Package: afni-atlases Source: afni-data Version: 0.20180120-1.1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 109419 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni-data/afni-atlases_0.20180120-1.1+nd18.04+1_all.deb Size: 98214444 SHA256: 0856660b51d43e481685002dd8599f4d1bbae5522cf7a4e81024b7abc201dcc4 SHA1: d93085ad5d93ae6804848ee27214a2bb5966d82e MD5sum: 1017a599b41327936b4da772fdc25dce Description: standard space brain atlases for AFNI AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provide AFNI's standard space brain templates in HEAD/BRIK format. Package: asciidoctor Version: 1.5.7.1-1~nd~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 283 Depends: neurodebian-popularity-contest, ruby | ruby-interpreter, ruby-asciidoctor Multi-Arch: foreign Homepage: http://asciidoctor.org Priority: optional Section: text Filename: pool/main/a/asciidoctor/asciidoctor_1.5.7.1-1~nd~nd18.04+1_i386.deb Size: 64176 SHA256: 87d3ac8af55817023ad9ab2b878fffac5a562900e27babd87dad0b9c2eb8f6ec SHA1: e5b2f2ad52bb91ef16829e04c6841be1dfca9f8b MD5sum: 955c42dd985b8b7c7f081145469bc597 Description: AsciiDoc to HTML rendering for Ruby Asciidoctor is a pure Ruby processor for converting AsciiDoc source files and strings into HTML 5, DocBook 4.5, DocBook 5.0 and other formats. Package: asciidoctor-doc Source: asciidoctor Version: 1.5.7.1-1~nd~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3304 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: asciidoctor Homepage: http://asciidoctor.org Priority: optional Section: doc Filename: pool/main/a/asciidoctor/asciidoctor-doc_1.5.7.1-1~nd~nd18.04+1_all.deb Size: 345560 SHA256: 4c4a3b27251a4400bb20229d164a82948e89b368f98081d66b2ea0e63878854f SHA1: b26f6a5adb171d9a6e18b199900502fc84470416 MD5sum: 2c7a64d03fdcf8039d62345a9c0f5a8f Description: AsciiDoc to HTML rendering for Ruby (documentation) Asciidoctor is a pure Ruby processor for converting AsciiDoc source files and strings into HTML 5, DocBook 4.5, DocBook 5.0 and other formats. . This package contains the documentation for asciidoctor. Package: btrbk Version: 0.27.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 323 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv, mbuffer Suggests: openssl, python3 Homepage: https://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.27.1-1~nd18.04+1_all.deb Size: 91080 SHA256: 9eb0b490d8f19a8d3b72efb7ef5e268d598916318607920a760e48c157fd5fad SHA1: 3a1653d429f993f882efd2d077954c664c1e8e23 MD5sum: 391f2e0d1d580fea69e36efa2943e32c Description: backup tool for btrfs subvolumes Backup tool for btrfs subvolumes, using a configuration file, allows creation of backups from multiple sources to multiple destinations, with ssh and flexible retention policy support (hourly, daily, weekly, monthly). Package: cnrun-tools Source: cnrun Version: 2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 59 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:3.0), libgsl23, libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 18308 SHA256: 7416a9ebd99d006411441adc8fe0ec12c223c18ee189f5636bdc470ab827071a SHA1: a2fdbe136fc2c6ae250e6e5cbb23cd37805e7aaa MD5sum: b657d6f790d468346d9570d144e47120 Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: connectome-workbench Version: 1.3.2-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 48362 Depends: neurodebian-popularity-contest, libc6 (>= 2.27), libftgl2 (>= 2.1.3~rc5), libgcc1 (>= 1:7), libgl1, libglu1-mesa | libglu1, libgomp1 (>= 4.9), libosmesa6 (>= 10.2~), libqt5core5a (>= 5.9.0~beta), libqt5gui5 (>= 5.2.0), libqt5network5 (>= 5.0.2), libqt5opengl5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5widgets5 (>= 5.7.0), libqt5xml5 (>= 5.1.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.2.3.4) Recommends: caret Suggests: ffmpeg Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: science Filename: pool/main/c/connectome-workbench/connectome-workbench_1.3.2-2~nd18.04+1_i386.deb Size: 21084292 SHA256: 2942823f2939830f10aaed91c1129f12533a441d9d58a37ca265a4a86644dfc4 SHA1: 70fdfa1834020ee6bd2e04296a1d57216e33ef90 MD5sum: 9fee4d958f21840c235a90a757e2ca91 Description: brain visualization, analysis and discovery tool Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. Package: connectome-workbench-dbg Source: connectome-workbench Version: 1.3.2-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 195259 Depends: neurodebian-popularity-contest, connectome-workbench (= 1.3.2-2~nd18.04+1) Homepage: http://www.nitrc.org/projects/workbench/ Priority: extra Section: debug Filename: pool/main/c/connectome-workbench/connectome-workbench-dbg_1.3.2-2~nd18.04+1_i386.deb Size: 193625888 SHA256: dbdb01831a5a049e8bce9dbcd7ce4cfdf1b76c71ebe99f874f7b52c7cf3b3b54 SHA1: b8cd7ae424a6d58e438947579ed58088f5672c28 MD5sum: 08bee277bfba6a5f368982c97aacb933 Description: brain visualization, analysis and discovery tool -- debug symbols Connectome Workbench is a brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. . Package includes wb_command, a command-line program for performing a variety of analytical tasks for volume, surface, and CIFTI grayordinates data. . This package contains debug symbols for the binaries. Build-Ids: 2a9f528752034a1f220a9c10aca9e99b84c17b42 837bc9bc8e5dbc736436cc9f9a9241c16160d8ab Package: convert3d Version: 0.0.20170606-1~pre1~nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 59943 Depends: neurodebian-popularity-contest, libc6 (>= 2.27), libgcc1 (>= 1:4.0), libgdcm2.8, libinsighttoolkit4.12 (>= 4.12.0-dfsg1-2~), libqt5core5a (>= 5.9.0~beta), libqt5gui5 (>= 5.8.0), libqt5widgets5 (>= 5.7.0), libstdc++6 (>= 5.2) Homepage: https://sourceforge.net/projects/c3d/ Priority: optional Section: science Filename: pool/main/c/convert3d/convert3d_0.0.20170606-1~pre1~nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 9667596 SHA256: 7a229a9824082ca60e42673f7ec45a0ead218fb371b6a514064843737e5a41e8 SHA1: 0daf6f2663e425568853e87c33a2fd3f3d317deb MD5sum: 1fd168a91da087c7ca263ac3f237349b Description: tool(s) for converting 3D images between common file formats C3D is a (command-line and GUI) tool for converting 3D images between common file formats. The tool also includes a growing list of commands for image manipulation, such as thresholding and resampling. Package: copyq Version: 3.6.1-1~nd1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4906 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.2), libqt5core5a (>= 5.9.0~beta), libqt5gui5 (>= 5.8.0), libqt5network5 (>= 5.0.2), libqt5script5 (>= 5.6.0~beta), libqt5svg5 (>= 5.6.0~beta), libqt5widgets5 (>= 5.7.0), libqt5x11extras5 (>= 5.6.0), libstdc++6 (>= 4.8), libx11-6, libxtst6 Recommends: copyq-plugins (= 3.6.1-1~nd1~nd18.04+1) Suggests: copyq-doc Homepage: https://hluk.github.io/CopyQ/ Priority: optional Section: utils Filename: pool/main/c/copyq/copyq_3.6.1-1~nd1~nd18.04+1_i386.deb Size: 1358172 SHA256: cbc8d6d6350532724b42a848da556570f0bbcd0d981694bdfe3e616304fd678a SHA1: 7431e74b8c8bcef15e1eca5013f8fe96704af633 MD5sum: 4f722e5525263d1b0db96b637187c50c Description: Advanced clipboard manager with editing and scripting features CopyQ monitors system clipboard and saves its content in customized tabs. Saved clipboard can be later copied and pasted directly into any application. . Items can be: * edited with internal editor or with preferred text editor, * moved to other tabs, * drag'n'dropped to applications, * marked with tag or a note, * passed to or changed by custom commands, * or simply removed. . Features: * Support for Linux, Windows and OS X 10.9+ * Store text, HTML, images or any other custom formats * Quickly browse and filter items in clipboard history * Sort, create, edit, remove, copy/paste, drag'n'drop items in tabs * Add notes or tags to items * System-wide shortcuts with customizable commands * Paste items with shortcut or from tray or main window * Fully customizable appearance * Advanced command-line interface and scripting * Ignore clipboard copied from some windows or containing some text * Support for simple Vim-like editor and shortcuts * Many more features Package: copyq-doc Source: copyq Version: 3.6.1-1~nd1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1601 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Built-Using: sphinx (= 1.6.7-1ubuntu1) Multi-Arch: foreign Homepage: https://hluk.github.io/CopyQ/ Priority: optional Section: doc Filename: pool/main/c/copyq/copyq-doc_3.6.1-1~nd1~nd18.04+1_all.deb Size: 897676 SHA256: 32757da046e32b1b57b590c0cbd3ab49b57d1dd138c6a97218b93257176519cc SHA1: 8a9556d7c7d5cc536bf117cef478603557f509de MD5sum: e66f573f7ecec602cbe951309c4068e7 Description: Documentation and examples for CopyQ - HTML format CopyQ monitors system clipboard and saves its content in customized tabs. Saved clipboard can be later copied and pasted directly into any application. . This contains the documentation in HTML format. Package: copyq-plugins Source: copyq Version: 3.6.1-1~nd1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2591 Depends: neurodebian-popularity-contest, copyq (= 3.6.1-1~nd1~nd18.04+1), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libqt5core5a (>= 5.9.0~beta), libqt5gui5 (>= 5.2.0), libqt5widgets5 (>= 5.7.0), libstdc++6 (>= 4.8) Homepage: https://hluk.github.io/CopyQ/ Priority: optional Section: utils Filename: pool/main/c/copyq/copyq-plugins_3.6.1-1~nd1~nd18.04+1_i386.deb Size: 608032 SHA256: e62f72b81d152225227cf88f65ecc474a278de26a98a5f511cf44f3c02f4dac3 SHA1: 11fc48f4570bfd48459f65e01b51117fec60d69f MD5sum: 822647d7a9a3fe6a3faaa755ac76ad55 Description: Plugins for CopyQ CopyQ monitors system clipboard and saves its content in customized tabs. Saved clipboard can be later copied and pasted directly into any application. . This package contains plugins that add various item types support and features to CopyQ, including: * Text with Highlighting * Images * Web Pages * Various Data * Notes * Encryption * FakeVim Editor * Synchronize Items to Disk * Item Tags * Pinned Items Package: datalad Version: 0.11.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 128 Depends: neurodebian-popularity-contest, python3-datalad (= 0.11.1-1~nd18.04+1), python3-argcomplete, python3:any Suggests: datalad-containers, datalad-crawler, datalad-neuroimaging Homepage: http://datalad.org Priority: optional Section: science Filename: pool/main/d/datalad/datalad_0.11.1-1~nd18.04+1_all.deb Size: 91712 SHA256: 0937ffc56d83493866346fb08694b31b31e883666a2d55674bb52b164b889560 SHA1: 4989cfb59fe038757a9519a010b43db6f0567594 MD5sum: 6c1514d4ac0078c79f53fc97b00d79be Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package provides the command line tools. Install without Recommends if you need only core functionality. Package: datalad-container Version: 0.2.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 72 Depends: neurodebian-popularity-contest, datalad (>= 0.11.1~), python-requests (>= 1.2), python3-datalad, python3-requests, python3:any (>= 3.3.2-2~) Recommends: singularity-container Suggests: docker.io Homepage: http://datalad-container.rtfd.org Priority: optional Section: science Filename: pool/main/d/datalad-container/datalad-container_0.2.2-1~nd18.04+1_all.deb Size: 14784 SHA256: 493e705b4521d9d232f6d3d94698ef6e39e89bfe200ea835b085944d8b9b5343 SHA1: 83ed44485110e30042290dc0e18521c124fd1189 MD5sum: 7da123f80041bf956caf9d48f731f361 Description: DataLad extension for working with containerized environments This extension enhances DataLad (http://datalad.org) for working with computational containers. Package: dcm2niix Version: 1:1.0.20181125-1~nd2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 745 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libyaml-cpp0.5v5 Homepage: https://github.com/rordenlab/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_1.0.20181125-1~nd2~nd18.04+1_i386.deb Size: 184916 SHA256: 0610929e149ed829fcbae8d78d2ac3f2d1eaec321f4ec314ba971190848e140b SHA1: ec7693a1d27c794703e5caf3c8c36ce71c78cf4e MD5sum: 6d7825d664801ec90540daca5b8a47f1 Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: dh-octave Version: 0.6.0~bpo9+1+nd1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 61 Depends: neurodebian-popularity-contest, liboctave-dev (>= 4.2.1-5), debhelper (>= 11), cme, libparse-debcontrol-perl, libmime-tools-perl, dh-octave-autopkgtest, perl Priority: optional Section: devel Filename: pool/main/d/dh-octave/dh-octave_0.6.0~bpo9+1+nd1~nd18.04+1_all.deb Size: 20048 SHA256: eabfa763f6f4ff1a2a3d0f2f7ae692ec97d8b9e1d5aaa19db52fdc5920d50430 SHA1: 911d062df41aa32686c8c3da2dc6c075fb58b4cd MD5sum: 1c4d777fc219be1cb0f542d5d8dbd579 Description: Debhelper-based infrastructure for building Octave add-on packages Since version 3.0 of Octave (a numerical computation software), add-ons can be installed through the pkg.m system. This package provides the infrastructure for packaging such add-ons for Debian, based on debhelper. It replaces the deprecated octave-pkg-dev package. This package contains debhelper-like scripts for building, checking and cleaning the add-on package as well as for generating the substitution variables in debian/control. . This package is intended to be used by the Debian Octave Group and should be of little interest to general users. Package: dh-octave-autopkgtest Source: dh-octave Version: 0.6.0~bpo9+1+nd1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, gnuplot-nox, fonts-freefont-otf Priority: optional Section: devel Filename: pool/main/d/dh-octave/dh-octave-autopkgtest_0.6.0~bpo9+1+nd1~nd18.04+1_all.deb Size: 8504 SHA256: 3ac9f32f9928b941fb71540cdc46ac707104454795149ec583b6fa044abe986e SHA1: 56de1b9fca49329a400a1169ae2d421d2a15b906 MD5sum: d40f224e24b9ddc68cbf73490e9a3bca Description: script for the automatic testing of Octave add-on packages This package contains the dh_octave_check script that runs the unit tests contained in all *.m and *.cc files available in the source tree from which it is launched. It is intended to be used by the support for Octave-Forge add-on packages, which is implemented in autodep8. Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73 Depends: neurodebian-popularity-contest, python-matplotlib, python-nibabel, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 14132 SHA256: dbb9a44857a6002fede9dfaf3790a25b49cfdc7c5177ab15482e5ec413be678b SHA1: fe682e7eaf4d362566f51f16269dc82dfd8f57bb MD5sum: 3d6113be820954219d515010846df847 Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: fsleyes Version: 0.15.2-1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 239791 Depends: neurodebian-popularity-contest, python-fsl, python-fsleyes-props, python-fsleyes-widgets, python-wxgtk3.0, python-six (>= 1.0~), python-jinja2, python-scipy, python-matplotlib, python-numpy, python-opengl (>= 3.1~), python-indexed-gzip, python-nibabel, python-pil, python-pyparsing, python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: science Filename: pool/main/f/fsleyes/fsleyes_0.15.2-1~nd17.10+1+nd18.04+1_all.deb Size: 26726256 SHA256: e5c11fdb600c2e3350c948c17d4906c30b533e198a0c2f9a973806891cb0acb0 SHA1: dfbe97d8d56f9de39585d952c56e2beb743e579c MD5sum: aeeaef340b4aa3016b68f120d4b04430 Description: FSL image viewer Feature-rich viewer for volumetric (medical) images. Package: git-annex-remote-rclone Version: 0.5-1~ndall+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Depends: neurodebian-popularity-contest, git-annex | git-annex-standalone, rclone Homepage: https://github.com/DanielDent/git-annex-remote-rclone Priority: optional Section: utils Filename: pool/main/g/git-annex-remote-rclone/git-annex-remote-rclone_0.5-1~ndall+1_all.deb Size: 7842 SHA256: 0b1d65c740ce1073ecdae6db121d304fe02c4bb95df552326894118a65b38319 SHA1: 34a2323c4387e61c4a69617150c463f9a7b772c5 MD5sum: 00c5a0407a998eba72d4f5eb0ad71189 Description: rclone-based git annex special remote This is a wrapper around rclone to make any destination supported by rclone usable with git-annex. . Cloud storage providers supported by rclone currently include: * Google Drive * Amazon S3 * Openstack Swift / Rackspace cloud files / Memset Memstore * Dropbox * Google Cloud Storage * Microsoft One Drive * Hubic * Backblaze B2 * Yandex Disk . Note: although Amazon Cloud Drive support is implemented, it is broken ATM see https://github.com/DanielDent/git-annex-remote-rclone/issues/22 . Package: git-annex-standalone Source: git-annex Version: 7.20181121+git58-gbc4aa3f0e-1~ndall+1 Architecture: i386 Maintainer: Richard Hartmann Installed-Size: 170686 Depends: git, netbase, openssh-client Recommends: lsof, gnupg, bind9-host, youtube-dl, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: xdot, bup, adb, tor, magic-wormhole, tahoe-lafs, libnss-mdns, uftp Conflicts: git-annex Breaks: datalad (<= 0.11.1~) Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_7.20181121+git58-gbc4aa3f0e-1~ndall+1_i386.deb Size: 63687574 SHA256: 78ca539add3fbfb34ba5f41dbe201b25cc7f64ee6270d6a6ad91c91534fb612a SHA1: 01fe89dd2a396f9383713527e3b50a1aa373f692 MD5sum: 2b31f2fe5dab8fa2a1e6b61a1a2d05f5 Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: golang-github-ncw-rclone-dev Source: rclone Version: 1.41-1~ndall0 Architecture: all Maintainer: Debian Go Packaging Team Installed-Size: 2492 Depends: golang-bazil-fuse-dev, golang-github-aws-aws-sdk-go-dev, golang-github-mreiferson-go-httpclient-dev, golang-github-ncw-go-acd-dev, golang-github-ncw-swift-dev, golang-github-pkg-errors-dev, golang-github-pkg-sftp-dev, golang-github-rfjakob-eme-dev, golang-github-skratchdot-open-golang-dev, golang-github-spf13-cobra-dev, golang-github-spf13-pflag-dev, golang-github-stacktic-dropbox-dev, golang-github-stretchr-testify-dev, golang-github-tsenart-tb-dev, golang-github-unknwon-goconfig-dev, golang-github-vividcortex-ewma-dev, golang-golang-x-crypto-dev, golang-golang-x-net-dev, golang-golang-x-oauth2-google-dev, golang-golang-x-sys-dev, golang-golang-x-text-dev, golang-google-api-dev Homepage: https://github.com/ncw/rclone Priority: optional Section: devel Filename: pool/main/r/rclone/golang-github-ncw-rclone-dev_1.41-1~ndall0_all.deb Size: 399416 SHA256: 528b53f3312375d31d5cebb95472a57272cf242e14a92cfdf99c45be2ff5511d SHA1: 75f8871fd668e815023267a857b37ad60b9d1c2f MD5sum: a87865eafe10185420838e2e4ffd7b55 Description: go source code of rclone Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers. . This package contains rclone's source code. Package: heudiconv Version: 0.5.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 958 Depends: neurodebian-popularity-contest, dcm2niix, python, python-dcmstack, python-dicom, python-nibabel, python-pathlib, python-numpy, python-nipype Recommends: python-pytest, python-datalad Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.5.3-1~nd18.04+1_all.deb Size: 246272 SHA256: feb21bb077f17e05c640f25bc22832dffea1c0f5677962fc87c192b2a224f6b3 SHA1: ceb4eac9080bea52bb51c862123dab56d7545789 MD5sum: 98873184e85eb43c0fed9dbbc2d61f0a Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: isympy-common Source: sympy Version: 1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 211 Depends: neurodebian-popularity-contest, python:any | python:any Recommends: isympy | isympy3 Conflicts: isympy (<< 1.0-2) Breaks: python-sympy (<< 0.7.5-4) Homepage: http://sympy.org/ Priority: optional Section: python Filename: pool/main/s/sympy/isympy-common_1.3-1~nd18.04+1_all.deb Size: 186592 SHA256: 719a7be51dd8e09fa1d6d8379c4ff2c21a108a8791b6cac65700deffd6a96305 SHA1: 1a8166281cd3b191d504cfa2bd85d602d9ec367f MD5sum: c9508f8e42e0f783349cc72ff881fa74 Description: Python shell for SymPy SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. . This support package contains the common isympy python script, a wrapper for SymPy which can be invoked with either python2 or python3. . Install the isympy or isympy3 package to ensure all required dependencies are loaded. Package: isympy3 Source: sympy Version: 1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20 Depends: neurodebian-popularity-contest, isympy-common, python3-sympy Enhances: ipython3 Provides: isympy Homepage: http://sympy.org/ Priority: optional Section: python Filename: pool/main/s/sympy/isympy3_1.3-1~nd18.04+1_all.deb Size: 8360 SHA256: 337898618c71b253c7b95823f24cef38cd52fe8fd548338feb3d3df1f4e89e52 SHA1: eefa40a08b3395b8024c166d0212a77aaf81fd05 MD5sum: 8051e8a830b3444169117dca592d09be Description: Python3 shell for SymPy SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. . This package contains a Python3 shell (IPython shell if you have the ipython3 package installed) wrapper for SymPy. Package: jasp Version: 0.8.1.0~dfsg.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 39974 Depends: neurodebian-popularity-contest, libarchive13 (>= 3.0.4), libboost-filesystem1.65.1, libboost-system1.65.1, libc6 (>= 2.4), libgcc1 (>= 1:4.2), libqt5core5a (>= 5.9.0~beta), libqt5gui5 (>= 5.2.0), libqt5network5 (>= 5.0.2), libqt5printsupport5 (>= 5.0.2), libqt5webkit5 (>= 5.6.0~rc), libqt5widgets5 (>= 5.6.0~beta), libqt5xml5 (>= 5.1.0), libstdc++6 (>= 5.2), libjs-marked, r-base-core, r-cran-afex, r-cran-bayesfactor, r-cran-car, r-cran-effects, r-cran-hypergeo, r-cran-lme4, r-cran-logspline, r-cran-rjson Recommends: r-cran-ggplot2, r-cran-lsmeans, r-cran-plotrix, r-cran-rcpp, r-cran-rinside, r-cran-vcd, r-cran-vcdextra Homepage: https://jasp-stats.org Priority: optional Section: science Filename: pool/main/j/jasp/jasp_0.8.1.0~dfsg.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 33468560 SHA256: c10c2f000641b5430bc871f5e3aff26c4825c257b2ace923204a5dab9ddffe16 SHA1: b6e80f9bfb7dbc862950b44d0e9dd90350249db0 MD5sum: bee7788e6eab4155f3cfb239b2362f46 Description: Bayesian statistics made accessible This is a statistics package with a graphical user interface. Its authors consider it "a low fat alternative to SPSS, a delicious alternative to R. Bayesian statistics made accessible." Package: libcnrun2 Source: cnrun Version: 2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 270 Depends: neurodebian-popularity-contest, libc6 (>= 2.8), libgcc1 (>= 1:3.0), libgsl23, libgslcblas0, libstdc++6 (>= 5.2), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 85804 SHA256: 9d3ef7a638bbb64a6b801f66767bf5cfec5c9b19d74e1bb38279b1f65614aa6e SHA1: 927ce3bb7f31445152f54df102e6d7a4f41db9b0 MD5sum: 2f16086404a11e49f3c0b922b3c02386 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 138 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 21632 SHA256: 9439913474d31b0e5bdbf1c66dbf9b9ee8ae1070164aa040cdf7478f63b9bec1 SHA1: 21768b4c923d0f0d3ef0c8967aa0eec83126b4f7 MD5sum: 0af517acf42c7fb2f436e4a425b7028f Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libvw-dev Source: vowpal-wabbit Version: 8.6.1.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 13235 Depends: neurodebian-popularity-contest, libvw0 (= 8.6.1.dfsg1-1~nd18.04+1) Homepage: http://hunch.net/~vw/ Priority: optional Section: libdevel Filename: pool/main/v/vowpal-wabbit/libvw-dev_8.6.1.dfsg1-1~nd18.04+1_i386.deb Size: 1613380 SHA256: e8f31794388ca3ce8f61c2289d0028f7cd0476d30e65a6e1de906f4c7d9092c8 SHA1: fb520c28aa7ef048bdb159535ee918cca65eb176 MD5sum: 93bdb383f7575cc521ec42c76137740f Description: fast and scalable online machine learning algorithm - development files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains development files needed to compile and link programs which use vowpal-wabbit's libraries. Package: libvw0 Source: vowpal-wabbit Version: 8.6.1.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3338 Depends: neurodebian-popularity-contest, libboost-program-options1.65.1, libc6 (>= 2.27), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Homepage: http://hunch.net/~vw/ Priority: optional Section: libs Filename: pool/main/v/vowpal-wabbit/libvw0_8.6.1.dfsg1-1~nd18.04+1_i386.deb Size: 932328 SHA256: c92609c6ff647b94d2dd4c7a37e2a326d5adf699f0a980246929873ece52864a SHA1: 2518a9c8407de697d01a126c2a4253504bd1c503 MD5sum: ab603c29e08329f61b07d0f0e7c63e3a Description: fast and scalable online machine learning algorithm - dynamic library Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains vowpal-wabbit's dynamic libraries. Package: lua-cnrun Source: cnrun Version: 2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 113 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.1.0-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 39712 SHA256: d16ea18e695d88dc591bf3d3a75d9e4dab80f098d7918f153fb9b046ff2c5330 SHA1: e574e728ad64986184a5fcbd321b7bd0f54d602b MD5sum: 5116bd92fe09bb1ed7c35392a5203e29 Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: mridefacer Version: 0.2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: neurodebian-popularity-contest, num-utils, fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 637452 SHA256: ab5a15de7c3ef796d813c5a2e14ae14dd36f338884bca80570f1ff4d6b5c3c8e SHA1: 760e57847e5005fd0a11a1a8d18ce42db9e541c9 MD5sum: f361b00ca73a41c0e14b72d59069bc29 Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: mrtrix Version: 0.2.13-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 9370 Depends: neurodebian-popularity-contest, libatkmm-1.6-1v5 (>= 2.24.0), libc6 (>= 2.27), libgcc1 (>= 1:3.0), libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1v5 (>= 2.54.0), libglu1-mesa | libglu1, libgsl23, libgslcblas0, libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1v5 (>= 1:2.24.0), libsigc++-2.0-0v5 (>= 2.2.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Suggests: mrtrix-doc, octave, matlab-support Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.13-1~nd18.04+1_i386.deb Size: 1507128 SHA256: f3188e6e3e8ef4ba09501e8b8cc0e778e1e4b0536275ab78c81314248bfc07ed SHA1: eb24e9730a6885dd9b2b9b83015e3682e80b5409 MD5sum: 2ed0b7ebee7e363b5d7fc064a20bcbd0 Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.13-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3402 Depends: neurodebian-popularity-contest Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.13-1~nd18.04+1_all.deb Size: 3180296 SHA256: b2b6e876e67bca20fb3d740d11841133b4a69ca24b821e73c40f81ea49043e50 SHA1: 6ebe3e5bbf8744e68868dc1dc23730d5fe6b1c47 MD5sum: ad4964b7183f6cf4d846400340a15319 Description: documentation for mrtrix Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: mrtrix3 Version: 3.0~rc3+git86-g4b523b413-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 50781 Depends: neurodebian-popularity-contest, libc6 (>= 2.27), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:4.2), libgl1, libgomp1 (>= 4.9), libqt4-opengl (>= 4:4.7.0~beta1), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.8.0), libstdc++6 (>= 7), zlib1g (>= 1:1.1.4) Recommends: python-numpy Suggests: mrtrix3-doc, octave, python, python2, matlab-support Conflicts: mrtrix Homepage: http://www.mrtrix.org Priority: optional Section: science Filename: pool/main/m/mrtrix3/mrtrix3_3.0~rc3+git86-g4b523b413-2~nd18.04+1_i386.deb Size: 8423528 SHA256: 540edf4f6cef99e3d5084ae49b980858e5d69b95e9f561900f519c153ed9a2d7 SHA1: a944bf7a37d58e8dc222e57554210913a83d7654 MD5sum: 8602ecd5f0c6f81d8802644e8ad945ec Description: diffusion-weighted MRI white matter tractography Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. Package: mrtrix3-doc Source: mrtrix3 Version: 3.0~rc3+git135-g2b8e7d0c2-3~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 86 Depends: neurodebian-popularity-contest Conflicts: mrtrix-doc Homepage: http://www.mrtrix.org Priority: optional Section: doc Filename: pool/main/m/mrtrix3/mrtrix3-doc_3.0~rc3+git135-g2b8e7d0c2-3~nd18.04+1_all.deb Size: 47904 SHA256: 0fb497081d355830812ed8d525f4f6228552179853558599034a8fd565f5de8f SHA1: 61cca85976855905cd619e1fa54df308c54e75d7 MD5sum: f9cea66866cb74623fe2fdede05a452b Description: documentation for mrtrix3 Set of tools to perform diffusion-weighted MRI white matter tractography of the brain in the presence of crossing fibres, using Constrained Spherical Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance images in DICOM, ANALYZE, or uncompressed NIfTI format are supported. . This package provides the documentation in HTML format. Package: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 93 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.38.2~nd18.04+1_all.deb Size: 33916 SHA256: 1b81ac68bfe18f14106b7c170c5b337b7abd6502e7cda0c90ce085208a370765 SHA1: 79966cfb63f72212923c41dc5b7a6f55882b92a9 MD5sum: 429b7c27870240128cbe757f15e2b27e Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Depends: gnupg2 | gnupg, dirmngr Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.38.2~nd18.04+1_all.deb Size: 10900 SHA256: 1696e85b3950ac9d26bab422b01be8dcad7d0d7782a969c6293594afa4add047 SHA1: 9ec7dc6330e6cefdcdcc8b36f3b221b0a75cc137 MD5sum: bdf933189bc5d8f64263936c00a904f4 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 190 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Recommends: reportbug-ng Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.38.2~nd18.04+1_all.deb Size: 116740 SHA256: ee69355746896b4f105856fdbbd004027d8849ff87a854a72deb075b90d83474 SHA1: 6b6b76c9aa25b4e80bfe4bbcc2a8f9b1398f33b1 MD5sum: f033eb86b19075d61dc6b96bd5d0f9e6 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 112 Depends: devscripts, neurodebian-archive-keyring Recommends: ubuntu-keyring, python, zerofree, moreutils, time, debian-archive-keyring, apt-utils, cowbuilder, neurodebian-freeze Suggests: virtualbox-ose, virtualbox-ose-fuse, singularity-container Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.38.2~nd18.04+1_all.deb Size: 33592 SHA256: 1926d0395c954e63114322bdc1facb1fdeec0a02e37e241b9c6ffb48dc7b76b8 SHA1: 45a4930b57a6596e8798cd7d7f658fc3e196cc67 MD5sum: f2941d5f4c1b1dfd2fbb476f8613a926 Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-freeze Source: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-freeze_0.38.2~nd18.04+1_all.deb Size: 13980 SHA256: e77c41b03a9e674627e967b8b54e15716d8b076012013b7101ed5d8602f8ff1c SHA1: a028ab5860c4289147b5a32d0c139424fb2fb83d MD5sum: 3672c230cb8ae529f9f13e9e187bae1e Description: nd_freeze tool to freeze APT sources to use snapshots The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This minimalistic package provides nd_freeze script to be used in rich or minimalistic environments (such as Docker or Singularity recipes) to freeze their APT sources. Intended to assist making such images reproducible. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.38.2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 28 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.38.2~nd18.04+1_all.deb Size: 12932 SHA256: 500dc59b066218fe9d7d9eed6051f3ed3dcd67f8a1a7716c8a0edf51df83e872 SHA1: c86506b387d573665f090cabc081220cdd7bfa8a MD5sum: 5aa35406862aa7eebf55fa1476ba075e Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.6.1.1+ds-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7442 Depends: neurodebian-popularity-contest, gcc (>= 5.0) | g++ (>= 4.4) | clang (>= 3.0), scons (>= 2.0.0), python-appdirs | base-files (<< 7.2), python3-appdirs | base-files (<< 7.2), python-dev (>= 2.6.6-2), python3-dev, python3:any (>= 3.3.2-2~), python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-pyqt5, strace, chrpath Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.6.1.1+ds-1~nd18.04+1_all.deb Size: 770456 SHA256: 8351b10f4ca8931ac324135a03e19f0fc5de7f489ed4e1d5d6f3d65b4342d812 SHA1: 1885840b24c27c9310c6eb765b5e51b9368b12ae MD5sum: b93eaa6a662b02c3ab93cd7a19cd97e9 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 4427 Depends: neurodebian-popularity-contest, octave (>= 4.2.2), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.12), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgcc1 (>= 1:3.0), libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.0.0), liboctave4, libopenal1 (>= 1.14), libpciaccess0 (>= 0.10.7), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3 (>= 1:5.0), libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.4.0), libxxf86vm1, psychtoolbox-3-common (= 3.0.14.20180526.dfsg1-1~nd18.04+1), psychtoolbox-3-lib (= 3.0.14.20180526.dfsg1-1~nd18.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics, octave-pkg-dev Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.14.20180526.dfsg1-1~nd18.04+1_i386.deb Size: 906340 SHA256: e297d5b59a4fdf1b63d9cf70aa00d02cfa4b08a2a01ac4d2e834777f36bfe15b SHA1: 2967d00cfbb85fda9e54edc19fc951c3d5a12737 MD5sum: 38a827adf5838d0592448deff53ba2ba Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: patool Version: 1.12-3+nd1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 412 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~), python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: file Suggests: arj, bzip2 | lbzip2 | pbzip2, cabextract | lcab, ncompress, cpio | bsdcpio, lzop, p7zip-full, rar | unrar | zip | unzip, rpm2cpio, binutils, lha, unace | unace-nonfree | nomarch, unalz, lrzip (>= 0.551), tar (>= 1.26) | bsdtar, xdms, orange, lzip | plzip | clzip | pdlzip, sharutils, flac, archmage, genisoimage, python-argcomplete Homepage: http://wummel.github.io/patool/ Priority: optional Section: utils Filename: pool/main/p/patool/patool_1.12-3+nd1~nd18.04+1_all.deb Size: 37380 SHA256: cc05f4a0f45196a8cf73a3a2513d0c911d6a9021507f4243b998f8994e50bd2a SHA1: dd80f06ba3c5bc30bdff8834499830b99365be62 MD5sum: fdb26ed711739a63fa8fe8a8710386d3 Description: command line archive file manager Various archive formats can be created, extracted, tested, listed, compared, searched and repacked by patool. The archive format is determined with file and as a fallback by the archive file extension. . patool supports 7z (.7z), ACE (.ace), ADF (.adf), ALZIP (.alz), AR (.a), ARC (.arc), ARJ (.arj), BZIP2 (.bz2), CAB (.cab), compress (.Z), CPIO (.cpio), DEB (.deb), DMS (.dms), FLAC (.flac), GZIP (.gz), ISO (.iso), LZH (.lha, .lzh), LZIP (.lz), LZMA (.lzma), LZOP (.lzo), RAR (.rar), RPM (.rpm), RZIP (.rz), SHAR (.shar), SHN (.shn), TAR (.tar), XZ (.xz), ZIP (.zip, .jar) and ZOO (.zoo) formats. . It relies on helper applications to handle those archive formats (for example bzip2 for BZIP2 archives). . The archive formats TAR, ZIP, BZIP2 and GZIP are supported natively and do not require helper applications to be installed. Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253835 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.14.20180526.dfsg1-1~nd18.04+1_all.deb Size: 24194328 SHA256: efbfcc47427c5d62e44760ad37a61053e754cbc8b15d0ec0879d039b20ae371a SHA1: 33db20ba0203c375342eebf33c2622c07b5f15c6 MD5sum: 8e0c0c94a44d3aaf496830ef780155b3 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 18444 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.14.20180526.dfsg1-1~nd18.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.14.20180526.dfsg1-1~nd18.04+1_i386.deb Size: 1270232 SHA256: a5065bfca54c82a0ff610f2dc675b92de68857d2e93f10849945c736d34e5593 SHA1: e517f4f72facc3871d34f8e1e330458f948d3ae7 MD5sum: 816ebf2806eb7e41d0f4d73a2ba41702 Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.14.20180526.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 185 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.12), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 5) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.14.20180526.dfsg1-1~nd18.04+1_i386.deb Size: 76164 SHA256: 5e193b6b0c68e9cf2982d4d12d28f216f59c23b4f7e65be9c75f6325255a26ae SHA1: 06b17cd58f2369550078231b90e4fc893c5e151b MD5sum: f1e3d3c1406dd75841a5f2eaa43c9b6f Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: pypy-hypothesis Source: python-hypothesis Version: 3.44.1-1~bpo9+1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 610 Depends: neurodebian-popularity-contest, pypy-enum34, pypy, pypy-attr, pypy-coverage Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/pypy-hypothesis_3.44.1-1~bpo9+1~nd18.04+1_all.deb Size: 120416 SHA256: 810b290223de0eb95f53aba1db7185b86f6db000dd201a5b67d5be30661c0c87 SHA1: 4a1d1f818b2be3d94ca58ebcef5cea1b2abe26a9 MD5sum: 3e73481f8a1476bc73106a27e65c0f63 Description: advanced Quickcheck style testing library for PyPy Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the PyPy module. Package: python-boto Version: 2.44.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5140 Depends: neurodebian-popularity-contest, python-requests, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-six Provides: python2.7-boto Homepage: https://github.com/boto/boto Priority: optional Section: python Filename: pool/main/p/python-boto/python-boto_2.44.0-1~nd18.04+1_all.deb Size: 739632 SHA256: 272bc22c063cc377b62b625271ec01c3a22a2d7030aa72be97b671c712c9620b SHA1: ae16c73682753c33148f744572fedf76f37fb8a1 MD5sum: 6259cefd0a2d8211dbfb5ec62ced59bd Description: Python interface to Amazon's Web Services - Python 2.x Boto is a Python interface to the infrastructure services available from Amazon. . Boto supports the following services: * Elastic Compute Cloud (EC2) * Elastic MapReduce * CloudFront * DynamoDB * SimpleDB * Relational Database Service (RDS) * Identity and Access Management (IAM) * Simple Queue Service (SQS) * CloudWatch * Route53 * Elastic Load Balancing (ELB) * Flexible Payment Service (FPS) * Simple Storage Service (S3) * Glacier * Elastic Block Store (EBS) * and many more... . This package provides the Python 2.x module. Package: python-bz2file Version: 0.98-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-bz2file Homepage: https://github.com/nvawda/bz2file Priority: optional Section: python Filename: pool/main/p/python-bz2file/python-bz2file_0.98-1~nd18.04+1_all.deb Size: 7920 SHA256: 8e05001a4c74dbb7b571230f657bf635b3ee63cdb99ba33a64600200bd7d4f4e SHA1: 2abb16321b37adfd36fb1c476543a26ef0aadc56 MD5sum: 1a1f71c61c7db903d9ba852fa6f3adc6 Description: Python library for reading and writing bzip2-compressed files Bz2file is a Python library for reading and writing bzip2-compressed files. . It contains a drop-in replacement for the file interface in the standard library's bz2 module, including features from the latest development version of CPython that are not available in older releases. . Bz2file for Python2. Package: python-dask-doc Source: dask Version: 0.17.5-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6964 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common, libjs-mathjax, libjs-bootstrap Built-Using: sphinx (= 1.6.7-1ubuntu1) Homepage: https://github.com/dask/dask Priority: optional Section: doc Filename: pool/main/d/dask/python-dask-doc_0.17.5-2~nd18.04+1_all.deb Size: 1768204 SHA256: e9532fdaf3677c39999cdc52e20cd5162442ecd8fa0ee5a00659a9abba997b14 SHA1: 1bcb678ef8953ce16ba0e2092a54aac913031d7f MD5sum: 7cc7adcc20210f486d54de0529e66e54 Description: Minimal task scheduling abstraction documentation Dask is a flexible parallel computing library for analytics, containing two components. . 1. Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads. 2. "Big Data" collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers. . This contains the documentation Package: python-datalad Source: datalad Version: 0.11.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4320 Depends: neurodebian-popularity-contest, git-annex (>= 6.20180509~) | git-annex-standalone (>= 6.20180509~), patool, python-appdirs, python-fasteners, python-git (>= 2.1.6~), python-humanize, python-iso8601, python-keyrings.alt | python-keyring (<= 8), python-secretstorage, python-keyring, python-mock, python-msgpack, python-pil, python-requests, python-simplejson, python-six (>= 1.8.0), python-tqdm, python-wrapt, python-boto, python-chardet, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-exif, python-github, python-jsmin, python-html5lib, python-httpretty, python-libxmp, python-lzma, python-mutagen, python-nose, python-pyperclip, python-requests-ftp, python-vcr, python-whoosh Suggests: python-duecredit, python-bs4, python-numpy Provides: python2.7-datalad Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python-datalad_0.11.1-1~nd18.04+1_all.deb Size: 899352 SHA256: 49f2f01ef73ac80ccaddc0286ce270e5df0fc7ec2c43e4e89e2322d7aeb29cd3 SHA1: 38bd56da3770a293838219bf49a9c3c9bec2c61d MD5sum: ddba3e3c1bf8153acc0a345d4488a28a Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 2, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python-dcmstack Source: dcmstack Version: 0.7-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 500 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: science Filename: pool/main/d/dcmstack/python-dcmstack_0.7-1~nd18.04+1_all.deb Size: 76032 SHA256: 76bd0483822282450e4bd05149b482eec0ec879ac67c7b7e32e25d286fee6e8f SHA1: b1321189a9ffae61015e706e35d6bf08c271acf5 MD5sum: 489f81c48497d714dc618152f9b3efcb Description: DICOM to NIfTI conversion DICOM to NIfTI conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a NIfTI header extension or written out as a JSON formatted text file. . This package provides the Python package, and command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-dicom Source: pydicom Version: 1.2.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python-pydicom Homepage: https://pydicom.github.io Priority: optional Section: oldlibs Filename: pool/main/p/pydicom/python-dicom_1.2.1-1~nd18.04+1_all.deb Size: 4904 SHA256: 4b2d3fca8623d2bd20dc4d5035c27b483a0958cef6c569f43233c76b4d430f63 SHA1: c7887a909c187af788f8bed2424243ed7186eada MD5sum: 105a20129bb4526db82a347f73a324fe Description: transitional package for python-pydicom This is a transitional package. It can safely be removed. Package: python-dipy Source: dipy Version: 0.14.0-1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8631 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), python-numpy (>= 1:1.7.1~), python-scipy, python-h5py, python-dipy-lib (>= 0.14.0-1~nd17.10+1+nd18.04+1) Recommends: python-matplotlib, python-vtk, python-nose, python-nibabel (>= 2.1.0) Suggests: ipython Provides: python2.7-dipy Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy_0.14.0-1~nd17.10+1+nd18.04+1_all.deb Size: 3047844 SHA256: cd1f3c6f9c9b00d9d94af6b03f2852e625f4b8d532f386c336543ee708bf3f68 SHA1: 2138cdeb7977c44d51898122fc3d77fdea96fece MD5sum: 647d06f0f4453feaac6b40a1fc9b74af Description: Python library for the analysis of diffusion MRI datasets DIPY is a software project for computational neuroanatomy. It focuses on diffusion magnetic resonance imaging (dMRI) analysis and tractography but also contains implementations of other computational imaging methods such as denoising and registration that are applicable to the greater medical imaging and image processing communities. Additionally, DIPY is an international project which brings together scientists across labs and countries to share their state-of-the-art code and expertise in the same codebase, accelerating scientific research in medical imaging. . Here are some of the highlights: - Reconstruction algorithms: CSD, DSI, GQI, DTI, DKI, QBI, SHORE and MAPMRI - Fiber tracking algorithms: deterministic and probabilistic - Native linear and nonlinear registration of images - Fast operations on streamlines (selection, resampling, registration) - Tractography segmentation and clustering - Many image operations, e.g., reslicing or denoising with NLMEANS - Estimation of distances/correspondences between streamlines and connectivity matrices - Interactive visualization of streamlines in the space of images Python-Version: 2.7 Package: python-dipy-doc Source: dipy Version: 0.14.0-1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 16545 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-dipy Homepage: http://dipy.org Priority: extra Section: doc Filename: pool/main/d/dipy/python-dipy-doc_0.14.0-1~nd17.10+1+nd18.04+1_all.deb Size: 12639612 SHA256: 0e598975843e08be440aa6953968e8215f93af0981b4875b444f886b8b9d5b1f SHA1: 8f130334485208428cb21c21036806274dd1d440 MD5sum: 7f8814cbb2032c5d97749fb0493a2776 Description: Python library for the analysis of diffusion MRI datasets -- documentation DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides the documentation in HTML format. Package: python-dipy-lib Source: dipy Version: 0.14.0-1~nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 11401 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.13.1), python-numpy-abi9, python (<< 2.8), python (>= 2.7), libc6 (>= 2.4), libgomp1 (>= 4.9) Provides: python2.7-dipy-lib Homepage: http://dipy.org Priority: extra Section: python Filename: pool/main/d/dipy/python-dipy-lib_0.14.0-1~nd17.10+1+nd18.04+1_i386.deb Size: 1712768 SHA256: 4273cdce8c8cd840933dc8b8268213fd2b3bbfee4c563d2f06deb13607b727e7 SHA1: 010e679b489083857b8698e38c479ff3856d9f87 MD5sum: aa559e1a3b423fa807a182b27f918d74 Description: Python library for the analysis of diffusion MRI datasets -- extensions DIPY is a library for the analysis of diffusion magnetic resonance imaging data. . This package provides architecture-dependent builds of the extensions. Python-Version: 2.7 Package: python-duecredit Source: duecredit Version: 0.6.5-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 246 Depends: neurodebian-popularity-contest, python-citeproc, python-requests, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python-duecredit_0.6.5-1~nd18.04+1_all.deb Size: 53020 SHA256: 0c0f93caa1dd5a265889d748a4c9c82fb2de0171ab76223073285b1ca01951a9 SHA1: bd22e4336bf7fb43ccccccac35c735e4eb41e61b MD5sum: 61e7307b65517018afef5d9ddef1e829 Description: Publications (and donations) tracer - Python 2.X duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python-exif Version: 2.1.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-exif Homepage: https://github.com/ianare/exif-py Priority: extra Section: python Filename: pool/main/p/python-exif/python-exif_2.1.2-1~nd18.04+1_all.deb Size: 27760 SHA256: f1744c010e29ac3c18594b06bee3aec8c7dae940ee7462816a886a2a433aa971 SHA1: a318f8898fc2489647c1dd4804f5b6d5df33a857 MD5sum: 227cf7e2094e182c0418f1cf4beef0be Description: Python library to extract Exif data from TIFF and JPEG files This is a Python library to extract Exif information from digital camera image files. It contains the EXIF.py script and the exifread library. . This package provides the Python 2.x module. Package: python-fsl Source: fslpy Version: 1.2.2-2~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, python-lxml, python-nibabel, python-six (>= 1.0~), python-deprecation, python-indexed-gzip, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Recommends: python-wxgtk3.0 Conflicts: fsl-melview (<= 1.0.1+git9-ge661e05~dfsg.1-1) Provides: python2.7-fsl Priority: optional Section: python Filename: pool/main/f/fslpy/python-fsl_1.2.2-2~nd17.10+1+nd18.04+1_all.deb Size: 84332 SHA256: 2afcd0dd580fe5131119664966196b3133b76a837413462b5b642e6ebae00830 SHA1: 30bed1680e6c061ecdb3f98dac5c429de105ee46 MD5sum: f5549bd48ab8dfd821766e80425c88bc Description: FSL Python library Support library for FSL. . This package provides the Python 2 module. Package: python-fsleyes-props Source: fsleyes-props Version: 1.2.1-3~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 404 Depends: neurodebian-popularity-contest, python-wxgtk3.0, python-six (>= 1.0~), python-deprecation, python-matplotlib, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Conflicts: python-props (<= 1.0~) Replaces: python-props Provides: python-props, python2.7-fsleyes-props Priority: optional Section: python Filename: pool/main/f/fsleyes-props/python-fsleyes-props_1.2.1-3~nd17.10+1+nd18.04+1_all.deb Size: 75444 SHA256: 5efe94d355bf5fe20c4cc664e6bca8d5b4cbba4afb9fc4b651a958413bdfe3eb SHA1: 9cafb04e34afaa8ccaaaa5acea5b703b010eb21f MD5sum: 263ef61bed98a7aa5b5907359ea5a166 Description: Python descriptor framework Event programming framework with the ability for automatic CLI generation, and automatic GUI generation (with wxPython). . This package provides the Python 2 module. Package: python-fsleyes-widgets Source: fsleyes-widgets Version: 0.2.0-2~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 374 Depends: neurodebian-popularity-contest, python-wxgtk3.0, python-six (>= 1.0~), python-deprecation, python-matplotlib, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-fsleyes-widgets Priority: optional Section: python Filename: pool/main/f/fsleyes-widgets/python-fsleyes-widgets_0.2.0-2~nd17.10+1+nd18.04+1_all.deb Size: 68972 SHA256: 954027d626199276d859fa932271ecdd6caeb001955eb0acef186e603d498d5a SHA1: fbe3723d7e15e2a81cbaec8d931475c21dbf621d MD5sum: b5570aecdb7d967443e30dcc4aa0145c Description: Python descriptor framework A collection of GUI widgets and utilities, based on wxPython. . This package provides the Python 2 module. Package: python-httpretty Version: 0.8.14-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 98 Depends: neurodebian-popularity-contest, python-urllib3, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/gabrielfalcao/httpretty Priority: optional Section: python Filename: pool/main/p/python-httpretty/python-httpretty_0.8.14-1~nd18.04+1_all.deb Size: 21032 SHA256: 41332aef69212fba4bfb6e0bbef56bf7607726eef270c187a981049441024137 SHA1: d380f040887108c0f01baaef8d6eb8485154a30f MD5sum: d5cab5ede9fc2875b8c9bdcb0b9fc088 Description: HTTP client mock - Python 2.x Once upon a time a Python developer wanted to use a RESTful API, everything was fine but until the day he needed to test the code that hits the RESTful API: what if the API server is down? What if its content has changed ? . Don't worry, HTTPretty is here for you. . This package provides the Python 2.x module. Package: python-hypothesis Version: 3.44.1-1~bpo9+1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 610 Depends: neurodebian-popularity-contest, python-enum34, python-attr, python-coverage, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python-hypothesis_3.44.1-1~bpo9+1~nd18.04+1_all.deb Size: 120320 SHA256: 0d5d1e690c7eacbaa85530239f2cdaa4d533a9fa64b40263b9b630d6d2c0b100 SHA1: 8d55c6e7fc450927e5218797e7b5c4adc94c7987 MD5sum: 1e2b575ff76fc4070c695b74d3189798 Description: advanced Quickcheck style testing library for Python 2 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 2 module. Package: python-hypothesis-doc Source: python-hypothesis Version: 3.44.1-1~bpo9+1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1079 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: doc Filename: pool/main/p/python-hypothesis/python-hypothesis-doc_3.44.1-1~bpo9+1~nd18.04+1_all.deb Size: 143692 SHA256: 2f4b40f4aacb486cfc890fd16b9f9a43ab162b3fe2ca54b098184935548f6984 SHA1: c5b906e561b1d4268ff4526fd6a0436e6de5f74b MD5sum: eef5642ed0212fa77e389b81ab77a8cf Description: advanced Quickcheck style testing library (documentation) Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the documentation for Hypothesis. Package: python-indexed-gzip Source: indexed-gzip Version: 0.8.6-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1225 Depends: neurodebian-popularity-contest, cython, python-numpy (>= 1:1.13.1), libc6 (>= 2.4), zlib1g (>= 1:1.2.2.4), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-indexed-gzip Homepage: https://github.com/pauldmccarthy/indexed_gzip Priority: optional Section: python Filename: pool/main/i/indexed-gzip/python-indexed-gzip_0.8.6-1~nd18.04+1_i386.deb Size: 296636 SHA256: e7f944605c881f83d1639d8fb4771544aeb50aa2f4c113b93bcf4344427573cb SHA1: 8a671c5db92ba02c62a2af59dd152c0f7e089646 MD5sum: 1a453628ee178281db426a582c2c25f6 Description: fast random access of gzip files in Python Drop-in replacement `IndexedGzipFile` for the built-in Python `gzip.GzipFile` class that does not need to start decompressing from the beginning of the file when for every `seek()`. It gets around this performance limitation by building an index, which contains *seek points*, mappings between corresponding locations in the compressed and uncompressed data streams. Each seek point is accompanied by a chunk (32KB) of uncompressed data which is used to initialise the decompression algorithm, allowing to start reading from any seek point. If the index is built with a seek point spacing of 1MB, only 512KB (on average) of data have to be decompressed to read from any location in the file. . This package provides the Python 2 module. Package: python-joblib Source: joblib Version: 0.13.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 866 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), procps Recommends: python-numpy, python-pytest, python-simplejson, python-lz4, python-psutil Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.13.0-1~nd18.04+1_all.deb Size: 190024 SHA256: 58e9a9f97a41348ddc26a0430a2b85a961a4c083318c51545ee266a2da839cc7 SHA1: 42e5adc0f24ede27f201b91d805c37547bb7bb86 MD5sum: 8faa7475c69de0d84d805a24b7449701 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 2 version. Package: python-libxmp Source: python-xmp-toolkit Version: 2.0.1+git20140309.5437b0a-4~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libexempi3, python-tz, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-libxmp-doc Homepage: http://python-xmp-toolkit.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-xmp-toolkit/python-libxmp_2.0.1+git20140309.5437b0a-4~nd18.04+1_all.deb Size: 23376 SHA256: 03bc5e25132cdda4b7188eddc804b1c02d5086281416b5c371e3ffc0f642b323 SHA1: 5c40af82cb44589374df6b1210dcf31cdbd9a8f5 MD5sum: 55c68c2de45bbde1be94b1f402d626ef Description: Python library for XMP metadata Python XMP Toolkit is a library for working with XMP metadata, as well as reading/writing XMP metadata stored in many different file formats. . XMP (Extensible Metadata Platform) facilitates embedding metadata in files using a subset of RDF. Most notably XMP supports embedding metadata in PDF and many image formats, though it is designed to support nearly any file type. . This package provides Python bindings. Package: python-libxmp-doc Source: python-xmp-toolkit Version: 2.0.1+git20140309.5437b0a-4~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 237 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Recommends: python-libxmp, python3-libxmp Homepage: http://python-xmp-toolkit.readthedocs.org/ Priority: optional Section: doc Filename: pool/main/p/python-xmp-toolkit/python-libxmp-doc_2.0.1+git20140309.5437b0a-4~nd18.04+1_all.deb Size: 37176 SHA256: 04d289c82048bfec89269cc5a34b2223b07151f6c9862305d15447077e4d8b57 SHA1: 6492a907a187125002598188955f6ea18728a5fe MD5sum: 0c6aee0c62f81246fc5d013de40d0a33 Description: Python library for XMP metadata - documentation Python XMP Toolkit is a library for working with XMP metadata, as well as reading/writing XMP metadata stored in many different file formats. . XMP (Extensible Metadata Platform) facilitates embedding metadata in files using a subset of RDF. Most notably XMP supports embedding metadata in PDF and many image formats, though it is designed to support nearly any file type. . This package contains the documentation. Package: python-msgpack Source: msgpack-python Version: 0.4.8-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 239 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~), libc6 (>= 2.4) Provides: msgpack-python Homepage: https://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python-msgpack_0.4.8-1~nd18.04+1_i386.deb Size: 66232 SHA256: 793ecf600b13abbdbc33c7212ca6c59d5d21f77a9eafee1c9aadee78a7318238 SHA1: 7ac1c8ca27bf889d1fb9e2557765fdcbb0178132 MD5sum: fd7b1b3d3981ff1b0d19afbec70dc2ba Description: Python implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python extension module implementing the MessagePack format. Package: python-mvpa2 Source: pymvpa2 Version: 2.6.5-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8602 Depends: neurodebian-popularity-contest, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-mvpa2-lib (>= 2.6.5-1~nd18.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib, python-duecredit, python-mock Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.6.5-1~nd18.04+1_all.deb Size: 5106356 SHA256: a859f9b209a5e056239bb53dd3ed2ce770459bfaeac7cfb0ff9dc04a7636a100 SHA1: 5589ca034730bf44863d1711c5bb530ab10818ee MD5sum: 5e04676a31cc1ef914b06b70aecf132c Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.6.5-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 20441 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.6.5-1~nd18.04+1_all.deb Size: 4260928 SHA256: 872c0eccce4cb62d4fc15822d80d0ae2288d1c6e3dc77ccdeaa2c53a3170f95d SHA1: 7b4f46f487f07312f0b0e64c2d056e1ef610f559 MD5sum: 498f26718581a15f2366e011c6d64d09 Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.6.5-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 136 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5), libsvm3, python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.13.1), python-numpy-abi9, python:any (<< 2.8), python:any (>= 2.7~) Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.6.5-1~nd18.04+1_i386.deb Size: 52140 SHA256: 3f1bfbcacb1158230e5a8357953b4924cd72a81093ba555798188a7041a86e18 SHA1: b88c6512140e62b1d66336152cb4ff3dca637da8 MD5sum: 9bdd7d3f62ae634bf82f57ec0e2b4e6c Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-nibabel Source: nibabel Version: 2.3.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65238 Depends: neurodebian-popularity-contest, python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-scipy, python-six, python-bz2file Recommends: python-dicom, python-fuse Suggests: python-nibabel-doc, python-mock Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_2.3.2-1~nd18.04+1_all.deb Size: 2592920 SHA256: d5be54e5f0071c7e48ef481de599f766f1a1faba9de1b0859bd1c5e85c669463 SHA1: ba11fca9448391667857e3e4a7d9db323c7f9c62 MD5sum: 0ec0abf40c513bb54078b1ea5e8aba6c Description: Python bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package also provides a commandline tools: . - dicomfs - FUSE filesystem on top of a directory with DICOMs - nib-ls - 'ls' for neuroimaging files - parrec2nii - for conversion of PAR/REC to NIfTI images Package: python-nibabel-doc Source: nibabel Version: 2.3.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9115 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_2.3.2-1~nd18.04+1_all.deb Size: 1474636 SHA256: de1b23dde20ce611f4fb86f15ec463e0ca8059fdf74cb8d37bece0e79b28c46d SHA1: 3d40bec0bca37e251edec4e13cdf54529142a461 MD5sum: a579ac4843a6137cd046bd963507aa43 Description: documentation for NiBabel NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. . This package provides the documentation in HTML format. Package: python-nipy Source: nipy Version: 0.4.2-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 3547 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.2), python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), python-scipy, python-nibabel, python-nipy-lib (>= 0.4.2-2~nd18.04+1) Recommends: python-matplotlib, mayavi2, python-sympy Suggests: python-mvpa Provides: python2.7-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy_0.4.2-2~nd18.04+1_all.deb Size: 783300 SHA256: 617f00aa81de8fc80887429b3f7ed7171e06ff6cfe2097a1c73625bfea91423f SHA1: 02583b2b03e380b004071b13620162708cc6e9ac MD5sum: 712efe8584f061298c471009e1c9922b Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for - General linear model (GLM) statistical analysis - Combined slice time correction and motion correction - General image registration routines with flexible cost functions, optimizers and re-sampling schemes - Image segmentation - Basic visualization of results in 2D and 3D - Basic time series diagnostics - Clustering and activation pattern analysis across subjects - Reproducibility analysis for group studies Python-Version: 2.7 Package: python-nipy-doc Source: nipy Version: 0.4.2-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9415 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Recommends: python-nipy Homepage: http://neuroimaging.scipy.org Priority: extra Section: doc Filename: pool/main/n/nipy/python-nipy-doc_0.4.2-2~nd18.04+1_all.deb Size: 1903248 SHA256: cb615a6500d769246c4e381651f1d4838829e1a4549de1e2a3ac42e0fb3bb26f SHA1: e6d7a67914aa9019e1521f19737db722c0da1153 MD5sum: 634cdd3de1c7bfa1e77c17457d58019c Description: documentation and examples for NiPy This package contains NiPy documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation Package: python-nipy-lib Source: nipy Version: 0.4.2-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2785 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.13.1), python-numpy-abi9, python (<< 2.8), python (>= 2.7) Provides: python2.7-nipy-lib Homepage: http://neuroimaging.scipy.org Priority: extra Section: python Filename: pool/main/n/nipy/python-nipy-lib_0.4.2-2~nd18.04+1_i386.deb Size: 573372 SHA256: c38d10473157241df1bf86dbeed629407fecfad7afeb2c7e9158b656c408d44d SHA1: 29b61f35bfa2e58e2c4199b88115433094752d4d MD5sum: 74c7d9dd07545a85bc5e6d103831a7a4 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipy-lib-dbg Source: nipy Version: 0.4.2-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3028 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), python-numpy (>= 1:1.13.1), python-numpy-abi9, python-dbg (<< 2.8), python-dbg (>= 2.7), python-nipy-lib (= 0.4.2-2~nd18.04+1) Provides: python2.7-nipy-lib-dbg Homepage: http://neuroimaging.scipy.org Priority: extra Section: debug Filename: pool/main/n/nipy/python-nipy-lib-dbg_0.4.2-2~nd18.04+1_i386.deb Size: 646832 SHA256: df9f06826aca58cc40944a573875d4e66cfe8ee41b71e21bd4b32140eb1508bc SHA1: d31be190d4d3279a1e9a3c4664d26de5c81e9baa MD5sum: 984fe1633a77f5335eb67c6ae9ee8e43 Description: Analysis of structural and functional neuroimaging data NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. . This package provides debugging symbols for architecture-dependent builds of the libraries. Python-Version: 2.7 Package: python-nipype Source: nipype Version: 1.1.8-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10984 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-click, python-concurrent.futures, python-configparser, python-dateutil (>= 2.2), python-funcsigs, python-future, python-networkx (>= 1.3), python-nibabel (>= 1.0.0~), python-numpy, python-packaging, python-prov, python-scipy, python-simplejson, python-traits, python:any (>= 2.6.6-7~), python-traits (>= 4.5.0) | python-traits4 (>= 4.5.0), python-psutil Recommends: ipython, python-pytest, graphviz, python-xvfbwrapper, mayavi2, python-mock, python-pydotplus, python-pydot, python-cfflib Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants, python-pytest-xdist, python-bids Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_1.1.8-1~nd18.04+1_all.deb Size: 1890904 SHA256: 4032003df103c3fdc402b90fd32babf492ff5bdf0706630e890fac8523004c13 SHA1: a65cb617e3abee751a5f67285b0345de2e776527 MD5sum: 80891acc831beef02368d094e4d482b0 Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 1.1.8-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38595 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_1.1.8-1~nd18.04+1_all.deb Size: 17635736 SHA256: 8f9cea1b86603a9def2f89629e0593f1eee617778017bf05bd4018543efd3b0d SHA1: dc3e38b520f458f6393f9088742540ea9a0e28db MD5sum: ccda902172731363c7bb58b45a1dceb4 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-pandas Source: pandas Version: 0.23.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12452 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-dateutil, python-numpy (>= 1:1.7~), python-tz, python:any (>= 2.6.6-7~), python-pandas-lib (>= 0.23.3-1~nd18.04+1), python-pkg-resources, python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: https://pandas.pydata.org/ Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.23.3-1~nd18.04+1_all.deb Size: 1743236 SHA256: 51f619068360de414a3f7487eb9b1dc9b6982e5876d91341c978c1883f4ea7f1 SHA1: 1cb5048e40fa73a88966fb656462cb458e3cb35d MD5sum: c8b5476836e10455bd2c6a48aca19080 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.23.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 36 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-mathjax Suggests: python-pandas Homepage: https://pandas.pydata.org/ Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.23.3-1~nd18.04+1_all.deb Size: 18236 SHA256: 22e2bb53b59b52d2fdee550a52feb79fbba12cf34ef043880645c9cdaf7c698b SHA1: 9472e41e18721d039692eb7fb072bb491a0e3b59 MD5sum: fb1aca469ba7c9e1d8c7650332fe0c9e Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.23.3-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 16831 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.13.1), python-numpy-abi9, python (<< 2.8), python (>= 2.7) Provides: python2.7-pandas-lib Homepage: https://pandas.pydata.org/ Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.23.3-1~nd18.04+1_i386.deb Size: 2789228 SHA256: 9bfb987ec1c1e6f0478c9cb1e5a514c8580741d924c57348271d9b22f6304793 SHA1: f58f5957edc01efc47013f7b17faedd6190dd439 MD5sum: 221d94c778067d4f918c106657991c61 Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-patsy Source: patsy Version: 0.5.0+git13-g54dcf7b-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 780 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-six, python:any (>= 2.6.6-7~) Recommends: python-pandas, python-openpyxl Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python-patsy_0.5.0+git13-g54dcf7b-1~nd18.04+1_all.deb Size: 168356 SHA256: 8efeef8c7b7ddf5e1c83e399b4fa22a2402900029fd3f44e4f586e8d1cd8e070 SHA1: 76bf15bf4717b77eac9c8832e3101fdaf3c99205 MD5sum: 079b4d1820538b630c0cc492c5b0000a Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 2 version. Package: python-patsy-doc Source: patsy Version: 0.5.0+git13-g54dcf7b-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1188 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-patsy Homepage: http://github.com/pydata/patsy Priority: optional Section: doc Filename: pool/main/p/patsy/python-patsy-doc_0.5.0+git13-g54dcf7b-1~nd18.04+1_all.deb Size: 343700 SHA256: 322973a22358b5e11f495deedd89a33e328bdd9dd5d240233f2d1a0e3b43f6ac SHA1: 558594330c09672372aa4a715fefe178c1a2d9dd MD5sum: db50469e0ef1a50614badf52d152918d Description: documentation and examples for patsy This package contains documentation and example scripts for python-patsy. Package: python-pprocess Source: pprocess Version: 0.5-2~nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 762 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-pprocess Homepage: http://www.boddie.org.uk/python/pprocess.html Priority: optional Section: python Filename: pool/main/p/pprocess/python-pprocess_0.5-2~nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 83108 SHA256: 8ae099383d8c157ae1300aaf8cf62bc0b9e23cb636813b168f781b2c8379df59 SHA1: d0073bb3d9099579f73c5f3bc814e88812cbc34d MD5sum: ac9d0604892092eb645835244e5eb2ba Description: elementary parallel programming for Python The pprocess module provides elementary support for parallel programming in Python using a fork-based process creation model in conjunction with a channel-based communications model implemented using socketpair and poll. On systems with multiple CPUs or multicore CPUs, processes should take advantage of as many CPUs or cores as the operating system permits. Package: python-props Source: props Version: 0.10.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 651 Depends: neurodebian-popularity-contest, python-wxgtk3.0, python-matplotlib, python-numpy, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Provides: python2.7-props Priority: optional Section: python Filename: pool/main/p/props/python-props_0.10.1-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 117480 SHA256: 25eda699c2fb413e4a54006ba2fe99acaf7e444d2b8377cf0d3ca8d6fb7c4ff0 SHA1: 13e829aa2775b53b096e8c0f075e79d4fac3a4bf MD5sum: 05009edec10f60423d2ce747b3b0e056 Description: Python descriptor framework Event programming framework with the ability for automatic CLI generation, and automatic GUI generation (with wxPython). . This package provides the Python 2 module. Package: python-pydicom Source: pydicom Version: 1.2.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14179 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~) Recommends: python-numpy, python-pil Suggests: python-matplotlib, python-gdcm Breaks: python-dicom (<< 1~) Replaces: python-dicom (<< 1~) Provides: python-dicom Homepage: https://pydicom.github.io Priority: optional Section: python Filename: pool/main/p/pydicom/python-pydicom_1.2.1-1~nd18.04+1_all.deb Size: 4396928 SHA256: b00193d6e31148d148bd759287447789d2143367655b573a410fcbc4e81cbf13 SHA1: 804ee27d0a16234a28580023d930a6664225d39a MD5sum: fd62acd6f02cf16443b10c2c1117ad47 Description: DICOM medical file reading and writing (Python 2) pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. . This package installs the module for Python 2. Package: python-pydicom-doc Source: pydicom Version: 1.2.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2791 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Breaks: python-dicom-doc (<< 1~) Replaces: python-dicom-doc (<< 1~) Provides: python-dicom-doc Homepage: https://pydicom.github.io Priority: optional Section: doc Filename: pool/main/p/pydicom/python-pydicom-doc_1.2.1-1~nd18.04+1_all.deb Size: 345884 SHA256: 339d8c5436f3dd776a669ef38952452a8f2522460cb009c89cc6e928b52fe823 SHA1: 1dc24a38862a3de40bbab2b2a896f1bae70fa4be MD5sum: da130241d4d5fab244f7f59dd1165f7a Description: DICOM medical file reading and writing (documentation) pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. . This package contains the documentation. Package: python-pydot Source: pydot Version: 1.2.3-1.1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, python-pyparsing (>= 2.0.1+dfsg1-1), python:any (<< 2.8), python:any (>= 2.7.5-5~), graphviz Homepage: https://github.com/erocarrera/pydot Priority: optional Section: python Filename: pool/main/p/pydot/python-pydot_1.2.3-1.1~nd17.10+1+nd18.04+1_all.deb Size: 20560 SHA256: 46529b3c6a0f2a0a924f39aa1875a0fba4a636eb76d614d02e90647918da9a5c SHA1: 7f1a688ad4549db5d372360eff00c339da287c3d MD5sum: ac2c61010959580243595a75c8732436 Description: Python interface to Graphviz's dot pydot allows one to easily create both directed and non directed graphs from Python. Currently all attributes implemented in the Dot language are supported. . Output can be inlined in Postscript into interactive scientific environments like TeXmacs, or output in any of the format's supported by the Graphviz tools dot, neato, twopi. Package: python-pynwb Source: pynwb Version: 0.5.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 687 Depends: neurodebian-popularity-contest, python-dateutil, python-h5py, python-numpy, python-pandas, python-requests, python-ruamel.yaml, python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/NeurodataWithoutBorders/pynwb Priority: optional Section: python Filename: pool/main/p/pynwb/python-pynwb_0.5.1-1~nd18.04+1_all.deb Size: 98156 SHA256: 3cc7b8a3da93334f4a3fb44e42f2bb425b6192db4cc2ffaaeb236ff6d03004a9 SHA1: d506818c38749c6da37f057c5b59b2d429d0d0d0 MD5sum: 2f4be911f2b80dbec3ec8e62f56a9c39 Description: Python library for working with Neurodata in the NWB format PyNWB is a Python package for working with NWB files. It provides a high-level API for efficiently working with Neurodata stored in the NWB format. . Neurodata Without Borders: Neurophysiology (NWB:N) is a project to develop a unified data format for cellular-based neurophysiology data, focused on the dynamics of groups of neurons measured under a large range of experimental conditions. Package: python-pyperclip Version: 1.6.0-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 42 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), xclip | xsel | python-gi | python-qt4 Homepage: https://github.com/asweigart/pyperclip Priority: optional Section: python Filename: pool/main/p/python-pyperclip/python-pyperclip_1.6.0-2~nd18.04+1_all.deb Size: 9516 SHA256: 03fbfab1fdeb0edce08c2bc8305ca1001062bac41998c1390e14d1d06fe669db SHA1: 09073d95bf783414de0c303f45e07793007c3e72 MD5sum: 4ba75f1dfbda8d071a9a5a3ad886694d Description: Cross-platform clipboard module for Python This module is a cross-platform Python module for copy and paste clipboard functions. . It currently only handles plaintext. Package: python-requests Source: requests Version: 2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 243 Depends: neurodebian-popularity-contest, python-urllib3 (>= 1.12), python:any (<< 2.8), python:any (>= 2.7.5-5~), ca-certificates, python-chardet Suggests: python-ndg-httpsclient, python-openssl, python-pyasn1 Breaks: httpie (<< 0.9.2) Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python-requests_2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 68300 SHA256: 00ea179e2885183c035a39cf0e9b3662275f88dc2a7f656a35ea1187b0fa8532 SHA1: 7346cfc18d6164c02a85a6d571cfa61835e41a00 MD5sum: 1c2977f809255bfdc23281e18af95632 Description: elegant and simple HTTP library for Python2, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts Package: python-requests-whl Source: requests Version: 2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 353 Depends: neurodebian-popularity-contest, ca-certificates, python-urllib3-whl Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python-requests-whl_2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 319100 SHA256: 835245b149dd24dc4ecfce54c285f7416a95421b1f3a28a04980e0bb80f2ac01 SHA1: 0db33718d54f707e368a8f7da749bfef07816373 MD5sum: 257c2a4ec35a3f87da20f2e62feb3609 Description: elegant and simple HTTP library for Python, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts . This package provides the universal wheel. Package: python-skimage Source: skimage Version: 0.14.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26057 Depends: neurodebian-popularity-contest, python-matplotlib (>= 1.3.1), python-networkx (>= 1.8), python-numpy, python-pil, python-scipy, python-six (>= 1.10.0), python-skimage-lib (>= 0.14.0-1~nd18.04+1), python (<< 2.8), python (>= 2.7), python-cloudpickle, python-pywt, python:any (>= 2.6.6-7~) Recommends: python-pytest, python-qt4 Suggests: python-opencv, python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage_0.14.0-1~nd18.04+1_all.deb Size: 19923008 SHA256: 2c0b7c597ab364af409dc9efaa5c41004b06435b1cd46764a65b974d7a0692bb SHA1: a526b8db5e19b6270e7997a4bbaec3d17fe2672b MD5sum: 62ca557896e419274a78e77b594f9d00 Description: Python modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 2 module. Package: python-skimage-doc Source: skimage Version: 0.14.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1672 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Suggests: python-skimage Multi-Arch: foreign Homepage: http://scikit-image.org Priority: optional Section: doc Filename: pool/main/s/skimage/python-skimage-doc_0.14.0-1~nd18.04+1_all.deb Size: 786844 SHA256: ecef6924626f3f9db373e7fda51a01c63452b412abe8638ba4b93623952c3fce SHA1: 0d94c3d3766f64f7fab928517c1cff1b66eb2385 MD5sum: e458c9f936989048694957f96a0a8dc9 Description: Documentation and examples for scikit-image scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package contains documentation and example scripts for python-skimage. Package: python-skimage-lib Source: skimage Version: 0.14.0-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10637 Depends: neurodebian-popularity-contest, python-numpy (>= 1:1.13.1), python-numpy-abi9, python (<< 2.8), python (>= 2.7), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Recommends: python-skimage Provides: python2.7-skimage-lib Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python-skimage-lib_0.14.0-1~nd18.04+1_i386.deb Size: 1401848 SHA256: 2ef1c1c9ac76b88f280d1f3febba5e685de558b8f6d68f618058c401c671b7a5 SHA1: cb58ed71a1d6480d1432be6daa09da77f79ce126 MD5sum: 2507d3ee0ecd59cc342c8b5d42e51182 Description: Optimized low-level algorithms for scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 2 libraries. Package: python-sklearn Source: scikit-learn Version: 0.20.0+dfsg-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7540 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.20.0+dfsg-2~nd18.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-pytest, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.20.0+dfsg-2~nd18.04+1_all.deb Size: 1517588 SHA256: fdc84dda0f0af1815d9e8670491673b141b0c43a0a70e2d7a10522be449be827 SHA1: b8e91bcdf6dd4f68349c8876731bbc16c5aaff89 MD5sum: 2636a70f83786c3205f466cf4fbf7afc Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.20.0+dfsg-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 87370 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), libjs-bootstrap, libjs-mathjax Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Built-Using: sphinx (= 1.6.7-1ubuntu1) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.20.0+dfsg-2~nd18.04+1_all.deb Size: 39843940 SHA256: e4434800a6ec6ee767ee7432119e2f0ca89c8b5c8699244191152da33e9b95ac SHA1: 7bf40186dd0aad80494be2cf8f43f1c680b5be16 MD5sum: 0f56f8817338ece186bb3d3febeafcc5 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.19.2-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 7012 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.13.1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7~) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.19.2-1~nd18.04+1_i386.deb Size: 1365932 SHA256: b4bce0edaf86e22451aab5126bb29c334d45e36579c8189d70256263a390a7c3 SHA1: 8bf33b1d1488a4504d700b1e9a6cfa4b24255cea MD5sum: 91279ac15345441ff65b756a644962af Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-sphinx-gallery Source: sphinx-gallery Version: 0.2.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 217 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-matplotlib, python-pil, python-sphinx Suggests: python-sphinx-gallery-doc, mayavi2, python-seaborn Homepage: https://sphinx-gallery.github.io/ Priority: optional Section: python Filename: pool/main/s/sphinx-gallery/python-sphinx-gallery_0.2.0-1~nd18.04+1_all.deb Size: 71888 SHA256: 187c96a7dc694bace9c60a3ecf33e40955a57f94161b4e7943a3f5bdd04217f6 SHA1: 0b44b91d42e5a2a2a37730e1616068faf3e4adc3 MD5sum: 2ea0bf7c48acd64c4f87b3dc054b1a90 Description: extension that builds an HTML gallery of examples from Python scripts * Simple examples that run out of the box are the best way to learn a library * Pleasing, organized, visual layouts * Links, searching, backlinks throughout examples and documentation . This package contains the Python 2 version of sphinx-gallery. Package: python-sphinx-gallery-doc Source: sphinx-gallery Version: 0.2.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2597 Depends: neurodebian-popularity-contest Homepage: https://sphinx-gallery.github.io/ Priority: optional Section: doc Filename: pool/main/s/sphinx-gallery/python-sphinx-gallery-doc_0.2.0-1~nd18.04+1_all.deb Size: 1328876 SHA256: f63a6b2046fcfa3abc217e3e837fdc05ecf1c76724300ca9e0eb9e55adec1c1d SHA1: e58fcdbdc4f33f153840530042dc86a64d17f56d MD5sum: 19613e357bb27018a73b292c95469c2c Description: extension that builds an HTML gallery of examples from Python scripts (Doc) * Simple examples that run out of the box are the best way to learn a library * Pleasing, organized, visual layouts * Links, searching, backlinks throughout examples and documentation . This package contains documentation for sphinx-gallery. Package: python-stfio Source: stimfit Version: 0.15.8-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1439 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.13.1), python-numpy-abi9, python2.7, python:any (<< 2.8), python:any (>= 2.7.5-5~), libblas3 | libblas.so.3, libc6 (>= 2.7), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:3.0), libhdf5-100, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libsuitesparse-dev, zlib1g-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.15.8-1~nd18.04+1_i386.deb Size: 503784 SHA256: d85f0f8d693af0411744f5e2721c6ee12cdd77435c6b68349889fd7fd6ab50a2 SHA1: 0dd8edcd2da3cc180066f5b6c38dee228717fd30 MD5sum: a9dc4ca2c9353d1b88d4e74203c16ed4 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-sympy Source: sympy Version: 1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26373 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-mpmath Recommends: python-pil, python-ctypes, ipython, python-numpy, python-pyglet, python-gmpy Suggests: texlive-fonts-extra, dvipng, python-sympy-doc Enhances: isympy Homepage: http://sympy.org/ Priority: optional Section: python Filename: pool/main/s/sympy/python-sympy_1.3-1~nd18.04+1_all.deb Size: 3499420 SHA256: 77e3ecb1c95afd35e9b2562192d734f82e50b29c67142bfa49931bf0da739b99 SHA1: 8fe0199bf603abc853ec8db4cfda2c3a32b572b2 MD5sum: 00b59c837d3c01b249245ba023cef078 Description: Computer Algebra System (CAS) in Python SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. Package: python-sympy-doc Source: sympy Version: 1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 58949 Depends: neurodebian-popularity-contest Suggests: python-sympy Homepage: http://sympy.org/ Priority: optional Section: doc Filename: pool/main/s/sympy/python-sympy-doc_1.3-1~nd18.04+1_all.deb Size: 7248216 SHA256: dc49d55e563905f985e295e8df67ecc02838547c8ad46d3fb8de229bdec557e5 SHA1: e3da47048666277ac57d28174f2d4aa45f5fc16a MD5sum: 726cd27aba9a4edd8e96303b10dab7d1 Description: Computer Algebra System (CAS) in Python - Documentation SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. . This package contains the documentation for sympy Python module. Package: python-urllib3 Version: 1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-six Recommends: ca-certificates, python-ndg-httpsclient, python-openssl, python-pyasn1 Suggests: python-ntlm Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3_1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 65532 SHA256: c145793413b31e82702be3241a1e66132d8893276ac9e49337753667c31be299 SHA1: 2829979657aa7e8c9a03a35c4680aa8f102af336 MD5sum: d43700c36d4af637d0e59926e4156dcb Description: HTTP library with thread-safe connection pooling for Python urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. Package: python-urllib3-whl Source: python-urllib3 Version: 1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 102 Depends: neurodebian-popularity-contest, python-six-whl Recommends: ca-certificates Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python-urllib3-whl_1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 93052 SHA256: 658e64c416fbafd9bc070f9a20c9d0ddab39668df2bf08b2f8e36468b798cfdd SHA1: 30caaaaf95c7b1227cce9e7c1cecef270b129e5c MD5sum: dce299ce3ade22de0085cded08bedab0 Description: HTTP library with thread-safe connection pooling urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. . This package contains the universal wheel. Package: python-wrapt Version: 1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python-six, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~), libc6 (>= 2.4) Homepage: https://github.com/GrahamDumpleton/wrapt Priority: optional Section: python Filename: pool/main/p/python-wrapt/python-wrapt_1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 28468 SHA256: 31e20f6f609a5051e69e54b793309a18cb5d8058b98127475fde57f3c2057d9f SHA1: 7b885c5e3e9ae781d94a4a96d5ae3cc8c5981ac7 MD5sum: 5902157192c95c9527b25a67311b9980 Description: decorators, wrappers and monkey patching. - Python 2.x The aim of the wrapt module is to provide a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions. . The wrapt module focuses very much on correctness. It therefore goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour. . To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled. . This package contains the Python 2.x module. Package: python-wrapt-doc Source: python-wrapt Version: 1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 461 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0), sphinx-rtd-theme-common Homepage: https://github.com/GrahamDumpleton/wrapt Priority: optional Section: doc Filename: pool/main/p/python-wrapt/python-wrapt-doc_1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 49736 SHA256: 5defb7d4bef5f2b569c3b7b2dce81c4afe346bdb9b7d5d971b6909743e328477 SHA1: dc2cd4e998317d4dbf8da1d58926798629b350cb MD5sum: 073fb58d36ceee0a4dadfee6a852098a Description: decorators, wrappers and monkey patching. - doc The aim of the wrapt module is to provide a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions. . The wrapt module focuses very much on correctness. It therefore goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour. . To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled. . This package contains the documentation. Package: python-xlwt Source: xlwt Version: 1.3.0-2~nd0~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 445 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-xlrd, python-xlrt-doc Homepage: https://pypi.python.org/pypi/xlwt Priority: optional Section: python Filename: pool/main/x/xlwt/python-xlwt_1.3.0-2~nd0~nd18.04+1_all.deb Size: 83872 SHA256: 5c953000522ed0a40179c07ea8dc0ea4ac2ae31e1b074081efae316f1562d48c SHA1: 4a06974461b0e57c4412136b0a720966037a8d89 MD5sum: f5e1690584d1b6246262282b0b2a478f Description: module for writing Microsoft Excel spreadsheet files - Python 2.7 This package provides a pure Python module for writing spreadsheet files readable by Excel 97/2000/XP/2003, OpenOffice.org Calc, and Gnumeric. Excel spreadsheets can be generated on any platform without needing Excel or a COM server. . Xlwt is a fork of the unmaintained pyExcelerator module with several bugfixes and enhancements. For the functionality previously provided by the parse_xls function, see the python-xlrd package. . This package provides the Python 2.7 module. Package: python-xlwt-doc Source: xlwt Version: 1.3.0-2~nd0~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 246 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Breaks: python-xlwt (<< 1.3.0) Replaces: python-xlwt (<< 1.3.0) Homepage: https://pypi.python.org/pypi/xlwt Priority: optional Section: doc Filename: pool/main/x/xlwt/python-xlwt-doc_1.3.0-2~nd0~nd18.04+1_all.deb Size: 52708 SHA256: ad2a10c48e05f4c94e60d9147e9bd4fa52e5c7b133d6ca325578bee0142023b0 SHA1: 4c4e7768dafda6758505b255ae8942dd9be7b389 MD5sum: 16b3706edf48716c2a3563d1a2089932 Description: module for writing Microsoft Excel spreadsheet files - doc This package provides a pure Python module for writing spreadsheet files readable by Excel 97/2000/XP/2003, OpenOffice.org Calc, and Gnumeric. Excel spreadsheets can be generated on any platform without needing Excel or a COM server. . Xlwt is a fork of the unmaintained pyExcelerator module with several bugfixes and enhancements. For the functionality previously provided by the parse_xls function, see the python-xlrd package. . This package provides the documentation. Package: python3-boto Source: python-boto Version: 2.44.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5140 Depends: neurodebian-popularity-contest, python3-requests, python3:any (>= 3.3.2-2~), python3-six Homepage: https://github.com/boto/boto Priority: optional Section: python Filename: pool/main/p/python-boto/python3-boto_2.44.0-1~nd18.04+1_all.deb Size: 739796 SHA256: d595e83ff222c6241630fd26fa46fb04a76e75e63cf614e22a54114fc858df27 SHA1: 031953dfdf305ffb24a442a94b31cfecec9136ab MD5sum: 86dd962c7e54994f10498e0a331f50ea Description: Python interface to Amazon's Web Services - Python 3.x Boto is a Python interface to the infrastructure services available from Amazon. . Boto supports the following services: * Elastic Compute Cloud (EC2) * Elastic MapReduce * CloudFront * DynamoDB * SimpleDB * Relational Database Service (RDS) * Identity and Access Management (IAM) * Simple Queue Service (SQS) * CloudWatch * Route53 * Elastic Load Balancing (ELB) * Flexible Payment Service (FPS) * Simple Storage Service (S3) * Glacier * Elastic Block Store (EBS) * and many more... . This package provides the Python 3.x module. Package: python3-bz2file Source: python-bz2file Version: 0.98-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 35 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/nvawda/bz2file Priority: optional Section: python Filename: pool/main/p/python-bz2file/python3-bz2file_0.98-1~nd18.04+1_all.deb Size: 8008 SHA256: 6da2d779a7143e865f5d2f04f7ef0eb0535651c5ceabe7f4c36f419e74ed4bd0 SHA1: bb2994e294d8f7e89d1fb08a5f6a191a04f2e04e MD5sum: 94de06b99b7d760c0e358da174bc84d1 Description: Python3 library for reading and writing bzip2-compressed files Bz2file is a Python library for reading and writing bzip2-compressed files. . It contains a drop-in replacement for the file interface in the standard library's bz2 module, including features from the latest development version of CPython that are not available in older releases. . Bz2file for Python3. Package: python3-dask Source: dask Version: 0.17.5-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2406 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-toolz Recommends: python3-cloudpickle, python3-partd, python3-numpy, python3-pandas, python3-requests Suggests: ipython, python-dask-doc, python3-bcolz, python3-blosc, python3-boto, python3-distributed (>= 1.21), python3-graphviz, python3-h5py, python3-psutil, python3-scipy, python3-sqlalchemy, python3-skimage, python3-sklearn, python3-tables Homepage: https://github.com/dask/dask Priority: optional Section: python Filename: pool/main/d/dask/python3-dask_0.17.5-2~nd18.04+1_all.deb Size: 429444 SHA256: e4e2e028704c221cf2f15ac486f0c9c07925e3b7c5029cd193d6062dcfe5858a SHA1: 8edbd6f93fcff30019dcd54dac803c7d2d6820b7 MD5sum: eb29c80b93c5f47a5e0b37932ddf7a06 Description: Minimal task scheduling abstraction for Python 3 Dask is a flexible parallel computing library for analytics, containing two components. . 1. Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads. 2. "Big Data" collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers. . This contains the Python 3 version. Package: python3-datalad Source: datalad Version: 0.11.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4320 Depends: neurodebian-popularity-contest, git-annex (>= 6.20180509~) | git-annex-standalone (>= 6.20180509~), patool, python3-appdirs, python3-distutils | libpython3-stdlib (<= 3.6.4~rc1-2), python3-fasteners, python3-git (>= 2.1.6~), python3-humanize, python3-iso8601, python3-keyrings.alt | python3-keyring (<= 8), python3-secretstorage, python3-keyring, python3-mock, python3-msgpack, python3-pil, python3-requests, python3-simplejson, python3-six (>= 1.8.0), python3-tqdm, python3-wrapt, python3-boto, python3-chardet, python3:any (>= 3.3.2-2~) Recommends: python3-exif, python3-github, python3-jsmin, python3-html5lib, python3-httpretty, python3-libxmp, python3-lzma, python3-mutagen, python3-nose, python3-pyperclip, python3-requests-ftp, python3-vcr, python3-whoosh Suggests: python3-duecredit, python3-bs4, python3-numpy, datalad-containers, datalad-crawler, datalad-neuroimaging Homepage: http://datalad.org Priority: optional Section: python Filename: pool/main/d/datalad/python3-datalad_0.11.1-1~nd18.04+1_all.deb Size: 899440 SHA256: 93ddd8f14c66d10761e016e5f9088a0813beea14358403a9a2c0a7aef1d76008 SHA1: 29561b6005e70b6af539ef53848d5f5d674d3400 MD5sum: 4b02cbf301a6107b9b8cc2f5d8548d99 Description: data files management and distribution platform DataLad is a data management and distribution platform providing access to a wide range of data resources already available online. Using git-annex as its backend for data logistics it provides following facilities built-in or available through additional extensions . - command line and Python interfaces for manipulation of collections of datasets (install, uninstall, update, publish, save, etc.) and separate files/directories (add, get) - extract, aggregate, and search through various sources of metadata (xmp, EXIF, etc; install datalad-neuroimaging for DICOM, BIDS, NIfTI support) - crawl web sites to automatically prepare and update git-annex repositories with content from online websites, S3, etc (install datalad-crawler) . This package installs the module for Python 3, and Recommends install all dependencies necessary for searching and managing datasets, publishing, and testing. If you need base functionality, install without Recommends. Package: python3-dcmstack Source: dcmstack Version: 0.7-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 186 Depends: neurodebian-popularity-contest, python3-dicom (>= 0.9.7~), python3-nibabel (>= 2.0~), python3-numpy, python3:any (>= 3.3.2-2~) Homepage: https://github.com/moloney/dcmstack Priority: optional Section: science Filename: pool/main/d/dcmstack/python3-dcmstack_0.7-1~nd18.04+1_all.deb Size: 35404 SHA256: 19625d707897416a8ccf524dcb795f22be674801039e418d368e951a39c3dbff SHA1: ec876269a5d192d958fdaa21b1c9f44099ba60ff MD5sum: 811308c223ac29cd4631c5af7979be21 Description: DICOM to NIfTI conversion - python3 package DICOM to NIfTI conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a NIfTI header extension or written out as a JSON formatted text file. . This package provides the Python3 package. Package: python3-dicom Source: pydicom Version: 1.2.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13 Depends: neurodebian-popularity-contest, python3-pydicom Homepage: https://pydicom.github.io Priority: optional Section: oldlibs Filename: pool/main/p/pydicom/python3-dicom_1.2.1-1~nd18.04+1_all.deb Size: 4904 SHA256: 76809ba6969e5f95059bc2fa9fc1ee3cc97a9d6a42ed7db074384ba2c51ca876 SHA1: cf3365611e9873603f994d216b7ac378b554dd86 MD5sum: a45830603c52e65f94e4ab885c90371e Description: transitional package for python3-pydicom This is a transitional package. It can safely be removed. Package: python3-duecredit Source: duecredit Version: 0.6.5-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 248 Depends: neurodebian-popularity-contest, python3-citeproc, python3-requests, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://github.com/duecredit/duecredit Priority: optional Section: python Filename: pool/main/d/duecredit/python3-duecredit_0.6.5-1~nd18.04+1_all.deb Size: 53296 SHA256: 61ea85c094f2056b47fb83da5ecdfdace08154eaf0495ff042cc1a6d347809a0 SHA1: ecd8e4a9e7d15617a94f538a794c86c1b4e49f6c MD5sum: 99323c2ed342b006c0c844358a2b51a5 Description: Publications (and donations) tracer duecredit is being conceived to address the problem of inadequate citation of scientific software and methods, and limited visibility of donation requests for open-source software. . It provides a simple framework (at the moment for Python only) to embed publication or other references in the original code so they are automatically collected and reported to the user at the necessary level of reference detail, i.e. only references for actually used functionality will be presented back if software provides multiple citeable implementations. . To get a sense of what duecredit is about, simply run or your analysis script with `-m duecredit`, e.g. . python3 -m duecredit examples/example_scipy.py Python-Egg-Name: duecredit Package: python3-exif Source: python-exif Version: 2.1.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 130 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Homepage: https://github.com/ianare/exif-py Priority: extra Section: python Filename: pool/main/p/python-exif/python3-exif_2.1.2-1~nd18.04+1_all.deb Size: 27832 SHA256: f8473c8061ec37db7bde4c804ace1b7e23038d9d5c646717d9f57a13b4bc8146 SHA1: 172c0124ababbcdc38099521895391b8ca5ef0a6 MD5sum: b30728754a0fc1c9264f95aa7147a4f0 Description: Python library to extract Exif data from TIFF and JPEG files This is a Python library to extract Exif information from digital camera image files. It contains the EXIF.py script and the exifread library. . This package provides the Python 3.x module. Package: python3-fsl Source: fslpy Version: 1.2.2-2~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 403 Depends: neurodebian-popularity-contest, python3-lxml, python3-nibabel, python3-six (>= 1.0~), python3-deprecation, python3-indexed-gzip, python3-numpy, python3-wxgtk4.0, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/f/fslpy/python3-fsl_1.2.2-2~nd17.10+1+nd18.04+1_all.deb Size: 84304 SHA256: 95d890bf94a09fc1ac1e3f0abec4704ea5efaec82c2a5aeca14835d0b9db2afc SHA1: a2d18cbd7f8b605aeb9cd831c56f349c1c2a6e25 MD5sum: 3eae59a019fbac0edf3f0124a0c5ea2f Description: FSL Python library Support library for FSL. . This package provides the Python 3 module. Package: python3-httpretty Source: python-httpretty Version: 0.8.14-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 98 Depends: neurodebian-popularity-contest, python3-urllib3, python3:any (>= 3.3.2-2~) Homepage: https://github.com/gabrielfalcao/httpretty Priority: optional Section: python Filename: pool/main/p/python-httpretty/python3-httpretty_0.8.14-1~nd18.04+1_all.deb Size: 21112 SHA256: 7871162f68154a7628fc9f5a51e82f1d6d89a357aecab26b74c2e2ad92a95ca1 SHA1: 76dd2f110a39d72c816f669ca2f1b92f04275b95 MD5sum: fe6acc47e8a7926eb3d23bd915e5ad53 Description: HTTP client mock - Python 3.x Once upon a time a Python developer wanted to use a RESTful API, everything was fine but until the day he needed to test the code that hits the RESTful API: what if the API server is down? What if its content has changed ? . Don't worry, HTTPretty is here for you. . This package provides the Python 3.x module. Package: python3-hypothesis Source: python-hypothesis Version: 3.44.1-1~bpo9+1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 610 Depends: neurodebian-popularity-contest, python3-attr, python3-coverage, python3:any (>= 3.3.2-2~) Suggests: python-hypothesis-doc Homepage: https://github.com/DRMacIver/hypothesis Priority: optional Section: python Filename: pool/main/p/python-hypothesis/python3-hypothesis_3.44.1-1~bpo9+1~nd18.04+1_all.deb Size: 120360 SHA256: 8483c480f0969af1f62f0c01476b3d0469371d0e5f2da39cc3c87526e288d6bf SHA1: 4120650bbf83f92f51f5a42096b542a58700be37 MD5sum: f957686ef39d10f908828d48a71c3b4a Description: advanced Quickcheck style testing library for Python 3 Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. . Hypothesis is both extremely practical and also advances the state of the art of unit testing by some way. It's easy to use, stable, and extremely powerful. If you're not using Hypothesis to test your project then you're missing out. . This package contains the Python 3 module. Package: python3-indexed-gzip Source: indexed-gzip Version: 0.8.6-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 1254 Depends: neurodebian-popularity-contest, cython3, python3-numpy, libc6 (>= 2.4), zlib1g (>= 1:1.2.2.4), python3 (<< 3.7), python3 (>= 3.6~), python3:any (>= 3.3.2-2~) Provides: python3.6-indexed-gzip Homepage: https://github.com/pauldmccarthy/indexed_gzip Priority: optional Section: python Filename: pool/main/i/indexed-gzip/python3-indexed-gzip_0.8.6-1~nd18.04+1_i386.deb Size: 308236 SHA256: c664e6c5b8f902b5cbea3332b13f4e65b4e67f50a5c6a34d90ec310cf97fe577 SHA1: 6925d4179421bfa98b281b8d1af3873967fd3735 MD5sum: 955f5e9247cf507cffd315b3d735de8f Description: fast random access of gzip files in Python Drop-in replacement `IndexedGzipFile` for the built-in Python `gzip.GzipFile` class that does not need to start decompressing from the beginning of the file when for every `seek()`. It gets around this performance limitation by building an index, which contains *seek points*, mappings between corresponding locations in the compressed and uncompressed data streams. Each seek point is accompanied by a chunk (32KB) of uncompressed data which is used to initialise the decompression algorithm, allowing to start reading from any seek point. If the index is built with a seek point spacing of 1MB, only 512KB (on average) of data have to be decompressed to read from any location in the file. . This package provides the Python 3 module. Package: python3-joblib Source: joblib Version: 0.13.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 861 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), procps Recommends: python3-numpy, python3-pytest, python3-simplejson, python3-psutil Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.13.0-1~nd18.04+1_all.deb Size: 187032 SHA256: 7b73d2ab248d6faf76a4c1b1fd5a1d7ec3dc2e58bad22b63071fec209101b846 SHA1: b9b4e54dcce46a9f4e60c7cbf4eccf8580588046 MD5sum: d0163a0fb3b3489d9be6e0a4b47a6b96 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: . - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. . This package contains the Python 3 version. Package: python3-libxmp Source: python-xmp-toolkit Version: 2.0.1+git20140309.5437b0a-4~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 145 Depends: neurodebian-popularity-contest, libexempi3, python3-tz, python3:any (>= 3.3.2-2~) Suggests: python-libxmp-doc Homepage: http://python-xmp-toolkit.readthedocs.org/ Priority: optional Section: python Filename: pool/main/p/python-xmp-toolkit/python3-libxmp_2.0.1+git20140309.5437b0a-4~nd18.04+1_all.deb Size: 23480 SHA256: 470301d9e17950b473864ca92376c79cbbf33b13e30964696087c838666e6b2a SHA1: 4fc2129798bcfd362848d68735e4070eb9691a98 MD5sum: a3b6a28dab3c32495fcd43036b49a5ad Description: Python3 library for XMP metadata Python XMP Toolkit is a library for working with XMP metadata, as well as reading/writing XMP metadata stored in many different file formats. . XMP (Extensible Metadata Platform) facilitates embedding metadata in files using a subset of RDF. Most notably XMP supports embedding metadata in PDF and many image formats, though it is designed to support nearly any file type. . This package provides Python3 bindings. Package: python3-msgpack Source: msgpack-python Version: 0.4.8-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 236 Depends: neurodebian-popularity-contest, python3 (<< 3.7), python3 (>= 3.6~), python3:any (>= 3.3.2-2~), libc6 (>= 2.4) Homepage: https://pypi.python.org/pypi/msgpack-python/ Priority: optional Section: python Filename: pool/main/m/msgpack-python/python3-msgpack_0.4.8-1~nd18.04+1_i386.deb Size: 65808 SHA256: 10bd4ade87a3fb9298344404b2e225ae8e579836870197c17d0979d15a7abe1c SHA1: 6646b9f5eaf877fb8f46ee6ca08605cb748ef066 MD5sum: b11413bd837ccb7d88852a4cce4359e8 Description: Python 3 implementation of MessagePack format MessagePack is a binary-based efficient object serialization format. It enables the exchange of structured objects between many languages like JSON. But unlike JSON, it is very fast and small. . This package contains a Python 3 extension module implementing the MessagePack format. Package: python3-nibabel Source: nibabel Version: 2.3.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65223 Depends: neurodebian-popularity-contest, python3-numpy (>= 1.2), python3:any (>= 3.3.2-2~), python3-scipy, python3-six Recommends: python3-dicom, python3-fuse Suggests: python-nibabel-doc, python3-mock Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python3-nibabel_2.3.2-1~nd18.04+1_all.deb Size: 2589456 SHA256: 5694b9e6f023a2b37e4baba67f2e10f9d34ee93ff971cf594d9d69a3efe89f3f SHA1: 1d953b266b8d5c69579e6b5140d6af0a706f4589 MD5sum: 09cfaa35e6de4f7ea471dee47935b5a1 Description: Python3 bindings to various neuroimaging data formats NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI. Package: python3-pandas Source: pandas Version: 0.23.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 12450 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.23.3-1~nd18.04+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: https://pandas.pydata.org/ Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.23.3-1~nd18.04+1_all.deb Size: 1743280 SHA256: 70ae0e91c6a422281c2d7a1688bfe73d8634fa423c5300b5afe84ee4625a6397 SHA1: 0dba4911012c5e4bdd229a88904fbad8c10492c4 MD5sum: 4ae88fae1397a00675baaa297c6f78fb Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.23.3-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 16664 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.13.1), python3-numpy-abi9, python3 (<< 3.7), python3 (>= 3.6~), python3:any (>= 3.2~) Homepage: https://pandas.pydata.org/ Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.23.3-1~nd18.04+1_i386.deb Size: 2769256 SHA256: 4a6e2bae7c82518fdbfe952e6130cb95e0cdc25510d1ad333ce762c6ce470d81 SHA1: b77aab581d92f8d82bda76f133dbe30b506b9358 MD5sum: 4cb9f1ffd46e3e469962928dd253308c Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-patsy Source: patsy Version: 0.5.0+git13-g54dcf7b-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 779 Depends: neurodebian-popularity-contest, python3-numpy, python3-six, python3:any (>= 3.3.2-2~) Recommends: python3-pandas Suggests: python-patsy-doc Homepage: http://github.com/pydata/patsy Priority: optional Section: python Filename: pool/main/p/patsy/python3-patsy_0.5.0+git13-g54dcf7b-1~nd18.04+1_all.deb Size: 168412 SHA256: 82234dc094bd4ef8eaf4369b9442d29b18697e9fac8d88fda8e5cce95a44ef5c SHA1: 31806f281b4c7bb04c5cbc377709640166b27d47 MD5sum: 610eab0fd127c02273d2f7758d298054 Description: statistical models in Python using symbolic formulas patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design matrices. . This package contains the Python 3 version. Package: python3-pydicom Source: pydicom Version: 1.2.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14179 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-pil Suggests: python3-matplotlib, python3-gdcm Breaks: python3-dicom (<< 1~) Replaces: python3-dicom (<< 1~) Provides: python3-dicom Homepage: https://pydicom.github.io Priority: optional Section: python Filename: pool/main/p/pydicom/python3-pydicom_1.2.1-1~nd18.04+1_all.deb Size: 4396728 SHA256: 8fb4a6fe72f83f2568ef06c2f69bfd975a16aa98bf2409c88e3eb0ca6dcedd06 SHA1: 8901ca70e7f7437d9a260e9ffe2e8d67fa48099b MD5sum: 247b967c1d58cb70a812a3e16745df5a Description: DICOM medical file reading and writing (Python 3) pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. . This package installs the module for Python 3. Package: python3-pydot Source: pydot Version: 1.2.3-1.1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: neurodebian-popularity-contest, python3-pyparsing (>= 2.0.1+dfsg1-1), python3:any (>= 3.3.2-2~), graphviz Homepage: https://github.com/erocarrera/pydot Priority: optional Section: python Filename: pool/main/p/pydot/python3-pydot_1.2.3-1.1~nd17.10+1+nd18.04+1_all.deb Size: 20008 SHA256: 41f4ca06d766dc94272217a3b5417db93a060b2c6164512af010f283ee97e6c1 SHA1: 066fd17c8ac2e53eaea3a917f229654a0a4d7a15 MD5sum: 45e40d63dca62c0694420a038d81522b Description: Python interface to Graphviz's dot (Python 3) pydot allows one to easily create both directed and non directed graphs from Python. Currently all attributes implemented in the Dot language are supported. . Output can be inlined in Postscript into interactive scientific environments like TeXmacs, or output in any of the format's supported by the Graphviz tools dot, neato, twopi. . This package contains pydot for Python 3. Package: python3-pynwb Source: pynwb Version: 0.5.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 687 Depends: neurodebian-popularity-contest, python3-dateutil, python3-h5py (>= 2.7.1), python3-numpy, python3-pandas, python3-requests, python3-ruamel.yaml, python3-six, python3:any (>= 3.3.2-2~) Homepage: https://github.com/NeurodataWithoutBorders/pynwb Priority: optional Section: python Filename: pool/main/p/pynwb/python3-pynwb_0.5.1-1~nd18.04+1_all.deb Size: 98164 SHA256: f612651e9723beb1a54208a033319cb3c4fe68725262b35c885917ee5d3edbbb SHA1: 2319c3d71cd8df7a2bbc4167efb5a17aedd78b45 MD5sum: e27b2e9778290c716aad3cf9be977ea8 Description: Python library for working with Neurodata in the NWB format PyNWB is a Python package for working with NWB files. It provides a high-level API for efficiently working with Neurodata stored in the NWB format. . Neurodata Without Borders: Neurophysiology (NWB:N) is a project to develop a unified data format for cellular-based neurophysiology data, focused on the dynamics of groups of neurons measured under a large range of experimental conditions. Package: python3-pyperclip Source: python-pyperclip Version: 1.6.0-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 42 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~), xclip | xsel | python3-gi | python3-pyqt4 Homepage: https://github.com/asweigart/pyperclip Priority: optional Section: python Filename: pool/main/p/python-pyperclip/python3-pyperclip_1.6.0-2~nd18.04+1_all.deb Size: 9624 SHA256: dbb4e17d7cc1047cff9a6d699f629cac709a491bdbe2a129e3cfe37c2be9fc34 SHA1: 9706c13d57ad0cfa3357062a7a72aa6b8422bbc9 MD5sum: c75563d873d66a10f3a2f823d87bb26f Description: Cross-platform clipboard module for Python3 This module is a cross-platform Python3 module for copy and paste clipboard functions. . It currently only handles plaintext. . This is the Python 3 version of the package. Package: python3-reprozip Source: reprozip Version: 1.0.14-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 167 Depends: neurodebian-popularity-contest, python3 (<< 3.7), python3 (>= 3.6~), python3-requests, python3-rpaths, python3-usagestats, python3-yaml, python3:any (>= 3.3.2-2~), libc6 (>= 2.7), libsqlite3-0 (>= 3.5.9) Multi-Arch: same Homepage: https://www.reprozip.org Priority: optional Section: python Filename: pool/main/r/reprozip/python3-reprozip_1.0.14-1~nd18.04+1_i386.deb Size: 46704 SHA256: d00b9565a2057b6d6e15d4ac3fc0db179cf43fbc9abfd0688d61dd82dd187343 SHA1: fd332c2497f6f33e95bc1e56ddb32617f1e37152 MD5sum: 05b6c3dad4013825c5cf46f544b05f78 Description: modules for the ReproZip packer ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science. . It tracks operating system calls and creates a package that contains all the binaries, files and dependencies required to run a given command on the author’s computational environment (packing step). A reviewer can then extract the experiment in his environment to reproduce the results (unpacking step). . This package provides the modules for Python 3. Package: python3-reprozip-dbg Source: reprozip Version: 1.0.14-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 202 Depends: neurodebian-popularity-contest, python3-dbg (<< 3.7), python3-dbg (>= 3.6~), python3-dbg:any (>= 3.3~), libc6 (>= 2.7), libsqlite3-0 (>= 3.5.9), python3-reprozip (= 1.0.14-1~nd18.04+1) Multi-Arch: same Homepage: https://www.reprozip.org Priority: optional Section: debug Filename: pool/main/r/reprozip/python3-reprozip-dbg_1.0.14-1~nd18.04+1_i386.deb Size: 99364 SHA256: 33ac6cadbfa3488b630bf48d48d5d41c08db41ed837e009047046c1fa808bf0e SHA1: 9e43b1443ed6e2ed33c99f86f3007a99675d9680 MD5sum: d0cab0009baccc738b069bbe67d093cc Description: debug extensions for the ReproZip packer ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science. . It tracks operating system calls and creates a package that contains all the binaries, files and dependencies required to run a given command on the author’s computational environment (packing step). A reviewer can then extract the experiment in his environment to reproduce the results (unpacking step). . This package provides the debug extensions for Python 3. Build-Ids: 61013398a2971d768011735f4dfd8654f7c1ba74 Package: python3-requests Source: requests Version: 2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 240 Depends: neurodebian-popularity-contest, python3-urllib3 (>= 1.12), python3:any (>= 3.3.2-2~), ca-certificates, python3-chardet Suggests: python3-ndg-httpsclient, python3-openssl, python3-pyasn1 Homepage: http://python-requests.org Priority: optional Section: python Filename: pool/main/r/requests/python3-requests_2.8.1-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 68096 SHA256: 294ae65338c8ed82338ad1634a1144f89129762c124744dc2977382cfeb036c4 SHA1: e4119f62c9c97e7a16db21879c881f349261a1a2 MD5sum: 89ca22e1cd036102bac29575c7c5cc8a Description: elegant and simple HTTP library for Python3, built for human beings Requests allow you to send HTTP/1.1 requests. You can add headers, form data, multipart files, and parameters with simple Python dictionaries, and access the response data in the same way. It's powered by httplib and urllib3, but it does all the hard work and crazy hacks for you. . Features . - International Domains and URLs - Keep-Alive & Connection Pooling - Sessions with Cookie Persistence - Browser-style SSL Verification - Basic/Digest Authentication - Elegant Key/Value Cookies - Automatic Decompression - Unicode Response Bodies - Multipart File Uploads - Connection Timeouts . This package contains the Python 3 version of the library. Package: python3-skimage Source: skimage Version: 0.14.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26053 Depends: neurodebian-popularity-contest, python3-matplotlib, python3-networkx, python3-numpy, python3-pil, python3-scipy, python3-six (>= 1.10.0), python3-skimage-lib (>= 0.14.0-1~nd18.04+1), python3-cloudpickle, python3-pywt, python3:any (>= 3.3.2-2~) Recommends: python3-pytest, python3-dask Suggests: python-skimage-doc Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage_0.14.0-1~nd18.04+1_all.deb Size: 19903844 SHA256: 4508b078b875aa138fd329c28cb513793e411df268fb51d49c5696433a55f4ce SHA1: 76db0817158359758e9b038f83d8af6fa41dc94f MD5sum: ec9253f15b08a3a6e46e1cfd3b7c1b6b Description: Python 3 modules for image processing scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations. . This package provides the Python 3 module. Package: python3-skimage-lib Source: skimage Version: 0.14.0-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 10161 Depends: neurodebian-popularity-contest, python3-numpy (>= 1:1.13.1), python3-numpy-abi9, python3 (<< 3.7), python3 (>= 3.6~), python3:any (>= 3.2~), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Recommends: python3-skimage Multi-Arch: same Homepage: http://scikit-image.org Priority: optional Section: python Filename: pool/main/s/skimage/python3-skimage-lib_0.14.0-1~nd18.04+1_i386.deb Size: 1331032 SHA256: 70b8f53edf5c9f4c1d581d8d44b695de1961b43afcb1091bd2fb335f952ba628 SHA1: 4b5ec71218d423e6de26ed67e8c244c6aae66eb0 MD5sum: bd9b1e7f08d433e6cdc9641ec8231569 Description: Optimized low-level algorithms for Python 3 scikit-image This is an add-on package for python-skimage. It provides optimized, low-level implementations of algorithms. . This package provides the Python 3 libraries. Package: python3-sklearn Source: scikit-learn Version: 0.20.0+dfsg-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7539 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.20.0+dfsg-2~nd18.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-pytest, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.20.0+dfsg-2~nd18.04+1_all.deb Size: 1517464 SHA256: 62578f769485fd99e9dd08863fb5c6eb336d0ddc98d3518cb836238c04d4a261 SHA1: 5e893a9dee32cdfe348b5eac185cb8633d818a6f MD5sum: 87fc62b92b92e7a70096642e6a14b612 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.19.2-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 6577 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.13.1), python3-numpy-abi9, python3 (<< 3.7), python3 (>= 3.6~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.19.2-1~nd18.04+1_i386.deb Size: 1287468 SHA256: 19785c8c87baa83e3d16190c41b6432bdaed849fc245c24ac9c08af7aed98aa1 SHA1: 2b34a84ca4acea3eb968f1b6daecbea4019b83d1 MD5sum: 5733877a73d406b6eca9fddd34ec856f Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-sphinx-gallery Source: sphinx-gallery Version: 0.2.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 217 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-matplotlib, python3-pil, python3-sphinx Suggests: python-sphinx-gallery-doc, python3-seaborn Homepage: https://sphinx-gallery.github.io/ Priority: optional Section: python Filename: pool/main/s/sphinx-gallery/python3-sphinx-gallery_0.2.0-1~nd18.04+1_all.deb Size: 71960 SHA256: feb786342f3e479c2184f7e628e2d0c4ee07c785394e20f08511d7883510706c SHA1: 4182e67ceabd0173bd72efb60d9c23881be7bc8b MD5sum: a37099ba5668d6a9ffb6d67cf42e004a Description: extension that builds an HTML gallery of examples from Python scripts (Python 3) * Simple examples that run out of the box are the best way to learn a library * Pleasing, organized, visual layouts * Links, searching, backlinks throughout examples and documentation . This package contains the Python 3 version of sphinx-gallery. Package: python3-sympy Source: sympy Version: 1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26373 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-mpmath Recommends: python3-pil, ipython3, python3-numpy Suggests: texlive-fonts-extra, dvipng, python-sympy-doc Enhances: isympy3 Homepage: http://sympy.org/ Priority: optional Section: python Filename: pool/main/s/sympy/python3-sympy_1.3-1~nd18.04+1_all.deb Size: 3499860 SHA256: 53cb14c2b1c4c1c9d6fbbba3fbc6264a8e87e2be45b3123d418614d89710a1c6 SHA1: 9ee3c3940df9a2dd9aa8aa853cc8346afcdd550b MD5sum: 278de7715c7f0137bf7e5615cea211e1 Description: Computer Algebra System (CAS) in Python (Python3) SymPy is a Python library for symbolic mathematics (manipulation). It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries, except optionally for plotting support. . This package contains the Python 3 version of sympy. Package: python3-urllib3 Source: python-urllib3 Version: 1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 254 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-six Recommends: ca-certificates Suggests: python3-ndg-httpsclient, python3-openssl, python3-pyasn1 Homepage: http://urllib3.readthedocs.org Priority: optional Section: python Filename: pool/main/p/python-urllib3/python3-urllib3_1.12-1~bpo8+1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 65652 SHA256: 2f09fcb63c34fe4fefab358337681b21f4a9370fa8dcb95b0b6af97327eaaba7 SHA1: 7902c9e8853b1d0d853496b318e8a07c2d54fe79 MD5sum: 45fb1be596dafa3b069af7cebd2df35f Description: HTTP library with thread-safe connection pooling for Python3 urllib3 supports features left out of urllib and urllib2 libraries. . - Re-use the same socket connection for multiple requests (HTTPConnectionPool and HTTPSConnectionPool) (with optional client-side certificate verification). - File posting (encode_multipart_formdata). - Built-in redirection and retries (optional). - Supports gzip and deflate decoding. - Thread-safe and sanity-safe. - Small and easy to understand codebase perfect for extending and building upon. . This package contains the Python 3 version of the library. Package: python3-wrapt Source: python-wrapt Version: 1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 119 Depends: neurodebian-popularity-contest, python3-six, python3 (<< 3.7), python3 (>= 3.6~), python3:any (>= 3.3.2-2~), libc6 (>= 2.4) Homepage: https://github.com/GrahamDumpleton/wrapt Priority: optional Section: python Filename: pool/main/p/python-wrapt/python3-wrapt_1.9.0-4~nd0~nd17.04+1+nd17.10+1+nd18.04+1_i386.deb Size: 28484 SHA256: d972892e5579cc7b21315e40d60e423c7a6fdf02215acba313c31bc9dcf87592 SHA1: 3dbfe69edf7ed53af0f45424dea94f049ab471a1 MD5sum: a4c0c174916fde617cc5ae91d785165c Description: decorators, wrappers and monkey patching. - Python 3.x The aim of the wrapt module is to provide a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions. . The wrapt module focuses very much on correctness. It therefore goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour. . To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled. . This package contains the Python 3.x module. Package: python3-xlwt Source: xlwt Version: 1.3.0-2~nd0~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 445 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-xlrd, python-xlrt-doc Homepage: https://pypi.python.org/pypi/xlwt Priority: optional Section: python Filename: pool/main/x/xlwt/python3-xlwt_1.3.0-2~nd0~nd18.04+1_all.deb Size: 83968 SHA256: 6d0022cfbde172d085b49b28144d97d9bb1536d00b3f36d2de16a669d49435f0 SHA1: da74706e07d2d85bf7218d34788b11d7d9710a10 MD5sum: ae10770e07bc32bca6ed431a1c02a884 Description: module for writing Microsoft Excel spreadsheet files - Python 3.x This package provides a pure Python module for writing spreadsheet files readable by Excel 97/2000/XP/2003, OpenOffice.org Calc, and Gnumeric. Excel spreadsheets can be generated on any platform without needing Excel or a COM server. . Xlwt is a fork of the unmaintained pyExcelerator module with several bugfixes and enhancements. For the functionality previously provided by the parse_xls function, see the python-xlrd package. . This package provides the Python 3.x module. Package: rclone Version: 1.41-1~ndall0 Architecture: i386 Maintainer: Debian Go Packaging Team Installed-Size: 16874 Depends: libc6 (>= 2.3.6-6~) Built-Using: go-md2man (= 1.0.8+ds-1), golang-1.10 (= 1.10.3-1), golang-bazil-fuse (= 0.0~git20160811.0.371fbbd-2), golang-github-a8m-tree (= 0.0~git20171213.cf42b1e-1), golang-github-abbot-go-http-auth (= 0.0~git20150714.0.46b9627-2), golang-github-aws-aws-sdk-go (= 1.12.79+dfsg-1), golang-github-azure-azure-sdk-for-go (= 10.3.0~beta-1), golang-github-azure-go-autorest (= 8.3.1-1), golang-github-coreos-bbolt (= 1.3.1-coreos.5-1), golang-github-davecgh-go-spew (= 1.1.0-4), golang-github-dgrijalva-jwt-go-v3 (= 3.1.0-2), golang-github-djherbis-times (= 1.0.1+git20170215.d25002f-1), golang-github-dropbox-dropbox-sdk-go-unofficial (= 4.1.0-1), golang-github-go-ini-ini (= 1.32.0-2), golang-github-google-go-querystring (= 0.0~git20170111.0.53e6ce1-4), golang-github-jlaffaye-ftp (= 0.0~git20170707.0.a05056b-1), golang-github-jmespath-go-jmespath (= 0.2.2-2), golang-github-kardianos-osext (= 0.0~git20170510.0.ae77be6-5), golang-github-kr-fs (= 0.0~git20131111.0.2788f0d-2), golang-github-mattn-go-runewidth (= 0.0.2+git20170510.3.97311d9-1), golang-github-ncw-go-acd (= 0.0~git20171120.887eb06-1), golang-github-unknwon-goconfig (= 0.0~git20160828.0.5aa4f8c-3), golang-github-vividcortex-ewma (= 0.0~git20160822.20.c595cd8-3), golang-google-cloud (= 0.9.0-5), golang-goprotobuf (= 0.0~git20170808.0.1909bc2-2) Homepage: https://github.com/ncw/rclone Priority: optional Section: net Filename: pool/main/r/rclone/rclone_1.41-1~ndall0_i386.deb Size: 4618876 SHA256: f3d9fca60ef0cfd3221be8ef088af8a9fc3a2a2c99955034fe6b29a9e18eb42e SHA1: 50b47feb7ce2f1441e1a5cef84f91ef20d1e104f MD5sum: 8c73c00b1e80467960cb535af6d6e58f Description: rsync for commercial cloud storage Rclone is a program to sync files and directories between the local file system and a variety of commercial cloud storage providers: . - Google Drive - Amazon S3 - Openstack Swift / Rackspace cloud files / Memset Memstore - Dropbox - Google Cloud Storage - Amazon Drive - Microsoft One Drive - Hubic - Backblaze B2 - Yandex Disk Package: reprozip Version: 1.0.14-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 14 Depends: neurodebian-popularity-contest, python3:any (>= 3.3~), python3-reprozip Multi-Arch: foreign Homepage: https://www.reprozip.org Priority: optional Section: utils Filename: pool/main/r/reprozip/reprozip_1.0.14-1~nd18.04+1_all.deb Size: 3640 SHA256: 33f8657ad4be0be129ec7be7db007bdaab9312625b805e19452e43e6cdf15a36 SHA1: e10ca304374f2e6adadc2d0192250d15d13fb97a MD5sum: 0b8aa86e68b8ce07042ba89843ee6bc6 Description: tool for reproducing scientific experiments (packer) ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science. . It tracks operating system calls and creates a package that contains all the binaries, files and dependencies required to run a given command on the author’s computational environment (packing step). A reviewer can then extract the experiment in his environment to reproduce the results (unpacking step). . This package provides the ReproZip packer. Package: ruby-asciidoctor Source: asciidoctor Version: 1.5.7.1-1~nd~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 817 Depends: neurodebian-popularity-contest, ruby | ruby-interpreter Breaks: asciidoctor (<< 1.5.6.2-1) Replaces: asciidoctor (<< 1.5.6.2-1) Homepage: http://asciidoctor.org Priority: optional Section: ruby Filename: pool/main/a/asciidoctor/ruby-asciidoctor_1.5.7.1-1~nd~nd18.04+1_all.deb Size: 183652 SHA256: 1bd60cf37c603d692317b3795a8d1d9554a325b7b68f77ac88a0f9dc1d557d09 SHA1: 4ff52a84a8161595393378756b12f27b02b74e23 MD5sum: 861e21d8cd6d63083ac44df52ffcf992 Description: AsciiDoc to HTML rendering for Ruby (core libraries) Asciidoctor is a pure Ruby processor for converting AsciiDoc source files and strings into HTML 5, DocBook 4.5, DocBook 5.0 and other formats. . This package contains the library files used by the asciidoctor package. Ruby-Versions: all Package: singularity-container Version: 2.6.1-2~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 2531 Depends: neurodebian-popularity-contest, python, squashfs-tools, ca-certificates, libarchive13 (>= 3.0.4), libc6 (>= 2.27) Recommends: e2fsprogs Homepage: http://www.sylabs.io Priority: optional Section: admin Filename: pool/main/s/singularity-container/singularity-container_2.6.1-2~nd18.04+1_i386.deb Size: 331448 SHA256: 4f8d7893e46ae0cc9a591d1fb19c0941300ae1d518acb4ccf7bf258afb4ff389 SHA1: e151d40bd756a9449f966040079b44371cefa79a MD5sum: c413c88146c54e34b85bef3ca79dfe31 Description: container platform focused on supporting "Mobility of Compute" Mobility of Compute encapsulates the development to compute model where developers can work in an environment of their choosing and creation and when the developer needs additional compute resources, this environment can easily be copied and executed on other platforms. Additionally as the primary use case for Singularity is targeted towards computational portability, many of the barriers to entry of other container solutions do not apply to Singularity making it an ideal solution for users (both computational and non-computational) and HPC centers. Package: stimfit Version: 0.15.8-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 3090 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.7), libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:3.0), libhdf5-100, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.4+dfsg), libwxgtk3.0-gtk3-0v5 (>= 3.0.4+dfsg), python-numpy (>= 1:1.13.1), python-numpy-abi9, python2.7, python:any (>= 2.7.5-5~), libsuitesparse-dev, zlib1g-dev, python-wxgtk3.0 | python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.15.8-1~nd18.04+1_i386.deb Size: 937760 SHA256: a60dc1cf36d4bf8748526cf15f35017792b7773e2c0f47c0cb5dac1be94826b1 SHA1: 30a4e115aa9c6acd9c7943e1fb432bdc311982af MD5sum: 84d6dd49bc69bb5eb3259ac5258f746e Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.15.8-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 8113 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.15.8-1~nd18.04+1_i386.deb Size: 7936184 SHA256: 68cb70c0b812dfe1a2bd6999199cb9cd05eb93a09cd395cf1124e1e3bc02213f SHA1: 93a7590b4a069a80bb6bddf3d9103d4ed3a76bbd MD5sum: 7b86ae00ba547b651e901e39472d5e54 Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. This package contains the debug symbols for Stimfit. Build-Ids: 4d454b4c49e184a94a977f20a82a1a141c720b89 53898a95150107890f1d026d37712119bf91f9ff 65b9c4d0e788ae592ff23563fe18581dbf087a5d 7faba885b4dc10e50f99e67b7f7ceaf60dfed176 86f63de347f22f7bb6a16ee4899862586482dc58 dc797041aa7d95060ee85b8a9888089f1a08038f de3f19ee4cb41820063ec2fb6d976777b4707a9e Package: vowpal-wabbit Version: 8.6.1.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 217 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 7), libvw0 (= 8.6.1.dfsg1-1~nd18.04+1) Suggests: vowpal-wabbit-doc Homepage: http://hunch.net/~vw/ Priority: optional Section: science Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit_8.6.1.dfsg1-1~nd18.04+1_i386.deb Size: 63240 SHA256: ae8bb1eda3574e1e1e362326dc3215cec70971b92c48239ae33dbad60a36939e SHA1: 0df5c5f951f3767d120bdd9f66a7763d526a3765 MD5sum: 69c0d6d06c19c3aad1e0771f5934ff95 Description: fast and scalable online machine learning algorithm Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing Package: vowpal-wabbit-dbg Source: vowpal-wabbit Version: 8.6.1.dfsg1-1~nd18.04+1 Architecture: i386 Maintainer: NeuroDebian Maintainers Installed-Size: 536 Depends: neurodebian-popularity-contest, vowpal-wabbit (= 8.6.1.dfsg1-1~nd18.04+1) Homepage: http://hunch.net/~vw/ Priority: optional Section: debug Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-dbg_8.6.1.dfsg1-1~nd18.04+1_i386.deb Size: 86344 SHA256: 6f81d5b37132156c1eacacf99aeaba6ea80099bb412280b42727327467d25215 SHA1: b62d849040287981631af28bd01f5e3c90a8c4f8 MD5sum: 82a3a042c7d425546465cba49bfe2aae Description: fast and scalable online machine learning algorithm - debug files Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains debug symbols for the binaries shipped by vowpal-wabbit packages. Build-Ids: 4af3e588376ef1eb7176a5e70f36a881297d3c07 4b10d1c1ef519b91b8c02e5c3c379188ccd57b8c 4dd0f507cd4b3b5e4e7530bc27e81bb3ffc8962d 91b1e04ec4346f6834c6e3e80ba0b1c34a3fe941 b8d64440da752f3987ab2728912ee540ef985114 ca2fd9108e553a03a0be0b0b6059ce7137cd7235 dafd9eed461d876b82c86d1e808a665b3fe88394 de3315d5f9c10416b38fe42cd08f143e18d1535d Package: vowpal-wabbit-doc Source: vowpal-wabbit Version: 8.6.1.dfsg1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 26318 Depends: neurodebian-popularity-contest Recommends: vowpal-wabbit Homepage: http://hunch.net/~vw/ Priority: optional Section: doc Filename: pool/main/v/vowpal-wabbit/vowpal-wabbit-doc_8.6.1.dfsg1-1~nd18.04+1_all.deb Size: 18693472 SHA256: 3924e0119fdad74b1b824f02e0fc6164d441ceccdace719147b230e040094c9e SHA1: f07e3653b997fcc203628a6cc5de088e49b02a45 MD5sum: 5ab092b1a3bbcbf35a22251fb68aefa2 Description: fast and scalable online machine learning algorithm - documentation Vowpal Wabbit is a fast online machine learning algorithm. The core algorithm is specialist gradient descent (GD) on a loss function (several are available). VW features: - flexible input data specification - speedy learning - scalability (bounded memory footprint, suitable for distributed computation) - feature pairing . This package contains examples (tests) for vowpal-wabbit.