cnn build/p2-20_2.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-20_2.cnr 245s Processing target: p2-20_2 246s Keeping 6308 of 6646 bins 246s Correcting for GC bias... 246s Correcting for density bias... 246s Processing antitarget: p2-20_2 246s Keeping 12455 of 12563 bins 246s Correcting for GC bias... 246s WARNING: Skipping correction for RepeatMasker bias 246s Targets are 1.10 x more variable than antitargets 246s Wrote build/p2-20_2.cnr with 18763 regions 246s cnvkit.py import-picard picard/p2-20_3.targetcoverage.csv -d build/ 248s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 248s Wrote build/p2-20_3.targetcoverage.cnn with 6646 regions 248s cnvkit.py import-picard picard/p2-20_3.antitargetcoverage.csv -d build/ 250s Wrote build/p2-20_3.antitargetcoverage.cnn with 12563 regions 250s cnvkit.py fix build/p2-20_3.targetcoverage.cnn build/p2-20_3.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-20_3.cnr 251s Processing target: p2-20_3 252s Keeping 6308 of 6646 bins 252s Correcting for GC bias... 252s Correcting for density bias... 252s Processing antitarget: p2-20_3 252s Keeping 12455 of 12563 bins 252s Correcting for GC bias... 252s WARNING: Skipping correction for RepeatMasker bias 252s Antitargets are 1.09 x more variable than targets 252s Wrote build/p2-20_3.cnr with 18763 regions 252s cnvkit.py import-picard picard/p2-20_4.targetcoverage.csv -d build/ 254s WARNING: Ambiguous gene name 'TERT|TERT Promoter'; using 'TERT Promoter' 254s Wrote build/p2-20_4.targetcoverage.cnn with 6646 regions 254s cnvkit.py import-picard picard/p2-20_4.antitargetcoverage.csv -d build/ 256s Wrote build/p2-20_4.antitargetcoverage.cnn with 12563 regions 256s cnvkit.py fix build/p2-20_4.targetcoverage.cnn build/p2-20_4.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-20_4.cnr 257s Processing target: p2-20_4 257s Keeping 6308 of 6646 bins 257s Correcting for GC bias... 258s Correcting for density bias... 258s Processing antitarget: p2-20_4 258s Keeping 12455 of 12563 bins 258s Correcting for GC bias... 258s WARNING: Skipping correction for RepeatMasker bias 258s Targets are 1.43 x more variable than antitargets 258s Wrote build/p2-20_4.cnr with 18763 regions 258s cnvkit.py fix build/p2-20_5.targetcoverage.cnn build/p2-20_5.antitargetcoverage.cnn build/reference-picard.cnn -o build/p2-20_5.cnr 260s Processing target: p2-20_5 260s Keeping 6308 of 6646 bins 260s Correcting for GC bias... 260s Correcting for density bias... 260s Processing antitarget: p2-20_5 260s Keeping 12455 of 12563 bins 260s Correcting for GC bias... 260s WARNING: Skipping correction for RepeatMasker bias 260s Targets are 2.50 x more variable than antitargets 261s Wrote build/p2-20_5.cnr with 18763 regions 261s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-5_5.cnr -o build/p2-5_5.cns 262s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.start.iat[0] = bins_start 263s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 263s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 263s A typical example is when you are setting values in a column of a DataFrame, like: 263s 263s df["col"][row_indexer] = value 263s 263s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 263s 263s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 263s 263s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.start.iat[0] = bins_start 264s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 264s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 264s A typical example is when you are setting values in a column of a DataFrame, like: 264s 264s df["col"][row_indexer] = value 264s 264s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 264s 264s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 264s 264s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.start.iat[0] = bins_start 265s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 265s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 265s A typical example is when you are setting values in a column of a DataFrame, like: 265s 265s df["col"][row_indexer] = value 265s 265s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 265s 265s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 265s 265s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.start.iat[0] = bins_start 266s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 266s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 266s A typical example is when you are setting values in a column of a DataFrame, like: 266s 266s df["col"][row_indexer] = value 266s 266s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 266s 266s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 266s 266s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.start.iat[0] = bins_start 267s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 267s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 267s A typical example is when you are setting values in a column of a DataFrame, like: 267s 267s df["col"][row_indexer] = value 267s 267s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 267s 267s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 267s 267s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 268s Dropped 8 / 49 bins on chromosome chrY 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.start.iat[0] = bins_start 268s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 268s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 268s A typical example is when you are setting values in a column of a DataFrame, like: 268s 268s df["col"][row_indexer] = value 268s 268s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 268s 268s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 268s 268s segments.end.iat[-1] = bins_end 269s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 269s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 269s A typical example is when you are setting values in a column of a DataFrame, like: 269s 269s df["col"][row_indexer] = value 269s 269s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 269s 269s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 269s 269s segments.start.iat[0] = bins_start 269s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 269s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 269s A typical example is when you are setting values in a column of a DataFrame, like: 269s 269s df["col"][row_indexer] = value 269s 269s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 269s 269s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 269s 269s segments.end.iat[-1] = bins_end 269s Wrote build/p2-5_5.cns with 71 regions 269s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-9_2.cnr -o build/p2-9_2.cns 270s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 270s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 270s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 270s A typical example is when you are setting values in a column of a DataFrame, like: 270s 270s df["col"][row_indexer] = value 270s 270s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 270s 270s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 270s 270s segments.start.iat[0] = bins_start 270s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 270s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 270s A typical example is when you are setting values in a column of a DataFrame, like: 270s 270s df["col"][row_indexer] = value 270s 270s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 270s 270s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 270s 270s segments.end.iat[-1] = bins_end 270s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 270s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 270s A typical example is when you are setting values in a column of a DataFrame, like: 270s 270s df["col"][row_indexer] = value 270s 270s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 270s 270s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 270s 270s segments.start.iat[0] = bins_start 270s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 270s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 270s A typical example is when you are setting values in a column of a DataFrame, like: 270s 270s df["col"][row_indexer] = value 270s 270s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 270s 270s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 270s 270s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.start.iat[0] = bins_start 271s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 271s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 271s A typical example is when you are setting values in a column of a DataFrame, like: 271s 271s df["col"][row_indexer] = value 271s 271s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 271s 271s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 271s 271s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s Dropped 1 / 949 bins on chromosome chr6 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.start.iat[0] = bins_start 272s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 272s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 272s A typical example is when you are setting values in a column of a DataFrame, like: 272s 272s df["col"][row_indexer] = value 272s 272s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 272s 272s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 272s 272s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.start.iat[0] = bins_start 273s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 273s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 273s A typical example is when you are setting values in a column of a DataFrame, like: 273s 273s df["col"][row_indexer] = value 273s 273s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 273s 273s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 273s 273s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.start.iat[0] = bins_start 274s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 274s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 274s A typical example is when you are setting values in a column of a DataFrame, like: 274s 274s df["col"][row_indexer] = value 274s 274s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 274s 274s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 274s 274s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.start.iat[0] = bins_start 275s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 275s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 275s A typical example is when you are setting values in a column of a DataFrame, like: 275s 275s df["col"][row_indexer] = value 275s 275s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 275s 275s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 275s 275s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.start.iat[0] = bins_start 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 276s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 276s A typical example is when you are setting values in a column of a DataFrame, like: 276s 276s df["col"][row_indexer] = value 276s 276s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 276s 276s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 276s 276s segments.end.iat[-1] = bins_end 276s Dropped 27 / 49 bins on chromosome chrY 277s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 277s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 277s A typical example is when you are setting values in a column of a DataFrame, like: 277s 277s df["col"][row_indexer] = value 277s 277s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 277s 277s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 277s 277s segments.start.iat[0] = bins_start 277s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 277s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 277s A typical example is when you are setting values in a column of a DataFrame, like: 277s 277s df["col"][row_indexer] = value 277s 277s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 277s 277s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 277s 277s segments.end.iat[-1] = bins_end 277s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 277s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 277s A typical example is when you are setting values in a column of a DataFrame, like: 277s 277s df["col"][row_indexer] = value 277s 277s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 277s 277s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 277s 277s segments.start.iat[0] = bins_start 277s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 277s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 277s A typical example is when you are setting values in a column of a DataFrame, like: 277s 277s df["col"][row_indexer] = value 277s 277s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 277s 277s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 277s 277s segments.end.iat[-1] = bins_end 277s Wrote build/p2-9_2.cns with 103 regions 277s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-20_1.cnr -o build/p2-20_1.cns 278s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.start.iat[0] = bins_start 279s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 279s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 279s A typical example is when you are setting values in a column of a DataFrame, like: 279s 279s df["col"][row_indexer] = value 279s 279s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 279s 279s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 279s 279s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.start.iat[0] = bins_start 280s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 280s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 280s A typical example is when you are setting values in a column of a DataFrame, like: 280s 280s df["col"][row_indexer] = value 280s 280s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 280s 280s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 280s 280s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.start.iat[0] = bins_start 281s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 281s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 281s A typical example is when you are setting values in a column of a DataFrame, like: 281s 281s df["col"][row_indexer] = value 281s 281s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 281s 281s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 281s 281s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.start.iat[0] = bins_start 282s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 282s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 282s A typical example is when you are setting values in a column of a DataFrame, like: 282s 282s df["col"][row_indexer] = value 282s 282s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 282s 282s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 282s 282s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.start.iat[0] = bins_start 283s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 283s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 283s A typical example is when you are setting values in a column of a DataFrame, like: 283s 283s df["col"][row_indexer] = value 283s 283s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 283s 283s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 283s 283s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.start.iat[0] = bins_start 284s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 284s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 284s A typical example is when you are setting values in a column of a DataFrame, like: 284s 284s df["col"][row_indexer] = value 284s 284s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 284s 284s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 284s 284s segments.end.iat[-1] = bins_end 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.start.iat[0] = bins_start 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.end.iat[-1] = bins_end 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.start.iat[0] = bins_start 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.end.iat[-1] = bins_end 285s Dropped 6 / 49 bins on chromosome chrY 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.start.iat[0] = bins_start 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.end.iat[-1] = bins_end 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.start.iat[0] = bins_start 285s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 285s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 285s A typical example is when you are setting values in a column of a DataFrame, like: 285s 285s df["col"][row_indexer] = value 285s 285s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 285s 285s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 285s 285s segments.end.iat[-1] = bins_end 285s Wrote build/p2-20_1.cns with 121 regions 285s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-20_2.cnr -o build/p2-20_2.cns 287s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.start.iat[0] = bins_start 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.end.iat[-1] = bins_end 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.start.iat[0] = bins_start 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.end.iat[-1] = bins_end 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.start.iat[0] = bins_start 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.end.iat[-1] = bins_end 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.start.iat[0] = bins_start 287s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 287s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 287s A typical example is when you are setting values in a column of a DataFrame, like: 287s 287s df["col"][row_indexer] = value 287s 287s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 287s 287s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 287s 287s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.start.iat[0] = bins_start 288s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 288s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 288s A typical example is when you are setting values in a column of a DataFrame, like: 288s 288s df["col"][row_indexer] = value 288s 288s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 288s 288s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 288s 288s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.start.iat[0] = bins_start 289s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 289s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 289s A typical example is when you are setting values in a column of a DataFrame, like: 289s 289s df["col"][row_indexer] = value 289s 289s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 289s 289s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 289s 289s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.start.iat[0] = bins_start 290s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 290s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 290s A typical example is when you are setting values in a column of a DataFrame, like: 290s 290s df["col"][row_indexer] = value 290s 290s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 290s 290s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 290s 290s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.start.iat[0] = bins_start 291s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 291s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 291s A typical example is when you are setting values in a column of a DataFrame, like: 291s 291s df["col"][row_indexer] = value 291s 291s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 291s 291s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 291s 291s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.start.iat[0] = bins_start 292s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 292s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 292s A typical example is when you are setting values in a column of a DataFrame, like: 292s 292s df["col"][row_indexer] = value 292s 292s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 292s 292s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 292s 292s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s Dropped 7 / 49 bins on chromosome chrY 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.start.iat[0] = bins_start 293s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 293s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 293s A typical example is when you are setting values in a column of a DataFrame, like: 293s 293s df["col"][row_indexer] = value 293s 293s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 293s 293s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 293s 293s segments.end.iat[-1] = bins_end 293s Wrote build/p2-20_2.cns with 117 regions 293s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-20_3.cnr -o build/p2-20_3.cns 295s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 295s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 295s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 295s A typical example is when you are setting values in a column of a DataFrame, like: 295s 295s df["col"][row_indexer] = value 295s 295s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 295s 295s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 295s 295s segments.start.iat[0] = bins_start 295s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 295s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 295s A typical example is when you are setting values in a column of a DataFrame, like: 295s 295s df["col"][row_indexer] = value 295s 295s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 295s 295s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 295s 295s segments.end.iat[-1] = bins_end 295s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 295s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 295s A typical example is when you are setting values in a column of a DataFrame, like: 295s 295s df["col"][row_indexer] = value 295s 295s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 295s 295s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 295s 295s segments.start.iat[0] = bins_start 295s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 295s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 295s A typical example is when you are setting values in a column of a DataFrame, like: 295s 295s df["col"][row_indexer] = value 295s 295s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 295s 295s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 295s 295s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.start.iat[0] = bins_start 296s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 296s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 296s A typical example is when you are setting values in a column of a DataFrame, like: 296s 296s df["col"][row_indexer] = value 296s 296s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 296s 296s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 296s 296s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.start.iat[0] = bins_start 297s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 297s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 297s A typical example is when you are setting values in a column of a DataFrame, like: 297s 297s df["col"][row_indexer] = value 297s 297s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 297s 297s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 297s 297s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.start.iat[0] = bins_start 298s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 298s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 298s A typical example is when you are setting values in a column of a DataFrame, like: 298s 298s df["col"][row_indexer] = value 298s 298s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 298s 298s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 298s 298s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.start.iat[0] = bins_start 299s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 299s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 299s A typical example is when you are setting values in a column of a DataFrame, like: 299s 299s df["col"][row_indexer] = value 299s 299s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 299s 299s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 299s 299s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.start.iat[0] = bins_start 300s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 300s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 300s A typical example is when you are setting values in a column of a DataFrame, like: 300s 300s df["col"][row_indexer] = value 300s 300s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 300s 300s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 300s 300s segments.end.iat[-1] = bins_end 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s Dropped 11 / 49 bins on chromosome chrY 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.start.iat[0] = bins_start 301s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 301s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 301s A typical example is when you are setting values in a column of a DataFrame, like: 301s 301s df["col"][row_indexer] = value 301s 301s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 301s 301s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 301s 301s segments.end.iat[-1] = bins_end 301s Wrote build/p2-20_3.cns with 64 regions 301s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-20_4.cnr -o build/p2-20_4.cns 303s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.start.iat[0] = bins_start 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.end.iat[-1] = bins_end 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.start.iat[0] = bins_start 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.end.iat[-1] = bins_end 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.start.iat[0] = bins_start 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.end.iat[-1] = bins_end 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.start.iat[0] = bins_start 303s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 303s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 303s A typical example is when you are setting values in a column of a DataFrame, like: 303s 303s df["col"][row_indexer] = value 303s 303s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 303s 303s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 303s 303s segments.end.iat[-1] = bins_end 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.start.iat[0] = bins_start 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.end.iat[-1] = bins_end 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.start.iat[0] = bins_start 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.end.iat[-1] = bins_end 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.start.iat[0] = bins_start 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.end.iat[-1] = bins_end 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.start.iat[0] = bins_start 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.end.iat[-1] = bins_end 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.start.iat[0] = bins_start 304s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 304s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 304s A typical example is when you are setting values in a column of a DataFrame, like: 304s 304s df["col"][row_indexer] = value 304s 304s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 304s 304s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 304s 304s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.start.iat[0] = bins_start 305s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 305s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 305s A typical example is when you are setting values in a column of a DataFrame, like: 305s 305s df["col"][row_indexer] = value 305s 305s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 305s 305s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 305s 305s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.start.iat[0] = bins_start 306s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 306s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 306s A typical example is when you are setting values in a column of a DataFrame, like: 306s 306s df["col"][row_indexer] = value 306s 306s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 306s 306s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 306s 306s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.start.iat[0] = bins_start 307s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 307s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 307s A typical example is when you are setting values in a column of a DataFrame, like: 307s 307s df["col"][row_indexer] = value 307s 307s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 307s 307s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 307s 307s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.start.iat[0] = bins_start 308s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 308s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 308s A typical example is when you are setting values in a column of a DataFrame, like: 308s 308s df["col"][row_indexer] = value 308s 308s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 308s 308s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 308s 308s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.start.iat[0] = bins_start 309s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 309s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 309s A typical example is when you are setting values in a column of a DataFrame, like: 309s 309s df["col"][row_indexer] = value 309s 309s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 309s 309s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 309s 309s segments.end.iat[-1] = bins_end 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.start.iat[0] = bins_start 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.end.iat[-1] = bins_end 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.start.iat[0] = bins_start 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.end.iat[-1] = bins_end 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.start.iat[0] = bins_start 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.end.iat[-1] = bins_end 310s Dropped 8 / 49 bins on chromosome chrY 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.start.iat[0] = bins_start 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.end.iat[-1] = bins_end 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.start.iat[0] = bins_start 310s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 310s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 310s A typical example is when you are setting values in a column of a DataFrame, like: 310s 310s df["col"][row_indexer] = value 310s 310s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 310s 310s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 310s 310s segments.end.iat[-1] = bins_end 310s Wrote build/p2-20_4.cns with 143 regions 310s cnvkit.py segment --rscript-path Rscript -p 2 --drop-low-coverage -t .01 build/p2-20_5.cnr -o build/p2-20_5.cns 312s Segmenting with method 'cbs', significance threshold 0.01, in 2 processes 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.start.iat[0] = bins_start 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.end.iat[-1] = bins_end 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.start.iat[0] = bins_start 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.end.iat[-1] = bins_end 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.start.iat[0] = bins_start 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.end.iat[-1] = bins_end 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.start.iat[0] = bins_start 312s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 312s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 312s A typical example is when you are setting values in a column of a DataFrame, like: 312s 312s df["col"][row_indexer] = value 312s 312s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 312s 312s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 312s 312s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.start.iat[0] = bins_start 313s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 313s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 313s A typical example is when you are setting values in a column of a DataFrame, like: 313s 313s df["col"][row_indexer] = value 313s 313s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 313s 313s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 313s 313s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.start.iat[0] = bins_start 314s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 314s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 314s A typical example is when you are setting values in a column of a DataFrame, like: 314s 314s df["col"][row_indexer] = value 314s 314s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 314s 314s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 314s 314s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.start.iat[0] = bins_start 315s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 315s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 315s A typical example is when you are setting values in a column of a DataFrame, like: 315s 315s df["col"][row_indexer] = value 315s 315s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 315s 315s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 315s 315s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.start.iat[0] = bins_start 316s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 316s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 316s A typical example is when you are setting values in a column of a DataFrame, like: 316s 316s df["col"][row_indexer] = value 316s 316s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 316s 316s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 316s 316s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.start.iat[0] = bins_start 317s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 317s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 317s A typical example is when you are setting values in a column of a DataFrame, like: 317s 317s df["col"][row_indexer] = value 317s 317s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 317s 317s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 317s 317s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s Smoothing overshot at 1 / 123 indices: (-0.30060035404086427, 0.3250888018519485) vs. original (-0.363302, 0.311218) 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s Dropped 6 / 49 bins on chromosome chrY 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.start.iat[0] = bins_start 318s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 318s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 318s A typical example is when you are setting values in a column of a DataFrame, like: 318s 318s df["col"][row_indexer] = value 318s 318s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 318s 318s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 318s 318s segments.end.iat[-1] = bins_end 318s Wrote build/p2-20_5.cns with 120 regions 319s cnvkit.py scatter -s build/p2-5_5.cns build/p2-5_5.cnr -t --y-min=-2.5 -o p2-5_5-scatter.pdf 322s Wrote p2-5_5-scatter.pdf 322s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -t --y-min=-2.5 -o p2-9_2-scatter.pdf 324s Smoothing overshot at 3 / 97 indices: (-19.900105868621704, -3.3099069223720528) vs. original (-19.294, -0.16431) 325s Wrote p2-9_2-scatter.pdf 325s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -c chr1 -t -o p2-9_2-chr1-scatter.pdf 327s Showing 1480 probes and 0 selected genes in region chr1 327s Wrote p2-9_2-chr1-scatter.pdf 327s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -c chr21 -t -o p2-9_2-chr21-scatter.pdf 329s Showing 201 probes and 0 selected genes in region chr21 329s Wrote p2-9_2-chr21-scatter.pdf 329s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -c 'chr9:150000-45000000' -o p2-9_2-chr9p-scatter.pdf 331s Showing 330 probes and 13 selected genes in region chr9:149999-45000000 331s Wrote p2-9_2-chr9p-scatter.pdf 331s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -g SMARCA2,PTPRD -w 4e6 -o p2-9_2-SMARCA2-PTPRD-scatter.pdf 333s Showing 179 probes and 2 selected genes in region chr9:0-14504268.0 333s Wrote p2-9_2-SMARCA2-PTPRD-scatter.pdf 333s cnvkit.py scatter -s build/p2-9_2.cns build/p2-9_2.cnr -l regions.bed -o p2-9_2-bed_regions-scatter.pdf 334s Detected file format: bed 334s Showing 41 probes and 1 selected genes in region chr9:2000000-4000000 335s Showing 53 probes and 1 selected genes in region chr9:8000000-12000000 335s which pdfunite && pdfunite p2-5_5-scatter.pdf p2-9_2-scatter.pdf p2-9_2-chr1-scatter.pdf p2-9_2-chr21-scatter.pdf p2-9_2-chr9p-scatter.pdf p2-9_2-SMARCA2-PTPRD-scatter.pdf p2-9_2-bed_regions-scatter.pdf all-scatters.pdf || touch all-scatters.pdf 335s /usr/bin/pdfunite 335s cnvkit.py diagram -y build/p2-5_5.cnr -o p2-5_5-diagram.pdf 336s Treating sample p2-5_5 as female 346s Wrote p2-5_5-diagram.pdf 347s cnvkit.py diagram -y build/p2-9_2.cnr -o p2-9_2-diagram.pdf 348s Treating sample p2-9_2 as female 358s Wrote p2-9_2-diagram.pdf 358s cnvkit.py diagram -y build/p2-20_1.cnr -o p2-20_1-diagram.pdf 360s Treating sample p2-20_1 as female 370s Wrote p2-20_1-diagram.pdf 370s cnvkit.py diagram -y build/p2-20_2.cnr -o p2-20_2-diagram.pdf 371s Treating sample p2-20_2 as female 381s Wrote p2-20_2-diagram.pdf 382s cnvkit.py diagram -y --segment=build/p2-5_5.cns -o p2-5_5-cbs-diagram.pdf 383s Treating sample p2-5_5 as female 383s Wrote p2-5_5-cbs-diagram.pdf 383s cnvkit.py diagram -y --segment=build/p2-9_2.cns -o p2-9_2-cbs-diagram.pdf 385s Treating sample p2-9_2 as female 385s Wrote p2-9_2-cbs-diagram.pdf 385s cnvkit.py diagram -y --segment=build/p2-20_1.cns -o p2-20_1-cbs-diagram.pdf 386s Treating sample p2-20_1 as female 387s Wrote p2-20_1-cbs-diagram.pdf 387s cnvkit.py diagram -y --segment=build/p2-20_2.cns -o p2-20_2-cbs-diagram.pdf 388s Treating sample p2-20_2 as female 388s Wrote p2-20_2-cbs-diagram.pdf 389s cnvkit.py diagram -y --segment=build/p2-5_5.cns build/p2-5_5.cnr -t 0.3 -o p2-5_5-both-diagram.pdf 390s Treating sample p2-5_5 as female 396s Wrote p2-5_5-both-diagram.pdf 397s cnvkit.py diagram -y --segment=build/p2-9_2.cns build/p2-9_2.cnr -t 0.3 -o p2-9_2-both-diagram.pdf 398s Treating sample p2-9_2 as female 405s Wrote p2-9_2-both-diagram.pdf 405s cnvkit.py diagram -y --segment=build/p2-20_1.cns build/p2-20_1.cnr -t 0.3 -o p2-20_1-both-diagram.pdf 406s Treating sample p2-20_1 as female 413s Wrote p2-20_1-both-diagram.pdf 413s cnvkit.py diagram -y --segment=build/p2-20_2.cns build/p2-20_2.cnr -t 0.3 -o p2-20_2-both-diagram.pdf 415s Treating sample p2-20_2 as female 421s Wrote p2-20_2-both-diagram.pdf 421s which pdfunite && pdfunite p2-5_5-diagram.pdf p2-9_2-diagram.pdf p2-20_1-diagram.pdf p2-20_2-diagram.pdf p2-5_5-cbs-diagram.pdf p2-9_2-cbs-diagram.pdf p2-20_1-cbs-diagram.pdf p2-20_2-cbs-diagram.pdf p2-5_5-both-diagram.pdf p2-9_2-both-diagram.pdf p2-20_1-both-diagram.pdf p2-20_2-both-diagram.pdf all-diagrams.pdf || touch all-diagrams.pdf 421s /usr/bin/pdfunite 421s cnvkit.py heatmap build/p2-5_5.cns build/p2-9_2.cns build/p2-20_1.cns build/p2-20_2.cns build/p2-20_3.cns build/p2-20_4.cns build/p2-20_5.cns -y -o heatmap-picard.pdf 423s Treating sample p2-5_5 as female 423s Treating sample p2-9_2 as female 423s Treating sample p2-20_1 as female 423s Treating sample p2-20_2 as female 423s Treating sample p2-20_3 as female 423s Treating sample p2-20_4 as female 423s Treating sample p2-20_5 as female 425s Wrote heatmap-picard.pdf 425s cnvkit.py breaks build/p2-9_2.cnr build/p2-9_2.cns -o p2-9_2-breaks.txt 427s Found 14 gene breakpoints 427s Wrote p2-9_2-breaks.txt 427s cnvkit.py genemetrics -y -m 2 -s build/p2-9_2.cns build/p2-9_2.cnr -o p2-9_2-genemetrics.txt 428s Treating sample p2-9_2 as female 430s Found 323 gene-level gains and losses 430s Wrote p2-9_2-genemetrics.txt 430s cnvkit.py sex -y build/p2-5_5.cnr build/p2-5_5.cns build/p2-9_2.cnr build/p2-9_2.cns build/p2-20_5.cnr build/p2-20_5.cns -o gender-picard.txt 432s Wrote gender-picard.txt 432s cnvkit.py export cdt build/p2-5_5.cnr build/p2-9_2.cnr build/p2-20_1.cnr build/p2-20_2.cnr build/p2-20_3.cnr build/p2-20_4.cnr build/p2-20_5.cnr -o p2-all.cdt 438s Wrote p2-all.cdt 438s cnvkit.py export jtv build/p2-5_5.cnr build/p2-9_2.cnr build/p2-20_1.cnr build/p2-20_2.cnr build/p2-20_3.cnr build/p2-20_4.cnr build/p2-20_5.cnr -o p2-all-jtv.txt 445s Wrote p2-all-jtv.txt 445s cnvkit.py export seg build/p2-5_5.cns build/p2-9_2.cns build/p2-20_1.cns build/p2-20_2.cns build/p2-20_3.cns build/p2-20_4.cns build/p2-20_5.cns -o p2-all.seg 446s Wrote p2-all.seg 447s cnvkit.py export nexus-basic build/p2-9_2.cnr -o p2-9_2.nexus 449s Wrote p2-9_2.nexus 449s cnvkit.py export nexus-ogt build/p2-9_2.cnr formats/na12878_na12882_mix.vcf -o p2-9_2.nexus-ogt 450s Selected test sample NA12882 and control sample NA12878 450s Loaded 3654 records; skipped: 514 somatic, 394 depth 450s Kept 2631 heterozygous of 3654 VCF records 454s Placed 705 variants into 18763 bins 454s Wrote p2-9_2.nexus-ogt 454s cnvkit.py call build/p2-5_5.cns -y -m clonal --purity 0.65 -o build/p2-5_5.call.cns 455s Treating sample p2-5_5 as female 455s Rescaling sample with purity 0.65, ploidy 2 455s Wrote build/p2-5_5.call.cns with 71 regions 456s cnvkit.py call build/p2-9_2.cns -y -m clonal --purity 0.65 -o build/p2-9_2.call.cns 457s Treating sample p2-9_2 as female 457s Rescaling sample with purity 0.65, ploidy 2 457s Wrote build/p2-9_2.call.cns with 103 regions 457s cnvkit.py call build/p2-20_1.cns -y -m clonal --purity 0.65 -o build/p2-20_1.call.cns 459s Treating sample p2-20_1 as female 459s Rescaling sample with purity 0.65, ploidy 2 459s Wrote build/p2-20_1.call.cns with 121 regions 459s cnvkit.py call build/p2-20_2.cns -y -m clonal --purity 0.65 -o build/p2-20_2.call.cns 460s Treating sample p2-20_2 as female 460s Rescaling sample with purity 0.65, ploidy 2 460s Wrote build/p2-20_2.call.cns with 117 regions 460s cnvkit.py call build/p2-20_3.cns -y -m clonal --purity 0.65 -o build/p2-20_3.call.cns 462s Treating sample p2-20_3 as female 462s Rescaling sample with purity 0.65, ploidy 2 462s Wrote build/p2-20_3.call.cns with 64 regions 462s cnvkit.py call build/p2-20_4.cns -y -m clonal --purity 0.65 -o build/p2-20_4.call.cns 463s Treating sample p2-20_4 as female 463s Rescaling sample with purity 0.65, ploidy 2 463s Wrote build/p2-20_4.call.cns with 143 regions 464s cnvkit.py call build/p2-20_5.cns -y -m clonal --purity 0.65 -o build/p2-20_5.call.cns 465s Treating sample p2-20_5 as female 465s Rescaling sample with purity 0.65, ploidy 2 465s Wrote build/p2-20_5.call.cns with 120 regions 465s cnvkit.py export bed build/p2-5_5.call.cns build/p2-9_2.call.cns build/p2-20_1.call.cns build/p2-20_2.call.cns build/p2-20_3.call.cns build/p2-20_4.call.cns build/p2-20_5.call.cns -y --show variant -o p2-all.bed 467s Treating sample p2-5_5.call as female 467s Treating sample p2-9_2.call as female 467s Treating sample p2-20_1.call as female 467s Treating sample p2-20_2.call as female 467s Treating sample p2-20_3.call as female 467s Treating sample p2-20_4.call as female 467s Treating sample p2-20_5.call as female 467s Wrote p2-all.bed 467s cnvkit.py export vcf -o p2-9_2.vcf -y --cnr build/p2-9_2.cnr build/p2-9_2.call.cns -y -o p2-9_2.vcf 468s Treating sample p2-9_2.call as female 469s Wrote p2-9_2.vcf 469s cnvkit.py export theta build/p2-9_2.cns -r build/reference-picard.cnn -o p2-9_2.theta2.input 470s Wrote p2-9_2.theta2.input 471s cnvkit.py segmetrics -s build/p2-9_2.cns build/p2-9_2.cnr -o p2-9_2-segmetrics.cns \ 471s --mean --median --mode --t-test \ 471s --stdev --mad --mse --iqr --bivar \ 471s --ci --pi --sem --smooth-bootstrap 473s Wrote p2-9_2-segmetrics.cns with 103 regions 473s cnvkit.py segmetrics -s build/p2-5_5.cns build/p2-5_5.cnr -o p2-5_5-segmetrics.cns \ 473s --ci -b 50 -a 0.5 475s Wrote p2-5_5-segmetrics.cns with 71 regions 475s cnvkit.py metrics build/p2-5_5.cnr -s build/p2-5_5.cns -o p2-5_5-metrics.tsv 476s Wrote p2-5_5-metrics.tsv 477s cnvkit.py metrics build/p2-9_2.cnr -s build/p2-9_2.cns -o p2-9_2-metrics.tsv 478s Wrote p2-9_2-metrics.tsv 478s cnvkit.py metrics build/p2-20_1.cnr build/p2-20_2.cnr build/p2-20_3.cnr build/p2-20_4.cnr build/p2-20_5.cnr -s build/p2-20_1.cns build/p2-20_2.cns build/p2-20_3.cns build/p2-20_4.cns build/p2-20_5.cns -o p2-20-metrics.tsv 480s Wrote p2-20-metrics.tsv 481s PASS 481s autopkgtest [13:14:39]: test run-unit-test: -----------------------] 482s run-unit-test PASS 482s autopkgtest [13:14:40]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 482s autopkgtest [13:14:40]: test pybuild-autopkgtest: preparing testbed 490s Creating nova instance adt-resolute-ppc64el-cnvkit-20251117-130637-juju-7f2275-prod-proposed-migration-environment-2-fa732215-0de0-4013-80e1-79492d6d8cdc from image adt/ubuntu-resolute-ppc64el-server-20251117.img (UUID c6f5b741-c77a-45db-84cb-f00b40e77676)... 550s autopkgtest [13:15:48]: testbed dpkg architecture: ppc64el 550s autopkgtest [13:15:48]: testbed apt version: 3.1.11 551s autopkgtest [13:15:49]: @@@@@@@@@@@@@@@@@@@@ test bed setup 551s autopkgtest [13:15:49]: testbed release detected to be: resolute 552s autopkgtest [13:15:50]: updating testbed package index (apt update) 552s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [87.8 kB] 552s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 552s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 552s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 552s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [868 kB] 553s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [81.1 kB] 553s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/restricted Sources [9848 B] 553s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [22.9 kB] 553s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el Packages [140 kB] 553s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted ppc64el Packages [940 B] 553s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el Packages [562 kB] 553s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse ppc64el Packages [11.0 kB] 553s Fetched 1784 kB in 1s (1606 kB/s) 554s Reading package lists... 555s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 555s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 555s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 555s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 556s Reading package lists... 556s Reading package lists... 556s Building dependency tree... 556s Reading state information... 556s Calculating upgrade... 556s The following packages will be upgraded: 556s libpython3-stdlib python3 python3-minimal usbutils 556s 4 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 556s Need to get 154 kB of archives. 556s After this operation, 0 B of additional disk space will be used. 556s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el python3-minimal ppc64el 3.13.7-2 [27.8 kB] 557s Get:2 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el python3 ppc64el 3.13.7-2 [23.9 kB] 557s Get:3 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el libpython3-stdlib ppc64el 3.13.7-2 [10.6 kB] 557s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el usbutils ppc64el 1:019-1 [91.5 kB] 557s dpkg-preconfigure: unable to re-open stdin: No such file or directory 557s Fetched 154 kB in 0s (378 kB/s) 557s (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 ... 81022 files and directories currently installed.) 557s Preparing to unpack .../python3-minimal_3.13.7-2_ppc64el.deb ... 557s Unpacking python3-minimal (3.13.7-2) over (3.13.7-1) ... 557s Setting up python3-minimal (3.13.7-2) ... 558s (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 ... 81022 files and directories currently installed.) 558s Preparing to unpack .../python3_3.13.7-2_ppc64el.deb ... 558s running python pre-rtupdate hooks for python3.13... 558s Unpacking python3 (3.13.7-2) over (3.13.7-1) ... 558s Preparing to unpack .../libpython3-stdlib_3.13.7-2_ppc64el.deb ... 558s Unpacking libpython3-stdlib:ppc64el (3.13.7-2) over (3.13.7-1) ... 558s Preparing to unpack .../usbutils_1%3a019-1_ppc64el.deb ... 558s Unpacking usbutils (1:019-1) over (1:018-2) ... 558s Setting up usbutils (1:019-1) ... 558s Setting up libpython3-stdlib:ppc64el (3.13.7-2) ... 558s Setting up python3 (3.13.7-2) ... 558s running python rtupdate hooks for python3.13... 558s running python post-rtupdate hooks for python3.13... 558s Processing triggers for man-db (2.13.1-1) ... 560s autopkgtest [13:15:58]: upgrading testbed (apt dist-upgrade and autopurge) 560s Reading package lists... 560s Building dependency tree... 560s Reading state information... 560s Calculating upgrade... 560s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 561s Reading package lists... 561s Building dependency tree... 561s Reading state information... 561s Solving dependencies... 561s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 564s Reading package lists... 564s Building dependency tree... 564s Reading state information... 564s Solving dependencies... 564s The following NEW packages will be installed: 564s autoconf automake autopoint autotools-dev blt build-essential cnvkit cpp 564s cpp-15 cpp-15-powerpc64le-linux-gnu cpp-powerpc64le-linux-gnu cython3 564s debhelper debugedit dh-autoreconf dh-python dh-strip-nondeterminism dwz 564s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono fonts-lyx 564s fonts-urw-base35 g++ g++-15 g++-15-powerpc64le-linux-gnu 564s g++-powerpc64le-linux-gnu gcc gcc-15 gcc-15-powerpc64le-linux-gnu 564s gcc-powerpc64le-linux-gnu gettext intltool-debian libarchive-zip-perl 564s libasan8 libblas3 libcairo2 libcc1-0 libdatrie1 libdebhelper-perl 564s libdeflate0 libfile-stripnondeterminism-perl libfontconfig1 libfontenc1 564s libgcc-15-dev libgfortran5 libgomp1 libgpgmepp6t64 libgraphite2-3 564s libharfbuzz0b libhts3t64 libhtscodecs2 libice6 libimagequant0 libisl23 564s libitm1 libjbig0 libjpeg-turbo8 libjpeg8 liblapack3 liblcms2-2 liblerc4 564s liblsan0 libmpc3 libopenjp2-7 libpango-1.0-0 libpangocairo-1.0-0 564s libpangoft2-1.0-0 libpaper-utils libpaper2 libpixman-1-0 libpoppler147 564s libpython3.14-minimal libpython3.14-stdlib libqhull-r8.0 libquadmath0 564s libraqm0 libsharpyuv0 libsm6 libstdc++-15-dev libtcl8.6 libthai-data 564s libthai0 libtiff6 libtk8.6 libtool libtsan2 libubsan1 libwebp7 libwebpdemux2 564s libwebpmux3 libxcb-render0 libxcb-shm0 libxft2 libxrender1 libxslt1.1 564s libxss1 libxt6t64 libzopfli1 m4 po-debconf poppler-utils 564s pybuild-plugin-autopkgtest pybuild-plugin-pyproject python-matplotlib-data 564s python3-all python3-biopython python3-brotli python3-build python3-cairo 564s python3-charset-normalizer python3-contourpy python3-cycler 564s python3-decorator python3-fonttools python3-freetype python3-fs 564s python3-iniconfig python3-installer python3-joblib python3-kiwisolver 564s python3-lxml python3-lz4 python3-matplotlib python3-mpmath python3-networkx 564s python3-numpy python3-numpy-dev python3-pandas python3-pandas-lib 564s python3-pil python3-pil.imagetk python3-platformdirs python3-pluggy 564s python3-pomegranate python3-pyfaidx python3-pyproject-hooks python3-pysam 564s python3-pytest python3-pytz python3-reportlab python3-rlpycairo 564s python3-scipy python3-sklearn python3-sklearn-lib python3-sympy 564s python3-threadpoolctl python3-tk python3-ufolib2 python3-wheel 564s python3-zopfli python3.13-tk python3.14 python3.14-minimal python3.14-tk 564s r-base-core r-bioc-biocgenerics r-bioc-dnacopy sgml-base tk8.6-blt2.5 564s unicode-data unzip w3c-sgml-lib x11-common xdg-utils xfonts-encodings 564s xfonts-utils xml-core zip 564s 0 upgraded, 170 newly installed, 0 to remove and 0 not upgraded. 564s Need to get 269 MB of archives. 564s After this operation, 1208 MB of additional disk space will be used. 564s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-numpy-dev ppc64el 1:2.2.4+ds-1ubuntu1 [153 kB] 565s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el libblas3 ppc64el 3.12.1-7 [291 kB] 565s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgfortran5 ppc64el 15.2.0-7ubuntu1 [620 kB] 565s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblapack3 ppc64el 3.12.1-7 [2960 kB] 566s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-numpy ppc64el 1:2.2.4+ds-1ubuntu1 [4887 kB] 566s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpython3.14-minimal ppc64el 3.14.0-4 [908 kB] 566s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.14-minimal ppc64el 3.14.0-4 [2705 kB] 566s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el m4 ppc64el 1.4.20-2 [236 kB] 566s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el autoconf all 2.72-3.1ubuntu1 [384 kB] 567s Get:10 http://ftpmaster.internal/ubuntu resolute/main ppc64el autotools-dev all 20240727.1 [43.4 kB] 567s Get:11 http://ftpmaster.internal/ubuntu resolute/main ppc64el automake all 1:1.18.1-2 [581 kB] 567s Get:12 http://ftpmaster.internal/ubuntu resolute/main ppc64el autopoint all 0.23.2-1 [620 kB] 567s Get:13 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtcl8.6 ppc64el 8.6.17+dfsg-1 [1239 kB] 567s Get:14 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-mono all 2.37-8 [502 kB] 567s Get:15 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-core all 2.37-8 [835 kB] 567s Get:16 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontenc1 ppc64el 1:1.1.8-1build1 [15.8 kB] 567s Get:17 http://ftpmaster.internal/ubuntu resolute/main ppc64el x11-common all 1:7.7+24ubuntu1 [22.4 kB] 567s Get:18 http://ftpmaster.internal/ubuntu resolute/main ppc64el xfonts-encodings all 1:1.0.5-0ubuntu2 [578 kB] 567s Get:19 http://ftpmaster.internal/ubuntu resolute/main ppc64el xfonts-utils ppc64el 1:7.7+7 [114 kB] 567s Get:20 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-urw-base35 all 20200910-8 [11.0 MB] 567s Get:21 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig-config ppc64el 2.15.0-2.3ubuntu1 [38.1 kB] 567s Get:22 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontconfig1 ppc64el 2.15.0-2.3ubuntu1 [188 kB] 567s Get:23 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxrender1 ppc64el 1:0.9.12-1 [23.0 kB] 567s Get:24 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxft2 ppc64el 2.3.6-1build1 [61.5 kB] 567s Get:25 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxss1 ppc64el 1:1.2.3-1build3 [7980 B] 567s Get:26 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtk8.6 ppc64el 8.6.17-1 [968 kB] 567s Get:27 http://ftpmaster.internal/ubuntu resolute/main ppc64el tk8.6-blt2.5 ppc64el 2.5.3+dfsg-8 [778 kB] 567s Get:28 http://ftpmaster.internal/ubuntu resolute/main ppc64el blt ppc64el 2.5.3+dfsg-8 [4830 B] 567s Get:29 http://ftpmaster.internal/ubuntu resolute/main ppc64el libisl23 ppc64el 0.27-1 [882 kB] 568s Get:30 http://ftpmaster.internal/ubuntu resolute/main ppc64el libmpc3 ppc64el 1.3.1-2 [62.5 kB] 568s Get:31 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-15-powerpc64le-linux-gnu ppc64el 15.2.0-7ubuntu1 [11.4 MB] 568s Get:32 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-15 ppc64el 15.2.0-7ubuntu1 [1032 B] 568s Get:33 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [5746 B] 568s Get:34 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp ppc64el 4:15.2.0-4ubuntu1 [22.4 kB] 568s Get:35 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcc1-0 ppc64el 15.2.0-7ubuntu1 [49.0 kB] 568s Get:36 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgomp1 ppc64el 15.2.0-7ubuntu1 [169 kB] 568s Get:37 http://ftpmaster.internal/ubuntu resolute/main ppc64el libitm1 ppc64el 15.2.0-7ubuntu1 [32.3 kB] 568s Get:38 http://ftpmaster.internal/ubuntu resolute/main ppc64el libasan8 ppc64el 15.2.0-7ubuntu1 [3006 kB] 568s Get:39 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblsan0 ppc64el 15.2.0-7ubuntu1 [1374 kB] 568s Get:40 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtsan2 ppc64el 15.2.0-7ubuntu1 [2728 kB] 568s Get:41 http://ftpmaster.internal/ubuntu resolute/main ppc64el libubsan1 ppc64el 15.2.0-7ubuntu1 [1231 kB] 568s Get:42 http://ftpmaster.internal/ubuntu resolute/main ppc64el libquadmath0 ppc64el 15.2.0-7ubuntu1 [160 kB] 568s Get:43 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgcc-15-dev ppc64el 15.2.0-7ubuntu1 [1670 kB] 568s Get:44 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-15-powerpc64le-linux-gnu ppc64el 15.2.0-7ubuntu1 [22.4 MB] 569s Get:45 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-15 ppc64el 15.2.0-7ubuntu1 [524 kB] 569s Get:46 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [1220 B] 569s Get:47 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc ppc64el 4:15.2.0-4ubuntu1 [5032 B] 569s Get:48 http://ftpmaster.internal/ubuntu resolute/main ppc64el libstdc++-15-dev ppc64el 15.2.0-7ubuntu1 [2744 kB] 569s Get:49 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-15-powerpc64le-linux-gnu ppc64el 15.2.0-7ubuntu1 [13.0 MB] 569s Get:50 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-15 ppc64el 15.2.0-7ubuntu1 [23.7 kB] 569s Get:51 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [970 B] 569s Get:52 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++ ppc64el 4:15.2.0-4ubuntu1 [1092 B] 569s Get:53 http://ftpmaster.internal/ubuntu resolute/main ppc64el build-essential ppc64el 12.12ubuntu1 [5094 B] 569s Get:54 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-charset-normalizer ppc64el 3.4.3-1 [174 kB] 569s Get:55 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.14-tk ppc64el 3.14.0-4 [109 kB] 569s Get:56 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.13-tk ppc64el 3.13.9-1 [108 kB] 569s Get:57 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-tk ppc64el 3.13.9-1 [8948 B] 569s Get:58 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pil.imagetk ppc64el 11.3.0-1ubuntu2 [10.3 kB] 569s Get:59 http://ftpmaster.internal/ubuntu resolute/main ppc64el libimagequant0 ppc64el 2.18.0-1build1 [43.2 kB] 569s Get:60 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-turbo8 ppc64el 2.1.5-4ubuntu2 [215 kB] 569s Get:61 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg8 ppc64el 8c-2ubuntu11 [2148 B] 569s Get:62 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblcms2-2 ppc64el 2.17-1 [246 kB] 569s Get:63 http://ftpmaster.internal/ubuntu resolute/main ppc64el libopenjp2-7 ppc64el 2.5.3-2.1 [251 kB] 569s Get:64 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgraphite2-3 ppc64el 1.3.14-2ubuntu1 [84.6 kB] 569s Get:65 http://ftpmaster.internal/ubuntu resolute/main ppc64el libharfbuzz0b ppc64el 12.1.0-1 [679 kB] 569s Get:66 http://ftpmaster.internal/ubuntu resolute/main ppc64el libraqm0 ppc64el 0.10.3-1 [19.6 kB] 569s Get:67 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdeflate0 ppc64el 1.23-2 [63.3 kB] 569s Get:68 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjbig0 ppc64el 2.1-6.1ubuntu2 [35.9 kB] 569s Get:69 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblerc4 ppc64el 4.0.0+ds-5ubuntu1 [298 kB] 569s Get:70 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsharpyuv0 ppc64el 1.5.0-0.1 [22.3 kB] 569s Get:71 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebp7 ppc64el 1.5.0-0.1 [315 kB] 570s Get:72 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtiff6 ppc64el 4.7.0-3ubuntu3 [307 kB] 570s Get:73 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebpdemux2 ppc64el 1.5.0-0.1 [14.6 kB] 570s Get:74 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebpmux3 ppc64el 1.5.0-0.1 [31.1 kB] 570s Get:75 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-pil ppc64el 11.3.0-1ubuntu2 [654 kB] 570s Get:76 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpixman-1-0 ppc64el 0.46.4-1 [347 kB] 570s Get:77 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-render0 ppc64el 1.17.0-2build1 [17.2 kB] 570s Get:78 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-shm0 ppc64el 1.17.0-2build1 [6078 B] 570s Get:79 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcairo2 ppc64el 1.18.4-1build1 [759 kB] 570s Get:80 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-cairo ppc64el 1.27.0-2build1 [150 kB] 570s Get:81 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-freetype all 2.5.1-2 [92.2 kB] 570s Get:82 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-rlpycairo all 0.3.0-4 [9332 B] 570s Get:83 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-reportlab all 4.4.4-2 [1147 kB] 570s Get:84 http://ftpmaster.internal/ubuntu resolute/main ppc64el sgml-base all 1.31+nmu1 [11.0 kB] 570s Get:85 http://ftpmaster.internal/ubuntu resolute/main ppc64el xml-core all 0.19 [20.3 kB] 570s Get:86 http://ftpmaster.internal/ubuntu resolute/universe ppc64el w3c-sgml-lib all 1.3-3 [280 kB] 570s Get:87 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-biopython ppc64el 1.85+dfsg-4 [1764 kB] 570s Get:88 http://ftpmaster.internal/ubuntu resolute/universe ppc64el fonts-lyx all 2.4.4-2 [171 kB] 570s Get:89 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python-matplotlib-data all 3.10.7+dfsg1-1 [2930 kB] 570s Get:90 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-contourpy ppc64el 1.3.1-2 [274 kB] 570s Get:91 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-cycler all 0.12.1-2 [9850 B] 570s Get:92 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-brotli ppc64el 1.1.0-2build6 [430 kB] 570s Get:93 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-platformdirs all 4.3.7-1 [16.9 kB] 570s Get:94 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-fs all 2.4.16-9ubuntu1 [91.5 kB] 570s Get:95 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxslt1.1 ppc64el 1.1.43-0.3 [190 kB] 570s Get:96 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-lxml ppc64el 6.0.2-1 [2452 kB] 570s Get:97 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-lz4 ppc64el 4.4.4+dfsg-3 [28.9 kB] 570s Get:98 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-decorator all 5.2.1-2 [28.1 kB] 570s Get:99 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-scipy ppc64el 1.15.3-1ubuntu1 [22.0 MB] 570s Get:100 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-mpmath all 1.3.0-2 [423 kB] 570s Get:101 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sympy all 1.14.0-2 [4306 kB] 571s Get:102 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-ufolib2 all 0.17.1+dfsg1-1 [33.5 kB] 571s Get:103 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpython3.14-stdlib ppc64el 3.14.0-4 [2446 kB] 571s Get:104 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3.14 ppc64el 3.14.0-4 [805 kB] 572s Get:105 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el python3-all ppc64el 3.13.7-2 [892 B] 572s Get:106 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libzopfli1 ppc64el 1.0.3-3 [160 kB] 572s Get:107 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-zopfli ppc64el 0.4.0-1 [11.3 kB] 572s Get:108 http://ftpmaster.internal/ubuntu resolute/universe ppc64el unicode-data all 16.0.0-1 [9513 kB] 572s Get:109 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-fonttools ppc64el 4.57.0-2build1 [1745 kB] 572s Get:110 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-kiwisolver ppc64el 1.4.10~rc0-1 [72.4 kB] 572s Get:111 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libqhull-r8.0 ppc64el 2020.2-7 [227 kB] 572s Get:112 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-matplotlib ppc64el 3.10.7+dfsg1-1 [17.2 MB] 572s Get:113 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-pytz all 2025.2-4 [32.3 kB] 572s Get:114 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pandas-lib ppc64el 2.3.3+dfsg-1ubuntu1 [7666 kB] 573s Get:115 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pandas all 2.3.3+dfsg-1ubuntu1 [2948 kB] 573s Get:116 http://ftpmaster.internal/ubuntu resolute/universe ppc64el cython3 ppc64el 3.1.6+dfsg-1ubuntu1 [3539 kB] 573s Get:117 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-joblib all 1.4.2-4 [205 kB] 573s Get:118 http://ftpmaster.internal/ubuntu resolute/main ppc64el python3-networkx all 3.2.1-4ubuntu1 [11.5 MB] 573s Get:119 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pomegranate ppc64el 0.15.0-2 [4794 kB] 573s Get:120 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pyfaidx all 0.8.1.3-2 [29.7 kB] 573s Get:121 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libhtscodecs2 ppc64el 1.6.1-2 [113 kB] 573s Get:122 http://ftpmaster.internal/ubuntu resolute/universe ppc64el libhts3t64 ppc64el 1.22.1+ds2-1 [617 kB] 573s Get:123 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pysam ppc64el 0.23.3+ds-2 [5011 kB] 573s Get:124 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sklearn-lib ppc64el 1.7.2+dfsg-3ubuntu1 [6203 kB] 573s Get:125 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-threadpoolctl all 3.1.0-1 [21.3 kB] 573s Get:126 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-sklearn all 1.7.2+dfsg-3ubuntu1 [2616 kB] 573s Get:127 http://ftpmaster.internal/ubuntu resolute/main ppc64el zip ppc64el 3.0-15ubuntu2 [198 kB] 574s Get:128 http://ftpmaster.internal/ubuntu resolute/main ppc64el unzip ppc64el 6.0-28ubuntu7 [201 kB] 574s Get:129 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper2 ppc64el 2.2.5-0.3 [18.0 kB] 574s Get:130 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper-utils ppc64el 2.2.5-0.3 [15.6 kB] 574s Get:131 http://ftpmaster.internal/ubuntu resolute/main ppc64el xdg-utils all 1.2.1-2ubuntu1 [66.0 kB] 574s Get:132 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig ppc64el 2.15.0-2.3ubuntu1 [192 kB] 574s Get:133 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai-data all 0.1.29-2build1 [158 kB] 574s Get:134 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdatrie1 ppc64el 0.2.13-4 [22.2 kB] 574s Get:135 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai0 ppc64el 0.1.29-2build1 [21.8 kB] 574s Get:136 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpango-1.0-0 ppc64el 1.56.3-2 [281 kB] 574s Get:137 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangoft2-1.0-0 ppc64el 1.56.3-2 [59.1 kB] 574s Get:138 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangocairo-1.0-0 ppc64el 1.56.3-2 [31.0 kB] 574s Get:139 http://ftpmaster.internal/ubuntu resolute/main ppc64el libice6 ppc64el 2:1.1.1-1 [49.9 kB] 574s Get:140 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsm6 ppc64el 2:1.2.6-1 [18.6 kB] 574s Get:141 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxt6t64 ppc64el 1:1.2.1-1.3 [203 kB] 574s Get:142 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-base-core ppc64el 4.5.2-1 [29.3 MB] 574s Get:143 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-biocgenerics all 0.52.0-2 [624 kB] 574s Get:144 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-dnacopy ppc64el 1.80.0-2 [504 kB] 574s Get:145 http://ftpmaster.internal/ubuntu resolute/universe ppc64el cnvkit all 0.9.12-1 [20.6 MB] 575s Get:146 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdebhelper-perl all 13.24.2ubuntu1 [95.7 kB] 575s Get:147 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtool all 2.5.4-7 [169 kB] 575s Get:148 http://ftpmaster.internal/ubuntu resolute/main ppc64el dh-autoreconf all 21 [12.5 kB] 575s Get:149 http://ftpmaster.internal/ubuntu resolute/main ppc64el libarchive-zip-perl all 1.68-1 [90.2 kB] 575s Get:150 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfile-stripnondeterminism-perl all 1.15.0-1 [20.5 kB] 575s Get:151 http://ftpmaster.internal/ubuntu resolute/main ppc64el dh-strip-nondeterminism all 1.15.0-1 [5090 B] 575s Get:152 http://ftpmaster.internal/ubuntu resolute/main ppc64el debugedit ppc64el 1:5.2-3 [57.3 kB] 575s Get:153 http://ftpmaster.internal/ubuntu resolute/main ppc64el dwz ppc64el 0.16-2 [142 kB] 575s Get:154 http://ftpmaster.internal/ubuntu resolute/main ppc64el gettext ppc64el 0.23.2-1 [1177 kB] 575s Get:155 http://ftpmaster.internal/ubuntu resolute/main ppc64el intltool-debian all 0.35.0+20060710.6 [23.2 kB] 575s Get:156 http://ftpmaster.internal/ubuntu resolute/main ppc64el po-debconf all 1.0.21+nmu1 [233 kB] 575s Get:157 http://ftpmaster.internal/ubuntu resolute/main ppc64el debhelper all 13.24.2ubuntu1 [896 kB] 575s Get:158 http://ftpmaster.internal/ubuntu resolute/universe ppc64el dh-python all 6.20250414 [119 kB] 575s Get:159 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgpgmepp6t64 ppc64el 1.24.2-3ubuntu2 [135 kB] 575s Get:160 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpoppler147 ppc64el 25.03.0-11.1 [1442 kB] 575s Get:161 http://ftpmaster.internal/ubuntu resolute/main ppc64el poppler-utils ppc64el 25.03.0-11.1 [250 kB] 575s Get:162 http://ftpmaster.internal/ubuntu resolute/universe ppc64el pybuild-plugin-autopkgtest all 6.20250414 [1746 B] 575s Get:163 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pyproject-hooks all 1.2.0-1 [10.2 kB] 575s Get:164 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-wheel all 0.46.1-2 [22.1 kB] 575s Get:165 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-build all 1.2.2-4 [31.0 kB] 575s Get:166 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-installer all 0.7.0+dfsg1-3 [17.4 kB] 575s Get:167 http://ftpmaster.internal/ubuntu resolute/universe ppc64el pybuild-plugin-pyproject all 6.20250414 [1728 B] 575s Get:168 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-iniconfig all 2.1.0-1 [6840 B] 575s Get:169 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pluggy all 1.6.0-1 [21.0 kB] 575s Get:170 http://ftpmaster.internal/ubuntu resolute/universe ppc64el python3-pytest all 8.3.5-2 [252 kB] 576s Preconfiguring packages ... 576s Fetched 269 MB in 11s (24.6 MB/s) 576s Selecting previously unselected package python3-numpy-dev:ppc64el. 576s (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 ... 81022 files and directories currently installed.) 576s Preparing to unpack .../000-python3-numpy-dev_1%3a2.2.4+ds-1ubuntu1_ppc64el.deb ... 576s Unpacking python3-numpy-dev:ppc64el (1:2.2.4+ds-1ubuntu1) ... 576s Selecting previously unselected package libblas3:ppc64el. 576s Preparing to unpack .../001-libblas3_3.12.1-7_ppc64el.deb ... 576s Unpacking libblas3:ppc64el (3.12.1-7) ... 576s Selecting previously unselected package libgfortran5:ppc64el. 576s Preparing to unpack .../002-libgfortran5_15.2.0-7ubuntu1_ppc64el.deb ... 576s Unpacking libgfortran5:ppc64el (15.2.0-7ubuntu1) ... 576s Selecting previously unselected package liblapack3:ppc64el. 576s Preparing to unpack .../003-liblapack3_3.12.1-7_ppc64el.deb ... 576s Unpacking liblapack3:ppc64el (3.12.1-7) ... 576s Selecting previously unselected package python3-numpy. 576s Preparing to unpack .../004-python3-numpy_1%3a2.2.4+ds-1ubuntu1_ppc64el.deb ... 576s Unpacking python3-numpy (1:2.2.4+ds-1ubuntu1) ... 576s Selecting previously unselected package libpython3.14-minimal:ppc64el. 576s Preparing to unpack .../005-libpython3.14-minimal_3.14.0-4_ppc64el.deb ... 576s Unpacking libpython3.14-minimal:ppc64el (3.14.0-4) ... 576s Selecting previously unselected package python3.14-minimal. 576s Preparing to unpack .../006-python3.14-minimal_3.14.0-4_ppc64el.deb ... 576s Unpacking python3.14-minimal (3.14.0-4) ... 576s Selecting previously unselected package m4. 576s Preparing to unpack .../007-m4_1.4.20-2_ppc64el.deb ... 576s Unpacking m4 (1.4.20-2) ... 576s Selecting previously unselected package autoconf. 576s Preparing to unpack .../008-autoconf_2.72-3.1ubuntu1_all.deb ... 576s Unpacking autoconf (2.72-3.1ubuntu1) ... 576s Selecting previously unselected package autotools-dev. 576s Preparing to unpack .../009-autotools-dev_20240727.1_all.deb ... 576s Unpacking autotools-dev (20240727.1) ... 576s Selecting previously unselected package automake. 576s Preparing to unpack .../010-automake_1%3a1.18.1-2_all.deb ... 576s Unpacking automake (1:1.18.1-2) ... 576s Selecting previously unselected package autopoint. 576s Preparing to unpack .../011-autopoint_0.23.2-1_all.deb ... 576s Unpacking autopoint (0.23.2-1) ... 576s Selecting previously unselected package libtcl8.6:ppc64el. 576s Preparing to unpack .../012-libtcl8.6_8.6.17+dfsg-1_ppc64el.deb ... 576s Unpacking libtcl8.6:ppc64el (8.6.17+dfsg-1) ... 576s Selecting previously unselected package fonts-dejavu-mono. 576s Preparing to unpack .../013-fonts-dejavu-mono_2.37-8_all.deb ... 576s Unpacking fonts-dejavu-mono (2.37-8) ... 576s Selecting previously unselected package fonts-dejavu-core. 576s Preparing to unpack .../014-fonts-dejavu-core_2.37-8_all.deb ... 576s Unpacking fonts-dejavu-core (2.37-8) ... 576s Selecting previously unselected package libfontenc1:ppc64el. 576s Preparing to unpack .../015-libfontenc1_1%3a1.1.8-1build1_ppc64el.deb ... 576s Unpacking libfontenc1:ppc64el (1:1.1.8-1build1) ... 576s Selecting previously unselected package x11-common. 576s Preparing to unpack .../016-x11-common_1%3a7.7+24ubuntu1_all.deb ... 576s Unpacking x11-common (1:7.7+24ubuntu1) ... 576s Selecting previously unselected package xfonts-encodings. 576s Preparing to unpack .../017-xfonts-encodings_1%3a1.0.5-0ubuntu2_all.deb ... 576s Unpacking xfonts-encodings (1:1.0.5-0ubuntu2) ... 576s Selecting previously unselected package xfonts-utils. 577s Preparing to unpack .../018-xfonts-utils_1%3a7.7+7_ppc64el.deb ... 577s Unpacking xfonts-utils (1:7.7+7) ... 577s Selecting previously unselected package fonts-urw-base35. 577s Preparing to unpack .../019-fonts-urw-base35_20200910-8_all.deb ... 577s Unpacking fonts-urw-base35 (20200910-8) ... 577s Selecting previously unselected package fontconfig-config. 577s Preparing to unpack .../020-fontconfig-config_2.15.0-2.3ubuntu1_ppc64el.deb ... 577s Unpacking fontconfig-config (2.15.0-2.3ubuntu1) ... 577s Selecting previously unselected package libfontconfig1:ppc64el. 577s Preparing to unpack .../021-libfontconfig1_2.15.0-2.3ubuntu1_ppc64el.deb ... 577s Unpacking libfontconfig1:ppc64el (2.15.0-2.3ubuntu1) ... 577s Selecting previously unselected package libxrender1:ppc64el. 577s Preparing to unpack .../022-libxrender1_1%3a0.9.12-1_ppc64el.deb ... 577s Unpacking libxrender1:ppc64el (1:0.9.12-1) ... 577s Selecting previously unselected package libxft2:ppc64el. 577s Preparing to unpack .../023-libxft2_2.3.6-1build1_ppc64el.deb ... 577s Unpacking libxft2:ppc64el (2.3.6-1build1) ... 577s Selecting previously unselected package libxss1:ppc64el. 577s Preparing to unpack .../024-libxss1_1%3a1.2.3-1build3_ppc64el.deb ... 577s Unpacking libxss1:ppc64el (1:1.2.3-1build3) ... 577s Selecting previously unselected package libtk8.6:ppc64el. 577s Preparing to unpack .../025-libtk8.6_8.6.17-1_ppc64el.deb ... 577s Unpacking libtk8.6:ppc64el (8.6.17-1) ... 577s Selecting previously unselected package tk8.6-blt2.5. 577s Preparing to unpack .../026-tk8.6-blt2.5_2.5.3+dfsg-8_ppc64el.deb ... 577s Unpacking tk8.6-blt2.5 (2.5.3+dfsg-8) ... 577s Selecting previously unselected package blt. 577s Preparing to unpack .../027-blt_2.5.3+dfsg-8_ppc64el.deb ... 577s Unpacking blt (2.5.3+dfsg-8) ... 577s Selecting previously unselected package libisl23:ppc64el. 577s Preparing to unpack .../028-libisl23_0.27-1_ppc64el.deb ... 577s Unpacking libisl23:ppc64el (0.27-1) ... 577s Selecting previously unselected package libmpc3:ppc64el. 577s Preparing to unpack .../029-libmpc3_1.3.1-2_ppc64el.deb ... 577s Unpacking libmpc3:ppc64el (1.3.1-2) ... 577s Selecting previously unselected package cpp-15-powerpc64le-linux-gnu. 577s Preparing to unpack .../030-cpp-15-powerpc64le-linux-gnu_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking cpp-15-powerpc64le-linux-gnu (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package cpp-15. 577s Preparing to unpack .../031-cpp-15_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking cpp-15 (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package cpp-powerpc64le-linux-gnu. 577s Preparing to unpack .../032-cpp-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 577s Unpacking cpp-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 577s Selecting previously unselected package cpp. 577s Preparing to unpack .../033-cpp_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 577s Unpacking cpp (4:15.2.0-4ubuntu1) ... 577s Selecting previously unselected package libcc1-0:ppc64el. 577s Preparing to unpack .../034-libcc1-0_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking libcc1-0:ppc64el (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package libgomp1:ppc64el. 577s Preparing to unpack .../035-libgomp1_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking libgomp1:ppc64el (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package libitm1:ppc64el. 577s Preparing to unpack .../036-libitm1_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking libitm1:ppc64el (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package libasan8:ppc64el. 577s Preparing to unpack .../037-libasan8_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking libasan8:ppc64el (15.2.0-7ubuntu1) ... 577s Selecting previously unselected package liblsan0:ppc64el. 577s Preparing to unpack .../038-liblsan0_15.2.0-7ubuntu1_ppc64el.deb ... 577s Unpacking liblsan0:ppc64el (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package libtsan2:ppc64el. 578s Preparing to unpack .../039-libtsan2_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking libtsan2:ppc64el (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package libubsan1:ppc64el. 578s Preparing to unpack .../040-libubsan1_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking libubsan1:ppc64el (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package libquadmath0:ppc64el. 578s Preparing to unpack .../041-libquadmath0_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking libquadmath0:ppc64el (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package libgcc-15-dev:ppc64el. 578s Preparing to unpack .../042-libgcc-15-dev_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking libgcc-15-dev:ppc64el (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package gcc-15-powerpc64le-linux-gnu. 578s Preparing to unpack .../043-gcc-15-powerpc64le-linux-gnu_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking gcc-15-powerpc64le-linux-gnu (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package gcc-15. 578s Preparing to unpack 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Preparing to unpack .../049-g++-15_15.2.0-7ubuntu1_ppc64el.deb ... 578s Unpacking g++-15 (15.2.0-7ubuntu1) ... 578s Selecting previously unselected package g++-powerpc64le-linux-gnu. 578s Preparing to unpack .../050-g++-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 578s Unpacking g++-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 578s Selecting previously unselected package g++. 578s Preparing to unpack .../051-g++_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 578s Unpacking g++ (4:15.2.0-4ubuntu1) ... 579s Selecting previously unselected package build-essential. 579s Preparing to unpack .../052-build-essential_12.12ubuntu1_ppc64el.deb ... 579s Unpacking build-essential (12.12ubuntu1) ... 579s Selecting previously unselected package python3-charset-normalizer. 579s Preparing to unpack .../053-python3-charset-normalizer_3.4.3-1_ppc64el.deb ... 579s Unpacking python3-charset-normalizer (3.4.3-1) ... 579s Selecting previously unselected package python3.14-tk. 579s Preparing to unpack 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.../059-libjpeg-turbo8_2.1.5-4ubuntu2_ppc64el.deb ... 579s Unpacking libjpeg-turbo8:ppc64el (2.1.5-4ubuntu2) ... 579s Selecting previously unselected package libjpeg8:ppc64el. 579s Preparing to unpack .../060-libjpeg8_8c-2ubuntu11_ppc64el.deb ... 579s Unpacking libjpeg8:ppc64el (8c-2ubuntu11) ... 579s Selecting previously unselected package liblcms2-2:ppc64el. 579s Preparing to unpack .../061-liblcms2-2_2.17-1_ppc64el.deb ... 579s Unpacking liblcms2-2:ppc64el (2.17-1) ... 579s Selecting previously unselected package libopenjp2-7:ppc64el. 579s Preparing to unpack .../062-libopenjp2-7_2.5.3-2.1_ppc64el.deb ... 579s Unpacking libopenjp2-7:ppc64el (2.5.3-2.1) ... 579s Selecting previously unselected package libgraphite2-3:ppc64el. 579s Preparing to unpack .../063-libgraphite2-3_1.3.14-2ubuntu1_ppc64el.deb ... 579s Unpacking libgraphite2-3:ppc64el (1.3.14-2ubuntu1) ... 579s Selecting previously unselected package libharfbuzz0b:ppc64el. 579s Preparing to unpack .../064-libharfbuzz0b_12.1.0-1_ppc64el.deb ... 579s Unpacking libharfbuzz0b:ppc64el (12.1.0-1) ... 579s Selecting previously unselected package libraqm0:ppc64el. 579s Preparing to unpack .../065-libraqm0_0.10.3-1_ppc64el.deb ... 579s Unpacking libraqm0:ppc64el (0.10.3-1) ... 579s Selecting previously unselected package libdeflate0:ppc64el. 579s Preparing to unpack .../066-libdeflate0_1.23-2_ppc64el.deb ... 579s Unpacking libdeflate0:ppc64el (1.23-2) ... 579s Selecting previously unselected package libjbig0:ppc64el. 579s Preparing to unpack .../067-libjbig0_2.1-6.1ubuntu2_ppc64el.deb ... 579s Unpacking libjbig0:ppc64el (2.1-6.1ubuntu2) ... 579s Selecting previously unselected package liblerc4:ppc64el. 579s Preparing to unpack .../068-liblerc4_4.0.0+ds-5ubuntu1_ppc64el.deb ... 579s Unpacking liblerc4:ppc64el (4.0.0+ds-5ubuntu1) ... 579s Selecting previously unselected package libsharpyuv0:ppc64el. 579s Preparing to unpack .../069-libsharpyuv0_1.5.0-0.1_ppc64el.deb ... 579s Unpacking libsharpyuv0:ppc64el (1.5.0-0.1) ... 579s Selecting previously unselected package libwebp7:ppc64el. 579s Preparing to unpack .../070-libwebp7_1.5.0-0.1_ppc64el.deb ... 579s Unpacking libwebp7:ppc64el (1.5.0-0.1) ... 579s Selecting previously unselected package libtiff6:ppc64el. 579s Preparing to unpack .../071-libtiff6_4.7.0-3ubuntu3_ppc64el.deb ... 579s Unpacking libtiff6:ppc64el (4.7.0-3ubuntu3) ... 579s Selecting previously unselected package libwebpdemux2:ppc64el. 579s Preparing to unpack .../072-libwebpdemux2_1.5.0-0.1_ppc64el.deb ... 579s Unpacking libwebpdemux2:ppc64el (1.5.0-0.1) ... 579s Selecting previously unselected package libwebpmux3:ppc64el. 579s Preparing to unpack .../073-libwebpmux3_1.5.0-0.1_ppc64el.deb ... 579s Unpacking libwebpmux3:ppc64el (1.5.0-0.1) ... 579s Selecting previously unselected package python3-pil:ppc64el. 579s Preparing to unpack .../074-python3-pil_11.3.0-1ubuntu2_ppc64el.deb ... 579s Unpacking python3-pil:ppc64el (11.3.0-1ubuntu2) ... 579s Selecting previously unselected package libpixman-1-0:ppc64el. 579s Preparing to unpack .../075-libpixman-1-0_0.46.4-1_ppc64el.deb ... 579s Unpacking libpixman-1-0:ppc64el (0.46.4-1) ... 579s Selecting previously unselected package libxcb-render0:ppc64el. 579s Preparing to unpack .../076-libxcb-render0_1.17.0-2build1_ppc64el.deb ... 579s Unpacking libxcb-render0:ppc64el (1.17.0-2build1) ... 579s Selecting previously unselected package libxcb-shm0:ppc64el. 579s Preparing to unpack .../077-libxcb-shm0_1.17.0-2build1_ppc64el.deb ... 579s Unpacking libxcb-shm0:ppc64el (1.17.0-2build1) ... 579s Selecting previously unselected package libcairo2:ppc64el. 579s Preparing to unpack .../078-libcairo2_1.18.4-1build1_ppc64el.deb ... 579s Unpacking libcairo2:ppc64el (1.18.4-1build1) ... 579s Selecting previously unselected package python3-cairo. 579s Preparing to unpack .../079-python3-cairo_1.27.0-2build1_ppc64el.deb ... 579s Unpacking python3-cairo (1.27.0-2build1) ... 579s Selecting previously unselected package python3-freetype. 579s Preparing to unpack .../080-python3-freetype_2.5.1-2_all.deb ... 579s Unpacking python3-freetype (2.5.1-2) ... 579s Selecting previously unselected package python3-rlpycairo. 579s Preparing to unpack .../081-python3-rlpycairo_0.3.0-4_all.deb ... 579s Unpacking python3-rlpycairo (0.3.0-4) ... 579s Selecting previously unselected package python3-reportlab. 579s Preparing to unpack .../082-python3-reportlab_4.4.4-2_all.deb ... 579s Unpacking python3-reportlab (4.4.4-2) ... 579s Selecting previously unselected package sgml-base. 579s Preparing to unpack .../083-sgml-base_1.31+nmu1_all.deb ... 579s Unpacking sgml-base (1.31+nmu1) ... 579s Selecting previously unselected package xml-core. 579s Preparing to unpack .../084-xml-core_0.19_all.deb ... 579s Unpacking xml-core (0.19) ... 579s Selecting previously unselected package w3c-sgml-lib. 579s Preparing to unpack .../085-w3c-sgml-lib_1.3-3_all.deb ... 579s Unpacking w3c-sgml-lib (1.3-3) ... 579s Selecting previously unselected package python3-biopython. 579s Preparing to unpack .../086-python3-biopython_1.85+dfsg-4_ppc64el.deb ... 579s Unpacking python3-biopython (1.85+dfsg-4) ... 579s Selecting previously unselected package fonts-lyx. 579s Preparing to unpack .../087-fonts-lyx_2.4.4-2_all.deb ... 579s Unpacking fonts-lyx (2.4.4-2) ... 579s Selecting previously unselected package python-matplotlib-data. 579s Preparing to unpack .../088-python-matplotlib-data_3.10.7+dfsg1-1_all.deb ... 579s Unpacking python-matplotlib-data (3.10.7+dfsg1-1) ... 580s Selecting previously unselected package python3-contourpy. 580s Preparing to unpack .../089-python3-contourpy_1.3.1-2_ppc64el.deb ... 580s Unpacking python3-contourpy (1.3.1-2) ... 580s Selecting previously unselected package python3-cycler. 580s Preparing to unpack .../090-python3-cycler_0.12.1-2_all.deb ... 580s Unpacking python3-cycler (0.12.1-2) ... 580s Selecting previously unselected package python3-brotli. 580s Preparing to unpack .../091-python3-brotli_1.1.0-2build6_ppc64el.deb ... 580s Unpacking python3-brotli (1.1.0-2build6) ... 580s Selecting previously unselected package python3-platformdirs. 580s Preparing to unpack .../092-python3-platformdirs_4.3.7-1_all.deb ... 580s Unpacking python3-platformdirs (4.3.7-1) ... 580s Selecting previously unselected package python3-fs. 580s Preparing to unpack .../093-python3-fs_2.4.16-9ubuntu1_all.deb ... 580s Unpacking python3-fs (2.4.16-9ubuntu1) ... 580s Selecting previously unselected package libxslt1.1:ppc64el. 580s Preparing to unpack .../094-libxslt1.1_1.1.43-0.3_ppc64el.deb ... 580s Unpacking libxslt1.1:ppc64el (1.1.43-0.3) ... 580s Selecting previously unselected package python3-lxml:ppc64el. 580s Preparing to unpack .../095-python3-lxml_6.0.2-1_ppc64el.deb ... 580s Unpacking python3-lxml:ppc64el (6.0.2-1) ... 580s Selecting previously unselected package python3-lz4. 580s Preparing to unpack .../096-python3-lz4_4.4.4+dfsg-3_ppc64el.deb ... 580s Unpacking python3-lz4 (4.4.4+dfsg-3) ... 580s Selecting previously unselected package python3-decorator. 580s Preparing to unpack .../097-python3-decorator_5.2.1-2_all.deb ... 580s Unpacking python3-decorator (5.2.1-2) ... 580s Selecting previously unselected package python3-scipy. 580s Preparing to unpack .../098-python3-scipy_1.15.3-1ubuntu1_ppc64el.deb ... 580s Unpacking python3-scipy (1.15.3-1ubuntu1) ... 580s Selecting previously unselected package python3-mpmath. 580s Preparing to unpack .../099-python3-mpmath_1.3.0-2_all.deb ... 580s Unpacking python3-mpmath (1.3.0-2) ... 581s Selecting previously unselected package python3-sympy. 581s Preparing to unpack .../100-python3-sympy_1.14.0-2_all.deb ... 581s Unpacking python3-sympy (1.14.0-2) ... 581s Selecting previously unselected package python3-ufolib2. 581s Preparing to unpack .../101-python3-ufolib2_0.17.1+dfsg1-1_all.deb ... 581s Unpacking python3-ufolib2 (0.17.1+dfsg1-1) ... 581s Selecting previously unselected package libpython3.14-stdlib:ppc64el. 581s Preparing to unpack .../102-libpython3.14-stdlib_3.14.0-4_ppc64el.deb ... 581s Unpacking libpython3.14-stdlib:ppc64el (3.14.0-4) ... 581s Selecting previously unselected package python3.14. 581s Preparing to unpack .../103-python3.14_3.14.0-4_ppc64el.deb ... 581s Unpacking python3.14 (3.14.0-4) ... 581s Selecting previously unselected package python3-all. 581s Preparing to unpack .../104-python3-all_3.13.7-2_ppc64el.deb ... 581s Unpacking python3-all (3.13.7-2) ... 581s Selecting previously unselected package libzopfli1. 581s Preparing to unpack .../105-libzopfli1_1.0.3-3_ppc64el.deb ... 581s Unpacking libzopfli1 (1.0.3-3) ... 581s Selecting previously unselected package python3-zopfli. 581s Preparing to unpack .../106-python3-zopfli_0.4.0-1_ppc64el.deb ... 581s Unpacking python3-zopfli (0.4.0-1) ... 581s Selecting previously unselected package unicode-data. 581s Preparing to unpack .../107-unicode-data_16.0.0-1_all.deb ... 581s Unpacking unicode-data (16.0.0-1) ... 581s Selecting previously unselected package python3-fonttools. 581s Preparing to unpack .../108-python3-fonttools_4.57.0-2build1_ppc64el.deb ... 581s Unpacking python3-fonttools (4.57.0-2build1) ... 581s Selecting previously unselected package python3-kiwisolver. 581s Preparing to unpack .../109-python3-kiwisolver_1.4.10~rc0-1_ppc64el.deb ... 581s Unpacking python3-kiwisolver (1.4.10~rc0-1) ... 581s Selecting previously unselected package libqhull-r8.0:ppc64el. 581s Preparing to unpack .../110-libqhull-r8.0_2020.2-7_ppc64el.deb ... 581s Unpacking libqhull-r8.0:ppc64el (2020.2-7) ... 581s Selecting previously unselected package python3-matplotlib. 581s Preparing to unpack .../111-python3-matplotlib_3.10.7+dfsg1-1_ppc64el.deb ... 581s Unpacking python3-matplotlib (3.10.7+dfsg1-1) ... 582s Selecting previously unselected package python3-pytz. 582s Preparing to unpack .../112-python3-pytz_2025.2-4_all.deb ... 582s Unpacking python3-pytz (2025.2-4) ... 582s Selecting previously unselected package python3-pandas-lib:ppc64el. 582s Preparing to unpack .../113-python3-pandas-lib_2.3.3+dfsg-1ubuntu1_ppc64el.deb ... 582s Unpacking python3-pandas-lib:ppc64el (2.3.3+dfsg-1ubuntu1) ... 582s Selecting previously unselected package python3-pandas. 582s Preparing to unpack .../114-python3-pandas_2.3.3+dfsg-1ubuntu1_all.deb ... 582s Unpacking python3-pandas (2.3.3+dfsg-1ubuntu1) ... 582s Selecting previously unselected package cython3. 582s Preparing to unpack .../115-cython3_3.1.6+dfsg-1ubuntu1_ppc64el.deb ... 582s Unpacking cython3 (3.1.6+dfsg-1ubuntu1) ... 582s Selecting previously unselected package python3-joblib. 582s Preparing to unpack .../116-python3-joblib_1.4.2-4_all.deb ... 582s Unpacking python3-joblib (1.4.2-4) ... 582s Selecting previously unselected package python3-networkx. 582s Preparing to unpack .../117-python3-networkx_3.2.1-4ubuntu1_all.deb ... 582s Unpacking python3-networkx (3.2.1-4ubuntu1) ... 583s Selecting previously unselected package python3-pomegranate. 583s Preparing to unpack .../118-python3-pomegranate_0.15.0-2_ppc64el.deb ... 583s Unpacking python3-pomegranate (0.15.0-2) ... 583s Selecting previously unselected package python3-pyfaidx. 583s Preparing to unpack .../119-python3-pyfaidx_0.8.1.3-2_all.deb ... 583s Unpacking python3-pyfaidx (0.8.1.3-2) ... 583s Selecting previously unselected package libhtscodecs2:ppc64el. 583s Preparing to unpack .../120-libhtscodecs2_1.6.1-2_ppc64el.deb ... 583s Unpacking libhtscodecs2:ppc64el (1.6.1-2) ... 583s Selecting previously unselected package libhts3t64:ppc64el. 583s Preparing to unpack .../121-libhts3t64_1.22.1+ds2-1_ppc64el.deb ... 583s Unpacking libhts3t64:ppc64el (1.22.1+ds2-1) ... 583s Selecting previously unselected package python3-pysam. 583s Preparing to unpack .../122-python3-pysam_0.23.3+ds-2_ppc64el.deb ... 583s Unpacking python3-pysam (0.23.3+ds-2) ... 584s Selecting previously unselected package python3-sklearn-lib:ppc64el. 584s Preparing to unpack .../123-python3-sklearn-lib_1.7.2+dfsg-3ubuntu1_ppc64el.deb ... 584s Unpacking python3-sklearn-lib:ppc64el (1.7.2+dfsg-3ubuntu1) ... 584s Selecting previously unselected package python3-threadpoolctl. 584s Preparing to unpack .../124-python3-threadpoolctl_3.1.0-1_all.deb ... 584s Unpacking python3-threadpoolctl (3.1.0-1) ... 584s Selecting previously unselected package python3-sklearn. 584s Preparing to unpack .../125-python3-sklearn_1.7.2+dfsg-3ubuntu1_all.deb ... 584s Unpacking python3-sklearn (1.7.2+dfsg-3ubuntu1) ... 584s Selecting previously unselected package zip. 584s Preparing to unpack .../126-zip_3.0-15ubuntu2_ppc64el.deb ... 584s Unpacking zip (3.0-15ubuntu2) ... 584s Selecting previously unselected package unzip. 584s Preparing to unpack .../127-unzip_6.0-28ubuntu7_ppc64el.deb ... 584s Unpacking unzip (6.0-28ubuntu7) ... 584s Selecting previously unselected package libpaper2:ppc64el. 584s Preparing to unpack .../128-libpaper2_2.2.5-0.3_ppc64el.deb ... 584s Unpacking libpaper2:ppc64el (2.2.5-0.3) ... 584s Selecting previously unselected package libpaper-utils. 584s Preparing to unpack .../129-libpaper-utils_2.2.5-0.3_ppc64el.deb ... 584s Unpacking libpaper-utils (2.2.5-0.3) ... 584s Selecting previously unselected package xdg-utils. 584s Preparing to unpack .../130-xdg-utils_1.2.1-2ubuntu1_all.deb ... 584s Unpacking xdg-utils (1.2.1-2ubuntu1) ... 584s Selecting previously unselected package fontconfig. 584s Preparing to unpack .../131-fontconfig_2.15.0-2.3ubuntu1_ppc64el.deb ... 584s Unpacking fontconfig (2.15.0-2.3ubuntu1) ... 584s Selecting previously unselected package libthai-data. 584s Preparing to unpack .../132-libthai-data_0.1.29-2build1_all.deb ... 584s Unpacking libthai-data (0.1.29-2build1) ... 584s Selecting previously unselected package libdatrie1:ppc64el. 584s Preparing to unpack .../133-libdatrie1_0.2.13-4_ppc64el.deb ... 584s Unpacking libdatrie1:ppc64el (0.2.13-4) ... 584s Selecting previously unselected package libthai0:ppc64el. 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unselected package libdebhelper-perl. 585s Preparing to unpack .../145-libdebhelper-perl_13.24.2ubuntu1_all.deb ... 585s Unpacking libdebhelper-perl (13.24.2ubuntu1) ... 585s Selecting previously unselected package libtool. 585s Preparing to unpack .../146-libtool_2.5.4-7_all.deb ... 585s Unpacking libtool (2.5.4-7) ... 585s Selecting previously unselected package dh-autoreconf. 585s Preparing to unpack .../147-dh-autoreconf_21_all.deb ... 585s Unpacking dh-autoreconf (21) ... 585s Selecting previously unselected package libarchive-zip-perl. 585s Preparing to unpack .../148-libarchive-zip-perl_1.68-1_all.deb ... 585s Unpacking libarchive-zip-perl (1.68-1) ... 585s Selecting previously unselected package libfile-stripnondeterminism-perl. 585s Preparing to unpack .../149-libfile-stripnondeterminism-perl_1.15.0-1_all.deb ... 585s Unpacking libfile-stripnondeterminism-perl (1.15.0-1) ... 585s Selecting previously unselected package dh-strip-nondeterminism. 585s Preparing to unpack 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Setting up libgpgmepp6t64:ppc64el (1.24.2-3ubuntu2) ... 587s Setting up liblerc4:ppc64el (4.0.0+ds-5ubuntu1) ... 587s Setting up libxrender1:ppc64el (1:0.9.12-1) ... 587s Setting up libdatrie1:ppc64el (0.2.13-4) ... 587s Setting up python3-joblib (1.4.2-4) ... 587s Setting up python3-lz4 (4.4.4+dfsg-3) ... 587s Setting up libxcb-render0:ppc64el (1.17.0-2build1) ... 587s Setting up libarchive-zip-perl (1.68-1) ... 587s Setting up python3-charset-normalizer (3.4.3-1) ... 587s Setting up fonts-lyx (2.4.4-2) ... 587s Setting up unzip (6.0-28ubuntu7) ... 587s Setting up libdebhelper-perl (13.24.2ubuntu1) ... 587s Setting up libpython3.14-minimal:ppc64el (3.14.0-4) ... 587s Setting up python3-threadpoolctl (3.1.0-1) ... 588s Setting up x11-common (1:7.7+24ubuntu1) ... 588s Setting up libdeflate0:ppc64el (1.23-2) ... 588s Setting up m4 (1.4.20-2) ... 588s Setting up libqhull-r8.0:ppc64el (2020.2-7) ... 588s Setting up python3-pytz (2025.2-4) ... 588s Setting up libxcb-shm0:ppc64el 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python3.14-minimal (3.14.0-4) ... 596s Setting up libcc1-0:ppc64el (15.2.0-7ubuntu1) ... 596s Setting up liblsan0:ppc64el (15.2.0-7ubuntu1) ... 596s Setting up libitm1:ppc64el (15.2.0-7ubuntu1) ... 597s Setting up libjpeg8:ppc64el (8c-2ubuntu11) ... 597s Setting up automake (1:1.18.1-2) ... 597s update-alternatives: using /usr/bin/automake-1.18 to provide /usr/bin/automake (automake) in auto mode 597s Setting up libfile-stripnondeterminism-perl (1.15.0-1) ... 597s Setting up python3-sympy (1.14.0-2) ... 609s /usr/lib/python3/dist-packages/sympy/testing/runtests.py:283: SyntaxWarning: 'return' in a 'finally' block 609s return p.returncode 609s Setting up libice6:ppc64el (2:1.1.1-1) ... 609s Setting up liblapack3:ppc64el (3.12.1-7) ... 609s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/powerpc64le-linux-gnu/liblapack.so.3 (liblapack.so.3-powerpc64le-linux-gnu) in auto mode 609s Setting up gettext (0.23.2-1) ... 609s Setting up python3-pysam (0.23.3+ds-2) ... 609s Setting up libgcc-15-dev:ppc64el (15.2.0-7ubuntu1) ... 609s Setting up libpython3.14-stdlib:ppc64el (3.14.0-4) ... 609s Setting up pybuild-plugin-pyproject (6.20250414) ... 609s Setting up fontconfig-config (2.15.0-2.3ubuntu1) ... 609s Setting up python3-pytest (8.3.5-2) ... 610s Setting up libwebpdemux2:ppc64el (1.5.0-0.1) ... 610s Setting up libpaper-utils (2.2.5-0.3) ... 610s Setting up xfonts-utils (1:7.7+7) ... 610s Setting up python3-zopfli (0.4.0-1) ... 610s Setting up intltool-debian (0.35.0+20060710.6) ... 610s Setting up libthai0:ppc64el (0.1.29-2build1) ... 610s Setting up cpp-15-powerpc64le-linux-gnu (15.2.0-7ubuntu1) ... 610s Setting up libstdc++-15-dev:ppc64el (15.2.0-7ubuntu1) ... 610s Setting up libraqm0:ppc64el (0.10.3-1) ... 610s Setting up python3-numpy (1:2.2.4+ds-1ubuntu1) ... 614s Setting up dh-strip-nondeterminism (1.15.0-1) ... 614s Setting up cpp-15 (15.2.0-7ubuntu1) ... 614s Setting up python3-lxml:ppc64el (6.0.2-1) ... 614s Setting up libtiff6:ppc64el (4.7.0-3ubuntu3) ... 614s Setting up xml-core (0.19) ... 614s Setting up python3-contourpy (1.3.1-2) ... 614s Setting up libfontconfig1:ppc64el (2.15.0-2.3ubuntu1) ... 614s Setting up python3.14 (3.14.0-4) ... 615s Setting up libsm6:ppc64el (2:1.2.6-1) ... 615s Setting up cpp-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 615s Setting up fontconfig (2.15.0-2.3ubuntu1) ... 618s Regenerating fonts cache... done. 618s Setting up libxft2:ppc64el (2.3.6-1build1) ... 618s Setting up python3-scipy (1.15.3-1ubuntu1) ... 623s /usr/lib/python3/dist-packages/scipy/optimize/_optimize.py:921: SyntaxWarning: 'break' in a 'finally' block 623s break 625s Setting up libpoppler147:ppc64el (25.03.0-11.1) ... 625s Setting up gcc-15-powerpc64le-linux-gnu (15.2.0-7ubuntu1) ... 625s Setting up po-debconf (1.0.21+nmu1) ... 625s Setting up python3-pomegranate (0.15.0-2) ... 625s Setting up libtk8.6:ppc64el (8.6.17-1) ... 625s Setting up python3-pandas-lib:ppc64el 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... 639s Setting up python3.14-tk (3.14.0-4) ... 639s Setting up python3-cairo (1.27.0-2build1) ... 639s Setting up libtool (2.5.4-7) ... 639s Setting up blt (2.5.3+dfsg-8) ... 639s Setting up python3-tk:ppc64el (3.13.9-1) ... 639s Setting up gcc (4:15.2.0-4ubuntu1) ... 640s Setting up dh-autoreconf (21) ... 640s Setting up python3-pil.imagetk:ppc64el (11.3.0-1ubuntu2) ... 640s Setting up python3-rlpycairo (0.3.0-4) ... 640s Setting up r-base-core (4.5.2-1) ... 640s Creating config file /etc/R/Renviron with new version 640s Setting up python3-reportlab (4.4.4-2) ... 642s Setting up g++-15 (15.2.0-7ubuntu1) ... 642s Setting up g++-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 642s Setting up r-bioc-biocgenerics (0.52.0-2) ... 642s Setting up debhelper (13.24.2ubuntu1) ... 642s Setting up g++ (4:15.2.0-4ubuntu1) ... 642s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 642s Setting up r-bioc-dnacopy (1.80.0-2) ... 642s Setting up build-essential (12.12ubuntu1) ... 642s Setting up pybuild-plugin-autopkgtest (6.20250414) ... 642s Setting up python3-ufolib2 (0.17.1+dfsg1-1) ... 642s Setting up python3-fonttools (4.57.0-2build1) ... 643s Setting up python3-matplotlib (3.10.7+dfsg1-1) ... 646s Processing triggers for libc-bin (2.42-2ubuntu2) ... 647s Processing triggers for systemd (257.9-0ubuntu2) ... 647s Processing triggers for man-db (2.13.1-1) ... 649s Processing triggers for install-info (7.2-5) ... 650s Processing triggers for sgml-base (1.31+nmu1) ... 650s Setting up w3c-sgml-lib (1.3-3) ... 678s Setting up python3-biopython (1.85+dfsg-4) ... 680s Setting up cnvkit (0.9.12-1) ... 688s autopkgtest [13:18:06]: test pybuild-autopkgtest: pybuild-autopkgtest 688s autopkgtest [13:18:06]: test pybuild-autopkgtest: [----------------------- 688s pybuild-autopkgtest 688s I: pybuild base:311: cd /tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build; python3.14 -m pytest test 690s ============================= test session starts ============================== 690s platform linux -- Python 3.14.0, pytest-8.3.5, pluggy-1.6.0 690s rootdir: /tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build 690s configfile: pyproject.toml 690s plugins: typeguard-4.4.2 690s collected 0 items / 5 errors 690s 690s ==================================== ERRORS ==================================== 690s _____________________ ERROR collecting test/test_cnvlib.py _____________________ 690s ImportError while importing test module '/tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build/test/test_cnvlib.py'. 690s Hint: make sure your test modules/packages have valid Python names. 690s Traceback: 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: in 690s from . import multiarray 690s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 690s from . import overrides 690s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: in 690s from numpy._core._multiarray_umath import ( 690s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 690s 690s During handling of the above exception, another exception occurred: 690s /usr/lib/python3/dist-packages/numpy/__init__.py:114: in 690s from numpy.__config__ import show_config 690s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 690s from numpy._core._multiarray_umath import ( 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: in 690s raise ImportError(msg) 690s E ImportError: 690s E 690s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 690s E 690s E Importing the numpy C-extensions failed. This error can happen for 690s E many reasons, often due to issues with your setup or how NumPy was 690s E installed. 690s E 690s E We have compiled some common reasons and troubleshooting tips at: 690s E 690s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 690s E 690s E Please note and check the following: 690s E 690s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 690s E * The NumPy version is: "2.2.4" 690s E 690s E and make sure that they are the versions you expect. 690s E Please carefully study the documentation linked above for further help. 690s E 690s E Original error was: No module named 'numpy._core._multiarray_umath' 690s 690s The above exception was the direct cause of the following exception: 690s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 690s return _bootstrap._gcd_import(name[level:], package, level) 690s test/test_cnvlib.py:14: in 690s import numpy as np 690s /usr/lib/python3/dist-packages/numpy/__init__.py:119: in 690s raise ImportError(msg) from e 690s E ImportError: Error importing numpy: you should not try to import numpy from 690s E its source directory; please exit the numpy source tree, and relaunch 690s E your python interpreter from there. 690s ____________________ ERROR collecting test/test_commands.py ____________________ 690s ImportError while importing test module '/tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build/test/test_commands.py'. 690s Hint: make sure your test modules/packages have valid Python names. 690s Traceback: 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: in 690s from . import multiarray 690s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 690s from . import overrides 690s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: in 690s from numpy._core._multiarray_umath import ( 690s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 690s 690s During handling of the above exception, another exception occurred: 690s /usr/lib/python3/dist-packages/numpy/__init__.py:114: in 690s from numpy.__config__ import show_config 690s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 690s from numpy._core._multiarray_umath import ( 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: in 690s raise ImportError(msg) 690s E ImportError: 690s E 690s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 690s E 690s E Importing the numpy C-extensions failed. This error can happen for 690s E many reasons, often due to issues with your setup or how NumPy was 690s E installed. 690s E 690s E We have compiled some common reasons and troubleshooting tips at: 690s E 690s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 690s E 690s E Please note and check the following: 690s E 690s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 690s E * The NumPy version is: "2.2.4" 690s E 690s E and make sure that they are the versions you expect. 690s E Please carefully study the documentation linked above for further help. 690s E 690s E Original error was: No module named 'numpy._core._multiarray_umath' 690s 690s The above exception was the direct cause of the following exception: 690s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 690s return _bootstrap._gcd_import(name[level:], package, level) 690s test/test_commands.py:18: in 690s import numpy as np 690s /usr/lib/python3/dist-packages/numpy/__init__.py:119: in 690s raise ImportError(msg) from e 690s E ImportError: Error importing numpy: you should not try to import numpy from 690s E its source directory; please exit the numpy source tree, and relaunch 690s E your python interpreter from there. 690s _____________________ ERROR collecting test/test_genome.py _____________________ 690s ImportError while importing test module '/tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build/test/test_genome.py'. 690s Hint: make sure your test modules/packages have valid Python names. 690s Traceback: 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:23: in 690s from . import multiarray 690s /usr/lib/python3/dist-packages/numpy/_core/multiarray.py:10: in 690s from . import overrides 690s /usr/lib/python3/dist-packages/numpy/_core/overrides.py:7: in 690s from numpy._core._multiarray_umath import ( 690s E ModuleNotFoundError: No module named 'numpy._core._multiarray_umath' 690s 690s During handling of the above exception, another exception occurred: 690s /usr/lib/python3/dist-packages/numpy/__init__.py:114: in 690s from numpy.__config__ import show_config 690s /usr/lib/python3/dist-packages/numpy/__config__.py:4: in 690s from numpy._core._multiarray_umath import ( 690s /usr/lib/python3/dist-packages/numpy/_core/__init__.py:49: in 690s raise ImportError(msg) 690s E ImportError: 690s E 690s E IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE! 690s E 690s E Importing the numpy C-extensions failed. This error can happen for 690s E many reasons, often due to issues with your setup or how NumPy was 690s E installed. 690s E 690s E We have compiled some common reasons and troubleshooting tips at: 690s E 690s E https://numpy.org/devdocs/user/troubleshooting-importerror.html 690s E 690s E Please note and check the following: 690s E 690s E * The Python version is: Python3.14 from "/usr/bin/python3.14" 690s E * The NumPy version is: "2.2.4" 690s E 690s E and make sure that they are the versions you expect. 690s E Please carefully study the documentation linked above for further help. 690s E 690s E Original error was: No module named 'numpy._core._multiarray_umath' 690s 690s The above exception was the direct cause of the following exception: 690s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 690s return _bootstrap._gcd_import(name[level:], package, level) 690s test/test_genome.py:12: in 690s import numpy as np 690s /usr/lib/python3/dist-packages/numpy/__init__.py:119: in 690s raise ImportError(msg) from e 690s E ImportError: Error importing numpy: you should not try to import numpy from 690s E its source directory; please exit the numpy source tree, and relaunch 690s E your python interpreter from there. 690s _______________________ ERROR collecting test/test_io.py _______________________ 690s ImportError while importing test module '/tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build/test/test_io.py'. 690s Hint: make sure your test modules/packages have valid Python names. 690s Traceback: 690s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 690s return _bootstrap._gcd_import(name[level:], package, level) 690s test/test_io.py:11: in 690s from skgenome import tabio 690s /usr/lib/python3/dist-packages/skgenome/__init__.py:1: in 690s from . import tabio 690s /usr/lib/python3/dist-packages/skgenome/tabio/__init__.py:10: in 690s import pandas as pd 690s /usr/lib/python3/dist-packages/pandas/__init__.py:19: in 690s raise ImportError( 690s E ImportError: Unable to import required dependencies: 690s E numpy: Error importing numpy: you should not try to import numpy from 690s E its source directory; please exit the numpy source tree, and relaunch 690s E your python interpreter from there. 690s _______________________ ERROR collecting test/test_r.py ________________________ 690s ImportError while importing test module '/tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build/test/test_r.py'. 690s Hint: make sure your test modules/packages have valid Python names. 690s Traceback: 690s /usr/lib/python3.14/importlib/__init__.py:88: in import_module 690s return _bootstrap._gcd_import(name[level:], package, level) 690s test/test_r.py:14: in 690s import cnvlib 690s /usr/lib/python3/dist-packages/cnvlib/__init__.py:1: in 690s from skgenome.tabio import write 690s /usr/lib/python3/dist-packages/skgenome/__init__.py:1: in 690s from . import tabio 690s /usr/lib/python3/dist-packages/skgenome/tabio/__init__.py:10: in 690s import pandas as pd 690s /usr/lib/python3/dist-packages/pandas/__init__.py:19: in 690s raise ImportError( 690s E ImportError: Unable to import required dependencies: 690s E numpy: Error importing numpy: you should not try to import numpy from 690s E its source directory; please exit the numpy source tree, and relaunch 690s E your python interpreter from there. 690s =========================== short test summary info ============================ 690s ERROR test/test_cnvlib.py 690s ERROR test/test_commands.py 690s ERROR test/test_genome.py 690s ERROR test/test_io.py 690s ERROR test/test_r.py 690s !!!!!!!!!!!!!!!!!!! Interrupted: 5 errors during collection !!!!!!!!!!!!!!!!!!!! 690s ============================== 5 errors in 0.73s =============================== 690s E: pybuild pybuild:389: test: plugin pyproject failed with: exit code=2: cd /tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build; python3.14 -m pytest test 690s I: pybuild base:311: cd /tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build; python3.13 -m pytest test 694s ============================= test session starts ============================== 694s platform linux -- Python 3.13.9, pytest-8.3.5, pluggy-1.6.0 694s rootdir: /tmp/autopkgtest.U8AZsL/autopkgtest_tmp/build 694s configfile: pyproject.toml 694s plugins: typeguard-4.4.2 694s collected 70 items 694s 699s test/test_cnvlib.py ........... [ 15%] 861s test/test_commands.py ............................. [ 57%] 867s test/test_genome.py ................... [ 84%] 868s test/test_io.py .......... [ 98%] 878s test/test_r.py . [100%] 878s 878s =============================== warnings summary =============================== 878s test/test_commands.py: 81 warnings 878s test/test_r.py: 24 warnings 878s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:317: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 878s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 878s A typical example is when you are setting values in a column of a DataFrame, like: 878s 878s df["col"][row_indexer] = value 878s 878s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 878s 878s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 878s 878s segments.start.iat[0] = bins_start 878s 878s test/test_commands.py: 81 warnings 878s test/test_r.py: 24 warnings 878s /usr/lib/python3/dist-packages/cnvlib/segmentation/__init__.py:318: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0! 878s You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy. 878s A typical example is when you are setting values in a column of a DataFrame, like: 878s 878s df["col"][row_indexer] = value 878s 878s Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`. 878s 878s See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy 878s 878s segments.end.iat[-1] = bins_end 878s 878s -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html 878s ================= 70 passed, 210 warnings in 187.76s (0:03:07) ================= 878s pybuild-autopkgtest: error: pybuild --autopkgtest --test-pytest -i python{version} -p "3.14 3.13" returned exit code 13 878s make: *** [/tmp/pRr52viij0/run:4: pybuild-autopkgtest] Error 25 878s pybuild-autopkgtest: error: /tmp/pRr52viij0/run pybuild-autopkgtest returned exit code 2 878s autopkgtest [13:21:16]: test pybuild-autopkgtest: -----------------------] 879s autopkgtest [13:21:17]: test pybuild-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 879s pybuild-autopkgtest FAIL non-zero exit status 25 879s autopkgtest [13:21:17]: @@@@@@@@@@@@@@@@@@@@ summary 879s run-unit-test PASS 879s pybuild-autopkgtest FAIL non-zero exit status 25