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-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: 0.27.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 322 Depends: neurodebian-popularity-contest, perl, btrfs-progs (>= 3.18.2) | btrfs-tools (>= 3.18.2) Recommends: openssh-client, pv, mbuffer Suggests: openssl Homepage: https://digint.ch/btrbk/ Priority: optional Section: utils Filename: pool/main/b/btrbk/btrbk_0.27.0-1~nd18.04+1_all.deb Size: 90780 SHA256: 7a7e3a42060a2c4564ec7cd799d7a8d580fc0a8339df3e11afad80c2e1382036 SHA1: 0a624e9fdd0faed0ff6780d1cb8b6581e8d6c070 MD5sum: 12446a08fba0a243908a0727890990f9 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: 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: datalad Version: 0.11.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 127 Depends: neurodebian-popularity-contest, python3-datalad (= 0.11.0-1~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_0.11.0-1~nd18.04+1_all.deb Size: 90500 SHA256: 998fb827b8867a7ef22317bc1a790f5a6117dc9a3b4b86a5174e6fbbf9cc45a9 SHA1: 065daf3c6dcdeb792a2fa6aa1fd80a7733c3fbd8 MD5sum: aa63bd2f5b523781e55c7a33e2371024 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: 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: 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: 0.5-1~nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 199 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_0.5-1~nd17.10+1+nd18.04+1_all.deb Size: 48012 SHA256: bacd504c620e64fe71700f55314f77996d6995180f67436cffb2a75ee9602062 SHA1: 5fab45da0cb5f0b2db19af75ea5efd5382d4d9d5 MD5sum: dcbe4c2c753acf8976cc9f48fa491648 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: 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-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-doc Source: mrtrix3 Version: 3.0~rc3+git86-g4b523b413-1~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+git86-g4b523b413-1~nd18.04+1_all.deb Size: 47364 SHA256: 8a8819b86a2a5b206114d796e7b7a7425009c88895af6fa58fbe5c449f58fd0b SHA1: 5b841821bbde30ac35ff3ab7a0c581b814a7cd31 MD5sum: d1adaec7b661552d0295a08c1de9d32a 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: nuitka Version: 0.5.32.7+ds-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7176 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_0.5.32.7+ds-1~nd18.04+1_all.deb Size: 750620 SHA256: 4e8ad7bb89476d7f0a06e7f47b069f0f9a27469491caeffbca575c212d464725 SHA1: 9c0c49ca938a7691d247eb1c7f97652d73161a84 MD5sum: 6b71a7df996e83e20396c1927c5a8f74 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: 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: 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-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: 0.11.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4286 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_0.11.0-1~nd18.04+1_all.deb Size: 890420 SHA256: dc8153bb59d002a31c12b528e6e40e0dbf0ac67b2fb93e1929e9ceb16c85c9f4 SHA1: 76cdd58b62a9f3a6e044c35e9b9836e835a9af7c MD5sum: af996376fd5483e730001c97af9c4fc8 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: 1.1.0-2~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_1.1.0-2~nd18.04+1_all.deb Size: 4760 SHA256: 012f4e82cacaae93f2f70638f53491ba4c1ecd9e95bb03b1cff766ca4a068cf4 SHA1: 122de81a2ce73e190ee74154162675b481132143 MD5sum: 4b3db276675607d58668d4e8fe81f731 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-duecredit Source: duecredit Version: 0.6.4-1~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_0.6.4-1~nd18.04+1_all.deb Size: 52976 SHA256: ed4ddb4429acf841ae32bb21cd2710db9892846d2f3f378f39a94f947bb7f0d9 SHA1: de2dd2b13e7e07b60d0be23855878585c64cf8d6 MD5sum: 0b23b6c7c9f10074823093ee2b79c779 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-joblib Source: joblib Version: 0.12.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 848 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 Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.12.3-1~nd18.04+1_all.deb Size: 185940 SHA256: 0d780a86db261d1f8e1a961a1ee587010ae4f475c69a4adfc00230709328da41 SHA1: 8ea303339e3d0484207979a6de939a4e07112ce8 MD5sum: 62d9ad624441be61fb99a91aee672a16 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-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-nibabel Source: nibabel Version: 2.3.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65207 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~), python-numpy, python-scipy, python-six 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_2.3.1-1~nd18.04+1_all.deb Size: 2591516 SHA256: b44586635afb4f4c58818437bea4667d3e35f4b0fd92003d78fc3c2e31b4443d SHA1: af3d482005354595d56e22daa518047a2f6ff9fe MD5sum: 71a3cce6c9d74bfa4b08456160a29cb8 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: 2.3.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 9110 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_2.3.1-1~nd18.04+1_all.deb Size: 1473528 SHA256: fb0dc1a50448704c04118472ff7ba65e95739a12af81f12e60ee0dc4c946c1a2 SHA1: d59eeab2286f0452c40819ab424e0228a1f48cfa MD5sum: a898c5c7dfb618eac730c582b24c1269 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-nipype Source: nipype Version: 1.1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10914 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-mock, python-networkx (>= 1.3), python-nibabel (>= 1.0.0~), python-numpy, python-packaging, python-prov, python-pytest, python-pytest-xdist, 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, graphviz, python-xvfbwrapper, mayavi2, python-pydotplus, python-pydot, python-cfflib Suggests: fsl, afni, python-nipy, slicer, matlab-spm8, python-pyxnat, mne-python, elastix, ants, python-bids Provides: python2.7-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_1.1.3-1~nd18.04+1_all.deb Size: 1873820 SHA256: 31da775aa6c340e02189ab4c842ab33082d56945f4aef1c79a914c12dc281b8a SHA1: ec40c2a9924258c0ac77860eedae1f045249719f MD5sum: cd3078ba858607da176fb57136eb8b96 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: 1.1.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 47141 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_1.1.3-1~nd18.04+1_all.deb Size: 19970020 SHA256: fb6c50852e3709ae90f87951011a2a52a279fc407ddca94a4d1ed2caa4cc4151 SHA1: 4a38e1a74c95eab1de6ea4615e329260176096fc MD5sum: a92911bf169ab4e88dd8a2214b469c14 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-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 779 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_0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 168312 SHA256: 0f04222e8ee44213a66a04c54ce4a61b58a212007b9dbc3c5f77cb252ed73c0a SHA1: 952c2cd48431f64ce8507fce19b5564c25c043cd MD5sum: 76d42cff69fb3479b35a4a6804061a9d 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: 0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+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_0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 343612 SHA256: 4ff7df2df8b881ae9403a4c4d5b1b9893216a9c2ab083139805c3b7670ece97f SHA1: 4886fa72049deb4101eb3e018b09b6f454236787 MD5sum: 562489b71ac0d3faf662d31934b99053 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: 1.1.0-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10042 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python:any (>= 2.6.6-7~) Recommends: python-numpy, python-pil, python-gdcm Suggests: python-matplotlib 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_1.1.0-2~nd18.04+1_all.deb Size: 4317496 SHA256: 613cce196ac6b0b0d1c2ed62aa848af9dc2bd6516b082aab0a7eb530cf0a34d9 SHA1: 42f6a4eb17cd1223120a9796a7f85203da31e3d2 MD5sum: 25100e92cf1ce49f583818094cb54d48 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: 1.1.0-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2789 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_1.1.0-2~nd18.04+1_all.deb Size: 323424 SHA256: 8818371a38b9082372c2f66ebf76cf2bf2e7d58099b0475623b02c108819da9b SHA1: ab9134d83ec5f241399fecdb9bdbdd688c14c230 MD5sum: 4e35a472e970e8e41259b2a7f6626deb 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-sklearn Source: scikit-learn Version: 0.19.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7024 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.19.2-1~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_0.19.2-1~nd18.04+1_all.deb Size: 1456104 SHA256: d49356d96b2ce6ed3adcadd09a24e79d1f33d047d027f3d2d632a85556992e77 SHA1: 8ba490755e547317b10461b59ca0240d4d17eb10 MD5sum: f7684df86bbd5612b94624818ebf9ace 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: 0.19.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 33573 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.19.2-1~nd18.04+1_all.deb Size: 5102952 SHA256: 456934917c26aabcb2949d2094749ce20b4e4e549e2b0a9d3ce38c71a47fda6d SHA1: 9f07bbcfa89f0997753b3bc90c09eba02608167e MD5sum: 80d42ff9086953132fa3c5db41ad5274 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. 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-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-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: 0.11.0-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4286 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_0.11.0-1~nd18.04+1_all.deb Size: 890572 SHA256: bf3bcbf2585ec78ff558686ce30f2e4de6cb6c7b0031108ba48987e30cfcdf35 SHA1: cef7f5654b005203c6ea1bf4bdd9268beb82dc23 MD5sum: 3333f16d2d334907c33b53ecf114ed09 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: 1.1.0-2~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_1.1.0-2~nd18.04+1_all.deb Size: 4764 SHA256: 797013c852a449581bd6b308cd873afce8a9b4c5d5ad5369350a6ca2c8c57e51 SHA1: 746422e47f2ba6fa39e3c54c957c3e9c9df22d00 MD5sum: 138f5e7475fec14f3bdfb91135054e6a Description: transitional package for python3-pydicom This is a transitional package. It can safely be removed. Package: python3-duecredit Source: duecredit Version: 0.6.4-1~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_0.6.4-1~nd18.04+1_all.deb Size: 53248 SHA256: 5b384d03b626047f2f27ec3d1357db3f521fb0b2de9ac0ac2f7c988440e6291b SHA1: b0ddf3076f82f1cb6aa7e056745d2cc04e18a56f MD5sum: 574577a36c922d2e2a63b7952e498f05 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-joblib Source: joblib Version: 0.12.3-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 843 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), procps Recommends: python3-numpy, python3-pytest, python3-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python3-joblib_0.12.3-1~nd18.04+1_all.deb Size: 182852 SHA256: 49f6161e22f832e9dd4eac0dedf3184223a82ca817cc136a44c692a7f03b3e17 SHA1: 068524a7b00659707f7a79a910a2cbbb5a151c1c MD5sum: 74877351e0ed18c9ee518f06268adb47 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-nibabel Source: nibabel Version: 2.3.1-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65192 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_2.3.1-1~nd18.04+1_all.deb Size: 2587520 SHA256: 62cffd0db5efdc2c225a90a63ec9a3d14ea11e6fb27d5ae66a7e85b753737809 SHA1: 5f48cb753ca5d832806d3963e8323bc1f11ae3a4 MD5sum: 02022d263f34bf2d6232be0907746408 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-patsy Source: patsy Version: 0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 778 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_0.4.1+git34-ga5b54c2-1~nd90+1+nd17.04+1+nd17.10+1+nd18.04+1_all.deb Size: 168408 SHA256: 581d89afc72695123dd9a8dbfce88423252f72407574f4ec8bcb06d3639b5e4c SHA1: d3338426d8c783e1e7f2ccdb2129246c6cc5e6f2 MD5sum: 50030fb684ea40012c8b7cae0cd60b3c 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: 1.1.0-2~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10042 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Recommends: python3-numpy, python3-pil, python3-gdcm Suggests: python3-matplotlib 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_1.1.0-2~nd18.04+1_all.deb Size: 4317828 SHA256: 93bc99eb8ac7e9d45882e7d58d96edf5fc1a34809cb974100f32edac0a72b1f5 SHA1: c82c9abb88649eedaa34371b7dd0a0189fe54071 MD5sum: ad52528cd6935f04f06704b1b6a7412e 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-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-sklearn Source: scikit-learn Version: 0.19.2-1~nd18.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 7023 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.19.2-1~nd18.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python-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_0.19.2-1~nd18.04+1_all.deb Size: 1456044 SHA256: 95dc34dce51eda45e0772de26fa5079ae62ca35d9b79c7d9ce341ba588c0d3ce SHA1: 4508edc110afb3014fc4d43bd5f1e91c21345c8b MD5sum: 8bd4e14f9a2c528df96d55b755e34d80 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-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-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: 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: 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.